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Sample records for identify factors predictive

  1. Identifying the necessary and sufficient number of risk factors for predicting academic failure.

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    Lucio, Robert; Hunt, Elizabeth; Bornovalova, Marina

    2012-03-01

    Identifying the point at which individuals become at risk for academic failure (grade point average [GPA] academic success or failure. This study focused on 12 school-related factors. Using a thorough 5-step process, we identified which unique risk factors place one at risk for academic failure. Academic engagement, academic expectations, academic self-efficacy, homework completion, school relevance, school safety, teacher relationships (positive relationship), grade retention, school mobility, and school misbehaviors (negative relationship) were uniquely related to GPA even after controlling for all relevant covariates. Next, a receiver operating characteristic curve was used to determine a cutoff point for determining how many risk factors predict academic failure (GPA academic failure, which provides a way for early identification of individuals who are at risk. Further implications of these findings are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  2. Identifying the bleeding trauma patient: predictive factors for massive transfusion in an Australasian trauma population.

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    Hsu, Jeremy Ming; Hitos, Kerry; Fletcher, John P

    2013-09-01

    Military and civilian data would suggest that hemostatic resuscitation results in improved outcomes for exsanguinating patients. However, identification of those patients who are at risk of significant hemorrhage is not clearly defined. We attempted to identify factors that would predict the need for massive transfusion (MT) in an Australasian trauma population, by comparing those trauma patients who did receive massive transfusion with those who did not. Between 1985 and 2010, 1,686 trauma patients receiving at least 1 U of packed red blood cells were identified from our prospectively maintained trauma registry. Demographic, physiologic, laboratory, injury, and outcome variables were reviewed. Univariate analysis determined significant factors between those who received MT and those who did not. A predictive multivariate logistic regression model with backward conditional stepwise elimination was used for MT risk. Statistical analysis was performed using SPSS PASW. MT patients had a higher pulse rate, lower Glasgow Coma Scale (GCS) score, lower systolic blood pressure, lower hemoglobin level, higher Injury Severity Score (ISS), higher international normalized ratio (INR), and longer stay. Initial logistic regression identified base deficit (BD), INR, and hemoperitoneum at laparotomy as independent predictive variables. After assigning cutoff points of BD being greater than 5 and an INR of 1.5 or greater, a further model was created. A BD greater than 5 and either INR of 1.5 or greater or hemoperitoneum was associated with 51 times increase in MT risk (odds ratio, 51.6; 95% confidence interval, 24.9-95.8). The area under the receiver operating characteristic curve for the model was 0.859. From this study, a combination of BD, INR, and hemoperitoneum has demonstrated good predictability for MT. This tool may assist in the determination of those patients who might benefit from hemostatic resuscitation. Prognostic study, level III.

  3. Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

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    Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

    2018-05-12

    Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

  4. Complexity factors and prediction of performance

    International Nuclear Information System (INIS)

    Braarud, Per Oeyvind

    1998-03-01

    Understanding of what makes a control room situation difficult to handle is important when studying operator performance, both with respect to prediction as well as improvement of the human performance. A factor analytic approach identified eight factors from operators' answers to an 39 item questionnaire about complexity of the operator's task in the control room. A Complexity Profiling Questionnaire was developed, based on the factor analytic results from the operators' conception of complexity. The validity of the identified complexity factors was studied by prediction of crew performance and prediction of plant performance from ratings of the complexity of scenarios. The scenarios were rated by both process experts and the operators participating in the scenarios, using the Complexity Profiling Questionnaire. The process experts' complexity ratings predicted both crew performance and plant performance, while the operators' rating predicted plant performance only. The results reported are from initial studies of complexity, and imply a promising potential for further studies of the concept. The approach used in the study as well as the reported results are discussed. A chapter about the structure of the conception of complexity, and a chapter about further research conclude the report. (author)

  5. Identify the dominant variables to predict stream water temperature

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    Chien, H.; Flagler, J.

    2016-12-01

    Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.

  6. Predictive model identifies key network regulators of cardiomyocyte mechano-signaling.

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    Philip M Tan

    2017-11-01

    Full Text Available Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

  7. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants.

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    Bonetti, Debbie; Johnston, Marie; Clarkson, Jan E; Grimshaw, Jeremy; Pitts, Nigel B; Eccles, Martin; Steen, Nick; Thomas, Ruth; Maclennan, Graeme; Glidewell, Liz; Walker, Anne

    2010-04-08

    Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs) in Scotland. Outcomes were behavioural simulation (scenario decision-making), and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model, and knowledge (a non-theoretical construct). Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value. Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT), timeline acute (CS-SRM), and outcome expectancy (SCT) entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT) and attitude (TPB) entered the equation, together explaining 68% of the variance in intention. The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that may predict clinical behaviour

  8. Predictive factors for complications in children with esophageal atresia and tracheoesophageal fistula.

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    Shah, R; Varjavandi, V; Krishnan, U

    2015-04-01

    The objective of this study was to describe the incidence of complications in children with esophageal atresia (EA) with or without tracheoesophageal fistula (TEF) at a tertiary pediatric hospital and to identify predictive factors for their occurrence. A retrospective chart review of 110 patients born in or transferred to Sydney Children's Hospital with EA/TEF between January 1999 and December 2010 was done. Univariate and multivariate regression analyses were performed to identify predictive factors for the occurrence of complications in these children. From univariate analysis, early esophageal stricture formation was more likely in children with 'long-gap' EA (odds ratio [OR] = 16.32). Patients with early strictures were more likely to develop chest infections (OR = 3.33). Patients with severe tracheomalacia were more likely to experience 'cyanotic/dying' (OR = 180) and undergo aortopexy (OR = 549). Patients who had gastroesophageal reflux disease were significantly more likely to require fundoplication (OR = 10.83) and undergo aortopexy (OR = 6.417). From multivariate analysis, 'long-gap' EA was a significant predictive factor for late esophageal stricture formation (P = 0.007) and for gastrostomy insertion (P = 0.001). Reflux was a significant predictive factor for requiring fundoplication (P = 0.007) and gastrostomy (P = 0.002). Gastrostomy insertion (P = 0.000) was a significant predictive factor for undergoing fundoplication. Having a prior fundoplication (P = 0.001) was a significant predictive factor for undergoing a subsequent aortopexy. Predictive factors for the occurrence of complications post EA/TEF repair were identified in this large single centre pediatric study. © 2014 International Society for Diseases of the Esophagus.

  9. Predictive Factors associated with Death of Elderly in Nursing Homes

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    Kiwol Sung, PhD, RN

    2014-06-01

    Conclusion: Dyspnea, problematic behaviors, and ADL data were identified as the key factors associated with death among nursing home residents. Future plans for the prediction of death among nursing home residents can be made by nursing staff, factoring in these identified variables, to ensure more comfortable conditions and more responsive care.

  10. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants

    Directory of Open Access Journals (Sweden)

    Maclennan Graeme

    2010-04-01

    identifying factors that may predict clinical behaviour and so provide possible targets for knowledge translation interventions. Results suggest that more evidence-based behaviour may be achieved by influencing beliefs about the positive outcomes of placing fissure sealants and building a habit of placing them as part of patient management. However a number of conceptual and methodological challenges remain.

  11. Predicting survival function and identifying associated factors in patients with renal insufficiency in the metropolitan area of Maringá, Paraná State, Brazil.

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    Ramires, Thiago G; Nakamura, Luiz R; Righetto, Ana J; Ortega, Edwin M M; Cordeiro, Gauss M

    2018-02-05

    Renal insufficiency is a serious medical and public health problem worldwide. Recently, although many surveys have been developed to identify factors related to the lifetime of patients with renal insufficiency, controversial results from several studies suggest that researches should be conducted by region. Thus, in this study we aim to predict and identify factors associated with the lifetime of patients with chronic renal failure (CRF) in the metropolitan area of Maringá, Paraná State, Brazil, based on the generalized additive models for location, scale and shape (GAMLSS) framework. Data used in this study were collected from the Maringá Kidney Institute and comprehends 177 patients (classified with CRF and mostly being treated under the Brazilian Unified National Health System) enrolled in a hemodialysis program from 1978 up to 2010. By using this approach, we concluded that in other regions, gender, kidney transplant indicator, antibodies to hepatitis B and antibodies to hepatitis C are significant factors that affect the expected lifetime.

  12. Predicting survival function and identifying associated factors in patients with renal insufficiency in the metropolitan area of Maringá, Paraná State, Brazil

    Directory of Open Access Journals (Sweden)

    Thiago G. Ramires

    2018-02-01

    Full Text Available Renal insufficiency is a serious medical and public health problem worldwide. Recently, although many surveys have been developed to identify factors related to the lifetime of patients with renal insufficiency, controversial results from several studies suggest that researches should be conducted by region. Thus, in this study we aim to predict and identify factors associated with the lifetime of patients with chronic renal failure (CRF in the metropolitan area of Maringá, Paraná State, Brazil, based on the generalized additive models for location, scale and shape (GAMLSS framework. Data used in this study were collected from the Maringá Kidney Institute and comprehends 177 patients (classified with CRF and mostly being treated under the Brazilian Unified National Health System enrolled in a hemodialysis program from 1978 up to 2010. By using this approach, we concluded that in other regions, gender, kidney transplant indicator, antibodies to hepatitis B and antibodies to hepatitis C are significant factors that affect the expected lifetime.

  13. Predictive Factors of Anxiety and Depression in Patients with Acute Coronary Syndrome.

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    Altino, Denise Meira; Nogueira-Martins, Luiz Antônio; de Barros, Alba Lucia Bottura Leite; Lopes, Juliana de Lima

    2017-12-01

    To identify the predictive factors of anxiety and depression in patients with acute coronary syndrome. Cross-sectional and retrospective study conducted with 120 patients hospitalized with acute coronary syndrome. Factors interfering with anxiety and depression were assessed. Anxiety was related to sex, stress, years of education, and depression, while depression was related to sex, diabetes mellitus, obesity, years of education, and trait-anxiety. Obesity and anxiety were considered predictive factors for depression, while depression and fewer years of education were considered predictive factors for anxiety. Copyright © 2017. Published by Elsevier Inc.

  14. kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

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    Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

    2013-01-01

    Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

  15. SitesIdentify: a protein functional site prediction tool

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    Doig Andrew J

    2009-11-01

    Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

  16. Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

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    Elnahal, Shereef M., E-mail: selnaha1@jhmi.edu [Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States); Blackford, Amanda [Department of Oncology Biostatistics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States); Smith, Koren; Souranis, Annette N.; Briner, Valerie; McNutt, Todd R.; DeWeese, Theodore L.; Wright, Jean L.; Terezakis, Stephanie A. [Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States)

    2016-04-01

    Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

  17. Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

    International Nuclear Information System (INIS)

    Elnahal, Shereef M.; Blackford, Amanda; Smith, Koren; Souranis, Annette N.; Briner, Valerie; McNutt, Todd R.; DeWeese, Theodore L.; Wright, Jean L.; Terezakis, Stephanie A.

    2016-01-01

    Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

  18. Predictive factors associated with death of elderly in nursing homes.

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    Sung, Kiwol

    2014-06-01

    An increasing elderly population reflects a great need for readily accessible, clinically useful methods to identify mortality-related factors in nursing home residents. The purpose of this study was to identify factors associated with the deaths of nursing home residents. Data was collected from a Minimal Data Set of 195 elderly nursing home residents, followed by analysis of demographic factors, disease and nursing condition factors, Activities of Daily Living (ADL), cognitive function, behavioral patterns, and dysfunctional status. Major factors associated with death among nursing home residents were identified as dyspnea (odds ratio [OR] = 4.88), problematic behaviors (OR = 3.95), and ADL (OR = 3.61). These variables accounted for 31.1% of the variance in death. Dyspnea, problematic behaviors, and ADL data were identified as the key factors associated with death among nursing home residents. Future plans for the prediction of death among nursing home residents can be made by nursing staff, factoring in these identified variables, to ensure more comfortable conditions and more responsive care. Copyright © 2014. Published by Elsevier B.V.

  19. Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes

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    Jia, Pengfei; Maloney, Tim

    2015-01-01

    Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to…

  20. Meta-analysis of the predictive factors of postpartum fatigue.

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    Badr, Hanan A; Zauszniewski, Jaclene A

    2017-08-01

    Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes. We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes. Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (r range =0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (r range =0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (r range =0.50+) for depression. Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue. Copyright © 2017 Elsevier

  1. Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

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    Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

    2018-01-01

    The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

  2. Predictive factors for early menarche in Taiwan.

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    Chie, W C; Liu, Y H; Chi, J; Wu, V; Chen, A

    1997-06-01

    The rapid increase of breast cancer in Taiwan has prompted the authors to evaluate the predictive factors of early menarche among contemporary Taiwanese girls. A total of 895 four-grade girls from eight elementary schools in Taipei City and County were identified as a closed cohort from the first semester of 1993. Data were collected from self-administered questionnaires and school records. A total of 799 girls who had not menstruated in the first year remained in the group through 1994. The effects of potential predictive factors were assessed by logistic regression. Among the 799 girls followed, 69 (8.6%) had first menstruation between the fourth and fifth grades. Height, weight, body mass index and maternal early onset of menarche were positively related to the onset of menarche within the preceding year. Energy consumption during exercise showed only moderate association after being adjusted for age and weight. Calorie intake from junk food was not associated with early menarche within the preceding year. Poor interpersonal family relationships and stressful life events also showed a moderate association with early menarche. The data obtained supported the hypothesis that height, weight, body mass index and maternal early menarche are positive predictive factors of early menarche. The effects of exercise and childhood stress are less prominent.

  3. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors

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    Theophilus O. Ogunyemi

    2012-01-01

    Full Text Available Longitudinal data for studying urinary incontinence (UI risk factors are rare. Data from one study, the hallmark Medical, Epidemiological, and Social Aspects of Aging (MESA, have been analyzed in the past; however, repeated measures analyses that are crucial for analyzing longitudinal data have not been applied. We tested a novel application of statistical methods to identify UI risk factors in older women. MESA data were collected at baseline and yearly from a sample of 1955 men and women in the community. Only women responding to the 762 baseline and 559 follow-up questions at one year in each respective survey were examined. To test their utility in mining large data sets, and as a preliminary step to creating a predictive index for developing UI, logistic regression, generalized estimating equations (GEEs, and proportional hazard regression (PHREG methods were used on the existing MESA data. The GEE and PHREG combination identified 15 significant risk factors associated with developing UI out of which six of them, namely, urinary frequency, urgency, any urine loss, urine loss after emptying, subject’s anticipation, and doctor’s proactivity, are found most highly significant by both methods. These six factors are potential candidates for constructing a future UI predictive index.

  4. Use of clinical risk factors to identify postmenopausal women with vertebral fractures.

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    Tobias, J H; Hutchinson, A P; Hunt, L P; McCloskey, E V; Stone, M D; Martin, J C; Thompson, P W; Palferman, T G; Bhalla, A K

    2007-01-01

    Previous studies have been unable to identify risk factors for prevalent vertebral fractures (VF), which are suitable for use in selection strategies intended to target high-risk sub-groups for diagnostic assessment. However, these studies generally consisted of large epidemiology surveys based on questionnaires and were only able to evaluate a limited number of risk factors. Here, we investigated whether a stronger relationship exists with prevalent VF when conventional risk factors are combined with additional information obtained from detailed one-to-one assessment. Women aged 65-75 registered at four geographically distinct GP practices were invited to participate (n=1,518), of whom 540 attended for assessment as follows: a questionnaire asking about risk factors for osteoporosis such as height loss compared to age 25 and history of non-vertebral fracture (NVF), the get-up-and-go test, Margolis back pain score, measurement of wall-tragus and rib-pelvis distances, and BMD as measured by the distal forearm BMD. A lateral thoraco-lumbar spine X-ray was obtained, which was subsequently scored for the presence of significant vertebral deformities. Of the 509 subjects who underwent spinal radiographs, 37 (7.3%) were found to have one or more VF. Following logistic regression analysis, the four most predictive clinical risk factors for prevalent VF were: height loss (P=0.006), past NVF (P=0.004), history of back pain (P=0.075) and age (P=0.05). BMD was also significantly associated with prevalent VF (P=0.002), but its inclusion did not affect associations with other variables. Factors elicited from detailed one-to-one assessment were not related to the risk of one or more prevalent VFs. The area under ROC curves derived from these regressions, which suggested that models for prevalent VF had modest predictive accuracy, were as follows: 0.68 (BMD), 0.74 (four clinical risk factors above) and 0.78 (clinical risk factors + BMD). Analyses were repeated in relation to the

  5. Predictive factors of dropout from inpatient treatment for anorexia nervosa.

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    Roux, H; Ali, A; Lambert, S; Radon, L; Huas, C; Curt, F; Berthoz, S; Godart, Nathalie

    2016-09-30

    Patients with severe Anorexia Nervosa (AN) whose condition is life-threatening or who are not receiving adequate ambulatory care are hospitalized. However, 40 % of these patients leave the hospital prematurely, without reaching the target weight set in the treatment plan, and this can compromise outcome. This study set out to explore factors predictive of dropout from hospital treatment among patients with AN, in the hope of identifying relevant therapeutic targets. From 2009 to 2011, 180 women hospitalized for AN (DSM-IV diagnosis) in 10 centres across France were divided into two groups: those under 18 years (when the decision to discharge belongs to the parents) and those aged 18 years and over (when the patient can legally decide to leave the hospital). Both groups underwent clinical assessment using the Morgan & Russell Global Outcome State questionnaire and the Eating Disorders Examination Questionnaire (EDE-Q) for assessment of eating disorder symptoms and outcome. Psychological aspects were assessed via the evaluation of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS). Socio-demographic data were also collected. A number of factors identified in previous research as predictive of dropout from hospital treatment were tested using stepwise descending Cox regressions. We found that factors predictive of dropout varied according to age groups (being under 18 as opposed to 18 and over). For participants under 18, predictive factors were living in a single-parent family, severe intake restriction as measured on the "dietary restriction" subscale of the Morgan & Russell scale, and a low patient-reported score on the EDE-Q "restraint concerns" subscale. For those over 18, dropout was predicted from a low depression score on the HADS, low level of concern about weight on the EDE-Q subscale, and lower educational status. To prevent dropout from hospitalization for AN, the appropriate therapeutic measures vary according to whether

  6. Predictive Factors for Death After Snake Envenomation in Myanmar.

    Science.gov (United States)

    Aye, Kyi-Phyu; Thanachartwet, Vipa; Soe, Chit; Desakorn, Varunee; Chamnanchanunt, Supat; Sahassananda, Duangjai; Supaporn, Thanom; Sitprija, Visith

    2018-06-01

    Factors predictive for death from snake envenomation vary between studies, possibly due to variation in host genetic factors and venom composition. This study aimed to evaluate predictive factors for death from snake envenomation in Myanmar. A prospective study was performed among adult patients with snakebite admitted to tertiary hospitals in Yangon, Myanmar, from May 2015 to August 2016. Data including clinical variables and laboratory parameters, management, and outcomes were evaluated. Multivariate regression analysis was performed to evaluate factors predictive for death at the time of presentation to the hospital. Of the 246 patients with snake envenomation recruited into the study, 225 (92%) survived and 21 (8%) died during hospitalization. The snake species responsible for a bite was identified in 74 (30%) of the patients; the majority of bites were from Russell's vipers (63 patients, 85%). The independent factors predictive for death included 1) duration from bite to arrival at the hospital >1 h (odds ratio [OR]: 9.0, 95% confidence interval [CI]: 1.1-75.2; P=0.04); 2) white blood cell counts >20 ×10 3 cells·μL -1 (OR: 8.9, 95% CI: 2.3-33.7; P=0.001); and 3) the presence of capillary leakage (OR: 3.7, 95% CI: 1.2-11.2; P=0.02). A delay in antivenom administration >4 h increases risk of death (11/21 deaths). Patients who present with these independent predictive factors should be recognized and provided with early appropriate intervention to reduce the mortality rate among adults with snake envenomation in Myanmar. Copyright © 2018 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

  7. Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

    Science.gov (United States)

    Chakraborty, Joheen; Banerji, Sugata

    2018-03-01

    Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.

  8. Return to Work: A Cut-Off of FIM Gain with Montebello Rehabilitation Factor Score in Order to Identify Predictive Factors in Subjects with Acquired Brain Injury.

    Science.gov (United States)

    Franceschini, Marco; Massimiani, Maria Pia; Paravati, Stefano; Agosti, Maurizio

    2016-01-01

    Return to work (RTW) for people with acquired brain injury (ABI) represents a main objective of rehabilitation: this work presents a strong correlation between personal well-being and quality of life. The aim of this study is to investigate the prognostic factors that can predict RTW after ABI (traumatic or non- traumatic aetiology) in patients without disorders of consciousness (e.g. coma, vegetative or minimally conscious state) at the beginning of their admission to rehabilitation. At the end of a 6-month follow-up after discharge, data were successfully collected in 69 patients. The rehabilitation effectiveness (functional Recovery) between admission and discharge was assessed by Functional Independent Measure (FIM) gain, through the Montebello Rehabilitation Factor Score (MRFS), which was obtained as follows: (discharge FIM-admission FIM)/(Maximum possible FIM-Admission FIM) x 100. The cut-off value (criterion) deriving from MRFS, which helped identify RTW patients, resulted in .659 (sn 88.9%; sp 52.4%). Considering the Mini Mental State Examination (MMSE) and the MRFS data, the multivariable binary logistic regression analysis presented 62.96% of correct RTW classification cases, 80.95% of non-RTW leading to an overall satisfactory predictability of 73.91%. The results of the present study suggest that occupational therapy intervention could modify cut-off in patients with an MFRS close to target at the end of an in-hospital rehabilitative program thus developing their capabilities and consequently surpassing cut-off itself.

  9. Return to Work: A Cut-Off of FIM Gain with Montebello Rehabilitation Factor Score in Order to Identify Predictive Factors in Subjects with Acquired Brain Injury.

    Directory of Open Access Journals (Sweden)

    Marco Franceschini

    Full Text Available Return to work (RTW for people with acquired brain injury (ABI represents a main objective of rehabilitation: this work presents a strong correlation between personal well-being and quality of life. The aim of this study is to investigate the prognostic factors that can predict RTW after ABI (traumatic or non- traumatic aetiology in patients without disorders of consciousness (e.g. coma, vegetative or minimally conscious state at the beginning of their admission to rehabilitation. At the end of a 6-month follow-up after discharge, data were successfully collected in 69 patients. The rehabilitation effectiveness (functional Recovery between admission and discharge was assessed by Functional Independent Measure (FIM gain, through the Montebello Rehabilitation Factor Score (MRFS, which was obtained as follows: (discharge FIM-admission FIM/(Maximum possible FIM-Admission FIM x 100. The cut-off value (criterion deriving from MRFS, which helped identify RTW patients, resulted in .659 (sn 88.9%; sp 52.4%. Considering the Mini Mental State Examination (MMSE and the MRFS data, the multivariable binary logistic regression analysis presented 62.96% of correct RTW classification cases, 80.95% of non-RTW leading to an overall satisfactory predictability of 73.91%. The results of the present study suggest that occupational therapy intervention could modify cut-off in patients with an MFRS close to target at the end of an in-hospital rehabilitative program thus developing their capabilities and consequently surpassing cut-off itself.

  10. Quadratic prediction of factor scores

    NARCIS (Netherlands)

    Wansbeek, T

    1999-01-01

    Factor scores are naturally predicted by means of their conditional expectation given the indicators y. Under normality this expectation is linear in y but in general it is an unknown function of y. II is discussed that under nonnormality factor scores can be more precisely predicted by a quadratic

  11. Identifying perinatal risk factors for infant maltreatment: an ecological approach

    Directory of Open Access Journals (Sweden)

    Hallisey Elaine J

    2006-12-01

    Full Text Available Abstract Background Child maltreatment and its consequences are a persistent problem throughout the world. Public health workers, human services officials, and others are interested in new and efficient ways to determine which geographic areas to target for intervention programs and resources. To improve assessment efforts, selected perinatal factors were examined, both individually and in various combinations, to determine if they are associated with increased risk of infant maltreatment. State of Georgia birth records and abuse and neglect data were analyzed using an area-based, ecological approach with the census tract as a surrogate for the community. Cartographic visualization suggested some correlation exists between risk factors and child maltreatment, so bivariate and multivariate regression were performed. The presence of spatial autocorrelation precluded the use of traditional ordinary least squares regression, therefore a spatial regression model coupled with maximum likelihood estimation was employed. Results Results indicate that all individual factors or their combinations are significantly associated with increased risk of infant maltreatment. The set of perinatal risk factors that best predicts infant maltreatment rates are: mother smoked during pregnancy, families with three or more siblings, maternal age less than 20 years, births to unmarried mothers, Medicaid beneficiaries, and inadequate prenatal care. Conclusion This model enables public health to take a proactive stance, to reasonably predict areas where poor outcomes are likely to occur, and to therefore more efficiently allocate resources. U.S. states that routinely collect the variables the National Center for Health Statistics (NCHS defines for birth certificates can easily identify areas that are at high risk for infant maltreatment. The authors recommend that agencies charged with reducing child maltreatment target communities that demonstrate the perinatal risks

  12. Predictive factors for pharyngocutaneous fistulization after total laryngectomy: a Dutch Head and Neck Society audit.

    Science.gov (United States)

    Lansaat, Liset; van der Noort, Vincent; Bernard, Simone E; Eerenstein, Simone E J; Plaat, Boudewijn E C; Langeveld, Ton A P M; Lacko, Martin; Hilgers, Frans J M; de Bree, Remco; Takes, Robert P; van den Brekel, Michiel W M

    2018-03-01

    Incidences of pharyngocutaneous fistulization (PCF) after total laryngectomy (TL) reported in the literature vary widely, ranging from 2.6 to 65.5%. Comparison between different centers might identify risk factors, but also might enable improvements in quality of care. To enable this on a national level, an audit in the 8 principle Dutch Head and Neck Centers (DHNC) was initiated. A retrospective chart review of all 324 patients undergoing laryngectomy in a 2-year (2012 and 2013) period was performed. Overall PCF%, PCF% per center and factors predictive for PCF were identified. Furthermore, a prognostic model predicting the PCF% per center was developed. To provide additional data, a survey among the head and neck surgeons of the participating centers was carried out. Overall PCF% was 25.9. The multivariable prediction model revealed that previous treatment with (chemo)radiotherapy in combination with a long interval between primary treatment and TL, previous tracheotomy, near total pharyngectomy, neck dissection, and BMI model. PCF performance rate (difference between the PCF% and the predicted PCF%) per DHNC, though, shows that not all differences are explained by factors established in the prediction model. However, these factors explain enough of the differences that, compensating for these factors, hospital is no longer independently predictive for PCF. This nationwide audit has provided valid comparative PCF data confirming the known risk factors from the literature which are important for counseling on PCF risks. Data show that variations in PCF% in the DHNCs (in part) are explainable by the variations in these predictive factors. Since elective neck dissection is a major risk factor for PCF, it only should be performed on well funded indication.

  13. Gender differences in the factors predicting initial engagement at cardiac rehabilitation.

    Science.gov (United States)

    Galdas, Paul Michael; Harrison, Alexander Stephen; Doherty, Patrick

    2018-01-01

    To determine whether there are gender differences in the factors that predict attendance at the initial cardiac rehabilitation baseline assessment (CR engagement) after referral. Using data from the National Audit of Cardiac Rehabilitation, we analysed data on 95 638 patients referred to CR following a cardiovascular diagnosis/treatment between 2013 and 2016. Eighteen factors that have been shown in previous research to be important predictors of CR participation were investigated and grouped into four categories: sociodemographic factors, cardiac risk factors, patient medical status and service-level factors. Logistic binary regression models were built for male patients and female patients, assessing the likelihood for CR engagement. Each included predictors such as age, number of comorbidities and social deprivation score. There were no important differences in the factors that predict the likelihood of CR engagement in men and women. Seven factors associated with a reduced probability of CR engagement, and eight factors associated with increased probability, were identified. Fourteen of the 15 factors identified as predicting the likelihood for engagement/non-engagement were the same for both men and women. Increasing age, being South Asian or non-white ethnicity (other than Black) and being single were all associated with a reduced likelihood of attending an initial CR baseline assessment in both men and women. Male patients with diabetes were 11% less likely to engage with CR; however, there was no significant association in women. Results showed that the overwhelmingly important determinant of CR engagement observed in both men and women was receiving an invitation to attend an assessment session (OR 4.223 men/4.033women; pgender differences in predictors of CR uptake should probably be more nuanced and informed by the stage of the patient care pathway.

  14. Factors predictive of sustained virological response following 72 weeks of combination therapy for genotype 1b hepatitis C.

    Science.gov (United States)

    Chayama, Kazuaki; Hayes, C Nelson; Yoshioka, Kentaro; Moriwaki, Hisataka; Okanoue, Takashi; Sakisaka, Shotaro; Takehara, Tetsuo; Oketani, Makoto; Toyota, Joji; Izumi, Namiki; Hiasa, Yoichi; Matsumoto, Akihiro; Nomura, Hideyuki; Seike, Masataka; Ueno, Yoshiyuki; Yotsuyanagi, Hiroshi; Kumada, Hiromitsu

    2011-04-01

    Treatment of genotype 1b chronic hepatitis C virus (HCV) infection has been improved by extending peg-interferon plus ribavirin combination therapy to 72 weeks, but predictive factors are needed to identify those patients who are likely to respond to long-term therapy. We analyzed amino acid (aa) substitutions in the core protein and the interferon sensitivity determining region (ISDR) of nonstructural protein (NS) 5A in 840 genotype 1b chronic hepatitis C patients with high viral load. We used logistic regression and classification and regression tree (CART) analysis to identify predictive factors for sustained virological response (SVR) for patients undergoing 72 weeks of treatment. When patients were separately analyzed by treatment duration using multivariate logistic regression, several factors, including sex, age, viral load, and core aa70 and ISDR substitutions (P = 0.0003, P = 0.02, P = 0.01, P = 0.0001, and P = 0.0004, respectively) were significant predictive factors for SVR with 48 weeks of treatment, whereas age, previous interferon treatment history, and ISDR substitutions (P = 0.03, P = 0.01, and P = 0.02, respectively) were the only significant predictive factors with 72 weeks of treatment. Using CART analysis, a decision tree was generated that identified age, cholesterol, sex, treatment length, and aa70 and ISDR substitutions as the most important predictive factors. The CART model had a sensitivity of 69.2% and specificity of 60%, with a positive predictive value of 68.4%. Complementary statistical and data mining approaches were used to identify a subgroup of patients likely to benefit from 72 weeks of therapy.

  15. Identifying and assessing the factors affecting skill gap in digital marketing in communication industry companies

    Directory of Open Access Journals (Sweden)

    Fereshteh Ghotbifar

    2017-03-01

    Full Text Available As far as new communication channels are concerned, there have been extensive developments in communications and marketing in digital era. Today, therefore, companies try to take advantage of digital marketing channels to provide suitable services to customers to improve their satisfaction level. However, this study aimed to identify and assess factors affecting skill gap in digital marketing. This was descriptive correlation study. The population consisted of experts in communications industry to identify most important skill gaps in digital marketing and factors affecting them; also, managers and specialists of these companies were investigated to determine the role of identified factors in reducing skills gaps. Using localized questionnaire and interviewing with ten experts who were selected by Delphi snowball method, the skill gaps in marketing and factors affecting them were identified. Also, a researcher made questionnaire with 32 questions was distributed among 226 employees to investigate the identified factors role in reducing skills gap in digital marketing. The results showed that from four identified factors, the components including operational strategic factors and environmental factors had direct and positive impact on creating skill gap in digital marketing of studied companies. The environmental factors such as social and cultural conditions, religion, technology, and economy had more proactive impact on skills gap in digital marketing. Also, the results showed that among skills gaps in digital marketing of studied companies, the skills (Principles of Communication and (Predicting Future had the highest and lowest gaps, respectively.

  16. [Predictive factors of anxiety disorders].

    Science.gov (United States)

    Domschke, K

    2014-10-01

    Anxiety disorders are among the most frequent mental disorders in Europe (12-month prevalence 14%) and impose a high socioeconomic burden. The pathogenesis of anxiety disorders is complex with an interaction of biological, environmental and psychosocial factors contributing to the overall disease risk (diathesis-stress model). In this article, risk factors for anxiety disorders will be presented on several levels, e.g. genetic factors, environmental factors, gene-environment interactions, epigenetic mechanisms, neuronal networks ("brain fear circuit"), psychophysiological factors (e.g. startle response and CO2 sensitivity) and dimensional/subclinical phenotypes of anxiety (e.g. anxiety sensitivity and behavioral inhibition), and critically discussed regarding their potential predictive value. The identification of factors predictive of anxiety disorders will possibly allow for effective preventive measures or early treatment interventions, respectively, and reduce the individual patient's suffering as well as the overall socioeconomic burden of anxiety disorders.

  17. Applying psychological theories to evidence-based clinical practice: Identifying factors predictive of managing upper respiratory tract infections without antibiotics

    Directory of Open Access Journals (Sweden)

    Glidewell Elizabeth

    2007-08-01

    try to avoid the use of antibiotics made significantly fewer scenario-based decisions to prescribe. In the cross theory analysis, perceived behavioural control (TPB, evidence of habitual behaviour (OLT, CS-SRM cause (chance/bad luck, and intention entered the equation, together explaining 36% of the variance. When predicting intention, at the theory level, the proportion of variance explained was: TPB, 30%; SCT, 29%; CS-SRM 27%; OLT, 43%. GPs who reported that they had already decided to change their management to try to avoid the use of antibiotics had a significantly higher intention to manage URTIs without prescribing antibiotics. In the cross theory analysis, OLT evidence of habitual behaviour, TPB attitudes, risk perception, CS-SRM control by doctor, TPB perceived behavioural control and CS-SRM control by treatment entered the equation, together explaining 49% of the variance in intention. Conclusion The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that predict clinical behaviour. However, a number of conceptual and methodological challenges remain.

  18. Factors predicting outcome in whiplash injury: a systematic meta-review of prognostic factors.

    Science.gov (United States)

    Sarrami, Pooria; Armstrong, Elizabeth; Naylor, Justine M; Harris, Ian A

    2017-03-01

    Whiplash injuries are among the leading injuries related to car crashes and it is important to determine the prognostic factors that predict the outcome of patients with these injuries. This meta-review aims to identify factors that are associated with outcome after acute whiplash injury. A systematic search for all systematic reviews on outcome prediction of acute whiplash injury was conducted across several electronic databases. The search was limited to publications in English, and there were no geographical or time of publication restrictions. Quality appraisal was conducted with A Measurement Tool to Assess Systematic Reviews. The initial search yielded 207 abstracts; of these, 195 were subsequently excluded by topic or method. Twelve systematic reviews with moderate quality were subsequently included in the analysis. Post-injury pain and disability, whiplash grades, cold hyperalgesia, post-injury anxiety, catastrophizing, compensation and legal factors, and early healthcare use were associated with continuation of pain and disability in patients with whiplash injury. Post-injury magnetic resonance imaging or radiographic findings, motor dysfunctions, or factors related to the collision were not associated with continuation of pain and disability in patients with whiplash injury. Evidence on demographic and three psychological factors and prior pain was conflicting, and there is a shortage of evidence related to the significance of genetic factors. This meta-review suggests an association between initial pain and anxiety and the outcome of acute whiplash injury, and less evidence for an association with physical factors. Level 1.

  19. A systems biology approach to transcription factor binding site prediction.

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    2010-03-01

    Full Text Available The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates.We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data.Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct-interaction detection and TFBS-discovery accuracy. We estimated the accuracy

  20. Risk Factors at Birth Predictive of Subsequent Injury Among Japanese Preschool Children: A Nationwide 5-Year Cohort Study.

    Science.gov (United States)

    Morioka, Hisayoshi; Itani, Osamu; Jike, Maki; Nakagome, Sachi; Otsuka, Yuichiro; Ohida, Takashi

    2018-03-19

    To identify risk factors at birth that are predictive of subsequent injury among preschool children. Retrospective analysis of population-based birth cohort data from the "Longitudinal Survey of Babies Born in the 21st Century" was performed from 2001 through 2007 in Japan (n = 47,015). The cumulative incidence and the total number of hospitalizations or examinations conducted at medical facilities for injury among children from birth up to the age of 5 years were calculated. To identify risk factors at birth that are predictive of injury, multivariate analysis of data for hospitalization or admission because of injury during a 5-year period (age, 0-5 years) was performed using the total number of hospital examinations as the dependent variable. The cumulative incidence (95% confidence interval) of hospital examinations for injury over the 5-year period was 34.8% (34.2%-35.4%) for boys and 27.6% (27.0%-28.2%) for girls. The predictive risk factors at birth we identified for injury among preschool children were sex (boys), heavy birth weight, late birth order, no cohabitation with the grandfather or grandmother, father's long working hours, mother's high education level, and strong intensity of parenting anxiety. Based on the results of this study, we identified a number of predictive factors for injury in children. To reduce the risk of injury in the juvenile population as a whole, it is important to pursue a high-risk or population approach by focusing on the predictive factors we have identified.

  1. Factors predicting weight-bearing asymmetry 1month after unilateral total knee arthroplasty: a cross-sectional study.

    Science.gov (United States)

    Christiansen, Cory L; Bade, Michael J; Weitzenkamp, David A; Stevens-Lapsley, Jennifer E

    2013-03-01

    Factors predicting weight-bearing asymmetry (WBA) after unilateral total knee arthroplasty (TKA) are not known. However, identifying modifiable and non-modifiable predictors of WBA is needed to optimize rehabilitation, especially since WBA is negatively correlated to poor functional performance. The purpose of this study was to identify factors predictive of WBA during sit-stand transitions for people 1month following unilateral TKA. Fifty-nine people were tested preoperatively and 1month following unilateral TKA for WBA using average vertical ground reaction force under each foot during the Five Times Sit-to-Stand Test. Candidate variables tested in the regression analysis represented physical impairments (strength, muscle activation, pain, and motion), demographics, anthropometrics, and movement compensations. WBA, measured as the ratio of surgical/non-surgical limb vertical ground reaction force, was 0.69 (0.18) (mean (SD)) 1month after TKA. Regression analysis identified preoperative WBA (β=0.40), quadriceps strength ratio (β=0.31), and hamstrings strength ratio (β=0.19) as factors predictive of WBA 1month after TKA (R(2)=0.30). Greater amounts of WBA 1month after TKA are predicted by modifiable factors including habitual movement pattern and asymmetry in quadriceps and hamstrings strength. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Consumer factors predicting level of treatment response to illness management and recovery.

    Science.gov (United States)

    White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

    2017-12-01

    This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  3. Identifying the important factors in simulation models with many factors

    NARCIS (Netherlands)

    Bettonvil, B.; Kleijnen, J.P.C.

    1994-01-01

    Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

  4. Predicting risk for childhood asthma by pre-pregnancy, perinatal, and postnatal factors.

    Science.gov (United States)

    Wen, Hui-Ju; Chiang, Tung-Liang; Lin, Shio-Jean; Guo, Yue Leon

    2015-05-01

    Symptoms of atopic disease start early in human life. Predicting risk for childhood asthma by early-life exposure would contribute to disease prevention. A birth cohort study was conducted to investigate early-life risk factors for childhood asthma and to develop a predictive model for the development of asthma. National representative samples of newborn babies were obtained by multistage stratified systematic sampling from the 2005 Taiwan Birth Registry. Information on potential risk factors and children's health was collected by home interview when babies were 6 months old and 5 yr old, respectively. Backward stepwise regression analysis was used to identify the risk factors of childhood asthma for predictive models that were used to calculate the probability of childhood asthma. A total of 19,192 children completed the study satisfactorily. Physician-diagnosed asthma was reported in 6.6% of 5-yr-old children. Pre-pregnancy factors (parental atopy and socioeconomic status), perinatal factors (place of residence, exposure to indoor mold and painting/renovations during pregnancy), and postnatal factors (maternal postpartum depression and the presence of atopic dermatitis before 6 months of age) were chosen for the predictive models, and the highest predicted probability of asthma in 5-yr-old children was 68.1% in boys and 78.1% in girls; the lowest probability in boys and girls was 4.1% and 3.2%, respectively. This investigation provides a technique for predicting risk of childhood asthma that can be used to developing a preventive strategy against asthma. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Treatment-Related Predictive and Prognostic Factors in Trimodality Approach in Stage IIIA/N2 Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Jeremić, Branislav; Casas, Francesc; Dubinsky, Pavol; Gomez-Caamano, Antonio; Čihorić, Nikola; Videtic, Gregory; Igrutinovic, Ivan

    2018-01-01

    While there are no established pretreatment predictive and prognostic factors in patients with stage IIIA/pN2 non-small cell lung cancer (NSCLC) indicating a benefit to surgery as a part of trimodality approach, little is known about treatment-related predictive and prognostic factors in this setting. A literature search was conducted to identify possible treatment-related predictive and prognostic factors for patients for whom trimodality approach was reported on. Overall survival was the primary endpoint of this study. Of 30 identified studies, there were two phase II studies, 5 "prospective" studies, and 23 retrospective studies. No study was found which specifically looked at treatment-related predictive factors of improved outcomes in trimodality treatment. Of potential treatment-related prognostic factors, the least frequently analyzed factors among 30 available studies were overall pathologic stage after preoperative treatment and UICC downstaging. Evaluation of treatment response before surgery and by pathologic tumor stage after induction therapy were analyzed in slightly more than 40% of studies and found not to influence survival. More frequently studied factors-resection status, degree of tumor regression, and pathologic nodal stage after induction therapy as well as the most frequently studied factor, the treatment (in almost 75% studies)-showed no discernible impact on survival, due to conflicting results. Currently, it is impossible to identify any treatment-related predictive or prognostic factors for selecting surgery in the treatment of patients with stage IIIA/pN2 NSCLC.

  6. Shoulder dystocia: risk factors, predictability, and preventability.

    Science.gov (United States)

    Mehta, Shobha H; Sokol, Robert J

    2014-06-01

    Shoulder dystocia remains an unpredictable obstetric emergency, striking fear in the hearts of obstetricians both novice and experienced. While outcomes that lead to permanent injury are rare, almost all obstetricians with enough years of practice have participated in a birth with a severe shoulder dystocia and are at least aware of cases that have resulted in significant neurologic injury or even neonatal death. This is despite many years of research trying to understand the risk factors associated with it, all in an attempt primarily to characterize when the risk is high enough to avoid vaginal delivery altogether and prevent a shoulder dystocia, whose attendant morbidities are estimated to be at a rate as high as 16-48%. The study of shoulder dystocia remains challenging due to its generally retrospective nature, as well as dependence on proper identification and documentation. As a result, the prediction of shoulder dystocia remains elusive, and the cost of trying to prevent one by performing a cesarean delivery remains high. While ultimately it is the injury that is the key concern, rather than the shoulder dystocia itself, it is in the presence of an identified shoulder dystocia that occurrence of injury is most common. The majority of shoulder dystocia cases occur without major risk factors. Moreover, even the best antenatal predictors have a low positive predictive value. Shoulder dystocia therefore cannot be reliably predicted, and the only preventative measure is cesarean delivery. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Predictive factor and antihypertensive usage of tyrosine kinase inhibitor-induced hypertension in kidney cancer patients

    Science.gov (United States)

    IZUMI, KOUJI; ITAI, SHINGO; TAKAHASHI, YOSHIKO; MAOLAKE, AERKEN; NAMIKI, MIKIO

    2014-01-01

    Hypertension (HT) is the common adverse event associated with vascular endothelial growth factor receptor-tyrosine kinase inhibitors (VEGFR-TKI). The present study was performed to identify the predictive factors of TKI-induced HT and to determine the classes of antihypertensive agents (AHTA) that demonstrate optimal efficacy against this type of HT. The charts of 50 cases of patients that had received VEGFR-TKI treatment were retrospectively examined. The association between patient background and TKI-induced HT, and the effect of administering AHTA were analyzed. High systolic blood pressure at baseline was identified to be a predictive factor for HT. In addition, there was no difference observed between calcium channel blockers (CCBs) and angiotensin receptor II blockers (ARBs) as first-line AHTA for the control of HT. The findings of the present study may aid with predicting the onset of TKI-induced HT, as well as for its management via the primary use of either CCBs or ARBs. PMID:24959266

  8. Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

    International Nuclear Information System (INIS)

    Thomassen, Mads; Tan, Qihua; Kruse, Torben A

    2008-01-01

    Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

  9. Factors associated with diabetes mellitus prediction among pregnant Arab subjects with gestational diabetes.

    Science.gov (United States)

    Aljohani, Naji; Al Serehi, Amal; Ahmed, Amjad M; Buhary, Badr Aldin M; Alzahrani, Saad; At-Taras, Eeman; Almujally, Najla; Alsharqi, Maha; Alqahtani, Mohammed; Almalki, Mussa

    2015-01-01

    There is scarcity of available information on the possible significant risk factors related to diabetes mellitus (DM) prediction among expectant Saudi mothers with gestational diabetes mellitus (GDM). The present study is the first to identify such risk factors in the Arab cohort. A total of 300 pregnant subjects (mean age 33.45 ± 6.5 years) were randomly selected from all the deliveries registered at the Obstetrics Department of King Fahad Medical City, Riyadh Saudi Arabia from April 2011 to March 2013. Demographic and baseline glycemic information were collected. A total of 7 highly significant and independent risk factors were identified: age, obesity, and family history of DM, GDM < 20 weeks, macrosomia, insulin therapy and recurrent GDM. Among these factors, subjects who had insulin therapy use are 5 times more likely to develop DMT2 (p-value 3.94 × 10(-14)) followed by recurrent GDM [odds-ratio 4.69 (Confidence Interval 2.34-4.84); P = 1.24 × 10(-13)). The identification of the risk factors mentioned with their respective predictive powers in the detection of DMT2 needs to be taken seriously in the post-partum assessment of Saudi pregnant patients at highest risk.

  10. Predictive Factors for Mortality and Morbidity of Ruptured Abdominal Aortic Aneurysm Repair

    Directory of Open Access Journals (Sweden)

    Manabu Shiraishi

    2012-04-01

    Conclusions: Emergency open repair can be safely performed in patients for infrarenal rAAA. In particular, we identified specific independent predictive factors of clinical examination and laboratory studies for mortality, major morbidity and renal insufficiency. [Arch Clin Exp Surg 2012; 1(2.000: 94-101

  11. Predictive Factors for Differentiating Between Septic Arthritis and Lyme Disease of the Knee in Children.

    Science.gov (United States)

    Baldwin, Keith D; Brusalis, Christopher M; Nduaguba, Afamefuna M; Sankar, Wudbhav N

    2016-05-04

    Differentiating between septic arthritis and Lyme disease of the knee in endemic areas can be challenging and has major implications for patient management. The purpose of this study was to identify a prediction rule to differentiate septic arthritis from Lyme disease in children presenting with knee pain and effusion. We retrospectively reviewed the records of patients younger than 18 years of age with knee effusions who underwent arthrocentesis at our institution from 2005 to 2013. Patients with either septic arthritis (positive joint fluid culture or synovial white blood-cell count of >60,000 white blood cells/mm(3) with negative Lyme titer) or Lyme disease (positive Lyme immunoglobulin G on Western blot analysis) were included. To avoid misclassification bias, undiagnosed knee effusions and joints with both a positive culture and positive Lyme titers were excluded. Historical, clinical, and laboratory data were compared between groups to identify variables for comparison. Binary logistic regression analysis was used to identify independent predictive variables. One hundred and eighty-nine patients were studied: 23 with culture-positive septic arthritis, 26 with culture-negative septic arthritis, and 140 with Lyme disease. Multivariate binary logistic regression identified pain with short arc motion, history of fever reported by the patient or a family member, C-reactive protein of >4 mg/L, and age younger than 2 years as independent predictive factors for septic arthritis. A simpler model was developed that showed that the risk of septic arthritis with none of these factors was 2%, with 1 of these factors was 18%, with 2 of these factors was 45%, with 3 of these factors was 84%, or with all 4 of these factors was 100%. Although septic arthritis of the knee and Lyme monoarthritis share common features that can make them difficult to distinguish clinically, the presence of pain with short arc motion, C-reactive protein of >4.0 mg/L, patient-reported history of

  12. Examining Factors Predicting Students’ Digital Competence

    Directory of Open Access Journals (Sweden)

    Ove Edvard Hatlevik

    2015-02-01

    Full Text Available The purpose of this study was to examine factors predicting lower secondary school students’ digital competence and to explore differences between students when it comes to digital competence. Results from a digital competence test and survey in lower secondary school will be presented. It is important to learn more about and investigate what characterizes students’ digital competence. A sample of 852 ninth-grade Norwegian students from 38 schools participated in the study. The students answered a 26 item multiple-choice digital competence test and a self-report questionnaire about family background, motivation, and previous grades. Structural equation modeling was used to test a model of the hypothesised relationship between family background, mastery orientation, previous achievements, and digital competence. The results indicate variation in digital competence among the ninth-graders. Further, analyses showed that students’ conditions at home, i.e., language integration and cultural capital, together with mastery orientation and academic achievements predict students digital competence. This study indicates that that there is evidence of digital diversity between lower secondary students. It does not seem like the development of digital competence among the students happens automatically. Students’ family background and school performance are the most important factors. Therefore, as this study shows, it is necessary to further investigate how schools can identify students’ level of competence and to develop plans and actions for how schools can help to try to equalize differences.

  13. Predictive factors for red blood cell transfusion in children undergoing noncomplex cardiac surgery.

    Science.gov (United States)

    Mulaj, Muj; Faraoni, David; Willems, Ariane; Sanchez Torres, Cristel; Van der Linden, Philippe

    2014-08-01

    Red blood cell (RBC) transfusion is frequently required in pediatric cardiac surgery and is associated with altered outcome and increased costs. Determining which factors predict transfusion in this context will enable clinicians to adopt strategies that will reduce the risk of RBC transfusion. This study aimed to assess predictive factors associated with RBC transfusion in children undergoing low-risk cardiac surgery with cardiopulmonary bypass (CPB). Children undergoing surgery to repair ventricular septal defect or atrioventricular septal defect from 2006 to 2011 were included in this retrospective study. Demography, preoperative laboratory testing, intraoperative data, and RBC transfusion were reviewed. Univariate and multivariate logistic regression analysis were used to define factors that were able to predict RBC transfusion. Then, we employed receiver operating characteristic analysis to design a predictive score. Among the 334 children included, 261 (78%) were transfused. Age (43 mL/kg), type of oxygenator used, minimal temperature reached during CPB (<32°C), and preoperative hematocrit (<34%) were independently associated with RBC transfusion in the studied population. A predictive score 2 or greater was the best predictor of RBC transfusion. The present study identified several factors that were significantly associated with perioperative RBC transfusion. Based on these factors, we designed a predictive score that can be used to develop a patient-based blood management program with the aim of reducing the incidence of RBC transfusion. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  14. Children's First Experience of Taking Anabolic-Androgenic Steroids can Occur before Their 10th Birthday: A Systematic Review Identifying 9 Factors That Predicted Doping among Young People

    Science.gov (United States)

    Nicholls, Adam R.; Cope, Ed; Bailey, Richard; Koenen, Katrin; Dumon, Detlef; Theodorou, Nikolaos C.; Chanal, Benoit; Saint Laurent, Delphine; Müller, David; Andrés, Mar P.; Kristensen, Annemarie H.; Thompson, Mark A.; Baumann, Wolfgang; Laurent, Jean-Francois

    2017-01-01

    Taking performance-enhancing drugs (PEDs) can cause serious and irreversible health consequences, which can ultimately lead to premature death. Some young people may take PEDs without fully understanding the ramifications of their actions or based on the advice from others. The purpose of this systematic review was to identify the main factors that predicted doping among young people. The literature was systematically reviewed using search engines, manually searching specialist journals, and pearl growing. Fifty-two studies, which included 187,288 young people aged between 10 and 21 years of age, 883 parents of adolescent athletes, and 11 adult coaches, who were interviewed regarding young athletes, were included in this review. Nine factors predicted doping among young people: gender; age; sports participation; sport type; psychological variables; entourage; ethnicity; nutritional supplements; and health harming behaviors. In regards to psychological variables, 22 different constructs were associated with doping among young people. Some psychological constructs were negatively associated with doping (e.g., self-esteem, resisting social pressure, and perfectionist strivings), whereas other were positively associated with doping (e.g., suicide risk, anticipated regret, and aggression). Policy makers and National Anti-Doping Organizations could use these findings to help identify athletes who are more at risk of doping and then expose these individuals to anti-doping education. Based on the current findings, it also appears that education programs should commence at the onset of adolescence or even late childhood, due to the young age in which some individuals start doping. PMID:28676778

  15. Children's First Experience of Taking Anabolic-Androgenic Steroids can Occur before Their 10th Birthday: A Systematic Review Identifying 9 Factors That Predicted Doping among Young People.

    Science.gov (United States)

    Nicholls, Adam R; Cope, Ed; Bailey, Richard; Koenen, Katrin; Dumon, Detlef; Theodorou, Nikolaos C; Chanal, Benoit; Saint Laurent, Delphine; Müller, David; Andrés, Mar P; Kristensen, Annemarie H; Thompson, Mark A; Baumann, Wolfgang; Laurent, Jean-Francois

    2017-01-01

    Taking performance-enhancing drugs (PEDs) can cause serious and irreversible health consequences, which can ultimately lead to premature death. Some young people may take PEDs without fully understanding the ramifications of their actions or based on the advice from others. The purpose of this systematic review was to identify the main factors that predicted doping among young people. The literature was systematically reviewed using search engines, manually searching specialist journals, and pearl growing. Fifty-two studies, which included 187,288 young people aged between 10 and 21 years of age, 883 parents of adolescent athletes, and 11 adult coaches, who were interviewed regarding young athletes, were included in this review. Nine factors predicted doping among young people: gender; age; sports participation; sport type; psychological variables; entourage; ethnicity; nutritional supplements; and health harming behaviors. In regards to psychological variables, 22 different constructs were associated with doping among young people. Some psychological constructs were negatively associated with doping (e.g., self-esteem, resisting social pressure, and perfectionist strivings), whereas other were positively associated with doping (e.g., suicide risk, anticipated regret, and aggression). Policy makers and National Anti-Doping Organizations could use these findings to help identify athletes who are more at risk of doping and then expose these individuals to anti-doping education. Based on the current findings, it also appears that education programs should commence at the onset of adolescence or even late childhood, due to the young age in which some individuals start doping.

  16. Prevalence and predictive factors of post-traumatic hypopituitarism

    DEFF Research Database (Denmark)

    Klose, M; Juul, A; Poulsgaard, L

    2007-01-01

    To estimate the prevalence and predictive factors of hypopituitarism following traumatic brain injury (TBI).......To estimate the prevalence and predictive factors of hypopituitarism following traumatic brain injury (TBI)....

  17. Factors predicting labor induction success: a critical analysis.

    Science.gov (United States)

    Crane, Joan M G

    2006-09-01

    Because of the risk of failed induction of labor, a variety of maternal and fetal factors as well as screening tests have been suggested to predict labor induction success. Certain characteristics of the woman (including parity, age, weight, height and body mass index), and of the fetus (including birth weight and gestational age) are associated with the success of labor induction; with parous, young women who are taller and lower weight having a higher rate of induction success. Fetuses with a lower birth weight or increased gestational age are also associated with increased induction success. The condition of the cervix at the start of induction is an important predictor, with the modified Bishop score being a widely used scoring system. The most important element of the Bishop score is dilatation. Other predictors, including transvaginal ultrasound (TVUS) and biochemical markers [including fetal fibronectin (fFN)] have been suggested. Meta-analyses of studies identified from MEDLINE, PubMed, and EMBASE and published from 1990 to October 2005 were performed evaluating the use of TVUS and fFN in predicting labor induction success in women at term with singleton gestations. Both TVUS and Bishop score predicted successful induction [likelihood ratio (LR)=1.82, 95% confidence interval (CI)=1.51-2.20 and LR=2.10, 95%CI=1.67-2.64, respectively]. As well, fFN and Bishop score predicted successful induction (LR=1.49, 95%CI=1.20-1.85, and LR=2.62, 95%CI=1.88-3.64, respectively). Although TVUS and fFN predicted successful labor induction, neither has been shown to be superior to Bishop score. Further research is needed to evaluate these potential predictors and insulin-like growth factor binding protein-1 (IGFBP-1), another potential biochemical marker.

  18. Technical Note: Assessing predictive capacity and conditional independence of landslide predisposing factors for shallow landslide susceptibility models

    Directory of Open Access Journals (Sweden)

    S. Pereira

    2012-04-01

    Full Text Available The aim of this study is to identify the landslide predisposing factors' combination using a bivariate statistical model that best predicts landslide susceptibility. The best model is one that has simultaneously good performance in terms of suitability and predictive power and has been developed using variables that are conditionally independent. The study area is the Santa Marta de Penaguião council (70 km2 located in the Northern Portugal.

    In order to identify the best combination of landslide predisposing factors, all possible combinations using up to seven predisposing factors were performed, which resulted in 120 predictions that were assessed with a landside inventory containing 767 shallow translational slides. The best landslide susceptibility model was selected according to the model degree of fitness and on the basis of a conditional independence criterion. The best model was developed with only three landslide predisposing factors (slope angle, inverse wetness index, and land use and was compared with a model developed using all seven landslide predisposing factors.

    Results showed that it is possible to produce a reliable landslide susceptibility model using fewer landslide predisposing factors, which contributes towards higher conditional independence.

  19. Beyond Engagement Analytics: Which Online Mixed-Data Factors Predict Student Learning Outcomes?

    Science.gov (United States)

    Strang, Kenneth David

    2017-01-01

    This mixed-method study focuses on online learning analytics, a research area of importance. Several important student attributes and their online activities are examined to identify what seems to work best to predict higher grades. The purpose is to explore the relationships between student grade and key learning engagement factors using a large…

  20. Developing Predictive Models for Algal Bloom Occurrence and Identifying Factors Controlling their Occurrence in the Charlotte County and Surroundings

    Science.gov (United States)

    Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.

    2017-12-01

    Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.

  1. Children's First Experience of Taking Anabolic-Androgenic Steroids can Occur before Their 10th Birthday: A Systematic Review Identifying 9 Factors That Predicted Doping among Young People

    Directory of Open Access Journals (Sweden)

    Adam R. Nicholls

    2017-06-01

    Full Text Available Taking performance-enhancing drugs (PEDs can cause serious and irreversible health consequences, which can ultimately lead to premature death. Some young people may take PEDs without fully understanding the ramifications of their actions or based on the advice from others. The purpose of this systematic review was to identify the main factors that predicted doping among young people. The literature was systematically reviewed using search engines, manually searching specialist journals, and pearl growing. Fifty-two studies, which included 187,288 young people aged between 10 and 21 years of age, 883 parents of adolescent athletes, and 11 adult coaches, who were interviewed regarding young athletes, were included in this review. Nine factors predicted doping among young people: gender; age; sports participation; sport type; psychological variables; entourage; ethnicity; nutritional supplements; and health harming behaviors. In regards to psychological variables, 22 different constructs were associated with doping among young people. Some psychological constructs were negatively associated with doping (e.g., self-esteem, resisting social pressure, and perfectionist strivings, whereas other were positively associated with doping (e.g., suicide risk, anticipated regret, and aggression. Policy makers and National Anti-Doping Organizations could use these findings to help identify athletes who are more at risk of doping and then expose these individuals to anti-doping education. Based on the current findings, it also appears that education programs should commence at the onset of adolescence or even late childhood, due to the young age in which some individuals start doping.

  2. Predicting performance at medical school: can we identify at-risk students?

    Directory of Open Access Journals (Sweden)

    Shaban S

    2011-05-01

    Full Text Available Sami Shaban, Michelle McLeanDepartment of Medical Education, Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab EmiratesBackground: The purpose of this study was to examine the predictive potential of multiple indicators (eg, preadmission scores, unit, module and clerkship grades, course and examination scores on academic performance at medical school, with a view to identifying students at risk.Methods: An analysis was undertaken of medical student grades in a 6-year medical school program at the Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates, over the past 14 years.Results: While high school scores were significantly (P < 0.001 correlated with the final integrated examination, predictability was only 6.8%. Scores for the United Arab Emirates university placement assessment (Common Educational Proficiency Assessment were only slightly more promising as predictors with 14.9% predictability for the final integrated examination. Each unit or module in the first four years was highly correlated with the next unit or module, with 25%–60% predictability. Course examination scores (end of years 2, 4, and 6 were significantly correlated (P < 0.001 with the average scores in that 2-year period (59.3%, 64.8%, and 55.8% predictability, respectively. Final integrated examination scores were significantly correlated (P < 0.001 with National Board of Medical Examiners scores (35% predictability. Multivariate linear regression identified key grades with the greatest predictability of the final integrated examination score at three stages in the program.Conclusion: This study has demonstrated that it may be possible to identify “at-risk” students relatively early in their studies through continuous data archiving and regular analysis. The data analysis techniques used in this study are not unique to this institution.Keywords: at-risk students, grade

  3. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    International Nuclear Information System (INIS)

    Brinkmann, Markus; Eichbaum, Kathrin; Kammann, Ulrike; Hudjetz, Sebastian; Cofalla, Catrina; Buchinger, Sebastian; Reifferscheid, Georg; Schüttrumpf, Holger; Preuss, Thomas

    2014-01-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios

  4. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    Energy Technology Data Exchange (ETDEWEB)

    Brinkmann, Markus; Eichbaum, Kathrin [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Kammann, Ulrike [Thünen-Institute of Fisheries Ecology, Palmaille 9, 22767 Hamburg (Germany); Hudjetz, Sebastian [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Cofalla, Catrina [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Buchinger, Sebastian; Reifferscheid, Georg [Federal Institute of Hydrology (BFG), Department G3: Biochemistry, Ecotoxicology, Am Mainzer Tor 1, 56068 Koblenz (Germany); Schüttrumpf, Holger [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Preuss, Thomas [Department of Environmental Biology and Chemodynamics, Institute for Environmental Research,ABBt- Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); and others

    2014-07-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios.

  5. Factors predictive for incidence and remission of internet addiction in young adolescents: a prospective study.

    Science.gov (United States)

    Ko, Chih-Hung; Yen, Ju-Yu; Yen, Cheng-Fang; Lin, Huang-Chi; Yang, Ming-Jen

    2007-08-01

    The aim of the study is to determine the incidence and remission rates for Internet addiction and the associated predictive factors in young adolescents over a 1-year follow-up. This was a prospective, population-based investigation. Five hundred seventeen students (267 male and 250 female) were recruited from three junior high schools in southern Taiwan. The factors examined included gender, personality, mental health, self-esteem, family function, life satisfaction, and Internet activities. The result revealed that the 1-year incidence and remission rates for Internet addiction were 7.5% and 49.5% respectively. High exploratory excitability, low reward dependence, low self-esteem, low family function, and online game playing predicted the emergency of the Internet addiction. Further, low hostility and low interpersonal sensitivity predicted remission of Internet addiction. The factors predictive incidence and remission of Internet addiction identified in this study could be provided for prevention and promoting remission of Internet addiction in adolescents.

  6. Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

    Science.gov (United States)

    Fu, Guangyuan; Wang, Jun; Domeniconi, Carlotta; Yu, Guoxian

    2018-05-01

    Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be. To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological

  7. Identifying factors affecting optimal management of agricultural water

    Directory of Open Access Journals (Sweden)

    Masoud Samian

    2015-01-01

    In addition to quantitative methodology such as descriptive statistics and factor analysis a qualitative methodology was employed for dynamic simulation among variables through Vensim software. In this study, the factor analysis technique was used through the Kaiser-Meyer-Olkin (KMO and Bartlett tests. From the results, four key elements were identified as factors affecting the optimal management of agricultural water in Hamedan area. These factors were institutional and legal factors, technical and knowledge factors, economic factors and social factors.

  8. Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

    Science.gov (United States)

    Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

    2018-02-01

    Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

  9. Identifying Factors for Worker Motivation in Zambia's Rural Health Facilities.

    Science.gov (United States)

    Cross, Samuel S; Baernholdt, Dr Marianne

    2017-01-01

    Within Zambia there is a shortage of health workers in rural areas. This study aims to identify motivating factors for retaining rural health workers. Sixty rural health workers completed surveys and 46 were interviewed. They rated the importance of six motivating factors and discussed these and other factors in interviews. An interview was conducted with a Government Human Resources Manager (HR Manager) to elicit contextual information. All six factors were identified as being very important motivators, as were two additional factors. Additional career training was identified by many as the most important factor. Comparison of results and the HR Manager interview revealed that workers lacked knowledge about opportunities and that the HR manager was aware of barriers to career development. The Zambian government might better motivate and retain rural health workers by offering them any combination of identified factors, and by addressing the barriers to career development.

  10. Identifying motivational factors within a multinational company

    Directory of Open Access Journals (Sweden)

    Daniela Bradutanu

    2011-08-01

    Full Text Available The aim of the study is to identify the main motivational factors within a multinational company. The first objective is to identify work functions, formulated on Abraham Maslow’s pyramid, following the identification of the key characteristics that motivate an employee at the work place and last, but not least, the type of motivation that employees focus, intrinsic or extrinsic. The research method targeted a questionnaire based survey, including various company employees and an interview with the manager. The results confirmed that in Romania, employees put great emphasis on extrinsic motivation, a certain income and job security being primary. These results have implications for managers that in order to effectively motivate staff, first, must know their needs and expectations. To identify the main needs and motivational factors we had as a starting point Maslow's pyramid.

  11. Using Hierarchical Linear Modelling to Examine Factors Predicting English Language Students' Reading Achievement

    Science.gov (United States)

    Fung, Karen; ElAtia, Samira

    2015-01-01

    Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…

  12. X-factor for innovation: identifying future excellent professionals

    NARCIS (Netherlands)

    den Hertog, J.H.

    2016-01-01

    In this study we wanted to identify which type of individual is capable of achieving professional excellence. Our main question therefore read: which individual antecedents predict professional excellence? We chose to focus on personality traits and specifically on proactive personality - the

  13. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. Contextual Predictive Factors of Child Sexual Abuse: The Role of Parent-Child Interaction

    Science.gov (United States)

    Ramirez, Clemencia; Pinzon-Rondon, Angela Maria; Botero, Juan Carlos

    2011-01-01

    Objectives: To determine the prevalence of child sexual abuse in the Colombian coasts, as well as to assess the role of parent-child interactions on its occurrence and to identify factors from different environmental levels that predict it. Methods: This cross-sectional study explores the results of 1,089 household interviews responded by mothers.…

  15. Predictive factors of gastroduodenal toxicity in cirrhotic patients after three-dimensional conformal radiotherapy for hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Kim, Haeyoung; Lim, Do Hoon; Paik, Seung Woon; Yoo, Byung Chul; Koh, Kwang Gheol; Lee, Joon Hyoek; Choi, Moon Seok; Park, Won; Park, Hee Chul; Huh, Seung Jae; Choi, Doo Ho; Ahn, Yong Chan

    2009-01-01

    Background and purpose: To identify predictive factors for the development of gastroduodenal toxicity (GDT) in cirrhotic patients treated with three-dimensional conformal radiotherapy (3D-CRT) for hepatocellular carcinoma (HCC). Materials and methods: We retrospectively analyzed dose-volume histograms (DVHs) and clinical records of 73 cirrhotic patients treated with 3D-CRT for HCC. The median radiation dose was 36 Gy (range, 30-54 Gy) with a daily dose of 3 Gy. The grade of GDT was defined by the Common Toxicity Criteria Version 2. The predictive factors of grade 3 GDT were identified. Results: Grade 3 GDT was found in 9 patients. Patient's age and the percentage of gastroduodenal volume receiving more than 35 Gy (V 35 ) significantly affected the development of grade 3 GDT. Patients over 50 years of age developed grade 3 GDT more frequently than patients under 50 years of age. The risk of grade 3 GDT grew exponentially as V 35 increased. The 1-year actuarial rate of grade 3 GDT in patients with V 35 35 ≥5% (4% vs. 48%, p 35 were the most predictive factors for the development of grade 3 GDT in patients treated with RT.

  16. High-throughput respirometric assay identifies predictive toxicophore of mitochondrial injury

    Energy Technology Data Exchange (ETDEWEB)

    Wills, Lauren P. [MitoHealth Inc., Charleston, SC 29403 (United States); Beeson, Gyda C.; Trager, Richard E.; Lindsey, Christopher C. [Department of Drug Discovery and Biomedical Sciences, Medical University of South Carolina, Charleston, SC 29425 (United States); Beeson, Craig C. [MitoHealth Inc., Charleston, SC 29403 (United States); Peterson, Yuri K. [Department of Drug Discovery and Biomedical Sciences, Medical University of South Carolina, Charleston, SC 29425 (United States); Schnellmann, Rick G., E-mail: schnell@musc.edu [Department of Drug Discovery and Biomedical Sciences, Medical University of South Carolina, Charleston, SC 29425 (United States); Ralph H. Johnson VA Medical Center, Charleston, SC 29401 (United States)

    2013-10-15

    Many environmental chemicals and drugs negatively affect human health through deleterious effects on mitochondrial function. Currently there is no chemical library of mitochondrial toxicants, and no reliable methods for predicting mitochondrial toxicity. We hypothesized that discrete toxicophores defined by distinct chemical entities can identify previously unidentified mitochondrial toxicants. We used a respirometric assay to screen 1760 compounds (5 μM) from the LOPAC and ChemBridge DIVERSet libraries. Thirty-one of the assayed compounds decreased uncoupled respiration, a stress test for mitochondrial dysfunction, prior to a decrease in cell viability and reduced the oxygen consumption rate in isolated mitochondria. The mitochondrial toxicants were grouped by chemical similarity and two clusters containing four compounds each were identified. Cheminformatic analysis of one of the clusters identified previously uncharacterized mitochondrial toxicants from the ChemBridge DIVERSet. This approach will enable the identification of mitochondrial toxicants and advance the prediction of mitochondrial toxicity for both drug discovery and risk assessment. - Highlights: • Respirometric assay conducted in RPTC to create mitochondrial toxicant database. • Chemically similar mitochondrial toxicants aligned as mitochondrial toxicophores • Mitochondrial toxicophore identifies five novel mitochondrial toxicants.

  17. High-throughput respirometric assay identifies predictive toxicophore of mitochondrial injury

    International Nuclear Information System (INIS)

    Wills, Lauren P.; Beeson, Gyda C.; Trager, Richard E.; Lindsey, Christopher C.; Beeson, Craig C.; Peterson, Yuri K.; Schnellmann, Rick G.

    2013-01-01

    Many environmental chemicals and drugs negatively affect human health through deleterious effects on mitochondrial function. Currently there is no chemical library of mitochondrial toxicants, and no reliable methods for predicting mitochondrial toxicity. We hypothesized that discrete toxicophores defined by distinct chemical entities can identify previously unidentified mitochondrial toxicants. We used a respirometric assay to screen 1760 compounds (5 μM) from the LOPAC and ChemBridge DIVERSet libraries. Thirty-one of the assayed compounds decreased uncoupled respiration, a stress test for mitochondrial dysfunction, prior to a decrease in cell viability and reduced the oxygen consumption rate in isolated mitochondria. The mitochondrial toxicants were grouped by chemical similarity and two clusters containing four compounds each were identified. Cheminformatic analysis of one of the clusters identified previously uncharacterized mitochondrial toxicants from the ChemBridge DIVERSet. This approach will enable the identification of mitochondrial toxicants and advance the prediction of mitochondrial toxicity for both drug discovery and risk assessment. - Highlights: • Respirometric assay conducted in RPTC to create mitochondrial toxicant database. • Chemically similar mitochondrial toxicants aligned as mitochondrial toxicophores • Mitochondrial toxicophore identifies five novel mitochondrial toxicants

  18. Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

    Science.gov (United States)

    Razavian, Narges; Blecker, Saul; Schmidt, Ann Marie; Smith-McLallen, Aaron; Nigam, Somesh; Sontag, David

    2015-12-01

    We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion, population-level risk

  19. Increasing organizational energy conservation behaviors: Comparing the theory of planned behavior and reasons theory for identifying specific motivational factors to target for change

    Science.gov (United States)

    Finlinson, Scott Michael

    Social scientists frequently assess factors thought to underlie behavior for the purpose of designing behavioral change interventions. Researchers commonly identify these factors by examining relationships between specific variables and the focal behaviors being investigated. Variables with the strongest relationships to the focal behavior are then assumed to be the most influential determinants of that behavior, and therefore often become the targets for change in a behavioral change intervention. In the current proposal, multiple methods are used to compare the effectiveness of two theoretical frameworks for identifying influential motivational factors. Assessing the relative influence of all factors and sets of factors for driving behavior should clarify which framework and methodology is the most promising for identifying effective change targets. Results indicated each methodology adequately predicted the three focal behaviors examined. However, the reasons theory approach was superior for predicting factor influence ratings compared to the TpB approach. While common method variance contamination had minimal impact on the results or conclusions derived from the present study's findings, there were substantial differences in conclusions depending on the questionnaire design used to collect the data. Examples of applied uses of the present study are discussed.

  20. Evaluation of easily measured risk factors in the prediction of osteoporotic fractures

    Directory of Open Access Journals (Sweden)

    Brown Jacques P

    2005-09-01

    Full Text Available Abstract Background Fracture represents the single most important clinical event in patients with osteoporosis, yet remains under-predicted. As few premonitory symptoms for fracture exist, it is of critical importance that physicians effectively and efficiently identify individuals at increased fracture risk. Methods Of 3426 postmenopausal women in CANDOO, 40, 158, 99, and 64 women developed a new hip, vertebral, wrist or rib fracture, respectively. Seven easily measured risk factors predictive of fracture in research trials were examined in clinical practice including: age (, 65–69, 70–74, 75–79, 80+ years, rising from a chair with arms (yes, no, weight (≥ 57kg, maternal history of hip facture (yes, no, prior fracture after age 50 (yes, no, hip T-score (>-1, -1 to >-2.5, ≤-2.5, and current smoking status (yes, no. Multivariable logistic regression analysis was conducted. Results The inability to rise from a chair without the use of arms (3.58; 95% CI: 1.17, 10.93 was the most significant risk factor for new hip fracture. Notable risk factors for predicting new vertebral fractures were: low body weight (1.57; 95% CI: 1.04, 2.37, current smoking (1.95; 95% CI: 1.20, 3.18 and age between 75–79 years (1.96; 95% CI: 1.10, 3.51. New wrist fractures were significantly identified by low body weight (1.71, 95% CI: 1.01, 2.90 and prior fracture after 50 years (1.96; 95% CI: 1.19, 3.22. Predictors of new rib fractures include a maternal history of a hip facture (2.89; 95% CI: 1.04, 8.08 and a prior fracture after 50 years (2.16; 95% CI: 1.20, 3.87. Conclusion This study has shown that there exists a variety of predictors of future fracture, besides BMD, that can be easily assessed by a physician. The significance of each variable depends on the site of incident fracture. Of greatest interest is that an inability to rise from a chair is perhaps the most readily identifiable significant risk factor for hip fracture and can be easily incorporated

  1. What are the most crucial soil factors for predicting the distribution of alpine plant species?

    Science.gov (United States)

    Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

    2017-12-01

    Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil p

  2. A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.

    Science.gov (United States)

    Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham

    2018-03-06

    Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.

  3. Factors predicting survival in amyotrophic lateral sclerosis patients on non-invasive ventilation.

    Science.gov (United States)

    Gonzalez Calzada, Nuria; Prats Soro, Enric; Mateu Gomez, Lluis; Giro Bulta, Esther; Cordoba Izquierdo, Ana; Povedano Panades, Monica; Dorca Sargatal, Jordi; Farrero Muñoz, Eva

    2016-01-01

    Non invasive ventilation (NIV) improves quality of life and extends survival in amyotrophic lateral sclerosis (ALS) patients. However, few data exist about the factors related to survival. We intended to assess the predictive factors that influence survival in patients after NIV initiation. Patients who started NIV from 2000 to 2014 and were tolerant (compliance ≥ 4 hours) were included; demographic, disease related and respiratory variables at NIV initiation were analysed. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. 213 patients were included with median survival from NIV initiation of 13.5 months. In univariate analysis, the identified risk factors for mortality were severity of bulbar involvement (HR 2), Forced Vital Capacity (FVC) % (HR 0.99) and ALSFRS-R (HR 0.97). Multivariate analysis showed that bulbar involvement (HR 1.92) and ALSFRS-R (HR 0.97) were independent predictive factors of survival in patients on NIV. In our study, the two prognostic factors in ALS patients following NIV were the severity of bulbar involvement and ALSFRS-R at the time on NIV initiation. A better assessment of bulbar involvement, including evaluation of the upper airway, and a careful titration on NIV are necessary to optimize treatment efficacy.

  4. Identifying Clinical Factors Which Predict for Early Failure Patterns Following Resection for Pancreatic Adenocarcinoma in Patients Who Received Adjuvant Chemotherapy Without Chemoradiation.

    Science.gov (United States)

    Walston, Steve; Salloum, Joseph; Grieco, Carmine; Wuthrick, Evan; Diaz, Dayssy A; Barney, Christian; Manilchuk, Andrei; Schmidt, Carl; Dillhoff, Mary; Pawlik, Timothy M; Williams, Terence M

    2018-05-04

    The role of radiation therapy (RT) in resected pancreatic cancer (PC) remains incompletely defined. We sought to determine clinical variables which predict for local-regional recurrence (LRR) to help select patients for adjuvant RT. We identified 73 patients with PC who underwent resection and adjuvant gemcitabine-based chemotherapy alone. We performed detailed radiologic analysis of first patterns of failure. LRR was defined as recurrence of PC within standard postoperative radiation volumes. Univariate analyses (UVA) were conducted using the Kaplan-Meier method and multivariate analyses (MVA) utilized the Cox proportional hazard ratio model. Factors significant on UVA were used for MVA. At median follow-up of 20 months, rates of local-regional recurrence only (LRRO) were 24.7%, LRR as a component of any failure 68.5%, metastatic recurrence (MR) as a component of any failure 65.8%, and overall disease recurrence (OR) 90.5%. On UVA, elevated postoperative CA 19-9 (>90 U/mL), pathologic lymph node positive (pLN+) disease, and higher tumor grade were associated with increased LRR, MR, and OR. On MVA, elevated postoperative CA 19-9 and pLN+ were associated with increased MR and OR. In addition, positive resection margin was associated with increased LRRO on both UVA and MVA. About 25% of patients with PC treated without adjuvant RT develop LRRO as initial failure. The only independent predictor of LRRO was positive margin, while elevated postoperative CA 19-9 and pLN+ were associated with predicting MR and overall survival. These data may help determine which patients benefit from intensification of local therapy with radiation.

  5. Factors Predictive of Alcohol Consumption among Elderly People in a Rural Community: A Case Study in Phayao Province Thailand

    International Nuclear Information System (INIS)

    Hongthong, D.; Wongchaiya, P.; Somrongthong, R.; Kumar, R.

    2016-01-01

    Background: Alcohol consumption is recognized as a public health issue. Study objectives were to identify factors predictive of alcohol consumption among elderly people in Phayao province Thailand, where there was high prevalence of alcohol consumption. Methods: This was a cross-sectional study. Four hundred elderly people participated in a survey. Data was collected by face-to-face interviews. Chi-square and multivariate logistic regression were used to determine the factors predictive of alcohol consumption among the study subjects. Results: One thirds of elderly (31.7 percent) had consumed alcohol in their lifetime, and (15.7 percent) of them were current drinkers. Following univariate analysis, seven factors included gender, working, sickness, smoking, quality of life (QOL), daily activities and economic recession were identified as being significantly associated with drinking (p<0.05). Multivariate analysis revealed four factors to be predictive of alcohol among elderly people: gender (OR=6.02, 95 percent CI=3.58-10.13), smoking (OR=4.34, 95 percent CI=2.57-7.34), economic recession (OR=2.79, 95 percent, CI=1.66-4.71), and QOL (OR=1.86, 95 percent, CI=1.09-3.16). Conclusion: Gender (male) and smoking were strongly predictive factors of elderly alcohol consumption. Hence, an effort to reduce alcohol consumption should be placed on male elderly and those who smoke. (author)

  6. Long-term results of preventive embolization of renal angiomyolipomas: evaluation of predictive factors of volume decrease

    Energy Technology Data Exchange (ETDEWEB)

    Hocquelet, A.; Cornelis, F.; Le Bras, Y.; Meyer, M.; Tricaud, E.; Lasserre, A.S.; Grenier, N. [Centre Hospitalier Universitaire Pellegrin, Diagnostic and Therapeutic Urology and Vascular Imaging, Bordeaux (France); Ferriere, J.M.; Robert, G. [Centre Hospitalier Universitaire Pellegrin, Urology Service, Bordeaux (France)

    2014-08-15

    To evaluate the efficacy of selective arterial embolization (SAE) of angiomyolipomas based on the percentage volume reduction after embolization and to identify predictive factors of volume decrease. Patients receiving prophylactic SAE of renal angiomyolipomas were included retrospectively over 3 years. The volume change after SAE and haemorrhagic or surgical events were recorded. Initial tumour volume, percentage tumour fat content, mean tumour density, embolic agent used, number of angiomyolipomas and tuberous sclerosis disease were evaluated as predictive factors of volume decrease. A total of 19 patients with 39 angiomyolipomas were included with median follow-up of 28 months (interquartile range 21-37 months). All treatments were technically successful (92 % primary and 8 % secondary). No distal bleeding or any increase in size or surgical nephrectomy after SAE was recorded. Mean volume reduction was 72 % (±24 %). Volumes before SAE (R{sup 2} = 0.276; p = 0.001), percentage fat content (R{sup 2} = 0.612; p < 0.0001) and mean angiomyolipoma density (R{sup 2} = 0.536; p < 0.0001) were identified as predictive factors of volume decrease. In multivariate regression, only percentage fat content influenced volume decreases. SAE is an efficient treatment for angiomyolipoma devascularisation and volume reduction. A significant reduction of volume is modulated by the initial volume and tissue composition of the tumour. (orig.)

  7. Incidental, small (< 3 cm), unilocular, pancreatic cysts: Factors that predict lesion progression during imaging surveillance

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Go Eun [Dept. of Radiology, Chonnam National University Hospital, Gwangju (Korea, Republic of); Shin, Sang Soo; Kim, Jin Woong; Heo, Suk Hee; Lim, Hyo Soon; Jun, Chung Hwan; Jeong, Yong Yeon [Chonnam National University Medical School, Gwangju (Korea, Republic of)

    2017-11-15

    To explore the features that predict size increase and development of potential malignant features in incidentally detected, unilocular cystic pancreatic lesions (CPLs) less than 3 cm in diameter, during subsequent follow-up. We retrieved data of patients diagnosed with unilocular CPLs less than 3 cm in diameter during the period from November 2003 through December 2014, using a computerized search. All serial CT and MR images were analyzed to identify the number, size, and location of CPLs; dilatation of the main pancreatic duct; and occurrence of worrisome features and high-risk stigmata of malignancy in the lesion. The characteristics of CPLs were compared between the increase (i.e., size increase during subsequent follow-up) and no-increase groups. For CPLs in the increase group, subgroup analysis was performed according to the lesion size at the last follow-up (< 3 cm vs. ≥ 3 cm). Among 553 eligible patients, 132 (23.9%) had CPLs that increased in size, and 421 (76.1%) had CPLs that did not, during follow-up. Of the 132, 12 (9.1%) CPLs increased to diameters ≥ 3 cm at the final follow-up. Among the various factors, follow-up duration was a significant independent factor for an interval size increase of CPLs (p < 0.001). In the increase group, initial cyst size was a significant independent factor to predict later size increase to or beyond 3 cm in diameter (p < 0.001), and the initial cyst diameter ≥ 1.5 cm predicted such a growth with a sensitivity and specificity of 83% and 72%, respectively. No significant factors to predict the development of potential malignant features were identified. Follow-up duration was associated with an interval size increase of CPLs. Among the growing CPLs, initial cyst size was associated with future lesion growth to and beyond 3 cm.

  8. Predictive risk factors for moderate to severe hyperbilirubinemia

    Directory of Open Access Journals (Sweden)

    Gláucia Macedo de Lima

    2007-12-01

    Full Text Available Objective: to describe predictive factors for severity of neonataljaundice in newborn infants treated at the University Neonatal Clinic,highlighting maternal, obstetric and neonatal factors. Methods: Acohort retrospective study by means of review of medical charts todefine risk factors associated with moderate and severe jaundice.The cohort consisted of newborns diagnosed with indirect neonatalhyperbilirubinemia and submitted to phototherapy. Risk was classifiedas maternal, prenatal, obstetric and neonatal factors; risk estimationwas based on the odds ratio (95% confidence interval; a bi-variantmultivariate regression logistic analysis was applied to variables forp < 0.1. Results: Of 818 babies born during the studied period, 94(11% had jaundice prior to hospital discharge. Phototherapy was usedon 69 (73% patients. Predictive factors for severity were multiparity;prolonged rupture of membranes, dystocia, cephalohematoma, a lowApgar score, prematurity and small-for-date babies. Following birth,breastfeeding, sepsis, Rh incompatibility, and jaundice presentingbefore the third day of life were associated with an increased risk ofhyperbilirubinemia and the need for therapy. Conclusion: Other thanthose characteristics that are singly associated with phototherapy,we concluded that multiparity, presumed neonatal asphyxia, low birthweight and infection are the main predictive factors leading to moderateand severe jaundice in newborn infants in our neonatal unit.

  9. Evaluating predictive factors for determining enteral nutrition in patients receiving radical radiotherapy for head and neck cancer: A retrospective review

    International Nuclear Information System (INIS)

    Mangar, Stephen; Slevin, Nicholas; Mais, Kathleen; Sykes, Andrew

    2006-01-01

    Background and purpose: To identify objective pre-treatment clinical parameters that could be used to predict for patients at high risk of requiring enteral tube feeding prior to head and neck radiotherapy. Patients and methods: A retrospective study was conducted on 160 consecutive patients attending for radiotherapy assessment. Regression analysis was used to determine various pre-treatment nutritional and tumour specific parameters associated with the use of enteral nutrition either before (prophylactic) or during (reactive) radiotherapy (RT). The significant parameters identified were then selected into categorical variables and compared between those who needed reactive enteral nutrition and the remainder of the group who did not. These results were used to generate predictive factors that could be used to identify those at high risk of malnutrition during RT for whom early or prophylactic enteral nutrition should be considered. Results: Fifty patients required enteral feeding of which 60% required this prior to radiotherapy. Multivariate analysis identified the following factors to be significant-body mass index, performance status (PS), advanced stage, pre-treatment weight loss, low serum albumin and protein, age, and smoking. The most significant categorical predictive parameters for reactive enteral feeding were stage 3-4 disease, PS 2-3, and smoking >20/day. The combination of these factors predicted a 75% chance of needing enteral nutrition. Conclusion: Nutritional assessment is important prior to radiotherapy and is multifactorial. Using a combination of relatively simple and objective parameters (performance status, smoking and disease stage) it is possible to identify those at high risk of needing enteral nutrition prior to starting RT

  10. Identification of the Predictive Power of Five Factor Personality Traits for Individual Instrument Performance Anxiety

    Science.gov (United States)

    Özdemir, Gökhan; Dalkiran, Esra

    2017-01-01

    This study, with the aim of identifying the predictive power of the five-factor personality traits of music teacher candidates on individual instrument performance anxiety, was designed according to the relational screening model. The study population was students attending the Music Education branch of Fine Arts Education Departments in…

  11. Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

    Science.gov (United States)

    Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

    2015-09-01

    Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

  12. Can Childhood Factors Predict Workplace Deviance?

    Science.gov (United States)

    Piquero, Nicole Leeper; Moffitt, Terrie E

    2014-07-01

    Compared to the more common focus on street crime, empirical research on workplace deviance has been hampered by highly select samples, cross-sectional research designs, and limited inclusion of relevant predictor variables that bear on important theoretical debates. A key debate concerns the extent to which childhood conduct-problem trajectories influence crime over the life-course, including adults' workplace crime, whether childhood low self-control is a more important determinant than trajectories, and/or whether each or both of these childhood factors relate to later criminal activity. This paper provides evidence on this debate by examining two types of workplace deviance: production and property deviance separately for males and females. We use data from the Dunedin Multidisciplinary Health and Development Study, a birth cohort followed into adulthood, to examine how childhood factors (conduct-problem trajectories and low self-control) and then adult job characteristics predict workplace deviance at age 32. Analyses revealed that none of the childhood factors matter for predicting female deviance in the workplace but that conduct-problem trajectories did account for male workplace deviance.

  13. Identifying main factors of capacity fading in lithium ion cells using orthogonal design of experiments

    International Nuclear Information System (INIS)

    Su, Laisuo; Zhang, Jianbo; Wang, Caijuan; Zhang, Yakun; Li, Zhe; Song, Yang; Jin, Ting; Ma, Zhao

    2016-01-01

    Highlights: • The effect of seven principal factors on the aging behavior of lithium ion cells is studied. • Orthogonal design of experiments is used to reduce the experiment units. • Capacity fades linearly during the initial 10% capacity fading period. • Statistical methods are used to compare the significance of each principal factor. • A multi-factor statistical model is developed to predict the aging rate of cells. - Abstract: The aging rate under cycling conditions for lithium-ion cells is affected by many factors. Seven principal factors are systematically examined using orthogonal design of experiments, and statistical analysis was used to identify the order of principal factors in terms of strength in causing capacity fade. These seven principal factors are: the charge and discharge currents (i_1, i_2) during the constant current regime, the charge and discharge cut-off voltages (V_1, V_2) and the corresponding durations (t_1, t_2) during the constant voltage regime, and the ambient temperature (T). An orthogonal array with 18 test units was selected for the experiments. The test results show that (1) during the initial 10% capacity fading period, the capacity faded linearly with Wh-throughput for all the test conditions; (2) after the initial period, certain cycling conditions exacerbated aging rates, while the others remain the same. The statistical results show that: (1) except for t_1, the other six principal factors significantly affect the aging rate; (2) the strength of the principal factors was ranked as: i_1 > V_1 > T > t_2 > V_2 > i_2 > t_1. Finally, a multi-factor statistical aging model is developed to predict the aging rate, and the accuracy of the model is validated.

  14. SHMF: Interest Prediction Model with Social Hub Matrix Factorization

    Directory of Open Access Journals (Sweden)

    Chaoyuan Cui

    2017-01-01

    Full Text Available With the development of social networks, microblog has become the major social communication tool. There is a lot of valuable information such as personal preference, public opinion, and marketing in microblog. Consequently, research on user interest prediction in microblog has a positive practical significance. In fact, how to extract information associated with user interest orientation from the constantly updated blog posts is not so easy. Existing prediction approaches based on probabilistic factor analysis use blog posts published by user to predict user interest. However, these methods are not very effective for the users who post less but browse more. In this paper, we propose a new prediction model, which is called SHMF, using social hub matrix factorization. SHMF constructs the interest prediction model by combining the information of blogs posts published by both user and direct neighbors in user’s social hub. Our proposed model predicts user interest by integrating user’s historical behavior and temporal factor as well as user’s friendships, thus achieving accurate forecasts of user’s future interests. The experimental results on Sina Weibo show the efficiency and effectiveness of our proposed model.

  15. Perceived participation and autonomy: aspects of functioning and contextual factors predicting participation after stroke.

    Science.gov (United States)

    Fallahpour, Mandana; Tham, Kerstin; Joghataei, Mohammad Taghi; Jonsson, Hans

    2011-04-01

    To describe perceived participation and autonomy among a sample of persons with stroke in Iran and to identify different aspects of functioning and contextual factors predicting participation after stroke. A cross-sectional study. A total of 102 persons, between 27 and 75 years of age, diagnosed with first-ever stroke. Participants were assessed for different aspects of functioning, contextual factors and health conditions. Participation was assessed using the Persian version of the Impact on Participation and Autonomy questionnaire. This study demonstrated that the majority of the study population perceived their participation and autonomy to be good to fair in the different domains of their participation, but not with respect to the autonomy outdoors domain. In addition, physical function was found to be the most important variable predicting performance-based participation, whereas mood state was the most important variable predicting social-based participation. The results emphasize the importance of physical function, mood state and access to caregiving services as predictors of participation in everyday life after stroke. Whilst there are two dimensions of participation in this Persian sample of persons with stroke, the factors explaining participation seem to be the same across the cultures.

  16. Predictive factors for the development of diabetes in women with previous gestational diabetes mellitus

    DEFF Research Database (Denmark)

    Damm, P.; Kühl, C.; Bertelsen, Aksel

    1992-01-01

    OBJECTIVES: The purpose of this study was to determine the incidence of diabetes in women with previous dietary-treated gestational diabetes mellitus and to identify predictive factors for development of diabetes. STUDY DESIGN: Two to 11 years post partum, glucose tolerance was investigated in 241...... women with previous dietary-treated gestational diabetes mellitus and 57 women without previous gestational diabetes mellitus (control group). RESULTS: Diabetes developed in 42 (17.4%) women with previous gestational diabetes mellitus (3.7% insulin-dependent diabetes mellitus and 13.7% non...... of previous patients with gestational diabetes mellitus in whom plasma insulin was measured during an oral glucose tolerance test in late pregnancy a low insulin response at diagnosis was found to be an independent predictive factor for diabetes development. CONCLUSIONS: Women with previous dietary...

  17. Predicting Factors of Chronic Subdural Hematoma Following Surgical Clipping in Unruptured and Ruptured Intracranial Aneurysm.

    Science.gov (United States)

    Kwon, Min-Yong; Kim, Chang-Hyun; Lee, Chang-Young

    2016-09-01

    The aim of this study is to analyze the differences in the incidence, predicting factors, and clinical course of chronic subdural hematoma (CSDH) following surgical clipping between unruptured (UIA) and ruptured intracranial aneurysm (RIA). We conducted a retrospective analysis of 752 patients (UIA : 368 and RIA : 384) who underwent surgical clipping during 8 years. The incidence and predicting factors of CSDH development in the UIA and RIA were compared according to medical records and radiological data. The incidence of postoperative CSDH was higher in the UIA (10.9%) than in the RIA (3.1%) (p=0.000). In multivariate analysis, a high Hounsfield (HF) unit (blood clots) for subdural fluid collection (SFC), persistence of SFC ≥5 mm and male sex in the UIA and A high HF unit for SFC and SFC ≥5 mm without progression to hydrocephalus in the RIA were identified as the independent predicting factors for CSDH development (psubdural space and persistence of SFC ≥5 mm were predicting factors in both UIA and RIA. However, progression to hydrocephalus may have in part contributed to low CSDH development in the RIA. We suggest that cleaning of blood clots in the subdural space and efforts to minimize SFC ≥5 mm at the end of surgery is helpful to prevent CSDH following aneurysmal clipping.

  18. Identifying risk profiles for childhood obesity using recursive partitioning based on individual, familial, and neighborhood environment factors.

    Science.gov (United States)

    Van Hulst, Andraea; Roy-Gagnon, Marie-Hélène; Gauvin, Lise; Kestens, Yan; Henderson, Mélanie; Barnett, Tracie A

    2015-02-15

    Few studies consider how risk factors within multiple levels of influence operate synergistically to determine childhood obesity. We used recursive partitioning analysis to identify unique combinations of individual, familial, and neighborhood factors that best predict obesity in children, and tested whether these predict 2-year changes in body mass index (BMI). Data were collected in 2005-2008 and in 2008-2011 for 512 Quebec youth (8-10 years at baseline) with a history of parental obesity (QUALITY study). CDC age- and sex-specific BMI percentiles were computed and children were considered obese if their BMI was ≥95th percentile. Individual (physical activity and sugar-sweetened beverage intake), familial (household socioeconomic status and measures of parental obesity including both BMI and waist circumference), and neighborhood (disadvantage, prestige, and presence of parks, convenience stores, and fast food restaurants) factors were examined. Recursive partitioning, a method that generates a classification tree predicting obesity based on combined exposure to a series of variables, was used. Associations between resulting varying risk group membership and BMI percentile at baseline and 2-year follow up were examined using linear regression. Recursive partitioning yielded 7 subgroups with a prevalence of obesity equal to 8%, 11%, 26%, 28%, 41%, 60%, and 63%, respectively. The 2 highest risk subgroups comprised i) children not meeting physical activity guidelines, with at least one BMI-defined obese parent and 2 abdominally obese parents, living in disadvantaged neighborhoods without parks and, ii) children with these characteristics, except with access to ≥1 park and with access to ≥1 convenience store. Group membership was strongly associated with BMI at baseline, but did not systematically predict change in BMI. Findings support the notion that obesity is predicted by multiple factors in different settings and provide some indications of potentially

  19. Predictive factors of thyroid cancer in patients with Graves' disease.

    Science.gov (United States)

    Ren, Meng; Wu, Mu Chao; Shang, Chang Zhen; Wang, Xiao Yi; Zhang, Jing Lu; Cheng, Hua; Xu, Ming Tong; Yan, Li

    2014-01-01

    The best preoperative examination in Graves' disease with thyroid cancer still remains uncertain. The objectives of the present study were to investigate the prevalence of thyroid cancer in Graves' disease patients, and to identify the predictive factors and ultrasonographic features of thyroid cancer that may aid the preoperative diagnosis in Graves' disease. This retrospective study included 423 patients with Graves' disease who underwent surgical treatment from 2002 to 2012 at our institution. The clinical features and ultrasonographic findings of thyroid nodules were recorded. The diagnosis of thyroid cancer was determined according to the pathological results. Thyroid cancer was discovered in 58 of the 423 (13.7 %) surgically treated Graves' disease patients; 46 of those 58 patients had thyroid nodules, and the other 12 patients were diagnosed with incidentally discovered thyroid carcinomas without thyroid nodules. Among the 58 patients with thyroid cancer, papillary microcarcinomas were discovered in 50 patients, and multifocality and lymph node involvement were detected in the other 8 patients. Multivariate regression analysis showed younger age was the only significant factor predictive of metastatic thyroid cancer. Ultrasonographic findings of calcification and intranodular blood flow in thyroid nodules indicate that they are more likely to harbor thyroid cancers. Because the influencing factor of metastatic thyroid cancers in Graves' disease is young age, every suspicious nodule in Graves' disease patients should be evaluated and treated carefully, especially in younger patients because of the potential for metastasis.

  20. Cowpeas in Northern Ghana and the Factors that Predict Caregivers’ Intention to Give Them to Schoolchildren

    NARCIS (Netherlands)

    Abizari, A.R.; Pilime, N.; Armar-Klemesu, M.; Brouwer, I.D.

    2013-01-01

    Background Cowpeas are important staple legumes among the rural poor in northern Ghana. Our objectives were to assess the iron and zinc content of cowpea landraces and identify factors that predict the intention of mothers/caregivers to give cowpeas to their schoolchildren. Methods and Findings We

  1. [Predictive factors associated with severity of asthma exacerbations].

    Science.gov (United States)

    Atiş, Sibel; Kaplan, Eylem Sercan; Ozge, Cengiz; Bayindir, Suzan

    2008-01-01

    Several factors have been accused for asthma exacerbations, however, very few studies have evaluated whether different factors predict severity of asthma exacerbation. We aimed to determine the predictive factors for severity of asthma exacerbation. Retrospective analysis of data on 93 patients visited our emergency-department because of asthma exacerbation was reviewed. Hospitalization in intensive care unit and/or intubation because of asthma was accepted as the criteria for severe exacerbation. Logistic regression analysis estimated the strength of association of each variable, potentially related to severe asthmatic exacerbation, with severe/very severe as compared to mild/moderate asthmatic exacerbation. Independent variables included in the analysis were age, sex, smoking history, inhaler steroid using, compliance with medication, chronic asthma severity, presence of additional atopic diseases, prick test positivity, provocative factors, number of short-acting beta(2)-agonist using, number of visits to emergency department for asthma over one year period, previous severe exacerbation, pulmonary functions, and blood eosinophil count. 20 were severe/very severe and 73 mild/moderate asthmatic exacerbation. Frequent using of short-acting beta(2)-agonist (OR= 1.5, 95% CI= 1.08-5.3, p= 0.003), noncompliance with medication (OR= 3.6, 95% CI= 1.3-9.9, p= 0.013), previous severe asthmatic exacerbation (OR= 3.8, 95% CI= 1.48-10.01, p= 0.005) and recent admission to hospital (OR= 2.9, 95% CI= 1.07-8.09, p= 0.037) were found to be predictive factors for severe asthmatic exacerbation. Different predictive factors, in particular frequent using of short-acting beta(2)-agonist and noncompliance with medication may be associated with severe asthma exacerbations compared to milder exacerbations. This suggests different mechanisms are responsible for severity of asthma exacerbation.

  2. Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels

    Directory of Open Access Journals (Sweden)

    Chika Sumiyoshi

    2015-09-01

    Full Text Available Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1 to identify which outcome factors predict occupational functioning, quantified as work hours, and 2 to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB, the UCSD Performance-based Skills Assessment-Brief (UPSA-B, and the Social Functioning Scale Individuals’ version modified for the MATRICS-PASS (Modified SFS for PASS, respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly and a multiple logistic regression analyses (predicting dichotomized work status based on work hours. ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60–70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

  3. Transcription factor binding sites prediction based on modified nucleosomes.

    Directory of Open Access Journals (Sweden)

    Mohammad Talebzadeh

    Full Text Available In computational methods, position weight matrices (PWMs are commonly applied for transcription factor binding site (TFBS prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method

  4. Predictive factors for cosmetic surgery: a hospital-based investigation.

    Science.gov (United States)

    Li, Jun; Li, Qian; Zhou, Bei; Gao, Yanli; Ma, Jiehua; Li, Jingyun

    2016-01-01

    Cosmetic surgery is becoming increasingly popular in China. However, reports on the predictive factors for cosmetic surgery in Chinese individuals are scarce in the literature. We retrospectively analyzed 4550 cosmetic surgeries performed from January 2010 to December 2014 at a single center in China. Data collection included patient demographics and type of cosmetic surgery. Predictive factors were age, sex, marital status, occupational status, educational degree, and having had children. Predictive factors for the three major cosmetic surgeries were determined using a logistic regression analysis. Patients aged 19-34 years accounted for the most popular surgical procedures (76.9 %). The most commonly requested procedures were eye surgery, Botox injection, and nevus removal. Logistic regression analysis showed that higher education level (college, P = 0.01, OR 1.21) was predictive for eye surgery. Age (19-34 years, P = 0.00, OR 33.39; 35-50, P = 0.00, OR 31.34; ≥51, P = 0.00, OR 16.42), female sex (P = 0.00, OR 9.19), employment (service occupations, P = 0.00, OR 2.31; non-service occupations, P = 0.00, OR 1.76), and higher education level (college, P = 0.00, OR 1.39) were independent predictive factors for Botox injection. Married status (P = 0.00, OR 1.57), employment (non-service occupations, P = 0.00, OR 1.50), higher education level (masters, P = 0.00, OR 6.61), and having children (P = 0.00, OR 1.45) were independent predictive factors for nevus removal. The principal three cosmetic surgeries (eye surgery, Botox injection, and nevus removal) were associated with multiple variables. Patients employed in non-service occupations were more inclined to undergo Botox injection and nevus removal. Cohort study, Level III.

  5. Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post- versus prepubertal Brahman heifers.

    Science.gov (United States)

    Fortes, M R S; Nguyen, L T; Weller, M M D C A; Cánovas, A; Islas-Trejo, A; Porto-Neto, L R; Reverter, A; Lehnert, S A; Boe-Hansen, G B; Thomas, M G; Medrano, J F; Moore, S S

    2016-09-01

    Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in (Brahman) in age- and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: , , , , and . These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric ( cancer and developmental processes. Mutations in were associated with puberty in humans. Mutations in these TF, together with other genetic determinants previously discovered, could be used in genomic selection to predict the genetic merit of cattle (i.e., the likelihood of the offspring presenting earlier than average puberty for Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy.

  6. Evaluation of an inpatient fall risk screening tool to identify the most critical fall risk factors in inpatients.

    Science.gov (United States)

    Hou, Wen-Hsuan; Kang, Chun-Mei; Ho, Mu-Hsing; Kuo, Jessie Ming-Chuan; Chen, Hsiao-Lien; Chang, Wen-Yin

    2017-03-01

    To evaluate the accuracy of the inpatient fall risk screening tool and to identify the most critical fall risk factors in inpatients. Variations exist in several screening tools applied in acute care hospitals for examining risk factors for falls and identifying high-risk inpatients. Secondary data analysis. A subset of inpatient data for the period from June 2011-June 2014 was extracted from the nursing information system and adverse event reporting system of an 818-bed teaching medical centre in Taipei. Data were analysed using descriptive statistics, receiver operating characteristic curve analysis and logistic regression analysis. During the study period, 205 fallers and 37,232 nonfallers were identified. The results revealed that the inpatient fall risk screening tool (cut-off point of ≥3) had a low sensitivity level (60%), satisfactory specificity (87%), a positive predictive value of 2·0% and a negative predictive value of 99%. The receiver operating characteristic curve analysis revealed an area under the curve of 0·805 (sensitivity, 71·8%; specificity, 78%). To increase the sensitivity values, the Youden index suggests at least 1·5 points to be the most suitable cut-off point for the inpatient fall risk screening tool. Multivariate logistic regression analysis revealed a considerably increased fall risk in patients with impaired balance and impaired elimination. The fall risk factor was also significantly associated with days of hospital stay and with admission to surgical wards. The findings can raise awareness about the two most critical risk factors for falls among future clinical nurses and other healthcare professionals and thus facilitate the development of fall prevention interventions. This study highlights the needs for redefining the cut-off points of the inpatient fall risk screening tool to effectively identify inpatients at a high risk of falls. Furthermore, inpatients with impaired balance and impaired elimination should be closely

  7. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.; Motwalli, Olaa Amin; Oliva, Romina; Jankovic, Boris R.; Medvedeva, Yulia; Ashoor, Haitham; Essack, Magbubah; Gao, Xin; Bajic, Vladimir B.

    2018-01-01

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  8. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.

    2018-03-20

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  9. Examining predictive relationships among consumer values: factors ...

    African Journals Online (AJOL)

    Examining predictive relationships among consumer values: factors influencing behavioural intentions in retail purchase in Ghana. ... Journal of Business Research ... effects of age and gender differentials on values among retail consumers.

  10. Factors Affecting Retention Behavior: A Model To Predict At-Risk Students. AIR 1997 Annual Forum Paper.

    Science.gov (United States)

    Sadler, William E.; Cohen, Frederic L.; Kockesen, Levent

    This paper describes a methodology used in an on-going retention study at New York University (NYU) to identify a series of easily measured factors affecting student departure decisions. Three logistic regression models for predicting student retention were developed, each containing data available at three distinct times during the first…

  11. Predictive factors for the development of persistent pain after breast cancer surgery

    DEFF Research Database (Denmark)

    Andersen, Kenneth Geving; Duriaud, Helle Molter; Jensen, Helle Elisabeth

    2015-01-01

    Previous studies have reported that 15% to 25% of patients treated for breast cancer experience long-term moderate-to-severe pain in the area of surgery, potentially lasting for several years. Few prospective studies have included all potential risk factors for the development of persistent pain...... after breast cancer surgery (PPBCS). The aim of this prospective cohort study was to comprehensively identify factors predicting PPBCS. Patients scheduled for primary breast cancer surgery were recruited. Assessments were conducted preoperatively, the first 3 days postoperatively, and 1 week, 6 months...... were included, and 475 (88%) were available for analysis at 1 year. At 1-year follow-up, the prevalence of moderate-to-severe pain at rest was 14% and during movement was 7%. Factors associated with pain at rest were age breast conserving surgery (OR: 2.0, P...

  12. Vocal fold hemorrhage: factors predicting recurrence.

    Science.gov (United States)

    Lennon, Christen J; Murry, Thomas; Sulica, Lucian

    2014-01-01

    Vocal fold hemorrhage is an acute phonotraumatic injury treated with voice rest; recurrence is a generally accepted indication for surgical intervention. This study aims to identify factors predictive of recurrence based on outcomes of a large clinical series. Retrospective cohort. Retrospective review of cases of vocal fold hemorrhage presenting to a university laryngology service. Demographic information was compiled. Videostroboscopic exams were evaluated for hemorrhage extent, presence of varix, mucosal lesion, and/or vocal fold paresis. Vocal fold hemorrhage recurrence was the main outcome measure. Follow-up telephone survey was used to complement clinical data. Forty-seven instances of vocal fold hemorrhage were evaluated (25M:22F; 32 professional voice users). Twelve of the 47 (26%) patients experienced recurrence. Only the presence of varix demonstrated significant association with recurrence (P = 0.0089) on multivariate logistic regression. Vocal fold hemorrhage recurred in approximately 26% of patients. Varix was a predictor of recurrence, with 48% of those with varix experiencing recurrence. Monitoring, behavioral management and/or surgical intervention may be indicated to treat patients with such characteristics. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

  13. Network-based prediction and analysis of HIV dependency factors.

    Directory of Open Access Journals (Sweden)

    T M Murali

    2011-09-01

    Full Text Available HIV Dependency Factors (HDFs are a class of human proteins that are essential for HIV replication, but are not lethal to the host cell when silenced. Three previous genome-wide RNAi experiments identified HDF sets with little overlap. We combine data from these three studies with a human protein interaction network to predict new HDFs, using an intuitive algorithm called SinkSource and four other algorithms published in the literature. Our algorithm achieves high precision and recall upon cross validation, as do the other methods. A number of HDFs that we predict are known to interact with HIV proteins. They belong to multiple protein complexes and biological processes that are known to be manipulated by HIV. We also demonstrate that many predicted HDF genes show significantly different programs of expression in early response to SIV infection in two non-human primate species that differ in AIDS progression. Our results suggest that many HDFs are yet to be discovered and that they have potential value as prognostic markers to determine pathological outcome and the likelihood of AIDS development. More generally, if multiple genome-wide gene-level studies have been performed at independent labs to study the same biological system or phenomenon, our methodology is applicable to interpret these studies simultaneously in the context of molecular interaction networks and to ask if they reinforce or contradict each other.

  14. Identifiable risk factors in hepatitis b and c

    International Nuclear Information System (INIS)

    Rehman, F.U.; Pervez, A.; Rafiq, A.

    2011-01-01

    Background: Both hepatitis B and C are common infections affecting masses and are leading causes of Chronic Liver Disease in Pakistan as well as worldwide. In majority of cases both viral diseases spread by factors that are preventable. The present study is conducted to determine the identifiable risk factors in patients admitted with Chronic Hepatitis B and C. Methods: An observational study was carried out for a period of 6 months. All age groups and both sexes were included. The patients were interviewed and the identifiable risk factors were looked for. The standard methods for detection of Hepatitis B and C were used. Results: One-hundred and ten patients were studied from January to July 2009. Sixty-five patients had Hepatitis C, 35 had Hepatitis B, and 10 had both Hepatitis B and C. Ninety-three patients had a history of injections and transfusions etc., and 38 had surgical scars. Tattoos were present in 42 patients and nose and/or ear piercing marks were present in 28 patients. The number of risk factors increased in co-infection. Conclusion: There is a role of unhygienic health delivery practices, lack of awareness and resources for standard screening protocol for spread of Hepatitis B and C. (author)

  15. Predictive risk factors for moderate to severe hyperbilirubinemia

    OpenAIRE

    Gláucia Macedo de Lima; Maria Amélia Sayeg Campos Porto; Arnaldo Prata Barbosa; Antonio José Ledo Alves da Cunha

    2007-01-01

    Objective: to describe predictive factors for severity of neonataljaundice in newborn infants treated at the University Neonatal Clinic,highlighting maternal, obstetric and neonatal factors. Methods: Acohort retrospective study by means of review of medical charts todefine risk factors associated with moderate and severe jaundice.The cohort consisted of newborns diagnosed with indirect neonatalhyperbilirubinemia and submitted to phototherapy. Risk was classifiedas maternal, prenatal, obstetri...

  16. Predictive factors of mortality within 30 days in patients with nonvariceal upper gastrointestinal bleeding.

    Science.gov (United States)

    Lee, Yoo Jin; Min, Bo Ram; Kim, Eun Soo; Park, Kyung Sik; Cho, Kwang Bum; Jang, Byoung Kuk; Chung, Woo Jin; Hwang, Jae Seok; Jeon, Seong Woo

    2016-01-01

    Nonvariceal upper gastrointestinal bleeding (NVUGIB) is a common medical emergency that can be life threatening. This study evaluated predictive factors of 30-day mortality in patients with this condition. A prospective observational study was conducted at a single hospital between April 2010 and November 2012, and 336 patients with symptoms and signs of gastrointestinal bleeding were consecutively enrolled. Clinical characteristics and endoscopic findings were reviewed to identify potential factors associated with 30-day mortality. Overall, 184 patients were included in the study (men, 79.3%; mean age, 59.81 years), and 16 patients died within 30 days (8.7%). Multivariate analyses revealed that comorbidity of diabetes mellitus (DM) or metastatic malignancy, age ≥ 65 years, and hypotension (systolic pressure < 90 mmHg) during hospitalization were significant predictive factors of 30-day mortality. Comorbidity of DM or metastatic malignancy, age ≥ 65 years, and hemodynamic instability during hospitalization were predictors of 30-day mortality in patients with NVUGIB. These results will help guide the management of patients with this condition.

  17. [Muscle and bone health as a risk factor of fall among the elderly. An approach to identify high-risk fallers by risk assessment].

    Science.gov (United States)

    Kikuchi, Reiko; Kozaki, Koichi; Nakamura, Tetsuro; Toba, Kenji

    2008-06-01

    Fall-induced hip fracture is one of the major causes rendering the elderly to be in a low ADL or bed-ridden status. Fall is not only the cause for fractures, but it lowers elderly peoples'ADL. History of fall, age, decline of motor function, orthostatic hypotension, balance deficit, dementia, drug and environmental factors were raised as possible risk factor for falls. We created a fall predicting score which consist of 21 risk factors and a history of falls. We found that the score is useful to identify high-risk fallers. It would be necessary to identify high-risk fallers early and give an appropriate individual approach.

  18. Examining Factors Predicting Students' Digital Competence

    Science.gov (United States)

    Hatlevik, Ove Edvard; Guðmundsdóttir, Gréta Björk; Loi, Massimo

    2015-01-01

    The purpose of this study was to examine factors predicting lower secondary school students' digital competence and to explore differences between students when it comes to digital competence. Results from a digital competence test and survey in lower secondary school will be presented. It is important to learn more about and investigate what…

  19. Sinusoidal obstruction syndrome (SOS) related to chemotherapy for colorectal liver metastases: factors predictive of severe SOS lesions and protective effect of bevacizumab.

    Science.gov (United States)

    Hubert, Catherine; Sempoux, Christine; Humblet, Yves; van den Eynde, Marc; Zech, Francis; Leclercq, Isabelle; Gigot, Jean-François

    2013-11-01

    The most frequent presentation of chemotherapy-related toxicity in colorectal liver metastases (CRLM) is sinusoidal obstruction syndrome (SOS). The purpose of the present study was to identify preoperative factors predictive of SOS and to establish associations between type of chemotherapy and severity of SOS. A retrospective study was carried out in a tertiary academic referral hospital. Patients suffering from CRLM who had undergone resection of at least one liver segment were included. Grading of SOS on the non-tumoral liver parenchyma was accomplished according to the Rubbia-Brandt criteria. A total of 151 patients were enrolled and divided into four groups according to the severity of SOS (grades 0-3). Multivariate analysis identified oxaliplatin and 5-fluorouracil as chemotherapeutic agents responsible for severe SOS lesions (P SOS lesions (P = 0.005). Univariate analysis identified the score on the aspartate aminotransferase : platelets ratio index (APRI) as the most significant biological factor predictive of severe SOS lesions. Splenomegaly is also significantly associated with the occurrence of severe SOS lesions. The APRI score and splenomegaly are effective as factors predictive of SOS. Bevacizumab has a protective effect against SOS. © 2013 International Hepato-Pancreato-Biliary Association.

  20. Lung cancer and risk factors: how to identify phenotypic markers?

    International Nuclear Information System (INIS)

    Clement-Duchene, Christelle

    2009-01-01

    Lung cancer is the leading cause of death in the world. Most lung cancer are diagnosed at an advanced stage (IIIB and IV), with a poor prognosis. The main risk factors are well known like active smoking, and occupational exposure (asbestos), but 10 a 20% occur in never smokers. In this population, various studies have been conducted in order to identify possible risk factors, and although many have been identified, none seem to explain more than a small percentage of the cases. According to the histological types, adenocarcinoma is now the more frequent type, and its association with the main risk factors (tobacco exposure, asbestos exposure) is still studied. The tumoral location is associated with the exposure to the risk factors. Finally, the survival seems to be different between gender, and between smokers, and never smokers. All these characteristics are perhaps associated with different pathways of carcinogenesis. In this context, we have analyzed a cohort of 1493 patients with lung cancer in order to identify phenotypic markers, and to understand the mechanisms of the lung carcinogenesis. (author) [fr

  1. Multiple-Factor Based Sparse Urban Travel Time Prediction

    Directory of Open Access Journals (Sweden)

    Xinyan Zhu

    2018-02-01

    Full Text Available The prediction of travel time is challenging given the sparseness of real-time traffic data and the uncertainty of travel, because it is influenced by multiple factors on the congested urban road networks. In our paper, we propose a three-layer neural network from big probe vehicles data incorporating multi-factors to estimate travel time. The procedure includes the following three steps. First, we aggregate data according to the travel time of a single taxi traveling a target link on working days as traffic flows display similar traffic patterns over a weekly cycle. We then extract feature relationships between target and adjacent links at 30 min interval. About 224,830,178 records are extracted from probe vehicles. Second, we design a three-layer artificial neural network model. The number of neurons in input layer is eight, and the number of neurons in output layer is one. Finally, the trained neural network model is used for link travel time prediction. Different factors are included to examine their influence on the link travel time. Our model is verified using historical data from probe vehicles collected from May to July 2014 in Wuhan, China. The results show that we could obtain the link travel time prediction results using the designed artificial neural network model and detect the influence of different factors on link travel time.

  2. Predictive factors for intrauterine growth restriction.

    Science.gov (United States)

    Albu, A R; Anca, A F; Horhoianu, V V; Horhoianu, I A

    2014-06-15

    Reduced fetal growth is seen in about 10% of the pregnancies but only a minority has a pathological background and is known as intrauterine growth restriction or fetal growth restriction (IUGR / FGR). Increased fetal and neonatal mortality and morbidity as well as adult pathologic conditions are often associated to IUGR. Risk factors for IUGR are easy to assess but have poor predictive value. For the diagnostic purpose, biochemical serum markers, ultrasound and Doppler study of uterine and spiral arteries, placental volume and vascularization, first trimester growth pattern are object of assessment today. Modern evaluations propose combined algorithms using these strategies, all with the goal of a better prediction of risk pregnancies.

  3. Predictive factors for birth weight of newborns of mothers with gestational diabetes mellitus.

    Science.gov (United States)

    Silva, Sara de Oliveira Corrêa da; Saunders, Cláudia; Zajdenverg, Lenita; Moreira, Luciana Novaes; Heidelmann, Sonaly Petronilho; Pereira, Ariane Cristine Dos Santos; Padilha, Patricia de Carvalho

    2018-04-01

    To evaluate the predictive factors of birth weight (BW) of newborns of women with gestational diabetes mellitus (GDM). A cross-sectional study was performed among pregnant women with GDM treated in a public maternity unit, Brazil. We selected 283 pregnant women, with nutritional follow-up initiated till the 28th gestational week, singleton pregnancy, without chronic diseases and with birth weight information of the newborns. The predictive factors of BW were identified by multivariate linear regression. Mean maternal age was 31.2 ± 5.8 years; 64.4% were non-white; 70.1% were pre-gestational overweight or obese. Mean BW was 3234.3 ± 478.8 g. An increase of 1 kg of weight in the first and third trimesters increased BW by 21 g (p = 0.01) and 27 g (p = 0.03), respectively. Similarly, the other predictive factors of BW were pre-gestational body mass index (β = 17.16, p = 0.02) and postprandial plasma glucose in the third trimester (β = 4.14, p = 0.008), in the model adjusted by gestational age at delivery (β = 194.68, p gestational age at birth, and maternal pre-gestational and gestational anthropometric characteristics. Maternal glycaemic levels may also influence BW. The results may contribute to a review of prenatal routines for pregnant women with GDM. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Identifying patients with therapy-resistant depression by using factor analysis

    DEFF Research Database (Denmark)

    Andreasson, K; Liest, V; Lunde, M

    2010-01-01

    with transcranial pulsed electromagnetic fields (T-PEMF)], in which the relative effect as percentage of improvement during the treatment period was analysed. RESULTS: We identified 2 major factors, the first of which was a general factor. The second was a dual factor consisting of a depression subscale comprising...

  5. Identified state-space prediction model for aero-optical wavefronts

    Science.gov (United States)

    Faghihi, Azin; Tesch, Jonathan; Gibson, Steve

    2013-07-01

    A state-space disturbance model and associated prediction filter for aero-optical wavefronts are described. The model is computed by system identification from a sequence of wavefronts measured in an airborne laboratory. Estimates of the statistics and flow velocity of the wavefront data are shown and can be computed from the matrices in the state-space model without returning to the original data. Numerical results compare velocity values and power spectra computed from the identified state-space model with those computed from the aero-optical data.

  6. Identifying critical success factors for designing selection processes into postgraduate specialty training: the case of UK general practice.

    Science.gov (United States)

    Plint, Simon; Patterson, Fiona

    2010-06-01

    The UK national recruitment process into general practice training has been developed over several years, with incremental introduction of stages which have been piloted and validated. Previously independent processes, which encouraged multiple applications and produced inconsistent outcomes, have been replaced by a robust national process which has high reliability and predictive validity, and is perceived to be fair by candidates and allocates applicants equitably across the country. Best selection practice involves a job analysis which identifies required competencies, then designs reliable assessment methods to measure them, and over the long term ensures that the process has predictive validity against future performance. The general practitioner recruitment process introduced machine markable short listing assessments for the first time in the UK postgraduate recruitment context, and also adopted selection centre workplace simulations. The key success factors have been identified as corporate commitment to the goal of a national process, with gradual convergence maintaining locus of control rather than the imposition of change without perceived legitimate authority.

  7. Preoperative predictive factors for hearing preservation in vestibular schwannoma surgery.

    Science.gov (United States)

    Rohit; Piccirillo, Enrico; Jain, Yogesh; Augurio, Angela; Sanna, Mario

    2006-01-01

    We performed a retrospective chart review to evaluate the various predictive factors for postoperative hearing preservation in the surgical management of vestibular schwannoma. Of 792 patients operated on for vestibular schwannoma between April 1987 and July 2002, 107 were candidates for hearing preservation surgery. These patients were divided into group 1 (hearing preserved) and group 2 (hearing not preserved), and both of these groups were evaluated for age, sex, pure tone average, sound discrimination score, tumor size, and auditory brain stem response parameters. A corrected chi2 test and a corrected t-test were used for statistical analysis. Multiple regression analysis was further done to evaluate independent predictive factors, either alone or in combination. The results were evaluated by use of the modified Sanna classification and the guidelines of the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS). Preoperative pure tone average and tumor size were the 2 predictive factors in our study. A Pearson correlation test showed that there was no multicollinearity between the factors. On multiple regression analysis by backward elimination of nonsignificant factors, we found that tumor size is an independent predictive factor for postoperative hearing. According to the modified Sanna classification, postoperative hearing was preserved in 11.2% of patients (equivalent to class A of AAO-HNS guidelines). In our series, preoperative pure tone average and tumor size were found to be predictors of postoperative hearing levels.

  8. Molecular modelling of the Norrie disease protein predicts a cystine knot growth factor tertiary structure.

    Science.gov (United States)

    Meitinger, T; Meindl, A; Bork, P; Rost, B; Sander, C; Haasemann, M; Murken, J

    1993-12-01

    The X-lined gene for Norrie disease, which is characterized by blindness, deafness and mental retardation has been cloned recently. This gene has been thought to code for a putative extracellular factor; its predicted amino acid sequence is homologous to the C-terminal domain of diverse extracellular proteins. Sequence pattern searches and three-dimensional modelling now suggest that the Norrie disease protein (NDP) has a tertiary structure similar to that of transforming growth factor beta (TGF beta). Our model identifies NDP as a member of an emerging family of growth factors containing a cystine knot motif, with direct implications for the physiological role of NDP. The model also sheds light on sequence related domains such as the C-terminal domain of mucins and of von Willebrand factor.

  9. Identifying influential factors of business process performance using dependency analysis

    Science.gov (United States)

    Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

    2011-02-01

    We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

  10. Predictive factors for somatization in a trauma sample

    DEFF Research Database (Denmark)

    Elklit, Ask; Christiansen, Dorte M

    2009-01-01

    ABSTRACT: BACKGROUND: Unexplained somatic symptoms are common among trauma survivors. The relationship between trauma and somatization appears to be mediated by posttraumatic stress disorder (PTSD). However, only few studies have focused on what other psychological risk factors may predispose...... a trauma victim towards developing somatoform symptoms. METHODS: The present paper examines the predictive value of PTSD severity, dissociation, negative affectivity, depression, anxiety, and feeling incompetent on somatization in a Danish sample of 169 adult men and women who were affected by a series...... of incompetence significantly predicted somatization in the trauma sample whereas dissociation, depression, and anxiety were not associated with degree of somatization. PTSD as a risk factor was mediated by negative affectivity....

  11. [Doppler ultrasonography of the renal artery: Guidelines and predictive factors for the presence of a tight stenosis. Retrospective analysis of 450 consecutive examinations].

    Science.gov (United States)

    Dejerome, C; Grange, C; De Laforcade, L; Bonin, O; Laville, M; Lermusiaux, P; Long, A

    2018-05-01

    Duplex ultrasonography screening for renal artery stenosis has been the object of guidelines published by four societies designed to optimize the cost-effectiveness of the examination. To determine how well guideline indications for ultrasonography matched with requests and results in our university hospital; to determine whether compliance with guidelines was predictive of renal artery stenosis; to identify guidelines predictive of presence of stenosis; and to determine whether other predictive factors can be recognized. Requests and results of 450 Duplex ultrasonography examinations of the renal arteries performed from January 1st 2014 to December 31st 2015 were compared with published guidelines. At least one guideline indication was identified for 212 of the 450 examinations performed (47.1%). Among these examinations, renal artery stenosis≥70% was identified in 18 patients (8.0%). No case of stenosis was identified during examinations performed outside guideline indications. Factors predictive of stenosis were: compliance with guidelines (OR=21.86 [2.88; 165.8]). Predictive guidelines were: resistant hypertension in spite of appropriate treatment (OR=3.85, [1.44; 10.33], P=0.011), accelerated hypertension (OR=7.30, [1.40; 37.99], P=0.049), sudden unexplained pulmonary edema (OR=7.30, [1.40; 37.99], P=0.049), unexplained renal insufficiency (OR=3.58, [1.37; 9.37], P=0.011), unexplained renal hypotrophy (OR=16.69, [4.38; 63.69], P<0.001), renal asymmetry (OR=4.32, [1.45; 12.85], P<0.016). No other factor was predictive of renal stenosis. These examinations had therapeutic consequences in only 50% of patients. This study confirms the relevance of published guidelines. The diagnostic-effectiveness of Duplex ultrasonography examinations to search for renal artery stenosis depends upon compliance with these guidelines. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

  12. Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns Study.

    Science.gov (United States)

    Seyednasrollah, Fatemeh; Mäkelä, Johanna; Pitkänen, Niina; Juonala, Markus; Hutri-Kähönen, Nina; Lehtimäki, Terho; Viikari, Jorma; Kelly, Tanika; Li, Changwei; Bazzano, Lydia; Elo, Laura L; Raitakari, Olli T

    2017-06-01

    Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity. © 2017 American Heart Association, Inc.

  13. Identifying influential factors on integrated marketing planning using information technology

    Directory of Open Access Journals (Sweden)

    Karim Hamdi

    2014-07-01

    Full Text Available This paper presents an empirical investigation to identify important factors influencing integrated marketing planning using information technology. The proposed study designs a questionnaire for measuring integrated marketing planning, which consists of three categories of structural factors, behavioral factors and background factors. There are 40 questions associated with the proposed study in Likert scale. Cronbach alphas have been calculated for structural factors, behavioral factors and background factors as 0.89, 0.86 and 0.83, respectively. Using some statistical test, the study has confirmed the effects of three factors on integrated marketing. In addition, the implementation of Freedman test has revealed that structural factors were the most important factor followed by background factors and behavioral factors.

  14. [Predictive factors of complications during CT-guided transthoracic biopsy].

    Science.gov (United States)

    Fontaine-Delaruelle, C; Souquet, P-J; Gamondes, D; Pradat, E; de Leusse, A; Ferretti, G R; Couraud, S

    2017-04-01

    CT-guided transthoracic core-needle biopsy (TTNB) is frequently used for the diagnosis of lung nodules. The aim of this study is to describe TTNBs' complications and to investigate predictive factors of complications. All consecutive TTNBs performed in three centers between 2006 and 2012 were included. Binary logistic regression was used for multivariate analysis. Overall, 970 TTNBs were performed in 929 patients. The complication rate was 34% (life-threatening complication in 6%). The most frequent complications were pneumothorax (29% included 4% which required chest-tube) and hemoptysis (5%). The mortality rate was 0.1% (n=1). In multivariate analysis, predictive factor for a complication was small target size (AOR=0.984; 95% CI [0.976-0.992]; P<0.001). This predictive factor was also found for occurrence of life-threatening complication (AOR=0.982; [0.965-0.999]; P=0.037), of pneumothorax (AOR=0.987; [0.978-0.995]; P=0.002) and of hemoptysis (AOR=0.973; [0.951-0.997]; P=0.024). One complication occurred in one-third of TTNBs. The proportion of life-threatening complication was 6%. A small lesion size was predictive of complication occurrence. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  15. Fetal and neonatal alloimmune thrombocytopenia: predictive factors of intracranial hemorrhage.

    Science.gov (United States)

    Delbos, Florent; Bertrand, Gérald; Croisille, Laure; Ansart-Pirenne, Hélène; Bierling, Philippe; Kaplan, Cécile

    2016-01-01

    In Caucasians, fetal/neonatal alloimmune thrombocytopenia (FNAIT) is most frequently caused by maternal alloimmunization against the human platelet antigen HPA-1a. The most serious complication of severe FNAIT is intracranial hemorrhage (ICH). ICH mainly occurs in utero; therefore, there is a need to identify noninvasive predictive factors of ICH to facilitate early identification of this condition and to determine response to maternal therapy. We studied gynecologic and immunogenetic variables of severe cases of anti-HPA-1a FNAIT within three groups: Group I, FNAIT without ICH; Group II, FNAIT with ICH; and Group III, suspected FNAIT cases without detectable maternal anti-HPA-1a alloantibodies. ICH was associated with a poor outcome because it led to death in 59% of cases. Multigravida (two or more pregnancies) was overrepresented in Group II, consistent with the high concentrations of maternal HPA-1a alloantibody and the frequent detection of a strong newborn-specific HLA class I antibody response at delivery. The proportion of HLA-DRB4*01:01P (*01:01 or *01:03) women was similar in Groups I and II, but this allele was overrepresented in Group III, in which FNAIT was less severe than in the other two groups. Finally, antenatal intravenous immunoglobulin therapy tended to be more effective in HLA-DRB3*01:01(+)/HLA-DRB4*01:01P(+) women than for HLA-DRB3*01:01(+)/HLA-DRB4*01:01P(-) women. The number of gestations is a predictive factor of ICH in anti-HPA-1a-alloimmunized women. Maternal immunogenetic variables should be investigated in the context of maternal immunization and may predict response to maternal therapy in subsequent pregnancies. © 2015 AABB.

  16. Ecological Factors Predict Transition Readiness/Self-Management in Youth With Chronic Conditions.

    Science.gov (United States)

    Javalkar, Karina; Johnson, Meredith; Kshirsagar, Abhijit V; Ocegueda, Sofia; Detwiler, Randal K; Ferris, Maria

    2016-01-01

    Health care transition readiness or self-management among adolescents and young adults (AYA) with chronic conditions may be influenced by factors related to their surrounding environment. Study participants were AYA diagnosed with a chronic condition and evaluated at pediatric- and adult-focused subspecialty clinics at the University of North Carolina Hospital Systems. All participants were administered a provider-administered self-management/transition-readiness tool, the UNC TRxANSITION Scale. Geographic area and associated characteristics (ecological factors) were identified for each participant's ZIP code using the published U.S. Census data. The Level 1 model of the hierarchical linear regression used individual-level predictors of transition readiness/self-management. The Level 2 model incorporated the ecological factors. We enrolled 511 AYA with different chronic conditions aged 12-31 years with the following characteristics: mean age of 20± 4 years, 45% white, 42% black, and 54% female. Participants represented 214 ZIP codes in or around North Carolina, USA. The Level 1 model showed that age, gender, and race were significant predictors of transition readiness/self-management. On adding the ecological factors in the Level 2 model, race was no longer significant. Participants from a geographic area with a greater percentage of females (β = .114, p = .005) and a higher median income (β = .126, p = .002) had greater overall transition readiness. Ecological factors also predicted subdomains of transition readiness/self-management. In this cohort of adolescents and young adults with different chronic conditions, ecological disparities such as sex composition, median income, and language predict self-management/transition readiness. It is important to take ecological risk factors into consideration when preparing patients for health self-management or transition. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All

  17. Delayed neuropsychological sequelae after carbon monoxide poisoning: predictive risk factors in the Emergency Department. A retrospective study

    Directory of Open Access Journals (Sweden)

    Botti Primo

    2011-03-01

    Full Text Available Abstract Background Delayed neuropsychological sequelae (DNS commonly occur after recovery from acute carbon monoxide (CO poisoning. The preventive role and the indications for hyperbaric oxygen therapy in the acute setting are still controversial. Early identification of patients at risk in the Emergency Department might permit an improvement in quality of care. We conducted a retrospective study to identify predictive risk factors for DNS development in the Emergency Department. Methods We retrospectively considered all CO-poisoned patients admitted to the Emergency Department of Careggi University General Hospital (Florence, Italy from 1992 to 2007. Patients were invited to participate in three follow-up visits at one, six and twelve months from hospital discharge. Clinical and biohumoral data were collected; univariate and multivariate analysis were performed to identify predictive risk factors for DNS. Results Three hundred forty seven patients were admitted to the Emergency Department for acute CO poisoning from 1992 to 2007; 141/347 patients participated in the follow-up visit at one month from hospital discharge. Thirty four/141 patients were diagnosed with DNS (24.1%. Five/34 patients previously diagnosed as having DNS presented to the follow-up visit at six months, reporting a complete recovery. The following variables (collected before or upon Emergency Department admission were associated to DNS development at one month from hospital discharge in the univariate analysis: CO exposure duration >6 hours, a Glasgow Coma Scale (GCS score Conclusions Our study identified several potential predictive risk factors for DNS. Treatment algorithms based on an appropriate risk-stratification of patients in the Emergency Department might reduce DNS incidence; however, more studies are needed. Adequate follow-up after hospital discharge, aimed at correct recognition of DNS, is also important.

  18. Identifying factors affecting about outsourcing in paraclinical services

    African Journals Online (AJOL)

    Objective: Outsourcing refers to the transfer of services or functions to an outsider supplier, which controls them through a contract or cooperative. The main problem of senior managers in health organizations is determining the services which should be outsourced. The present study seeks to identify the factors that affect ...

  19. Factors Predicting the Provision of Smoking Cessation Services Among Occupational Health Nurses in Thailand.

    Science.gov (United States)

    Chatdokmaiprai, Kannikar; Kalampakorn, Surintorn; McCullagh, Marjorie; Lagampan, Sunee; Keeratiwiriyaporn, Sansanee

    2017-06-01

    The purpose of this study was to identify factors predicting occupational health nurses' provision of smoking cessation services. Data were collected via a self-administered questionnaire distributed to 254 occupational health nurses in Thailand. Analysis by structural equation modeling revealed that self-efficacy directly and positively influenced smoking cessation services, and mediated the relationship between workplace factors, nurse factors, and smoking cessation services. The final model had good fit to the data, accounting for 20.4% and 38.0% of the variance in self-efficacy and smoking cessation services, respectively. The findings show that self-efficacy is a mediator that influences provision of smoking cessation services by occupational health nurses. Interventions to enhance nurses' self-efficacy in providing smoking cessation services are expected to promote provision of smoking cessation services to workers.

  20. Beyond the first episode: candidate factors for a risk prediction model of schizophrenia.

    Science.gov (United States)

    Murphy, Brendan P

    2010-01-01

    Many early psychosis services are financially compromised and cannot offer a full tenure of care to all patients. To maintain viability of services it is important that those with schizophrenia are identified early to maximize long-term outcomes, as are those with better prognoses who can be discharged early. The duration of untreated psychosis remains the mainstay in determining those who will benefit from extended care, yet its ability to inform on prognosis is modest in both the short and medium term. There are a number of known or putative genetic and environmental risk factors that have the potential to improve prognostication, though a multivariate risk prediction model combining them with clinical characteristics has yet to be developed. Candidate risk factors for such a model are presented, with an emphasis on environmental risk factors. More work is needed to corroborate many putative factors and to determine which of the established factors are salient and which are merely proxy measures. Future research should help clarify how gene-environment and environment-environment interactions occur and whether risk factors are dose-dependent, or if they act additively or synergistically, or are redundant in the presence (or absence) of other factors.

  1. Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?

    Science.gov (United States)

    Alavi, Mousa; Baharlooei, Omeleila; AdelMehraban, Marzieh

    2017-01-01

    Despite advances in diabetes treatment, the rate of readmission is still relatively high among these patients, especially in older population. Various factors may predict readmission in these patients; hence, the aim of this study was to assess the role of psychosocial factors in predicting readmission among diabetic elderly hospitalized in selected hospitals of Isfahan. In this cross-sectional study conducted from January to September 2016, 150 diabetic elderly hospitalized in selected hospitals affiliated with Isfahan University of medical sciences were chosen using a convenient sampling method. The initial information was collected by a three-part questionnaire consisting of (a) demographic characteristics, (b) 21-item depression, anxiety, and stress scale (DASS-21), and (c) multidimensional scale of perceived social support (MSPSS). Further information about readmission was gathered 3 months after completing the questionnaires through a phone call follow-up. Descriptive and inferential statistics (discriminant function analysis test) were used to analyze the data. During 3 months after discharge, 44% of hospitalized diabetic elderly were readmitted. Analytical model predicted the readmission status of 109 individuals (of total 150 persons) in the studied units (success rate of 72.2%). Among predicting factors, depression and social support had the most and the least important roles in predicting readmission rate, respectively. Interventions to improve mental status (i.e., decreasing levels of depression, anxiety, and stress) and develop social support are suggested to reduce the risk of readmission among diabetic elderly patients. Nevertheless, future studies are needed to verify the value of such interventions.

  2. Predictive and prognostic factors associated with soft tissue sarcoma response to chemotherapy

    DEFF Research Database (Denmark)

    Young, Robin J; Litière, Saskia; Lia, Michela

    2017-01-01

    BACKGROUND: The European Organization for Research and Treatment of Cancer (EORTC) 62012 study was a Phase III trial of doxorubicin versus doxorubicin-ifosfamide chemotherapy in 455 patients with advanced soft tissue sarcoma (STS). Analysis of the main study showed that combination chemotherapy...... improved tumor response and progression-free survival, but differences in overall survival (OS) were not statistically significant. We analyzed factors prognostic for tumor response and OS, and assessed histological subgroup and tumor grade as predictive factors to identify patients more likely to benefit...... patients had improved tumor response compared to other histological subgroups, whilst patients with metastases other than lung, liver or bone had a poorer response [odds ratio (OR) 0.42, 95% confidence interval (CI) 0.23-0.78; p = 0.006]. Patients with bone metastases had reduced OS [hazard ratio (HR) 1...

  3. Predictive factors of the nursing diagnosis sedentary lifestyle in people with high blood pressure.

    Science.gov (United States)

    Guedes, Nirla Gomes; Lopes, Marcos Venícios de Oliveira; Araujo, Thelma Leite de; Moreira, Rafaella Pessoa; Martins, Larissa Castelo Guedes

    2011-01-01

    To verify the reproducibility of defining the characteristics and related factors in order to identify a sedentary lifestyle in patients with high blood pressure. A cross-sectional study. 310 patients diagnosed with high blood pressure. Socio-demographics and variables related to defining the characteristics and related factors of a sedentary lifestyle. The coefficient Kappa was utilized to analyze the reproducibility. The sensitivity, specificity, and predictive value of the defining characteristics were also analyzed. Logistic regression was applied in the analysis of possible predictors. The defining characteristic with the greatest sensitivity was demonstrates physical deconditioning (98.92%). The characteristics chooses a daily routine lacking physical exercise and verbalizes preference for activities low in physical activity presented higher values of specificity (99.21% and 95.97%, respectively). The following indicators were identified as powerful predictors (85.2%) for the identification of a sedentary lifestyle: demonstrates physical deconditioning, verbalizes preference for activities low in physical activity, and lack of training for accomplishment of physical exercise. © 2010 Wiley Periodicals, Inc.

  4. Identifying risk factors for first-episode neck pain: A systematic review.

    Science.gov (United States)

    Kim, Rebecca; Wiest, Colin; Clark, Kelly; Cook, Chad; Horn, Maggie

    2018-02-01

    Neck pain affects 15.1% of the United States' general population every 3 months, and ranks fourth in global disability. Because of the tendency for neck pain to become a chronic issue, it is important to identify risk factors that could encourage prevention and early diagnosis. The purpose of this systematic review was to identify risk factors for a first episode of neck pain. Three databases were searched with key words such as "neck pain" and "first incidence." Risk factors from the resulting articles were reported as either a physical or psychosocial risk factor and ranked by the strength of their odds/risk/hazard ratio: empowering leadership, high perceived social climate, leisure physical activity, and cervical extensor endurance. Most risk factors found for neck pain were related to psychosocial characteristics, rather than physical characteristics. A number of these risk factors were mediating factors, suggesting that a prevention-based program may be useful in modifying the existence of the risk factors before the occurrence of neck pain. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Use of a twin dataset to identify AMD-related visual patterns controlled by genetic factors

    Science.gov (United States)

    Quellec, Gwénolé; Abràmoff, Michael D.; Russell, Stephen R.

    2010-03-01

    The mapping of genotype to the phenotype of age-related macular degeneration (AMD) is expected to improve the diagnosis and treatment of the disease in a near future. In this study, we focused on the first step to discover this mapping: we identified visual patterns related to AMD which seem to be controlled by genetic factors, without explicitly relating them to the genes. For this purpose, we used a dataset of eye fundus photographs from 74 twin pairs, either monozygotic twins, who have the same genotype, or dizygotic twins, whose genes responsible for AMD are less likely to be identical. If we are able to differentiate monozygotic twins from dizygotic twins, based on a given visual pattern, then this pattern is likely to be controlled by genetic factors. The main visible consequence of AMD is the apparition of drusen between the retinal pigment epithelium and Bruch's membrane. We developed two automated drusen detectors based on the wavelet transform: a shape-based detector for hard drusen, and a texture- and color- based detector for soft drusen. Forty visual features were evaluated at the location of the automatically detected drusen. These features characterize the texture, the shape, the color, the spatial distribution, or the amount of drusen. A distance measure between twin pairs was defined for each visual feature; a smaller distance should be measured between monozygotic twins for visual features controlled by genetic factors. The predictions of several visual features (75.7% accuracy) are comparable or better than the predictions of human experts.

  6. Environmental factors predict the severity of delirium symptoms in long-term care residents with and without delirium.

    Science.gov (United States)

    McCusker, Jane; Cole, Martin G; Voyer, Philippe; Vu, Minh; Ciampi, Antonio; Monette, Johanne; Champoux, Nathalie; Belzile, Eric; Dyachenko, Alina

    2013-04-01

    To identify potentially modifiable environmental factors (including number of medications) associated with changes over time in the severity of delirium symptoms and to explore the interactions between these factors and resident baseline vulnerability. Prospective, observational cohort study. Seven long-term care (LTC) facilities. Two hundred seventy-two LTC residents aged 65 and older with and without delirium. Weekly assessments (for up to 6 months) of the severity of delirium symptoms using the Delirium Index (DI), environmental risk factors, and number of medications. Baseline vulnerability measures included a diagnosis of dementia and a delirium risk score. Associations between environmental factors, medications, and weekly changes in DI were analyzed using a general linear model with correlated errors. Six potentially modifiable environmental factors predicted weekly changes in DI (absence of reading glasses, aids to orientation, family member, and glass of water and presence of bed rails and other restraints) as did the prescription of two or more new medications. Residents with dementia appeared to be more sensitive to the effects of these factors. Six environmental factors and prescription of two or more new medications predicted changes in the severity of delirium symptoms. These risk factors are potentially modifiable through improved LTC clinical practices. © 2013, Copyright the Authors Journal compilation © 2013, The American Geriatrics Society.

  7. Osteoporosis-Related Mortality: Time-Trends and Predictive Factors

    Directory of Open Access Journals (Sweden)

    Nelly Ziadé

    2014-07-01

    Full Text Available Osteoporosis is one of the leading causes of handicap worldwide and a major contributor to the global burden of diseases. In particular, osteoporosis is associated with excess mortality. We reviewed the impact of osteoporosis on mortality in a population by defining three categories: mortality following hip fractures, mortality following other sites of fractures, and mortality associated with low bone mineral density (BMD. Hip fractures, as well as other fractures at major sites are all associated with excess mortality, except at the forearm site. This excess mortality is higher during the first 3-6 months after the fracture and then declines over time, but remains higher than the mortality of the normal population up to 22 years after the fracture. Low BMD is also associated with high mortality, with hazard ratios of around 1.3 for every decrease in 1 standard deviation of bone density at 5 years, independently of fractures, reflecting a more fragile population. Finally predictors of mortality were identified and categorised in demographic known factors (age and male gender and in factors reflecting a poor general health status such as the number of comorbidities, low mental status, or level of social dependence. Our results indicate that the management of a patient with osteoporosis should include a multivariate approach that could be based on predictive models in the future.

  8. Genome wide predictions of miRNA regulation by transcription factors.

    Science.gov (United States)

    Ruffalo, Matthew; Bar-Joseph, Ziv

    2016-09-01

    Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Predictive factors of cytomegalovirus seropositivity among pregnant women in Paris, France.

    Directory of Open Access Journals (Sweden)

    Dieynaba S N'Diaye

    Full Text Available Cytomegalovirus (CMV is the most frequent cause of congenital infection. The objective of this study was to evaluate predictive factors for CMV seronegativity in a cohort of pregnant women in Paris, France.Pregnant women enrolled in a prospective cohort during the 2009 A/H1N1 pandemic were tested for CMV IgG antibodies. Variables collected were age, geographic origin, lifestyle, work characteristics, socioeconomic status, gravidity, parity and number of children at home. A multivariate logistic regression model was used to identify independent predictive factors for CMV seropositivity.Among the 826 women enrolled, 389 (47.1% were primiparous, and 552 (67.1% had Metropolitan France as a geographic origin. Out of these, 355 (i.e. 57.0%, 95% confidence interval (CI: [53.6%-60.4%] were CMV seropositive: 43.7% (95% CI:[39.5%-47.9%] in those whose geographic origin was Metropolitan France and 84.1% in those with other origins (95% CI:[79.2%-88.3%]. Determinants associated with CMV seropositivity in a multivariate logistic regression model were: (i geographic origin (p<0.001(compared with Metropolitan France, geographic origins of Africa adjusted odds ratio (aOR 21.2, 95% CI:[9.7-46.5], French overseas departments and territories and other origin, aOR 7.5, 95% CI:[3.9-14.6], and Europe or Asia, aOR 2.2, 95% CI: [1.3-3.7]; and (ii gravidity (p = 0.019, (compared with gravidity = 1, if gravidity≥3, aOR = 1.5, 95% CI: [1.1-2.2]; if gravidity = 2, aOR = 1.0, 95% CI: [0.7-1.4]. Work characteristics and socioeconomic status were not independently associated with CMV seropositivity.In this cohort of pregnant women, a geographic origin of Metropolitan France and a low gravidity were predictive factors for CMV low seropositivity. Such women are therefore the likely target population for prevention of CMV infection during pregnancy in France.

  10. Identifying depression severity risk factors in persons with traumatic spinal cord injury.

    Science.gov (United States)

    Williams, Ryan T; Wilson, Catherine S; Heinemann, Allen W; Lazowski, Linda E; Fann, Jesse R; Bombardier, Charles H

    2014-02-01

    Examine the relationship between demographic characteristics, health-, and injury-related characteristics, and substance misuse across multiple levels of depression severity. 204 persons with traumatic spinal cord injury (SCI) volunteered as part of screening efforts for a randomized controlled trial of venlafaxine extended release for major depressive disorder (MDD). Instruments included the Patient Health Questionnaire-9 (PHQ-9) depression scale, the Alcohol Use Disorders Identification Test (AUDIT), and the Substance Abuse in Vocational Rehabilitation-Screener (SAVR-S), which contains 3 subscales: drug misuse, alcohol misuse, and a subtle items scale. Each of the SAVR-S subscales contributes to an overall substance use disorder (SUD) outcome. Three proportional odds models were specified, varying the substance misuse measure included in each model. 44% individuals had no depression symptoms, 31% had mild symptoms, 16% had moderate symptoms, 6% had moderately severe symptoms, and 3% had severe depression symptoms. Alcohol misuse, as indicated by the AUDIT and the SAVR-S drug misuse subscale scores were significant predictors of depression symptom severity. The SAVR-S substance use disorder (SUD) screening outcome was the most predictive variable. Level of education was only significantly predictive of depression severity in the model using the AUDIT alcohol misuse indicator. Likely SUD as measured by the SAVR-S was most predictive of depression symptom severity in this sample of persons with traumatic SCI. Drug and alcohol screening are important for identifying individuals at risk for depression, but screening for both may be optimal. Further research is needed on risk and protective factors for depression, including psychosocial characteristics. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  11. Integrating the ICF with positive psychology: Factors predicting role participation for mothers with multiple sclerosis.

    Science.gov (United States)

    Farber, Ruth S; Kern, Margaret L; Brusilovsky, Eugene

    2015-05-01

    Being a mother has become a realizable life role for women with disabilities and chronic illnesses, including multiple sclerosis (MS). Identifying psychosocial factors that facilitate participation in important life roles-including motherhood-is essential to help women have fuller lives despite the challenge of their illness. By integrating the International Classification of Functioning, Disability, and Health (ICF) and a positive psychology perspective, this study examined how environmental social factors and positive personal factors contribute to daily role participation and satisfaction with parental participation. One hundred and 11 community-dwelling mothers with MS completed Ryff's Psychological Well-Being Scales, the Medical Outcome Study Social Support Survey, the Short Form-36, and the Parental Participation Scale. Hierarchical regression analyses examined associations between social support and positive personal factors (environmental mastery, self-acceptance, purpose in life) with daily role participation (physical and emotional) and satisfaction with parental participation. One-way ANOVAs tested synergistic combinations of social support and positive personal factors. Social support predicted daily role participation (fewer limitations) and greater satisfaction with parental participation. Positive personal factors contributed additional unique variance. Positive personal factors and social support synergistically predicted better function and greater satisfaction than either alone. Integrating components of the ICF and positive psychology provides a useful model for understanding how mothers with MS can thrive despite challenge or impairment. Both positive personal factors and environmental social factors were important contributors to positive role functioning. Incorporating these paradigms into treatment may help mothers with MS participate more fully in meaningful life roles. (c) 2015 APA, all rights reserved).

  12. Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

    Science.gov (United States)

    Choi, Jonghwan; Park, Sanghyun; Yoon, Youngmi; Ahn, Jaegyoon

    2017-11-15

    Identification of genes that can be used to predict prognosis in patients with cancer is important in that it can lead to improved therapy, and can also promote our understanding of tumor progression on the molecular level. One of the common but fundamental problems that render identification of prognostic genes and prediction of cancer outcomes difficult is the heterogeneity of patient samples. To reduce the effect of sample heterogeneity, we clustered data samples using K-means algorithm and applied modified PageRank to functional interaction (FI) networks weighted using gene expression values of samples in each cluster. Hub genes among resulting prioritized genes were selected as biomarkers to predict the prognosis of samples. This process outperformed traditional feature selection methods as well as several network-based prognostic gene selection methods when applied to Random Forest. We were able to find many cluster-specific prognostic genes for each dataset. Functional study showed that distinct biological processes were enriched in each cluster, which seems to reflect different aspect of tumor progression or oncogenesis among distinct patient groups. Taken together, these results provide support for the hypothesis that our approach can effectively identify heterogeneous prognostic genes, and these are complementary to each other, improving prediction accuracy. https://github.com/mathcom/CPR. jgahn@inu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  13. Identifying factors affecting destination choice of medical tourists: a ...

    African Journals Online (AJOL)

    medical tourism”, has emerged as a new source of competitive advantage all over the world. The present study seeks to identify the factors that affect destination choice of medical tourists. Methods: We systematically searched relevant databases ...

  14. Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

    Science.gov (United States)

    Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2015-01-01

    Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin β4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.

  15. Factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus: decision-curve analysis.

    Science.gov (United States)

    Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, Tsuyoshi; Tanizawa, Y

    2018-04-29

    To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  16. Factors Predicting Treatment Failure in Patients Treated with Iodine-131 for Graves’ Disease

    International Nuclear Information System (INIS)

    Manohar, Kuruva; Mittal, Bhagwant Rai; Bhoil, Amit; Bhattacharya, Anish; Dutta, Pinaki; Bhansali, Anil

    2013-01-01

    Treatment of Graves' disease with iodine-131 ( 131 I) is well-known; however, all patients do not respond to a single dose of 131 I and may require higher and repeated doses. This study was carried out to identify the factors, which can predict treatment failure to a single dose of 131 I treatment in these patients. Data of 150 patients with Graves' disease treated with 259-370 MBq of 131 I followed-up for at least 1-year were retrospectively analyzed. Logistic regression analysis was used to predict factors which can predict treatment failure, such as age, sex, duration of disease, grade of goiter, duration of treatment with anti-thyroid drugs, mean dosage of anti-thyroid drugs used, 99m Tc-pertechnetate ( 99m TcO 4 - ) uptake at 20 min, dose of 131 I administered, total triiodothyronine and thyroxine levels. Of the 150 patients, 25 patients required retreatment within 1 year of initial treatment with 131 I. Logistic regression analysis revealed that male sex and 99m TcO 4 - uptake were associated with treatment failure. On receiver operating characteristic (ROC) curve analysis, area under the curve (AUC) was significant for 99m TcO 4 - uptake predicting treatment failure (AUC = 0.623; P = 0.039). Optimum cutoff for 99m TcO 4 - uptake was 17.75 with a sensitivity of 68% and specificity of 66% to predict treatment failure. Patients with >17.75% 99m TcO 4 - uptake had odds ratio of 3.14 (P = 0.014) for treatment failure and male patients had odds ratio of 1.783 for treatment failure. Our results suggest that male patients and patients with high pre-treatment 99m TcO 4 - uptake are more likely to require repeated doses of 131 I to achieve complete remission

  17. To identify factors of predictive value i

    African Journals Online (AJOL)

    hi-tech

    2000-01-01

    Jan 1, 2000 ... the development of mid-brain cones if left untreated. The resultant fatality that ... the duration between the event and presentation to hospital was less .... conformed to the situation of vascular structures that had been damaged ...

  18. Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics.

    Science.gov (United States)

    Rho, Mi Jung; Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Jung, Dong Jin; Kim, Dai-Jin; Choi, In Young

    2017-12-27

    Background : Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods : Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results : The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions : These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment.

  19. Screening for violence risk factors identifies young adults at risk for return emergency department visit for injury.

    Science.gov (United States)

    Hankin, Abigail; Wei, Stanley; Foreman, Juron; Houry, Debra

    2014-08-01

    Homicide is the second leading cause of death among youth aged 15-24. Prior cross-sectional studies, in non-healthcare settings, have reported exposure to community violence, peer behavior, and delinquency as risk factors for violent injury. However, longitudinal cohort studies have not been performed to evaluate the temporal or predictive relationship between these risk factors and emergency department (ED) visits for injuries among at-risk youth. The objective was to assess whether self-reported exposure to violence risk factors in young adults can be used to predict future ED visits for injuries over a 1-year period. This prospective cohort study was performed in the ED of a Southeastern US Level I trauma center. Eligible participants were patients aged 18-24, presenting for any chief complaint. We excluded patients if they were critically ill, incarcerated, or could not read English. Initial recruitment occurred over a 6-month period, by a research assistant in the ED for 3-5 days per week, with shifts scheduled such that they included weekends and weekdays, over the hours from 8AM-8PM. At the time of initial contact in the ED, patients were asked to complete a written questionnaire, consisting of previously validated instruments measuring the following risk factors: a) aggression, b) perceived likelihood of violence, c) recent violent behavior, d) peer behavior, e) community exposure to violence, and f) positive future outlook. At 12 months following the initial ED visit, the participants' medical records were reviewed to identify any subsequent ED visits for injury-related complaints. We analyzed data with chi-square and logistic regression analyses. Three hundred thirty-two patients were approached, of whom 300 patients consented. Participants' average age was 21.1 years, with 60.1% female, 86.0% African American. After controlling for participant gender, ethnicity, or injury complaint at time of first visit, return visits for injuries were significantly

  20. Factores predictivos de las infecciones posoperatorias Prediction factors of the postoperative infections

    Directory of Open Access Journals (Sweden)

    Manuel Pascual Bestard

    2011-09-01

    Full Text Available Introducción: la génesis de las infecciones posquirúrgicas es multifactorial. Existen estudios internacionales que evidencian los diversos factores predictivos relacionados con la aparición de estas complicaciones, las que todavía afectan a un número considerable de pacientes intervenidos, todo lo cual justifica el interés en la realización de este trabajo. Objetivo: describir el comportamiento de algunos de los factores predictivos relacionados con la aparición de las infecciones posoperatorias en nuestro medio. Métodos: se realizó un estudio observacional, descriptivo y transversal de los pacientes ingresados y operados que presentaron infecciones posquirúrgicas en el servicio de cirugía general del Hospital Provincial Docente "Saturnino Lora" de Santiago de Cuba, durante el año 2008, según posibles factores predictivos seleccionados. Resultados: con relación al grado de contaminación, la tasa global de infección posoperatoria y la de heridas limpias estuvo en límites universalmente aceptados, aunque fueron más elevadas en las intervenciones urgentes, sucias y contaminadas para las localizadas en el sitio quirúrgico, así como en enfermos con estado físico preoperatorio según la American Society of Anaesthesiology (ASA ASA II Y ASA III, con independencia de su estado nutricional y el tiempo quirúrgico en que se efectuaron las intervenciones. Conclusiones: las tasas de infecciones posquirúrgicas aumentaron en la medida en que fueron desfavorables las condiciones bajo las que se efectuaron las operaciones, y los factores predictivos seleccionados se relacionaron principalmente para las localizadas en el sitio quirúrgico, con el grado de contaminación, el tipo de intervención y el estado físico preoperatorio del paciente.Introduction: the genesis of the postsurgical infections is multifactor. The are many international studies evidencing the different prediction factors related to the appearance of these complications

  1. Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

    Science.gov (United States)

    Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

  2. Risk Factors and Predictive Model Development of Thirty-Day Post-Operative Surgical Site Infection in the Veterans Administration Surgical Population.

    Science.gov (United States)

    Li, Xinli; Nylander, William; Smith, Tracy; Han, Soonhee; Gunnar, William

    2018-04-01

    Surgical site infection (SSI) complicates approximately 2% of surgeries in the Veterans Affairs (VA) hospitals. Surgical site infections are responsible for increased morbidity, length of hospital stay, cost, and mortality. Surgical site infection can be minimized by modifying risk factors. In this study, we identified risk factors and developed accurate predictive surgical specialty-specific SSI risk prediction models for the Veterans Health Administration (VHA) surgery population. In a retrospective observation study, surgical patients who underwent surgery from October 2013 to September 2016 from 136 VA hospitals were included. The Veteran Affairs Surgical Quality Improvement Program (VASQIP) database was used for the pre-operative demographic and clinical characteristics, intra-operative characteristics, and 30-day post-operative outcomes. The study population represents 11 surgical specialties: neurosurgery, urology, podiatry, otolaryngology, general, orthopedic, plastic, thoracic, vascular, cardiac coronary artery bypass graft (CABG), and cardiac valve/other surgery. Multivariable logistic regression models were developed for the 30-day post-operative SSIs. Among 354,528 surgical procedures, 6,538 (1.8%) had SSIs within 30 days. Surgical site infection rates varied among surgical specialty (0.7%-3.0%). Surgical site infection rates were higher in emergency procedures, procedures with long operative duration, greater complexity, and higher relative value units. Other factors associated with increased SSI risk were high level of American Society of Anesthesiologists (ASA) classification (level 4 and 5), dyspnea, open wound/infection, wound classification, ascites, bleeding disorder, chemotherapy, smoking, history of severe chronic obstructive pulmonary disease (COPD), radiotherapy, steroid use for chronic conditions, and weight loss. Each surgical specialty had a distinct combination of risk factors. Accurate SSI risk-predictive surgery specialty

  3. PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease.

    Science.gov (United States)

    Noyce, Alastair J; R'Bibo, Lea; Peress, Luisa; Bestwick, Jonathan P; Adams-Carr, Kerala L; Mencacci, Niccolo E; Hawkes, Christopher H; Masters, Joseph M; Wood, Nicholas; Hardy, John; Giovannoni, Gavin; Lees, Andrew J; Schrag, Anette

    2017-02-01

    A number of early features can precede the diagnosis of Parkinson's disease (PD). To test an online, evidence-based algorithm to identify risk indicators of PD in the UK population. Participants aged 60 to 80 years without PD completed an online survey and keyboard-tapping task annually over 3 years, and underwent smell tests and genotyping for glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 (LRRK2) mutations. Risk scores were calculated based on the results of a systematic review of risk factors and early features of PD, and individuals were grouped into higher (above 15th centile), medium, and lower risk groups (below 85th centile). Previously defined indicators of increased risk of PD ("intermediate markers"), including smell loss, rapid eye movement-sleep behavior disorder, and finger-tapping speed, and incident PD were used as outcomes. The correlation of risk scores with intermediate markers and movement of individuals between risk groups was assessed each year and prospectively. Exploratory Cox regression analyses with incident PD as the dependent variable were performed. A total of 1323 participants were recruited at baseline and >79% completed assessments each year. Annual risk scores were correlated with intermediate markers of PD each year and baseline scores were correlated with intermediate markers during follow-up (all P values < 0.001). Incident PD diagnoses during follow-up were significantly associated with baseline risk score (hazard ratio = 4.39, P = .045). GBA variants or G2019S LRRK2 mutations were found in 47 participants, and the predictive power for incident PD was improved by the addition of genetic variants to risk scores. The online PREDICT-PD algorithm is a unique and simple method to identify indicators of PD risk. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder

  4. Perforated Peptic Ulcer Repair: Factors Predicting Conversion in Laparoscopy and Postoperative Septic Complications.

    Science.gov (United States)

    Muller, Markus K; Wrann, Simon; Widmer, Jeannette; Klasen, Jennifer; Weber, Markus; Hahnloser, Dieter

    2016-09-01

    The surgical treatment for perforated peptic ulcers can be safely performed laparoscopically. The aim of the study was to define simple predictive factors for conversion and septic complications. This retrospective case-control study analyzed patients treated with either laparoscopic surgery or laparotomy for perforated peptic ulcers. A total of 71 patients were analyzed. Laparoscopically operated patients had a shorter hospital stay (13.7 vs. 15.1 days). In an intention-to-treat analysis, patients with conversion to open surgery (analyzed as subgroup from laparoscopic approach group) showed no prolonged hospital stay (15.3 days) compared to patients with a primary open approach. Complication and mortality rates were not different between the groups. The statistical analysis identified four intraoperative risk factors for conversion: Mannheim peritonitis index (MPI) > 21 (p = 0.02), generalized peritonitis (p = 0.04), adhesions, and perforations located in a region other than the duodenal anterior wall. We found seven predictive factors for septic complications: age >70 (p = 0.02), cardiopulmonary disease (p = 0.04), ASA > 3 (p = 0.002), CRP > 100 (p = 0.005), duration of symptoms >24 h (p = 0.02), MPI > 21(p = 0.008), and generalized peritonitis (p = 0.02). Our data suggest that a primary laparoscopic approach has no disadvantages. Factors necessitating conversions emerged during the procedure inhibiting a preoperative selection. Factors suggesting imminent septic complications can be assessed preoperatively. An assessment of the proposed parameters may help optimize the management of possible septic complications.

  5. [Predicting individual risk of high healthcare cost to identify complex chronic patients].

    Science.gov (United States)

    Coderch, Jordi; Sánchez-Pérez, Inma; Ibern, Pere; Carreras, Marc; Pérez-Berruezo, Xavier; Inoriza, José M

    2014-01-01

    To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients. A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC). Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902). High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

  6. Factors predicting the development of pressure ulcers in an at-risk population who receive standardized preventive care: secondary analyses of a multicentre randomised controlled trial.

    Science.gov (United States)

    Demarre, Liesbet; Verhaeghe, Sofie; Van Hecke, Ann; Clays, Els; Grypdonck, Maria; Beeckman, Dimitri

    2015-02-01

    To identify predictive factors associated with the development of pressure ulcers in patients at risk who receive standardized preventive care. Numerous studies have examined factors that predict risk for pressure ulcer development. Only a few studies identified risk factors associated with pressure ulcer development in hospitalized patients receiving standardized preventive care. Secondary analyses of data collected in a multicentre randomized controlled trial. The sample consisted of 610 consecutive patients at risk for pressure ulcer development (Braden Score Pressure ulcers in category II-IV were significantly associated with non-blanchable erythema, urogenital disorders and higher body temperature. Predictive factors significantly associated with superficial pressure ulcers were admission to an internal medicine ward, incontinence-associated dermatitis, non-blanchable erythema and a lower Braden score. Superficial sacral pressure ulcers were significantly associated with incontinence-associated dermatitis. Despite the standardized preventive measures they received, hospitalized patients with non-blanchable erythema, urogenital disorders and a higher body temperature were at increased risk for developing pressure ulcers. Improved identification of at-risk patients can be achieved by taking into account specific predictive factors. Even if preventive measures are in place, continuous assessment and tailoring of interventions is necessary in all patients at risk. Daily skin observation can be used to continuously monitor the effectiveness of the intervention. © 2014 John Wiley & Sons Ltd.

  7. Analytical prediction of turbulent friction factor for a rod bundle

    International Nuclear Information System (INIS)

    Bae, Jun Ho; Park, Joo Hwan

    2011-01-01

    An analytical calculation has been performed to predict the turbulent friction factor in a rod bundle. For each subchannel constituting a rod bundle, the geometry parameters are analytically derived by integrating the law of the wall over each subchannel with the consideration of a local shear stress distribution. The correlation equations for a local shear stress distribution are supplied from a numerical simulation for each subchannel. The explicit effect of a subchannel shape on the geometry parameter and the friction factor is reported. The friction factor of a corner subchannel converges to a constant value, while the friction factor of a central subchannel steadily increases with a rod distance ratio. The analysis for a rod bundle shows that the friction factor of a rod bundle is largely affected by the characteristics of each subchannel constituting a rod bundle. The present analytic calculations well predict the experimental results from the literature with rod bundles in circular, hexagonal, and square channels.

  8. What Factors are Predictive of Patient-reported Outcomes? A Prospective Study of 337 Shoulder Arthroplasties.

    Science.gov (United States)

    Matsen, Frederick A; Russ, Stacy M; Vu, Phuong T; Hsu, Jason E; Lucas, Robert M; Comstock, Bryan A

    2016-11-01

    a better outcome). A cutoff probability of 0.68 yielded the best performance of the model with cross-validation predictions of better outcomes for 236 patients (80%) and worse outcomes for 58 patients (20%); sensitivity of 91% (95% CI, 88%-95%); specificity of 65% (95% CI, 53%-77%); positive predictive value of 92% (95% CI, 88%-95%); and negative predictive value of 64% (95% CI, 51%-76%). We found six easy-to-determine preoperative patient and shoulder factors that were significantly associated with better outcomes of shoulder arthroplasty. A model based on these characteristics had good predictive properties for identifying patients likely to have a better outcome from shoulder arthroplasty. Future research could refine this model with larger patient populations from multiple practices. Level II, therapeutic study.

  9. Factors Predicting Survival after Transarterial Chemoembolization of Unresectable Hepatocellular Carcinoma

    Directory of Open Access Journals (Sweden)

    Farina M. Hanif

    2014-10-01

    Full Text Available Background: Transarterial chemoembolization is the preferred treatment for unresectable, intermediate-stage hepatocellular carcinoma. Survival after transarterial chemoembolization can be highly variable. The purpose of this study is to identify the factors that predict overall survival of patients with unresectable hepatocellular carcinoma who undergo transarterial chemoembolization as the initial therapy. Methods:We included patients who underwent transarterial chemoembolization from 2007 to 2012 in this study. Patient’s age, gender, cause of cirrhosis, Child-Turcotte-Pugh score, model of end-stage liver disease score, Cancer of the Liver Italian Program score, Okuda stage, alpha- fetoprotein level, site, size and number of tumors were recorded. Radiological response to transarterial chemoembolization was assessed by computerized tomography scan at 1 and 3 months after the procedure. Repeat sessions of transarterial chemoembolization were performed according to the response. We performed survival assessment and all patients were assessed for survival at the last follow-up. Results: Included in this study were 71 patients of whom there were 57 (80.3 % males, with a mean age of 51.9±12.1 years (range: 18-76 years. The mean follow-up period was 12.5±10.7 months. A total of 31 (43.7% patients had only one session of transarterial chemoembolization, 17 (23.9% underwent 2 and 11 (15.5% had 3 or more sessions. On univariate analysis, significant factors that predicted survival included serum bilirubin (P=0.02, esophageal varices (P=0.002, Cancer of the Liver Italian Program score (P=0.003, tumor size (P=0.005, >3 sessions of transarterial chemoembolization (P=0.006 and patient's age (P=0.001. Cox regression analysis showed that tumor size of 1 transarterial chemoembolization session (P=0.004 were associated with better survival. Conclusion: Our study demonstrates that survival after transarterial chemoem- bolization is predicted by tumor size

  10. Factors predicting visual improvement post pars plana vitrectomy for proliferative diabetic retinopathy

    Directory of Open Access Journals (Sweden)

    Evelyn Tai Li Min

    2017-08-01

    Full Text Available AIM: To identify factors predicting visual improvement post vitrectomy for sequelae of proliferative diabetic retinopathy(PDR.METHODS: This was a retrospective analysis of pars plana vitrectomy indicated for sequelae of PDR from Jan. to Dec. 2014 in Hospital Sultanah Bahiyah, Alor Star, Kedah, Malaysia. Data collected included patient demographics, baseline visual acuity(VAand post-operative logMAR best corrected VA at 1y. Data analysis was performed with IBM SPSS Statistics Version 22.0. RESULTS: A total of 103 patients were included. The mean age was 51.2y. On multivariable analysis, each pre-operative positive deviation of 1 logMAR from a baseline VA of 0 logMAR was associated with a post-operative improvement of 0.859 logMAR(P0.001. Likewise, an attached macula pre-operatively was associated with a 0.374(P=0.003logMAR improvement post vitrectomy. Absence of iris neovascularisation and absence of post-operative complications were associated with a post vitrectomy improvement in logMAR by 1.126(P=0.001and 0.377(P=0.005respectively. Absence of long-acting intraocular tamponade was associated with a 0.302(P=0.010improvement of logMAR post vitrectomy.CONCLUSION: Factors associated with visual improvement after vitrectomy are poor pre-operative VA, an attached macula, absence of iris neovascularisation, absence of post-operative complications and abstaining from use of long-acting intraocular tamponade. A thorough understanding of the factors predicting visual improvement will facilitate decision-making in vitreoretinal surgery.

  11. A novel method of predicting microRNA-disease associations based on microRNA, disease, gene and environment factor networks.

    Science.gov (United States)

    Peng, Wei; Lan, Wei; Zhong, Jiancheng; Wang, Jianxin; Pan, Yi

    2017-07-15

    MicroRNAs have been reported to have close relationship with diseases due to their deregulation of the expression of target mRNAs. Detecting disease-related microRNAs is helpful for disease therapies. With the development of high throughput experimental techniques, a large number of microRNAs have been sequenced. However, it is still a big challenge to identify which microRNAs are related to diseases. Recently, researchers are interesting in combining multiple-biological information to identify the associations between microRNAs and diseases. In this work, we have proposed a novel method to predict the microRNA-disease associations based on four biological properties. They are microRNA, disease, gene and environment factor. Compared with previous methods, our method makes predictions not only by using the prior knowledge of associations among microRNAs, disease, environment factors and genes, but also by using the internal relationship among these biological properties. We constructed four biological networks based on the similarity of microRNAs, diseases, environment factors and genes, respectively. Then random walking was implemented on the four networks unequally. In the walking course, the associations can be inferred from the neighbors in the same networks. Meanwhile the association information can be transferred from one network to another. The results of experiment showed that our method achieved better prediction performance than other existing state-of-the-art methods. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Malnutrition predicting factors in hemodialysis patients.

    Science.gov (United States)

    Jahromi, Soodeh Razeghi; Hosseini, Saeed; Razeghi, Effat; Meysamie, Ali pasha; Sadrzadeh, Haleh

    2010-09-01

    Malnutrition is a predictor of increased mortality in chronic hemodialysis (HD) patients. Various factors may contribute to malnutrition in these patients including energy and protein intake, inflammation, and comorbidity. To determine the importance of these factors in malnutrition of chronic HD patients, we studied 112 chronic HD patients in two centers was evaluated with the Dialysis Malnutrition Score (DMS) and anthropometric and biochemical indices. Seventy six (67.8%) patients were classified as malnourished. According to DMS score, poor protein intake (r= -0.34, Penergy intake (r= - 0.18, Pmalnutrition in descending order of importance. Multiple regression analysis showed that only poor protein intake was the explanatory variable of anthropometric measurements decline including body mass index, triceps skin fold thick-ness, mid arm circumference, mid arm muscle circumference, fat free mass, fat mass, albumin, creatinine and transferrine. None of the mentioned factors predicted the decrease of biochemical markers. We conclude that the frequency of malnutrition is high in our population and poor protein intake is the primary contributing factor for this condition. Therefore, providing enough protein may be a simple and effective way in preventing malnutrition in these patients.

  13. PREDICTION OF THE EXTREMAL SHAPE FACTOR OF SPHEROIDAL PARTICLES

    Directory of Open Access Journals (Sweden)

    Daniel Hlubinka

    2011-05-01

    Full Text Available In the stereological unfolding problem for spheroidal particles the extremal shape factor is predicted. The theory of extreme values has been used to show that extremes of the planar shape factor of particle sections tend to the same limit distribution as extremes of the original shape factor for both the conditional and marginal distribution. Attention is then paid to the extreme shape factor conditioned by the particle size. Normalizing constants are evaluated for a parametric model and the numerical procedure is tested on real data from metallography.

  14. Factors predicting survival following noninvasive ventilation in amyotrophic lateral sclerosis.

    Science.gov (United States)

    Peysson, S; Vandenberghe, N; Philit, F; Vial, C; Petitjean, T; Bouhour, F; Bayle, J Y; Broussolle, E

    2008-01-01

    The involvement of respiratory muscles is a major predicting factor for survival in amyotrophic lateral sclerosis (ALS). Recent studies show that noninvasive ventilation (NIV) can relieve symptoms of alveolar hypoventilation. However, factors predicting survival in ALS patients when treated with NIV need to be clarified. We conducted a retrospective study of 33 consecutive ALS patients receiving NIV. Ten patients had bulbar onset. We determined the median survivals from onset, diagnosis and initiation of NIV and factors predicting survival. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. The median initial and maximal total uses of NIV were 10 and 14 h/24h. The overall median survival from ALS onset was 34.2 months and worsened with increasing age and bulbar onset of the disease. The median survival from initiation of NIV was 8.4 months and was significantly poorer in patients with advanced age or with airway mucus accumulation. Survival from initiation of NIV was not influenced by respiratory parameters or bulbar symptoms. Advanced age at diagnosis and airway mucus accumulation represent poorer prognostic factors of ALS patients treated with NIV. NIV is a helpful treatment of sleep-disordered breathing, including patients with bulbar involvement. Copyright 2008 S. Karger AG, Basel.

  15. Assessing vulnerability to drought: identifying underlying factors across Europe

    Science.gov (United States)

    Urquijo, Julia; Gonzalez Tánago, Itziar; Ballesteros, Mario; De Stefano, Lucia

    2015-04-01

    Drought is considered one of the most severe and damaging natural hazards in terms of people and sectors affected and associated losses. Drought is a normal and recurrent climatic phenomenon that occurs worldwide, although its spatial and temporal characteristics vary significantly among climates. In the case of Europe, in the last thirty years, the region has suffered several drought events that have caused estimated economic damages over a €100 billion and have affected almost 20% of its territory and population. In recent years, there has been a growing awareness among experts and authorities of the need to shift from a reactive crisis approach to a drought risk management approach, as well as of the importance of designing and implementing policies, strategies and plans at country and river basin levels to deal with drought. The identification of whom and what is vulnerable to drought is a central aspect of drought risk mitigation and planning and several authors agree that societal vulnerability often determines drought risk more than the actual precipitation shortfalls. The final aim of a drought vulnerability assessment is to identify the underlying sources of drought impact, in order to develop policy options that help to enhance coping capacity and therefore to prevent drought impact. This study identifies and maps factors underlying vulnerability to drought across Europe. The identification of factors influencing vulnerability starts from the analysis of past drought impacts in four European socioeconomic sectors. This analysis, along with an extensive literature review, led to the selection of vulnerability factors that are both relevant and adequate for the European context. Adopting the IPCC model, vulnerability factors were grouped to describe exposure, sensitivity and adaptive capacity. The aggregation of these components has resulted in the mapping of vulnerability to drought across Europe at NUTS02 level. Final results have been compared with

  16. Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics

    Directory of Open Access Journals (Sweden)

    Mi Jung Rho

    2017-12-01

    Full Text Available Background: Understanding the risk factors associated with Internet gaming disorder (IGD is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods: Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5 criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results: The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138, belief self-control (1.034, anxiety (1.086, pursuit of desired appetitive goals (1.105, money spent on gaming (1.005, weekday game time (1.081, offline community meeting attendance (2.060, and game community membership (1.393; p < 0.05 for all eight risk factors; Conclusions: These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment.

  17. Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics

    Science.gov (United States)

    Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Kim, Dai-Jin; Choi, In Young

    2017-01-01

    Background: Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods: Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results: The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions: These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment. PMID:29280953

  18. Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes: A systematic review and meta-analysis and analysis of two pregnancy cohorts.

    Directory of Open Access Journals (Sweden)

    Diane Farrar

    Full Text Available Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT to diagnose gestational diabetes (GDM. Evidence regarding these risk factors is limited however. We conducted a systematic review (SR and meta-analysis and individual participant data (IPD analysis to evaluate the performance of risk factors in identifying women with GDM.We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included.Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives. Strategies that use the risk factors of age (>25 or >30 and BMI (>25 or 30 perform as well as other strategies with additional risk factors included.Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple

  19. Identify the Important Decision Factors of Online Shopping Adoption in Indonesia

    Directory of Open Access Journals (Sweden)

    Lailatul HIJRAH

    2017-12-01

    Full Text Available The objective of this study is to identify factors encouraging a consumer to engage in online shopping activities. The expected contribution of this study is for online entrepreneurs, in order to develop the most suitable business strategy, so that it will be clearly identified and sorted out which factors are the most important and the main motivation of Indonesian consumers to shop via online by using responses from respondents who usually shop online and offline in 3 cities in Indonesia, Jakarta, Surabaya and Samarinda. The research instruments were developed by conducting FGDs on relevant groups, either academics, online shopping activists, suppliers and courier businessmen in Jakarta, Surabaya and Samarinda Cities in effort to extract any information that encourages consumers to online shopping. After conducting FGD, the researcher produced 48 items proposed for factor analysis and after extracted to form eleven constructs, some items were removed because they had less loading factors. The eleven constructs or dimensions are trust, risk, consumer factors, website factors, price, service quality, convenience, subjective norm, product guarantee, variety of products and lifestyle. The implications of this study provide valuable insights about consumer decisions to online shopping or not online shopping.

  20. Factors predicting successful discontinuation of continuous renal replacement therapy.

    Science.gov (United States)

    Katayama, S; Uchino, S; Uji, M; Ohnuma, T; Namba, Y; Kawarazaki, H; Toki, N; Takeda, K; Yasuda, H; Izawa, J; Tokuhira, N; Nagata, I

    2016-07-01

    This multicentre, retrospective observational study was conducted from January 2010 to December 2010 to determine the optimal time for discontinuing continuous renal replacement therapy (CRRT) by evaluating factors predictive of successful discontinuation in patients with acute kidney injury. Analysis was performed for patients after CRRT was discontinued because of renal function recovery. Patients were divided into two groups according to the success or failure of CRRT discontinuation. In multivariate logistic regression analysis, urine output at discontinuation, creatinine level and CRRT duration were found to be significant variables (area under the receiver operating characteristic curve for urine output, 0.814). In conclusion, we found that higher urine output, lower creatinine and shorter CRRT duration were significant factors to predict successful discontinuation of CRRT.

  1. Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

    Science.gov (United States)

    Haltigan, John D; Vaillancourt, Tracy

    2016-03-01

    To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

  2. A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

    Science.gov (United States)

    Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

    2015-12-01

    This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Some new results on correlation-preserving factor scores prediction methods

    NARCIS (Netherlands)

    Ten Berge, J.M.F.; Krijnen, W.P.; Wansbeek, T.J.; Shapiro, A.

    1999-01-01

    Anderson and Rubin and McDonald have proposed a correlation-preserving method of factor scores prediction which minimizes the trace of a residual covariance matrix for variables. Green has proposed a correlation-preserving method which minimizes the trace of a residual covariance matrix for factors.

  4. Predictive Factors associated with Death of Elderly in Nursing Homes

    OpenAIRE

    Kiwol Sung, PhD, RN

    2014-01-01

    Purpose: An increasing elderly population reflects a great need for readily accessible, clinically useful methods to identify mortality-related factors in nursing home residents. The purpose of this study was to identify factors associated with the deaths of nursing home residents. Methods: Data was collected from a Minimal Data Set of 195 elderly nursing home residents, followed by analysis of demographic factors, disease and nursing condition factors, Activities of Daily Living (ADL), co...

  5. Predictive factors in patients eligible for pegfilgrastim prophylaxis focusing on RDI using ordered logistic regression analysis.

    Science.gov (United States)

    Kanbayashi, Yuko; Ishikawa, Takeshi; Kanazawa, Motohiro; Nakajima, Yuki; Kawano, Rumi; Tabuchi, Yusuke; Yoshioka, Tomoko; Ihara, Norihiko; Hosokawa, Toyoshi; Takayama, Koichi; Shikata, Keisuke; Taguchi, Tetsuya

    2018-03-16

    Although pegfilgrastim prophylaxis is expected to maintain the relative dose intensity (RDI) of chemotherapy and improve safety, information is limited. However, the optimal selection of patients eligible for pegfilgrastim prophylaxis is an important issue from a medical economics viewpoint. Therefore, this retrospective study identified factors that could predict these eligible patients to maintain the RDI. The participants included 166 cancer patients undergoing pegfilgrastim prophylaxis combined with chemotherapy in our outpatient chemotherapy center between March 2015 and April 2017. Variables were extracted from clinical records for regression analysis of factors related to maintenance of the RDI. RDI was classified into four categories: 100% = 0, 85% or predictive factors in patients eligible for pegfilgrastim prophylaxis to maintain the RDI. Threshold measures were examined using a receiver operating characteristic (ROC) analysis curve. Age [odds ratio (OR) 1.07, 95% confidence interval (CI) 1.04-1.11; P maintenance. ROC curve analysis of the group that failed to maintain the RDI indicated that the threshold for age was 70 years and above, with a sensitivity of 60.0% and specificity of 80.2% (area under the curve: 0.74). In conclusion, younger age, anemia (less), and administration of pegfilgrastim 24-72 h after chemotherapy were significant factors for RDI maintenance.

  6. Spontaneous regression of retinopathy of prematurity:incidence and predictive factors

    Directory of Open Access Journals (Sweden)

    Rui-Hong Ju

    2013-08-01

    Full Text Available AIM:To evaluate the incidence of spontaneous regression of changes in the retina and vitreous in active stage of retinopathy of prematurity(ROP and identify the possible relative factors during the regression.METHODS: This was a retrospective, hospital-based study. The study consisted of 39 premature infants with mild ROP showed spontaneous regression (Group A and 17 with severe ROP who had been treated before naturally involuting (Group B from August 2008 through May 2011. Data on gender, single or multiple pregnancy, gestational age, birth weight, weight gain from birth to the sixth week of life, use of oxygen in mechanical ventilation, total duration of oxygen inhalation, surfactant given or not, need for and times of blood transfusion, 1,5,10-min Apgar score, presence of bacterial or fungal or combined infection, hyaline membrane disease (HMD, patent ductus arteriosus (PDA, duration of stay in the neonatal intensive care unit (NICU and duration of ROP were recorded.RESULTS: The incidence of spontaneous regression of ROP with stage 1 was 86.7%, and with stage 2, stage 3 was 57.1%, 5.9%, respectively. With changes in zone Ⅲ regression was detected 100%, in zoneⅡ 46.2% and in zoneⅠ 0%. The mean duration of ROP in spontaneous regression group was 5.65±3.14 weeks, lower than that of the treated ROP group (7.34±4.33 weeks, but this difference was not statistically significant (P=0.201. GA, 1min Apgar score, 5min Apgar score, duration of NICU stay, postnatal age of initial screening and oxygen therapy longer than 10 days were significant predictive factors for the spontaneous regression of ROP (P<0.05. Retinal hemorrhage was the only independent predictive factor the spontaneous regression of ROP (OR 0.030, 95%CI 0.001-0.775, P=0.035.CONCLUSION:This study showed most stage 1 and 2 ROP and changes in zone Ⅲ can spontaneously regression in the end. Retinal hemorrhage is weakly inversely associated with the spontaneous regression.

  7. Identifying predictive features in drug response using machine learning: opportunities and challenges.

    Science.gov (United States)

    Vidyasagar, Mathukumalli

    2015-01-01

    This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

  8. Human Factors Predicting Failure and Success in Hospital Information System Implementations in Sub-Saharan Africa.

    Science.gov (United States)

    Verbeke, Frank; Karara, Gustave; Nyssen, Marc

    2015-01-01

    From 2007 through 2014, the authors participated in the implementation of open source hospital information systems (HIS) in 19 hospitals in Rwanda, Burundi, DR Congo, Congo-Brazzaville, Gabon, and Mali. Most of these implementations were successful, but some failed. At the end of a seven-year implementation effort, a number of risk factors, facilitators, and pragmatic approaches related to the deployment of HIS in Sub-Saharan health facilities have been identified. Many of the problems encountered during the HIS implementation process were not related to technical issues but human, cultural, and environmental factors. This study retrospectively evaluates the predictive value of 14 project failure factors and 15 success factors in HIS implementation in the Sub-Saharan region. Nine of the failure factors were strongly correlated with project failure, three were moderately correlated, and one weakly correlated. Regression analysis also confirms that eight factors were strongly correlated with project success, four moderately correlated, and two weakly correlated. The study results may help estimate the expedience of future HIS projects.

  9. Patient factors predicting early dropout from psychiatric outpatient care for borderline personality disorder.

    Science.gov (United States)

    De Panfilis, Chiara; Marchesi, Carlo; Cabrino, Chiara; Monici, Alberto; Politi, Virginia; Rossi, Matteo; Maggini, Carlo

    2012-12-30

    Despite obvious clinical need, factors underlying early treatment discontinuation among 'real world' borderline personality disorder (BPD) patients are still unknown. This study investigates individual characteristics that can predict early (Disorders, fourth edition (DSM-IV) Personality. Sociodemographic, clinical and personality variables potentially relevant for dropout were assessed for all participants at baseline. Early dropouts (n=54) were compared to continuers (n=108) on all measures. Logistic regression was then used to identify independent predictors of early dropout. A history of suicide attempts predicted early discontinuation, whereas the presence of an eating disorder and of avoidant personality features protected from early dropout. If confirmed, these findings may help clinicians operating in general psychiatric settings with estimating the risk of premature treatment discontinuation, and stress the need to specifically address suicidal behaviours in order to improve treatment retention among borderline outpatients. In this regard, implementing general psychiatric care with specialised, evidence-based psychotherapeutic interventions may be deemed necessary. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  10. On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

    Science.gov (United States)

    Torres, César Iván

    2014-06-01

    The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

    Directory of Open Access Journals (Sweden)

    Karacali Bilge

    2007-10-01

    Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

  12. Using TESS to predict transcription factor binding sites in DNA sequence.

    Science.gov (United States)

    Schug, Jonathan

    2008-03-01

    This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence-specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites.

  13. Factors Predicting a Good Symptomatic Outcome After Prostate Artery Embolisation (PAE).

    Science.gov (United States)

    Maclean, D; Harris, M; Drake, T; Maher, B; Modi, S; Dyer, J; Somani, B; Hacking, N; Bryant, T

    2018-02-26

    As prostate artery embolisation (PAE) becomes an established treatment for benign prostatic obstruction, factors predicting good symptomatic outcome remain unclear. Pre-embolisation prostate size as a predictor is controversial with a handful of papers coming to conflicting conclusions. We aimed to investigate if an association existed in our patient cohort between prostate size and clinical benefit, in addition to evaluating percentage volume reduction as a predictor of symptomatic outcome following PAE. Prospective follow-up of 86 PAE patients at a single institution between June 2012 and January 2016 was conducted (mean age 64.9 years, range 54-80 years). Multiple linear regression analysis was performed to assess strength of association between clinical improvement (change in IPSS) and other variables, of any statistical correlation, through Pearson's bivariate analysis. No major procedural complications were identified and clinical success was achieved in 72.1% (n = 62) at 12 months. Initial prostate size and percentage reduction were found to have a significant association with clinical improvement. Multiple linear regression analysis (r 2  = 0.48) demonstrated that percentage volume reduction at 3 months (r = 0.68, p < 0.001) had the strongest correlation with good symptomatic improvement at 12 months after adjusting for confounding factors. Both the initial prostate size and percentage volume reduction at 3 months predict good symptomatic outcome at 12 months. These findings therefore aid patient selection and counselling to achieve optimal outcomes for men undergoing prostate artery embolisation.

  14. A systematic review of the factors predicting the interest in cosmetic plastic surgery

    Directory of Open Access Journals (Sweden)

    Panagiotis Milothridis

    2016-01-01

    Full Text Available Background: A systematic review of the literature was performed to clarify the psychosocial characteristics of patients who have an interest in cosmetic plastic surgery. Methods: Medical literature was reviewed by two independent researchers, and a third reviewer evaluated their results. Results: Twelve studies addressing the predictors of interest in cosmetic surgery were finally identified and analysed. Interest in cosmetic surgery was associated with epidemiological factors, their social networks, their psychological characteristics, such as body image, self-esteem and other personality traits and for specific psychopathology and found that these may either positively or negatively predict their motivation to seek and undergo a cosmetic procedure. Conclusions: The review examined the psychosocial characteristics associated with an interest in cosmetic surgery. Understanding cosmetic patients' characteristics, motivation and expectation for surgery is an important aspect of their clinical care to identify those patients more likely to benefit most from the procedure.

  15. Prediction of software operational reliability using testing environment factors

    International Nuclear Information System (INIS)

    Jung, Hoan Sung; Seong, Poong Hyun

    1995-01-01

    A number of software reliability models have been developed to estimate and to predict software reliability. However, there are no established standard models to quantify software reliability. Most models estimate the quality of software in reliability figures such as remaining faults, failure rate, or mean time to next failure at the testing phase, and they consider them ultimate indicators of software reliability. Experience shows that there is a large gap between predicted reliability during development and reliability measured during operation, which means that predicted reliability, or so-called test reliability, is not operational reliability. Customers prefer operational reliability to test reliability. In this study, we propose a method that predicts operational reliability rather than test reliability by introducing the testing environment factor that quantifies the changes in environments

  16. [Predictive factors of the outcomes of prenatal hydronephrosis.

    Science.gov (United States)

    Bragagnini, Paolo; Estors, Blanca; Delgado, Reyes; Rihuete, Miguel Ángel; Gracia, Jesús

    2016-12-01

    To determine prenatal and postnatal independent predictors of poor outcome, spontaneous resolution, or the need for surgery in patients with prenatal hydronephrosis. We performed a retrospective study of patients with prenatal hydronephrosis. The renal pelvis APD was measured in the third prenatal trimester ultrasound, as well as in the first and second postnatal ultrasound. Other variables were taken into account, both prenatal and postnatal. For statistical analysis we used Student t-test, chi-square test, survival analysis, logrank test, and ROC curves. We included 218 patients with 293 renal units (RU). Of these, 147/293 (50.2%) RU were operated. 76/293 (25.9%) RU had spontaneous resolution and other 76/293 (25.9%) RU had poor outcome. As risk factors for surgery we found low birth weight (OR 3.84; 95% CI 1.24-11.84), prematurity (OR 4.17; 95% CI 1.35-12.88), duplication (OR 4.99; 95% CI 2.21-11.23) and the presence of nephrourological underlying pathology (OR 53.54; 95% CI 26.23-109.27). For the non-spontaneous resolution, we found as risk factors the alterations of amniotic fluid volume (RR 1.46; 95% CI 1.33-1.60) as well as the underlying nephrourological pathology and duplication. In the poor outcome, we found as risk factors the alterations of amniotic fluid volume (OR 4.54; 95% CI 1.31-15.62), the presence of nephrourological pathology (OR 4.81 95% CI 2.60-8.89) and RU that was operated (OR 4.23, 95% CI 2.35-7.60). The APD of the renal pelvis in all three ultrasounds were reliable for surgery prediction (area under the curve 0.65; 0.82; 0.71) or spontaneous resolution (area under the curve 0.80; 0.91; 0.80), only the first postnatal ultrasound has predictive value in the poor outcome (area under the curve 0.73). The higher sensitivity and specificity of the APD as predictor value was on the first postnatal ultrasound, 14.60 mm for surgery; 11.35 mm for spontaneous resolution and 15.50 mm for poor outcome. The higher APD in the renal pelvis in any of the

  17. Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

    Science.gov (United States)

    Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

    2016-10-01

    Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Psychosocial Factors Predicting First-Year College Student Success

    Science.gov (United States)

    Krumrei-Mancuso, Elizabeth J.; Newton, Fred B.; Kim, Eunhee; Wilcox, Dan

    2013-01-01

    This study made use of a model of college success that involves students achieving academic goals and life satisfaction. Hierarchical regressions examined the role of six psychosocial factors for college success among 579 first-year college students. Academic self-efficacy and organization and attention to study were predictive of first semester…

  19. The Role of Socioeconomic Factors in the Prediction of Persistence in Puerto Rico

    Science.gov (United States)

    Dika, Sandra L.

    2014-01-01

    While research literature suggests that socioeconomic factors play a role in predicting educational attainment, very little research has been done to examine these relationships using data from Puerto Rico. A logistic regression approach was adopted to investigate the extent to which family and school socioeconomic factors predict retention from…

  20. Identifying risk factors that contribute to acute mountain sickness ...

    African Journals Online (AJOL)

    This study is a questionnaire-based study conducted in London and at Everest Base Camp, in which 116 lowlanders were invited to participate and fill in a questionnaire to identify potential risk factors in their history that may have contributed to development of or protection against AMS. Results. A total of 89 lowlanders ...

  1. Predicting establishment of non-native fishes in Greece: identifying key features

    Directory of Open Access Journals (Sweden)

    Christos Gkenas

    2015-11-01

    Full Text Available Non-native fishes are known to cause economic damage to human society and are considered a major threat to biodiversity loss in freshwater ecosystems. The growing concern about these impacts has driven to an investigation of the biological traits that facilitate the establishment of non-native fish. However, invalid assessment in choosing the appropriate statistical model can lead researchers to ambiguous conclusions. Here, we present a comprehensive comparison of traditional and alternative statistical methods for predicting fish invasions using logistic regression, classification trees, multicorrespondence analysis and random forest analysis to determine characteristics of successful and failed non-native fishes in Hellenic Peninsula through establishment. We defined fifteen categorical predictor variables with biological relevance and measures of human interest. Our study showed that accuracy differed according to the model and the number of factors considered. Among all the models tested, random forest and logistic regression performed best, although all approaches predicted non-native fish establishment with moderate to excellent results. Detailed evaluation among the models corresponded with differences in variables importance, with three biological variables (parental care, distance from nearest native source and maximum size and two variables of human interest (prior invasion success and propagule pressure being important in predicting establishment. The analyzed statistical methods presented have a high predictive power and can be used as a risk assessment tool to prevent future freshwater fish invasions in this region with an imperiled fish fauna.

  2. Systematic mutagenesis of genes encoding predicted autotransported proteins of Burkholderia pseudomallei identifies factors mediating virulence in mice, net intracellular replication and a novel protein conferring serum resistance.

    Directory of Open Access Journals (Sweden)

    Natalie R Lazar Adler

    Full Text Available Burkholderia pseudomallei is the causative agent of the severe tropical disease melioidosis, which commonly presents as sepsis. The B. pseudomallei K96243 genome encodes eleven predicted autotransporters, a diverse family of secreted and outer membrane proteins often associated with virulence. In a systematic study of these autotransporters, we constructed insertion mutants in each gene predicted to encode an autotransporter and assessed them for three pathogenesis-associated phenotypes: virulence in the BALB/c intra-peritoneal mouse melioidosis model, net intracellular replication in J774.2 murine macrophage-like cells and survival in 45% (v/v normal human serum. From the complete repertoire of eleven autotransporter mutants, we identified eight mutants which exhibited an increase in median lethal dose of 1 to 2-log10 compared to the isogenic parent strain (bcaA, boaA, boaB, bpaA, bpaC, bpaE, bpaF and bimA. Four mutants, all demonstrating attenuation for virulence, exhibited reduced net intracellular replication in J774.2 macrophage-like cells (bimA, boaB, bpaC and bpaE. A single mutant (bpaC was identified that exhibited significantly reduced serum survival compared to wild-type. The bpaC mutant, which demonstrated attenuation for virulence and net intracellular replication, was sensitive to complement-mediated killing via the classical and/or lectin pathway. Serum resistance was rescued by in trans complementation. Subsequently, we expressed recombinant proteins of the passenger domain of four predicted autotransporters representing each of the phenotypic groups identified: those attenuated for virulence (BcaA, those attenuated for virulence and net intracellular replication (BpaE, the BpaC mutant with defects in virulence, net intracellular replication and serum resistance and those displaying wild-type phenotypes (BatA. Only BcaA and BpaE elicited a strong IFN-γ response in a restimulation assay using whole blood from seropositive donors

  3. High level of Brazilian men´s volleyball: characterization and difference of predictive factors of back row attack

    Directory of Open Access Journals (Sweden)

    Gustavo de Conti Teixeira Costa Conti

    2018-05-01

    Full Text Available This study aimed to identify the predictive factors of attacks, performed from positions 1 and 6 according to the effect of reception in high level Brazilian male volleyball and to find the predictive factors that differentiate the game practiced from these positions. The sample consisted in the observation of 142 games of the Brazilian Men's Super League, totalling 2969 actions of reception, setting and attack from positions 1 and 6. The significance value adopted was 5% (p ≤ 0.05. The analysis of the predictive factors of the game performed by the attacker of position 1 showed greater chances to score after an excellent (odds ratio adjusted – ORA = 1.48 and moderate effect of reception (ORA = 1.31, the second attack tempo (ORA = 1.32, the powerful attack in parallel (ORA = 1.91 and in diagonal (ORA =3.44. The attacker of position 6 showed higher chances of scoring after a high effect of reception (ORA = 3.39 and powerful attack in the parallel (ORA = 1.53. In conclusion, regardless the effect of reception, the use of the back-row attackers is recommended to increase the uncertainty on the opposing team and the chances to score.

  4. Risk factors for atherosclerosis - can they be used to identify the ...

    African Journals Online (AJOL)

    Risk factors are often used in preventive care programmes to identify the patient at particular risk for developing atherosclerosis. Risk factors for atherosclerosis have also been shown to be linked to the presence of the disease at a given time, a fact that may be helpful when screening for additional atherosclerotic disease in ...

  5. A Proteomic Approach Identifies Candidate Early Biomarkers to Predict Severe Dengue in Children.

    Directory of Open Access Journals (Sweden)

    Dang My Nhi

    2016-02-01

    Full Text Available Severe dengue with severe plasma leakage (SD-SPL is the most frequent of dengue severe form. Plasma biomarkers for early predictive diagnosis of SD-SPL are required in the primary clinics for the prevention of dengue death.Among 63 confirmed dengue pediatric patients recruited, hospital based longitudinal study detected six SD-SPL and ten dengue with warning sign (DWS. To identify the specific proteins increased or decreased in the SD-SPL plasma obtained 6-48 hours before the shock compared with the DWS, the isobaric tags for relative and absolute quantification (iTRAQ technology was performed using four patients each group. Validation was undertaken in 6 SD-SPL and 10 DWS patients.Nineteen plasma proteins exhibited significantly different relative concentrations (p<0.05, with five over-expressed and fourteen under-expressed in SD-SPL compared with DWS. The individual protein was classified to either blood coagulation, vascular regulation, cellular transport-related processes or immune response. The immunoblot quantification showed angiotensinogen and antithrombin III significantly increased in SD-SPL whole plasma of early stage compared with DWS subjects. Even using this small number of samples, antithrombin III predicted SD-SPL before shock occurrence with accuracy.Proteins identified here may serve as candidate predictive markers to diagnose SD-SPL for timely clinical management. Since the number of subjects are small, so further studies are needed to confirm all these biomarkers.

  6. Incidence and predicting factors of falls of older inpatients

    Directory of Open Access Journals (Sweden)

    Hellen Cristina de Almeida Abreu

    2015-01-01

    Full Text Available OBJECTIVE To estimate the incidence and predicting factors associated with falls among older inpatients. METHODS Prospective cohort study conducted in clinical units of three hospitals in Cuiaba, MT, Midwestern Brazil, from March to August 2013. In this study, 221 inpatients aged 60 or over were followed until hospital discharge, death, or fall. The method of incidence density was used to calculate incidence rates. Bivariate analysis was performed by Chi-square test, and multiple analysis was performed by Cox regression. RESULTS The incidence of falls was 12.6 per 1,000 patients/day. Predicting factors for falls during hospitalization were: low educational level (RR = 2.48; 95%CI 1.17;5.25, polypharmacy (RR = 4.42; 95%CI 1.77;11.05, visual impairment (RR = 2.06; 95%CI 1.01;4.23, gait and balance impairment (RR = 2.95; 95%CI 1.22;7.14, urinary incontinence (RR = 5.67; 95%CI 2.58;12.44 and use of laxatives (RR = 4.21; 95%CI 1.15;15.39 and antipsychotics (RR = 4.10; 95%CI 1.38;12.13. CONCLUSIONS The incidence of falls of older inpatients is high. Predicting factors found for falls were low education level, polypharmacy, visual impairment, gait and balance impairment, urinary incontinence and use of laxatives and antipsychotics. Measures to prevent falls in hospitals are needed to reduce the incidence of this event.

  7. Father involvement: Identifying and predicting family members' shared and unique perceptions.

    Science.gov (United States)

    Dyer, W Justin; Day, Randal D; Harper, James M

    2014-08-01

    Father involvement research has typically not recognized that reports of involvement contain at least two components: 1 reflecting a view of father involvement that is broadly recognized in the family, and another reflecting each reporter's unique perceptions. Using a longitudinal sample of 302 families, this study provides a first examination of shared and unique views of father involvement (engagement and warmth) from the perspectives of fathers, children, and mothers. This study also identifies influences on these shared and unique perspectives. Father involvement reports were obtained when the child was 12 and 14 years old. Mother reports overlapped more with the shared view than father or child reports. This suggests the mother's view may be more in line with broadly recognized father involvement. Regarding antecedents, for fathers' unique view, a compensatory model partially explains results; that is, negative aspects of family life were positively associated with fathers' unique view. Children's unique view of engagement may partially reflect a sentiment override with father antisocial behaviors being predictive. Mothers' unique view of engagement was predicted by father and mother work hours and her unique view of warmth was predicted by depression and maternal gatekeeping. Taken, together finding suggests a far more nuanced view of father involvement should be considered.

  8. Can Predictive Modeling Identify Head and Neck Oncology Patients at Risk for Readmission?

    Science.gov (United States)

    Manning, Amy M; Casper, Keith A; Peter, Kay St; Wilson, Keith M; Mark, Jonathan R; Collar, Ryan M

    2018-05-01

    Objective Unplanned readmission within 30 days is a contributor to health care costs in the United States. The use of predictive modeling during hospitalization to identify patients at risk for readmission offers a novel approach to quality improvement and cost reduction. Study Design Two-phase study including retrospective analysis of prospectively collected data followed by prospective longitudinal study. Setting Tertiary academic medical center. Subjects and Methods Prospectively collected data for patients undergoing surgical treatment for head and neck cancer from January 2013 to January 2015 were used to build predictive models for readmission within 30 days of discharge using logistic regression, classification and regression tree (CART) analysis, and random forests. One model (logistic regression) was then placed prospectively into the discharge workflow from March 2016 to May 2016 to determine the model's ability to predict which patients would be readmitted within 30 days. Results In total, 174 admissions had descriptive data. Thirty-two were excluded due to incomplete data. Logistic regression, CART, and random forest predictive models were constructed using the remaining 142 admissions. When applied to 106 consecutive prospective head and neck oncology patients at the time of discharge, the logistic regression model predicted readmissions with a specificity of 94%, a sensitivity of 47%, a negative predictive value of 90%, and a positive predictive value of 62% (odds ratio, 14.9; 95% confidence interval, 4.02-55.45). Conclusion Prospectively collected head and neck cancer databases can be used to develop predictive models that can accurately predict which patients will be readmitted. This offers valuable support for quality improvement initiatives and readmission-related cost reduction in head and neck cancer care.

  9. Psychosocial factors predicting risky sexual behaviour among long ...

    African Journals Online (AJOL)

    Social factors that included age, number of years of education, number of wives, number of intercourses in the last three months, number of partners apart from primary partners, and number of weeks spent outside home significantly jointly predicted sexual risk behaviour (R2 = .15, F(6, 147) = 4.39; p < .05) by accounting for ...

  10. Factors predictive of abnormal semen parameters in male partners ...

    African Journals Online (AJOL)

    analysis was used to determine the predictive factors associated with abnormal semen parameters. .... for frequency, mean and χ2 with the level of significance set at p<0.05. ... was obtained from each couple participating in the study, following.

  11. Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph.

    Directory of Open Access Journals (Sweden)

    Shuai Zhao

    Full Text Available In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.

  12. Staging of early lymph node metastases with the sentinel lymph node technique and predictive factors in T1/T2 oral cavity cancer

    DEFF Research Database (Denmark)

    Pedersen, Nicklas Juel; Jensen, David Hebbelstrup; Hedbäck, Nora

    2015-01-01

    BACKGROUND: The purpose of this study was to examine the diagnostic accuracy of detecting lymph node metastases and to identify predictive and prognostic clinicopathological factors in patients with oral squamous cell carcinoma (OSCC) undergoing sentinel lymph node biopsy (SLNB). METHODS: All...

  13. Use of model plant hosts to identify Pseudomonas aeruginosa virulence factors

    Science.gov (United States)

    Rahme, Laurence G.; Tan, Man-Wah; Le, Long; Wong, Sandy M.; Tompkins, Ronald G.; Calderwood, Stephen B.; Ausubel, Frederick M.

    1997-01-01

    We used plants as an in vivo pathogenesis model for the identification of virulence factors of the human opportunistic pathogen Pseudomonas aeruginosa. Nine of nine TnphoA mutant derivatives of P. aeruginosa strain UCBPP-PA14 that were identified in a plant leaf assay for less pathogenic mutants also exhibited significantly reduced pathogenicity in a burned mouse pathogenicity model, suggesting that P. aeruginosa utilizes common strategies to infect both hosts. Seven of these nine mutants contain TnphoA insertions in previously unknown genes. These results demonstrate that an alternative nonvertebrate host of a human bacterial pathogen can be used in an in vivo high throughput screen to identify novel bacterial virulence factors involved in mammalian pathogenesis. PMID:9371831

  14. Gender identity outcomes in children with disorders/differences of sex development: Predictive factors.

    Science.gov (United States)

    Bakula, Dana M; Mullins, Alexandria J; Sharkey, Christina M; Wolfe-Christensen, Cortney; Mullins, Larry L; Wisniewski, Amy B

    2017-06-01

    Disorders/differences of sex development (DSD) comprise multiple congenital conditions in which chromosomal, gonadal, and/or anatomical sex are discordant. The prediction of future gender identity (i.e., self-identifying as male, female, or other) in children with DSD can be imprecise, and current knowledge about the development of gender identity in people with, and without DSD, is limited. However, sex of rearing is the strongest predictor of gender identity for the majority of individuals with various DSD conditions. When making decisions regarding sex of rearing biological factors (e.g., possession of a Y chromosome, degree and duration of pre- and postnatal androgen exposure, phenotypic presentation of the external genitalia, and fertility potential), social and cultural factors, as well as quality of life should be considered. Information on gender identity outcomes across a range of DSD diagnoses is presented to aid in sex of rearing assignment. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Utility of antenatal clinical factors for prediction of postpartum outcomes in women with gestational diabetes mellitus (GDM).

    Science.gov (United States)

    Ingram, Emily R; Robertson, Iain K; Ogden, Kathryn J; Dennis, Amanda E; Campbell, Joanne E; Corbould, Anne M

    2017-06-01

    Gestational diabetes mellitus (GDM) is associated with life-long increased risk of type 2 diabetes: affected women are advised to undergo oral glucose tolerance testing (OGTT) at 6-12 weeks postpartum, then glucose screening every 1-3 years. We investigated whether in women with GDM, antenatal clinical factors predicted postpartum abnormal glucose tolerance and compliance with screening. In women with GDM delivering 2007 to mid-2009 in a single hospital, antenatal/obstetric data and glucose tests at 6-12 weeks postpartum and during 5.5 years post-pregnancy were retrospectively collected. Predictors of return for testing and abnormal glucose tolerance were identified using multivariate analysis. Of 165 women, 117 (70.9%) returned for 6-12 week postpartum OGTT: 23 (19.6%) were abnormal. Smoking and parity, independent of socioeconomic status, were associated with non-return for testing. Fasting glucose ≥5.4 mmol/L on pregnancy OGTT predicted both non-return for testing and abnormal OGTT. During 5.5 years post-pregnancy, 148 (89.7%) women accessed glucose screening: nine (6.1%) developed diabetes, 33 (22.3%) had impaired fasting glucose / impaired glucose tolerance. Predictors of abnormal glucose tolerance were fasting glucose ≥5.4 mmol/L and 2-h glucose ≥9.3 mmol/L on pregnancy OGTT (~2.5-fold increased risk), and polycystic ovary syndrome (~3.4 fold increased risk). Risk score calculation, based on combined antenatal factors, did not improve predictions. Antenatal clinical factors were modestly predictive of return for testing and abnormal glucose tolerance post-pregnancy in women with GDM. Risk score calculations were ineffective in predicting outcomes: risk scores developed in other populations require validation. Ongoing glucose screening is indicated for all women with GDM. © 2016 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

  16. Factors Predicting Difficulty of Laparoscopic Low Anterior Resection for Rectal Cancer with Total Mesorectal Excision and Double Stapling Technique.

    Directory of Open Access Journals (Sweden)

    Weiping Chen

    Full Text Available Laparoscopic sphincter-preserving low anterior resection for rectal cancer is a surgery demanding great skill. Immense efforts have been devoted to identifying factors that can predict operative difficulty, but the results are inconsistent.Our study was conducted to screen patients' factors to build models for predicting the operative difficulty using well controlled data.We retrospectively reviewed records of 199 consecutive patients who had rectal cancers 5-8 cm from the anal verge. All underwent laparoscopic sphincter-preserving low anterior resections with total mesorectal excision (TME and double stapling technique (DST. Data of 155 patients from one surgeon were utilized to build models to predict standardized endpoints (operative time, blood loss and postoperative morbidity. Data of 44 patients from other surgeons were used to test the predictability of the built models.Our results showed prior abdominal surgery, preoperative chemoradiotherapy, tumor distance to anal verge, interspinous distance, and BMI were predictors for the standardized operative times. Gender and tumor maximum diameter were related to the standardized blood loss. Temporary diversion and tumor diameter were predictors for postoperative morbidity. The model constructed for the operative time demonstrated excellent predictability for patients from different surgeons.With a well-controlled patient population, we have built a predictable model to estimate operative difficulty. The standardized operative time will make it possible to significantly increase sample size and build more reliable models to predict operative difficulty for clinical use.

  17. CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

    Science.gov (United States)

    Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

    2018-03-01

    In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and

  18. Factors predictive of successful learning in postgraduate medical education

    NARCIS (Netherlands)

    Smits, P. B. A.; Verbeek, J. H. A. M.; Nauta, M. C. E.; ten Cate, Th J.; Metz, J. C. M.; van Dijk, F. J. H.

    2004-01-01

    PURPOSE To establish which personal and contextual factors are predictive of successful outcomes in postgraduate medical education. METHOD We performed a follow-up study of 118 doctors on a postgraduate occupational health training programme on the management of mental health problems. The following

  19. Marital Intimacy and Predictive Factors Among Infertile Women in Northern Iran.

    Science.gov (United States)

    Pasha, Hajar; Basirat, Zahra; Esmailzadeh, Sedigheh; Faramarzi, Mahbobeh; Adibrad, Hajar

    2017-05-01

    Infertility is a stressful state that may decrease attachment between spouses. Marital intimacy is a real need in infertile women. The aim of this study was to evaluate marital intimacy and predictive factors among infertile women in Northern Iran. This cross-sectional study was conducted at Fatemeh Zahra Infertility and Reproductive Health Center of Babol Medical Sciences University in 2014. A total of 221 infertile women participated in this study. The instrument used in this research was Marital Intimacy Need Questionnaire (MINQ). Statistical analyses was performed using linear and logistic regression with pintimacy. The mean and standard deviation of the marital intimacy was 349.11±49.26 and in marital intimacy domains including: emotional (42.28±7.23), psychological (41.84±7.59), intellectual (42.56±7.46), sexual (42.90±7.41), physical (43.59±6.96), spiritual (51.61±8.06), aesthetic (42.66±6.75), and social intimacy (42.59±6.89). The highest mean of marital intimacy domains is related to spirituality in infertile women. Physical and sexual domains had the high mean in infertile women. The lowest mean in marital intimacy domains was psychological intimacy. There was a significant correlation between the domains of marital intimacy. The strongest correlation was between the physical and sexual intimacy (r=0.85). There was a significant inverse association in marital intimacy with the age difference of spouses (pintimacy with husband's occupation, and cause of infertility (p<0.02). Early screening and psychosocial intervention strategies suggest in the setting of female infertility to identify and prevent the predictive factors that may cause marital conflict.

  20. PREDICTION OF SURGICAL TREATMENT WITH POUR PERITONITIS QUANTIFYING RISK FACTORS

    Directory of Open Access Journals (Sweden)

    І. К. Churpiy

    2012-11-01

    Full Text Available Explored the possibility of quantitative assessment of risk factors of complications in the treatment of diffuse peritonitis. Highlighted 53 groups of features that are important in predicting the course of diffuse peritonitis. The proposed scheme of defining the risk of clinical course of diffuse peritonitis can quantify the severity of the source of patients and in most cases correctly predict the results of treatment of disease.

  1. Predicting Resident Performance from Preresidency Factors: A Systematic Review and Applicability to Neurosurgical Training.

    Science.gov (United States)

    Zuckerman, Scott L; Kelly, Patrick D; Dewan, Michael C; Morone, Peter J; Yengo-Kahn, Aaron M; Magarik, Jordan A; Baticulon, Ronnie E; Zusman, Edie E; Solomon, Gary S; Wellons, John C

    2018-02-01

    Neurosurgical educators strive to identify the best applicants, yet formal study of resident selection has proved difficult. We conducted a systematic review to answer the following question: What objective and subjective preresidency factors predict resident success? PubMed, ProQuest, Embase, and the CINAHL databases were queried from 1952 to 2015 for literature reporting the impact of preresidency factors (PRFs) on outcomes of residency success (RS), among neurosurgery and all surgical subspecialties. Due to heterogeneity of specialties and outcomes, a qualitative summary and heat map of significant findings were constructed. From 1489 studies, 21 articles met inclusion criteria, which evaluated 1276 resident applicants across five surgical subspecialties. No neurosurgical studies met the inclusion criteria. Common objective PRFs included standardized testing (76%), medical school performance (48%), and Alpha Omega Alpha (43%). Common subjective PRFs included aggregate rank scores (57%), letters of recommendation (38%), research (33%), interviews (19%), and athletic or musical talent (19%). Outcomes of RS included faculty evaluations, in-training/board exams, chief resident status, and research productivity. Among objective factors, standardized test scores correlated well with in-training/board examinations but poorly correlated with faculty evaluations. Among subjective factors, aggregate rank scores, letters of recommendation, and athletic or musical talent demonstrated moderate correlation with faculty evaluations. Standardized testing most strongly correlated with future examination performance but correlated poorly with faculty evaluations. Moderate predictors of faculty evaluations were aggregate rank scores, letters of recommendation, and athletic or musical talent. The ability to predict success of neurosurgical residents using an evidence-based approach is limited, and few factors have correlated with future resident performance. Given the importance of

  2. Identifying black swans in NextGen: predicting human performance in off-nominal conditions.

    Science.gov (United States)

    Wickens, Christopher D; Hooey, Becky L; Gore, Brian F; Sebok, Angelia; Koenicke, Corey S

    2009-10-01

    The objective is to validate a computational model of visual attention against empirical data--derived from a meta-analysis--of pilots' failure to notice safety-critical unexpected events. Many aircraft accidents have resulted, in part, because of failure to notice nonsalient unexpected events outside of foveal vision, illustrating the phenomenon of change blindness. A model of visual noticing, N-SEEV (noticing-salience, expectancy, effort, and value), was developed to predict these failures. First, 25 studies that reported objective data on miss rate for unexpected events in high-fidelity cockpit simulations were identified, and their miss rate data pooled across five variables (phase of flight, event expectancy, event location, presence of a head-up display, and presence of a highway-in-the-sky display). Second, the parameters of the N-SEEV model were tailored to mimic these dichotomies. The N-SEEV model output predicted variance in the obtained miss rate (r = .73). The individual miss rates of all six dichotomous conditions were predicted within 14%, and four of these were predicted within 7%. The N-SEEV model, developed on the basis of an independent data set, was able to successfully predict variance in this safety-critical measure of pilot response to abnormal circumstances, as collected from the literature. As new technology and procedures are envisioned for the future airspace, it is important to predict if these may compromise safety in terms of pilots' failing to notice unexpected events. Computational models such as N-SEEV support cost-effective means of making such predictions.

  3. The Analysis of Predictive Factors for the Identification of Patients Who Could Benefit from Respiratory-Gated Radiotherapy in Non-Small Cell Lung Cancer

    International Nuclear Information System (INIS)

    Jang, Seong Soon; Park, Ji Chan

    2009-01-01

    4DCT scans performed for radiotherapy were retrospectively analyzed to assess the possible benefits of respiratory gating in non-small cell lung cancer (NSCLC) and established the predictive factors for identifying patients who could benefit from this approach. Three treatment planning was performed for 15 patients with stage I∼III NSCLC using different planning target volumes (PTVs) as follows: 1) PTVroutine, derived from the addition of conventional uniform margins to gross tumor volume (GTV) of a single bin, 2) PTVall phases (patient-specific PTV), derived from the composite GTV of all 6 bins of the 4DCT, and 3) PTVgating, derived from the composite GTV of 3 consecutive bins at end-exhalation. The reductions in PTV were 43.2% and 9.5%, respectively, for the PTVall phases vs. PTVroutine and PTVgating vs. PTVall phases. Compared to PTVroutine, the use of PTVall phases and PTVgating reduced the mean lung dose (MLD) by 18.1% and 21.6%, and V20 by 18.2% and 22.0%, respectively. Significant correlations were seen between certain predictive factors selected from the tumor mobility and volume analysis, such as the 3D mobility vector, the reduction in 3D mobility and PTV with gating, and the ratio of GTV overlap between 2 extreme bins and additional reductions in both MLD and V20 with gating. The additional benefits with gating compared to the use of patient-specific PTV were modest; however, there were distinct correlations and differences according to the predictive factors. Therefore, these predictive factors might be useful for identifying patients who could benefit from respiratory-gated radiotherapy

  4. Using an artificial neural network to predict carbon dioxide compressibility factor at high pressure and temperature

    Energy Technology Data Exchange (ETDEWEB)

    Mohagheghian, Erfan [Memorial University of Newfoundland, St. John' s (Canada); Zafarian-Rigaki, Habiballah; Motamedi-Ghahfarrokhi, Yaser; Hemmati-Sarapardeh, Abdolhossein [Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

    2015-10-15

    Carbon dioxide injection, which is widely used as an enhanced oil recovery (EOR) method, has the potential of being coupled with CO{sub 2} sequestration and reducing the emission of greenhouse gas. Hence, knowing the compressibility factor of carbon dioxide is of a vital significance. Compressibility factor (Z-factor) is traditionally measured through time consuming, expensive and cumbersome experiments. Hence, developing a fast, robust and accurate model for its estimation is necessary. In this study, a new reliable model on the basis of feed forward artificial neural networks is presented to predict CO{sub 2} compressibility factor. Reduced temperature and pressure were selected as the input parameters of the proposed model. To evaluate and compare the results of the developed model with pre-existing models, both statistical and graphical error analyses were employed. The results indicated that the proposed model is more reliable and accurate compared to pre-existing models in a wide range of temperature (up to 1,273.15 K) and pressure (up to 140MPa). Furthermore, by employing the relevancy factor, the effect of pressure and temprature on the Z-factor of CO{sub 2} was compared for below and above the critical pressure of CO{sub 2}, and the physcially expected trends were observed. Finally, to identify the probable outliers and applicability domain of the proposed ANN model, both numerical and graphical techniques based on Leverage approach were performed. The results illustrated that only 1.75% of the experimental data points were located out of the applicability domain of the proposed model. As a result, the developed model is reliable for the prediction of CO{sub 2} compressibility factor.

  5. Clinical significance and predictive factors of early massive recurrence after radiofrequency ablation in patients with a single small hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Ju-Yeon Cho

    2016-12-01

    Full Text Available Background/Aims Radiofrequency ablation (RFA is one of the most frequently applied curative treatments in patients with a single small hepatocellular carcinoma (HCC. However, the clinical significance of and risk factors for early massive recurrence after RFA—a dreadful event limiting further curative treatment—have not been fully evaluated. Methods In total, 438 patients with a single HCC of size ≤3 cm who underwent percutaneous RFA as an initial treatment between 2006 and 2009 were included. Baseline patient characteristics, overall survival, predictive factors, and recurrence after RFA were evaluated. In addition, the incidence, impact on survival, and predictive factors of early massive recurrence, and initial recurrence beyond the Milan criteria within 2 years were also investigated. Results During the median follow-up of 68.4 months, recurrent HCC was confirmed in 302 (68.9% patients, with early massive recurrence in 27 patients (6.2%. The 1-, 3-, and 5-year overall survival rates were 95.4%, 84.7%, and 81.8%, respectively, in patients with no recurrence, 99.6%, 86.4%, and 70.1% in patients with recurrence within the Milan criteria or late recurrence, and 92.6%, 46.5%, and 0.05% in patients with early massive recurrence. Multivariable analysis identified older age, Child-Pugh score B or C, and early massive recurrence as predictive of poor overall survival. A tumor size of ≥2 cm and tumor location adjacent to the colon were independent risk factors predictive of early massive recurrence. Conclusions Early massive recurrence is independently predictive of poor overall survival after RFA in patients with a single small HCC. Tumors sized ≥2 cm and located adjacent to the colon appear to be independent risk factors for early massive recurrence.

  6. Frequency and predictive factors for overlap syndrome between autoimmune hepatitis and primary cholestatic liver disease.

    Science.gov (United States)

    Gheorghe, Liana; Iacob, Speranta; Gheorghe, Cristian; Iacob, Razvan; Simionov, Iulia; Vadan, Roxana; Becheanu, Gabriel; Parvulescu, Iuliana; Toader, Cristina

    2004-06-01

    To evaluate the frequency of cholestatic pattern in patients with autoimmune hepatitis (AIH) and to identify predictive factors associated with the development of the overlap syndrome. Eighty-two consecutive patients diagnosed with AIH at the referral centre between January 1998 and June 2002 were included in the study. The new scoring system modified by the International Autoimmune Hepatitis Group was used to classify patients as definite/probable. Overlap syndrome was considered when the patient had clinical, serological and histological characteristics of two conditions: AIH and primary biliary cirrhosis (PBC) or AIH and primary sclerosing cholangitis (PSC). From the 82 AIH patients (76 female and six male), 84.1% presented definite AIH (> 15 points) and 15.9% probable AIH (10 - 15 points). The frequency of the overlap syndrome was 20%: 13% with PBC and 7% with PSC. In the univariate analysis the overlap syndrome was associated with male gender (P = 0.01), age < 35 years (P < 0.0001), histopathological aspect of cholestasis (P < 0.0001), suboptimal response to treatment (P < 0.0001) and probable AIH (P < 0.0001). Age < 35 years, probable AIH and the absence of anti-nuclear antibody (ANA) have been identified as independent indicators of the overlap diagnosis by the logistic regression analysis. Patients with overlap syndrome between AIH and primary cholestatic liver disease are frequently diagnosed in clinical practice, representing 20% of AIH cases in our study. The independent predictive factors associated with the diagnosis of overlap syndrome are young age, ANA(-) profile, and probable diagnosis according with the scoring system for AIH.

  7. Sensitized mutagenesis screen in Factor V Leiden mice identifies thrombosis suppressor loci.

    Science.gov (United States)

    Westrick, Randal J; Tomberg, Kärt; Siebert, Amy E; Zhu, Guojing; Winn, Mary E; Dobies, Sarah L; Manning, Sara L; Brake, Marisa A; Cleuren, Audrey C; Hobbs, Linzi M; Mishack, Lena M; Johnston, Alexander J; Kotnik, Emilee; Siemieniak, David R; Xu, Jishu; Li, Jun Z; Saunders, Thomas L; Ginsburg, David

    2017-09-05

    Factor V Leiden ( F5 L ) is a common genetic risk factor for venous thromboembolism in humans. We conducted a sensitized N -ethyl- N -nitrosourea (ENU) mutagenesis screen for dominant thrombosuppressor genes based on perinatal lethal thrombosis in mice homozygous for F5 L ( F5 L/L ) and haploinsufficient for tissue factor pathway inhibitor ( Tfpi +/- ). F8 deficiency enhanced the survival of F5 L/L Tfpi +/- mice, demonstrating that F5 L/L Tfpi +/- lethality is genetically suppressible. ENU-mutagenized F5 L/L males and F5 L/+ Tfpi +/- females were crossed to generate 6,729 progeny, with 98 F5 L/L Tfpi +/- offspring surviving until weaning. Sixteen lines, referred to as "modifier of Factor 5 Leiden ( MF5L1-16 )," exhibited transmission of a putative thrombosuppressor to subsequent generations. Linkage analysis in MF5L6 identified a chromosome 3 locus containing the tissue factor gene ( F3 ). Although no ENU-induced F3 mutation was identified, haploinsufficiency for F3 ( F3 +/- ) suppressed F5 L/L Tfpi +/- lethality. Whole-exome sequencing in MF5L12 identified an Actr2 gene point mutation (p.R258G) as the sole candidate. Inheritance of this variant is associated with suppression of F5 L/L Tfpi +/- lethality ( P = 1.7 × 10 -6 ), suggesting that Actr2 p.R258G is thrombosuppressive. CRISPR/Cas9 experiments to generate an independent Actr2 knockin/knockout demonstrated that Actr2 haploinsufficiency is lethal, supporting a hypomorphic or gain-of-function mechanism of action for Actr2 p.R258G Our findings identify F8 and the Tfpi/F3 axis as key regulators in determining thrombosis balance in the setting of F5 L and also suggest a role for Actr2 in this process.

  8. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

    Science.gov (United States)

    Tsai, Zing Tsung-Yeh; Shiu, Shin-Han; Tsai, Huai-Kuang

    2015-08-01

    Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy) that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

  9. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

    Directory of Open Access Journals (Sweden)

    Zing Tsung-Yeh Tsai

    2015-08-01

    Full Text Available Transcription factor (TF binding is determined by the presence of specific sequence motifs (SM and chromatin accessibility, where the latter is influenced by both chromatin state (CS and DNA structure (DS properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

  10. Identifying the customer satisfaction factors in furniture market

    Directory of Open Access Journals (Sweden)

    Majid Azizi

    2017-05-01

    Full Text Available Purpose – the purpose of this research is to identify the influential factors on customer satisfaction in the Iranian furniture market in order to get acquainted with the fundamental items for planning future sales programs with the purposes of extolling competitive advantages. Design/methodology/approach – A commixture of 6 items and 31 factors were educed from interviewing with 20 experts in furniture designing and manufacturing industry. The collected data from customer need indexes in previous research were also used. Findings – results showed that such factors as economic factors weighting 0.32, product specifications weighting 0.21 and credibility weighting 0.19 were the most important indexes and price weighting 0.195, fame weighting 0.131, quality, durability and resistance weighting 0.116, paying conditions weighting 0.095, designing and decorating in virtual softwares before ordering weighting 0.074, updatedness weighting 0.064 and interaction approach with the weight of 0.42 were the most considerable influential sub-indexes on the satisfaction of the Iranian furniture market customers. Research limitations/implications – by the enhancement of competition throughout the world markets and the inevitable presence of Iran in it, the market activists’ concentration should shift towards paying comprehensive attention to desires and needs of furniture market customers. Practical implications – some important issues on planning suitable manufacturing and marketing programs in furniture market are introduce so that the activists be aware of considering the growing knowledge and awareness of end-users which increases the pressure on the manufacturer side. There are also some solutions in terms of internal and external organizational factors with regard to the complex nature of competitive environment in furniture market. Originality/value – the paper provides an examination of effective factors on customer satisfaction with a

  11. Identifying important motivational factors for professionals in Greek hospitals

    Science.gov (United States)

    Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

    2009-01-01

    Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

  12. Predicting the cosmological constant with the scale-factor cutoff measure

    International Nuclear Information System (INIS)

    De Simone, Andrea; Guth, Alan H.; Salem, Michael P.; Vilenkin, Alexander

    2008-01-01

    It is well known that anthropic selection from a landscape with a flat prior distribution of cosmological constant Λ gives a reasonable fit to observation. However, a realistic model of the multiverse has a physical volume that diverges with time, and the predicted distribution of Λ depends on how the spacetime volume is regulated. A very promising method of regulation uses a scale-factor cutoff, which avoids a number of serious problems that arise in other approaches. In particular, the scale-factor cutoff avoids the 'youngness problem' (high probability of living in a much younger universe) and the 'Q and G catastrophes' (high probability for the primordial density contrast Q and gravitational constant G to have extremely large or small values). We apply the scale-factor cutoff measure to the probability distribution of Λ, considering both positive and negative values. The results are in good agreement with observation. In particular, the scale-factor cutoff strongly suppresses the probability for values of Λ that are more than about 10 times the observed value. We also discuss qualitatively the prediction for the density parameter Ω, indicating that with this measure there is a possibility of detectable negative curvature.

  13. The Promise of Virtual Teams: Identifying Key Factors in Effectiveness and Failure

    Science.gov (United States)

    Horwitz, Frank M.; Bravington, Desmond; Silvis, Ulrik

    2006-01-01

    Purpose: The aim of the investigation is to identify enabling and disenabling factors in the development and operation of virtual teams; to evaluate the importance of factors such as team development, cross-cultural variables, leadership, communication and social cohesion as contributors to virtual team effectiveness. Design/methodology/approach:…

  14. Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

    Science.gov (United States)

    Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

    2018-01-12

    Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

  15. A nomogram for predicting pathological complete response in patients with human epidermal growth factor receptor 2 negative breast cancer

    International Nuclear Information System (INIS)

    Jin, Xi; Jiang, Yi-Zhou; Chen, Sheng; Yu, Ke-Da; Ma, Ding; Sun, Wei; Shao, Zhi-Min; Di, Gen-Hong

    2016-01-01

    The response to neoadjuvant chemotherapy has been proven to predict long-term clinical benefits for patients. Our research is to construct a nomogram to predict pathological complete response of human epidermal growth factor receptor 2 negative breast cancer patients. We enrolled 815 patients who received neoadjuvant chemotherapy from 2003 to 2015 and divided them into a training set and a validation set. Univariate logistic regression was performed to screen for predictors and construct the nomogram; multivariate logistic regression was performed to identify independent predictors. After performing the univariate logistic regression analysis in the training set, tumor size, hormone receptor status, regimens of neoadjuvant chemotherapy and cycles of neoadjuvant chemotherapy were the final predictors for the construction of the nomogram. The multivariate logistic regression analysis demonstrated that T4 status, hormone receptor status and receiving regimen of paclitaxel and carboplatin were independent predictors of pathological complete response. The area under the receiver operating characteristic curve of the training set and the validation set was 0.779 and 0.701, respectively. We constructed and validated a nomogram to predict pathological complete response in human epidermal growth factor receptor 2 negative breast cancer patients. We also identified tumor size, hormone receptor status and paclitaxel and carboplatin regimen as independent predictors of pathological complete response. The online version of this article (doi:10.1186/s12885-016-2652-z) contains supplementary material, which is available to authorized users

  16. Cognitive factors predicting intentions to search for health information: an application of the theory of planned behaviour.

    Science.gov (United States)

    Austvoll-Dahlgren, Astrid; Falk, Ragnhild S; Helseth, Sølvi

    2012-12-01

    Peoples' ability to obtain health information is a precondition for their effective participation in decision making about health. However, there is limited evidence describing which cognitive factors can predict the intention of people to search for health information. To test the utility of a questionnaire in predicting intentions to search for health information, and to identify important predictors associated with this intention such that these could be targeted in an Intervention. A questionnaire was developed based on the Theory of Planned Behaviour and tested on both a mixed population sample (n=30) and a sample of parents (n = 45). The questionnaire was explored by testing for internal consistency, calculating inter-correlations between theoretically-related constructs, and by using multiple regression analysis. The reliability and validity of the questionnaire were found to be satisfactory and consistent across the two samples. The questionnaires' direct measures prediction of intention was high and accounted for 47% and 55% of the variance in behavioural intentions. Attitudes and perceived behavioural control were identified as important predictors to intention for search for health information. The questionnaire may be a useful tool for understanding and evaluating behavioural intentions and beliefs related to searches for health information. © 2012 The authors. Health Information and Libraries Journal © 2012 Health Libraries Group.

  17. BENCHMARKING - PRACTICAL TOOLS IDENTIFY KEY SUCCESS FACTORS

    Directory of Open Access Journals (Sweden)

    Olga Ju. Malinina

    2016-01-01

    Full Text Available The article gives a practical example of the application of benchmarking techniques. The object of study selected fashion store Company «HLB & M Hennes & Mauritz», located in the shopping center «Gallery», Krasnodar. Hennes & Mauritz. The purpose of this article is to identify the best ways to develop a fashionable brand clothing store Hennes & Mauritz on the basis of benchmarking techniques. On the basis of conducted market research is a comparative analysis of the data from different perspectives. The result of the author’s study is a generalization of the ndings, the development of the key success factors that will allow to plan a successful trading activities in the future, based on the best experience of competitors.

  18. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  19. Identifying and Predicting Profiles of Medical Noncompliance: Pediatric Caregivers' Antibiotic Stewardship.

    Science.gov (United States)

    Smith, Rachel A; Kim, Youllee; M'Ikanatha, Nkuchia M

    2018-05-14

    Sometimes compliance with medical recommendations is problematic. We investigated pediatric caregivers' (N = 606) patterns of noncompliance with antibiotic stewardship based on the obstacle hypothesis. We tested predictors of noncompliance framed by the obstacle hypothesis, dissonance theory, and psychological reactance. The results revealed four profiles of caregivers' stewardship: one marked by compliance (Stewards) and three marked by types of noncompliance (Stockers, Persuaders, and Dissenters). The covariate analysis showed that, although psychological reactance predicted being noncompliant, it was types of obstacles and discrepant experiences that predicted caregivers' patterns of noncompliance with antibiotic stewardship. Campaign planning often focuses on identifying the belief most associated with the targeted outcome, such as compliance. Noncompliance research, however, points out that persuaders may be successful to the extent to which they anticipate obstacles to compliance and address them in their influence attempts. A shift from medical noncompliance to patient engagement also affords an opportunity to consider how some recommendations create obstacles for others and to find positive ways to embrace conflicting needs, tensions, and reasons for refusal in order to promote collective goals.

  20. Identifying key hospital service quality factors in online health communities.

    Science.gov (United States)

    Jung, Yuchul; Hur, Cinyoung; Jung, Dain; Kim, Minki

    2015-04-07

    The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. We defined social media-based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea's two biggest online portals were used to test the effectiveness of detection of social media-based key quality factors for hospitals. To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and

  1. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing.

    Science.gov (United States)

    Ko, Minsam; Yeo, Jaeryong; Lee, Juyeong; Lee, Uichin; Jang, Young Jae

    2016-01-01

    Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers' online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans' interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users.

  2. Systematic review of prognostic factors predicting outcome in non-surgically treated patients with sciatica.

    Science.gov (United States)

    Verwoerd, A J H; Luijsterburg, P A J; Lin, C W C; Jacobs, W C H; Koes, B W; Verhagen, A P

    2013-09-01

    Identification of prognostic factors for surgery in patients with sciatica is important to be able to predict surgery in an early stage. Identification of prognostic factors predicting persistent pain, disability and recovery are important for better understanding of the clinical course, to inform patient and physician and support decision making. Consequently, we aimed to systematically review prognostic factors predicting outcome in non-surgically treated patients with sciatica. A search of Medline, Embase, Web of Science and Cinahl, up to March 2012 was performed for prospective cohort studies on prognostic factors for non-surgically treated sciatica. Two reviewers independently selected studies for inclusion and assessed the risk of bias. Outcomes were pain, disability, recovery and surgery. A best evidence synthesis was carried out in order to assess and summarize the data. The initial search yielded 4392 articles of which 23 articles reporting on 14 original cohorts met the inclusion criteria. High clinical, methodological and statistical heterogeneity among studies was found. Reported evidence regarding prognostic factors predicting the outcome in sciatica is limited. The majority of factors that have been evaluated, e.g., age, body mass index, smoking and sensory disturbance, showed no association with outcome. The only positive association with strong evidence was found for leg pain intensity at baseline as prognostic factor for subsequent surgery. © 2013 European Federation of International Association for the Study of Pain Chapters.

  3. Determining and predictive factors for the tumor radiosensitivity

    International Nuclear Information System (INIS)

    Hennequin, Ch.; Quero, L.; Hennequin, Ch.; Quero, L.; Favaudon, V.

    2008-01-01

    Many predictive factors of tumor radiosensitivity have been described. Number of clonogenic cells, proliferation rate, hypoxia and intrinsic radiosensitivity are usually considered as the main parameters of tumor control. Intrinsic radiosensitivity is correlated in a first approach to the ability of the cell to detect and repair DNA damages, and so integrity of the different pathways involved in this function: P.A.R.P.-1, X.R.C.C.1, A.T.M., p 53, M.R.N. complex or B.R.C.A.1. Genetic polymorphisms of some of these genes, found in normal lymphocytes, have been correlated to late toxicity of normal tissues. But, in tumors, because of the difficulty to obtain samplings and heterogeneity, accurate molecular analysis is not possible in many cases, and no valuable test of radiosensitivity exist at this moment. For example, T.P. 53 gene has been evaluated in many studies and results regarding its potential as a predictive factor of tumor sensitivity are conflicting. Surviving fraction at 2 Gy (S.F.2) allowed a global evaluation of sensitivity, but the obtention of this parameter often takes a long time and failed in 20 to 40%. Evaluation of double-strand break repair capacity by immuno chemistry quantification of phosphorylated forms of A.T.M., H.2 A.X. or M.R.E.11 is an interesting topic. However, discovery of tumor stem cells in a number of epithelial tumors could revolutionize the understanding of radiosensitivity. Combination of genomic and functional techniques are probably essential to better predict this parameter. (authors)

  4. Identifying and ranking the factors affecting entrepreneurial marketing to facilitate exports

    Directory of Open Access Journals (Sweden)

    Mehdi Habibzadeh

    2016-04-01

    Full Text Available Small and medium enterprises (SMEs are believed the most important components of today’s businesses and they can boost the growth of economy. This paper presents an empirical investigation to identify and rank important factors influencing on entrepreneurial marketing to facilitate exports of SMEs. The study designs a questionnaire in Likert scale and distributes it among 387 randomly selected entrepreneurs who act as managers of some SMEs in city of Tehran, Iran. Cronbach alpha is calculated as 0.873, which is well above the acceptable level. Using principle component analysis, the study has determined four factors including competitive intelligence, competitive advantage, external factors and internal factors to facilitate the export of SMEs.

  5. Identifying Human Factors Issues in Aircraft Maintenance Operations

    Science.gov (United States)

    Veinott, Elizabeth S.; Kanki, Barbara G.; Shafto, Michael G. (Technical Monitor)

    1995-01-01

    Maintenance operations incidents submitted to the Aviation Safety Reporting System (ASRS) between 1986-1992 were systematically analyzed in order to identify issues relevant to human factors and crew coordination. This exploratory analysis involved 95 ASRS reports which represented a wide range of maintenance incidents. The reports were coded and analyzed according to the type of error (e.g, wrong part, procedural error, non-procedural error), contributing factors (e.g., individual, within-team, cross-team, procedure, tools), result of the error (e.g., aircraft damage or not) as well as the operational impact (e.g., aircraft flown to destination, air return, delay at gate). The main findings indicate that procedural errors were most common (48.4%) and that individual and team actions contributed to the errors in more than 50% of the cases. As for operational results, most errors were either corrected after landing at the destination (51.6%) or required the flight crew to stop enroute (29.5%). Interactions among these variables are also discussed. This analysis is a first step toward developing a taxonomy of crew coordination problems in maintenance. By understanding what variables are important and how they are interrelated, we may develop intervention strategies that are better tailored to the human factor issues involved.

  6. Cognitive deficits in long-term survivors of childhood brain tumors: Identification of predictive factors

    DEFF Research Database (Denmark)

    Reimers, Tonny Solveig; Ehrenfels, Susanne; Mortensen, Erik Lykke

    2003-01-01

    To describe cognitive function and to evaluate the association between potentially predictive factors and cognitive outcome in an unselected population of survivors of childhood brain tumors.......To describe cognitive function and to evaluate the association between potentially predictive factors and cognitive outcome in an unselected population of survivors of childhood brain tumors....

  7. Marital Intimacy and Predictive Factors Among Infertile Women in Northern Iran

    Science.gov (United States)

    Pasha, Hajar; Esmailzadeh, Sedigheh; Faramarzi, Mahbobeh; Adibrad, Hajar

    2017-01-01

    Introduction Infertility is a stressful state that may decrease attachment between spouses. Marital intimacy is a real need in infertile women. Aim The aim of this study was to evaluate marital intimacy and predictive factors among infertile women in Northern Iran. Materials and Methods This cross-sectional study was conducted at Fatemeh Zahra Infertility and Reproductive Health Center of Babol Medical Sciences University in 2014. A total of 221 infertile women participated in this study. The instrument used in this research was Marital Intimacy Need Questionnaire (MINQ). Statistical analyses was performed using linear and logistic regression with pintimacy. The mean and standard deviation of the marital intimacy was 349.11±49.26 and in marital intimacy domains including: emotional (42.28±7.23), psychological (41.84±7.59), intellectual (42.56±7.46), sexual (42.90±7.41), physical (43.59±6.96), spiritual (51.61±8.06), aesthetic (42.66±6.75), and social intimacy (42.59±6.89). The highest mean of marital intimacy domains is related to spirituality in infertile women. Physical and sexual domains had the high mean in infertile women. The lowest mean in marital intimacy domains was psychological intimacy. There was a significant correlation between the domains of marital intimacy. The strongest correlation was between the physical and sexual intimacy (r=0.85). There was a significant inverse association in marital intimacy with the age difference of spouses (pintimacy with husband’s occupation, and cause of infertility (p<0.02). Conclusion Early screening and psychosocial intervention strategies suggest in the setting of female infertility to identify and prevent the predictive factors that may cause marital conflict. PMID:28658854

  8. Cell-type specificity of ChIP-predicted transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Håndstad Tony

    2012-08-01

    Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

  9. Prediction of beef carcass and meat traits from rearing factors in young bulls and cull cows.

    Science.gov (United States)

    Soulat, J; Picard, B; Léger, S; Monteils, V

    2016-04-01

    The aim of this study was to predict the beef carcass and LM (thoracis part) characteristics and the sensory properties of the LM from rearing factors applied during the fattening period. Individual data from 995 animals (688 young bulls and 307 cull cows) in 15 experiments were used to establish prediction models. The data concerned rearing factors (13 variables), carcass characteristics (5 variables), LM characteristics (2 variables), and LM sensory properties (3 variables). In this study, 8 prediction models were established: dressing percentage and the proportions of fat tissue and muscle in the carcass to characterize the beef carcass; cross-sectional area of fibers (mean fiber area) and isocitrate dehydrogenase activity to characterize the LM; and, finally, overall tenderness, juiciness, and flavor intensity scores to characterize the LM sensory properties. A random effect was considered in each model: the breed for the prediction models for the carcass and LM characteristics and the trained taste panel for the prediction of the meat sensory properties. To evaluate the quality of prediction models, 3 criteria were measured: robustness, accuracy, and precision. The model was robust when the root mean square errors of prediction of calibration and validation sub-data sets were near to one another. Except for the mean fiber area model, the obtained predicted models were robust. The prediction models were considered to have a high accuracy when the mean prediction error (MPE) was ≤0.10 and to have a high precision when the was the closest to 1. The prediction of the characteristics of the carcass from the rearing factors had a high precision ( > 0.70) and a high prediction accuracy (MPE 0.10). Only the flavor intensity of the beef score could be satisfactorily predicted from the rearing factors with high precision ( = 0.72) and accuracy (MPE = 0.10). All the prediction models displayed different effects of the rearing factors according to animal categories

  10. PRISM offers a comprehensive genomic approach to transcription factor function prediction

    KAUST Repository

    Wenger, A. M.; Clarke, S. L.; Guturu, H.; Chen, J.; Schaar, B. T.; McLean, C. Y.; Bejerano, G.

    2013-01-01

    The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

  11. PRISM offers a comprehensive genomic approach to transcription factor function prediction

    KAUST Repository

    Wenger, A. M.

    2013-02-04

    The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

  12. Predictive risk factors for persistent postherniotomy pain

    DEFF Research Database (Denmark)

    Aasvang, Eske K; Gmaehle, Eliza; Hansen, Jeanette B

    2010-01-01

    BACKGROUND: Persistent postherniotomy pain (PPP) affects everyday activities in 5-10% of patients. Identification of predisposing factors may help to identify the risk groups and guide anesthetic or surgical procedures in reducing risk for PPP. METHODS: A prospective study was conducted in 464...... patients undergoing open or laparoscopic transabdominal preperitoneal elective groin hernia repair. Primary outcome was identification of risk factors for substantial pain-related functional impairment at 6 months postoperatively assessed by the validated Activity Assessment Scale (AAS). Data on potential...... risk factors for PPP were collected preoperatively (pain from the groin hernia, preoperative AAS score, pain from other body regions, and psychometric assessment). Pain scores were collected on days 7 and 30 postoperatively. Sensory functions including pain response to tonic heat stimulation were...

  13. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing.

    Directory of Open Access Journals (Sweden)

    Minsam Ko

    Full Text Available Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers' online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans' interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users.

  14. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing

    Science.gov (United States)

    Yeo, Jaeryong; Lee, Juyeong

    2016-01-01

    Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers’ online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans’ interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users. PMID:26849568

  15. An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

    Science.gov (United States)

    Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

    2014-01-01

    Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances Ch

  16. Predictive factors for moderate or severe exacerbations in asthma patients receiving outpatient care

    OpenAIRE

    Guti?rrez, Francisco Javier ?lvarez; Galv?n, Marta Ferrer; Gallardo, Juan Francisco Medina; Mancera, Marta Barrera; Romero, Beatriz Romero; Falc?n, Auxiliadora Romero

    2017-01-01

    Background Asthma exacerbations are important events that affect disease control, but predictive factors for severe or moderate exacerbations are not known. The objective was to study the predictive factors for moderate (ME) and severe (SE) exacerbations in asthma patients receiving outpatient care. Methods Patients aged?>?12?years with asthma were included in the study and followed-up at 4-monthly intervals over a 12-month period. Clinical (severity, level of control, asthma control test [AC...

  17. Identificación de factores de predicción del incumplimiento terapéutico en adultos mayores hipertensos de una comunidad del sur de Chile Identifying predictive factors for therapy nonadherence among hypertensive, older adults from a community in southern Chile

    Directory of Open Access Journals (Sweden)

    Sara Mendoza-Parra

    2009-02-01

    Full Text Available OBJETIVO: Identificar factores de predicción del incumplimiento terapéutico en adultos ma yores hipertensos a partir de su dependencia funcional, trastornos de memoria, percepción de bienestar, maltrato y depresión en una región del sur de Chile. MÉTODOS: Estudio cuantitativo exploratorio en una muestra de 211 adultos mayores hiper tensos (29,1% de los atendidos en el Programa Cardiovascular del Centro de Salud Familiar San Pedro, en la provincia de Concepción, Región del Bío Bío, Chile. Se aplicaron siete ins trumentos: el cuestionario abreviado de Pfeiffer para el estado mental, la escala de Yesavage para la depresión geriátrica, la escala de maltrato senil, la escala moral del Centro Geriátrico de Filadelfia, la escala de conductas en salud y las escalas de Lawton y Katz para medir la ca pacidad de realizar actividades instrumentales y básicas de la vida diaria, respectivamente. Mediante el análisis de componentes principales se definieron variables latentes. RESULTADOS: Se determinaron dos variables latentes: vinculación con el medio -medida a partir de las variables depresión, maltrato y satisfacción con el medio- y autonomía -medida a partir de las variables estado mental y capacidad para realizar actividades instrumentales y básicas-. Estas variables latentes explicaron 39,7% y 20,7% del incumplimiento terapéutico, respectivamente. CONCLUSIONES: Las variables latentes propuestas pueden emplearse como factores de predic ción del incumplimiento terapéutico de los adultos mayores con hipertensión arterial. Las cau sas del incumplimiento terapéutico no pueden medirse solamente en los establecimientos de salud, es necesario conocer el entorno primario en el hogar y adecuar la atención sanitaria a partir de las necesidades que allí se detecten.OBJECTIVE: To identify the predictive factors associated with therapy nonadherence among hypertensive older adults, based on functional dependency, memory disorders, self

  18. Absence of back disorders in adults and work-related predictive factors in a 5-year perspective.

    Science.gov (United States)

    Reigo, T; Tropp, H; Timpka, T

    2001-06-01

    Factors important for avoiding back disorders in different age-groups have seldom been compared and studied over time. We therefore set out to study age-related differences in socio-economic and work-related factors associated with the absence of back disorders in a 5-year comparative cohort study using a mailed questionnaire. Two subgroups (aged 25-34 and 54-59 years) derived from a representative sample of the Swedish population were followed at baseline, 1 year and 5 years. Questions were asked about the duration of back pain episodes, relapses, work changes and work satisfaction. A work adaptability, partnership, growth, affection, resolve (APGAR) score was included in the final questionnaire. Multivariate logistic regression was used to identify factors predicting the absence of back disorders. Absence of physically heavy work predicted an absence of back disorders [odds ratio (OR), 2.86; 95% confidence interval (CI), 1.3-6.3] in the older group. In the younger age-group, the absence of stressful work predicted absence of back disorders (OR, 2.0; 95% CI, 1.1-3.6). Thirty-seven per cent of the younger age-group and 43% of the older age-group did not experience any back pain episodes during the study period. The exploratory work APGAR scores indicated that back disorders were only associated with lower work satisfaction in the older group. The analyses point out the importance of avoiding perceived psychological stress in the young and avoiding perceived physically heavy work in the older age-group for avoiding back disorders. The results suggest a need for different programmes at workplaces to avoid back disorders depending on the age of the employees concerned.

  19. Sexual harassment: identifying risk factors.

    Science.gov (United States)

    O'Hare, E A; O'Donohue, W

    1998-12-01

    A new model of the etiology of sexual harassment, the four-factor model, is presented and compared with several models of sexual harassment including the biological model, the organizational model, the sociocultural model, and the sex role spillover model. A number of risk factors associated with sexually harassing behavior are examined within the framework of the four-factor model of sexual harassment. These include characteristics of the work environment (e.g., sexist attitudes among co-workers, unprofessional work environment, skewed sex ratios in the workplace, knowledge of grievance procedures for sexual harassment incidents) as well as personal characteristics of the subject (e.g., physical attractiveness, job status, sex-role). Subjects were 266 university female faculty, staff, and students who completed the Sexual Experience Questionnaire to assess the experience of sexual harassment and a questionnaire designed to assess the risk factors stated above. Results indicated that the four-factor model is a better predictor of sexual harassment than the alternative models. The risk factors most strongly associated with sexual harassment were an unprofessional environment in the workplace, sexist atmosphere, and lack of knowledge about the organization's formal grievance procedures.

  20. Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

    Science.gov (United States)

    Yu, Hui; Mao, Kui-Tao; Shi, Jian-Yu; Huang, Hua; Chen, Zhi; Dong, Kai; Yiu, Siu-Ming

    2018-04-11

    Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Computational approaches have exhibited their abilities to predict potential DDIs on a large scale by utilizing pre-market drug properties (e.g. chemical structure). Nevertheless, none of them can predict two comprehensive types of DDIs, including enhancive and degressive DDIs, which increases and decreases the behaviors of the interacting drugs respectively. There is a lack of systematic analysis on the structural relationship among known DDIs. Revealing such a relationship is very important, because it is able to help understand how DDIs occur. Both the prediction of comprehensive DDIs and the discovery of structural relationship among them play an important guidance when making a co-prescription. In this work, treating a set of comprehensive DDIs as a signed network, we design a novel model (DDINMF) for the prediction of enhancive and degressive DDIs based on semi-nonnegative matrix factorization. Inspiringly, DDINMF achieves the conventional DDI prediction (AUROC = 0.872 and AUPR = 0.605) and the comprehensive DDI prediction (AUROC = 0.796 and AUPR = 0.579). Compared with two state-of-the-art approaches, DDINMF shows it superiority. Finally, representing DDIs as a binary network and a signed network respectively, an analysis based on NMF reveals crucial knowledge hidden among DDIs. Our approach is able to predict not only conventional binary DDIs but also comprehensive DDIs. More importantly, it reveals several key points about the DDI network: (1) both binary and signed networks show fairly clear clusters, in which both drug degree and the difference between positive degree and negative degree show significant distribution; (2) the drugs having large degrees tend to have a larger difference between positive degree

  1. Prediction of nucleosome positioning based on transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Xianfu Yi

    Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

  2. A comprehensive review of nongenetic prognostic and predictive factors influencing the heterogeneity of outcomes in advanced non-small-cell lung cancer

    Directory of Open Access Journals (Sweden)

    Cuyún Carter G

    2014-10-01

    Full Text Available Gebra Cuyún Carter,1 Amy M Barrett,2 James A Kaye,3 Astra M Liepa,1 Katherine B Winfree,1 William J John1 1Eli Lilly and Company, Indianapolis, IN, USA; 2RTI Health Solutions, Research Triangle Park, NC, USA; 3RTI Health Solutions, Waltham, MA, USA Abstract: While there have been advances in treatment options for those with advanced non-small-cell lung cancer, unmet medical needs remain, partly due to the heterogeneity of treatment effect observed among patients. The goals of this literature review were to provide updated information to complement past reviews and to identify a comprehensive set of nongenetic prognostic and predictive baseline factors that may account for heterogeneity of outcomes in advanced non-small-cell lung cancer. A review of the literature between 2000 and 2010 was performed using PubMed, Embase, and Cochrane Library. All relevant studies that met the inclusion criteria were selected and data elements were abstracted. A classification system was developed to evaluate the level of evidence for each study. A total of 54 studies were selected for inclusion. Patient-related factors (eg, performance status, sex, and age were the most extensively researched nongenetic prognostic factors, followed by disease stage and histology. Moderately researched prognostic factors were weight-related variables and number or site of metastases, and the least studied were comorbidities, previous therapy, smoking status, hemoglobin level, and health-related quality of life/symptom severity. The prognostic factors with the most consistently demonstrated associations with outcomes were performance status, number or site of metastases, previous therapy, smoking status, and health-related quality of life. Of the small number of studies that assessed predictive factors, those that were found to be significantly predictive of outcomes were performance status, age, disease stage, previous therapy, race, smoking status, sex, and histology. These

  3. A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2004-06-01

    Full Text Available Abstract Background The PathoLogic program constructs Pathway/Genome databases by using a genome's annotation to predict the set of metabolic pathways present in an organism. PathoLogic determines the set of reactions composing those pathways from the enzymes annotated in the organism's genome. Most annotation efforts fail to assign function to 40–60% of sequences. In addition, large numbers of sequences may have non-specific annotations (e.g., thiolase family protein. Pathway holes occur when a genome appears to lack the enzymes needed to catalyze reactions in a pathway. If a protein has not been assigned a specific function during the annotation process, any reaction catalyzed by that protein will appear as a missing enzyme or pathway hole in a Pathway/Genome database. Results We have developed a method that efficiently combines homology and pathway-based evidence to identify candidates for filling pathway holes in Pathway/Genome databases. Our program not only identifies potential candidate sequences for pathway holes, but combines data from multiple, heterogeneous sources to assess the likelihood that a candidate has the required function. Our algorithm emulates the manual sequence annotation process, considering not only evidence from homology searches, but also considering evidence from genomic context (i.e., is the gene part of an operon? and functional context (e.g., are there functionally-related genes nearby in the genome? to determine the posterior belief that a candidate has the required function. The method can be applied across an entire metabolic pathway network and is generally applicable to any pathway database. The program uses a set of sequences encoding the required activity in other genomes to identify candidate proteins in the genome of interest, and then evaluates each candidate by using a simple Bayes classifier to determine the probability that the candidate has the desired function. We achieved 71% precision at a

  4. Prediction of software operational reliability using testing environment factors

    International Nuclear Information System (INIS)

    Jung, Hoan Sung; Seong, Poong Hyun

    1995-01-01

    For many years, many researches have focused on the quantification of software reliability and there are many models developed to quantify software reliability. Most software reliability models estimate the reliability with the failure data collected during the test assuming that the test environments well represent the operation profile. The experiences show that the operational reliability is higher than the test reliability User's interest is on the operational reliability rather than on the test reliability, however. With the assumption that the difference in reliability results from the change of environment, testing environment factors comprising the aging factor and the coverage factor are defined in this study to predict the ultimate operational reliability with the failure data. It is by incorporating test environments applied beyond the operational profile into testing environment factors. The application results are close to the actual data

  5. Pulmonary embolism in intensive care unit: Predictive factors, clinical manifestations and outcome

    Directory of Open Access Journals (Sweden)

    Bahloul Mabrouk

    2010-01-01

    Full Text Available Objective : To determine predictive factors, clinical and demographics characteristics of patients with pulmonary embolism (PE in ICU, and to identify factors associated with poor outcome in the hospital and in the ICU. Methods : During a four-year prospective study, a medical committee of six ICU physicians prospectively examined all available data for each patient in order to classify patients according to the level of clinical suspicion of pulmonary thromboembolism. During the study periods, all patients admitted to our ICU were classified into four groups. The first group includes all patients with confirmed PE; the second group includes some patients without clinical manifestations of PE; the third group includes patients with suspected and not confirmed PE and the fourth group includes all patients with only deep vein thromboses (DVTs without suspicion of PE. The diagnosis of PE was confirmed either by a high-probability ventilation/perfusion (V/Q scan or by a spiral computed tomography (CT scan showing one or more filling defects in the pulmonary artery or in its branches. The diagnosis was also confirmed by echocardiography when a thrombus in the pulmonary artery was observed. Results : During the study periods, 4408 patients were admitted in our ICU. The diagnosis of PE was confirmed in 87 patients (1.9%. The mean delay of development of PE was 7.8 ± 9.5 days. On the day of PE diagnosis, clinical examination showed that 50 patients (57.5% were hypotensive, 63 (72.4% have SIRS, 15 (17.2% have clinical manifestations of DVT and 71 (81.6% have respiratory distress requiring mechanical ventilation. In our study, intravenous unfractionated heparin was used in 81 cases (93.1% and low molecular weight heparins were used in 4 cases (4.6%. The mean ICU stay was 20.2 ± 25.3 days and the mean hospital stay was 25.5 ± 25 days. The mortality rate in ICU was 47.1% and the in-hospital mortality rate was 52.9%. Multivariate analysis showed that

  6. Predictive factors associated with neck pain in patients with cervical disc degeneration

    Science.gov (United States)

    Kong, Lingde; Tian, Weifeng; Cao, Peng; Wang, Haonan; Zhang, Bing; Shen, Yong

    2017-01-01

    Abstract The predictive factors associated with neck pain remain unclear. We conducted a cross-sectional study to assess predictive factors, especially Modic changes (MCs), associated with the intensity and duration of neck pain in patients with cervical disc degenerative disease. We retrospectively reviewed patients in our hospital from January 2013 to December 2016. Severe neck pain (SNP) and persistent neck pain (PNP) were the 2 main outcomes, and were assessed based on the numerical rating scale (NRS). Basic data, and also imaging data, were collected and analyzed as potential predictive factors. Univariate analysis and multiple logistic regression analysis were performed to assess the predictive factors for neck pain. In all, 381 patients (193 males and 188 females) with cervical degenerative disease were included in our study. The number of patients with SNP and PNP were 94 (24.67%) and 109 (28.61%), respectively. The NRS of neck pain in patients with type 1 MCs was significantly higher than type 2 MCs (4.8 ± 0.9 vs 3.9 ± 1.1; P = .004). The multivariate logistic analysis showed that kyphosis curvature (odds ratio [OR] 1.082, 95% confidence interval [CI] 1.044–1.112), spondylolisthesis (OR 1.339, 95% CI 1.226–1.462), and annular tear (OR 1.188, 95% CI 1.021–1.382) were factors associated with SNP, whereas kyphosis curvature (OR 1.568, 95% CI 1.022–2.394), spondylolisthesis (OR 1.486, 95% CI 1.082–2.041), and MCs (OR 1.152, 95% CI 1.074–1.234) were associated with PNP. We concluded that kyphosis curvature, spondylolisthesis, and annular tear are associated with SNP, whereas kyphosis curvature, spondylolisthesis, and MCs are associated with PNP. This study supports the view that MCs can lead to a long duration of neck pain. PMID:29069048

  7. Identifying and describing feelings and psychological flexibility predict mental health in men with HIV.

    Science.gov (United States)

    Landstra, Jodie M B; Ciarrochi, Joseph; Deane, Frank P; Hillman, Richard J

    2013-11-01

    Difficulty identifying and describing feelings (DIDF) and psychological flexibility (PF) predict poor emotional adjustment. To examine the relationship between DIDF and PF and whether DIDF and low PF would put men undergoing cancer screening at risk for poor adjustment. Longitudinal self-report survey. Two hundred and one HIV-infected men who have sex with men participated in anal cancer screening at two time points over 14 weeks. Psychological flexibility was assessed by the Acceptance and Action Questionnaire II and DIDF by the Toronto Alexithymia Scale-20. We also measured depression, anxiety, stress (DASS) and health-related quality of life (QOL; SF-12). Both DIDF and PF were reliable predictors of mental health. When levels of baseline mental health were controlled, greater DIDF predicted increases in Time 2 depression, anxiety and stress and decreases in mental and physical QOL. The link between PF and mental health was entirely mediated by DIDF. Being chronically low in PF could lead to greater DIDF and thereby worse mental health. Having more PF promotes the ability to identify and differentiate the nuances of pleasant and unpleasant emotions, which enhances an individual's mental health. Intentionally enhancing men's ability to identify and describe feelings or PF may assist them to better manage a range of difficult life experiences such as health screenings and other potentially threatening information. © 2013 The British Psychological Society.

  8. Quantifying prognosis with risk predictions.

    Science.gov (United States)

    Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R

    2012-01-01

    Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.

  9. Nurse-Administered, Gut-Directed Hypnotherapy in IBS: Efficacy and Factors Predicting a Positive Response.

    Science.gov (United States)

    Lövdahl, Jenny; Ringström, Gisela; Agerforz, Pia; Törnblom, Hans; Simrén, Magnus

    2015-07-01

    Hypnotherapy is an effective treatment in irritable bowel syndrome (IBS). It is often delivered by a psychotherapist and is costly and time consuming. Nurse-administered hypnotherapy could increase availability and reduce costs. In this study the authors evaluate the effectiveness of nurse-administered, gut-directed hypnotherapy and identify factors predicting treatment outcome. Eighty-five patients were included in the study. Participants received hypnotherapy by a nurse once/week for 12 weeks. Patients reported marked improvement in gastrointestinal (GI) and extra-colonic symptoms after treatment, as well as a reduction in GI-specific anxiety, general anxiety, and depression. Fifty-eight percent were responders after the 12 weeks treatment period, and of these 82% had a favorable clinical response already at week 6. Women were more likely than men to respond favorably to the treatment. Nurse-administered hypnotherapy is an effective treatment for IBS. Being female and reporting a favorable response to treatment by week 6 predicted a positive treatment response at the end of the 12 weeks treatment period.

  10. Predicting Short-Term Subway Ridership and Prioritizing Its Influential Factors Using Gradient Boosting Decision Trees

    Directory of Open Access Journals (Sweden)

    Chuan Ding

    2016-10-01

    Full Text Available Understanding the relationship between short-term subway ridership and its influential factors is crucial to improving the accuracy of short-term subway ridership prediction. Although there has been a growing body of studies on short-term ridership prediction approaches, limited effort is made to investigate the short-term subway ridership prediction considering bus transfer activities and temporal features. To fill this gap, a relatively recent data mining approach called gradient boosting decision trees (GBDT is applied to short-term subway ridership prediction and used to capture the associations with the independent variables. Taking three subway stations in Beijing as the cases, the short-term subway ridership and alighting passengers from its adjacent bus stops are obtained based on transit smart card data. To optimize the model performance with different combinations of regularization parameters, a series of GBDT models are built with various learning rates and tree complexities by fitting a maximum of trees. The optimal model performance confirms that the gradient boosting approach can incorporate different types of predictors, fit complex nonlinear relationships, and automatically handle the multicollinearity effect with high accuracy. In contrast to other machine learning methods—or “black-box” procedures—the GBDT model can identify and rank the relative influences of bus transfer activities and temporal features on short-term subway ridership. These findings suggest that the GBDT model has considerable advantages in improving short-term subway ridership prediction in a multimodal public transportation system.

  11. Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects?

    Directory of Open Access Journals (Sweden)

    Lu Liping

    2011-01-01

    Full Text Available Abstract Background Obesity is associated with metabolic risk factors. Body mass index (BMI, waist circumference, waist-hip ratio (WHR and waist-height ratio (WHtR are used to predict the risk of obesity related diseases. However, it has not been examined whether these four indicators can detect the clustering of metabolic risk factors in Chinese subjects. Methods There are 772 Chinese subjects in the present study. Metabolic risk factors including high blood pressure, dyslipidemia, and glucose intolerance were identified according to the criteria from WHO. All statistical analyses were performed separately according to sex by using the SPSS 12.0. Results BMI, waist circumference and WHtR values were all significantly associated with blood pressure, glucose, triglyceride and also with the number of metabolic risk factors in both male and female subjects (all of P Conclusion The BMI, waist circumference and WHtR values can similarly predict the presence of multiple metabolic risk factors in Chinese subjects.

  12. Prediction of the methane conversion factor (Ym) for dairy cows on the basis of national farm data

    DEFF Research Database (Denmark)

    Hellwing, Anne Louise Frydendahl; Weisbjerg, Martin Riis; Brask, Maike

    2016-01-01

    Methane constitutes a significant loss of feed gross energy in ruminants, and there is an ongoing struggle for identifying feed and animal characteristics feasible for documentation of National Greenhouse Gas Inventories. The aim of the current study was to develop a model that predicts the methane...... and feed composition as variables, and one using yield of energy corrected milk and feed composition as variables. The methane conversion factor was significantly reduced with increased content of starch and fat in the ration, whereas neutral detergent fibre content surprisingly did not have a significant...

  13. Factors predicting mortality in elderly patients admitted to a ...

    African Journals Online (AJOL)

    The median age was 70 years (interquartile range 67 - 75 years). The overall ICU mortality was 44.7%, and 64% of deaths occurred within 5 days of admission. On univariate analysis, the factors predicting mortality were alcohol misuse (p=0.09), pneumonia (p.0.001), shock (p=0.001), dehydration (p=0.007), urine output ...

  14. The predictive factors for perceived social support among cancer patients and caregiver burden of their family caregivers in Turkish population.

    Science.gov (United States)

    Oven Ustaalioglu, Basak; Acar, Ezgi; Caliskan, Mecit

    2018-03-01

    We aimed to identify the predictive factors for the perceived family social support among cancer patients and caregiver burden of their family caregivers. Participants were 302 cancer patients and their family caregivers. Family social support scale was used for cancer patients, burden interview was used for family caregivers.All subjects also completed Beck depression invantery. The related socio-demographical factors with perceived social support (PSS) and caregiver burden were evaluated by correlation analysis. To find independent factors predicting caregiver burden and PSS, logistic regression analysis were conducted. Depression scores was higher among patients than their family caregivers (12.5 vs. 8). PSS was lower in depressed patients (p Family caregiver burden were also higher in depressive groups (p family caregiver role was negatively correlated (p caregiver burden. Presence of depression was the independent predictor for both, lower PSS for patients and higher burden for caregivers. The results of this study is noteworthy because it may help for planning any supportive care program not only for patients but together with their caregiver at the same time during chemotherapy period in Turkish population.

  15. IDENTIFYING MOTIVATION FACTOR INVOLVEMENT OF SARAWAK MALAY WOMEN ENTREPRENEUR

    Directory of Open Access Journals (Sweden)

    Masyantie Mohamad

    2016-03-01

    Full Text Available Sarawak multilayered cake among Sarawak product signature famous among the local as well as international tourist visiting Sarawak. In fact, Sarawak Malay women entrepreneurs have become very necessary players in the entrepreneurial field specifically in this cottage industries from the early introduction of this business, they have facing various problem in this businesses. Thus, this research aims to build an understanding of motivational factor that encourage Sarawak Malay women entrepreneurial experiences especially in multilayered cake businesses. Using qualitative methods, this research aims to identify the entrepreneurial motivations factors; with regards to start-up motivation by Sarawak Malay women. The finding shows that the motivations that influence Malay women within Kuching, Sarawak areas to start and grow their business are involve self-driven and context driven that motivate them involve in multilayered cakes businesses.

  16. Clinical and Radiologic Predictive Factors of Rib Fractures in Outpatients With Chest Pain.

    Science.gov (United States)

    Zhang, Liang; McMahon, Colm J; Shah, Samir; Wu, Jim S; Eisenberg, Ronald L; Kung, Justin W

    To identify the clinical and radiologic predictive factors of rib fractures in stable adult outpatients presenting with chest pain and to determine the utility of dedicated rib radiographs in this population of patients. Following Institutional Review Board approval, we performed a retrospective review of 339 consecutive cases in which a frontal chest radiograph and dedicated rib series had been obtained for chest pain in the outpatient setting. The frontal chest radiograph and dedicated rib series were sequentially reviewed in consensus by two fellowship-trained musculoskeletal radiologists blinded to the initial report. The consensus interpretation of the dedicated rib series was used as the gold standard. Multiple variable logistic regression analysis assessed clinical and radiological factors associated with rib fractures. Fisher exact test was used to assess differences in medical treatment between the 2 groups. Of the 339 patients, 53 (15.6%) had at least 1 rib fracture. Only 20 of the 53 (37.7%) patients' fractures could be identified on the frontal chest radiograph. The frontal chest radiograph had a sensitivity of 38% and specificity of 100% when using the rib series as the reference standard. No pneumothorax, new mediastinal widening or pulmonary contusion was identified. Multiple variable logistic regression analysis of clinical factors associated with the presence of rib fractures revealed a significant association of trauma history (odds ratio 5.7 [p rib fractures in this population demonstrated a significant association of pleural effusion with rib fractures (odds ratio 18.9 [p rib fractures received narcotic analgesia in 47.2% of the cases, significantly more than those without rib fractures (21.3%, p rib fractures have a higher association with a history of minor trauma and age ≥40 in the adult population. Radiographic findings associated with rib fractures include pleural effusion. The frontal chest radiograph alone has low sensitivity in

  17. Incidence, predictive factors, and clinical outcomes of acute kidney injury after gastric surgery for gastric cancer.

    Directory of Open Access Journals (Sweden)

    Chang Seong Kim

    Full Text Available BACKGROUND: Postoperative acute kidney injury (AKI, a serious surgical complication, is common after cardiac surgery; however, reports on AKI after noncardiac surgery are limited. We sought to determine the incidence and predictive factors of AKI after gastric surgery for gastric cancer and its effects on the clinical outcomes. METHODS: We conducted a retrospective study of 4718 patients with normal renal function who underwent partial or total gastrectomy for gastric cancer between June 2002 and December 2011. Postoperative AKI was defined by serum creatinine change, as per the Kidney Disease Improving Global Outcomes guideline. RESULTS: Of the 4718 patients, 679 (14.4% developed AKI. Length of hospital stay, intensive care unit admission rates, and in-hospital mortality rate (3.5% versus 0.2% were significantly higher in patients with AKI than in those without. AKI was also associated with requirement of renal replacement therapy. Multivariate analysis revealed that male gender; hypertension; chronic obstructive pulmonary disease; hypoalbuminemia (<4 g/dl; use of diuretics, vasopressors, and contrast agents; and packed red blood cell transfusion were independent predictors for AKI after gastric surgery. Postoperative AKI and vasopressor use entailed a high risk of 3-month mortality after multiple adjustments. CONCLUSIONS: AKI was common after gastric surgery for gastric cancer and associated with adverse outcomes. We identified several factors associated with postoperative AKI; recognition of these predictive factors may help reduce the incidence of AKI after gastric surgery. Furthermore, postoperative AKI in patients with gastric cancer is an important risk factor for short-term mortality.

  18. Risk factors predict post-traumatic stress disorder differently in men and women

    Directory of Open Access Journals (Sweden)

    Elklit Ask

    2008-11-01

    Full Text Available Abstract Background About twice as many women as men develop post-traumatic stress disorder (PTSD, even though men as a group are exposed to more traumatic events. Exposure to different trauma types does not sufficiently explain why women are more vulnerable. Methods The present work examines the effect of age, previous trauma, negative affectivity (NA, anxiety, depression, persistent dissociation, and social support on PTSD separately in men and women. Subjects were exposed to either a series of explosions in a firework factory near a residential area or to a high school stabbing incident. Results Some gender differences were found in the predictive power of well known risk factors for PTSD. Anxiety predicted PTSD in men, but not in women, whereas the opposite was found for depression. Dissociation was a better predictor for PTSD in women than in men in the explosion sample but not in the stabbing sample. Initially, NA predicted PTSD better in women than men in the explosion sample, but when compared only to other significant risk factors, it significantly predicted PTSD for both men and women in both studies. Previous traumatic events and age did not significantly predict PTSD in either gender. Conclusion Gender differences in the predictive value of social support on PTSD appear to be very complex, and no clear conclusions can be made based on the two studies included in this article.

  19. A Western diet ecological module identified from the 'humanized' mouse microbiota predicts diet in adults and formula feeding in children.

    Science.gov (United States)

    Siddharth, Jay; Holway, Nicholas; Parkinson, Scott J

    2013-01-01

    The interplay between diet and the microbiota has been implicated in the growing frequency of chronic diseases associated with the Western lifestyle. However, the complexity and variability of microbial ecology in humans and preclinical models has hampered identification of the molecular mechanisms underlying the association of the microbiota in this context. We sought to address two key questions. Can the microbial ecology of preclinical models predict human populations? And can we identify underlying principles that surpass the plasticity of microbial ecology in humans? To do this, we focused our study on diet; perhaps the most influential factor determining the composition of the gut microbiota. Beginning with a study in 'humanized' mice we identified an interactive module of 9 genera allied with Western diet intake. This module was applied to a controlled dietary study in humans. The abundance of the Western ecological module correctly predicted the dietary intake of 19/21 top and 21/21 of the bottom quartile samples inclusive of all 5 Western and 'low-fat' diet subjects, respectively. In 98 volunteers the abundance of the Western module correlated appropriately with dietary intake of saturated fatty acids, fat-soluble vitamins and fiber. Furthermore, it correlated with the geographical location and dietary habits of healthy adults from the Western, developing and third world. The module was also coupled to dietary intake in children (and piglets) correlating with formula (vs breast) feeding and associated with a precipitous development of the ecological module in young children. Our study provides a conceptual platform to translate microbial ecology from preclinical models to humans and identifies an ecological network module underlying the association of the gut microbiota with Western dietary habits.

  20. A Western diet ecological module identified from the 'humanized' mouse microbiota predicts diet in adults and formula feeding in children.

    Directory of Open Access Journals (Sweden)

    Jay Siddharth

    Full Text Available The interplay between diet and the microbiota has been implicated in the growing frequency of chronic diseases associated with the Western lifestyle. However, the complexity and variability of microbial ecology in humans and preclinical models has hampered identification of the molecular mechanisms underlying the association of the microbiota in this context. We sought to address two key questions. Can the microbial ecology of preclinical models predict human populations? And can we identify underlying principles that surpass the plasticity of microbial ecology in humans? To do this, we focused our study on diet; perhaps the most influential factor determining the composition of the gut microbiota. Beginning with a study in 'humanized' mice we identified an interactive module of 9 genera allied with Western diet intake. This module was applied to a controlled dietary study in humans. The abundance of the Western ecological module correctly predicted the dietary intake of 19/21 top and 21/21 of the bottom quartile samples inclusive of all 5 Western and 'low-fat' diet subjects, respectively. In 98 volunteers the abundance of the Western module correlated appropriately with dietary intake of saturated fatty acids, fat-soluble vitamins and fiber. Furthermore, it correlated with the geographical location and dietary habits of healthy adults from the Western, developing and third world. The module was also coupled to dietary intake in children (and piglets correlating with formula (vs breast feeding and associated with a precipitous development of the ecological module in young children. Our study provides a conceptual platform to translate microbial ecology from preclinical models to humans and identifies an ecological network module underlying the association of the gut microbiota with Western dietary habits.

  1. Macrophage Migration Inhibitory Factor Induces Inflammation and Predicts Spinal Progression in Ankylosing Spondylitis.

    Science.gov (United States)

    Ranganathan, Vidya; Ciccia, Francesco; Zeng, Fanxing; Sari, Ismail; Guggino, Guiliana; Muralitharan, Janogini; Gracey, Eric; Haroon, Nigil

    2017-09-01

    To investigate the role of macrophage migration inhibitory factor (MIF) in the pathogenesis of ankylosing spondylitis (AS). Patients who met the modified New York criteria for AS were recruited for the study. Healthy volunteers, rheumatoid arthritis patients, and osteoarthritis patients were included as controls. Based on the annual rate of increase in modified Stoke AS Spine Score (mSASSS), AS patients were classified as progressors or nonprogressors. MIF levels in serum and synovial fluid were quantitated by enzyme-linked immunosorbent assay. Predictors of AS progression were evaluated using logistic regression analysis. Immunohistochemical analysis of ileal tissue was performed to identify MIF-producing cells. Flow cytometry was used to identify MIF-producing subsets, expression patterns of the MIF receptor (CD74), and MIF-induced tumor necrosis factor (TNF) production in the peripheral blood. MIF-induced mineralization of osteoblast cells (SaOS-2) was analyzed by alizarin red S staining, and Western blotting was used to quantify active β-catenin levels. Baseline serum MIF levels were significantly elevated in AS patients compared to healthy controls and were found to independently predict AS progression. MIF levels were higher in the synovial fluid of AS patients, and MIF-producing macrophages and Paneth cells were enriched in their gut. MIF induced TNF production in monocytes, activated β-catenin in osteoblasts, and promoted the mineralization of osteoblasts. Our findings indicate an unexplored pathogenic role of MIF in AS and a link between inflammation and new bone formation. © 2017, American College of Rheumatology.

  2. Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines.

    KAUST Repository

    Foley, Joseph W; Sidow, Arend

    2013-01-01

    BACKGROUND: High-occupancy target (HOT) regions are compact genome loci occupied by many different transcription factors (TFs). HOT regions were initially defined in invertebrate model organisms, and we here show that they are a ubiquitous feature of the human gene-regulation landscape. RESULTS: We identified HOT regions by a comprehensive analysis of ChIP-seq data from 96 DNA-associated proteins in 5 human cell lines. Most HOT regions co-localize with RNA polymerase II binding sites, but many are not near the promoters of annotated genes. At HOT promoters, TF occupancy is strongly predictive of transcription preinitiation complex recruitment and moderately predictive of initiating Pol II recruitment, but only weakly predictive of elongating Pol II and RNA transcript abundance. TF occupancy varies quantitatively within human HOT regions; we used this variation to discover novel associations between TFs. The sequence motif associated with any given TF's direct DNA binding is somewhat predictive of its empirical occupancy, but a great deal of occupancy occurs at sites without the TF's motif, implying indirect recruitment by another TF whose motif is present. CONCLUSIONS: Mammalian HOT regions are regulatory hubs that integrate the signals from diverse regulatory pathways to quantitatively tune the promoter for RNA polymerase II recruitment.

  3. Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines.

    KAUST Repository

    Foley, Joseph W

    2013-10-20

    BACKGROUND: High-occupancy target (HOT) regions are compact genome loci occupied by many different transcription factors (TFs). HOT regions were initially defined in invertebrate model organisms, and we here show that they are a ubiquitous feature of the human gene-regulation landscape. RESULTS: We identified HOT regions by a comprehensive analysis of ChIP-seq data from 96 DNA-associated proteins in 5 human cell lines. Most HOT regions co-localize with RNA polymerase II binding sites, but many are not near the promoters of annotated genes. At HOT promoters, TF occupancy is strongly predictive of transcription preinitiation complex recruitment and moderately predictive of initiating Pol II recruitment, but only weakly predictive of elongating Pol II and RNA transcript abundance. TF occupancy varies quantitatively within human HOT regions; we used this variation to discover novel associations between TFs. The sequence motif associated with any given TF\\'s direct DNA binding is somewhat predictive of its empirical occupancy, but a great deal of occupancy occurs at sites without the TF\\'s motif, implying indirect recruitment by another TF whose motif is present. CONCLUSIONS: Mammalian HOT regions are regulatory hubs that integrate the signals from diverse regulatory pathways to quantitatively tune the promoter for RNA polymerase II recruitment.

  4. Predictive factors for anterior chamber fibrin formation after vitreoretinal surgery

    Directory of Open Access Journals (Sweden)

    Leonardo Provetti Cunha

    2014-04-01

    Full Text Available Purpose: The aim of this study was to investigate possible predictive factors related to anterior chamber fibrin formation after vitreoretinal surgery in a large series of patients. Methods: The data of 185 eyes of 185 patients submitted to vitreoretinal surgery was reviewed. The following variables were evaluated: the postoperatively presence of fibrin, age, diabetes mellitus, the vitrectomy system gauge (20, 23 or 25 gauge, the type of vitreous substitute, the influence of prior surgical procedures and the combination with cataract extraction. To evaluate predictive factors for anterior chamber fibrin formation, univariate analysis was performed. A multivariate stepwise logistic regression model was adjusted to investigate factors associated with fibrin formation (p<0.05. Results: Fibrinoid anterior chamber reaction was found in 12 (6.4% patients. For multivariate logistic regression analysis, balanced salt solution (BSS, the chance of fibrin occurrence was 5 times greater (odds ratio 4.83, CI 95% 1.302 - 17.892; p=0.019, while combination with phacoemulsification increased the chance of fibrin formation by 20 times (odds ratio 20, CI 95% 2.480 - 161.347; p=0.005. No significant difference was found regarding other variables. Conclusion: Anterior chamber fibrin formation is an unwanted complication after vitreoretinal surgery. Factors such as combined performance of phacoemulsification and the use of balanced salt solution as a vitreous substitute may predispose the occurrence of this complication.

  5. Brain-Derived Neurotrophic Factor Predicts Mortality Risk in Older Women

    DEFF Research Database (Denmark)

    Krabbe, K.S.; Mortensen, E.L.; Avlund, K.

    2009-01-01

    OBJECTIVES To test the hypothesis that low circulating brain-derived neurotrophic factor (BDNF), a secretory member of the neurotrophin family that has a protective role in neurodegeneration and stress responses and a regulatory role in metabolism, predicts risk of all-cause mortality in 85-year...

  6. [Two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education].

    Science.gov (United States)

    Lee, Soon Ok; Lee, Sang Yeoup; Baek, Sunyong; Woo, Jae Seok; Im, Sun Ju; Yune, So Jung; Lee, Sun Hee; Kam, Beesung

    2015-06-01

    We performed a two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education. Strategy factors in successful learning were identified using a content analysis of open-ended responses from 30 medical students who were ranked in the top 10 of their class. Core words were selected among their responses in each category and the frequency of the words were counted. Then, a factors survey was conducted among year 2 students, before the second semester. Finally, we performed an analysis to assess the association between the factors score and academic achievement for the same students 2.5 years later. The core words were "planning and execution," "daily reviews" in the study schedule category; "focusing in class" and "taking notes" among class-related category; and "lecture notes," "previous exams or papers," and "textbooks" in the primary self-learning resources category. There were associations between the factors scores for study planning and execution, focusing in class, and taking notes and academic achievement, representing the second year second semester credit score, third year written exam scores and fourth year written and skill exam scores. Study planning was only one independent variable to predict fourth year summative written exam scores. In a two-and-a-half year follow-up study, associations were founded between academic achievement and the factors scores for study planning and execution, focusing in class, and taking notes. Study planning as only one independent variable is useful for predicting fourth year summative written exam score.

  7. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain, which...

  8. Learning in manufacturing organizations : what factors predict effectiveness?

    NARCIS (Netherlands)

    Shipton, H.; Dawson, J.; West, M.A.; Patterson, M.G.

    2002-01-01

    This paper argues that it is possible to identify factors which pre-dispose organizations to adopt effective learning strategies and processes. It is hypothesized that effective OL is associated with: profitability, environmental uncertainty, structure, approach to HRM and quality orientation. The

  9. Predictive risk factors of postoperative urinary incontinence following holmium laser enucleation of the prostate during the initial learning period

    Directory of Open Access Journals (Sweden)

    Shuichiro Kobayashi

    Full Text Available ABSTRACT Purpose: To determine the predictive factors for postoperative urinary incontinence (UI following holmium laser enucleation of the prostate (HoLEP during the initial learning period. Patients and Methods: We evaluated 127 patients with benign prostatic hyperplasia who underwent HoLEP between January 2011 and December 2013. We recorded clinical variables, including blood loss, serum prostate-specific antigen levels, and the presence or absence of UI. Blood loss was estimated as a decline in postoperative hemoglobin levels. The predictive factors for postoperative UI were determined using a multivariable logistic regression analysis. Results: Postoperative UI occurred in 31 patients (24.4%, but it cured in 29 patients (93.5% after a mean duration of 12 weeks. Enucleation time >100 min (p=0.043 and blood loss >2.5g/dL (p=0.032 were identified as significant and independent risk factors for postoperative UI. Conclusions: Longer enucleation time and increased blood loss were independent predictors of postoperative UI in patients who underwent HoLEP during the initial learning period. Surgeons in training should take care to perform speedy enucleation maneuver with hemostasis.

  10. Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction.

    Science.gov (United States)

    Liu, Yong; Wu, Min; Miao, Chunyan; Zhao, Peilin; Li, Xiao-Li

    2016-02-01

    In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches.

  11. Could cognitive vulnerability identify high-risk subjects for schizophrenia?

    Science.gov (United States)

    Sarfati, Yves; Hardy-Baylé, Marie-Christine

    2002-12-08

    This review puts into questions the possible role of cognitive vulnerability markers in prediction and prevention of schizophrenia. Until recently, none of the identified cognitive anomalies has been proved to be definitive. However, as new promising candidates are emerging (DS-CPT, CPT-IP, P suppression, Saccadic Eye Movements), the predictive value of these trait-type anomalies may be criticized regarding four issues, which are discussed: technical, metrological, theoretical, and clinical. As things stand, the existence of a cognitive vulnerability marker, which testify to a permanent pathological trait, does not constitute a sufficient factor to identify and treat subjects who are at risk for schizophrenia. Copyright 2002 Wiley-Liss, Inc.

  12. Can shoulder dystocia be reliably predicted?

    Science.gov (United States)

    Dodd, Jodie M; Catcheside, Britt; Scheil, Wendy

    2012-06-01

    To evaluate factors reported to increase the risk of shoulder dystocia, and to evaluate their predictive value at a population level. The South Australian Pregnancy Outcome Unit's population database from 2005 to 2010 was accessed to determine the occurrence of shoulder dystocia in addition to reported risk factors, including age, parity, self-reported ethnicity, presence of diabetes and infant birth weight. Odds ratios (and 95% confidence interval) of shoulder dystocia was calculated for each risk factor, which were then incorporated into a logistic regression model. Test characteristics for each variable in predicting shoulder dystocia were calculated. As a proportion of all births, the reported rate of shoulder dystocia increased significantly from 0.95% in 2005 to 1.38% in 2010 (P = 0.0002). Using a logistic regression model, induction of labour and infant birth weight greater than both 4000 and 4500 g were identified as significant independent predictors of shoulder dystocia. The value of risk factors alone and when incorporated into the logistic regression model was poorly predictive of the occurrence of shoulder dystocia. While there are a number of factors associated with an increased risk of shoulder dystocia, none are of sufficient sensitivity or positive predictive value to allow their use clinically to reliably and accurately identify the occurrence of shoulder dystocia. © 2012 The Authors ANZJOG © 2012 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

  13. Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

    Science.gov (United States)

    Ma, Xiaoke; Sun, Penggang; Wang, Yu

    2018-04-01

    Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

  14. Optimal factors of diffusion tensor imaging predicting cortico spinal tract injury in patients with brain tumors

    Energy Technology Data Exchange (ETDEWEB)

    Min, Zhi Gang; Niu, Chen; Zhang, Qiu Li; Zhang, Ming [Dept. of Radiology, First Affiliated Hospital of Xi' an Jiaotong University, Xi' an (China); Qian, Yu Cheng [Dept. of Medical Imaging, School of Medicine, Jiangsu University, Zhenjiang (China)

    2017-09-15

    To identify the optimal factors in diffusion tensor imaging for predicting corticospinal tract (CST) injury caused by brain tumors. This prospective study included 33 patients with motor weakness and 64 patients with normal motor function. The movement of the CST, minimum distance between the CST and the tumor, and relative fractional anisotropy (rFA) of the CST on diffusion tensor imaging, were compared between patients with motor weakness and normal function. Logistic regression analysis was used to obtain the optimal factor predicting motor weakness. In patients with motor weakness, the displacement (8.44 ± 6.64 mm) of the CST (p = 0.009), minimum distance (3.98 ± 7.49 mm) between the CST and tumor (p < 0.001), and rFA (0.83 ± 0.11) of the CST (p < 0.001) were significantly different from those of the normal group (4.64 ± 6.65 mm, 14.87 ± 12.04 mm, and 0.98 ± 0.05, respectively) (p = 0.009, p < 0.001, and p < 0.001). The frequencies of patients with the CST passing through the tumor (6%, p = 0.002), CST close to the tumor (23%, p < 0.001), CST close to a malignant tumor (high grade glioma, metastasis, or lymphoma) (19%, p < 0.001), and CST passing through infiltrating edema (19%, p < 0.001) in the motor weakness group, were significantly different from those of the patients with normal motor function (0, 8, 1, and 10%, respectively). Logistic regression analysis showed that decreased rFA and CST close to a malignant tumor were effective variables related to motor weakness. Decreased fractional anisotropy, combined with closeness of a malignant tumor to the CST, is the optimal factor in predicting CST injury caused by a brain tumor.

  15. [Lightning-caused fire, its affecting factors and prediction: a review].

    Science.gov (United States)

    Zhang, Ji-Li; Bi, Wu; Wang, Xiao-Hong; Wang, Zi-Bo; Li, Di-Fei

    2013-09-01

    Lightning-caused fire is the most important natural fire source. Its induced forest fire brings enormous losses to human beings and ecological environment. Many countries have paid great attention to the prediction of lightning-caused fire. From the viewpoint of the main factors affecting the formation of lightning-caused fire, this paper emphatically analyzed the effects and action mechanisms of cloud-to-ground lightning, fuel, meteorology, and terrain on the formation and development process of lightning-caused fire, and, on the basis of this, summarized and reviewed the logistic model, K-function, and other mathematical methods widely used in prediction research of lightning-caused fire. The prediction methods and processes of lightning-caused fire in America and Canada were also introduced. The insufficiencies and their possible solutions for the present researches as well as the directions of further studies were proposed, aimed to provide necessary theoretical basis and literature reference for the prediction of lightning-caused fire in China.

  16. Predictive factors for postoperative visual function of primary chronic rhegmatogenous retinal detachment after scleral buckling.

    Science.gov (United States)

    Fang, Wei; Li, Jiu-Ke; Jin, Xiao-Hong; Dai, Yuan-Min; Li, Yu-Min

    2016-01-01

    To evaluate predictive factors for postoperative visual function of primary chronic rhegmatgenous retinal detachment (RRD) after sclera buckling (SB). Totally 48 patients (51 eyes) with primary chronic RRD were included in this prospective interventional clinical cases study, which underwent SB alone from June 2008 to December 2014. Age, sex, symptoms duration, detached extension, retinal hole position, size, type, fovea on/off, proliferative vitreoretinopathy (PVR), posterior vitreous detachment (PVD), baseline best corrected visual acuity (BCVA), operative duration, follow up duration, final BCVA were measured. Pearson correlation analysis, Spearman correlation analysis and multivariate linear stepwise regression were used to confirm predictive factors for better final visual acuity. Student's t-test, Wilcoxon two-sample test, Chi-square test and logistic stepwise regression were used to confirm predictive factors for better vision improvement. Baseline BCVA was 0.8313±0.6911 logMAR and final BCVA was 0.4761±0.4956 logMAR. Primary surgical success rate was 92.16% (47/51). Correlation analyses revealed shorter symptoms duration (r=0.3850, P=0.0053), less detached area (r=0.5489, Ppredictive factors were better baseline BCVA [partial R-square (PR(2))=0.5316, Ppredictive factors for better vision improvement were better baseline vision [odds ratio (OR) =50.369, P=0.0041] and longer follow up duration (OR=1.144, P=0.0067). Independent predictive factors for better visual outcome of primary chronic RRD after SB are better baseline BCVA, shorter symptoms duration, shorter operative duration and longer follow up duration, while independent predictive factors for better vision improvement after operation are better baseline vision and longer follow up duration.

  17. Use of NMR and NMR Prediction Software to Identify Components in Red Bull Energy Drinks

    Science.gov (United States)

    Simpson, Andre J.; Shirzadi, Azadeh; Burrow, Timothy E.; Dicks, Andrew P.; Lefebvre, Brent; Corrin, Tricia

    2009-01-01

    A laboratory experiment designed as part of an upper-level undergraduate analytical chemistry course is described. Students investigate two popular soft drinks (Red Bull Energy Drink and sugar-free Red Bull Energy Drink) by NMR spectroscopy. With assistance of modern NMR prediction software they identify and quantify major components in each…

  18. Identifying and tracking pedestrians based on sensor fusion and motion stability predictions.

    Science.gov (United States)

    Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Maria; de la Escalera, Arturo

    2010-01-01

    The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

  19. Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

    Directory of Open Access Journals (Sweden)

    Arturo de la Escalera

    2010-08-01

    Full Text Available The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem and dense disparity maps and u-v disparity (vision subsystem. Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

  20. Predictive factors for mortality in Fournier' gangrene: a series of 59 cases.

    Science.gov (United States)

    García Marín, Andrés; Turégano Fuentes, Fernando; Cuadrado Ayuso, Marta; Andueza Lillo, Juan Antonio; Cano Ballesteros, Juan Carlos; Pérez López, Mercedes

    2015-01-01

    Fournier's gangrene (FG) is the necrotizing fasciitis of the perineum and genital area and presents a high mortality rate. The aim was to assess prognostic factors for mortality, create a new mortality predictive scale and compare it with previously published scales in patients diagnosed with FG in our Emergency Department. Retrospective analysis study between 1998 and 2012. Of the 59 patients, 44 survived (74%) (S) and 15 died (26%) (D). Significant differences were found in peripheral vasculopathy (S 5 [11%]; D 6 [40%]; P=.023), hemoglobin (S 13; D 11; P=.014), hematocrit (S 37; D 31.4; P=.009), white blood cells (S 17,400; D 23,800; P=.023), serum urea (S 58; D 102; PFournier's gangrene severity index score (FGSIS) (S 4; D 7; P=.002) and Uludag Fournier's Gangrene Severity Index (UFGSI) (S 9; D 13; P=.004). Independent predictive factors were peripheral vasculopathy, serum potassium and severe sepsis criteria, and a model was created with an area under the ROC curve of 0.850 (0.760-0.973), higher than FGSIS (0.746 [0.601-0.981]) and UFGSI (0.760 [0.617-0.904]). FG showed a high mortality rate. Independent predictive factors were peripheral vasculopathy, potassium and severe sepsis criteria creating a predictive model that performed better than those previously described. Copyright © 2014 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

  1. Predictive factors for beneficial application of high-frequency electromagnetics for tumour vaporization and coagulation in neurosurgery

    Directory of Open Access Journals (Sweden)

    Koerbel Andrei

    2008-04-01

    Full Text Available Abstract Objective To identify preoperative and intraoperative factors and conditions that predicts the beneficial application of a high-frequency electromagnetic field (EMF system for tumor vaporization and coagulation. Methods One hundred three subsequent patients with brain tumors were microsurgically treated using the EMF system in addition to the standard neurosurgical instrumentarium. A multivariate analysis was performed regarding the usefulness (ineffective/useful/very helpful/essential of the new technology for tumor vaporization and coagulation, with respect to tumor histology and location, tissue consistency and texture, patients' age and sex. Results The EMF system could be used effectively during tumor surgery in 83 cases with an essential contribution to the overall success in 14 cases. In the advanced category of effectiveness (very helpful/essential, there was a significant difference between hard and soft tissue consistency (50 of 66 cases vs. 3 of 37 cases. The coagulation function worked well (very helpful/essential for surface (73 of 103 cases and spot (46 of 103 cases coagulation when vessels with a diameter of less than one millimeter were involved. The light-weight bayonet hand piece and long malleable electrodes made the system especially suited for the resection of deep-seated lesions (34 of 52 cases compared to superficial tumors (19 of 50 cases. The EMF system was less effective than traditional electrosurgical devices in reducing soft glial tumors. Standard methods where also required for coagulation of larger vessels. Conclusion It is possible to identify factors and conditions that predict a beneficial application of high-frequency electromagnetics for tumor vaporization and coagulation. This allows focusing the use of this technology on selective indications.

  2. Predicting coronary heart disease

    DEFF Research Database (Denmark)

    Sillesen, Henrik; Fuster, Valentin

    2012-01-01

    Atherosclerosis is the leading cause of death and disabling disease. Whereas risk factors are well known and constitute therapeutic targets, they are not useful for prediction of risk of future myocardial infarction, stroke, or death. Therefore, methods to identify atherosclerosis itself have bee...

  3. A method to identify dependencies between organizational factors using statistical independence test

    International Nuclear Information System (INIS)

    Kim, Y.; Chung, C.H.; Kim, C.; Jae, M.; Jung, J.H.

    2004-01-01

    A considerable number of studies on organizational factors in nuclear power plants have been made especially in recent years, most of which have assumed organizational factors to be independent. However, since organizational factors characterize the organization in terms of safety and efficiency etc. and there would be some factors that have close relations between them. Therefore, from whatever point of view, if we want to identify the characteristics of an organization, the dependence relationships should be considered to get an accurate result. In this study the organization of a reference nuclear power plant in Korea was analyzed for the trip cases of that plant using 20 organizational factors that Jacobs and Haber had suggested: 1) coordination of work, 2) formalization, 3) organizational knowledge, 4) roles and responsibilities, 5) external communication, 6) inter-department communications, 7) intra-departmental communications, 8) organizational culture, 9) ownership, 10) safety culture, 11) time urgency, 12) centralization, 13) goal prioritization, 14) organizational learning, 15) problem identification, 16) resource allocation, 17) performance evaluation, 18) personnel selection, 19) technical knowledge, and 20) training. By utilizing the results of the analysis, a method to identify the dependence relationships between organizational factors is presented. The statistical independence test for the analysis result of the trip cases is adopted to reveal dependencies. This method is geared to the needs to utilize many kinds of data that has been obtained as the operating years of nuclear power plants increase, and more reliable dependence relations may be obtained by using these abundant data

  4. A characterization of factors determining postoperative ileus after laparoscopic colectomy enables the generation of a novel predictive score.

    Science.gov (United States)

    Kronberg, Udo; Kiran, Ravi P; Soliman, Mohamed S M; Hammel, Jeff P; Galway, Ursula; Coffey, John Calvin; Fazio, Victor W

    2011-01-01

    Postoperative ileus (POI) after colorectal surgery is associated with prolonged hospital stay and increased costs. The aim of this study is to investigate pre-, intra-, and postoperative risk factors associated with the development of POI in patients undergoing laparoscopic partial colectomy. Patients operated between 2004 and 2008 were retrospectively identified from a prospectively maintained database, and clinical, metabolic, and pharmacologic data were obtained. Postoperative ileus was defined as the absence of bowel function for 5 or more days or the need for reinsertion of a nasogastric tube after starting oral diet in the absence of mechanical obstruction. Associations between likelihood of POI and study variables were assessed univariably by using χ tests, Fisher exact tests, and logistic regression models. A scoring system for prediction of POI was constructed by using a multivariable logistic regression model based on forward stepwise selection of preoperative factors. A total of 413 patients (mean age, 58 years; 53.5% women) were included, and 42 (10.2%) of them developed POI. Preoperative albumin, postoperative deep-vein thrombosis, and electrolyte levels were associated with POI. Age, previous abdominal surgery, and chronic preoperative use of narcotics were independently correlated with POI on multivariate analysis, which allowed the creation of a predictive score. Patients with a score of 2 or higher had an 18.3% risk of POI (P POI can be predicted by using a preoperative scoring system. Addressing the postoperative factors may be expected to reduce the incidence of this common complication in high-risk patients.

  5. The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy.

    Science.gov (United States)

    Thiels, Cornelius A; Yu, Denny; Abdelrahman, Amro M; Habermann, Elizabeth B; Hallbeck, Susan; Pasupathy, Kalyan S; Bingener, Juliane

    2017-01-01

    Reliable prediction of operative duration is essential for improving patient and care team satisfaction, optimizing resource utilization and reducing cost. Current operative scheduling systems are unreliable and contribute to costly over- and underestimation of operative time. We hypothesized that the inclusion of patient-specific factors would improve the accuracy in predicting operative duration. We reviewed all elective laparoscopic cholecystectomies performed at a single institution between 01/2007 and 06/2013. Concurrent procedures were excluded. Univariate analysis evaluated the effect of age, gender, BMI, ASA, laboratory values, smoking, and comorbidities on operative duration. Multivariable linear regression models were constructed using the significant factors (p historical surgeon-specific and procedure-specific operative duration. External validation was done using the ACS-NSQIP database (n = 11,842). A total of 1801 laparoscopic cholecystectomy patients met inclusion criteria. Female sex was associated with reduced operative duration (-7.5 min, p < 0.001 vs. male sex) while increasing BMI (+5.1 min BMI 25-29.9, +6.9 min BMI 30-34.9, +10.4 min BMI 35-39.9, +17.0 min BMI 40 + , all p < 0.05 vs. normal BMI), increasing ASA (+7.4 min ASA III, +38.3 min ASA IV, all p < 0.01 vs. ASA I), and elevated liver function tests (+7.9 min, p < 0.01 vs. normal) were predictive of increased operative duration on univariate analysis. A model was then constructed using these predictive factors. The traditional surgical scheduling system was poorly predictive of actual operative duration (R 2  = 0.001) compared to the patient factors model (R 2  = 0.08). The model remained predictive on external validation (R 2  = 0.14).The addition of surgeon as a variable in the institutional model further improved predictive ability of the model (R 2  = 0.18). The use of routinely available pre-operative patient factors improves the prediction of operative

  6. Identify and rank key factors influencing the adoption of cloud computing for a healthy Electronics

    Directory of Open Access Journals (Sweden)

    Javad Shukuhy

    2015-02-01

    Full Text Available Cloud computing as a new technology with Internet infrastructure and new approaches can be significant benefits in providing medical services electronically. Aplying this technology in E-Health requires consideration of various factors. The main objective of this study is to identify and rank the factors influencing the adoption of e-health cloud. Based on the Technology-Organization-Environment (TOE framework and Human-Organization-Technology fit (HOT-fit model, 16 sub-factors were identified in four major factors. With survey of 60 experts, academics and experts in health information technology and with the help of fuzzy analytic hierarchy process had ranked these sub-factors and factors. In the literature, considering newness this study, no internal or external study, have not alluded these number of criteria. The results show that when deciding to adopt cloud computing in E-Health, respectively, must be considered technological, human, organizational and environmental factors.

  7. Simplified method to predict mutual interactions of human transcription factors based on their primary structure

    KAUST Repository

    Schmeier, Sebastian

    2011-07-05

    Background: Physical interactions between transcription factors (TFs) are necessary for forming regulatory protein complexes and thus play a crucial role in gene regulation. Currently, knowledge about the mechanisms of these TF interactions is incomplete and the number of known TF interactions is limited. Computational prediction of such interactions can help identify potential new TF interactions as well as contribute to better understanding the complex machinery involved in gene regulation. Methodology: We propose here such a method for the prediction of TF interactions. The method uses only the primary sequence information of the interacting TFs, resulting in a much greater simplicity of the prediction algorithm. Through an advanced feature selection process, we determined a subset of 97 model features that constitute the optimized model in the subset we considered. The model, based on quadratic discriminant analysis, achieves a prediction accuracy of 85.39% on a blind set of interactions. This result is achieved despite the selection for the negative data set of only those TF from the same type of proteins, i.e. TFs that function in the same cellular compartment (nucleus) and in the same type of molecular process (transcription initiation). Such selection poses significant challenges for developing models with high specificity, but at the same time better reflects real-world problems. Conclusions: The performance of our predictor compares well to those of much more complex approaches for predicting TF and general protein-protein interactions, particularly when taking the reduced complexity of model utilisation into account. © 2011 Schmeier et al.

  8. Simplified method to predict mutual interactions of human transcription factors based on their primary structure.

    Directory of Open Access Journals (Sweden)

    Sebastian Schmeier

    Full Text Available BACKGROUND: Physical interactions between transcription factors (TFs are necessary for forming regulatory protein complexes and thus play a crucial role in gene regulation. Currently, knowledge about the mechanisms of these TF interactions is incomplete and the number of known TF interactions is limited. Computational prediction of such interactions can help identify potential new TF interactions as well as contribute to better understanding the complex machinery involved in gene regulation. METHODOLOGY: We propose here such a method for the prediction of TF interactions. The method uses only the primary sequence information of the interacting TFs, resulting in a much greater simplicity of the prediction algorithm. Through an advanced feature selection process, we determined a subset of 97 model features that constitute the optimized model in the subset we considered. The model, based on quadratic discriminant analysis, achieves a prediction accuracy of 85.39% on a blind set of interactions. This result is achieved despite the selection for the negative data set of only those TF from the same type of proteins, i.e. TFs that function in the same cellular compartment (nucleus and in the same type of molecular process (transcription initiation. Such selection poses significant challenges for developing models with high specificity, but at the same time better reflects real-world problems. CONCLUSIONS: The performance of our predictor compares well to those of much more complex approaches for predicting TF and general protein-protein interactions, particularly when taking the reduced complexity of model utilisation into account.

  9. An exploratory study to identify critical factors of innovation culture in organizations

    Directory of Open Access Journals (Sweden)

    Hamed Asgari

    2013-07-01

    Full Text Available During the past two decades, there has been a growing trend on knowledge-based organizations. Innovation, on the other hand, plays essential role on building competitive business units. In this paper, we present an exploratory study to identify critical factors of innovation culture in organizations. We detect important factors influencing innovation culture in construction industry based on the implementation of factor analysis. The proposed study designs a questionnaire and distributes it among 400 experts who are involved in construction industry. Cronbach alpha has been calculated as 0.779, which validates the overall questionnaire. The results of factor analysis have indicated that six factors of building cultural infrastructures, education, organizational vision, established culture, strategic culture and flexible culture are the most important items influencing innovation culture.

  10. Automatically Identifying and Predicting Unplanned Wind Turbine Stoppages Using SCADA and Alarms System Data: Case Study and Results

    Science.gov (United States)

    Leahy, Kevin; Gallagher, Colm; Bruton, Ken; O'Donovan, Peter; O'Sullivan, Dominic T. J.

    2017-11-01

    Using 10-minute wind turbine SCADA data for fault prediction offers an attractive way of gaining additional prognostic capabilities without needing to invest in extra hardware. To use these data-driven methods effectively, the historical SCADA data must be labelled with the periods when the turbine was in faulty operation as well the sub-system the fault was attributed to. Manually identifying faults using maintenance logs can be effective, but is also highly time consuming and tedious due to the disparate nature of these logs across manufacturers, operators and even individual maintenance events. Turbine alarm systems can help to identify these periods, but the sheer volume of alarms and false positives generated makes analysing them on an individual basis ineffective. In this work, we present a new method for automatically identifying historical stoppages on the turbine using SCADA and alarms data. Each stoppage is associated with either a fault in one of the turbine’s sub-systems, a routine maintenance activity, a grid-related event or a number of other categories. This is then checked against maintenance logs for accuracy and the labelled data fed into a classifier for predicting when these stoppages will occur. Results show that the automated labelling process correctly identifies each type of stoppage, and can be effectively used for SCADA-based prediction of turbine faults.

  11. Factors predicting recovery from suicide in attempted suicide patients.

    Science.gov (United States)

    Sun, Fan-Ko; Lu, Chu-Yun; Tseng, Yun Shan; Chiang, Chun-Ying

    2017-12-01

    The aim of this study was to explore the factors predicting suicide recovery and to provide guidance for healthcare professionals when caring for individuals who have attempted suicide. The high rate of suicide is a global health problem. Suicide prevention has become an important issue in contemporary mental health. Most suicide research has focused on suicidal prevention and care. There is a lack of research on the factors predicting suicidal recovery. A cross-sectional design was adopted. A correlational study with a purposive sample of 160 individuals from a suicide prevention centre in southern Taiwan was conducted. The questionnaires included the Brief Symptom Rating Scale-5, Suicidal Recovery Assessment Scale and Beck Hopelessness Scale. Descriptive statistics and linear regressions were used for the analysis. The mean age of the participants was 40.2 years. Many participants were striving to make changes to create a more stable and fulfilling life, had an improved recovery from suicide and had a good ability to adapt or solve problems. The linear regression showed that the Beck Hopelessness Scale scores (ß = -.551, p suicidal behaviour (ß = -.145, p = .008) were significant predictors of individuals' recovery from suicide. They accounted for 57.1% of the variance. Suicidal individuals who have a lower level of hopelessness, a better ability to cope with their mental condition and fewer past suicidal behaviours may better recover from suicide attempts. The nurses could use the results of this study to predict recovery from suicide in patients with attempted suicide. © 2017 John Wiley & Sons Ltd.

  12. Predictive factors for malignancy in incidental pulmonary nodules detected in breast cancer patients at baseline CT

    Energy Technology Data Exchange (ETDEWEB)

    Hammer, Mark M.; Mortani Barbosa, Eduardo J. [University of Pennsylvania, Division of Cardiothoracic Imaging, Department of Radiology, Perelman School of Medicine, Philadelphia, PA (United States)

    2017-07-15

    Pulmonary nodules are commonly encountered at staging CTs in patients with extrathoracic malignancies, but their significance on a per-patient basis remains uncertain. We undertook a retrospective analysis of pulmonary nodules identified in patients with a diagnosis of breast cancer from 2010 - 2015, evaluating nodules present at a baseline CT (i.e. prevalent nodules). We reviewed 211 patients with 248 individual nodules. The rate of malignancy in prevalent nodules is low, approximately 13 %. Variables associated with metastasis include pleural studding, hilar lymphadenopathy and the presence of extrapulmonary metastasis, as well as number of nodules, nodule size and nodule shape. Using a combination of these factors, we have developed an evidence-based multivariate decision tree to predict which nodules are malignant in these patients, which is 91 % accurate and 100 % sensitive for metastasis. We propose a simplified clinical prediction algorithm to guide radiologists and oncologists in managing patients with breast cancer and incidental pulmonary nodules. (orig.)

  13. Formulating the strength factor α for improved predictability of radiation hardening

    Energy Technology Data Exchange (ETDEWEB)

    Tan, L., E-mail: tanl@ornl.gov; Busby, J.T.

    2015-10-15

    Analytical equations were developed to calculate the strength factors of precipitates, Frank loops, and cavities in austenitic alloys, which strongly depend on barrier type, size, geometry and density, as well as temperature. Calculated strength factors were successfully used to estimate radiation hardening using the broadly employed dispersed barrier-hardening model, leading to good agreement with experimentally measured hardening in neutron-irradiated type 304 and 316 stainless steel variants. The formulated strength factor provides a route for more reliable hardening predictions and can be easily incorporated into component simulations and design.

  14. Controlling factors of uranium mineralization and prospect prediction in Qimantage area

    International Nuclear Information System (INIS)

    Yao Chunling; Zhu Pengfei; Cai Yuqi; Zhang Wenming; Zhao Yong'an; Song Jiye; Zhang Xiaojin

    2011-01-01

    Based on the analysis of regional geology in Qimantage area, the condition for uranium mineralization is summarized in regional geology setting, volcanic, granite and faults. This study shows that this area has favorable prospect for uranium mineralization. The metallogenic model is built up according to the controlling factors over uranium mineralization. Under this model, six potential areas are predicted in MRAS software with mineralization factors of synthetically geological information method. (authors)

  15. Predicting dropout using student- and school-level factors: An ecological perspective.

    Science.gov (United States)

    Wood, Laura; Kiperman, Sarah; Esch, Rachel C; Leroux, Audrey J; Truscott, Stephen D

    2017-03-01

    High school dropout has been associated with negative outcomes, including increased rates of unemployment, incarceration, and mortality. Dropout rates vary significantly depending on individual and environmental factors. The purpose of our study was to use an ecological perspective to concurrently explore student- and school-level predictors associated with dropout for the purpose of better understanding how to prevent it. We used the Education Longitudinal Study of 2002 dataset. Participants included 14,106 sophomores across 684 public and private schools. We identified variables of interest based on previous research on dropout and implemented hierarchical generalized linear modeling. In the final model, significant student-level predictors included academic achievement, retention, sex, family socioeconomic status (SES), and extracurricular involvement. Significant school-level predictors included school SES and school size. Race/ethnicity, special education status, born in the United States, English as first language, school urbanicity, and school region did not significantly predict dropout after controlling for the aforementioned predictors. Implications for prevention and intervention efforts within a multitiered intervention model are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  16. Can we predict the outcome for people with patellofemoral pain? A systematic review on prognostic factors and treatment effect modifiers.

    Science.gov (United States)

    Matthews, M; Rathleff, M S; Claus, A; McPoil, T; Nee, R; Crossley, K; Vicenzino, B

    2017-12-01

    Patellofemoral pain (PFP) is a multifactorial and often persistent knee condition. One strategy to enhance patient outcomes is using clinically assessable patient characteristics to predict the outcome and match a specific treatment to an individual. A systematic review was conducted to determine which baseline patient characteristics were (1) associated with patient outcome (prognosis); or (2) modified patient outcome from a specific treatment (treatment effect modifiers). 6 electronic databases were searched (July 2016) for studies evaluating the association between those with PFP, their characteristics and outcome. All studies were appraised using the Epidemiological Appraisal Instrument. Studies that aimed to identify treatment effect modifiers underwent a checklist for methodological quality. The 24 included studies evaluated 180 participant characteristics. 12 studies investigated prognosis, and 12 studies investigated potential treatment effect modifiers. Important methodological limitations were identified. Some prognostic studies used a retrospective design. Studies aiming to identify treatment effect modifiers often analysed too many variables for the limiting sample size and typically failed to use a control or comparator treatment group. 16 factors were reported to be associated with a poor outcome, with longer duration of symptoms the most reported (>4 months). Preliminary evidence suggests increased midfoot mobility may predict those who have a successful outcome to foot orthoses. Current evidence can identify those with increased risk of a poor outcome, but methodological limitations make it difficult to predict the outcome after one specific treatment compared with another. Adequately designed randomised trials are needed to identify treatment effect modifiers. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  17. Predicting transcription factor binding sites using local over-representation and comparative genomics

    Directory of Open Access Journals (Sweden)

    Touzet Hélène

    2006-08-01

    Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

  18. Mathematical models for prediction of safety factors for a simply ...

    African Journals Online (AJOL)

    From the results obtained, mathematical prediction models were developed using a least square regression analysis for bending, shear and deflection modes of failure considered in the study. The results showed that the safety factors for material, dead and live load are not unique, but they are influenced by safety index ...

  19. Prediction of postpartum blood transfusion – risk factors and recurrence

    DEFF Research Database (Denmark)

    Wikkelsø, Anne J; Hjortøe, Sofie; Gerds, Thomas A

    2014-01-01

    OBJECTIVE: The aim was to find clinically useful risk factors for postpartum transfusion and to assess the joint predictive value in a population of women with a first and second delivery. METHODS: All Danish women with a first and second delivery from January 2001 to September 2009 who gave birt...

  20. Predictive risk modelling under different data access scenarios: who is identified as high risk and for how long?

    Science.gov (United States)

    Johnson, Tracy L; Kaldor, Jill; Sutherland, Kim; Humphries, Jacob; Jorm, Louisa R; Levesque, Jean-Frederic

    2018-01-01

    Objective This observational study critically explored the performance of different predictive risk models simulating three data access scenarios, comparing: (1) sociodemographic and clinical profiles; (2) consistency in high-risk designation across models; and (3) persistence of high-risk status over time. Methods Cross-sectional health survey data (2006–2009) for more than 260 000 Australian adults 45+ years were linked to longitudinal individual hospital, primary care, pharmacy and mortality data. Three risk models predicting acute emergency hospitalisations were explored, simulating conditions where data are accessed through primary care practice management systems, or through hospital-based electronic records, or through a hypothetical ‘full’ model using a wider array of linked data. High-risk patients were identified using different risk score thresholds. Models were reapplied monthly for 24 months to assess persistence in high-risk categorisation. Results The three models displayed similar statistical performance. Three-quarters of patients in the high-risk quintile from the ‘full’ model were also identified using the primary care or hospital-based models, with the remaining patients differing according to age, frailty, multimorbidity, self-rated health, polypharmacy, prior hospitalisations and imminent mortality. The use of higher risk prediction thresholds resulted in lower levels of agreement in high-risk designation across models and greater morbidity and mortality in identified patient populations. Persistence of high-risk status varied across approaches according to updated information on utilisation history, with up to 25% of patients reassessed as lower risk within 1 year. Conclusion/implications Small differences in risk predictors or risk thresholds resulted in comparatively large differences in who was classified as high risk and for how long. Pragmatic predictive risk modelling design decisions based on data availability or projected

  1. On predicting student performance using low-rank matrix factorization techniques

    DEFF Research Database (Denmark)

    Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

    2017-01-01

    Predicting the score of a student is one of the important problems in educational data mining. The scores given by an individual student reflect how a student understands and applies the knowledge conveyed in class. A reliable performance prediction enables teachers to identify weak students...... that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools...... and the current version of the data set is very sparse, the very low-rank approximation can capture enough information. This means that the simple baseline approach achieves similar performance compared to other advanced methods. In future work, we will restrict the quiz data set, e.g. only including quizzes...

  2. An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

    Directory of Open Access Journals (Sweden)

    Liang Yu

    2008-12-01

    Full Text Available Abstract Background Patients diagnosed with lung adenocarcinoma (AD and squamous cell carcinoma (SCC, two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy. Methods MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays. Results Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively. Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette

  3. An analysis of predictive factors for concurrent acute-on-chronic liver failure and hepatorenal syndrome

    Directory of Open Access Journals (Sweden)

    CHEN Yanfang

    2015-09-01

    Full Text Available ObjectiveTo learn the clinical characteristics of concurrent acute-on-chronic liver failure (ACLF and hepatorenal syndrome (HRS, and to investigate the predictive factors for HRS in patients with ACLF. MethodsA total of 806 patients with ACLF who were admitted to our hospital from January 2012 to May 2014 were selected and divided into two groups according to the incidence of concurrent HRS. Clinical indices and laboratory test results were analyzed in the two groups, and the multivariate logistic regression analysis was used to figure out independent indices for the prediction of HRS in patients with ACLF. A prediction model was established and the receiver operating characteristic curve was drawn to evaluate the accuracy of the prediction model. Comparison of continuous data between the two groups was made by t test, and comparison of categorical data between the two groups was made by χ2 test. ResultsIn all patients with ACLF, 229 had HRS and 577 had no HRS. The univariate logistic regression analysis showed that hepatic encephalopathy, peritonitis, infection, age, cystatin C (Cys-C, serum creatinine (SCr, blood urea nitrogen, albumin, prealbumin, total bilirubin, direct bilirubin, total cholesterol, K+, Na+, phosphorus, Ca2+, prothrombin time, prothrombin activity, international normalized ratio, and hematocrit were significant predictive factors for HRS. The multivariate logistic regression analysis showed that concurrent peritonitis, Cys-C, SCr, and HCO3- were independent predictive factors for HRS in patients with ACLF (OR=3.155, P<0.01; OR=30.773, P<0.01; OR=1062, P<0.01; OR=0.915, P<0.05. The model was proved of great value in prediction. ConclusionConcurrent peritonitis, Cys-C, SCr, and HCO3- are effective predictive factors for HRS in patients with ACLF.

  4. Combined and interactive effects of environmental and GWAS-identified risk factors in ovarian cancer

    DEFF Research Database (Denmark)

    Pearce, Celeste Leigh; Rossing, Mary Anne; Lee, Alice W

    2013-01-01

    There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied....

  5. Early dropout predictive factors in obesity treatment.

    Science.gov (United States)

    Michelini, Ilaria; Falchi, Anna Giulia; Muggia, Chiara; Grecchi, Ilaria; Montagna, Elisabetta; De Silvestri, Annalisa; Tinelli, Carmine

    2014-02-01

    Diet attrition and failure of long term treatment are very frequent in obese patients. This study aimed to identify pre-treatment variables determining dropout and to customise the characteristics of those most likely to abandon the program before treatment, thus making it possible to modify the therapy to increase compliance. A total of 146 outpatients were consecutively enrolled; 73 patients followed a prescriptive diet while 73 followed a novel brief group Cognitive Behavioural Treatment (CBT) in addition to prescriptive diet. The two interventions lasted for six months. Anthropometric, demographic, psychological parameters and feeding behaviour were assessed, the last two with the Italian instrument VCAO Ansisa; than, a semi-structured interview was performed on motivation to lose weight. To identify the baseline dropout risk factors among these parameters, univariate and multivariate logistic models were used. Comparison of the results in the two different treatments showed a higher attrition rate in CBT group, despite no statistically significant difference between the two treatment arms (P = 0.127). Dropout patients did not differ significantly from those who did not dropout with regards to sex, age, Body Mass Index (BMI), history of cycling, education, work and marriage. Regardless of weight loss, the most important factor that determines the dropout appears to be a high level of stress revealed by General Health Questionnaire-28 items (GHQ-28) score within VCAO test. The identification of hindering factors during the assessment is fundamental to reduce the dropout risk. For subjects at risk, it would be useful to dedicate a stress management program before beginning a dietary restriction.

  6. Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization.

    Science.gov (United States)

    Ezzat, Ali; Zhao, Peilin; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

    2017-01-01

    Experimental determination of drug-target interactions is expensive and time-consuming. Therefore, there is a continuous demand for more accurate predictions of interactions using computational techniques. Algorithms have been devised to infer novel interactions on a global scale where the input to these algorithms is a drug-target network (i.e., a bipartite graph where edges connect pairs of drugs and targets that are known to interact). However, these algorithms had difficulty predicting interactions involving new drugs or targets for which there are no known interactions (i.e., "orphan" nodes in the network). Since data usually lie on or near to low-dimensional non-linear manifolds, we propose two matrix factorization methods that use graph regularization in order to learn such manifolds. In addition, considering that many of the non-occurring edges in the network are actually unknown or missing cases, we developed a preprocessing step to enhance predictions in the "new drug" and "new target" cases by adding edges with intermediate interaction likelihood scores. In our cross validation experiments, our methods achieved better results than three other state-of-the-art methods in most cases. Finally, we simulated some "new drug" and "new target" cases and found that GRMF predicted the left-out interactions reasonably well.

  7. Potential predictive factors of positive prostate biopsy in the Chinese ...

    African Journals Online (AJOL)

    Yomi

    2012-01-16

    Jan 16, 2012 ... Therefore, it might be inappropriate that we apply these western models to the. Chinese population that has a lower incidence of PCa. Therefore, this retrospective study aimed to determine predictive factors for a positive prostate biopsy in Chinese men. Our ultimate goal is to develop a simple model for ...

  8. Factors associated with therapeutic inertia in hypertension: validation of a predictive model.

    Science.gov (United States)

    Redón, Josep; Coca, Antonio; Lázaro, Pablo; Aguilar, Ma Dolores; Cabañas, Mercedes; Gil, Natividad; Sánchez-Zamorano, Miguel Angel; Aranda, Pedro

    2010-08-01

    To study factors associated with therapeutic inertia in treating hypertension and to develop a predictive model to estimate the probability of therapeutic inertia in a given medical consultation, based on variables related to the consultation, patient, physician, clinical characteristics, and level of care. National, multicentre, observational, cross-sectional study in primary care and specialist (hospital) physicians who each completed a questionnaire on therapeutic inertia, provided professional data and collected clinical data on four patients. Therapeutic inertia was defined as a consultation in which treatment change was indicated (i.e., SBP >or= 140 or DBP >or= 90 mmHg in all patients; SBP >or= 130 or DBP >or= 80 in patients with diabetes or stroke), but did not occur. A predictive model was constructed and validated according to the factors associated with therapeutic inertia. Data were collected on 2595 patients and 13,792 visits. Therapeutic inertia occurred in 7546 (75%) of the 10,041 consultations in which treatment change was indicated. Factors associated with therapeutic inertia were primary care setting, male sex, older age, SPB and/or DBP values close to normal, treatment with more than one antihypertensive drug, treatment with an ARB II, and more than six visits/year. Physician characteristics did not weigh heavily in the association. The predictive model was valid internally and externally, with acceptable calibration, discrimination and reproducibility, and explained one-third of the variability in therapeutic inertia. Although therapeutic inertia is frequent in the management of hypertension, the factors explaining it are not completely clear. Whereas some aspects of the consultations were associated with therapeutic inertia, physician characteristics were not a decisive factor.

  9. Identifying Coronary Artery Disease in Asymptomatic Middle-Aged Sportsmen: The Additional Value of Pulse Wave Velocity.

    Directory of Open Access Journals (Sweden)

    Thijs L Braber

    Full Text Available Cardiovascular screening may benefit middle-aged sportsmen, as coronary artery disease (CAD is the main cause of exercise-related sudden cardiac death. Arterial stiffness, as measured by pulse wave velocity (PWV, may help identify sportsmen with subclinical CAD. We examined the additional value of PWV measurements to traditional CAD risk factors for identifying CAD.From the Measuring Athlete's Risk of Cardiovascular events (MARC cohort of asymptomatic, middle-aged sportsmen who underwent low-dose Cardiac CT (CCT after routine sports medical examination (SME, 193 consecutive sportsmen (aged 55 ± 6.6 years were included with additional PWV measurements before CCT. Sensitivity, specificity and predictive values of PWV values (>8.3 and >7.5 m/s assessed by Arteriograph were used to identify CAD (coronary artery calcium scoring ≥ 100 Agatston Units or coronary CT angiography luminal stenosis ≥ 50% and to assess the additional diagnostic value of PWV to established cardiovascular risk factors.Forty-seven sportsmen (24% had CAD on CCT. They were older (58.9 vs. 53.8 years, p8.3m/s respectively >7.5 m/s sensitivity to detect CAD on CT was 43% and 74%, specificity 69% and 45%, positive predictive value 31% and 30%, and negative predictive value 79% and 84%. Adding PWV to traditional risk factor models did not change the area under the curve (from 0.78 (95% CI = 0.709-0.848 to AUC 0.78 (95% CI 0.710-0.848, p = 0.99 for prediction of CAD on CCT.Limited additional value was found for PWV on top of established risk factors to identify CAD. PWV might still have a role to identify CAD in middle-aged sportsmen if risk factors such as cholesterol are unknown.

  10. Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews

    OpenAIRE

    Cheng, Zhiyong; Ding, Ying; Zhu, Lei; Kankanhalli, Mohan

    2018-01-01

    Although latent factor models (e.g., matrix factorization) achieve good accuracy in rating prediction, they suffer from several problems including cold-start, non-transparency, and suboptimal recommendation for local users or items. In this paper, we employ textual review information with ratings to tackle these limitations. Firstly, we apply a proposed aspect-aware topic model (ATM) on the review text to model user preferences and item features from different aspects, and estimate the aspect...

  11. Identify and Classify Critical Success Factor of Agile Software Development Methodology Using Mind Map

    OpenAIRE

    Tasneem Abd El Hameed; Mahmoud Abd EL Latif; Sherif Kholief

    2016-01-01

    Selecting the right method, right personnel and right practices, and applying them adequately, determine the success of software development. In this paper, a qualitative study is carried out among the critical factors of success from previous studies. The factors of success match with their relative principles to illustrate the most valuable factor for agile approach success, this paper also prove that the twelve principles poorly identified for few factors resulting from qualitative and qua...

  12. Link Prediction via Convex Nonnegative Matrix Factorization on Multiscale Blocks

    Directory of Open Access Journals (Sweden)

    Enming Dong

    2014-01-01

    Full Text Available Low rank matrices approximations have been used in link prediction for networks, which are usually global optimal methods and lack of using the local information. The block structure is a significant local feature of matrices: entities in the same block have similar values, which implies that links are more likely to be found within dense blocks. We use this insight to give a probabilistic latent variable model for finding missing links by convex nonnegative matrix factorization with block detection. The experiments show that this method gives better prediction accuracy than original method alone. Different from the original low rank matrices approximations methods for link prediction, the sparseness of solutions is in accord with the sparse property for most real complex networks. Scaling to massive size network, we use the block information mapping matrices onto distributed architectures and give a divide-and-conquer prediction method. The experiments show that it gives better results than common neighbors method when the networks have a large number of missing links.

  13. Prediction of chronic post-operative pain: pre-operative DNIC testing identifies patients at risk.

    Science.gov (United States)

    Yarnitsky, David; Crispel, Yonathan; Eisenberg, Elon; Granovsky, Yelena; Ben-Nun, Alon; Sprecher, Elliot; Best, Lael-Anson; Granot, Michal

    2008-08-15

    Surgical and medical procedures, mainly those associated with nerve injuries, may lead to chronic persistent pain. Currently, one cannot predict which patients undergoing such procedures are 'at risk' to develop chronic pain. We hypothesized that the endogenous analgesia system is key to determining the pattern of handling noxious events, and therefore testing diffuse noxious inhibitory control (DNIC) will predict susceptibility to develop chronic post-thoracotomy pain (CPTP). Pre-operative psychophysical tests, including DNIC assessment (pain reduction during exposure to another noxious stimulus at remote body area), were conducted in 62 patients, who were followed 29.0+/-16.9 weeks after thoracotomy. Logistic regression revealed that pre-operatively assessed DNIC efficiency and acute post-operative pain intensity were two independent predictors for CPTP. Efficient DNIC predicted lower risk of CPTP, with OR 0.52 (0.33-0.77 95% CI, p=0.0024), i.e., a 10-point numerical pain scale (NPS) reduction halves the chance to develop chronic pain. Higher acute pain intensity indicated OR of 1.80 (1.28-2.77, p=0.0024) predicting nearly a double chance to develop chronic pain for each 10-point increase. The other psychophysical measures, pain thresholds and supra-threshold pain magnitudes, did not predict CPTP. For prediction of acute post-operative pain intensity, DNIC efficiency was not found significant. Effectiveness of the endogenous analgesia system obtained at a pain-free state, therefore, seems to reflect the individual's ability to tackle noxious events, identifying patients 'at risk' to develop post-intervention chronic pain. Applying this diagnostic approach before procedures that might generate pain may allow individually tailored pain prevention and management, which may substantially reduce suffering.

  14. A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize.

    Directory of Open Access Journals (Sweden)

    Matt eGeisler

    2015-06-01

    Full Text Available Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6,004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize.

  15. Identifying Social Satisfaction from Social Media

    OpenAIRE

    Bai, Shuotian; Gao, Rui; Hao, Bibo; Yuan, Sha; Zhu, Tingshao

    2014-01-01

    We demonstrate the critical need to identify social situation and instability factors by acquiring public social satisfaction in this research. However, subject to the large amount of manual work cost in subject recruitment and data processing, conventional self-reported method cannot be implemented in real time or applied in large scale investigation. To solve the problem, this paper proposed an approach to predict users' social satisfaction, especially for the economy-related satisfaction b...

  16. Serum Macrophage Migration Inhibitory Factor in the Prediction of Preterm Delivery

    DEFF Research Database (Denmark)

    Pearce, Brad; Garvin, Sicily; Grove, Jakob

    2008-01-01

    Objective: Macrophage migration inhibitory factor (MIF) is a soluble mediator that helps govern the interaction between cytokines and stress hormones (e.g. cortisol). We determined if maternal MIF levels predicted subsequent preterm delivery (PTD). Study Design: A nested case-control study...

  17. What Predicts Exercise Maintenance and Well-Being? Examining The Influence of Health-Related Psychographic Factors and Social Media Communication.

    Science.gov (United States)

    Zhou, Xin; Krishnan, Archana

    2018-01-26

    Habitual exercising is an important precursor to both physical and psychological well-being. There is, thus, a strong interest in identifying key factors that can best motivate individuals to sustain regular exercise regimen. In addition to the importance of psychographic factors, social media use may act as external motivator by allowing users to interact and communicate about exercise. In this study, we examined the influence of health consciousness, health-oriented beliefs, intrinsic motivation, as willingness to communicate about health on social media, social media activity on exercise, and online social support on exercise maintenance and well-being on a sample of 532 American adults. Employing structural equation modeling, we found that health-oriented beliefs mediated the effect of health consciousness on intrinsic motivation which in turn was a significant predictor of exercise maintenance. Exercise maintenance significantly predicted both physical and psychological well-being. Extrinsic motivators, as measured by willingness to communicate about health on social media, social media activity on exercise, and online social support did not however significantly influence exercise maintenance. These findings have implications for the design and implementation of exercise-promoting interventions by identifying underlying factors that influence exercise maintenance.

  18. Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

    Science.gov (United States)

    Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

    2017-07-01

    The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

  19. Identifying risk factors for PTSD in women seeking medical help after rape

    OpenAIRE

    Möller, Anna Tiihonen; Bäckström, Torbjörn; Söndergaard, Hans Peter; Helström, Lotti

    2014-01-01

    Objectives: Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD) among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD. Methods: Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at S...

  20. Baseline placental growth factor levels for the prediction of benefit from early aspirin prophylaxis for preeclampsia prevention.

    Science.gov (United States)

    Moore, Gaea S; Allshouse, Amanda A; Winn, Virginia D; Galan, Henry L; Heyborne, Kent D

    2015-10-01

    Placental growth factor (PlGF) levels early in pregnancy are lower in women who ultimately develop preeclampsia. Early initiation of low-dose aspirin reduces preeclampsia risk in some high risk women. We hypothesized that low PlGF levels may identify women at increased risk for preeclampsia who would benefit from aspirin. Secondary analysis of the MFMU High-Risk Aspirin study including singleton pregnancies randomized to aspirin 60mg/d (n=102) or placebo (n=72), with PlGF collected at 13w 0d-16w 6d. Within the placebo group, we estimated the probability of preeclampsia by PlGF level using logistic regression analysis, then determined a potential PlGF threshold for preeclampsia prediction using ROC analysis. We performed logistic regression modeling for potential confounders. ROC analysis indicated 87.71pg/ml as the threshold between high and low PlGF for preeclampsia-prediction. Within the placebo group high PlGF weakly predicted preeclampsia (AUC 0.653, sensitivity/specificity 63%/66%). We noted a 2.6-fold reduction in preeclampsia with aspirin in the high-PlGF group (12.15% aspirin vs 32.14% placebo, p=0.057), but no significant differences in preeclampsia in the low PlGF group (21.74% vs 15.91%, p=0.445). Unlike other studies, we found that high rather than low PlGF levels were associated with an increased preeclampsia risk. Low PlGF neither identified women at increased risk of preeclampsia nor women who benefitted from aspirin. Further research is needed to determine whether aspirin is beneficial in women with high PlGF, and whether the paradigm linking low PlGF and preeclampsia needs to be reevaluated. High-risk women with low baseline PlGF, a risk factor for preeclampsia, did not benefit from early initiation of low-dose aspirin. Copyright © 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

  1. Prediction of response to PPI therapy and factors influencing treatment outcome in patients with GORD: a prospective pragmatic trial using pantoprazole

    Directory of Open Access Journals (Sweden)

    Tholen Anne

    2011-05-01

    Full Text Available Abstract Background Management of patients with gastro-oesophageal reflux disease (GORD can be assisted by information predicting the likely response to proton pump inhibitor (PPI treatment. The aim was to undertake a study of GORD patients designed to approximate ordinary clinical practice that would identify patient characteristics predicting symptomatic response to pantoprazole treatment. Methods 1888 patients with symptoms of GORD were enrolled in a multicentre, multinational, prospective, open study of 8 weeks pantoprazole treatment, 40 mg daily. Response was assessed by using the ReQuest™ questionnaire, by the investigator making conventional clinical enquiry and by asking patients about their satisfaction with symptom control. Factors including pre-treatment oesophagitis, gender, age, body mass index (BMI, Helicobacter pylori status, anxiety and depression, and concurrent IBS symptoms were examined using logistic regression to determine if they were related to response, judged from the ReQuest™-GI score. Results Poorer treatment responses were associated with non-erosive reflux disease, female gender, lower BMI, anxiety and concurrent irritable bowel syndrome symptoms before treatment. No association was found with age, Helicobacter pylori status or oesophagitis grade. Some reflux-related symptoms were still present in 14% of patients who declared themselves 'well-satisfied' with their symptom control. Conclusions Some readily identifiable features help to predict symptomatic responses to a PPI and consequently may help in managing patient expectation. ClinicalTrial.gov identifier: NCT00312806.

  2. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Malnutrition: a highly predictive risk factor of short-term mortality in elderly presenting to the emergency department.

    Science.gov (United States)

    Gentile, S; Lacroix, O; Durand, A C; Cretel, E; Alazia, M; Sambuc, R; Bonin-Guillaume, S

    2013-04-01

    To identify independent risk factors of mortality among elderly patients in the 3 months after their visit (T3) to an emergency department (ED). Prospective cohort study. University hospital ED in an urban setting in France. One hundred seventy-three patients aged 75 and older were admitted to the ED over two weeks (18.7% of the 924 ED visits). Of these, 164 patients (94.8%) were included in our study, and 157 (95.7%) of them were followed three months after their ED visit. During the inclusion period (T0), a standardized questionnaire was used to collect data on socio-demographic and environmental characteristics, ED visit circumstances, medical conditions and geriatric assessment including functional and nutritional status. Three months after the ED visits (T3), patients or their caregivers were interviewed to collect data on vital status, and ED return or hospitalization. Among the 157 patients followed at T3, 14.6% had died, 19.9% had repeated ED visits, and 63.1% had been hospitalized. The two independent predictive factors for mortality within the 3 months after ED visit were: malnutrition screened by the Mini Nutritional Assessment short-form (MNA-SF) (OR=20.2; 95% CI: 5.74-71.35; pMalnutrition is the strongest independent risk factor predicting short-term mortality in elderly patients visiting the ED, and it was easily detected by MNA-SF and supported from the ED visit.

  4. Identifying the factors underlying discontinuation of triptans.

    Science.gov (United States)

    Wells, Rebecca E; Markowitz, Shira Y; Baron, Eric P; Hentz, Joseph G; Kalidas, Kavita; Mathew, Paul G; Halker, Rashmi; Dodick, David W; Schwedt, Todd J

    2014-02-01

    To identify factors associated with triptan discontinuation among migraine patients. It is unclear why many migraine patients who are prescribed triptans discontinue this treatment. This study investigated correlates of triptan discontinuation with a focus on potentially modifiable factors to improve compliance. This multicenter cross-sectional survey (n = 276) was performed at US tertiary care headache clinics. Headache fellows who were members of the American Headache Society Headache Fellows Research Consortium recruited episodic and chronic migraine patients who were current triptan users (use within prior 3 months and for ≥1 year) or past triptan users (no use within 6 months; prior use within 2 years). Univariate analyses were first completed to compare current triptan users to past users for: migraine characteristics, other migraine treatments, triptan education, triptan efficacy, triptan side effects, type of prescribing provider, Migraine Disability Assessment (MIDAS) scores and Beck Depression Inventory (BDI) scores. Then, a multivariable logistic regression model was selected from all possible combinations of predictor variables to determine the factors that best correlated with triptan discontinuation. Compared with those still using triptans (n = 207), those who had discontinued use (n = 69) had higher rates of medication overuse (30 vs. 18%, P = .04) and were more likely to have ever used opioids for migraine treatment (57 vs. 38%, P = .006) as well as higher MIDAS (mean 63 vs. 37, P = .001) and BDI scores (mean 10.4 vs. 7.4, P = .009). Compared with discontinued users, current triptan users were more likely to have had their triptan prescribed by a specialist (neurologist, headache specialist, or pain specialist) (74 vs. 54%, P = .002) and were more likely to report headache resolution (53 vs. 14%, P  24 (2.6, [1.5, 4.6]), BDI >4 (2.5, [1.4, 4.5]), and a history of ever using opioids for migraine therapy (2.2, [1

  5. Higher neonatal growth rate and body condition score at 7 months are predictive factors of obesity in adult female Beagle dogs.

    Science.gov (United States)

    Leclerc, Lucie; Thorin, Chantal; Flanagan, John; Biourge, Vincent; Serisier, Samuel; Nguyen, Patrick

    2017-04-13

    The risks during early growth on becoming overweight in adulthood are widely studied in humans. However, early-life predictive factors for canine adult overweight and obesity have not yet been studied. To identify factors that may help explain the development of overweight and obesity at adulthood in dogs, a longitudinal study of 2 years was conducted in 24 female Beagle dogs of the same age, sexual status, and raised under identical environmental conditions. By means of a hierarchical classification on principal components with the following quantitative values: fat-free mass (FFM), percentage fat mass and pelvic circumference at 2 years of age, three groups of dogs were established and were nominally named: ideal weight (IW, n = 9), slightly overweight (OW1, n = 6) and overweight (OW2, n = 9). With the aim of identifying predictive factors of development of obesity at adulthood parental characteristics, growth pattern, energy balance and plasma factors were analysed by logistic regression analysis. At 24 months, the group compositions were in line with the body condition scores (BCS 1-9) values of the IW (5 or 6/9), the OW1 (6/9) and the OW2 (7 or 8/9) groups. Logistic regression analysis permitted the identification of neonatal growth rate during the first 2 weeks of life (GR 2W ) and BCS at 7 months as predictors for the development of obesity at adulthood. Seventy percent of dogs with either GR 2W >125% or with BCS > 6/9 at 7 months belonged to the OW2 group. Results from energy intake and expenditure, corrected for FFM, showed that there was a greater positive energy imbalance between 7 and 10 months for the OW2, compared to the IW group. This study expands the understanding of previously reported risk factors for being overweight or obese in dogs, establishing that (i) 15 out of 24 of the studied dogs became overweight and (ii) GR 2W and BCS at 7 months of age could be used as predictive factors as overweight adult dogs in the OW2

  6. Predictive model of thrombospondin-1 and vascular endothelial growth factor in breast tumor tissue.

    Science.gov (United States)

    Rohrs, Jennifer A; Sulistio, Christopher D; Finley, Stacey D

    2016-01-01

    Angiogenesis, the formation of new blood capillaries from pre-existing vessels, is a hallmark of cancer. Thus far, strategies for reducing tumor angiogenesis have focused on inhibiting pro-angiogenic factors, while less is known about the therapeutic effects of mimicking the actions of angiogenesis inhibitors. Thrombospondin-1 (TSP1) is an important endogenous inhibitor of angiogenesis that has been investigated as an anti-angiogenic agent. TSP1 impedes the growth of new blood vessels in many ways, including crosstalk with pro-angiogenic factors. Due to the complexity of TSP1 signaling, a predictive systems biology model would provide quantitative understanding of the angiogenic balance in tumor tissue. Therefore, we have developed a molecular-detailed, mechanistic model of TSP1 and vascular endothelial growth factor (VEGF), a promoter of angiogenesis, in breast tumor tissue. The model predicts the distribution of the angiogenic factors in tumor tissue, revealing that TSP1 is primarily in an inactive, cleaved form due to the action of proteases, rather than bound to its cellular receptors or to VEGF. The model also predicts the effects of enhancing TSP1's interactions with its receptors and with VEGF. To provide additional predictions that can guide the development of new anti-angiogenic drugs, we simulate administration of exogenous TSP1 mimetics that bind specific targets. The model predicts that the CD47-binding TSP1 mimetic dramatically decreases the ratio of receptor-bound VEGF to receptor-bound TSP1, in favor of anti-angiogenesis. Thus, we have established a model that provides a quantitative framework to study the response to TSP1 mimetics.

  7. Predicting outcome of acute kidney transplant rejection using

    NARCIS (Netherlands)

    Rekers, Niels Vincent

    2014-01-01

    Acute kidney transplant rejection is an important risk factors for adverse graft outcome. Once diagnosed, it remains difficult to predict the risk of graft loss and the response to anti-rejection treatment. The aim of this thesis was to identify biomarkers during acute rejection, which predict the

  8. Predicting incursion of plant invaders into Kruger National Park, South Africa: the interplay of general drivers and species-specific factors.

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    Vojtěch Jarošík

    Full Text Available BACKGROUND: Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here we explore the similarity between determinants of incursions identified by the general model based on a multispecies assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant species in 1.0×1.5 km segments along the border of the park as a function of environmental characteristics from outside and inside the KNP boundary, using two data-mining techniques: classification trees and random forests. PRINCIPAL FINDINGS: The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park. CONCLUSIONS: The predictors from the outside and inside of the park are complementary, and are approximately equally reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the cost-effectiveness of management, to locate invasive plants and target them for

  9. Predicting Incursion of Plant Invaders into Kruger National Park, South Africa: The Interplay of General Drivers and Species-Specific Factors

    Science.gov (United States)

    Jarošík, Vojtěch; Pyšek, Petr; Foxcroft, Llewellyn C.; Richardson, David M.; Rouget, Mathieu; MacFadyen, Sandra

    2011-01-01

    Background Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here we explore the similarity between determinants of incursions identified by the general model based on a multispecies assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant species in 1.0×1.5 km segments along the border of the park as a function of environmental characteristics from outside and inside the KNP boundary, using two data-mining techniques: classification trees and random forests. Principal Findings The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park. Conclusions The predictors from the outside and inside of the park are complementary, and are approximately equally reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the cost-effectiveness of management, to locate invasive plants and target them for eradication. PMID:22194893

  10. Risk Factors in Preschool Children for Predicting Asthma During the Preschool Age and the Early School Age: a Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Bao, Yixia; Chen, Zhimin; Liu, Enmei; Xiang, Li; Zhao, Deyu; Hong, Jianguo

    2017-11-18

    The aim of this study was to identify risk factors of asthma among children asthma during the preschool age and early school age (≤ 10 years of age). MEDLINE, Cochrane, EMBASE, and Google Scholar databases were searched until June 30, 2017. Prospective or retrospective cohort and case-control studies were included. Studies had to have evaluated risk factors or a predictive model for developing asthma in children ≤ 6 years of age or persistent asthma in early school age. A total of 17 studies were included in the analysis. Factors associated with developing asthma in children ≤ 10 years of age (both pre-school and early school age) included male gender (pooled OR = 1.70, P asthma (pooled OR = 2.20, P asthma in early school age (pooled OR = 1.51, P = 0.030 and pooled OR = 2.59, P asthma predictive models (e.g., API, PIAMA, PAPS) had relatively low sensitivity (range, 21% to 71.4%) but high specificity (range, 69% to 98%). The study found that male gender, exposure to smoke, atopic dermatitis, family history of asthma, history of wheezing, and serum IgE level ≥ 60 kU/l or having specific IgE were significantly associated with developing asthma by either preschool or early school age. Asthma predictive models can be developed by those risk factors.

  11. Identifying and Assessing Gaps in Subseasonal to Seasonal Prediction Skill using the North American Multi-model Ensemble

    Science.gov (United States)

    Pegion, K.; DelSole, T. M.; Becker, E.; Cicerone, T.

    2016-12-01

    Predictability represents the upper limit of prediction skill if we had an infinite member ensemble and a perfect model. It is an intrinsic limit of the climate system associated with the chaotic nature of the atmosphere. Producing a forecast system that can make predictions very near to this limit is the ultimate goal of forecast system development. Estimates of predictability together with calculations of current prediction skill are often used to define the gaps in our prediction capabilities on subseasonal to seasonal timescales and to inform the scientific issues that must be addressed to build the next forecast system. Quantification of the predictability is also important for providing a scientific basis for relaying to stakeholders what kind of climate information can be provided to inform decision-making and what kind of information is not possible given the intrinsic predictability of the climate system. One challenge with predictability estimates is that different prediction systems can give different estimates of the upper limit of skill. How do we know which estimate of predictability is most representative of the true predictability of the climate system? Previous studies have used the spread-error relationship and the autocorrelation to evaluate the fidelity of the signal and noise estimates. Using a multi-model ensemble prediction system, we can quantify whether these metrics accurately indicate an individual model's ability to properly estimate the signal, noise, and predictability. We use this information to identify the best estimates of predictability for 2-meter temperature, precipitation, and sea surface temperature from the North American Multi-model Ensemble and compare with current skill to indicate the regions with potential for improving skill.

  12. Tombusvirus-yeast interactions identify conserved cell-intrinsic viral restriction factors

    Directory of Open Access Journals (Sweden)

    Zsuzsanna eSasvari

    2014-08-01

    Full Text Available To combat viral infections, plants possess innate and adaptive immune pathways, such as RNA silencing, R gene and recessive gene-mediated resistance mechanisms. However, it is likely that additional cell-intrinsic restriction factors (CIRF are also involved in limiting plant virus replication. This review discusses novel CIRFs with antiviral functions, many of them RNA-binding proteins or affecting the RNA binding activities of viral replication proteins. The CIRFs against tombusviruses have been identified in yeast (Saccharomyces cerevisiae, which is developed as an advanced model organism. Grouping of the identified CIRFs based on their known cellular functions and subcellular localization in yeast reveals that TBSV replication is limited by a wide variety of host gene functions. Yeast proteins with the highest connectivity in the network map include the well-characterized Xrn1p 5’-3’ exoribonuclease, Act1p actin protein and Cse4p centromere protein. The protein network map also reveals an important interplay between the pro-viral Hsp70 cellular chaperone and the antiviral co-chaperones, and possibly key roles for the ribosomal or ribosome-associated factors. We discuss the antiviral functions of selected CIRFs, such as the RNA binding nucleolin, ribonucleases, WW-domain proteins, single- and multi-domain cyclophilins, TPR-domain co-chaperones and cellular ion pumps. These restriction factors frequently target the RNA-binding region in the viral replication proteins, thus interfering with the recruitment of the viral RNA for replication and the assembly of the membrane-bound viral replicase. Although many of the characterized CIRFs act directly against TBSV, we propose that the TPR-domain co-chaperones function as guardians of the cellular Hsp70 chaperone system, which is subverted efficiently by TBSV for viral replicase assembly in the absence of the TPR-domain co-chaperones.

  13. Incremental validity of positive orientation: predictive efficiency beyond the five-factor model

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    Łukasz Roland Miciuk

    2016-05-01

    Full Text Available Background The relation of positive orientation (a basic predisposition to think positively of oneself, one’s life and one’s future and personality traits is still disputable. The purpose of the described research was to verify the hypothesis that positive orientation has predictive efficiency beyond the five-factor model. Participants and procedure One hundred and thirty participants (at the mean age M = 24.84 completed the following questionnaires: the Self-Esteem Scale (SES, the Satisfaction with Life Scale (SWLS, the Life Orientation Test-Revised (LOT-R, the Positivity Scale (P-SCALE, the NEO Five Factor Inventory (NEO-FFI, the Self-Concept Clarity Scale (SCC, the Generalized Self-Efficacy Scale (GSES and the Life Engagement Test (LET. Results The introduction of positive orientation as an additional predictor in the second step of regression analyses led to better prediction of the following variables: purpose in life, self-concept clarity and generalized self-efficacy. This effect was the strongest for predicting purpose in life (i.e. 14% increment of the explained variance. Conclusions The results confirmed our hypothesis that positive orientation can be characterized by incremental validity – its inclusion in the regression model (in addition to the five main factors of personality increases the amount of explained variance. These findings may provide further evidence for the legitimacy of measuring positive orientation and personality traits separately.

  14. MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

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    Wasserman Wyeth W

    2011-03-01

    Full Text Available Abstract Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs, microRNAs (miRNAs and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs. Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL. In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT, an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http

  15. Personality and Defense Styles: Clinical Specificities and Predictive Factors of Alcohol Use Disorder in Women.

    Science.gov (United States)

    Ribadier, Aurélien; Dorard, Géraldine; Varescon, Isabelle

    2016-01-01

    This study investigated personality traits and defense styles in order to determine clinical specificities and predictive factors of alcohol use disorders (AUDs) in women. A female sample, composed of AUD outpatients (n = 48) and a control group (n = 50), completed a sociodemographic self-report and questionnaires assessing personality traits (BFI), defense mechanisms and defense styles (DSQ-40). Comparative and correlational analyses, as well as univariate and multivariate logistic regressions, were performed. AUD women presented with higher neuroticism and lower extraversion and conscientiousness. They used less mature and more neurotic and immature defense styles than the control group. Concerning personality traits, high neuroticism and lower conscientiousness were predictive of AUD, as well as low mature, high neurotic, and immature defense styles. Including personality traits and defense styles in a logistic model, high neuroticism was the only AUD predictive factor. AUD women presented clinical specificities and predictive factors in personality traits and defense styles that must be taken into account in AUD studies. Implications for specific treatment for women are discussed.

  16. Progression of diffuse esophageal spasm to achalasia: incidence and predictive factors.

    Science.gov (United States)

    Fontes, L H S; Herbella, F A M; Rodriguez, T N; Trivino, T; Farah, J F M

    2013-07-01

    The progression of certain primary esophageal motor disorders to achalasia has been documented; however, the true incidence of this decay is still elusive. This study aims to evaluate: (i) the incidence of the progression of diffuse esophageal spasm to achalasia, and (ii) predictive factors to this progression. Thirty-five patients (mean age 53 years, 80% females) with a manometric picture of diffuse esophageal spasm were followed for at least 1 year. Patients with gastroesophageal reflux disease confirmed by pH monitoring or systemic diseases that may affect esophageal motility were excluded. Esophageal manometry was repeated in all patients. Five (14%) of the patients progressed to achalasia at a mean follow-up of 2.1 (range 1-4) years. Demographic characteristics were not predictive of transition to achalasia, while dysphagia (P= 0.005) as the main symptom and the wave amplitude of simultaneous waves less than 50 mmHg (P= 0.003) were statistically significant. In conclusion, the transition of diffuse esophageal spasm to achalasia is not frequent at a 2-year follow-up. Dysphagia and simultaneous waves with low amplitude are predictive factors for this degeneration. © 2012 Copyright the Authors. Journal compilation © 2012, Wiley Periodicals, Inc. and the International Society for Diseases of the Esophagus.

  17. Blood loss predictive factors and transfusion practice during percutaneous nephrolithotomy of kidney stones: a prospective study [version 1; referees: 1 approved, 2 approved with reservations

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    Firtantyo Adi Syahputra

    2016-06-01

    Full Text Available Objectives Bleeding is the most common complication of percutaneous nephrolithotomy (PCNL. Injudicious transfusion is frequently performed in current practice, even though it is not always needed. This study aimed to identify the predictive factors of blood loss in the PCNL procedure and evaluate the perioperative transfusion practice.   Methods A prospective study of PCNL was randomly performed by two consultants of endo-urology at our institution. The inclusion criteria were adults with kidney pelvic stones >20 mm or stone in inferior calyx >10 mm or staghorn stone. Those with coagulopathy, under anti-coagulant treatment or open conversion were excluded. A full blood count was taken at baseline and during 12, 24, 36, 72-hours post-operatively. Factors such as stone burden, sex, body surface area, shifting of hematocrit level and amount of blood transfused were analyzed statistically using line regression to identify the predictive factors of total blood loss (TBL.   Results Eighty-five patients were enrolled in this study. Mean TBL was 560.92 ± 428.43 mL for both endo-urology surgeons. Stone burden was the most influential factor for TBL (p=0.037. Our results revealed that TBL (mL = -153.379 + 0.229 × stone burden (mm2 + 0.203 x baseline serum hematocrit (%; thus considerably predicted the need for blood transfusion. A total of 87.1% patients did not receive perioperative transfusion, 3.5% received intra-operative transfusion, 7.1% received post-operative transfusion, 23% had both intra and post-operative transfusion, resulting in a cross-matched transfusion ratio of 7.72. Mean perioperative blood transfused was 356.00 ± 145.88 mL.

  18. A predictive score for retinopathy of prematurity by using clinical risk factors and serum insulin-like growth factor-1 levels

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    Yeşim Coşkun

    2017-11-01

    Full Text Available AIM: To detect the impact of insulin-like growth factor-1 (IGF-1 and other risk factors for the early prediction of retinopathy of prematurity (ROP and to establish a scoring system for ROP prediction by using clinical criteria and serum IGF-1 levels. METHODS: The study was conducted with 127 preterm infants. IGF-1 levels in the 1st day of life, 1st, 2nd, 3rd and 4th week of life was analyzed. The score was established after logistic regression analysis, considering the impact of each variable on the occurrences of any stage ROP. A validation cohort containing 107 preterm infants was included in the study and the predictive ability of ROP score was calculated. RESULTS: Birth weights (BW, gestational weeks (GW and the prevalence of breast milk consumption were lower, respiratory distress syndrome (RDS, bronchopulmonary dysplasia (BPD and necrotizing enterocolitis (NEC were more frequent, the duration of mechanical ventilation and oxygen supplementation was longer in patients with ROP (P<0.05. Initial serum IGF-1 levels tended to be lower in newborns who developed ROP. Logistic regression analysis revealed that low BW (<1250 g, presence of intraventricular hemorrhage (IVH and formula feeding increased the risk of ROP. Afterwards, the scoring system was validated on 107 infants. The negative predictive values of a score less than 4 were 84.3%, 74.7% and 79.8% while positive predictive values were 76.3%, 65.5% and 71.6% respectively. CONCLUSION: In addition to BW <1250 g and IVH, formula consumption was detected as a risk factor for the development of ROP. Breastfeeding is important for prevention of ROP in preterm infants.

  19. Induction of labour: clinical predictive factors for success and failure.

    Science.gov (United States)

    Batinelli, Laura; Serafini, Andrea; Nante, Nicola; Petraglia, Felice; Severi, Filiberto Maria; Messina, Gabriele

    2018-04-01

    Induction of labour (IOL) is a widely-used practice in obstetrics. Our aim was to evaluate predictors of vaginal delivery in postdate pregnancies induced with prostaglandins. We conducted a retrospective cross-sectional study with analytic component. A total of 145 women, admitted for IOL after the 41st week of gestation, were induced with a vaginal pessary releasing prostaglandins. Type of delivery, whether vaginal or caesarean, was the outcome. Several maternal and foetal variables were investigated. The Kaplan-Maier curves, monovariate and a multivariate logistic regression were carried out. In our population, 80.7% of women had vaginal delivery after the induction. Multiparity and a high Bishop score at the beginning of the IOL were protective factors for a vaginal delivery (respectively OR 0.16, p = .028 and OR 0.62, p = .034) while age >35 years, and the foetal birth weight >3500 g at the birth, resulted in being risk factors for caesarean section (respectively OR 4.20, p = .006 and OR 3.63, p = .013). IMPACT STATEMENT What is already known on this subject: Induction of labour (IOL) is a widely used practice in obstetrics. Scientific literature shows several predictors of successful induction, although there is no unanimity except for 'multiparity' and 'favourable Bishop score' which are associated with positive outcome of the induction. The main difficulty in finding other predictive factors is the heterogeneity of this field (different local protocols in each hospital, type of induction, populations and outcomes chosen in each study). In addition to that, populations are not always comparable due to the different gestation. For this reason, we decided to select a specific population of women, such as low risk postterm pregnancies induced with prostaglandins, in order to detect possible predictive factors for the success of the IOL for women with uncomplicated pregnancies. What the results of this study add: Our study agrees with existing

  20. Predicting Ranger Assessment and Selection Program 1 Success and Optimizing Class Composition

    Science.gov (United States)

    2017-06-01

    Healthcare Specialist) 149 150 68X ( Mental Health Specialist) 1 74 74D (Chemical Operations Specialist) 15 15 88 88M (Motor Transport Operator) 27 27 89...regression and partition tree models to identify significant factors that contribute to a candidate’s success at RASP1 and predict graduation rates. We...tree models to identify significant factors that contribute to a candidate’s success at RASP1 and predict graduation rates. We use an integer linear

  1. Identifying the Prognosis Factors in Death after Liver Transplantation via Adaptive LASSO in Iran

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    Hadi Raeisi Shahraki

    2016-01-01

    Full Text Available Despite the widespread use of liver transplantation as a routine therapy in liver diseases, the effective factors on its outcomes are still controversial. This study attempted to identify the most effective factors on death after liver transplantation. For this purpose, modified least absolute shrinkage and selection operator (LASSO, called Adaptive LASSO, was utilized. One of the best advantages of this method is considering high number of factors. Therefore, in a historical cohort study from 2008 to 2013, the clinical findings of 680 patients undergoing liver transplant surgery were considered. Ridge and Adaptive LASSO regression methods were then implemented to identify the most effective factors on death. To compare the performance of these two models, receiver operating characteristic (ROC curve was used. According to the results, 12 factors in Ridge regression and 9 ones in Adaptive LASSO regression were significant. The area under the ROC curve (AUC of Adaptive LASSO was equal to 89% (95% CI: 86%–91%, which was significantly greater than Ridge regression (64%, 95% CI: 61%–68% (p<0.001. As a conclusion, the significant factors and the performance criteria revealed the superiority of Adaptive LASSO method as a penalized model versus traditional regression model in the present study.

  2. Semen parameters can be predicted from environmental factors and lifestyle using artificial intelligence methods.

    Science.gov (United States)

    Girela, Jose L; Gil, David; Johnsson, Magnus; Gomez-Torres, María José; De Juan, Joaquín

    2013-04-01

    Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors as well as life habits may affect semen quality. In this paper we use artificial intelligence techniques in order to predict semen characteristics resulting from environmental factors, life habits, and health status, with these techniques constituting a possible decision support system that can help in the study of male fertility potential. A total of 123 young, healthy volunteers provided a semen sample that was analyzed according to the World Health Organization 2010 criteria. They also were asked to complete a validated questionnaire about life habits and health status. Sperm concentration and percentage of motile sperm were related to sociodemographic data, environmental factors, health status, and life habits in order to determine the predictive accuracy of a multilayer perceptron network, a type of artificial neural network. In conclusion, we have developed an artificial neural network that can predict the results of the semen analysis based on the data collected by the questionnaire. The semen parameter that is best predicted using this methodology is the sperm concentration. Although the accuracy for motility is slightly lower than that for concentration, it is possible to predict it with a significant degree of accuracy. This methodology can be a useful tool in early diagnosis of patients with seminal disorders or in the selection of candidates to become semen donors.

  3. A six-factor model of brand personality and its predictive validity

    Directory of Open Access Journals (Sweden)

    Živanović Marko

    2017-01-01

    Full Text Available The study examines applicability and usefulness of HEXACO-based model in the description of brand personality. Following contemporary theoretical developments in human personality research, Study 1 explored the latent personality structure of 120 brands using descriptors of six personality traits as defined in HEXACO model: Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness. The results of exploratory factor analyses have supported HEXACO personality six-factor structure to a large extent. In Study 2 we addressed the question of predictive validity of HEXACO-based brand personality. Brand personality traits, but predominantly Honesty-Humility, accounted for substantial amount of variance in prediction of important aspects of consumer-brand relationship: attitude toward brand, perceived quality of a brand, and brand loyalty. The implications of applying HEXACO-based brand personality in marketing research are discussed. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 179018 and Grant no. 175012

  4. Predictive Factors for Developing Venous Thrombosis during Cisplatin-Based Chemotherapy in Testicular Cancer.

    Science.gov (United States)

    Heidegger, Isabel; Porres, Daniel; Veek, Nica; Heidenreich, Axel; Pfister, David

    2017-01-01

    Malignancies and cisplatin-based chemotherapy are both known to correlate with a high risk of venous thrombotic events (VTT). In testicular cancer, the information regarding the incidence and reason of VTT in patients undergoing cisplatin-based chemotherapy is still discussed controversially. Moreover, no risk factors for developing a VTT during cisplatin-based chemotherapy have been elucidated so far. We retrospectively analyzed 153 patients with testicular cancer undergoing cisplatin-based chemotherapy at our institution for the development of a VTT during or after chemotherapy. Clinical and pathological parameters for identifying possible risk factors for VTT were analyzed. The Khorana risk score was used to calculate the risk of VTT. Student t test was applied for calculating the statistical significance of differences between the treatment groups. Twenty-six out of 153 patients (17%) developed a VTT during chemotherapy. When we analyzed the risk factors for developing a VTT, we found that Lugano stage ≥IIc was significantly (p = 0.0006) correlated with the risk of developing a VTT during chemotherapy. On calculating the VTT risk using the Khorana risk score model, we found that only 2 out of 26 patients (7.7%) were in the high-risk Khorana group (≥3). Patients with testicular cancer with a high tumor volume have a significant risk of developing a VTT with cisplatin-based chemotherapy. The Khorana risk score is not an accurate tool for predicting VTT in testicular cancer. © 2017 S. Karger AG, Basel.

  5. Safety of Workers in Indian Mines: Study, Analysis, and Prediction

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    Shikha Verma

    2017-09-01

    Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

  6. Identifying functional transcription factor binding sites in yeast by considering their positional preference in the promoters.

    Directory of Open Access Journals (Sweden)

    Fu-Jou Lai

    Full Text Available Transcription factor binding site (TFBS identification plays an important role in deciphering gene regulatory codes. With comprehensive knowledge of TFBSs, one can understand molecular mechanisms of gene regulation. In the recent decades, various computational approaches have been proposed to predict TFBSs in the genome. The TFBS dataset of a TF generated by each algorithm is a ranked list of predicted TFBSs of that TF, where top ranked TFBSs are statistically significant ones. However, whether these statistically significant TFBSs are functional (i.e. biologically relevant is still unknown. Here we develop a post-processor, called the functional propensity calculator (FPC, to assign a functional propensity to each TFBS in the existing computationally predicted TFBS datasets. It is known that functional TFBSs reveal strong positional preference towards the transcriptional start site (TSS. This motivates us to take TFBS position relative to the TSS as the key idea in building our FPC. Based on our calculated functional propensities, the TFBSs of a TF in the original TFBS dataset could be reordered, where top ranked TFBSs are now the ones with high functional propensities. To validate the biological significance of our results, we perform three published statistical tests to assess the enrichment of Gene Ontology (GO terms, the enrichment of physical protein-protein interactions, and the tendency of being co-expressed. The top ranked TFBSs in our reordered TFBS dataset outperform the top ranked TFBSs in the original TFBS dataset, justifying the effectiveness of our post-processor in extracting functional TFBSs from the original TFBS dataset. More importantly, assigning functional propensities to putative TFBSs enables biologists to easily identify which TFBSs in the promoter of interest are likely to be biologically relevant and are good candidates to do further detailed experimental investigation. The FPC is implemented as a web tool at http://santiago.ee.ncku.edu.tw/FPC/.

  7. TU-H-CAMPUS-JeP3-04: Factors Predicting a Need for Treatment Replanning with Proton Radiotherapy for Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Teng, C; Janssens, G; Ainsley, C; Teo, B; Valdes, G; Burgdorf, B; Berman, A; Levin, W; Xiao, Y; Lin, L; Gabriel, P; Simone, C; Solberg, T [University of Pennsylvania, Philadelphia, PA (United States)

    2016-06-15

    Purpose: Proton dose distribution is sensitive to tumor regression and tissue and normal anatomy changes. Replanning is sometimes necessary during treatment to ensure continue tumor coverage or avoid overtreatment of organs at risk (OARs). We investigated action thresholds for replanning and identified both dosimetric and non-dosimetric metrics that would predict a need for replan. Methods: All consecutive lung cancer patients (n = 188) who received definitive proton radiotherapy and had more than two evaluation CT scans at the Roberts Proton Therapy Center (Philadelphia, USA) from 2011 to 2015 were included in this study. The cohort included a variety of tumor sizes, locations, histology, beam angles, as well as radiation-induced tumor and lung change. Dosimetric changes during therapy were characterized by changes in the dose volume distribution of PTV, ITV, and OARs (heart, cord, esophagus, brachial plexus and lungs). Tumor and lung change were characterized by changes in sizes, and in the distribution of Hounsfield numbers and water equivalent thickness (WET) along the beam path. We applied machine learning tools to identify both dosimetric and non-dosimetric metrics that predicted a replan. Results: Preliminary data showed that clinical indicators (n = 54) were highly correlated; thus, a simple indicator may be derived to guide the action threshold for replanning. Additionally, tumor regression alone could not predict dosimetric changes in OARs; it required further information about beam angles and tumor locations. Conclusion: Both dosimetric and non-dosimetric factors are predictive of the need for replanning during proton treatment.

  8. A Western Diet Ecological Module Identified from the ‘Humanized’ Mouse Microbiota Predicts Diet in Adults and Formula Feeding in Children

    Science.gov (United States)

    Siddharth, Jay; Holway, Nicholas; Parkinson, Scott J.

    2013-01-01

    The interplay between diet and the microbiota has been implicated in the growing frequency of chronic diseases associated with the Western lifestyle. However, the complexity and variability of microbial ecology in humans and preclinical models has hampered identification of the molecular mechanisms underlying the association of the microbiota in this context. We sought to address two key questions. Can the microbial ecology of preclinical models predict human populations? And can we identify underlying principles that surpass the plasticity of microbial ecology in humans? To do this, we focused our study on diet; perhaps the most influential factor determining the composition of the gut microbiota. Beginning with a study in ‘humanized’ mice we identified an interactive module of 9 genera allied with Western diet intake. This module was applied to a controlled dietary study in humans. The abundance of the Western ecological module correctly predicted the dietary intake of 19/21 top and 21/21 of the bottom quartile samples inclusive of all 5 Western and ‘low-fat’ diet subjects, respectively. In 98 volunteers the abundance of the Western module correlated appropriately with dietary intake of saturated fatty acids, fat-soluble vitamins and fiber. Furthermore, it correlated with the geographical location and dietary habits of healthy adults from the Western, developing and third world. The module was also coupled to dietary intake in children (and piglets) correlating with formula (vs breast) feeding and associated with a precipitous development of the ecological module in young children. Our study provides a conceptual platform to translate microbial ecology from preclinical models to humans and identifies an ecological network module underlying the association of the gut microbiota with Western dietary habits. PMID:24391809

  9. Frost tolerance in wild potatoes : Assessing the predictivity of taxonomic, geographic and ecological factors

    NARCIS (Netherlands)

    Hijmans, R.J.; Jacobs, M.; Bamberg, J.B.; Spooner, D.M.

    2003-01-01

    The use of genetic resources could be more effective and efficient if we were able to predict the presence or absence of useful traits in different populations or accessions. We analyzed the extent to which taxonomic, geographic and ecological factors can predict the presence of frost tolerance in

  10. Factors related to drug approvals : predictors of outcome?

    NARCIS (Netherlands)

    Liberti, Lawrence; Breckenridge, Alasdair; Hoekman, Jarno; McAuslane, Neil; Stolk, Pieter; Leufkens, Bert

    2017-01-01

    There is growing interest in characterising factors associated with positive regulatory outcomes for drug marketing authorisations. We assessed empirical studies published over the past 15 years seeking to identify predictive factors. Factors were classified to one of four 'factor clusters':

  11. Predictive factors for cardiovascular diseases in women from the city of Jataí, Goiás states

    Directory of Open Access Journals (Sweden)

    Célia Scapin Duarte

    2017-03-01

    Full Text Available This study aimed to identify prevalent diseases and to correlate predictive factors to cardiovascular diseases (CVDs in women older than 18 years of age living in Jataí-Goiás-Brazil. This is a cross-sectional, quantitative descriptive study carried out in the year 2015 with the evaluation of 255 women members of two Strategic Family Health Units. The research instrument used was a questionnaire with closed answer questions, whose results were analyzed by the SPSS Program - Statistical Package for the Social Sciences, version 17.0. The results show that changes in pressure levels found in this study correlate with marked obesity, anthropometric measurements and Body Mass Index (BMI above normal levels. The risk factors for prevalent CVD were alcoholism, physical inactivity, extensive work hours and smoking. These data reinforce the importance of the implementation of preventive actions to be adopted by multiprofessional health teams in the city of Jataí, since the life habits practiced by the participants contribute to the increase of modifiable risk factors for cardiovascular diseases (CVDs.

  12. Predicting General Academic Performance and Identifying the Differential Contribution of Participating Variables Using Artificial Neural Networks

    Science.gov (United States)

    Musso, Mariel F.; Kyndt, Eva; Cascallar, Eduardo C.; Dochy, Filip

    2013-01-01

    Many studies have explored the contribution of different factors from diverse theoretical perspectives to the explanation of academic performance. These factors have been identified as having important implications not only for the study of learning processes, but also as tools for improving curriculum designs, tutorial systems, and students'…

  13. Factors Predicting Burnout Among Chaplains: Compassion Satisfaction, Organizational Factors, and the Mediators of Mindful Self-Care and Secondary Traumatic Stress.

    Science.gov (United States)

    Hotchkiss, Jason T; Lesher, Ruth

    2018-06-01

    This study predicted Burnout from the self-care practices, compassion satisfaction, secondary traumatic stress, and organizational factors among chaplains who participated from all 50 states (N = 534). A hierarchical regression model indicated that the combined effect of compassion satisfaction, secondary traumatic stress, mindful self-care, demographic, and organizational factors explained 83.2% of the variance in Burnout. Chaplains serving in a hospital were slightly more at risk for Burnout than those in hospice or other settings. Organizational factors that most predicted Burnout were feeling bogged down by the "system" (25.7%) and an overwhelming caseload (19.9%). Each self-care category was a statistically significant protective factor against Burnout risk. The strongest protective factors against Burnout in order of strength were self-compassion and purpose, supportive structure, mindful self-awareness, mindful relaxation, supportive relationships, and physical care. For secondary traumatic stress, supportive structure, mindful self-awareness, and self-compassion and purpose were the strongest protective factors. Chaplains who engaged in multiple and frequent self-care strategies experienced higher professional quality of life and low Burnout risk. In the chaplain's journey toward wellness, a reflective practice of feeling good about doing good and mindful self-care are vital. The significance, implications, and limitations of the study were discussed.

  14. Sequence Analysis of Hypothetical Proteins from 26695 to Identify Potential Virulence Factors

    Directory of Open Access Journals (Sweden)

    Ahmad Abu Turab Naqvi

    2016-09-01

    Full Text Available Helicobacter pylori is a Gram-negative bacteria that is responsible for gastritis in human. Its spiral flagellated body helps in locomotion and colonization in the host environment. It is capable of living in the highly acidic environment of the stomach with the help of acid adaptive genes. The genome of H. pylori 26695 strain contains 1,555 coding genes that encode 1,445 proteins. Out of these, 340 proteins are characterized as hypothetical proteins (HP. This study involves extensive analysis of the HPs using an established pipeline which comprises various bioinformatics tools and databases to find out probable functions of the HPs and identification of virulence factors. After extensive analysis of all the 340 HPs, we found that 104 HPs are showing characteristic similarities with the proteins with known functions. Thus, on the basis of such similarities, we assigned probable functions to 104 HPs with high confidence and precision. All the predicted HPs contain representative members of diverse functional classes of proteins such as enzymes, transporters, binding proteins, regulatory proteins, proteins involved in cellular processes and other proteins with miscellaneous functions. Therefore, we classified 104 HPs into aforementioned functional groups. During the virulence factors analysis of the HPs, we found 11 HPs are showing significant virulence. The identification of virulence proteins with the help their predicted functions may pave the way for drug target estimation and development of effective drug to counter the activity of that protein.

  15. Root Cause Analyses of Suicides of Mental Health Clients: Identifying Systematic Processes and Service-Level Prevention Strategies.

    Science.gov (United States)

    Gillies, Donna; Chicop, David; O'Halloran, Paul

    2015-01-01

    The ability to predict imminent risk of suicide is limited, particularly among mental health clients. Root cause analysis (RCA) can be used by health services to identify service-wide approaches to suicide prevention. To (a) develop a standardized taxonomy for RCAs; (b) to quantitate service-related factors associated with suicides; and (c) to identify service-related suicide prevention strategies. The RCAs of all people who died by suicide within 1 week of contact with the mental health service over 5 years were thematically analyzed using a data collection tool. Data were derived from RCAs of all 64 people who died by suicide between 2008 and 2012. Major themes were categorized as individual, situational, and care-related factors. The most common factor was that clients had recently denied suicidality. Reliance on carers, recent changes in medication, communication problems, and problems in follow-through were also commonly identified. Given the difficulty in predicting suicide in people whose expressions of suicidal ideation change so rapidly, services may consider the use of strategies aimed at improving the individual, stressor, support, and care factors identified in this study.

  16. Predictive factors of user acceptance on the primary educational mathematics aids product

    Science.gov (United States)

    Hidayah, I.; Margunani; Dwijanto

    2018-03-01

    Mathematics learning in primary schools requires instructional media. According to Piaget's theory, students are still in the concrete operational stage. For this reason, the development of the primary level mathematics aids is needed to support the development of successful mathematics learning. The stages of this research are the stages of commercialization with preparatory, marketing, and measurement analysis procedures. Promotion as part of marketing is done by doing a demonstration to the teacher. Measurements were performed to explore the predictive factors of user feasibility in adopting the product. Measurements were conducted using the concept of Technology Acceptance Model (TAM). Measurement variables include external variables, perceived usefulness, perceived ease of use, attitude, intention to use, and actual use. The result of this research shows that the contribution of predictive factors of mathematics teachers on the teaching aids product as follows: the external variable and perceived ease of use at 74%, perceived usefulness at 72%, intention to use (behavioral) at 58%, attitude at 52%, and the consequence factor (actual use) at 42%.

  17. Patient and carer identified factors which contribute to safety incidents in primary care: a qualitative study.

    Science.gov (United States)

    Hernan, Andrea L; Giles, Sally J; Fuller, Jeffrey; Johnson, Julie K; Walker, Christine; Dunbar, James A

    2015-09-01

    Patients can have an important role in reducing harm in primary-care settings. Learning from patient experience and feedback could improve patient safety. Evidence that captures patients' views of the various contributory factors to creating safe primary care is largely absent. The aim of this study was to address this evidence gap. Four focus groups and eight semistructured interviews were conducted with 34 patients and carers from south-east Australia. Participants were asked to describe their experiences of primary care. Audio recordings were transcribed verbatim and specific factors that contribute to safety incidents were identified in the analysis using the Yorkshire Contributory Factors Framework (YCFF). Other factors emerging from the data were also ascertained and added to the analytical framework. Thirteen factors that contribute to safety incidents in primary care were ascertained. Five unique factors for the primary-care setting were discovered in conjunction with eight factors present in the YCFF from hospital settings. The five unique primary care contributing factors to safety incidents represented a range of levels within the primary-care system from local working conditions to the upstream organisational level and the external policy context. The 13 factors included communication, access, patient factors, external policy context, dignity and respect, primary-secondary interface, continuity of care, task performance, task characteristics, time in the consultation, safety culture, team factors and the physical environment. Patient and carer feedback of this type could help primary-care professionals better understand and identify potential safety concerns and make appropriate service improvements. The comprehensive range of factors identified provides the groundwork for developing tools that systematically capture the multiple contributory factors to patient safety. Published by the BMJ Publishing Group Limited. For permission to use (where not

  18. Major controlling factors and predictions for cadmium transfer from the soil into spinach plants.

    Science.gov (United States)

    Liang, Zhenfei; Ding, Qiong; Wei, Dongpu; Li, Jumei; Chen, Shibao; Ma, Yibing

    2013-07-01

    Predicting the mobility, bioavailability and transfer of cadmium (Cd) in the soil-plant system is of great importance with regards to food safety and environmental management. In this study, the transfer characteristics of Cd (exogenous salts) from a wide range of Chinese soils to spinach (Spinacia oleracea L.) were investigated. The major controlling factors and prediction equations for Cd transfer in the soil-plant system were also investigated. The results showed that plant Cd concentration was positively correlated with soil Cd concentration. The maximum transfer factor (ratio of the Cd concentration in the plant to that in the soil) was found in acid soils. The extended Freundlich-type function was able to describe the Cd transfer from soil to spinach plants. Combining soil total Cd, pH and organic carbon (OC) content in the prediction equation greatly improved the correlation performance compared with predictions based on total Cd only. A slight protection effect of OC on Cd uptake was observed at low soil Cd concentrations. The results are a useful tool that can be used to predict Cd transfer from soil to plant. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Predictive factors of occult neck metastasis in patients with oral squamous cell carcinoma

    Directory of Open Access Journals (Sweden)

    Renato Fortes Bittar

    Full Text Available ABSTRACT INTRODUCTION: It is well established that cervical lymph node metastasis is the most important prognostic factor in patients with oral squamous cell carcinoma of the upper aerodigestive tract. The definition of parameters and classifications that could separate patients in groups of low, intermediate and high-risk is being attempted for several years. OBJECTIVE: The objective of this study was to determine possible predictive factors related to the occurrence of occult cervical lymph node metastasis through the analysis of histopathological reports of surgical specimens obtained after oral squamous cell carcinoma resection and selective neck dissections of patients initially classified as N0. METHODS: This was a primary, retrospective, observational, case-control study. Histopathological reports were reviewed to determine if some findings were related to the occurrence of occult lymph node metastasis. The events analyzed were oral cavity subsites, pT-stage, muscular infiltration, desmoplasia, vascular emboli, perineural infiltration, tumor thickness and compromised margins. RESULTS: Occult cervical metastasis accounted for 19.10 percent of the cases. Desmoplasia, perineural infiltration, tumor thickness and pT4a stage are predictive factors of occult neck metastasis (p-value = 0.0488, 0.0326, 0.0395, 0.0488, respectively. CONCLUSION: The accurate definition of predictive factors of occult cervical metastasis may guide the selection of patients that should be referred to radiotherapy, avoiding the unnecessary exposure of low-risk patients to radiation and allowing a better regional control of the disease in those of moderate or high risk.

  20. Reliability of self-reported childhood physical abuse by adults and factors predictive of inconsistent reporting.

    Science.gov (United States)

    McKinney, Christy M; Harris, T Robert; Caetano, Raul

    2009-01-01

    Little is known about the reliability of self-reported child physical abuse (CPA) or CPA reporting practices. We estimated reliability and prevalence of self-reported CPA and identified factors predictive of inconsistent CPA reporting among 2,256 participants using surveys administered in 1995 and 2000. Reliability of CPA was fair to moderate (kappa = 0.41). Using a positive report from either survey, the prevalence of moderate (61.8%) and severe (12.0%) CPA was higher than at either survey alone. Compared to consistent reporters of having experienced CPA, inconsistent reporters were less likely to be > or = 30 years old (vs. 18-29) or Black (vs. White) and more likely to have report one type (vs. > or = 2) of CPA. These findings may assist researchers conducting and interpreting studies of CPA.

  1. Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy.

    Science.gov (United States)

    Braadland, Peder R; Giskeødegård, Guro; Sandsmark, Elise; Bertilsson, Helena; Euceda, Leslie R; Hansen, Ailin F; Guldvik, Ingrid J; Selnæs, Kirsten M; Grytli, Helene H; Katz, Betina; Svindland, Aud; Bathen, Tone F; Eri, Lars M; Nygård, Ståle; Berge, Viktor; Taskén, Kristin A; Tessem, May-Britt

    2017-11-21

    Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy. We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan-Meier survival analyses and concordance index (C-index). High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively). Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

  2. Predicting and influencing voice therapy adherence using social-cognitive factors and mobile video.

    Science.gov (United States)

    van Leer, Eva; Connor, Nadine P

    2015-05-01

    Patient adherence to voice therapy is an established challenge. The purpose of this study was (a) to examine whether adherence to treatment could be predicted from three social-cognitive factors measured at treatment onset: self-efficacy, goal commitment, and the therapeutic alliance, and (b) to test whether the provision of clinician, self-, and peer model mobile treatment videos on MP4 players would influence the same triad of social cognitive factors and the adherence behavior of patients. Forty adults with adducted hyperfunction with and without benign lesions were prospectively randomized to either 4 sessions of voice therapy enhanced by MP4 support or without MP4 support. Adherence between sessions was assessed through self-report. Social cognitive factors and voice outcomes were assessed at the beginning and end of therapy. Utility of MP4 support was assessed via interviews. Self-efficacy and the therapeutic alliance predicted a significant amount of adherence variance. MP4 support significantly increased generalization, self-efficacy for generalization, and the therapeutic alliance. An interaction effect demonstrated that MP4 support was particularly effective for patients who started therapy with poor self-efficacy for generalization. Adherence may be predicted and influenced via social-cognitive means. Mobile technology can extend therapy to extraclinical settings.

  3. Reduced mandibular range of motion in Duchenne muscular dystrophy : Predictive factors

    NARCIS (Netherlands)

    van Bruggen, H. W.; Van Den Engel-Hoek, L.; Steenks, M. H.; Bronkhorst, E. M.; Creugers, N. H J; de Groot, I. J M; Kalaykova, S. I.

    2015-01-01

    Patients with Duchenne muscular dystrophy (DMD) experience negative effects upon feeding and oral health. We aimed to determine whether the mandibular range of motion in DMD is impaired and to explore predictive factors for the active maximum mouth opening (aMMO). 23 patients with DMD (mean age 16·7

  4. Outcome of Patients Underwent Emergency Department Thoracotomy and Its Predictive Factors

    Directory of Open Access Journals (Sweden)

    Shahram Paydar

    2014-08-01

    Full Text Available Introduction: Emergency department thoracotomy (EDT may serve as the last survival chance for patients who arrive at hospital in extremis. It is considered as an effective tool for improvement of traumatic patients’ outcome. The present study was done with the goal of assessing the outcome of patients who underwent EDT and its predictive factors. Methods: In the present study, medical charts of 50 retrospective and 8 prospective cases underwent emergency department thoracotomy (EDT were reviewed during November 2011 to June 2013. Comparisons between survived and died patients were performed by Mann-Whitney U test and the predictive factors of EDT outcome were measured using multivariate logistic regression analysis. P < 0.05 considered statistically significant. Results: Fifty eight cases of EDT were enrolled (86.2% male. The mean age of patients was 43.27±19.85 years with the range of 18-85. The mean time duration of CPR was recorded as 37.12±12.49 minutes. Eleven cases (19% were alive to be transported to OR (defined as ED survived. The mean time of survival in ED survived patients was 223.5±450.8 hours. More than 24 hours survival rate (late survived was 6.9% (4 cases. Only one case (1.7% survived to discharge from hospital (mortality rate=98.3%. There were only a significant relation between ED survival and SBP, GCS, CPR duration, and chest trauma (p=0.04. The results demonstrated that initial SBP lower than 80 mmHg (OR=1.03, 95% CI: 1.001-1.05, p=0.04 and presence of chest trauma (OR=2.6, 95% CI: 1.75-3.16, p=0.02 were independent predictive factors of EDT mortality. Conclusion: The findings of the present study showed that the survival rate of trauma patients underwent EDT was 1.7%. In addition, it was defined that falling systolic blood pressure below 80 mmHg and blunt trauma of chest are independent factors that along with poor outcome.

  5. The nematode Caenorhabditis elegans as a tool to predict chemical activity on mammalian development and identify mechanisms influencing toxicological outcome.

    Science.gov (United States)

    Harlow, Philippa H; Perry, Simon J; Widdison, Stephanie; Daniels, Shannon; Bondo, Eddie; Lamberth, Clemens; Currie, Richard A; Flemming, Anthony J

    2016-03-18

    To determine whether a C. elegans bioassay could predict mammalian developmental activity, we selected diverse compounds known and known not to elicit such activity and measured their effect on C. elegans egg viability. 89% of compounds that reduced C. elegans egg viability also had mammalian developmental activity. Conversely only 25% of compounds found not to reduce egg viability in C. elegans were also inactive in mammals. We conclude that the C. elegans egg viability assay is an accurate positive predictor, but an inaccurate negative predictor, of mammalian developmental activity. We then evaluated C. elegans as a tool to identify mechanisms affecting toxicological outcomes among related compounds. The difference in developmental activity of structurally related fungicides in C. elegans correlated with their rate of metabolism. Knockdown of the cytochrome P450s cyp-35A3 and cyp-35A4 increased the toxicity to C. elegans of the least developmentally active compounds to the level of the most developmentally active. This indicated that these P450s were involved in the greater rate of metabolism of the less toxic of these compounds. We conclude that C. elegans based approaches can predict mammalian developmental activity and can yield plausible hypotheses for factors affecting the biological potency of compounds in mammals.

  6. Biological lifestyle factors in adult distance education: predicting cognitive and learning performance

    NARCIS (Netherlands)

    Gijselaers, Jérôme

    2015-01-01

    Gijselaers, H. J. M. (2015, 20 October). Biological lifestyle factors in adult distance education: predicting cognitive and learning performance. Presentation given for the inter-faculty Data Science group at the Open University of the Netherlands, Heerlen, The Netherlands.

  7. Risk factors and a prediction model for lower limb lymphedema following lymphadenectomy in gynecologic cancer: a hospital-based retrospective cohort study.

    Science.gov (United States)

    Kuroda, Kenji; Yamamoto, Yasuhiro; Yanagisawa, Manami; Kawata, Akira; Akiba, Naoya; Suzuki, Kensuke; Naritaka, Kazutoshi

    2017-07-25

    Lower limb lymphedema (LLL) is a chronic and incapacitating condition afflicting patients who undergo lymphadenectomy for gynecologic cancer. This study aimed to identify risk factors for LLL and to develop a prediction model for its occurrence. Pelvic lymphadenectomy (PLA) with or without para-aortic lymphadenectomy (PALA) was performed on 366 patients with gynecologic malignancies at Yaizu City Hospital between April 2002 and July 2014; we retrospectively analyzed 264 eligible patients. The intervals between surgery and diagnosis of LLL were calculated; the prevalence and risk factors were evaluated using the Kaplan-Meier and Cox proportional hazards methods. We developed a prediction model with which patients were scored and classified as low-risk or high-risk. The cumulative incidence of LLL was 23.1% at 1 year, 32.8% at 3 years, and 47.7% at 10 years post-surgery. LLL developed after a median 13.5 months. Using regression analysis, body mass index (BMI) ≥25 kg/m 2 (hazard ratio [HR], 1.616; 95% confidence interval [CI], 1.030-2.535), PLA + PALA (HR, 2.323; 95% CI, 1.126-4.794), postoperative radiation therapy (HR, 2.469; 95% CI, 1.148-5.310), and lymphocyst formation (HR, 1.718; 95% CI, 1.120-2.635) were found to be independently associated with LLL; age, type of cancer, number of lymph nodes, retroperitoneal suture, chemotherapy, lymph node metastasis, herbal medicine, self-management education, or infection were not associated with LLL. The predictive score was based on the 4 associated variables; patients were classified as high-risk (scores 3-6) and low-risk (scores 0-2). LLL incidence was significantly greater in the high-risk group than in the low-risk group (HR, 2.19; 95% CI, 1.440-3.324). The cumulative incidence at 5 years was 52.1% [95% CI, 42.9-62.1%] for the high-risk group and 28.9% [95% CI, 21.1-38.7%] for the low-risk group. The area under the receiver operator characteristics curve for the prediction model was 0.631 at 1 year, 0

  8. Independent Predictive Factors of Hospitalization in a North-West Burn Center of Iran; an Epidemiologic Study

    Directory of Open Access Journals (Sweden)

    Samad Shams Vahdati

    2015-01-01

    Full Text Available Introduction: A high grade burn is one of the most devastating injuries with several medical, social, economic, and psychological effects. These injuries are the most common cause of accidental deaths after traffic injuries in both the developed and developing countries. Therefore this research was aimed to determine demographic characteristics of patients with burn injury admitted to the emergency department and identify predictive factors of hospitalization. Methods: This is a cross sectional descriptive study, which is done in 20 March up to 20 September 2011 in emergency department of Sina Hospital, Tabriz, Iran. Patients’ information including demographic characteristic, cause of burn, place of accident, anatomical areas burned, grading and percent of burning and disposition were gathered and analyzed using SPSS version 18.0 statistical software. Stepwise multivariate regression analysis was used for recognition of independent predictive factors of hospitalization in burned patients. Results: One hundred and sixty patients were enrolled (54.4% female. The average age of those was 20.47±13.5 years. The prevalence of burn was significantly higher in ages under 20 years (p<0.001. Lower limb (37.5%, head and neck (21.25% and upper limb (17.5% were three frequent site of burn. The most common cause of burns was boiling water scalding (34.4%. Home related burn was significantly higher than other place (p<0.001. The most frequent percent of burn was <5% (46.25%. Finally 50 (31.25% cases hospitalized. Univariate analysis demonstrated that age under 20 years old (p=0.02 female gender (p=0.02, burning site (p=0.002, cause (p=0.005, place (p<0.001, grade (p<0.001, and percent (p<0.001 was related to disposition of patients. Stepwise multiple logistic regression showed female gender (OR=3.52; 95% CI: 1.57-7.88; p=0.002, work related burning (OR=1.78; 95% CI: 1.26-2.52; p=0.001, and burning over 5 percent (OR=2.15; 95% CI: 1.35-3.41; p=0.001 as

  9. Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

    Science.gov (United States)

    Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

    2017-03-01

    The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

  10. Development of scaling factor prediction method for radionuclide composition in low-level radioactive waste

    International Nuclear Information System (INIS)

    Park, Jin Beak

    1995-02-01

    Low-level radioactive waste management require the knowledge of the natures and quantities of radionuclides in the immobilized or packaged waste. U. S. NRC rules require programs that measure the concentrations of all relevant nuclides either directly or indirectly by relating difficult-to-measure radionuclides to other easy-to-measure radionuclides with application of scaling factors. Scaling factors previously developed through statistical approach can give only generic ones and have many difficult problem about sampling procedures. Generic scaling factors can not take into account for plant operation history. In this study, a method to predict plant-specific and operational history dependent scaling factors is developed. Realistic and detailed approach are taken to find scaling factors at reactor coolant. This approach begin with fission product release mechanisms and fundamental release properties of fuel-source nuclide such as fission product and transuranic nuclide. Scaling factors at various waste streams are derived from the predicted reactor coolant scaling factors with the aid of radionuclide retention and build up model. This model make use of radioactive material balance within the radioactive waste processing systems. Scaling factors at reactor coolant and waste streams which can include the effects of plant operation history have been developed according to input parameters of plant operation history

  11. Predictive factors of cessation of ambulation in patients with Duchenne muscular dystrophy

    NARCIS (Netherlands)

    Bakker, Jan P. J.; de Groot, Imelda J. M.; Beelen, Anita; Lankhorst, Gustaaf J.

    2002-01-01

    To identify baseline patient and treatment characteristics that can predict wheelchair dependency within 2 yr. This prospective cohort study included 44 subjects who met study inclusion criteria. The same investigator examined them at 6-mo intervals. Ambulatory status, anthropometric data, muscle

  12. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Bita Najafian

    2015-02-01

    Full Text Available Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS.Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure. The patients were divided into failure or successful groups and factors which can predict success of INSURE were investigated by logistic regression in SPSS 16th version.Results:29 and16 neonates were observed in successful and failure groups, respectively. Birth weight was the only variable with significant difference between two groups (P=0.002. Finally logistic regression test showed that birth weight is only predicting factor for success (P: 0.001, EXP[β]: 0.009, CI [95%]: 1.003-0.014 and mortality (P: 0.029, EXP[β]: 0.993, CI [95%]: 0.987-0.999 of neonates treated with INSURE method.Conclusion:Predicting factors which affect on success rate of INSURE can be useful for treating and reducing charge of neonate with RDS and the birth weight is one of the effective factor on INSURE Success in this study.

  13. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Bita Najafian

    2015-02-01

    Full Text Available Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS. Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure. The patients were divided into failure or successful groups and factors which can predict success of INSURE were investigated by logistic regression in SPSS 16th version. Results:29 and16 neonates were observed in successful and failure groups, respectively. Birth weight was the only variable with significant difference between two groups (P=0.002. Finally logistic regression test showed that birth weight is only predicting factor for success (P: 0.001, EXP[β]: 0.009, CI [95%]: 1.003-0.014 and mortality (P: 0.029, EXP[β]: 0.993, CI [95%]: 0.987-0.999 of neonates treated with INSURE method. Conclusion:Predicting factors which affect on success rate of INSURE can be useful for treating and reducing charge of neonate with RDS and the birth weight is one of the effective factor on INSURE Success in this study.

  14. Prospective validation of a predictive model that identifies homeless people at risk of re-presentation to the emergency department.

    Science.gov (United States)

    Moore, Gaye; Hepworth, Graham; Weiland, Tracey; Manias, Elizabeth; Gerdtz, Marie Frances; Kelaher, Margaret; Dunt, David

    2012-02-01

    To prospectively evaluate the accuracy of a predictive model to identify homeless people at risk of representation to an emergency department. A prospective cohort analysis utilised one month of data from a Principal Referral Hospital in Melbourne, Australia. All visits involving people classified as homeless were included, excluding those who died. Homelessness was defined as living on the streets, in crisis accommodation, in boarding houses or residing in unstable housing. Rates of re-presentation, defined as the total number of visits to the same emergency department within 28 days of discharge from hospital, were measured. Performance of the risk screening tool was assessed by calculating sensitivity, specificity, positive and negative predictive values and likelihood ratios. Over the study period (April 1, 2009 to April 30, 2009), 3298 presentations from 2888 individuals were recorded. The homeless population accounted for 10% (n=327) of all visits and 7% (n=211) of all patients. A total of 90 (43%) homeless people re-presented to the emergency department. The predictive model included nine variables and achieved 98% (CI, 0.92-0.99) sensitivity and 66% (CI, 0.57-0.74) specificity. The positive predictive value was 68% and the negative predictive value was 98%. The positive likelihood ratio 2.9 (CI, 2.2-3.7) and the negative likelihood ratio was 0.03 (CI, 0.01-0.13). The high emergency department re-presentation rate for people who were homeless identifies unresolved psychosocial health needs. The emergency department remains a vital access point for homeless people, particularly after hours. The risk screening tool is key to identify medical and social aspects of a homeless patient's presentation to assist early identification and referral. Copyright © 2012 College of Emergency Nursing Australasia Ltd. Published by Elsevier Ltd. All rights reserved.

  15. Predictive factors for oropharyngeal dysphagia after prolonged orotracheal intubation.

    Science.gov (United States)

    Oliveira, Ana Carolina Martins de; Friche, Amélia Augusta de Lima; Salomão, Marina Silva; Bougo, Graziela Chamarelli; Vicente, Laélia Cristina Caseiro

    2017-09-13

    Lesions in the oral cavity, pharynx and larynx due to endotracheal intubation can cause reduction in the local motility and sensitivity, impairing the swallowing process, resulting in oropharyngeal dysphagia. To verify the predictive factors for the development of oropharyngeal dysphagia and the risk of aspiration in patients with prolonged orotracheal intubation admitted to an intensive care unit. This is an observational, analytical, cross-sectional and retrospective data collection study of 181 electronic medical records of patients submitted to prolonged orotracheal intubation. Data on age; gender; underlying disease; associated comorbidities; time and reason for orotracheal intubation; Glasgow scale on the day of the Speech Therapist assessment; comprehension; vocal quality; presence and severity of dysphagia; risk of bronchoaspiration; and the suggested oral route were collected. The data were analyzed through logistic regression. The level of significance was set at 5%, with a 95% Confidence Interval. The prevalence of dysphagia in this study was 35.9% and the risk of aspiration was 24.9%. As the age increased, the altered vocal quality and the degree of voice impairment increased the risk of the presence of dysphagia by 5-; 45.4- and 6.7-fold, respectively, and of aspiration by 6-; 36.4- and 4.8-fold. The increase in the time of orotracheal intubation increased the risk of aspiration by 5.5-fold. Patients submitted to prolonged intubation who have risk factors associated with dysphagia and aspiration should be submitted to an early speech-language/audiology assessment and receive appropriate and timely treatment. The recognition of these predictive factors by the entire multidisciplinary team can minimize the possibility of clinical complications inherent to the risk of dysphagia and aspiration in extubated patients. Copyright © 2017. Published by Elsevier Editora Ltda.

  16. The Predictive Effect of Big Five Factor Model on Social Reactivity ...

    African Journals Online (AJOL)

    The study tested a model of providing a predictive explanation of Big Five Factor on social reactivity among secondary school adolescents of Cross River State, Nigeria. A sample of 200 students randomly selected across 12 public secondary schools in the State participated in the study (120 male and 80 female). Data ...

  17. Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data

    International Nuclear Information System (INIS)

    Pauget, B.; Gimbert, F.; Scheifler, R.; Coeurdassier, M.; Vaufleury, A. de

    2012-01-01

    Although soil characteristics modulate metal mobility and bioavailability to organisms, they are often ignored in the risk assessment of metal transfer. This paper aims to determine the ability of chemical methods to assess and predict cadmium (Cd), lead (Pb) and zinc (Zn) environmental bioavailability to the land snail Cantareus aspersus. Snails were exposed in the laboratory for 28 days to 17 soils from around a former smelter. The soils were selected for their range of pH, organic matter, clay content, and Cd, Pb and Zn concentrations. The influence of soil properties on environmental availability (estimated using HF-HClO 4 , EDTA, CaCl 2 , NH 4 NO 3 , NaNO 3 , free ion activity and total dissolved metal concentration in soil solution) and on environmental bioavailability (modelled using accumulation kinetics) was identified. Among the seven chemical methods, only the EDTA and the total soil concentration can be used to assess Cd and Pb environmental bioavailability to snails (r² adj = 0.67 and 0.77, respectively). For Zn, none of the chemical methods were suitable. Taking into account the influence of the soil characteristics (pH and CEC) allows a better prediction of Cd and Pb environmental bioavailability (r² adj = 0.82 and 0.83, respectively). Even though alone none of the chemical methods tested could assess Zn environmental bioavailability to snails, the addition of pH, iron and aluminium oxides allowed the variation of assimilation fluxes to be predicted. A conceptual and practical method to use soil characteristics for risk assessment is proposed based on these results. We conclude that as yet there is no universal chemical method to predict metal environmental bioavailability to snails, and that the soil factors having the greatest impact depend on the metal considered. - Highlights: ► New approach to identify chemical methods able to predict metal bioavailability to snails. ► Bioavailability of cadmium, lead and zinc to snails was determined by

  18. Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data

    Energy Technology Data Exchange (ETDEWEB)

    Pauget, B.; Gimbert, F., E-mail: frederic.gimbert@univ-fcomte.fr; Scheifler, R.; Coeurdassier, M.; Vaufleury, A. de

    2012-08-01

    Although soil characteristics modulate metal mobility and bioavailability to organisms, they are often ignored in the risk assessment of metal transfer. This paper aims to determine the ability of chemical methods to assess and predict cadmium (Cd), lead (Pb) and zinc (Zn) environmental bioavailability to the land snail Cantareus aspersus. Snails were exposed in the laboratory for 28 days to 17 soils from around a former smelter. The soils were selected for their range of pH, organic matter, clay content, and Cd, Pb and Zn concentrations. The influence of soil properties on environmental availability (estimated using HF-HClO{sub 4}, EDTA, CaCl{sub 2}, NH{sub 4}NO{sub 3}, NaNO{sub 3}, free ion activity and total dissolved metal concentration in soil solution) and on environmental bioavailability (modelled using accumulation kinetics) was identified. Among the seven chemical methods, only the EDTA and the total soil concentration can be used to assess Cd and Pb environmental bioavailability to snails (r Superscript-Two {sub adj} = 0.67 and 0.77, respectively). For Zn, none of the chemical methods were suitable. Taking into account the influence of the soil characteristics (pH and CEC) allows a better prediction of Cd and Pb environmental bioavailability (r Superscript-Two {sub adj} = 0.82 and 0.83, respectively). Even though alone none of the chemical methods tested could assess Zn environmental bioavailability to snails, the addition of pH, iron and aluminium oxides allowed the variation of assimilation fluxes to be predicted. A conceptual and practical method to use soil characteristics for risk assessment is proposed based on these results. We conclude that as yet there is no universal chemical method to predict metal environmental bioavailability to snails, and that the soil factors having the greatest impact depend on the metal considered. - Highlights: Black-Right-Pointing-Pointer New approach to identify chemical methods able to predict metal bioavailability

  19. Prediction of 90Y Radioembolization Outcome from Pretherapeutic Factors with Random Survival Forests.

    Science.gov (United States)

    Ingrisch, Michael; Schöppe, Franziska; Paprottka, Karolin; Fabritius, Matthias; Strobl, Frederik F; De Toni, Enrico N; Ilhan, Harun; Todica, Andrei; Michl, Marlies; Paprottka, Philipp Marius

    2018-05-01

    Our objective was to predict the outcome of 90 Y radioembolization in patients with intrahepatic tumors from pretherapeutic baseline parameters and to identify predictive variables using a machine-learning approach based on random survival forests. Methods: In this retrospective study, 366 patients with primary ( n = 92) or secondary ( n = 274) liver tumors who had received 90 Y radioembolization were analyzed. A random survival forest was trained to predict individual risk from baseline values of cholinesterase, bilirubin, type of primary tumor, age at radioembolization, hepatic tumor burden, presence of extrahepatic disease, and sex. The predictive importance of each baseline parameter was determined using the minimal-depth concept, and the partial dependency of predicted risk on the continuous variables bilirubin level and cholinesterase level was determined. Results: Median overall survival was 11.4 mo (95% confidence interval, 9.7-14.2 mo), with 228 deaths occurring during the observation period. The random-survival-forest analysis identified baseline cholinesterase and bilirubin as the most important variables (forest-averaged lowest minimal depth, 1.2 and 1.5, respectively), followed by the type of primary tumor (1.7), age (2.4), tumor burden (2.8), and presence of extrahepatic disease (3.5). Sex had the highest forest-averaged minimal depth (5.5), indicating little predictive value. Baseline bilirubin levels above 1.5 mg/dL were associated with a steep increase in predicted mortality. Similarly, cholinesterase levels below 7.5 U predicted a strong increase in mortality. The trained random survival forest achieved a concordance index of 0.657, with an SE of 0.02, comparable to the concordance index of 0.652 and SE of 0.02 for a previously published Cox proportional hazards model. Conclusion: Random survival forests are a simple and straightforward machine-learning approach for prediction of overall survival. The predictive performance of the trained model

  20. A study of risk factors and predictive factors in intraoperative floppy iris syndrome during phacoemulsification

    Directory of Open Access Journals (Sweden)

    Jie-Xin Yu

    2017-11-01

    Full Text Available AIM: To determine the incidence of intraoperative floppy iris syndrome(IFISin patients undergoing phacoemulsification in a Chinese hospital, and to assess new risk factors and predictive factors for IFIS. METHODS: A prospective, observational case series. In the consecutive cataract surgeries performed in one year, the medicine administration, pupil size(PSbefore and after mydriasis, and signs of IFIS were recorded. RESULTS: Totally 807 patients(1 068 eyesunderwent cataract surgeries. Among the 1 068 eyes, signs of IFIS were noted in 34 eyes. Strong positive correlations were showed between finasteride(6.4%, OR=5.885, tamsulosin(25%, OR=21.578, reserpine(16.7%, OR=12.947, clozapine(66.7%, OR=139.467, post-panretinal photocoagulation(14.3%, OR=10.789and IFIS. Pupil size was inversely related to IFIS incidence(PPCONCLUSION: The incidence rate of IFIS was 3.18%. Reserpine, clozapine and post-panretinal photocoagulation emerged as new risk factors for IFIS. A small dilated pupil may imply IFIS occurrence.

  1. Value of multiple risk factors in predicting coronary artery disease

    International Nuclear Information System (INIS)

    Zhu Zhengbin; Zhang Ruiyan; Zhang Qi; Yang Zhenkun; Hu Jian; Zhang Jiansheng; Shen Weifeng

    2008-01-01

    Objective: This study sought to assess the relationship between correlative comprehension risk factors and coronary arterial disease and to build up a simple mathematical model to evaluate the extension of coronary artery lesion in patients with stable angina. Methods: A total of 1024 patients with chest pain who underwent coronary angiography were divided into CAD group(n=625)and control group(n=399) based on at least one significant coronary artery narrowing more than 50% in diameter. Independent risk factors for CAD were evaluated and multivariate logistic regression model and receiver-operating characteristic(ROC) curves were used to estimate the independent influence factor for CAD and built up a simple formula for clinical use. Results: Multivariate regression analysis revealed that UACR > 7.25 μg/mg(OR=3.6; 95% CI 2.6-4.9; P 20 mmol/L(OR=3.2; 95% CI 2.3-4.4; P 2 (OR=2.3; 95% CI 1.4-3.8; P 2.6 mmol/L (OR 2.141; 95% CI 1.586-2.890; P 7.25 μg/mg + 1.158 x hsCRP > 20 mmol/L + 0.891 GFR 2 + 0.831 x LVEF 2.6 mmol/L + 0.676 x smoking history + 0.594 x male + 0.459 x diabetes + 0.425 x hypertension). Area under the curve was 0.811 (P < 0.01), and the optimal probability value for predicting severe stage of CAD was 0.977 (sensitivity 49.0%, specificity 92.7% ). Conclusions: Risk factors including renal insufficiency were the main predictors for CAD. The logistic regression model is the non-invasive method of choice for predicting the extension of coronary artery lesion in patients with stable agiana. (authors)

  2. Spontaneous prematurity in fetuses with congenital diaphragmatic hernia: a retrospective cohort study about prenatal predictive factors.

    Science.gov (United States)

    Barbosa, Bruna Maria Lopes; Rodrigues, Agatha S; Carvalho, Mario Henrique Burlacchini; Bittar, Roberto Eduardo; Francisco, Rossana Pulcineli Vieira; Bernardes, Lisandra Stein

    2018-01-12

    To evaluate possible predictive factors of spontaneous prematurity in fetuses with congenital diaphragmatic hernia (CDH). A retrospective cohort study was performed. Inclusion criteria were presence of CDH; absence of fetoscopy; absence of karyotype abnormality; maximum of one major malformation associated with diaphragmatic hernia; ultrasound monitoring at the Obstetrics Clinic of Clinicas Hospital at the University of São Paulo School of Medicine, from January 2001 to October 2014. The data were obtained through the electronic records and ultrasound system of our fetal medicine service. The following variables were analyzed: maternal age, primiparity, associated maternal diseases, smoking, previous spontaneous preterm birth, fetal malformation associated with hernia, polyhydramnios, fetal growth restriction, presence of intrathoracic liver, invasive procedures performed, side of hernia and observed-to- expected lung to head ratio (o/e LHR). On individual analysis, variables were assessed using the Chi-square test and the Mann-Whitney test. A multiple logistic regression model was applied to select variables independently influencing the prediction of preterm delivery. A ROC curve was constructed with the significant variable, identifying the values with best sensitivity and specificity to be suggested for use in clinical practice. Eighty fetuses were evaluated, of which, 21 (26.25%) were premature. O/e LHR was the only factor associated with prematurity (p = 0.020). The ROC curve showed 93% sensitivity with 48.4% specificity for the cutoff of 40%. O/e LHR was the only predictor of prematurity in this sample.

  3. Psychological, interpersonal, and clinical factors predicting time spent on physical activity among Mexican patients with hypertension.

    Science.gov (United States)

    Ybarra Sagarduy, José Luis; Camacho Mata, Dacia Yurima; Moral de la Rubia, José; Piña López, Julio Alfonso; Yunes Zárraga, José Luis Masud

    2018-01-01

    It is widely known that physical activity is the key to the optimal management and clinical control of hypertension. This research was conducted to identify factors that can predict the time spent on physical activity among Mexican adults with hypertension. This cross-sectional study was conducted among 182 Mexican patients with hypertension, who completed a set of self-administered questionnaires related to personality, social support, and medical adherence and health care behaviors, body mass index, and time since the disease diagnosis. Several path analyses were performed in order to test the predictors of the study behavior. Lower tolerance to frustration, more tolerance to ambiguity, more effective social support, and less time since the disease diagnosis predicted more time spent on physical activity, accounting for 13.3% of the total variance. The final model shows a good fit to the sample data ( p BS =0.235, χ 2 / gl =1.519, Jöreskog and Sörbom's Goodness of Fit Index =0.987, adjusted modality =0.962, Bollen's Incremental Fit Index =0.981, Bentler-Bonett Normed Fit Index =0.946, standardized root mean square residual =0.053). The performance of physical activity in patients with hypertension depends on a complex set of interactions between personal, interpersonal, and clinical variables. Understanding how these factors interact might enhance the design of interdisciplinary intervention programs so that quality of life of patients with hypertension improves and they might be able to manage and control their disease well.

  4. Risk factors predicting onset and persistence of subthreshold expression of bipolar psychopathology among youth from the community.

    Science.gov (United States)

    Tijssen, M J A; Van Os, J; Wittchen, H U; Lieb, R; Beesdo, K; Wichers, Marieke

    2010-09-01

    To examine factors increasing the risk for onset and persistence of subthreshold mania and depression. In a prospective cohort community study, the association between risk factors [a family history of mood disorders, trauma, substance use, attention-deficit/hyperactivity disorder (ADHD) and temperamental/personality traits] and onset of manic/depressive symptoms was determined in 705 adolescents. The interaction between baseline risk factors and baseline symptoms in predicting 8-year follow-up symptoms was used to model the impact of risk factors on persistence. Onset of manic symptoms was associated with cannabis use and novelty seeking (NS), but NS predicted a transitory course. Onset of depressive symptoms was associated with a family history of depression. ADHD and harm avoidance (HA) were associated with persistence of depressive symptoms, while trauma and a family history of depression predicted a transitory course. Different risk factors may operate during onset and persistence of subthreshold mania and depression. The differential associations found for mania and depression dimensions suggest partly different underlying mechanisms.

  5. Predictive factors for gastroduodenal toxicity based on endoscopy following radiotherapy in patients with hepatocellular carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, H. [Sungkyunkwan Univ., Seoul (Korea, Republic of). Dept. of Health Sciences and Technology; Oh, D.; Park, H.C.; Han, Y.; Lim, D.H. [Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of). Dept. of Radiation Oncology; Kang, S.W. [Korea Univ., Seoul (Korea, Republic of). Dept. of Radiologic Science; Paik, S.W. [Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of). Dept. of Medicine

    2013-07-15

    Purpose: The aim of this work was to determine predictive factors for gastroduodenal (GD) toxicity in hepatocellular carcinoma (HCC) patients who were treated with radiotherapy (RT). Patients and methods: A total of 90 HCC patients who underwent esophagogastroduodenoscopy (EGD) before and after RT were enrolled. RT was delivered as 30-50 Gy (median 37.5 Gy) in 2-5 Gy (median 3.5 Gy) per fraction. All endoscopic findings were reviewed and GD toxicities related to RT were graded by the Common Toxicity Criteria for Adverse Events, version 3.0. The predictive factors for the {>=} grade 2 GD toxicity were investigated. Results: Endoscopic findings showed erosive gastritis in 14 patients (16 %), gastric ulcers in 8 patients (9 %), erosive duodenitis in 15 patients (17 %), and duodenal ulcers in 14 patients (16 %). Grade 2 toxicity developed in 19 patients (21 %) and grade 3 toxicity developed in 8 patients (9 %). V{sub 25} for stomach and V{sub 35} for duodenum (volume receiving a RT dose of more than x Gy) were the most predictive factors for {>=} grade 2 toxicity. The gastric toxicity rate at 6 months was 2.9 % for V{sub 25} {<=} 6.3 % and 57.1 % for V{sub 25} > 6.3 %. The duodenal toxicity rate at 6 months was 9.4 % for V{sub 35} > 5.4 % and 45.9 % for V{sub 35} > 5.4 %. By multivariate analysis including the clinical factors, V{sub 25} for stomach and V{sub 35} for duodenum were the significant factors. Conclusion: EGD revealed that GD toxicity is common following RT for HCC. V{sub 25} for the stomach and V{sub 35} for the duodenum were the significant factors to predict {>=} grade 2 GD toxicity. (orig.)

  6. Fuzzy Regression Prediction and Application Based on Multi-Dimensional Factors of Freight Volume

    Science.gov (United States)

    Xiao, Mengting; Li, Cheng

    2018-01-01

    Based on the reality of the development of air cargo, the multi-dimensional fuzzy regression method is used to determine the influencing factors, and the three most important influencing factors of GDP, total fixed assets investment and regular flight route mileage are determined. The system’s viewpoints and analogy methods, the use of fuzzy numbers and multiple regression methods to predict the civil aviation cargo volume. In comparison with the 13th Five-Year Plan for China’s Civil Aviation Development (2016-2020), it is proved that this method can effectively improve the accuracy of forecasting and reduce the risk of forecasting. It is proved that this model predicts civil aviation freight volume of the feasibility, has a high practical significance and practical operation.

  7. Data mining in bone marrow transplant records to identify patients with high odds of survival.

    Science.gov (United States)

    Taati, Babak; Snoek, Jasper; Aleman, Dionne; Ghavamzadeh, Ardeshir

    2014-01-01

    Patients undergoing a bone marrow stem cell transplant (BMT) face various risk factors. Analyzing data from past transplants could enhance the understanding of the factors influencing success. Records up to 120 measurements per transplant procedure from 1751 patients undergoing BMT were collected (Shariati Hospital). Collaborative filtering techniques allowed the processing of highly sparse records with 22.3% missing values. Ten-fold cross-validation was used to evaluate the performance of various classification algorithms trained on predicting the survival status. Modest accuracy levels were obtained in predicting the survival status (AUC = 0.69). More importantly, however, operations that had the highest chances of success were shown to be identifiable with high accuracy, e.g., 92% or 97% when identifying 74 or 31 recipients, respectively. Identifying the patients with the highest chances of survival has direct application in the prioritization of resources and in donor matching. For patients where high-confidence prediction is not achieved, assigning a probability to their survival odds has potential applications in probabilistic decision support systems and in combination with other sources of information.

  8. Intraoperative Factors that Predict the Successful Placement of Essure Microinserts.

    Science.gov (United States)

    Arthuis, Chloé J; Simon, Emmanuel G; Hébert, Thomas; Marret, Henri

    To determine whether the number of coils visualized in the uterotubal junction at the end of hysteroscopic microinsert placement predicts successful tubal occlusion. Cohort retrospective study (Canadian Task Force classification II-2). Department of obstetrics and gynecology in a teaching hospital. One hundred fifty-three women underwent tubal microinsert placement for permanent birth control from 2010 through 2014. The local institutional review board approved this study. Three-dimensional transvaginal ultrasound (3D TVU) was routinely performed 3 months after hysteroscopic microinsert placement to check position in the fallopian tube. The correlation between the number of coils visible at the uterotubal junction at the end of the hysteroscopic microinsert placement procedure and the device position on the 3-month follow-up 3D TVU in 141 patients was evaluated. The analysis included 276 microinserts placed during hysteroscopy. The median number of coils visible after the hysteroscopic procedure was 4 (interquartile range, 3-5). Devices for 30 patients (21.3%) were incorrectly positioned according to the 3-month follow-up 3D TVU, and hysterosalpingography was recommended. In those patients the median number of coils was in both the right (interquartile range, 2-4) and left (interquartile range, 1-3) uterotubal junctions. The number of coils visible at the uterotubal junction at the end of the placement procedure was the only factor that predicted whether the microinsert was well positioned at the 3-month 3D TVU confirmation (odds ratio, .44; 95% confidence interval, .28-.63). When 5 or more coils were visible, no incorrectly placed microinsert could be seen on the follow-up 3D TVU; the negative predictive value was 100%. No pregnancies were reported. The number of coils observed at the uterotubal junction at the time of microinsert placement should be considered a significant predictive factor of accurate and successful microinsert placement. Copyright © 2017

  9. Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Amy L Bauer

    2010-11-01

    Full Text Available An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF. Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in different local neighborhoods. For each of 54 TFs in Escherichia coli, for which at least five DNA binding sites are documented in RegulonDB, the TF binding sites and portions of the non-coding genome sequence are mapped to feature vectors and used in training. According to cross-validation analysis and a comparison of computational predictions against ChIP-chip data available for the TF Fis, SiteSleuth outperforms three conventional approaches: Match, MATRIX SEARCH, and the method of Berg and von Hippel. SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate.

  10. Factors Predicting Mathematics Achievement of 8th Graders in TIMSS 2015

    Directory of Open Access Journals (Sweden)

    Mehmet Hayri SARI

    2017-09-01

    Full Text Available In the study, it is aimed to investigate the student, teacher and school factors predicting mathematics achievement of Turkish 8th grade students in TIMSS 2015. The group of the study consists of 6079 students and 220 teachers who attended TIMSS from Turkey. The data of the study was obtained from student and teacher questionnaires and mathematics cognitive test scores. In the data analysis, multilevel regression analysis was used in which dependent variables were plausible mathematics scores and independent variables were student, teacher and school scale scores. According to results, 34% percent of student-level variance was explained by student-level variables. It was found that self-confidence level of students was the most important predictor of mathematics achievement among student-level variables. Additionally, educational resources at home variable was also among the important predictors of mathematics achievement. Teacher and school factors explained 29% of between school variance. Among these variables, school emphasis on academic success and teaching limited by student needs were two significant variables that could predict mathematics achievement of students.

  11. Identifying Critical Factors Influencing the Rents of Public Rental Housing Delivery by PPPs: The Case of Nanjing

    Directory of Open Access Journals (Sweden)

    Jingfeng Yuan

    2017-02-01

    Full Text Available The occupancy rate of Public Rental Housing (PRH in China is relatively low due to the unreasonable rents. At the same time, the development of PRH using Public Private Partnerships (PPPs increases the complexity of the rents. Therefore, the critical factors influencing the rents of PRH delivery by PPPs should be identified. Based on the comprehensive literature, this article identified a conceptual model for the factors influencing the rents of PRH delivery by PPPs in China, composed of 14 factors grouped in three factor packages, and discussed the relationships among three factor packages. A survey based on Nanjing was conducted to assess the relative significance of 14 factors. According to the results, six critical factors were identified: construction costs, household income, floor area and structure, transportation, market rents in the same district and public facilities. In addition, the proposed conceptual model had a good fit. The results also supported two hypothetical relationships among three factor packages: (1 the increase of the affordability of the target tenants had a positive effect on the increase of profits of private sectors; and (2 the increase of the affordability of the target tenants had a positive effect on the increase of level of the characteristics of PRH units. For future research, six critical factors and the relationships among three factor packages can be used to determine the reasonable rents for PRH delivery by PPPs in China.

  12. Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance

    OpenAIRE

    Ribeiro, Marco Tulio; Singh, Sameer; Guestrin, Carlos

    2016-01-01

    At the core of interpretable machine learning is the question of whether humans are able to make accurate predictions about a model's behavior. Assumed in this question are three properties of the interpretable output: coverage, precision, and effort. Coverage refers to how often humans think they can predict the model's behavior, precision to how accurate humans are in those predictions, and effort is either the up-front effort required in interpreting the model, or the effort required to ma...

  13. Cytological Sampling Versus Forceps Biopsy During Percutaneous Transhepatic Biliary Drainage and Analysis of Factors Predicting Success

    Energy Technology Data Exchange (ETDEWEB)

    Tapping, C. R.; Byass, O. R.; Cast, J. E. I., E-mail: james.cast@hey.nhs.uk [Hull Royal Infirmary, Department of Radiology (United Kingdom)

    2012-08-15

    Purpose: To assess the accuracy of cytological sampling and forceps biopsy in obstructing biliary lesions and to identify factors predictive of success. Methods: Consecutive patients (n = 119) with suspected malignant inoperable obstructive jaundice treated with percutaneous transhepatic biliary drainage during 7 years were included (60 male; mean age 72.5 years). All patients underwent forceps biopsy plus cytological sampling by washing the forceps device in cytological solution. Patient history, procedural and pathological records, and clinical follow-up were reviewed. Statistical analysis included chi-square test and multivariate regression analysis. Results: Histological diagnosis after forceps biopsy was more successful than cytology: Sensitivity was 78 versus 61%, and negative predictive value was 30 versus 19%. Cytology results were never positive when the forceps biopsy was negative. The cytological sample was negative and forceps sample positive in 2 cases of cholangiocarcinoma, 16 cases of pancreatic carcinoma, and 1 case of benign disease. Diagnostic accuracy was predicted by low bilirubin (p < 0.001), aspartate transaminase (p < 0.05), and white cell count (p {<=} 0.05). Conclusions: This technique is safe and effective and is recommended for histological diagnosis during PTBD in patients with inoperable malignant biliary strictures. Diagnostic yield is greater when bilirubin levels are low and there is no sepsis; histological diagnosis by way of forceps biopsy renders cytological sampling unnecessary.

  14. Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.

    Science.gov (United States)

    Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

    2016-08-01

    This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. PREDICTION OF SURGICAL TREATMENT WITH POUR PERITONITIS TAKING INTO ACCOUNT QUANTIFYING RISK FACTORS

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    І. К. Churpiy

    2012-11-01

    Full Text Available There was investigated the possibility of quantitative assessment of risk factors of complications in the treatment of diffuse peritonitis. There were ditermined 70 groups of features that are important in predicting the course of diffuse peritonitis. The proposed scheme is the definition of risk clinical course of diffuse peritonitis can quantify the severity of the original patients and in most cases is correctly to predict the results of treatment of disease.

  16. Factores pronósticos del abandono del tratamiento antituberculoso en una región endémica del Perú Predictive factors for noncompliance with tuberculosis treatment in an endemic region of Peru

    Directory of Open Access Journals (Sweden)

    Dante Roger Culqui

    2005-07-01

    Full Text Available OBJETIVO: Identificar factores de pronóstico del abandono del tratamiento antituberculoso en la provincia de Ica, Perú. MÉTODOS: Entre 1998 y 2000 se llevó a cabo un estudio de casos y testigos (razón numérica de 1:1 en la provincia de Ica. Se identificaron 55 casos de abandono del tratamiento antituberculoso. Los factores evaluados se seleccionaron a partir del modelo del campo de la salud de Lalonde. Las respectivas razones de posibilidades se calcularon por medio de análisis unifactorial y multifactorial. RESULTADOS: Se identificaron como factores pronósticos del abandono del tratamiento anti-tuberculoso los siguientes: considerar insuficiente la información proporcionada por el personal de salud sobre el tratamiento (razón de posibilidades [odds ratio, OR]: 4,20; intervalo de confianza de 95% [IC95%]: 1,77 a 10,02, considerar inadecuados los horarios para recibir el tratamiento (OR: 9,95; IC95%: 1,97 a 50,21 y consumir drogas ilícitas (OR: 7,15; IC95%: 1,69 a 30,23. CONCLUSIONES: Para mejorar el cumplimiento del régimen antituberculoso es necesario brindar a los pacientes información personalizada sobre la enfermedad y su tratamiento, además de ofrecerles horarios flexibles y apropiados para recibirlo. El consumo de drogas es el factor de riesgo más alto de abandono, por lo que resultan cruciales su identificación y seguimiento.OBJECTIVE: To identify factors that predict noncompliance with tuberculosis treatment in the province of Ica, Peru. METHODS: Between 1998 and 2000 a case-control study (1:1 ratio was conducted in the province of Ica, with 55 cases (persons who dropped out of treatment being identified. The factors evaluated were chosen from Lalonde's model of the field of health. The respective odds ratios were calculated by means of univariate analysis and multivariate analysis. RESULTS: The following factors were identified as being predictive of noncompliance with tuberculosis treatment: thinking that the

  17. Metallic ureteral stents in malignant ureteral obstruction: clinical factors predicting stent failure.

    Science.gov (United States)

    Chow, Po-Ming; Hsu, Jui-Shan; Huang, Chao-Yuan; Wang, Shuo-Meng; Lee, Yuan-Ju; Huang, Kuo-How; Yu, Hong-Jheng; Pu, Yeong-Shiau; Liang, Po-Chin

    2014-06-01

    To provide clinical outcomes of the Resonance metallic ureteral stent in patients with malignant ureteral obstruction, as well as clinical factors predicting stent failure. Cancer patients who have received Resonance stents from July 2009 to March 2012 for ureteral obstruction were included for chart review. Stent failure was detected by clinical symptoms, image studies, and renal function tests. Survival analysis for stent duration was used to estimate patency rate and factors predicting stent failure. A total of 117 stents were inserted successfully into 94 ureteral units in 79 patients. There were no major complications. These stents underwent survival analysis and proportional hazard regression. The median duration for the stents was 5.77 months. In multivariate analysis, age (P=0.043), preoperative serum creatinine level (P=0.0174), and cancer type (P=0.0494) were significant factors associated with stent failure. Cancer treatment before and after stent insertion had no effect on stent duration. Resonance stents are effective and safe in relieving malignant ureteral obstructions. Old age and high serum creatinine level are predictors for stent failure. Stents in patients with lower gastrointestinal cancers have longer functional duration.

  18. Gender and age effects on risk factor-based prediction of coronary artery calcium in symptomatic patients

    DEFF Research Database (Denmark)

    Nicoll, R; Wiklund, U; Zhao, Y

    2016-01-01

    BACKGROUND AND AIMS: The influence of gender and age on risk factor prediction of coronary artery calcification (CAC) in symptomatic patients is unclear. METHODS: From the European Calcific Coronary Artery Disease (EURO-CCAD) cohort, we retrospectively investigated 6309 symptomatic patients, 62......, diabetes and smoking were independently predictive of CAC presence in both genders. In addition to a progressive increase in CAC with age, the most important predictors of CAC presence were dyslipidaemia and diabetes (β = 0.64 and 0.63, respectively) in males and diabetes (β = 1.08) followed by smoking (β...... = 0.68) in females; these same risk factors were also important in predicting increasing CAC scores. There was no difference in the predictive ability of diabetes, hypertension and dyslipidaemia in either gender for CAC presence in patients aged 70, only...

  19. Evaluation of related factors, prediction and treatment drugs of no-reflow phenomenon in patients with acute ST-segment elevation myocardial infarction after direct PCI.

    Science.gov (United States)

    Li, Hui; Fu, Du-Guan; Liu, Fu-Yuan; Zhou, Heng; Li, Xiao-Mei

    2018-04-01

    This study determined the related factors of no-reflow phenomenon in patients with acute ST-segment elevation myocardial infarction (STEMI) after direct percutaneous coronary intervention (PCI), and evaluated related factor scores in predicting the occurrence of no-reflow phenomenon and drug treatments. A total of 203 patients with acute STEMI receiving PCI who were admitted to the Department of Cardiovascularology, Xiangyang No. 1 People's Hospital, Hubei University of Medicine (Xiangyang, China) from January 2015 to December 2016 were selected. The clinical and image data were analyzed to determine the related factors of no-reflow phenomenon after operation, and related factor scores were quantified to predict the occurrence of no-reflow phenomenon. Three drugs (diltiazem, nitroglycerin and tirofiban needles) were continuously injected in coronary arteries of patients with no-reflow phenomenon, and the effects of these drugs were analyzed. There were 38 patients (18.7%) with no-reflow phenomenon. The correlation analysis showed that 10 factors were associated with no-reflow phenomenon, in which five factors were identified as risk factors, including IRA open-up time ≥8 h, SBP 18 mg/l, thrombus loads, length of the culprit vessel ≥20 mm. The score analysis of related factors of 38 patients with no-reflow phenomenon was conducted. Three points were set for five risk factors each, and 1 point was set for the other five factors each. It was found that the score was approximately normally distributed. The average was 11.5±1.57 points and the lower limit of 95% confidence interval was >8.93 points. The effective rates of three drugs were different (P<0.05), and the pairwise comparison showed their effective rates were not fully identical (P<0.05). The results showed that: i) Τhere are 10 related factors, including five risk factors; ii) related factors with the score ≥9 points can be used for clinical prediction of STEMI after direct PCI; and iii) it is

  20. Identifying protective and risk factors for injurious falls in patients hospitalized for acute care: a retrospective case-control study

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    Emmanuel Aryee

    2017-11-01

    Full Text Available Abstract Background Admitted patients who fall and injure themselves during an acute hospitalization incur increased costs, morbidity, and mortality, but little research has been conducted on identifying inpatients at high risk to injure themselves in a fall. Falls risk assessment tools have been unsuccessful due to their low positive predictive value when applied broadly to entire hospital populations. We aimed to identify variables associated with the risk of or protection against injurious fall in the inpatient setting. We also aimed to test the variables in the ABCs mnemonic (Age > 85, Bones-orthopedic conditions, anti-Coagulation and recent surgery for correlation with injurious fall. Methods We performed a retrospective case-control study at an academic tertiary care center comparing admitted patients with injurious fall to admitted patients without fall. We collected data on the demographics, medical and fall history, outcomes, and discharge disposition of injured fallers and control patients. We performed multivariate analysis of potential risk factors for injurious fall with logistic regression to calculate adjusted odds ratios. Results We identified 117 injured fallers and 320 controls. There were no differences in age, anti-coagulation use or fragility fractures between cases and controls. In multivariate analysis, recent surgery (OR 0.46, p = 0.003 was protective; joint replacement (OR 5.58, P = 0.002, psychotropic agents (OR 2.23, p = 0.001, the male sex (OR 2.08, p = 0.003 and history of fall (OR 2.08, p = 0.02 were significantly associated with injurious fall. Conclusion In this study, the variables in the ABCs parameters were among the variables not useful for identifying inpatients at risk of injuring themselves in a fall, while other non-ABCs variables demonstrated a significant association with injurious fall. Recent surgery was a protective factor, and practices around the care of surgical patients could be

  1. In-training factors predictive of choosing and sustaining a productive academic career path in neurological surgery.

    Science.gov (United States)

    Crowley, R Webster; Asthagiri, Ashok R; Starke, Robert M; Zusman, Edie E; Chiocca, E Antonio; Lonser, Russell R

    2012-04-01

    Factors during neurosurgical residency that are predictive of an academic career path and promotion have not been defined. To determine factors associated with selecting and sustaining an academic career in neurosurgery by analyzing in-training factors for all graduates of American College of Graduate Medical Education (ACGME)-accredited programs between 1985 and 1990. Neurological surgery residency graduates (between 1985 and 1990) from ACGME-approved training programs were analyzed to determine factors associated with choosing an academic career path and having academic success. Information was available for 717 of the 720 (99%) neurological surgery resident training graduates (678 male, 39 female). One hundred thirty-eight graduates (19.3%) held full-time academic positions. One hundred seven (14.9%) were professors and 35 (4.9%) were department chairs/chiefs. An academic career path/success was associated with more total (5.1 vs 1.9; P female trainees (2.6 vs 0.9 publications; P career but not predictive of becoming professor or chair/chief (P > .05). Defined in-training factors including number of total publications, number of first-author publications, and program size are predictive of residents choosing and succeeding in an academic career path.

  2. Thyroiditis de Quervain. Are there predictive factors for long-term hormone-replacement?

    Science.gov (United States)

    Schenke, S; Klett, R; Braun, S; Zimny, M

    2013-01-01

    Subacute thyroiditis is a usually self-limiting disease of the thyroid. However, approximately 0.5-15% of the patients require permanent thyroxine substitution. Aim was to determine predictive factors for the necessity of long-term hormone-replacement (LTH). We retrospectively reviewed the records of 72 patients with subacute thyroiditis. Morphological and serological parameters as well as type of therapy were tested as predictive factors of consecutive hypothyroidism. Mean age was 49 ± 11 years, f/m-ratio was 4.5 : 1. Thyroid pain and signs of hyperthyroidism were leading symptoms. Initial subclinical or overt hyperthyroidism was found in 20% and 37%, respectively. Within six months after onset 15% and 1.3% of the patients developed subclinical or overt hypothyroidism, respectively. At latest follow-up 26% were classified as liable to LTH. At onset the thyroid was enlarged in 64%, and at latest follow-up in 8.3%, with a significant reduction of the thyroid volume after three months. At the endpoint the thyroid volume was less in patients in the LTH group compared with the non-LTH group (41.7% vs. 57.2% of sex-adjusted upper norm, p = 0.041). Characteristic ultrasonographic features occurred in 74% of the patients in both lobes. Serological and morphological parameters as well as type of therapy were not related with the need of LTH. In this study the proportion of patients who received LTH was 26%. At the endpoint these patients had a lower thyroid volume compared with euthyroid patients. No predictive factors for LTH were found.

  3. Modelo Preditivo para Cesariana com Uso de Fatores de Risco Predictive Model using Risk Factors for Cesarean Section

    Directory of Open Access Journals (Sweden)

    Alfredo de Almeida Cunha

    2002-01-01

    dependent variable was cesarean section (c-section. Independent variables were antepartum factors related to c-section. Logistic regression was used to develop a predictive model. Results: our model showed risk of c-section according to the following variables: maternal age under 20 years (OR = 0.396 and over 28 years (OR = 2.133; previous vaginal deliveries (OR = 0.626; previous c-section (OR = 4.576; prenatal care (OR = 2.346; breech presentation (OR = 4.174; twin pregnancies (OR = 14.065; late obstetrical hemorrhage (OR = 28.189; mild preeclampsia (OR = 2.180; severe preeclampsia OR=16.738; chronic hypertension OR=4.927 and other clinical problems (OR = 2.012. The predictive model had a concordance of 82.3% between probabilities and responses. Conclusions: our study identified 12 antepartum factors related to c-section. It was possible to develop a cesarean section predictive model taking into account all previously identified antepartum risk factors.

  4. Intrinsic predictive factors for ankle sprain in active university students: a prospective study.

    Science.gov (United States)

    de Noronha, M; França, L C; Haupenthal, A; Nunes, G S

    2013-10-01

    The ankle is the joint most affected among the sports-related injuries. The current study investigated whether certain intrinsic factors could predict ankle sprains in active students. The 125 participants were submitted to a baseline assessment in a single session were then followed-up for 52 weeks regarding the occurrence of sprain. The baseline assessment were performed in both ankles and included the questionnaire Cumberland ankle instability tool - Portuguese, the foot lift test, dorsiflexion range of motion, Star Excursion Balance Test (SEBT), the side recognition task, body mass index, and history of previous sprain. Two groups were used for analysis: one with those who suffered an ankle sprain and the other with those who did not suffer an ankle sprain. After Cox regression analysis, participants with history of previous sprain were twice as likely to suffer subsequent sprains [hazard ratio (HR) 2.21 and 95% confidence interval (CI) 1.07-4.57] and people with better performance on the SEBT in the postero-lateral (PL) direction were less likely to suffer a sprain (HR 0.96 and 95% CI 0.92-0.99). History of previous sprain was the strongest predictive factor and a weak performance on SEBT PL was also considered a predictive factor for ankle sprains. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Predictive factors of work disability in rheumatoid arthritis: a systematic literature review.

    NARCIS (Netherlands)

    Croon, de E.M.; Sluiter, J.K.; Nijssen, TF; Dijkmans, B.A.C.; Lankhorst, G.J.; Frings-Dresen, MH

    2004-01-01

    BACKGROUND: Work disability-a common outcome of rheumatoid arthritis (RA)-is a societal (for example, financial costs) and individual problem (for example, loss of status, income, social support, and distraction from pain and distress). Until now, factors that predict work disability in RA have not

  6. [Dysphagia screening on resumption of oral intake in inpatients predictive factor for the resumption of oral intake].

    Science.gov (United States)

    Takayanagi, Hirohisa; Endo, Tomonori; Nakayama, Tuguhisa; Kato, Takakuni

    2013-06-01

    There is much concern about the acute phase of restarting an oral diet for hospital inpatients who have been prohibited from any oral intake. We found predictive factors for the successful resumption of oral intake in such patients. A total of 186 subjects who had been hospitalized without oral intake were screened for dysphagia between January 1st and December 31st in 2010 (mean age 80.9 years), and formed the study population. We observed them from the initial consultation day until the discharge. (mean days 32.6) We examined factors of age, sex, appetite, gag reflex, tongue activity, the repetitive saliva swallowing test (RSST), obeying commands, the status of the laryngopharynx, laryngeal sensation and the 3 ml water swallowing test under endoscopy. We excluded those who died in hospital after dysphagia screening because they were obviously lost to follow-up. One hundred and twelve patients (60.2%) could resume oral intake, 54 patients could not and 20 (10.8%) died. Logistic regression analysis identified seven significant factors in predicting the resumption of oral intake : 1) age (p = 0.01, OR = 0.938, 95% CI 0.903-0.976); 2) sex (p = 0.21, OR = 2.15, 95% CI 1.124-4.128); 3) appetite (p = 0.041, OR = 1.983, 95% CI 1.029-3.821); 4) gag reflex (p = 0.06, OR = 1.932, 95% CI 0.971-3.844); 5) tongue activity (P = 0.002, OR = 3.825, 95% CI 1.647-8.883); 6) RSST (P = 0.013, OR = 2.284, 95% CI 1.186-4.397); 7) obeying commands (p = 0.02, OR = 3.005, 95% CI 1.507-5.993); 8) the status of the laryngopharynx (P = 0.668, OR = 0.668, 95% CI 0.351-1.272); 9) laryngeal sensation (P = 0.081, OR = 1.841, 95% CI 0.928-3.650); and the 3 ml water swallowing test under endoscopy (P = 0.000, OR = 0.226, 95% CI 0.102-0.499). These predictive factors could be very useful for dysphagia screening to help forecast the successful resumption of oral intake in affected patients. When the likelihood of dysphagia and the onset of aspiration pneumonia are suggested by dysphagia screening

  7. On the incremental validity of irrational beliefs to predict subjective well-being while controlling for personality factors.

    Science.gov (United States)

    Spörrle, Matthias; Strobel, Maria; Tumasjan, Andranik

    2010-11-01

    This research examines the incremental validity of irrational thinking as conceptualized by Albert Ellis to predict diverse aspects of subjective well-being while controlling for the influence of personality factors. Rational-emotive behavior therapy (REBT) argues that irrational beliefs result in maladaptive emotions leading to reduced well-being. Although there is some early scientific evidence for this relation, it has never been investigated whether this connection would still persist when statistically controlling for the Big Five personality factors, which were consistently found to be important determinants of well-being. Regression analyses revealed significant incremental validity of irrationality over personality factors when predicting life satisfaction, but not when predicting subjective happiness. Results are discussed with respect to conceptual differences between these two aspects of subjective well-being.

  8. Using exploratory factor analysis of FFQ data to identify dietary patterns among Yup'ik people.

    Science.gov (United States)

    Ryman, Tove K; Austin, Melissa A; Hopkins, Scarlett; Philip, Jacques; O'Brien, Diane; Thummel, Kenneth; Boyer, Bert B

    2014-03-01

    An FFQ developed by the Center for Alaska Native Health Research for studies in Yup'ik people includes market foods and subsistence foods such as moose, seal, waterfowl and salmon that may be related to disease risk. Because the FFQ contains >100 food items, we sought to characterize dietary patterns more simply for use in ongoing pharmacogenomics studies. Exploratory factor analysis was used to derive a small number of 'factors' that explain a substantial amount of the variation in the Yup'ik diet. We estimated factor scores and measured associations with demographic characteristics and biomarkers. South-west Alaska, USA. Yup'ik people (n 358) aged ≥18 years. We identified three factors that each accounted for ≥10 % of the common variance: the first characterized by 'processed foods' (e.g. salty snacks, sweetened cereals); the second by 'fruits and vegetables' (e.g. fresh citrus, potato salad); and the third by 'subsistence foods' (seal or walrus soup, non-oily fish). Participants from coastal communities had higher values for the 'subsistence' factor, whereas participants from inland communities had higher values for the 'fruits and vegetables' factor. A biomarker of marine intake, δ 15N, was correlated with the 'subsistence' factor, whereas a biomarker of corn- and sugarcane-based market food intake, δ 13C, was correlated with 'processed foods'. The exploratory factor analysis identified three factors that appeared to reflect dietary patterns among Yup'ik based on associations with participant characteristics and biomarkers. These factors will be useful for chronic disease studies in this population.

  9. A general psychopathology factor in early adolescence.

    Science.gov (United States)

    Patalay, Praveetha; Fonagy, Peter; Deighton, Jessica; Belsky, Jay; Vostanis, Panos; Wolpert, Miranda

    2015-07-01

    Recently, a general psychopathology dimension reflecting common aspects among disorders has been identified in adults. This has not yet been considered in children and adolescents, where the focus has been on externalising and internalising dimensions. To examine the existence, correlates and predictive value of a general psychopathology dimension in young people. Alternative factor models were estimated using self-reports of symptoms in a large community-based sample aged 11-13.5 years (N = 23 477), and resulting dimensions were assessed in terms of associations with external correlates and future functioning. Both a traditional two-factor model and a bi-factor model with a general psychopathology bi-factor fitted the data well. The general psychopathology bi-factor best predicted future psychopathology and academic attainment. Associations with correlates and factor loadings are discussed. A general psychopathology factor, which is equal across genders, can be identified in young people. Its associations with correlates and future functioning indicate that investigating this factor can increase our understanding of the aetiology, risk and correlates of psychopathology. © The Royal College of Psychiatrists 2015.

  10. Identifying risk factors for PTSD in women seeking medical help after rape.

    Science.gov (United States)

    Tiihonen Möller, Anna; Bäckström, Torbjörn; Söndergaard, Hans Peter; Helström, Lotti

    2014-01-01

    Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD) among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD. Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at Stockholm South Hospital, Sweden. Baseline assessments of mental health were carried out and followed up after six months. Thirty-nine percent of the women had developed PTSD at the six month assessment, and 47% suffered from moderate or severe depression. The major risk factors for PTSD were having been sexually assaulted by more than one person, suffering from acute stress disorder (ASD) shortly after the assault, having been exposed to several acts during the assault, having been injured, having co-morbid depression, and having a history of more than two earlier traumas. Further, ASD on its own was found to be a poor predictor of PTSD because of the substantial ceiling effect after sexual assaults. Development of PTSD is common in the aftermath of sexual assaults. Increased risk of developing PTSD is caused by a combination of victim vulnerability and the extent of the dramatic nature of the current assault. By identifying those women at greatest risk of developing PTSD appropriate therapeutic resources can be directed.

  11. Factors affecting seasonal habitat use, and predicted range of two tropical deer in Indonesian rainforest

    Science.gov (United States)

    Rahman, Dede Aulia; Gonzalez, Georges; Haryono, Mohammad; Muhtarom, Aom; Firdaus, Asep Yayus; Aulagnier, Stéphane

    2017-07-01

    There is an urgent recognized need for conservation of tropical forest deer. In order to identify some environmental factors affecting conservation, we analyzed the seasonal habitat use of two Indonesian deer species, Axis kuhlii in Bawean Island and Muntiacus muntjak in south-western Java Island, in response to several physical, climatic, biological, and anthropogenic variables. Camera trapping was performed in different habitat types during both wet and dry season to record these elusive species. The highest number of photographs was recorded in secondary forest and during the dry season for both Bawean deer and red muntjac. In models, anthropogenic and climatic variables were the main predictors of habitat use. Distances to cultivated area and to settlement were the most important for A. kuhlii in the dry season. Distances to cultivated area and annual rainfall were significant for M. muntjak in both seasons. Then we modelled their predictive range using Maximum entropy modelling (Maxent). We concluded that forest landscape is the fundamental scale for deer management, and that secondary forests are potentially important landscape elements for deer conservation. Important areas for conservation were identified accounting of habitat transformation in both study areas.

  12. Identifying risk factors associated with smear positivity of pulmonary tuberculosis in Kazakhstan.

    Directory of Open Access Journals (Sweden)

    Sabrina Hermosilla

    Full Text Available Sputum smear-positive tuberculosis (TB patients have a high risk of transmission and are of great epidemiological and infection control significance. Little is known about the smear-positive populations in high TB burden regions, such as Kazakhstan. The objective of this study is to characterize the smear-positive population in Kazakhstan and identify associated modifiable risk factors.Data on incident TB cases' (identified between April 2012 and March 2014 socio-demographic, risk behavior, and comorbidity characteristics were collected in four regions of Kazakhstan through structured survey and medical record review. We used multivariable logistic regression to determine factors associated with smear positivity.Of the total sample, 193 (34.3% of the 562 study participants tested smear-positive. In the final adjusted multivariable logistic regression model, sex (adjusted odds ratio (aOR = 2.0, 95% CI:1.3-3.1, p < 0.01, incarceration (aOR = 3.6, 95% CI:1.2-11.1, p = 0.03, alcohol dependence (aOR = 2.6, 95% CI:1.2-5.7, p = 0.02, diabetes (aOR = 5.0, 95% CI:2.4-10.7, p < 0.01, and physician access (aOR = 2.7, 95% CI:1.3-5.5p < 0.01 were associated with smear-positivity.Incarceration, alcohol dependence, diabetes, and physician access are associated with smear positivity among incident TB cases in Kazakhstan. To stem the TB epidemic, screening, treatment and prevention policies should address these factors.

  13. High-risk carotid plaques identified by CT-angiogram can predict acute myocardial infarction.

    Science.gov (United States)

    Mosleh, Wassim; Adib, Keenan; Natdanai, Punnanithinont; Carmona-Rubio, Andres; Karki, Roshan; Paily, Jacienta; Ahmed, Mohamed Abdel-Aal; Vakkalanka, Sujit; Madam, Narasa; Gudleski, Gregory D; Chung, Charles; Sharma, Umesh C

    2017-04-01

    Prior studies identified the incremental value of non-invasive imaging by CT-angiogram (CTA) to detect high-risk coronary atherosclerotic plaques. Due to their superficial locations, larger calibers and motion-free imaging, the carotid arteries provide the best anatomic access for the non-invasive characterization of atherosclerotic plaques. We aim to assess the ability of predicting obstructive coronary artery disease (CAD) or acute myocardial infarction (MI) based on high-risk carotid plaque features identified by CTA. We retrospectively examined carotid CTAs of 492 patients that presented with acute stroke to characterize the atherosclerotic plaques of the carotid arteries and examined development of acute MI and obstructive CAD within 12-months. Carotid lesions were defined in terms of calcifications (large or speckled), presence of low-attenuation plaques, positive remodeling, and presence of napkin ring sign. Adjusted relative risks were calculated for each plaque features. Patients with speckled (<3 mm) calcifications and/or larger calcifications on CTA had a higher risk of developing an MI and/or obstructive CAD within 1 year compared to patients without (adjusted RR of 7.51, 95%CI 1.26-73.42, P = 0.001). Patients with low-attenuation plaques on CTA had a higher risk of developing an MI and/or obstructive CAD within 1 year than patients without (adjusted RR of 2.73, 95%CI 1.19-8.50, P = 0.021). Presence of carotid calcifications and low-attenuation plaques also portended higher sensitivity (100 and 79.17%, respectively) for the development of acute MI. Presence of carotid calcifications and low-attenuation plaques can predict the risk of developing acute MI and/or obstructive CAD within 12-months. Given their high sensitivity, their absence can reliably exclude 12-month events.

  14. Predictive factors from videourodynamic study for delayed urinary continence after laparoscopic radical prostatectomy

    Directory of Open Access Journals (Sweden)

    Kuan-Tang Huang

    2015-03-01

    Conclusion: Preoperative small bladder capacity at FS, large prostate, and BOO are predicting factors of SUI at 6 months after LRP. Baseline DO and BOO did not have an impact on postoperative urgency or UUI.

  15. Serial analysis of gene expression identifies connective tissue growth factor expression as a prognostic biomarker in gallbladder cancer.

    Science.gov (United States)

    Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban

    2008-05-01

    Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

  16. Prediction of human pharmacokinetics of activated recombinant factor VII and B-domain truncated factor VIII from animal population pharmacokinetic models of haemophilia

    DEFF Research Database (Denmark)

    Larsen, Malte Selch; Juul, Rasmus Vestergaard; Groth, Andreas Velsing

    2018-01-01

    activated factor VII (rFVIIa) and recombinant factor VIII (rFVIII) in several experimental animal models using population PK modelling, and apply a simulation-based approach to evaluate how well the developed animal population PK models predict human PK. PK models were developed for rFVIIa and r...

  17. Predictive factors for perioperative blood transfusion in neck dissection.

    Science.gov (United States)

    Abu-Ghanem, Sara; Warshavsky, Anton; Carmel, Narin-Nard; Abu-Ghanem, Yasmin; Abergel, Avraham; Fliss, Dan M; Yehuda, Moshe

    2016-04-01

    There is growing interest in reducing the exposure of patients to allogeneic blood transfusions by lowering preoperative cross-matched blood ordering and adopting alternative practices, such as autologous blood donations. Our aim was to investigate the predictors for perioperative blood transfusion (PBT) in head and neck cancer patients undergoing neck dissection (ND). Retrospective cohort study. Retrospective observational study. All patients who underwent ND between January 2011 and August 2014. The primary outcome measure was PBT. Predictors tested included: gender, age, American Society of Anesthesiologists comorbidity score, Charlson comorbidity index, preoperative hemoglobin level, head and neck primary tumor location, tumor and nodal staging, side and laterality of ND, central versus lateral ND, elective ND, preoperative chemotherapy/radiotherapy/I(131) therapy, history of previous ND, other surgical procedures in addition to the ND, bone resection, use and type of reconstruction, and the use of bony free flap reconstruction. Twenty-one preoperative and operative variables were tested for an association with PBT using univariate and multivariate analyses. Multivariate analysis found only the following three predictors to be significantly associated with PBT in patients undergoing ND: low preoperative hemoglobin level, advanced N stage, and concurrent reconstructive surgery. Evaluation of specific risk factors for predicting the need for PBT prior to neck dissection may be helpful in identifying the head and neck cancer patients in whom preoperative ordering of cross-matched blood is required or who could benefit from alternative means, such as preoperative autologous blood donation. 4. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  18. State-of-the-Art Review on Sustainable Design and Construction of Quieter Pavements—Part 2: Factors Affecting Tire-Pavement Noise and Prediction Models

    Directory of Open Access Journals (Sweden)

    Okan Sirin

    2016-07-01

    Full Text Available Traffic noise is a combination of noises produced from a number of sources. Of all the traffic noise sources, tire-pavement noise, which is emitted as a result of the interaction of rolling, slipping, or dragging tires and the pavement surface, is the dominant contributor of overall noise, particularly when vehicles are moving at higher speeds. Therefore, a number of research studies have been conducted to identify and analyze the factors affecting the generation of tire-pavement interaction noise. This helps in identifying and selecting appropriate noise mitigation techniques. In this paper, an extensive literature survey on the factors affecting tire-pavement noise is presented, and different views on the impact of each individual factor are discussed. From the literature survey, it is also evident that there is a potential correlation between pavement’s material characteristics and tire-pavement noise. A comprehensive discussion about this correlation is presented in the paper. In addition, this paper discusses various mathematical models for predicting pavement noise, and their advantages and shortcomings.

  19. Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

    Science.gov (United States)

    Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

    2003-01-01

    Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

  20. A study on improvement of scaling factor prediction using artificial neural network

    International Nuclear Information System (INIS)

    Lee, Sang Chul; Hwang, Ki Ha; Kang, Sang Hee; Lee, Kun Jai

    2003-01-01

    Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed knowledge of the natures and quantities of radionuclides in waste package. Many of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the indirect method by which the concentrations of DTM (Difficult-to Measure) nuclide is decided using the relation of concentrations (Scaling Factor) between Key (Easy-to-Measure) nuclide and DTM nuclide with measured concentrations of Key nuclide. In general, scaling factor is determined by using of log mean average (LMA) and regression. These methods are adequate to apply most corrosion product nuclides. But in case of fission product nuclides and some corrosion product nuclides, the predicted values aren't well matched with the original values. In this study, the models using artificial neural network (ANN) for C-14 and Sr-90 are compared with those using LMA and regression. The assessment of models is executed in the two parts divided by a training part and a validation part. For all of two nuclides in the training part, the predicted values using ANN are well matched with the measured values compared with those using LMA and regression. In the validation part, the accuracy of the predicted values using ANN is better than that using LMA and is similar to or better than that using regression. It is concluded that the predicted values using ANN model are better than those using conventional model in some nuclides and ANN model can be used as the complement of LMA and regression model

  1. Factors Predicting HBsAg Seroclearance and Alanine Transaminase Elevation in HBeAg-Negative Hepatitis B Virus-Infected Patients with Persistently Normal Liver Function.

    Directory of Open Access Journals (Sweden)

    Tai-Long Chien

    Full Text Available A certain proportion of hepatitis B virus (HBV-infected patients with persistently normal alanine transaminase (ALT levels have significant fibrosis. Using liver stiffness measurements (Fibroscan® and laboratory data, including serum ALT, quantitative HBsAg (qHBsAg, and HBV DNA, we attempted to predict the natural histories of these patients.Non-cirrhotic HBeAg-negative chronic hepatitis B patients with persistently normal ALT were followed up prospectively with the end points of HBsAg seroclearance and ALT elevation above the upper limit of normal. The factors that were predictive of the end points were identified.A total of 235 patients with an average age of 48.1 +/- 10.7 years were followed up for 7 years. Eight patients (3.4% lost HBsAg, and 15 patients (6.4% experienced ALT elevation. The overall cumulative HBsAg seroclearances were 0.4%, 1.3% and 2.3% at years 1, 3 and 5, respectively. Regarding HBsAg seroclearance, the qHBsAg (< 30 IU/ml cutoff resulted in a hazard ratio (HR of 19.6 with a 95% confidence interval (CI of 2.2-166.7 (P = 0.008. The baseline ALT level (odd ratio (OR 1.075, 95% CI 1.020-1.132, P = 0.006 and a qHBsAg above 1000 IU/ml (3.7, 1.1-12.4, P = 0.032 were associated with ALT elevation. Limited to men, the baseline liver stiffness (1.6, 1.0-2.5, P = 0.031 and a qHBsAg above 1000 IU/ml (10.4, 2.1-52.4, P = 0.004 were factors that were independently associated with ALT elevation.A low qHBsAg level predicted HBsAg clearance. Baseline ALT and a qHBsAg above 1000 IU/ml were independent predictive factors for ALT elevation. Among the men, the independent predictive factors for ALT elevation were qHBsAg and liver stiffness.

  2. Prediction of safety critical software operational reliability from test reliability using testing environment factors

    International Nuclear Information System (INIS)

    Jung, Hoan Sung; Seong, Poong Hyun

    1999-01-01

    It has been a critical issue to predict the safety critical software reliability in nuclear engineering area. For many years, many researches have focused on the quantification of software reliability and there have been many models developed to quantify software reliability. Most software reliability models estimate the reliability with the failure data collected during the test assuming that the test environments well represent the operation profile. User's interest is however on the operational reliability rather than on the test reliability. The experiences show that the operational reliability is higher than the test reliability. With the assumption that the difference in reliability results from the change of environment, from testing to operation, testing environment factors comprising the aging factor and the coverage factor are developed in this paper and used to predict the ultimate operational reliability with the failure data in testing phase. It is by incorporating test environments applied beyond the operational profile into testing environment factors. The application results show that the proposed method can estimate the operational reliability accurately. (Author). 14 refs., 1 tab., 1 fig

  3. Highly predictive support vector machine (SVM) models for anthrax toxin lethal factor (LF) inhibitors.

    Science.gov (United States)

    Zhang, Xia; Amin, Elizabeth Ambrose

    2016-01-01

    Anthrax is a highly lethal, acute infectious disease caused by the rod-shaped, Gram-positive bacterium Bacillus anthracis. The anthrax toxin lethal factor (LF), a zinc metalloprotease secreted by the bacilli, plays a key role in anthrax pathogenesis and is chiefly responsible for anthrax-related toxemia and host death, partly via inactivation of mitogen-activated protein kinase kinase (MAPKK) enzymes and consequent disruption of key cellular signaling pathways. Antibiotics such as fluoroquinolones are capable of clearing the bacilli but have no effect on LF-mediated toxemia; LF itself therefore remains the preferred target for toxin inactivation. However, currently no LF inhibitor is available on the market as a therapeutic, partly due to the insufficiency of existing LF inhibitor scaffolds in terms of efficacy, selectivity, and toxicity. In the current work, we present novel support vector machine (SVM) models with high prediction accuracy that are designed to rapidly identify potential novel, structurally diverse LF inhibitor chemical matter from compound libraries. These SVM models were trained and validated using 508 compounds with published LF biological activity data and 847 inactive compounds deposited in the Pub Chem BioAssay database. One model, M1, demonstrated particularly favorable selectivity toward highly active compounds by correctly predicting 39 (95.12%) out of 41 nanomolar-level LF inhibitors, 46 (93.88%) out of 49 inactives, and 844 (99.65%) out of 847 Pub Chem inactives in external, unbiased test sets. These models are expected to facilitate the prediction of LF inhibitory activity for existing molecules, as well as identification of novel potential LF inhibitors from large datasets. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Identifying the factors that affect the job satisfaction of early career Notre Dame graduate physiotherapists.

    Science.gov (United States)

    Bacopanos, Eleni; Edgar, Susan

    2016-11-01

    Objective Previous studies have highlighted the short career intentions and high attrition rates of physiotherapists from the profession. The aim of the present study was to examine the job satisfaction and attrition rates of early career physiotherapists graduating from one Western Australian university. Methods A self-administered online survey was conducted of 157 Notre Dame physiotherapy graduates (2006-2012), incorporating a job satisfaction rating scale. Results Results showed that lowered job satisfaction was related to working in the cardiorespiratory area of physiotherapy and working in multiple jobs since graduation. The majority of graduates did not predict a long-term career in physiotherapy, highlighting a lack of career progression and limited scope of practice as influential factors. Conclusions Job satisfaction in early career physiotherapists varies across different clinical areas of practice related to several factors, including challenge and flexibility. New roles in the profession, including extended scope roles, may impact on the future job satisfaction of physiotherapists. Further studies are needed to explore the effect of these roles on workforce trends, including attrition rates. What is known about the topic? Physiotherapists predict careers of 10 years or less on entry into the profession. No previous studies have explored the individual factors influencing job satisfaction in early career physiotherapists across different clinical settings. What does this paper add? This study highlights specific factors influencing the job satisfaction of early career physiotherapists, including clinical area of practice. Physiotherapists working in the cardiorespiratory area were less satisfied, as were physiotherapists undertaking multiple positions since graduation. What are the implications for practitioners? This study informs employers and workforce planners on the factors affecting job satisfaction in early career physiotherapists. In addition

  5. Comparison of Predictive Factors for Postoperative Incontinence of Holmium Laser Enucleation of the Prostate by the Surgeons' Experience During Learning Curve.

    Science.gov (United States)

    Shigemura, Katsumi; Tanaka, Kazushi; Yamamichi, Fukashi; Chiba, Koji; Fujisawa, Masato

    2016-03-01

    To detect predictive factors for postoperative incontinence following holmium laser enucleation of the prostate (HoLEP) according to surgeon experience (beginner or experienced) and preoperative clinical data. Of 224 patients, a total of 203 with available data on incontinence were investigated. The potential predictive factors for post-HoLEP incontinence included clinical factors, such as patient age, and preoperative urodynamic study results, including detrusor overactivity (DO). We also classified the surgeons performing the procedure according to their HoLEP experience: beginner (predictive factor at the super-short period (the next day of catheter removal: odds ratio [OR], 3.375; P=0.000). Additionally, patient age, surgeon mentorship (inverse correlation), and prostate volume were significant predictive factors at the 1-month interval after HoLEP (OR, 1.072; P=0.004; OR, 0.251; P=0.002; and OR, 1.008; P=0.049, respectively). With regards to surgeon experience, DO and preoperative International Prostate Symptom Score (inverse) at the super-short period, and patient age and mentorship (inverse correlation) at the 1-month interval after HoLEP (OR, 3.952; P=0.002; OR, 1.084; P=0.015; and OR,1.084; P=0.015; OR, 0.358; P=0.003, respectively) were significant predictive factors for beginners, and first desire to void (FDV) at 1 month after HoLEP (OR, 1.009; P=0.012) was a significant predictive factor for experienced surgeons in multivariate analysis. Preoperative DO, IPSS, patient age, and surgeon mentorship were significant predictive factors of postoperative patient incontinence for beginner surgeons, while FDV was a significant predictive factors for experienced surgeons. These findings should be taken into account by surgeons performing HoLEP to maximize the patient's quality of life with regards to urinary continence.

  6. A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

    Science.gov (United States)

    Zhang, Yongqin; Iman, Kory

    2018-05-01

    Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

  7. [Encopresis--predictive factors and outcome].

    Science.gov (United States)

    Mehler-Wex, Claudia; Scheuerpflug, Peter; Peschke, Nicole; Roth, Michael; Reitzle, Karl; Warnke, Andreas

    2005-10-01

    comparison of diagnostic, clinical and therapeutic features and their predictive value for the outcome of encopresis in children and adolescents. 85 children and adolescents (aged 9.6 +/- 3.2 years) with severe encopresis (ICD 10: F98.1) were investigated during inpatient treatment and 35 of them again 5.5 +/- 1.8 years later. Mentally retarded patients were excluded. Inpatient therapy consisted of treating constipation and/or stool regulation by means of laxatives, behavioural approaches, and the specific therapy of comorbid psychiatric disorders. During inpatient treatment 22% of the patients experienced total remission, 8% an unchanged persistence of symptoms. Of the 35 patients studied at follow-up 5.5 years later, 40% were symptom-free. As main result, prognostic outcome depended significantly on sufficient treatment of obstipation. Another important factor was the specific therapeutic approach to psychiatric comorbidity, especially to ADHD. The outcome for patients with comorbid ICD 10: F43 was significantly better than for the other patients. Those who were symptom-free at discharge had significantly better long-term outcomes. Decisive to the success of encopresis treatment were the stool regulation and the specific therapy of associated psychiatric illnesses, in particular of ADHD. Inpatient treatment revealed significantly better long-term outcomes where total remission had been achieved by the time of discharge from hospital.

  8. Identifying factors associated with the discharge of male State patients from Weskoppies Hospital

    Directory of Open Access Journals (Sweden)

    Riaan G. Prinsloo

    2017-12-01

    Full Text Available Background: Designated psychiatric facilities are responsible for the care, treatment and reintegration of State patients. The necessary long-term care places a considerable strain on health-care resources. Resource use should be optimised while managing the risks that patients pose to themselves and the community. Identifying unique factors associated with earlier discharge may decrease the length of stay. Factors associated with protracted inpatient care without discharge could identify patients who require early and urgent intervention. Aim: We identify socio-economic, demographic, psychiatric and charge-related factors associated with the discharge of male State patients. Methods: We reviewed the files of discharged and admitted forensic State patients at Weskoppies Psychiatric Hospital. Data were captured in an electronic recording sheet. The association between factors and the outcome measure (discharged vs. admitted was determined using chi-squared tests and Fischer’s exact tests. Results: Discharged State patients were associated with being a primary caregiver (p = 0.031 having good insight into illness (p = 0.025 or offence (p = 0.005 and having had multiple successful leaves of absences. A lack of substance abuse during admission (p = 0.027, an absence of a diagnosis of substance use disorder (p = 0.013 and the absence of verbal and physical aggression (p = 0.002 and p = 0.016 were associated with being discharged. Prolonged total length of stay (9–12 years, p = 0.031 and prolonged length of stay in open wards (6–9 years, p = 0.000 were associated with being discharged. A history of previous offences (p = 0.022, a diagnosis of substance use disorder (p = 0.023, recent substance abuse (p = 0.018 and a history of physical aggression since admission (p = 0.017 were associated with continued admission. Conclusion: Discharge of State patients is associated with an absence of substance abuse, lack of aggression

  9. Predictive models for pressure ulcers from intensive care unit electronic health records using Bayesian networks.

    Science.gov (United States)

    Kaewprag, Pacharmon; Newton, Cheryl; Vermillion, Brenda; Hyun, Sookyung; Huang, Kun; Machiraju, Raghu

    2017-07-05

    We develop predictive models enabling clinicians to better understand and explore patient clinical data along with risk factors for pressure ulcers in intensive care unit patients from electronic health record data. Identifying accurate risk factors of pressure ulcers is essential to determining appropriate prevention strategies; in this work we examine medication, diagnosis, and traditional Braden pressure ulcer assessment scale measurements as patient features. In order to predict pressure ulcer incidence and better understand the structure of related risk factors, we construct Bayesian networks from patient features. Bayesian network nodes (features) and edges (conditional dependencies) are simplified with statistical network techniques. Upon reviewing a network visualization of our model, our clinician collaborators were able to identify strong relationships between risk factors widely recognized as associated with pressure ulcers. We present a three-stage framework for predictive analysis of patient clinical data: 1) Developing electronic health record feature extraction functions with assistance of clinicians, 2) simplifying features, and 3) building Bayesian network predictive models. We evaluate all combinations of Bayesian network models from different search algorithms, scoring functions, prior structure initializations, and sets of features. From the EHRs of 7,717 ICU patients, we construct Bayesian network predictive models from 86 medication, diagnosis, and Braden scale features. Our model not only identifies known and suspected high PU risk factors, but also substantially increases sensitivity of the prediction - nearly three times higher comparing to logistical regression models - without sacrificing the overall accuracy. We visualize a representative model with which our clinician collaborators identify strong relationships between risk factors widely recognized as associated with pressure ulcers. Given the strong adverse effect of pressure ulcers

  10. Prediction of Balance Compensation After Vestibular Schwannoma Surgery.

    Science.gov (United States)

    Parietti-Winkler, Cécile; Lion, Alexis; Frère, Julien; Perrin, Philippe P; Beurton, Renaud; Gauchard, Gérome C

    2016-06-01

    Background Balance compensation after vestibular schwannoma (VS) surgery is under the influence of specific preoperative patient and tumor characteristics. Objective To prospectively identify potential prognostic factors for balance recovery, we compared the respective influence of these preoperative characteristics on balance compensation after VS surgery. Methods In 50 patients scheduled for VS surgical ablation, we measured postural control before surgery (BS), 8 (AS8) days after, and 90 (AS90) days after surgery. Based on factors found previously in the literature, we evaluated age, body mass index and preoperative physical activity (PA), tumor grade, vestibular status, and preference for visual cues to control balance as potential prognostic factors using stepwise multiple regression models. Results An asymmetric vestibular function was the sole significant explanatory factor for impaired balance performance BS, whereas the preoperative PA alone significantly contributed to higher performance at AS8. An evaluation of patients' balance recovery over time showed that PA and vestibular status were the 2 significant predictive factors for short-term postural compensation (BS to AS8), whereas none of these preoperative factors was significantly predictive for medium-term postoperative postural recovery (AS8 to AS90). Conclusions We identified specific preoperative patient and vestibular function characteristics that may predict postoperative balance recovery after VS surgery. Better preoperative characterization of these factors in each patient could inform more personalized presurgical and postsurgical management, leading to a better, more rapid balance recovery, earlier return to normal daily activities and work, improved quality of life, and reduced medical and societal costs. © The Author(s) 2015.

  11. Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

    Science.gov (United States)

    Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki

    2017-01-01

    The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.

  12. Clinicopathologic Predictive Factors of Cervical Lymph Node Metastasis in Differentiated Thyroid Cancer.

    Science.gov (United States)

    Sun, Ronghao; Zhang, Hua; Liu, Kun; Fan, Jinchuan; Li, Guojun; Song, Xicheng; Li, Chao

    Cervical lymph node metastasis (LNM) has been proven to be a predictor for locoregional recurrence in differentiated thyroid carcinoma (DTC). Clinicopathological features could be effective predictive factors for central and lateral LNM of DTC, and provide references to surgeons for cervical neck dissection. Retrospective analysis of clinicopathological data was performed on 420 patients who underwent initial surgery from 2010 to 2015. The incidence of central and lateral LNM was calculated. Of 420 patients, 247 (58.8%) exhibited central LNM, and 185 (44.1%) exhibited lateral LNM. There were 29 (6.9%) cases confirmed to have skip metastasis. Univariate and multivariate analysis revealed that tumour location, tumour size, multifocality, capsular invasion, affected lobes, and age were independent predictors of central LNM. Tumour location, capsular invasion, affected lobes, and tumour size were independent predictors of lateral LNM. Our findings suggest that tumour location, affected lobes, capsular invasion, age, tumour size and multifocality may be taken as predictive factors for cervical LNM of DTC. Meticulous perioperative evaluation of cervical LNM and prophylactic cervical lymph node dissection that aims to remove the occult lymph nodes may be an option for DTC with risk factors. Copyright © 2017. Publicado por Elsevier España, S.L.U.

  13. [Risk factors of venous thromboembolism recurrence and the predictive value of simplified pulmonary embolism severity index in medical inpatients].

    Science.gov (United States)

    Shi, C L; Zhou, H X; Tang, Y J; Wang, L; Yi, Q; Liang, Z A

    2016-04-12

    To explore the risk factors of venous thromboembolism (VTE) recurrence and the predictive value of simplified pulmonary embolism severity index (sPESI) in medical inpatients. A total of 149 consecutive patients with first diagnosed VTE from the medical departments of West China Hospital of Sichuan University from January 2011 and December 2012 were enrolled and followed-up for 24 months. The VTE recurrence rate was calculated and univariate and multivariate cox proportional hazards regression analysis were performed to identify the risk factors associated with VTE recurrence. All the patients were evaluated by sPESI, and survival analysis was used to explore its value in predicting VTE recurrence in these medical patients. Out of the included 149 patients, 23(15.4%) patients had VTE recurrence during the 2 years' follow-up and median recurrence time was 167 days. The univariate analysis showed bed rest, severe lung disease, nephrotic syndrome, inappropriate anticoagulant therapy, smoking, diabetes, and malignant neoplasm might be associated with VTE recurrence (P=0.043, 0.006, 0.009, 0.032, 0.098, 0.048, 0.021). Among these risk factors, the multivariate analysis revealed severe lung disease, nephrotic syndrome, and malignant neoplasm were the independent risk factors (HR=3.45, 5.67, 3.60; P=0.020, 0.020, 0.047); while for inappropriate anticoagulant therapy, the P value was marginal (HR=3.94, 95% CI: 0.99-15.63, P=0.051). The median sPESI scores of the patients with VTE recurrence was higher than that of the patients without VTE recurrence[1(1, 2) vs 0(0, 1), P=0.001], and patients with sPESI≥1 were associated with 5.57-fold increased risk of VTE recurrence compared with patients with sPESI=0 (95%CI: 1.79-17.30, P=0.001). Survival analysis also showed that the 2-year cumulative VTE recurrence rate of patients with sPESI≥1 was significant higher than that of patients with sPESI=0 (38.4% vs 5.7%, P=0.001). The medical VTE patients have high VTE recurrence risk

  14. Predicting dropout in adolescents receiving therapy for depression.

    Science.gov (United States)

    O'Keeffe, Sally; Martin, Peter; Goodyer, Ian M; Wilkinson, Paul; Consortium, Impact; Midgley, Nick

    2017-10-30

    Therapy dropout is a common occurrence, especially in adolescence. This study investigated whether dropout could be predicted from a range of child, family, and treatment factors in a sample of adolescents receiving therapy for depression. This study draws on data from 406 participants of the IMPACT study, a randomized controlled trial, investigating three types of therapy in the treatment of adolescent depression. Logistic regression was used to estimate the effects of predictors on the odds of dropout. Few pre-treatment predictors of dropout were found, with the only significant predictors being older age, antisocial behaviour, and lower scores of verbal intelligence. Missed sessions and poorer therapeutic alliance early in treatment also predicted dropout. Most child and family factors investigated were not significantly associated with dropout. There may be little about depressed adolescents' presentation prior to therapy starting that indicates their risk of dropout. However, within-treatment factors indicated that warning signs of dropout may be identifiable during the initial phase of therapy. Identifying and targeting early treatment indicators of dropout may provide possibilities for improving engagement. Clinical and methodological significance of this article: In the literature, a great deal of attention has been paid to child and family factors that predict therapy dropout, yet in this study, few pre-treatment characteristics were predictive of dropout. However, findings revealed possible warning signs of dropout in the early part of treatment, as poor therapeutic alliance and missed sessions were both found to be predictive of dropout. These findings call for therapists to be aware of such warning signs and clinical guidelines for managing cases at risk of dropout are warranted.

  15. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    Directory of Open Access Journals (Sweden)

    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  16. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    Science.gov (United States)

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

  17. Predictive factors for intraoperative excessive bleeding in Graves' disease.

    Science.gov (United States)

    Yamanouchi, Kosho; Minami, Shigeki; Hayashida, Naomi; Sakimura, Chika; Kuroki, Tamotsu; Eguchi, Susumu

    2015-01-01

    In Graves' disease, because a thyroid tends to have extreme vascularity, the amount of intraoperative blood loss (AIOBL) becomes significant in some cases. We sought to elucidate the predictive factors of the AIOBL. A total of 197 patients underwent thyroidectomy for Graves' disease between 2002 and 2012. We evaluated clinical factors that would be potentially related to AIOBL retrospectively. The median period between disease onset and surgery was 16 months (range: 1-480 months). Conventional surgery was performed in 125 patients, whereas video-assisted surgery was performed in 72 patients. Subtotal and near-total/total thyroidectomies were performed in 137 patients and 60 patients, respectively. The median weight of the thyroid was 45 g (range: 7.3-480.0 g). Univariate analysis revealed that the strongest correlation of AIOBL was noted with the weight of thyroid (p Graves' disease, and preparation for blood transfusion should be considered in cases where thyroids weigh more than 200 g. Copyright © 2014. Published by Elsevier Taiwan.

  18. Identifying risk factors for PTSD in women seeking medical help after rape.

    Directory of Open Access Journals (Sweden)

    Anna Tiihonen Möller

    Full Text Available Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD.Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at Stockholm South Hospital, Sweden. Baseline assessments of mental health were carried out and followed up after six months.Thirty-nine percent of the women had developed PTSD at the six month assessment, and 47% suffered from moderate or severe depression. The major risk factors for PTSD were having been sexually assaulted by more than one person, suffering from acute stress disorder (ASD shortly after the assault, having been exposed to several acts during the assault, having been injured, having co-morbid depression, and having a history of more than two earlier traumas. Further, ASD on its own was found to be a poor predictor of PTSD because of the substantial ceiling effect after sexual assaults.Development of PTSD is common in the aftermath of sexual assaults. Increased risk of developing PTSD is caused by a combination of victim vulnerability and the extent of the dramatic nature of the current assault. By identifying those women at greatest risk of developing PTSD appropriate therapeutic resources can be directed.

  19. Orthopedic Surgery among Patients with Rheumatoid Arthritis: A Population-based study to Identify Risk factors, Sex differences, and Time trends.

    Science.gov (United States)

    Richter, Michael; Crowson, Cynthia S; Matteson, Eric L; Makol, Ashima

    2017-12-20

    To identify risk factors for large joint (LJS) versus small joint surgery (SJS) in rheumatoid arthritis (RA) and evaluate trends in surgery rates over time. A retrospective medical record review was performed of all orthopedic surgeries following first fulfillment of 1987 ACR criteria for adult-onset RA among residents of Olmsted County, Minnesota, USA in 1980-2013. Risk factors were examined using Cox models adjusted for age, sex and calendar year of RA incidence. Trends in incidence of joint surgeries were examined using Poisson regression models. A total of 1077 patients with RA (mean age 56 years, 69% female, 66% seropositive) were followed for a median of 10.7 years during which 112 (90 women) underwent at least one SJS and 204 (141 women) underwent at least one LJS. Risk factors included advanced age, rheumatoid factor and anti-CCP antibody positivity for both SJS and LJS, and BMI≥30 kg/m 2 for LJS. Risk factors for SJS and LJS at any time during follow-up included the presence of radiographic erosions, large joint swelling, and methotrexate use. SJS rates decreased by calendar year of incidence (hazard ratio 0.53; p=0.001), with significant decline in SJS after 1995. The cumulative incidence of SJS was higher in women than men (p=0.008). In recent years, there has been a significant decline in rates of SJS but not LJS in patients with RA. The incidence of SJS is higher among women. Traditional RA risk factors are strong predictors for SJS and LJS. Increasing age and obesity are predictive of LJS. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  20. Factors Predictive of Tumor Recurrence and Survival After Initial Complete Response of Esophageal Squamous Cell Carcinoma to Definitive Chemoradiotherapy

    International Nuclear Information System (INIS)

    Ishihara, Ryu; Yamamoto, Sachiko; Iishi, Hiroyasu; Takeuchi, Yoji; Sugimoto, Naotoshi; Higashino, Koji; Uedo, Noriya; Tatsuta, Masaharu; Yano, Masahiko; Imai, Atsushi; Nishiyama, Kinji

    2010-01-01

    Purpose: To assess factors predictive of recurrent disease and survival after achieving initial complete response (CR) to chemoradiotherapy (CRT) for esophageal cancer. Methods and Materials: Patients who had clinical Stage I-IVA esophageal cancer and received definitive CRT between 2001 and 2007 were retrospectively analyzed. Results: Of 269 patients with esophageal cancer, 110 who achieved CR after definitive CRT were included in the analyses. Chemoradiotherapy mainly consisted of 2 cycles of cisplatin and fluorouracil with concurrent radiotherapy of 60 Gy in 30 fractions. We identified 28 recurrences and 28 deaths during follow-up. The cumulative 1- and 3-year recurrence rates were 18% and 32%, respectively. By univariate and multivariate analyses, tumor category (hazard ratio [HR] 6.6; 95% confidence interval [CI] 1.4-30.2; p = 0.015) was an independent risk factor for local recurrence, whereas age (HR 3.9; 95% CI 1.1-14.0; p = 0.034) and primary tumor location (HR 4.5; 95% CI 1.6-12.4; p = 0.004) were independent risk factors for regional lymph node or distant recurrences. The cumulative overall 1- and 3-year survival rates were 91% and 66%, respectively. As expected, recurrence was associated with poor survival (p = 0.019). By univariate and multivariate analyses, primary tumor location (HR 3.8; 95% CI 1.2-12.0; p = 0.024) and interval to recurrence (HR 4.3; 95% CI 1.3-14.4; p = 0.018) were independent factors predictive of survival after recurrence. Conclusion: Risk of recurrence after definitive CRT for esophageal cancer was associated with tumor category, age, and primary tumor location; this information may help in improved prognostication for these patients.

  1. A Real-time Breakdown Prediction Method for Urban Expressway On-ramp Bottlenecks

    Science.gov (United States)

    Ye, Yingjun; Qin, Guoyang; Sun, Jian; Liu, Qiyuan

    2018-01-01

    Breakdown occurrence on expressway is considered to relate with various factors. Therefore, to investigate the association between breakdowns and these factors, a Bayesian network (BN) model is adopted in this paper. Based on the breakdown events identified at 10 urban expressways on-ramp in Shanghai, China, 23 parameters before breakdowns are extracted, including dynamic environment conditions aggregated with 5-minutes and static geometry features. Different time periods data are used to predict breakdown. Results indicate that the models using 5-10 min data prior to breakdown performs the best prediction, with the prediction accuracies higher than 73%. Moreover, one unified model for all bottlenecks is also built and shows reasonably good prediction performance with the classification accuracy of breakdowns about 75%, at best. Additionally, to simplify the model parameter input, the random forests (RF) model is adopted to identify the key variables. Modeling with the selected 7 parameters, the refined BN model can predict breakdown with adequate accuracy.

  2. Organisational Issues for E-Learning: Critical Success Factors as Identified by HE Practitioners

    Science.gov (United States)

    McPherson, Maggie; Nunes, Miguel Baptista

    2006-01-01

    Purpose: The purpose of this paper is to report on a research project that identified organisational critical success factors (CSFs) for e-learning implementation in higher education (HE). These CSFs can be used as a theoretical foundation upon which to base decision-making and strategic thinking about e-learning. Design/methodology/approach: The…

  3. Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

    Directory of Open Access Journals (Sweden)

    Chen Xiaoyu

    2007-12-01

    Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

  4. The role of anti-cyclic citrullinated peptide antibodies in predicting rheumatoid arthritis.

    Science.gov (United States)

    Rexhepi, Sylejman; Rexhepi, Mjellma; Sahatçiu-Meka, Vjollca; Tafaj, Argjend; Izairi, Remzi; Rexhepi, Blerta

    2011-01-01

    The study presents the results of predicting role of anti-cyclic citrullinated peptide antibodies in rheumatoid arthritis, compared to rheumatoid factor. 32 patients with rheumatoid arthritis were identified from a retrospective chart review. The results of our study show that presence of the rheumatoid factor has less diagnostic and prognostic significance than the anti-cyclic citrullinated peptide, and suggests its superiority in predicting an erosive disease course.

  5. Early Risk and Resiliency Factors Predict Chronic Posttraumatic Stress Disorder in Caregivers of Patients Admitted to a Neuroscience ICU.

    Science.gov (United States)

    Choi, Karmel W; Shaffer, Kelly M; Zale, Emily L; Funes, Christopher J; Koenen, Karestan C; Tehan, Tara; Rosand, Jonathan; Vranceanu, Ana-Maria

    2018-05-01

    Informal caregivers-that is, close family and friends providing unpaid emotional or instrumental care-of patients admitted to ICUs are at risk for posttraumatic stress disorder. As a first step toward developing interventions to prevent posttraumatic stress disorder in ICU caregivers, we examined the predictive validity of psychosocial risk screening during admission for caregiver posttraumatic stress disorder at 3 and 6 months post hospitalization. An observational, prospective study. Ninety-nine caregivers were recruited as part of a longitudinal research program of patient-caregiver dyads in a neuroscience ICU. None. Caregiver posttraumatic stress disorder symptoms were assessed during admission (baseline), 3 months, and 6 months post hospitalization. We 1) characterized prevalence of clinically significant symptoms at each time point 2); calculated sensitivity and specificity of baseline posttraumatic stress disorder screening in predicting posttraumatic stress disorder at 3 and 6 months; and 3) used recursive partitioning to select potential baseline factors and examine the extent to which they helped predict clinically significant posttraumatic stress disorder symptoms at each time point. Rates of caregiver posttraumatic stress disorder remained relatively stable over time (16-22%). Screening for posttraumatic stress disorder at baseline predicted posttraumatic stress disorder at 3 and 6 months with moderate sensitivity (75-80%) and high specificity (92-95%). Screening for posttraumatic stress disorder at baseline was associated with caregiver anxiety, mindfulness (i.e., ability to be aware of one's thoughts and feelings in the moment), and bond with patient. Furthermore, baseline posttraumatic stress disorder screening was the single most relevant predictor of posttraumatic stress disorder at 3 and 6 months, such that other baseline factors did not significantly improve predictive ability. Screening neuroscience ICU caregivers for clinically significant

  6. A Prediction Model for ROS1-Rearranged Lung Adenocarcinomas based on Histologic Features

    OpenAIRE

    Zhou, Jianya; Zhao, Jing; Zheng, Jing; Kong, Mei; Sun, Ke; Wang, Bo; Chen, Xi; Ding, Wei; Zhou, Jianying

    2016-01-01

    Aims To identify the clinical and histological characteristics of ROS1-rearranged non-small-cell lung carcinomas (NSCLCs) and build a prediction model to prescreen suitable patients for molecular testing. Methods and Results We identified 27 cases of ROS1-rearranged lung adenocarcinomas in 1165 patients with NSCLCs confirmed by real-time PCR and FISH and performed univariate and multivariate analyses to identify predictive factors associated with ROS1 rearrangement and finally developed predi...

  7. Predicting the effect of extrinsic and intrinsic job satisfaction factors on recruitment and retention of rehabilitation professionals.

    Science.gov (United States)

    Randolph, Diane Smith

    2005-01-01

    The purpose of this study was to ascertain which extrinsic and intrinsic job satisfaction areas are most predictive of rehabilitation professionals' career satisfaction and desire to stay on the job. This article discusses the results of a survey conducted on practicing occupational therapists, physical therapists, and speech-language pathologists regarding factors that contribute to career satisfaction and desire to stay on the job. Five hundred surveys were mailed to each profession; 463 were returned, of which 328 were able to be analyzed. Results from regression analysis showed that intrinsic factors such as professional growth and having a work environment in line with personal values are more significant in predicting career satisfaction than are extrinsic factors such as pay and continuing education. These same intrinsic factors are also significant in predicting the rehabilitation professional's desire to stay on the job. These findings are significant to healthcare managers desiring to recruit and retain qualified occupational therapists, physical therapists, and speech-language pathologists. In addition to extrinsic benefits such as pay, healthcare managers need to focus on provision of intrinsic factors such as opportunities for professional growth, recognition of accomplishments, and opportunities for departmental input to motivate rehabilitation professionals.

  8. Identifying at-risk profiles and protective factors for problem gambling: A longitudinal study across adolescence and early adulthood.

    Science.gov (United States)

    Allami, Youssef; Vitaro, Frank; Brendgen, Mara; Carbonneau, René; Tremblay, Richard E

    2018-05-01

    Past studies have identified various risk and protective factors for problem gambling (PG). However, no study has examined the interplay between these factors using a combination of person-centered and variable-centered approaches embedded within a longitudinal design. The present study aimed to (a) identify distinct profiles in early adolescence based on a set of risk factors commonly associated with PG (impulsivity, depression, anxiety, drug-alcohol use, aggressiveness, and antisociality), (b) explore the difference in reported gambling problems between these profiles during midadolescence and early adulthood, and (c) identify family- and peer-related variables that could operate as protective or compensatory factors in this context. Two samples were used: (a) a population sample (N = 1,033) living in low socioeconomic-status neighborhoods and (b) a population sample (N = 3,017) representative of students attending Quebec schools. Latent profile analyses were conducted to identify at-risk profiles based on individual risk factors measured at age 12 years. Negative binomial regression models were estimated to compare profiles in terms of their reported gambling problems at ages 16 and 23. Finally, family- and peer-related variables measured at age 14 were included to test their protective or compensatory role with respect to the link between at-risk profiles and gambling problems. Four profiles were identified: well-adjusted, internalizing, externalizing, and comorbid. Compared to the well-adjusted profile, the externalizing and comorbid profiles reported more gambling problems at ages 16 and 23, but the internalizing profile did not differ significantly. Various protective and compensatory factors emerged for each profile at both time points. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  9. IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

    Directory of Open Access Journals (Sweden)

    Anne-Laure Boulesteix

    2017-01-01

    Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

  10. A Risk Prediction Model for In-hospital Mortality in Patients with Suspected Myocarditis.

    Science.gov (United States)

    Xu, Duo; Zhao, Ruo-Chi; Gao, Wen-Hui; Cui, Han-Bin

    2017-04-05

    Myocarditis is an inflammatory disease of the myocardium that may lead to cardiac death in some patients. However, little is known about the predictors of in-hospital mortality in patients with suspected myocarditis. Thus, the aim of this study was to identify the independent risk factors for in-hospital mortality in patients with suspected myocarditis by establishing a risk prediction model. A retrospective study was performed to analyze the clinical medical records of 403 consecutive patients with suspected myocarditis who were admitted to Ningbo First Hospital between January 2003 and December 2013. A total of 238 males (59%) and 165 females (41%) were enrolled in this study. We divided the above patients into two subgroups (survival and nonsurvival), according to their clinical in-hospital outcomes. To maximize the effectiveness of the prediction model, we first identified the potential risk factors for in-hospital mortality among patients with suspected myocarditis, based on data pertaining to previously established risk factors and basic patient characteristics. We subsequently established a regression model for predicting in-hospital mortality using univariate and multivariate logistic regression analyses. Finally, we identified the independent risk factors for in-hospital mortality using our risk prediction model. The following prediction model for in-hospital mortality in patients with suspected myocarditis, including creatinine clearance rate (Ccr), age, ventricular tachycardia (VT), New York Heart Association (NYHA) classification, gender and cardiac troponin T (cTnT), was established in the study: P = ea/(1 + ea) (where e is the exponential function, P is the probability of in-hospital death, and a = -7.34 + 2.99 × [Ccr model demonstrated that a Ccr prediction model for in-hospital mortality in patients with suspected myocarditis. In addition, sufficient life support during the early stage of the disease might improve the prognoses of patients with

  11. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    Energy Technology Data Exchange (ETDEWEB)

    Alves, Vinicius M. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Muratov, Eugene [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Laboratory of Theoretical Chemistry, A.V. Bogatsky Physical-Chemical Institute NAS of Ukraine, Odessa 65080 (Ukraine); Fourches, Denis [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Strickland, Judy; Kleinstreuer, Nicole [ILS/Contractor Supporting the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), P.O. Box 13501, Research Triangle Park, NC 27709 (United States); Andrade, Carolina H. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States)

    2015-04-15

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  12. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    International Nuclear Information System (INIS)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  13. Predictive factors of occupational noise-induced hearing loss in Spanish workers: A prospective study.

    Science.gov (United States)

    Pelegrin, Armando Carballo; Canuet, Leonides; Rodríguez, Ángeles Arias; Morales, Maria Pilar Arévalo

    2015-01-01

    The purpose of our study was to identify the main factors associated with objective noise-induced hearing loss (NIHL), as indicated by abnormal audiometric testing, in Spanish workers exposed to occupational noise in the construction industry. We carried out a prospective study in Tenerife, Spain, using 150 employees exposed to occupational noise and 150 age-matched controls who were not working in noisy environments. The variables analyzed included sociodemographic data, noise-related factors, types of hearing protection, self-report hearing loss, and auditory-related symptoms (e.g., tinnitus, vertigo). Workers with pathological audiograms had significantly longer noise-exposure duration (16.2 ± 11.4 years) relative to those with normal audiograms (10.2 ± 7.0 years; t = 3.99, P hearing protection measures had audiometric abnormalities (94.1%). Additionally, workers using at least one of the protection devices (earplugs or earmuffs) had significantly more audiometric abnormalities than those using both protection measures simultaneously (Chi square = 16.07; P hearing protection measures [odds ratio (OR) = 12.30, confidence interval (CI) = 4.36-13.81, P hearing protection measures, in particular earplugs and earmuffs, associates with a lower rate of audiometric abnormalities in subjects with high occupational noise exposure. The use of hearing protection measures at work and noise-exposure duration are best predictive factors of NIHL. Auditory-related symptoms and self-report hearing loss do not represent good indicators of objective NIHL. Routine monitoring of noise levels and hearing status are of great importance as part of effective hearing conservation programs.

  14. Pre-typhoon socioeconomic status factors predict post-typhoon psychiatric symptoms in a Vietnamese sample.

    Science.gov (United States)

    Brown, Ruth C; Trapp, Stephen K; Berenz, Erin C; Bigdeli, Tim Bernard; Acierno, Ron; Tran, Trinh Luong; Trung, Lam Tu; Tam, Nguyen Thanh; Tuan, Tran; Buoi, La Thi; Ha, Tran Thu; Thach, Tran Duc; Amstadter, Ananda B

    2013-11-01

    Exposure to natural disasters has been associated with increased risk for various forms of psychopathology. Evidence indicates that socioeconomic status (SES) may be important for understanding post-disaster psychiatric distress; however, studies of SES-relevant factors in non-Western, disaster-exposed samples are lacking. The primary aim of the current study was to examine the role of pre-typhoon SES-relevant factors in relation to post-typhoon psychiatric symptoms among Vietnamese individuals exposed to Typhoon Xangsane. In 2006, Typhoon Xangsane disrupted a mental health needs assessment in Vietnam in which the Self Reporting Questionnaire-20 (SRQ-20), and the Demographic and Health Surveys Wealth Index, a measure of SES created for use in low-income countries, were administered pre-typhoon. The SRQ-20 was re-administered post-typhoon. Results of a linear mixed model indicated that the covariates of older age, female sex, and higher levels of pre-typhoon psychiatric symptoms were associated with higher levels of post-typhoon psychiatric symptoms. Analysis of SES indicators revealed that owning fewer consumer goods, having lower quality of household services, and having attained less education were associated with higher levels of post-typhoon symptoms, above and beyond the covariates, whereas quality of the household build, employment status, and insurance status were not related to post-typhoon psychiatric symptoms. Even after controlling for demographic characteristics and pre-typhoon psychiatric symptoms, certain SES factors uniquely predicted post-typhoon psychiatric distress. These SES characteristics may be useful for identifying individuals in developing countries who are in need of early intervention following disaster exposure.

  15. Identifying and Ranking the Effective Factors on Successful Implementation of Social Commerce in Iran, Using AHP Fuzzy

    Directory of Open Access Journals (Sweden)

    Zahra Rahimi

    2016-07-01

    Full Text Available Social commerce has been introduced as a new approach to increase sales, number of customers and reduce marketing expenditures. This approach is a combination of business, communication between people, as well as communicative and informative technologies based on web 2.0 Its achievement originated from different factors relied on business, individuals, culture, and technology. These factors have been primarily identified on the basis of library researches and classified into six infrastructural groups including:  technical, economical and human resources, cultural, rules governing the countries, style of management, and business. Then, it identified priority of the factors by using the fuzzy analytic hierarchy process (AHP. Innovation of this research was to extract a comprehensive list of factors and to prioritize them based on specific conditions in Iran.

  16. Factors predicting emotional cue-responding behaviors of nurses in Taiwan: An observational study.

    Science.gov (United States)

    Lin, Mei-Feng; Lee, An-Yu; Chou, Cheng-Chen; Liu, Tien-Yu; Tang, Chia-Chun

    2017-10-01

    Responding to emotional cues is an essential element of therapeutic communication. The purpose of this study is to examine nurses' competence of responding to emotional cues (CRE) and related factors while interacting with standardized patients with cancer. This is an exploratory and predictive correlational study. A convenience sample of registered nurses who have passed the probationary period in southern Taiwan was recruited to participate in 15-minute videotaped interviews with standardized patients. The Medical Interview Aural Rating Scale was used to describe standardized patients' emotional cues and to measure nurses' CRE. The State-Trait Anxiety Inventory was used to evaluate nurses' anxiety level before the conversation. We used descriptive statistics to describe the data and stepwise regression to examine the predictors of nurses' CRE. A total of 110 nurses participated in the study. Regardless of the emotional cue level, participants predominately responded to cues with inappropriate distancing strategies. Prior formal communication training, practice unit, length of nursing practice, and educational level together explain 36.3% variances of the nurses' CRE. This study is the first to explore factors related to Taiwanese nurses' CRE. Compared to nurses in other countries, Taiwanese nurses tended to respond to patients' emotional cues with more inappropriate strategies. We also identified significant predictors of CRE that show the importance of communication training. Future research and education programs are needed to enhance nurses' CRE and to advocate for emotion-focused communication. Copyright © 2016 John Wiley & Sons, Ltd.

  17. Comparison of Predictive Factors for Postoperative Incontinence of Holmium Laser Enucleation of the Prostate by the Surgeons’ Experience During Learning Curve

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    Katsumi Shigemura

    2016-03-01

    Full Text Available Purpose: To detect predictive factors for postoperative incontinence following holmium laser enucleation of the prostate (HoLEP according to surgeon experience (beginner or experienced and preoperative clinical data. Methods: Of 224 patients, a total of 203 with available data on incontinence were investigated. The potential predictive factors for post-HoLEP incontinence included clinical factors, such as patient age, and preoperative urodynamic study results, including detrusor overactivity (DO. We also classified the surgeons performing the procedure according to their HoLEP experience: beginner (<21 cases and experienced (≥21 cases. Results: Our statistical data showed DO was a significant predictive factor at the super-short period (the next day of catheter removal: odds ratio [OR], 3.375; P=0.000. Additionally, patient age, surgeon mentorship (inverse correlation, and prostate volume were significant predictive factors at the 1-month interval after HoLEP (OR, 1.072; P=0.004; OR, 0.251; P=0.002; and OR, 1.008; P=0.049, respectively. With regards to surgeon experience, DO and preoperative International Prostate Symptom Score (inverse at the super-short period, and patient age and mentorship (inverse correlation at the 1-month interval after HoLEP (OR, 3.952; P=0.002; OR, 1.084; P=0.015; and OR,1.084; P=0.015; OR, 0.358; P=0.003, respectively were significant predictive factors for beginners, and first desire to void (FDV at 1 month after HoLEP (OR, 1.009; P=0.012 was a significant predictive factor for experienced surgeons in multivariate analysis. Conclusions: Preoperative DO, IPSS, patient age, and surgeon mentorship were significant predictive factors of postoperative patient incontinence for beginner surgeons, while FDV was a significant predictive factors for experienced surgeons. These findings should be taken into account by surgeons performing HoLEP to maximize the patient’s quality of life with regards to urinary continence.

  18. Prognostic factors for specific lower extremity and spinal musculoskeletal injuries identified through medical screening and training load monitoring in professional football (soccer): a systematic review

    Science.gov (United States)

    Sergeant, Jamie C; Parkes, Matthew J; Callaghan, Michael J

    2017-01-01

    Background Medical screening and load monitoring procedures are commonly used in professional football to assess factors perceived to be associated with injury. Objectives To identify prognostic factors (PFs) and models for lower extremity and spinal musculoskeletal injuries in professional/elite football players from medical screening and training load monitoring processes. Methods The MEDLINE, AMED, EMBASE, CINAHL Plus, SPORTDiscus and PubMed electronic bibliographic databases were searched (from inception to January 2017). Prospective and retrospective cohort studies of lower extremity and spinal musculoskeletal injury incidence in professional/elite football players aged between 16 and 40 years were included. The Quality in Prognostic Studies appraisal tool and the modified Grading of Recommendations Assessment, Development and Evaluation synthesis approach was used to assess the quality of the evidence. Results Fourteen studies were included. 16 specific lower extremity injury outcomes were identified. No spinal injury outcomes were identified. Meta-analysis was not possible due to heterogeneity and study quality. All evidence related to PFs and specific lower extremity injury outcomes was of very low to low quality. On the few occasions where multiple studies could be used to compare PFs and outcomes, only two factors demonstrated consensus. A history of previous hamstring injuries (HSI) and increasing age may be prognostic for future HSI in male players. Conclusions The assumed ability of medical screening tests to predict specific musculoskeletal injuries is not supported by the current evidence. Screening procedures should currently be considered as benchmarks of function or performance only. The prognostic value of load monitoring modalities is unknown. PMID:29177074

  19. Does inhalation injury predict mortality in burns patients or require redefinition?

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    Youngmin Kim

    Full Text Available Inhalation injury is known to be an important factor in predicting mortality in burns patients. However, the diagnosis is complicated by the heterogeneous presentation and inability to determine the severity of inhalation injury. The purpose of this study was to identify clinical features of inhalation injury that affect mortality and the values that could predict the outcome more precisely in burns patients with inhalation injury. This retrospective observational study included 676 burns patients who were over 18 years of age and hospitalized in the Burns Intensive Care Unit between January 2012 and December 2015. We analyzed variables that are already known to be prognostic factors (age, percentage of total body surface area (%TBSA burned, and inhalation injury and factors associated with inhalation injury (carboxyhemoglobin and PaO2/FiO2 [PF] ratio by univariate and multivariate logistic regression. Age group (odds ratio [OR] 1.069, p<0.001, %TBSA burned (OR 1.100, p<0.001, and mechanical ventilation (OR 3.774, p<0.001 were identified to be significant predictive factors. The findings for presence of inhalation injury, PF ratio, and carboxyhemoglobin were not statistically significant in multivariate logistic regression. Being in the upper inhalation group, the lower inhalation group, and having a PF ratio <100 were identified to be significant predictors only in univariate logistic regression analysis (OR 4.438, p<0.001; OR 2.379, p<0.001; and OR 2.765, p<0.001, respectively. History and physical findings are not appropriate for diagnosis of inhalation injury and do not predict mortality. Mechanical ventilation should be recognized as a risk factor for mortality in burns patients with inhalation injury.

  20. Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population

    Science.gov (United States)

    Najmi, Laeya Abdoli; Aukrust, Ingvild; Flannick, Jason; Molnes, Janne; Burtt, Noel; Molven, Anders; Groop, Leif; Altshuler, David; Johansson, Stefan; Njølstad, Pål Rasmus

    2017-01-01

    Variants in HNF1A encoding hepatocyte nuclear factor 1α (HNF-1A) are associated with maturity-onset diabetes of the young form 3 (MODY 3) and type 2 diabetes. We investigated whether functional classification of HNF1A rare coding variants can inform models of diabetes risk prediction in the general population by analyzing the effect of 27 HNF1A variants identified in well-phenotyped populations (n = 4,115). Bioinformatics tools classified 11 variants as likely pathogenic and showed no association with diabetes risk (combined minor allele frequency [MAF] 0.22%; odds ratio [OR] 2.02; 95% CI 0.73–5.60; P = 0.18). However, a different set of 11 variants that reduced HNF-1A transcriptional activity to diabetes in the general population (combined MAF 0.22%; OR 5.04; 95% CI 1.99–12.80; P = 0.0007). Our functional investigations indicate that 0.44% of the population carry HNF1A variants that result in a substantially increased risk for developing diabetes. These results suggest that functional characterization of variants within MODY genes may overcome the limitations of bioinformatics tools for the purposes of presymptomatic diabetes risk prediction in the general population. PMID:27899486

  1. Perceived heart risk factors can predict experienced psychological stress in outpatient cardiac rehabilitation

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    Mozhgan Saeidi

    2018-01-01

    Full Text Available Background: The study was done to investigate the role of perceived heart risk factors (PHRFs in the prediction of psychological symptoms of cardiac rehabilitation (CR patients. Methods: In this cross-sectional study, 124 CR patients referred to Kermanshah Hospital of Imam Ali were assessed during April–July 2015. PHRFs scale and Depression, Anxiety, and Stress scale-21 used for data collection. The data were analyzed using linear multiple regression analysis. Results: The mean age of samples (69.4% male was 58.9 ± 9.7 years. The results of regression analysis evidenced that there is no significant relationship between any of the PHRFs with depression and anxiety (P > 0.05; however, biological (P = 0.018 and psychological (P = 0.019 risk factors significantly can predict stress. The model generally can explain 6.4% of the stress variance. Conclusion: PHRFs are included some significant predictors for experienced stress among the CR patients. Given that the biological and psychological risk factors are more effective in experienced stress by the patients, it is recommended that specialists pay more attention to the potential psychological outcomes of this group of patients.

  2. Predicting homophobic behavior among heterosexual youth: domain general and sexual orientation-specific factors at the individual and contextual level.

    Science.gov (United States)

    Poteat, V Paul; DiGiovanni, Craig D; Scheer, Jillian R

    2013-03-01

    As a form of bias-based harassment, homophobic behavior remains prominent in schools. Yet, little attention has been given to factors that underlie it, aside from bullying and sexual prejudice. Thus, we examined multiple domain general (empathy, perspective-taking, classroom respect norms) and sexual orientation-specific factors (sexual orientation identity importance, number of sexual minority friends, parents' sexual minority attitudes, media messages). We documented support for a model in which these sets of factors converged to predict homophobic behavior, mediated through bullying and prejudice, among 581 students in grades 9-12 (55 % female). The structural equation model indicated that, with the exception of media messages, these additional factors predicted levels of prejudice and bullying, which in turn predicted the likelihood of students to engage in homophobic behavior. These findings highlight the importance of addressing multiple interrelated factors in efforts to reduce bullying, prejudice, and discrimination among youth.

  3. Multi-parametric MRI in cervical cancer. Early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Wei; Chen, Bing; Wang, Ai Jun; Zhao, Jian Guo [The General Hospital of Ningxia Medical University, Department of Radiology, Yinchuan (China); Qiang, Jin Wei [Fudan University, Department of Radiology, Jinshan Hospital, Shanghai (China); Tian, Hai Ping [The General Hospital of Ningxia Medical University, Department of Pathology, Yinchuan (China)

    2018-01-15

    To investigate the prediction of response to concurrent chemoradiotherapy (CCRT) through a combination of pretreatment multi-parametric magnetic resonance imaging (MRI) with clinical prognostic factors (CPF) in cervical cancer patients. Sixty-five patients underwent conventional MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI (DCE-MRI) before CCRT. The patients were divided into non- and residual tumour groups according to post-treatment MRI. Pretreatment MRI parameters and CPF between the two groups were compared and prognostic factors, optimal thresholds, and predictive performance for post-treatment residual tumour occurrence were estimated. The residual group showed a lower maximum slope of increase (MSI{sub L}) and signal enhancement ratio (SER{sub L}) in low-perfusion subregions, a higher apparent diffusion coefficient (ADC) value, and a higher stage than the non-residual tumour group (p < 0.001, p = 0.003, p < 0.001, and p < 0.001, respectively). MSI{sub L} and ADC were independent prognostic factors. The combination of both measures improved the diagnostic performance compared with individual MRI parameters. A further combination of these two factors with CPF exhibited the highest predictive performance. Pretreatment MSI{sub L} and ADC were independent prognostic factors for cervical cancer. The predictive capacity of multi-parametric MRI was superior to individual MRI parameters. The combination of multi-parametric MRI with CPF further improved the predictive performance. (orig.)

  4. Predictive factors of unfavorable prostate cancer in patients who underwent prostatectomy but eligible for active surveillance

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    Seol Ho Choo

    2014-06-01

    Conclusions: A significant proportion of patients who were candidates for active surveillance had unfavorable prostate cancer. Age, PSA density, and two positive cores were independent significant predictive factors for unfavorable prostate cancer. These factors should be considered when performing active surveillance.

  5. Gemcitabine-Based Chemotherapy in Adrenocortical Carcinoma: A Multicenter Study of Efficacy and Predictive Factors.

    Science.gov (United States)

    Henning, Judith E K; Deutschbein, Timo; Altieri, Barbara; Steinhauer, Sonja; Kircher, Stefan; Sbiera, Silviu; Wild, Vanessa; Schlötelburg, Wiebke; Kroiss, Matthias; Perotti, Paola; Rosenwald, Andreas; Berruti, Alfredo; Fassnacht, Martin; Ronchi, Cristina L

    2017-11-01

    Adrenocortical carcinoma (ACC) is rare and confers an unfavorable prognosis in advanced stages. Other than combination chemotherapy with cisplatin, etoposide, doxorubicin, and mitotane, the second- and third-line regimens are not well-established. Gemcitabine (GEM)-based chemotherapy was suggested in a phase 2 clinical trial with 28 patients. In other solid tumors, human equilibrative nucleoside transporter type 1 (hENT1) and/or ribonucleotide reductase catalytic subunit M1 (RRM1) expression have been associated with resistance to GEM. To assess the efficacy of GEM-based chemotherapy in ACC in a real-world setting and the predictive role of molecular parameters. Retrospective multicenter study. Referral centers of university hospitals. A total of 145 patients with advanced ACC were treated with GEM-based chemotherapy (132 with concomitant capecitabine). Formalin-fixed paraffin-embedded tumor material was available for 70 patients for immunohistochemistry. The main outcome measures were progression-free survival (PFS) and an objective response to GEM-based chemotherapy. The secondary objective was the predictive role of hENT1 and RRM1. The median PFS for the patient population was 12 weeks (range, 1 to 94). A partial response or stable disease was achieved in 4.9% and 25.0% of cases, with a median duration of 26.8 weeks. Treatment was generally well tolerated, with adverse events of grade 3 or 4 occurring in 11.0% of cases. No substantial effect of hENT1 and/or RRM1 expression was observed in response to GEM-based chemotherapy. GEM-based chemotherapy is a well-tolerated, but modestly active, regimen against advanced ACC. No reliable molecular predictive factors could be identified. Owing to the scarce alternative therapeutic options, GEM-based chemotherapy remains an important option for salvage treatment for advanced ACC. Copyright © 2017 Endocrine Society

  6. Generalizability of the Disease State Index Prediction Model for Identifying Patients Progressing from Mild Cognitive Impairment to Alzheimer's Disease

    NARCIS (Netherlands)

    Hall, A.; Munoz-Ruiz, M.; Mattila, J.; Koikkalainen, J.; Tsolaki, M.; Mecocci, P.; Kloszewska, I.; Vellas, B.; Lovestone, S.; Visser, P.J.; Lotjonen, J.; Soininen, H.

    2015-01-01

    Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. Objectives: We evaluated how well the DSI generalizes across

  7. Predictive Risk Factors for Impaired Quality of Life in Middle-Aged Women with Urinary Incontinence

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    Youn-Jung Son

    2010-12-01

    Full Text Available Purpose Urinary incontinence (UI has substantial and important impacts on quality of life (QoL. The purpose of this study was to identify the associated risk factors of QoL in middle-aged women with UI. Methods The participants were 127 women aged 40-64 years who experienced UI. Data were collected from October to November, 2008 using a self-reported questionnaires. The data were analyzed through t-test, one-way ANOVA, Scheffe test, and multiple linear regression with SPSS ver. 16.0 program. Results The distribution of UI severity was mild 18.1%, moderate 40.2% and severe 41.7%. In univariate analysis, differences in the score for QoL according to participants' characteristics were statistically significant on the type of delivery, number of births and severity of UI. In multiple linear regression analysis after adjustment of other variables, the most powerful predictor of QoL is severity of UI. Number of births was also significant predictor. These two variables explained 25% of variance in QoL of women with UI. Conclusions UI is highly prevalent and causes suffering and impaired QoL among middle-aged women, but it stands beyond our attention. The results of this study suggest that women with moderate to severe UI should be screened for QoL by health care providers regularly. Further research is needed to determine comprehensive factors including psychosocial factors predicting the QoL for incontinent women.

  8. MYC Amplification as a Predictive Factor of Complete Pathologic Response to Docetaxel-based Neoadjuvant Chemotherapy for Breast Cancer.

    Science.gov (United States)

    Pereira, Cynthia Brito Lins; Leal, Mariana Ferreira; Abdelhay, Eliana Saul Furquim Werneck; Demachki, Sâmia; Assumpção, Paulo Pimentel; de Souza, Mirian Carvalho; Moreira-Nunes, Caroline Aquino; Tanaka, Adriana Michiko da Silva; Smith, Marília Cardoso; Burbano, Rommel Rodríguez

    2017-06-01

    Neoadjuvant chemotherapy is a standard treatment for stage II and III breast cancer. The identification of biomarkers that may help in the prediction of response to neoadjuvant therapies is necessary for a more precise definition of the best drug or drug combination to induce a better response. We assessed the role of Ki67, hormone receptors expression, HER2, MYC genes and their protein status, and KRAS codon 12 mutations as predictor factors of pathologic response to anthracycline-cyclophosphamide (AC) followed by taxane docetaxel (T) neoadjuvant chemotherapy (AC+T regimen) in 51 patients with invasive ductal breast cancer. After neoadjuvant chemotherapy, 82.4% of patients showed pathologic partial response, with only 9.8% showing pathologic complete response. In multivariate analysis, MYC immunoreactivity and high MYC gain defined as MYC/nucleus ≥ 5 were significant predictor factors for pathologic partial response. Using the receiver operating characteristic curve analysis, the ratio of 2.5 MYC/CEP8 (sensitivity of 80% and specificity of 89.1%) or 7 MYC/nuclei copies (sensitivity of 80% and specificity of 73.9%) as the best cutoff in predicting a pathologic complete response was identified. Thus, MYC may have a role in chemosensitivity to AC and/or docetaxel drugs. Additionally, MYC amplification may be a predictor factor of pathologic response to the AC+T regimen in patients with breast cancer. Moreover, patients with an increased number of MYC copies showed pathologic complete response to this neoadjuvant treatment more frequently. The analysis of MYC amplification may help in the identification of patients that may have a better response to AC+T treatment. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Identifying and prioritizing the factors effective in customer satisfaction using the TOPSIS method

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    H Forougozar

    2014-01-01

    Full Text Available Introduction: Customer satisfaction has been suggested as one of the interesting and challenging issues of management in the new millennium. In addition, oral and dental health and the quality of the services the health centers delivered to the patients directly affect the customer satisfaction. Therefore, the present study aimed to identify, investigate, and rank the factors affecting the customer satisfaction in the department of dentistry of Shiraz Farhangiyan health center. Method: The present descriptive study was conducted on the specialists and patients of the department of dentistry of Shiraz Farhangiyan health center. The validity of the questionnaire utilized in the study was confirmed by expert professors and its reliability was approved using the Cronbach’s alpha formula. Finally, the study data were analyzed in SPSS statistical software (v. 16, using inferential statistics. Results: All the hypotheses were confirmed by the results of the statistical analyses and quality, services, and expenditures revealed to affect the customer satisfaction in the department of dentistry of Shiraz Farhangiyan health center. Moreover, these factors were ranked using the TOPSIS method and the results showed quality and expenditures as the most and the least effective factors in customer satisfaction, respectively. Conclusion: Since restoring and arranging the organization based on the customer needs is among the main priorities of designing an organization, managers are suggested to take measures for organizational reformation based on the customers’ priorities. Of course, conducting such programs is of utmost importance in health and treatment environments, leading to provision of better services and facilitation of learning, education, and research. Thus, identifying the effective factors in customer satisfaction and ranking them are highly important.

  10. NECESSITY FACTORS AND PREDICTORS OF DENTAL CROWDING TREATMENT

    Directory of Open Access Journals (Sweden)

    Georgeta ZEGAN

    2015-09-01

    Full Text Available The aim of the study was to identify the significant necessity and predictive factors of dental crowding treatment, on 422 subjects (165 boys and 257 girls from the North-East part of Romania. Correlations have been established between dental crowding and age, dentition, Angle class of malocclusions, the etiological factors, types and modalities of treatments, and types of orthodontic appliances employed (p0.05. The necessity and predictive factors of the treatment were adequate with age, dentition, severity of crowding and Angle class of malocclusion.

  11. Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

    Science.gov (United States)

    2011-01-01

    Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der

  12. Biological and socio-cultural factors during the school years predicting women’s lifetime educational attainment

    Science.gov (United States)

    Hendrick, C. Emily; Cohen, Alison K.; Deardorff, Julianna

    2015-01-01

    BACKGROUND Lifetime educational attainment is an important predictor of health and well-being for women in the United States. In the current study, we examine the roles of socio-cultural factors in youth and an understudied biological life event, pubertal timing, in predicting women’s lifetime educational attainment. METHODS Using data from the National Longitudinal Survey of Youth 1997 cohort (N = 3889), we conducted sequential multivariate linear regression analyses to investigate the influences of macro-level and family-level socio-cultural contextual factors in youth (region of country, urbanicity, race/ethnicity, year of birth, household composition, mother’s education, mother’s age at first birth) and early menarche, a marker of early pubertal development, on women’s educational attainment after age 24. RESULTS Pubertal timing and all socio-cultural factors in youth, other than year of birth, predicted women’s lifetime educational attainment in bivariate models. Family factors had the strongest associations. When family factors were added to multivariate models, geographic region in youth and pubertal timing were no longer significant. CONCLUSION Our findings provide additional evidence that family factors should be considered when developing comprehensive and inclusive interventions in childhood and adolescence to promote lifetime educational attainment among girls. PMID:26830508

  13. Individual differences in maternal response to immune challenge predict offspring behavior: Contribution of environmental factors

    Science.gov (United States)

    Bronson, Stefanie L.; Ahlbrand, Rebecca; Horn, Paul S.; Kern, Joseph R.; Richtand, Neil M.

    2011-01-01

    Maternal infection during pregnancy elevates risk for schizophrenia and related disorders in offspring. Converging evidence suggests the maternal inflammatory response mediates the interaction between maternal infection, altered brain development, and behavioral outcome. The extent to which individual differences in the maternal response to immune challenge influence the development of these abnormalities is unknown. The present study investigated the impact of individual differences in maternal response to the viral mimic polyinosinic:polycytidylic acid (poly I:C) on offspring behavior. We observed significant variability in body weight alterations of pregnant rats induced by administration of poly I:C on gestational day 14. Furthermore, the presence or absence of maternal weight loss predicted MK-801 and amphetamine stimulated locomotor abnormalities in offspring. MK-801 stimulated locomotion was altered in offspring of all poly I:C treated dams; however, the presence or absence of maternal weight loss resulted in decreased and modestly increased locomotion, respectively. Adult offspring of poly I:C treated dams that lost weight exhibited significantly decreased amphetamine stimulated locomotion, while offspring of poly I:C treated dams without weight loss performed similarly to vehicle controls. Social isolation and increased maternal age predicted weight loss in response to poly I:C but not vehicle injection. In combination, these data identify environmental factors associated with the maternal response to immune challenge and functional outcome of offspring exposed to maternal immune activation. PMID:21255612

  14. Predictive factors for relapse in patients on buprenorphine maintenance.

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    Ferri, Michael; Finlayson, Alistair J Reid; Wang, Li; Martin, Peter R

    2014-01-01

    Despite the dramatic increase in the use of buprenorphine for the treatment of opioid dependence, clinical outcomes of this treatment approach continue to need evaluation. This study examines factors associated with relapse and retention during buprenorphine treatment in a sample of opioid dependent outpatients. In a retrospective chart review of 62 patients with opioid dependence, relapse was determined by self-report, urine toxicology screens, and by checking the state controlled substance monitoring database. Data was analyzed using two-way tests of association and logistic regression. Patients with comorbid anxiety disorders, active benzodiazepine use (contrary to clinic policy), or active alcohol abuse, were significantly more likely to relapse. Patients who relapsed were also more likely to be on a higher buprenorphine maintenance dose. This study identifies relapse risk factors during buprenorphine treatment for opioid dependence. Future research is needed to determine whether modifying these factors may lead to improved treatment outcomes. © American Academy of Addiction Psychiatry.

  15. Predicting knee replacement damage in a simulator machine using a computational model with a consistent wear factor.

    Science.gov (United States)

    Zhao, Dong; Sakoda, Hideyuki; Sawyer, W Gregory; Banks, Scott A; Fregly, Benjamin J

    2008-02-01

    Wear of ultrahigh molecular weight polyethylene remains a primary factor limiting the longevity of total knee replacements (TKRs). However, wear testing on a simulator machine is time consuming and expensive, making it impractical for iterative design purposes. The objectives of this paper were first, to evaluate whether a computational model using a wear factor consistent with the TKR material pair can predict accurate TKR damage measured in a simulator machine, and second, to investigate how choice of surface evolution method (fixed or variable step) and material model (linear or nonlinear) affect the prediction. An iterative computational damage model was constructed for a commercial knee implant in an AMTI simulator machine. The damage model combined a dynamic contact model with a surface evolution model to predict how wear plus creep progressively alter tibial insert geometry over multiple simulations. The computational framework was validated by predicting wear in a cylinder-on-plate system for which an analytical solution was derived. The implant damage model was evaluated for 5 million cycles of simulated gait using damage measurements made on the same implant in an AMTI machine. Using a pin-on-plate wear factor for the same material pair as the implant, the model predicted tibial insert wear volume to within 2% error and damage depths and areas to within 18% and 10% error, respectively. Choice of material model had little influence, while inclusion of surface evolution affected damage depth and area but not wear volume predictions. Surface evolution method was important only during the initial cycles, where variable step was needed to capture rapid geometry changes due to the creep. Overall, our results indicate that accurate TKR damage predictions can be made with a computational model using a constant wear factor obtained from pin-on-plate tests for the same material pair, and furthermore, that surface evolution method matters only during the initial

  16. Chronic dry eye in PRK and LASIK: manifestations, incidence and predictive factors

    Science.gov (United States)

    Bower, Kraig S.; Sia, Rose K.; Ryan, Denise S.; Mines, Michael J.; Dartt, Darlene A.

    2017-01-01

    Purpose To evaluate dry eye manifestations following photorefractive keratectomy (PRK) and laser in situ keratomileusis (LASIK) and determine the incidence and predictive factors of chronic dry eye using a set of dry eye criteria. Setting Walter Reed Army Medical Center, Washington, DC, USA Methods This is a prospective non-randomized clinical study of 143 active duty U.S. Army personnel aged 29.9±5.2 years with myopia or myopic astigmatism (manifest spherical equivalent −3.83±1.96 diopters) undergoing either PRK or LASIK. Dry eye evaluation was performed pre- and postoperatively. Main outcome measures included dry eye manifestations, incidence, and predictive factors of chronic dry eye. Results Schirmer scores, corneal sensitivity, ocular surface staining, surface regularity index (SRI), and responses to dry eye questionnaire significantly changed over time after PRK. After LASIK, significant changes were observed in tear breakup time, corneal sensitivity, ocular surface staining, and responses to questionnaire. At twelve months postoperatively, 5.0% of PRK and 0.8% of LASIK participants developed chronic dry eye. Regression analysis showed preoperatively lower Schirmer score will significantly influence development of chronic dry eye after PRK whereas preoperatively lower Schirmer score or higher ocular surface staining score will significantly influence the occurrence of chronic dry eye after LASIK. Conclusions Chronic dry eye is uncommon after PRK and LASIK. Ocular surface and tear film characteristics during preoperative examination may help predict chronic dry eye development in PRK and LASIK. PMID:26796443

  17. Gender and age effects on risk factor-based prediction of coronary artery calcium in symptomatic patients: A Euro-CCAD study.

    Science.gov (United States)

    Nicoll, R; Wiklund, U; Zhao, Y; Diederichsen, A; Mickley, H; Ovrehus, K; Zamorano, J; Gueret, P; Schmermund, A; Maffei, E; Cademartiri, F; Budoff, M; Henein, M

    2016-09-01

    The influence of gender and age on risk factor prediction of coronary artery calcification (CAC) in symptomatic patients is unclear. From the European Calcific Coronary Artery Disease (EURO-CCAD) cohort, we retrospectively investigated 6309 symptomatic patients, 62% male, from Denmark, France, Germany, Italy, Spain and USA. All of them underwent risk factor assessment and CT scanning for CAC scoring. The prevalence of CAC among females was lower than among males in all age groups. Using multivariate logistic regression, age, dyslipidaemia, hypertension, diabetes and smoking were independently predictive of CAC presence in both genders. In addition to a progressive increase in CAC with age, the most important predictors of CAC presence were dyslipidaemia and diabetes (β = 0.64 and 0.63, respectively) in males and diabetes (β = 1.08) followed by smoking (β = 0.68) in females; these same risk factors were also important in predicting increasing CAC scores. There was no difference in the predictive ability of diabetes, hypertension and dyslipidaemia in either gender for CAC presence in patients aged 70, only dyslipidaemia predicted CAC presence in males and only smoking and diabetes were predictive in females. In symptomatic patients, there are significant differences in the ability of conventional risk factors to predict CAC presence between genders and between patients aged role of age in predicting CAC presence. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. Predictive Factors and Treatment Outcomes of Tuberculous Pleural Effusion in Patients With Cancer and Pleural Effusion.

    Science.gov (United States)

    Lee, Jaehee; Lee, Yong Dae; Lim, Jae Kwang; Lee, Deok Heon; Yoo, Seung Soo; Lee, Shin Yup; Cha, Seung Ick; Park, Jae Yong; Kim, Chang Ho

    2017-08-01

    Patients with cancer are at an increased risk of tuberculosis. As pleural effusion has great clinical significance in patients with cancer, the differential diagnosis between tuberculous pleural effusion (TPE) and malignant pleural effusion (MPE) is important. However, the predictive factors and treatment outcomes of TPE in patients with cancer have rarely been studied. Confirmed TPE cases identified at cancer diagnosis and during anticancer management from 2008-2015 were retrospectively investigated. Patients in the study included coexisting TPE and cancer (n = 20), MPE (n = 40) and TPE without cancer (n = 40). Control groups were patients with MPE, and patients with TPE without cancer. Clinical, laboratory and pleural fluid characteristics were compared among groups. Treatment outcomes were compared between patients with TPE with and without cancer. In the final analysis, serum C-reactive protein (S-CRP) ≥3.0mg/dL and pleural fluid adenosine deaminase (ADA) ≥40U/L were independent predictors for identifying TPE in patients with cancer having pleural effusion. The combination of S-CRP with pleural fluid ADA using an "or" rule achieved a sensitivity of 100%, whereas both parameters combined in an "and" rule had a specificity of 98%. Treatment outcomes were not different between the TPE groups with and without cancer. S-CRP and pleural fluid ADA levels may be helpful for predicting TPE in patients with cancer with pleural effusion. The combination of these biomarkers provides better information for distinguishing between TPE and MPE in these patients. Treatment outcomes of TPE in patients with cancer are comparable to those in patients without cancer. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

  19. Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

    Science.gov (United States)

    Wright, David; Thyer, Mark; Westra, Seth

    2015-04-01

    Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this

  20. Shame and guilt as shared vulnerability factors: Shame, but not guilt, prospectively predicts both social anxiety and bulimic symptoms.

    Science.gov (United States)

    Levinson, Cheri A; Byrne, Meghan; Rodebaugh, Thomas L

    2016-08-01

    Social anxiety disorder (SAD) and bulimia nervosa (BN) are highly comorbid. However, little is known about the shared vulnerability factors that prospectively predict both SA and BN symptoms. Two potential factors that have not yet been tested are shame and guilt. In the current study we tested if shame and guilt were shared vulnerability factors for SA and BN symptoms. Women (N=300) completed measures of SA symptoms, BN symptoms, state shame and guilt, and trait negative affect at two time points, two months apart. Utilizing structural equation modeling we tested a cross-sectional and prospective model of SA and BN vulnerability. We found that shame prospectively predicted both SA and BN symptoms. We did not find that guilt prospectively predicted SA or BN symptoms. However, higher levels of both BN and SA symptoms predicted increased guilt over time. We found support for shame as a shared prospective vulnerability factor between BN and SA symptoms. Interventions that focus on decreasing shame could potentially alleviate symptoms of BN and SA in one protocol. Copyright © 2016 Elsevier Ltd. All rights reserved.