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Sample records for clinical prediction rule

  1. Mining Clinical Data using Minimal Predictive Rules

    OpenAIRE

    Batal, Iyad; Hauskrecht, Milos

    2010-01-01

    Modern hospitals and health-care institutes collect huge amounts of clinical data. Those who deal with such data know that there is a widening gap between data collection and data comprehension. Thus, it is very important to develop data mining techniques capable of automatically extracting useful knowledge to support clinical decision-making in various diagnostic and patient-management tasks. In this paper, we develop a new framework for rule mining based on minimal predictive rules (MPR). O...

  2. 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.

  3. 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.

  4. 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.

  5. Clinical Prediction Rule of Drug Resistant Epilepsy in Children

    Science.gov (United States)

    Boonluksiri, Pairoj; Visuthibhan, Anannit; Katanyuwong, Kamornwan

    2015-01-01

    Background and Purpose: Clinical prediction rules (CPR) are clinical decision-making tools containing variables such as history, physical examination, diagnostic tests by developing scoring model from potential risk factors. This study is to establish clinical prediction scoring of drug-resistant epilepsy (DRE) in children using clinical manifestationa and only basic electroencephalography (EEG). Methods: Retrospective cohort study was conducted. A total of 308 children with diagnosed epilepsy were recruited. Primary outcome was the incidence of DRE. Independent determinants were patient characteristics, clinical manifestations and electroencephalography. CPR was performed based on multiple logistic regression. Results: The incidence of DRE was 42%. Risk factors were age onset, prior neurological deficits, and abnormal EEG. CPR can be established and stratified the prediction using scores into 3 levels such as low risk (score12) with positive likelihood ratio of 0.5, 1.8 and 12.5 respectively. Conclusions: CPR with scoring risks were stratified into 3 levels. The strongest risk is prior global neurological deficits. PMID:26819940

  6. Integrating knowledge-driven and data-driven approaches in the derivation of clinical prediction rules

    OpenAIRE

    Kwiatkowska, Bogumila

    2006-01-01

    Clinical prediction rules play an important role in medical practice. They expedite diagnosis and treatment for the serious cases and limit unnecessary tests for low-probability cases. However, the creation process for prediction rules is costly, lengthy, and involves several steps: initial clinical trials, rule generation and refinement, validation, and evaluation in clinical settings. With the current development of efficient data mining algorithms and growing accessibility to a vast amount...

  7. Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study

    OpenAIRE

    Ban, J-W.; Emparanza, J I; Urreta, I.; Burls, A

    2016-01-01

    BACKGROUND: Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules' performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. METHODS: Electronic databases were searched for system...

  8. 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

    Abstract Objective. The aim of the present study was to compare the ability of four clinical prediction rules to predict adverse outcome in perforated peptic ulcer (PPU): the Boey score, the American Society of Anesthesiologists (ASA) score, the Acute Physiology and Chronic Health Evaluation...... breastfeeding women, non-surgically treated patients, patients with malignant ulcers, and patients with perforation of other organs were excluded. Primary outcome measure: 30-day mortality rate. Statistical analysis: the ability of four clinical prediction rules to distinguish survivors from non...... 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...

  9. A systematic review of studies comparing diagnostic clinical prediction rules with clinical judgment.

    Directory of Open Access Journals (Sweden)

    Sharon Sanders

    Full Text Available Diagnostic clinical prediction rules (CPRs are developed to improve diagnosis or decrease diagnostic testing. Whether, and in what situations diagnostic CPRs improve upon clinical judgment is unclear.We searched MEDLINE, Embase and CINAHL, with supplementary citation and reference checking for studies comparing CPRs and clinical judgment against a current objective reference standard. We report 1 the proportion of study participants classified as not having disease who hence may avoid further testing and or treatment and 2 the proportion, among those classified as not having disease, who do (missed diagnoses by both approaches. 31 studies of 13 medical conditions were included, with 46 comparisons between CPRs and clinical judgment. In 2 comparisons (4%, CPRs reduced the proportion of missed diagnoses, but this was offset by classifying a larger proportion of study participants as having disease (more false positives. In 36 comparisons (78% the proportion of diagnoses missed by CPRs and clinical judgment was similar, and in 9 of these, the CPRs classified a larger proportion of participants as not having disease (fewer false positives. In 8 comparisons (17% the proportion of diagnoses missed by the CPRs was greater. This was offset by classifying a smaller proportion of participants as having the disease (fewer false positives in 2 comparisons. There were no comparisons where the CPR missed a smaller proportion of diagnoses than clinical judgment and classified more participants as not having the disease. The design of the included studies allows evaluation of CPRs when their results are applied independently of clinical judgment. The performance of CPRs, when implemented by clinicians as a support to their judgment may be different.In the limited studies to date, CPRs are rarely superior to clinical judgment and there is generally a trade-off between the proportion classified as not having disease and the proportion of missed diagnoses

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. Learning predictive clustering rules

    OpenAIRE

    Ženko, Bernard; Džeroski, Sašo; Struyf, Jan

    2005-01-01

    The two most commonly addressed data mining tasks are predictive modelling and clustering. Here we address the task of predictive clustering, which contains elements of both and generalizes them to some extent. We propose a novel approach to predictive clustering called predictive clustering rules, present an initial implementation and its preliminary experimental evaluation.

  15. 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.

  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. Amsterdam wrist rules: A clinical decision aid

    Directory of Open Access Journals (Sweden)

    Bentohami Abdelali

    2011-10-01

    Full Text Available Abstract Background Acute trauma of the wrist is one of the most frequent reasons for visiting the Emergency Department. These patients are routinely referred for radiological examination. Most X-rays however, do not reveal any fractures. A clinical decision rule determining the need for X-rays in patients with acute wrist trauma may help to percolate and select patients with fractures. Methods/Design This study will be a multi-center observational diagnostic study in which the data will be collected cross-sectionally. The study population will consist of all consecutive adult patients (≥18 years presenting with acute wrist trauma at the Emergency Department in the participating hospitals. This research comprises two components: one study will be conducted to determine which clinical parameters are predictive for the presence of a distal radius fracture in adult patients presenting to the Emergency Department following acute wrist trauma. These clinical parameters are defined by trauma-mechanism, physical examination, and functional testing. This data will be collected in two of the three participating hospitals and will be assessed by using logistic regression modelling to estimate the regression coefficients after which a reduced model will be created by means of a log likelihood ratio test. The accuracy of the model will be estimated by a goodness of fit test and an ROC curve. The final model will be validated internally through bootstrapping and by shrinking it, an adjusted model will be generated. In the second component of this study, the developed prediction model will be validated in a new dataset consisting of a population of patients from the third hospital. If necessary, the model will be calibrated using the data from the validation study. Discussion Wrist trauma is frequently encountered at the Emergency Department. However, to this date, no decision rule regarding this type of trauma has been created. Ideally, radiographs are

  19. Can Taylor rule fundamentals predict exchange rates?

    OpenAIRE

    Wan, Yiding

    2012-01-01

    Recent research suggests that there are many favourable features of the asset- pricing model of exchange rates incorporating Taylor rules. Against this back- ground, this thesis focuses on the relationship between the exchange rate and Taylor rule fundamentals. The introductory chapter provides a short summary of the most relevant literature, and explains the connections between the main chapters. In chapter 2, we mainly follow Engel and West's (2006) framework of the asset-...

  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. Promoter Sequences Prediction Using Relational Association Rule Mining

    OpenAIRE

    Gabriela Czibula; Maria-Iuliana Bocicor; Istvan Gergely Czibula

    2012-01-01

    In this paper we are approaching, from a computational perspective, the problem of promoter sequences prediction, an important problem within the field of bioinformatics. As the conditions for a DNA sequence to function as a promoter are not known, machine learning based classification models are still developed to approach the problem of promoter identification in the DNA. We are proposing a classification model based on relational association rules mining. Relational association rules are a...

  4. Clinical importance of predicting radiosensitivity

    International Nuclear Information System (INIS)

    Full text: The optimal use of radiation therapy in cancer treatment is hampered by the application of normal tissue tolerance limits that are derived from population averages. Such limits do not reflect the considerable differences in susceptibility to radiation injury that exist among individuals. Development of assays that accurately predicted normal tissue tolerance in individual patients would permit real application of the concept of treatment to tolerance. By adjusting doses upwards or downwards to achieve a uniform probability of complication in each patient, the therapeutic ratio, i e., the probability of an uncomplicated cure, would be increased for the population as a whole. Although the pathogenesis of radiation injury is highly complex, clinical studies have demonstrated a significant correlation between the in vitro radiosensitivity of patients' fibroblasts and their risk of developing late connective tissue type complications of radiotherapy. While such assays lack the precision and practicality to be used clinically, they do establish the principle of prediction of normal tissue tolerance. Newer assays using surrogate endpoints for cell survival and incorporating insights into the effects of radiation on cellular growth, differentiation, senescence and cytokine production are being developed. Such assays may, in the future, be complemented or replaced by molecular and/or cytogenetic probes to derive robust estimates of individual tolerance. The goal of accurate prediction of individual tolerance for clinical use, while not imminent, does seem achievable

  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. 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.

  7. 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.

  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. Fast rule-based bioactivity prediction using associative classification mining

    Directory of Open Access Journals (Sweden)

    Yu Pulan

    2012-11-01

    Full Text Available Abstract Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM, which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, classification based on predictive association rules (CPAR, classification based on multiple association rules (CMAR and classification based on association rules (CBA are employed on three datasets using various descriptor sets. Experimental evaluations on anti-tuberculosis (antiTB, mutagenicity and hERG (the human Ether-a-go-go-Related Gene blocker datasets show that these three methods are computationally scalable and appropriate for high speed mining. Additionally, they provide comparable accuracy and efficiency to the commonly used Bayesian and support vector machines (SVM methods, and produce highly interpretable models.

  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. A Comparison of the Pathogenesis of Marburg Virus Disease in Humans and Nonhuman Primates and Evaluation of the Suitability of These Animal Models for Predicting Clinical Efficacy under the 'Animal Rule'.

    Science.gov (United States)

    Glaze, Elizabeth R; Roy, Michael J; Dalrymple, Lonnie W; Lanning, Lynda L

    2015-06-01

    Marburg virus outbreaks are sporadic, infrequent, brief, and relatively small in terms of numbers of subjects affected. In addition, outbreaks most likely will occur in remote regions where clinical trials are not feasible; therefore, definitive, well-controlled human efficacy studies to test the effectiveness of a drug or biologic product are not feasible. Healthy human volunteers cannot ethically be deliberately exposed to a lethal agent such as Marburg virus in order to test the efficacy of a therapy or preventive prior to licensure. When human efficacy studies are neither ethical nor feasible, the US Food and Drug Administration may grant marketing approval of a drug or biologic product under the 'Animal Rule,' through which demonstration of the efficacy of a product can be 'based on adequate and well-controlled animal efficacy studies when the results of those studies establish that the drug is reasonably likely to produce clinical benefit in humans.' This process requires that the pathogenic determinants of the disease in the animal model are similar to those that have been identified in humans. After reviewing primarily English-language, peer-reviewed journal articles, we here summarize the clinical manifestations of Marburg virus disease and the results of studies in NHP showing the characteristics and progression of the disease. We also include a detailed comparison of the characteristics of the human disease relative to those for NHP. This review reveals that the disease characteristics of Marburg virus disease are generally similar for humans and 3 NHP species: cynomolgus macaques (Macaca fascicularis), rhesus macaques (Macaca mulatta), and African green monkeys (Chlorocebus aethiops). PMID:26141449

  15. How to Establish Clinical Prediction Models.

    Science.gov (United States)

    Lee, Yong Ho; Bang, Heejung; Kim, Dae Jung

    2016-03-01

    A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice. PMID:26996421

  16. 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...

  17. Outcome Prediction in Clinical Treatment Processes.

    Science.gov (United States)

    Huang, Zhengxing; Dong, Wei; Ji, Lei; Duan, Huilong

    2016-01-01

    Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or patient physical factors, to estimate clinical outcomes at early stages of CTPs (e.g., admission). They lack the ability to deal with temporal evolution of CTPs. In addition, most of the existing studies employ data mining or machine learning methods to generate a prediction model for a specific type of clinical outcome, however, a mathematical model that predicts multiple clinical outcomes simultaneously, has not yet been established. In this study, a hybrid approach is proposed to provide a continuous predictive monitoring service on multiple clinical outcomes. More specifically, a probabilistic topic model is applied to discover underlying treatment patterns of CTPs from electronic medical records. Then, the learned treatment patterns, as low-dimensional features of CTPs, are exploited for clinical outcome prediction across various stages of CTPs based on multi-label classification. The proposal is evaluated to predict three typical classes of clinical outcomes, i.e., length of stay, readmission time, and the type of discharge, using 3492 pieces of patients' medical records of the unstable angina CTP, extracted from a Chinese hospital. The stable model was characterized by 84.9% accuracy and 6.4% hamming-loss with 3 latent treatment patterns discovered from data, which outperforms the benchmark multi-label classification algorithms for clinical outcome prediction. Our study indicates the proposed approach can potentially improve the quality of clinical outcome prediction, and assist physicians to understand the patient conditions, treatment inventions, and clinical outcomes in an integrated view. PMID:26573645

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

    OpenAIRE

    Loza, E; Vaschenko, V.

    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.

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

    Science.gov (United States)

    Sengupta, Dipankar; 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 can be associated with occurrence of brain tumor. In this study, a brain tumor warehouse was developed comprising of clinical data for 550 patients. Apriori association rule algorithm was applied to discover associative rules among the clinical parameters. The rules discovered in the study suggests - high values of Creatinine, Blood Urea Nitrogen (BUN), SGOT & SGPT to be directly associated with tumor occurrence for patients in the primary stage with atleast 85% confidence and more than 50% support. A normalized regression model is proposed based on these parameters along with Haemoglobin content, Alkaline Phosphatase and Serum Bilirubin for prediction of occurrence of STATE (brain tumor) as 0 (absent) or 1 (present). The results indicate that the methodology followed will be of good value for the diagnostic procedure of brain tumor, especially when large data volumes are involved and screening based on discovered parameters would allow clinicians to detect tumors at an early stage of development. PMID:23888095

  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. 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)

  2. 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...

  3. 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

  4. 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 ...

  5. Radiogenomics: predicting clinical normal tissue radiosensitivity

    DEFF Research Database (Denmark)

    Alsner, Jan

    2006-01-01

    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...

  6. 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.

  7. 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.

  8. A clinical rules taxonomy for the implementation of a computerized physician order entry (CPOE) system.

    OpenAIRE

    Wang, Jerome K.; Shabot, M. Michael; Duncan, Raymond G.; Polaschek, Jeanette X.; Jones, Douglas T.

    2002-01-01

    Many of the benefits of computerized physician order entry (CPOE) stem from its ability to support medical decision-making and error-reduction during patient care. This automated "intelligence" is typically represented by a network of rules. We describe a taxonomic representation of clinical decision-support rules in the context of developing and implementing a de novo CPOE and decision-support system. In our experience, this clinical rules taxonomy facilitated our implementation goals in the...

  9. 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.

  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. 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.

  12. 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.

  13. 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.

  14. 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

    analyzed data from 3 randomly selected groups in the general population of urban Copenhagen (age, 30-70 y) participating in an international study of cardiovascular risk factors (the Multinational mONItoring of trends and determinants in CArdiovascular disease study). In this study, participants (n = 6037...... the highest risk for events (HR, 11.05; 95% CI, 3.76-32.44; unadjusted absolute risk, 0.0235 events/person-years). CONCLUSIONS: Fewer than 20% of subjects with gallstones develop clinical events. Larger, multiple, and older gallstones are associated with events. Further studies are needed to confirm...

  15. 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...

  16. 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...

  17. A prediction rule for shoulder pain related sick leave: a prospective cohort study

    Directory of Open Access Journals (Sweden)

    van der Heijden Geert JMG

    2006-12-01

    Full Text Available Abstract Background Shoulder pain is common in primary care, and has an unfavourable outcome in many patients. Information about predictors of shoulder pain related sick leave in workers is scarce and inconsistent. The objective was to develop a clinical prediction rule for calculating the risk of shoulder pain related sick leave for individual workers, during the 6 months following first consultation in general practice. Methods A prospective cohort study with 6 months follow-up was conducted among 350 workers with a new episode of shoulder pain. Potential predictors included the results of a physical examination, sociodemographic variables, disease characteristics (duration of symptoms, sick leave in the 2 months prior to consultation, pain intensity, disability, comorbidity, physical activity, physical work load, psychological factors, and the psychosocial work environment. The main outcome measure was sick leave during 6 months following first consultation in general practice. Results Response rate to the follow-up questionnaire at 6 months was 85%. During the 6 months after first consultation 30% (89/298 of the workers reported sick leave. 16% (47 reported 10 days sick leave or more. Sick leave during this period was predicted in a multivariable model by a longer duration of sick leave prior to consultation, more shoulder pain, a perceived cause of strain or overuse during regular activities, and co-existing psychological complaints. The discriminative ability of the prediction model was satisfactory with an area under the curve of 0.70 (95% CI 0.64–0.76. Conclusion Although 30% of all workers with shoulder pain reported sick leave during follow-up, the duration of sick leave was limited to a few days in most workers. We developed a prediction rule and a score chart that can be used by general practitioners and occupational health care providers to calculate the absolute risk of sick leave in individual workers with shoulder pain, which

  18. 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

  19. Injury and death in clinical trials and compensation: Rule 122 DAB

    Directory of Open Access Journals (Sweden)

    Ravindra B Ghooi

    2013-01-01

    Full Text Available Three amendments to the drugs and cosmetics rules were published in quick succession in 2013. These addressed the issues of compensation of injury and death in clinical trials in addition to the role and registration of Ethics Committees. Of the three, the first and the third make an impact on the clinical research activities in India. The second amendment has codified the conduct of clinical trials, putting together rules, which appeared in different sections of Schedule Y. The first amendment deals with the compensation for injuries and deaths taking place during clinical trials while the third deals with registration of Ethics Committees. Despite the long delay in the issue of compensation rules, there appears significant room for improvement. The most problematic are conditions of injury and death in which compensation has to be paid. When compared with other countries, the Indian rules seem unduly harsh on sponsors and are at significant variance with those in UK. The rules are very generous toward subjects and compensation is likely to become an alternative to insurance in terminally ill subjects. The implementation of these rules will make clinical trials in India more expensive and hurt the industry that is already struggling through other handicaps. There is an urgent need to make the the environment more industry friendly to attract more clinical work.

  20. Integrating association rules and case-based reasoning to predict retinopathy

    Directory of Open Access Journals (Sweden)

    Vimala Balakrishnan

    Full Text Available This study proposes a retinopathy prediction system based on data mining,particularly association rules using Apriori algorithm, and case-based reasoning. The association rules are used to analyse patterns in the data set and to calculate retinopathy probability whereas case-based reasoning is used to retrieve similar cases. This paper discusses the proposed system. It is believed that great improvements can be provided to medical practitioners and also to diabetics with the implementation of this system.

  1. 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.

  2. Matching lightcone- and anomaly-sum-rule predictions for the pion-photon transition form factor

    CERN Document Server

    Oganesian, A G; Stefanis, N G; Teryaev, O V

    2015-01-01

    The pion-photon transition form factor is studied by employing two types of Sum Rules: Light Cone Sum Rules (LCSR) and Anomaly Sum Rules (ASR). By comparing the predictions for the pion-photon transition form factor, obtained from these two approaches, the applicability limit of the LCSRs at low momenta is determined. Reciprocally, the ASR threshold dependence on the momentum was extracted using our LCSR-based method in combination with two different types of pion distribution amplitudes and found that at higher Q2 it approaches a constant.

  3. 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.)

  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

    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.)

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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%.

  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. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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...

  18. 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

  19. Bayesian rules and stochastic models for high accuracy prediction of solar radiation

    International Nuclear Information System (INIS)

    Highlights: • Global radiation prediction and PV energy integration. • Artificial intelligence and stochastic modeling in order to use the time series formalism. • Using Bayesian rules to select models. • MLP and ARMA forecasters are equivalent (nRMSE close to 40.5% for the both). • The hybridization of the three predictors (ARMA, MLP and persistence) induces very good results (nRMSE = 36.6%). - Abstract: It is essential to find solar predictive methods to massively insert renewable energies on the electrical distribution grid. The goal of this study is to find the best methodology allowing predicting with high accuracy the hourly global radiation. The knowledge of this quantity is essential for the grid manager or the private PV producer in order to anticipate fluctuations related to clouds occurrences and to stabilize the injected PV power. In this paper, we test both methodologies: single and hybrid predictors. In the first class, we include the multi-layer perceptron (MLP), auto-regressive and moving average (ARMA), and persistence models. In the second class, we mix these predictors with Bayesian rules to obtain ad hoc models selections, and Bayesian averages of outputs related to single models. If MLP and ARMA are equivalent (nRMSE close to 40.5% for the both), this hybridization allows a nRMSE gain upper than 14% points compared to the persistence estimation (nRMSE = 37% versus 51%)

  20. 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...

  1. 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...

  2. 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.

  3. Use of conditional rule structure to automate clinical decision support: a comparison of artificial intelligence and deterministic programming techniques.

    Science.gov (United States)

    Friedman, R H; Frank, A D

    1983-08-01

    A rule-based computer system was developed to perform clinical decision-making support within a medical information system, oncology practice, and clinical research. This rule-based system, which has been programmed using deterministic rules, possesses features of generalizability, modularity of structure, convenience in rule acquisition, explanability, and utility for patient care and teaching, features which have been identified as advantages of artificial intelligence (AI) rule-based systems. Formal rules are primarily represented as conditional statements; common conditions and actions are stored in system dictionaries so that they can be recalled at any time to form new decision rules. Important similarities and differences exist in the structure of this system and clinical computer systems utilizing artificial intelligence (AI) production rule techniques. The non-AI rule-based system possesses advantages in cost and ease of implementation. The degree to which significant medical decision problems can be solved by this technique remains uncertain as does whether the more complex AI methodologies will be required. PMID:6352165

  4. 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.

  5. 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

  6. icuARM-An ICU Clinical Decision Support System Using Association Rule Mining

    Science.gov (United States)

    Chanani, Nikhil; Venugopalan, Janani; Maher, Kevin; Wang, May Dongmei

    2013-01-01

    The rapid development of biomedical monitoring technologies has enabled modern intensive care units (ICUs) to gather vast amounts of multimodal measurement data about their patients. However, processing large volumes of complex data in real-time has become a big challenge. Together with ICU physicians, we have designed and developed an ICU clinical decision support system icuARM based on associate rule mining (ARM), and a publicly available research database MIMIC-II (Multi-parameter Intelligent Monitoring in Intensive Care II) that contains more than 40,000 ICU records for 30,000+patients. icuARM is constructed with multiple association rules and an easy-to-use graphical user interface (GUI) for care providers to perform real-time data and information mining in the ICU setting. To validate icuARM, we have investigated the associations between patients' conditions such as comorbidities, demographics, and medications and their ICU outcomes such as ICU length of stay. Coagulopathy surfaced as the most dangerous co-morbidity that leads to the highest possibility (54.1%) of prolonged ICU stay. In addition, women who are older than 50 years have the highest possibility (38.8%) of prolonged ICU stay. For clinical conditions treatable with multiple drugs, icuARM suggests that medication choice can be optimized based on patient-specific characteristics. Overall, icuARM can provide valuable insights for ICU physicians to tailor a patient's treatment based on his or her clinical status in real time.

  7. Prediction of labor induction outcome using different clinical parameters

    OpenAIRE

    Tatić-Stupar Žaklina; Novakov-Mikić Aleksandra; Bogavac Mirjana; Milatović Stevan; Sekulić Slobodan

    2013-01-01

    Introduction. Induction of labor is one of the most common obstetric interventions in contemporary obstetrics. Objective. The aim of the study was to evaluate the clinical and sonographic parameters in prediction of success of labor induction. Methods. The prospective study included 422 women in whom induction of labor was carried out at the Department of Obstetrics and Gynecology of Clinical Centre of Vojvodina. The role of body mass index and age of women...

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

    OpenAIRE

    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 im...

  9. 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.

  10. 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

  11. How Beyond Rule of 5 Drugs and Clinical Candidates Bind to Their Targets.

    Science.gov (United States)

    Doak, Bradley C; Zheng, Jie; Dobritzsch, Doreen; Kihlberg, Jan

    2016-03-24

    To improve discovery of drugs for difficult targets, the opportunities of chemical space beyond the rule of 5 (bRo5) were examined by retrospective analysis of a comprehensive set of structures for complexes between drugs and clinical candidates and their targets. The analysis illustrates the potential of compounds far beyond rule of 5 space to modulate novel and difficult target classes that have large, flat, and groove-shaped binding sites. However, ligand efficiencies are significantly reduced for flat- and groove-shape binding sites, suggesting that adjustments of how to use such metrics are required. Ligands bRo5 appear to benefit from an appropriate balance between rigidity and flexibility to bind with sufficient affinity to their targets, with macrocycles and nonmacrocycles being found to have similar flexibility. However, macrocycles were more disk- and spherelike, which may contribute to their superior binding to flat sites, while rigidification of nonmacrocycles lead to rodlike ligands that bind well to groove-shaped binding sites. These insights should contribute to altering perceptions of what targets are considered "druggable" and provide support for drug design in beyond rule of 5 space. PMID:26457449

  12. Parenting Practices and Adolescent Risk Behavior: Rules on Smoking and Drinking Also Predict Cannabis Use and Early Sexual Debut

    OpenAIRE

    de Looze, Margaretha; van den Eijnden, Regina; Verdurmen, Jacqueline; Vermeulen-Smit, Evelien; Schulten, Ingrid; Vollebergh, Wilma; ter Bogt, Tom

    2012-01-01

    Previous research has provided considerable support for idea that increased parental support and control are strong determinants of lower prevalence levels of adolescent risk behavior. Much less is known on the association between specific parenting practices, such as concrete rules with respect to smoking and drinking and adolescent risk behavior. The present paper examined whether such concrete parental rules (1) have an effect on the targeted behaviors and (2) predict other, frequently co-...

  13. 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...

  14. 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.

  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. A Clinical Prediction Formula for Apnea-Hypopnea Index

    OpenAIRE

    Mustafa Sahin; Cem Bilgen; M. Sezai Tasbakan; Rasit Midilli; Basoglu, Ozen K.

    2014-01-01

    Objectives. There are many studies regarding unnecessary polysomnography (PSG) when obstructive sleep apnea syndrome (OSAS) is suspected. In order to reduce unnecessary PSG, this study aims to predict the apnea-hypopnea index (AHI) via simple clinical data for patients who complain of OSAS symptoms. Method. Demographic, anthropometric, physical examination and laboratory data of a total of 390 patients (290 men, average age 50 ± 11) who were subject to diagnostic PSG were obtained and evaluat...

  18. 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

  19. Beyond Atomic Sizes and Hume-Rothery Rules: Understanding and Predicting High-Entropy Alloys

    Science.gov (United States)

    Troparevsky, M. Claudia; Morris, James R.; Daene, Markus; Wang, Yang; Lupini, Andrew R.; Stocks, G. Malcolm

    2015-09-01

    High-entropy alloys constitute a new class of materials that provide an excellent combination of strength, ductility, thermal stability, and oxidation resistance. Although they have attracted extensive attention due to their potential applications, little is known about why these compounds are stable or how to predict which combination of elements will form a single phase. In this article, we present a review of the latest research done on these alloys focusing on the theoretical models devised during the last decade. We discuss semiempirical methods based on the Hume-Rothery rules and stability criteria based on enthalpies of mixing and size mismatch. To provide insights into the electronic and magnetic properties of high-entropy alloys, we show the results of first-principles calculations of the electronic structure of the disordered solid-solution phase based on both Korringa-Kohn-Rostoker coherent potential approximation and large supercell models of example face-centered cubic and body-centered cubic systems. We also discuss in detail a model based on enthalpy considerations that can predict which elemental combinations are most likely to form a single-phase high-entropy alloy. The enthalpies are evaluated via first-principles "high-throughput" density functional theory calculations of the energies of formation of binary compounds, and therefore it requires no experimental or empirically derived input. The model correctly accounts for the specific combinations of metallic elements that are known to form single-phase alloys while rejecting similar combinations that have been tried and shown not to be single phase.

  20. 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.

  1. 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

  2. A resource range invariance rule for optimal offspring size predicts patterns of variability in parental phenotypes

    OpenAIRE

    Downhower, Jerry F.; Charnov, Eric L.

    1998-01-01

    Previous analysis of the rules regarding how much more a female should invest in a litter of size C rather than producing a litter with one more offspring revealed an invariance relationship between litter size and the range of resources per offspring in any litter size. The rule is that the range of resources per offspring should be inversely proportional to litter size. Here we present a modification of this rule that relates litter size to the total resources devoted to reproduction at tha...

  3. 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...

  4. Systematic prediction of drug combinations based on clinical side-effects.

    Science.gov (United States)

    Huang, Hui; Zhang, Ping; Qu, Xiaoyan A; Sanseau, Philippe; Yang, Lun

    2014-01-01

    Drug co-prescription (or drug combination) is a therapeutic strategy widely used as it may improve efficacy and reduce side-effect (SE). Since it is impractical to screen all possible drug combinations for every indication, computational methods have been developed to predict new combinations. In this study, we describe a novel approach that utilizes clinical SEs from post-marketing surveillance and the drug label to predict 1,508 novel drug-drug combinations. It outperforms other prediction methods, achieving an AUC of 0.92 compared to an AUC of 0.69 in a previous method, on a much larger drug combination set (245 drug combinations in our dataset compared to 75 in previous work.). We further found from the feature selection that three FDA black-box warned serious SEs, namely pneumonia, haemorrhage rectum, and retinal bleeding, contributed mostly to the predictions and a model only using these three SEs can achieve an average area under curve (AUC) at 0.80 and accuracy at 0.91, potentially with its simplicity being recognized as a practical rule-of-three in drug co-prescription or making fixed-dose drug combination. We also demonstrate this performance is less likely to be influenced by confounding factors such as biased disease indications or chemical structures. PMID:25418113

  5. 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...

  6. 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...

  7. 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.

  8. Prediction of labor induction outcome using different clinical parameters

    Directory of Open Access Journals (Sweden)

    Tatić-Stupar Žaklina

    2013-01-01

    Full Text Available Introduction. Induction of labor is one of the most common obstetric interventions in contemporary obstetrics. Objective. The aim of the study was to evaluate the clinical and sonographic parameters in prediction of success of labor induction. Methods. The prospective study included 422 women in whom induction of labor was carried out at the Department of Obstetrics and Gynecology of Clinical Centre of Vojvodina. The role of body mass index and age of women, parity Bishop score, cervical length measured by transvaginal ultrasound was evaluated in regard of the success of induction, which was considered successful if a vaginal delivery occurred within 24 hours after the onset of induction. Data were statistically analyzed by univariate statistical analysis and Pearson’s χ2 test. Results. Out of 422 women, induction of labor was successful in 356 (84.4%, and it failed in 66 (15.6% cases. The values of Bishop score and cervical length had positive correlation with the success of induction. Conclusion. Bishop score and transvaginal cervical length were both reliable predictors in determining the success of labor induction, as well as parity and BMI. These parameters are mostly complementary, not competitive in prediction of labor induction success.

  9. Fuzzy rule-based prediction of lovastatin productivity in continuous mode using pellets of Aspergillus terreus in an airlift reactor

    OpenAIRE

    Kamakshi Gupta; Bodhisatta Maiti; Mishra, P. K.; Pradeep Srivastava

    2009-01-01

    Lovastatin production using pellets of Aspergillus terreus was investigated in an airlift reactor. A fuzzy system has been developed for predicting the lovastatin productivity. Analysis of the effect of dilution rate and biomass concentration on the productivity of lovastatin was carried out and hence these were taken as inputs for the fuzzy system. The rule base has been developed using the conceptions of developmental processes in lovastatin production. The fuzzy system has been constructed...

  10. A text mining approach to the prediction of disease status from clinical discharge summaries.

    Science.gov (United States)

    Yang, Hui; Spasic, Irena; Keane, John A; Nenadic, Goran

    2009-01-01

    OBJECTIVE The authors present a system developed for the Challenge in Natural Language Processing for Clinical Data-the i2b2 obesity challenge, whose aim was to automatically identify the status of obesity and 15 related co-morbidities in patients using their clinical discharge summaries. The challenge consisted of two tasks, textual and intuitive. The textual task was to identify explicit references to the diseases, whereas the intuitive task focused on the prediction of the disease status when the evidence was not explicitly asserted. DESIGN The authors assembled a set of resources to lexically and semantically profile the diseases and their associated symptoms, treatments, etc. These features were explored in a hybrid text mining approach, which combined dictionary look-up, rule-based, and machine-learning methods. MEASUREMENTS The methods were applied on a set of 507 previously unseen discharge summaries, and the predictions were evaluated against a manually prepared gold standard. The overall ranking of the participating teams was primarily based on the macro-averaged F-measure. RESULTS The implemented method achieved the macro-averaged F-measure of 81% for the textual task (which was the highest achieved in the challenge) and 63% for the intuitive task (ranked 7(th) out of 28 teams-the highest was 66%). The micro-averaged F-measure showed an average accuracy of 97% for textual and 96% for intuitive annotations. CONCLUSIONS The performance achieved was in line with the agreement between human annotators, indicating the potential of text mining for accurate and efficient prediction of disease statuses from clinical discharge summaries. PMID:19390098

  11. Systematic review of clinical prediction tools and prognostic factors in aneurysmal subarachnoid hemorrhage

    OpenAIRE

    Lo, Benjamin W. Y.; Hitoshi Fukuda; Yusuke Nishimura; Forough Farrokhyar; Lehana Thabane; Mitchell A. H. Levine

    2015-01-01

    Background: Clinical prediction tools assist in clinical outcome prediction. They quantify the relative contributions of certain variables and condense information that identifies important indicators or predictors to a targeted condition. This systematic review synthesizes and critically appraises the methodologic quality of studies that derive both clinical predictors and clinical predictor tools used to determine outcome prognosis in patients suffering from aneurysmal subarachnoid hemorrha...

  12. 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

  13. 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.

  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. Improving Clinical Prediction of Bipolar Spectrum Disorders in Youth.

    Science.gov (United States)

    Frazier, Thomas W; Youngstrom, Eric A; Fristad, Mary A; Demeter, Christine; Birmaher, Boris; Kowatch, Robert A; Arnold, L Eugene; Axelson, David; Gill, Mary K; Horwitz, Sarah M; Findling, Robert L

    2014-01-01

    This report evaluates whether classification tree algorithms (CTA) may improve the identification of individuals at risk for bipolar spectrum disorders (BPSD). Analyses used the Longitudinal Assessment of Manic Symptoms (LAMS) cohort (629 youth, 148 with BPSD and 481 without BPSD). Parent ratings of mania symptoms, stressful life events, parenting stress, and parental history of mania were included as risk factors. Comparable overall accuracy was observed for CTA (75.4%) relative to logistic regression (77.6%). However, CTA showed increased sensitivity (0.28 vs. 0.18) at the expense of slightly decreased specificity and positive predictive power. The advantage of CTA algorithms for clinical decision making is demonstrated by the combinations of predictors most useful for altering the probability of BPSD. The 24% sample probability of BPSD was substantially decreased in youth with low screening and baseline parent ratings of mania, negative parental history of mania, and low levels of stressful life events (2%). High screening plus high baseline parent-rated mania nearly doubled the BPSD probability (46%). Future work will benefit from examining additional, powerful predictors, such as alternative data sources (e.g., clinician ratings, neurocognitive test data); these may increase the clinical utility of CTA models further. PMID:25143826

  16. Improving Clinical Prediction of Bipolar Spectrum Disorders in Youth

    Directory of Open Access Journals (Sweden)

    Thomas W. Frazier

    2014-03-01

    Full Text Available This report evaluates whether classification tree algorithms (CTA may improve the identification of individuals at risk for bipolar spectrum disorders (BPSD. Analyses used the Longitudinal Assessment of Manic Symptoms (LAMS cohort (629 youth, 148 with BPSD and 481 without BPSD. Parent ratings of mania symptoms, stressful life events, parenting stress, and parental history of mania were included as risk factors. Comparable overall accuracy was observed for CTA (75.4% relative to logistic regression (77.6%. However, CTA showed increased sensitivity (0.28 vs. 0.18 at the expense of slightly decreased specificity and positive predictive power. The advantage of CTA algorithms for clinical decision making is demonstrated by the combinations of predictors most useful for altering the probability of BPSD. The 24% sample probability of BPSD was substantially decreased in youth with low screening and baseline parent ratings of mania, negative parental history of mania, and low levels of stressful life events (2%. High screening plus high baseline parent-rated mania nearly doubled the BPSD probability (46%. Future work will benefit from examining additional, powerful predictors, such as alternative data sources (e.g., clinician ratings, neurocognitive test data; these may increase the clinical utility of CTA models further.

  17. Fuzzy rule-based prediction of lovastatin productivity in continuous mode using pellets of Aspergillus terreus in an airlift reactor

    Directory of Open Access Journals (Sweden)

    Kamakshi Gupta

    2009-12-01

    Full Text Available Lovastatin production using pellets of Aspergillus terreus was investigated in an airlift reactor. A fuzzy system has been developed for predicting the lovastatin productivity. Analysis of the effect of dilution rate and biomass concentration on the productivity of lovastatin was carried out and hence these were taken as inputs for the fuzzy system. The rule base has been developed using the conceptions of developmental processes in lovastatin production. The fuzzy system has been constructed on the basis of experimental results and operator’s knowledge. The values predicted for lovastatin productivity by the fuzzy system has been compared with the experimental data. The R squared value and mean squared error has been calculated to evaluate the quality of the fuzzy system. The performance measures show that the rule-based results of the fuzzy system is in accordance with the experimental results. The utilization of fuzzy system aided in the increase of lovastatin productivity by about 1.3 times when compared to previous empirical experimental results. Keywords: Lovastatin, airlift reactor, fuzzy rule-based system, Aspergillus terreus, continuous fermentation, pellets. Received: 27 November 2009 / Received in revised form: 18 January 2010, Accepted: 11 February 2010, Published online: 23 March 2010

  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. Improved therapy-success prediction with GSS estimated from clinical HIV-1 sequences

    Directory of Open Access Journals (Sweden)

    Alejandro Pironti

    2014-11-01

    Full Text Available Introduction: Rules-based HIV-1 drug-resistance interpretation (DRI systems disregard many amino-acid positions of the drug's target protein. The aims of this study are (1 the development of a drug-resistance interpretation system that is based on HIV-1 sequences from clinical practice rather than hard-to-get phenotypes, and (2 the assessment of the benefit of taking all available amino-acid positions into account for DRI. Materials and Methods: A dataset containing 34,934 therapy-naïve and 30,520 drug-exposed HIV-1 pol sequences with treatment history was extracted from the EuResist database and the Los Alamos National Laboratory database. 2,550 therapy-change-episode baseline sequences (TCEB were assigned to test set A. Test set B contains 1,084 TCEB from the HIVdb TCE repository. Sequences from patients absent in the test sets were used to train three linear support vector machines to produce scores that predict drug exposure pertaining to each of 20 antiretrovirals: the first one uses the full amino-acid sequences (DEfull, the second one only considers IAS drug-resistance positions (DEonlyIAS, and the third one disregards IAS drug-resistance positions (DEnoIAS. For performance comparison, test sets A and B were evaluated with DEfull, DEnoIAS, DEonlyIAS, geno2pheno[resistance], HIVdb, ANRS, HIV-GRADE, and REGA. Clinically-validated cut-offs were used to convert the continuous output of the first four methods into susceptible-intermediate-resistant (SIR predictions. With each method, a genetic susceptibility score (GSS was calculated for each therapy episode in each test set by converting the SIR prediction for its compounds to integer: S=2, I=1, and R=0. The GSS were used to predict therapy success as defined by the EuResist standard datum definition. Statistical significance was assessed using a Wilcoxon signed-rank test. Results: A comparison of the therapy-success prediction performances among the different interpretation systems for test

  20. 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.

  1. 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

    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 and...... inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system....

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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)

  7. 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.

  8. 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.

  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. How Subtyping Shapes Perception: Predictable Exceptions to the Rule Reduce Attention to Stereotype-Associated Dimensions

    OpenAIRE

    Deutsch, Roland; Fazio, Russell H.

    2008-01-01

    Two experiments examined the relation between stereotype disconfirmation and attentional processes. Using an instrumental learning-paradigm, we successfully simulated stereotype acquisition and the subsequent subtyping of disconfirming exemplars. While replicating established markers of subtyping, the present research demonstrates a hitherto neglected cognitive consequence of subtyping: Predictable stereotype disconfirmation increased attention to features that facilitated discriminating betw...

  11. 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.

  12. 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.

  13. Prediction of transcription factor binding to DNA using rule induction methods

    OpenAIRE

    Huss, Mikael; Nordström, Karin

    2005-01-01

    The transcription of DNA into mRNA is initiated and aided by a number of transcription factors (TFs), proteins with DNA-binding regions that attach themselves to binding sites in the DNA (transcription factor binding sites, TFBSs). As it has become apparent that both TFs and TFBSs are highly variable, tools are needed to quantify the strength of the interaction resulting from a certain TF variant binding to a certain TFBS. We used a simple way to predict interactions between protein and DNA: ...

  14. 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.

  15. Linear combination rule in genetic algorithm for optimization of finite impulse response neural network to predict natural chaotic time series

    International Nuclear Information System (INIS)

    A finite impulse response neural network, with tap delay lines after each neuron in hidden layer, is used. Genetic algorithm with arithmetic decimal crossover and Roulette selection with normal probability mutation method with linear combination rule is used for optimization of FIR neural network. The method is applied for prediction of several important and benchmarks chaotic time series such as: geomagnetic activity index natural time series and famous Mackey-Glass time series. The results of simulations shows that applying dynamic neural models for modeling of highly nonlinear chaotic systems is more satisfactory with respect to feed forward neural networks. Likewise, global optimization method such as genetic algorithm is more efficient in comparison of nonlinear gradient based optimization methods like momentum term, conjugate gradient.

  16. 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.

  17. 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

  18. Do Institutional Logics Predict Interpretation of Contract Rules at the Dental Chair-side?

    DEFF Research Database (Denmark)

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

    2014-01-01

    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......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...

  19. Fatigue analysis of crack like defect experimental verification of practical rules to predict initiation

    International Nuclear Information System (INIS)

    This paper presents an experimental verification of analysis methods aiming at predicting initiation of cracking by fatigue in crack like defects existing on start up of pressure vessel components. A few calculation methods available in the literature and usable by design engineers are selected. Some of them are given by the french construction codes like RCC-M or RCC-MR. They are applied and compared with numerous experimental results obtained on austenitic steel specimens. The comparison of results reveals a satisfactory correlation with the simplest method based on elastic stress component calculated at 0.05 mm distance from the surface crack and on the classical design fatigue curve relevant for the material. The elastoplastic methods that permit a more precise evaluation of real strain range lead to more complex calculations and require the use of the design fatigue curve too. The plastic zone size, stress triaxiality and experimental initiation detection influence the results

  20. Basal ganglia contribution to rule expectancy and temporal predictability in speech.

    Science.gov (United States)

    Kotz, Sonja A; Schmidt-Kassow, Maren

    2015-07-01

    The current work set out to answer three questions: (1) Are reported syntactic deficits in patients with structural damage to the basal ganglia (BG) in the cortico-striato-thalamo-cortical systems (CSTCS) the result of a syntax specific computational deficit or are they potentially a consequence of a generalized timing deficit? (2) Do BG patients suffer from a simple beat perception deficit in speech comparable to the one reported in music? (3) Can regular speech meter (i.e., a pattern of beats induced by the regular alteration of stressed and unstressed syllable accents) ameliorate the computation of syntactically marked information by making speech events temporally predictable and salient? The latter 'remediation' hypothesis would predict that when speech events (i.e., those that are syntactically marked) are metrically aligned to the syllabic accent structure, the computation of syntactic information is facilitated or in the case of patients ameliorated. During continuous EEG measurement nineteen patients with focal BG lesions and matched healthy controls listened to metrically regular and syntactically well-formed sentences and metrically well-formed sentences that either violated syntactic expectancy, metrical expectancy, or both. While healthy controls showed an expected P600 response in the event-related brain potential (ERP) to all expectancy violations, BG patients showed overall comparable P600 responses to all, but the metrical expectancy violation. These results confirm that (1) BG patients suffer from a simple beat perception deficit in speech and (2) regular speech meter ameliorates the computation of syntactically marked information in the speech signal. We propose that a domain general sensorimotor cerebello-thalamo-cortical system (CTCS), involved in event-based temporal processing, engages in the remediation of dysfunctional cortico-striato-thalamo-cortical timing that affects the timely computation of linguistic (i.e., syntax) information in the

  1. 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...

  2. 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.; Loganathan, Gopalakrishnan; Colton, Clark K.; Koulmanda, Maria; Weir, Gordon C; Wilhelm, Josh J.

    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 confoundin...

  3. 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 ...

  4. 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

    RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of...... European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and...... how the PREDICT consortium will endeavour to identify a new generation of predictive biomarkers....

  5. 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…

  6. 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.

  7. 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.

  8. 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

  9. 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)

  10. 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...

  11. 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

  12. 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.

  13. Translating clinical findings into knowledge in drug safety evaluation--drug induced liver injury prediction system (DILIps.

    Directory of Open Access Journals (Sweden)

    Zhichao Liu

    2011-12-01

    Full Text Available Drug-induced liver injury (DILI is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps. The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91% when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

  14. 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...

  15. Predictive biomarkers for personalised anti-cancer drug use: discovery to clinical implementation.

    Science.gov (United States)

    Alymani, Nayef A; Smith, Murray D; Williams, David J; Petty, Russell D

    2010-03-01

    A priority translational research objective in cancer medicine is the discovery of novel therapeutic targets for solid tumours. Ideally, co-discovery of predictive biomarkers occurs in parallel to facilitate clinical development of agents and ultimately personalise clinical use. However, the identification of clinically useful predictive biomarkers for solid tumours has proven challenging with many initially promising biomarkers failing to translate into clinically useful applications. In particular, the 'failure' of a predictive biomarker has often only become apparent at a relatively late stage in investigation. Recently, the field has recognised the need to develop a robust clinical biomarker development methodology to facilitate the process. This review discusses the recent progress in this area focusing on the key stages in the biomarker development process: discovery, validation, qualification and implementation. Concentrating on predictive biomarkers for selecting systemic therapies for individual patients in the clinic, the advances and progress in each of these stages in biomarker development are outlined and the key remaining challenges are discussed. Specific examples are discussed to illustrate the challenges identified and how they have been addressed. Overall, we find that significant progress has been made towards a formalised biomarker developmental process. This holds considerable promise for facilitating the translation of predictive biomarkers from discovery to clinical implementation. Further enhancements could eventually be found through alignment with regulatory processes. PMID:20138504

  16. 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...

  17. Precision and Negative Predictive Value of Links between ClinicalTrials.gov and PubMed

    OpenAIRE

    Huser, Vojtech; Cimino, James J.

    2012-01-01

    One of the goals of translational science is to shorten the time from discovery to clinical use. Clinical trial registries were established to increase transparency in completed and ongoing clinical trials, and they support linking trials with resulting publications. We set out to investigate precision and negative predictive value (NPV) of links between ClinicalTrials.gov (CT.gov) and PubMed. CT.gov has been established to increase transparency in clinical trials and the link to PubMed is cr...

  18. Sixty-Six Years of Research on the Clinical Versus Actuarial Prediction of Violence

    Science.gov (United States)

    Hilton, N. Zoe; Harris, Grant T.; Rice, Marnie E.

    2006-01-01

    In their meta-analysis of clinical versus statistical prediction models, Aegisdottir et al. (this issue) extended previous findings of statistical-method superiority across such variables as clinicians' experience and familiarity with data. In this reaction, the authors are particularly interested in violence prediction, which yields the greatest…

  19. 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

  20. 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,...

  1. 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

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

    Science.gov (United States)

    Swanton, Charles; Larkin, James M; Gerlinger, Marco; Eklund, Aron C; Howell, Michael; Stamp, Gordon; Downward, Julian; Gore, Martin; Futreal, P Andrew; Escudier, Bernard; Andre, Fabrice; Albiges, Laurence; Beuselinck, Benoit; Oudard, Stephane; Hoffmann, Jens; Gyorffy, Balázs; Torrance, Chris J; Boehme, Karen A; Volkmer, Hansjuergen; Toschi, Luisella; Nicke, Barbara; Beck, Marlene; Szallasi, Zoltan

    2010-01-01

    The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding

  3. 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.

  4. A noninvasive method for coronary artery diseases diagnosis using a clinically-interpretable fuzzy rule-based system

    Directory of Open Access Journals (Sweden)

    Hamid Reza Marateb

    2015-01-01

    Full Text Available Background: Coronary heart diseases/coronary artery diseases (CHDs/CAD, the most common form of cardiovascular disease (CVD, are a major cause for death and disability in developing/developed countries. CAD risk factors could be detected by physicians to prevent the CAD occurrence in the near future. Invasive coronary angiography, a current diagnosis method, is costly and associated with morbidity and mortality in CAD patients. The aim of this study was to design a computer-based noninvasive CAD diagnosis system with clinically interpretable rules. Materials and Methods: In this study, the Cleveland CAD dataset from the University of California UCI (Irvine was used. The interval-scale variables were discretized, with cut points taken from the literature. A fuzzy rule-based system was then formulated based on a neuro-fuzzy classifier (NFC whose learning procedure was speeded up by the scaled conjugate gradient algorithm. Two feature selection (FS methods, multiple logistic regression (MLR and sequential FS, were used to reduce the required attributes. The performance of the NFC (without/with FS was then assessed in a hold-out validation framework. Further cross-validation was performed on the best classifier. Results: In this dataset, 16 complete attributes along with the binary CHD diagnosis (gold standard for 272 subjects (68% male were analyzed. MLR + NFC showed the best performance. Its overall sensitivity, specificity, accuracy, type I error (α and statistical power were 79%, 89%, 84%, 0.1 and 79%, respectively. The selected features were "age and ST/heart rate slope categories," "exercise-induced angina status," fluoroscopy, and thallium-201 stress scintigraphy results. Conclusion: The proposed method showed "substantial agreement" with the gold standard. This algorithm is thus, a promising tool for screening CAD patients.

  5. 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

  6. 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.

  7. Accuracy of the “traffic light” clinical decision rule for serious bacterial infections in young children with fever: a retrospective cohort study

    OpenAIRE

    Sukanya; Williams, Gabrielle J; Hayen, Andrew; Macaskill, Petra; McCaskill, Mary; Isaacs, David; Craig, Jonathan C.

    2013-01-01

    Objectives To determine the accuracy of a clinical decision rule (the traffic light system developed by the National Institute for Health and Clinical Excellence (NICE)) for detecting three common serious bacterial infections (urinary tract infection, pneumonia, and bacteraemia) in young febrile children. Design Retrospective analysis of data from a two year prospective cohort study Setting A paediatric emergency department. Participants 15 781 cases of children under 5 years of age presentin...

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. A comparison of a new multinomial stopping rule with stopping rules of fleming and gehan in single arm phase II cancer clinical trials

    Directory of Open Access Journals (Sweden)

    Tu Dongsheng

    2011-06-01

    Full Text Available Abstract Background Response rate (RR alone may be insensitive to drug activity in phase II trials. Early progressive disease (EPD could improve sensitivity as well as increase stage I stopping rates. This study compares the previously developed dual endpoint stopping rule (DESR, which incorporates both RR and EPD into a two-stage, phase II trial, with rules using only RR. Methods Stopping rules according to the DESR were compared with studies conducted under the Fleming (16 trials or Gehan (23 trials designs. The RR hypothesis for the DESR was consistent with the comparison studies (ralt = 0.2, rnul = 0.05. Two parameter sets were used for EPD rates of interest and disinterest respectively (epdalt, epdnul: (0.4, 0.6 and (0.3, 0.5. Results Compared with Fleming, the DESR was more likely to allow stage two of accrual and to reject the null hypothesis (Hnul after stage two, with rejection being more common with EPD parameters (0.4, 0.6 than (0.3, 0.5. Compared with Gehan, both DESR parameter sets accepted Hnul in 15 trials after stage I compared with 8 trials by Gehan, with consistent conclusions in all 23 trials after stage II. Conclusions The DESR may reject Hnul when EPD rates alone are low, and thereby may improve phase II trial sensitivity to active, cytostatic drugs having limited response rates. Conversely, the DESR may invoke early stopping when response rates are low and EPD rates are high, thus shortening trials when drug activity is unlikely. EPD parameters should be chosen specific to each trial.

  13. 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.

  14. 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。

  15. 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...

  16. 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...

  17. 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...

  18. Endometrial histology and predictable clinical factors for endometrial disease in women with polycystic ovary syndrome

    OpenAIRE

    Park, Joon Cheol; Lim, Su Yeon; Jang, Tae Kyu; Bae, Jin Gon; Kim, Jong In; Rhee, Jeong Ho

    2011-01-01

    Objective This study was aimed to investigate endometrial histology and to find predictable clinical factors for endometrial disease (hyperplasia or cancer) in women with polycystic ovary syndrome (PCOS). Methods We investigated the endometrial histology and analyzed the relationship between endometrial histology and clinical parameters, such as LH, FSH, estradiol, testosterone, fasting and 2 hours postprandial glucose and insulin, insulin resistance, body mass index, endometrial thickness, m...

  19. 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...

  20. Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction

    OpenAIRE

    Phan, John H.; Andrew N. Young; Wang, May D.

    2012-01-01

    Combining multiple microarray datasets increases sample size and leads to improved reproducibility in identification of informative genes and subsequent clinical prediction. Although microarrays have increased the rate of genomic data collection, sample size is still a major issue when identifying informative genetic biomarkers. Because of this, feature selection methods often suffer from false discoveries, resulting in poorly performing predictive models. We develop a simple meta-analysis-ba...

  1. 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...

  2. 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.

  3. Perfusion CT in acute stroke: prediction of vessel recanalization and clinical outcome in intravenous thrombolytic therapy

    International Nuclear Information System (INIS)

    This study evaluated perfusion computed tomography (PCT) for the prediction of vessel recanalization and clinical outcome in patients undergoing intravenous thrombolysis. Thirty-nine patients with acute ischemic stroke of the middle cerebral artery territory underwent intravenous thrombolysis within 3 h of symptom onset. They all had non-enhanced CT (NECT), PCT, and CT angiography (CTA) before treatment. The Alberta Stroke Program Early Computed Tomography (ASPECT) score was applied to NECT and PCT maps to assess the extent of ischemia. CTA was assessed for the site of vessel occlusion. The National Institute of Health Stroke Scale (NIHSS) score was used for initial clinical assessment. Three-month clinical outcome was assessed using the modified Rankin scale. Vessel recanalization was determined by follow-up ultrasound. Of the PCT maps, a cerebral blood volume (CBV) ASPECT score of >6 versus ≤6 was the best predictor for clinical outcome (odds ratio, 31.43; 95% confidence interval, 3.41-289.58; P < 0.002), and was superior to NIHSS, NECT and CTA. No significant differences in ASPECT scores were found for the prediction of vessel recanalization. ASPECT score applied to PCT maps in acute stroke patients predicts the clinical outcome of intravenous thrombolysis and is superior to both early NECT and clinical parameters. (orig.)

  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. 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

  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. 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.

  8. Clinical and Actuarial Prediction of Physical Violence in a Forensic Intellectual Disability Hospital: A Longitudinal Study

    Science.gov (United States)

    McMillan, Dean; Hastings, Richard P.; Coldwell, Jon

    2004-01-01

    Background: There is a high rate of physical violence in populations with intellectual disabilities, and this has been linked to problems for the victim, the assailant, members of staff and services. Despite the clinical significance of this behaviour, few studies have assessed methods of predicting its occurrence. The present study examined…

  9. 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. Patie...

  10. Clinical implementation of dose-volume histogram predictions for organs-at-risk in IMRT planning

    International Nuclear Information System (INIS)

    True quality control (QC) of the planning process requires quantitative assessments of treatment plan quality itself, and QC in IMRT has been stymied by intra-patient anatomical variability and inherently complex three-dimensional dose distributions. In this work we describe the development of an automated system to reduce clinical IMRT planning variability and improve plan quality using mathematical models that predict achievable OAR DVHs based on individual patient anatomy. These models rely on the correlation of expected dose to the minimum distance from a voxel to the PTV surface, whereby a three-parameter probability distribution function (PDF) was used to model iso-distance OAR subvolume dose distributions. DVH models were obtained by fitting the evolution of the PDF with distance. Initial validation on clinical cohorts of 40 prostate and 24 head-and-neck plans demonstrated highly accurate model-based predictions for achievable DVHs in rectum, bladder, and parotid glands. By quantifying the integrated difference between candidate DVHs and predicted DVHs, the models correctly identified plans with under-spared OARs, validated by replanning all cases and correlating any realized improvements against the predicted gains. Clinical implementation of these predictive models was demonstrated in the PINNACLE treatment planning system by use of existing margin expansion utilities and the scripting functionality inherent to the system. To maintain independence from specific planning software, a system was developed in MATLAB to directly process DICOM-RT data. Both model training and patient-specific analyses were demonstrated with significant computational accelerations from parallelization.

  11. Clinical implementation of dose-volume histogram predictions for organs-at-risk in IMRT planning

    Science.gov (United States)

    Moore, K. L.; Appenzoller, L. M.; Tan, J.; Michalski, J. M.; Thorstad, W. L.; Mutic, S.

    2014-03-01

    True quality control (QC) of the planning process requires quantitative assessments of treatment plan quality itself, and QC in IMRT has been stymied by intra-patient anatomical variability and inherently complex three-dimensional dose distributions. In this work we describe the development of an automated system to reduce clinical IMRT planning variability and improve plan quality using mathematical models that predict achievable OAR DVHs based on individual patient anatomy. These models rely on the correlation of expected dose to the minimum distance from a voxel to the PTV surface, whereby a three-parameter probability distribution function (PDF) was used to model iso-distance OAR subvolume dose distributions. DVH models were obtained by fitting the evolution of the PDF with distance. Initial validation on clinical cohorts of 40 prostate and 24 head-and-neck plans demonstrated highly accurate model-based predictions for achievable DVHs in rectum, bladder, and parotid glands. By quantifying the integrated difference between candidate DVHs and predicted DVHs, the models correctly identified plans with under-spared OARs, validated by replanning all cases and correlating any realized improvements against the predicted gains. Clinical implementation of these predictive models was demonstrated in the PINNACLE treatment planning system by use of existing margin expansion utilities and the scripting functionality inherent to the system. To maintain independence from specific planning software, a system was developed in MATLAB to directly process DICOM-RT data. Both model training and patient-specific analyses were demonstrated with significant computational accelerations from parallelization.

  12. 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

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

    OpenAIRE

    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-identification must be executed properly to ensure the elimination of identifying patient data within the DICOM header. From this, several issues arise when dealing with this data sharing and de-identi...

  14. 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...

  15. 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.

  16. 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

  17. 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

  18. 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

  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. 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......, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the...... that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors....

  1. Method for evaluation of predictive models of microwave ablation via post-procedural clinical imaging

    Science.gov (United States)

    Collins, Jarrod A.; Brown, Daniel; Kingham, T. Peter; Jarnagin, William R.; Miga, Michael I.; Clements, Logan W.

    2015-03-01

    Development of a clinically accurate predictive model of microwave ablation (MWA) procedures would represent a significant advancement and facilitate an implementation of patient-specific treatment planning to achieve optimal probe placement and ablation outcomes. While studies have been performed to evaluate predictive models of MWA, the ability to quantify the performance of predictive models via clinical data has been limited to comparing geometric measurements of the predicted and actual ablation zones. The accuracy of placement, as determined by the degree of spatial overlap between ablation zones, has not been achieved. In order to overcome this limitation, a method of evaluation is proposed where the actual location of the MWA antenna is tracked and recorded during the procedure via a surgical navigation system. Predictive models of the MWA are then computed using the known position of the antenna within the preoperative image space. Two different predictive MWA models were used for the preliminary evaluation of the proposed method: (1) a geometric model based on the labeling associated with the ablation antenna and (2) a 3-D finite element method based computational model of MWA using COMSOL. Given the follow-up tomographic images that are acquired at approximately 30 days after the procedure, a 3-D surface model of the necrotic zone was generated to represent the true ablation zone. A quantification of the overlap between the predicted ablation zones and the true ablation zone was performed after a rigid registration was computed between the pre- and post-procedural tomograms. While both model show significant overlap with the true ablation zone, these preliminary results suggest a slightly higher degree of overlap with the geometric model.

  2. Effective feature selection of clinical and genetic to predict warfarin dose using artificial neural network

    OpenAIRE

    Mohammad Karim Sohrabi; Alireza Tajik

    2016-01-01

    Background: Warfarin is one of the most common oral anticoagulant, which role is to prevent the clots. The dose of this medicine is very important because changes can be dangerous for patients. Diagnosis is difficult for physicians because increase and decrease in use of warfarin is so dangerous for patients. Identifying the clinical and genetic features involved in determining dose could be useful to predict using data mining techniques. The aim of this paper is to provide a convenient way t...

  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. 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 ...

  5. A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

    International Nuclear Information System (INIS)

    Purpose: To develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic. Methods and Materials: Sixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model. Results: Six prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS ≤13 (n=133); 67%, 41%, and 20% for patients with SPS 14-19 (n=129); and 36%, 18%, and 4% for patients with SPS ≥20 (n=133) (p<0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (≤3 risk factors) (n=98); 68%, 47%, and 24% (4 risk factors) (n=117); and 46%, 24%, and 11% (≥5 factors) (n=180) (p<0.0001). Conclusion: Clinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use

  6. 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.

  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. 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

  9. 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.

  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. 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.

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

    International Nuclear Information System (INIS)

    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

  13. 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.

  14. Predicting the clinical effect of a short acting bronchodilator in individual patients using artificial neural networks.

    Science.gov (United States)

    de Matas, Marcel; Shao, Qun; Biddiscombe, Martyn F; Meah, Sally; Chrystyn, Henry; Usmani, Omar S

    2010-12-23

    Artificial neural networks were used in this study to model the relationships between in vitro data, subject characteristics and in vivo outcomes from N=18 mild-moderate asthmatics receiving monodisperse salbutamol sulphate aerosols of 1.5, 3 and 6 μm mass median aerodynamic diameter in a cumulative dosing schedule of 10, 20, 40 and 100 μg. Input variables to the model were aerodynamic particle size (APS), body surface area (BSA), age, pre-treatment forced expiratory volume in one-second (FEV(1)), forced vital capacity, cumulative emitted drug dose and bronchodilator reversibility to a standard salbutamol sulphate 200 μg dose MDI (REV(%)). These factors were used by the model to predict the bronchodilator response at 10 (T10) and 20 (T20) min after receiving each of the 4 doses for each of the 3 different particle sizes. Predictability was assessed using data from selected patients in this study, which were set aside and not used in model generation. Models reliably predicted ΔFEV(1)(%) in individual subjects with non-linear determinants (R(2)) of ≥ 0.8. The average error between predicted and observed ΔFEV(1)(%) for individual subjects was <4% across the cumulative dosing regimen. Increases in APS and drug dose gave improved ΔFEV(1)(%). Models also showed trends towards improved responses in younger patients and those having greater REV(%), whilst BSA was also shown to influence clinical effect. These data show that APS can be used to discriminate predictably between aerosols giving different bronchodilator responses across a cumulative dosing schedule, whilst patient characteristics can be used to reliably estimate clinical response in individual subjects. PMID:20932900

  15. Artificial neural networks based early clinical prediction of mortality after spontaneous intracerebral hemorrhage.

    Science.gov (United States)

    Lukić, Stevo; Ćojbasić, Žarko; Perić, Zoran; Milošević, Zoran; Spasić, Mirjana; Pavlović, Vukašin; Milojević, Andrija

    2012-12-01

    Numerous outcome prediction models have been developed for mortality and functional outcome after spontaneous intracerebral haemorrhage (ICH). However, no outcome prediction model for ICH has considered the impact of care restriction. To develop and compare results of the artificial neural networks (ANN) and logistic regression (LR) models, based on initial clinical parameters, for prediction of mortality after spontaneous ICH. Analysis has been conducted on consecutive dataset of patients with spontaneous ICH, over 5-year period in tertiary care academic hospital. Patients older than 18 years were eligible for inclusion if they had been presented within 6 h from the start of symptoms and had evidence of spontaneous supratentorial ICH on initial brain computed tomography within 24 h. Initial clinical parameters have been used to develop LR and ANN prediction models for hospital mortality as outcome measure. Models have been accessed for discrimination and calibration abilities. We have analyzed 411 patients (199 males and 212 females) with spontaneous ICH, medically treated and not withdrawn from therapy, with average age of 67.35 years. From them, 256 (62.29%) patients died during hospital treatment and 155 (37.71%) patients survived. In the observed dataset, ANN model overall correctly classified outcome in 93.55% of patients, compared with 79.32% of correct classification for the LR model. Discrimination and calibration parameters indicate that both models show an adequate fit of expected and observed values, with superiority of ANN model. Our results favour the ANN model for prediction of mortality after spontaneous ICH. Further studies of the strengths and limitations of this method are needed with larger prospective samples. PMID:22674031

  16. Clinical utility of polymorphisms in one-carbon metabolism for breast cancer risk prediction

    Directory of Open Access Journals (Sweden)

    Shaik Mohammad Naushad

    2011-01-01

    Full Text Available This study addresses the issues in translating the laboratory derived data obtained during discovery phase of research to a clinical setting using a breast cancer model. Laboratory-based risk assessment indi-cated that a family history of breast cancer, reduced folate carrier 1 (RFC1 G80A, thymidylate synthase (TYMS 5’-UTR 28bp tandem repeat, methylene tetrahydrofolate reductase (MTHFR C677T and catecholamine-O-methyl transferase (COMT genetic polymorphisms in one-carbon metabolic pathway increase the risk for breast cancer. Glutamate carboxypeptidase II (GCPII C1561T and cytosolic serine hydroxymethyl transferase (cSHMT C1420T polymorphisms were found to decrease breast cancer risk. In order to test the clinical validity of this information in the risk prediction of breast cancer, data was stratified based on number of protective alleles into four categories and in each category sensitivity and 1-specificity values were obtained based on the distribution of number of risk alleles in cases and controls. Receiver operating characteristic (ROC curves were plotted and the area under ROC curve (C was used as a measure of discriminatory ability between cases and controls. In subjects without any protective allele, aberrations in one-carbon metabolism showed perfect prediction (C=0.93 while the predictability was lost in subjects with one protective allele (C=0.60. However, predictability increased steadily with increasing number of protective alleles (C=0.63 for 2 protective alleles and C=0.71 for 3 protective alleles. The cut-off point for discrimination was >4 alleles in all predictable combinations. Models of this kind can serve as valuable tools in translational re-search, especially in identifying high-risk individuals and reducing the disease risk either by life style modification or by medical intervention.

  17. 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.

  18. 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.

  19. Quantitative prediction and clinical evaluation of an unexplored herb-drug interaction mechanism in healthy volunteers.

    Science.gov (United States)

    Gufford, B T; Barr, J T; González-Pérez, V; Layton, M E; White, J R; Oberlies, N H; Paine, M F

    2015-12-01

    Quantitative prediction of herb-drug interaction risk remains challenging. A quantitative framework to assess a potential interaction was used to evaluate a mechanism not previously tested in humans. The semipurified milk thistle product, silibinin, was selected as an exemplar herbal product inhibitor of raloxifene intestinal glucuronidation. Physiologically based pharmacokinetic (PBPK) model simulations of the silibinin-raloxifene interaction predicted up to 30% increases in raloxifene area under the curve (AUC0-inf) and maximal concentration (Cmax). Model-informed clinical evaluation of the silibinin-raloxifene interaction indicated minimal clinical interaction liability, with observed geometric mean raloxifene AUC0-inf and Cmax ratios lying within the predefined no effect range (0.75-1.33). Further refinement of PBPK modeling and simulation approaches will enhance confidence in predictions and facilitate generalizability to additional herb-drug combinations. This quantitative framework can be used to develop guidances to evaluate potential herb-drug interactions prospectively, providing evidenced-based information about the risk or safety of these interactions. PMID:26904384

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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)

  7. 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.

  8. Association Rule Mining and Classifier Approach for 48-Hour Rainfall Prediction Over Cuddalore Station of East Coast of India

    OpenAIRE

    S. Meganathan; T.R. Sivaramakrishnan

    2013-01-01

    The methodology of data mining techniques has been presented for the rain forecasting models for the Cuddalore (11°43′ N/79°49′ E) station of Tamilnadu in East Coast of India. Data mining approaches like classification and association mining was applied to generate results for rain prediction before 48 hour of the actual occurrence of the rain. The objective of this study is to demonstrate what relationship models are there between various atmospheric variables and to interconnect these varia...

  9. Lipocalin-2 as an Infection-Related Biomarker to Predict Clinical Outcome in Ischemic Stroke

    Science.gov (United States)

    Hochmeister, Sonja; Engel, Odilo; Adzemovic, Milena Z.; Pekar, Thomas; Kendlbacher, Paul; Zeitelhofer, Manuel; Haindl, Michaela; Meisel, Andreas; Fazekas, Franz; Seifert-Held, Thomas

    2016-01-01

    Objectives From previous data in animal models of cerebral ischemia, lipocalin-2 (LCN2), a protein related to neutrophil function and cellular iron homeostasis, is supposed to have a value as a biomarker in ischemic stroke patients. Therefore, we examined LCN2 expression in the ischemic brain in an animal model and measured plasma levels of LCN2 in ischemic stroke patients. Methods In the mouse model of transient middle cerebral artery occlusion (tMCAO), LCN2 expression in the brain was analyzed by immunohistochemistry and correlated to cellular nonheme iron deposition up to 42 days after tMCAO. In human stroke patients, plasma levels of LCN2 were determined one week after ischemic stroke. In addition to established predictive parameters such as age, National Institutes of Health Stroke Scale and thrombolytic therapy, LCN2 was included into linear logistic regression modeling to predict clinical outcome at 90 days after stroke. Results Immunohistochemistry revealed expression of LCN2 in the mouse brain already at one day following tMCAO, and the amount of LCN2 subsequently increased with a maximum at 2 weeks after tMCAO. Accumulation of cellular nonheme iron was detectable one week post tMCAO and continued to increase. In ischemic stroke patients, higher plasma levels of LCN2 were associated with a worse clinical outcome at 90 days and with the occurrence of post-stroke infections. Conclusions LCN2 is expressed in the ischemic brain after temporary experimental ischemia and paralleled by the accumulation of cellular nonheme iron. Plasma levels of LCN2 measured in patients one week after ischemic stroke contribute to the prediction of clinical outcome at 90 days and reflect the systemic response to post-stroke infections. PMID:27152948

  10. 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

  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. Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer’s Disease Progression

    Science.gov (United States)

    Chen, Xueqi; Zhou, Yun; Wang, Rongfu; Cao, Haoyin; Reid, Savina; Gao, Rui; Han, Dong

    2016-01-01

    Objective To evaluate the potential clinical value of quantitative functional FDG PET and pathological amyloid-β PET with cerebrospinal fluid (CSF) biomarkers and clinical assessments in the prediction of Alzheimer’s disease (AD) progression. Methods We studied 82 subjects for up to 96 months (median = 84 months) in a longitudinal Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. All preprocessed PET images were spatially normalized to standard Montreal Neurologic Institute space. Regions of interest (ROI) were defined on MRI template, and standard uptake values ratios (SUVRs) to the cerebellum for FDG and amyloid-β PET were calculated. Predictive values of single and multiparametric PET biomarkers with and without clinical assessments and CSF biomarkers for AD progression were evaluated using receiver operating characteristic (ROC) analysis and logistic regression model. Results The posterior precuneus and cingulate SUVRs were identified for both FDG and amyloid-β PET in predicating progression in normal controls (NCs) and subjects with mild cognitive impairment (MCI). FDG parietal and lateral temporal SUVRs were suggested for monitoring NCs and MCI group progression, respectively. 18F-AV45 global cortex attained (78.6%, 74.5%, 75.4%) (sensitivity, specificity, accuracy) in predicting NC progression, which is comparable to the 11C-PiB global cortex SUVR’s in predicting MCI to AD. A logistic regression model to combine FDG parietal and posterior precuneus SUVR and Alzheimer’s Disease Assessment Scale-Cognitive (ADAS-Cog) Total Mod was identified in predicating NC progression with (80.0%, 94.9%, 93.9%) (sensitivity, specificity, accuracy). The selected model including FDG posterior cingulate SUVR, ADAS-Cog Total Mod, and Mini-Mental State Exam (MMSE) scores for predicating MCI to AD attained (96.4%, 81.2%, 83.6%) (sensitivity, specificity, accuracy). 11C-PiB medial temporal SUVR with MMSE significantly increased 11C-PiB PET AUC to 0.915 (p<0

  13. 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

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

    International Nuclear Information System (INIS)

    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. Conclusions: There is a lack of correlation between

  15. 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

  16. 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...

  17. Association Rule Mining and Classifier Approach for 48-Hour Rainfall Prediction Over Cuddalore Station of East Coast of India

    Directory of Open Access Journals (Sweden)

    S. Meganathan

    2013-04-01

    Full Text Available The methodology of data mining techniques has been presented for the rain forecasting models for the Cuddalore (11°43′ N/79°49′ E station of Tamilnadu in East Coast of India. Data mining approaches like classification and association mining was applied to generate results for rain prediction before 48 hour of the actual occurrence of the rain. The objective of this study is to demonstrate what relationship models are there between various atmospheric variables and to interconnect these variables according to the pattern obtained out of data mining technique. Using this approach rainfall estimates can be obtained to support the decisions to launch cloud-seeding operations. There are 3 main parts in this study. First, the obtained raw data was filtered using discretization approach based on the best fit ranges. Then, association mining has been performed on it using Predictive Apriori algorithm. Thirdly, the data has been validated using K* classifier approach. Results show that the overall classification accuracy of the data mining technique is satisfactory

  18. 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.

  19. 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...

  20. 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...

  1. 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

  2. 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

  3. 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. PMID:24891572

  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. Expression profiling to predict the clinical behaviour of ovarian cancer fails independent evaluation

    International Nuclear Information System (INIS)

    In a previously published pilot study we explored the performance of microarrays in predicting clinical behaviour of ovarian tumours. For this purpose we performed microarray analysis on 20 patients and estimated that we could predict advanced stage disease with 100% accuracy and the response to platin-based chemotherapy with 76.92% accuracy using leave-one-out cross validation techniques in combination with Least Squares Support Vector Machines (LS-SVMs). In the current study we evaluate whether tumour characteristics in an independent set of 49 patients can be predicted using the pilot data set with principal component analysis or LS-SVMs. The results of the principal component analysis suggest that the gene expression data from stage I, platin-sensitive advanced stage and platin-resistant advanced stage tumours in the independent data set did not correspond to their respective classes in the pilot study. Additionally, LS-SVM models built using the data from the pilot study – although they only misclassified one of four stage I tumours and correctly classified all 45 advanced stage tumours – were not able to predict resistance to platin-based chemotherapy. Furthermore, models based on the pilot data and on previously published gene sets related to ovarian cancer outcomes, did not perform significantly better than our models. We discuss possible reasons for failure of the model for predicting response to platin-based chemotherapy and conclude that existing results based on gene expression patterns of ovarian tumours need to be thoroughly scrutinized before these results can be accepted to reflect the true performance of microarray technology

  6. 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...

  7. Return to work in a cohort of low back pain patients: development and validation of a clinical prediction rule

    OpenAIRE

    Heymans, M.W.; Anema, J.R.; Buuren, van, S.; Knol, D. L.; Mechelen, Van; Vet, van der, Paul E.

    2009-01-01

    BACKGROUND: From the viewpoint of cost prevention, it is necessary to identify patients that are of high risk for long-term work disability, production loss and sick-leave. METHODS: Secondary data analysis in a cohort of 628 workers on sick-leave between 3 and 6 weeks due to low back pain (LBP). The association of a broad set of demographic, work, LBP and psychosocial related factors on lasting return to work was studied using Cox regression analysis with backward selection. The most relevant...

  8. 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...

  9. 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.

  10. 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

  11. Clinical Dementia Rating Performed Several Years prior to Death Predicts Regional Alzheimer’s Neuropathology

    Science.gov (United States)

    Beeri, Michal Schnaider; Silverman, Jeremy M.; Schmeidler, James; Wysocki, Michael; Grossman, Hillel Z.; Purohit, Dushyant P.; Perl, Daniel P.; Haroutunian, Vahram

    2011-01-01

    Aims To assess the relationships between early and late antemortem measures of dementia severity and Alzheimer disease (AD) neuropathology severity. Methods 40 residents of a nursing home, average age at death 82.0, participated in this longitudinal cohort study with postmortem assessment. Severity of dementia was measured by Clinical Dementia Rating (CDR) at two time points, averaging 4.5 and 1.0 years before death. Densities of postmortem neuritic plaques (NPs) and neurofibrillary tangles (NFTs) were measured in the cerebral cortex, hippocampus, and entorhinal cortex. Results For most brain areas, both early and late CDRs were significantly associated with NPs and NFTs. CDRs assessed proximal to death predicted NFTs beyond the contribution of early CDRs. NPs were predicted by both early and late CDRs. NPs were predictive of both early and late CDRs after controlling for NFTs. NFTs were only associated significantly with late CDR in the cerebral cortex after controlling for NPs. Conclusions Even if assessed several years before death, dementia severity is associated with AD neuropathology. NPs are more strongly associated with dementia severity than NFTs. NFTs consistently associate better with late than early CDR, suggesting that these neuropathological changes may occur relatively later in the course of the disease. PMID:18367838

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

    Energy Technology Data Exchange (ETDEWEB)

    Mortimer, A.M., E-mail: alex_mortimer@hotmail.co [Severn School of Radiology, Bristol (United Kingdom); Department of Radiology, Great Western Hospital, Swindon (United Kingdom); Saunders, T.; Cook, J.-L. [Department of Radiology, Great Western Hospital, Swindon (United Kingdom)

    2011-06-15

    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.

  13. 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.

  14. 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

  15. Tissue spectrophotometry and thermographic imaging applied to routine clinical prediction of amputation level viability

    Science.gov (United States)

    Hanson, Jon M.; Harrison, David K.; Hawthorn, Ian E.

    2002-06-01

    About 5% of British males over 50 years develop peripheral arterial occlusive disease. Of these about 2% ultimately require lower limb amputation. In 1995 we proposed a new technique using lightguide spectrophotometry to measure the oxygen saturation level of haemoglobin (SO2) in the skin as a method for predicting tissue viability. This technique, in combination with thermographic imaging, was compared with skin blood flow measurements using the I125)4- Iodoantipyrine (IAP) clearance technique. The optical techniques gave a sensitivity and selectivity of 1.0 for the prediction of successful outcome of a below knee amputation compared with a specificity of 93% using the traditional IAP technique at a below knee to above knee amputation ratio (BKA:AKA) of 75%. The present study assesses the routine clinical application of these optical techniques. The study is ongoing, but the data to date comprises 22 patients. 4 patients were recommended for above knee amputation (AKA) and 18 patients for below knee amputation on the basis of thermographic and tissue SO2 measurements. All but one of the predicted BKA amputations healed. The study to date produces evidence of 94% healing rate (specificity) for a BKA:AKA ratio of 82%. This compares favorably with the previous figures given above.

  16. 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.

  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. 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...

  19. Etiologies of acute undifferentiated fever and clinical prediction of scrub typhus in a non-tropical endemic area.

    Science.gov (United States)

    Jung, Ho-Chul; Chon, Sung-Bin; Oh, Won Sup; Lee, Dong-Hyun; Lee, Ho-Jin

    2015-02-01

    Scrub typhus usually presents as acute undifferentiated fever. This cross-sectional study included adult patients presenting with acute undifferentiated fever defined as any febrile illness for ≤ 14 days without evidence of localized infection. Scrub typhus cases were defined by an antibody titer of a ≥ fourfold increase in paired sera, a ≥ 1:160 in a single serum using indirect immunofluorescence assay, or a positive result of the immunochromatographic test. Multiple regression analysis identified predictors associated with scrub typhus to develop a prediction rule. Of 250 cases with known etiology of acute undifferentiated fever, influenza (28.0%), hepatitis A (25.2%), and scrub typhus (16.4%) were major causes. A prediction rule for identifying suspected cases of scrub typhus consisted of age ≥ 65 years (two points), recent fieldwork/outdoor activities (one point), onset of illness during an outbreak period (two points), myalgia (one point), and eschar (two points). The c statistic was 0.977 (95% confidence interval = 0.960-0.994). At a cutoff value ≥ 4, the sensitivity and specificity were 92.7% (79.0-98.1%) and 90.9% (86.0-94.3%), respectively. Scrub typhus, the third leading cause of acute undifferentiated fever in our region, can be identified early using the prediction rule. PMID:25448236

  20. Can outpatient non-attendance be predicted from the referral letter? An audit of default at neurology clinics.

    OpenAIRE

    Dickey, W; Morrow, J I

    1991-01-01

    Data obtained from new patient referral letters to regional and peripheral neurology clinics were studied prospectively over a 6-month period in an attempt to determine factors predicting non-attendance. Attendance at peripheral clinics was significantly better, confirming their value. At regional clinics, factors associated with non-attendance were male sex, patient age less than 50 years, urban home address, referral from Accident and Emergency Departments, symptom duration less than 12 mon...

  1. 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...

  2. 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

  3. 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

  4. 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

  5. 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.

  6. Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach.

    Science.gov (United States)

    Niculescu, A B; Levey, D F; Phalen, P L; Le-Niculescu, H; Dainton, H D; Jain, N; Belanger, E; James, A; George, S; Weber, H; Graham, D L; Schweitzer, R; Ladd, T B; Learman, R; Niculescu, E M; Vanipenta, N P; Khan, F N; Mullen, J; Shankar, G; Cook, S; Humbert, C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R

    2015-11-01

    biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would

  7. 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

  8. 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

  9. Predictable risk factors and clinical courses for prolonged transient tachypnea of the newborn

    Directory of Open Access Journals (Sweden)

    Ji Young Chang

    2010-03-01

    Full Text Available Purpose : Transient tachypnea of the newborn (TTN is usually benign and improves within 72 hours. However, it can also progress to prolonged tachypnea over 72 hours, profound hypoxemia, respiratory failure, and even death. The aim of this study is to find predictable risk factors and describe the clinical courses and outcomes of prolonged TTN (PTTN. Methods : The medical records of 107 newborns, &gt;35+0 weeks of gestational age with TTN, who were admitted to the NICU at Seoul Asan Medical Center from January 2001 to September 2007 were reviewed. They were divided into 2 groups based on duration of tachypnea. PTTN was defined as tachypnea ?#247;2 hours of age, and simple TTN (STTN as tachypnea &lt;72 hours of age. We randomly selected 126 healthy-term newborns as controls. We evaluated neonatal and maternal demographic findings, and various clinical factors. Results : Fifty-five infants (51% with total TTN were PTTN. PTTN infants had grunting, tachypnea &gt;90/min, FiO2 &gt;0.4, and required ventilator care more frequently than STTN infants. PTTN had lower level of serum total protein and albumin than STTN. The independent predictable risk factors for PTTN were grunting, maximal respiration rate &gt;90/min, and FiO2 &gt;0.4 within 6 hours of life. Conclusion : When a newborn has grunting, respiration rate &gt;90/min, and oxygen requirement &gt;0.4 of FiO2 within 6 hours of life, the infant is at high risk of having persistent tachypnea ?#247;2 hours. We need further study to find the way to reduce PTTN.

  10. Tax Rules

    OpenAIRE

    Gersbach, Hans; Hahn, Volker; Imhof, Stephan

    2010-01-01

    We examine the provision of public projects under tax and subsidy rules. We find that tax rules separated from project cum subsidy decisions exhibit several advantages when incentive problems of the agenda-setter are taken into account. In particular, tax rules may prevent the proposal of inefficient projects that benefit only a small lobby group. We propose “redistribution efficiency” as a socially desirable property of proposals and find that tax rules always guarantee this kind of efficien...

  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. Predicting loss of employment over three years in multiple sclerosis: clinically meaningful cognitive decline.

    Science.gov (United States)

    Morrow, Sarah A; Drake, Allison; Zivadinov, Robert; Munschauer, Frederick; Weinstock-Guttman, Bianca; Benedict, Ralph H B

    2010-10-01

    Cognitive dysfunction is common in multiple sclerosis (MS), yet the magnitude of change on objective neuropsychological (NP) tests that is clinically meaningful is unclear. We endeavored to determine NP markers of the transition from employment to work disability in MS, as indicated by degree of decline on individual tests. Participants were 97 employed MS patients followed over 41.3 ± 17.6 months with a NP battery covering six domains of cognitive function. Deterioration at follow-up was designated as documented and paid disability benefits (conservative definition) or a reduction in hours/work responsibilities (liberal definition). Using the conservative definition, 28.9% reported deteriorated employment status and for the liberal definition, 45.4%. The Symbol Digit Modalities Test (SDMT) and California Verbal Learning Test, Total Learning (CVLT2-TL) measures distinguished employed and disabled patients at follow-up. Controlling for demographic and MS characteristics, the odds ratio of a deterioration based on a change of 2.0 on the CVLT2-TL was 3.7 (95% CI 1.2-11.4 and SDMT by 4.0 was 4.2 (95% CI 1.2-14.8), accounting for 86.7% of the area under the ROC curve. We conclude that decline on NP testing over time is predictive of deterioration in vocational status, establishing a magnitude of decline on NP tests that is clinically meaningful. PMID:20830649

  13. 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.)

  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. Early treatment response predicted subsequent clinical response in patients with schizophrenia taking paliperidone extended-release.

    Science.gov (United States)

    Yeh, En-Chi; Huang, Ming-Chyi; Tsai, Chang-Jer; Chen, Chun-Tse; Chen, Kuan-Yu; Chiu, Chih-Chiang

    2015-11-30

    This 6-week open-labeled study investigated whether early treatment response in patients receiving paliperidone extended-release (paliperidone ER) can facilitate prediction of responses at Week 6. Patients with schizophrenia or schizoaffective disorder were administered 9mg/day of paliperidone ER during the first 2 weeks, after which the dose was adjusted clinically. They were assessed on Days 0, 4, 7, 14, 28, and 42 by the Positive and Negative Syndrome Scale (PANSS). The serum concentrations of 9-hydroxyrisperidone were examined on Days 14 and 42. Among the 41 patients enrolled, 26 were classified as responders (≧50% improvement on total PANSS scores at Week 6). In the receiver-operator curves (ROC) analyses, the changes in total PANSS scores at Week 2 appeared to show more accurate predictability compared to Day 4 and Day 7. At Week 6, no significant correlation was observed between blood 9-hydroxyrisperidone concentration and the total score or changes of PANSS scores. The results suggest that early treatment response to paliperidone ER, particularly at Week 2, can serve as a suitable outcome predictor at Week 6. Using 9mg/day paliperidone ER as an initial dose for schizophrenia treatment exhibited relatively favorable tolerability and feasibility. PMID:26319696

  16. 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.)

  17. 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

  18. Biochemical recurrence and survival prediction models for the management of clinically localized prostate cancer.

    Science.gov (United States)

    Tewari, Ashuthosh; Gamito, Eduard J; Crawford, E David; Menon, Mani

    2004-03-01

    A number of new predictive modeling techniques have emerged in the past several years. These methods, which have been developed in fields such as artificial intelligence research, engineering, and meteorology, are now being applied to problems in medicine with promising results. This review outlines our recent work with use of selected advanced techniques such as artificial neural networks, genetic algorithms, and propensity scoring to develop useful models for estimating the risk of biochemical recurrence and long-term survival in men with clinically localized prostate cancer. In addition, we include a description of our efforts to develop a comprehensive prostate cancer database that, along with these novel modeling techniques, provides a powerful research tool that allows for the stratification of risk for treatment failure and survival by such factors as age, race, and comorbidities. Clinical and pathologic data from 1400 patients were used to develop the biochemical recurrence model. The area under the receiver operating characteristic curve for this model was 0.83, with a sensitivity of 85% and specificity of 74%. For the survival model, data from 6149 men were used. Our analysis indicated that age, income, and comorbidities had a statistically significant impact on survival. The effect of race did not reach statistical significance in this regard. The C index value for the model was 0.69 for overall survival. We conclude that these methods, along with a comprehensive database, allow for the development of models that provide estimates of treatment failure risk and survival probability that are more meaningful and clinically useful than those previously developed. PMID:15072605

  19. Human leukocyte antigen-G overexpression predicts poor clinical outcomes in low-grade gliomas.

    Science.gov (United States)

    Fan, Xing; Wang, Yinyan; Zhang, Chuanbao; Liu, Xing; Qian, Zenghui; Jiang, Tao

    2016-05-15

    Overexpression of human leukocyte antigen-G (HLA-G), a non-classical major histocompatibility complex class-I molecule associated with immunosuppression, has been reported in various human malignancies. In the present study, we examined the role of HLA-G in gliomas. Clinical characteristics, mRNA expression microarrays and follow-up data pertaining to 293 patients with histologically confirmed gliomas were analyzed. The expression levels of HLA-G were compared between different grades of gliomas and correlated with progression-free survival (PFS) and overall survival (OS) to evaluate its prognostic value. We found that HLA-G was overexpressed in gliomas as compared to that in normal brain tissue samples (-1.288±0.265). The highest expression levels were in glioblastomas (GBMs), anaplastic gliomas (AGs) and low-grade gliomas (LGGs), in that order (0.328±0.778, 0.176±0.881, -0.388±0.686, respectively). Significant inter-group differences were observed between low-grade and high-grade glioma tissues (pexpression as compared to other LGG patients (p=0.004, Chi-square test). Significant differences were observed with respect to PFS and OS (p=0.009 and 0.032, log-rank test, for PFS and OS, respectively) between the high- and low-expression subgroups in patients with LGGs. On Cox regression analysis, overexpression of HLA-G appeared to be an independent predictor of clinical outcomes (p=0.007 and 0.026, for PFS and OS, respectively). Our results suggest that HLA-G expression may serve as a potential biomarker for predicting aggressive tumor grades of gliomas and for histological subtype of LGGs. Elevated HLA-G expression could serve as an independent predictor of poor clinical outcomes in patients with low-grade gliomas. PMID:27138095

  20. Clinical features, predictive factors and outcome of hyperglycaemic emergencies in a developing country

    Directory of Open Access Journals (Sweden)

    Unachukwu Chioma

    2009-03-01

    Full Text Available Abstract Background Hyperglycaemic emergencies are common acute complications of diabetes mellitus (DM but unfortunately, there is a dearth of published data on this entity from Nigeria. This study attempts to describe the clinical and laboratory scenario associated with this complication of DM. Methods This study was carried out in DM patients who presented to an urban hospital in Nigeria with hyperglycaemic emergencies (HEs. The information extracted included biodata, laboratory data and hospitalization outcome. Outcome measures included mortality rates, case fatality rates and predictive factors for HEs mortality. Statistical tests used are χ2, Student's t test and logistic regression. Results A total of 111 subjects with HEs were recruited for the study. Diabetes ketoacidosis (DKA and hyperosomolar hyperglycaemic state (HHS accounted for 94 (85% and 17 (15% respectively of the HEs. The mean age (SD of the subjects was 53.9 (14.4 years and their ages ranged from 22 to 86 years. DKA occurred in all subjects with type 1 DM and 73 (81% of subjects with type 2 DM. The presence of HSS was noted in 17 (19% of the subjects with type 2 DM. Hypokalaemia (HK was documented in 41 (37% of the study subjects. Elevated urea levels and hyponatraemia were noted more in subjects with DKA than in those subjects with HHS (57.5%,19% vs 53%,18%. The mortality rate for HEs in this report is 20% and the case fatality rates for DKA and HHS are 18% and 35% respectively. The predictive factors for HEs mortality include, sepsis, foot ulceration, previously undetected DM, hypokalaemia and being elderly. Conclusion HHS carry a higher case fatality rate than DKA and the predictive factors for hyperglycaemic emergencies' mortality in the Nigerian with DM include foot ulcers, hypokalaemia and being elderly.

  1. 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

  2. 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

  3. 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

  4. Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models.

    Science.gov (United States)

    Garibaldi, Jonathan M; Zhou, Shang-Ming; Wang, Xiao-Ying; John, Robert I; Ellis, Ian O

    2012-06-01

    It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variability when making difficult decisions. In contrast, the vast majority of computerized models that aim to provide automated support for such decisions do not explicitly recognize or replicate this variability. Furthermore, the perfect consistency of computerized models is often presented as a de facto benefit. In this paper, we describe a novel approach to incorporate variability within a fuzzy inference system using non-stationary fuzzy sets in order to replicate human variability. We apply our approach to a decision problem concerning the recommendation of post-operative breast cancer treatment; specifically, whether or not to administer chemotherapy based on assessment of five clinical variables: NPI (the Nottingham Prognostic Index), estrogen receptor status, vascular invasion, age and lymph node status. In doing so, we explore whether such explicit modeling of variability provides any performance advantage over a more conventional fuzzy approach, when tested on a set of 1310 unselected cases collected over a fourteen year period at the Nottingham University Hospitals NHS Trust, UK. The experimental results show that the standard fuzzy inference system (that does not model variability) achieves overall agreement to clinical practice around 84.6% (95% CI: 84.1-84.9%), while the non-stationary fuzzy model can significantly increase performance to around 88.1% (95% CI: 88.0-88.2%), pdecision support systems in any application domain. PMID:22265814

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Risk factor model to predict a missed clinic appointment in an urban, academic, and underserved setting.

    Science.gov (United States)

    Torres, Orlando; Rothberg, Michael B; Garb, Jane; Ogunneye, Owolabi; Onyema, Judepatricks; Higgins, Thomas

    2015-04-01

    In the chronic care model, a missed appointment decreases continuity, adversely affects practice efficiency, and can harm quality of care. The aim of this study was to identify predictors of a missed appointment and develop a model to predict an individual's likelihood of missing an appointment. The research team performed a retrospective study in an urban, academic, underserved outpatient internal medicine clinic from January 2008 to June 2011. A missed appointment was defined as either a "no-show" or cancellation within 24 hours of the appointment time. Both patient and visit variables were considered. The patient population was randomly divided into derivation and validation sets (70/30). A logistic model from the derivation set was applied in the validation set. During the period of study, 11,546 patients generated 163,554 encounters; 45% of appointments in the derivation sample were missed. In the logistic model, percent previously missed appointments, wait time from booking to appointment, season, day of the week, provider type, and patient age, sex, and language proficiency were all associated with a missed appointment. The strongest predictors were percentage of previously missed appointments and wait time. Older age and non-English proficiency both decreased the likelihood of missing an appointment. In the validation set, the model had a c-statistic of 0.71, and showed no gross lack of fit (P=0.63), indicating acceptable calibration. A simple risk factor model can assist in predicting the likelihood that an individual patient will miss an appointment. PMID:25299396

  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. 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

  13. 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......, respectively, whereas quintiles 2-4 defined normal responders. All patients were assigned PREDICT score points in clinical categories (age > 65, reduced left ventricular function, reduced kidney function, acute coronary syndrome (ACS) and diabetes). We found an association between the cumulative number...

  14. The ability of synovitis to predict structural damage in rheumatoid arthritis: a comparative study between clinical examination and ultrasound

    OpenAIRE

    Dougados, Maxime; Devauchelle-Pensec, Valérie; Ferlet, Jean françois; Jousse-Joulin, Sandrine; D'Agostino, Maria-Antonietta; Backhaus, Marina; Bentin, Jacques; Chalès, Gérard; Chary-Valckenaere, Isabelle; Conaghan, Philip; Wakefield, Richard J; Etcheparre, Frédéric; Gaudin, Philippe; Grassi, Walter; van der Heijde, Désirée

    2012-01-01

    Objectives To evaluate synovitis (clinical vs ultrasound (US)) to predict structural progression in rheumatoid arthritis (RA). Methods Patients with RA. Study design Prospective, 2-year follow-up. Data collected Synovitis (32 joints (2 wrists, 10 metacarpophalangeal, 10 proximal interphalangeal, 10 metatarsophalangeal)) at baseline and after 4 months of therapy by clinical, US grey scale (GS-US) and power doppler (PD-US); x-rays at baseline and at year 2. Analysis Measures of association (OR)...

  15. 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...

  16. 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...

  17. Outcome Prediction in Pneumonia Induced ALI/ARDS by Clinical Features and Peptide Patterns of BALF Determined by Mass Spectrometry

    OpenAIRE

    Frenzel, Jochen; Gessner, Christian; Sandvoss, Torsten; Hammerschmidt, Stefan; Schellenberger, Wolfgang; Sack, Ulrich; Eschrich, Klaus; Wirtz, Hubert

    2011-01-01

    Background Peptide patterns of bronchoalveolar lavage fluid (BALF) were assumed to reflect the complex pathology of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) better than clinical and inflammatory parameters and may be superior for outcome prediction. Methodology/Principal Findings A training group of patients suffering from ALI/ARDS was compiled from equal numbers of survivors and nonsurvivors. Clinical history, ventilation parameters, Murray's lung injury severity sc...

  18. 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.

  19. 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 ...

  20. Discovery of predictive models in an injury surveillance database: an application of data mining in clinical research.

    OpenAIRE

    Holmes, J. H.; Durbin, D R; Winston, F. K.

    2000-01-01

    A new, evolutionary computation-based approach to discovering prediction models in surveillance data was developed and evaluated. This approach was operationalized in EpiCS, a type of learning classifier system specially adapted to model clinical data. In applying EpiCS to a large, prospective injury surveillance database, EpiCS was found to create accurate predictive models quickly that were highly robust, being able to classify > 99% of cases early during training. After training, EpiCS cla...

  1. 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...

  2. 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

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. Clinical Factors Predicting the Pathologic Tumor Response after Preoperative Concurrent Chemoradiotherapy for Rectal Cancer

    International Nuclear Information System (INIS)

    The objective of this retrospective study was to identify predictive factors for the complete pathologic response and tumor down staging after preoperative concurrent chemoradiotherapy for locally advanced rectal cancer. Materials and Methods: Between the years 2000 and 2008, 39 patients with newly diagnosed rectal cancer without prior evidence of distant metastasis received preoperative concurrent chemoradiotherapy followed by surgery. The median radiation dose was 50.4 Gy (range, 45-59.4 Gy). Thirty-eight patients received concurrent infusional 5-fluorouracil and leucovorin, while one patient received oral capecitabine twice daily during radiotherapy. Results: A complete pathologic response (CR) was demonstrated in 12 of 39 patients (31%), while T-downstaging was observed in 24 of 39 patients (63%). N-downstaging was observed in 18 of 28 patients (64%), with a positive node in the CT scan or ultrasound. Two patients with clinical negative nodes were observed in surgical specimens. The results from a univariate analysis indicated that the tumor circumferential extent was less than 50% (p=0.031). Moreover, the length of the tumor was less than 5 cm (p=0.004), while the post-treatment carcinoembryonic antigen (CEA) levels were less than or equal to 3.0 ng/mL (p=0.015) and were significantly associated with high pathologic CR rates. The univariate analysis also indicated that the adenocarcinoma (p=0.045) and radiation dose greater than or equal to 50 Gy (p=0.021) were significantly associated with high T-downstaging, while a radiotherapy duration of less than or equal to 42 days (p=0.018) was significantly associated with N-downstaging. The results from the multivariate analysis indicated that the lesser circumferential extent of the tumor (hazard ratio [HR], 0.150; p=0.028) and shorter tumor length (HR, 0.084; p=0.005) independently predicted a higher pathologic CR. The multivariate analysis also indicated that a higher radiation dose was significantly associated

  8. Clinical and pathologic factors predictive of biochemical control following post-prostatectomy irradiation

    International Nuclear Information System (INIS)

    Purpose/Objective: Indications for post-prostatectomy radiation therapy are not well defined. We reviewed our experience treating post-prostatectomy patients with external beam irradiation to assess clinical and pathologic factors predictive of biochemical control. Materials and Methods: Between 1/87 and 3/93, 61 patients received post-operative tumor bed irradiation with a median dose of 59.4 Gy (50.4 - 68 Gy). Median follow-up was 4.1 years (7.6 months - 8.3 years) from irradiation. Patients were treated for the following reasons: 1) adjuvantly, within 6 months of surgery for extracapsular extension, seminal vesicle involvement, or positive surgical margins (n=38); 2) persistently elevated PSA post-operatively (n=2); 3) rising PSA >6 months after surgery (n=9); and 4) biopsy proven local recurrence (n=12). No patients had known nodal or metastatic disease. All patients had post-radiation PSA data available. Biochemical control was the endpoint studied using Kaplan-Meier life table analysis. Biochemical control was defined as the ability to maintain an undetectable PSA (4 and ≤1 0, >10 and ≤20, and > 20 ng/ml. The 3 year actuarial rates of biochemical control were 100% for group 1, 66.7% for group 2, 61.5% for group 3, and 28.6% for group 4. Pre-RT PSA values were also evaluated. Univariate Cox models indicated lower presurgical and pre-RT PSA values were predictive of biochemical control (p=0.017, p6 months after surgery (group 3), the 3 year actuarial rate of biochemical control was 55.6%. The 3 year actuarial rate of biochemical control for patients treated for a biopsy proven recurrence (group 4) was 8.3%. By pair-wise log rank test, the rates of biochemical control were significantly different between groups 1 and 3 (p=0.036), groups 1 and 4 (p<0.001), and groups 3 and 4 (p=0.009). Conclusion: Biochemical control was achieved in approximately half of the patients treated with post-operative prostatic fossa irradiation. Elevated presurgical and pre-RT PSA

  9. 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

  10. 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.

  11. 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.

  12. Thrombin generation assay: a new tool to predict and optimize clinical outcome in cardiovascular patients?

    Science.gov (United States)

    Campo, Gianluca; Pavasini, Rita; Pollina, Alberto; Fileti, Luca; Marchesini, Jlenia; Tebaldi, Matteo; Ferrari, Roberto

    2012-12-01

    Antithrombotic therapy (including antiplatelet and anticoagulant drugs) is the cornerstone of the current medical treatment of patients with acute coronary syndromes (ACS). This therapy and particularly the new antiplatelet and anticoagulant drugs have significantly reduced the ischemic risk, but have increased bleeding complications. Recently, several studies have emphasized the negative prognostic impact on long-term mortality of these bleeding adverse events. Thus, new assays to estimate the bleeding risk and the efficacy of these antithrombotic drugs are clearly in demand. Regarding the anticoagulant drugs, new promising data have emerged about the thrombin generation assay (TGA). TGA measures the ability of plasma to generate thrombin. TGA may be used to check coagulation function, to value risk of thrombosis and to compare the efficacy of different anticoagulants employed in clinical management of patients with ACS. The TGA result is a curve which describes the variation of thrombin's amount during the activation of the coagulation cascade. All available anticoagulant drugs influence the principal parameters generated by TGA and so it is possible to evaluate the effects of the medical treatment. In this review we provide a brief description of the assay and we summarize the principals of previous studies by analyzing the relationship between anticoagulant drugs and TGA. Moreover, a brief summary of its ability to predict ischemic and bleeding risks has been provided. PMID:22688556

  13. 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.

  14. Discovery of predictive models in an injury surveillance database: an application of data mining in clinical research.

    Science.gov (United States)

    Holmes, J H; Durbin, D R; Winston, F K

    2000-01-01

    A new, evolutionary computation-based approach to discovering prediction models in surveillance data was developed and evaluated. This approach was operationalized in EpiCS, a type of learning classifier system specially adapted to model clinical data. In applying EpiCS to a large, prospective injury surveillance database, EpiCS was found to create accurate predictive models quickly that were highly robust, being able to classify > 99% of cases early during training. After training, EpiCS classified novel data more accurately (p building predictive models. PMID:11079905

  15. 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...... bacteremia’. Data on clinical history, comorbid illnesses, physical observations, and laboratory tests were used to evaluate the application of the clinical decision rule. We report the sensitivity, specificity, and area under the curve. Results Among 1526 patients, 105 (6.9%) patients were classified with...... and is likely to be a useful supplement to clinical judgment....

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

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

    International Nuclear Information System (INIS)

    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

  3. 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...

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

    OpenAIRE

    Meagher, Frances M; Butler, Marcus W.; Miller, Stanley DW; Costello, Richard; Conroy, Ronán; McElvaney, Noel G.

    2009-01-01

    BACKGROUND: 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. AIM: This study explores the utility of the team objective structured bedside assessment (TOSBA),...

  5. 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

  6. Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks

    OpenAIRE

    Gevaert, Olivier; De Smet, Frank; Timmerman, Dirk; Moreau, Yves; De Moor, Bart

    2006-01-01

    MOTIVATION: Clinical data, such as patient history, laboratory analysis, ultrasound parameters--which are the basis of day-to-day clinical decision support--are often underused to guide the clinical management of cancer in the presence of microarray data. We propose a strategy based on Bayesian networks to treat clinical and microarray data on an equal footing. The main advantage of this probabilistic model is that it allows to integrate these data sources in several ways and that it allows t...

  7. An integrated model of clinical information and gene expression for prediction of survival in ovarian cancer patients.

    Science.gov (United States)

    Yang, Rendong; Xiong, Jie; Deng, Defeng; Wang, Yiren; Liu, Hequn; Jiang, Guli; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

    2016-06-01

    Accumulating evidence shows that clinical factors alone are not adequate for predicting the survival of patients with ovarian cancer (OvCa), and many genes have been found to be associated with OvCa prognosis. The objective of this study was to develop a model that integrates clinical information and a gene signature to predict the survival durations of patients diagnosed with OvCa. We constructed mRNA and microRNA expression profiles and gathered the corresponding clinical data of 552 OvCa patients and 8 normal controls from The Cancer Genome Atlas. Using univariate Cox regression followed by a permutation test, elastic net-regulated Cox regression, and ridge regression, we generated a prognosis index consisting of 2 clinical variables, 7 protective mRNAs, 12 risky mRNAs, and 1 protective microRNA. The area under the curve of the receiver operating characteristic of the integrated clinical-and-gene model was 0.756, larger than that of the clinical-alone model (0.686) or the gene-alone model (0.703). OvCa patients in the high-risk group had a significantly shorter overall survival time compared with patients in the low-risk group (hazard ratio = 8.374, 95% confidence interval = 4.444-15.780, P = 4.90 × 10(-11), by the Wald test). The reliability of the gene signature was confirmed by a public external data set from the Gene Expression Omnibus. Our conclusions that we have identified an integrated clinical-and-gene model superior to the traditional clinical-alone model in ascertaining the survival prognosis of patients with OvCa. Our findings may prove valuable for improving the clinical management of OvCa. PMID:27059002

  8. 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

  9. 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

    , 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. PMID:27138448

  10. 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

  11. Prediction

    OpenAIRE

    Woollard, W.J.

    2006-01-01

    In this chapter we will look at the ways in which you can use ICT in the classroom to support hypothesis and prediction and how modern technology is enabling: pattern seeking, extrapolation and interpolation to meet the challenges of the information explosion of the 21st century.

  12. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Shibayama, Masaki [Sysmex Corporation, Central Research Laboratories, Kobe 651-2271 (Japan); Maak, Matthias; Nitsche, Ulrich [Chirurgische Klinik, Klinikum Rechts der Isar der TUM, München 81657 (Germany); Gotoh, Kengo [Sysmex Corporation, Central Research Laboratories, Kobe 651-2271 (Japan); Rosenberg, Robert; Janssen, Klaus-Peter, E-mail: klaus-peter.janssen@lrz.tum.de [Chirurgische Klinik, Klinikum Rechts der Isar der TUM, München 81657 (Germany)

    2011-07-07

    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.

  14. Clinical outcomes and prediction of survival following percutaneous biliary drainage for malignant obstructive jaundice

    OpenAIRE

    Zhang, Guang Yuan; LI, WEN TAO; PENG, WEI JUN; LI, GUO DONG; HE, XIN HONG; XU, LI CHAO

    2014-01-01

    The present study aimed to investigate the clinical outcomes of percutaneous transhepatic biliary drainage in patients with obstructive jaundice and identify potential predictors of patient survival. Clinical data from 102 patients (66 males and 36 females; median age, 63.50 years; range, 29–84 years) with a mean (± standard deviation) pre-drainage serum bilirubin level of 285.4 (±136.7 μmol/l), were retrospectively studied. Technical and clinical success, complications and survival time were...

  15. 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

  16. 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. PMID:15720207

  17. Local control after radiosurgery for brain metastases: predictive factors and implications for clinical decision

    International Nuclear Information System (INIS)

    To evaluate the local control of brain metastases (BM) in patients treated with stereotactic radiosurgery (SRS), correlate the outcome with treatment parameters and lesion characteristics, and define its implications for clinical decisions. Between 2007 and 2012, 305 BM in 141 consecutive patients were treated with SRS. After exclusions, 216 BM in 100 patients were analyzed. Doses were grouped as follows: ≤15 Gy, 16–20 Gy, and ≥21 Gy. Sizes were classified as ≤10 mm and >10 mm. Local control (LC) and overall survival (OS) were estimated using the Kaplan-Meier method. Log-rank statistics were used to identify the prognostic factors affecting LC and OS. For multivariate analyses, a Cox proportional model was applied including all potentially significant variables reached on univariate analyses. Median age was 54 years (18–80). Median radiological follow-up of the lesions was 7 months (1–66). Median LC and the LC at 1 year were 22.3 months and 69.7%, respectively. On univariate analysis, tumor size, SRS dose, and previous whole brain irradiation (WBRT) were significant factors for LC. Patients with lesions >10 and ≤10 mm had an LC at 1 year of 58.6% and 79.1%, respectively (p = 0.008). In lesions receiving ≤15 Gy, 16–20 Gy, and ≥21 Gy, the 1-year LC rates were 39.6%, 71.7%, and 92.3%, respectively (p < 0.001). When WBRT was done previously, LC at 1 year was 57.9% compared with 78.4% for those who did not undergo WBRT (p = 0.004). On multivariate analysis, dose remained the single most powerful prognostic factor for LC. Median OS for all patients was 17 months, with no difference among the groups. Dose is the most important predictive factor for LC of BM. Doses below 16 Gy correlated with poor LC. The SRS dose as salvage treatment after previous WBRT should not be reduced unless there is a pressing reason to do so

  18. 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...

  19. Clinical versus Actuarial Predictions of Violence in Patients with Mental Illness.

    Science.gov (United States)

    Gardner, William; And Others

    1996-01-01

    Compared accuracy of an actuarial procedure for the prediction of community violence by patients with mental illnesses to accuracy of clinicians' concern ratings of patient violence. Data came from a study of 357 pairs of patients seen in a psychiatric emergency room. Actuarial predictions based only on patients' histories of violence were more…

  20. 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…

  1. Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography

    OpenAIRE

    Sha, SJ; Ghosh, PM; Lee, Se; Corbetta-Rastelli, C; Jagust, WJ; Kornak, J.; Rankin, KP; Grinberg, LT; Vinter, HV; Mendez, MF; Dickson, DW; Seeley, WW; Gorno-Tempini, M; Kramer, J.; Miller, BL

    2015-01-01

    Introduction Group comparisons demonstrate greater visuospatial and memory deficits and temporoparietal-predominant degeneration on neuroimaging in patients with corticobasal syndrome (CBS) found to have Alzheimer’s disease (AD) pathology versus those with underlying frontotemporal lobar degeneration (FTLD). The value of these features in predicting underlying AD pathology in individual patients is unknown. The goal of this study is to evaluate the utility of modified clinical criteria and vi...

  2. Prognostic index score and clinical prediction model of local regional recurrence after mastectomy in breast cancer patients

    International Nuclear Information System (INIS)

    Purpose: To develop clinical prediction models for local regional recurrence (Lr) of breast carcinoma after mastectomy that will be superior to the conventional measures of tumor size and nodal status. Methods and Materials: Clinical information from 1,010 invasive breast cancer patients who had primary modified radical mastectomy formed the database of the training and testing of clinical prognostic and prediction models of LRR. Cox proportional hazards analysis and Bayesian tree analysis were the core methodologies from which these models were built. To generate a prognostic index model, 15 clinical variables were examined for their impact on LRR. Patients were stratified by lymph node involvement (<4 vs. ≥4) and local regional status (recurrent vs. control) and then, within strata, randomly split into training and test data sets of equal size. To establish prediction tree models, 255 patients were selected by the criteria of having had LRR (53 patients) or no evidence of LRR without postmastectomy radiotherapy (PMRT) (202 patients). Results: With these models, patients can be divided into low-, intermediate-, and high-risk groups on the basis of axillary nodal status, estrogen receptor status, lymphovascular invasion, and age at diagnosis. In the low-risk group, there is no influence of PMRT on either LRR or survival. For intermediate-risk patients, PMRT improves LR control but not metastases-free or overall survival. For the high-risk patients, however, PMRT improves both LR control and metastasis-free and overall survival. Conclusion: The prognostic score and predictive index are useful methods to estimate the risk of LRR in breast cancer patients after mastectomy and for estimating the potential benefits of PMRT. These models provide additional information criteria for selection of patients for PMRT, compared with the traditional selection criteria of nodal status and tumor size

  3. 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, ...

  4. 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 ...

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. Comparison of three clinical and three ultrasonic equations in predicting fetal birth weight

    Directory of Open Access Journals (Sweden)

    Renuka Malik

    2016-01-01

    Conclusions: The major finding of this study is that clinical estimation of fetal weight is as accurate as ultrasonographic method of estimation within normal range of birth weight Ultrasonographic methods was statistically more accurate with smaller mean errors and more within 10% of actual birth weight. Johnson formula gave most accuracy in clinical methods Ultrasound should be used to confirm clinical methods if IUGR or Macrosomia is suspected. No single method should be used if EBW is a part of decision but two or more methods should be combined. [Int J Reprod Contracept Obstet Gynecol 2016; 5(1.000: 210-216

  11. Validation of a Predictive Model for Survival in Metastatic Cancer Patients Attending an Outpatient Palliative Radiotherapy Clinic

    International Nuclear Information System (INIS)

    Purpose: To validate a predictive model for survival of patients attending a palliative radiotherapy clinic. Methods and Materials: We described previously a model that had good predictive value for survival of patients referred during 1999 (1). The six prognostic factors (primary cancer site, site of metastases, Karnofsky performance score, and the fatigue, appetite and shortness-of-breath items from the Edmonton Symptom Assessment Scale) identified in this training set were extracted from the prospective database for the year 2000. We generated a partial score whereby each prognostic factor was assigned a value proportional to its prognostic weight. The sum of the partial scores for each patient was used to construct a survival prediction score (SPS). Patients were also grouped according to the number of these risk factors (NRF) that they possessed. The probability of survival at 3, 6, and 12 months was generated. The models were evaluated for their ability to predict survival in this validation set with appropriate statistical tests. Results: The median survival and survival probabilities of the training and validation sets were similar when separated into three groups using both SPS and NRF methods. There was no statistical difference in the performance of the SPS and NRF methods in survival prediction. Conclusion: Both the SPS and NRF models for predicting survival in patients referred for palliative radiotherapy have been validated. The NRF model is preferred because it is simpler and avoids the need to remember the weightings among the prognostic factors

  12. 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.

  13. Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database

    Science.gov (United States)

    Coleman, Craig I; Kohn, Christine G; Crivera, Concetta; Schein, Jeffrey R; Peacock, W Frank

    2015-01-01

    Objective To validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule, in a database consisting only of inpatient claims. Design Retrospective claims database analysis. Setting The 2012 Healthcare Cost and Utilization Project National Inpatient Sample. Participants Pulmonary embolism (PE) admissions were identified by an International Classification of Diseases, ninth edition (ICD-9) code either in the primary position or secondary position when accompanied by a primary code for a PE complication. The multivariable IMPACT rule, which includes age and 11 comorbidities, was used to estimate patients’ probability of in-hospital mortality and classify them as low or higher risk (≤1.5% deemed low risk). Primary and secondary outcome measures The rule's sensitivity, specificity, positive and negative predictive values (PPV and NPV) and area under the receiver operating characteristic curve statistic for predicting in-hospital mortality with accompanying 95% CIs. Results A total of 34 108 admissions for PE were included, with a 3.4% in-hospital case-fatality rate. IMPACT classified 11 025 (32.3%) patients as low risk, and low risk patients had lower in-hospital mortality (OR, 0.17, 95% CI 0.13 to 0.21), shorter length of stay (−1.2 days, p99%), low PPV (4.6%) and an AUC of 0.74, 95% CI 0.73 to 0.76. Conclusions The IMPACT rule appeared valid when used in this all payer, inpatient only administrative claims database. Its high sensitivity and NPV suggest the probability of in-hospital death in those classified as low risk by IMPACT was minimal. PMID:26510731

  14. 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.

  15. Novel Computed Tomography-based Metric Reliably Estimates bone Strength, Offering Potentially Meaningful Enhancement in Clinical Fracture Risk Prediction

    Directory of Open Access Journals (Sweden)

    S Imran A. Shah

    2015-12-01

    Full Text Available Osteoporosis with resultant fractures is a major global health problem with huge socio-economic implications for patients, families and healthcare services. Areal (2D bone mineral density (BMD assessment is commonly used for predicting such fracture risk, but is unreliable, estimating only about 50% of bone strength. By contrast, computed tomography (CT based techniques could provide improved metrics for estimating bone strength such as bone volume fraction (BVF; a 3D volumetric measure of mineralised bone, enabling cheap, safe and reliable strategies for clinical application, and to help divert resources to patients identified as most likely to benefit, meeting an unmet need. Here we describe a novel method for measuring BVF at clinical-CT like low-resolution (550µm voxel size. Femoral heads (n=8 were micro-CT scanned ex-vivo. Micro-CT data were downgraded in resolution from 30µm to 550µm voxel size and BVF calculated at high and low resolution. Experimental mechanical testing was applied to measure ex vivo bone strength of samples. BVF measures collected at high-resolution showed high correlation (correlation coefficient r2=0.95 with low-resolution data. Low-resolution BVF metrics showed high correlation (r2=0.96 with calculated sample strength. These results demonstrate that measuring BVF at low resolution is feasible, which also predicts bone strength. Measures of BVF should be useful for clinically estimating bone strength and fracture risk. The method needs to be validated using clinical CT scans.

  16. 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...

  17. 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

  18. 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.

  19. 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

  20. Microinvasion of liver metastases from colorectal cancer: predictive factors and application for determining clinical target volume

    OpenAIRE

    Qian, Yang; Zeng, Zhao-Chong; Ji, Yuan; Xiao, Yin-Ping

    2015-01-01

    Objectives 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). Methods 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 gen...

  1. 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....

  2. 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...

  3. 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

  4. 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

  5. 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

  6. 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

  7. Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening.

    Science.gov (United States)

    Brandt, Kathleen R; Scott, Christopher G; Ma, Lin; Mahmoudzadeh, Amir P; Jensen, Matthew R; Whaley, Dana H; Wu, Fang Fang; Malkov, Serghei; Hruska, Carrie B; Norman, Aaron D; Heine, John; Shepherd, John; Pankratz, V Shane; Kerlikowske, Karla; Vachon, Celine M

    2016-06-01

    Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra

  8. 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

  9. 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

  10. 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

  11. 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.

  12. Rule, Britannia

    DEFF Research Database (Denmark)

    Christensen, Jørgen Riber

    2011-01-01

    climax of the masque was “Rule, Britannia!” This song advocated a strong navy as a guard against the absolutist European powers with their lack of civil liberties. Furthermore, a strong navy made a standing army superfluous, and so an army could not be deployed as a repressive force of the state. Later a...

  13. 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...

  14. 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 was...

  15. Predictive factors for a severe clinical course in ulcerative colitis: Results from population-based studies

    Science.gov (United States)

    Wanderås, Magnus Hofrenning; Moum, Bjørn A; Høivik, Marte Lie; Hovde, Øistein

    2016-01-01

    Ulcerative colitis (UC) is characterized by chronic inflammation of the large bowel in genetically susceptible individuals exposed to environmental risk factors. The disease course can be difficult to predict, with symptoms ranging from mild to severe. There is no generally accepted definition of severe UC, and no single outcome is sufficient to classify a disease course as severe. There are several outcomes indicating a severe disease course, including progression of the disease’s extension, a high relapse rate, the development of acute severe colitis, colectomy, the occurrence of colorectal cancer and UC-related mortality. When evaluating a patient’s prognosis, it is helpful to do so in relation to these outcomes. Using these outcomes also makes it easier to isolate factors predictive of severe disease. The aims of this article are to evaluate different disease outcomes and to present predictive factors for these outcomes.

  16. 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 ...

  17. 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

  18. 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.

  19. The REFER (REFer for EchocaRdiogram protocol: a prospective validation of a clinical decision rule, NT-proBNP, or their combination, in the diagnosis of heart failure in primary care. Rationale and design

    Directory of Open Access Journals (Sweden)

    Tait Lynda

    2012-10-01

    Full Text Available Abstract Background Heart failure is a major cause of mortality and morbidity. As mortality rates are high, it is important that patients seen by general practitioners with symptoms suggestive of heart failure are identified quickly and treated appropriately. Identifying patients with heart failure or deciding which patients need further tests is a challenge. All patients with suspected heart failure should be diagnosed using objective tests such as echocardiography, but it is expensive, often delayed, and limited by the significant skill shortage of trained echocardiographers. Alternative approaches for diagnosing heart failure are currently limited. Clinical decision tools that combine clinical signs, symptoms or patient characteristics are designed to be used to support clinical decision-making and validated according to strict methodological procedures. The REFER Study aims to determine the accuracy and cost-effectiveness of our previously derived novel, simple clinical decision rule, a natriuretic peptide assay, or their combination, in the triage for referral for echocardiography of symptomatic adult patients who present in general practice with symptoms suggestive of heart failure. Methods/design This is a prospective, Phase II observational, diagnostic validation study of a clinical decision rule, natriuretic peptides or their combination, for diagnosing heart failure in primary care. Consecutive adult primary care patients 55 years of age or over presenting to their general practitioner with a chief complaint of recent new onset shortness of breath, lethargy or peripheral ankle oedema of over 48 hours duration, with no obvious recurrent, acute or self-limiting cause will be enrolled. Our reference standard is based upon a three step expert specialist consensus using echocardiography and clinical variables and tests. Discussion Our clinical decision rule offers a potential solution to the diagnostic challenge of providing a timely and

  20. 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.

  1. 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. PMID:15689612

  2. Prospective computerized simulation of breast cancer: comparison of computer predictions with nine sets of biological and clinical data.

    Science.gov (United States)

    Retsky, M W; Wardwell, R H; Swartzendruber, D E; Headley, D L

    1987-09-15

    A computer program which accepts clinically relevant information can be used to predict breast cancer growth, response to chemotherapy, and disease-free survival. The computer output is patient individualized because the program is highly iterative and simulates up to 2500 patients with exactly the same clinical presentation. Computer predictions have been compared to a broad spectrum of breast cancer data, and a high degree of correlation has been established. There are numerous significant clinical implications which can be derived from the computer model. Among these are the following. (a) Breast cancer tumors do not grow continuously but may have up to five growth plateaus each lasting from a small fraction of a year up to approximately 8 yr. (b) Adjuvant chemotherapy, such as 6-mo treatment with cyclophosphamide-methotrexate-5-fluorouracil, does not eradicate tumors but just reduces the number of viable cells by a factor of 10 to 100 and sets the eventual growth back by several years. This may partially explain why the age-adjusted death rate from breast cancer has not changed in the past 50 yr. (c) The computer model challenges the underlying principles in support of short-term intensive adjuvant chemotherapy, namely Gompertzian kinetics and genetically acquired tumor resistance to drugs. (d) The computer model questions the evidence opposing long-term maintenance chemotherapy protocols and suggests that maintenance protocols should be reexamined. PMID:2441859

  3. Does sensitivity measured from screening test-sets predict clinical performance?

    Science.gov (United States)

    Soh, BaoLin P.; Lee, Warwick B.; Mello-Thoms, Claudia R.; Tapia, Kriscia A.; Ryan, John; Hung, Wai Tak; Thompson, Graham J.; Heard, Rob; Brennan, Patrick C.

    2014-03-01

    Aim: To examine the relationship between sensitivity measured from the BREAST test-set and clinical performance. Background: Although the UK and Australia national breast screening programs have regarded PERFORMS and BREAST test-set strategies as possible methods of estimating readers' clinical efficacy, the relationship between test-set and real life performance results has never been satisfactorily understood. Methods: Forty-one radiologists from BreastScreen New South Wales participated in this study. Each reader interpreted a BREAST test-set which comprised sixty de-identified mammographic examinations sourced from the BreastScreen Digital Imaging Library. Spearman's rank correlation coefficient was used to compare the sensitivity measured from the BREAST test-set with screen readers' clinical audit data. Results: Results shown statistically significant positive moderate correlations between test-set sensitivity and each of the following metrics: rate of invasive cancer per 10 000 reads (r=0.495; p DCIS per 10 000 reads (r=0.444; p < 0.01). Conclusion: Comparison between sensitivity measured from the BREAST test-set and real life detection rate demonstrated statistically significant positive moderate correlations which validated that such test-set strategies can reflect readers' clinical performance and be used as a quality assurance tool. The strength of correlation demonstrated in this study was higher than previously found by others.

  4. 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…

  5. 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…

  6. 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

  7. Information Technology and the Clinical Curriculum: Some Predictions and Their Implications for the Class of 2003.

    Science.gov (United States)

    Faughnan, John G.; Elson, Robert

    1998-01-01

    Drawing on academic studies and on personal clinical and industry experiences, argues that ubiquitous, simple network computing and "power tools" for managing medical knowledge are coming to medicine in the near future. Implications are drawn for how medical school curricula cover issues such as patient confidentiality, systems thinking and error…

  8. Risk Assessment: Actuarial Prediction and Clinical Judgement of Offending Incidents and Behaviour for Intellectual Disability Services

    Science.gov (United States)

    Lindsay, William R.; Beail, Nigel

    2004-01-01

    Background: Research on prediction of violent and sexual offending behaviour has developed considerably in the mainstream criminological literature. Apart from one publication [Quinsey (2004) "Offenders with Developmental Disabilities," pp. 131-142] this has not been extended to the field of intellectual disabilities. Methods: Work on actuarial…

  9. Predicting Future Antisocial Personality Disorder in Males from a Clinical Assessment in Childhood

    Science.gov (United States)

    Lahey, Benjamin B.; Loeber, Rolf; Burke, Jeffrey D.; Applegate, Brooks

    2005-01-01

    It is essential to identify childhood predictors of adult antisocial personality disorder (APD) to target early prevention. It has variously been hypothesized that APD is predicted by childhood conduct disorder (CD), attention-deficit/hyperactivity disorder (ADHD), or both disorders. To test these competing hypotheses, the authors used data from a…

  10. 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

  11. 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...

  12. Clinical and Magnetic Resonance Imaging Factors Which May Predict the Need for Surgery in Lumbar Disc Herniation

    Science.gov (United States)

    Motiei-Langroudi, Rouzbeh; Sadeghian, Homa

    2014-01-01

    Study Design Case-control. Purpose Evaluate clinical and imaging factors which may predict the risk of failure of medical therapy in patients with lumbar disc herniation (LDH). Overview of Literature LDH is a common cause of low back pain and radicular leg pain, with a generally favorable natural course. At present, however, it is not possible to identify patients who may be candidates for surgery in an early stage of their disease by means of clinical signs or diagnostic imaging criteria. Methods We designed a study investigating patients with untreated low back pain to assess the predictive value of demographic, clinical or imaging findings in identifying patients who finally would meet the classic current criteria for surgery. Results Among 134 patients, 80.6% were successfully treated with conservative therapy and 19.4% finally underwent surgery. Sex, occupation, involved root level, presence of Modic changes, osteophytes or annular tears were not significantly different between the 2 groups, while cerebrospinal fluid block, Pfirrmann's grade, location of herniation with regard to the midline, and type of herniation were significantly different. Anteroposterior fragment size was significantly higher and intervertebral foramen height and thecal sac diameters were significantly lower in the surgical group. Conclusions Although it is strongly recommended to practice conservative management at first for patients with LDH symptoms, the results of this study shows that higher Pfirrmann's grade, more laterally located discs, extrusion and protrusion herniation types, and larger fragments could predict the risk of conservative treatment failure. This way, unnecessarily prolonged conservative management (beyond 4-8 weeks) may be precluded. PMID:25187861

  13. Machine Ruling

    OpenAIRE

    Chen, Zhe

    2015-01-01

    Emerging technologies, such as big data, Internet of things, cloud computing, mobile Internet, and robotics, breed and expedite new applications and fields. In the mean while, the long-term prosperity and happiness of human race demands advanced technologies. In this paper, the aforementioned emerging technologies are applied to management and governance for the long-term prosperity and happiness of human race. The term "machine ruling" is coined, introduced, and justified. Moreover, the fram...

  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. Burnout and Work Demands Predict Reduced Job Satisfaction in Health Professionals Working In a Surgery Clinic

    OpenAIRE

    Dragan Mijakoski; Jovanka Karadzinska-Bislimovska; Vera Basarovska; Sasho Stoleski; Jordan Minov

    2015-01-01

    BACKGROUND: Burnout syndrome develops in health professionals (HPs) as a result of exposure to chronic emotional and interpersonal workplace stressors. Research demonstrates the links between burnout, work demands, and job satisfaction in hospital HPs. AIMS: To examine the associations between burnout, work demands and job satisfaction, and to demonstrate the mediation effect of emotional exhaustion on the relationship between work demands and job satisfaction in surgery clinic HPs. M...

  16. 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 ...

  17. 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

  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. 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.

  20. Degree of Predicted Minor Histocompatibility Antigen Mismatch Correlates with Poorer Clinical Outcomes of Nonmyeloablative Allogeneic Hematopoietic Cell Transplantation

    DEFF Research Database (Denmark)

    Larsen, Malene Erup; Kornblit, B; Larsen, Mette Voldby; Masmas, TN; Nielsen, Morten; Thiim, Martin Hansen; Garred, P; Stryhn, A; Lund, Ole; Buus, S; Vindelov, L

    2010-01-01

    In fully HLA-matched allogeneic hematopoietic cell transplantations (HCT), the main mechanism of the beneficial graft-versus-tumor (GVT) effect and of the detrimental graft-versus-host disease (GVHD) is believed to be caused by donor cytotoxic T cells directed against disparate recipient minor...... HCT (matched related donor, n=70; matched unrelated donor, n=56) for hematologic malignancies. Initially, the cohort was genotyped for 53 nsSNPs in 11 known miHA source proteins. Twenty-three nsSNPs within six miHA source proteins showed variation in the graft-versus-host (GVH) direction. No...... mortality (39% vs 10%, P=0.0094, adjusted HR 4.6, P=0.0038). No association between number of predicted miHAs and any other clinical outcome parameters was observed. Collectively, our data suggest that the clinical outcome of HCT is not affected by disparate nsSNPs per se, but rather by the HLA...

  1. Exome mutation burden predicts clinical outcome in ovarian cancer carrying mutated BRCA1 and BRCA2 genes

    DEFF Research Database (Denmark)

    Birkbak, Nicolai Juul; Kochupurakkal, Bose; Gonzalez-Izarzugaza, Jose Maria;

    2013-01-01

    Reliable biomarkers predicting resistance or sensitivity to anti-cancer therapy are critical for oncologists to select proper therapeutic drugs in individual cancer patients. Ovarian and breast cancer patients carrying germline mutations in BRCA1 or BRCA2 genes are often sensitive to DNA damaging......-type BRCA1 and BRCA2 genes. These results suggest that in cancers with DNA repair deficiency caused by functional BRCA loss, higher versus lower Nmut may reflect the status of deficiency or rescue by alternative mechanism(s) for DNA repair, with lower Nmut predicting for resistance to DNA-damaging drugs in...... drugs and relative to non-mutation carriers present a favorable clinical outcome following therapy. Genome sequencing studies have shown a high number of mutations in the tumor genome in patients carrying BRCA1 or BRCA2 mutations (mBRCA). The present study used exome-sequencing and SNP 6 array data of...

  2. 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

  3. 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...

  4. Evidence that a psychopathology interactome has diagnostic value, predicting clinical needs: an experience sampling study

    OpenAIRE

    van Os, Jim; Lataster, Tineke; Delespaul, Philippe; Wichers, Marieke; Myin-Germeys, Inez

    2014-01-01

    Background For the purpose of diagnosis, psychopathology can be represented as categories of mental disorder, symptom dimensions or symptom networks. Also, psychopathology can be assessed at different levels of temporal resolution (monthly episodes, daily fluctuating symptoms, momentary fluctuating mental states). We tested the diagnostic value, in terms of prediction of treatment needs, of the combination of symptom networks and momentary assessment level. Method Fifty-seven patients with a ...

  5. 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.

  6. 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...

  7. 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.

  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. 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.

  10. Predicting analysis time in events-driven clinical trials using accumulating time-to-event surrogate information.

    Science.gov (United States)

    Wang, Jianming; Ke, Chunlei; Yu, Zhinuan; Fu, Lei; Dornseif, Bruce

    2016-05-01

    For clinical trials with time-to-event endpoints, predicting the accrual of the events of interest with precision is critical in determining the timing of interim and final analyses. For example, overall survival (OS) is often chosen as the primary efficacy endpoint in oncology studies, with planned interim and final analyses at a pre-specified number of deaths. Often, correlated surrogate information, such as time-to-progression (TTP) and progression-free survival, are also collected as secondary efficacy endpoints. It would be appealing to borrow strength from the surrogate information to improve the precision of the analysis time prediction. Currently available methods in the literature for predicting analysis timings do not consider utilizing the surrogate information. In this article, using OS and TTP as an example, a general parametric model for OS and TTP is proposed, with the assumption that disease progression could change the course of the overall survival. Progression-free survival, related both to OS and TTP, will be handled separately, as it can be derived from OS and TTP. The authors seek to develop a prediction procedure using a Bayesian method and provide detailed implementation strategies under certain assumptions. Simulations are performed to evaluate the performance of the proposed method. An application to a real study is also provided. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26689725

  11. Post-Exercise Heart Rate Recovery Independently Predicts Clinical Outcome in Patients with Acute Decompensated Heart Failure

    Science.gov (United States)

    Youn, Jong-Chan; Lee, Hye Sun; Choi, Suk-Won; Han, Seong-Woo; Ryu, Kyu-Hyung; Shin, Eui-Cheol; Kang, Seok-Min

    2016-01-01

    Background Post-exercise heart rate recovery (HRR) is an index of parasympathetic function associated with clinical outcome in patients with chronic heart failure. However, its relationship with the pro-inflammatory response and prognostic value in consecutive patients with acute decompensated heart failure (ADHF) has not been investigated. Methods We measured HRR and pro-inflammatory markers in 107 prospectively and consecutively enrolled, recovered ADHF patients (71 male, 59 ± 15 years, mean ejection fraction 28.9 ± 14.2%) during the pre-discharge period. The primary endpoint included cardiovascular (CV) events defined as CV mortality, cardiac transplantation, or rehospitalization due to HF aggravation. Results The CV events occurred in 30 (28.0%) patients (5 cardiovascular deaths and 7 cardiac transplantations) during the follow-up period (median 214 days, 11–812 days). When the patients with ADHF were grouped by HRR according to the Contal and O’Quigley’s method, low HRR was shown to be associated with significantly higher levels of serum monokine-induced by gamma interferon (MIG) and poor clinical outcome. Multivariate Cox regression analysis revealed that low HRR was an independent predictor of CV events in both enter method and stepwise method. The addition of HRR to a model significantly increased predictability for CV events across the entire follow-up period. Conclusion Impaired post-exercise HRR is associated with a pro-inflammatory response and independently predicts clinical outcome in patients with ADHF. These findings may explain the relationship between autonomic dysfunction and clinical outcome in terms of the inflammatory response in these patients. PMID:27135610

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Model to predict survival after surgical resection of intrahepatic cholangiocarcinoma: the Mayo Clinic experience

    Science.gov (United States)

    Ali, Shahzad M; Clark, Clancy J; Mounajjed, Taofic; Wu, Tsung-Teh; Harmsen, William S; Reid-Lombardo, KMarie; Truty, Mark J; Kendrick, Michael L; Farnell, Michael B; Nagorney, David M; Que, Florencia G

    2015-01-01

    Background The 7th edition of the American Joint Committee on Cancer (AJCC) staging system has recently been validated and shown to predict survival in patients with intrahepatic cholangiocarcinoma (ICC). The present study attempted to investigate the validity of these findings. Methods A single-centre, retrospective cohort study was conducted. Histopathological restaging of disease subsequent to primary surgical resection was carried out in all consecutive ICC patients. Overall survival was compared using Kaplan–Meier estimates and log-rank tests. Results A total of 150 patients underwent surgery, 126 (84%) of whom met the present study's inclusion criteria. Of these 126 patients, 68 (54%) were female. The median length of follow-up was 4.5 years. The median patient age was 58 years (range: 24–79 years). Median body mass index was 27 kg/m2 (range: 17–46 kg/m2). Staging according to the AJCC 7th edition categorized 33 (26%) patients with stage I disease, 27 (21%) with stage II disease, five (4%) with stage III disease, and 61 (48%) with stage IVa disease. The AJCC 7th edition failed to accurately stratify survival in the current cohort; analysis revealed significantly worse survival in those with microvascular invasion, tumour size of >5 cm, grade 4 disease, multiple tumours and positive lymph nodes (P < 0.001). A negative resection margin was associated with improved survival (P < 0.001). Conclusions The AJCC 7th edition did not accurately predict survival in patients with ICC. A multivariable model including tumour size and differentiation in addition to the criteria used in the AJCC 7th edition may offer a more accurate method of predicting survival in patients with ICC. PMID:25410716

  17. A systematic review of models to predict recruitment to multicentre clinical trials

    Directory of Open Access Journals (Sweden)

    Cook Andrew

    2010-07-01

    Full Text Available Abstract Background Less than one third of publicly funded trials managed to recruit according to their original plan often resulting in request for additional funding and/or time extensions. The aim was to identify models which might be useful to a major public funder of randomised controlled trials when estimating likely time requirements for recruiting trial participants. The requirements of a useful model were identified as usability, based on experience, able to reflect time trends, accounting for centre recruitment and contribution to a commissioning decision. Methods A systematic review of English language articles using MEDLINE and EMBASE. Search terms included: randomised controlled trial, patient, accrual, predict, enrol, models, statistical; Bayes Theorem; Decision Theory; Monte Carlo Method and Poisson. Only studies discussing prediction of recruitment to trials using a modelling approach were included. Information was extracted from articles by one author, and checked by a second, using a pre-defined form. Results Out of 326 identified abstracts, only 8 met all the inclusion criteria. Of these 8 studies examined, there are five major classes of model discussed: the unconditional model, the conditional model, the Poisson model, Bayesian models and Monte Carlo simulation of Markov models. None of these meet all the pre-identified needs of the funder. Conclusions To meet the needs of a number of research programmes, a new model is required as a matter of importance. Any model chosen should be validated against both retrospective and prospective data, to ensure the predictions it gives are superior to those currently used.

  18. 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

  19. A multi-centre phase IIa clinical study of predictive testing for preeclampsia

    DEFF Research Database (Denmark)

    Navaratnam, Kate; Alfirevic, Zarko; Baker, Philip N; Gluud, Christian; Grüttner, Berthold; Kublickiene, Karolina; Zeeman, Gerda; Kenny, Louise C

    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....

  20. 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...

  1. Circulating cell death products predict clinical outcome of colorectal cancer patients

    International Nuclear Information System (INIS)

    Tumor cell death generates products that can be measured in the circulation of cancer patients. CK18-Asp396 (M30 antigen) is a caspase-degraded product of cytokeratin 18 (CK18), produced by apoptotic epithelial cells, and is elevated in breast and lung cancer patients. We determined the CK18-Asp396 and total CK18 levels in plasma of 49 colorectal cancer patients, before and after surgical resection of the tumor, by ELISA. Correlations with patient and tumor characteristics were determined by Kruskal-Wallis H and Mann-Whitney U tests. Disease-free survival was determined using Kaplan-Meier methodology with Log Rank tests, and univariate and multivariate Cox proportional hazard analysis. Plasma CK18-Asp396 and total CK18 levels in colorectal cancer patients were related to disease stage and tumor diameter, and were predictive of disease-free survival, independent of disease-stage, with hazard ratios (HR) of patients with high levels (> median) compared to those with low levels (≤ median) of 3.58 (95% CI: 1.17–11.02) and 3.58 (95% CI: 0.97–7.71), respectively. The CK18-Asp396/CK18 ratio, which decreased with tumor progression, was also predictive of disease-free survival, with a low ratio (≤ median) associated with worse disease-free survival: HR 2.78 (95% CI: 1.06–7.19). Remarkably, the plasma CK18-Asp396 and total CK18 levels after surgical removal of the tumor were also predictive of disease-free survival, with patients with high levels having a HR of 3.78 (95% CI: 0.77–18.50) and 4.12 (95% CI: 0.84–20.34), respectively, indicating that these parameters can be used also to monitor patients after surgery. CK18-Asp396 and total CK18 levels in the circulation of colorectal cancer patients are predictive of tumor progression and prognosis and might be helpful for treatment selection and monitoring of these patients

  2. 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...

  3. 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...

  4. 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

  5. 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.

  6. 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

  7. Neurobiological markers predicting treatment response in anxiety disorders: A systematic review and implications for clinical application.

    Science.gov (United States)

    Lueken, Ulrike; Zierhut, Kathrin C; Hahn, Tim; Straube, Benjamin; Kircher, Tilo; Reif, Andreas; Richter, Jan; Hamm, Alfons; Wittchen, Hans-Ulrich; Domschke, Katharina

    2016-07-01

    Anxiety disorders constitute the largest group of mental disorders with a high individual and societal burden. Neurobiological markers of treatment response bear potential to improve response rates by informing stratified medicine approaches. A systematic review was performed on the current evidence of the predictive value of genetic, neuroimaging and other physiological markers for treatment response (pharmacological and/or psychotherapeutic treatment) in anxiety disorders. Studies published until March 2015 were selected through search in PubMed, Web of Science, PsycINFO, Embase, and CENTRAL. Sixty studies were included, among them 27 on genetic, 17 on neuroimaging and 16 on other markers. Preliminary evidence was found for the functional 5-HTTLPR/rs25531 genotypes, anterior cingulate cortex function and cardiovascular flexibility to modulate treatment outcome. Studies varied considerably in methodological quality. Application of more stringent study methodology, predictions on the individual patient level and cross-validation in independent samples are recommended to set the next stage of biomarker research and to avoid flawed conclusions in the emerging field of "Mental Health Predictomics". PMID:27168345

  8. [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

  9. Predicting the Pathogenic Potential of BRCA1 and BRCA2 Gene Variants Identified in Clinical Genetic Testing

    Directory of Open Access Journals (Sweden)

    Clare Brookes

    2015-05-01

    Full Text Available Objectives: Missense variants are very commonly detected when screening for mutations in the BRCA1 and BRCA2 genes. Pathogenic mutations in the BRCA1 and BRCA2 genes lead to an increased risk of developing breast, ovarian, prostate and/or pancreatic cancer. This study aimed to assess the predictive capability of in silico programmes and mutation databases in assisting diagnostic laboratories to determine the pathogenicity of sequence-detectable mutations. Methods: Between July 2011 and April 2013, an analysis was undertaken of 13 missense BRCA gene variants that had been detected in patients referred to the Genetic Health Services New Zealand (Northern Hub for BRCA gene analysis. The analysis involved the use of 13 in silico protein prediction programmes, two in silico transcript analysis programmes and the examination of three BRCA gene databases. Results: In most of the variants, the analysis showed different in silico interpretations. This illustrates the interpretation challenges faced by diagnostic laboratories. Conclusion: Unfortunately, when using online mutation databases and carrying out in silico analyses, there is significant discordance in the classification of some missense variants in the BRCA genes. This discordance leads to complexities in interpreting and reporting these variants in a clinical context. The authors have developed a simple procedure for analysing variants; however, those of unknown significance largely remain unknown. As a consequence, the clinical value of some reports may be negligible.

  10. Visualisation of metastatic oesophageal and gastric cancer and prediction of clinical response to palliative chemotherapy using {sup 18}FDG PET

    Energy Technology Data Exchange (ETDEWEB)

    Lorenzen, S.; Peschel, C.; Lordick, F. [Dept. of Internal Medicine, Haematology/Medical Oncology, Technical Univ. Munich (Germany); Herrmann, K.; Wieder, H.; Schwaiger, M. [Dept. of Nuclear Medicine, Technical Univ. Munich (Germany); Weber, W.A.; Hennig, M. [Inst. for Medical Statistics and Epidemiology, Technical Univ. Munich (Germany); Ott, K. [Dept. of Surgery, Technical Univ. of Munich (Germany); Bredenkamp, R. [Munich Centre for Clinical Studies, Munich (Germany)

    2007-07-01

    Aim: This study assessed the value of {sup 18}F-deoxyglucose positron emission tomography (FDG-PET) for visualisation and early metabolic response assessment in metastatic gastro-oesophageal cancer. Patients, methods: Twenty-six patients who were treated for metastatic disease (20 adenocarcinomas, 6 squamous cell cancers) underwent FDG-PET before and two weeks after the onset of palliative chemotherapy with either oxaliplatin + 5-FU/LV or with docetaxel + capecitabine. PET results were validated according to clinical response based on RECIST criteria. Results: Twenty-four tumours (92%) could be visualised by FDG-PET and were also assessable by a second PET scan at 2 weeks. The 2 tumours that were not detectable by PET were both gastric cancers belonging to the non-intestinal subtype according to Lauren. Median time to progression and overall survival were not significantly different for metabolic responders and non-responders (6.3 vs 5.3 months and 14.1 vs 12.5 months, respectively). Conclusion: In this heterogeneous study population, FDG-PET had a limited accuracy in predicting clinical response. However, the metabolic response prediction was particularly good in the subgroup of patients with oesophageal squamous cell cancer. Therefore, FDG-PET and assessment of cancer therapy clearly merits further investigation in circumscribed patient populations with metastatic disease. (orig.)

  11. 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.

  12. 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 ...

  13. Outcome prediction in pneumonia induced ALI/ARDS by clinical features and peptide patterns of BALF determined by mass spectrometry.

    Directory of Open Access Journals (Sweden)

    Jochen Frenzel

    Full Text Available BACKGROUND: Peptide patterns of bronchoalveolar lavage fluid (BALF were assumed to reflect the complex pathology of acute lung injury (ALI/acute respiratory distress syndrome (ARDS better than clinical and inflammatory parameters and may be superior for outcome prediction. METHODOLOGY/PRINCIPAL FINDINGS: A training group of patients suffering from ALI/ARDS was compiled from equal numbers of survivors and nonsurvivors. Clinical history, ventilation parameters, Murray's lung injury severity score (Murray's LISS and interleukins in BALF were gathered. In addition, samples of bronchoalveolar lavage fluid were analyzed by means of hydrophobic chromatography and MALDI-ToF mass spectrometry (MALDI-ToF MS. Receiver operating characteristic (ROC analysis for each clinical and cytokine parameter revealed interleukin-6>interleukin-8>diabetes mellitus>Murray's LISS as the best outcome predictors. Outcome predicted on the basis of BALF levels of interleukin-6 resulted in 79.4% accuracy, 82.7% sensitivity and 76.1% specificity (area under the ROC curve, AUC, 0.853. Both clinical parameters and cytokines as well as peptide patterns determined by MALDI-ToF MS were analyzed by classification and regression tree (CART analysis and support vector machine (SVM algorithms. CART analysis including Murray's LISS, interleukin-6 and interleukin-8 in combination was correct in 78.0%. MALDI-ToF MS of BALF peptides did not reveal a single identifiable biomarker for ARDS. However, classification of patients was successfully achieved based on the entire peptide pattern analyzed using SVM. This method resulted in 90% accuracy, 93.3% sensitivity and 86.7% specificity following a 10-fold cross validation (AUC = 0.953. Subsequent validation of the optimized SVM algorithm with a test group of patients with unknown prognosis yielded 87.5% accuracy, 83.3% sensitivity and 90.0% specificity. CONCLUSIONS/SIGNIFICANCE: MALDI-ToF MS peptide patterns of BALF, evaluated by appropriate

  14. 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

  15. Brain-derived neurotrophic factor expression predicts adverse pathological & clinical outcomes in human breast cancer

    Directory of Open Access Journals (Sweden)

    Mokbel Kefah

    2011-07-01

    Full Text Available Abstract Introduction Brain-derived neurotrophic factor (BDNF has established physiological roles in the development and function of the vertebrate nervous system. BDNF has also been implicated in several human malignancies, including breast cancer (BC. However, the precise biological role of BDNF and its utility as a novel biomarker have yet to be determined. The objective of this study was to determine the mRNA and protein expression of BDNF in a cohort of women with BC. Expression levels were compared with normal background tissues and evaluated against established pathological parameters and clinical outcome over a 10 year follow-up period. Methods BC tissues (n = 127 and normal tissues (n = 33 underwent RNA extraction and reverse transcription, BDNF transcript levels were determined using real-time quantitative PCR. BDNF protein expression in mammary tissues was assessed with standard immuno-histochemical methodology. Expression levels were analyzed against tumour size, grade, nodal involvement, TNM stage, Nottingham Prognostic Index (NPI and clinical outcome over a 10 year follow-up period. Results Immuno-histochemical staining revealed substantially greater BDNF expression within neoplastic cells, compared to normal mammary epithelial cells. Significantly higher mRNA transcript levels were found in the BC specimens compared to background tissues (p = 0.007. The expression of BDNF mRNA was demonstrated to increase with increasing NPI; NPI-1 vs. NPI-2 (p = 0.009. Increased BDNF transcript levels were found to be significantly associated with nodal positivity (p = 0.047. Compared to patients who remained disease free, higher BDNF expression was significantly associated with local recurrence (LR (p = 0.0014, death from BC (p = 0.018 and poor prognosis overall (p = 0.013. After a median follow up of 10 years, higher BDNF expression levels were significantly associated with reduced overall survival (OS (106 vs. 136 months, p = 0.006. BDNF

  16. 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

  17. 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

  18. CT colonography without cathartic preparation: positive predictive value and patient experience in clinical practice

    Energy Technology Data Exchange (ETDEWEB)

    Zueco Zueco, Carmen; Sobrido Sampedro, Carolina; Corroto, Juan D.; Rodriguez Fernandez, Paula; Fontanillo Fontanillo, Manuela [Complexo Hospitalario Universitario de Vigo - CHUVI, Vigo, Pontevedra (Spain)

    2012-06-15

    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.)

  19. 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.)

  20. Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

    International Nuclear Information System (INIS)

    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

  1. 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

  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. 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.

  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. 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

  6. 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.

  7. 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

  8. Hip and fragility fracture prediction by 4-item clinical risk score and mobile heel BMD: a women cohort study

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    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.

  9. Old wine in new bottles: validating the clinical utility of SPECT in predicting cognitive performance in mild traumatic brain injury.

    Science.gov (United States)

    Romero, Kristoffer; Lobaugh, Nancy J; Black, Sandra E; Ehrlich, Lisa; Feinstein, Anthony

    2015-01-30

    The neural underpinnings of cognitive dysfunction in mild traumatic brain injury (TBI) are not fully understood. Consequently, patient prognosis using existing clinical imaging is somewhat imprecise. Single photon emission computed tomography (SPECT) is a frequently employed investigation in this population, notwithstanding uncertainty over the clinical utility of the data obtained. In this study, subjects with mild TBI underwent (99m)Tc-ECD SPECT scanning, and were administered a brief battery of cognitive tests and self-report symptom scales of concussion and emotional distress. Testing took place 2 weeks (n=84) and 1 year (n=49) post-injury. Multivariate analysis (i.e., partial least squares analysis) revealed that frontal perfusion in right superior frontal and middle frontal gyri predicted poorer performance on the Stroop test, an index of executive function, both at initial and follow-up testing. Conversely, SPECT scans categorized as normal or abnormal by radiologists did not differentiate cognitively impaired from intact subjects. These results demonstrate the clinical utility of SPECT in mild TBI, but only when data are subjected to blood flow quantification analysis. PMID:25466236

  10. 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.

  11. 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

  12. 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

  13. 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

  14. Synuclein gamma predicts poor clinical outcome in colon cancer with normal levels of carcinoembryonic antigen

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    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.

  15. DIAGNOSTIC AND PREDICTIVE VALUES OF PHOTO ALBUMS AND VIDEOCLIPS IN PEDIATRIC NEUROLOGY CLINICS

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    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. 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.

  17. 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.)

  18. Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer

    International Nuclear Information System (INIS)

    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 10-6 mm2/s) than the LVI-negative group (n = 59, 1002 ± 163 x 10-6 mm2/s; p < 0.0001). Peritumoral maximum-ADC was significantly higher in the LVI-positive (1805 ± 355 x 10-6 mm2/s) than the LVI-negative group (1625 ± 346 x 10-6 mm2/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.)

  19. Somatostatin receptor scintigraphy to predict the clinical evolution and therapeutic response of thyroid-associated ophthalmopathy

    Energy Technology Data Exchange (ETDEWEB)

    Nocaudie, M.; Bailliez, A.; Itti, E. [Centre Hospitalier Regional et Universitaire, Lille (France). Service Central de Medecine Nucleaire et Imagerie Fonctionnelle; Bauters, C.; Wemeau, J.L. [Clinique d`Endocrinologie, Centre Hospitalier Regional et Universitaire de Lille (France); Marchandise, X.

    1999-05-01

    Management of thyroid-associated ophthalmopathy remains a topic of controversy. Immunosuppressive treatments have to be applied at peak disease activity and before criteria of severity develop. Expression of somatostatin receptors on activated lymphocytes allows scintigraphic imaging with indium-111 pentetreotide. We conducted a prospective study with 17 patients who presented severe ophthalmopathy (11 Graves` disease, four Hashimoto`s thyroiditis, two isolated in appearance: Means` syndrome). Each patient underwent hormonal (free T{sub 3} and TSH) and immunological (TBII) assessment, an orbital computed tomography scan or magnetic resonance imaging, a visual functional examination and {sup 111}In-pentetreotide orbital scintigraphy before undergoing treatment by steroids and/or radiotherapy, independently of scintigraphic results. At 4 and 24 h after the intravenous injection of 111 MBq of {sup 111}In-pentetreotide, planar imaging centred on the head and neck (anterior and both lateral views) was carried out. Retrobulbar uptake was assessed by visual semi-quantitative analysis (score given by two independent trained observers) and by quantitative analyses (regions of interest, orbit/brain uptake indices). Patients were ophthalmologically followed up for 6 months and then classified as improved or not. Visual semi-quantitative analysis of 4-h/24-h planar images was correlated with the ophthalmological evolution ({chi}{sup 2} test, P<0.01). All ten patients in whom scintigraphy was considered positive were clinically improved at 6 months, and of the seven patients in whom scintigraphy was negative, six were not improved. Nevertheless, objective quantitative analysis did not succeed in confirming these results. We conclude that {sup 111}In-pentetreotide scintigraphy requires further developments, including quantitative single-photon emission tomographic acquisition, if its role as a guide to therapeutic strategy in thyroid-associated ophthalmopathy is to be confirmed

  20. CIAPIN1 nuclear accumulation predicts poor clinical outcome in epithelial ovarian cancer

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    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. Clinical effectiveness of grip strength in predicting ambulation of elderly inpatients

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    Beseler MR

    2014-11-01

    Full Text Available MR Beseler,1 C Rubio,1 E Duarte,1 D Hervás,2 MC Guevara,1 M Giner-Pascual,1 E Viosca1 1Physical Medicine and Rehabilitation, La Fe Hospital, Valencia, Spain; 2Statistical Unit, La Fe Hospital, Valencia, Spain Background: Assessing the clinical effectiveness of measuring grip strength as a prognostic tool in recovering ambulation in bed-confined frail elderly patients. Methods: A prospective study was carried out with 50 elderly inpatients (mean age: 81.6 years old. Manual muscle test was used for checking strength of hip flexor muscles, hip abductor muscles and knee extensor muscles. Grip strength was assessed by hydraulic dynamometer. Walking ability was assessed by functional ambulation categories and Functional Classification of Sagunto Hospital Ambulation. Existence of cognitive impairment (Short Portable Mental Status of Pfeiffer and comorbidity (abbreviated Charlson index were considered to be confounding variables. Statistical analysis: Simple comparisons and mixed models of multiple ordinal regression. Results: The sample presented generalized weakness in scapular (mean 4.22 and pelvic (mean 3.82 muscle. Mean hand grip values were similar: 11.98 kg right hand; 11.70 kg left hand. The patients had lost walking ability. After treatment, there was a statistically significant for scapular waist strength (P=0.001, pelvic waist strength (P=0.005 and walking ability (P=0.001. A statistically significant relationship in the regression analysis was found between the grip (right and left hands and walking ability post-treatment (P=0.009; odds ratio 1.14 and P=0.0014 odds ratio 1.113 for each walking scale. The confounding variables showed no statistical significance in the results.Conclusion: Grip strength is associated with walking ability in hospitalized frail elderly. Grip strength assessment by hydraulic dynamometry is useful in patients with poor collaboration. Walking ability training in frail elderly inpatients is useful. Keywords: gait

  2. Transcription factor E2F3 overexpressed in prostate cancer independently predicts clinical outcome.

    Science.gov (United States)

    Foster, Christopher S; Falconer, Alison; Dodson, Andrew R; Norman, Andrew R; Dennis, Nening; Fletcher, Anne; Southgate, Christine; Dowe, Anna; Dearnaley, David; Jhavar, Sameer; Eeles, Rosalind; Feber, Andrew; Cooper, Colin S

    2004-08-01

    E2F transcription factors, including E2F3, directly modulate expression of EZH2. Recently, overexpression of the EZH2 gene has been implicated in the development of human prostate cancer. In tissue microrarray studies we now show that expression of high levels of nuclear E2F3 occurs in a high proportion (98/147, 67%) of human prostate cancers, but is a rare event in non-neoplastic prostatic epithelium suggesting a role for E2F3 overexpression in prostate carcinogenesis. Patients with prostate cancer exhibiting immunohistochemically detectable nuclear E2F3 expression have poorer overall survival (P=0.0022) and cause-specific survival (P=0.0047) than patients without detectable E2F3 expression. When patients are stratified according to the maximum percentage of E2F3-positive nuclei identified within their prostate cancers (up to 20, 21-40%, etc.), there is an increasingly significant association between E2F3 staining and risk of death both for overall survival (P=0.0014) and for cause-specific survival (P=0.0004). Multivariate analyses select E2F3 expression as an independent factor predicting overall survival (unstratified P=0.0103, stratified P=0.0086) and cause-specific survival (unstratified P=0.0288, stratified P=0.0072). When these results are considered together with published data on EZH2 and on the E2F3 control protein pRB, we conclude that the pRB-E2F3-EZH2 control axis may have a critical role in modulating aggressiveness of individual human prostate cancer. PMID:15184867

  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. 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

  6. 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

  7. Prediction of clinical and endoscopic responses to anti-tumor necrosis factor-α antibodies in ulcerative colitis.

    Science.gov (United States)

    Morita, Yukihiro; Bamba, Shigeki; Takahashi, Kenichiro; Imaeda, Hirotsugu; Nishida, Atsushi; Inatomi, Osamu; Sasaki, Masaya; Tsujikawa, Tomoyuki; Sugimoto, Mitsushige; Andoh, Akira

    2016-08-01

    Objective In patients with ulcerative colitis (UC), the relationship between the initial endoscopic findings and the response to anti-tumor necrosis factor (TNF)-α antibodies remains unclear. We herein evaluated the potential of endoscopic assessment using the ulcerative colitis endoscopic index of severity (UCEIS) to predict the response to anti-TNF-α antibodies. Methods We enrolled 64 patients with UC undergoing anti-TNF-α maintenance therapy with infliximab (IFX) or adalimumab (ADA) between April 2010 and March 2015. Anti-TNF-α trough levels were determined by ELISA. Endoscopic disease activity was assessed using the UCEIS. Results The clinical response rate at 8 weeks was 77.4% for IFX and 66.7% for ADA. Serum albumin levels were significantly higher and the UCEIS bleeding descriptor before treatment was significantly lower in the responders than in the non-responders (p CRP levels at 2 weeks were significantly lower in the responders (p CRP levels), is useful for the prediction of the treatment outcome of UC patients in response to anti-TNF-α antibodies. PMID:26888161

  8. 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.

  9. The role of LDH serum levels in predicting global outcome in HCC patients treated with sorafenib: implications for clinical management

    International Nuclear Information System (INIS)

    In many tumour types serumlactate dehydrogenase (LDH) levels proved to represent an indirect marker of tumour hypoxia, neo-angiogenesis and worse prognosis. As we previously reported LDH is an important predictive factor in hepatocellular carcinoma (HCC) patients undergoing transarterial chemoembolization (TACE). Sorafenib represents the therapeutic stronghold in advanced HCC patients. As a tyrosine kinase inhibitor (TKI) mainly directed against the angiogenetic pathway, the correlation of sorafenib administration with markers of hypoxia could be an important tool in patients management. Aim of our analysis was to evaluate the role of LDH pre-treatment levels and its variation during treatment in HCC patients receiving sorafenib. 78 patients were available for our analysis. For all patients LDH values were collected within one month before the start of treatment and after the end of therapy. For study purposes we divided our patients into two groups, according to LDH pre-treatment levels, cut-off levels was determined with ROC curve analysis. Patients were, also, classified according to the variation in LDH serum levels pre- and post-treatment (increased vs decreased). Patients proved homogeneous for all clinical characteristics analyzed. In patients with LDH values under the cut-off median progression free survival (PFS) was 6.7 months, whereas it was 1.9 months in patients above the cut-off (p = 0.0002). Accordingly median overall survival (OS) was 13.2 months and 4.9 months (p = 0.0006). In patients with decreased LDH values after treatment median PFS was 6.8 months, and median OS was 21.0 months, whereas PFS was 2.9 months and OS 8.6 months in patients with increased LDH levels (PFS: p = 0.0087; OS: p = 0.0035). In our experience, LDH seemed able to predict clinical outcome in terms of PFS and OS for HCC patients treated with sorafenib. Given the correlation between LDH levels and tumour angiogenesis we can speculate that patients with high LDH pretreatment

  10. 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

  11. 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.

  12. Clinical biochemical and hormonal profiling in plasma: a promising strategy to predict growth hormone abuse in cattle.

    Science.gov (United States)

    Doué, Mickael; Dervilly-Pinel, Gaud; Cesbron, Nora; Stefani, Annalisa; Moro, Letizia; Biancotto, Giancarlo; Le Bizec, Bruno

    2015-06-01

    Recombinant bovine somatotrophin (rbST) is widely used in some countries to increase milk production. Since 1994, both marketing and use of this substance have been prohibited within the European Union. In this context, the targeted plasma biochemical and hormonal profiling was assessed as a potential screening strategy to highlight rbST (ab)use in cattle. Twenty-one routinely measured clinical blood parameters, representative of main biological profiles (energetic, proteic, etc.), were measured in the plasma of six lactating cows before and after rbST treatment throughout a 23-day study period. Appropriate multivariate statistical analyses [principal component analysis (PCA) and orthogonal partial least square (OPLS)] enabled discriminating animal samples before and after treatment (days 0 vs. 2 to 9, P = 2.10(-9)) and highlighted the five most relevant blood parameters in this discrimination. Based on each five-analyte contribution, a simple mathematically weighted equation was suggested to predict the status of samples. A suspicious threshold was proposed, and the model was further tested with the status prediction of the supplementary samples from untreated (n = 20) and treated cows (n = 22). The calculated false-positive (10%) and false-negative (4.5%) rates were in accordance with the EU requirements for screening methods. Although the model needs to be further validated with additional samples, such targeted plasma biochemical and hormonal profiling already appears as a potential promising screening strategy to highlight rbST (ab)use in cattle. PMID:25716468

  13. 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.

  14. 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.

  15. 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

  16. Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients

    OpenAIRE

    Colubri, Andres; Silver, Tom; Fradet, Terrence; Retzepi, Kalliroi; Fry, Ben; Sabeti, Pardis

    2016-01-01

    Background Assessment of the response to the 2014–15 Ebola outbreak indicates the need for innovations in data collection, sharing, and use to improve case detection and treatment. Here we introduce a Machine Learning pipeline for Ebola Virus Disease (EVD) prognosis prediction, which packages the best models into a mobile app to be available in clinical care settings. The pipeline was trained on a public EVD clinical dataset, from 106 patients in Sierra Leone. Methods/Principal Findings We us...

  17. 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...

  18. 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。

  19. The value of endorectal MR imaging to predict positive biopsies in clinically intermediate-risk prostate cancer patients

    International Nuclear Information System (INIS)

    The aim of this study was to assess the effectiveness of endorectal MR imaging in predicting the positive biopsy results in patients with clinically intermediate risk for prostate cancer. We performed a prospective endorectal MR imaging study with 81 patients at intermediate risk to detect prostate cancer between January 1997 and December 1998. Intermediate risk was defined as: prostatic specific antigen (PSA) levels between 4 and 10 ng/ml or PSA levels in the range of 10-20 ng/ml but negative digital rectal examination (DRE) or PSA levels progressively higher (0.75 ng/ml year-1). A transrectal sextant biopsy was performed after the endorectal MR exam, and also of the area of suspicion detected by MR imaging. The accuracies were measured, both singly for MR imaging and combined for PSA level and DRE, by calculating the area index of the receiver operating characteristics (ROC) curve. Cancer was detected in 23 patients (28 %). Overall sensitivity and specificity of endorectal MRI was 70 and 76 %, respectively. Accuracy was 71 % estimated from the area under the ROC curve for the total patient group and 84 % for the group of patients with PSA level between 10-20 ng/ml. Positive biopsy rate (PBR) was 63 % for the group with PSA 10-20 ng/ml and a positive MR imaging, and 15 % with a negative MR exam. The PBR was 43 % for the group with PSA 4-10 ng/ml and a positive MR study, and 13 % with a negative MR imaging examination. We would have avoided 63 % of negative biopsies, while missing 30 % of cancers for the total group of patients. Endorectal MR imaging was not a sufficient predictor of positive biopsies for patients clinically at intermediate risk for prostate cancer. Although we should not avoid performing systematic biopsies in patients with endorectal MR imaging negative results, as it will miss a significant number of cancers, selected patients with a PSA levels between 10-20 ng/ml or clinical-biopsy disagreement might benefit from endorectal MR imaging. (orig.)

  20. 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

  1. 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...

  2. 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

  3. Lack of meaningful effect of ridaforolimus on the pharmacokinetics of midazolam in cancer patients: model prediction and clinical confirmation.

    Science.gov (United States)

    Stroh, Mark; Talaty, Jennifer; Sandhu, Punam; McCrea, Jacqueline; Patnaik, Amita; Tolcher, Anthony; Palcza, John; Orford, Keith; Breidinger, Sheila; Narasimhan, Narayana; Panebianco, Deborah; Lush, Richard; Papadopoulos, Kyriakos P; Wagner, John A; Trucksis, Michele; Agrawal, Nancy

    2014-11-01

    Ridaforolimus, a unique non-prodrug analog of rapamycin, is a potent inhibitor of mTOR under development for cancer treatment. In vitro data suggest ridaforolimus is a reversible and time-dependent inhibitor of CYP3A. A model-based evaluation suggested an increase in midazolam area under the curve (AUC(0- ∞)) of between 1.13- and 1.25-fold in the presence of therapeutic concentrations of ridaforolimus. The pharmacokinetic interaction between multiple oral doses of ridaforolimus and a single oral dose of midazolam was evaluated in an open-label, fixed-sequence study, in which cancer patients received a single oral dose of 2 mg midazolam followed by 5 consecutive daily single oral doses of 40 mg ridaforolimus with a single dose of 2 mg midazolam with the fifth ridaforolimus dose. Changes in midazolam exposure were minimal [geometric mean ratios and 90% confidence intervals: 1.23 (1.07, 1.40) for AUC(0-∞) and 0.92 (0.82, 1.03) for maximum concentrations (C(max)), respectively]. Consistent with model predictions, ridaforolimus had no clinically important effect on midazolam pharmacokinetics and is not anticipated to be a perpetrator of drug-drug interactions (DDIs) when coadministered with CYP3A substrates. Model-based approaches can provide reasonable estimates of DDI liability, potentially obviating the need to conduct dedicated DDI studies especially in challenging populations like cancer patients. PMID:24827931

  4. 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

  5. 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

  6. 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...

  7. OPTIMAL RULE SET GENERATION USING PSO ALGORITHM

    Directory of Open Access Journals (Sweden)

    Shampa sengupta

    2014-05-01

    Full Text Available Classification and Prediction is an important research area of data mining. Construction of classifier model for any decision system is an important job for many data mining applications. The objective of developing such a classifier is to classify unlabeled dataset into classes. Here we have applied a discrete Particle Swarm Optimization (PSO algorithm for selecting optimal classification rule sets from huge number of rules possibly exist in a dataset. In the proposed DPSO algorithm, decision matrix approach was used for generation of initial possible classification rules from a dataset. Then the proposed algorithm discovers important or significant rules from all possible classification rules without sacrificing predictive accuracy. The proposed algorithm deals with discrete valued data, and its initial population of candidate solutions contains particles of different sizes. The experiment has been done on the task of optimal rule selection in the data sets collected from UCI repository. Experimental results show that the proposed algorithm can automatically evolve on average the small number of conditions per rule and a few rules per rule set, and achieved better classification performance of predictive accuracy for few classes.

  8. 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

  9. 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

  10. 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 ...

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. The Hip Lag Sign--prospective blinded trial of a new clinical sign to predict hip abductor damage.

    Directory of Open Access Journals (Sweden)

    Alexander Kaltenborn

    Full Text Available This study introduces and validates the Hip Lag Sign, a new clinical parameter to determine hip abductor damage, which appears to be one major cause for greater trochanteric pain syndrome. 26 patients who underwent standardized MRI-examination were prospectively enrolledbetween October 2009 and March 2012. A standard physical examination of the hip was performed, including the Hip Lag Sign as it is defined for the first time in this work. Hip Lag Sign results were statistically compared toMR images, to pain levels measured with the visual analogue scale and to results of the modified Harris Hip Score as a universal and well established diagnostic tool for the hip. Chi2- and Mann-Whitney-U-analysis were applied. Diagnostic accuracy was tested with 2×2-table-calculations.Kappa statistics were used to analyze inter-observer variability. A positive Hip Lag Sign is significantly associated with MRI-proven hip abductor damage (p<0.001. The Hip Lag Sign has a sensitivity of 89.47% and a specificity of 96.55%. The positive and negative predictive values are 94.44%, resp. 93.33%. Its diagnostic Odds Ratio is 239.000 (p<0.001; 95%-CI: 20.031-2827.819. The number needed to diagnose was 1.16.Inter-observer consistency was 98.1% and kappa statistics for inter-observer variability were 0.911. The Hip Lag Sign is specific and sensitive, easy and fast to perform and allows a reliable assessment on the hip abductors' status, especially when there is no access to further diagnostic devices such as MRI for example due to restricted resources like in developing countries. Thus, we recommend the inclusion of the Hip Lag Sign into everyday hip examinations, especially dealing with patients suffering from greater trochanteric pain syndrome.

  16. Predictive models for ocular chronic graft-versus-host disease diagnosis and disease activity in transplant clinical practice.

    Science.gov (United States)

    Curtis, Lauren M; Datiles, Manuel B; Steinberg, Seth M; Mitchell, Sandra A; Bishop, Rachel J; Cowen, Edward W; Mays, Jacqueline; McCarty, John M; Kuzmina, Zoya; Pirsl, Filip; Fowler, Daniel H; Gress, Ronald E; Pavletic, Steven Z

    2015-09-01

    Ocular chronic graft-versus-host disease is one of the most bothersome common complications following allogeneic hematopoietic stem cell transplantation. The National Institutes of Health Chronic Graft-versus-Host Disease Consensus Project provided expert recommendations for diagnosis and organ severity scoring. However, ocular chronic graft-versus-host disease can be diagnosed only after examination by an ophthalmologist. There are no currently accepted definitions of ocular chronic graft-versus-host disease activity. The goal of this study was to identify predictive models of diagnosis and activity for use in clinical transplant practice. A total of 210 patients with moderate or severe chronic graft-versus-host disease were enrolled in a prospective, cross-sectional, observational study (clinicaltrials.gov identifier: 00092235). Experienced ophthalmologists determined presence of ocular chronic graft-versus-host disease, diagnosis and activity. Measures gathered by the transplant clinician included Schirmer's tear test and National Institutes of Health 0-3 Eye Score. Patient-reported outcome measures were the ocular subscale of the Lee Chronic Graft-versus-Host Disease Symptom Scale and Chief Eye Symptom Intensity Score. Altogether, 157 (75%) patients were diagnosed with ocular chronic graft-versus-host disease; 133 of 157 patients (85%) had active disease. In a multivariable model, the National Institutes of Health Eye Score (Pscore (P=0.027). These results support the use of selected transplant clinician- and patient-reported outcome measures for ocular chronic graft-versus-host disease screening when providing care to allogeneic hematopoietic stem cell transplantation survivors with moderate to severe chronic graft-versus-host disease. Prospective studies are needed to determine if the Lee ocular subscale demonstrates adequate responsiveness as a disease activity outcome measure. PMID:26088932

  17. 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.

  18. 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 associate