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Sample records for clinical prediction rule

  1. Clinical prediction rule for nonmelanoma skin cancer

    Directory of Open Access Journals (Sweden)

    John Alexander Nova

    2015-01-01

    Full Text Available Background: Skin cancer is the most frequent neoplasia in the world. Even though ultraviolet radiation is the main cause, established prevention campaigns have not proved to be effective for controlling the incidence of this disease. Objective: To develop clinical prediction rules based on medical consultation and a questionnaire to estimate the risk of developing nonmelanoma skin cancer. Methods: This study was developed in several steps. They were: Identifying risk factors that could be possible predictors of nonmelanoma skin cancer; their clinical validation; developing a prediction rule using logistic regression; and collecting information from 962 patients in a case and control design (481 cases and 481 controls. We developed independent prediction rules for basal cell and squamous cell carcinomas. Finally, we evaluated reliability for each of the variables. Results: The variables that made up the final prediction rule were: Family history of skin cancer, history of outdoor work, age, phototypes 1-3 and the presence of poikiloderma of civatte, actinic keratosis and conjunctivitis in band. Prediction rules specificity was 87% for basal cell carcinomas and 92% for squamous cell carcinomas. Inter- and intra-observer reliability was good except for the conjunctivitis in band variable. Conclusions: The prediction rules let us calculate the individual risk of developing basal cell carcinoma and squamous cell carcinoma. This is an economic easy-to-apply tool that could be useful in primary and secondary prevention of skin cancer.

  2. Clinical Prediction Rules for Physical Therapy Interventions: A Systematic Review

    OpenAIRE

    Beneciuk, Jason M.; Bishop, Mark D; George, Steven Z.

    2009-01-01

    Background and Purpose: Clinical prediction rules (CPRs) involving physical therapy interventions have been published recently. The quality of the studies used to develop the CPRs was not previously considered, a fact that has potential implications for clinical applications and future research. The purpose of this systematic review was to determine the quality of published CPRs developed for physical therapy interventions.

  3. A clinical prediction rule for histological chorioamnionitis in preterm newborns.

    Directory of Open Access Journals (Sweden)

    Jasper V Been

    Full Text Available BACKGROUND: Histological chorioamnionitis (HC is an intrauterine inflammatory process highly associated with preterm birth and adverse neonatal outcome. HC is often clinically silent and diagnosed postnatally by placental histology. Earlier identification could facilitate treatment individualisation to improve outcome in preterm newborns. AIM: Develop a clinical prediction rule at birth for HC and HC with fetal involvement (HCF in preterm newborns. METHODS: Clinical data and placental pathology were obtained from singleton preterm newborns (gestational age ≤ 32.0 weeks born at Erasmus UMC Rotterdam from 2001 to 2003 (derivation cohort; n = 216 or Máxima MC Veldhoven from 2009 to 2010 (validation cohort; n = 206. HC and HCF prediction rules were developed with preference for high sensitivity using clinical variables available at birth. RESULTS: HC and HCF were present in 39% and 24% in the derivation cohort and in 44% and 22% in the validation cohort, respectively. HC was predicted with 87% accuracy, yielding an area under ROC curve of 0.95 (95%CI = 0.92-0.98, a positive predictive value of 80% (95%CI = 74-84%, and a negative predictive value of 93% (95%CI = 88-96%. Corresponding figures for HCF were: accuracy 83%, area under ROC curve 0.92 (95%CI = 0.88-0.96, positive predictive value 59% (95%CI = 52-62%, and negative predictive value 97% (95%CI = 93-99%. External validation expectedly resulted in some loss of test performance, preferentially affecting positive predictive rather than negative predictive values. CONCLUSION: Using a clinical prediction rule composed of clinical variables available at birth, HC and HCF could be predicted with good test characteristics in preterm newborns. Further studies should evaluate the clinical value of these rules to guide early treatment individualisation.

  4. Clinical prediction rules for failed nonoperative reduction of intussusception

    Science.gov (United States)

    Khorana, Jiraporn; Patumanond, Jayanton; Ukarapol, Nuthapong; Laohapensang, Mongkol; Visrutaratna, Pannee; Singhavejsakul, Jesda

    2016-01-01

    Purpose The nonoperative reduction of intussusception in children can be performed safely if there are no contraindications. Many risk factors associated with failed reduction were defined. The aim of this study was to develop a scoring system for predicting the failure of nonoperative reduction using various determinants. Patients and methods The data were collected from Chiang Mai University Hospital and Siriraj Hospital from January 2006 to December 2012. Inclusion criteria consisted of patients with intussusception aged 0–15 years with no contraindications for nonoperative reduction. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. Results A total of 170 patients with intussusception were included in the study. In the final analysis model, 154 patients were used for identifying the significant risk factors of failure of reduction. Ten factors clustering by the age of 3 years were identified and used for developing the clinical prediction rules, and the factors were as follows: body weight 48 hours (RR =1.26, P37.8°C (RR =1.51, P<0.001), palpable mass (RR =1.26, P<0.001), location of mass (left over right side RR =1.48, P<0.001), ultrasound showed poor prognostic signs (RR =1.35, P<0.001), and the method of reduction (hydrostatic over pneumatic, RR =1.34, P=0.023). Prediction scores ranged from 0 to 16. A high-risk group (scores 12–16) predicted a greater chance of reduction failure (likelihood ratio of positive [LR+] =18.22, P<0.001). A low-risk group (score 0–11) predicted a lower chance of reduction failure (LR+ =0.79, P<0.001). The performance of the scoring model was 80.68% (area under the receiver operating characteristic curve). Conclusion This scoring guideline was used to predict the results of nonoperative reduction and forecast the prognosis of the failed reduction. The usefulness of these prediction scores is for informing the parents before the reduction. This scoring system can be

  5. [Clinical probability of PE: should we use a clinical prediction rule?].

    Science.gov (United States)

    Le Gal, G; Righini, M; Perrier, A

    2008-12-01

    The determination of the clinical pretest probability using clinical prediction models is an important step in the assessment of patients with suspected pulmonary embolism (PE). It helps establish which test or sequence of tests can effectively corroborate or safely rule out PE. For example, it has been demonstrated that it is safe to withhold anticoagulant therapy in patients with negative d-dimer results and low pretest probability at initial presentation. Clinical probability will also increase the diagnostic yield of ventilation perfusion lung scan. Compared with clinical gestalt, clinical prediction rules provide a standardized and more reproducible estimate of a patient's probability of having a PE. Clinical prediction models combine aspects of the history and physical examination to categorize a patient's probability of having a disease. The models classify patients as having a low, moderate, or high likelihood of having PE. Clinical prediction models have been validated and are well established for the diagnosis of PE in symptomatic patients. They allow all physicians, whatever their expertise, to reliably determine the clinical pretest probability of PE, and thus safely manage their patients using diagnostic and therapeutic algorithms. PMID:19084205

  6. Critical appraisal of clinical prediction rules that aim to optimize treatment selection for musculoskeletal conditions

    NARCIS (Netherlands)

    T.R. Stanton (Tasha); M.J. Hancock (Mark J.); C. Maher (Chris); B.W. Koes (Bart)

    2010-01-01

    textabstractBackground. Clinical prediction rules (CPRs) for treatment selection in musculoskeletal conditions have become increasingly popular. Purpose. The purposes of this review are: (1) to critically appraise studies evaluating CPRs and (2) to consider the clinical utility and stage of developm

  7. Predicting pressure ulcers: cases missed using a new clinical prediction rule.

    NARCIS (Netherlands)

    Schoonhoven, L.; Grobbee, D.E.; Bousema, M.T.; Buskens, E.

    2005-01-01

    AIM: The aim of this paper is to report a study describing patients with pressure ulcers that were incorrectly classified as 'not at risk' by the prediction rule and comparing them with patients who were correctly classified as 'not at risk'. BACKGROUND: Patients admitted to hospital are at risk of

  8. Clinical prediction rules in Staphylococcus aureus bacteremia demonstrate the usefulness of reporting likelihood ratios in infectious diseases.

    Science.gov (United States)

    Bai, A D; Showler, A; Burry, L; Steinberg, M; Tomlinson, G A; Bell, C M; Morris, A M

    2016-09-01

    Infectious diseases specialists often use diagnostic tests to assess the probability of a disease based on knowledge of the diagnostic properties. It has become standard for published studies on diagnostic tests to report sensitivity, specificity and predictive values. Likelihood ratios are often omitted. We compared published clinical prediction rules in Staphylococcus aureus bacteremia to illustrate the importance of likelihood ratios. We performed a narrative review comparing published clinical prediction rules used for excluding endocarditis in S. aureus bacteremia. Of nine published clinical prediction rules, only three studies reported likelihood ratios. Many studies concluded that the clinical prediction rule could safely exclude endocarditis based on high sensitivity and high negative predictive value. Of the studies with similar high sensitivity and high negative predictive value, calculated negative likelihood ratios were able to differentiate and identify the best clinical prediction rule for excluding endocarditis. Compared to sensitivity, specificity and predictive values, likelihood ratios can be more directly used to interpret diagnostic test results to assist in ruling in or ruling out a disease. Therefore, a new standard should be set to include likelihood ratios in reporting of diagnostic tests in infectious diseases research. PMID:27357965

  9. Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score

    Directory of Open Access Journals (Sweden)

    Burnand Bernard

    2010-01-01

    Full Text Available Abstract Background Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. Methods Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. Results The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increasing with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774 revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81 with a sensitivity of 85.6% and a specificity of 47.2%. Conclusions This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.

  10. Translation of clinical prediction rules for febrile children to primary care practice: an observational cohort study

    Science.gov (United States)

    van Ierland, Yvette; Elshout, Gijs; Berger, Marjolein Y; Vergouwe, Yvonne; de Wilde, Marcel; van der Lei, Johan; Mol, Henriëtte A; Oostenbrink, Rianne

    2015-01-01

    Background Clinical prediction rules (CPRs) to identify children with serious infections lack validation in low-prevalence populations, which hampers their implementation in primary care practice. Aim To evaluate the diagnostic value of published CPRs for febrile children in primary care. Design and setting Observational cohort study among febrile children (<16 years) who consulted five GP cooperatives (GPCs) in the Netherlands. Method Alarm signs of serious infection and clinical management were extracted from routine clinical practice data and manually recoded with a structured electronic data-entry program. Eight CPRs were selected from literature. CPR-variables were matched with alarm signs and CPRs were applied to the GPC-population. ‘Referral to emergency department (ED)’ was used as a proxy outcome measure for ‘serious infection’. CPR performance was assessed by calibration analyses, sensitivity, specificity, and area under the ROC-curve (ROC-area). Results A total of 9794 GPC-contacts were eligible, 54% male, median age 2.3 years (interquartile range 1.0–4.6 years) and 8.1% referred to ED. Frequencies of CPR-variables varied from 0.5% (cyanosis, drowsy) to 25% (temperature ≥40°C). Alarm signs frequently included in CPRs were ‘ill appearance’, ‘inconsolable’, and ‘abnormal circulatory or respiratory signs’. The height of the CPR’s predicted risks generally corresponded with being (or not being) referred to the ED in practice. However, calibration-slopes indicated that three CPRs underestimated the risk of serious infection in the GPC-population. Sensitivities ranged from 42% to 54%, specificities from 68% to 89%. ROC-areas ranged from 0.52 to 0.81, with best performance of CPRs for children aged <3 months. Conclusion Published CPRs performed moderately well in the primary out-of-hours care population. Advice is given on how to improve translation of CPRs to primary care practice. PMID:25824182

  11. A clinical prediction rule for ambulation outcomes after traumatic spinal cord injury: a longitudinal cohort study

    NARCIS (Netherlands)

    Middendorp, J.J. van; Hosman, A.J.F.; Donders, A.R.T.; Pouw, M.H.; Ditunno Jr., J.F.; Curt, A.; Geurts, A.C.H.; Meent, H. van de

    2011-01-01

    BACKGROUND: Traumatic spinal cord injury is a serious disorder in which early prediction of ambulation is important to counsel patients and to plan rehabilitation. We developed a reliable, validated prediction rule to assess a patient's chances of walking independently after such injury. METHODS: We

  12. Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs)

    LENUS (Irish Health Repository)

    Wallace, Emma

    2011-10-14

    Abstract Clinical Prediction Rules (CPRs) are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.

  13. Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs

    Directory of Open Access Journals (Sweden)

    Verbakel Jan

    2011-10-01

    Full Text Available Abstract Clinical Prediction Rules (CPRs are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies. We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR. There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.

  14. Diagnostic accuracy of the STRATIFY clinical prediction rule for falls: A systematic review and meta-analysis

    LENUS (Irish Health Repository)

    Billington, Jennifer

    2012-08-07

    AbstractBackgroundThe STRATIFY score is a clinical prediction rule (CPR) derived to assist clinicians to identify patients at risk of falling. The purpose of this systematic review and meta-analysis is to determine the overall diagnostic accuracy of the STRATIFY rule across a variety of clinical settings.MethodsA literature search was performed to identify all studies that validated the STRATIFY rule. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A STRATIFY score of ≥2 points was used to identify individuals at higher risk of falling. All included studies were combined using a bivariate random effects model to generate pooled sensitivity and specificity of STRATIFY at ≥2 points. Heterogeneity was assessed using the variance of logit transformed sensitivity and specificity.ResultsSeventeen studies were included in our meta-analysis, incorporating 11,378 patients. At a score ≥2 points, the STRATIFY rule is more useful at ruling out falls in those classified as low risk, with a greater pooled sensitivity estimate (0.67, 95% CI 0.52–0.80) than specificity (0.57, 95% CI 0.45 – 0.69). The sensitivity analysis which examined the performance of the rule in different settings and subgroups also showed broadly comparable results, indicating that the STRATIFY rule performs in a similar manner across a variety of different ‘at risk’ patient groups in different clinical settings.ConclusionThis systematic review shows that the diagnostic accuracy of the STRATIFY rule is limited and should not be used in isolation for identifying individuals at high risk of falls in clinical practice.

  15. Accuracy of clinical prediction rules in peptic ulcer perforation: an observational study

    DEFF Research Database (Denmark)

    Buck, David Levarett; Vester-Andersen, Morten; Møller, Morten Hylander

    2012-01-01

    (APACHE) II score, and the sepsis score. Material and methods. Design: an observational multicenter study. Participants and settings: a total of 117 patients surgically treated for PPU between 1 January 2008 and 31 December 2009 in seven gastrointestinal departments in Denmark were included. Pregnant......% of the patients had at least one co-existing disease. The 30-day mortality proportion was 17% (20/117). The AUCs: the Boey score, 0.63; the sepsis score, 0.69; the ASA score, 0.73; and the APACHE II score, 0.76. Overall, the PPVs of all four prediction rules were low and the NPVs high. Conclusions. The Boey score......, the ASA score, the APACHE II score, and the sepsis score predict mortality poorly in patients with PPU....

  16. Developing a Clinical Prediction Rule for First Hospital-Onset Clostridium difficile Infections: A Retrospective Observational Study.

    Science.gov (United States)

    Press, Anne; Ku, Benson; McCullagh, Lauren; Rosen, Lisa; Richardson, Safiya; McGinn, Thomas

    2016-08-01

    BACKGROUND The healthcare burden of hospital-acquired Clostridium difficile infection (CDI) demands attention and calls for a solution. Identifying patients' risk of developing a primary nosocomial CDI is a critical first step in reducing the development of new cases of CDI. OBJECTIVE To derive a clinical prediction rule that can predict a patient's risk of acquiring a primary CDI. DESIGN Retrospective cohort study. SETTING Large tertiary healthcare center. PATIENTS Total of 61,482 subjects aged at least 18 admitted over a 1-year period (2013). INTERVENTION None. METHODS Patient demographic characteristics, evidence of CDI, and other risk factors were retrospectively collected. To derive the CDI clinical prediction rule the patient population was divided into a derivation and validation cohort. A multivariable analysis was performed in the derivation cohort to identify risk factors individually associated with nosocomial CDI and was validated on the validation sample. RESULTS Among 61,482 subjects, CDI occurred in 0.46%. CDI outcome was significantly associated with age, admission in the past 60 days, mechanical ventilation, dialysis, history of congestive heart failure, and use of antibiotic medications. The sensitivity and specificity of the score, in the validation set, were 82.0% and 75.7%, respectively. The area under the receiver operating characteristic curve was 0.85. CONCLUSION This study successfully derived a clinical prediction rule that will help identify patients at high risk for primary CDI. This tool will allow physicians to systematically recognize those at risk for CDI and will allow for early interventional strategies. Infect Control Hosp Epidemiol 2016;37:896-900. PMID:27123975

  17. Rationale, design, and implementation protocol of an electronic health record integrated clinical prediction rule (iCPR randomized trial in primary care

    Directory of Open Access Journals (Sweden)

    Wisnivesky Juan

    2011-09-01

    Full Text Available Abstract Background Clinical prediction rules (CPRs represent well-validated but underutilized evidence-based medicine tools at the point-of-care. To date, an inability to integrate these rules into an electronic health record (EHR has been a major limitation and we are not aware of a study demonstrating the use of CPR's in an ambulatory EHR setting. The integrated clinical prediction rule (iCPR trial integrates two CPR's in an EHR and assesses both the usability and the effect on evidence-based practice in the primary care setting. Methods A multi-disciplinary design team was assembled to develop a prototype iCPR for validated streptococcal pharyngitis and bacterial pneumonia CPRs. The iCPR tool was built as an active Clinical Decision Support (CDS tool that can be triggered by user action during typical workflow. Using the EHR CDS toolkit, the iCPR risk score calculator was linked to tailored ordered sets, documentation, and patient instructions. The team subsequently conducted two levels of 'real world' usability testing with eight providers per group. Usability data were used to refine and create a production tool. Participating primary care providers (n = 149 were randomized and intervention providers were trained in the use of the new iCPR tool. Rates of iCPR tool triggering in the intervention and control (simulated groups are monitored and subsequent use of the various components of the iCPR tool among intervention encounters is also tracked. The primary outcome is the difference in antibiotic prescribing rates (strep and pneumonia iCPR's encounters and chest x-rays (pneumonia iCPR only between intervention and control providers. Discussion Using iterative usability testing and development paired with provider training, the iCPR CDS tool leverages user-centered design principles to overcome pervasive underutilization of EBM and support evidence-based practice at the point-of-care. The ongoing trial will determine if this collaborative

  18. Clinical prediction rules combining signs, symptoms and epidemiological context to distinguish influenza from influenza-like illnesses in primary care: a cross sectional study

    Directory of Open Access Journals (Sweden)

    Van Royen Paul

    2011-02-01

    Full Text Available Abstract Background During an influenza epidemic prompt diagnosis of influenza is important. This diagnosis however is still essentially based on the interpretation of symptoms and signs by general practitioners. No single symptom is specific enough to be useful in differentiating influenza from other respiratory infections. Our objective is to formulate prediction rules for the diagnosis of influenza with the best diagnostic performance, combining symptoms, signs and context among patients with influenza-like illness. Methods During five consecutive winter periods (2002-2007 138 sentinel general practitioners sampled (naso- and oropharyngeal swabs 4597 patients with an influenza-like illness (ILI and registered their symptoms and signs, general characteristics and contextual information. The samples were analysed by a DirectigenFlu-A&B and RT-PCR tests. 4584 records were useful for further analysis. Starting from the most relevant variables in a Generalized Estimating Equations (GEE model, we calculated the area under the Receiver Operating Characteristic curve (ROC AUC, sensitivity, specificity and likelihood ratios for positive (LR+ and negative test results (LR- of single and combined signs, symptoms and context taking into account pre-test and post-test odds. Results In total 52.6% (2409/4584 of the samples were positive for influenza virus: 64% (2066/3212 during and 25% (343/1372 pre/post an influenza epidemic. During and pre/post an influenza epidemic the LR+ of 'previous flu-like contacts', 'coughing', 'expectoration on the first day of illness' and 'body temperature above 37.8°C' is 3.35 (95%CI 2.67-4.03 and 1.34 (95%CI 0.97-1.72, respectively. During and pre/post an influenza epidemic the LR- of 'coughing' and 'a body temperature above 37.8°C' is 0.34 (95%CI 0.27-0.41 and 0.07 (95%CI 0.05-0.08, respectively. Conclusions Ruling out influenza using clinical and contextual information is easier than ruling it in. Outside an influenza

  19. Evolving Decision Rules to Predict Investment Opportunities

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper is motivated by the interest in finding significant movements in financial stock prices. However, when the number of profitable opportunities is scarce, the prediction of these cases is difficult. In a previous work, we have introduced evolving decision rules (EDR) to detect financial opportunities. The objective of EDR is to classify the minority class (positive cases) in imbalanced environments. EDR provides a range of classifications to find the best balance between not making mistakes and not missing opportunities. The goals of this paper are: 1) to show that EDR produces a range of solutions to suit the investor's preferences and 2) to analyze the factors that benefit the performance of EDR. A series of experiments was performed. EDR was tested using a data set from the London Financial Market. To analyze the EDR behaviour, another experiment was carried out using three artificial data sets, whose solutions have different levels of complexity. Finally, an illustrative example was provided to show how a bigger collection of rules is able to classify more positive cases in imbalanced data sets. Experimental results show that: 1) EDR offers a range of solutions to fit the risk guidelines of different types of investors, and 2) a bigger collection of rules is able to classify more positive cases in imbalanced environments.

  20. LERM (Logical Elements Rule Method): A method for assessing and formalizing clinical rules for decision support

    NARCIS (Netherlands)

    S. Medlock; D. Opondo; S. Eslami; M. Askari; P. Wierenga; S.E. de Rooij; A. Abu-Hanna

    2011-01-01

    Purpose: The aim of this study was to create a step-by-step method for transforming clinical rules for use in decision support, and to validate this method for usability and reliability. Methods: A sample set of clinical rules was identified from the relevant literature. Using an iterative approach

  1. On the Predictivity of Neutrino Mass Sum Rules

    CERN Document Server

    Gehrlein, Julia; Spinrath, Martin

    2016-01-01

    Correlations between light neutrino observables are arguably the strongest predictions of lepton flavour models based on (discrete) symmetries, except for the very few cases which unambiguously predict the full set of leptonic mixing angles. A subclass of these correlations are neutrino mass sum rules, which connect the three (complex) light neutrino mass eigenvalues among each other. This connection constrains both the light neutrino mass scale and the Majorana phases, so that mass sum rules generically lead to a non-zero value of the lightest neutrino mass and to distinct predictions for the effective mass probed in neutrinoless double beta decay. However, in nearly all cases known, the neutrino mass sum rules are not exact and receive corrections from various sources. We introduce a formalism to handle these corrections perturbatively in a model-independent manner, which overcomes issues present in earlier approaches. Our ansatz allows us to quantify the modification of the predictions derived from neutrin...

  2. Knowledge Discovery for A Temporal Prediction Rules

    Institute of Scientific and Technical Information of China (English)

    TIAN Yuan; MENG Zhi-qing

    2007-01-01

    We are obtaining a large database of some objects' records of fluctuations of a stock market,medical treatments,changes of weather in certain area and so on,where each record consists of multi-attributes taking multi-values changing with time.Our worlk is motivated by prediction,which is difierent from the work in[4,5,8,11].We want to help learn from past data and make informed decisions for the future.This paper is very significant to perfect the theory and the development of the temporal data mining.

  3. Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule

    NARCIS (Netherlands)

    Vergouwe, Y.; Soedamah-Muthu, S.S.; Zgibor, J.; Chaturvedi, N.; Forsblom, C.; Snell-Bergeon, J.K.; Maahs, D.M.; Groop, P.H.; Rewers, M.; Orchard, T.J.; Fuller, J.H.; Moons, K.G.M.

    2010-01-01

    AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Pros

  4. PHARM – Association Rule Mining for Predictive Health

    Science.gov (United States)

    Cheng, Chih-Wen; Martin, Greg S.; Wu, Po-Yen; Wang, May D.

    2016-01-01

    Predictive health is a new and innovative healthcare model that focuses on maintaining health rather than treating diseases. Such a model may benefit from computer-based decision support systems, which provide more quantitative health assessment, enabling more objective advice and action plans from predictive health providers. However, data mining for predictive health is more challenging compared to that for diseases. This is a reason why there are relatively fewer predictive health decision support systems embedded with data mining. The purpose of this study is to research and develop an interactive decision support system, called PHARM, in conjunction with Emory Center for Health Discovery and Well Being (CHDWB®). PHARM adopts association rule mining to generate quantitative and objective rules for health assessment and prediction. A case study results in 12 rules that predict mental illness based on five psychological factors. This study shows the value and usability of the decision support system to prevent the development of potential illness and to prioritize advice and action plans for reducing disease risks.

  5. The derivation and validation of a prediction rule for differential diagnosis of thyroid nodules

    Institute of Scientific and Technical Information of China (English)

    李拓

    2013-01-01

    Objective To set up a prediction rule for the pro-operative differential diagnosis of thyroid nodules and evaluate its clinical value.Methods All patients of thyroid nodules undergoing thyroid operations in Changzheng hospital from June,1997 to July,2012 were included in this study.They were randomly divided into the derivation cohort (2/3) and the validation cohort (1/3) .A prediction rule was developed based on the logistic regression model and the scoring system was established in accordance with assigning of the value of each variableβ

  6. Associative Regressive Decision Rule Mining for Predicting Customer Satisfactory Patterns

    Directory of Open Access Journals (Sweden)

    P. Suresh

    2016-04-01

    Full Text Available Opinion mining also known as sentiment analysis, involves cust omer satisfactory patterns, sentiments and attitudes toward entities, products, service s and their attributes. With the rapid development in the field of Internet, potential customer’s provi des a satisfactory level of product/service reviews. The high volume of customer rev iews were developed for product/review through taxonomy-aware processing but, it was di fficult to identify the best reviews. In this paper, an Associative Regression Decisio n Rule Mining (ARDRM technique is developed to predict the pattern for service provider and to improve customer satisfaction based on the review comments. Associative Regression based Decisi on Rule Mining performs two- steps for improving the customer satisfactory level. Initial ly, the Machine Learning Bayes Sentiment Classifier (MLBSC is used to classify the cla ss labels for each service reviews. After that, Regressive factor of the opinion words and Class labels w ere checked for Association between the words by using various probabilistic rules. Based on t he probabilistic rules, the opinion and sentiments effect on customer reviews, are analyzed to arrive at specific set of service preferred by the customers with their review com ments. The Associative Regressive Decision Rule helps the service provider to take decision on imp roving the customer satisfactory level. The experimental results reveal that the Associ ative Regression Decision Rule Mining (ARDRM technique improved the performance in terms of true positive rate, Associative Regression factor, Regressive Decision Rule Generation time a nd Review Detection Accuracy of similar pattern.

  7. A systematic review of clinical decision rules for epilepsy.

    Science.gov (United States)

    Josephson, Colin B; Sandy, Sherry; Jette, Nathalie; Sajobi, Tolulope T; Marshall, Deborah; Wiebe, Samuel

    2016-04-01

    Clinical decision rules (CDRs) have been empirically demonstrated to improve patient satisfaction and enhance cost-effective care. The use of CDRs has not yet been robustly explored for epilepsy. We performed a systematic review of MEDLINE (from 1946) and Embase (from 1947) using Medical Subject Headings and keywords related to CDRs and epilepsy. We included original research of any language deriving, validating, or implementing a CDR using standardized definitions. Study quality was determined using a modified version of previously published criteria. A bivariate model was used to meta-analyze studies undergoing sequential derivation and validation studies. Of 2445 unique articles, 5 were determined to be relevant to this review. Three were derivation studies (three diagnostic and one therapeutic), one validation study, and one combined derivation and validation study. No implementation studies were identified. Study quality varied but was primarily of a moderate level. Two CDRs were validated and, thus, able to be meta-analyzed. Although initial measures of accuracy were high (sensitivity ~80% or above), they tended to diminish significantly in the validation studies. The pooled estimates of sensitivity and specificity both exhibited wide 95% confidence and prediction intervals that may limit their utility in routine practice. Despite the advances in therapeutic and diagnostic interventions for epilepsy, few CDRs have been developed to guide their use. Future CDRs should address common clinical scenarios such as efficient use of diagnostic tools and optimal clinical treatment decisions. Given their potential for advancing efficient, evidence-based, patient-centered healthcare, CDR development should be a priority in epilepsy. PMID:26922491

  8. Prediction of users webpage access behaviour using association rule mining

    Indian Academy of Sciences (India)

    R Geetharamani; P Revathy; Shomona G Jacob

    2015-12-01

    Web Usage mining is a technique used to identify the user needs from the web log. Discovering hidden patterns from the logs is an upcoming research area. Association rules play an important role in many web mining applications to detect interesting patterns. However, it generates enormous rules that cause researchers to spend ample time and expertise to discover the really interesting ones. This paper works on the server logs from the MSNBC dataset for the month of September 1999. This research aims at predicting the probable subsequent page in the usage of web pages listed in this data based on their navigating behaviour by using Apriori prefix tree (PT) algorithm. The generated rules were ranked based on the support, confidence and lift evaluation measures. The final predictions revealed that the interestingness of pages mainly depended on the support and lift measure whereas confidence assumed a uniform value among all the pages. It proved that the system guaranteed 100% confidence with the support of 1.3E−05. It revealed that the pages such as Front page, On-air, News, Sports and BBS attracted more interested subsequent users compared to Travel, MSN-News and MSN-Sports which were of less interest.

  9. ASSOCIATION RULE DISCOVERY FOR STUDENT PERFORMANCE PREDICTION USING METAHEURISTIC ALGORITHMS

    Directory of Open Access Journals (Sweden)

    Roghayeh Saneifar

    2015-11-01

    Full Text Available According to the increase of using data mining techniques in improving educational systems operations, Educational Data Mining has been introduced as a new and fast growing research area. Educational Data Mining aims to analyze data in educational environments in order to solve educational research problems. In this paper a new associative classification technique has been proposed to predict students final performance. Despite of several machine learning approaches such as ANNs, SVMs, etc. associative classifiers maintain interpretability along with high accuracy. In this research work, we have employed Honeybee Colony Optimization and Particle Swarm Optimization to extract association rule for student performance prediction as a multi-objective classification problem. Results indicate that the proposed swarm based algorithm outperforms well-known classification techniques on student performance prediction classification problem.

  10. Clinical Trials Registration and Results Information Submission. Final rule.

    Science.gov (United States)

    2016-09-21

    This final rule details the requirements for submitting registration and summary results information, including adverse event information, for specified clinical trials of drug products (including biological products) and device products and for pediatric postmarket surveillances of a device product to ClinicalTrials.gov, the clinical trial registry and results data bank operated by the National Library of Medicine (NLM) of the National Institutes of Health (NIH). This rule provides for the expanded registry and results data bank specified in Title VIII of the Food and Drug Administration Amendments Act of 2007 (FDAAA) to help patients find trials for which they might be eligible, enhance the design of clinical trials and prevent duplication of unsuccessful or unsafe trials, improve the evidence base that informs clinical care, increase the efficiency of drug and device development processes, improve clinical research practice, and build public trust in clinical research. The requirements apply to the responsible party (meaning the sponsor or designated principal investigator) for certain clinical trials of drug products (including biological products) and device products that are regulated by the Food and Drug Administration (FDA) and for pediatric postmarket surveillances of a device product that are ordered by FDA. PMID:27658315

  11. Using data-driven rules to predict mortality in severe community acquired pneumonia.

    Directory of Open Access Journals (Sweden)

    Chuang Wu

    Full Text Available Prediction of patient-centered outcomes in hospitals is useful for performance benchmarking, resource allocation, and guidance regarding active treatment and withdrawal of care. Yet, their use by clinicians is limited by the complexity of available tools and amount of data required. We propose to use Disjunctive Normal Forms as a novel approach to predict hospital and 90-day mortality from instance-based patient data, comprising demographic, genetic, and physiologic information in a large cohort of patients admitted with severe community acquired pneumonia. We develop two algorithms to efficiently learn Disjunctive Normal Forms, which yield easy-to-interpret rules that explicitly map data to the outcome of interest. Disjunctive Normal Forms achieve higher prediction performance quality compared to a set of state-of-the-art machine learning models, and unveils insights unavailable with standard methods. Disjunctive Normal Forms constitute an intuitive set of prediction rules that could be easily implemented to predict outcomes and guide criteria-based clinical decision making and clinical trial execution, and thus of greater practical usefulness than currently available prediction tools. The Java implementation of the tool JavaDNF will be publicly available.

  12. Rule based Part of speech Tagger for Homoeopathy Clinical realm

    CERN Document Server

    Dwivedi, Sanjay K

    2011-01-01

    A tagger is a mandatory segment of most text scrutiny systems, as it consigned a s yntax class (e.g., noun, verb, adjective, and adverb) to every word in a sentence. In this paper, we present a simple part of speech tagger for homoeopathy clinical language. This paper reports about the anticipated part of speech tagger for homoeopathy clinical language. It exploit standard pattern for evaluating sentences, untagged clinical corpus of 20085 words is used, from which we had selected 125 sentences (2322 tokens). The problem of tagging in natural language processing is to find a way to tag every word in a text as a meticulous part of speech. The basic idea is to apply a set of rules on clinical sentences and on each word, Accuracy is the leading factor in evaluating any POS tagger so the accuracy of proposed tagger is also conversed.

  13. Rule based Part of speech Tagger for Homoeopathy Clinical realm

    Directory of Open Access Journals (Sweden)

    Sanjay Kumar Dwivedi

    2011-07-01

    Full Text Available A tagger is a mandatory segment of most text scrutiny systems, as it consigned a syntax class (e.g., noun, verb, adjective, and adverb to every word in a sentence. In this paper, we present a simple part of speech tagger for homoeopathy clinical language. This paper reports about the anticipated part of speech tagger for homoeopathy clinical language. It exploit standard pattern for evaluating sentences, untagged clinical corpus of 20085 words is used, from which we had selected 125 sentences (2322 tokens. The problem of tagging in natural language processing is to find a way to tag every word in a text as a meticulous part of speech. The basic idea is to apply a set of rules on clinical sentences and on each word, Accuracy is the leading factor in evaluating any POS tagger so the accuracy of proposed tagger is also conversed.

  14. Madelung rule violation statistics and superheavy elements electron shell prediction

    CERN Document Server

    Loza, E

    2012-01-01

    The paper presents tetrahedron periodic table to conveniently include superheavy elements. Madelung rule violation statistics is discussed and a model for Madelung rule violation probability calculation is proposed. On its basis superheavy elements probable electron shell structure is determined.

  15. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  16. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    Science.gov (United States)

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  17. Rule base system in developing groundwater pollution expert system: predicting model

    International Nuclear Information System (INIS)

    New techniques are now available for use in the protection of the environment. One of these techniques is the use of expert system for prediction groundwater pollution potential. Groundwater Pollution Expert system (GWPES) rules are a collection of principles and procedures used to know the comprehension of groundwater pollution prediction. The rules of groundwater pollution expert system in the form of questions, choice, radio-box, slide rule, button or frame are translated in to IF-THEN rule. The rules including of variables, types, domains and descriptions were used by the function of wxCLIPS (C Language Integrate Production System) expert system shell. (author)

  18. Dopaminergic Genetic Polymorphisms Predict Rule-based Category Learning.

    Science.gov (United States)

    Byrne, Kaileigh A; Davis, Tyler; Worthy, Darrell A

    2016-07-01

    Dopaminergic genes play an important role in cognitive function. DRD2 and DARPP-32 dopamine receptor gene polymorphisms affect striatal dopamine binding potential, and the Val158Met single-nucleotide polymorphism of the COMT gene moderates dopamine availability in the pFC. Our study assesses the role of these gene polymorphisms on performance in two rule-based category learning tasks. Participants completed unidimensional and conjunctive rule-based tasks. In the unidimensional task, a rule along a single stimulus dimension can be used to distinguish category members. In contrast, a conjunctive rule utilizes a combination of two dimensions to distinguish category members. DRD2 C957T TT homozygotes outperformed C allele carriers on both tasks, and DARPP-32 AA homozygotes outperformed G allele carriers on both tasks. However, we found an interaction between COMT and task type where Met allele carriers outperformed Val homozygotes in the conjunctive rule task, but both groups performed equally well in the unidimensional task. Thus, striatal dopamine binding may play a critical role in both types of rule-based tasks, whereas prefrontal dopamine binding is important for learning more complex conjunctive rule tasks. Modeling results suggest that striatal dopaminergic genes influence selective attention processes whereas cortical genes mediate the ability to update complex rule representations. PMID:26918585

  19. An Analysis on Qualitative Bankruptcy Prediction Rules using Ant-Miner

    OpenAIRE

    Martin, A. (Alan); T.Miranda Lakshmi; V. Prasanna Venkatesan

    2013-01-01

    Qualitative bankruptcy prediction rules represent experts' problem-solving knowledge to predict qualitative bankruptcy. The objective of this research is predicting qualitative bankruptcy using ant-miner algorithm. Qualitative data are subjective and more difficult to measure. This approach uses qualitative risk factors which include fourteen internal risk factors and sixty eight external risk factors associated with it. By using these factors qualitative prediction rules are generated using ...

  20. Meta-analysis of clinical prediction models

    NARCIS (Netherlands)

    Debray, T.P.A.

    2013-01-01

    The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro

  1. On Implementing Clinical Decision Support: Achieving Scalability and Maintainability by Combining Business Rules and Ontologies.

    OpenAIRE

    Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

    2006-01-01

    We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances...

  2. An Analysis on Qualitative Bankruptcy Prediction Rules using Ant-Miner

    Directory of Open Access Journals (Sweden)

    A. Martin

    2013-12-01

    Full Text Available Qualitative bankruptcy prediction rules represent experts' problem-solving knowledge to predict qualitative bankruptcy. The objective of this research is predicting qualitative bankruptcy using ant-miner algorithm. Qualitative data are subjective and more difficult to measure. This approach uses qualitative risk factors which include fourteen internal risk factors and sixty eight external risk factors associated with it. By using these factors qualitative prediction rules are generated using ant-miner algorithm and the influence of these factors in bankruptcy is also analyzed. Ant-Miner algorithm is a application of ant colony optimization and data mining concepts. Qualitative rules generated by ant miner algorithm are validated using measure of agreement. These prediction rules yields better accuracy with lesser number of terms than previously applied qualitative bankruptcy prediction methodologies.

  3. Slide rule-type color chart predicts reproduced photo tones

    Science.gov (United States)

    Griffin, J. D.

    1966-01-01

    Slide rule-type color chart determines the final reproduced gray tones in the production of briefing charts that are photographed in black and white. The chart shows both the color by drafting paint manufacturers name and mixture number, and the gray tone resulting from black and white photographic reproduction.

  4. A Prediction Rule for Risk Stratification of Incidentally Discovered Gallstones

    DEFF Research Database (Denmark)

    Shabanzadeh, Daniel Mønsted; Sørensen, Lars Tue; Jørgensen, Torben

    2016-01-01

    BACKGROUND & AIMS: No one knows exactly what proportion of gallstones cause clinical events among subjects unaware of their gallstone status. We investigated the long-term occurrence of clinical events of gallstones and associations between ultrasound observations and clinical events. METHODS: We...

  5. Radiogenomics: predicting clinical normal tissue radiosensitivity

    DEFF Research Database (Denmark)

    Alsner, Jan

    2006-01-01

    of subcutaneous fibrosis in breast cancer patients will be presented and discussed in relation to possible future studies in radiogenomics. One important and necessary basis for future studies is the collection of carefully designed clinical studies with the accrual of very large numbers of patients (the ESTRO......Studies on the genetic basis of normal tissue radiosensitivity, or  'radiogenomics', aims at predicting clinical radiosensitivity and optimize treatment from individual genetic profiles. Several studies have now reported links between variations in certain genes related to the biological response...... to radiation injury and risk of normal tissue morbidity in cancer patients treated with radiotherapy. However, after these initial association studies including few genes, we are still far from being able to predict clinical radiosensitivity on an individual level. Recent data from our own studies on risk...

  6. Prediction on carbon dioxide emissions based on fuzzy rules

    Science.gov (United States)

    Pauzi, Herrini; Abdullah, Lazim

    2014-06-01

    There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

  7. Outcome Prediction Rule for Neonatal Hypoxic-Ischemic Encephalopathy

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2006-08-01

    Full Text Available A prognostic model for term infants with postasphyxial hypoxic-ischemic encephalopathy (HIE based on clinical and laboratory predictors available at age 4 hours was developed at Mount Sinai Hospital and Hospital for Sick Children, Toronto, Ontario.

  8. Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

    Science.gov (United States)

    Wang, Shan; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

    2015-12-01

    Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient.

  9. A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions.

    Directory of Open Access Journals (Sweden)

    Anirban Mukhopadhyay

    Full Text Available Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1-human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1-human interaction network. Novel HIV-1-human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed.

  10. Performance of thirteen clinical rules to distinguish bacterial and presumed viral meningitis in Vietnamese children.

    Directory of Open Access Journals (Sweden)

    Nguyen Tien Huy

    Full Text Available BACKGROUND AND PURPOSE: Successful outcomes from bacterial meningitis require rapid antibiotic treatment; however, unnecessary treatment of viral meningitis may lead to increased toxicities and expense. Thus, improved diagnostics are required to maximize treatment and minimize side effects and cost. Thirteen clinical decision rules have been reported to identify bacterial from viral meningitis. However, few rules have been tested and compared in a single study, while several rules are yet to be tested by independent researchers or in pediatric populations. Thus, simultaneous test and comparison of these rules are required to enable clinicians to select an optimal diagnostic rule for bacterial meningitis in settings and populations similar to ours. METHODS: A retrospective cross-sectional study was conducted at the Infectious Department of Pediatric Hospital Number 1, Ho Chi Minh City, Vietnam. The performance of the clinical rules was evaluated by area under a receiver operating characteristic curve (ROC-AUC using the method of DeLong and McNemar test for specificity comparison. RESULTS: Our study included 129 patients, of whom 80 had bacterial meningitis and 49 had presumed viral meningitis. Spanos's rule had the highest AUC at 0.938 but was not significantly greater than other rules. No rule provided 100% sensitivity with a specificity higher than 50%. Based on our calculation of theoretical sensitivity and specificity, we suggest that a perfect rule requires at least four independent variables that posses both sensitivity and specificity higher than 85-90%. CONCLUSIONS: No clinical decision rules provided an acceptable specificity (>50% with 100% sensitivity when applying our data set in children. More studies in Vietnam and developing countries are required to develop and/or validate clinical rules and more very good biomarkers are required to develop such a perfect rule.

  11. Medicare Program; Medicare Clinical Diagnostic Laboratory Tests Payment System. Final rule.

    Science.gov (United States)

    2016-06-23

    This final rule implements requirements of section 216 of the Protecting Access to Medicare Act of 2014 (PAMA), which significantly revises the Medicare payment system for clinical diagnostic laboratory tests. This final rule also announces an implementation date of January 1, 2018 for the private payor rate-based fee schedule required by PAMA.

  12. Research on spatial state conversion rule mining and stochastic predicting based on CA

    Science.gov (United States)

    Li, Xinyun; Kong, Xiangqiang

    2007-06-01

    Spatial dynamic prediction in GIS is the process of spatial calculation that infers the thematic maps in future according to the historical thematic maps, and it is space-time calculation from map to map. There is great application value that spatial dynamic prediction applied to the land planning, urban land-use planning and town planning, but there is some imperfect in method and technique at present. The main technical difficulty is excavation and expression of spatial state conversion rule. In allusion to the deficiency in spatial dynamic prediction using CA, the method which excavated spatial state conversion rule based on spatial data mining was put forward. Stochastic simulation mechanism was put into the prediction calculating based on state conversion rule. The result of prediction was more rational and the relation between the prediction steps and the time course was clearer. The method was applied to prediction of spatial structure change of urban land-use in Jinan. The Urban land-use change maps were predicted in 2006 and 2010 by using the land-use maps in 1998 and 2002. The result of this test was rational by analyzing.

  13. A programmable rules engine to provide clinical decision support using HTML forms.

    OpenAIRE

    Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A te...

  14. Clinical predictive factors of pathologic tumor response

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Chi Hwan; Kim, Won Dong; Lee, Sang Jeon; Park, Woo Yoon [Chungbuk National University College of Medicine, Cheongju (Korea, Republic of)

    2012-09-15

    The aim of this study was to identify clinical predictive factors for tumor response after preoperative chemoradiotherapy (CRT) in rectal cancer. The study involved 51 patients who underwent preoperative CRT followed by surgery between January 2005 and February 2012. Radiotherapy was delivered to the whole pelvis at a dose of 45 Gy in 25 fractions, followed by a boost of 5.4 Gy in 3 fractions to the primary tumor with 5 fractions per week. Three different chemotherapy regimens were used. Tumor responses to preoperative CRT were assessed in terms of tumor downstaging and pathologic complete response (ypCR). Statistical analyses were performed to identify clinical factors associated with pathologic tumor response. Tumor downstaging was observed in 28 patients (54.9%), whereas ypCR was observed in 6 patients (11.8%). Multivariate analysis found that predictors of downstaging was pretreatment relative lymphocyte count (p = 0.023) and that none of clinical factors was significantly associated with ypCR. Pretreatment relative lymphocyte count (%) has a significant impact on the pathologic tumor response (tumor downstaging) after preoperative CRT for locally advanced rectal cancer. Enhancement of lymphocyte-mediated immune reactions may improve the effect of preoperative CRT for rectal cancer.

  15. Rule based Part of speech Tagger for Homoeopathy Clinical realm

    OpenAIRE

    Sanjay Kumar Dwivedi; Pramod P Sukhadeve

    2011-01-01

    A tagger is a mandatory segment of most text scrutiny systems, as it consigned a syntax class (e.g., noun, verb, adjective, and adverb) to every word in a sentence. In this paper, we present a simple part of speech tagger for homoeopathy clinical language. This paper reports about the anticipated part of speech tagger for homoeopathy clinical language. It exploit standard pattern for evaluating sentences, untagged clinical corpus of 20085 words is used, from which we had selected 125 sentence...

  16. Clinical value of the Ottawa ankle rules for diagnosis of fractures in acute ankle injuries.

    Directory of Open Access Journals (Sweden)

    Xin Wang

    Full Text Available BACKGROUND: The Ottawa ankle rules (OAR are clinical decision guidelines used to identify whether patients with ankle injuries need to undergo radiography. The OAR have been proven that their application reduces unnecessary radiography. They have nearly perfect sensitivity for identifying clinically significant ankle fractures. OBJECTIVES: The purpose of this study was to assess the applicability of the OAR in China, to examine their accuracy for the diagnosis of fractures in patients with acute ankle sprains, and to assess their clinical utility for the detection of occult fractures. METHODS: In this prospective study, patients with acute ankle injuries were enrolled during a 6-month period. The eligible patients were examined by emergency orthopedic specialists using the OAR, and then underwent ankle radiography. The results of examination using the OAR were compared with the radiographic results to assess the accuracy of the OAR for ankle fractures. Patients with OAR results highly suggestive of fracture, but no evidence of a fracture on radiographs, were advised to undergo 3-dimensional computed tomography (3D-CT. RESULTS: 183 patients with ankle injuries were enrolled in the study and 63 of these injuries involved fractures. The pooled sensitivity, specificity, positive predictive value and negative predictive value of the OAR for detection of fractures of the ankle were 96.8%, 45.8%, 48.4% and 96.5%, respectively. Our results suggest that clinical application of the OAR could decrease unnecessary radiographs by 31.1%. Of the 21 patients with positive OAR results and negative radiographic findings who underwent 3D-CT examination, five had occult fractures of the lateral malleolus. CONCLUSIONS: The OAR are applicable in the Chinese population, and have high sensitivity and modest specificity for the diagnosis of fractures associated with acute ankle injury. They may detect some occult fractures of the malleoli that are not visible on

  17. A study of diverse clinical decision support rule authoring environments and requirements for integration

    Directory of Open Access Journals (Sweden)

    Zhou Li

    2012-11-01

    Full Text Available Abstract Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs, Software Engineers (SEs, and Subject Matter Experts (SMEs to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR systems, testing, and reporting.

  18. Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning.

    Science.gov (United States)

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-07-01

    Often the world is structured such that distinct sensory contexts signify the same abstract rule set. Learning from feedback thus informs us not only about the value of stimulus-action associations but also about which rule set applies. Hierarchical clustering models suggest that learners discover structure in the environment, clustering distinct sensory events into a single latent rule set. Such structure enables a learner to transfer any newly acquired information to other contexts linked to the same rule set, and facilitates re-use of learned knowledge in novel contexts. Here, we show that humans exhibit this transfer, generalization and clustering during learning. Trial-by-trial model-based analysis of EEG signals revealed that subjects' reward expectations incorporated this hierarchical structure; these structured neural signals were predictive of behavioral transfer and clustering. These results further our understanding of how humans learn and generalize flexibly by building abstract, behaviorally relevant representations of the complex, high-dimensional sensory environment. PMID:27082659

  19. A clinical decision rule for the use of plain radiography in children after acute wrist injury: development and external validation of the Amsterdam Pediatric Wrist Rules

    International Nuclear Information System (INIS)

    In most hospitals, children with acute wrist trauma are routinely referred for radiography. To develop and validate a clinical decision rule to decide whether radiography in children with wrist trauma is required. We prospectively developed and validated a clinical decision rule in two study populations. All children who presented in the emergency department of four hospitals with pain following wrist trauma were included and evaluated for 18 clinical variables. The outcome was a wrist fracture diagnosed by plain radiography. Included in the study were 787 children. The prediction model consisted of six variables: age, swelling of the distal radius, visible deformation, distal radius tender to palpation, anatomical snuffbox tender to palpation, and painful or abnormal supination. The model showed an area under the receiver operator characteristics curve of 0.79 (95% CI: 0.76-0.83). The sensitivity and specificity were 95.9% and 37.3%, respectively. The use of this model would have resulted in a 22% absolute reduction of radiographic examinations. In a validation study, 7/170 fractures (4.1%, 95% CI: 1.7-8.3%) would have been missed using the decision model. The decision model may be a valuable tool to decide whether radiography in children after wrist trauma is required. (orig.)

  20. A clinical decision rule for the use of plain radiography in children after acute wrist injury: development and external validation of the Amsterdam Pediatric Wrist Rules

    Energy Technology Data Exchange (ETDEWEB)

    Slaar, Annelie; Maas, Mario; Rijn, Rick R. van [University of Amsterdam, Department of Radiology, Academic Medical Centre, Meibergdreef 9, 1105, AZ, Amsterdam (Netherlands); Walenkamp, Monique M.J.; Bentohami, Abdelali; Goslings, J.C. [University of Amsterdam, Trauma Unit, Department of Surgery, Academic Medical Centre, Amsterdam (Netherlands); Steyerberg, Ewout W. [Erasmus MC - University Medical Centre, Department of Public Health, Rotterdam (Netherlands); Jager, L.C. [University of Amsterdam, Emergency Department, Academic Medical Centre, Amsterdam (Netherlands); Sosef, Nico L. [Spaarne Hospital, Department of Surgery, Hoofddorp (Netherlands); Velde, Romuald van [Tergooi Hospitals, Department of Surgery, Hilversum (Netherlands); Ultee, Jan M. [Sint Lucas Andreas Hospital, Department of Surgery, Amsterdam (Netherlands); Schep, Niels W.L. [University of Amsterdam, Trauma Unit, Department of Surgery, Academic Medical Centre, Amsterdam (Netherlands); Maasstadziekenhuis Rotterdam, Department of Surgery, Rotterdam (Netherlands)

    2016-01-15

    In most hospitals, children with acute wrist trauma are routinely referred for radiography. To develop and validate a clinical decision rule to decide whether radiography in children with wrist trauma is required. We prospectively developed and validated a clinical decision rule in two study populations. All children who presented in the emergency department of four hospitals with pain following wrist trauma were included and evaluated for 18 clinical variables. The outcome was a wrist fracture diagnosed by plain radiography. Included in the study were 787 children. The prediction model consisted of six variables: age, swelling of the distal radius, visible deformation, distal radius tender to palpation, anatomical snuffbox tender to palpation, and painful or abnormal supination. The model showed an area under the receiver operator characteristics curve of 0.79 (95% CI: 0.76-0.83). The sensitivity and specificity were 95.9% and 37.3%, respectively. The use of this model would have resulted in a 22% absolute reduction of radiographic examinations. In a validation study, 7/170 fractures (4.1%, 95% CI: 1.7-8.3%) would have been missed using the decision model. The decision model may be a valuable tool to decide whether radiography in children after wrist trauma is required. (orig.)

  1. A SYSTEM OF SERIAL COMPUTATION FOR CLASSIFIED RULES PREDICTION IN NONREGULAR ONTOLOGY TREES

    Directory of Open Access Journals (Sweden)

    Kennedy E. Ehimwenma

    2016-03-01

    Full Text Available Objects or structures that are regular take uniform dimensions. Based on the concepts of regular models, our previous research work has developed a system of a regular ontology that models learning structures in a multiagent system for uniform pre-assessments in a learning environment. This regular ontology has led to the modelling of a classified rules learning algorithm that predicts the actual number of rules needed for inductive learning processes and decision making in a multiagent system. But not all processes or models are regular. Thus this paper presents a system of polynomial equation that can estimate and predict the required number of rules of a non-regular ontology model given some defined parameters.

  2. Behavioral rules of bank’s point-of-sale for segments description and scoring prediction

    Directory of Open Access Journals (Sweden)

    Mehdi Bizhani

    2011-04-01

    Full Text Available One of the important factors for the success of a bank industry is to monitor their customers' behavior and their point-of-sale (POS. The bank needs to know its merchants' behavior to find interesting ones to attract more transactions which results in the growth of its income and assets. The recency, frequency and monetary (RFM analysis is a famous approach for extracting behavior of customers and is a basis for marketing and customer relationship management (CRM, but it is not aligned enough for banking context. Introducing RF*M* in this article results in a better understanding of groups of merchants. Another artifact of RF*M* is RF*M* scoring which is applied in two ways, preprocessing the POSs and assigning behavioral meaningful labels to the merchants’ segments. The class labels and the RF*M* parameters are entered into a rule-based classification algorithm to achieve descriptive rules of the clusters. These descriptive rules outlined the boundaries of RF*M* parameters for each cluster. Since the rules are generated by a classification algorithm, they can also be applied for predicting the behavioral label and scoring of the upcoming POSs. These rules are called behavioral rules.

  3. Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules.

    Science.gov (United States)

    Lezcano, Leonardo; Sicilia, Miguel-Angel; Rodríguez-Solano, Carlos

    2011-04-01

    Semantic interoperability is essential to facilitate the computerized support for alerts, workflow management and evidence-based healthcare across heterogeneous electronic health record (EHR) systems. Clinical archetypes, which are formal definitions of specific clinical concepts defined as specializations of a generic reference (information) model, provide a mechanism to express data structures in a shared and interoperable way. However, currently available archetype languages do not provide direct support for mapping to formal ontologies and then exploiting reasoning on clinical knowledge, which are key ingredients of full semantic interoperability, as stated in the SemanticHEALTH report [1]. This paper reports on an approach to translate definitions expressed in the openEHR Archetype Definition Language (ADL) to a formal representation expressed using the Ontology Web Language (OWL). The formal representations are then integrated with rules expressed with Semantic Web Rule Language (SWRL) expressions, providing an approach to apply the SWRL rules to concrete instances of clinical data. Sharing the knowledge expressed in the form of rules is consistent with the philosophy of open sharing, encouraged by archetypes. Our approach also allows the reuse of formal knowledge, expressed through ontologies, and extends reuse to propositions of declarative knowledge, such as those encoded in clinical guidelines. This paper describes the ADL-to-OWL translation approach, describes the techniques to map archetypes to formal ontologies, and demonstrates how rules can be applied to the resulting representation. We provide examples taken from a patient safety alerting system to illustrate our approach. PMID:21118725

  4. Analysis and prediction of fatigue-ratcheting: Comparison with tests and code rules

    International Nuclear Information System (INIS)

    Piping response evaluations for dynamic loads that produce high stress intensities require careful consideration of ratcheting and fatigue. Recent experimental observations have shown piping code rules to have areas of large conservatism, which has resulted in proposals for rule changes. This paper offers an evaluation of these changes by means of detailed, inelastic, finite element analyses of an elbow-pipe assembly. Various load combinations investigated in this work consist of a steady bending due to weight, internal pressure, and cyclic inertial load, applied statically in the analyses. Important structural and material response characteristics are determined analytically and compared with recent test results. The observations and analytical predictions support the new code rule changes which increase the allowable stress limits for reversed dynamic loads. The analytical tool offers a means for quantitative assessment of related safety margins, and fatigue and ratcheting behavior of engineering components; some useful results for a piping elbow are derived

  5. Fuzzy C-means Rule Generation for Fuzzy Entry Temperature Prediction in a Hot Strip Mill

    Institute of Scientific and Technical Information of China (English)

    JosAngel BARRIOS; Csar VILLANUEVA; Alberto CAVAZOS; Rafael COLS

    2016-01-01

    Variable estimation for finishing mill set-up in hot rolling is greatly affected by measurement uncertainties, variations in the incoming bar conditions and product changes.The fuzzy C-means algorithm was evaluated for rule-base generation for fuzzy and fuzzy grey-box temperature estimation.Experimental data were collected from a real-life mill and three different sets were randomly drawn.The first set was used for rule-generation,the second set was used for training those systems with learning capabilities,while the third one was used for validation.The perform-ance of the developed systems was evaluated by five performance measures applied over the prediction error with the validation set and was compared with that of the empirical rule-base fuzzy systems and the physical model used in plant.The results show that the fuzzy C-means generated rule-bases improve temperature estimation;however,the best results are obtained when fuzzy C-means algorithm,grey-box modeling and learning functions are combined. Application of fuzzy C-means rule generation brings improvement on performance of up to 72%.

  6. Use of Feedback in Clinical Prediction

    Science.gov (United States)

    Schroeder, Harold E.

    1972-01-01

    Results indicated that predictive accuracy is greater when feedback is applied to the basis for the prediction than when applied to gut" impressions. Judges forming hypotheses were also able to learn from experience. (Author)

  7. Simplified sonic-boom prediction. [using aerodynamic configuration charts and calculators or slide rules

    Science.gov (United States)

    Carlson, H. W.

    1978-01-01

    Sonic boom overpressures and signature duration may be predicted for the entire affected ground area for a wide variety of supersonic airplane configurations and spacecraft operating at altitudes up to 76 km in level flight or in moderate climbing or descending flight paths. The outlined procedure relies to a great extent on the use of charts to provide generation and propagation factors for use in relatively simple expressions for signature calculation. Computational requirements can be met by hand-held scientific calculators, or even by slide rules. A variety of correlations of predicted and measured sonic-boom data for airplanes and spacecraft serve to demonstrate the applicability of the simplified method.

  8. A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm

    CERN Document Server

    Martin, A; Venkatesan, Dr V Prasanna

    2011-01-01

    Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.

  9. A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm

    Directory of Open Access Journals (Sweden)

    A Martin

    2011-05-01

    Full Text Available Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Z-score model a new business intelligence model is developed to predict the bankruptcy.

  10. Rule monitoring ability predicts event-based prospective memory performance in individuals with TBI.

    Science.gov (United States)

    Paxton, Jessica; Chiaravalloti, Nancy

    2014-08-01

    Numerous studies have demonstrated that prospective memory (PM) abilities are impaired following traumatic brain injury (TBI). PM refers to the ability to remember to complete a planned action following a delay. PM post-TBI has been shown to be related to performance on neuropsychological tests of executive functioning and retrospective episodic memory (RM). However, the relative influence of impairments in RM versus executive functioning on PM performance post-TBI remains uninvestigated. In the current study, PM and neuropsychological test performance were examined in 45 persons with a history of moderate to severe TBI at least 1 year before enrollment. Regression analyses examined the relative contributions of RM and executive functioning in the prediction of PM performance on the Rivermead Behavioral Memory Test (RBMT). Results indicated that scores on tests of delayed RM and rule monitoring (i.e., ability to avoid making errors on executive measures) were the strongest predictors of PM. When the interaction between RM impairment and rule monitoring was examined, a positive relationship between PM and rule monitoring was found only in TBI participants with impaired RM. Results suggest that PM performance is dependent upon rule monitoring abilities only when RM is impaired following TBI. PMID:25068409

  11. Clinical Value of the Ottawa Ankle Rules for Diagnosis of Fractures in Acute Ankle Injuries

    OpenAIRE

    Xin Wang; Shi-min Chang; Guang-rong Yu; Zhi-tao Rao

    2013-01-01

    BACKGROUND: The Ottawa ankle rules (OAR) are clinical decision guidelines used to identify whether patients with ankle injuries need to undergo radiography. The OAR have been proven that their application reduces unnecessary radiography. They have nearly perfect sensitivity for identifying clinically significant ankle fractures. OBJECTIVES: The purpose of this study was to assess the applicability of the OAR in China, to examine their accuracy for the diagnosis of fractures in patients with a...

  12. A patient with a large pulmonary saddle embolus eluding both clinical gestalt and validated decision rules.

    Science.gov (United States)

    Hennessey, Adam; Setyono, Devy A; Lau, Wayne Bond; Fields, Jason Matthew

    2012-06-01

    We report a patient with chest pain who was classified as having low risk for pulmonary embolism with clinical gestalt and accepted clinical decision rules. An inadvertently ordered D-dimer and abnormal result, however, led to the identification of a large saddle embolus. This case illustrates the fallibility of even well-validated decision aids and that an embolism missed by these tools is not necessarily low risk or indicative of a low clot burden.

  13. The efficiency of the RULES-4 classification learning algorithm in predicting the density of agents

    Directory of Open Access Journals (Sweden)

    Ziad Salem

    2014-12-01

    Full Text Available Learning is the act of obtaining new or modifying existing knowledge, behaviours, skills or preferences. The ability to learn is found in humans, other organisms and some machines. Learning is always based on some sort of observations or data such as examples, direct experience or instruction. This paper presents a classification algorithm to learn the density of agents in an arena based on the measurements of six proximity sensors of a combined actuator sensor units (CASUs. Rules are presented that were induced by the learning algorithm that was trained with data-sets based on the CASU’s sensor data streams collected during a number of experiments with “Bristlebots (agents in the arena (environment”. It was found that a set of rules generated by the learning algorithm is able to predict the number of bristlebots in the arena based on the CASU’s sensor readings with satisfying accuracy.

  14. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    Science.gov (United States)

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. PMID:27089522

  15. Inter-transactional association rules for multi-dimensional contexts for prediction and their application to studying meteorological data

    NARCIS (Netherlands)

    Feng, Ling; Dillon, Tharam; Liu, James; Chen, P.P.

    2001-01-01

    Inter-transactional association rules, first presented in our early work [H. Lu, J. Han, L. Feng, Stock movement prediction and n-dimensional inter-transaction association rules, in: Proceedings of the ACM SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, Seattle, Washington

  16. Identifying influenza-like illness presentation from unstructured general practice clinical narrative using a text classifier rule-based expert system versus a clinical expert

    OpenAIRE

    MacRae, Jayden; Love, Tom; Michael G Baker; Dowell, Anthony; Carnachan, Matthew; Stubbe, Maria; McBain, Lynn

    2015-01-01

    Background We designed and validated a rule-based expert system to identify influenza like illness (ILI) from routinely recorded general practice clinical narrative to aid a larger retrospective research study into the impact of the 2009 influenza pandemic in New Zealand. Methods Rules were assessed using pattern matching heuristics on routine clinical narrative. The system was trained using data from 623 clinical encounters and validated using a clinical expert as a gold standard against a m...

  17. Pharmacogenetics : the science of predictive clinical pharmacology

    OpenAIRE

    Fenech, Anthony G; Grech, Godfrey

    2014-01-01

    The study of pharmacogenetics has expanded from what were initially casual family-based clinical drug response observations, to a fully-fledged science with direct therapeutic applications, all within a time-span of less than 60 years. A wide spectrum of polymorphisms, located within several genes, are now recognised to influence the pharmacokinetics and pharmacodynamics of the majority of drugs within our therapeutic armamentarium. This information forms the basis for the new development of ...

  18. Prediction of high-grade vesicoureteral reflux after pediatric urinary tract infection: external validation study of procalcitonin-based decision rule.

    Directory of Open Access Journals (Sweden)

    Sandrine Leroy

    Full Text Available BACKGROUND: Predicting vesico-ureteral reflux (VUR ≥3 at the time of the first urinary tract infection (UTI would make it possible to restrict cystography to high-risk children. We previously derived the following clinical decision rule for that purpose: cystography should be performed in cases with ureteral dilation and a serum procalcitonin level ≥0.17 ng/mL, or without ureteral dilatation when the serum procalcitonin level ≥0.63 ng/mL. The rule yielded a 86% sensitivity with a 46% specificity. We aimed to test its reproducibility. STUDY DESIGN: A secondary analysis of prospective series of children with a first UTI. The rule was applied, and predictive ability was calculated. RESULTS: The study included 413 patients (157 boys, VUR ≥3 in 11% from eight centers in five countries. The rule offered a 46% specificity (95% CI, 41-52, not different from the one in the derivation study. However, the sensitivity significantly decreased to 64% (95%CI, 50-76, leading to a difference of 20% (95%CI, 17-36. In all, 16 (34% patients among the 47 with VUR ≥3 were misdiagnosed by the rule. This lack of reproducibility might result primarily from a difference between derivation and validation populations regarding inflammatory parameters (CRP, PCT; the validation set samples may have been collected earlier than for the derivation one. CONCLUSIONS: The rule built to predict VUR ≥3 had a stable specificity (ie. 46%, but a decreased sensitivity (ie. 64% because of the time variability of PCT measurement. Some refinement may be warranted.

  19. Reporting and Methods in Clinical Prediction Research: A Systematic Review

    OpenAIRE

    Bouwmeester, W; Zuithoff, NP; Mallett, S.; Geerlings, MI; Vergouwe, Y.; Steyerberg, EW; Altman, DG; Moons, KG

    2012-01-01

    Editors' Summary Background There are often times in our lives when we would like to be able to predict the future. Is the stock market going to go up, for example, or will it rain tomorrow? Being able predict future health is also important, both to patients and to physicians, and there is an increasing body of published clinicalprediction research.” Diagnostic prediction research investigates the ability of variables or test results to predict the presence or absence of a specific diagnos...

  20. Predictive data mining in clinical medicine: Current issues and guidelines

    OpenAIRE

    Bellazzi, Riccado; Zupan, Blaz

    2008-01-01

    BACKGROUND: The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as 'data mining' offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. A large variety of these met...

  1. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  2. Prediction of Metabolic Pathway Involvement in Prokaryotic UniProtKB Data by Association Rule Mining

    KAUST Repository

    Boudellioua, Imane

    2016-07-08

    The widening gap between known proteins and their functions has encouraged the development of methods to automatically infer annotations. Automatic functional annotation of proteins is expected to meet the conflicting requirements of maximizing annotation coverage, while minimizing erroneous functional assignments. This trade-off imposes a great challenge in designing intelligent systems to tackle the problem of automatic protein annotation. In this work, we present a system that utilizes rule mining techniques to predict metabolic pathways in prokaryotes. The resulting knowledge represents predictive models that assign pathway involvement to UniProtKB entries. We carried out an evaluation study of our system performance using cross-validation technique. We found that it achieved very promising results in pathway identification with an F1-measure of 0.982 and an AUC of 0.987. Our prediction models were then successfully applied to 6.2 million UniProtKB/TrEMBL reference proteome entries of prokaryotes. As a result, 663,724 entries were covered, where 436,510 of them lacked any previous pathway annotations.

  3. Creating a prediction model for weather forecasting based on artificial neural network supported by association rules mining

    OpenAIRE

    Kadlec, Jakub

    2016-01-01

    This diploma thesis focuses on creating a predictive model for the purpose of automated weather predictions based on a neural network. Attributes for input layer of the network are selected through association rules mining using the 4ft-Miner procedure. First part of the thesis consists of collection of theoretical knowledge enabling the creation of such predictive model, whereas the second part describes the creation of the model itself using the CRISP-DM methodology. Final part of the thesi...

  4. A clinical decision rule for the use of plain radiography in children after acute wrist injury: development and external validation of the Amsterdam Pediatric Wrist Rules

    NARCIS (Netherlands)

    A. Slaar (Annelie); M.M.J. Walenkamp (Monique); A. Bentohami (Abdelali); M. Maas (Mario); R.R. van Rijn (Rick); E.W. Steyerberg (Ewout); L.C. Jager (L. Cara); N.L. Sosef (Nico L.); R. van Velde (Romuald); J.M. Ultee (Jan); J.C. Goslings (Carel); N.W.L. Schep (Niels)

    2016-01-01

    textabstractBackground: In most hospitals, children with acute wrist trauma are routinely referred for radiography. Objective: To develop and validate a clinical decision rule to decide whether radiography in children with wrist trauma is required. Materials and methods: We prospectively developed a

  5. Clinical prediction of occupational and non-specific low back pain

    Directory of Open Access Journals (Sweden)

    Ingrid Tolosa-Guzmán

    2012-09-01

    Full Text Available Non-specific Occupational Low Back Pain (NOLBP is a health condition that generates a high absenteeism and disability. Due to multifactorial causes is difficult to determine accurate diagnosis and prognosis. The clinical prediction of NOLBP is identified as a series of models that integrate a multivariate analysis to determine early diagnosis, course, and occupational impact of this health condition. Objective: to identify predictor factors of NOLBP, and the type of material referred to in the scientific evidence and establish the scopes of the prediction. Materials and method: the title search was conducted in the databases PubMed, Science Direct, and Ebsco Springer, between 1985 and 2012. The selected articles were classified through a bibliometric analysis allowing to define the most relevant ones. Results: 101 titles met the established criteria, but only 43 met the purpose of the review. As for NOLBP prediction, the studies varied in relation to the factors for example: diagnosis, transition of lumbar pain from acute to chronic, absenteeism from work, disability and return to work. Conclusion: clinical prediction is considered as a strategic to determine course and prognostic of NOLBP, and to determine the characteristics that increase the risk of chronicity in workers with this health condition. Likewise, clinical prediction rules are tools that aim to facilitate decision making about the evaluation, diagnosis, prognosis and intervention for low back pain, which should incorporate risk factors of physical, psychological and social.

  6. Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials

    Science.gov (United States)

    Tétreault, Pascal; Mansour, Ali; Vachon-Presseau, Etienne; Schnitzer, Thomas J.; Apkarian, A. Vania

    2016-01-01

    Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo’s effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active

  7. SAE: an R package for early stopping rules in clinical trials.

    Science.gov (United States)

    Bascoul-Mollevi, C; Laplanche, A; Le Deley, M C; Kramar, A

    2011-11-01

    In the case of an unexpected high frequency of serious adverse events (SAE), statistical methods are needed to help in the decision making process as to continuation of accrual to the trial. This paper describes an R package, named SAE that implements a method recently developed by defining stopping rules after each observed SAE. The package function control for excessive toxicity either during the trial at the observation of each SAE (function SAE) or during the planning phase of a clinical trial (function DESIGN). This description and the package documentation are complementary to help the users to apply the method. The main difficulty in the implementation of the method is the choice of a priori parameters. Data from an ongoing clinical trial are presented as an example to improve the understanding and the use of the package.

  8. On-time clinical phenotype prediction based on narrative reports

    Science.gov (United States)

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  9. Evaluation of Clinical Decision Rules for Bone Mineral Density Testing among White Women

    Directory of Open Access Journals (Sweden)

    Michael E. Anders

    2013-01-01

    Full Text Available Background. Osteoporosis is a devastating, insidious disease that causes skeletal fragility. Half of women will suffer osteoporotic fractures during their lifetimes. Many fractures occur needlessly, because of inattentiveness to assessment, diagnosis, prevention, and treatment of osteoporosis. Study Purpose. Study Purpose. To evaluate the discriminatory performance of clinical decision rules to determine the need to undergo bone mineral density testing. Methods. A nationally representative sample from the Third National Health and Nutrition Examination Survey consisted of 14,060 subjects who completed surveys, physical examinations, laboratory tests, and bone mineral density exams. Multivariable linear regression tested the correlation of covariates that composed the clinical decision rules with bone mineral density. Results. Increased age and decreased weight were variables in the final regression models for each gender and race/ethnicity. Among the indices, the Osteoporosis Self-Assessment Tool, which is composed of age and weight, performed best for White women. Study Implications. These results have implications for the prevention, assessment, diagnosis, and treatment of osteoporosis. The Osteoporosis Self-Assessment Tool performed best and is inexpensive and the least time consuming to implement.

  10. Knowledge discovery and sequence-based prediction of pandemic influenza using an integrated classification and association rule mining (CBA) algorithm.

    Science.gov (United States)

    Kargarfard, Fatemeh; Sami, Ashkan; Ebrahimie, Esmaeil

    2015-10-01

    Pandemic influenza is a major concern worldwide. Availability of advanced technologies and the nucleotide sequences of a large number of pandemic and non-pandemic influenza viruses in 2009 provide a great opportunity to investigate the underlying rules of pandemic induction through data mining tools. Here, for the first time, an integrated classification and association rule mining algorithm (CBA) was used to discover the rules underpinning alteration of non-pandemic sequences to pandemic ones. We hypothesized that the extracted rules can lead to the development of an efficient expert system for prediction of influenza pandemics. To this end, we used a large dataset containing 5373 HA (hemagglutinin) segments of the 2009 H1N1 pandemic and non-pandemic influenza sequences. The analysis was carried out for both nucleotide and protein sequences. We found a number of new rules which potentially present the undiscovered antigenic sites at influenza structure. At the nucleotide level, alteration of thymine (T) at position 260 was the key discriminating feature in distinguishing non-pandemic from pandemic sequences. At the protein level, rules including I233K, M334L were the differentiating features. CBA efficiently classifies pandemic and non-pandemic sequences with high accuracy at both the nucleotide and protein level. Finding hotspots in influenza sequences is a significant finding as they represent the regions with low antibody reactivity. We argue that the virus breaks host immunity response by mutation at these spots. Based on the discovered rules, we developed the software, "Prediction of Pandemic Influenza" for discrimination of pandemic from non-pandemic sequences. This study opens a new vista in discovery of association rules between mutation points during evolution of pandemic influenza.

  11. Prediction of Early Recurrence of Liver Cancer by a Novel Discrete Bayes Decision Rule for Personalized Medicine

    Science.gov (United States)

    Ogihara, Hiroyuki

    2016-01-01

    We discuss a novel diagnostic method for predicting the early recurrence of liver cancer with high accuracy for personalized medicine. The difficulty with cancer treatment is that even if the types of cancer are the same, the cancers vary depending on the patient. Thus, remarkable attention has been paid to personalized medicine. Unfortunately, although the Tokyo Score, the Modified JIS, and the TNM classification have been proposed as liver scoring systems, none of these scoring systems have met the needs of clinical practice. In this paper, we convert continuous and discrete data to categorical data and keep the natively categorical data as is. Then, we propose a discrete Bayes decision rule that can deal with the categorical data. This may lead to its use with various types of laboratory data. Experimental results show that the proposed method produced a sensitivity of 0.86 and a specificity of 0.49 for the test samples. This suggests that our method may be superior to the well-known Tokyo Score, the Modified JIS, and the TNM classification in terms of sensitivity. Additional comparative study shows that if the numbers of test samples in two classes are the same, this method works well in terms of the F1 measure compared to the existing scoring methods. PMID:27800494

  12. Predicting postoperative mortality after colorectal surgery : a novel clinical model

    NARCIS (Netherlands)

    van der Sluis, F. J.; Espin, E.; Vallribera, F.; de Bock, G. H.; Hoekstra, H. J.; van Leeuwen, B. L.; Engel, A. F.

    2014-01-01

    Aim The aim of this study was to develop and externally validate a clinically, practical and discriminative prediction model designed to estimate in-hospital mortality of patients undergoing colorectal surgery. Method All consecutive patients who underwent elective or emergency colorectal surgery fr

  13. Computational prediction of formulation strategies for beyond-rule-of-5 compounds.

    Science.gov (United States)

    Bergström, Christel A S; Charman, William N; Porter, Christopher J H

    2016-06-01

    The physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets

  14. Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

    Science.gov (United States)

    Park, J.; Yoo, K.

    2013-12-01

    For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

  15. Using local lexicalized rules to identify heart disease risk factors in clinical notes.

    Science.gov (United States)

    Karystianis, George; Dehghan, Azad; Kovacevic, Aleksandar; Keane, John A; Nenadic, Goran

    2015-12-01

    Heart disease is the leading cause of death globally and a significant part of the human population lives with it. A number of risk factors have been recognized as contributing to the disease, including obesity, coronary artery disease (CAD), hypertension, hyperlipidemia, diabetes, smoking, and family history of premature CAD. This paper describes and evaluates a methodology to extract mentions of such risk factors from diabetic clinical notes, which was a task of the i2b2/UTHealth 2014 Challenge in Natural Language Processing for Clinical Data. The methodology is knowledge-driven and the system implements local lexicalized rules (based on syntactical patterns observed in notes) combined with manually constructed dictionaries that characterize the domain. A part of the task was also to detect the time interval in which the risk factors were present in a patient. The system was applied to an evaluation set of 514 unseen notes and achieved a micro-average F-score of 88% (with 86% precision and 90% recall). While the identification of CAD family history, medication and some of the related disease factors (e.g. hypertension, diabetes, hyperlipidemia) showed quite good results, the identification of CAD-specific indicators proved to be more challenging (F-score of 74%). Overall, the results are encouraging and suggested that automated text mining methods can be used to process clinical notes to identify risk factors and monitor progression of heart disease on a large-scale, providing necessary data for clinical and epidemiological studies. PMID:26133479

  16. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    Directory of Open Access Journals (Sweden)

    Hurwitz Eric L

    2008-08-01

    Full Text Available Abstract Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source and 3 (which investigates perpetuating factors of the pain experience. In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed.

  17. Common clinical practice versus new PRIM score in predicting coronary heart disease risk

    DEFF Research Database (Denmark)

    Frikke-Schmidt, Ruth; Tybjærg-Hansen, Anne; Schnohr, Peter;

    2010-01-01

    To compare the new Patient Rule Induction Method (PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease (CHD) risk.......To compare the new Patient Rule Induction Method (PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease (CHD) risk....

  18. Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset.

    Science.gov (United States)

    Zhang, Haitao; Chen, Zewei; Liu, Zhao; Zhu, Yunhong; Wu, Chenxue

    2016-01-01

    Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users' privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502

  19. Cytokines and signaling molecules predict clinical outcomes in sepsis.

    Directory of Open Access Journals (Sweden)

    Christopher D Fjell

    Full Text Available INTRODUCTION: Inflammatory response during sepsis is incompletely understood due to small sample sizes and variable timing of measurements following the onset of symptoms. The vasopressin in septic shock trial (VASST compared the addition of vasopressin to norepinephrine alone in patients with septic shock. During this study plasma was collected and 39 cytokines measured in a 363 patients at both baseline (before treatment and 24 hours. Clinical features relating to both underlying health and the acute organ dysfunction induced by the severe infection were collected during the first 28 days of admission. HYPOTHESIS: Cluster analysis of cytokines identifies subgroups of patients at differing risk of death and organ failure. METHODS: Circulating cytokines and other signaling molecules were measured using a Luminex multi-bead analyte detection system. Hierarchical clustering was performed on plasma values to create patient subgroups. Enrichment analysis identified clinical outcomes significantly different according to these chemically defined patient subgroups. Logistic regression was performed to assess the importance of cytokines for predicting patient subgroups. RESULTS: Plasma levels at baseline produced three subgroups of patients, while 24 hour levels produced two subgroups. Using baseline cytokine data, one subgroup of 47 patients showed a high level of enrichment for severe septic shock, coagulopathy, renal failure, and risk of death. Using data at 24 hours, a larger subgroup of 81 patients that largely encompassed the 47 baseline subgroup patients had a similar enrichment profile. Measurement of two cytokines, IL2 and CSF2 and their product were sufficient to classify patients into these subgroups that defined clinical risks. CONCLUSIONS: A distinct pattern of cytokine levels measured early in the course of sepsis predicts disease outcome. Subpopulations of patients have differing clinical outcomes that can be predicted accurately from

  20. A Modified Mixing Rule for PSRK Model and Application for the Prediction of Vapor-Liquid Equilibria of Polymer Solutions

    Institute of Scientific and Technical Information of China (English)

    李敏; 王利生; J.Gmehling

    2004-01-01

    To extend the PSRK (predictive Soave-Redlich-Kwong equation of state) model to vapor-liquid equilibria of polymer solutions, a new EOS-gE mixing rule is applied in which the term ∑xiln(b/bi) in the PSRK mixing rule for the parameter a, and the combinatorial part in the original universal functional activity coefficient (UNIFAC) model are cancelled. To take into account the free volume contribution to the excess Gibbs energy in polymer solution, a quadratic mixing rule for the cross co-volume bij with an exponent equals to 1/2 is applied [bij1/2=1/2(bi1/2+bj1/2)]. The literature reported Soave-Redlich-Kwong equation of state (SRK EOS) parameters of i3 - 2- pure polymer are employed. The PSRK model with the modified mixing rule is used to predict the vapor-liquid equilibrium (VLE) of 37 solvent-polymer systems over a large range of temperature and pressure with satisfactory results.

  1. Rule pruning and prediction methods for associative classification approach in data mining

    OpenAIRE

    Abu Mansour, Hussein Y

    2012-01-01

    Recent studies in data mining revealed that Associative Classification (AC) data mining approach builds competitive classification classifiers with reference to accuracy when compared to classic classification approaches including decision tree and rule based. Nevertheless, AC algorithms suffer from a number of known defects as the generation of large number of rules which makes it hard for end-user to maintain and understand its outcome and the possible over-fitting issue caused by the confi...

  2. Post-error slowing predicts rule-based but not information-integration category learning

    OpenAIRE

    Tam, Helen; Maddox, W. Todd; Huang-Pollock, Cynthia L.

    2013-01-01

    We examine whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e, post-error slowing), is differentially important in the learning of rule-based vs. information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g. sort by color). In contrast, information-integration categories are believed to be learned in a trial-by-trial associative manne...

  3. Host genetics predict clinical deterioration in HCV-related cirrhosis.

    Directory of Open Access Journals (Sweden)

    Lindsay Y King

    Full Text Available Single nucleotide polymorphisms (SNPs in the epidermal growth factor (EGF, rs4444903, patatin-like phospholipase domain-containing protein 3 (PNPLA3, rs738409 genes, and near the interleukin-28B (IL28B, rs12979860 gene are linked to treatment response, fibrosis, and hepatocellular carcinoma (HCC in chronic hepatitis C. Whether these SNPs independently or in combination predict clinical deterioration in hepatitis C virus (HCV-related cirrhosis is unknown. We genotyped SNPs in EGF, PNPLA3, and IL28B from liver tissue from 169 patients with biopsy-proven HCV cirrhosis. We estimated risk of clinical deterioration, defined as development of ascites, encephalopathy, variceal hemorrhage, HCC, or liver-related death using Cox proportional hazards modeling. During a median follow-up of 6.6 years, 66 of 169 patients experienced clinical deterioration. EGF non-AA, PNPLA3 non-CC, and IL28B non-CC genotypes were each associated with increased risk of clinical deterioration in age, sex, and race-adjusted analysis. Only EGF non-AA genotype was independently associated with increased risk of clinical deterioration (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.31-6.25 after additionally adjusting for bilirubin, albumin, and platelets. Compared to subjects who had 0-1 unfavorable genotypes, the HR for clinical deterioration was 1.79 (95%CI 0.96-3.35 for 2 unfavorable genotypes and 4.03 (95%CI 2.13-7.62 for unfavorable genotypes for all three loci (Ptrend<0.0001. In conclusion, among HCV cirrhotics, EGF non-AA genotype is independently associated with increased risk for clinical deterioration. Specific PNPLA3 and IL28B genotypes also appear to be associated with clinical deterioration. These SNPs have potential to identify patients with HCV-related cirrhosis who require more intensive monitoring for decompensation or future therapies preventing disease progression.

  4. A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis

    Science.gov (United States)

    Osório, Nuno S.; Castro, António Gil; Ramos, Angélica; Carvalho, Teresa; Meira, Leonor; Araújo, David; Almeida, Leonor; Boaventura, Rita; Fragata, Patrícia; Chaves, Catarina; Costa, Patrício; Portela, Miguel; Ferreira, Ivo; Magalhães, Sara Pinto; Rodrigues, Fernando; Sarmento-Castro, Rui; Duarte, Raquel; Guimarães, João Tiago; Saraiva, Margarida

    2016-01-01

    Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8–7.9), age ≥50 years (OR 2.9, 95% CI 1.7–4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4–4.4), ≥1 significant comorbidity—HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease–(OR 2.3, 95% CI 1.3–3.8), and hemoglobin <12 g/dL (OR 1.8, 95% CI 1.1–3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score ≤2), moderate (score 3–5) and high (score ≥6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment. PMID:27636095

  5. Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences

    Directory of Open Access Journals (Sweden)

    Benjamin W. Y. Lo

    2013-01-01

    Full Text Available Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH. Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients. Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs. Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique denoted cut-off points for poor prognosis at greater than 2.5 clusters. Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication.

  6. Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

    OpenAIRE

    Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

    2014-01-01

    Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowle...

  7. Predictable Outcomes with Porcelain Laminate Veneers: A Clinical Report.

    Science.gov (United States)

    Pimentel, Welson; Teixeira, Marcelo Lucchesi; Costa, Priscila Paganini; Jorge, Mônica Zacharias; Tiossi, Rodrigo

    2016-06-01

    This clinical report describes how to achieve predictable outcomes for anterior teeth esthetic restorations with porcelain laminate veneers by associating the digital planning and design of the restoration with interim restorations. The previous digital smile design of the restoration eliminates the communication barrier with the patient and assists the clinician throughout patient treatment. Interim restorations (diagnostic mock-ups) further enhance communication with the patient and prevent unnecessary tooth reduction for conservative tooth preparation. Adequate communication between patient and clinician contributes to successful definitive restorations and patient satisfaction with the final esthetic outcome.

  8. An improved predictive association rule based classifier using gain ratio and T-test for health care data diagnosis

    Indian Academy of Sciences (India)

    M Nandhini; S N Sivanandam

    2015-09-01

    Health care data diagnosis is a significant task that needs to be executed precisely, which requires much experience and domain-knowledge. Traditional symptoms-based disease diagnosis may perhaps lead to false presumptions. In recent times, Associative Classification (AC), the combination of association rule mining and classification has received attention in health care applications which desires maximum accuracy. Though several AC techniques exist, they lack in generating quality rules for building efficient associative classifier. This paper aims to enhance the accuracy of the existing CPAR (Classification based on Predictive Association Rule) algorithm by generating quality rules using Gain Ratio. Mostly, health care applications deal with high dimensional datasets. Existence of high dimensions causes unfair estimates in disease diagnosis. Dimensionality reduction is commonly applied as a preprocessing step before classification task to improve classifier accuracy. It eliminates redundant and insignificant dimensions by keeping good ones without information loss. In this work, dimensionality reductions by T-test and reduct sets (or simply reducts) are performed as preprocessing step before CPAR and CPAR using Gain Ratio (CPAR-GR) algorithms. An investigation was also performed to determine the impact of T-test and reducts on CPAR and CPAR-GR. This paper synthesizes the existing work carried out in AC, and also discusses the factors that influence the performance of CPAR and CPAR-GR. Experiments were conducted using six health care datasets from UCI machine learning repository. Based on the experiments, CPAR-GR with T-test yields better classification accuracy than CPAR.

  9. How the brain predicts people's behavior in relation to rules and desires. Evidence of a medio-prefrontal dissociation.

    Science.gov (United States)

    Corradi-Dell'Acqua, Corrado; Turri, Francesco; Kaufmann, Laurence; Clément, Fabrice; Schwartz, Sophie

    2015-09-01

    Forming and updating impressions about others is critical in everyday life and engages portions of the dorsomedial prefrontal cortex (dMPFC), the posterior cingulate cortex (PCC) and the amygdala. Some of these activations are attributed to "mentalizing" functions necessary to represent people's mental states, such as beliefs or desires. Evolutionary psychology and developmental studies, however, suggest that interpersonal inferences can also be obtained through the aid of deontic heuristics, which dictate what must (or must not) be done in given circumstances. We used fMRI and asked 18 participants to predict whether unknown characters would follow their desires or obey external rules. Participants had no means, at the beginning, to make accurate predictions, but slowly learned (throughout the experiment) each character's behavioral profile. We isolated brain regions whose activity changed during the experiment, as a neural signature of impression updating: whereas dMPFC was progressively more involved in predicting characters' behavior in relation to their desires, the medial orbitofrontal cortex and the amygdala were progressively more recruited in predicting rule-based behavior. Our data provide evidence of a neural dissociation between deontic inference and theory-of-mind (ToM), and support a differentiation of orbital and dorsal prefrontal cortex in terms of low- and high-level social cognition.

  10. How the brain predicts people's behavior in relation to rules and desires. Evidence of a medio-prefrontal dissociation.

    Science.gov (United States)

    Corradi-Dell'Acqua, Corrado; Turri, Francesco; Kaufmann, Laurence; Clément, Fabrice; Schwartz, Sophie

    2015-09-01

    Forming and updating impressions about others is critical in everyday life and engages portions of the dorsomedial prefrontal cortex (dMPFC), the posterior cingulate cortex (PCC) and the amygdala. Some of these activations are attributed to "mentalizing" functions necessary to represent people's mental states, such as beliefs or desires. Evolutionary psychology and developmental studies, however, suggest that interpersonal inferences can also be obtained through the aid of deontic heuristics, which dictate what must (or must not) be done in given circumstances. We used fMRI and asked 18 participants to predict whether unknown characters would follow their desires or obey external rules. Participants had no means, at the beginning, to make accurate predictions, but slowly learned (throughout the experiment) each character's behavioral profile. We isolated brain regions whose activity changed during the experiment, as a neural signature of impression updating: whereas dMPFC was progressively more involved in predicting characters' behavior in relation to their desires, the medial orbitofrontal cortex and the amygdala were progressively more recruited in predicting rule-based behavior. Our data provide evidence of a neural dissociation between deontic inference and theory-of-mind (ToM), and support a differentiation of orbital and dorsal prefrontal cortex in terms of low- and high-level social cognition. PMID:25820129

  11. FDA publishes conflict of interest rules for clinical trials. Food and Drug Administration.

    Science.gov (United States)

    James, J S

    1998-03-01

    The Food and Drug Administration (FDA) published new rules defining conflict of interests between drug companies and medical researchers and clinicians. Certain financial arrangements will need to be disclosed, although the FDA estimates that only one to ten percent of pharmaceutical companies will need to submit disclosures for one or more of their investigators. The purpose of the new rule is to prevent bias in safety and efficacy studies of drugs and medical devices. The full rule is published in the Federal Register.

  12. Formalized prediction of clinically significant prostate cancer: is it possible?

    Institute of Scientific and Technical Information of China (English)

    Carvell T Nguyen; Michael W Kattan

    2012-01-01

    Greater understanding of the biology and epidemiology of prostate cancer in the last several decades have led to significant advances in its management.Prostate cancer is now detected in greater numbers at lower stages of disease and is amenable to multiple forms of efficacious treatment.However,there is a lack of conclusive data demonstrating a definitive mortality benefit from this earlier diagnosis and treatment of prostate cancer.It is likely due to the treatment of a large proportion of indolent cancers that would have had little adverse impact on health or lifespan if left alone.Due to this overtreatment phenomenon,active surveillance with delayed intervention is gaining traction as a viable management approach in contemporary practice.The ability to distinguish clinically insignificant cancers from those with a high risk of progression and/or lethality is critical to the appropriate selection of patients for surveillance protocols versus immediate intervention.This chapter will review the ability of various prediction models,including risk groupings and nomograms,to predict indolent disease and determine their role in the contemporary management of clinically localized prostate cancer.

  13. Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines

    Directory of Open Access Journals (Sweden)

    Kerckhove Wannes

    2010-01-01

    Full Text Available Abstract Background Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs. The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase. Methods A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA. Results The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows

  14. Integration of Rule Based Expert Systems and Case Based Reasoning in an Acute Bacterial Meningitis Clinical Decision Support System

    CERN Document Server

    Cabrera, Mariana Maceiras

    2010-01-01

    This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.

  15. Confirming a predicted selection rule in inelastic neutron scattering spectroscopy: the quantum translator-rotator H2 entrapped inside C60.

    Science.gov (United States)

    Xu, Minzhong; Jiménez-Ruiz, Mónica; Johnson, Mark R; Rols, Stéphane; Ye, Shufeng; Carravetta, Marina; Denning, Mark S; Lei, Xuegong; Bačić, Zlatko; Horsewill, Anthony J

    2014-09-19

    We report an inelastic neutron scattering (INS) study of a H2 molecule encapsulated inside the fullerene C60 which confirms the recently predicted selection rule, the first to be established for the INS spectroscopy of aperiodic, discrete molecular compounds. Several transitions from the ground state of para-H2 to certain excited translation-rotation states, forbidden according to the selection rule, are systematically absent from the INS spectra, thus validating the selection rule with a high degree of confidence. Its confirmation sets a precedent, as it runs counter to the widely held view that the INS spectroscopy of molecular compounds is not subject to any selection rules. PMID:25279623

  16. Sensitivity of palm print, modified mallampati score and 3-3-2 rule in prediction of difficult intubation

    Directory of Open Access Journals (Sweden)

    Ata Mahmoodpoor

    2013-01-01

    Full Text Available Background: This study evaluated the performance of modified Mallampati score, 3-3-2 rule and palm print in prediction of difficult intubation. Methods: In a prospective descriptive study, data from 500 patients scheduled for elective surgery under general anesthesia were collected. An anesthesiologist evaluated the airway using mentioned tests and another anesthesiologist evaluated difficult intubation. Laryngoscopic views were determined by Cormack and Lehane score. Grades 3 and 4 were defined as difficult intubation. Sensitivity, specificity, positive predictive value, negative predictive value and Youden index were determined for all tests. Results: Difficult intubation was reported in 8.9% of the patients. There was a significant correlation between body mass index and difficult intubation (P : 0.004; however, other demographic characteristics didn′t have a significant correlation with difficult intubation. Among three tests, palm print was of highest specificity (96.46% and modified Mallampati of highest sensitivity (98.40%. In a combination of the tests, the highest specificity, sensitivity and Youden index were observed when using all three tests together. Conclusions: Palm print has a high specificity for prediction of difficult intubation, but the best way for prediction of difficult intubation is using all three tests together.

  17. Do Rapoport's rule, mid-domain effect or environmental factors predict latitudinal range size patterns of terrestrial mammals in China?

    Directory of Open Access Journals (Sweden)

    Zhenhua Luo

    Full Text Available BACKGROUND: Explaining species range size pattern is a central issue in biogeography and macroecology. Although several hypotheses have been proposed, the causes and processes underlying range size patterns are still not clearly understood. In this study, we documented the latitudinal mean range size patterns of terrestrial mammals in China, and evaluated whether that pattern conformed to the predictions of the Rapoport's rule several analytical methods. We also assessed the influence of the mid-domain effect (MDE and environmental factors on the documented range size gradient. METHODOLOGY/PRINCIPAL FINDINGS: Distributions of 515 terrestrial mammals and data on nine environmental variables were compiled. We calculated mean range size of the species in each 5° latitudinal band, and created a range size map on a 100 km×100 km quadrat system. We evaluated Rapoport's rule according to Steven's, mid-point, Pagel's and cross-species methods. The effect of the MDE was tested based on a Monte Carlo simulation and linear regression. We used stepwise generalized linear models and correlation analyses to detect the impacts of mean climate condition, climate variability, ambient energy and topography on range size. The results of the Steven's, Pagel's and cross-species methods supported Rapoport's rule, whereas the mid-point method resulted in a hump-shaped pattern. Our range size map showed that larger mean latitudinal extents emerged in the mid-latitudes. We found that the MDE explained 80.2% of the range size variation, whereas, environmental factors accounted for <30% of that variation. CONCLUSIONS/SIGNIFICANCE: Latitudinal range size pattern of terrestrial mammals in China supported Rapoport's rule, though the extent of that support was strongly influenced by methodology. The critical factor underlying the observed gradient was the MDE, and the effects of climate, energy and topography were limited. The mean climate condition hypothesis, climate

  18. Clinical manifestations that predict abnormal brain computed tomography (CT in children with minor head injury

    Directory of Open Access Journals (Sweden)

    Nesrin Alharthy

    2015-01-01

    Full Text Available Background: Computed tomography (CT used in pediatric pediatrics brain injury (TBI to ascertain neurological manifestations. Nevertheless, this practice is associated with adverse effects. Reports in the literature suggest incidents of morbidity and mortality in children due to exposure to radiation. Hence, it is found imperative to search for a reliable alternative. Objectives: The aim of this study is to find a reliable clinical alternative to detect an intracranial injury without resorting to the CT. Materials and Methods: Retrospective cross-sectional study was undertaken in patients (1-14 years with blunt head injury and having a Glasgow Coma Scale (GCS of 13-15 who had CT performed on them. Using statistical analysis, the correlation between clinical examination and positive CT manifestation is analyzed for different age-groups and various mechanisms of injury. Results: No statistically significant association between parameteres such as Loss of Consciousness, ′fall′ as mechanism of injury, motor vehicle accidents (MVA, more than two discrete episodes of vomiting and the CT finding of intracranial injury could be noted. Analyzed data have led to believe that GCS of 13 at presentation is the only important clinical predictor of intracranial injury. Conclusion: Retrospective data, small sample size and limited number of factors for assessing clinical manifestation might present constraints on the predictive rule that was derived from this review. Such limitations notwithstanding, the decision to determine which patients should undergo neuroimaging is encouraged to be based on clinical judgments. Further analysis with higher sample sizes may be required to authenticate and validate findings.

  19. An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems.

    Science.gov (United States)

    Sáez, Carlos; Bresó, Adrián; Vicente, Javier; Robles, Montserrat; García-Gómez, Juan Miguel

    2013-03-01

    The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus. PMID:23199936

  20. Exceptions to the rule: case studies in the prediction of pathogenicity for genetic variants in hereditary cancer genes.

    Science.gov (United States)

    Rosenthal, E T; Bowles, K R; Pruss, D; van Kan, A; Vail, P J; McElroy, H; Wenstrup, R J

    2015-12-01

    Based on current consensus guidelines and standard practice, many genetic variants detected in clinical testing are classified as disease causing based on their predicted impact on the normal expression or function of the gene in the absence of additional data. However, our laboratory has identified a subset of such variants in hereditary cancer genes for which compelling contradictory evidence emerged after the initial evaluation following the first observation of the variant. Three representative examples of variants in BRCA1, BRCA2 and MSH2 that are predicted to disrupt splicing, prematurely truncate the protein, or remove the start codon were evaluated for pathogenicity by analyzing clinical data with multiple classification algorithms. Available clinical data for all three variants contradicts the expected pathogenic classification. These variants illustrate potential pitfalls associated with standard approaches to variant classification as well as the challenges associated with monitoring data, updating classifications, and reporting potentially contradictory interpretations to the clinicians responsible for translating test outcomes to appropriate clinical action. It is important to address these challenges now as the model for clinical testing moves toward the use of large multi-gene panels and whole exome/genome analysis, which will dramatically increase the number of genetic variants identified. PMID:25639900

  1. Predicting the planform configuration of the braided Toklat River, AK with a suite of rule-based models

    Science.gov (United States)

    Podolak, Charles J.

    2013-01-01

    An ensemble of rule-based models was constructed to assess possible future braided river planform configurations for the Toklat River in Denali National Park and Preserve, Alaska. This approach combined an analysis of large-scale influences on stability with several reduced-complexity models to produce the predictions at a practical level for managers concerned about the persistence of bank erosion while acknowledging the great uncertainty in any landscape prediction. First, a model of confluence angles reproduced observed angles of a major confluence, but showed limited susceptibility to a major rearrangement of the channel planform downstream. Second, a probabilistic map of channel locations was created with a two-parameter channel avulsion model. The predicted channel belt location was concentrated in the same area as the current channel belt. Finally, a suite of valley-scale channel and braid plain characteristics were extracted from a light detection and ranging (LiDAR)-derived surface. The characteristics demonstrated large-scale stabilizing topographic influences on channel planform. The combination of independent analyses increased confidence in the conclusion that the Toklat River braided planform is a dynamically stable system due to large and persistent valley-scale influences, and that a range of avulsive perturbations are likely to result in a relatively unchanged planform configuration in the short term.

  2. ECG dispersion mapping predicts clinical deterioration, measured by increase in the Simple Clinical Score.

    LENUS (Irish Health Repository)

    Kellett, J

    2012-01-01

    Objective: ECG dispersion mapping (ECG-DM) is a novel technique that reports abnormal ECG microalternations. We report the ability of ECG-DM to predict clinical deterioration of acutely ill medical patients, as measured by an increase in the Simple Clinical Score (SCS) the day after admission to hospital. Methods: 453 acutely ill medical patients (mean age 69.7 +\\/- 14.0 years) had the SCS recorded and ECGDM performed immediately after admission to hospital. Results: 46 patients had an SCS increase 20.8 +\\/- 7.6 hours after admission. Abnormal micro-alternations during left ventricular re-polarization had the highest association with SCS increase (p=0.0005). Logistic regression showed that only nursing home residence and abnormal micro-alternations during re-polarization of the left ventricle were independent predictors of SCS increase with an odds ratio of 2.84 and 3.01, respectively. Conclusion: ECG-DM changes during left ventricular re-polarization are independent predictors of clinical deterioration the day after hospital admission.

  3. A combined clinical and biomarker approach to predict diuretic response in acute heart failure

    NARCIS (Netherlands)

    Ter Maaten, Jozine M; Valente, Mattia A E; Metra, Marco; Bruno, Noemi; O'Connor, Christopher M; Ponikowski, Piotr; Teerlink, John R; Cotter, Gad; Davison, Beth; Cleland, John G; Givertz, Michael M; Bloomfield, Daniel M; Dittrich, Howard C; van Veldhuisen, Dirk J; Hillege, Hans L; Damman, Kevin; Voors, Adriaan A

    2015-01-01

    BACKGROUND: Poor diuretic response in acute heart failure is related to poor clinical outcome. The underlying mechanisms and pathophysiology behind diuretic resistance are incompletely understood. We evaluated a combined approach using clinical characteristics and biomarkers to predict diuretic resp

  4. Dealing with missing predictor values when applying clinical prediction models.

    NARCIS (Netherlands)

    Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.

    2009-01-01

    BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with suc

  5. Rorschach Prediction of Success in Clinical Training: A Second Look

    Science.gov (United States)

    Carlson, Rae

    1969-01-01

    A Rorschach Index based on ego-psychological conceptualization of an optimal personality picture predicted for 155 trainees was compared with predictions from the Miller Analogies Test (MAT) and the Strong Vocational Interest Blank (SVIB). The Index predicted success and failure more effectively. (Author)

  6. Do institutional logics predict interpretation of contract rules at the dental chair-side?

    Science.gov (United States)

    Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth

    2014-12-01

    In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. PMID:25441320

  7. Do institutional logics predict interpretation of contract rules at the dental chair-side?

    Science.gov (United States)

    Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth

    2014-01-01

    In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. PMID:25441320

  8. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Science.gov (United States)

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  9. Clinical prediction and diagnosis of neurosyphilis in HIV-infected patients with early Syphilis.

    Science.gov (United States)

    Dumaresq, Jeannot; Langevin, Stéphanie; Gagnon, Simon; Serhir, Bouchra; Deligne, Benoît; Tremblay, Cécile; Tsang, Raymond S W; Fortin, Claude; Coutlée, François; Roger, Michel

    2013-12-01

    The diagnosis of neurosyphilis (NS) is a challenge, especially in HIV-infected patients, and the criteria for deciding when to perform a lumbar puncture (LP) in HIV-infected patients with syphilis are controversial. We retrospectively reviewed demographic, clinical, and laboratory data from 122 cases of HIV-infected patients with documented early syphilis who underwent an LP to rule out NS, and we evaluated 3 laboratory-developed validated real-time PCR assays, the Treponema pallidum particle agglutination (TPPA) assay, the fluorescent treponemal antibody absorption (FTA-ABS) assay, and the line immunoassay INNO-LIA Syphilis, for the diagnosis of NS from cerebrospinal fluid (CSF) samples of these patients. NS was defined by a reactive CSF-VDRL test result and/or a CSF white blood cell (WBC) count of >20 cells/μl. Thirty of the 122 patients (24.6%) had early NS. Headache, visual symptoms, a CD4 cell count of RPR) titers were not associated with early NS (P = 0.575). For the diagnosis of NS, the PCR, FTA-ABS, TPPA, and INNO-LIA assays had sensitivities of 58%, 100%, 68%, and 100%, specificities of 67%, 12%, 49%, and 13%, and negative predictive values of 85%, 100%, 84%, and 100%, respectively. Visual disturbances, headache, uncontrolled HIV-1 viremia, and a CD4 cell count of syphilis, while blood serum RPR titers were not; therefore, RPR titers should not be used as the sole criterion for deciding whether to perform an LP in early syphilis. When applied to CSF samples, the INNO-LIA Syphilis assay easily helped rule out NS. PMID:24088852

  10. Physiological functions and clinical implications of the N-end rule pathway.

    Science.gov (United States)

    Liu, Yujiao; Liu, Chao; Dong, Wen; Li, Wei

    2016-09-01

    The N-end rule pathway is a unique branch of the ubiquitin-proteasome system in which the determination of a protein's half-life is dependent on its N-terminal residue. The N-terminal residue serves as the degradation signal of a protein and thus called N-degron. N-degron can be recognized and modifed by several steps of post-translational modifications, such as oxidation, deamination, arginylation or acetylation, it then polyubiquitinated by the N-recognin for degradation. The molecular basis of the N-end rule pathway has been elucidated and its physiological functions have been revealed in the past 30 years. This pathway is involved in several biological aspects, including transcription, differentiation, chromosomal segregation, genome stability, apoptosis, mitochondrial quality control, cardiovascular development, neurogenesis, carcinogenesis, and spermatogenesis. Disturbance of this pathway often causes the failure of these processes, resulting in some human diseases. This review summarized the physiological functions of the N-end rule pathway, introduced the related biological processes and diseases, with an emphasis on the inner link between this pathway and certain symptoms.

  11. New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs

    Institute of Scientific and Technical Information of China (English)

    Robert A.Beckman; Cong Chen

    2013-01-01

    Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy,increase the value of cancer medicines,and decrease the size and cost of clinical trials while increasing their chance of success.But predictive biomarkers do not always work.When unsuccessful,they add cost,complexity,and time to drug development.This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes.In the end,the biomarker is emphasized to the extent that it can actually predict.

  12. On the Rule of Mixtures for Predicting Stress-Softening and Residual Strain Effects in Biological Tissues and Biocompatible Materials

    Directory of Open Access Journals (Sweden)

    Alex Elías-Zúñiga

    2014-01-01

    Full Text Available In this work, we use the rule of mixtures to develop an equivalent material model in which the total strain energy density is split into the isotropic part related to the matrix component and the anisotropic energy contribution related to the fiber effects. For the isotropic energy part, we select the amended non-Gaussian strain energy density model, while the energy fiber effects are added by considering the equivalent anisotropic volumetric fraction contribution, as well as the isotropized representation form of the eight-chain energy model that accounts for the material anisotropic effects. Furthermore, our proposed material model uses a phenomenological non-monotonous softening function that predicts stress softening effects and has an energy term, derived from the pseudo-elasticity theory, that accounts for residual strain deformations. The model’s theoretical predictions are compared with experimental data collected from human vaginal tissues, mice skin, poly(glycolide-co-caprolactone (PGC25 3-0 and polypropylene suture materials and tracheal and brain human tissues. In all cases examined here, our equivalent material model closely follows stress-softening and residual strain effects exhibited by experimental data.

  13. CLINICAL DATABASE ANALYSIS USING DMDT BASED PREDICTIVE MODELLING

    Directory of Open Access Journals (Sweden)

    Srilakshmi Indrasenan

    2013-04-01

    Full Text Available In recent years, predictive data mining techniques play a vital role in the field of medical informatics. These techniques help the medical practitioners in predicting various classes which is useful in prediction treatment. One of such major difficulty is prediction of survival rate in breast cancer patients. Breast cancer is a common disease these days and fighting against it is a tough battle for both the surgeons and the patients. To predict the survivability rate in breast cancer patients which helps the medical practitioner to select the type of treatment a predictive data mining technique called Diversified Multiple Decision Tree (DMDT classification is used. Additionally, to avoid difficulties from the outlier and skewed data, it is also proposed to perform the improvement of training space by outlier filtering and over sampling. As a result, this novel approach gives the survivability rate of the cancer patients based on which the medical practitioners can choose the type of treatment.

  14. Clinical prediction of 5-year survival in systemic sclerosis

    DEFF Research Database (Denmark)

    Fransen, Julie Munk; Popa-Diaconu, D; Hesselstrand, R;

    2011-01-01

    Systemic sclerosis (SSc) is associated with a significant reduction in life expectancy. A simple prognostic model to predict 5-year survival in SSc was developed in 1999 in 280 patients, but it has not been validated in other patients. The predictions of a prognostic model are usually less accurate...... in other patients, especially from other centres or countries. A study was undertaken to validate the prognostic model to predict 5-year survival in SSc in other centres throughout Europe....

  15. Prediction of persistent shoulder pain in general practice: Comparing clinical consensus from a Delphi procedure with a statistical scoring system

    Directory of Open Access Journals (Sweden)

    van der Windt Daniëlle AWM

    2011-06-01

    Full Text Available Abstract Background In prognostic research, prediction rules are generally statistically derived. However the composition and performance of these statistical models may strongly depend on the characteristics of the derivation sample. The purpose of this study was to establish consensus among clinicians and experts on key predictors for persistent shoulder pain three months after initial consultation in primary care and assess the predictive performance of a model based on clinical expertise compared to a statistically derived model. Methods A Delphi poll involving 3 rounds of data collection was used to reach consensus among health care professionals involved in the assessment and management of shoulder pain. Results Predictors selected by the expert panel were: symptom duration, pain catastrophizing, symptom history, fear-avoidance beliefs, coexisting neck pain, severity of shoulder disability, multisite pain, age, shoulder pain intensity and illness perceptions. When tested in a sample of 587 primary care patients consulting with shoulder pain the predictive performance of the two prognostic models based on clinical expertise were lower compared to that of a statistically derived model (Area Under the Curve, AUC, expert-based dichotomous predictors 0.656, expert-based continuous predictors 0.679 vs. 0.702 statistical model. Conclusions The three models were different in terms of composition, but all confirmed the prognostic importance of symptom duration, baseline level of shoulder disability and multisite pain. External validation in other populations of shoulder pain patients should confirm whether statistically derived models indeed perform better compared to models based on clinical expertise.

  16. A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Hossain, Emran; Khalid, Md. Saifuddin;

    2014-01-01

    Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty such as ......Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty...... such as vagueness; imprecision; randomness; ignorance and incompleteness. Consequently; traditional disease diagnosis; which is performed by a physician; cannot deliver accurate results. Therefore; this paper presents the design; development and application of a decision support system for assessing asthma under...... conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation...

  17. Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor

    OpenAIRE

    Dipankar SENGUPTA; Sood, Meemansa; Vijayvargia, Poorvika; Hota, Sunil; Naik, Pradeep K

    2013-01-01

    Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that...

  18. Predictive value of clinical history compared with urodynamic study in 1,179 women

    Directory of Open Access Journals (Sweden)

    Jorge Milhem Haddad

    2016-02-01

    Full Text Available SUMMARY Objective: to determine the positive predictive value of clinical history in comparison with urodynamic study for the diagnosis of urinary incontinence. Methods: retrospective analysis comparing clinical history and urodynamic evaluation of 1,179 women with urinary incontinence. The urodynamic study was considered the gold standard, whereas the clinical history was the new test to be assessed. This was established after analyzing each method as the gold standard through the difference between their positive predictive values. Results: the positive predictive values of clinical history compared with urodynamic study for diagnosis of stress urinary incontinence, overactive bladder and mixed urinary incontinence were, respectively, 37% (95% CI 31-44, 40% (95% CI 33-47 and 16% (95% CI 14-19. Conclusion: we concluded that the positive predictive value of clinical history was low compared with urodynamic study for urinary incontinence diagnosis. The positive predictive value was low even among women with pure stress urinary incontinence.

  19. A biometric approach to predictable treatment of clinical crown discrepancies.

    Science.gov (United States)

    Chu, Stephen J

    2007-08-01

    Dental professionals have long been guided by mathematical principles when interpreting aesthetic and tooth proportions for their patients. While many acknowledge that such principles are merely launch points for a smile design or reconstructive procedure, their existence appears to indicate practitioners' desire for predictable, objective, and reproducible means of achieving success in aesthetic dentistry. This article introduces innovative aesthetic measurement gauges as a means of objectively quantifying tooth size discrepancies and enabling the clinician to perform aesthetic restorative dentistry with success and predictability.

  20. Islet Oxygen Consumption Rate (OCR) Dose Predicts Insulin Independence in Clinical Islet Autotransplantation

    OpenAIRE

    Papas, Klearchos K; Bellin, Melena D.; Sutherland, David E. R.; Suszynski, Thomas M.; Kitzmann, Jennifer P.; Avgoustiniatos, Efstathios S.; Gruessner, Angelika C.; Mueller, Kathryn R.; Beilman, Gregory J.; Balamurugan, Appakalai N.; Gopalakrishnan Loganathan; Colton, Clark K.; Maria Koulmanda; Weir, Gordon C.; Josh J Wilhelm

    2015-01-01

    Background: Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR) in predicting clinical islet autotransplant (IAT) insulin independence (II). IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding ...

  1. Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

    Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

  2. Pressure Ulcers in Adults: Prediction and Prevention. Clinical Practice Guideline Number 3.

    Science.gov (United States)

    Agency for Health Care Policy and Research (DHHS/PHS), Rockville, MD.

    This package includes a clinical practice guideline, quick reference guide for clinicians, and patient's guide to predicting and preventing pressure ulcers in adults. The clinical practice guideline includes the following: overview of the incidence and prevalence of pressure ulcers; clinical practice guideline (introduction, risk assessment tools…

  3. A prospective observational study to assess the diagnostic accuracy of clinical decision rules for children presenting to emergency departments after head injuries (protocol): the Australasian Paediatric Head Injury Rules Study (APHIRST)

    OpenAIRE

    Babl, Franz E; Lyttle, Mark D; Bressan, Silvia; Borland, Meredith; Phillips, Natalie; Kochar, Amit; Stuart R Dalziel; Dalton, Sarah; Cheek, John A; Furyk, Jeremy; Gilhotra, Yuri; Neutze, Jocelyn; Ward, Brenton; Donath, Susan; Jachno, Kim

    2014-01-01

    Background Head injuries in children are responsible for a large number of emergency department visits. Failure to identify a clinically significant intracranial injury in a timely fashion may result in long term neurodisability and death. Whilst cranial computed tomography (CT) provides rapid and definitive identification of intracranial injuries, it is resource intensive and associated with radiation induced cancer. Evidence based head injury clinical decision rules have been derived to aid...

  4. Somatic cell count distributions during lactation predict clinical mastitis

    NARCIS (Netherlands)

    Green, M.J.; Green, L.E.; Schukken, Y.H.; Bradley, A.J.; Peeler, E.J.; Barkema, H.W.; Haas, de Y.; Collis, V.J.; Medley, G.F.

    2004-01-01

    This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n = 14

  5. The Prediction of Academic and Clinical Performance in Medical School

    Science.gov (United States)

    Gough, Harrison G.; Hall, Wallace B.

    1975-01-01

    A study of medical student performance showed the clinical performance factor more or less unpredictable from aptitude and premedical academic achievement indices while the academic performance factor was forecast with acceptable accuracy by equations based on the Medical College Admissions Test and premedical grade point average. (JT)

  6. An Integrative Pathway-based Clinical-genomic Model for Cancer Survival Prediction.

    Science.gov (United States)

    Chen, Xi; Wang, Lily; Ishwaran, Hemant

    2010-09-01

    Prediction models that use gene expression levels are now being proposed for personalized treatment of cancer, but building accurate models that are easy to interpret remains a challenge. In this paper, we describe an integrative clinical-genomic approach that combines both genomic pathway and clinical information. First, we summarize information from genes in each pathway using Supervised Principal Components (SPCA) to obtain pathway-based genomic predictors. Next, we build a prediction model based on clinical variables and pathway-based genomic predictors using Random Survival Forests (RSF). Our rationale for this two-stage procedure is that the underlying disease process may be influenced by environmental exposure (measured by clinical variables) and perturbations in different pathways (measured by pathway-based genomic variables), as well as their interactions. Using two cancer microarray datasets, we show that the pathway-based clinical-genomic model outperforms gene-based clinical-genomic models, with improved prediction accuracy and interpretability.

  7. Clinical Decision Support Rules in an Archetype-Based Health Record System : Combining Archetype Query Language (AQL) and Semantic Web Rule Language (SWRL)

    OpenAIRE

    Viklund, Herman; Karlsson, Hanna

    2009-01-01

    By using archetypes, it is possible to define how data are stored in the EHR,which facilitates querying for data. The objective of this thesis is to investigate the possibility of connecting a decisionsupport system to archetype-based medical records by using the ArchetypeQuery Language (AQL) and the Semantic Web Rule Language (SWRL). The result shows that, since SWRL is a logic language rather than a programminglanguage, built-ins are necessary to allow SWRL rules to function as programmingr...

  8. Ethics and epistemology of accurate prediction in clinical research.

    Science.gov (United States)

    Hey, Spencer Phillips

    2015-07-01

    All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with the principles of ethical research.

  9. Prenatal prediction of pulmonary hypoplasia: clinical, biometric, and Doppler velocity correlates

    NARCIS (Netherlands)

    J.A.M. Laudij (Jacqueline); D. Tibboel (Dick); S.G.F. Robben (Simon); R.R. de Krijger (Ronald); M.A.J. de Ridder (Maria); J.W. Wladimiroff (Juriy)

    2002-01-01

    textabstractOBJECTIVES: To determine the value of pulmonary artery Doppler velocimetry relative to fetal biometric indices and clinical correlates in the prenatal prediction of lethal lung hypoplasia (LH) in prolonged (>1 week) oligohydramnios. METHODS: Forty-two singleton pregnanc

  10. Do clinical prediction models improve concordance of treatment decisions in reproductive medicine?

    NARCIS (Netherlands)

    J.W. van der Steeg; P. Steures; M.J.C. Eijkemans; J.D.F. Habbema; P.M.M. Bossuyt; P.G.A. Hompes; F. van der Veen; B.W.J. Mol

    2006-01-01

    Objective To assess whether the use of clinical prediction models improves concordance between gynaecologists with respect to treatment decisions in reproductive medicine. Design We constructed 16 vignettes of subfertile couples by varying fertility history, postcoital test, sperm motility, follicle

  11. Locus heterogeneity for Waardenburg syndrome is predictive of clinical subtypes

    Energy Technology Data Exchange (ETDEWEB)

    Farrer, L.A.; Hoth, C. [Boston Univ. School of Medicine, MA (United States); Arnos, K.S. [Galludet Univ., Washington, DC (United States); Asher, J.H. Jr.; Friedman, T.B. [Michigan State Univ., East Lansing, MI (United States); Grundfast, K.M.; Lalwani, A.K. [National Institute on Deafness and Other Communication Disorders, Bethesda, MD (United States); Greenberg, J. [Univ. of Cape Town (South Africa); Diehl, S.R. [and others

    1994-10-01

    Waardenburg syndrome (WS) is a dominantly inherited and clinically variable syndrome of deafness, pigmentary changes, and distinctive facial features. Clinically, WS type I (WS1) is differentiated from WS type II (WS2) by the high frequency of dystopia canthorum in the family. In some families, WS is caused by mutations in the PAX3 gene on chromosome 2q. We have typed microsatellite markers within and flanking PAX3 in 41 WS1 kindreds and 26 WS2 kindreds in order to estimate the proportion of families with probable mutations in PAX3 and to study the relationship between phenotypic and genotypic heterogeneity. Evaluation of heterogeneity in location scores obtained by multilocus analysis indicated that WS is linked to PAX3 in 60% of all WS families and in 100% of WS1 families. None of the WS2 families were linked. In those families in which equivocal lod scores (between -2 and +1) were found, PAX3 mutations have been identified in 5 of the 15 WS1 families but in none of the 4 WS2 families. Although preliminary studies do not suggest any association between the phenotype and the molecular pathology in 20 families with known PAX3 mutations and in four patients with chromosomal abnormalities in the vicinity of PAX3, the presence of dystopia in multiple family members is a reliable indicator for identifying families likely to have a defect in PAX3. 59 refs., 3 figs., 5 tabs.

  12. Clinical Prediction and Diagnosis of Neurosyphilis in HIV-Infected Patients with Early Syphilis

    OpenAIRE

    Dumaresq, Jeannot; Langevin, Stéphanie; Gagnon, Simon; Serhir, Bouchra; Deligne, Benoît; Tremblay, Cécile; Tsang, Raymond S.W.; Fortin, Claude; Coutlée, François; Roger, Michel

    2013-01-01

    The diagnosis of neurosyphilis (NS) is a challenge, especially in HIV-infected patients, and the criteria for deciding when to perform a lumbar puncture (LP) in HIV-infected patients with syphilis are controversial. We retrospectively reviewed demographic, clinical, and laboratory data from 122 cases of HIV-infected patients with documented early syphilis who underwent an LP to rule out NS, and we evaluated 3 laboratory-developed validated real-time PCR assays, the Treponema pallidum particle...

  13. How electrodiagnosis predicts clinical outcome of focal peripheral nerve lesions.

    Science.gov (United States)

    Robinson, Lawrence R

    2015-09-01

    This article reviews the electrodiagnostic (EDX) prognostic factors for focal traumatic and nontraumatic peripheral nerve injuries. Referring physicians and patients often benefit from general and nerve-specific prognostic information from the EDX consultant. Knowing the probable outcome from a nerve injury allows the referring physician to choose the best treatment options for his/her patients. Nerve injuries are variable in their mechanism, location, and pathophysiology. The general effects of the injuries on nerve and muscle are well known, but more research is needed for nerve-specific information. Several factors currently known to influence prognosis include: nature of the nerve trauma, amount of axon loss, recruitment in muscles supplied by the nerve, the extent of demyelination, and the distance to reinnervate functional muscles. This article reviews these general concepts and also nerve-specific EDX measures that predict outcome after focal neuropathies.

  14. Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions

    Science.gov (United States)

    Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.

    2006-01-01

    In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…

  15. A Hybrid Data Mining Model to Predict Coronary Artery Disease Cases Using Non-Invasive Clinical Data.

    Science.gov (United States)

    Verma, Luxmi; Srivastava, Sangeet; Negi, P C

    2016-07-01

    Coronary artery disease (CAD) is caused by atherosclerosis in coronary arteries and results in cardiac arrest and heart attack. For diagnosis of CAD, angiography is used which is a costly time consuming and highly technical invasive method. Researchers are, therefore, prompted for alternative methods such as machine learning algorithms that could use noninvasive clinical data for the disease diagnosis and assessing its severity. In this study, we present a novel hybrid method for CAD diagnosis, including risk factor identification using correlation based feature subset (CFS) selection with particle swam optimization (PSO) search method and K-means clustering algorithms. Supervised learning algorithms such as multi-layer perceptron (MLP), multinomial logistic regression (MLR), fuzzy unordered rule induction algorithm (FURIA) and C4.5 are then used to model CAD cases. We tested this approach on clinical data consisting of 26 features and 335 instances collected at the Department of Cardiology, Indira Gandhi Medical College, Shimla, India. MLR achieves highest prediction accuracy of 88.4 %.We tested this approach on benchmarked Cleaveland heart disease data as well. In this case also, MLR, outperforms other techniques. Proposed hybridized model improves the accuracy of classification algorithms from 8.3 % to 11.4 % for the Cleaveland data. The proposed method is, therefore, a promising tool for identification of CAD patients with improved prediction accuracy. PMID:27286983

  16. Use of clinical movement screening tests to predict injury in sport

    OpenAIRE

    Chimera, Nicole J.; Warren, Meghan

    2016-01-01

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention,...

  17. Clinical parameters predictive of malignancy of thyroid follicular neoplasms

    International Nuclear Information System (INIS)

    Needle aspiration biopsy is commonly employed in the evaluation of thyroid nodules. Unfortunately, the cytologic finding of a 'follicular neoplasm' does not distinguish between a thyroid adenoma and a follicular cancer. The purpose of this study was to identify clinical parameters that characterize patients with an increased risk of having a thyroid follicular cancer who preoperatively have a 'follicular neoplasm' identified by needle aspiration biopsy. A total of 395 patients initially treated at Vancouver General Hospital and the British Columbia Cancer Agency between the years of 1965 and 1985 were identified and their data were entered into a computer database. Patients with thyroid adenomas were compared to patients with follicular cancer using the chi-square test and Student's t-test. Statistically significant parameters that distinguished patients at risk of having a thyroid cancer (p less than 0.05) included age greater than 50 years, nodule size greater than 3 cm, and a history of neck irradiation. Sex, family history of goiter or neoplasm, alcohol and tobacco use, and use of exogenous estrogen were not significant parameters. Patients can be identified preoperatively to be at an increased risk of having a follicular cancer and accordingly appropriate surgical resection can be planned

  18. Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease

    DEFF Research Database (Denmark)

    Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G;

    2009-01-01

    This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination...... that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors....

  19. Creep-fatigue life prediction for different heats of Type 304 stainless steel by linear-damage rule, strain-range partitioning method, and damage-rate approach

    Energy Technology Data Exchange (ETDEWEB)

    Maiya, P.S.

    1978-07-01

    The creep-fatigue life results for five different heats of Type 304 stainless steel at 593/sup 0/C (1100/sup 0/F), generated under push-pull conditions in the axial strain-control mode, are presented. The life predictions for the various heats based on the linear-damage rule, strain-range partitioning method, and damage-rate approach are discussed. The appropriate material properties required for computation of fatigue life are also included.

  20. Prognosis after Acute Myocardial Infarction as Predicted by C-reactive Protein and Clinical Variables

    Directory of Open Access Journals (Sweden)

    Angelo Modica MD, PhD

    2013-02-01

    Full Text Available Background:Raised concentrations of C-reactive protein (CRP have been reported to be strongly related to an adverse long term prognosis in patients with acute myocardial infarction (AMI. However, adjustments for clinical variables as well as interaction between variables have been incomplete. The aims of this study were to examine the predictive value of baseline concentrations of CRP for mortality after adjustment for important clinical variables and to compare the clinical usefulness of CRP with easily available clinical variables in the prediction of long term survival.Methods:Five hundred and thirty-one patients with AMI were included. A blood sample for CRP was obtained on admission. All patients were followed for a minimum of two years and death of any cause was recorded as the study end point.Results:In logistic regression analysis, the interaction term Age by Killip class > 1, the variable glomerular filtration rate as well as the interaction term Age by Atrial fibrillation were retained. The resulting model correctly predicted death or not in 81% of the patients. CRP did not contribute to the final model.Conclusions:CRP does not independently predict long-term mortality after an AMI after adjustments for clinical variables and interaction. CRP has no value beyond clinical variables in predicting death after AMI.

  1. The age-adjusted D-dimer safely excludes a high number of pulmonary embolisms in combination with four different clinical decision rules

    NARCIS (Netherlands)

    van Es, J.; Mos, I.C.M.; Douma, R.A.; Nizet, T.A.C.; Durian, M.; van Houten, A.A.; Hofstee, H.M.A.; ten Cate, H.; Ullmann, E.F.; Buller, H.R.; Huisman, M.V.; Kamphuisen, P.W.

    2011-01-01

    Background: Four different clinical decision rules (CDRs) (Wells score, Revised Geneva score (RGS), simplified Wells score and simplified RGS) safely exclude pulmonary embolism (PE), when combined with a normal D-dimer test. Recently, an age adjusted cut-off of the D-dimer (patient's age x 10 ig/L)

  2. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech

    Directory of Open Access Journals (Sweden)

    Jennifer L. Whitwell

    2016-01-01

    Full Text Available Beta-amyloid (Aβ deposition can be observed in primary progressive aphasia (PPA and progressive apraxia of speech (PAOS. While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified and PAOS (n = 42 subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+ status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+ status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+ status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified

  3. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech.

    Science.gov (United States)

    Whitwell, Jennifer L; Weigand, Stephen D; Duffy, Joseph R; Strand, Edythe A; Machulda, Mary M; Senjem, Matthew L; Gunter, Jeffrey L; Lowe, Val J; Jack, Clifford R; Josephs, Keith A

    2016-01-01

    Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects

  4. Ottawa ankle rules.

    OpenAIRE

    Stiell, I.

    1996-01-01

    The Ottawa ankle rule project demonstrated that more than 95% of patients with ankle injuries had radiographic examinations but that 85% of the films showed no fractures. A group of Ottawa emergency physicians developed two rules to identify clinically important fractures of the malleoli and the midfoot. Use of these rules reduced radiographic examinations by 28% for the ankle and 14% for the foot.

  5. Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes.

    Directory of Open Access Journals (Sweden)

    Yan P Yu

    Full Text Available Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason's grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy.

  6. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

    Science.gov (United States)

    Gao, Hui; Korn, Joshua M; Ferretti, Stéphane; Monahan, John E; Wang, Youzhen; Singh, Mallika; Zhang, Chao; Schnell, Christian; Yang, Guizhi; Zhang, Yun; Balbin, O Alejandro; Barbe, Stéphanie; Cai, Hongbo; Casey, Fergal; Chatterjee, Susmita; Chiang, Derek Y; Chuai, Shannon; Cogan, Shawn M; Collins, Scott D; Dammassa, Ernesta; Ebel, Nicolas; Embry, Millicent; Green, John; Kauffmann, Audrey; Kowal, Colleen; Leary, Rebecca J; Lehar, Joseph; Liang, Ying; Loo, Alice; Lorenzana, Edward; Robert McDonald, E; McLaughlin, Margaret E; Merkin, Jason; Meyer, Ronald; Naylor, Tara L; Patawaran, Montesa; Reddy, Anupama; Röelli, Claudia; Ruddy, David A; Salangsang, Fernando; Santacroce, Francesca; Singh, Angad P; Tang, Yan; Tinetto, Walter; Tobler, Sonja; Velazquez, Roberto; Venkatesan, Kavitha; Von Arx, Fabian; Wang, Hui Qin; Wang, Zongyao; Wiesmann, Marion; Wyss, Daniel; Xu, Fiona; Bitter, Hans; Atadja, Peter; Lees, Emma; Hofmann, Francesco; Li, En; Keen, Nicholas; Cozens, Robert; Jensen, Michael Rugaard; Pryer, Nancy K; Williams, Juliet A; Sellers, William R

    2015-11-01

    Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

  7. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    Institute of Scientific and Technical Information of China (English)

    Jin-You Wang; Yao Zhu; Chao-Fu Wang; Shi-Lin Zhang; Bo Dai; Ding-Wei Ye

    2014-01-01

    Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinical y diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of al included patients, 220 (81.8%) were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5%) patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.

  8. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    Directory of Open Access Journals (Sweden)

    Jin-You Wang

    2014-05-01

    Full Text Available Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of all included patients, 220 (81.8% were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5% patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.

  9. Clinical presentation and outcome prediction of clinical, serological, and histopathological classification schemes in ANCA-associated vasculitis with renal involvement.

    Science.gov (United States)

    Córdova-Sánchez, Bertha M; Mejía-Vilet, Juan M; Morales-Buenrostro, Luis E; Loyola-Rodríguez, Georgina; Uribe-Uribe, Norma O; Correa-Rotter, Ricardo

    2016-07-01

    Several classification schemes have been developed for anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), with actual debate focusing on their clinical and prognostic performance. Sixty-two patients with renal biopsy-proven AAV from a single center in Mexico City diagnosed between 2004 and 2013 were analyzed and classified under clinical (granulomatosis with polyangiitis [GPA], microscopic polyangiitis [MPA], renal limited vasculitis [RLV]), serological (proteinase 3 anti-neutrophil cytoplasmic antibodies [PR3-ANCA], myeloperoxidase anti-neutrophil cytoplasmic antibodies [MPO-ANCA], ANCA negative), and histopathological (focal, crescenteric, mixed-type, sclerosing) categories. Clinical presentation parameters were compared at baseline between classification groups, and the predictive value of different classification categories for disease and renal remission, relapse, renal, and patient survival was analyzed. Serological classification predicted relapse rate (PR3-ANCA hazard ratio for relapse 2.93, 1.20-7.17, p = 0.019). There were no differences in disease or renal remission, renal, or patient survival between clinical and serological categories. Histopathological classification predicted response to therapy, with a poorer renal remission rate for sclerosing group and those with less than 25 % normal glomeruli; in addition, it adequately delimited 24-month glomerular filtration rate (eGFR) evolution, but it did not predict renal nor patient survival. On multivariate models, renal replacement therapy (RRT) requirement (HR 8.07, CI 1.75-37.4, p = 0.008) and proteinuria (HR 1.49, CI 1.03-2.14, p = 0.034) at presentation predicted renal survival, while age (HR 1.10, CI 1.01-1.21, p = 0.041) and infective events during the induction phase (HR 4.72, 1.01-22.1, p = 0.049) negatively influenced patient survival. At present, ANCA-based serological classification may predict AAV relapses, but neither clinical nor serological

  10. Predictive capacity of risk assessment scales and clinical judgment for pressure ulcers: a meta-analysis.

    Science.gov (United States)

    García-Fernández, Francisco Pedro; Pancorbo-Hidalgo, Pedro L; Agreda, J Javier Soldevilla

    2014-01-01

    A systematic review with meta-analysis was completed to determine the capacity of risk assessment scales and nurses' clinical judgment to predict pressure ulcer (PU) development. Electronic databases were searched for prospective studies on the validity and predictive capacity of PUs risk assessment scales published between 1962 and 2010 in English, Spanish, Portuguese, Korean, German, and Greek. We excluded gray literature sources, integrative review articles, and retrospective or cross-sectional studies. The methodological quality of the studies was assessed according to the guidelines of the Critical Appraisal Skills Program. Predictive capacity was measured as relative risk (RR) with 95% confidence intervals. When 2 or more valid original studies were found, a meta-analysis was conducted using a random-effect model and sensitivity analysis. We identified 57 studies, including 31 that included a validation study. We also retrieved 4 studies that tested clinical judgment as a risk prediction factor. Meta-analysis produced the following pooled predictive capacity indicators: Braden (RR = 4.26); Norton (RR = 3.69); Waterlow (RR = 2.66); Cubbin-Jackson (RR = 8.63); EMINA (RR = 6.17); Pressure Sore Predictor Scale (RR = 21.4); and clinical judgment (RR = 1.89). Pooled analysis of 11 studies found adequate risk prediction capacity in various clinical settings; the Braden, Norton, EMINA (mEntal state, Mobility, Incontinence, Nutrition, Activity), Waterlow, and Cubbin-Jackson scales showed the highest predictive capacity. The clinical judgment of nurses was found to achieve inadequate predictive capacity when used alone, and should be used in combination with a validated scale.

  11. Predictive indices of empirical clinical diagnosis of malaria among under-five febrile children attending paediatric outpatient clinic

    Directory of Open Access Journals (Sweden)

    Hassan A Elechi

    2015-01-01

    Full Text Available Background: Malaria has remained an important public health problem in Nigeria with children under 5 years of age bearing the greatest burden. Accurate and prompt diagnosis of malaria is an important element in the fight against the scourge. Due to the several limitations of microscopy, diagnosis of malaria has continued to be made based on clinical ground against several World Health Organization (WHO recommendations. Thus, we aim to assess the performance of empirical clinical diagnosis among febrile children under 5 years of age in a busy pediatric outpatient clinic. Materials and Methods: The study was a cross-sectional study. Children aged <5 years with fever or 72 h history of fever were recruited. Children on antimalarial prophylaxis or on treatment for malaria were excluded. Relevant information was obtained from the caregiver and clinical note of the child using interviewer administered questionnaire. Two thick and two thin films were made, stained, and read for each recruited child. Data was analysed using SPSS version 16. Results: Of the 433 children studied, 98 (22.6% were empirically diagnosed as having malaria and antimalarial drug prescribed. Twenty-three (23.5% of these children were confirmed by microscopy to have malaria parasitemia, while 75 (76.5% were negative for malaria parasitemia. Empirical clinical diagnosis show poor predictive indices with sensitivity of 19.2%, specificity of 76.0%, positive predictive value of 23.5% and negative predictive value of 71%. Conclusion and Recommendations: Empirical clinical diagnosis of malaria among the under-five children with symptoms suggestive of acute malaria is highly not reliable and hence the need to strengthen parasitological diagnosis.

  12. Use of clinical movement screening tests to predict injury in sport.

    Science.gov (United States)

    Chimera, Nicole J; Warren, Meghan

    2016-04-18

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention, and prevention. This editorial will review the following clinical movement screening tests: Functional Movement Screen™, Star Excursion Balance Test, Y Balance Test, Drop Jump Screening Test, Landing Error Scoring System, and the Tuck Jump Analysis in regards to test administration, reliability, validity, factors that affect test performance, intervention programs, and usefulness for injury prediction. It is important to review the aforementioned factors for each of these clinical screening tests as this may help clinicians interpret the current body of literature. While each of these screening tests were developed by clinicians based on what appears to be clinical practice, this paper brings to light that this is a need for collaboration between clinicians and researchers to ensure validity of clinically meaningful tests so that they are used appropriately in future clinical practice. Further, this editorial may help to identify where the research is lacking and, thus, drive future research questions in regards to applicability and appropriateness of clinical movement screening tools. PMID:27114928

  13. Clinical decision rules for the application of computed tomography in children with minor head injury%儿童轻型头部外伤 CT 检查临床决策规则及应用现状

    Institute of Scientific and Technical Information of China (English)

    张靖; 丁华新

    2015-01-01

    Pediatric head injury is the leading cause of death and disability,about 40% to 60% of kids of head injury get a CT,and the majority are those with minor head injury,about 10% of these CT scans are positive.Clinical decision rules for pediatric head injury exist to identify children at risk of traumatic brain injury.Those of the highest quality are children's head injury algorithm for the prediction of important clinical events(CHALICE),Pediatric Emergency Care Applied Research Network(PECARN)and the Canadian as-sessment of tomography for childhood head injury(CATCH)clinical decision rules.This review aimed to systematically introduce primary clinical decision rules for children with minor head injury and compare them for diagnostic accuracy in detecting intracranial injury and injury requiring neurosurgery.%脑外伤是儿童主要创伤性疾病和致死、致残原因,儿童头部外伤大约40%~60%进行了头部 CT 检查,其中不到10%发生外伤性脑损伤。为减少儿童不必要的头部 CT 检查,国外研究主要有预测儿童头部损伤重要临床事件、儿科急救治疗应用研究网络和加拿大儿童头部外伤 X 线检查评估等临床决策规则,指导临床医生决策儿童轻型头部外伤后 CT 的应用,现就目前临床应用的主要临床决策规则进行综述。

  14. Clinical algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury.

    Science.gov (United States)

    Zörner, Björn; Blanckenhorn, Wolf U; Dietz, Volker; Curt, Armin

    2010-01-01

    The extent of ambulatory recovery after motor incomplete spinal cord injury (miSCI) differs considerably amongst affected persons. This makes individual outcome prediction difficult and leads to increased within-group variation in clinical trials. The aims of this study on subjects with miSCI were: (1) to rank the strongest single predictors and predictor combinations of later walking capacity; (2) to develop a reliable algorithm for clinical prediction; and (3) to identify subgroups with only limited recovery of walking function. Correlation and logistic regression analyses were performed on a dataset of 90 subjects with tetra- or paraparesis, recruited in a prospective European multicenter study. Eleven measures obtained in the subacute injury period, including clinical examination, tibial somatosensory evoked potentials (tSSEP), and demographic factors, were related to ambulatory outcome (WISCI II, 6minWT) 6 months after injury. The lower extremity motor score (LEMS) alone and in combination was identified as most predictive for later walking capacity in miSCI. Ambulatory outcome of subjects with tetraparesis was correctly predicted for 92% (WISCI II) or 100% (6minWT) of the cases when LEMS was combined with either tSSEP or the ASIA Impairment Scale, respectively. For individuals with paraparesis, prediction was less distinct, mainly due to low prediction rates for individuals with poor walking outcome. A clinical algorithm was generated that allowed for the identification of a subgroup composed of individuals with tetraparesis and poor ambulatory recovery. These data provide evidence that a combination of predictors enables a reliable prediction of walking function and early patient stratification for clinical trials in miSCI.

  15. Ensuring patient privacy in image data sharing for clinical research : Design and implementation of rules and infrastructure

    NARCIS (Netherlands)

    Aryanto, Kadek Yota Ernanda

    2016-01-01

    The protection of personal data has become an important yet challenging process when patient data are distributed among health institutions. Regulations and rules have been issued to govern the protection of the privacy of personal information. To conform to these rules and regulations, data de-iden

  16. 足踝关节骨折快速诊断规则的临床应用%Clinical application of Ottawa ankle rules in ankle fracture

    Institute of Scientific and Technical Information of China (English)

    殷军明; 蒲祖辉; 陈伟南; 雷益

    2013-01-01

    目的 研究成人足踝扭伤是否有骨折的快速诊断规则(OAR)的准确性,探讨足踝关节外伤X线摄片合理选择的必要性.方法 总结736例足踝扭伤患者(年龄18~82岁),其中足扭伤342例,踝扭伤394例.在X线摄片前,由当班医师或当班技师按OAR进行临床检查,验证该诊断试验的准确性.结果 在394例踝扭伤患者中有136例骨折,OAR漏诊4例,对踝部骨折的诊断敏感性为97.1%,特异性为49.6%,阳性预测值为50.4%,阴性预测值为97.0%.在342例足扭伤患者中有117例骨折,无漏诊,OAR 对足部骨折的诊断敏感性为100%,特异性为75.6%,阳性预测值为68.0%,阴性预测值为100%.结论 OAR对排除足踝骨折具有很高的准确性,对诊断足踝扭伤骨折具有极高的敏感性和适度的特异性;OAR的应用有望节约时间,并降低医疗费用和减少射线照射.%Objective To evaluate the accuracy of adult Ottawa ankle rules for screening possible ankle fracture,and the necessity of X-ray examination. Methods 736 cases with ankle sprain (age 18 - 82 years old) were studied. The clinical examination according to the OAR were proceed before X-ray examination by the physician or technician on duty. The accuracy of diagnostic tests were verified by comparing the results of X-ray imaging. Results 136 out of 394 cases with ankle sprain were proved to be fractures. 4 cases were missed by OAR. The sensitivity of OAR was 97. 1% ,specificity was 49. 6%,positive predictive was 50. 4% and negative predictive was 97. 0%. There were 117 fractures in 342 cases with midfoot sprain. Without missing diagnosis, the sensitivity of OAR was 100% , specificity was 75. 6%,positive predictive was 68. 0% and negative predictive was 100%. Conclusion The OAR have a high accurate instrument in excluding fractures of the ankle and midfoot. The rules have a high sensitivity (almost 100%) and modest specificity. Using the OAR holds promise for saving time and reducing both costs and

  17. GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes

    Directory of Open Access Journals (Sweden)

    Fine Howard A

    2010-07-01

    Full Text Available Abstract Background Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine. Results We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework. Conclusions GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision-making. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.

  18. Nomograms for the Prediction of Pathologic Stage of Clinically Localized Prostate Cancer in Korean Men

    OpenAIRE

    Song, Cheryn; Kang, Taejin; Ro, Jae Y.; Lee, Moo-Song; Kim, Choung-Soo; Ahn, Hanjong

    2005-01-01

    We analyzed the prostate cancer data of 317 Korean men with clinically localized prostate cancer who underwent radical prostatectomy at Asan Medical Center between June 1990 and November 2003 to construct nomograms predicting the pathologic stage of these tumors, and compared the outcome with preexisting nomograms. Multinomial log-linear regression was performed for the simultaneous prediction of organ-confined disease (OCD), extracapsular extension (ECE), seminal vesicle invasion (SVI) and l...

  19. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    OpenAIRE

    Jin-You Wang; Yao Zhu; Chao-Fu Wang; Shi-Lin Zhang; Bo Dai; Ding-Wei Ye

    2014-01-01

    Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and w...

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

    OpenAIRE

    Bahloul Mabrouk; Chaari Anis; Kallel Hatem; Abid Leila; Hamida Chokri Ben; Dammak Hassen; Rekik Noureddine; Mnif Jameleddine; Chelly Hedi; Bouaziz Mounir

    2010-01-01

    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...

  1. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    OpenAIRE

    Jinlin Cao; Ping Yuan; Luming Wang; Yiqing Wang; Honghai Ma; Xiaoshuai Yuan; Wang Lv; Jian Hu

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resamp...

  2. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    OpenAIRE

    Andrea Alberti; Maurizio Paciaroni; Valeria Caso; Michele Venti; Francesco Palmerini; Giancarlo Agnelli

    2008-01-01

    Andrea Alberti, Maurizio Paciaroni, Valeria Caso, Michele Venti, Francesco Palmerini, Giancarlo AgnelliStroke Unit and Division of Internal and Cardiovascular Medicine, University of Perugia, Perugia, ItalyBackground: Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke.Patie...

  3. Comparison of four clinical scores for the predicting lower limb deep venous thrombosis in Chinese patients

    Institute of Scientific and Technical Information of China (English)

    Li Zhua; Min Liu; Xiaojuan Guo; Jianguo Wang; Youmin Guo; Chen Wang; Hongxia Ma; Yulin Guo

    2008-01-01

    To evaluate Wells, Kahn, St.Andr é and Constans scores for the prediction of deep venous thrombosis in Chinese patients.Methods:One hundred and seventy-two patients, prospectively, blinded referred for evaluation with four clinical-score systems for suspected deep venous thrombosis, were examined by ultrasonography.Sensitivity, specificity, positive predictive value, nega- tive predictive value and receiver operation curves were calculated for four clinical scores.The difference between areas of the ROC curve for each of the scores was compared with others and reference line.Results:Forty-six of 172 patients had deep venous throm- bosis proven by sonography.The sensitivity, specificity, positive predictive value and negative predictive value for Wells score was 91.3%, 27.4% and 74.2% respectively, for Constans score; 95.7%, 34.9%, 34.9% and 95.7% respectively.Area under ROV curve of Constans with the reference line.Conclusion:Based on the results of our study, the sensitivity, negative prediction value and area under ROC Considering the aim of the clinical assessment, Constans score and Wells score are more efficient for Chinese hospitalized patients.

  4. A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection.

    LENUS (Irish Health Repository)

    Na, Xi

    2015-04-23

    Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI.

  5. Correlation of Ordered Cervical Spine X-rays in Emergency Department with NEXUS and Canadian C-Spine Rules; a Clinical Audit

    Directory of Open Access Journals (Sweden)

    Hamid Kariman

    2015-10-01

    Full Text Available Introduction: Evaluation of cervical spine injuries makes up a major part of trauma patient assessments. Based on the existing sources, more than 98% of the cervical spine X-rays show no positive findings. Therefore, the present clinical audit aimed to evaluate the correlation of ordered cervical spine X-rays in multiple trauma patients with NEXUS and Canadian c-spine clinical decision rules. Methods: The present clinical audit, evaluated the correlation of cervical spine imaging orders in multiple trauma patients presented to the emergency department, with NEXUS and Canadian c-spine rules. Initially, in a pilot study, the mentioned correlation was evaluated, and afterwards the results of this phase was analyzed. Since the correlation was low, an educational training was planned for all the physicians in charge. Finally, the calculated correlations for before and after training were compared using SPSS version 21. Results: Before and after training, cervical spine X-ray was ordered for 98 (62.82% and 85 (54.48% patients, respectively. Accuracy of cervical spine X-ray orders, based on the standard clinical decision rules, increased from 100 (64.1% cases before training, to 143 (91.7% cases after training (p < 0.001. Area under the receiver operating characteristic (ROC curve regarding the correlation also raised from 52 (95% confidence interval (CI: 43 – 61 to 92 (95% CI: 87 – 97. Conclusion: Teaching NEXUS and Canadian c-spine clinical decision rules plays a significant role in improving the correlation of cervical spine X-ray orders in multiple trauma patients with the existing standards.

  6. Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model

    Science.gov (United States)

    Hu, Scott B.; Wong, Deborah J. L.; Correa, Aditi; Li, Ning; Deng, Jane C.

    2016-01-01

    Introduction Clinical deterioration (ICU transfer and cardiac arrest) occurs during approximately 5–10% of hospital admissions. Existing prediction models have a high false positive rate, leading to multiple false alarms and alarm fatigue. We used routine vital signs and laboratory values obtained from the electronic medical record (EMR) along with a machine learning algorithm called a neural network to develop a prediction model that would increase the predictive accuracy and decrease false alarm rates. Design Retrospective cohort study. Setting The hematologic malignancy unit in an academic medical center in the United States. Patient Population Adult patients admitted to the hematologic malignancy unit from 2009 to 2010. Intervention None. Measurements and Main Results Vital signs and laboratory values were obtained from the electronic medical record system and then used as predictors (features). A neural network was used to build a model to predict clinical deterioration events (ICU transfer and cardiac arrest). The performance of the neural network model was compared to the VitalPac Early Warning Score (ViEWS). Five hundred sixty five consecutive total admissions were available with 43 admissions resulting in clinical deterioration. Using simulation, the neural network outperformed the ViEWS model with a positive predictive value of 82% compared to 24%, respectively. Conclusion We developed and tested a neural network-based prediction model for clinical deterioration in patients hospitalized in the hematologic malignancy unit. Our neural network model outperformed an existing model, substantially increasing the positive predictive value, allowing the clinician to be confident in the alarm raised. This system can be readily implemented in a real-time fashion in existing EMR systems. PMID:27532679

  7. Predictive Validity of DSM-IV Oppositional Defiant and Conduct Disorders in Clinically Referred Preschoolers

    Science.gov (United States)

    Keenan, Kate; Boeldt, Debra; Chen, Diane; Coyne, Claire; Donald, Radiah; Duax, Jeanne; Hart, Katherine; Perrott, Jennifer; Strickland, Jennifer; Danis, Barbara; Hill, Carri; Davis, Shante; Kampani, Smita; Humphries, Marisha

    2011-01-01

    Background: Diagnostic validity of oppositional defiant and conduct disorders (ODD and CD) for preschoolers has been questioned based on concerns regarding the ability to differentiate normative, transient disruptive behavior from clinical symptoms. Data on concurrent validity have accumulated, but predictive validity is limited. Predictive…

  8. Predicting dynamic knee joint load with clinical measures in people with medial knee osteoarthritis.

    Science.gov (United States)

    Hunt, Michael A; Bennell, Kim L

    2011-08-01

    Knee joint loading, as measured by the knee adduction moment (KAM), has been implicated in the pathogenesis of knee osteoarthritis (OA). Given that the KAM can only currently be accurately measured in the laboratory setting with sophisticated and expensive equipment, its utility in the clinical setting is limited. This study aimed to determine the ability of a combination of four clinical measures to predict KAM values. Three-dimensional motion analysis was used to calculate the peak KAM at a self-selected walking speed in 47 consecutive individuals with medial compartment knee OA and varus malalignment. Clinical predictors included: body mass; tibial angle measured using an inclinometer; walking speed; and visually observed trunk lean toward the affected limb during the stance phase of walking. Multiple linear regression was performed to predict KAM magnitudes using the four clinical measures. A regression model including body mass (41% explained variance), tibial angle (17% explained variance), and walking speed (9% explained variance) explained a total of 67% of variance in the peak KAM. Our study demonstrates that a set of measures easily obtained in the clinical setting (body mass, tibial alignment, and walking speed) can help predict the KAM in people with medial knee OA. Identifying those patients who are more likely to experience high medial knee loads could assist clinicians in deciding whether load-modifying interventions may be appropriate for patients, whilst repeated assessment of joint load could provide a mechanism to monitor disease progression or success of treatment.

  9. Linguistic Valued Association Rules

    Institute of Scientific and Technical Information of China (English)

    LU Jian-jiang; QIAN Zuo-ping

    2002-01-01

    Association rules discovering and prediction with data mining method are two topics in the field of information processing. In this paper, the records in database are divided into many linguistic values expressed with normal fuzzy numbers by fuzzy c-means algorithm, and a series of linguistic valued association rules are generated. Then the records in database are mapped onto the linguistic values according to largest subject principle, and the support and confidence definitions of linguistic valued association rules are also provided. The discovering and prediction methods of the linguistic valued association rules are discussed through a weather example last.

  10. Clinical and Radiographic Factors Predicting Hearing Preservation Rates in Large Vestibular Schwannomas.

    Science.gov (United States)

    Mendelsohn, Daniel; Westerberg, Brian D; Dong, Charles; Akagami, Ryojo

    2016-06-01

    Objectives Postoperative hearing preservation rates for patients with large vestibular schwannomas range from 0 to 43%. The clinical and radiographic factors predicting hearing preservation in smaller vestibular schwannomas are well described; however, their importance in larger tumors is unclear. We investigated factors predicting hearing preservation in large vestibular schwannomas. Design Retrospective review. Setting Quaternary care academic center. Participants A total of 85 patients with unilateral vestibular schwannomas > 3 cm underwent retrosigmoid resections. Main Outcomes Measures Preoperative and postoperative serviceable hearing rates. Methods Clinical and radiographic data including preoperative and postoperative audiograms, preoperative symptoms, magnetic resonance imaging features, and postoperative facial weakness were analyzed. Results Hearing was preserved in 41% of patients (17 of 42) with preoperative serviceable hearing. Hypertension and diabetes increased the likelihood of preoperative hearing loss. Preoperative tinnitus predicted a lower likelihood of hearing preservation. No radiographic factors predicted hearing preservation; however, larger tumor size, smaller fourth ventricular width, and the presence of a cerebrospinal fluid cleft surrounding the tumor predicted postoperative facial weakness. Conclusion Systemic comorbidities may influence hearing loss preoperatively in patients with large vestibular schwannomas. The absence of tinnitus may reflect hearing reserve and propensity for hearing preservation. Preoperative radiographic features did not predict hearing preservation despite some associations with postoperative facial weakness. PMID:27175312

  11. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. Methods: We describe a case study of 423 patients treated by Centerstone within Tennessee and Indiana in which we utilized electronic health record data to generate predictive algorithms of individual patient treatment response. Multiple models were constructed using predictor variables derived from clinical, financial and geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved and in 99 there was no change in clinical condition. Based on modeling of various clinical indicators at baseline, the high...

  12. Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model

    Science.gov (United States)

    Yamamoto, Kimiyo N.; Ishii, Masatsugu; Inoue, Yoshihiro; Hirokawa, Fumitoshi; MacArthur, Ben D.; Nakamura, Akira; Haeno, Hiroshi; Uchiyama, Kazuhisa

    2016-01-01

    Although the capacity of the liver to recover its size after resection has enabled extensive liver resection, post-hepatectomy liver failure remains one of the most lethal complications of liver resection. Therefore, it is clinically important to discover reliable predictive factors after resection. In this study, we established a novel mathematical framework which described post-hepatectomy liver regeneration in each patient by incorporating quantitative clinical data. Using the model fitting to the liver volumes in series of computed tomography of 123 patients, we estimated liver regeneration rates. From the estimation, we found patients were divided into two groups: i) patients restored the liver to its original size (Group 1, n = 99); and ii) patients experienced a significant reduction in size (Group 2, n = 24). From discriminant analysis in 103 patients with full clinical variables, the prognosis of patients in terms of liver recovery was successfully predicted in 85–90% of patients. We further validated the accuracy of our model prediction using a validation cohort (prediction = 84–87%, n = 39). Our interdisciplinary approach provides qualitative and quantitative insights into the dynamics of liver regeneration. A key strength is to provide better prediction in patients who had been judged as acceptable for resection by current pragmatic criteria. PMID:27694914

  13. Islet Oxygen Consumption Rate (OCR Dose Predicts Insulin Independence in Clinical Islet Autotransplantation.

    Directory of Open Access Journals (Sweden)

    Klearchos K Papas

    Full Text Available Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR in predicting clinical islet autotransplant (IAT insulin independence (II. IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding factors such as immune rejection and immunosuppressant toxicity.Membrane integrity staining (FDA/PI, OCR normalized to DNA (OCR/DNA, islet equivalent (IE and OCR (viable IE normalized to recipient body weight (IE dose and OCR dose, and OCR/DNA normalized to islet size index (ISI were used to characterize autoislet preparations (n = 35. Correlation between pre-IAT islet product characteristics and II was determined using receiver operating characteristic analysis.Preparations that resulted in II had significantly higher OCR dose and IE dose (p<0.001. These islet characterization methods were highly correlated with II at 6-12 months post-IAT (area-under-the-curve (AUC = 0.94 for IE dose and 0.96 for OCR dose. FDA/PI (AUC = 0.49 and OCR/DNA (AUC = 0.58 did not correlate with II. OCR/DNA/ISI may have some utility in predicting outcome (AUC = 0.72.Commonly used assays to determine whether a clinical islet preparation is of high quality prior to transplantation are greatly lacking in sensitivity and specificity. While IE dose is highly predictive, it does not take into account islet cell quality. OCR dose, which takes into consideration both islet cell quality and quantity, may enable a more accurate and prospective evaluation of clinical islet preparations.

  14. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

    Science.gov (United States)

    De Buck, Stefan S; Sinha, Vikash K; Fenu, Luca A; Nijsen, Marjoleen J; Mackie, Claire E; Gilissen, Ron A H J

    2007-10-01

    The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics. PMID:17620347

  15. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures.

    Science.gov (United States)

    Yu, Kun-Hsing; Levine, Douglas A; Zhang, Hui; Chan, Daniel W; Zhang, Zhen; Snyder, Michael

    2016-08-01

    Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers. PMID:27312948

  16. Predicting reoffense in pedophilic child molesters by clinical diagnoses and risk assessment.

    Science.gov (United States)

    Eher, Reinhard; Olver, Mark E; Heurix, Isabelle; Schilling, Frank; Rettenberger, Martin

    2015-12-01

    A Diagnostic and Statistical Manual of Mental Disorders (DSM)-based diagnosis of pedophilia has so far failed to predict sexual reoffense in convicted child molesters, probably because of its broad and unspecific conceptualization. In this study, therefore, we investigated the prognostic value of the subtype exclusive pedophilia and a series of customary risk assessment instruments (SSPI, Static-99, Stable-2007, VRS:SO) and the PCL-R in a sample of prison released pedophilic sexual offenders. First, we examined the convergent validity of risk assessment instruments (N = 261). Then, we calculated the predictive accuracy of the measures and diagnosis for sexual recidivism by ROC analyses and subsequent Cox regression (N = 189). Also, predictive values with more clinical immediacy were calculated (sensitivity, specificity, PPV and NPV). The VRS:SO, the SSPI, and the Static-99 significantly predicted sexual recidivism, as did a diagnosis of exclusive pedophilia. Also, the VRS:SO predicted sexual reoffense significantly better than the Stable-2007, the Static-99/Stable-2007 combined score, and the PCL-R. When used combined, only the VRS:SO and a diagnosis of exclusive pedophilia added incremental validity to each other. Our findings support that the clinical diagnosis of an exclusive pedophilia based on DSM criteria and VRS:SO defined risk factors can reliably discriminate higher from lower risk offenders, even within the select subgroup of pedophilic child molesters. PMID:26146817

  17. A novel neural-inspired learning algorithm with application to clinical risk prediction.

    Science.gov (United States)

    Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

    2015-04-01

    Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. PMID:25576352

  18. Prediction of Clinically Relevant Safety Signals of Nephrotoxicity through Plasma Metabolite Profiling

    Directory of Open Access Journals (Sweden)

    W. B. Mattes

    2013-01-01

    Full Text Available Addressing safety concerns such as drug-induced kidney injury (DIKI early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC. The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound’s well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity, not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

  19. Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies.

    Science.gov (United States)

    Glassman, Patrick M; Balthasar, Joseph P

    2016-08-01

    Accurate prediction of the clinical pharmacokinetics of new therapeutic entities facilitates decision making during drug discovery, and increases the probability of success for early clinical trials. Standard strategies employed for predicting the pharmacokinetics of small-molecule drugs (e.g., allometric scaling) are often not useful for predicting the disposition monoclonal antibodies (mAbs), as mAbs frequently demonstrate species-specific non-linear pharmacokinetics that is related to mAb-target binding (i.e., target-mediated drug disposition, TMDD). The saturable kinetics of TMDD are known to be influenced by a variety of factors, including the sites of target expression (which determines the accessibility of target to mAb), the extent of target expression, the rate of target turnover, and the fate of mAb-target complexes. In most cases, quantitative information on the determinants of TMDD is not available during early phases of drug discovery, and this has complicated attempts to employ mechanistic mathematical models to predict the clinical pharmacokinetics of mAbs. In this report, we introduce a simple strategy, employing physiologically-based modeling, to predict mAb disposition in humans. The approach employs estimates of inter-antibody variability in rate processes of extravasation in tissues and fluid-phase endocytosis, estimates for target concentrations in tissues derived through use of categorical immunohistochemical scores, and in vitro measures of the turnover of target and target-mAb complexes. Monte Carlo simulations were performed for four mAbs (cetuximab, figitumumab, dalotuzumab, trastuzumab) directed against three targets (epidermal growth factor receptor, insulin-like growth factor receptor 1, human epidermal growth factor receptor 2). The proposed modeling strategy was able to predict well the pharmacokinetics of cetuximab, dalotuzumab, and trastuzumab at a range of doses, but trended towards underprediction of figitumumab concentrations

  20. External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

    Science.gov (United States)

    Hickey, Graeme L; Blackstone, Eugene H

    2016-08-01

    Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting.

  1. Predictive Power of the Baseline QRS Complex Duration for Clinical Response to Cardiac Resynchronisation Therapy

    Directory of Open Access Journals (Sweden)

    Ali Kazemisaeid

    2011-02-01

    Full Text Available Background: Determination of predictors of response to cardiac resynchronisation therapy (CRT in patients with moderate to severe heart failure accompanied by a ventricular dyssynchrony can play a major role in improving candidate selection for CRT.Objectives: We evaluated whether the baseline QRS duration could be used to discriminate responders from non-responders to CRT.Methods: Eighty three consecutive patients with moderate to severe heart failure and with successful implantation of a CRT device at our centre were included in the study. QRS durations were measured on 12-lead surface electrocardiogram before and 6 months after implantation of the CRT device, using the widest QRS complex in leads II, V1 and V6. Clinical response to CRT was defined as an improvement of ≥1 grade in NYHA class.Results: Optimal cut-off value to discriminate baseline QRS duration for predicting clinical response to CRT was identified at 152 ms, yielding a sensitivity of 73.3%, a specificity of 56.5% as well as positive and negative predictive values of 81.5% and 44.8%, respectively. The discriminatory pow- er of the baseline QRS duration for response to CRT assessed by the ROC curve was 0.6402 (95% CI: 0.4976 – 0.7829. Baseline QRS duration ≥ 152 ms could effectively predict clinical response to CRT after adjusting for covariates (OR = 3.743, p = 0.017.Conclusion: Baseline QRS duration can effectively predict clinical response to CRT and optimal cut-off value to discriminate baseline QRS duration for response to CRT is 152 ms.

  2. A Clinical Scoring System to Predict the Development of Bronchopulmonary Dysplasia

    OpenAIRE

    Gürsoy, Tuğba; Hayran, Mutlu; Derin, Hatice; Ovalı, Fahri

    2015-01-01

    ObjectiveThis study aims to develop a scoring system for the prediction of bronchopulmonary dysplasia (BPD). MethodsMedical records of 652 infants whose gestational age and birth weight were below 32 weeks and 1,500g, respectively, and who survived beyond 28th postnatal day were reviewed retrospectively. Logistic regression methods were used to determine the clinical and demographic risk factors within the first 72 hours of life associated with BPD, as well as the weights of these factors on ...

  3. Fusion of clinical and stochastic finite element data for hip fracture risk prediction.

    Science.gov (United States)

    Jiang, Peng; Missoum, Samy; Chen, Zhao

    2015-11-26

    Hip fracture affects more than 250,000 people in the US and 1.6 million worldwide per year. With an aging population, the development of reliable fracture risk models is therefore of prime importance. Due to the complexity of the hip fracture phenomenon, the use of clinical data only, as it is done traditionally, might not be sufficient to ensure an accurate and robust hip fracture prediction model. In order to increase the predictive ability of the risk model, the authors propose to supplement the clinical data with computational data from finite element models. The fusion of the two types of data is performed using deterministic and stochastic computational data. In the latter case, uncertainties in loading and material properties of the femur are accounted for and propagated through the finite element model. The predictive capability of a support vector machine (SVM) risk model constructed by combining clinical and finite element data was assessed using a Women׳s Health Initiative (WHI) dataset. The dataset includes common factors such as age and BMD as well as geometric factors obtained from DXA imaging. The fusion of computational and clinical data systematically leads to an increase in predictive ability of the SVM risk model as measured by the AUC metric. It is concluded that the largest gains in AUC are obtained by the stochastic approach. This gain decreases as the dimensionality of the problem increases: a 5.3% AUC improvement was achieved for a 9 dimensional problem involving geometric factors and weight while a 1.3% increase was obtained for a 20 dimensional case including geometric and conventional factors. PMID:26482733

  4. Evaluating clinical abdominal scoring system in predict- ing the necessity of laparotomy in blunt abdominal trauma

    Directory of Open Access Journals (Sweden)

    Erfantalab-Avini Peyman

    2011-06-01

    Full Text Available 【Abstract】 Objectives: Trauma is among the lead- ing causes of death. Medical management of blunt abdomi- nal trauma (BAT relies on judging patients for whom lap- arotomy is mandatory. This study aimed to determine BAT patients’ signs, as well as paraclinical data, and to clarify the accuracy, sensitivity, specificity, positive and negative predictive value of clinical abdominal scoring system (CASS, a new scoring system based on clinical signs, in predicting whether a BAT patient needs laparotomy or not. Methods: Totally 400 patients suspected of BAT that arrived at the emergency department of two university hos- pitals in Tehran from March 20, 2007 to March 19, 2009 were included in this study. They were evaluated for age, sex, type of trauma, systolic blood pressure, Glasgow coma scale (GCS, pulse rate, time of presentation after trauma, abdomi- nal clinical findings, respiratory rate, temperature, hemoglo- bin (Hb concentration, focused abdominal sonography in trauma (FAST and CASS. Results: Our measurements showed that CASS had an accuracy of 94%, sensitivity of 100%, specificity of 88%, positive predictive value of 90% and negative predictive value of 100% in determining the necessity of laparotomy in BAT patients. Moreover, in our analysis, systolic blood pressure, GCS, pulse rate, Hb concentration, time of presen- tation after trauma, abdominal clinical findings and FAST were also shown to be helpful in confirming the need for laparotomy (P<0.05. Conclusion: CASS is a promising scoring system in rapid detection of the need for laparotomy as well as in minimizing auxiliary expense for further evaluation in BAT patients, thus to promote the cost-benefit ratio and accu- racy of diagnosis. Key words: Abdominal injuries; Laparotomy; Patients; Wounds, nonpenetrating

  5. Spatial Rule-Based Assessment of Habitat Potential to Predict Impact of Land Use Changes on Biodiversity at Municipal Scale

    Science.gov (United States)

    Scolozzi, Rocco; Geneletti, Davide

    2011-03-01

    In human dominated landscapes, ecosystems are under increasing pressures caused by urbanization and infrastructure development. In Alpine valleys remnant natural areas are increasingly affected by habitat fragmentation and loss. In these contexts, there is a growing risk of local extinction for wildlife populations; hence assessing the consequences on biodiversity of proposed land use changes is extremely important. The article presents a methodology to assess the impacts of land use changes on target species at a local scale. The approach relies on the application of ecological profiles of target species for habitat potential (HP) assessment, using high resolution GIS-data within a multiple level framework. The HP, in this framework, is based on a species-specific assessment of the suitability of a site, as well of surrounding areas. This assessment is performed through spatial rules, structured as sets of queries on landscape objects. We show that by considering spatial dependencies in habitat assessment it is possible to perform better quantification of impacts of local-level land use changes on habitats.

  6. Idiopathic normal pressure hydrocephalus: diagnostic and predictive value of clinical testing, lumbar drainage, and CSF dynamics.

    Science.gov (United States)

    Mahr, Cynthia V; Dengl, Markus; Nestler, Ulf; Reiss-Zimmermann, Martin; Eichner, Gerrit; Preuß, Matthias; Meixensberger, Jürgen

    2016-09-01

    OBJECTIVE The aim of the study was to analyze the diagnostic and predictive values of clinical tests, CSF dynamics, and intracranial pulsatility tests, compared with external lumbar drainage (ELD), for shunt response in patients with idiopathic normal pressure hydrocephalus (iNPH). METHODS Sixty-eight consecutive patients with suspected iNPH were prospectively evaluated. Preoperative assessment included clinical tests, overnight intracranial pressure (ICP) monitoring, lumbar infusion test (LIFT), and ELD for 24-72 hours. Simple and multiple linear regression analyses were conducted to identify predictive parameters concerning the outcome after shunt therapy. RESULTS Positive response to ELD correctly predicted improvement after CSF diversion in 87.9% of the patients. A Mini-Mental State Examination (MMSE) value below 21 was associated with nonresponse after shunt insertion (specificity 93%, sensitivity 67%). Resistance to outflow of CSF (ROut) > 12 mm Hg/ml/min was false negative in 21% of patients. Intracranial pulsatility parameters yielded different results in various parameters (correlation coefficient between pulse amplitude and ICP, slow wave amplitude, and mean ICP) but did not correlate to outcome. In multiple linear regression analysis, a calculation of presurgical MMSE versus the value after ELD, ROut, and ICP amplitude quotient during LIFT was significantly associated with outcome (p = 0.04). CONCLUSIONS Despite a multitude of invasive tests, presurgical clinical testing and response to ELD yielded the best prediction for improvement of symptoms following surgery. The complication rate of invasive testing was 5.4%. Multiple and simple linear regression analyses indicated that outcome can only be predicted by a combination of parameters, in accordance with a multifactorial pathogenesis of iNPH. PMID:26824377

  7. Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data

    KAUST Repository

    Xie, Qing

    2016-02-23

    Alzheimer\\'s Disease (AD) is currently attracting much attention in elders\\' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD\\'s progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients\\' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer\\'s Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.

  8. Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

    Energy Technology Data Exchange (ETDEWEB)

    Fagedet, Dorothee, E-mail: DFagedet@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de medecine interne, Pole Pluridisciplinaire de Medecine (France); Thony, Frederic, E-mail: FThony@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Timsit, Jean-Francois, E-mail: JFTimsit@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de reanimation, Pole Medecine Aiguee Communautaire (France); Rodiere, Mathieu, E-mail: MRodiere@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Monnin-Bares, Valerie, E-mail: v-monnin@chu-montpellier.fr [CHRU Arnaud de Villeneuve, Imagerie Medicale Thoracique Cardiovasculaire (France); Ferretti, Gilbert R., E-mail: GFerretti@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Vesin, Aurelien; Moro-Sibilot, Denis, E-mail: DMoro.pneumo@chu-grenoble.fr [University Grenoble 1 e Albert Bonniot Institute, Inserm U823 (France)

    2013-02-15

    To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable rate of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.

  9. PREDICTION OF CLINICAL EFFICIENCY OF SIMVASTATIN TREATMENT IN PATIENTS WITH RHEUMATOID ARTHRITIS

    Directory of Open Access Journals (Sweden)

    I. V. Shirinsky

    2009-01-01

    Full Text Available Abstract. Treatment with statins results in reduction of disease activity in one-third of patients with rheumatoid arthritis (RA. The aim of this study was to assess some factors that may predict clinical response to simvastatin therapy before starting the treatment. We evaluated an association of treatment efficacy with baseline clinical and laboratory parameters including disease activity measures, cytokine profiles in sera and culture supernatants of peripheral blood mononuclear cells. Thirty-three patients with active RA were enrolled in the study. The patients were treated with simvastatin at 40 mg/day for three months. Eleven patients (33% developed a moderate response according to EULAR criteria. It was shown that serum IL-10 concentrations was higher in responders, and positively correlated with clinical response to simvastatin. We carried out a receiver operating characteristic curve (ROC analysis in order to assess the accuracy of serum IL-10 for the predicting of EULAR response development. The cut-off threshold corresponding to the highest sensitivity (89% and specificity (62% was a value of 6.5 pg/ml. In conclusion, the performance characteristics of serum IL-10 measurement proved to be good enough to predict EULAR response to simvastatin therapy in RA patients.

  10. Rules for the certification of good practices in clinical laboratories. No regulation. 3-2009. Good Laboratory Practice

    International Nuclear Information System (INIS)

    Regulation for Certification of Good Practices in clinical laboratories, hereinafter Regulation establishes the methodology and procedures for clinical laboratories to demonstrate their state of compliance with good practices, according to Regulation 3-2009, and that the CECMED can verify.

  11. Development of an algorithm to predict comfort of wheelchair fit based on clinical measures.

    Science.gov (United States)

    Kon, Keisuke; Hayakawa, Yasuyuki; Shimizu, Shingo; Nosaka, Toshiya; Tsuruga, Takeshi; Matsubara, Hiroyuki; Nomura, Tomohiro; Murahara, Shin; Haruna, Hirokazu; Ino, Takumi; Inagaki, Jun; Kobayashi, Toshiki

    2015-09-01

    [Purpose] The purpose of this study was to develop an algorithm to predict the comfort of a subject seated in a wheelchair, based on common clinical measurements and without depending on verbal communication. [Subjects] Twenty healthy males (mean age: 21.5 ± 2 years; height: 171 ± 4.3 cm; weight: 56 ± 12.3 kg) participated in this study. [Methods] Each experimental session lasted for 60 min. The clinical measurements were obtained under 4 conditions (good posture, with and without a cushion; bad posture, with and without a cushion). Multiple regression analysis was performed to determine the relationship between a visual analogue scale and exercise physiology parameters (respiratory and metabolism), autonomic nervous parameters (heart rate, blood pressure, and salivary amylase level), and 3D-coordinate posture parameters (good or bad posture). [Results] For the equation (algorithm) to predict the visual analogue scale score, the adjusted multiple correlation coefficient was 0.72, the residual standard deviation was 1.2, and the prediction error was 12%. [Conclusion] The algorithm developed in this study could predict the comfort of healthy male seated in a wheelchair with 72% accuracy. PMID:26504299

  12. Microsatellite Instability Predicts Clinical Outcome in Radiation-Treated Endometrioid Endometrial Cancer

    International Nuclear Information System (INIS)

    Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival, disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.

  13. A few remarks on the rules about personal data protection when conducting clinical trials in Italy, also from abroad.

    Science.gov (United States)

    Petrini, Carlo

    2009-01-01

    The Italian Authority for the Protection of Personal Data has definitively adopted the Guidelines for data processing within the framework of clinical drug trials. The Guidelines are addressed to sponsors and other subjects who intervene, also from abroad, in clinical trials. The document provides practical instructions for the processing of personal data of human subject participating in clinical trials.

  14. Clinical picture and risk prediction of short-term mortality in cardiogenic shock

    DEFF Research Database (Denmark)

    Harjola, Veli-Pekka; Lassus, Johan; Sionis, Alessandro;

    2015-01-01

    AIMS: The aim of this study was to investigate the clinical picture and outcome of cardiogenic shock and to develop a risk prediction score for short-term mortality. METHODS AND RESULTS: The CardShock study was a multicentre, prospective, observational study conducted between 2010 and 2012....... Patients with either acute coronary syndrome (ACS) or non-ACS aetiologies were enrolled within 6 h from detection of cardiogenic shock defined as severe hypotension with clinical signs of hypoperfusion and/or serum lactate >2 mmol/L despite fluid resuscitation (n = 219, mean age 67, 74% men). Data...... on clinical presentation, management, and biochemical variables were compared between different aetiologies of shock. Systolic blood pressure was on average 78 mmHg (standard deviation 14 mmHg) and mean arterial pressure 57 (11) mmHg. The most common cause (81%) was ACS (68% ST-elevation myocardial infarction...

  15. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

    Science.gov (United States)

    Benson, M

    2016-03-01

    Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide

  16. Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

    Directory of Open Access Journals (Sweden)

    Pereira J.C.R.

    2004-01-01

    Full Text Available The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA and by fuzzy max-min compositions (fuzzy, and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

  17. Acute pyelonephritis: role of enhanced CT scan in the prediction of clinical outcome

    Energy Technology Data Exchange (ETDEWEB)

    Jo, Byung June; Kim, Ki Whang; Yu, Jeong Sik; Kim, Jai Keun; Yoon, Sang Wook; Ha, Sung Kyu; Park, Chong Hoon [Yonsei Univ. College of Medicine, Seoul (Korea, Republic of)

    1997-04-01

    To correlate the CT findings of acute pyelonephritis with its outcome and with clinical data. Thirty five contrast enhanced CT scans in patients diagnosed as suffering from acute pyelonephritis were retrospectively analyzed. Findings based on the morphology of perfusion defect in the renal parenchyma were classified as normal, focal wedge, multifocal wedge, focal mass, or mixed form composed of wedge and mass. These findings were correlated with clinical data such as degree of fever, leukocytosis, the period after antibiotic treatment during which fever was reduced, and the presence of pyuria in each group Analysis was then performed. Perfusion defects were seen in 23 of 35 cases, and their morphology was classified as follow; focal wedge (n=2), multifocal wedge (n=8), focal mass (n=4), and mixed form (n=9). Twelve cases (34.3%) showed no perfusion defect. The duration of fever was significantly prolonged in patients with focal mass form (p < .05). There was no significant correlation between the morphology of perfusion defect, bilaterality, and other clinical factors. The present study shows that the clinical course of the focal mass form of perfusion defect, as seen on CT, is different from that of other types. CT could be effective in predicting clinical progress and the outcome of treatment in cases of acute pyelonephritis.

  18. Magnetic resonance imaging and morphometric histologic analysis of prostate tissue composition in predicting the clinical outcome of terazosin therapy in benign prostatic hyperplasia

    Energy Technology Data Exchange (ETDEWEB)

    Isen, K. [Karaelmas Univ., Zonguldak (Turkey). School of Medicine; Sinik, Z.; Alkibay, T.; Sezer, C.; Soezen, S.; Atilla, S.; Ataoglu, O.; Isik, S.

    2001-02-01

    The purpose of this study was to determine whether magnetic resonance imaging (MRI) or quantitative color-imaged morphometric analysis (MA) of the prostate gland are related to the clinical response to terazosin. Thirty-six male patients with symptomatic benign prostatic hyperplasia (BPH) with a serum prostate-specific antigen level of 4-10 ng/mL underwent MRI with body coil, transrectal prostate unltrasonography and biopsy prior to terazosin therapy. For MRI-determined stromal and non-stromal BPH, the ratio of the signal intensity of the inner gland to the obturator internus muscle was evaluated. Histologic sections were stained with hematoxylin and eosin. The MA of the specimens was performed by Samba 2000. Results of the two techniques were interpreted according to the terazosin therapy results. The mean stromal percentage was 60.5{+-}18.0%. No statistically significant relationship was found between the clinical outcome of terazosin and the MRI findings. The MA results showed a significant relationship between the percentage of stroma and the percent change of the peak urinary flow rate, but not with the percent change of the international prostate symptom score after terazosin therapy (P<0.05). Magnetic resonance imaging alone is not sufficient in predicting the response to terazosin therapy. Morphometric analysis of BPH tissue composition can be used in predicting the clinical outcome of terazosin therapy but it is suitable only in patients for whom prostatic biopsy is necessary in order to rule out prostate cancer. (author)

  19. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    Science.gov (United States)

    Cao, Jinlin; Yuan, Ping; Wang, Luming; Wang, Yiqing; Ma, Honghai; Yuan, Xiaoshuai; Lv, Wang; Hu, Jian

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations. PMID:27215834

  20. Predicting clinically unrecognized coronary artery disease: use of two- dimensional echocardiography

    Directory of Open Access Journals (Sweden)

    Nagueh Sherif F

    2009-03-01

    Full Text Available Abstract Background 2-D Echo is often performed in patients without history of coronary artery disease (CAD. We sought to determine echo features predictive of CAD. Methods 2-D Echo of 328 patients without known CAD performed within one year prior to stress myocardial SPECT and angiography were reviewed. Echo features examined were left ventricular and atrial enlargement, LV hypertrophy, wall motion abnormality (WMA, LV ejection fraction (EF 15% LV perfusion defect or multivessel distribution. Severe coronary artery stenosis (CAS was defined as left main, 3 VD or 2VD involving proximal LAD. Results The mean age was 62 ± 13 years, 59% men, 29% diabetic (DM and 148 (45% had > 2 risk factors. Pharmacologic stress was performed in 109 patients (33%. MPA was present in 200 pts (60% of which, 137 were high risk. CAS was present in 166 pts (51%, 75 were severe. Of 87 patients with WMA, 83% had MPA and 78% had CAS. Multivariate analysis identified age >65, male, inability to exercise, DM, WMA, MAC and AS as independent predictors of MPA and CAS. Independent predictors of high risk MPA and severe CAS were age, DM, inability to exercise and WMA. 2-D echo findings offered incremental value over clinical information in predicting CAD by angiography. (Chi square: 360 vs. 320 p = 0.02. Conclusion 2-D Echo was valuable in predicting presence of physiological and anatomical CAD in addition to clinical information.

  1. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    Directory of Open Access Journals (Sweden)

    Andrea Alberti

    2008-06-01

    Full Text Available Andrea Alberti, Maurizio Paciaroni, Valeria Caso, Michele Venti, Francesco Palmerini, Giancarlo AgnelliStroke Unit and Division of Internal and Cardiovascular Medicine, University of Perugia, Perugia, ItalyBackground: Early seizure (ES may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke.Patients and methods: A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic, admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded.Results: Thirty-one patients (4.8% had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability. After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003.Conclusion: ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke.Keywords: seizures, stroke, cortical involvement, hemorrhagic transformation

  2. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    Science.gov (United States)

    Alberti, Andrea; Paciaroni, Maurizio; Caso, Valeria; Venti, Michele; Palmerini, Francesco; Agnelli, Giancarlo

    2008-01-01

    Background Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke. Patients and methods A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic), admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded. Results Thirty-one patients (4.8%) had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability). After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003). Conclusion ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke. PMID:18827922

  3. Biomarkers for predicting clinical response to immunosuppressive therapy in aplastic anemia.

    Science.gov (United States)

    Narita, Atsushi; Kojima, Seiji

    2016-08-01

    The decision to select hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST) as initial therapy in acquired aplastic anemia (AA) is currently based on patient age and the availability of a human leukocyte antigen (HLA)-matched donor. Although IST is a promising treatment option, the ability to predict its long-term outcomes remains poor due to refractoriness, relapses, and the risk of clonal evolution. Several predictive biomarkers for response to IST have been posited, including age, gender, pre-treatment blood cell counts, cytokines, gene mutations, paroxysmal nocturnal hemoglobinuria (PNH), and telomere length (TL). While previous studies have provided substantial biological insights into the utility of IST, the prognostic power of the reported biomarkers is currently insufficient to contribute to clinical decision making. Recently, a large retrospective analysis proposed the combination of minor PNH clones and TL as an efficient predictor of IST response. Identification of a reliable predictor would provide a useful tool for determining the most appropriate treatment choice for AA patients, including up-front HSCT from HLA-matched unrelated donor. The present review summarizes studies evaluating the utility of biomarkers in predicting the clinical response to IST of patients with AA, and provides a baseline for prospective studies aimed at validating previously reported biomarkers. PMID:27091471

  4. The clinical factors′ prediction of increased intradialytic qt dispersion on the electrocardiograms of chronic hemodialysis patients

    Directory of Open Access Journals (Sweden)

    Dina Oktavia

    2013-01-01

    Full Text Available Ventricular arrhythmias and sudden death are common in patients on maintenance hemodialysis (HD. The increase in QT dispersion (QTd on the electrocardiogram (ECG reflects increased tendency for ventricular repolarization that predisposes to arrhythmias. The purpose of the study was to identify the clinical factors that may predict the increased intradialytic QTd and to assess differences in QTd before and after HD. Each of 61 chronic HD patients underwent 12-lead ECG and blood pressure (BP measurement before and every 1 h during a single HD session. The QT intervals were corrected for heart rate using Bazett′s formula. Intradialytic QTd increased in 30 (49% patients. There was no correlation between the increased QTd and the clinical factors including hypertension, pulse pressure, intradialytic hypotension, left ventricular hypertrophy, old myocardial infarct, diabetes mellitus, and nutritional status. The means of QT interval and QTd increased after HD session (from 382 ± 29 to 444 ± 26 ms, P <0.05; and from 74 ± 21 to 114 ± 53 ms, respectively, P <0.05. We conclude that the increased intradialytic QTd could not be predicted by any of the clinical factors evaluated in this study. There was significant difference in the means of QTd before and after HD session.

  5. A Panel of Cancer Testis Antigens and Clinical Risk Factors to Predict Metastasis in Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Ramyar Molania

    2014-01-01

    Full Text Available Colorectal cancer (CRC is the third common carcinoma with a high rate of mortality worldwide and several studies have investigated some molecular and clinicopathological markers for diagnosis and prognosis of its malignant phenotypes. The aim of this study is to evaluate expression frequency of PAGE4, SCP-1, and SPANXA/D cancer testis antigen (CTA genes as well as some clinical risk markers to predict liver metastasis of colorectal cancer patients. The expression frequency of PAGE4, SCP-1, and SPANXA/D cancer/testis antigen (CTA genes was obtained using reverse transcription polymerase chain reaction (RT-PCR assay in 90 colorectal tumor samples including both negative and positive liver metastasis tumors. Statistical analysis was performed to assess the association of three studied genes and clinical risk factors with CRC liver metastasis. The frequency of PAGE4 and SCP-1 genes expression was significantly higher in the primary tumours with liver metastasis when statistically compared with primary tumors with no liver metastasis (P<0.05. Among all clinical risk factors studied, the lymph node metastasis and the depth of invasion were statistically correlated with liver metastasis of CRC patients. In addition, using multiple logistic regression, we constructed a model based on PAGE4 and lymph node metastasis to predict liver metastasis of CRC.

  6. Predicting PTSD using the New York Risk Score with genotype data: potential clinical and research opportunities

    Directory of Open Access Journals (Sweden)

    Boscarino JA

    2013-04-01

    Full Text Available Joseph A Boscarino,1,2 H Lester Kirchner,3,4 Stuart N Hoffman,5 Porat M Erlich1,4 1Center for Health Research, Geisinger Clinic, Danville, 2Department of Psychiatry, Temple University School of Medicine, Philadelphia, 3Division of Medicine, Geisinger Clinic, Danville, 4Department of Medicine, Temple University School of Medicine, Philadelphia, 5Department of Neurology, Geisinger Clinic, Danville, PA, USA Background: We previously developed a post-traumatic stress disorder (PTSD screening instrument, ie, the New York PTSD Risk Score (NYPRS, that was effective in predicting PTSD. In the present study, we assessed a version of this risk score that also included genetic information. Methods: Utilizing diagnostic testing methods, we hierarchically examined different prediction variables identified in previous NYPRS research, including genetic risk-allele information, to assess lifetime and current PTSD status among a population of trauma-exposed adults. Results: We found that, in predicting lifetime PTSD, the area under the receiver operating characteristic curve (AUC for the Primary Care PTSD Screen alone was 0.865. When we added psychosocial predictors from the original NYPRS to the model, including depression, sleep disturbance, and a measure of health care access, the AUC increased to 0.902, which was a significant improvement (P = 0.0021. When genetic information was added in the form of a count of PTSD risk alleles located within FKBP, COMT, CHRNA5, and CRHR1 genetic loci (coded 0–6, the AUC increased to 0.920, which was also a significant improvement (P = 0.0178. The results for current PTSD were similar. In the final model for current PTSD with the psychosocial risk factors included, genotype resulted in a prediction weight of 17 for each risk allele present, indicating that a person with six risk alleles or more would receive a PTSD risk score of 17 × 6 = 102, the highest risk score for any of the predictors studied. Conclusion: Genetic

  7. Preoperative MRI findings predict two-year postoperative clinical outcome in lumbar spinal stenosis.

    Directory of Open Access Journals (Sweden)

    Pekka Kuittinen

    Full Text Available To study the predictive value of preoperative magnetic resonance imaging (MRI findings for the two-year postoperative clinical outcome in lumbar spinal stenosis (LSS.84 patients (mean age 63±11 years, male 43% with symptoms severe enough to indicate LSS surgery were included in this prospective observational single-center study. Preoperative MRI of the lumbar spine was performed with a 1.5-T unit. The imaging protocol conformed to the requirements of the American College of Radiology for the performance of MRI of the adult spine. Visual and quantitative assessment of MRI was performed by one experienced neuroradiologist. At the two-year postoperative follow-up, functional ability was assessed with the Oswestry Disability Index (ODI 0-100% and treadmill test (0-1000 m, pain symptoms with the overall Visual Analogue Scale (VAS 0-100 mm, and specific low back pain (LBP and specific leg pain (LP separately with a numeric rating scale from 0-10 (NRS-11. Satisfaction with the surgical outcome was also assessed.Preoperative severe central stenosis predicted postoperatively lower LP, LBP, and VAS when compared in patients with moderate central stenosis (p<0.05. Moreover, severe stenosis predicted higher postoperative satisfaction (p = 0.029. Preoperative scoliosis predicted an impaired outcome in the ODI (p = 0.031 and lowered the walking distance in the treadmill test (p = 0.001. The preoperative finding of only one stenotic level in visual assessment predicted less postoperative LBP when compared with patients having 2 or more stenotic levels (p = 0.026. No significant differences were detected between quantitative measurements and the patient outcome.Routine preoperative lumbar spine MRI can predict the patient outcome in a two-year follow up in patients with LSS surgery. Severe central stenosis and one-level central stenosis are predictors of good outcome. Preoperative finding of scoliosis may indicate worse functional ability.

  8. Sensitivity, specificity and predictive value of blood cultures from cattle clinically suspected of bacterial endocarditis

    DEFF Research Database (Denmark)

    Houe, Hans; Eriksen, L.; Jungersen, Gregers;

    1993-01-01

    This study investigated the number of blood culture-positive cattle among 215 animals clinically suspected of having bacterial endocarditis. For animals that were necropsied, the sensitivity, specificity and predictive value of the diagnosis of endocarditis were calculated on the basis...... of the isolation of the causative bacteria from blood. Furthermore, it was investigated whether the glutaraldehyde coagulation time, total leucocyte count, per cent neutrophil granulocytes, pulse rate and duration of disease could help to discriminate endocarditis from other diseases. Among 138 animals necropsied...... the sensitivity, specificity and predictive value of blood cultivation were 70.7 per cent, 93.8 per cent and 89.1 per cent, respectively. None of the other measurements could be used to discriminate between endocarditis and non-endocarditis cases....

  9. Predictive Factors of Gastrointestinal Caustic Injury According to Clinical and Endoscopic Findings

    Directory of Open Access Journals (Sweden)

    Cherie Quingking

    2013-03-01

    Full Text Available Background: Ingestion of caustic substances is the main reason for referral to Philippines National Poison Management and Control Center among other causes of acute poisoning. Rapid assessment of severity of injury is important for treatment and prognosis of these cases. This study was aimed to investigate the correlation of clinical factors with severity of gastrointestinal (GI mucosal injury. Methods: In this retrospective study, a total of 105 patients were included. Patients were categorized into two groups including 35 patients with low grade and 70 patients with high grade GI injury to compare the predictive value of clinical findings. Results: Mean (SD age of patients was 27 (10 and 47% of patients were male. Oral burns (P

  10. An Update on Crown Lengthening. Part 2: Increasing Clinical Crown Height to Facilitate Predictable Restorations.

    Science.gov (United States)

    Kalsi, Harpoonam Jeet; Bomfim, Deborah Iola; Darbar, Ulpee

    2015-04-01

    This is the second paper in this two-part series. Paper one provided an overview of managing gingival tissue excess and paper two will focus on increasing clinical crown height to facilitate restorative treatment. Crown lengthening is a surgical procedure aimed at the removal of gingival tissue with or without adjunctive bone removal. The different types of procedure undertaken will be discussed over the two papers. In order to provide predictable restorations, care must be taken to ensure the integrity of the margins. If this is not taken into account it can lead to an impingement on the biologic width, which may in turn lead to chronic inflammation resulting in recession or the development of periodontal problems which can be hard to manage. Clinical Relevance: This paper aims to reinforce the need for thorough diagnosis and treatment planning and provides an overview of the various procedures that can be undertaken.

  11. Molecular biomarkers of colorectal cancer: prognostic and predictive tools for clinical practice

    Institute of Scientific and Technical Information of China (English)

    Wei-qin JIANG; Fang-fang FU; Yang-xia LI; Wei-bin WANG; Hao-hao WANG; Hai-ping JIANG; Li-song TENG

    2012-01-01

    Colorectal cancer remains one of the most common types of cancer and leading causes of cancer death worldwide.Although we have made steady progress in chemotherapy and targeted therapy,evidence suggests that the majority of patients undergoing drug therapy experience severe,debilitating,and even lethal adverse drug events which considerably outweigh the benefits.The identification of suitable biomarkers will allow clinicians to deliver the most appropriate drugs to specific patients and spare them ineffective and expensive treatments.Prognostic and predictive biomarkers have been the subjects of many published papers,but few have been widely incorporated into clinical practice.Here,we want to review recent biomarker data related to colorectal cancer,which may have been ready for clinical use.

  12. Optimal marker-strategy clinical trial design to detect predictive markers for targeted therapy.

    Science.gov (United States)

    Zang, Yong; Liu, Suyu; Yuan, Ying

    2016-07-01

    In developing targeted therapy, the marker-strategy design (MSD) provides an important approach to evaluate the predictive marker effect. This design first randomizes patients into non-marker-based or marker-based strategies. Patients allocated to the non-marker-based strategy are then further randomized to receive either the standard or targeted treatments, while patients allocated to the marker-based strategy receive treatments based on their marker statuses. Little research has been done on the statistical properties of the MSD, which has led to some widespread misconceptions and placed clinical researchers at high risk of using inefficient designs. In this article, we show that the commonly used between-strategy comparison has low power to detect the predictive effect and is valid only under a restrictive condition that the randomization ratio within the non-marker-based strategy matches the marker prevalence. We propose a Wald test that is generally valid and also uniformly more powerful than the between-strategy comparison. Based on that, we derive an optimal MSD that maximizes the power to detect the predictive marker effect by choosing the optimal randomization ratios between the two strategies and treatments. Our numerical study shows that using the proposed optimal designs can substantially improve the power of the MSD to detect the predictive marker effect. We use a lung cancer trial to illustrate the proposed optimal designs.

  13. Sputum biomarkers and the prediction of clinical outcomes in patients with cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

    Full Text Available Lung function, acute pulmonary exacerbations (APE, and weight are the best clinical predictors of survival in cystic fibrosis (CF; however, underlying mechanisms are incompletely understood. Biomarkers of current disease state predictive of future outcomes might identify mechanisms and provide treatment targets, trial endpoints and objective clinical monitoring tools. Such CF-specific biomarkers have previously been elusive. Using observational and validation cohorts comprising 97 non-transplanted consecutively-recruited adult CF patients at the Intermountain Adult CF Center, University of Utah, we identified biomarkers informative of current disease and predictive of future clinical outcomes. Patients represented the majority of sputum producers. They were recruited March 2004-April 2007 and followed through May 2011. Sputum biomarker concentrations were measured and clinical outcomes meticulously recorded for a median 5.9 (interquartile range 5.0 to 6.6 years to study associations between biomarkers and future APE and time-to-lung transplantation or death. After multivariate modeling, only high mobility group box-1 protein (HMGB-1, mean=5.84 [log ng/ml], standard deviation [SD] =1.75 predicted time-to-first APE (hazard ratio [HR] per log-unit HMGB-1=1.56, p-value=0.005, number of future APE within 5 years (0.338 APE per log-unit HMGB-1, p<0.001 by quasi-Poisson regression and time-to-lung transplantation or death (HR=1.59, p=0.02. At APE onset, sputum granulocyte macrophage colony stimulating factor (GM-CSF, mean 4.8 [log pg/ml], SD=1.26 was significantly associated with APE-associated declines in lung function (-10.8 FEV(1% points per log-unit GM-CSF, p<0.001 by linear regression. Evaluation of validation cohorts produced similar results that passed tests of mutual consistency. In CF sputum, high HMGB-1 predicts incidence and recurrence of APE and survival, plausibly because it mediates long-term airway inflammation. High APE-associated GM

  14. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors

    Energy Technology Data Exchange (ETDEWEB)

    Nelms, Benjamin E.; Zhen Heming; Tome, Wolfgang A. [Canis Lupus LLC and Department of Human Oncology, University of Wisconsin, Merrimac, Wisconsin 53561 (United States); Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705 (United States); Departments of Human Oncology, Medical Physics, and Biomedical Engineering, University of Wisconsin, Madison, Wisconsin 53792 (United States)

    2011-02-15

    Purpose: The purpose of this work is to determine the statistical correlation between per-beam, planar IMRT QA passing rates and several clinically relevant, anatomy-based dose errors for per-patient IMRT QA. The intent is to assess the predictive power of a common conventional IMRT QA performance metric, the Gamma passing rate per beam. Methods: Ninety-six unique data sets were created by inducing four types of dose errors in 24 clinical head and neck IMRT plans, each planned with 6 MV Varian 120-leaf MLC linear accelerators using a commercial treatment planning system and step-and-shoot delivery. The error-free beams/plans were used as ''simulated measurements'' (for generating the IMRT QA dose planes and the anatomy dose metrics) to compare to the corresponding data calculated by the error-induced plans. The degree of the induced errors was tuned to mimic IMRT QA passing rates that are commonly achieved using conventional methods. Results: Analysis of clinical metrics (parotid mean doses, spinal cord max and D1cc, CTV D95, and larynx mean) vs IMRT QA Gamma analysis (3%/3 mm, 2/2, 1/1) showed that in all cases, there were only weak to moderate correlations (range of Pearson's r-values: -0.295 to 0.653). Moreover, the moderate correlations actually had positive Pearson's r-values (i.e., clinically relevant metric differences increased with increasing IMRT QA passing rate), indicating that some of the largest anatomy-based dose differences occurred in the cases of high IMRT QA passing rates, which may be called ''false negatives.'' The results also show numerous instances of false positives or cases where low IMRT QA passing rates do not imply large errors in anatomy dose metrics. In none of the cases was there correlation consistent with high predictive power of planar IMRT passing rates, i.e., in none of the cases did high IMRT QA Gamma passing rates predict low errors in anatomy dose metrics or vice versa

  15. Do clinical factors help to predict disease course in inflammatory bowel disease?

    Institute of Scientific and Technical Information of China (English)

    Edouard; Louis; Jacques; Belaiche; Catherine; Reenaers

    2010-01-01

    While therapeutic strategies able to change the natural history of the disease are developing,it is of major importance to have available predictive factors for aggressive disease to try and target these therapeutic strategies.Clinical predictors have probably been the most broadly studied.In both Crohn's disease(CD) and ulcerative colitis(UC),age at diagnosis,disease location and smoking habit are currently the strongest predictors of disease course.A younger age at onset is associated with more aggressive...

  16. Predicting hydrogen-bond strengths from acid-base molecular properties. The pK(a) slide rule: toward the solution of a long-lasting problem.

    Science.gov (United States)

    Gilli, Paola; Pretto, Loretta; Bertolasi, Valerio; Gilli, Gastone

    2009-01-20

    Unlike normal chemical bonds, hydrogen bonds (H-bonds) characteristically feature binding energies and contact distances that do not simply depend on the donor (D) and acceptor (:A) nature. Instead, their chemical context can lead to large variations even for a same donor-acceptor couple. As a striking example, the weak HO-H...OH(2) bond in neutral water changes, in acidic or basic medium, to the 6-fold stronger and 15% shorter [H(2)O...H...OH(2)](+) or [HO...H...OH](-) bonds. This surprising behavior, sometimes called the H-bond puzzle, practically prevents prediction of H-bond strengths from the properties of the interacting molecules. Explaining this puzzle has been the main research interest of our laboratory in the last 20 years. Our first contribution was the proposal of RAHB (resonance-assisted H-bond), a new type of strong H-bond where donor and acceptor are linked by a short pi-conjugated fragment. The RAHB discovery prompted new studies on strong H-bonds, finally leading to a general H-bond classification in six classes, called the six chemical leitmotifs, four of which include all known types of strong bonds. These studies attested to the covalent nature of the strong H-bond showing, by a formal valence-bond treatment, that weak H-bonds are basically electrostatic while stronger ones are mixtures of electrostatic and covalent contributions. The covalent component gradually increases as the difference of donor-acceptor proton affinities, DeltaPA, or acidic constants, DeltapK(a), approaches zero. At this limit, the strong and symmetrical D...H...A bonds formed can be viewed as true three-center-four-electron covalent bonds. These results emphasize the role PA/pK(a) equalization plays in strengthening the H-bond, a hypothesis often invoked in the past but never fully verified. In this Account, this hypothesis is reconsidered by using a new instrument, the pK(a) slide rule, a bar chart that reports in separate scales the pK(a)'s of the D-H proton donors and

  17. Phonological reduplication in sign language: rules rule

    Directory of Open Access Journals (Sweden)

    Iris eBerent

    2014-06-01

    Full Text Available Productivity—the hallmark of linguistic competence—is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL. As a case study, we examine reduplication (X→XX—a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating, and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task. The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal.

  18. The Impact of Maternal Characteristics on the Moderately Premature Infant: An Antenatal Maternal Transport Clinical Prediction Rule

    OpenAIRE

    Dukhovny, Dmitry; Dukhovny, Stephanie; Pursley, DeWayne; Escobar, Gabriel J.; McCormick, Marie C.; Mao, Wenyang; Zupancic, John AF

    2012-01-01

    Background: Moderately premature infants, defined here as those born between 30 \\(\\frac{0}{7}\\) and 34 \\(\\frac{6}{7}\\) weeks gestation, comprise 3.9% of all births in the United States and 32% of all preterm births. While long-term outcomes for these infants are better than for less mature infants, morbidity and mortality are still substantially increased in comparison to infants born at term. There is an added survival benefit resulting from birth at a tertiary neonatal care center, and alth...

  19. The design of a rule-based clinical event monitor in a multi-vendor hospital computing environment.

    OpenAIRE

    Nguyen, L. T.; Margulies, D. M.

    1992-01-01

    The Clinical Event Monitor (CEM) described here is a prototype system designed to explore the issues involved in building an institutional CEM that permits rapid, automated evaluation of clinical transactions and notification to clinicians of exceptional events in a multi-vendor computing environment. The CEM uses expert systems, database, and systems integration techniques. Ancillary (departmental) applications, including as Patient Registration, Laboratories, and Pharmacy have been licensed...

  20. An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems

    OpenAIRE

    Sáez Silvestre, Carlos; BRESÓ GUARDADO, ADRIÁN; Vicente Robledo, Javier; Robles Viejo, Montserrat; García Gómez, Juan Miguel

    2013-01-01

    The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic int...

  1. Cleavage of highly structured viral RNA molecules by combinatorial libraries of hairpin ribozymes. The most effective ribozymes are not predicted by substrate selection rules.

    Science.gov (United States)

    Yu, Q; Pecchia, D B; Kingsley, S L; Heckman, J E; Burke, J M

    1998-09-01

    Combinatorial libraries of hairpin ribozymes representing all possible cleavage specificities (>10(5)) were used to evaluate all ribozyme cleavage sites within a large (4.2-kilobase) and highly structured viral mRNA, the 26 S subgenomic RNA of Sindbis virus. The combinatorial approach simultaneously accounts for target site structure and dynamics, together with ribozyme folding, and the sequences that result in a ribozyme-substrate complex with maximal activity. Primer extension was used to map and rank the relative activities of the ribozyme pool against individual sites and revealed two striking findings. First, only a small fraction of potential recognition sites are effectively cleaved (activity-selected sites). Second, nearly all of the most effectively cleaved sites deviated substantially from the established consensus selection rules for the hairpin ribozyme and were not predicted by examining the sequence, or through the use of computer-assisted predictions of RNA secondary structure. In vitro selection methods were used to isolate ribozymes with increased activity against substrates that deviate from the GUC consensus sequence. trans-Acting ribozymes targeting nine of the activity-selected sites were synthesized, together with ribozymes targeting four sites with a perfect match to the cleavage site consensus (sequence-selected sites). Activity-selected ribozymes have much higher cleavage activity against the long, structured RNA molecules than do sequence-selected ribozymes, although the latter are effective in cleaving oligoribonucleotides, as predicted. These results imply that, for Sindbis virus 26 S RNA, designing ribozymes based on matches to the consensus sequence may be an ineffective strategy. PMID:9722591

  2. Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: Diagnostic study

    NARCIS (Netherlands)

    R.G. Nijman (Ruud); Y. Vergouwe (Yvonne); M.J. Thompson (Matthew); M.V. Veen (Mirjam Van); A.H.J. van Meurs (Alfred); J. van der Lei (Johan); E.W. Steyerberg (Ewout); H.A. Moll (Henriëtte); R. Oostenbrink (Rianne)

    2013-01-01

    textabstractObjective: To derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department. Design: Prospective observational diagnostic study. Setting: Three paediatric em

  3. Factors predicting suicidal ideation in the preceding 12 months among patients attending a community psychiatric outpatient clinic.

    LENUS (Irish Health Repository)

    Anyansi, Tochukwu E

    2013-06-01

    Predictive factors are used to alert the clinician to the necessity of carrying out a suicide risk assessment in those patients whose demographic and clinical characteristics suggest the possibility of suicide.

  4. Developing a clinical utility framework to evaluate prediction models in radiogenomics

    Science.gov (United States)

    Wu, Yirong; Liu, Jie; Munoz del Rio, Alejandro; Page, David C.; Alagoz, Oguzhan; Peissig, Peggy; Onitilo, Adedayo A.; Burnside, Elizabeth S.

    2015-03-01

    Combining imaging and genetic information to predict disease presence and behavior is being codified into an emerging discipline called "radiogenomics." Optimal evaluation methodologies for radiogenomics techniques have not been established. We aim to develop a clinical decision framework based on utility analysis to assess prediction models for breast cancer. Our data comes from a retrospective case-control study, collecting Gail model risk factors, genetic variants (single nucleotide polymorphisms-SNPs), and mammographic features in Breast Imaging Reporting and Data System (BI-RADS) lexicon. We first constructed three logistic regression models built on different sets of predictive features: (1) Gail, (2) Gail+SNP, and (3) Gail+SNP+BI-RADS. Then, we generated ROC curves for three models. After we assigned utility values for each category of findings (true negative, false positive, false negative and true positive), we pursued optimal operating points on ROC curves to achieve maximum expected utility (MEU) of breast cancer diagnosis. We used McNemar's test to compare the predictive performance of the three models. We found that SNPs and BI-RADS features augmented the baseline Gail model in terms of the area under ROC curve (AUC) and MEU. SNPs improved sensitivity of the Gail model (0.276 vs. 0.147) and reduced specificity (0.855 vs. 0.912). When additional mammographic features were added, sensitivity increased to 0.457 and specificity to 0.872. SNPs and mammographic features played a significant role in breast cancer risk estimation (p-value < 0.001). Our decision framework comprising utility analysis and McNemar's test provides a novel framework to evaluate prediction models in the realm of radiogenomics.

  5. Can clinical colour vision tests be used to predict the results of the Farnsworth lantern test?

    Science.gov (United States)

    Cole, B L; Maddocks, J D

    1998-11-01

    Clinicians usually do not have access to a lantern test when making an occupational assessment of the ability of a person with defective colour vision to recognise signal light colours: they must rely on the results of ordinary clinical tests. While all colour vision defectives fail the Holmes Wright Type B lantern test and most fail the Holmes Wright Type A lantern, 35% of colour vision defectives pass the Farnsworth lantern. Can clinical tests predict who will pass and fail the Farnsworth lantern? We find that a pass (less than two or more diametrical crossings) at the Farnsworth Panel D 15 Dichotomous test has a sensitivity of 0.67 and specificity of 0.94 in predicting a pass or fail at the Farnsworth lantern test: a Nagel range of > 10 has a sensitivity of 0.87 and a specificity of 0.57. We conclude that neither the D 15 nor the Nagel Anomaloscope matching range are satisfactory predictors of performance on the Farnsworth Lantern.

  6. Predicting the risk of suicide by analyzing the text of clinical notes.

    Directory of Open Access Journals (Sweden)

    Chris Poulin

    Full Text Available We developed linguistics-driven prediction models to estimate the risk of suicide. These models were generated from unstructured clinical notes taken from a national sample of U.S. Veterans Administration (VA medical records. We created three matched cohorts: veterans who committed suicide, veterans who used mental health services and did not commit suicide, and veterans who did not use mental health services and did not commit suicide during the observation period (n = 70 in each group. From the clinical notes, we generated datasets of single keywords and multi-word phrases, and constructed prediction models using a machine-learning algorithm based on a genetic programming framework. The resulting inference accuracy was consistently 65% or more. Our data therefore suggests that computerized text analytics can be applied to unstructured medical records to estimate the risk of suicide. The resulting system could allow clinicians to potentially screen seemingly healthy patients at the primary care level, and to continuously evaluate the suicide risk among psychiatric patients.

  7. Integration of noninvasive prenatal prediction of fetal blood group into clinical prenatal care.

    Science.gov (United States)

    Clausen, Frederik Banch

    2014-05-01

    Incompatibility of red blood cell blood group antigens between a pregnant woman and her fetus can cause maternal immunization and, consequently, hemolytic disease of the fetus and newborn. Noninvasive prenatal testing of cell-free fetal DNA can be used to assess the risk of hemolytic disease of the fetus and newborn to fetuses of immunized women. Prediction of the fetal RhD type has been very successful and is now integrated into clinical practice to assist in the management of the pregnancies of RhD immunized women. In addition, noninvasive prediction of the fetal RhD type can be applied to guide targeted prenatal prophylaxis, thus avoiding unnecessary exposure to anti-D in pregnant women. The analytical aspect of noninvasive fetal RHD typing is very robust and accurate, and its routine utilization has demonstrated high sensitivities for fetal RHD detection. A high compliance with administering anti-D is essential for obtaining a clinical effect. Noninvasive fetal typing of RHC/c, RHE/e, and KEL may become more widely used in the future. PMID:24431264

  8. Knee shape might predict clinical outcome after an anterior cruciate ligament rupture.

    Science.gov (United States)

    Eggerding, V; van Kuijk, K S R; van Meer, B L; Bierma-Zeinstra, S M A; van Arkel, E R A; Reijman, M; Waarsing, J H; Meuffels, D E

    2014-06-01

    We have investigated whether shape of the knee can predict the clinical outcome of patients after an anterior cruciate ligament rupture. We used statistical shape modelling to measure the shape of the knee joint of 182 prospectively followed patients on lateral and Rosenberg view radiographs of the knee after a rupture of the anterior cruciate ligament. Subsequently, we associated knee shape with the International Knee Documentation Committee subjective score at two years follow-up. The mean age of patients was 31 years (21 to 51), the majority were male (n = 121) and treated operatively (n = 135). We found two modes (shape variations) that were significantly associated with the subjective score at two years: one for the operatively treated group (p = 0.002) and one for the non-operatively treated group (p = 0.003). Operatively treated patients who had higher subjective scores had a smaller intercondylar notch and a smaller width of the intercondylar eminence. Non-operatively treated patients who scored higher on the subjective score had a more pyramidal intercondylar notch as opposed to one that was more dome-shaped. We conclude that the shape of the femoral notch and the intercondylar eminence is predictive of clinical outcome two years after a rupture of the anterior cruciate ligament.

  9. Comparison of Existing Clinical Scoring Systems in Predicting Severity and Prognoses of Hyperlipidemic Acute Pancreatitis in Chinese Patients

    OpenAIRE

    Qiu, Lei; Sun, Rui Qing; Jia, Rong Rong; Ma, Xiu Ying; Cheng, Li; Tang, Mao Chun; Zhao, Yan

    2015-01-01

    Abstract It is important to identify the severity of acute pancreatitis (AP) in the early course of the disease. Clinical scoring systems may be helpful to predict the prognosis of patients with early AP; however, few analysts have forecast the accuracy of scoring systems for the prognosis in hyperlipidemic acute pancreatitis (HLAP). The purpose of this study was to summarize the clinical characteristics of HLAP and compare the accuracy of conventional scoring systems in predicting the progno...

  10. Outcomes of Health System Structures, Highly Pertinent Clinical Information, Idea Stimulators, Clinical Reviews, and Prediction Tools: JABFM Exemplified.

    Science.gov (United States)

    Bowman, Marjorie A; Neale, Anne Victoria; Seehusen, Dean A

    2016-01-01

    This issue exemplifies the types of articles that JABFM publishes to advance family medicine. We have articles on the implications of health system organizational structures. Three of these are international articles at the level of the national health system (1 from China) and systematic local health interventions (1 from Canada and 1 from Netherlands). Inside the United States, where there are more family physicians, there is less obesity, and designation as a Patient Centered Medical Home is related to increased rates of colorectal cancer screening. Review articles on common clinical topics discuss treatments that are changing (acne in pregnancy) or lack consensus (distal radial fractures). We have articles on making life easier in the office, such as for predicting Vitamin D levels, osteoporosis, and pre-diabetes in normal weight adults. There are articles to raise awareness of the "newest" testing or treatments, that is, auditory brainstem implants. "Reminder" articles highlight known entities that need to be reinforced to prevent over-/underdiagnosis or treatment, for example, "cotton fever." Another article discusses the increased risk for postoperative complications with sleep apnea. We also provide "thought" pieces, in this case about the terminology we are using to extend our concept of patient-centered medical homes.

  11. Outcomes of Health System Structures, Highly Pertinent Clinical Information, Idea Stimulators, Clinical Reviews, and Prediction Tools: JABFM Exemplified.

    Science.gov (United States)

    Bowman, Marjorie A; Neale, Anne Victoria; Seehusen, Dean A

    2016-01-01

    This issue exemplifies the types of articles that JABFM publishes to advance family medicine. We have articles on the implications of health system organizational structures. Three of these are international articles at the level of the national health system (1 from China) and systematic local health interventions (1 from Canada and 1 from Netherlands). Inside the United States, where there are more family physicians, there is less obesity, and designation as a Patient Centered Medical Home is related to increased rates of colorectal cancer screening. Review articles on common clinical topics discuss treatments that are changing (acne in pregnancy) or lack consensus (distal radial fractures). We have articles on making life easier in the office, such as for predicting Vitamin D levels, osteoporosis, and pre-diabetes in normal weight adults. There are articles to raise awareness of the "newest" testing or treatments, that is, auditory brainstem implants. "Reminder" articles highlight known entities that need to be reinforced to prevent over-/underdiagnosis or treatment, for example, "cotton fever." Another article discusses the increased risk for postoperative complications with sleep apnea. We also provide "thought" pieces, in this case about the terminology we are using to extend our concept of patient-centered medical homes. PMID:26957371

  12. How to develop, validate, and compare clinical prediction models involving radiological parameters: Study design and statistical methods

    Energy Technology Data Exchange (ETDEWEB)

    Han, Kyung Hwa; Choi, Byoung Wook [Dept. of Radiology, and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Song, Ki Jun [Dept. of Biostatistics and Medical Informatics, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2016-06-15

    Clinical prediction models are developed to calculate estimates of the probability of the presence/occurrence or future course of a particular prognostic or diagnostic outcome from multiple clinical or non-clinical parameters. Radiologic imaging techniques are being developed for accurate detection and early diagnosis of disease, which will eventually affect patient outcomes. Hence, results obtained by radiological means, especially diagnostic imaging, are frequently incorporated into a clinical prediction model as important predictive parameters, and the performance of the prediction model may improve in both diagnostic and prognostic settings. This article explains in a conceptual manner the overall process of developing and validating a clinical prediction model involving radiological parameters in relation to the study design and statistical methods. Collection of a raw dataset; selection of an appropriate statistical model; predictor selection; evaluation of model performance using a calibration plot, Hosmer-Lemeshow test and c-index; internal and external validation; comparison of different models using c-index, net reclassification improvement, and integrated discrimination improvement; and a method to create an easy-to-use prediction score system will be addressed. This article may serve as a practical methodological reference for clinical researchers.

  13. Predicting progression of IgA nephropathy: new clinical progression risk score.

    Directory of Open Access Journals (Sweden)

    Jingyuan Xie

    Full Text Available IgA nephropathy (IgAN is a common cause of end-stage renal disease (ESRD in Asia. In this study, based on a large cohort of Chinese patients with IgAN, we aim to identify independent predictive factors associated with disease progression to ESRD. We collected retrospective clinical data and renal outcomes on 619 biopsy-diagnosed IgAN patients with a mean follow-up time of 41.3 months. In total, 67 individuals reached the study endpoint defined by occurrence of ESRD necessitating renal replacement therapy. In the fully adjusted Cox proportional hazards model, there were four baseline variables with a significant independent effect on the risk of ESRD. These included: eGFR [HR = 0.96(0.95-0.97], serum albumin [HR = 0.47(0.32-0.68], hemoglobin [HR = 0.79(0.72-0.88], and SBP [HR = 1.02(1.00-1.03]. Based on these observations, we developed a 4-variable equation of a clinical risk score for disease progression. Our risk score explained nearly 22% of the total variance in the primary outcome. Survival ROC curves revealed that the risk score provided improved prediction of ESRD at 24th, 60th and 120th month of follow-up compared to the three previously proposed risk scores. In summary, our data indicate that IgAN patients with higher systolic blood pressure, lower eGFR, hemoglobin, and albumin levels at baseline are at a greatest risk of progression to ESRD. The new progression risk score calculated based on these four baseline variables offers a simple clinical tool for risk stratification.

  14. A Clinical Indications Prediction Scale Based on TWIST1 for Human Mesenchymal Stem Cells

    Directory of Open Access Journals (Sweden)

    Siddaraju V. Boregowda

    2016-02-01

    Full Text Available In addition to their stem/progenitor properties, mesenchymal stem cells (MSCs also exhibit potent effector (angiogenic, antiinflammatory, immuno-modulatory functions that are largely paracrine in nature. It is widely believed that effector functions underlie most of the therapeutic potential of MSCs and are independent of their stem/progenitor properties. Here we demonstrate that stem/progenitor and effector functions are coordinately regulated at the cellular level by the transcription factor Twist1 and specified within populations according to a hierarchical model. We further show that manipulation of Twist1 levels by genetic approaches or by exposure to widely used culture supplements including fibroblast growth factor 2 (Ffg2 and interferon gamma (IFN-gamma alters MSC efficacy in cell-based and in vivo assays in a predictable manner. Thus, by mechanistically linking stem/progenitor and effector functions our studies provide a unifying framework in the form of an MSC hierarchy that models the functional complexity of populations. Using this framework, we developed a CLinical Indications Prediction (CLIP scale that predicts how donor-to-donor heterogeneity and culture conditions impact the therapeutic efficacy of MSC populations for different disease indications.

  15. A Clinical Indications Prediction Scale Based on TWIST1 for Human Mesenchymal Stem Cells.

    Science.gov (United States)

    Boregowda, Siddaraju V; Krishnappa, Veena; Haga, Christopher L; Ortiz, Luis A; Phinney, Donald G

    2016-02-01

    In addition to their stem/progenitor properties, mesenchymal stem cells (MSCs) also exhibit potent effector (angiogenic, antiinflammatory, immuno-modulatory) functions that are largely paracrine in nature. It is widely believed that effector functions underlie most of the therapeutic potential of MSCs and are independent of their stem/progenitor properties. Here we demonstrate that stem/progenitor and effector functions are coordinately regulated at the cellular level by the transcription factor Twist1 and specified within populations according to a hierarchical model. We further show that manipulation of Twist1 levels by genetic approaches or by exposure to widely used culture supplements including fibroblast growth factor 2 (Ffg2) and interferon gamma (IFN-gamma) alters MSC efficacy in cell-based and in vivo assays in a predictable manner. Thus, by mechanistically linking stem/progenitor and effector functions our studies provide a unifying framework in the form of an MSC hierarchy that models the functional complexity of populations. Using this framework, we developed a CLinical Indications Prediction (CLIP) scale that predicts how donor-to-donor heterogeneity and culture conditions impact the therapeutic efficacy of MSC populations for different disease indications. PMID:26981553

  16. Thyroid Hormones, Autoantibodies, Ultrasonography, and Clinical Parameters for Predicting Thyroid Cancer

    Science.gov (United States)

    He, Lin-zheng; Zeng, Tian-shu; Pu, Lin; Pan, Shi-xiu; Xia, Wen-fang; Chen, Lu-lu

    2016-01-01

    Our objective was to evaluate thyroid nodule malignancy prediction using thyroid function tests, autoantibodies, ultrasonographic imaging, and clinical data. We conducted a retrospective cohort study in 1400 patients with nodular thyroid disease (NTD). The thyroid stimulating hormone (TSH) concentration was significantly higher in patients with differentiated thyroid cancer (DTC) versus benign thyroid nodular disease (BTND) (p = 0.004). The receiver operating characteristic curve of TSH showed an AUC of 0.58 (95% CI 0.53–0.62, p = 0.001), sensitivity of 74%, and specificity of 57% at a cut-off of 1.59 mIU/L. There was an incremental increase in TSH concentration along with the increasing tumor size (p < 0.001). Thyroglobulin antibody (TgAb) concentration was associated with an increased risk of malignancy (p = 0.029), but this association was lost when the effect of TSH was taken into account (p = 0.11). Thyroid ultrasonographic characteristics, including fewer than three nodules, hypoechoic appearance, solid component, poorly defined margin, intranodular or peripheral-intranodular flow, and punctate calcification, can be used to predict the risk of thyroid cancer. In conclusion, our study suggests that preoperative serum TSH concentration, age, and ultrasonographic features can be used to predict the risk of malignancy in patients with NTD. PMID:27313612

  17. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  18. Cross-sectional imaging for diagnosis and clinical outcome prediction of acute basilar artery thrombosis

    International Nuclear Information System (INIS)

    Basilar artery occlusion is a potentially fatal condition and imaging findings can be subtle. Prompt diagnosis is vital, as recognition may lead to therapeutic recanalization that may improve functional outcome and survival. Furthermore, cross-sectional imaging signs may help predict eventual outcome and, therefore, guide which patients should be subjected to aggressive treatment. Computed tomography (CT) signs include a hyperdense basilar artery that has a high specificity, accuracy, positive and negative predictive value. Evidence regarding the prognostic significance of the hyperdense basilar artery sign is conflicting. Early magnetic resonance imaging (MRI) features include loss of flow void, seen as increased signal intensity within the basilar artery on T2-weigted images and identification of acute thrombus, seen as intermediate signal on T1-weighted images. MRI sequences are more sensitive for early detection of acute ischaemia or infarction, ideally with diffusion-weighted imaging (DWI). Both CT and MR angiography are sensitive for detection of acute thrombus, seen as a filling defect or occlusion. These are the non-invasive imaging techniques of choice to confirm diagnosis, with perhaps the speed and accessibility of CT angiography resulting in this technique being valuable in the acute setting. Several new scoring systems based on arterial segmentation rather than global volume assessment using CT angiography source images and DWI have shown early promise in the prediction of eventual clinical outcome in order to isolate those patients who may benefit from therapeutic recanalization.

  19. Predictive Value of IL-8 for Sepsis and Severe Infections After Burn Injury: A Clinical Study.

    Science.gov (United States)

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C; Cox, Robert A; Song, Juquan; Jeschke, Marc G

    2015-03-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring postburn inflammation is of paramount importance but, so far, there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As interleukin 8 (IL-8) is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict postburn sepsis, infections, and mortality. Plasma cytokines, acute-phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days after injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure [MOF], and mortality) were recorded. A cutoff level for IL-8 was determined using receiver operating characteristic analysis. Statistical significance is set at P Patients were grouped according to their average IL-8 levels relative to this cutoff and stratified into high (H) (n = 133) and low (L) (n = 335) groups. In the L group, regression analysis revealed a significant predictive value of IL-8 to percent of total body surface area burned and incidence of MOF (P inflammatory and acute-phase responses compared with the L group (P burn patients.

  20. Prediction of clinical factors associated with pandemic influenza A (H1N1 2009 in Pakistan.

    Directory of Open Access Journals (Sweden)

    Nadia Nisar

    Full Text Available BACKGROUND: Influenza is a viral infection that can lead to serious complications and death(s in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. METHODOLOGY: A retrospective cross sectional analysis was done on demographic and epidemiological data collected from March 2009 to March 2010. Patients were classified as ILI or SARI using WHO case definitions. Respiratory specimens were tested by RT-PCR. Clinical symptoms and co-morbid conditions were analyzed using binary logistic regression models. RESULTS: In the first approach, analysis compared children (≤12 and adults (>12. Of 1,243 cases, 262 (21% tested positive for A(H1N1pdm09 and the proportion of children (≤12 and adults (>12 were 27% and 73% respectively. Four symptoms predicted influenza in children: fever (OR 2.849, 95% CI 1.931-8.722, cough (OR 1.99, 95% CI 1.512-3.643, diarrhea (OR 2.100, 95% CI 2.040-3.25 and respiratory disease (OR 3.269, 95% CI 2.128-12.624. In adults, the strongest clinical predictor was fever (OR 2.80, 95% CI 1.025-3.135 followed by cough (OR 1.431, 95% CI 1.032-2.815. In the second instance, patients were separated into two groups: SARI 326 (26% and ILI 917 (74% cases. Male to female ratio was 1.41∶1.12 for SARI and 2∶1.5 for ILI cases. Chi-square test showed that fever, cough and sore throat were significant factors for A(H1N1pdm09 infections (p = 0.008. CONCLUSION: Studies in a primary care setting should be encouraged focused on patients with influenza-like illness to develop sensitive clinical case definition that will help to improve accuracy of detecting influenza infections. Formulation of a standard "one size fits all" case definition that best correlates with influenza infections can help guide decisions for additional diagnostic testing and also discourage unjustified antibiotic prescription and usage

  1. Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5-hydroxytryptamine reuptake inhibitors in mice

    DEFF Research Database (Denmark)

    Kreilgaard, Mads; Smith, D. G.; Brennum, L. T.;

    2008-01-01

    Bridging the gap between preclinical research and clinical trials is vital for drug development. Predicting clinically relevant steady-state drug concentrations (Css) in serum from preclinical animal models may facilitate this transition. Here we used a pharmacokinetic/pharmacodynamic (PK/PD) mod...

  2. Innovative Drugs to Treat Depression: Did Animal Models Fail to Be Predictive or Did Clinical Trials Fail to Detect Effects?

    OpenAIRE

    Belzung, Catherine

    2014-01-01

    Over recent decades, encouraging preclinical evidence using rodent models pointed to innovative pharmacological targets to treat major depressive disorder. However, subsequent clinical trials have failed to show convincing results. Two explanations for these rather disappointing results can be put forward, either animal models of psychiatric disorders have failed to predict the clinical effectiveness of treatments or clinical trials have failed to detect the effects of these new drugs. A care...

  3. Predictive Value of IL-8 for Sepsis and Severe Infections after Burn Injury - A Clinical Study

    Science.gov (United States)

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C; Cox, Robert A; Song, Juquan; Jeschke, Marc G

    2014-01-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring post-burn inflammation is of paramount importance but so far there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As IL-8 is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict post-burn sepsis, infections, and mortality other outcomes post-burn. Plasma cytokines, acute phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days post injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure (MOF), and mortality were recorded. A cut-off level for IL-8 was determined using receiver operating characteristic (ROC) analysis. Statistical significance is set at (p<0.05). ROC analysis identified a cut-off level of 234 pg/ml for IL-8 for survival. Patients were grouped according to their average IL-8 levels relative to this cut off and stratified into high (H) (n=133) and low (L) (n=335) groups. In the L group, regression analysis revealed a significant predictive value of IL-8 to percent of total body surface area (TBSA) burned and incidence of MOF (p<0.001). In the H group IL-8 levels were able to predict sepsis (p<0.002). In the H group, elevated IL-8 was associated with increased inflammatory and acute phase responses compared to the L group (p<0.05). High levels of IL-8 correlated with increased MOF, sepsis, and mortality. These data suggest that serum levels of IL-8 may be a valid biomarker for monitoring sepsis, infections, and mortality in burn patients. PMID:25514427

  4. Elevated expression of stromal palladin predicts poor clinical outcome in renal cell carcinoma.

    Directory of Open Access Journals (Sweden)

    Vivekanand Gupta

    Full Text Available The role that stromal renal cell carcinoma (RCC plays in support of tumor progression is unclear. Here we sought to determine the predictive value on patient survival of several markers of stromal activation and the feasibility of a fibroblast-derived extracellular matrix (ECM based three-dimensional (3D culture stemming from clinical specimens to recapitulate stromal behavior in vitro. The clinical relevance of selected stromal markers was assessed using a well annotated tumor microarray where stromal-marker levels of expression were evaluated and compared to patient outcomes. Also, an in vitro 3D system derived from fibroblasts harvested from patient matched normal kidney, primary RCC and metastatic tumors was employed to evaluate levels and localizations of known stromal markers such as the actin binding proteins palladin, alpha-smooth muscle actin (α-SMA, fibronectin and its spliced form EDA. Results suggested that RCCs exhibiting high levels of stromal palladin correlate with a poor prognosis, as demonstrated by overall survival time. Conversely, cases of RCCs where stroma presents low levels of palladin expression indicate increased survival times and, hence, better outcomes. Fibroblast-derived 3D cultures, which facilitate the categorization of stromal RCCs into discrete progressive stromal stages, also show increased levels of expression and stress fiber localization of α-SMA and palladin, as well as topographical organization of fibronectin and its splice variant EDA. These observations are concordant with expression levels of these markers in vivo. The study proposes that palladin constitutes a useful marker of poor prognosis in non-metastatic RCCs, while in vitro 3D cultures accurately represent the specific patient's tumor-associated stromal compartment. Our observations support the belief that stromal palladin assessments have clinical relevance thus validating the use of these 3D cultures to study both progressive RCC

  5. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

    Science.gov (United States)

    Levey, D F; Niculescu, E M; Le-Niculescu, H; Dainton, H L; Phalen, P L; Ladd, T B; Weber, H; Belanger, E; Graham, D L; Khan, F N; Vanipenta, N P; Stage, E C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R; Niculescu, A B

    2016-06-01

    Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We

  6. Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?

    NARCIS (Netherlands)

    Schiemanck, S.K.; Kwakkel, G.; Post, M.W.; Kappelle, L.J.; Prevo, A.J.

    2006-01-01

    BACKGROUND AND PURPOSE: To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke. METHODS: Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in l

  7. Strategy as simple rules.

    Science.gov (United States)

    Eisenhardt, K M; Sull, D N

    2001-01-01

    The success of Yahoo!, eBay, Enron, and other companies that have become adept at morphing to meet the demands of changing markets can't be explained using traditional thinking about competitive strategy. These companies have succeeded by pursuing constantly evolving strategies in market spaces that were considered unattractive according to traditional measures. In this article--the third in an HBR series by Kathleen Eisenhardt and Donald Sull on strategy in the new economy--the authors ask, what are the sources of competitive advantage in high-velocity markets? The secret, they say, is strategy as simple rules. The companies know that the greatest opportunities for competitive advantage lie in market confusion, but they recognize the need for a few crucial strategic processes and a few simple rules. In traditional strategy, advantage comes from exploiting resources or stable market positions. In strategy as simple rules, advantage comes from successfully seizing fleeting opportunities. Key strategic processes, such as product innovation, partnering, or spinout creation, place the company where the flow of opportunities is greatest. Simple rules then provide the guidelines within which managers can pursue such opportunities. Simple rules, which grow out of experience, fall into five broad categories: how- to rules, boundary conditions, priority rules, timing rules, and exit rules. Companies with simple-rules strategies must follow the rules religiously and avoid the temptation to change them too frequently. A consistent strategy helps managers sort through opportunities and gain short-term advantage by exploiting the attractive ones. In stable markets, managers rely on complicated strategies built on detailed predictions of the future. But when business is complicated, strategy should be simple. PMID:11189455

  8. 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

  9. DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.

    Directory of Open Access Journals (Sweden)

    Kirill Litovkin

    Full Text Available Prostate cancer (PCa is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF in high-risk patients.A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07 and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72 as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27 in multivariate analysis.Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.

  10. A clinical index to predict progression from mild cognitive impairment to dementia due to Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Sei J Lee

    Full Text Available BACKGROUND: Mild cognitive impairment is often a precursor to dementia due to Alzheimer's disease, but many patients with mild cognitive impairment never develop dementia. New diagnostic criteria may lead to more patients receiving a diagnosis of mild cognitive impairment. OBJECTIVE: To develop a prediction index for the 3-year risk of progression from mild cognitive impairment to dementia relying only on information that can be readily obtained in most clinical settings. DESIGN AND PARTICIPANTS: 382 participants diagnosed with amnestic mild cognitive impairment enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI, a multi-site, longitudinal, observational study. MAIN PREDICTORS MEASURES: Demographics, comorbid conditions, caregiver report of participant symptoms and function, and participant performance on individual items from basic neuropsychological scales. MAIN OUTCOME MEASURE: Progression to probable Alzheimer's disease. KEY RESULTS: Subjects had a mean (SD age of 75 (7 years and 43% progressed to probable Alzheimer's disease within 3 years. Important independent predictors of progression included being female, resisting help, becoming upset when separated from caregiver, difficulty shopping alone, forgetting appointments, number of words recalled from a 10-word list, orientation and difficulty drawing a clock. The final point score could range from 0 to 16 (mean [SD]: 4.2 [2.9]. The optimism-corrected Harrell's c-statistic was 0.71(95% CI: 0.68-0.75. Fourteen percent of subjects with low risk scores (0-2 points, n = 124 converted to probable Alzheimer's disease over 3 years, compared to 51% of those with moderate risk scores (3-8 points, n = 223 and 91% of those with high risk scores (9-16 points, n = 35. CONCLUSIONS: An index using factors that can be obtained in most clinical settings can predict progression from amnestic mild cognitive impairment to probable Alzheimer's disease and may help clinicians

  11. Endometrial thickness, Caucasian ethnicity, and age predict clinical pregnancy following fresh blastocyst embryo transfer: a retrospective cohort

    Directory of Open Access Journals (Sweden)

    Santoro Nanette

    2009-04-01

    Full Text Available Abstract Background In-vitro fertilization (IVF with blastocyst as opposed to cleavage stage embryos has been advocated to improve success rates. Limited information exists on which to predict which patients undergoing blastocyst embryo transfer (BET will achieve pregnancy. This study's objective was to evaluate the predictive value of patient and cycle characteristics for clinical pregnancy following fresh BET. Methods This was a retrospective cohort study from 2003–2007 at an academic assisted reproductive program. 114 women with infertility underwent fresh IVF with embryo transfer. We studied patients undergoing transfer of embryos at the blastocyst stage of development. Our main outcome of interest was clinical pregnancy. Clinical pregnancy and its associations with patient characteristics (age, body mass index, FSH, ethnicity and cycle parameters (thickness of endometrial stripe, number eggs, available cleaving embryos, number blastocysts available, transferred, and cryopreserved, and embryo quality were examined using Student's T test and Mann-Whitney-U tests as appropriate. Multivariable logistic regression models were created to determine independent predictors of CP following BET. Receiver Operating Characteristic analyses were used to determine the optimal thickness of endometrial stripe for predicting clinical pregnancy. Results Patients achieving clinical pregnancy demonstrated a thicker endometrial stripe and were younger preceding embryo transfer. On multivariable logistic regression analyses, Caucasian ethnicity (OR 2.641, 95% CI 1.054–6.617, thickness of endometrial stripe, (OR 1.185, 95% CI 1.006–1.396 and age (OR 0.879, 95% CI 0.789–0.980 predicted clinical pregnancy. By receiver operating characteristic analysis, endometrial stripe ≥ 9.4 mm demonstrated a sensitivity of 83% for predicting clinical pregnancy following BET. Conclusion In a cohort of patients undergoing fresh BET, thicker endometrial stripe, Caucasian

  12. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Heyer, Christoph M.; Lemburg, Stefan P.; Nicolas, Volkmar; Roggenland, Daniela [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Ruhr-University of Bochum, Institute of Diagnostic Radiology, Interventional Radiology and Nuclear Medicine, Bochum (Germany); Knoop, Heiko [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Medical Clinic III - Pneumology, Allergology, and Sleep Medicine, Bochum (Germany); Holland-Letz, Tim [Ruhr-University of Bochum, Department of Medical Informatics, Biometry and Epidemiology, Bochum (Germany)

    2011-09-15

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 {+-} 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 {+-} 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  13. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    International Nuclear Information System (INIS)

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 ± 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 ± 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  14. Prognostic prediction through biclustering-based classification of clinical gene expression time series.

    Science.gov (United States)

    Carreiro, André V; Anunciação, Orlando; Carriço, João A; Madeira, Sara C

    2011-01-01

    The constant drive towards a more personalized medicine led to an increasing interest in temporal gene expression analyzes. It is now broadly accepted that considering a temporal perpective represents a great advantage to better understand disease progression and treatment results at a molecular level. In this context, biclustering algorithms emerged as an important tool to discover local expression patterns in biomedical applications, and CCC-Biclustering arose as an efficient algorithm relying on the temporal nature of data to identify all maximal temporal patterns in gene expression time series. In this work, CCC-Biclustering was integrated in new biclustering-based classifiers for prognostic prediction. As case study we analyzed multiple gene expression time series in order to classify the response of Multiple Sclerosis patients to the standard treatment with Interferon-β, to which nearly half of the patients reveal a negative response. In this scenario, using an effective predictive model of a patient's response would avoid useless and possibly harmful therapies for the non-responder group. The results revealed interesting potentialities to be further explored in classification problems involving other (clinical) time series. PMID:21926438

  15. Clinical usefulness of the clock drawing test applying rasch analysis in predicting of cognitive impairment.

    Science.gov (United States)

    Yoo, Doo Han; Lee, Jae Shin

    2016-07-01

    [Purpose] This study examined the clinical usefulness of the clock drawing test applying Rasch analysis for predicting the level of cognitive impairment. [Subjects and Methods] A total of 187 stroke patients with cognitive impairment were enrolled in this study. The 187 patients were evaluated by the clock drawing test developed through Rasch analysis along with the mini-mental state examination of cognitive evaluation tool. An analysis of the variance was performed to examine the significance of the mini-mental state examination and the clock drawing test according to the general characteristics of the subjects. Receiver operating characteristic analysis was performed to determine the cutoff point for cognitive impairment and to calculate the sensitivity and specificity values. [Results] The results of comparison of the clock drawing test with the mini-mental state showed significant differences in according to gender, age, education, and affected side. A total CDT of 10.5, which was selected as the cutoff point to identify cognitive impairement, showed a sensitivity, specificity, Youden index, positive predictive, and negative predicive values of 86.4%, 91.5%, 0.8, 95%, and 88.2%. [Conclusion] The clock drawing test is believed to be useful in assessments and interventions based on its excellent ability to identify cognitive disorders.

  16. Clinical diaries in COPD: compliance and utility in predicting acute exacerbations

    Directory of Open Access Journals (Sweden)

    Walters EH

    2012-07-01

    Full Text Available E Haydn Walters,1 Julia Walters,1 Karen E Wills,1 Andrew Robinson,2 Richard Wood-Baker11Menzies Research Institute Tasmania, University of Tasmania, Hobart; 2School of Nursing and Midwifery, University of Tasmania, Hobart, AustraliaBackground: Daily diaries are often used to collect data on disease activity, but are burdensome and compliance may be poor. Their use in chronic obstructive pulmonary disease (COPD and impact on the prevention and treatment of exacerbations is poorly researched.Methods: We investigated diary-keeping in COPD and ascertained items that best predicted emergency attendances for exacerbations. Participants in the active limb of a clinical trial in COPD kept daily diaries rating breathlessness, cough, sputum, physical activity, and use of reliever medication.Results: Data on 55 participants, 67% of whom were female, showed that overall compliance with diary-keeping was 62%. Participants educated to primary school level only had lower compliance (P = 0.05. Twenty patients had at least one emergency attendance, in whom the relative risk of an acute exacerbation for an increase in item score rose from six days prior to hospitalization, most sharply in the last two days. Even for optimal combinations of items, the positive predictive value was poor, the best combination being cough, activity level, and inhaler use.Conclusion: Good compliance can be achieved using daily diaries in COPD, although this is worse in those with a poor educational level. Diary-keeping is not accurate in predicting acute exacerbations, but could be substantially simplified without loss of efficiency.Keywords: chronic obstructive pulmonary disease, daily diary, secondary prevention

  17. Traditional clinical risk factors predict clopidogrel hypo-responsiveness in unselected patients undergoing non-emergent percutaneous coronary intervention

    DEFF Research Database (Denmark)

    Ratcovich, Hanna; Holmvang, Lene; Johansson, Pär Inge;

    2016-01-01

    High and low platelet reactivity, HPR and LPR respectively, to clopidogrel and aspirin have previously been associated with adverse events following percutaneous coronary intervention (PCI). The aim is to test the ability of a previously developed clinical risk-score, the PREDICT score, to identify...... of PREDICT score variables and the incidence of HPR for clopidogrel (HPR (ADP)) (p ... = 0.003); 7-9 points OR 9.84 (95% CI 3.49-27.7, p clopidogrel LPR (LPR (ADP)). On the other hand, there was no clear association between PREDICT score and AA response. The PREDICT...

  18. Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

    Science.gov (United States)

    Maurel, Joan; Postigo, Antonio

    2015-01-01

    Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients. PMID:26452385

  19. PREDICTING OUTCOME AND SEVERITY IN ACUTE ORGANOPHOSPHOROUS POISONING WITH CLINICAL SCORING AND SERUM CHOLINESTERASE LEVELS

    Directory of Open Access Journals (Sweden)

    Basavaraj R

    2014-11-01

    Full Text Available BACKGROUND AND OBJECTIVES: Organophosphorus compound poisoning is the most common medico toxic emergency in India the increase in pesticide use in agriculture has paralleled the increase in the use of these products for deliberate self-warm. Respiratory failure is the most common complication of OP poisoning leading to death. Early recognition and prompt ventilator support may improve survival. Owing to limited availability of resources, all OP poisoning patients are not managed in ICUs in Indian setup. It is therefore important that clinical features and criteria to predict the need for ventilator support be identified at initial examination. Hence this study was undertaken to assess the severity of organophosphorus compound poisoning both clinically by using Peradeniya scoring and by estimating serum choline esterase levels. METHODS: Cross sectional study was done at basaveswar teaching and general hospital attached to MR Medical College. Cases with history of exposure to organophosphorus compound within previous 24 hours were chosen after applying inclusion and exclusion criteria. Patients were evaluated for Peradeniya OP poisoning scale and serum cholinesterase levels for assessment of severity of poisoning. Serum cholinesterase levels and Peradeniya OP poisoning scale were studied to predict the need for ventilator support. The results were analyzed using Chi-square test. STATISTICAL ANALYSIS: It was done using pearson’s chi square test. RESULTS: In this study requirement of ventilator support was seen in 36% of patients. Mortality in our study was 18%. Only 15.6% of patients with mild grade of poisoning according to Peradeniya OP poisoning scale required ventilator support, whereas 84.4% did not require ventilator support. Most of patients with moderate (70.6% and severe poisoning (100% according to Peradeniya OP poisoning scale required ventilator support. 93.7% of patients with serum cholinesterase levels more than 50% did not require

  20. Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.

    Science.gov (United States)

    Kamkar, Iman; Gupta, Sunil Kumar; Phung, Dinh; Venkatesh, Svetha

    2015-02-01

    Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are captured through a set of diagnoses and procedures codes. These codes are usually represented in a tree form (e.g. ICD-10 tree) and the codes within a tree branch may be highly correlated. These codes can be used as features to build a prediction model and an appropriate feature selection can inform a clinician about important risk factors for a disease. Traditional feature selection methods (e.g. Information Gain, T-test, etc.) consider each variable independently and usually end up having a long feature list. Recently, Lasso and related l1-penalty based feature selection methods have become popular due to their joint feature selection property. However, Lasso is known to have problems of selecting one feature of many correlated features randomly. This hinders the clinicians to arrive at a stable feature set, which is crucial for clinical decision making process. In this paper, we solve this problem by using a recently proposed Tree-Lasso model. Since, the stability behavior of Tree-Lasso is not well understood, we study the stability behavior of Tree-Lasso and compare it with other feature selection methods. Using a synthetic and two real-world datasets (Cancer and Acute Myocardial Infarction), we show that Tree-Lasso based feature selection is significantly more stable than Lasso and comparable to other methods e.g. Information Gain, ReliefF and T-test. We further show that, using different types of classifiers such as logistic regression, naive Bayes, support vector machines, decision trees and Random Forest, the classification performance of Tree-Lasso is comparable to Lasso and better than other methods. Our result has implications in identifying stable risk factors for many healthcare problems and therefore can

  1. Semi-empirical correlation for binary interaction parameters of the Peng–Robinson equation of state with the van der Waals mixing rules for the prediction of high-pressure vapor–liquid equilibrium

    Directory of Open Access Journals (Sweden)

    Seif-Eddeen K. Fateen

    2013-03-01

    Full Text Available Peng–Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij. In this work, we developed a semi-empirical correlation for kij partly based on the Huron–Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation.

  2. Cosmic Sum Rules

    DEFF Research Database (Denmark)

    T. Frandsen, Mads; Masina, Isabella; Sannino, Francesco

    2011-01-01

    We introduce new sum rules allowing to determine universal properties of the unknown component of the cosmic rays and show how it can be used to predict the positron fraction at energies not yet explored by current experiments and to constrain specific models.......We introduce new sum rules allowing to determine universal properties of the unknown component of the cosmic rays and show how it can be used to predict the positron fraction at energies not yet explored by current experiments and to constrain specific models....

  3. Predictive factors of clinical response in steroid-refractory ulcerative colitis treated with granulocyte-monocyte apheresis

    Institute of Scientific and Technical Information of China (English)

    Valeria D'Ovidio; Donatella Meo; Angelo Viscido; Giampaolo Bresci; Piero Vernia; Renzo Caprilli

    2011-01-01

    AIM: To identify factors predicting the clinical response of ulcerative colitis patients to granulocyte-monocyte apheresis (GMA).METHODS: Sixty-nine ulcerative colitis patients (39 F, 30 M) dependent upon/refractory to steroids were treated with GMA.Steroid dependency, clinical activity index (CAI), C reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), values at baseline, use of immunosuppressant, duration of disease, and age and extent of disease were considered for statistical analysis as predictive factors of clinical response.Univariate and multivariate logistic regression models were used.RESULTS: In the univariate analysis, CAI (P = 0.039) and ESR (P = 0.017) levels at baseline were singled out as predictive of clinical remission.In the multivariate analysis steroid dependency [Odds ratio (OR) = 0.390, 95% Confidence interval (CI): 0.176-0.865, Wald 5.361, P = 0.0160] and low CAI levels at baseline (4 < CAI < 7) (OR = 0.770, 95% CI: 0.425-1.394, Wald 3.747, P = 0.028) proved to be effective as factors predicting clinical response.CONCLUSION: GMA may be a valid therapeutic option for steroid-dependent ulcerative colitis patients with mild-moderate disease and its clinical efficacy seems to persist for 12 mo.

  4. Evaluation of clinical and immunological markers for predicting virological failure in a HIV/AIDS treatment cohort in Busia, Kenya.

    Directory of Open Access Journals (Sweden)

    Cecilia Ferreyra

    Full Text Available BACKGROUND: In resource-limited settings where viral load (VL monitoring is scarce or unavailable, clinicians must use immunological and clinical criteria to define HIV virological treatment failure. This study examined the performance of World Health Organization (WHO clinical and immunological failure criteria in predicting virological failure in HIV patients receiving antiretroviral therapy (ART. METHODS: In a HIV/AIDS program in Busia District Hospital, Kenya, a retrospective, cross-sectional cohort analysis was performed in April 2008 for all adult patients (>18 years old on ART for ≥12 months, treatment-naive at ART start, attending the clinic at least once in last 6 months, and who had given informed consent. Treatment failure was assessed per WHO clinical (disease stage 3 or 4 and immunological (CD4 cell count criteria, and compared with virological failure (VL >5,000 copies/mL. RESULTS: Of 926 patients, 123 (13.3% had clinically defined treatment failure, 53 (5.7% immunologically defined failure, and 55 (6.0% virological failure. Sensitivity, specificity, positive predictive value, and negative predictive value of both clinical and immunological criteria (combined in predicting virological failure were 36.4%, 83.5%, 12.3%, and 95.4%, respectively. CONCLUSIONS: In this analysis, clinical and immunological criteria were found to perform relatively poorly in predicting virological failure of ART. VL monitoring and new algorithms for assessing clinical or immunological treatment failure, as well as improved adherence strategies, are required in ART programs in resource-limited settings.

  5. Prediction consistency and clinical presentations of breast cancer molecular subtypes for Han Chinese population

    Directory of Open Access Journals (Sweden)

    Huang Chi-Cheng

    2012-09-01

    Full Text Available Abstract Background Breast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50 as well as clinical presentations of each molecualr subtype in Han Chinese population. Methods In all, 169 breast cancer samples (44 from Taiwan and 125 from China of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50 were retrieved for molecular subtype prediction. Results For Sørlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed. Conclusions We suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective

  6. Development, external validation and clinical usefulness of a practical prediction model for radiation-induced dysphagia in lung cancer patients

    International Nuclear Information System (INIS)

    Introduction: Acute dysphagia is a distressing dose-limiting toxicity occurring frequently during concurrent chemo-radiation or high-dose radiotherapy for lung cancer. It can lead to treatment interruptions and thus jeopardize survival. Although a number of predictive factors have been identified, it is still not clear how these could offer assistance for treatment decision making in daily clinical practice. Therefore, we have developed and validated a nomogram to predict this side-effect. In addition, clinical usefulness was assessed by comparing model predictions to physicians' predictions. Materials and methods: Clinical data from 469 inoperable lung cancer patients, treated with curative intent, were collected prospectively. A prediction model for acute radiation-induced dysphagia was developed. Model performance was evaluated by the c-statistic and assessed using bootstrapping as well as two external datasets. In addition, a prospective study was conducted comparing model to physicians' predictions in 138 patients. Results: The final multivariate model consisted of age, gender, WHO performance status, mean esophageal dose (MED), maximum esophageal dose (MAXED) and overall treatment time (OTT). The c-statistic, assessed by bootstrapping, was 0.77. External validation yielded an AUC of 0.94 on the Ghent data and 0.77 on the Washington University St. Louis data for dysphagia ≥ grade 3. Comparing model predictions to the physicians' predictions resulted in an AUC of 0.75 versus 0.53, respectively. Conclusions: The proposed model performed well was successfully validated and demonstrated the ability to predict acute severe dysphagia remarkably better than the physicians. Therefore, this model could be used in clinical practice to identify patients at high or low risk.

  7. Predictive validity of measurements of clinical competence using the team objective structured bedside assessment (TOSBA): assessing the clinical competence of final year medical students.

    LENUS (Irish Health Repository)

    Meagher, Frances M

    2009-11-01

    The importance of valid and reliable assessment of student competence and performance is gaining increased recognition. Provision of valid patient-based formative assessment is an increasing challenge for clinical teachers in a busy hospital setting. A formative assessment tool that reliably predicts performance in the summative setting would be of value to both students and teachers.

  8. Predicting asthma in preschool children at high risk presenting in primary care: Development of a clinical asthma prediction score

    NARCIS (Netherlands)

    L.B. Van Der Mark (Lonneke); K.E. Wonderen (Karina); J. Mohrs (Jacob); W.M.C. van Aalderen (Willem); G. ter Riet; P.J.E. Bindels (Patrick)

    2014-01-01

    textabstractBackground: A setting-specific asthma prediction score for preschool children with wheezing and/or dyspnoea presenting in primary healthcare is needed since existing indices are mainly based on general populations. Aims: To find an optimally informative yet practical set of predictors fo

  9. pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels.

    Directory of Open Access Journals (Sweden)

    Paul Geeleher

    Full Text Available We recently described a methodology that reliably predicted chemotherapeutic response in multiple independent clinical trials. The method worked by building statistical models from gene expression and drug sensitivity data in a very large panel of cancer cell lines, then applying these models to gene expression data from primary tumor biopsies. Here, to facilitate the development and adoption of this methodology we have created an R package called pRRophetic. This also extends the previously described pipeline, allowing prediction of clinical drug response for many cancer drugs in a user-friendly R environment. We have developed several other important use cases; as an example, we have shown that prediction of bortezomib sensitivity in multiple myeloma may be improved by training models on a large set of neoplastic hematological cell lines. We have also shown that the package facilitates model development and prediction using several different classes of data.

  10. READMIT: a clinical risk index to predict 30-day readmission after discharge from acute psychiatric units.

    Science.gov (United States)

    Vigod, Simone N; Kurdyak, Paul A; Seitz, Dallas; Herrmann, Nathan; Fung, Kinwah; Lin, Elizabeth; Perlman, Christopher; Taylor, Valerie H; Rochon, Paula A; Gruneir, Andrea

    2015-02-01

    Our aim was to create a clinically useful risk index, administered prior to discharge, for determining the probability of psychiatric readmission within 30 days of hospital discharge for general psychiatric inpatients. We used population-level sociodemographic and health administrative data to develop a predictive model for 30-day readmission among adults discharged from an acute psychiatric unit in Ontario, Canada (2008-2011), and converted the final model into a risk index system. We derived the predictive model in one-half of the sample (n = 32,749) and validated it in the other half of the sample (n = 32,750). Variables independently associated with 30-day readmission (forming the mnemonic READMIT) were: (R) Repeat admissions; (E) Emergent admissions (i.e. harm to self/others); (D) Diagnoses (psychosis, bipolar and/or personality disorder), and unplanned Discharge; (M) Medical comorbidity; (I) prior service use Intensity; and (T) Time in hospital. Each 1-point increase in READMIT score (range 0-41) increased the odds of 30-day readmission by 11% (odds ratio 1.11, 95% CI 1.10-1.12). The index had moderate discriminative capacity in both derivation (C-statistic = 0.631) and validation (C-statistic = 0.630) datasets. Determining risk of psychiatric readmission for individual patients is a critical step in efforts to address the potentially avoidable high rate of this negative outcome. The READMIT index provides a framework for identifying patients at high risk of 30-day readmission prior to discharge, and for the development, evaluation and delivery of interventions that can assist with optimizing the transition to community care for patients following psychiatric discharge.

  11. Pediatric in-Hospital Death from Infectious Disease in Uganda: Derivation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Nasim Lowlaavar

    Full Text Available Pediatric hospital mortality from infectious diseases in resource constrained countries remains unacceptably high. Improved methods of risk-stratification can assist in referral decision making and resource allocation. The purpose of this study was to create prediction models for in-hospital mortality among children admitted with suspected infectious diseases.This two-site prospective observational study enrolled children between 6 months and 5 years admitted with a proven or suspected infection. Baseline clinical and laboratory variables were collected on enrolled children. The primary outcome was death during admission. Stepwise logistic regression minimizing Akaike's information criterion was used to identify the most promising multivariate models. The final model was chosen based on parsimony.1307 children were enrolled consecutively, and 65 (5% of whom died during their admission. Malaria, pneumonia and gastroenteritis were diagnosed in 50%, 31% and 8% of children, respectively. The primary model included an abnormal Blantyre coma scale, HIV and weight-for-age z-score. This model had an area under the curve (AUC of 0.85 (95% CI, 0.80-0.89 with a sensitivity and specificity of 83% and 76%, respectively. The positive and negative predictive values were 15% and 99%, respectively. Two alternate models with similar performance characteristics were developed withholding HIV and weight-for-age z-score, for use when these variables are not available.Risk stratification of children admitted with infectious diseases can be calculated based on several easily measured variables. Risk stratification at admission can be used for allocation of scarce human and physical resources and to guide referral among children admitted to lower level health facilities.

  12. Near-infrared spectroscopy in schizophrenia: A possible biomarker for predicting clinical outcome and treatment response

    Directory of Open Access Journals (Sweden)

    Shinsuke eKoike

    2013-11-01

    Full Text Available Functional near-infrared spectroscopy (fNIRS is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography, fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and noninvasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an

  13. VIDAS D-dimer in combination with clinical pre-test probability to rule out pulmonary embolism. A systematic review of management outcome studies.

    Science.gov (United States)

    Carrier, Marc; Righini, Marc; Djurabi, Reza Karami; Huisman, Menno V; Perrier, Arnaud; Wells, Philip S; Rodger, Marc; Wuillemin, Walter A; Le Gal, Grégoire

    2009-05-01

    Clinical outcome studies have shown that it is safe to withhold anticoagulant therapy in patients with suspected pulmonary embolism (PE) who have a negative D-dimer result and a low pretest probability (PTP) either using a PTP model or clinical gestalt. It was the objective of the present study to assess the safety of the combination of a negative VIDAS D-dimer result in combination with a non-high PTP using the Wells or Geneva models to exclude PE. A systematic literature search strategy was conducted using MEDLINE, EMBASE, the Cochrane Register of Controlled Trials and all EBM Reviews. Seven studies (6 prospective management studies and 1 randomised controlled trial) reporting failure rates at three months were included in the analysis. Non-high PTP was defined as "unlikely" using the Wells' model, or "low/intermediate" PTP using either the Geneva score, the Revised Geneva Score, or clinical gestalt. Two reviewers independently extracted data onto standardised forms. A total of 5,622 patients with low/intermediate or unlikely PTP were assessed using the VIDAS D-dimer. PE was ruled out by a negative D-dimer test in 2,248 (40%, 95% confidence intervals [CI] 38.7 to 41.3%) of them. The three-month thromboembolic risk in patients left untreated on the basis of a low/intermediate or unlikely PTP and a negative D-dimer test was 3/2,166 (0.14%, 95% CI 0.05 to 0.41%). In conclusion, the combination of a negative VIDAS D-dimer result and a non-high PTP effectively and safely excludes PE in an important proportion of outpatients with suspected PE. PMID:19404542

  14. DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES

    OpenAIRE

    L. V. Mirylenko; O. G. Sukonko; A. V. Pravorov; A. I. Rolevich; A. S. Mavrichev

    2014-01-01

    Objective: to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (рN+) in bladder cancer patients.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. Mono- and multivariate logistic regression analyses were used for pN+ prediction on preoperative data. Coefficients from logistic regression equation were used to construct the n...

  15. Predictive validity of the UK clinical aptitude test in the final years of medical school: a prospective cohort study

    OpenAIRE

    Husbands, Adrian; Mathieson, Alistair; Dowell, Jonathan; Cleland, Jennifer; MacKenzie, Rhoda

    2014-01-01

    Background The UK Clinical Aptitude Test (UKCAT) was designed to address issues identified with traditional methods of selection. This study aims to examine the predictive validity of the UKCAT and compare this to traditional selection methods in the senior years of medical school. This was a follow-up study of two cohorts of students from two medical schools who had previously taken part in a study examining the predictive validity of the UKCAT in first year. Methods The sample consisted of ...

  16. Innovative drugs to treat depression: did animal models fail to be predictive or did clinical trials fail to detect effects?

    Science.gov (United States)

    Belzung, Catherine

    2014-04-01

    Over recent decades, encouraging preclinical evidence using rodent models pointed to innovative pharmacological targets to treat major depressive disorder. However, subsequent clinical trials have failed to show convincing results. Two explanations for these rather disappointing results can be put forward, either animal models of psychiatric disorders have failed to predict the clinical effectiveness of treatments or clinical trials have failed to detect the effects of these new drugs. A careful analysis of the literature reveals that both statements are true. Indeed, in some cases, clinical efficacy has been predicted on the basis of inappropriate animal models, although the contrary is also true, as some clinical trials have not targeted the appropriate dose or clinical population. On the one hand, refinement of animal models requires using species that have better homological validity, designing models that rely on experimental manipulations inducing pathological features, and trying to model subtypes of depression. On the other hand, clinical research should consider carefully the results from preclinical studies, in order to study these compounds at the correct dose, in the appropriate psychiatric nosological entity or symptomatology, in relevant subpopulations of patients characterized by specific biomarkers. To achieve these goals, translational research has to strengthen the dialogue between basic and clinical science. PMID:24345817

  17. Pre- and Post-Operative Nomograms to Predict Recurrence-Free Probability in Korean Men with Clinically Localized Prostate Cancer

    OpenAIRE

    Minyong Kang; Chang Wook Jeong; Woo Suk Choi; Yong Hyun Park; Sung Yong Cho; Sangchul Lee; Seung Bae Lee; Ja Hyeon Ku; Sung Kyu Hong; Seok-Soo Byun; Hyeon Jeong; Cheol Kwak; Hyeon Hoe Kim; Eunsik Lee; Sang Eun Lee

    2014-01-01

    OBJECTIVES: Although the incidence of prostate cancer (PCa) is rapidly increasing in Korea, there are few suitable prediction models for disease recurrence after radical prostatectomy (RP). We established pre- and post-operative nomograms estimating biochemical recurrence (BCR)-free probability after RP in Korean men with clinically localized PCa. PATIENTS AND METHODS: Our sampling frame included 3,034 consecutive men with clinically localized PCa who underwent RP at our tertiary centers from...

  18. Combination of Circulating Tumor Cells with Serum Carcinoembryonic Antigen Enhances Clinical Prediction of Non-Small Cell Lung Cancer

    OpenAIRE

    Xi Chen; Xu Wang; Hua He; Ziling Liu; Ji-Fan Hu; Wei Li

    2015-01-01

    Circulating tumor cells (CTCs) have emerged as a potential biomarker in the diagnosis, prognosis, treatment, and surveillance of lung cancer. However, CTC detection is not only costly, but its sensitivity is also low, thus limiting its usage and the collection of robust data regarding the significance of CTCs in lung cancer. We aimed to seek clinical variables that enhance the prediction of CTCs in patients with non-small cell lung cancer (NSCLC). Clinical samples and pathological data were c...

  19. Preoperative neutrophil response as a predictive marker of clinical outcome following open heart surgery and the impact of leukocyte filtration.

    LENUS (Irish Health Repository)

    Soo, Alan W

    2010-11-01

    Open heart surgery is associated with a massive systemic inflammatory response. Neutrophils, are the main mediator of this response. We hypothesised that the degree of neutrophil activation and inflammatory response to open heart surgery varies individually and correlates with clinical outcome. The aim of this study was to determine if individual clinical outcome can be predicted preoperatively through assessment of in-vitro stimulated neutrophil responses. Following that, the effects of neutrophil depletion through leukocyte filters are examined.

  20. Neutrino Mass Sum Rules

    CERN Document Server

    Spinrath, Martin

    2016-01-01

    Neutrino mass sum rules are an important class of predictions in flavour models relating the Majorana phases to the neutrino masses. This leads, for instance, to enormous restrictions on the effective mass as probed in experiments on neutrinoless double beta decay. While up to now these sum rules have in practically all cases been taken to hold exactly, we will go here beyond that. While the effect of the renormalisation group running can be visible, the qualitative features do not change. This changes somewhat for model dependent corrections which might alter even the qualitative predictions but only for large corrections and a high neutrino mass scale close to the edge of the current limits. This finding backs up the solidity of the predictions derived in the literature apart from some exceptions, and it thus marks a very important step in deriving testable and robust predictions from neutrino flavour models.

  1. Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.

    Science.gov (United States)

    Lee, Ing-Kit; Liu, Jien-Wei; Chen, Yen-Hsu; Chen, Yi-Chun; Tsai, Ching-Yen; Huang, Shi-Yu; Lin, Chun-Yu; Huang, Chung-Hao

    2016-01-01

    the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management. PMID:27138448

  2. Development of a Simple Clinical Risk Score for Early Prediction of Severe Dengue in Adult Patients.

    Directory of Open Access Journals (Sweden)

    Ing-Kit Lee

    , irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management.

  3. Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects

    Directory of Open Access Journals (Sweden)

    Michael Ewers

    2014-01-01

    Full Text Available Brain changes reminiscent of Alzheimer disease (AD have been previously reported in a substantial portion of elderly cognitive healthy (HC subjects. The major aim was to evaluate the accuracy of MRI assessed regional gray matter (GM volume, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET, and neuropsychological test scores to identify those HC subjects who subsequently convert to mild cognitive impairment (MCI or AD dementia. We obtained in 54 healthy control (HC subjects a priori defined region of interest (ROI values of medial temporal and parietal FDG-PET and medial temporal GM volume. In logistic regression analyses, these ROI values were tested together with neuropsychological test scores (free recall, trail making test B (TMT-B as predictors of HC conversion during a clinical follow-up between 3 and 4 years. In voxel-based analyses, FDG-PET and MRI GM maps were compared between HC converters and HC non-converters. Out of the 54 HC subjects, 11 subjects converted to MCI or AD dementia. Lower FDG-PET ROI values were associated with higher likelihood of conversion (p = 0.004, with the area under the curve (AUC yielding 82.0% (95% CI = (95.5%, 68.5%. The GM volume ROI was not a significant predictor (p = 0.07. TMT-B but not the free recall tests were a significant predictor (AUC = 71% (95% CI = 50.4%, 91.7%. For the combination of FDG-PET and TMT-B, the AUC was 93.4% (sensitivity = 82%, specificity = 93%. Voxel-based group comparison showed reduced FDG-PET metabolism within the temporo-parietal and prefrontal cortex in HC converters. In conclusion, medial temporal and-parietal FDG-PET and executive function show a clinically acceptable accuracy for predicting clinical progression in elderly HC subjects.

  4. Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT)

    Science.gov (United States)

    Saiag, P.; Gutzmer, R.; Ascierto, P. A.; Maio, M.; Grob, J.-J.; Murawa, P.; Dreno, B.; Ross, M.; Weber, J.; Hauschild, A.; Rutkowski, P.; Testori, A.; Levchenko, E.; Enk, A.; Misery, L.; Vanden Abeele, C.; Vojtek, I.; Peeters, O.; Brichard, V. G.; Therasse, P.

    2016-01-01

    Background Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. Patients and methods An open-label prospective phase II trial (‘PREDICT’) in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Results Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS− populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS− patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS−). There was one complete response (GS−) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Conclusion Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS− and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study. This study is registered at www.clinicatrials.gov NCT00942162. PMID:27502712

  5. XPG rs2296147 T>C polymorphism predicted clinical outcome in colorectal cancer.

    Science.gov (United States)

    Wang, Fang; Zhang, Shao-Dan; Xu, Hong-Mei; Zhu, Jin-Hong; Hua, Rui-Xi; Xue, Wen-Qiong; Li, Xi-Zhao; Wang, Tong-Min; He, Jing; Jia, Wei-Hua

    2016-03-01

    Xeroderma pigmentosum group G (XPG), one of key components of nucleotide excision repair pathway (NER), is involved in excision repair of UV-induced DNA damage. Single nucleotide polymorphisms (SNPs) in the XPG gene have been reported to associate with the clinical outcome of various cancer patients. We aimed to assess the impact of four potentially functional SNPs (rs2094258 C>T, rs2296147 T>C, rs751402 G>A, and rs873601 G>A) in the XPG gene on prognosis in colorectal cancer (CRC) patients. A total of 1901 patients diagnosed with pathologically confirmed CRC were genotyped for four XPG polymorphisms. Cox proportional hazards model analysis controlled for several confounding factors was conducted to compute hazard ratios (HRs) and 95% confidence intervals (CIs). Of the four included SNPs, only rs2296147 was shown to significantly affect progression-free survival (PFS) in CRC. Patients carrying rs2296147 CT/TT genotype had a significantly shorter median 10 years PFS than those carrying CC genotype (88.5 months vs. 118.1 months), and an increased progression risk were observed with rs2296147 (HR = 1.324, 95% CI = 1.046-1.667). Moreover, none of the four SNPs were associated with overall survival. In conclusion, our study showed that XPG rs2296147 CT/TT variants conferred significant survival disadvantage in CRC patients in term of PFS. XPG rs2296147 polymorphism could be predictive of unfavorable prognosis of CRC patients. PMID:26887052

  6. Late gadolinium enhancement cardiovascular magnetic resonance predicts clinical worsening in patients with pulmonary hypertension

    Directory of Open Access Journals (Sweden)

    Freed Benjamin H

    2012-02-01

    Full Text Available Abstract Background Late gadolinium enhancement (LGE occurs at the right ventricular (RV insertion point (RVIP in patients with pulmonary hypertension (PH and has been shown to correlate with cardiovascular magnetic resonance (CMR derived RV indices. However, the prognostic role of RVIP-LGE and other CMR-derived parameters of RV function are not well established. Our aim was to evaluate the predictive value of contrast-enhanced CMR in patients with PH. Methods RV size, ejection fraction (RVEF, and the presence of RVIP-LGE were determined in 58 patients with PH referred for CMR. All patients underwent right heart catheterization, exercise testing, and N-terminal pro-brain natriuretic peptide (NT-proBNP evaluation; results of which were included in the final analysis if performed within 4 months of the CMR study. Patients were followed for the primary endpoint of time to clinical worsening (death, decompensated right ventricular heart failure, initiation of prostacyclin, or lung transplantation. Results Overall, 40/58 (69% of patients had RVIP-LGE. Patients with RVIP- LGE had larger right ventricular volume index, lower RVEF, and higher mean pulmonary artery pressure (mPAP, all p Conclusions The presence of RVIP-LGE in patients with PH is a marker for more advanced disease and poor prognosis. In addition, this study reveals for the first time that CMR-derived RVEF is an independent non-invasive imaging predictor of adverse outcomes in this patient population.

  7. Angiographically Negative Acute Arterial Upper and Lower Gastrointestinal Bleeding: Incidence, Predictive Factors, and Clinical Outcomes

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Hyoung; Shin, Ji Hoon; Yoon, Hyun Ki; Chae, Eun Young; Myung, Seung Jae; Ko, Gi Young; Gwon, Dong Il; Sung, Kyu Bo [Asan Medical Center, Seoul (Korea, Republic of)

    2009-08-15

    To evaluate the incidence, predictive factors, and clinical outcomes of angiographically negative acute arterial upper and lower gastrointestinal (GI) bleeding. From 2001 to 2008, 143 consecutive patients who underwent an angiography for acute arterial upper or lower GI bleeding were examined. The angiographies revealed a negative bleeding focus in 75 of 143 (52%) patients. The incidence of an angiographically negative outcome was significantly higher in patients with a stable hemodynamic status (p < 0.001), or in patients with lower GI bleeding (p = 0.032). A follow-up of the 75 patients (range: 0-72 months, mean: 8 {+-} 14 months) revealed that 60 of the 75 (80%) patients with a negative bleeding focus underwent conservative management only, and acute bleeding was controlled without rebleeding. Three of the 75 (4%) patients underwent exploratory surgery due to prolonged bleeding; however, no bleeding focus was detected. Rebleeding occurred in 12 of 75 (16%) patients. Of these, six patients experienced massive rebleeding and died of disseminated intravascular coagulation within four to nine hours after the rebleeding episode. Four of the 16 patients underwent a repeat angiography and the two remaining patients underwent a surgical intervention to control the bleeding. Angiographically negative results are relatively common in patients with acute GI bleeding, especially in patients with a stable hemodynamic status or lower GI bleeding. Most patients with a negative bleeding focus have experienced spontaneous resolution of their condition.

  8. Prediction of the potential clinical outcomes for post-resuscitated patients after cardiac arrest

    Science.gov (United States)

    Hong, Sungmin; Kwon, Bojun; Yun, Il Dong; Lee, Sang Uk; Kim, Kyuseok; Kim, Joonghee

    2013-02-01

    Cerebral injuries after cardiac arrest are serious causes for morbidity. Many previous researches in the medical society have been proposed to prognosticate the functional recoveries of post-resuscitated patients after cardiac arrest, but the validity of suggested features and the automation of prognostication have not been made yet. This paper presents the automatic classification method which predicts the potential clinical outcomes of post-resuscitated patients who suffered from cardiac arrest. The global features and the local features are adapted from the researches from the medical society. The global features, which are consisted of the percentage of the partial volume under the uniformly increasing thresholds, represent the global tendency of apparent diffusion coefficient value in a DWI. The local features are localized and measured on the refined local apparent diffusion coefficient minimal points. The local features represent the ischemic change of small areas in a brain. The features are trained and classified by the random forest method, which have been widely used in the machine learning society for classification. The validity of features is automatically evaluated during the classification process. The proposed method achieved the 0.129 false-positive rate while maintaining the perfect true-positive rate. The area-under-curve of the proposed method was 0.9516, which showed the feasibility and the robustness of the proposed method.

  9. Primary gastric mucosa associated lymphoid tissue lymphoma: Clinical data predicted treatment outcome

    Institute of Scientific and Technical Information of China (English)

    Milena Todorovic; Miodrag Krstic; Bela Balint; Miodrag Jevtic; Nada Suvajdzic; Amela Ceric; Dragana Stamatovic; Olivera Markovic; Maja Perunicic; Slobodan Marjanovic

    2008-01-01

    AIM: To determine clinical characteristics and treatmentoutcome of gastric lymphoma after chemotherapy and immuno-chemotherapy.METHODS: Thirty four patients with primary gastric mucosa associated lymphoid tissue (MALT) lymphoma (Ann Arbor stages I to IV) were enrolled. All had upper gastric endoscopy, abdominal ultrasonography, CT and H py/or/status assessment (histology and serology).After anti-/-/py/or/treatment and initial chemotherapy,patients were re-examined every 4 mo.RESULTS: Histological regression of the lymphoma wascomplete in 22/34 (64.7%) and partial in 9 (26.5%)patients. Median follow up time for these 31 responders was 60 mo (range 48-120). No regression was noted in 3 patients. Among the 25 (73.5%) H py/or/positive patients, the eradication rate was 100%.CONCLUSION: Using univariate analysis, predictive factors for overall survival were international prognostic index (IPI) score, hemoglobin level, erythrocyte sedimentation rate (ESR), and platelet numbers (P < 0.005). In addition to this, Cox proportion hazard model differentiate IPI score, ESR, and platelets as predictors of survival.

  10. The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School

    Directory of Open Access Journals (Sweden)

    James David

    2010-07-01

    Full Text Available Abstract Background The UK Clinical Aptitude Test (UKCAT was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis, and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown. The study objective was to determine whether UKCAT scores predict performance during the first two years of the 5-year undergraduate medical course at Nottingham. Methods We studied a single cohort of students, who entered Nottingham Medical School in October 2007 and had taken the UKCAT. We used linear regression analysis to identify independent predictors of marks for different parts of the 2-year preclinical course. Results Data were available for 204/260 (78% of the entry cohort. The UKCAT total score had little predictive value. Quantitative Reasoning was a significant independent predictor of course marks in Theme A ('The Cell', (p = 0.005, and Verbal Reasoning predicted Theme C ('The Community' (p Conclusion This limited study from a single entry cohort at one medical school suggests that the predictive value of the UKCAT, particularly the total score, is low. Section scores may predict success in specific types of course assessment. The ultimate test of validity will not be available for some years, when current cohorts of students graduate. However, if this test of mental ability does not predict preclinical performance, it is arguably less likely to predict the outcome in the clinical years. Further research from medical schools with different types of curriculum and assessment is needed, with longitudinal studies throughout the course.

  11. Following the Rules Set by Accreditation Agencies and Governing Bodies to Maintain In-Compliance Status: Applying Critical Thinking Skills When Evaluating the Need for Change in the Clinical Laboratory.

    Science.gov (United States)

    Byrne, Karen M; Levy, Kimberly Y; Reese, Erika M

    2016-05-01

    Maintaining an in-compliance clinical laboratory takes continuous awareness and review of standards, regulations, and best practices. A strong quality assurance program and well informed leaders who maintain professional networks can aid in this necessary task. This article will discuss a process that laboratories can follow to interpret, understand, and comply with the rules and standards set by laboratory accreditation bodies. PMID:26945880

  12. Following the Rules Set by Accreditation Agencies and Governing Bodies to Maintain In-Compliance Status: Applying Critical Thinking Skills When Evaluating the Need for Change in the Clinical Laboratory.

    Science.gov (United States)

    Byrne, Karen M; Levy, Kimberly Y; Reese, Erika M

    2016-05-01

    Maintaining an in-compliance clinical laboratory takes continuous awareness and review of standards, regulations, and best practices. A strong quality assurance program and well informed leaders who maintain professional networks can aid in this necessary task. This article will discuss a process that laboratories can follow to interpret, understand, and comply with the rules and standards set by laboratory accreditation bodies.

  13. Comparison of AIMS65 Score and Other Scoring Systems for Predicting Clinical Outcomes in Koreans with Nonvariceal Upper Gastrointestinal Bleeding

    Science.gov (United States)

    Park, Sung Min; Yeum, Seok Cheon; Kim, Byung-Wook; Kim, Joon Sung; Kim, Ji Hee; Sim, Eun Hui; Ji, Jeong-Seon; Choi, Hwang

    2016-01-01

    Background/Aims The AIMS65 score has not been sufficiently validated in Korea. The objective of this study was to compare the AIMS65 and other scoring systems for the prediction of various clinical outcomes in Korean patients with acute nonvariceal upper gastrointestinal bleeding (NVUGIB). Methods The AIMS65 score, clinical and full Rockall scores (cRS and fRS) and Glasgow-Blatchford (GBS) score were calculated in patients with NVUGIB in a single center retrospectively. The performance of these scores for predicting mortality, rebleeding, transfusion requirement, and endoscopic intervention was assessed by calculating the area under the receiver-operating characteristic curve. Results Of the 523 patients, 3.4% died within 30 days, 2.5% experienced rebleeding, 40.0% required endoscopic intervention, and 75.7% needed transfusion. The AIMS65 score was useful for predicting the 30-day mortality, the need for endoscopic intervention and for transfusion. The fRS was superior to the AIMS65, GBS, and cRS for predicting endoscopic intervention and the GBS was superior to the AIMS65, fRS, and cRS for predicting the transfusion requirement. Conclusions The AIMS65 score was useful for predicting the 30-day mortality, transfusion requirement, and endoscopic intervention in Korean patients with acute NVUGIB. However, it was inferior to the GBS and fRS for predicting the transfusion requirement and endoscopic intervention, respectively. PMID:27377742

  14. External validation of a clinical scoring system for the risk of gestational diabetes mellitus

    NARCIS (Netherlands)

    van Leeuwen, M.; Opmeer, B. C.; Zweers, E. J. K.; van Ballegooie, E.; ter Brugge, H. G.; de Valk, H. W.; Visser, G. H. A.; Mol, B. W. J.

    2009-01-01

    Aim: A prediction rule for gestational diabetes mellitus (GDM) could be helpful in early detection and increased efficiency of screening. A prediction rule by means of a clinical scoring system is available, but has never been validated externally. The aim of this study was to validate the scoring s

  15. Applying psychological theory to evidence-based clinical practice: identifying factors predictive of taking intra-oral radiographs.

    Science.gov (United States)

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

    2006-10-01

    This study applies psychological theory to the implementation of evidence-based clinical practice. The first objective was to see if variables from psychological frameworks (developed to understand, predict and influence behaviour) could predict an evidence-based clinical behaviour. The second objective was to develop a scientific rationale to design or choose an implementation intervention. Variables from the Theory of Planned Behaviour, Social Cognitive Theory, Self-Regulation Model, Operant Conditioning, Implementation Intentions and the Precaution Adoption Process were measured, with data collection by postal survey. The primary outcome was the number of intra-oral radiographs taken per course of treatment collected from a central fee claims database. Participants were 214 Scottish General Dental Practitioners. At the theory level, the Theory of Planned Behaviour explained 13% variance in the number of radiographs taken, Social Cognitive Theory explained 7%, Operant Conditioning explained 8%, Implementation Intentions explained 11%. Self-Regulation and Stage Theory did not predict significant variance in radiographs taken. Perceived behavioural control, action planning and risk perception explained 16% of the variance in number of radiographs taken. Knowledge did not predict the number of radiographs taken. The results suggest an intervention targeting predictive psychological variables could increase the implementation of this evidence-based practice, while influencing knowledge is unlikely to do so. Measures which predicted number of radiographs taken also predicted intention to take radiographs, and intention accounted for significant variance in behaviour (adjusted R(2)=5%: F(1,166)=10.28, pservice-level trial. Since psychological frameworks incorporate methodologies to measure and change component variables, taking a theory-based approach enabled the creation of a methodology that can be replicated for identifying factors predictive of clinical behaviour

  16. Factors predictive of clinical pregnancy in the first intrauterine insemination cycle of 306 couples with favourable female patient characteristics.

    Science.gov (United States)

    Aydin, Yunus; Hassa, Hikmet; Oge, Tufan; Tokgoz, Vehbi Yavuz

    2013-12-01

    The objective of this study was to evaluate the factors predictive of clinical pregnancy in the first superovulation/intrauterine insemination (SO/IUI) cycle of couples with favourable female characteristics. We analyzed retrospectively the first SO/IUI cycle of 306 infertile couples with mild male factor infertility and unexplained infertility. The women had a favourable prognosis in terms of ovarian reserve. Univariate logistic regression analyses identified body mass index (BMI) [odds ratio (OR) = 0.9, P = 0.014], sperm concentration [OR = 1.007, P = 0.007] and inseminating motile sperm count (IMC) [OR = 1.007, P = 0.032] as significant predictive factors of clinical pregnancy. Multivariate logistic regression analysis identified BMI [OR = 0.87, P = 0.008] and sperm concentration [OR = 1.008, P = 0.011] as significant factors. Pregnant and non-pregnant groups did not differ significantly in terms of the age and smoking status of the woman, duration and type of infertility, length of the stimulation, total gonadotropin dosage or antral follicle count. Of the female characteristics investigated, BMI was the most significant predictive factor of clinical pregnancy in the first SO/IUI cycle of couples with unexplained or mild male factor infertility and favourable female characteristics. In overweight women, weight loss should be advised before starting SO/IUI. Sperm concentration and IMC were significant male predictive factors for clinical pregnancy in the first SO/IUI. PMID:24171641

  17. Clinical Frailty Scale in an Acute Medicine Unit: a Simple Tool That Predicts Length of Stay

    Science.gov (United States)

    Juma, Salina; Taabazuing, Mary-Margaret; Montero-Odasso, Manuel

    2016-01-01

    Background Frailty is characterized by increased vulnerability to external stressors. When frail older adults are admitted to hospital, they are at increased risk of adverse events including falls, delirium, and disability. The Clinical Frailty Scale (CFS) is a practical and efficient tool for assessing frailty; however, its ability to predict outcomes has not been well studied within the acute medical service. Objective To examine the CFS in elderly patients admitted to the acute medical ward and its association with length of stay. Design Prospective cohort study in an acute care university hospital in London, Ontario, Canada, involving 75 patients over age 65, admitted to the general internal medicine clinical teaching units (CTU). Measurements Patient demographics were collected through chart review, and CFS score was assigned to each patient after brief clinician assessment. The CFS ranges from 1 (very fit) to 9 (terminally ill) based on descriptors and pictographs of activity and functional status. The CFS was collapsed into three categories: non-frail (CFS 1–4), mild-to-moderately frail (CFS 5–6), and severely frail (CFS 7–8). Outcomes of length of stay and 90-day readmission were gathered through the LHSC electronic patient record. Results Severe frailty was associated with longer lengths of stay (Mean = 12.6 ± 12.7 days) compared to mild-to-moderate frailty (mean = 11.2 ± 10.8 days), and non-frailty (mean = 4.1 ± 2.1 days, p = .014). This finding was significant after adjusting for age, sex, and number of medications. Participants with higher frailty scores showed higher readmission rates when compared with those with no frailty (31.2% for severely frail, vs. 34.2% for mild-to-moderately frail vs. 19% for non-frail) although there was no significant difference in the adjusted analysis. Conclusion The CFS helped identify patients that are more likely to have prolonged hospital stays on the acute medical ward. The CFS is an easy to use tool which

  18. A rat retinal damage model predicts for potential clinical visual disturbances induced by Hsp90 inhibitors

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Dan, E-mail: DZhou@syntapharma.com [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States); Liu, Yuan; Ye, Josephine; Ying, Weiwen; Ogawa, Luisa Shin; Inoue, Takayo; Tatsuta, Noriaki; Wada, Yumiko; Koya, Keizo [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States); Huang, Qin [Department of Pathology and Laboratory Medicine, Veterans Affairs Boston Healthcare System, 1400 VFW Parkway, West Roxbury, MA 02132 (United States); Bates, Richard C.; Sonderfan, Andrew J. [Synta Pharmaceuticals Corp., 45 Hartwell Avenue, Lexington, MA 02421 (United States)

    2013-12-01

    In human trials certain heat shock protein 90 (Hsp90) inhibitors, including 17-DMAG and NVP-AUY922, have caused visual disorders indicative of retinal dysfunction; others such as 17-AAG and ganetespib have not. To understand these safety profile differences we evaluated histopathological changes and exposure profiles of four Hsp90 inhibitors, with or without clinical reports of adverse ocular effects, using a rat retinal model. Retinal morphology, Hsp70 expression (a surrogate marker of Hsp90 inhibition), apoptotic induction and pharmacokinetic drug exposure analysis were examined in rats treated with the ansamycins 17-DMAG and 17-AAG, or with the second-generation compounds NVP-AUY922 and ganetespib. Both 17-DMAG and NVP-AUY922 induced strong yet restricted retinal Hsp70 up-regulation and promoted marked photoreceptor cell death 24 h after the final dose. In contrast, neither 17-AAG nor ganetespib elicited photoreceptor injury. When the relationship between drug distribution and photoreceptor degeneration was examined, 17-DMAG and NVP-AUY922 showed substantial retinal accumulation, with high retina/plasma (R/P) ratios and slow elimination rates, such that 51% of 17-DMAG and 65% of NVP-AUY922 present at 30 min post-injection were retained in the retina 6 h post-dose. For 17-AAG and ganetespib, retinal elimination was rapid (90% and 70% of drugs eliminated from the retina at 6 h, respectively) which correlated with lower R/P ratios. These findings indicate that prolonged inhibition of Hsp90 activity in the eye results in photoreceptor cell death. Moreover, the results suggest that the retina/plasma exposure ratio and retinal elimination rate profiles of Hsp90 inhibitors, irrespective of their chemical class, may predict for ocular toxicity potential. - Highlights: • In human trials some Hsp90 inhibitors cause visual disorders, others do not. • Prolonged inhibition of Hsp90 in the rat eye results in photoreceptor cell death. • Retina/plasma ratio and retinal

  19. Early Low Urinary CXCL9 and CXCL10 Might Predict Immunological Quiescence in Clinically and Histologically Stable Kidney Recipients.

    Science.gov (United States)

    Rabant, M; Amrouche, L; Morin, L; Bonifay, R; Lebreton, X; Aouni, L; Benon, A; Sauvaget, V; Le Vaillant, L; Aulagnon, F; Sberro, R; Snanoudj, R; Mejean, A; Legendre, C; Terzi, F; Anglicheau, D

    2016-06-01

    We monitored the urinary C-X-C motif chemokine (CXCL)9 and CXCL10 levels in 1722 urine samples from 300 consecutive kidney recipients collected during the first posttransplantation year and assessed their predictive value for subsequent acute rejection (AR). The trajectories of urinary CXCL10 showed an early increase at 1 month (p = 0.0005) and 3 months (p = 0.0009) in patients who subsequently developed AR. At 1 year, the AR-free allograft survival rates were 90% and 54% in patients with CXCL10:creatinine (CXCL10:Cr) levels 2.79 ng/mmoL at 1 month, respectively (p CXCL10:Cr levels 5.32 ng/mmoL at 3 months (p CXCL9:Cr levels also associate, albeit less robustly, with AR-free allograft survival. Early CXCL10:Cr levels predicted clinical and subclinical rejection and both T cell- and antibody-mediated rejection. In 222 stable patients, CXCL10:Cr at 3 months predicted AR independent of concomitant protocol biopsy results (p = 0.009). Although its positive predictive value was low, a high negative predictive value suggests that early CXCL10:Cr might predict immunological quiescence on a triple-drug calcineurin inhibitor-based immunosuppressive regimen in the first posttransplantation year, even in clinically and histologically stable patients. The clinical utility of this test will need to be addressed by dedicated prospective clinical trials. PMID:26694099

  20. The Implications of Endoscopic Ulcer in Early Gastric Cancer: Can We Predict Clinical Behaviors from Endoscopy?

    Science.gov (United States)

    Lee, Yoo Jin; Kim, Jie-Hyun; Park, Jae Jun; Youn, Young Hoon; Park, Hyojin; Kim, Jong Won; Choi, Seung Ho; Noh, Sung Hoon

    2016-01-01

    Background The presence of ulcer in early gastric cancer (EGC) is important for the feasibility of endoscopic resection, only a few studies have examined the clinicopathological implications of endoscopic ulcer in EGC. Objectives To determine the role of endoscopic ulcer as a predictor of clinical behaviors in EGC. Methods Data of 3,270 patients with EGC who underwent surgery between January 2005 and December 2012 were reviewed. Clinicopathological characteristics were analyzed in relation to the presence and stage of ulcer in EGC. Based on endoscopic findings, the stage of ulcer was categorized as active, healing, or scar. Logistic regression analysis was performed to analyze factors associated with lymph node metastasis (LNM). Results 2,343 (71.7%) patients had endoscopic findings of ulceration in EGC. Submucosal (SM) invasion, LNM, lymphovascular invasion (LVI), perineural invasion, and undifferentiated-type histology were significantly higher in ulcerative than non-ulcerative EGC. Comparison across different stages of ulcer revealed that SM invasion, LNM, and LVI were significantly associated with the active stage, and that these features exhibited significant stage-based differences, being most common at the active stage, and least common at the scar stage. The presence of endoscopic ulcer and active status of the ulcer were identified as independent risk factors for LNM. Conclusions Ulcerative EGC detected by endoscopy exhibited more aggressive behaviors than non-ulcerative EGC. Additionally, the endoscopic stage of ulcer may predict the clinicopathological behaviors of EGC. Therefore, the appearance of ulcers should be carefully evaluated to determine an adequate treatment strategy for EGC. PMID:27741275

  1. Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification.

    Directory of Open Access Journals (Sweden)

    Igor O Korolev

    Full Text Available Individuals with mild cognitive impairment (MCI have a substantially increased risk of developing dementia due to Alzheimer's disease (AD. In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139 and those who did not (n = 120 during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87. Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex. Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.We developed an accurate prognostic model for predicting MCI-to-dementia progression

  2. The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School

    OpenAIRE

    James David; Yates Janet

    2010-01-01

    Abstract Background The UK Clinical Aptitude Test (UKCAT) was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis), and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown. The study objective was to d...

  3. Positive Predictive Value of the WHO Clinical and Immunologic Criteria to Predict Viral Load Failure among Adults on First, or Second-Line Antiretroviral Therapy in Kenya

    Science.gov (United States)

    Muttai, Hellen; Ng’ang’a, Lucy; Ackers, Marta; Kim, Andrea; Miruka, Fredrick; Erick, Opiyo; Okonji, Julie; Ayuaya, Tolbert; Schwarcz, Sandra

    2016-01-01

    Routine HIV viral load (VL) monitoring is the standard of care for persons receiving antiretroviral therapy (ART) in developed countries. Although the World Health Organization recommends annual VL monitoring of patients on ART, recognizing difficulties in conducting routine VL testing, the WHO continues to recommend targeted VL testing to confirm treatment failure for persons who meet selected immunologic and clinical criteria. Studies have measured positive predictive value (PPV), negative predictive value, sensitivity and specificity of these criteria among patients receiving first-line ART but not specifically among those on second-line or subsequent regimens. Between 2008 and 2011, adult ART patients in Nyanza, Kenya who met national clinical or immunologic criteria for treatment failure received targeted VL testing. We calculated PPV and 95% confidence intervals (CI) of these criteria to detect virologic treatment failure among patients receiving a) first-line ART, b) second/subsequent ART, and c) any regimen. Of 12,134 patient specimens tested, 2,874 (23.7%) were virologically confirmed as treatment failures. The PPV for 2,834 first-line ART patients who met either the clinical or immunologic criteria for treatment failure was 34.4% (95% CI 33.2–35.7), 33.1% (95% CI 24.7–42.3) for the 40 patients on second-line/subsequent regimens, and 33.4% (95% CI 33.1–35.6) for any ART. PPV, regardless of criteria, for first-line ART patients was lowest among patients over 44 years old and highest for patients aged 15 to 34 years. PPV of immunological and clinical criteria for correctly identifying treatment failure was similarly low for adult patients receiving either first-line or second-line/subsequent ART regimens. Our data confirm the inadequacy of clinical and immunologic criteria to correctly identify treatment failure and support the implementation of routine VL testing. PMID:27383834

  4. Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers

    Science.gov (United States)

    Clark, S R; Baune, B T; Schubert, K O; Lavoie, S; Smesny, S; Rice, S M; Schäfer, M R; Benninger, F; Feucht, M; Klier, C M; McGorry, P D; Amminger, G P

    2016-01-01

    Current criteria identifying patients with ultra-high risk of psychosis (UHR) have low specificity, and less than one-third of UHR cases experience transition to psychosis within 3 years of initial assessment. We explored whether a Bayesian probabilistic multimodal model, combining baseline historical and clinical risk factors with biomarkers (oxidative stress, cell membrane fatty acids, resting quantitative electroencephalography (qEEG)), could improve this specificity. We analyzed data of a UHR cohort (n=40) with a 1-year transition rate of 28%. Positive and negative likelihood ratios were calculated for predictor variables with statistically significant receiver operating characteristic curves (ROCs), which excluded oxidative stress markers and qEEG parameters as significant predictors of transition. We clustered significant variables into historical (history of drug use), clinical (Positive and Negative Symptoms Scale positive, negative and general scores and Global Assessment of Function) and biomarker (total omega-3, nervonic acid) groups, and calculated the post-test probability of transition for each group and for group combinations using the odds ratio form of Bayes' rule. Combination of the three variable groups vastly improved the specificity of prediction (area under ROC=0.919, sensitivity=72.73%, specificity=96.43%). In this sample, our model identified over 70% of UHR patients who transitioned within 1 year, compared with 28% identified by standard UHR criteria. The model classified 77% of cases as very high or low risk (P>0.9, <0.1) based on history and clinical assessment, suggesting that a staged approach could be most efficient, reserving fatty-acid markers for 23% of cases remaining at intermediate probability following bedside interview. PMID:27648919

  5. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  6. Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

    International Nuclear Information System (INIS)

    Cancers of the colon and rectum, which rank among the most frequent human tumors, are currently treated by surgical resection in locally restricted tumor stages. However, disease recurrence and formation of local and distant metastasis frequently occur even in cases with successful curative resection of the primary tumor (R0). Recent technological advances in molecular diagnostic analysis have led to a wealth of knowledge about the changes in gene transcription in all stages of colorectal tumors. Differential gene expression, or transcriptome analysis, has been proposed by many groups to predict disease recurrence, clinical outcome, and also response to therapy, in addition to the well-established clinico-pathological factors. However, the clinical usability of gene expression profiling as a reliable and robust prognostic tool that allows evidence-based clinical decisions is currently under debate. In this review, we will discuss the most recent data on the prognostic significance and potential clinical application of genome wide expression analysis in colorectal cancer

  7. Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning.

    Science.gov (United States)

    Fusar-Poli, P; Schultze-Lutter, F

    2016-02-01

    Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes' theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment.

  8. Predicting dangerousness with two Millon Adolescent Clinical Inventory psychopathy scales: the importance of egocentric and callous traits.

    Science.gov (United States)

    Salekin, Randall T; Ziegler, Tracey A; Larrea, Maria A; Anthony, Virginia Lee; Bennett, Allyson D

    2003-04-01

    Psychopathy in youth has received increased recognition as a critical clinical construct for the evaluation and management of adolescents who have come into contact with the law (e.g., Forth, Hare, & Hart, 1990; Frick, 1998; Lynam, 1996, 1998). Although considerable attention has been devoted to the adult construct of psychopathy and its relation to recidivism, psychopathy in adolescents has been less thoroughly researched. Recently, a psychopathy scale (Murrie and Cornell Psychopathy Scale; Murrie & Cornell, 2000) was developed from items of the Millon Adolescent Clinical Inventory (MACI; Millon, 1993). This scale was found to be highly related to the Psychopathy Checklist-Revised (Hare, 1991) and was judged to have demonstrated good criterion validity. A necessary step in the validation process of any psychopathy scale is establishing its predictive validity. With this in mind, we investigated the ability of the MACI Psychopathy Scale to predict recidivism with 55 adolescent offenders 2 years after they had been evaluated at a juvenile court evaluation unit. In addition, we devised a psychopathy scale from MACI items that aligned more closely with Cooke and Michie (2001) and Frick, Bodin, and Barry's (2001) recommendations for the refinement of psychopathy and tested its predictive validity. Results indicate that both scales had predictive utility. Interpersonal and affective components of the revised scale were particularly important in the prediction of both general and violent reoffending. PMID:12700018

  9. Cerebrospinal fluid total tau concentration predicts clinical phenotype in Huntington's disease.

    Science.gov (United States)

    Rodrigues, Filipe Brogueira; Byrne, Lauren; McColgan, Peter; Robertson, Nicola; Tabrizi, Sarah J; Leavitt, Blair R; Zetterberg, Henrik; Wild, Edward J

    2016-10-01

    Huntington's disease (HD) is a hereditary neurodegenerative condition with no therapeutic intervention known to alter disease progression, but several trials are ongoing and biomarkers of disease progression are needed. Tau is an axonal protein, often altered in neurodegeneration, and recent studies pointed out its role on HD neuropathology. Our goal was to study whether cerebrospinal fluid (CSF) tau is a biomarker of disease progression in HD. After informed consent, healthy controls, pre-symptomatic and symptomatic gene expansion carriers were recruited from two HD clinics. All participants underwent assessment with the Unified HD Rating Scale '99 (UHDRS). CSF was obtained according to a standardized lumbar puncture protocol. CSF tau was quantified using enzyme-linked immunosorbent assay. Comparisons between two groups were tested using ancova. Pearson's correlation coefficients were calculated for disease progression. Significance level was defined as p international pilot study. Age-adjusted CSF tau was significantly elevated in gene expansion carriers compared with healthy controls (p = 0.002). UHDRS total functional capacity was significantly correlated with CSF tau (r = -0.29, p = 0.004) after adjustment for age, and UHDRS total motor score was significantly correlated with CSF tau after adjustment for age (r = 0.32, p = 0.002). Several UHDRS cognitive tasks were also significantly correlated with CST total tau after age-adjustment. This study confirms that CSF tau concentrations in HD gene mutation carriers are increased compared with healthy controls and reports for the first time that CSF tau concentration is associated with phenotypic variability in HD. These conclusions strengthen the case for CSF tau as a biomarker in HD. In the era of novel targeted approaches to Huntington's disease, reliable biomarkers are needed. We quantified Tau protein, a marker of neuronal death, in cerebrospinal fluid and found it was increased in patients with

  10. The usefulness of holotranscobalamin in predicting vitamin B12 status in different clinical settings.

    Science.gov (United States)

    Herrmann, Wolfgang; Obeid, Rima; Schorr, Heike; Geisel, Jürgen

    2005-02-01

    Serum concentrations of homocysteine (Hcy) and methylmalonic acid (MMA) become increased in B12-deficient subjects and are therefore, considered specific markers of B12 deficiency. Serum level of holotranscobalamin (holoTC) becomes decreased before the development of the metabolic dysfunction. We investigated the usefulness of holoTC in diagnosing B12 deficiency in some clinical settings. We measured serum concentrations of holoTC, MMA, Hcy and total B12 in omnivores, vegetarians, elderly people and haemodialysis patients. Our results indicated that the incidence of holoTC vegans (76%). Low holoTC and elevated MMA were detected in 64% of the vegans and 43% of the lacto- and lacto-ovovegetarians. An elevated MMA and a low holoTC were found in subjects with total serum B12 as high as 300 pmol/L. The distribution of holoTC in elderly people was similar to that in younger adults (median holoTC 55 pmol/L in both groups). A low holoTC and an elevated MMA were found in 16% of the elderly group. An elevated MMA and a normal holoTC were found in 20% of the elderly group who had a relatively high median serum concentration of creatinine (106.1 micromol/L). Serum concentrations of holoTC in dialysis patients were considerably higher than all other groups (median 100 pmol/L). This was also associated with severely increased serum levels of MMA (median 987 nmol/L). From these results it can be concluded that serum concentration of holoTC is a much better predictor of B12 status than total B12. This was particularly evident in case of dietary B12 deficiency. Serum concentrations of holoTC as well as MMA can be affected by renal dysfunction. Elevated MMA and normal holoTC in patients with renal insufficiency may not exclude vitamin B12 deficiency. HoloTC seems not to be a promising marker in predicting B12 status in renal patients.

  11. CREATION OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LOCAL EXTENT OF THE BLADDER CANCER BASED ON CLINICAL VARIABLES

    OpenAIRE

    L. V. Mirylenka; O. G. Sukonko; A. V. Pravorov; A. I. Rolevich; A. S. Mavrichev

    2014-01-01

    Objective: to develop nomogram based on clinical variables, that predicts pathological local extent of the bladder cancer рТ3-рТ4 (рТ3+).Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. For prediction of pT3+ on preoperative data were used mono- and multivariate logistic regression analysis. Coefficients from logistic regression equalization were used to construct nom...

  12. 多时间序列关联规则分析的论坛舆情趋势预测%Forum Sentiment Trend Prediction Based on Multi Time Series Association Rule Analysis

    Institute of Scientific and Technical Information of China (English)

    钱爱玲; 瞿彬彬; 卢炎生; 陈攀攀; 陈国栋

    2012-01-01

    为了预测论坛舆情及其动态演变趋势,基于多时间序列的关联分析,集中分析了论坛中3个量的时间序列之间的关联规则:活跃者之间的关系强度的时间序列、坚定支持者人数的时间序列以及坚定支持者成员的变化频度的时间序列.然后给出了一种新的基于多时间序列关联分析的论坛舆情预测算法(Forum sentiment trend prediction based on multi time series association rule analysis,TPMTSA),并在真实数据集和拟合数据集上进行了大量的实验.结果表明:TPMTSA算法具有有效性和较高的运行效率.研究结果可用于论坛舆情预警监控.%In order to predict the evolving trend of forum sentiment, based on the association analysis of multi time series, the association rules of three-quantity time series over forum sentiment are anlyzed, namely, the strength of relationship between actors, the number of pillars, and the changing frequency of pillars. Then a novel prediction algorithm, forum sentiment trend prediction based on multi time series association rule analysis (TPMTSA), is proposed. Extensive experiments over real and synthetic datasets are conducted. Results show the effectiveness and the efficiency of TPMTSA. The research results can be used to monitor the forum opinion.

  13. Society for immunotherapy of cancer (SITC) statement on the proposed changes to the common rule.

    Science.gov (United States)

    Kaufman, Howard L; Butterfield, Lisa H; Coulie, Pierre G; Demaria, Sandra; Ferris, Robert L; Galon, Jérôme; Khleif, Samir N; Mellman, Ira; Ohashi, Pamela S; Overwijk, Willem W; Topalian, Suzanne L; Marincola, Francesco M

    2016-01-01

    The Common Rule is a set of ethical principles that provide guidance on the management of human subjects taking part in biomedical and behavioral research in the United States. The elements of the Common Rule were initially developed in 1981 following a revision of the Declaration of Helsinki in 1975. Most academic facilities follow the Common Rule in the regulation of clinical trials research. Recently, the government has suggested a revision of the Common Rule to include more contemporary and streamlined oversight of clinical research. In this commentary, the leadership of the Society for Immunotherapy of Cancer (SITC) provides their opinion on this plan. While the Society recognizes the considerable contribution of clinical research in supporting progress in tumor immunotherapy and supports the need for revisions to the Common Rule, there is also some concern over certain elements which may restrict access to biospecimens and clinical data at a time when high throughput technologies, computational biology and assay standardization is allowing major advances in understanding cancer biology and providing potential predictive biomarkers of immunotherapy response. The Society values its professional commitment to patients for improving clinical outcomes with tumor immunotherapy and supports continued discussion with all stakeholders before implementing changes to the Common Rule in order to ensure maximal patient protections while promoting continued clinical research at this historic time in cancer research. PMID:27330810

  14. Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

    Science.gov (United States)

    Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

    2013-01-01

    The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

  15. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.;

    2010-01-01

    The EU multi-disciplinary personalised RNA interference to enhance the delivery of individualised chemotherapeutics and targeted therapies (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer a...

  16. Acute axonal damage predicts clinical outcome in patients with multiple sclerosis

    DEFF Research Database (Denmark)

    Lim, E.T; Sellebjerg, F; Jensen, C.V;

    2005-01-01

    ) to correlate neurofilament and myelin basic protein (MBP) concentrations, particularly as the latter was previously associated with clinical disability. Fifty subjects participated in two double-blind, randomized, placebo-controlled clinical trials. Eight/18 patients in the ON trial and 15/32 subjects...

  17. High IFIT1 expression predicts improved clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

    Science.gov (United States)

    Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong

    2016-06-01

    Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma. PMID:26980050

  18. Free Recall Episodic Memory Performance Predicts Dementia Ten Years prior to Clinical Diagnosis: Findings from the Betula Longitudinal Study

    OpenAIRE

    Boraxbekk, Carl-Johan; Lundquist, Anders; Nordin, Annelie; Nyberg, Lars; Nilsson, Lars-Göran; Adolfsson, Rolf

    2015-01-01

    Background/Aims: Early dementia diagnosis is a considerable challenge. The present study examined the predictive value of cognitive performance for a future clinical diagnosis of late-onset Alzheimer's disease or vascular dementia in a random population sample. Methods: Cognitive performance was retrospectively compared between three groups of participants from the Betula longitudinal cohort. Group 1 developed dementia 11-22 years after baseline testing (n = 111) and group 2 after 1-10 years ...

  19. A Simple Clinical Score “TOPRS” to Predict Outcome in Pediatric Emergency Department in a Teaching Hospital in India

    OpenAIRE

    Ravinder Kumar Soni; Bains, Harmesh S.

    2012-01-01

    Objective: To develop a simple clinical scoring system for severity of illness to help prioritize care and predict outcome in emergency department.Methods: Prospective hospital based observational study. Out of a total of 874 children who attended emergency department in one year, 777 were included in the study. Data was collected at the time of admission in emergency department. The baseline information like age, gender, etc and variables of ‘toprs’ score viz temperature, oxygen saturation, ...

  20. Flight experience and executive functions predict unlike professional pilots who are limited by the FAA's age rule, no age limit is defined in general aviation (GA)

    OpenAIRE

    Causse, Mickael; Dehais, Frédéric; Pastor, Josette

    2010-01-01

    Unlike professional pilots who are limited by the FAA's age rule, no age limit is defined in general aviation (GA). Some studies revealed significant aging issues on accident rates but these results are criticized. Our overall goal is to study how the effect of age on executive functions (EFs), high level cognitive abilities, impacts on the flying performance in GA pilots. This study relies on three components: EFs assessment, pilot characteristics (age, flight experience), and the naviga...

  1. Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

    2016-07-15

    Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. PMID:27288771

  2. CREATION OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LOCAL EXTENT OF THE BLADDER CANCER BASED ON CLINICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    L. V. Mirylenka

    2012-01-01

    Full Text Available Objective: to develop nomogram based on clinical variables, that predicts pathological local extent of the bladder cancer рТ3-рТ4 (рТ3+.Material and methods: We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. For prediction of pT3+ on preoperative data were used mono- and multivariate logistic regression analysis. Coefficients from logistic regression equalization were used to construct nomogram. Nomogram accuracy was evaluated with concordance index (с-index and by building the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.Results: We developed nomogram, that include: clinical stage сТ, tumor grade, tumor macroscopic appearance, presence of upper tract dilatation, prostatic urethra and/or prostatic lobe(s involvement, 3 or more bladder walls involvement, ESR and creatinine level. Bootstrapcorrected prognostic accuracy of nomogram was 81,4%, that 12,6% better than clinical stage accuracy.Conclusion: developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.

  3. Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs

    Directory of Open Access Journals (Sweden)

    Joana R. Sousa

    2014-01-01

    Full Text Available The performance of the cerebral state index (CSI in reflecting different levels of isoflurane anaesthesia was evaluated in ten cats subjected to four end-tidal isoflurane concentrations (EtIso, each maintained for 15 minutes (0.8%, 1.2%, 1.6%, or 2.0% EtIso. The CSI, hemodynamic data, ocular reflexes, and eye position were recorded for each EtIso concentration. Pharmacodynamic analysis of CSI with EtIso was performed, as well as prediction probability analysis with a clinical scale based on the eye reflexes. The CSI values showed great variability. Between all parameters, burst suppression ratio showed the better fitting with the sigmoidal concentration-effect model (R2=0.93 followed by CSI (R2=0.82 and electromyographic activity (R2=0.79. EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94. Although the CSI values decrease with increasing isoflurane concentrations, the huge variability in CSI values may be a strong limitation for its use in cats and it seems to be no better than EtIso as a predictor of clinical signs.

  4. Assessment of clinical methods and ultrasound in predicting fetal birth weight in term pregnant women

    Directory of Open Access Journals (Sweden)

    Ruby Yadav

    2016-08-01

    Conclusions: Clinical estimation of birth weight clearly has a role in management of labour and delivery in a term pregnancy. Clinical estimation especially by SFH and times;AG method is as accurate as routine USG estimated in average birth weight. SFH and times; AG clinical formula can be of great value in developing countries like ours, where ultrasound is not available at many health care centers especially in a rural area. [Int J Reprod Contracept Obstet Gynecol 2016; 5(8.000: 2775-2779

  5. Predicting Clinical Syndrome in Students with Emotional Breakdown Experience based on Personality Structures: the Moderating Role of Perceived Social Support

    Directory of Open Access Journals (Sweden)

    Samad Fahimi

    2015-10-01

    Full Text Available Introduction: This study investigated the role of personality constructs in predicting the clinical syndrome of students with emotional breakdown and moderating role of perceived social support in this relationship. Methods: Using purposive sampling and based on questionnaires of the love trauma, Beck depression and GHQ in students with emotional breakdown experience, 65 students with and 65 students without the clinical syndrome were selected from Payam Noor University of Tabriz, Tabriz University, and Islamic Azad University of Tabriz, and completed HEXACO questionnaire and multidimensional scale of perceived social support (MSPSS. Data analysis was done using SPSS16 and LISREL 8.54 by multivariate analysis of variance (MANOVA and path analysis. Results: The results showed that there was a significant difference between two groups in personality characteristics and social support (P<0.05, and social support had a moderating role in developing clinical syndrome after emotional breakdown. Conclusion: Personality characteristics and social support affect everyone's romantic relationships and would predict how to deal with the challenges in these relationships. After an emotional breakdown, if families are able to bring children out of this crisis with their direct and indirect support, this will lead to passing the trauma naturally and will prevent the continuation of the clinical syndrome.

  6. Procalcitonin Levels Predict Clinical Course and Progression-Free Survival in Patients With Medullary Thyroid Cancer

    NARCIS (Netherlands)

    Walter, Martin A.; Meier, Christian; Radimerski, Tanja; Iten, Fabienne; Kraenzlin, Marius; Mueller-Brand, Jan; de Groot, Jan Willem B.; Kema, Ido P.; Links, Thera P.; Mueller, Beat

    2010-01-01

    BACKGROUND: Procalcitonin has been well established as an important marker of sepsis and systemic infection. The authors evaluated the diagnostic and predictive value of calcitonin and its prohormone procalcitonin in medullary thyroid cancer. METHODS: The authors systematically explored the ability

  7. Predictive Value of IL-8 for Sepsis and Severe Infections after Burn Injury - A Clinical Study

    OpenAIRE

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C.; Cox, Robert A.; Song, Juquan; Jeschke, Marc G.

    2015-01-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring post-burn inflammation is of paramount importance but so far there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As IL-8 is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict post-burn sepsis, infections, and m...

  8. Nutrition Screening Tools and the Prediction of Clinical Outcomes among Chinese Hospitalized Gastrointestinal Disease Patients.

    Science.gov (United States)

    Wang, Fang; Chen, Wei; Bruening, Kay Stearns; Raj, Sudha; Larsen, David A

    2016-01-01

    Nutrition risk Screening 2002 (NRS-2002) and Subjective Global Assessment (SGA) are widely used screening tools but have not been compared in a Chinese population. We conducted secondary data analysis of a cross-sectional study which included 332 hospitalized gastrointestinal disease patients, collected by the Gastrointestinal department of Peking Union Medical College Hospital (PUMCH) in 2008. Results of NRS-2002 and SGA screening tools, complications, length of stay (LOS), cost, and death were measured. The agreement between the tools was assessed via Kappa (κ) statistics. The performance of NRS-2002 and SGA in predicting LOS and cost was assessed via linear regression. The complications and death prediction of tools was assessed using receiver operating characteristic (ROC) curves. NRS-2002 and SGA identified nutrition risk at 59.0% and 45.2% respectively. Moderate agreement (κ >0.50) between the two tools was found among all age groups except individuals aged ≤ 20, which only slight agreement was found (κ = 0.087). NRS-2002 (R square 0.130) and SGA (R square 0.140) did not perform differently in LOS prediction. The cost prediction of NRS-2002 (R square 0.198) and SGA (R square 0.190) were not significantly different. There was no difference between NRS-2002 (infectious complications: area under ROC (AUROC) = 0.615, death: AUROC = 0.810) and SGA (infectious complications: AUROC = 0.600, death: AUROC = 0.846) in predicting infectious complication and death, but NRS-2002 (0.738) seemed to perform better than SGA (0.552) in predicting non-infectious complications. The risk of malnutrition among patients was high. NRS-2002 and SGA have similar capacity to predict LOS, cost, infectious complications and death, but NRS-2002 performed better in predicting non-infectious complications. PMID:27490480

  9. Predicting Relapse in Patients With Medulloblastoma by Integrating Evidence From Clinical and Genomic Features

    NARCIS (Netherlands)

    P. Tamayo; Y.J. Cho; A. Tsherniak; H. Greulich; L. Ambrogio; N. Schouten-van Meeteren; T. Zhou; A. Buxton; M. Kool; M. Meyerson; S.L. Pomeroy; J.P. Mesirov

    2011-01-01

    Purpose Despite significant progress in the molecular understanding of medulloblastoma, stratification of risk in patients remains a challenge. Focus has shifted from clinical parameters to molecular markers, such as expression of specific genes and selected genomic abnormalities, to improve accurac

  10. Burnout and Work Demands Predict Reduced Job Satisfaction in Health Professionals Working In a Surgery Clinic

    Directory of Open Access Journals (Sweden)

    Dragan Mijakoski

    2015-03-01

    CONCLUSIONS: Adequate management of work demands, particularly excessive workload, time pressure, and lack of staff can lead to prevention of burnout and reduced job satisfaction in surgery clinic HPs, and contribute to better quality of patient care.

  11. Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis

    DEFF Research Database (Denmark)

    Giorgio, Antonio; Battaglini, Marco; Rocca, Maria Assunta;

    2013-01-01

    converting group in projection, association, and commissural WM tracts, with larger clusters being in the corpus callosum, corona radiata, and cingulum. CONCLUSIONS: Higher frequency of lesion occurrence in clinically eloquent WM tracts can characterize CIS subjects with different types of onset. The...... involvement of specific WM tracts, in particular those traversed by fibers involved in motor function and near the corpus callosum, seems to be associated with a higher risk of clinical conversion to MS in the short term....

  12. Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis.

    Science.gov (United States)

    Borràs, Eva; Cantó, Ester; Choi, Meena; Maria Villar, Luisa; Álvarez-Cermeño, José Carlos; Chiva, Cristina; Montalban, Xavier; Vitek, Olga; Comabella, Manuel; Sabidó, Eduard

    2016-01-01

    Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

  13. Can Psychological, Social and Demographical Factors Predict Clinical Characteristics Symptomatology of Bipolar Affective Disorder and Schizophrenia?

    Science.gov (United States)

    Maciukiewicz, Malgorzata; Pawlak, Joanna; Kapelski, Pawel; Łabędzka, Magdalena; Skibinska, Maria; Zaremba, Dorota; Leszczynska-Rodziewicz, Anna; Dmitrzak-Weglarz, Monika; Hauser, Joanna

    2016-09-01

    Schizophrenia (SCH) is a complex, psychiatric disorder affecting 1 % of population. Its clinical phenotype is heterogeneous with delusions, hallucinations, depression, disorganized behaviour and negative symptoms. Bipolar affective disorder (BD) refers to periodic changes in mood and activity from depression to mania. It affects 0.5-1.5 % of population. Two types of disorder (type I and type II) are distinguished by severity of mania episodes. In our analysis, we aimed to check if clinical and demographical characteristics of the sample are predictors of symptom dimensions occurrence in BD and SCH cases. We included total sample of 443 bipolar and 439 schizophrenia patients. Diagnosis was based on DSM-IV criteria using Structured Clinical Interview for DSM-IV. We applied regression models to analyse associations between clinical and demographical traits from OPCRIT and symptom dimensions. We used previously computed dimensions of schizophrenia and bipolar affective disorder as quantitative traits for regression models. Male gender seemed protective factor for depression dimension in schizophrenia and bipolar disorder sample. Presence of definite psychosocial stressor prior disease seemed risk factor for depressive and suicidal domain in BD and SCH. OPCRIT items describing premorbid functioning seemed related with depression, positive and disorganised dimensions in schizophrenia and psychotic in BD. We proved clinical and demographical characteristics of the sample are predictors of symptom dimensions of schizophrenia and bipolar disorder. We also saw relation between clinical dimensions and course of disorder and impairment during disorder. PMID:26646576

  14. Predicting Anxiety Among Patients In LPU Clinical Dispensary During Dental Treatment: Towards Student’s Clinical Performance Enhancement

    Directory of Open Access Journals (Sweden)

    Maribel D. Mayuga-Barrion

    2013-12-01

    Full Text Available The study aimed to determine the respondents’ profile in terms of age, gender, frequency of dental visit, and type of patient whether dental phobic or not; to determine the dental anxiety of patients in LPU dental dispensary; to identify the causes and severity of anxiety of the patients in LPU dental dispensary; to determine if there is a significant difference between the respondents’ demographic profile and their level of anxiety; and lastly, to propose a program that will help the patients cope with dental anxiety and a program that will enhance the students’ clinical performance. The study used the descriptive research design with the combination of content analysis of documents and related materials. Results showed that majority of the respondents belonged to age range of 14-18 years old range whereas for gender or sex, majority who avail of the clinic’s services are males. This is because women are more afraid than men in terms of dental problems. Further, younger people are more afraid than older ones. The weighted mean distribution of the level of anxiety showed that the level of anxiety of patients varies on moderately to not anxious. Feeling or experiencing pain during dental treatment ranked first followed by the fear or worry of not working the proposed treatment and thirdly, the dentist is in a hurry while treating also made the patients moderately anxious. Overall, the level of anxiety of patients is moderately anxious. Probing to asses gum disease, dislike the numb feeling and injection were the top three causes of dental anxiety. Only type of patient shows significant difference, thus the null hypothesis of no significant difference on the level of anxiety when grouped according to profile variables is rejected. This means that the level of anxiety of both phobic and not phobic differs.

  15. Pre- and post-operative nomograms to predict recurrence-free probability in korean men with clinically localized prostate cancer.

    Directory of Open Access Journals (Sweden)

    Minyong Kang

    Full Text Available OBJECTIVES: Although the incidence of prostate cancer (PCa is rapidly increasing in Korea, there are few suitable prediction models for disease recurrence after radical prostatectomy (RP. We established pre- and post-operative nomograms estimating biochemical recurrence (BCR-free probability after RP in Korean men with clinically localized PCa. PATIENTS AND METHODS: Our sampling frame included 3,034 consecutive men with clinically localized PCa who underwent RP at our tertiary centers from June 2004 through July 2011. After inappropriate data exclusion, we evaluated 2,867 patients for the development of nomograms. The Cox proportional hazards regression model was used to develop pre- and post-operative nomograms that predict BCR-free probability. Finally, we resampled from our study cohort 200 times to determine the accuracy of our nomograms on internal validation, which were designated with concordance index (c-index and further represented by calibration plots. RESULTS: Over a median of 47 months of follow-up, the estimated BCR-free rate was 87.8% (1 year, 83.8% (2 year, and 72.5% (5 year. In the pre-operative model, Prostate-Specific Antigen (PSA, the proportion of positive biopsy cores, clinical T3a and biopsy Gleason score (GS were independent predictive factors for BCR, while all relevant predictive factors (PSA, extra-prostatic extension, seminal vesicle invasion, lymph node metastasis, surgical margin, and pathologic GS were associated with BCR in the post-operative model. The c-index representing predictive accuracy was 0.792 (pre- and 0.821 (post-operative, showing good fit in the calibration plots. CONCLUSIONS: In summary, we developed pre- and post-operative nomograms predicting BCR-free probability after RP in a large Korean cohort with clinically localized PCa. These nomograms will be provided as the mobile application-based SNUH Prostate Cancer Calculator. Our nomograms can determine patients at high risk of disease recurrence

  16. Two new prediction rules for spontaneous pregnancy leading to live birth among subfertile couples, based on the synthesis of three previous models.

    NARCIS (Netherlands)

    C.C. Hunault; J.D.F. Habbema (Dik); M.J.C. Eijkemans (René); J.A. Collins (John); J.L.H. Evers (Johannes); E.R. te Velde (Egbert)

    2004-01-01

    textabstractBACKGROUND: Several models have been published for the prediction of spontaneous pregnancy among subfertile patients. The aim of this study was to broaden the empirical basis for these predictions by making a synthesis of three previously published models. METHODS: We u

  17. Prediction of bacteremia in the emergency department

    DEFF Research Database (Denmark)

    Pedersen, Marie Kristine Jessen; Mackenhauer, Julie; Hvass, Anne Mette Sondrup Wulff;

    2016-01-01

    Objective The objective of this study was to validate a previously published clinical decision rule for predicting a positive blood culture in emergency department (ED) patients with suspected infection on the basis of major and minor criteria and a total score (Shapiro et al., J Emerg Med, 2008...

  18. Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth.

    Science.gov (United States)

    Bertocci, M A; Bebko, G; Versace, A; Fournier, J C; Iyengar, S; Olino, T; Bonar, L; Almeida, J R C; Perlman, S B; Schirda, C; Travis, M J; Gill, M K; Diwadkar, V A; Forbes, E E; Sunshine, J L; Holland, S K; Kowatch, R A; Birmaher, B; Axelson, D; Horwitz, S M; Frazier, T W; Arnold, L E; Fristad, M A; Youngstrom, E A; Findling, R L; Phillips, M L

    2016-09-01

    Behavioral and emotional dysregulation in childhood may be understood as prodromal to adult psychopathology. Additionally, there is a critical need to identify biomarkers reflecting underlying neuropathological processes that predict clinical/behavioral outcomes in youth. We aimed to identify such biomarkers in youth with behavioral and emotional dysregulation in the Longitudinal Assessment of Manic Symptoms (LAMS) study. We examined neuroimaging measures of function and white matter in the whole brain using 80 youth aged 14.0 (s.d.=2.0) from three clinical sites. Linear regression using the LASSO (Least Absolute Shrinkage and Selection Operator) method for variable selection was used to predict severity of future behavioral and emotional dysregulation measured by the Parent General Behavior Inventory-10 Item Mania Scale (PGBI-10M)) at a mean of 14.2 months follow-up after neuroimaging assessment. Neuroimaging measures, together with near-scan PGBI-10M, a score of manic behaviors, depressive behaviors and sex, explained 28% of the variance in follow-up PGBI-10M. Neuroimaging measures alone, after accounting for other identified predictors, explained ~1/3 of the explained variance, in follow-up PGBI-10M. Specifically, greater bilateral cingulum length predicted lower PGBI-10M at follow-up. Greater functional connectivity in parietal-subcortical reward circuitry predicted greater PGBI-10M at follow-up. For the first time, data suggest that multimodal neuroimaging measures of underlying neuropathologic processes account for over a third of the explained variance in clinical outcome in a large sample of behaviorally and emotionally dysregulated youth. This may be an important first step toward identifying neurobiological measures with the potential to act as novel targets for early detection and future therapeutic interventions. PMID:26903272

  19. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures.

    Science.gov (United States)

    Ye, Zheng; Rae, Charlotte L; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle-Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R; Maxwell, Helen; Sahakian, Barbara J; Barker, Roger A; Robbins, Trevor W; Rowe, James B

    2016-03-01

    Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double-blind randomized three-way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion-weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave-one-out cross-validation (LOOCV) to predict patients' responses in terms of improved stopping efficiency. We identified two optimal models: (1) a "clinical" model that predicted the response of an individual patient with 77-79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion-weighted imaging scan; and (2) a "mechanistic" model that explained the behavioral response with 85% accuracy for each drug, using drug-induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. PMID:26757216

  20. Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth

    Science.gov (United States)

    Bertocci, Michele A.; Bebko, Genna; Versace, Amelia; Fournier, Jay C.; Iyengar, Satish; Olino, Thomas; Bonar, Lisa; Almeida, Jorge R. C.; Perlman, Susan B.; Schirda, Claudiu; Travis, Michael J.; Gill, Mary Kay; Diwadkar, Vaibhav A.; Forbes, Erika E.; Sunshine, Jeffrey L.; Holland, Scott K; Kowatch, Robert A.; Birmaher, Boris; Axelson, David; Horwitz, Sarah M.; Frazier, Thomas W.; Arnold, L. Eugene; Fristad, Mary. A; Youngstrom, Eric A.; Findling, Robert L.; Phillips, Mary L.

    2015-01-01

    Behavioral and emotional dysregulation in childhood may be understood as prodromal to adult psychopathology. Additionally, there is a critical need to identify biomarkers reflecting underlying neuropathological processes that predict clinical/behavioral outcomes in youth. We aimed to identify such biomarkers in youth with behavioral and emotional dysregulation in the Longitudinal Assessment of Manic Symptoms (LAMS) study. We examined neuroimaging measures of function and white matter in the whole brain using 80 youth aged 14.0(sd=2.0) from 3 clinical sites. Linear regression using the LASSO method for variable selection was used to predict severity of future behavioral and emotional dysregulation [measured by the Parent General Behavior Inventory-10 Item Mania Scale (PGBI-10M)] at a mean of 14.2 months follow-up after neuroimaging assessment. Neuroimaging measures, together with near-scan PGBI-10M, a score of manic behaviors, depressive behaviors, and sex, explained 28% of the variance in follow-up PGBI-10M. Neuroimaging measures alone, after accounting for other identified predictors, explained approximately one-third of the explained variance, in follow-up PGBI-10M. Specifically, greater bilateral cingulum length predicted lower PGBI-10M at follow-up. Greater functional connectivity in parietal-subcortical reward circuitry predicted greater PGBI-10M at follow-up. For the first time, data suggest that multimodal neuroimaging measures of underlying neuropathologic processes account for over a third of the explained variance in clinical outcome in a large sample of behaviorally and emotionally dysregulated youth. This may be an important first step toward identifying neurobiological measures with the potential to act as novel targets for early detection and future therapeutic interventions. PMID:26903272

  1. Application of a biochemical and clinical model to predict individual survival in patients with end-stage liver disease

    Institute of Scientific and Technical Information of China (English)

    Eduardo Vilar Gomez; Luis Calzadilla Bertot; Bienvenido Gra Oramas; Enrique Arus Soler; Raimundo Llanio Navarro; Javier Diaz Elias; Oscar Villa Jiménez; Maria del Rosario Abreu Vazquez

    2009-01-01

    AIM:To investigate the capability of a biochemical and clinical model,BioCliM,in predicting the survival of cirrhotic patients.METHODS:We prospectively evaluated the survival of 172 cirrhotic patients.The model was constructed using clinical (ascites,encephalopathy and variceal bleeding) and biochemical (serum creatinine and serum total bilirubin) variables that were selected from a Cox proportional hazards model.It was applied to estimate 12-,52- and 104-wk survival.The model's calibration using the Hosmer-Lemeshow statistic was computed at 104 wk in a validation dataset.Finally,the model's validity was tested among an independent set of 85 patients who were stratified into 2 risk groups (low risk ≤8 and high risk>8).RESULTS:In the validation cohort,all measures of fit,discrimination and calibration were improved when the biochemical and clinical model was used.The proposed model had better predictive values (c-statistic:0.90,0.91,0.91) than the Model for End-stage Liver Disease (MELD) and Child-Pugh (CP) scores for 12-,52- and 104-wk mortality,respectively.In addition,the Hosmer-Lemeshow (H-L) statistic revealed that the biochemical and clinical model (H-L,4.69) is better calibrated than MELD (H-L,17.06) and CP (H-L,14.23).There were no significant differences between the observed and expected survival curves in the stratified risk groups (low risk,P=0.61;high risk,P=0.77).CONCLUSION:Our data suggest that the proposed model is able to accurately predict survival in cirrhotic patients.

  2. Predicted Aerobic Capacity of Asthmatic Children: A Research Study from Clinical Origin

    Directory of Open Access Journals (Sweden)

    Lene Lochte

    2012-01-01

    Full Text Available Objective. To compare longitudinally PAC of asthmatic children against that of healthy controls during ten months. Methods. Twenty-eight asthmatic children aged 7–15 years and 27 matched controls each performed six submaximal exercise tests on treadmill, which included a test of EIA (exercise-induced asthma. Predicted aerobic capacity (mLO2/min/kg was calculated. Spirometry and development were measured. Physical activity, medication, and “ever asthma/current asthma” were reported by questionnaire. Results. Predicted aerobic capacity of asthmatics was lower than that of controls (P=0.0015 across observation times and for both groups an important increase in predicted aerobic capacity according to time was observed (P<0.001. FEV1 of the asthmatic children was within normal range. The majority (86% of the asthmatics reported pulmonary symptoms to accompany their physical activity. Physical activity (hours per week showed important effects for the variation in predicted aerobic capacity at baseline (F=2.28, P=0.061 and at the T4 observation (F=3.03, P=0.027 and the analyses showed important asthma/control group effects at baseline, month four, and month ten. Physical activity of the asthmatics correlated positively with predicted aerobic capacity. Conclusion. The asthmatic children had consistently low PAC when observed across time. Physical activity was positively associated with PAC in the asthmatics.

  3. Tinbergen Rules the Taylor Rule

    OpenAIRE

    Thomas R. Michl

    2008-01-01

    This paper elaborates a simple model of growth with a Taylor-like monetary policy rule that includes inflation-targeting as a special case. When the inflation process originates in the product market, inflation-targeting locks in the unemployment rate prevailing at the time the policy matures. Although there is an apparent NAIRU and Phillips curve, this long-run position depends on initial conditions; in the presence of stochastic shocks, it would be path dependent. Even with an employment ta...

  4. Selecting new health technologies for evaluation:Can clinical experts predict which new anticancer drugswill impact Danish health care?

    DEFF Research Database (Denmark)

    Douw, Karla; Vondeling, Hindrik

    2007-01-01

    Several countries have systems in place to support the managed entry of new health technologies. The big challenge for these so-called horizon-scanning systems is to select those technologies that require decision support by means of an early evaluation. Clinical experts are considered a valuable...... source of information on new health technologies, but research on the relevance of their input is scarce. In 2000, we asked six Danish expert oncologists to predict whether a sample of 19 new anticancer drugs would impact Danish health care over the next 5 years. In 2005, we assessed the accuracy...... of these predictions in a delayed type cross-sectional study. The specificity of the Danish experts' prediction was 1 (95% confidence interval 0.74-1.00) and the sensitivity was 0.63 (0.31-0.86). The negative predictive value was 0.79 (0.52-0.92) and the positive predictive value was 1 (0.57-1.00). This indicates...

  5. Inferring comprehensible business/ICT alignment rules.

    OpenAIRE

    Cumps, Bjorn; Martens, David; De Backer, Manu; Haesen, Raf; Viaene, Stijn; Dedene, Guido; Baesens, Bart; Snoeck, Monique

    2009-01-01

    We inferred business rules for business/ICT alignment by applying a novel rule induction algorithm on a data set containing rich alignment information polled from 641 organisations in 7 European countries. The alignment rule set was created using AntMiner+, a rule induction technique with a reputation of inducing accurate, comprehensible, and intuitive predictive models from data. Our data set consisted of 18 alignment practices distilled from an analysis of relevant publications and validate...

  6. Clinical value of CT-based preoperative software assisted lung lobe volumetry for predicting postoperative pulmonary function after lung surgery

    Science.gov (United States)

    Wormanns, Dag; Beyer, Florian; Hoffknecht, Petra; Dicken, Volker; Kuhnigk, Jan-Martin; Lange, Tobias; Thomas, Michael; Heindel, Walter

    2005-04-01

    This study was aimed to evaluate a morphology-based approach for prediction of postoperative forced expiratory volume in one second (FEV1) after lung resection from preoperative CT scans. Fifteen Patients with surgically treated (lobectomy or pneumonectomy) bronchogenic carcinoma were enrolled in the study. A preoperative chest CT and pulmonary function tests before and after surgery were performed. CT scans were analyzed by prototype software: automated segmentation and volumetry of lung lobes was performed with minimal user interaction. Determined volumes of different lung lobes were used to predict postoperative FEV1 as percentage of the preoperative values. Predicted FEV1 values were compared to the observed postoperative values as standard of reference. Patients underwent lobectomy in twelve cases (6 upper lobes; 1 middle lobe; 5 lower lobes; 6 right side; 6 left side) and pneumonectomy in three cases. Automated calculation of predicted postoperative lung function was successful in all cases. Predicted FEV1 ranged from 54% to 95% (mean 75% +/- 11%) of the preoperative values. Two cases with obviously erroneous LFT were excluded from analysis. Mean error of predicted FEV1 was 20 +/- 160 ml, indicating absence of systematic error; mean absolute error was 7.4 +/- 3.3% respective 137 +/- 77 ml/s. The 200 ml reproducibility criterion for FEV1 was met in 11 of 13 cases (85%). In conclusion, software-assisted prediction of postoperative lung function yielded a clinically acceptable agreement with the observed postoperative values. This method might add useful information for evaluation of functional operability of patients with lung cancer.

  7. A dynamic model of once-daily 5-aminosalicylic acid predicts clinical efficacy

    Institute of Scientific and Technical Information of China (English)

    Deepak; Parakkal; Eli; D; Ehrenpreis; Matthew; P; Thorpe; Karson; S; Putt; Bruce; Hannon

    2010-01-01

    New once daily mesalamine formulations may improve adherence to medication usage.Response to Asacol and other forms of 5-aminosalicyclic acid(5-ASA)is better correlated with tissue concentrations and best predicted by concentrations of the drug within the lumen of the colon.Our group used computer simulation to predict colonic 5-ASA levels after Asacol administration.In our study,the model simulated Asacol distribution in the healthy colon,and during quiescent and active ulcerative colitis.An Asacol dosage ...

  8. Admission to intensive care can be reliably predicted using only clinical judgment

    DEFF Research Database (Denmark)

    Brabrand, M.

    2015-01-01

    Introduction Not all patients in need of critical care arrive in clinical distress and some deteriorate after arrival. Identifying these patients early in their clinical course could potentially improve outcome. The present study was performed with the aim of assessing whether nursing and physician...... staffwere able to identify patients in need of critical care using only clinical judgment and to compare this with the National Early Warning Score (NEWS). Methods This was a prospective cohort study of all adult patients with a first-time admission to a medical admission unit at a 450-bed regional teaching...... hospital over a 3-month period in 2010. All subspecialties of internal medicine are present as well as a level 2 ICU. Upon first contact with the patient after arrival, nursing staffand physicians were asked to report their estimation of the probability of ICU admission (0 to 100%). Survival status...

  9. Goldbach's Rule

    OpenAIRE

    Aktay, Metin

    2000-01-01

    Goldbach`s Conjecture, "every even number greater than 2 can be expressed as the sum of two primes" is renamed Goldbach`s Rule for it can not be otherwise. The conjecture is proven by showing that the existence of prime pairs adding to any even number greater than 2 is a natural by-product of the existence of the prime sequence less than that even number. First it is shown that the remainder of cancellations process which identifies primes less than an even number also remainders prime pairs ...

  10. A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore.

    Directory of Open Access Journals (Sweden)

    Vernon J Lee

    Full Text Available INTRODUCTION: Influenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI to determine predictors of influenza infection. METHODS: Personnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model. RESULTS: 821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9% had 2009 influenza A (H1N1, 58 (7.1% seasonal influenza A (H3N2 and 269 (32.8% influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%, specificity of 69% (95% CI: 62%, 75%, and overall accuracy of 68% (95% CI: 64%, 71%, performing significantly better than conventional influenza-like illness (ILI criteria. CONCLUSIONS: Use of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.

  11. Development of a classification rule for four clinical therapeutic psychotropic drug classes with EEG power-spectrum variables of human volunteers.

    Science.gov (United States)

    Herrmann, W M; Fichte, K; Itil, T M; Kubicki, S

    1979-01-01

    An objective rule for the classification of psychotropic substances has been developed. Classification is based on data from five basic studies simultaneously designed and performed and involving 75 healthy volunteers who ingested 20 different psychotropic drugs and 5 placebos in single oral dosages. Each volunteer took one psychostimulant, one antidepressant, one neuroleptic, one minor tranquilizer and one placebo in a double-blind Latin square cross-over design. The variables were 6 frequency bands, based on power spectrum estimates and determined by factor analysis, plus total power in the 1.5-30.0 Hz range. An objective classification rule was established by multi-group (5 groups) linear discriminant analysis. Reclassification of the substances by the new rule yielded correct results for 17 out of 20 psychotropic drugs and 4 out of 5 placebos. Of placebos from various studies not used for the establishment of the classification rule, 7/9 were classified correctly. The validity of the rule for other classes of substances will have to be verified in independent studies. PMID:419163

  12. Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: a decade of the PREDICT-HD study

    Directory of Open Access Journals (Sweden)

    Jane S Paulsen

    2014-04-01

    Full Text Available There is growing consensus that intervention and treatment of Huntington disease (HD should occur at the earliest stage possible. Various early-intervention methods for this fatal neurodegenerative disease have been identified, but preventive clinical trials for HD are limited by a lack of knowledge of the natural history of the disease and a dearth of appropriate outcome measures. Objectives of the current study are to document the natural history of premanifest HD progression in the largest cohort ever studied and to develop a battery of imaging and clinical markers of premanifest HD progression that can be used as outcome measures in preventive clinical trials. PREDICT-HD is a 32-site, international, observational study of premanifest HD, with annual examination of 1013 participants with premanifest HD and 301 gene-expansion negative controls between 2001 and 2012. Findings document 39 variables representing imaging, motor, cognitive, functional, and psychiatric domains, showing different rates of decline between premanifest Huntington disease and controls. Required sample size and models of premanifest HD are presented to inform future design of clinical and preclinical research. Preventive clinical trials in premanifest HD with participants who have a medium or high probability of motor onset are calculated to be as resource-effective as those conducted in diagnosed HD and could interrupt disease seven to twelve years earlier. Methods and measures for preventive clinical trials in premanifest HD more than a dozen years from motor onset are also feasible. These findings represent the most thorough documentation of a clinical battery for experimental therapeutics in stages of premanifest HD, the time period for which effective intervention may provide the most positive possible outcome for patients and their families affected by this devastating disease.

  13. Simple blood tests as predictive markers of disease severity and clinical condition in patients with venous insufficiency.

    Science.gov (United States)

    Karahan, Oguz; Yavuz, Celal; Kankilic, Nazim; Demirtas, Sinan; Tezcan, Orhan; Caliskan, Ahmet; Mavitas, Binali

    2016-09-01

    Chronic venous insufficiency (CVI) is a progressive inflammatory disease. Because of its inflammatory nature, several circulating markers were investigated for predicting disease progression. We aimed to investigate simple inflammatory blood markers as predictors of clinical class and disease severity in patients with CVI. Eighty patients with CVI were divided into three groups according to clinical class (grade 1, 2 and 3) and score of disease severity (mild, moderate and severe). The basic inflammatory blood markers [neutrophil, lymphocyte, mean platelet volume (MPV), white blood cell (WBC), platelet, albumin, D-dimer, fibrinogen, fibrinogen to albumin ratio, and neutrophil to lymphocyte ratio] were investigated in each group. Serum neutrophil, lymphocyte, MPV, platelet count, D-dimer and neutrophil to lymphocyte ratio levels were similar among the groups (P > 0.05). Although the serum WBC levels were significant in the clinical severity groups (P < 0.05), it was useless to separate each severity class. However, albumin, fibrinogen and the fibrinogen to albumin ratio were significant predictors of clinical class and disease severity. Especially, the fibrinogen to albumin ratio was detected as an independent indicator for a clinical class and disease severity with high sensitivity and specificity (75% sensitivity and 87.5% specificity for clinical class and 90% sensitivity and 88.3% specificity for disease severity). Serum fibrinogen and albumin levels can be useful parameters to determine clinical class and disease severity in patients with CVI. Moreover, the fibrinogen to albumin ratio is a more sensitive and specific predictor of the progression of CVI. PMID:26650463

  14. Predictive factors for familiality in a Danish clinical cohort of children with Tourette syndrome

    DEFF Research Database (Denmark)

    Debes, Nanette M M M; Hjalgrim, Helle; Skov, Liselotte

    2010-01-01

    ). The fact that TS aggregates strongly in families suggests that family members share either genetic and/or environmental risk factors contributing to TS. Numerous studies have been performed to examine the familiality in TS, but clear-cut factors to predict hereditability in TS have not been found yet. We...

  15. CONFIRMATION OF CLINICAL-DIAGNOSIS IN REQUESTS FOR PRENATAL PREDICTION OF SMA TYPE-I

    NARCIS (Netherlands)

    COBBEN, JM; DEVISSER, M; SCHEFFER, H; OSINGA, J; VANDERSTEEGE, G; BUYS, CHCM; VANOMMEN, GJ; TENKATE, LP

    1993-01-01

    The recent discovery of a major SMA-locus in the chromosomal region 5q makes it possible to carry out prenatal DNA studies in families in which a child with SMA type I has been born. Since direct mutation analysis is not yet possible, the reliability of prenatal prediction of SMA type I usually depe

  16. Predicting academic performance and clinical competency for international dental students: seeking the most efficient and effective measures.

    Science.gov (United States)

    Stacey, D Graham; Whittaker, John M

    2005-02-01

    Measures used in the selection of international dental students to a U.S. D.D.S. program were examined to identify the grouping that most effectively and efficiently predicted academic performance and clinical competency. Archival records from the International Dental Program (IDP) at Loma Linda University provided data on 171 students who had trained in countries outside the United States. The students sought admission to the D.D.S. degree program, successful completion of which qualified them to sit for U.S. licensure. As with most dental schools, competition is high for admission to the D.D.S. program. The study's goal was to identify what measures contributed to a fair and accurate selection process for dental school applicants from other nations. Multiple regression analyses identified National Board Part II and dexterity measures as significant predictors of academic performance and clinical competency. National Board Part I, TOEFL, and faculty interviews added no significant additional help in predicting eventual academic performance and clinical competency.

  17. Do medical students’ scores using different assessment instruments predict their scores in clinical reasoning using a computer-based simulation?

    Directory of Open Access Journals (Sweden)

    Fida M

    2015-02-01

    Full Text Available Mariam Fida,1 Salah Eldin Kassab2 1Department of Molecular Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain; 2Department of Medical Education, Faculty of Medicine, Suez Canal University, Ismailia, Egypt Purpose: The development of clinical problem-solving skills evolves over time and requires structured training and background knowledge. Computer-based case simulations (CCS have been used for teaching and assessment of clinical reasoning skills. However, previous studies examining the psychometric properties of CCS as an assessment tool have been controversial. Furthermore, studies reporting the integration of CCS into problem-based medical curricula have been limited. Methods: This study examined the psychometric properties of using CCS software (DxR Clinician for assessment of medical students (n=130 studying in a problem-based, integrated multisystem module (Unit IX during the academic year 2011–2012. Internal consistency reliability of CCS scores was calculated using Cronbach's alpha statistics. The relationships between students' scores in CCS components (clinical reasoning, diagnostic performance, and patient management and their scores in other examination tools at the end of the unit including multiple-choice questions, short-answer questions, objective structured clinical examination (OSCE, and real patient encounters were analyzed using stepwise hierarchical linear regression. Results: Internal consistency reliability of CCS scores was high (α=0.862. Inter-item correlations between students' scores in different CCS components and their scores in CCS and other test items were statistically significant. Regression analysis indicated that OSCE scores predicted 32.7% and 35.1% of the variance in clinical reasoning and patient management scores, respectively (P<0.01. Multiple-choice question scores, however, predicted only 15.4% of the variance in diagnostic performance scores (P<0.01, while

  18. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    Science.gov (United States)

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  19. Levels of uninvolved immunoglobulins predict clinical status and progression-free survival for multiple myeloma patients.

    Science.gov (United States)

    Harutyunyan, Nika M; Vardanyan, Suzie; Ghermezi, Michael; Gottlieb, Jillian; Berenson, Ariana; Andreu-Vieyra, Claudia; Berenson, James R

    2016-07-01

    Multiple myeloma (MM) is characterized by the enhanced production of the same monoclonal immunoglobulin (M-Ig or M protein). Techniques such as serum protein electrophoresis and nephelometry are routinely used to quantify levels of this protein in the serum of MM patients. However, these methods are not without their shortcomings and problems accurately quantifying M proteins remain. Precise quantification of the types and levels of M-Ig present is critical to monitoring patient response to therapy. In this study, we investigated the ability of the HevyLite (HLC) immunoassay to correlate with clinical status based on levels of involved and uninvolved antibodies. In our cohort of MM patients, we observed that significantly higher ratios and greater differences of involved HLC levels compared to uninvolved HLC levels correlated with a worse clinical status. Similarly, higher absolute levels of involved HLC antibodies and lower levels of uninvolved HLC antibodies also correlated with a worse clinical status and a shorter progression-free survival. These findings suggest that the HLC assay is a useful and a promising tool for determining the clinical status and survival time for patients with multiple myeloma. PMID:27017948

  20. Cultural Responsivity in Clinical Psychology Graduate Students: A Developmental Approach to the Prediction of Learning

    Science.gov (United States)

    Berrin, Sebastian Everett

    2010-01-01

    This study used a mixed-method approach to examine students' experiences in multicultural training and their opinions about various aspects of their course(s). A developmental model of learning was employed to analyze results. More specifically, this study explored the relationship between clinical psychology doctoral students' self-reported…

  1. Levels of uninvolved immunoglobulins predict clinical status and progression-free survival for multiple myeloma patients.

    Science.gov (United States)

    Harutyunyan, Nika M; Vardanyan, Suzie; Ghermezi, Michael; Gottlieb, Jillian; Berenson, Ariana; Andreu-Vieyra, Claudia; Berenson, James R

    2016-07-01

    Multiple myeloma (MM) is characterized by the enhanced production of the same monoclonal immunoglobulin (M-Ig or M protein). Techniques such as serum protein electrophoresis and nephelometry are routinely used to quantify levels of this protein in the serum of MM patients. However, these methods are not without their shortcomings and problems accurately quantifying M proteins remain. Precise quantification of the types and levels of M-Ig present is critical to monitoring patient response to therapy. In this study, we investigated the ability of the HevyLite (HLC) immunoassay to correlate with clinical status based on levels of involved and uninvolved antibodies. In our cohort of MM patients, we observed that significantly higher ratios and greater differences of involved HLC levels compared to uninvolved HLC levels correlated with a worse clinical status. Similarly, higher absolute levels of involved HLC antibodies and lower levels of uninvolved HLC antibodies also correlated with a worse clinical status and a shorter progression-free survival. These findings suggest that the HLC assay is a useful and a promising tool for determining the clinical status and survival time for patients with multiple myeloma.

  2. Undergraduate Nurse Variables that Predict Academic Achievement and Clinical Competence in Nursing

    Science.gov (United States)

    Blackman, Ian; Hall, Margaret; Darmawan, I Gusti Ngurah.

    2007-01-01

    A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for undergraduate nursing students. Sixteen latent variables were considered including the students' background, gender, type of first language, age, their previous successes with their undergraduate nursing studies and status given for…

  3. A Novel Rule Induction Algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHENG Jianguo; LIU Fang; WANG Lei; JIAO Licheng

    2001-01-01

    Knowledge discovery in databases is concerned with extracting useful information from databases, and the immune algorithm is a biological theory-based and globally searching algorithm. A specific immune algorithm is designed for discovering a few interesting, high-level prediction rules from databases, rather than discovering classification knowledge as usual in the literatures. Simulations show that this novel algorithm is able to improve the stability of the population, increase the holistic performance and make the rules extracted have higher precision.

  4. Application of the Eötvos and Guggenheim empirical rules for predicting the density and surface tension of ionic liquids analogues

    International Nuclear Information System (INIS)

    Highlights: • Critical temperatures of eight common DES were calculated using two methods. • Density and surface tension were calculated using the Rackett and Guggenheim equations. • The Rackett method should be used in the low temperature range only. • The Eötvos and Guggenheim methods gave best density and surface tension predictions. - Abstract: The recent continuing interest in deep eutectic solvents (DES) as ionic liquids analogues and their successful applications in different areas of separation necessities the existence of reliable physical and thermodynamic properties database. The scarcity of data on the physical properties of such solvents, increases the need for their prediction using reliable methods. In this study, first the critical temperatures of eight DES systems have been calculated based on the Eötvos empirical equation using the experimental data of the density and surface tension at various temperatures, then the density and surface tension values of these systems were predicted from the calculated critical temperatures. For the density prediction the Eötvos and Guggenheim equations were combined to introduce a simple power law equation using the estimated critical temperatures from the Eötvos and the Modified Lydersen–Joback–Reid group contribution methods. Finally, the estimated critical temperatures by these two methods were used in the Guggenheim empirical equation to calculate the surface tension of the DES systems. The prediction quality of the two physical properties under investigation were compared and proper recommendations were postulated

  5. Effect of differences in saturation sensitivity of phospholipid stains on clinical predictivity of L/S ratios.

    Science.gov (United States)

    Spillman, T; Cotton, D B; Gonik, B

    1985-10-31

    Owing to the importance of the degree of fatty acid side chain saturation in the ability of lecithin molecules to function as surfactant, we assessed the clinical effectiveness of analytical methods which differ with respect to methodologic influences by saturated and unsaturated phospholipids. The lecithin/sphingomyelin ratios, determined with either cupric acetate or phosphomolybdate as the detection reagent, are compared for their abilities to predict respiratory distress syndrome (RDS), transient tachypnea (TTN), or the absence of respiratory difficulty in neonates. A group of 47 amniotic fluids were analyzed from 25 non-problem cases, 13 cases of TTN and 9 cases of RDS. Receiver operating characteristic analysis shows that in our sample population, the measurement of total lecithin for the prediction of neonatal respiratory distress failed to demonstrate an advantage over the measurement of unsaturated lecithin alone. PMID:2414041

  6. Predicted Aerobic Capacity of Asthmatic Children: A Research Study from Clinical Origin

    OpenAIRE

    Lene Lochte

    2012-01-01

    Objective. To compare longitudinally PAC of asthmatic children against that of healthy controls during ten months. Methods. Twenty-eight asthmatic children aged 7–15 years and 27 matched controls each performed six submaximal exercise tests on treadmill, which included a test of EIA (exercise-induced asthma). Predicted aerobic capacity (mLO2/min/kg) was calculated. Spirometry and development were measured. Physical activity, medication, and “ever asthma/current asthma” were reported by questi...

  7. Prediction of clinical outcome in glioblastoma using a biologically relevant nine-microRNA signature

    OpenAIRE

    Hayes, J.; Thygesen, H., Helene; Tumilson, C; Droop, A; Boissinot, M; Hughes, TA; Westhead, D; Alder, JE; Shaw, L; Short, SC; Lawler, SE

    2015-01-01

    Background: Glioblastoma is the most aggressive primary brain tumor, and is associated with a very poor prognosis. In this study we investigated the potential of microRNA expression profiles to predict survival in this challenging disease. Methods: MicroRNA and mRNA expression data from glioblastoma (n=475) and grade II and III glioma (n=178) were accessed from The Cancer Genome Atlas. LASSO regression models were used to identify a prognostic microRNA signature. Functionally relevant targets...

  8. Pediatric in-Hospital Death from Infectious Disease in Uganda: Derivation of Clinical Prediction Models

    OpenAIRE

    Nasim Lowlaavar; Larson, Charles P.; Elias Kumbakumba; Guohai Zhou; J. Mark Ansermino; Joel Singer; Niranjan Kissoon; Hubert Wong; Andrew Ndamira; Jerome Kabakyenga; Julius Kiwanuka; Matthew O Wiens

    2016-01-01

    Background Pediatric hospital mortality from infectious diseases in resource constrained countries remains unacceptably high. Improved methods of risk-stratification can assist in referral decision making and resource allocation. The purpose of this study was to create prediction models for in-hospital mortality among children admitted with suspected infectious diseases. Methods This two-site prospective observational study enrolled children between 6 months and 5 years admitted with a proven...

  9. Validation of a novel clinical prediction score for severe coronary artery diseases before elective coronary angiography.

    Directory of Open Access Journals (Sweden)

    Zhang-Wei Chen

    Full Text Available OBJECTIVES: Coronary artery disease (CAD severity is associated with patient prognosis. However, few efficient scoring systems have been developed to screen severe CAD in patients with stable angina and suspected CAD before coronary angiography. Here, we present a novel scoring system for CAD severity before elective coronary angiography. METHODS: Five hundred fifty-one patients with stable angina who were admitted for coronary angiography were enrolled in this study. Patients were divided into training (n = 347 and validation (n = 204 cohorts. Severe CAD was defined as having a Gensini score of 20 or more. All patients underwent echocardiography (ECG to detect ejection fraction and aortic valve calcification (AVC. Multivariable analysis was applied to determine independent risk factors and develop the scoring system. RESULTS: In the training cohort, age, male sex, AVC, abnormal ECG, diabetes, hyperlipidemia, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol were identified as independent factors for severe CAD by multivariable analysis, and the Severe Prediction Scoring (SPS system was developed. C-indices of receiver operating characteristic (ROC curves for severe CAD were 0.744 and 0.710 in the training and validation groups, respectively. The SPS system also performed well during calibration, as demonstrated by Hosmer-Lemeshow analysis in the validation group. Compared with the Diamond-Forrester score, the SPS system performed better for severe CAD prediction before elective coronary angiography. CONCLUSIONS: Severe CAD prediction was achieved by analyzing age, sex, AVC, ECG, diabetes status, and lipid levels. Angina patients who achieve high scores using this predicting system should undergo early coronary angiography.

  10. Graph-based clinical diagnosis and prediction using multi-modal neuroimaging data

    OpenAIRE

    Klein, Arno; Ghosh, Satrajit

    2016-01-01

    The proposed research develops new computational tools to identify, diagnose, and predict treatment outcome for different mental illnesses. The research will be applied first to major depressive disorder, which affects millions of Americans, but is intended to be applied to any mental illness, such as Alzheimer’s disease, bipolar disorder, schizophrenia – indeed to analyze differences in brain structure, activity, or connectivity between any two populations.

  11. Nonzero Solubility Rule

    Institute of Scientific and Technical Information of China (English)

    尉志武; 周蕊; 刘芸

    2002-01-01

    A solubility-related rule, nonzero solubility rule, is introduced in this paper. It is complementary to the existing rules such as the "like dissolves like" rule and can be understood on the basis of classical chemical thermodynamics.

  12. Matrix Metalloproteinase-9/Neutrophil Gelatinase-Associated Lipocalin Complex Activity in Human Glioma Samples Predicts Tumor Presence and Clinical Prognosis

    Directory of Open Access Journals (Sweden)

    Ming-Fa Liu

    2015-01-01

    Full Text Available Matrix metalloproteinase-9/neutrophil gelatinase-associated lipocalin (MMP-9/NGAL complex activity is elevated in brain tumors and may serve as a molecular marker for brain tumors. However, the relationship between MMP-9/NGAL activity in brain tumors and patient prognosis and treatment response remains unclear. Here, we compared the clinical characteristics of glioma patients with the MMP-9/NGAL activity measured in their respective tumor and urine samples. Using gelatin zymography assays, we found that MMP-9/NGAL activity was significantly increased in tumor tissues (TT and preoperative urine samples (Preop-1d urine. Activity was reduced by seven days after surgery (Postop-1w urine and elevated again in cases of tumor recurrence. The MMP-9/NGAL status correlated well with MRI-based tumor assessments. These findings suggest that MMP-9/NGAL activity could be a novel marker to detect gliomas and predict the clinical outcome of patients.

  13. Prediction of new drug indications based on clinical data and network modularity

    Science.gov (United States)

    Yu, Liang; Ma, Xiaoke; Zhang, Long; Zhang, Jing; Gao, Lin

    2016-01-01

    Drug repositioning is commonly done within the drug discovery process in order to adjust or expand the application line of an active molecule. Previous computational methods in this domain mainly focused on shared genes or correlations between genes to construct new drug-disease associations. We propose a method that can not only handle drugs or diseases with or without related genes but consider the network modularity. Our method firstly constructs a drug network and a disease network based on side effects and symptoms respectively. Because similar drugs imply similar diseases, we then cluster the two networks to identify drug and disease modules, and connect all possible drug-disease module pairs. Further, based on known drug-disease associations in CTD and using local connectivity of modules, we predict potential drug-disease associations. Our predictions are validated by testing their overlaps with drug indications reported in published literatures and CTD, and KEGG enrichment analysis are also made on their related genes. The experimental results demonstrate that our approach can complement the current computational approaches and its predictions can provide new clues for the candidate discovery of drug repositioning. PMID:27678071

  14. Prediction of Dengue Disease Severity among Pediatric Thai Patients Using Early Clinical Laboratory Indicators

    OpenAIRE

    James A Potts; Gibbons, Robert V.; Rothman, Alan L.; Anon Srikiatkhachorn; Thomas, Stephen J.; Pra-On Supradish; Lemon, Stephenie C.; Libraty, Daniel H.; Sharone Green; Siripen Kalayanarooj

    2010-01-01

    Background Dengue virus is endemic in tropical and sub-tropical resource-poor countries. Dengue illness can range from a nonspecific febrile illness to a severe disease, Dengue Shock Syndrome (DSS), in which patients develop circulatory failure. Earlier diagnosis of severe dengue illnesses would have a substantial impact on the allocation of health resources in endemic countries. Methods and Findings We compared clinical laboratory findings collected within 72 hours of fever onset from a pros...

  15. Mexiletine Therapy for Chronic Pain: Survival Analysis Identifies Factors Predicting Clinical Success

    OpenAIRE

    Carroll, Ian R; Kaplan, Kimberly M.; Mackey, Sean C.

    2008-01-01

    Mexiletine, a sodium channel blocker, treats neuropathic pain but its clinical value has been questioned due to its significant side effects and limited efficacy. We hypothesized that ongoing therapy with mexiletine would have limited patient acceptance, but that an analgesic response to intravenous (IV) lidocaine (a pharmacologically similar drug) would identify patients most likely to choose ongoing therapy with mexiletine. We identified a cohort of 37 patients with neuropathic pain who und...

  16. Clinical prediction of the need for interventions for the control of myopia.

    Science.gov (United States)

    McMonnies, Charles W

    2015-11-01

    The prevalence of myopia is increasing in Western populations but in East Asian countries, it is increasing to epidemic levels, where there are also markedly increased rates of progression to pathological myopia. Measures to more effectively control the development and progression of myopia are urgently needed. Notwithstanding a large volume of research, especially regarding the different mechanisms for the development of myopia and the efficacy of particular methods of intervention, there is still a great need and scope for improvements in clinical efforts to prevent and/or control myopic progression. Too often clinical efforts may involve only one method of intervention; however, the heterogenous nature of myopia suggests that clinical intervention may be more successful when interventions are employed in combination. The decision to prescribe interventions for the control of myopia in children, especially prior to onset, may be better framed by a comprehensive estimation of the degree of risk for the development and/or progression of myopia. For example, rather than ascribing equal weight to any degree of parental myopia, more accurate estimates may be obtained, if risk is judged to increase with the degree of parental myopia and the extent of any associated degenerative pathology. Risk estimates may be limited to broad mild, moderate and severe classifications due to lack of accurate weighting of risk factors. Nevertheless, comprehensive assessment of risk factors appears likely to better inform a prognosis and discussions with parents. Consideration of numerous environmental influences, for example, such as continuity and intensity of near work and time spent outdoors, may contribute to better risk estimation. Family-based practice appears to be ideally suited for risk estimation and the clinical application of approaches to control myopia. A proactive approach to estimating risk of developing myopia prior to its onset may be beneficial. Earlier implementation

  17. Do clinical foot and ankle assessments improve the prediction of patient reported outcomes in knee arthroplasty?

    OpenAIRE

    Gates, Lucy

    2015-01-01

    Knee arthroplasty (KA) has been considered to be a successful and cost-effective intervention for individuals with severe end stage Osteoarthritis (OA). A number of clinically important predictors of outcomes following KA have been established, however there are still other factors to be identified to improve our ability to recognise patients at risk of poor KA outcomes. Although the relationship between foot, ankle and knee kinematics has become widely accepted, it is not known whether foot ...

  18. Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology

    OpenAIRE

    Simon, Richard

    2010-01-01

    Physicians need improved tools for selecting treatments for individual patients. Many diagnostic entities hat were traditionally viewed as individual diseases are heterogeneous in their molecular pathogenesis and treatment responsiveness. This results in the treatment of many patients with ineffective drugs, incursion of substantial medical costs for the treatment of patients who do not benefit and the conducting of large clinical trials to identify small, average treatment benefits for heter...

  19. Endomysial antibodies predict celiac disease irrespective of the titers or clinical presentation

    Institute of Scientific and Technical Information of China (English)

    Kalle Kurppa; Markku M(a)ki; Katri Kaukinen; Tiia R(a)s(a)nen; Pekka Collin; Sari Iltanen; Heini Huhtala; Merja Ashorn; P(a)ivi Saavalainen; Katri Haimila; Jukka Partanen

    2012-01-01

    AIM:To investigate the association between serum antibody levels and a subsequent celiac disease diagnosis in a large series of children and adults.METHODS:Besides subjects with classical gastrointestinal presentation of celiac disease,the study cohort included a substantial number of individuals with extraintestinal symptoms and those found by screening in at-risk groups.Altogether 405 patients underwent clinical,serological and histological evaluations.After collection of data,the antibody values were further graded as low [endomysial (EmA) 1:5-200,transglutaminase 2 antibodies (TG2-ab) 5.0-30.0 U/L] and high (EmA 1:≥ 500,TG2-ab ≥ 30.0 U/L),and the serological results were compared with the small intestinal mucosal histology and clinical presentation.RESULTS:In total,79% of the subjects with low and 94% of those with high serum EmA titers showed small-bowel mucosal villous atrophy.Furthermore,96% of the 47 EmA positive subjects who had normal mucosal villi and remained on follow-up either subsequently developed mucosal atrophy while on a glutencontaining diet,or responded positively to a glutenfree diet.CONCLUSION:Irrespective of the initial serum titers or clinical presentation,EmA positivity as such is a very strong predictor of a subsequent celiac disease diagnosis.

  20. Three-tiered risk stratification model to predict progression in Barrett's esophagus using epigenetic and clinical features.

    Directory of Open Access Journals (Sweden)

    Fumiaki Sato

    Full Text Available Barrett's esophagus predisposes to esophageal adenocarcinoma. However, the value of endoscopic surveillance in Barrett's esophagus has been debated because of the low incidence of esophageal adenocarcinoma in Barrett's esophagus. Moreover, high inter-observer and sampling-dependent variation in the histologic staging of dysplasia make clinical risk assessment problematic. In this study, we developed a 3-tiered risk stratification strategy, based on systematically selected epigenetic and clinical parameters, to improve Barrett's esophagus surveillance efficiency.We defined high-grade dysplasia as endpoint of progression, and Barrett's esophagus progressor patients as Barrett's esophagus patients with either no dysplasia or low-grade dysplasia who later developed high-grade dysplasia or esophageal adenocarcinoma. We analyzed 4 epigenetic and 3 clinical parameters in 118 Barrett's esophagus tissues obtained from 35 progressor and 27 non-progressor Barrett's esophagus patients from Baltimore Veterans Affairs Maryland Health Care Systems and Mayo Clinic. Based on 2-year and 4-year prediction models using linear discriminant analysis (area under the receiver-operator characteristic (ROC curve: 0.8386 and 0.7910, respectively, Barrett's esophagus specimens were stratified into high-risk (HR, intermediate-risk (IR, or low-risk (LR groups. This 3-tiered stratification method retained both the high specificity of the 2-year model and the high sensitivity of the 4-year model. Progression-free survivals differed significantly among the 3 risk groups, with p = 0.0022 (HR vs. IR and p<0.0001 (HR or IR vs. LR. Incremental value analyses demonstrated that the number of methylated genes contributed most influentially to prediction accuracy.This 3-tiered risk stratification strategy has the potential to exert a profound impact on Barrett's esophagus surveillance accuracy and efficiency.

  1. A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer.

    Directory of Open Access Journals (Sweden)

    Sijia Huang

    2014-09-01

    Full Text Available Breast cancer is the most common malignancy in women worldwide. With the increasing awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is much needed for more personalized treatment and disease management. Towards this goal, we have developed a novel computational model for breast cancer prognosis by combining the Pathway Deregulation Score (PDS based pathifier algorithm, Cox regression and L1-LASSO penalization method. We trained the model on a set of 236 patients with gene expression data and clinical information, and validated the performance on three diversified testing data sets of 606 patients. To evaluate the performance of the model, we conducted survival analysis of the dichotomized groups, and compared the areas under the curve based on the binary classification. The resulting prognosis genomic model is composed of fifteen pathways (e.g., P53 pathway that had previously reported cancer relevance, and it successfully differentiated relapse in the training set (log rank p-value = 6.25e-12 and three testing data sets (log rank p-value < 0.0005. Moreover, the pathway-based genomic models consistently performed better than gene-based models on all four data sets. We also find strong evidence that combining genomic information with clinical information improved the p-values of prognosis prediction by at least three orders of magnitude in comparison to using either genomic or clinical information alone. In summary, we propose a novel prognosis model that harnesses the pathway-based dysregulation as well as valuable clinical information. The selected pathways in our prognosis model are promising targets for therapeutic intervention.

  2. 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

    Full Text Available Abstract Background Psychological models can be used to understand and predict behaviour in a wide range of settings. However, they have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. The aim of this study was to explore the usefulness of a range of psychological theories to predict health professional behaviour relating to management of upper respiratory tract infections (URTIs without antibiotics. Methods Psychological measures were collected by postal questionnaire survey from a random sample of general practitioners (GPs in Scotland. The outcome measures were clinical behaviour (using antibiotic prescription rates as a proxy indicator, behavioural simulation (scenario-based decisions to managing URTI with or without antibiotics and behavioural intention (general intention to managing URTI without antibiotics. Explanatory variables were the constructs within the following theories: 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 (SM, and knowledge (a non-theoretical construct. For each outcome measure, multiple regression analysis was used to examine the predictive value of each theoretical model individually. Following this 'theory level' analysis, a 'cross theory' analysis was conducted to investigate the combined predictive value of all significant individual constructs across theories. Results All theories were tested, but only significant results are presented. When predicting behaviour, at the theory level, OLT explained 6% of the variance and, in a cross theory analysis, OLT 'evidence of habitual behaviour' also explained 6%. When predicting behavioural simulation, at the theory level, the proportion of variance explained was: TPB, 31%; SCT, 26%; II, 6%; OLT, 24%. GPs who reported having already decided to change their management to

  3. 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

    Full Text Available Abstract Background 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. Methods 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 Results 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. Summary 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

  4. The impact of p53 in predicting clinical outcome of breast cancer patients with visceral metastasis

    OpenAIRE

    Yang, P.; C. W. Du; Kwan, M.; Liang, S. X.; G. J. Zhang

    2013-01-01

    In the study, we analyzed role of p53 in predicting outcome in visceral metastasis breast cancer (VMBC) patients. 97 consecutive VMBC patients were studied. P53 positivity rate was 29.9%. In the p53-negative group, median disease free survival (DFS), and time from primary breast cancer diagnosis to death (OS1), time from metastases to death (OS2) were 25, 42.5, and 13.5 months, respectively. In the p53-positive group, they were 10, 22, and 8 months, respectively. Statistically significant dif...

  5. Clinical characteristics of hand, foot and mouth disease in Harbin and the prediction of severe cases

    Institute of Scientific and Technical Information of China (English)

    ZHOU Hong; GUO Shu-zhen; ZHOU Hao; ZHU Yue-feng; ZHANG Li-juan; ZHANG Wei

    2012-01-01

    Background Hand,foot and mouth disease (HFMD) is an emerging public health problem in China,not only threatening the health of children,but also causing tremendous loss and burden to both families and society.The aim of this study was to characterize the epidemiology and clinical features of HFMD,and to understand the key factors affecting HFMD in the Harbin region to provide scientific evidence for effective prevention and control strategies.@@Methods Epidemiological and clinical information from 2379 randomly chosen cases of HFMD treated at the Harbin Center for Disease Control and Prevention from May 2008 to November 2011 were analyzed.All cases were separated into common and severe HFMD,with key factors for severe HFMD analyzed using multivariable Logistic regression.@@Results Among the 2379 patients,1798 were common cases and 581 severe cases,14 of which resulted in death.Most cases were in children younger than 5 years.Morbidity peaked in July and was higher in the surrounding country and cities than in Harbin proper.Medical expenses were significantly higher for severe than for common cases (P <0.001).The primary clinical symptoms were fever and erythema; laboratory examination showed leucocytosis together with pneumonia,carditis,and abnormal electrocardiogram and electroencephalogram in severe cases.Multivariable Logistic regression analysis showed that the key factors for severe HFMD were age,morbidity location,morbidity area,fever duration,mouth mucosal symptoms,and abnormal serum levels of neutrophils (NEUT),hemoglobin and glucose (P <0.05).@@Conclusions To improve prognosis,reduce medical expense and prevent the development of severe cases,we should improve the epidemiological detection of HFMD to treat patients quickly.We should also closely monitor children with the EV71 virus,who present with continuous fever as well as abnormal laboratory results,from areas highly susceptible to HFMD attacks.

  6. Prediction of dengue disease severity among pediatric Thai patients using early clinical laboratory indicators.

    Directory of Open Access Journals (Sweden)

    James A Potts

    Full Text Available Dengue virus is endemic in tropical and sub-tropical resource-poor countries. Dengue illness can range from a nonspecific febrile illness to a severe disease, Dengue Shock Syndrome (DSS, in which patients develop circulatory failure. Earlier diagnosis of severe dengue illnesses would have a substantial impact on the allocation of health resources in endemic countries.We compared clinical laboratory findings collected within 72 hours of fever onset from a prospective cohort children presenting to one of two hospitals (one urban and one rural in Thailand. Classification and regression tree analysis was used to develop diagnostic algorithms using different categories of dengue disease severity to distinguish between patients at elevated risk of developing a severe dengue illness and those at low risk. A diagnostic algorithm using WBC count, percent monocytes, platelet count, and hematocrit achieved 97% sensitivity to identify patients who went on to develop DSS while correctly excluding 48% of non-severe cases. Addition of an indicator of severe plasma leakage to the WHO definition led to 99% sensitivity using WBC count, percent neutrophils, AST, platelet count, and age.This study identified two easily applicable diagnostic algorithms using early clinical indicators obtained within the first 72 hours of illness onset. The algorithms have high sensitivity to distinguish patients at elevated risk of developing severe dengue illness from patients at low risk, which included patients with mild dengue and other non-dengue febrile illnesses. Although these algorithms need to be validated in other populations, this study highlights the potential usefulness of specific clinical indicators early in illness.

  7. Clinical and psychosocial factors predicting health-related quality of life in hemodialysis patients.

    Science.gov (United States)

    Kang, Gun Woo; Lee, In Hee; Ahn, Ki Sung; Lee, Jonghun; Ji, Yunmi; Woo, Jungmin

    2015-07-01

    Many patients with end-stage renal disease have significant impairment in health-related quality of life (HRQoL). Most previous studies have focused on clinical factors; however, quality of life can also be affected by psychosocial factors. The aim of this study was to identify the possible predictors of HRQoL among clinical and psychosocial factors in hemodialysis (HD) patients. The study included 101 patients who were undergoing HD. Psychosocial factors were evaluated using the Hospital Anxiety and Depression Scale, Multidimensional Scale of Perceived Social Support, Montreal Cognitive Assessment, and Pittsburgh Sleep Quality Index. We also assessed laboratory and clinical factors, including albumin, Kt/V as a marker of dialysis adequacy, normalized protein catabolic rate, and duration of HD. The Euro Quality of Life Questionnaire 5-Dimensional Classification (EQ-5D) was used to evaluate HRQoL. The mean EQ-5D index score was 0.704 ± 0.199. The following variables showed a significant association with the EQ-5D index: age (P < 0.001), depression (P < 0.001), anxiety (P < 0.001), support from friends (P < 0.001), cognitive function (P < 0.001), duration of HD (P = 0.034), triglyceride (P = 0.031), total iron-binding capacity (P = 0.036), and phosphorus (P = 0.037). Multiple regression analysis showed that age (95% confidence interval [CI] -0.008 to -0.002), anxiety (95% CI -0.025 to -0.009), and support from friends (95% CI 0.004 to 0.018) were independent predictors of impaired HRQoL. This study explored determinants of impaired HRQoL in HD patients. We found that impaired HRQoL was independently associated with age, anxiety, and support from friends. We should consider psychosocial as well as clinical factors when evaluating ways to improve HRQoL in HD patients.

  8. A multi-centre phase IIa clinical study of predictive testing for preeclampsia

    DEFF Research Database (Denmark)

    Navaratnam, Kate; Alfirevic, Zarko; Baker, Philip N;

    2013-01-01

    5% of first time pregnancies are complicated by pre-eclampsia, the leading cause of maternal death in Europe. No clinically useful screening test exists; consequentially clinicians are unable to offer targeted surveillance or preventative strategies. IMPROvED Consortium members have pioneered...... a personalised medicine approach to identifying blood-borne biomarkers through recent technological advancements, involving mapping of the blood metabolome and proteome. The key objective is to develop a sensitive, specific, high-throughput and economically viable early pregnancy screening test for pre-eclampsia....

  9. Can Preterm Labour Be Predicted in Low Risk Pregnancies? Role of Clinical, Sonographic, and Biochemical Markers

    Directory of Open Access Journals (Sweden)

    Reva Tripathi

    2014-01-01

    Full Text Available Background and Objectives. This is a prospective nested cohort study conducted over a period of 3 years. 2644 women were recruited, out of which final analysis was done for 1884 women. Methods. Cervicovaginal and blood samples were collected for all recruited women. Out of these, 137 women who delivered before 35 weeks were treated as cases and equal number of matched controls were chosen. Analysis of samples for serum G-CSF, AFP, ferritin, and cervicovaginal interleukin-6 and IGFBP-1 was done. Results. Poor orodental hygiene, which can be a social marker, was significantly more common in women who delivered preterm (P=0.008. Serum alkaline phosphatase and serum ferritin were found to be significantly associated with preterm deliveries. The 90th percentile value of these parameters was considered as cut-off as there is no specific cut-off. Conclusions. Our study did not prove usefulness of any predictive marker. Serum ferritin and alkaline phosphatase were found to have correlation but their values are affected in many conditions and need to be elucidated with caution. Larger studies are needed for predicting preterm labour in asymptomatic women.

  10. Presepsin is an early monitoring biomarker for predicting clinical outcome in patients with sepsis.

    Science.gov (United States)

    Ali, Fahmy T; Ali, Mohamed A M; Elnakeeb, Mostafa M; Bendary, Heba N M

    2016-09-01

    Despite their undoubted helpfulness in diagnosing sepsis, increased blood C-reactive protein (CRP) and procalcitonin (PCT) levels have been described in many noninfectious conditions. Presepsin is a soluble fragment of the cluster of differentiation 14 involved in pathogen recognition by innate immunity. We aimed to investigate the diagnostic and prognostic performance of presepsin in comparison to PCT and CRP in patients presenting with systemic inflammatory response syndrome (SIRS) and suspected sepsis. Seventy-six subjects were enrolled in this study, including 51 patients with SIRS as well as 25 healthy subjects. Plasma presepsin, PCT and CRP levels were serially measured on admission and at days 1, 3, 7 and 15. Presepsin and PCT yielded similar diagnostic accuracy, whereas presepsin performed significantly better than CRP. Presepsin and PCT showed comparable performance for predicting 28-day mortality, and both biomarkers performed significantly better than CRP. In septic patients, presepsin revealed earlier concentration changes over time when compared to PCT and CRP. Presepsin and PCT could differentiate between septic and non-septic patients with comparable accuracy and both biomarkers showed similar performance for predicting 28-day mortality. Early changes in presepsin concentrations might reflect the appropriateness of the therapeutic modality and could be useful for making effective treatment decisions. PMID:27353646

  11. Review of a large clinical series: Predicting death for patients with abdominal septic shock.

    Science.gov (United States)

    Hanisch, Ernst; Brause, Rüdiger; Paetz, Jürgen; Arlt, Björn

    2011-01-01

    This paper reports the result of the MEDAN project that analyzes a multicenter septic shock patient data collection. The mortality prognosis based on 4 scores that are often used is compared with the prognosis of a trained neural network. We built an alarm system using the network classification results. Method. We analyzed the data of 382 patients with abdominal septic shock who were admitted to the intensive care unit (ICU) from 1998 to 2002. The analysis includes the calculation of daily sepsis-related organ failure assessment (SOFA), Acute Physiological and Chronic Health Evaluation (APACHE) II, simplified acute physiology score (SAPS) II, multiple-organ dysfunction score (MODS) scores for each patient and the training and testing of an appropriate neural network. Results. For our patients with abdominal septic shock, the analysis shows that it is not possible to predict their individual fate correctly on the day of admission to the ICU on the basis of any current score. However, when the trained network computes a score value below the threshold during the ICU stay, there is a high probability that the patient will die within 3 days. The trained neural network obtains the same outcome prediction performance as the best score, the SOFA score, using narrower confidence intervals and considering three variables only: systolic blood pressure, diastolic blood pressure and the number of thrombocytes. We conclude that the currently best available score for abdominal septic shock may be replaced by the output of a trained neural network with only 3 input variables. PMID:21262751

  12. 解读《药物临床试验机构资格认定检查细则》(试行)%Interpretation of"Clinical Test Qualification Examination Rules"(Trial)

    Institute of Scientific and Technical Information of China (English)

    闫妍; 时钢

    2015-01-01

    2014年9月5日,国家食品药品监督管理局颁布了《药物临床试验机构资格认定检查细则(试行)》征求意见稿,该文件是总局审核查验中心根据《药物临床试验质量管理规范》以及药物临床试验机构管理的有关规定,对《药物临床试验机构资格认定标准》的相关条款进行全面细化而产生。本文将主要从《药物临床试验机构资格认定检查细则》(试行)的制定意义、检查内容、检查方法以及存在问题等几个方面进行阐述,为药物临床试验机构迎接资格认定检查工作及规范管理提供一定参考。%September 5, 2014, the State Food and Drug Administration issued a "drug clinical trial institution accreditation inspection rules (Trial)" the draft, the document is in accordance with the General Administration of audit inspection center"Good Clinical Practice" and drugs relevant provisions of the institutional management of clinical trials, on the "clinical test qualification standards,"the relevant provisions of the overal refinement and production. This article wil focus on the "drug clinical trial institution recognized qualification examination Rules" (Trial) formulation meaning, check the contents of several aspects, inspection methods and problems and so forth, to meet the qualification checks and standardize the management of clinical trials for drug agencies certain reference.

  13. Positron emission tomography scan for predicting clinical outcome of patients with recurrent cervical carcinoma following radiation therapy

    Directory of Open Access Journals (Sweden)

    Daya Nand Sharma

    2012-01-01

    Materials and Methods: Twenty two patients of post irradiated recurrent cervical carcinoma (PIRCC were enrolled in this prospective study. 18-fluorodeoxyglucose (FDG PET imaging was performed in each patient before the salvage therapy. The maximum standardized uptake value (SUVmax and metabolic tumor volume (MTV were measured and correlated with cumulative progression free survival (PFS. Results: Median age of patients was 42 years. Majority of patients had stage III disease at the initial presentation and all 22 patients had received prior definitive RT. The median recurrence free period was 11 months. Salvage therapy consisted of surgical resection or re-irradiation depending upon the various clinical and radiological factors. Median SUVmax was 5.8 (range 1.8-50.6 and median MTV was 43 cm 3 (range 5.8-243. The cumulative PFS for all patients was 20% at 30 months. The one-year PFS was 28% for patients with SUVmax value of >5.8 versus 42% for those with SUVmax value of 43 cm 3 versus 45% for those with MTV value of <43 cm 3 (P value 0.8. Conclusion: Our preliminary experience has suggested that FDG uptake on PET scan can predict the clinical outcome of PIRCC patients. Further randomized studies may be conducted with large sample size and longer follow up to establish its definite predictive value.

  14. Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer.

    Science.gov (United States)

    Chung, Mi Joo; Lee, Jong Hoon; Kim, Sung Hwan; Suh, Young Jin; Choi, Hyun Joo

    2016-05-01

    The aim of this study was to evaluate the association between pretreatment molecular and clinical factors and axillary lymph node metastases in early breast cancer. A total of 367 consecutive breast cancer patients with cT1-2NxM0 who underwent breast conserving surgery and axillary lymph node dissection followed by whole breast irradiation were enrolled. We evaluated the pathologic tumor and node status, tumor differentiation, calcification, and lymphovascular invasion, the status of estrogen receptor (ER), progesterone receptor (PR), epidermal growth factor receptor 1 (EGFR1), and human epidermal growth factor receptor 2 (HER2), the expression of E-cadherin, P53, and Ki-67 index. Totally, 108 (29.4%) of the 367 patients had positive axillary lymph nodes. An increased tumor size (P = 0.024), the presence of lymphovascular invasion (P 20% (P = 0.038) were significantly associated with axillary lymph node metastases on the multivariate analysis. In our study, 86.2% of the patients with all the unfavorable factors had an involvement of axillary nodal metastases, and only 12.2% of the patients with all the favorable predictors had positive axillary nodes. The predictive power was significant on the receiver operating curve (P positive ALNM on multivariate analysis for the patients with cT1-2 breast cancer. Clinicians simply could predict the probability of ALNM after verifying the molecular and clinical factors in early breast cancer. PMID:27196477

  15. [Critical evaluation and predictive value of clinical presentation in out-patients with acute community-acquired pneumonia].

    Science.gov (United States)

    Mayaud, C; Fartoukh, M; Prigent, H; Parrot, A; Cadranel, J

    2006-01-01

    Diagnostic probability of community-acquired pneumonia (CAP) depends on data related to age and clinical and radiological findings. The critical evaluation of data in the literature leads to the following conclusions: 1) the prevalence of CAP in a given population with acute respiratory disease is 5% in outpatients and 10% in an emergency care unit. This could be as low as 2% in young people and even higher than 40% in hospitalized elderly patients; 2) the collection of clinical data is linked to the way the patient is examined and to the expertise of the clinician. The absolute lack of "vital signs" has a good negative predictive value in CAP; presence of unilateral crackles has a good positive predictive value; 3) there is a wide range of X-ray abnormalities: localized alveolar opacities; interstitial opacities, limited of diffused. The greatest radiological difficulties are encountered in old people with disorders including chronic respiratory or cardiac opacities and as a consequence of the high prevalence of bronchopneumonia episodes at this age; 4) among patients with lower respiratory tract (LRT) infections, the blood levels of leukocytes, CRP and procalcitonine are higher in CAP patients, mainly when their disease has a bacterial origin. Since you have not a threshold value reliably demonstrated in large populations with LRT infections or acute respiratory disease, presence or absence of these parameters could only be taken as a slight hint for a CAP diagnosis. PMID:17084571

  16. Serum BAP as the clinically useful marker for predicting BMD reduction in diabetic hemodialysis patients with low PTH.

    Science.gov (United States)

    Ueda, Misako; Inaba, Masaaki; Okuno, Senji; Maeno, Yoshifumi; Ishimura, Eiji; Yamakawa, Tomoyuki; Nishizawa, Yoshiki

    2005-07-22

    With decrease of serum PTH in hemodialysis (HD) patients, other factors besides parathyroid hormone (PTH) become important in regulating bone metabolism. We investigated which serum bone metabolic marker is the best to predict the bone mineral density (BMD) reduction in HD patients with serum PTHBAP), intact osteocalcin (OC), and N-terminal propeptide of type I collagen (PINP), and the bone resorption markers, deoxypyridinoline (DPD), pyridinoline (PYD), and beta-crossLaps (beta-CTx) were measured in serum from 137 HD patients. BMD of all patients was measured twice, approximately 1.5 years before and 1.5 years after measurement of their markers of bone metabolism. In all 137 HD patients, serum BAP was the only marker significantly higher in those with BMD reduction than in those without. In 42 diabetes mellitus (DM) HD patients with serum PTHBAP was again the only marker to discriminate those with BMD reduction from those without. At serum PTHBAP retained tendency toward higher value. These findings suggest that serum BAP might be the most sensitive to identify small changes of bone metabolism in low bone turnover state. Retrospective study confirmed the usefulness of serum BAP in clinical practice by significantly higher values in those with bone loss at PTHBAP is a clinically useful bone formation marker to predict the BMD reduction in DM HD patients with low level of PTH.

  17. International Study to Predict Optimized Treatment for Depression (iSPOT-D, a randomized clinical trial: rationale and protocol

    Directory of Open Access Journals (Sweden)

    Cooper Nicholas J

    2011-01-01

    Full Text Available Abstract Background Clinically useful treatment moderators of Major Depressive Disorder (MDD have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. Methods/Design The International Study to Predict Optimized Treatment - in Depression (iSPOT-D is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65 from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls. Study-eligible patients are antidepressant medication (ADM naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary. Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. Discussion First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. Trial registration International Study to Predict Optimised Treatment - in Depression (iSPOT-D ClinicalTrials.gov Identifier

  18. What differences are detected by superiority trials or ruled out by noninferiority trials? A cross-sectional study on a random sample of two-hundred two-arms parallel group randomized clinical trials

    Directory of Open Access Journals (Sweden)

    Courvoisier Delphine S

    2010-10-01

    Full Text Available Abstract Background The smallest difference to be detected in superiority trials or the largest difference to be ruled out in noninferiority trials is a key determinant of sample size, but little guidance exists to help researchers in their choice. The objectives were to examine the distribution of differences that researchers aim to detect in clinical trials and to verify that those differences are smaller in noninferiority compared to superiority trials. Methods Cross-sectional study based on a random sample of two hundred two-arm, parallel group superiority (100 and noninferiority (100 randomized clinical trials published between 2004 and 2009 in 27 leading medical journals. The main outcome measure was the smallest difference in favor of the new treatment to be detected (superiority trials or largest unfavorable difference to be ruled out (noninferiority trials used for sample size computation, expressed as standardized difference in proportions, or standardized difference in means. Student t test and analysis of variance were used. Results The differences to be detected or ruled out varied considerably from one study to the next; e.g., for superiority trials, the standardized difference in means ranged from 0.007 to 0.87, and the standardized difference in proportions from 0.04 to 1.56. On average, superiority trials were designed to detect larger differences than noninferiority trials (standardized difference in proportions: mean 0.37 versus 0.27, P = 0.001; standardized difference in means: 0.56 versus 0.40, P = 0.006. Standardized differences were lower for mortality than for other outcomes, and lower in cardiovascular trials than in other research areas. Conclusions Superiority trials are designed to detect larger differences than noninferiority trials are designed to rule out. The variability between studies is considerable and is partly explained by the type of outcome and the medical context. A more explicit and rational approach to

  19. Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, J. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Department of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg 69117 (Germany); Moteabbed, M.; Paganetti, H., E-mail: hpaganetti@mgh.harvard.edu [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02114 (United States)

    2015-01-15

    Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio

  20. CT colonography without cathartic preparation: positive predictive value and patient experience in clinical practice

    International Nuclear Information System (INIS)

    To determine the positive predictive value (PPV) for polyps ≥6 mm detected at CT colonography (CTC) performed without cathartic preparation, with low-dose iodine faecal tagging regimen and to evaluate patient experience. 1920 average-risk patients underwent CTC without cathartic preparation. Faecal tagging was performed by diatrizoate meglumine and diatrizoate sodium at a total dose of 60 ml (22.2 g of iodine).The standard interpretation method was primary 3D with 2D problem solving. We calculated per-patient and per-polyp PPV in relation to size and morphology. All colonic segments were evaluated for image quality (faecal tagging, amount of liquid and solid residual faeces and luminal distension). Patients completed a questionnaire before and after CTC to assess preparation and examination experience. Per-polyp PPV for detected lesions of ≥6 mm, 6-9 mm, ≥10 mm and ≥30 mm were 94.3%, 93.1%, 94.7% and 98%, respectively. Per-polyp PPV, according to lesion morphology, was 94.6%, 97.3% and 85.1% for sessile, pedunculated and flat polyps, respectively. Per-patient PPV was 92.8%. Preparation without frank cathartics was reported to cause minimal discomfort by 78.9% of patients. CTC without cathartic preparation and low-dose iodine faecal tagging may yield high PPVs for lesions ≥6 mm and is well accepted by patients. circle Computed tomographic colonography (CTC) without cathartic preparation is well accepted by patients circle Cathartic-free faecal tagging CTC yields high positive predictive values circle CTC without cathartic preparation could improve uptake of colorectal cancer screening. (orig.)

  1. A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

    Science.gov (United States)

    Rahmim, Arman; Schmidtlein, C. Ross; Jackson, Andrew; Sheikhbahaei, Sara; Marcus, Charles; Ashrafinia, Saeed; Soltani, Madjid; Subramaniam, Rathan M.

    2016-01-01

    Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

  2. Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

    Science.gov (United States)

    Vukicevic, Arso M; Stojadinovic, Miroslav; Radovic, Milos; Djordjevic, Milena; Cirkovic, Bojana Andjelkovic; Pejovic, Tomislav; Jovicic, Gordana; Filipovic, Nenad

    2016-08-01

    Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains limited since the development of ANNs represents a slow process that requires additional expertize from potential users. The aim of this study was to propose an ES for automated development of ANNs and validate its performances on the problem of prediction of CBDS. Automated development of the ANN was achieved by applying the evolutionary assembling approach, which assumes optimal configuring of the ANN parameters by using Genetic algorithm. Automated selection of optimal features for the ANN training was performed using a Backward sequential feature selection algorithm. The assessment of the developed ANN included the evaluation of predictive ability and clinical utility. For these purposes, we collected data from 303 patients who underwent surgery in the period from 2008 to 2014. The results showed that the total bilirubin, alanine aminotransferase, common bile duct diameter, number of stones, size of the smallest calculus, biliary colic, acute cholecystitis and pancreatitis had the best prognostic value of CBDS. Compared to the alternative approaches, the ANN obtained by the proposed ES had better sensitivity and clinical utility, which are considered to be the most important for the particular problem. Besides the fact that it enabled the development of ANNs with better performances, the proposed ES significantly reduced the complexity of ANNs' development compared to previous studies that required manual selection of optimal features and/or ANN configuration. Therefore, it is concluded that the proposed ES represents a robust and user-friendly framework that, apart from the prediction of CBDS, could advance and simplify the application of ANNs for solving a wider range of problems. PMID:27261565

  3. Finite-Element Model Predicts Current Density Distribution for Clinical Applications of tDCS and tACS.

    Science.gov (United States)

    Neuling, Toralf; Wagner, Sven; Wolters, Carsten H; Zaehle, Tino; Herrmann, Christoph S

    2012-01-01

    Transcranial direct current stimulation (tDCS) has been applied in numerous scientific studies over the past decade. However, the possibility to apply tDCS in therapy of neuropsychiatric disorders is still debated. While transcranial magnetic stimulation (TMS) has been approved for treatment of major depression in the United States by the Food and Drug Administration (FDA), tDCS is not as widely accepted. One of the criticisms against tDCS is the lack of spatial specificity. Focality is limited by the electrode size (35 cm(2) are commonly used) and the bipolar arrangement. However, a current flow through the head directly from anode to cathode is an outdated view. Finite-element (FE) models have recently been used to predict the exact current flow during tDCS. These simulations have demonstrated that the current flow depends on tissue shape and conductivity. To face the challenge to predict the location, magnitude, and direction of the current flow induced by tDCS and transcranial alternating current stimulation (tACS), we used a refined realistic FE modeling approach. With respect to the literature on clinical tDCS and tACS, we analyzed two common setups for the location of the stimulation electrodes which target the frontal lobe and the occipital lobe, respectively. We compared lateral and medial electrode configuration with regard to their usability. We were able to demonstrate that the lateral configurations yielded more focused stimulation areas as well as higher current intensities in the target areas. The high resolution of our simulation allows one to combine the modeled current flow with the knowledge of neuronal orientation to predict the consequences of tDCS and tACS. Our results not only offer a basis for a deeper understanding of the stimulation sites currently in use for clinical applications but also offer a better interpretation of observed effects. PMID:23015792

  4. Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions.

    Directory of Open Access Journals (Sweden)

    Jon D Duke

    Full Text Available Drug-drug interactions (DDIs are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69; loratadine and alprazolam (RR = 1.86; loratadine and duloxetine (RR = 1.94; loratadine and ropinirole (RR = 3.21; and promethazine and tegaserod (RR = 3.00. When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms.

  5. EGFR CA repeat polymorphism predict clinical outcome in EGFR mutation positive NSCLC patients treated with erlotinib

    DEFF Research Database (Denmark)

    Winther Larsen, Anne; Nissen, Peter Henrik; Meldgaard, Peter;

    2014-01-01

    OBJECTIVES: Somatic mutations in the epidermal growth factor receptor (EGFR) are predictors of efficacy for treatment with the EGFR tyrosine kinase inhibitor erlotinib in non-small cell lung cancer (NSCLC). A CA repeat polymorphism in intron 1 of the EGFR gene influences the transcription...... of the EGFR gene. This study evaluates the association between the CA repeat polymorphism and outcome in NSCLC patients treated with erlotinib.MATERIALS AND METHODS: Number of CA repeats in the EGFR gene was evaluated with PCR-fragment length analysis by capillary electrophoresis in 432 advanced NSCLC...... patients treated with erlotinib irrespective of EGFR mutation status. Patients were dichotomized into harboring short allele (CA≤16 in any allele) or long alleles (CA>16 in both alleles). Number of repeats was correlated with clinical characteristic and outcome. A subgroup analysis was performed based...

  6. Microinvasion of liver metastases from colorectal cancer: predictive factors and application for determining clinical target volume

    International Nuclear Information System (INIS)

    This study evaluates the microscopic characteristics of liver metastases from colorectal cancer (LMCRC) invasion and provides a reference for expansion from gross tumor volume (GTV) to clinical targeting volume (CTV). Data from 129 LMCRC patients treated by surgical resection at our hospital between January 2008 and September 2009 were collected for study. Tissue sections used for pathology and clinical data were reviewed. Patient information used for the study included gender, age, original tumor site, number of tumors, tumor size, levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 199 (CA199), synchronous or metachronous liver metastases, and whether patients received chemotherapy. The distance of liver microinvasion from the tumor boundary was measured microscopically by two senior pathologists. Of 129 patients evaluated, 81 (62.8 %) presented microinvasion distances from the tumor boundary ranging between 1.0 − 7.0 mm. A GTV-to-CTV expansion of 5, 6.7, or 7.0 mm was required to provide a 95, 99, or 100 % probability, respectively, of obtaining clear resection margins by microscopic observation. The extent of invasion was not related to gender, age, synchronous or metachronous liver metastases, tumor size, CA199 level, or chemotherapy. The extent of invasion was related to original tumor site, CEA level, and number of tumors. A scoring system was established based on the latter three positive predictors. Using this system, an invasion distance less than 3 mm was measured in 93.4 % of patients with a score of ≤1 point, but in only 85.7 % of patients with a score of ≤2 points. The extent of tumor invasion in our LMCRC patient cohort correlated with original tumor site, CEA level, and number of tumors. These positive predictors may potentially be used as a scoring system for determining GTV-to-CTV expansion

  7. The Anion Gap is a Predictive Clinical Marker for Death in Patients with Acute Pesticide Intoxication.

    Science.gov (United States)

    Lee, Sun-Hyo; Park, Samel; Lee, Jung-Won; Hwang, Il-Woong; Moon, Hyung-Jun; Kim, Ki-Hwan; Park, Su-Yeon; Gil, Hyo-Wook; Hong, Sae-Yong

    2016-07-01

    Pesticide formulation includes solvents (methanol and xylene) and antifreeze (ethylene glycol) whose metabolites are anions such as formic acid, hippuric acid, and oxalate. However, the effect of the anion gap on clinical outcome in acute pesticide intoxication requires clarification. In this prospective study, we compared the anion gap and other parameters between surviving versus deceased patients with acute pesticide intoxication. The following parameters were assessed in 1,058 patients with acute pesticide intoxication: blood chemistry (blood urea nitrogen, creatinine, glucose, lactic acid, liver enzymes, albumin, globulin, and urate), urinalysis (ketone bodies), arterial blood gas analysis, electrolytes (Na(+), K(+), Cl(-) HCO3 (-), Ca(++)), pesticide field of use, class, and ingestion amount, clinical outcome (death rate, length of hospital stay, length of intensive care unit stay, and seriousness of toxic symptoms), and the calculated anion gap. Among the 481 patients with a high anion gap, 52.2% had a blood pH in the physiologic range, 35.8% had metabolic acidosis, and 12.1% had acidemia. Age, anion gap, pesticide field of use, pesticide class, seriousness of symptoms (all P < 0.001), and time lag after ingestion (P = 0.048) were significant risk factors for death in univariate analyses. Among these, age, anion gap, and pesticide class were significant risk factors for death in a multiple logistic regression analysis (P < 0.001). In conclusions, high anion gap is a significant risk factor for death, regardless of the accompanying acid-base balance status in patients with acute pesticide intoxication. PMID:27366016

  8. A Simple Clinical Score “TOPRS” to Predict Outcome in Pediatric Emergency Department in a Teaching Hospital in India

    Directory of Open Access Journals (Sweden)

    2012-03-01

    Full Text Available Objective: To develop a simple clinical scoring system for severity of illness to help prioritize care and predict outcome in emergency department.Methods: Prospective hospital based observational study. Out of a total of 874 children who attended emergency department in one year, 777 were included in the study. Data was collected at the time ofadmission in emergency department. The baseline information like age, gender, etc and variables of ‘toprs’score viz temperature, oxygen saturation, pulse rate, respiratory rate, sensorium and seizures were recorded.Variables were categorized as normal (score zero or abnormal (score 1 based on systemic inflammatory response syndrome (SIRS criteria and criteria mentioned in advanced pediatric life support (APLS and the total scores were computed for each child. The outcome (death/discharge was correlated with the studyvariables and total score. The predictive ability of score was calculated using receiver operating characteristic (ROC curve analysis.Findings: Of the six variables, temperature, oxygen saturation and respiratory rate were found to be significantly associated with mortality. Mortality increased with the increase in the number of abnormal variables. Based on the regression coefficients, maximum possible score was 6.68. The predictive ability of score was 81.7 calculated using ROC curve. Maximum discrimination was observed at a score of 2.5.Conclusion: For triage in emergency, any patient with 2 or more abnormal variables should be closely monitored and evaluated. These patients require admission as they have a potential risk of death.

  9. Role of p-glycoprotein expression in predicting response to neoadjuvant chemotherapy in breast cancer-a prospective clinical study

    Directory of Open Access Journals (Sweden)

    Bhatia Ashima

    2005-09-01

    Full Text Available Abstract Background Neoadjuvant chemotherapy (NACT is an integral part of multi-modality approach in the management of locally advanced breast cancer. It is vital to predict response to chemotherapy in order to tailor the regime for a particular patient. The prediction would help in avoiding the toxicity induced by an ineffective chemotherapeutic regime in a non-responder and would also help in the planning of an alternate regime. Development of resistance to chemotherapeutic agents is a major problem and one of the mechanisms considered responsible is the expression of 170-k Da membrane glycoprotein (usually referred to as p-170 or p-glycoprotein, which is encoded by multidrug resistance (MDR1 gene. This glycoprotein acts as an energy dependent pump, which actively extrudes certain families of chemotherapeutic agents from the cells. The expression of p-glycoprotein at initial presentation has been found to be associated with refractoriness to chemotherapy and a poor outcome. Against this background a prospective study was conducted using C219 mouse monoclonal antibody specific for p-glycoprotein to ascertain whether pretreatment detection of p-glycoprotein expression could be utilized as a reliable predictor of response to neoadjuvant chemotherapy in patients with breast cancer. Patients and methods Fifty cases of locally advanced breast cancer were subjected to trucut® biopsy and the tissue samples were evaluated immunohistochemically for p-glycoprotein expression and ER, PR status. The response to neoadjuvant chemotherapy was assessed clinically and by using ultrasound after three cycles of FAC regime (cyclophosphamide 600 mg/m2, Adriamycin 50 mg/m2, 5-fluorourail 600 mg/m2 at an interval of three weeks. The clinical response was correlated with both the pre and post chemotherapy p-glycoprotein expression. Descriptive studies were performed with SPSS version 10. The significance of correlation between tumor response and p

  10. Hip and fragility fracture prediction by 4-item clinical risk score and mobile heel BMD: a women cohort study

    Directory of Open Access Journals (Sweden)

    Thulesius Hans

    2010-03-01

    Full Text Available Abstract Background One in four Swedish women suffers a hip fracture yielding high morbidity and mortality. We wanted to revalidate a 4-item clinical risk score and evaluate a portable heel bone mineral density (BMD technique regarding hip and fragility fracture risk among elderly women. Methods In a population-based prospective cohort study we used clinical risk factors from a baseline questionnaire and heel BMD to predict a two-year hip and fragility fracture outcome for women, in a fracture preventive program. Calcaneal heel BMD was measured by portable dual X-ray laser absorptiometry (DXL and compared to hip BMD, measured with stationary dual X-ray absorptiometry (DXA technique. Results Seven women suffered hip fracture and 14 women fragility fracture/s (at hip, radius, humerus and pelvis among 285 women; 60% having heel BMD ≤ -2.5 SD. The 4-item FRAMO (Fracture and Mortality Index combined the clinical risk factors age ≥80 years, weight Conclusions In a follow-up study we identified high risk groups for hip and fragility fracture with our plain 4-item risk model. Increased fracture risk was also related to decreasing heel BMD in calcaneal bone, measured with a mobile DXL technique. A combination of high FRAMO Index, prior fragility fracture, and very low BMD restricted the high risk group to 11%, among whom most hip fractures occurred (71%. These practical screening methods could eventually reduce hip fracture incidence by concentrating preventive resources to high fracture risk women.

  11. Genetic markers predicting sulphonylurea treatment outcomes in type 2 diabetes patients: current evidence and challenges for clinical implementation.

    Science.gov (United States)

    Loganadan, N K; Huri, H Z; Vethakkan, S R; Hussein, Z

    2016-06-01

    The clinical response to sulphonylurea, an oral antidiabetic agent often used in combination with metformin to control blood glucose in type 2 diabetes (T2DM) patients, has been widely associated with a number of gene polymorphisms, particularly those involved in insulin release. We have reviewed the genetic markers of CYP2C9, ABCC8, KCNJ11, TCF7L2 (transcription factor 7-like 2), IRS-1 (insulin receptor substrate-1), CDKAL1, CDKN2A/2B, KCNQ1 and NOS1AP (nitric oxide synthase 1 adaptor protein) genes that predict treatment outcomes of sulphonylurea therapy. A convincing pattern for poor sulphonylurea response was observed in Caucasian T2DM patients with rs7903146 and rs1801278 polymorphisms of the TCF7L2 and IRS-1 genes, respectively. However, limitations in evaluating the available studies including dissimilarities in study design, definitions of clinical end points, sample sizes and types and doses of sulphonylureas used as well as ethnic variability make the clinical applications challenging. Future studies need to address these limitations to develop personalized sulphonylurea medicine for T2DM management. PMID:26810132

  12. Construction and clinical significance of a predictive system for prognosis of hepatocellular carcinoma

    Institute of Scientific and Technical Information of China (English)

    Jun Cui; Bao-Wei Dong; Ping Liang; Xiao-Ling Yu; De-Jiang Yu

    2005-01-01

    AIM: The aims of this study were to explore individualized treatment method for hepatocellular carcinoma (HCC)patients whose maximum tumor size was less than 5 cm to improve prognosis and survival quality. METHODS: Thirty cases of primary HCC patients undergoing tumor resection were retrospectively analyzed (resection group). All the tumors were proved as primary HCC with pathologic examination. The patients were divided into two groups according to follow-up results: group A, with tumor recurrence within 1 year after resection; group B, without tumor recurrence within 1 year. Immunohist ochemical stainings were performed using 11 kinds of monoclonal antibodies (AFP, c-erbB2, c-met, c-myc, HBsAg, HCV, Ki-67, MMP-2, nm23-H1, P53, and VEGF), and expressing intensities were quantitatively analyzed. Regression equation using factors affecting prognosis of HCC was constructed with binary logistic method. HCC patients undergoing percutaneous microwave coagulation therapy (PMCT) were also retrospectively analyzed (PMCT group). Immunohistochemical stainings of tumor biopsy samples were performed with molecules related to HCC prognosis, staining intensities were quantitatively analyzed, coincidence rate of prediction was calculated. RESULTS: In resection group, the expressing intensities of c-myc, Ki-67, MMP-2 and VEGF in cancer tissue in group A were significantly higher than those in group B (t = 2.97, P= 0.01; t= 2.42,P= 0.03<0.05; t= 2.57,P= 0.02<0.05;t = 3.43, P = 0.004<0.01, respectively); the expressingintensities of 11 kinds of detected molecules in para-cancer tissue in groups A and B were not significantly different (P>0.05). The regression equation predicting prognosis of HCC is as follows: P(1) = 1/[1+e-(3.663-0.412mycc-2.187Ki-67c-0.387vegfc)].It demonstrates that prognosis of HCC in resection group was related with c-myc, Ki-67 and VEGF expressing intensity in cancer tissue. In PMCT group, the expressing intensities of c-myc, Ki-67 and VEGF in cancer

  13. The clinical value of hybrid sentinel lymphoscintigraphy to predict metastatic sentinel lymph nodes in breast cancer

    International Nuclear Information System (INIS)

    Hybrid imaging techniques can provide functional and anatomical information about sentinel lymph nodes in breast cancer. Our aim in this study was to evaluate which imaging parameters on hybrid sentinel lymphoscintigraphy predicted metastatic involvement of sentinel lymph nodes (SLNs) in patients with breast cancer. Among 56 patients who underwent conventional sentinel lymphoscintigraphy, 45 patients (age, 53.1 ± 9.5 years) underwent hybrid sentinel lymphoscintigraphy using a single-photon emission computed tomography (SPECT)/computed tomography (CT) gamma camera. On hybrid SPECT/CT images, we compared the shape and size (long-to-short axis [L/S] ratio) of the SLN, and SLN/periareolar injection site (S/P) count ratio between metastatic and non-metastatic SLNs. Metastatic involvement of sentinel lymph nodes was confirmed by pathological biopsy. Pathological biopsy revealed that 21 patients (46.7 %) had metastatic SLNs, while 24 (53.3 %) had non-metastatic SLNs. In the 21 patients with metastatic SLNs, the SLN was mostly round (57.1 %) or had an eccentric cortical rim (38.1 %). Of 24 patients with non-metastatic SLNs, 13 patients (54.1 %) had an SLN with a C-shape rim or eccentric cortex. L/S ratio was 2.04 for metastatic SLNs and 2.38 for non-metastatic SLNs. Seven (33 %) patients had T1 primary tumors and 14 (66 %) had T2 primary tumors in the metastatic SLN group. In contrast, 18 (75 %) patients had T1 primary tumors and six (25 %) had T2 tumors in the non-metastatic SLN group. S/P count ratio was significantly lower in the metastatic SLN group than the non-metastatic SLN group for those patients with a T1 primary tumor (p = 0.007). Hybrid SPECT/CT offers the physiologic data of SPECT together with the anatomic data of CT in a single image. This hybrid imaging improved the anatomic localization of SLNs in breast cancer patients and predicted the metastatic involvement of SLNs in the subgroup of breast cancer patients with T1 primary tumors

  14. DIAGNOSTIC AND PREDICTIVE VALUES OF PHOTO ALBUMS AND VIDEOCLIPS IN PEDIATRIC NEUROLOGY CLINICS

    Directory of Open Access Journals (Sweden)

    M. Mohammadi MD

    2009-04-01

    Full Text Available Photo-albums and video-clips are simple means for diagnosis of diverseneurologic disorders in children. Most families either own or can borrow a still or video camera. Even when a purchase is required, it is more costeffective than brain imaging as well as other sophisticated studies, and the family has something useful to show for expenditure. On the other hand many families have a photo-album which could be very informative for pediatric neurologists. These useful and simple means are invaluable in:Differentiation of progressive from static diseases of central nervous system in children.Helping in diagnosis of diverse types of seizures in pediatric epileptic patients.Differential diagnosis of epilepsy like disorders (e.g. sleep disorders vs. epilepsy in children.Diagnosis as well as differential diagnosis of movement disorders in children.Therapeutic follow-up in many disorders (i.e. epilepsy, movement and sleep disorders in children.In my review article, I have indicated the importance of photo-albums and video-clips as invaluable means of diagnosis and  prediction in child neurology by giving simple examples in this regard.

  15. DIAGNOSTIC AND PREDICTIVE VALUES OF PHOTO ALBUMS AND VIDEOCLIPS IN PEDIATRIC NEUROLOGY CLINICS

    Directory of Open Access Journals (Sweden)

    M. Mohammadi

    2006-10-01

    Full Text Available Photo-albums and video-clips are simple means for diagnosis of diverseneurologic disorders in children. Most families either own or can borrow astill or video camera. Even when a purchase is required, it is more costeffective than brain imaging as well as other sophisticated studies, and thefamily has something useful to show for expenditure. On the other handmany families have a photo-album which could be very informative forpediatric neurologists. These useful and simple means are invaluable in: • Differentiation of progressive from static diseases of central nervoussystem in children. • Helping in diagnosis of diverse types of seizures in pediatric epilepticpatients. • Differential diagnosis of epilepsy like disorders (e.g. sleep disorders vs.epilepsy in children. • Diagnosis as well as differential diagnosis of movement disorders inchildren. • Therapeutic follow-up in many disorders (i.e. epilepsy, movement andsleep disorders in children.In my review article, I have indicated the importance of photo-albums andvideo-clips as invaluable means of diagnosis and prediction in child neurologyby giving simple examples in this regard.

  16. Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Mori, Naoko; Mugikura, Shunji; Takasawa, Chiaki; Shimauchi, Akiko; Ota, Hideki; Takase, Kei; Takahashi, Shoki [Tohoku University Graduate School of Medicine, Department of Diagnostic Radiology, Sendai (Japan); Miyashita, Minoru; Ishida, Takanori [Tohoku University Graduate School of Medicine, Department of Surgical Oncology, Sendai (Japan); Kasajima, Atsuko [Tohoku University Graduate School of Medicine, Department of Pathology, Sendai (Japan); Kodama, Tetsuya [Tohoku University Graduate School of Medicine, Department of Biomedical Engineering, Sendai (Japan)

    2016-02-15

    To evaluate whether visual assessment of T2-weighted imaging (T2WI) or an apparent diffusion coefficient (ADC) could predict lymphovascular invasion (LVI) status in cases with clinically node-negative invasive breast cancer. One hundred and thirty-six patients with 136 lesions underwent MRI. Visual assessment of T2WI, tumour-ADC, peritumoral maximum-ADC and the peritumour-tumour ADC ratio (the ratio between them) were compared with LVI status of surgical specimens. No significant relationship was found between LVI and T2WI. Tumour-ADC was significantly lower in the LVI-positive (n = 77, 896 ± 148 x 10{sup -6} mm{sup 2}/s) than the LVI-negative group (n = 59, 1002 ± 163 x 10{sup -6} mm{sup 2}/s; p < 0.0001). Peritumoral maximum-ADC was significantly higher in the LVI-positive (1805 ± 355 x 10{sup -6} mm{sup 2}/s) than the LVI-negative group (1625 ± 346 x 10{sup -6} mm{sup 2}/s; p = 0.0003). Peritumour-tumour ADC ratio was significantly higher in the LVI-positive (2.05 ± 0.46) than the LVI-negative group (1.65 ± 0.40; p < 0.0001). Receiver operating characteristic curve analysis revealed that the area under the curve (AUC) of the peritumour-tumour ADC ratio was the highest (0.81). The most effective threshold for the peritumour-tumour ADC ratio was 1.84, and the sensitivity, specificity, positive predictive value and negative predictive value were 77 % (59/77), 76 % (45/59), 81 % (59/73) and 71 % (45/63), respectively. We suggest that the peritumour-tumour ADC ratio can assist in predicting LVI status on preoperative imaging. (orig.)

  17. Regional MRI Perfusion Measures Predict Motor/Executive Function in Patients with Clinically Isolated Syndrome

    Directory of Open Access Journals (Sweden)

    Efrosini Z. Papadaki

    2014-01-01

    Full Text Available Background. Patients with clinically isolated syndrome (CIS demonstrate brain hemodynamic changes and also suffer from difficulties in processing speed, memory, and executive functions. Objective. To explore whether brain hemodynamic disturbances in CIS patients correlate with executive functions. Methods. Thirty CIS patients and forty-three healthy subjects, matched for age, gender, education level, and FSIQ, were administered tests of visuomotor learning and set shifting ability. Cerebral blood volume (CBV, cerebral blood flow (CBF, and mean transit time (MTT values were estimated in normal-appearing white matter (NAWM and normal-appearing deep gray Matter (NADGM structures, using a perfusion MRI technique. Results. CIS patients showed significantly elevated reaction time (RT on both tasks, while their CBV and MTT values were globally increased, probably due to inflammatory vasodilation. Significantly, positive correlation coefficients were found between error rates on the inhibition condition of the visuomotor learning task and CBV values in occipital, periventricular NAWM and both thalami. On the set shifting condition of the respective task significant, positive associations were found between error rates and CBV values in the semioval center and periventricular NAWM bilaterally. Conclusion. Impaired executive function in CIS patients correlated positively with elevated regional CBV values thought to reflect inflammatory processes.

  18. Synuclein gamma predicts poor clinical outcome in colon cancer with normal levels of carcinoembryonic antigen

    Directory of Open Access Journals (Sweden)

    Xing Xiaofang

    2010-07-01

    Full Text Available Abstract Background Synuclein gamma (SNCG, initially identified as a breast cancer specific gene, is aberrantly expressed in many different malignant tumors but rarely expressed in matched nonneoplastic adjacent tissues. In this study, we investigated the prognostic potential of SNCG in colon cancer particularly in the patients with normal carcinoembryonic antigen (CEA levels. Methods SNCG levels were assessed immunohistochemically in cancer tissues from 229 colon adenocarcinoma patients with a mean follow-up of 44 months. Correlations between SNCG levels and clinicopathologic features, preoperative serum CEA level, and clinical outcome were analyzed statistically using SPSS. Results SNCG levels in colon adenocarcinoma were closely associated with intravascular embolus and tumor recurrence but independent of preoperative serum CEA levels. SNCG expression was an independent prognostic factor of a shorter disease-free survival (DFS and overall survival (OS (P P = 0.001, P = 0.001, 0.002 for 97 patients with normal preoperative serum CEA level. Conclusions Our results suggest for the first time that SNCG is a new independent predicator for poor prognosis in patients with colon adenocarcinoma, including those with normal CEA levels. Combination of CEA with SNCG improves prognostic evaluation for patients with colon adenocarcinoma.

  19. MicroRNA expression profiles predict progression and clinical outcome in lung adenocarcinoma

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    Lin K

    2016-09-01

    Full Text Available Kang Lin,1,* Tao Xu,1,* Bang-Shun He,1 Yu-Qin Pan,1 Hui-Ling Sun,1 Hong-Xin Peng,2 Xiu-Xiu Hu,2 Shu-Kui Wang1 1Central Laboratory, Nanjing First Hospital, Nanjing Medical University, 2Medical School, Southeast University, Nanjing, Jiangsu, People’s Republic of China *These authors contributed equally to this work Abstract: Lung cancer is one of the leading causes of cancer death worldwide. Accumulating evidence has indicated that microRNAs (miRNAs can be proposed as promising diagnostic and prognostic markers for various cancers. The current study analyzed the miRNA expression profiles of 418 lung adenocarcinoma (LUAD cases obtained from The Cancer Genome Atlas dataset, with the aim to investigate the relationship of miRNAs with progression and prognosis of LUAD. A total of 185 miRNAs were found to be differentially expressed between LUAD tumor tissues and adjacent normal tissues. Among them, 13, 10, 0, and 10 miRNAs were discovered to be associated with pathologic T, N, M, and Stage, respectively. Interestingly, mir-200 family (mir-200a, mir-200b, and mir-429 was shown to play a critical role in the progression of LUAD. In the multivariate Cox regression analysis, mir-1468 (P=0.009, mir-212 (P=0.026, mir-3653 (P=0.012, and mir-31 (P=0.002 were significantly correlated with recurrence-free survival. With regard to overall survival, mir-551b (P=0.011, mir-3653 (P=0.016, and mir-31 (P=0.001 were proven as independent prognostic markers. In summary, this study identified the cancer-specific miRNAs that may predict the progression and prognosis of LUAD. Keywords: microRNA, progression, prognosis, lung adenocarcinoma

  20. CIAPIN1 nuclear accumulation predicts poor clinical outcome in epithelial ovarian cancer

    Directory of Open Access Journals (Sweden)

    Cai Xiaolan

    2012-06-01

    Full Text Available Abstract Background Epithelial ovarian cancer (EOC is an aggressive disease with poor prognosis. The expression of cytokine-induced apoptosis inhibitor 1 (CIAPIN1 correlates with the malignant progression of several cancers. However, the relationship between the subcellular localization of CIAPIN1 and clinical characteristics in EOC remains unclear. Methods Immunohistochemistry was performed to detect CIAPIN1 expression in 108 EOC tissues. CIAPIN1 expressions in eight fresh EOC tissues were detected by Western blotting. The relationship between CIAPIN1 subcellular expression and patients’ clinicopathological features, including prognosis, was evaluated. Immunohistochemistry and immunofluorescence were employed to assess the CIAPIN1 subcellular localization in the EOC cell lines A2780 and HO8910. In addition, all patients were followed up to assess the prognostic value of CIAPIN1 in patients with EOC. Results CIAPIN1 is highly expressed in EOC, but is present at low levels in paired non-cancerous ovarian epithelial tissues. The results of Western blotting were in accordance with the immunohistochemical results. Poor differentiation of the tumors and EOC cell lines correlated with higher levels of CIAPIN1 nuclear expression. CIAPIN1 nuclear expression significantly correlated with the Federation International of Gynecology and Obstetrics (FIGO stage and histological differentiation (P = 0.034 and P P  Conclusions CIAPIN1 might play a crucial role in the differentiation of EOC cells. Elevated expression of nuclear CIAPIN1 negatively correlated with the survival of EOC patients, suggesting that nuclear CIAPIN1 might serve as a prognostic biomarker for EOC patients.

  1. Improving the Predictive Value of Preclinical Studies in Support of Radiotherapy Clinical Trials.

    Science.gov (United States)

    Coleman, C Norman; Higgins, Geoff S; Brown, J Martin; Baumann, Michael; Kirsch, David G; Willers, Henning; Prasanna, Pataje G S; Dewhirst, Mark W; Bernhard, Eric J; Ahmed, Mansoor M

    2016-07-01

    There is an urgent need to improve reproducibility and translatability of preclinical data to fully exploit opportunities for molecular therapeutics involving radiation and radiochemotherapy. For in vitro research, the clonogenic assay remains the current state-of-the-art of preclinical assays, whereas newer moderate and high-throughput assays offer the potential for rapid initial screening. Studies of radiation response modification by molecularly targeted agents can be improved using more physiologic 3D culture models. Elucidating effects on the cancer stem cells (CSC, and CSC-like) and developing biomarkers for defining targets and measuring responses are also important. In vivo studies are necessary to confirm in vitro findings, further define mechanism of action, and address immunomodulation and treatment-induced modification of the microenvironment. Newer in vivo models include genetically engineered and patient-derived xenograft mouse models and spontaneously occurring cancers in domesticated animals. Selection of appropriate endpoints is important for in vivo studies; for example, regrowth delay measures bulk tumor killing, whereas local tumor control assesses effects on CSCs. The reliability of individual assays requires standardization of procedures and cross-laboratory validation. Radiation modifiers must be tested as part of clinical standard of care, which includes radiochemotherapy for most tumors. Radiation models are compatible with but also differ from those used for drug screening. Furthermore, the mechanism of a drug as a chemotherapeutic agent may be different from its interaction with radiation and/or radiochemotherapy. This provides an opportunity to expand the use of molecular-targeted agents. Clin Cancer Res; 22(13); 3138-47. ©2016 AACR. PMID:27154913

  2. Ictal SPECT Using an Attachable Automated Injector: Clinical Usefulness in the Prediction of Ictal Onset Zone

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung-Ju (Dept. of Neurology, Eulji General Hospital, Eulji Univ. College of Medicine, Seoul (Korea)). e-mail. sangunlee@dreamwiz.com; Lee, Sang Kun (Dept. of Neurology, Seoul National Univ. College of Medicine, Seoul (Korea)); Choi, Jang Wuk (Dept. of Neurology, Seoul National Univ. Hospital, Seoul (Korea)) (and others)

    2009-12-15

    Background: Ictal single-photon emission computed tomography (SPECT) is a valuable method for localizing the ictal onset zone in the presurgical evaluation of patients with intractable epilepsy. Conventional methods used to localize the ictal onset zone have problems with time lag from seizure onset to injection. Purpose: To evaluate the clinical usefulness of a method that we developed, which involves an attachable automated injector (AAI), in reducing time lag and improving the ability to localize the zone of seizure onset. Material and Methods: Patients admitted to the epilepsy monitoring unit (EMU) between January 1, 2003, and June 30, 2008, were included. The definition of ictal onset zone was made by comprehensive review of medical records, magnetic resonance imaging (MRI), data from video electroencephalography (EEG) monitoring, and invasive EEG monitoring if available. We comprehensively evaluated the time lag to injection and the image patterns of ictal SPECT using traditional visual analysis, statistical parametric mapping-assisted, and subtraction ictal SPECT coregistered to an MRI-assisted means of analysis. Image patterns were classified as localizing, lateralizing, and nonlateralizing. The whole number of patients was 99: 48 in the conventional group and 51 in the AAI group. Results: The mean (SD) delay time to injection from seizure onset was 12.4+-12.0 s in the group injected by our AAI method and 40.4+-26.3 s in the group injected by the conventional method (P=0.000). The mean delay time to injection from seizure detection was 3.2+-2.5 s in the group injected by the AAI method and 21.4+-9.7 s in the group injected by the conventional method (P=0.000). The AAI method was superior to the conventional method in localizing the area of seizure onset (36 out of 51 with AAI method vs. 21 out of 48 with conventional method, P=0.009), especially in non-temporal lobe epilepsy (non-TLE) patients (17 out of 27 with AAI method vs. 3 out of 13 with conventional

  3. The predictability of renin-angiotensin-aldosterone system factors for clinical outcome in patients with acute decompensated heart failure.

    Science.gov (United States)

    Nakada, Yasuki; Takahama, Hiroyuki; Kanzaki, Hideaki; Sugano, Yasuo; Hasegawa, Takuya; Ohara, Takahiro; Amaki, Makoto; Funada, Akira; Yoshida, Akemi; Yasuda, Satoshi; Ogawa, Hisao; Anzai, Toshihisa

    2016-06-01

    Although counter-regulation between B-type natriuretic peptide (BNP) levels and renin-angiotensin-aldosterone system (RAAS) activation in heart failure (HF) has been suggested, whether the regulation is preserved in acute decompensated heart failure (ADHF) patients remains unclear. This study aimed to determine: (1) the relationship between RAAS activation and clinical outcomes in ADHF patients, and (2) the relationships between plasma BNP levels and degrees of activation in RAAS factors. This study included ADHF patients (n = 103, NYHA3-4, plasma BNP > 200 pg/ml). We studied the predictability of RAAS factors for cardiovascular events and the relationships between plasma BNP levels and the degrees of activation in RAAS factors, which were evaluated by plasma renin activity (PRA) and aldosterone concentration (PAC). PRA was a strong predictor of cardiovascular (CV) events over 1 year, even after accounting for plasma BNP levels (hazard ratio (HR): 1.04, CI [1.02-1.06], p analysis, p = 0.06). Cut-off value of PRA (5.3 ng/ml/h) was determined by AUC curve. Of the enrolled patients, higher PRA was found in 40 % of them. Although no correlation between the plasma BNP levels and PRA was found (p = 0.36), after adjusting for hemodynamic parameters, eGFR and medication, a correlation was found between them (p = 0.01). Elevated RAAS factors were found in a substantial number of ADHF patients with high plasma BNP levels in the association with hemodynamic state, which predicts poor clinical outcomes. The measurements of RAAS factors help to stratify ADHF patients at risk for further CV events. PMID:25964073

  4. Identification of clinical and simple laboratory variables predicting responsible gastrointestinal lesions in patients with iron deficiency anemia

    Directory of Open Access Journals (Sweden)

    Songul Serefhanoglu, Yahya Buyukasik, Hakan Emmungil, Nilgun Sayinalp, Ibrahim Celalettin Haznedaroglu, Hakan Goker, Salih Aksu, Osman Ilhami Ozcebe

    2011-01-01

    Full Text Available Iron deficiency anemia (IDA is a frequent disorder. Also, it may be a sign of underlying serious diseases. Iron deficiency points to an occult or frank bleeding lesion when occurred in men or postmenopausal women. In this study, we aimed to evaluate the diagnostic yield of endoscopy in patients with IDA and to define predictive factors of gastrointestinal (GI lesions causing IDA. Ninety-one patients (77 women, 14 men; mean age: 43 years who were decided to have esophago-duodenoscopy and/or colonoscopy for iron deficiency anemia were interviewed and responded to a questionnaire that included clinical and biochemical variables. The endoscopic findings were recorded as GI lesions causing IDA or not causing IDA. Endoscopy revealed a source of IDA in 18.6 % of cases. The risk factors for finding GI lesions causing IDA were as follows: male gender (p= 0.004, advanced age (> 50 years (p= 0.010, weight loss (over 20% of total body weight lost in last 6 month (p= 0.020, chronic diarrhea (p= 0.006, change of bowel habits (p= 0.043, epigastric tenderness (p= 0.037, raised carcinoembryonic antigen (CEA level (normal range: 0-7 ng/mL (p= 0.039, < 10 gr/dl hemoglobin (Hb level (p=0.054. None of these risk factors had been present in 21 (23% women younger than 51 years. In this group, no patient had any GI lesion likely to cause IDA (negative predictive value= 100%. In multivariate analysis, advanced age (p=0.017, male gender (p< 0.01 and weight lost (p=0.012 found that associated with GI lesions in all patients. It may be an appropriate clinical approach to consider these risk factors when deciding for gastrointestinal endoscopic evaluation in iron deficiency anemia.

  5. 黑河流域径流变化规律及趋势预测%Runoff Variation Rule and Trend Prediction in Heihe River Basin

    Institute of Scientific and Technical Information of China (English)

    凌文韬; 谢利云; 何玉琛; 张伟

    2014-01-01

    According to the runoff data of each hydrological station of Heihe River basin in 1956—2012,non-parametric Mann-Kendall method was applied to analyze the trends of runoff change,and the future runoff trend was predicted by using BP neural network. The results show that a) the proportion that water to flow of main stream and main tributaries in flood season accounted for the annual runoff is larger,which is 63. 18% ~94. 56%,and the runoff which is out of the mountains in Heihe River basin will increase;b)the test results of Mann-Kendall trend show that the forecasting future trends are coincident well with the measured results in the stations of Yingluoxia,Qilian,Xindi and Jiayuguan. However,the forecasting trends and the measured results are opposite in the stations of Zhamashike,and the absolute value becomes smaller and tends to 0,which can speculate the future runoff will increase in this station,and that is in line with the prediction of BP neural network.%根据黑河1956—2012年各水文站径流量数据,应用Mann-Kendall非参数检验法对黑河流域径流变化规律进行了分析,并利用BP神经网络对未来黑河径流演变趋势进行了预测。结果表明:①黑河干流及主要支流汛期来水量占年径流量的比例较大,为63.18%~94.56%,出山口径流量未来总的趋势为增加;②Mann-Kendall趋势检验结果表明莺落峡、祁连、新地及嘉峪关站未来径流预测趋势与实测序列趋势较为一致,而札马什克站未来径流预测趋势和实测序列趋势相反,但该站M-K值的绝对值逐渐变小并趋于0,可以推测未来该站径流量趋势将由减少转为增加,这与BP神经网络预测的结果一致。

  6. Functional Activities Questionnaire items that best discriminate and predict progression from clinically normal to mild cognitive impairment

    Science.gov (United States)

    Marshall, Gad A.; Zoller, Amy S.; Lorius, Natacha; Amariglio, Rebecca E.; Locascio, Joseph J.; Johnson, Keith A.; Sperling, Reisa A.; Rentz, Dorene M.

    2015-01-01

    Background Impairment in instrumental activities of daily living (IADL) emerges in the transition from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia. Some IADL scales are sensitive to early deficits in MCI, but none have been validated for detecting subtle functional changes in clinically normal (CN) elderly at risk for AD. Methods Data from 624 subjects participating in the Alzheimer’s Disease Neuroimaging Initiative and 524 subjects participating in the Massachusetts Alzheimer’s Disease Research Center, which are two large cohorts including CN elderly and MCI subjects, were used to determine which Functional Activities Questionnaire items best discriminate between and predict progression from CN to MCI. Results We found that “Remembering appointments” and “assembling tax records” best discriminated between CN and MCI subjects, while worse performance on “paying attention and understanding a TV program”, “paying bills/balancing checkbook”, and “heating water and turning off the stove” predicted greater hazard of progressing from a diagnosis of CN to MCI. Conclusions These results demonstrate that certain questions are especially sensitive in detecting the earliest functional changes in CN elderly at risk for AD. As the field moves toward earlier intervention in preclinical AD, it is important to determine which IADL changes can be detected at that stage and track decline over time. PMID:26017560

  7. An Intelligent Clinical Decision Support System for Patient-Specific Predictions to Improve Cervical Intraepithelial Neoplasia Detection

    Directory of Open Access Journals (Sweden)

    Panagiotis Bountris

    2014-01-01

    Full Text Available Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV, including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS, composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%, high specificity (97.1%, high positive predictive value (89.4%, and high negative predictive value (97.1%, for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+. In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

  8. A Case-Control Comparison of Retracted and Non-Retracted Clinical Trials: Can Retraction Be Predicted?

    Directory of Open Access Journals (Sweden)

    R. Grant Steen

    2014-01-01

    Full Text Available Does scientific misconduct severe enough to result in retraction disclose itself with warning signs? We test a hypothesis that variables in the results section of randomized clinical trials (RCTs are associated with retraction, even without access to raw data. We evaluated all English-language RCTs retracted from the PubMed database prior to 2011. Two controls were selected for each case, matching publication journal, volume, issue, and page as closely as possible. Number of authors, subjects enrolled, patients at risk, and patients treated were tallied in cases and controls. Among case RCTs, 17.5% had ≤2 authors, while 6.3% of control RCTs had ≤2 authors. Logistic regression shows that having few authors is associated with retraction (p < 0.03, although the number of subjects enrolled, patients at risk, or treated patients is not. However, none of the variables singly, nor all of the variables combined, can reliably predict retraction, perhaps because retraction is such a rare event. Exploratory analysis suggests that retraction rate varies by medical field (p < 0.001. Although retraction cannot be predicted on the basis of the variables evaluated, concern is warranted when there are few authors, enrolled subjects, patients at risk, or treated patients. Ironically, these features urge caution in evaluating any RCT, since they identify studies that are statistically weaker.

  9. The role of LDH serum levels in predicting global outcome in HCC patients undergoing TACE: implications for clinical management.

    Directory of Open Access Journals (Sweden)

    Mario Scartozzi

    Full Text Available In many tumor types serum lactate dehydrogenase (LDH levels is an indirect marker of tumor hypoxia, neo-angiogenesis and worse prognosis. However data about hepatocellular carcinoma (HCC are lacking in the clinical setting of patients undergoing transarterial-chemoembolization (TACE in whom hypoxia and neo-angiogenesis may represent a molecular key to treatment failure. Aim of our analysis was to evaluate the role of LDH pre-treatment levels in determining clinical outcome for patients with HCC receiving TACE. One hundred and fourteen patients were available for our analysis. For all patients LDH values were collected within one month before the procedure. We divided our patients into two groups, according to LDH serum concentration registered before TACE (first: LDH≤450 U/l 84 patients; second: LDH>450 U/l 30 patients. Patients were classified according to the variation in LDH serum levels pre- and post-treatment (increased: 62 patients vs. decreased 52 patients. No statistically significant differences were found between the groups for all clinical characteristics analyzed (gender, median age, performance status ECOG, staging systems. In patients with LDH values below 450 U/l median time to progression (TTP was 16.3 months, whereas it was of 10.1 months in patients above the cut-off (p = 0.0085. Accordingly median overall survival (OS was 22.4 months and 11.7 months (p = 0.0049. In patients with decreased LDH values after treatment median TTP was 12.4 months, and median OS was 22.1 months, whereas TTP was 9.1 months and OS was 9.5 in patients with increased LDH levels (TTP: p = 0.0087; OS: p<0.0001. In our experience, LDH seemed able to predict clinical outcome for HCC patients undergoing TACE. Given the correlation between LDH levels and tumor angiogenesis we can speculate that patients with high LDH pretreatment levels may be optimal candidates for clinical trial exploring a multimodality treatment approach with TACE and anti

  10. T Cell Receptor Excision Circle (TREC) Monitoring after Allogeneic Stem Cell Transplantation; a Predictive Marker for Complications and Clinical Outcome

    Science.gov (United States)

    Gaballa, Ahmed; Sundin, Mikael; Stikvoort, Arwen; Abumaree, Muhamed; Uzunel, Mehmet; Sairafi, Darius; Uhlin, Michael

    2016-01-01

    Allogeneic hematopoietic stem cell transplantation (HSCT) is a well-established treatment modality for a variety of malignant diseases as well as for inborn errors of the metabolism or immune system. Regardless of disease origin, good clinical effects are dependent on proper immune reconstitution. T cells are responsible for both the beneficial graft-versus-leukemia (GVL) effect against malignant cells and protection against infections. The immune recovery of T cells relies initially on peripheral expansion of mature cells from the graft and later on the differentiation and maturation from donor-derived hematopoietic stem cells. The formation of new T cells occurs in the thymus and as a byproduct, T cell receptor excision circles (TRECs) are released upon rearrangement of the T cell receptor. Detection of TRECs by PCR is a reliable method for estimating the amount of newly formed T cells in the circulation and, indirectly, for estimating thymic function. Here, we discuss the role of TREC analysis in the prediction of clinical outcome after allogeneic HSCT. Due to the pivotal role of T cell reconstitution we propose that TREC analysis should be included as a key indicator in the post-HSCT follow-up. PMID:27727179

  11. Prevalence of delirium among patients at a cancer ward: Clinical risk factors and prediction by bedside cognitive tests.

    Science.gov (United States)

    Grandahl, Mia Gall; Nielsen, Svend Erik; Koerner, Ejnar Alex; Schultz, Helga Holm; Arnfred, Sidse Marie

    2016-08-01

    Background Delirium is a frequent psychiatric complication to cancer, but rarely recognized by oncologists. Aims 1. To estimate the prevalence of delirium among inpatients admitted at an oncological cancer ward 2. To investigate whether simple clinical factors predict delirium 3. To examine the value of cognitive testing in the assessment of delirium. Methods On five different days, we interviewed and assessed patients admitted to a Danish cancer ward. The World Health Organization International Classification of Diseases Version 10, WHO ICD-10 Diagnostic System and the Confusion Assessment Method (CAM) were used for diagnostic categorization. Clinical information was gathered from medical records and all patients were tested with Mini Cognitive Test, The Clock Drawing Test, and the Digit Span Test. Results 81 cancer patients were assessed and 33% were diagnosed with delirium. All delirious participants were CAM positive. Poor performance on the cognitive tests was associated with delirium. Medical records describing CNS metastases, benzodiazepine or morphine treatment were associated with delirium. Conclusions Delirium is prevalent among cancer inpatients. The Mini Cognitive Test, The Clock Drawing Test, and the Digit Span Test can be used as screening tools for delirium among inpatients with cancer, but even in synergy, they lack specificity. Combining cognitive testing and attention to nurses' records might improve detection, yet further studies are needed to create a more detailed patient profile for the detection of delirium. PMID:26882016

  12. Everyday Cognition scale items that best discriminate between and predict progression from clinically normal to mild cognitive impairment

    Science.gov (United States)

    Marshall, Gad A.; Zoller, Amy S.; Kelly, Kathleen E.; Amariglio, Rebecca E.; Locascio, Joseph J.; Johnson, Keith A.; Sperling, Reisa A.; Rentz, Dorene M.

    2014-01-01

    Background Impairment in instrumental activities of daily living (IADL) starts as individuals with amnestic mild cognitive impairment (MCI) transition to Alzheimer’s disease (AD) dementia. However, most IADL scales have not shown IADL alterations in clinically normal (CN) elderly. The objective of this study was to determine which of the IADL-related Everyday Cognition (ECog) scale items are most sensitive for detection of early functional changes. Methods We assessed 290 CN and 495 MCI participants from the Alzheimer’s Disease Neuroimaging Initiative. We performed logistic regression analyses predicting the probability of CN vs. MCI diagnosis using only the 17 participant-based and 17 informant-based ECog items related to IADL. We then performed Cox regression analyses to predict progression from CN to MCI. All analyses were adjusted for demographic characteristics. Results We found that worse performance on “remembering a few shopping items” (participant and informant-based p<0.0001), “remembering appointments” (participant and informant-based p<0.0001), “developing a schedule in advance of anticipated events” (participant-based p=0.007), “balancing checkbook” (participant-based p=0.02), and “keeping mail and papers organized” (informant-based p=0.002) best discriminated MCI from CN. We found that worse performance on “keeping mail and papers organized” (participant-based Hazard Ratio (HR)=2.27, p=0.07) marginally predicted greater hazard of progressing from CN to MCI. Conclusions Our results indicate that a few simple questions targeting early functional changes, addressed either to the individual or informant, can effectively distinguish between CN elderly and individuals with MCI. Additionally, one of the above questions related to organization suggested which CN individuals are likely to progress to MCI. PMID:25274110

  13. How do Expenditure Rules affect Fiscal Behaviour?

    OpenAIRE

    Peter Wierts

    2008-01-01

    This paper investigates the role of self-enforced national expenditure rules in limiting the expenditure bias and procyclical expenditure increases/decreases due to revenue windfalls/shortfalls. A simple model predicts that expenditure rules can have the intended effects, but only if the political and institutional costs of non compliance are sufficiently large. Empirical estimations provide some support that expenditure rules affect expenditure outcomes in the hypothesised manner, especially...

  14. Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP): Derivation and Validation of a Tool to Improve the Accuracy of Blood Pressure Measurement in Clinical Practice.

    Science.gov (United States)

    Sheppard, James P; Stevens, Richard; Gill, Paramjit; Martin, Una; Godwin, Marshall; Hanley, Janet; Heneghan, Carl; Hobbs, F D Richard; Mant, Jonathan; McKinstry, Brian; Myers, Martin; Nunan, David; Ward, Alison; Williams, Bryan; McManus, Richard J

    2016-05-01

    Patients often have lower (white coat effect) or higher (masked effect) ambulatory/home blood pressure readings compared with clinic measurements, resulting in misdiagnosis of hypertension. The present study assessed whether blood pressure and patient characteristics from a single clinic visit can accurately predict the difference between ambulatory/home and clinic blood pressure readings (the home-clinic difference). A linear regression model predicting the home-clinic blood pressure difference was derived in 2 data sets measuring automated clinic and ambulatory/home blood pressure (n=991) using candidate predictors identified from a literature review. The model was validated in 4 further data sets (n=1172) using area under the receiver operator characteristic curve analysis. A masked effect was associated with male sex, a positive clinic blood pressure change (difference between consecutive measurements during a single visit), and a diagnosis of hypertension. Increasing age, clinic blood pressure level, and pulse pressure were associated with a white coat effect. The model showed good calibration across data sets (Pearson correlation, 0.48-0.80) and performed well-predicting ambulatory hypertension (area under the receiver operator characteristic curve, 0.75; 95% confidence interval, 0.72-0.79 [systolic]; 0.87; 0.85-0.89 [diastolic]). Used as a triaging tool for ambulatory monitoring, the model improved classification of a patient's blood pressure status compared with other guideline recommended approaches (93% [92% to 95%] classified correctly; United States, 73% [70% to 75%]; Canada, 74% [71% to 77%]; United Kingdom, 78% [76% to 81%]). This study demonstrates that patient characteristics from a single clinic visit can accurately predict a patient's ambulatory blood pressure. Usage of this prediction tool for triaging of ambulatory monitoring could result in more accurate diagnosis of hypertension and hence more appropriate treatment. PMID:27001299

  15. Finite element model predicts current density distribution for clinical applications of tDCS and tACS

    Directory of Open Access Journals (Sweden)

    Toralf eNeuling

    2012-09-01

    Full Text Available Transcranial direct current stimulation (tDCS has been applied in numerous scientific studies over the past decade. However, the possibility to apply tDCS in therapy of neuropsychiatric disorders is still debated. While transcranial magnetic stimulation (TMS has been approved for treatment of major depression in the United States by the Food and Drug Administration (FDA, tDCS is not as widely accepted. One of the criticisms against tDCS is the lack of spatial specificity. Focality is limited by the electrode size (35 cm2 are commonly used and the bipolar arrangement. However, a current flow through the head directly from anode to cathode is an outdated view. Finite element (FE models have recently been used to predict the exact current flow during tDCS. These simulations have demonstrated that the current flow depends on tissue shape and conductivity. Toface the challenge to predict the location, magnitude and direction of the current flow induced by tDCS and transcranial alternating current stimulation (tACS, we used a refined realistic FE modeling approach. With respect to the literature on clinical tDCS and tACS, we analyzed two common setups for the location of the stimulation electrodes which target the frontal lobe and the occipital lobe, respectively. We compared lateral and medial electrode configuration with regard to theirusability. We were able to demonstrate that the lateral configurations yielded more focused stimulation areas as well as higher current intensities in the target areas. The high resolution of our simulation allows one to combine the modeled current flow with the knowledge of neuronal orientation to predict the consequences of tDCS and tACS. Our results not only offer a basis for a deeper understanding of the stimulation sites currently in use for clinical applications but also offer a better interpretation of observed effects.

  16. Predicting persistence of asthma in preschool wheezers : crystal balls or muddy waters?

    NARCIS (Netherlands)

    Fouzas, Sotirios; Brand, Paul L. P.

    2013-01-01

    Since preschool wheezing is the common expression of several heterogeneous disorders, identification of children at risk for persistent asthma is particularly challenging. To date, efforts to predict the outcome of preschool wheeze have mainly relied on predictive rules consisting of simple clinical

  17. RGANN: An Efficient Algorithm to Extract Rules from ANNs

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    This paper describes an efficient rule generation algorithm, called rule generation from artificial neural networks (RGANN) to generate symbolic rules from ANNs. Classification rules are sought in many areas from automatic knowledge acquisition to data mining and ANN rule extraction. This is because classification rules possess some attractive features. They are explicit, understandable and verifiable by domain experts, and can be modified, extended and passed on as modular knowledge. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Comparing them to the symbolic rules generated by other methods supports explicitness of the generated rules. Generated rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, including breast cancer, wine, season, golf-playing, and ...

  18. Biological couplings:Classification and characteristic rules

    Institute of Scientific and Technical Information of China (English)

    REN LuQuan; LIANG YunHong

    2009-01-01

    introduced from the bionic viewpoint.Constitution,classification and characteristic rules of biological coupling are illuminated,the general modes of biological coupling studies are analyzed,and the prospects of multi-coupling bionics are predicted.

  19. The Cat nRules

    CERN Document Server

    Mould, R A

    2004-01-01

    The nRules that are developed in another paper are applied to two versions of the Schrodinger cat experiment. In version I the initially conscious cat is made unconscious by a mechanism that is initiated by a radioactive decay. In version II the initially unconscious cat is awakened by a mechanism that is initiated by a radioactive decay. In both cases an observer is permitted to check the statues of the cat at any time during the experiment. In all cases the nRules correctly and unambiguously predict the conscious experience of the cat and the observer. Keywords: brain states of observer, stochastic choice, state reduction, wave collapse.

  20. The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator.

    Science.gov (United States)

    Grant, Claire; Ewart, Lorna; Muthas, Daniel; Deavall, Damian; Smith, Simon A; Clack, Glen; Newham, Pete

    2016-04-01

    Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility of integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive "pica" behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting.

  1. Concept and rules of exploratory clinical trial%探索性临床试验相关概念及法规介绍

    Institute of Scientific and Technical Information of China (English)

    赵烨; 邵蓉

    2014-01-01

    探究性的临床试验为人们日益增多的药物研究活动提供了一种快捷的方法。此类临床研究通常是在早期临床发展的第一阶段进行,不以治疗为目的,也不侧重监测药物的临床耐受性,在研究过程中只涉及到少数人群并服用有限剂量。本文客观介绍了多种探究性临床试验方法及相关安全管理要求。在这基础之上,文章着重介绍并比较了探索性临床试验、微剂量试验及多剂量试验的概念。%Exploratory clinical trials provide a strategy for rapid human entry of investigational drugs. Such clinical studies are typically conducted during early clinical development in phase I as ifrst-in-human studies. They have no therapeutic intent and are not intended to examine clinical tolerability, which involve a small number of human subjects at limited dose. This review critically discusses the various exploratory clinical trial strategies, their advantages and disadvantages as well as the regulatory safety requirements. In this respect, strategies for exploratory investigational new drugs (eIND), micro dose and multiple dose examination are highlighted and compared.

  2. Neutrophil gelatinase-associated lipocalin (NGAL predicts response to neoadjuvant chemotherapy and clinical outcome in primary human breast cancer.

    Directory of Open Access Journals (Sweden)

    Antonia Sophie Wenners

    Full Text Available In our previous work we showed that NGAL, a protein involved in the regulation of proliferation and differentiation, is overexpressed in human breast cancer (BC and predicts poor prognosis. In neoadjuvant chemotherapy (NACT pathological complete response (pCR is a predictor for outcome. The aim of this study was to evaluate NGAL as a predictor of response to NACT and to validate NGAL as a prognostic factor for clinical outcome in patients with primary BC. Immunohistochemistry was performed on tissue microarrays from 652 core biopsies from BC patients, who underwent NACT in the GeparTrio trial. NGAL expression and intensity was evaluated separately. NGAL was detected in 42.2% of the breast carcinomas in the cytoplasm. NGAL expression correlated with negative hormone receptor (HR status, but not with other baseline parameters. NGAL expression did not correlate with pCR in the full population, however, NGAL expression and staining intensity were significantly associated with higher pCR rates in patients with positive HR status. In addition, strong NGAL expression correlated with higher pCR rates in node negative patients, patients with histological grade 1 or 2 tumors and a tumor size <40 mm. In univariate survival analysis, positive NGAL expression and strong staining intensity correlated with decreased disease-free survival (DFS in the entire cohort and different subgroups, including HR positive patients. Similar correlations were found for intense staining and decreased overall survival (OS. In multivariate analysis, NGAL expression remained an independent prognostic factor for DFS. The results show that in low-risk subgroups, NGAL was found to be a predictive marker for pCR after NACT. Furthermore, NGAL could be validated as an independent prognostic factor for decreased DFS in primary human BC.

  3. Country, sex, EDSS change and therapy choice independently predict treatment discontinuation in multiple sclerosis and clinically isolated syndrome.

    Directory of Open Access Journals (Sweden)

    Claire Meyniel

    Full Text Available OBJECTIVES: We conducted a prospective study, MSBASIS, to assess factors leading to first treatment discontinuation in patients with a clinically isolated syndrome (CIS and early relapsing-remitting multiple sclerosis (RRMS. METHODS: The MSBASIS Study, conducted by MSBase Study Group members, enrols patients seen from CIS onset, reporting baseline demographics, cerebral magnetic resonance imaging (MRI features and Expanded Disability Status Scale (EDSS scores. Follow-up visits report relapses, EDSS scores, and the start and end dates of MS-specific therapies. We performed a multivariable survival analysis to determine factors within this dataset that predict first treatment discontinuation. RESULTS: A total of 2314 CIS patients from 44 centres were followed for a median of 2.7 years, during which time 1247 commenced immunomodulatory drug (IMD treatment. Ninety percent initiated IMD after a diagnosis of MS was confirmed, and 10% while still in CIS status. Over 40% of these patients stopped their first IMD during the observation period. Females were more likely to cease medication than males (HR 1.36, p = 0.003. Patients treated in Australia were twice as likely to cease their first IMD than patients treated in Spain (HR 1.98, p = 0.001. Increasing EDSS was associated with higher rate of IMD cessation (HR 1.21 per EDSS unit, p<0.001, and intramuscular interferon-β-1a (HR 1.38, p = 0.028 and subcutaneous interferon-β-1a (HR 1.45, p = 0.012 had higher rates of discontinuation than glatiramer acetate, although this varied widely in different countries. Onset cerebral MRI features, age, time to treatment initiation or relapse on treatment were not associated with IMD cessation. CONCLUSION: In this multivariable survival analysis, female sex, country of residence, EDSS change and IMD choice independently predicted time to first IMD cessation.

  4. Current methods of assessing the accuracy of three-dimensional soft tissue facial predictions: technical and clinical considerations.

    Science.gov (United States)

    Khambay, B; Ullah, R

    2015-01-01

    Since the introduction of three-dimensional (3D) orthognathic planning software, studies have reported on their predictive ability. The aim of this study was to highlight the limitations of the current methods of analysis. The predicted 3D soft tissue image was compared to the postoperative soft tissue. For the full face, the maximum and 95th and 90th percentiles, the percentage of 3D mesh points ≤ 2 mm, and the root mean square (RMS) error, were calculated. For specific anatomical regions, the percentage of 3D mesh points ≤ 2 mm and the distance between the two meshes at 10 landmarks were determined. For the 95th and 90th percentiles, the maximum difference ranged from 7.7 mm to 2.2 mm and from 3.7 mm to 1.5 mm, respectively. The absolute mean distance ranged from 0.98 mm to 0.56 mm and from 0.91 mm to 0.50 mm, respectively. The percentage of mesh with ≤ 2 mm for the full face was 94.4-85.2% and 100-31.3% for anatomical regions. The RMS error ranged from 2.49 mm to 0.94 mm. The majority of mean linear distances between the surfaces were ≤ 0.8 mm, but increased for the mean absolute distance. At present the use of specific anatomical regions is more clinically meaningful than the full face. It is crucial to understand these and adopt a protocol for conducting such studies.

  5. Can carbapenem-resistant enterobacteriaceae susceptibility results obtained from surveillance cultures predict the susceptibility of a clinical carbapenem-resistant enterobacteriaceae?

    Science.gov (United States)

    Perez, Leandro Reus Rodrigues; Rodrigues, Diógenes; Dias, Cícero

    2016-08-01

    We evaluated the susceptibility profile of a colonizing carbapenem-resistant enterobacteriaceae to predict its susceptibility when recovered from a clinical specimen. An overall agreement of 88.7% (517 out of 583; 95% confidence interval, 85.8%-91.0%) was observed for the combinations of 11 antibiotics with 53 pairs of Klebsiella pneumoniae carbapenemase-producing K pneumoniae (the only carbapenem-resistant enterobacteriaceae detected). Very major errors were observed mainly for aminoglycoside agents and colistin, limiting the predictability of the susceptibility profile for these clinical isolates. PMID:27021509

  6. Predicting the severity of acute bronchiolitis in infants: should we use a clinical score or a biomarker?

    Science.gov (United States)

    Amat, Flore; Henquell, Cécile; Verdan, Matthieu; Roszyk, Laurence; Mulliez, Aurélien; Labbé, André

    2014-11-01

    Krebs von den Lungen 6 antigen (KL-6) has been shown to be a useful biomarker of the severity of Respiratory syncytial virus bronchiolitis. To assess the correlation between the clinical severity of acute bronchiolitis, serum KL-6, and the causative viruses, 222 infants with acute bronchiolitis presenting at the Pediatric Emergency Department of Estaing University Hospital, Clermont-Ferrand, France, were prospectively enrolled from October 2011 to May 2012. Disease severity was assessed with a score calculated from oxygen saturation, respiratory rate, and respiratory effort. A nasopharyngeal aspirate was collected to screen for a panel of 20 respiratory viruses. Serum was assessed and compared with a control group of 38 bronchiolitis-free infants. No significant difference in KL-6 levels was found between the children with bronchiolitis (mean 231 IU/mL ± 106) and those without (230 IU/mL ± 102), or between children who were hospitalized or not, or between the types of virus. No correlation was found between serum KL-6 levels and the disease severity score. The absence of Human Rhinovirus was a predictive factor for hospitalization (OR 3.4 [1.4-7.9]; P = 0.006). Older age and a higher oxygen saturation were protective factors (OR 0.65[0.55-0.77]; P < 0.0001 and OR 0.67 [0.54-0.85] P < 0.001, respectively). These results suggest that in infants presenting with bronchiolitis for the first time, clinical outcome depends more on the adaptive capacities of the host than on epithelial dysfunction intensity. Many of the features of bronchiolitis are affected by underlying disease and by treatment. PMID:24374757

  7. Predicting the severity of acute bronchiolitis in infants: should we use a clinical score or a biomarker?

    Science.gov (United States)

    Amat, Flore; Henquell, Cécile; Verdan, Matthieu; Roszyk, Laurence; Mulliez, Aurélien; Labbé, André

    2014-11-01

    Krebs von den Lungen 6 antigen (KL-6) has been shown to be a useful biomarker of the severity of Respiratory syncytial virus bronchiolitis. To assess the correlation between the clinical severity of acute bronchiolitis, serum KL-6, and the causative viruses, 222 infants with acute bronchiolitis presenting at the Pediatric Emergency Department of Estaing University Hospital, Clermont-Ferrand, France, were prospectively enrolled from October 2011 to May 2012. Disease severity was assessed with a score calculated from oxygen saturation, respiratory rate, and respiratory effort. A nasopharyngeal aspirate was collected to screen for a panel of 20 respiratory viruses. Serum was assessed and compared with a control group of 38 bronchiolitis-free infants. No significant difference in KL-6 levels was found between the children with bronchiolitis (mean 231 IU/mL ± 106) and those without (230 IU/mL ± 102), or between children who were hospitalized or not, or between the types of virus. No correlation was found between serum KL-6 levels and the disease severity score. The absence of Human Rhinovirus was a predictive factor for hospitalization (OR 3.4 [1.4-7.9]; P = 0.006). Older age and a higher oxygen saturation were protective factors (OR 0.65[0.55-0.77]; P bronchiolitis for the first time, clinical outcome depends more on the adaptive capacities of the host than on epithelial dysfunction intensity. Many of the features of bronchiolitis are affected by underlying disease and by treatment.

  8. Metabolic rates of ATP transfer through creatine kinase (CK Flux) predict clinical heart failure events and death.

    Science.gov (United States)

    Bottomley, Paul A; Panjrath, Gurusher S; Lai, Shenghan; Hirsch, Glenn A; Wu, Katherine; Najjar, Samer S; Steinberg, Angela; Gerstenblith, Gary; Weiss, Robert G

    2013-12-11

    Morbidity and mortality from heart failure (HF) are high, and current risk stratification approaches for predicting HF progression are imperfect. Adenosine triphosphate (ATP) is required for normal cardiac contraction, and abnormalities in creatine kinase (CK) energy metabolism, the primary myocardial energy reserve reaction, have been observed in experimental and clinical HF. However, the prognostic value of abnormalities in ATP production rates through CK in human HF has not been investigated. Fifty-eight HF patients with nonischemic cardiomyopathy underwent ³¹P magnetic resonance spectroscopy (MRS) to quantify cardiac high-energy phosphates and the rate of ATP synthesis through CK (CK flux) and were prospectively followed for a median of 4.7 years. Multiple-event analysis (MEA) was performed for HF-related events including all-cause and cardiac death, HF hospitalization, cardiac transplantation, and ventricular-assist device placement. Among baseline demographic, clinical, and metabolic parameters, MEA identified four independent predictors of HF events: New York Heart Association (NYHA) class, left ventricular ejection fraction (LVEF), African-American race, and CK flux. Reduced myocardial CK flux was a significant predictor of HF outcomes, even after correction for NYHA class, LVEF, and race. For each increase in CK flux of 1 μmol g⁻¹ s⁻¹, risk of HF-related composite outcomes decreased by 32 to 39%. These findings suggest that reduced CK flux may be a potential HF treatment target. Newer imaging strategies, including noninvasive ³¹P MRS that detect altered ATP kinetics, could thus complement risk stratification in HF and add value in conditions involving other tissues with high energy demands, including skeletal muscle and brain.

  9. Return to work after percutaneous coronary intervention: the predictive value of self-reported health compared to clinical measures.

    Directory of Open Access Journals (Sweden)

    Karin Biering

    Full Text Available AIMS: Coronary heart disease is prevalent in the working-age population. Traditional outcome measures like mortality and readmission are of importance to evaluate the prognosis but are hardly sufficient. Ability to work is an additional outcome of clinical and societal significance. We describe trends and predictors of Return To Work (RTW after PCI and describe a possible benefit using patient-reported measures in risk stratification of RTW. METHODS: A total of 1585 patients aged less than 67 years treated with PCI in 2006-2008 at the Aarhus University Hospital were enrolled. Clinical information was provided through the West Denmark Heart Registry, and 4 weeks after PCI we mailed a questionnaire regarding self-rated health (response rate 83.5%. RTW was defined at weekly basis using extensive register data on transfer payments. Predictors of RTW were analysed as time to event. ROC curves constructed by logistic regression of predicting variables were evaluated by the c-statistic. RESULTS: Four weeks before PCI 50% of the patients were working; the corresponding figures were 25% after 4 weeks, 36% after 12 weeks, and 43% after one year. The patients' self-rated health one month after the procedure was a significant better predictor of RTW compared to other variables including LVEF, both at short (12 weeks and long (one year term. CONCLUSIONS: The patient's self-rated health four weeks after the procedure was a stronger predictor than left ventricular ejection fraction (LVEF, and consequently useful when patients seek medical advice with respect to RWT.

  10. Development of a Clinical Forecasting Model to Predict Comorbid Depression Among Diabetes Patients and an Application in Depression Screening Policy Making

    OpenAIRE

    Jin, Haomiao; Wu, Shinyi; Di Capua, Paul

    2015-01-01

    Introduction Depression is a common but often undiagnosed comorbid condition of people with diabetes. Mass screening can detect undiagnosed depression but may require significant resources and time. The objectives of this study were 1) to develop a clinical forecasting model that predicts comorbid depression among patients with diabetes and 2) to evaluate a model-based screening policy that saves resources and time by screening only patients considered as depressed by the clinical forecasting...

  11. The Explanatory Power of Monetary Policy Rules

    OpenAIRE

    John B. Taylor

    2007-01-01

    Over the past 20 years, the use of monetary policy rules has become pervasive in analyzing and prescribing monetary policy. This paper traces the development of such rules and their use in the analysis, prediction, and stabilization of national economies. In particular, rules provide insight into eras in which monetary policy was not effective as well as when it was, such as the persistence of the ongoing “Great Moderation.” The paper stresses the “scientific” contributions of rules, includin...

  12. Extraction of Symbolic Rules from Artificial Neural Networks

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification ...

  13. Quantum nRules

    OpenAIRE

    Mould, Richard A

    2004-01-01

    Quantum mechanics traditionally places the observer outside of the system being studied and employs the Born interpretation. In this and related papers the observer is placed inside the system. To accomplish this, special rules are required to engage and interpret the Schrodinger solutions in individual measurements. The rules in this paper (called the nRules) do not include the Born rule that connects probability with square modulus. It is required that the rules allow all conscious observer...

  14. Does GEM-Encoding Clinical Practice Guidelines Improve the Quality of Knowledge Bases? A Study with the Rule-Based Formalism

    OpenAIRE

    Georg, Gersende; Séroussi, Brigitte; Bouaud, Jacques

    2003-01-01

    The aim of this work was to determine whether the GEM-encoding step could improve the representation of clinical practice guidelines as formalized knowledge bases. We used the 1999 Canadian recommendations for the management of hypertension, chosen as the knowledge source in the ASTI project. We first clarified semantic ambiguities of therapeutic sequences recommended in the guideline by proposing an interpretative framework of therapeutic strategies. Then, after a formalization step to stand...

  15. Maximising the efficiency of clinical screening programmes: balancing predictive genetic testing with a right not to know.

    Science.gov (United States)

    Schuurman, Agnes G; van der Kolk, Dorina M; Verkerk, Marian A; Birnie, Erwin; Ranchor, Adelita V; Plantinga, Mirjam; van Langen, Irene M

    2015-09-01

    We explored the dilemma between patients' right not to know their genetic status and the efficient use of health-care resources in the form of clinical cancer screening programmes. Currently, in the Netherlands, 50% risk carriers of heritable cancer syndromes who choose not to know their genetic status have access to the same screening programmes as proven mutation carriers. This implies an inefficient use of health-care resources, because half of this group will not carry the familial mutation. At the moment, only a small number of patients are involved; however, the expanding possibilities for genetic risk profiling means this issue must be addressed because of potentially adverse societal and financial impact. The trade-off between patients' right not to know their genetic status and efficient use of health-care resources was discussed in six focus groups with health-care professionals and patients from three Dutch university hospitals. Professionals prefer patients to undergo a predictive DNA test as a prerequisite for entering cancer screening programmes. Professionals prioritise treating sick patients or proven mutation carriers over screening untested individuals. Participation in cancer screening programmes without prior DNA testing is, however, supported by most professionals, as testing is usually delayed and relatively few patients are involved at present. Reducing the number of 50% risk carriers undergoing screening is expected to be achieved by: offering more psychosocial support, explaining the iatrogenic risks of cancer screening, increasing out-of-pocket costs, and offering a less stringent screening programme for 50% risk carriers. PMID:25564039

  16. Maximising the efficiency of clinical screening programmes: balancing predictive genetic testing with a right not to know

    Science.gov (United States)

    Schuurman, Agnes G; van der Kolk, Dorina M; Verkerk, Marian A; Birnie, Erwin; Ranchor, Adelita V; Plantinga, Mirjam; van Langen, Irene M

    2015-01-01

    We explored the dilemma between patients' right not to know their genetic status and the efficient use of health-care resources in the form of clinical cancer screening programmes. Currently, in the Netherlands, 50% risk carriers of heritable cancer syndromes who choose not to know their genetic status have access to the same screening programmes as proven mutation carriers. This implies an inefficient use of health-care resources, because half of this group will not carry the familial mutation. At the moment, only a small number of patients are involved; however, the expanding possibilities for genetic risk profiling means this issue must be addressed because of potentially adverse societal and financial impact. The trade-off between patients' right not to know their genetic status and efficient use of health-care resources was discussed in six focus groups with health-care professionals and patients from three Dutch university hospitals. Professionals prefer patients to undergo a predictive DNA test as a prerequisite for entering cancer screening programmes. Professionals prioritise treating sick patients or proven mutation carriers over screening untested individuals. Participation in cancer screening programmes without prior DNA testing is, however, supported by most professionals, as testing is usually delayed and relatively few patients are involved at present. Reducing the number of 50% risk carriers undergoing screening is expected to be achieved by: offering more psychosocial support, explaining the iatrogenic risks of cancer screening, increasing out-of-pocket costs, and offering a less stringent screening programme for 50% risk carriers. PMID:25564039

  17. Is myocardial stress perfusion MR-imaging suitable to predict the long term clinical outcome after revascularization?

    International Nuclear Information System (INIS)

    Introduction: Aim of our study was to evaluate, whether myocardial ischemia or myocardial infarction (MI) depicted by myocardial stress perfusion MR imaging (SP CMR) can predict the clinical outcome in patients with coronary artery disease (CAD). Materials and method: 220 patients were included. Myocardial perfusion was assessed at stress and at rest, using a 2D saturation recovery gradient echo sequence (SR GRE) and myocardial viability by late gadolinium enhancement magnetic resonance images (LGE CMR). MR-images were assessed in regard of presence and extent of MI and ischemia. Patients were monitored for major adverse cardiac events (MACE) (monitoring period: 5–7 years). MACE were correlated with the initial results of SP CMR. Results: Ischemia was found in 143 patients, MI in 107 patients. Number of MACE was in patients with normal SP CMR 0 (51 patients), with ischemia 21 (62 patients), with MI 14 (26 patients), with ischemia and MI 52 (81 patients). In all patients with severe MACE (MI, death) and in 63 of those with recurring symptoms LGE CMR revealed MI at baseline. Conclusion: Negative SP CMR indicates low risk for MACE. In patients with stress induced ischemia, MACE might occur even after myocardial revascularization. The presence of MI proved by LGE CMR is associated with a significantly increased risk for MACE

  18. To what extent do single symptoms from a depression rating scale predict risk of long-term sickness absence among employees who are free of clinical depression?

    DEFF Research Database (Denmark)

    Rugulies, R; Hjarsbech, PU; Aust, B;

    2013-01-01

    PURPOSE: Depression rating scales have predicted long-term sickness absence (LTSA) in previous studies. With this study, we investigated to what extent single symptoms from a depression rating scale predicted LTSA among employees who were free of clinical depression. METHODS: We studied 6...... on LTSA (≥3 weeks). We calculated hazard ratios (HR) from Cox's proportional hazard models to analyze whether a symptom predicted time to onset of LTSA during a 1-year follow-up. Analyses were adjusted for age, family status, health behaviors, occupational group, and previous LTSA. RESULTS: Of the 12...

  19. 基于Lorenz映射的混沌系统分支变换预报规律研究*%Rules for predicting regime change in the Lorenz chaotic system based on the Lorenz map∗

    Institute of Scientific and Technical Information of China (English)

    黎爱兵; 张立凤

    2013-01-01

      Corresponding to two strange Lorenz attractors, in the Lorenz model there exist two opposite regimes which can be called as positive and negative regimes. Despite the trajectory of the Lorenz system changing between the two regimes back and forth with an unfixed period, the regime change is predictable. In this paper, with the help of the Lorenz map, three rules for predicting regime change are obtained. In particular, besides two generic predictable rules for the condition of regime transition and duration in new regime, a new rule about length for reaching transition condition, which has not been reported in previous work, is also very important. It provides another approach to forecasting the evolution of the nonlinear dynamical system. The results show that the position for highest point in cusps is the critical value for regime change. When the value of variable z is greater than the corresponding critical value, the current regime is about to end, and the Lorenz model will move to other regime in the next cycle. The length for reaching transition condition in the current regime decreases monotonically with local maximum value zmax, and the smaller zmax in current status implies the bigger length for reaching transition condition. The duration in new regime increases monotonically with the maximum value zM in the previous regime, and the bigger the value of zM, the larger the range for the duration increase is. In addition, the forcing is also associated with the prediction rules for regime change. It not only makes transition conditions for positive and negative regimes different, but also determines the speed of decrease in length for reaching transition condition and the range of increase for duration in new regime.%  尽管Lorenz系统具有混沌和非周期性质,但其分支变换是可预报的。本文以强迫Lorenz系统为数学模型,基于Lorenz映射,研究了混沌系统分支变换的预报规律,将原有

  20. Mining association rule efficiently based on data warehouse

    Institute of Scientific and Technical Information of China (English)

    陈晓红; 赖邦传; 罗铤

    2003-01-01

    The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed.By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.

  1. HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors

    NARCIS (Netherlands)

    M.C. de Jong; J. Pramana; J.L. Knegjens; A.J.M. Balm; M.W.M. van den Brekel; M. Hauptmann; A.C. Begg; C.R.N. Rasch

    2010-01-01

    Purpose: The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. Material and methods: Gene expression data were available for a series of 92 advanced stage

  2. HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors.

    NARCIS (Netherlands)

    Jong, M.C.J. de; Pramana, J.; Knegjens, J.L.; Balm, A.J.; Brekel, M.W. van den; Hauptmann, M.; Begg, A.C.; Rasch, C.R.

    2010-01-01

    PURPOSE: The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. MATERIAL AND METHODS: Gene expression data were available for a series of 92 advanced stage

  3. Prediction of the need for an MRI after surgical treatment of symptomatic lumbar herniated disc at discharge: evaluation of the necessity for regular visits at the outpatient clinic.

    NARCIS (Netherlands)

    Bartels, R.H.M.A.; Beems, T.; Verbeek, A.L.M.

    2010-01-01

    BACKGROUND: Surgical treatment of symptomatic lumbar disc herniations has been well established. The need for regular postoperative visits at the outpatient clinic has never been evaluated. In this study, factors predicting the need for magnetic resonance imaging, denoting an unfavorable outcome nee

  4. Extracting Symbolic Rules for Medical Diagnosis Problem

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Neural networks (NNs) have been successfully applied to solve a variety of application problems involving classification and function approximation. Although backpropagation NNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained NNs for the users to gain a better understanding of how the networks solve the problems. An algorithm is proposed and implemented to extract symbolic rules for medical diagnosis problem. Empirical study on three benchmarks classification problems, such as breast cancer, diabetes, and lenses demonstrates that the proposed algorithm generates high quality rules from NNs comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy.

  5. Comparing of Light Transmittance Aggregometry and Modified Thrombelastograph in Predicting Clinical Outcomes in Chinese Patients Undergoing Coronary Stenting with Clopidogrel

    Directory of Open Access Journals (Sweden)

    Xiao-Fang Tang

    2015-01-01

    Full Text Available Background: Several platelet function tests are currently used to measure responsiveness to antiplatelet therapy. This study was to compare two tests, light transmittance aggregometry (LTA and modified thrombelastography (mTEG, for predicting clinical outcomes in Chinese patients after percutaneous coronary intervention (PCI. Methods: Prospective, observational, single-center study of 789 Chinese patients undergoing PCI was enrolled. This study was investigated the correlations between the two tests and performed receiver operating characteristic curve (ROC analysis for major adverse cardiovascular events (MACEs at 1-year follow-up. Results: MACEs occurred in 32 patients (4.1%. Correlations were well between the two tests in the adenosine diphosphate induced platelet reactivity (Spearman r = 0.733, P < 0.001. ROC-curve analysis demonstrated that LTA (area under the curve [AUC]: 0.677; 95% confidence interval [CI]: 0.643-0.710; P = 0.0009, and mTEG (AUC: 0.684; 95% CI: 0.650-0.716; P = 0.0001 had moderate ability to discriminate between patients with and without MACE. MACE occurred more frequently in patients with high on-treatment platelet reactivity (HPR when assessed by LTA (7.4% vs. 2.7%; P < 0.001, and by TEG (6.7% vs. 2.6%; P < 0.001. Kaplan-Meier analysis demonstrated that HPR based on the LTA and mTEG was associated with almost 3-fold increased risk of MACE at 1-year follow-up. Conclusions: The correlation between LTA and mTEG is relatively high in Chinese patients. HPR measured by LTA and mTEG were significantly associated with MACE in Chinese patients undergoing PCI.

  6. Comparing of Light Transmittance Aggregometry and Modified Thrombelastograph in Predicting Clinical Outcomes in Chinese Patients Undergoing Coronary Stenting with Clopidogrel

    Institute of Scientific and Technical Information of China (English)

    Xiao-Fang Tang; Ya-Ling Han; Jia-Hui Zhang; Jing Wang; Yin Zhang; Bo Xu; Zhan Gao

    2015-01-01

    Background:Several platelet function tests are currently used to measure responsiveness to antiplatelet therapy.This study was to compare two tests,light transmittance aggregometry (LTA) and modified thrombelastography (mTEG),for predicting clinical outcomes in Chinese patients after percutaneous coronary intervention (PCI).Methods:Prospective,observational,single-center study of 789 Chinese patients undergoing PCI was enrolled.This study was investigated the correlations between the two tests and performed receiver operating characteristic curve (ROC) analysis for major adverse cardiovascular events (MACEs) at 1-year follow-up.Results:MACEs occurred in 32 patients (4.1%).Correlations were well between the two tests in the adenosine diphosphate induced platelet reactivity (Spearman r =0.733,P < 0.001).ROC-curve analysis demonstrated that LTA (area under the curve [AUC]:0.677; 95% confidence interval [CI]:0.643-0.710; P =0.0009),and mTEG (AUC:0.684; 95% CI:0.650-0.716; P =0.0001) had moderate ability to discriminate between patients with and without MACE.MACE occurred more frequently in patients with high on-treatment platelet reactivity (HPR) when assessed by LTA (7.4% vs.2.7%; P < 0.001),and by TEG (6.7% vs.2.6%; P < 0.001).Kaplan-Meier analysis demonstrated that HPR based on the LTA and mTEG was associated with almost 3-fold increased risk of MACE at 1-year follow-up.Conclusions:The correlation between LTA and mTEG is relatively high in Chinese patients.HPR measured by LTA and mTEG were significantly associated with MACE in Chinese patients undergoing PCI.

  7. Early Prediction of Acute Kidney Injury by Clinical Features of Snakebite Patients at the Time of Hospital Admission

    Directory of Open Access Journals (Sweden)

    Jayanta Paul

    2012-01-01

    Full Text Available Background: Snakebite is a major health problem in India. Venomous snakebite, which is an important medical hazard in several tropical countries including India, affects thousands of people per year and some of them develop acute kidney injury (AKI. Aims: This study was performed to find out 1 early clinical predictors for acute kidney injury in snakebite patients at the time of hospital admission and 2 incidence of acute kidney injury in snakebite patients. Materials and Methods: 171 consecutively admitted non-diabetic, non-hypertensive snakebite patients were examined. Multivariate linear regression analysis with 95 percent confidence interval (CI was done for statistical analysis. Analyses were performed by software Statistical Package for the Social Sciences (SPSS (17 th version for Windows. Results: Incidence of acute kidney injury was 43.27%. Development of acute kidney injury was independently associated with 20 min whole blood clotting test (20 min WBCT (P value = 0.029; CI 95%, dark or brown color urine (P value = 0.000; CI 95%, and time interval between snakebite and anti-snake venom administration (P value = 0.000; CI 95%. Age (P value = 0.011; CI 95% and presence of neurological signs (P value = 0.000; CI 95% were negatively correlated with development of acute kidney injury. Conclusion: Incidence of acute kidney injury is slightly higher in our study than previous studies. Early prediction of acute kidney injury development in snakebite patients can be done by presence of black or brown urine, 20 min WBCT > 20 min, and increased time interval between snakebite and administration of anti-snake venom at the time of hospital admission. Young age group of snakebite patients develops acute kidney injury more commonly.

  8. Clinical applications of gene-based risk prediction for Lung Cancer and the central role of Chronic Obstructive Pulmonary Disease.

    Directory of Open Access Journals (Sweden)

    Robert P Young

    2012-10-01

    Full Text Available Lung cancer is the leading cause of cancer death worldwide and nearly 90% of cases are attributable to smoking. Quitting smoking and early diagnosis of lung cancer, through computed tomographic screening, are the only ways to reduce mortality from lung cancer. Recent epidemiological studies show that risk prediction for lung cancer is optimized by using multivariate risk models that include age, smoking exposure, history of chronic obstructive pulmonary disease (COPD, family history of lung cancer and body mass index. Several recent epidemiological studies have shown that COPD predates lung cancer in 65-70% of cases and confers a 4-6 fold greater risk of lung cancer compared to smokers with normal lung function. In separate studies, genome-wide association studies have identified a number of genetic variants associated with COPD or lung cancer, several of which overlap. In a case control study, where smokers with normal lungs were compared to those who had spirometry-defined COPD and histology confirmed lung cancer, several of these overlapping variants were shown to confer the same susceptibility or protective effects on both COPD and lung cancer (independent of COPD status. In this perspective article, we demonstrate how combining clinical data with genetic variants can help identify heavy smokers at the greatest risk of lung cancer. Using this approach, we found that gene-based risk testing helped engage smokers in risk mitigating activities like quitting smoking and undertaking lung cancer screening. We suggest that such an approach could facilitate the targeted selection of smokers for cost-effective, life-saving interventions.

  9. Elevation in liver enzymes is associated with increased IL-2 and predicts severe outcomes in clinically apparent dengue virus infection.

    Science.gov (United States)

    Senaratne, Thamarasi; Carr, Jillian; Noordeen, Faseeha

    2016-07-01

    The objective of the present study was to assess the circulating TNF-α and IL-2 levels in dengue virus (DENV) infected patients and to correlate these with clinical severity of DENV infections. A single analyte quantitative immunoassay was used to detect TNF-α and IL-2 in 24 dengue fever (DF) and 43 dengue haemorrhagic fever (DHF) patients, 15 healthy adults and 6 typhoid patients. The mean TNF-α and IL-2 levels of DENV- infected patients were higher than that of healthy adults and typhoid patients. No significant difference in TNF-α levels was noted between DF and DHF patients (p=0.5) but a significant increase in IL-2 levels was observed in DHF compared with DF patients (mean of DF=59.7pg/mL, mean of DHF=166.9pg/mL; p=0.02). No significant association of TNF-α or IL-2 levels was noted with packed cell volume (>45), thrombocytopenia, leucopenia or the presence of viraemia. The liver function tests measuring AST (aspartate aminotransferase) (p=0.01) and ALT (alanine aminotransferase) (p=0.02) levels were significantly elevated in DENV-infected patients. AST:ALT was significantly elevated in DHF/DSS (dengue shock syndrome) compared with DF patients. A significant positive linear correlation was noted between AST and IL-2 (r=0.31; p=0.01) and ALT and IL-2 elevations (r=0.2; p=0.02). Thus, AST and ALT levels correlate with both disease severity and circulating IL-2 levels. We suggest a role for circulating IL-2 in liver dysfunction and propose that a combined assessment of AST/ALT in conjunction with IL-2 at the early stages of symptomatic DENV infection may be useful to predict the severe forms of dengue. PMID:27155816

  10. Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice

    Directory of Open Access Journals (Sweden)

    Price D

    2016-01-01

    Full Text Available David Price,1,2 Andrew M Wilson,3 Alison Chisholm,4 Anna Rigazio,2 Anne Burden,2 Michael Thomas,5 Christine King2 1Centre for Academic Primary Care, The Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, 2Research in Real-Life, Cambridge, 3Norwich Medical School, University of East Anglia, Norwich, 4Respiratory Effectiveness Group, Cambridge, 5Primary Medical Care, University of Southampton, Southampton, UK Purpose: Acute, severe asthma exacerbations can be difficult to predict and thus prevent. Patients who have frequent exacerbations are of particular concern. Practical exacerbation predictors are needed for these patients in the primary-care setting. Patients and methods: Medical records of 130,547 asthma patients aged 12–80 years from the UK Optimum Patient Care Research Database and Clinical Practice Research Datalink, 1990–2013, were examined for 1 year before (baseline and 1 year after (outcome their most recent blood eosinophil count. Baseline variables predictive (P<0.05 of exacerbation in the outcome year were compared between patients who had two or more exacerbations and those who had no exacerbation or only one exacerbation, using uni- and multivariable logistic regression models. Exacerbation was defined as asthma-related hospital attendance/admission (emergency or inpatient or acute oral corticosteroid (OCS course. Results: Blood eosinophil count >400/µL (versus ≤400/µL increased the likelihood of two or more exacerbations >1.4-fold (odds ratio [OR]: 1.48 (95% confidence interval [CI]: 1.39, 1.58; P<0.001. Variables that significantly increased the odds by up to 1.4-fold included increasing age (per year, female gender (versus male, being overweight or obese (versus normal body mass index, being a smoker (versus nonsmoker, having anxiety/depression, diabetes, eczema, gastroesophageal reflux disease, or rhinitis, and prescription for acetaminophen or nonsteroidal anti-inflammatory drugs. Compared with

  11. Bonnet Ruled Surfaces

    Institute of Scientific and Technical Information of China (English)

    Filiz KANBAY

    2005-01-01

    We consider the Bonnet ruled surfaces which admit only one non-trivial isometry that preserves the principal curvatures. We determine the Bonnet ruled surfaces whose generators and orthogonal trajectories form a special net called an A-net.

  12. Computation of bankruptcy rules

    OpenAIRE

    Saavedra, Verónica; Lopez, Marcelo; Necco, Claudia Mónica; Quintas, Luis Guillermo

    2003-01-01

    We implemented a system that computes bankruptcy rules. The implemented rules are: The Talmud, the Proportional, the Truncated Proportional, the Adjusted Proportional, the Constrained Equal Awards and the Random Arrival rule. The system computes, compares and graphics the different allocations to claimants. We present some applications and examples exported by the system.

  13. Use Of Clinical Decision Analysis In Predicting The Efficacy Of Newer Radiological Imaging Modalities: Radioscintigraphy Versus Single Photon Transverse Section Emission Computed Tomography

    Science.gov (United States)

    Prince, John R.

    1982-12-01

    Sensitivity, specificity, and predictive accuracy have been shown to be useful measures of the clinical efficacy of diagnostic tests and can be used to predict the potential improvement in diagnostic certitude resulting from the introduction of a competing technology. This communication demonstrates how the informal use of clinical decision analysis may guide health planners in the allocation of resources, purchasing decisions, and implementation of high technology. For didactic purposes the focus is on a comparison between conventional planar radioscintigraphy (RS) and single photon transverse section emission conputed tomography (SPECT). For example, positive predictive accuracy (PPA) for brain RS in a specialist hospital with a 50% disease prevalance is about 95%. SPECT should increase this predicted accuracy to 96%. In a primary care hospital with only a 15% disease prevalance the PPA is only 77% and SPECT may increase this accuracy to about 79%. Similar calculations based on published data show that marginal improvements are expected with SPECT in the liver. It is concluded that: a) The decision to purchase a high technology imaging modality such as SPECT for clinical purposes should be analyzed on an individual organ system and institutional basis. High technology may be justified in specialist hospitals but not necessarily in primary care hospitals. This is more dependent on disease prevalance than procedure volume; b) It is questionable whether SPECT imaging will be competitive with standard RS procedures. Research should concentrate on the development of different medical applications.

  14. The Applicability of the Density Rule of Pathwardhan and Kumer and the Rule Based on Linear Isopiestic Relation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The applicability of the density rule of Pathwardhan and Kumer and the rule based on the linear isopiestic relation is studied by comparison with experimental density data in the literature. Predicted and measured values for 18 electrolyte mixtures are compared. The two rules are good for mixtures with and without common ions, including those containing associating ions. The deviations of the rule based on the linear isopiestic relation are slightly higher for the mixtures involving very strong ion complexes, but the predictions are still quite satisfactory. The density rule of Pathwardhan and Kumer is more accurate for these mixtures. However, it is not applicable for mixtures containing non-electrolytes. The rule based on the linear isopiestic relation is extended to mixtures involving non-electrolytes. The predictions for the mixtures containing both electrolytes and non-electrolytes and the non-electrolyte mixtures are accurate. All these results indicate that this rule is a widely applicable approach.

  15. The Applicability of the Density Rule of Pathwardhan and Kumer and the Rule Based on Linear Isopiestic Relation

    Institute of Scientific and Technical Information of China (English)

    胡玉峰

    2001-01-01

    The applicability of the density rule of Pathwardhan and Kumer and the rule based on the linear isopiestic relation is studied by comparison with experimental density data in the literature. Predicted and measured values for 18 electrolyte mixtures are compared. The two rules are good for mixtures with and without common ions, including those containing associating ions. The deviations of the rule based on the linear isopiestic relation are slightly higher for the mixtures involving very strong ion complexes, but the predictions are still quite satisfactory.The density rule of Pathwardhan and Kumer is more accurate for these mixtures. However, it is not applicable for mixtures containing non-electrolytes. The rule based on the linear isopiestic relation is extended to mixtures involving non-electrolytes. The predictions for the mixtures containing both electrolytes and non-electrolytes and the non-electrolyte mixtures are accurate. All these results indicate that this rule is a widely avvlicable approach.

  16. Early object rule acquisition.

    Science.gov (United States)

    Pierce, D E

    1991-05-01

    The purpose of this study was to generate a grounded theory of early object rule acquisition. The grounded theory approach and computer coding were used to analyze videotaped samples of an infant's and a toddler's independent object play, which produced the categories descriptive of three primary types of object rules; rules of object properties, rules of object action, and rules of object affect. This occupational science theory offers potential for understanding the role of objects in human occupations, for development of instruments, and for applications in occupational therapy early intervention. PMID:2048625

  17. Spontaneous intracerebral hemorrhage: Clinical and computed tomography findings in predicting in-hospital mortality in Central Africans

    Directory of Open Access Journals (Sweden)

    Michel Lelo Tshikwela

    2012-01-01

    Full Text Available Background and Purpose: Intracerebral hemorrhage (ICH constitutes now 52% of all strokes. Despite of its deadly pattern, locally there is no clinical grading scale for ICH-related mortality prediction. The first objective of this study was to develop a risk stratification scale (Kinshasa ICH score by assessing the strength of independent predictors and their association with in-hospital 30-day mortality. The second objective of the study was to create a specific local and African model for ICH prognosis. Materials and Methods: Age, sex, hypertension, type 2 diabetes mellitus (T2DM, smoking, alcohol intake, and neuroimaging data from CT scan (ICH volume, Midline shift of patients admitted with primary ICH and follow-upped in 33 hospitals of Kinshasa, DR Congo, from 2005 to 2008, were analyzed using logistic regression models. Results: A total of 185 adults and known hypertensive patients (140 men and 45 women were examined. 30-day mortality rate was 35% (n=65. ICH volume>25 mL (OR=8 95% CI: 3.1-20.2; P 7 mm, a consequence of ICH volume, was also a significant predictor of mortality. The Kinshasa ICH score was the sum of individual points assigned as follows: Presence of coma coded 2 (2 × 2 = 4, absence of coma coded 1 (1 × 2 = 2, ICH volume>25 mL coded 2 (2 × 2=4, ICH volume of ≤25 mL coded 1(1 × 2=2, left hemispheric site of ICH coded 2 (2 × 1=2, and right hemispheric site of hemorrhage coded 1(1 × 1 = 1. All patients with Kinshasa ICH score ≤7 survived and the patients with a score >7 died. In considering sex influence (Model 3, points were allowed as follows: Presence of coma (2 × 3 = 6, absence of coma (1 × 3 = 3, men (2 × 2 = 4, women (1 × 2 = 2, midline shift ≤7 mm (1 × 3 = 3, and midline shift >7 mm (2 × 3 = 6. Patients who died had the Kinshasa ICH score ≥16. Conclusion: In this study, the Kinshasa ICH score seems to be an accurate method for distinguishing those ICH patients who need continuous and special management

  18. High Pretreatment D-Dimer Levels Correlate with Adverse Clinical Features and Predict Poor Survival in Patients with Natural Killer/T-Cell Lymphoma

    OpenAIRE

    Bi, Xi-wen; Wang, Liang; Zhang, Wen-Wen; Sun, Peng; Yan, Shu-Mei; Liu, Pan-pan; Li, Zhi-Ming; Jiang, Wen-qi

    2016-01-01

    Pretreatment plasma D-dimer levels have been reported to predict survival in several types of malignancies. The aim of this study was to evaluate the prognostic value of D-dimer levels in patients with newly diagnosed natural killer/T-cell lymphoma (NKTCL). The cut-off value of D-dimer to predict survival was set as 1.2 μg/mL based on the receiver operating curve analysis. Patients with a D-dimer level ≥ 1.2 μg/mL had significantly more adverse clinical features, including poor performance st...

  19. New Safety rules

    CERN Multimedia

    Safety Commission

    2008-01-01

    The revision of CERN Safety rules is in progress and the following new Safety rules have been issued on 15-04-2008: Safety Procedure SP-R1 Establishing, Updating and Publishing CERN Safety rules: http://cern.ch/safety-rules/SP-R1.htm; Safety Regulation SR-S Smoking at CERN: http://cern.ch/safety-rules/SR-S.htm; Safety Regulation SR-M Mechanical Equipment: http://cern.ch/safety-rules/SR-M.htm; General Safety Instruction GSI-M1 Standard Lifting Equipment: http://cern.ch/safety-rules/GSI-M1.htm; General Safety Instruction GSI-M2 Standard Pressure Equipment: http://cern.ch/safety-rules/GSI-M2.htm; General Safety Instruction GSI-M3 Special Mechanical Equipment: http://cern.ch/safety-rules/GSI-M3.htm. These documents apply to all persons under the Director General’s authority. All Safety rules are available at the web page: http://www.cern.ch/safety-rules The Safety Commission

  20. The risk factors for abnormal ankle-brachial index in type 2 diabetic patients and clinical predictive value for diabetic foot

    Institute of Scientific and Technical Information of China (English)

    张净

    2013-01-01

    Objective To investigate the prevalence of diabetic foot (DF) and the normal,high and low ankle brachial index (ABI) in type 2 diabetic patients and explore the risk factor for abnormal ABI and the clinical predictive value for DF.Methods A total of 2 681 type 2 diabetic patients who visited our hospital between January,2007and December,2009 were enrolled in the study.The clinical data were analyzed and the risk factors for abnormal ABI were determined by logistic regression analysis.Results ABI was normal (0.9-<1.3) in 2 362 cases