Cognitive and emotional factors associated with elective breast augmentation among young women.

PubMed

Moser, Stephanie E; Aiken, Leona S

2011-01-01

The purpose of this research was to propose and evaluate a psychosocial model of young women's intentions to obtain breast implants and the preparatory steps taken towards having breast implant surgery. The model integrated anticipated regret, descriptive norms and image norms from the media into the theory of planned behaviour (TPB). Focus groups (n = 58) informed development of measures of outcome expectancies, preparatory steps and normative influence. The model was tested and replicated among two samples of young women who had ever considered getting breast implants (n = 200, n = 152). Intentions and preparatory steps served as outcomes. Model constructs and outcomes were initially assessed; outcomes were re-assessed 11 weeks later. Evaluative attitudes and anticipated regret predicted intentions; in turn, intentions, along with descriptive norms, predicted subsequent preparatory steps. Perceived risk (susceptibility, severity) of negative medical consequences of breast implants predicted anticipated regret, which predicted evaluative attitudes. Intentions and preparatory steps exhibited interplay over time. This research provides the first comprehensive model predicting intentions and preparatory steps towards breast augmentation surgery. It supports the addition of anticipated regret to the TPB and suggests mutual influence between intentions and preparatory steps towards a final behavioural outcome.

Individualized prediction of seizure relapse and outcomes following antiepileptic drug withdrawal after pediatric epilepsy surgery.

PubMed

Lamberink, Herm J; Boshuisen, Kim; Otte, Willem M; Geleijns, Karin; Braun, Kees P J

2018-03-01

The objective of this study was to create a clinically useful tool for individualized prediction of seizure outcomes following antiepileptic drug withdrawal after pediatric epilepsy surgery. We used data from the European retrospective TimeToStop study, which included 766 children from 15 centers, to perform a proportional hazard regression analysis. The 2 outcome measures were seizure recurrence and seizure freedom in the last year of follow-up. Prognostic factors were identified through systematic review of the literature. The strongest predictors for each outcome were selected through backward selection, after which nomograms were created. The final models included 3 to 5 factors per model. Discrimination in terms of adjusted concordance statistic was 0.68 (95% confidence interval [CI] 0.67-0.69) for predicting seizure recurrence and 0.73 (95% CI 0.72-0.75) for predicting eventual seizure freedom. An online prediction tool is provided on www.epilepsypredictiontools.info/ttswithdrawal. The presented models can improve counseling of patients and parents regarding postoperative antiepileptic drug policies, by estimating individualized risks of seizure recurrence and eventual outcome. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Risk factors for Apgar score using artificial neural networks.

PubMed

Ibrahim, Doaa; Frize, Monique; Walker, Robin C

2006-01-01

Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified.

Effect of sample size on multi-parametric prediction of tissue outcome in acute ischemic stroke using a random forest classifier

NASA Astrophysics Data System (ADS)

Forkert, Nils Daniel; Fiehler, Jens

2015-03-01

The tissue outcome prediction in acute ischemic stroke patients is highly relevant for clinical and research purposes. It has been shown that the combined analysis of diffusion and perfusion MRI datasets using high-level machine learning techniques leads to an improved prediction of final infarction compared to single perfusion parameter thresholding. However, most high-level classifiers require a previous training and, until now, it is ambiguous how many subjects are required for this, which is the focus of this work. 23 MRI datasets of acute stroke patients with known tissue outcome were used in this work. Relative values of diffusion and perfusion parameters as well as the binary tissue outcome were extracted on a voxel-by- voxel level for all patients and used for training of a random forest classifier. The number of patients used for training set definition was iteratively and randomly reduced from using all 22 other patients to only one other patient. Thus, 22 tissue outcome predictions were generated for each patient using the trained random forest classifiers and compared to the known tissue outcome using the Dice coefficient. Overall, a logarithmic relation between the number of patients used for training set definition and tissue outcome prediction accuracy was found. Quantitatively, a mean Dice coefficient of 0.45 was found for the prediction using the training set consisting of the voxel information from only one other patient, which increases to 0.53 if using all other patients (n=22). Based on extrapolation, 50-100 patients appear to be a reasonable tradeoff between tissue outcome prediction accuracy and effort required for data acquisition and preparation.

Contribution of neurocognition to 18-month employment outcomes in first-episode psychosis.

PubMed

Karambelas, George J; Cotton, Sue M; Farhall, John; Killackey, Eóin; Allott, Kelly A

2017-10-27

To examine whether baseline neurocognition predicts vocational outcomes over 18 months in patients with first-episode psychosis enrolled in a randomized controlled trial of Individual Placement and Support or treatment as usual. One-hundred and thirty-four first-episode psychosis participants completed an extensive neurocognitive battery. Principal axis factor analysis using PROMAX rotation was used to determine the underlying structure of the battery. Setwise (hierarchical) multiple linear and logistic regressions were used to examine predictors of (1) total hours employed over 18 months and (2) employment status, respectively. Neurocognition factors were entered in the models after accounting for age, gender, premorbid IQ, negative symptoms, treatment group allocation and employment status at baseline. Five neurocognitive factors were extracted: (1) processing speed, (2) verbal learning and memory, (3) knowledge and reasoning, (4) attention and working memory and (5) visual organization and memory. Employment status over 18 months was not significantly predicted by any of the predictors in the final model. Total hours employed over 18 months were significantly predicted by gender (P = .027), negative symptoms (P = .032) and verbal learning and memory (P = .040). Every step of the regression model was a significant predictor of total hours worked overall (final model: P = .013). Verbal learning and memory, negative symptoms and gender were implicated in duration of employment in first-episode psychosis. The other neurocognitive domains did not significantly contribute to the prediction of vocational outcomes over 18 months. Interventions targeting verbal memory may improve vocational outcomes in early psychosis. © 2017 John Wiley & Sons Australia, Ltd.

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Riley, Richard D; Abrams, Keith R

2016-03-30

A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Predictive Value of Glasgow Coma Score and Full Outline of Unresponsiveness Score on the Outcome of Multiple Trauma Patients.

PubMed

Baratloo, Alireza; Shokravi, Masumeh; Safari, Saeed; Aziz, Awat Kamal

2016-03-01

The Full Outline of Unresponsiveness (FOUR) score was developed to compensate for the limitations of Glasgow coma score (GCS) in recent years. This study aimed to assess the predictive value of GCS and FOUR score on the outcome of multiple trauma patients admitted to the emergency department. The present prospective cross-sectional study was conducted on multiple trauma patients admitted to the emergency department. GCS and FOUR scores were evaluated at the time of admission and at the sixth and twelfth hours after admission. Then the receiver operating characteristic (ROC) curve, sensitivity, specificity, as well as positive and negative predictive value of GCS and FOUR score were evaluated to predict patients' outcome. Patients' outcome was divided into discharge with and without a medical injury (motor deficit, coma or death). Finally, 89 patients were studied. Sensitivity and specificity of GCS in predicting adverse outcome (motor deficit, coma or death) were 84.2% and 88.6% at the time of admission, 89.5% and 95.4% at the sixth hour and 89.5% and 91.5% at the twelfth hour, respectively. These values for the FOUR score were 86.9% and 88.4% at the time of admission, 89.5% and 100% at the sixth hour and 89.5% and 94.4% at the twelfth hour, respectively. Findings of this study indicate that the predictive value of FOUR score and GCS on the outcome of multiple trauma patients admitted to the emergency department is similar.

Genomic and Histopathological Tissue Biomarkers That Predict Radiotherapy Response in Localised Prostate Cancer

PubMed Central

Wilkins, Anna; Dearnaley, David; Somaiah, Navita

2015-01-01

Localised prostate cancer, in particular, intermediate risk disease, has varied survival outcomes that cannot be predicted accurately using current clinical risk factors. External beam radiotherapy (EBRT) is one of the standard curative treatment options for localised disease and its efficacy is related to wide ranging aspects of tumour biology. Histopathological techniques including immunohistochemistry and a variety of genomic assays have been used to identify biomarkers of tumour proliferation, cell cycle checkpoints, hypoxia, DNA repair, apoptosis, and androgen synthesis, which predict response to radiotherapy. Global measures of genomic instability also show exciting capacity to predict survival outcomes following EBRT. There is also an urgent clinical need for biomarkers to predict the radiotherapy fraction sensitivity of different prostate tumours and preclinical studies point to possible candidates. Finally, the increased resolution of next generation sequencing (NGS) is likely to enable yet more precise molecular predictions of radiotherapy response and fraction sensitivity. PMID:26504789

Predicting Well-being Longitudinally for Mothers Rearing Offspring with Intellectual and Developmental Disabilities

PubMed Central

Grein, Katherine A.; Glidden, Laraine Masters

2014-01-01

Background Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. Methods The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother, and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well–being. Results Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. Conclusions These findings confirm that 1) Characteristics of the child, mother, and family during childhood can predict outcomes of maternal well-being 20 years later; and 2) Different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent, and family characteristics. PMID:25185956

Predicting Positive Education Outcomes for Emerging Adults in Mental Health Systems of Care.

PubMed

Brennan, Eileen M; Nygren, Peggy; Stephens, Robert L; Croskey, Adrienne

2016-10-01

Emerging adults who receive services based on positive youth development models have shown an ability to shape their own life course to achieve positive goals. This paper reports secondary data analysis from the Longitudinal Child and Family Outcome Study including 248 culturally diverse youth ages 17 through 22 receiving mental health services in systems of care. After 12 months of services, school performance was positively related to youth ratings of school functioning and service participation and satisfaction. Regression analysis revealed ratings of young peoples' perceptions of school functioning, and their experience in services added to the significant prediction of satisfactory school performance, even controlling for sex and attendance. Finally, in addition to expected predictors, participation in planning their own services significantly predicted enrollment in higher education for those who finished high school. Findings suggest that programs and practices based on positive youth development approaches can improve educational outcomes for emerging adults.

Delayed risk stratification, to include the response to initial treatment (surgery and radioiodine ablation), has better outcome predictivity in differentiated thyroid cancer patients.

PubMed

Castagna, Maria Grazia; Maino, Fabio; Cipri, Claudia; Belardini, Valentina; Theodoropoulou, Alexandra; Cevenini, Gabriele; Pacini, Furio

2011-09-01

After initial treatment, differentiated thyroid cancer (DTC) patients are stratified as low and high risk based on clinical/pathological features. Recently, a risk stratification based on additional clinical data accumulated during follow-up has been proposed. To evaluate the predictive value of delayed risk stratification (DRS) obtained at the time of the first diagnostic control (8-12 months after initial treatment). We reviewed 512 patients with DTC whose risk assessment was initially defined according to the American (ATA) and European Thyroid Association (ETA) guidelines. At the time of the first control, 8-12 months after initial treatment, patients were re-stratified according to their clinical status: DRS. Using DRS, about 50% of ATA/ETA intermediate/high-risk patients moved to DRS low-risk category, while about 10% of ATA/ETA low-risk patients moved to DRS high-risk category. The ability of the DRS to predict the final outcome was superior to that of ATA and ETA. Positive and negative predictive values for both ATA (39.2 and 90.6% respectively) and ETA (38.4 and 91.3% respectively) were significantly lower than that observed with the DRS (72.8 and 96.3% respectively, P<0.05). The observed variance in predicting final outcome was 25.4% for ATA, 19.1% for ETA, and 62.1% for DRS. Delaying the risk stratification of DTC patients at a time when the response to surgery and radioiodine ablation is evident allows to better define individual risk and to better modulate the subsequent follow-up.

Early starting, aggressive, and/or callous-unemotional? Examining the overlap and predictive utility of antisocial behavior subtypes

PubMed Central

Hyde, Luke W.; Burt, S. Alexandra; Shaw, Daniel S.; Donnellan, M. Brent; Forbes, Erika E.

2015-01-01

Antisocial behavior (AB) in adolescence predicts problematic outcomes in adulthood. However, researchers have noted marked heterogeneity within the broad group of youth engaging in these destructive behaviors and have attempted to identify those with distinct etiologies and different trajectories of symptoms. In the present study, we evaluate three prominent AB subtyping approaches: age of onset, presence of callous-unemotional (CU) traits, and aggressive versus rule breaking symptoms. We examined the overlap of these subtypes and their predictive validity in a diverse sample of 268 low-income young men followed prospectively from adolescence into emerging adulthood. We found that those with early starting AB were uniquely high on aggressive symptoms but not on CU traits. Early starting AB and both aggression and rule breaking measured during adolescence predicted most subsequent psychiatric and AB outcomes in early adulthood in univariate models, whereas CU traits were only predictive of adolescent arrests, later substance dependence diagnosis, and later CU traits. Finally, after accounting for shared variance among predictor variables, we found that aggressive symptoms explained the most unique variance in predicting several later outcomes (e.g., antisocial personality disorder) over and above other subtyping approaches. Results are discussed in relation to of the utility of existing subtyping approaches to AB, noting that aggression and age of onset, but not CU traits, appear to be the best at predicting later negative outcome. PMID:25603360

Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

PubMed

Hung, Andrew J; Chen, Jian; Che, Zhengping; Nilanon, Tanachat; Jarc, Anthony; Titus, Micha; Oh, Paul J; Gill, Inderbir S; Liu, Yan

2018-05-01

Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting. The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p < 0.001, r = 0.73), LOS (p = 0.05, r = 0.52), and Foley duration (p < 0.001, r = 0.45). The five most relevant APMs, adopted by the RF-50 algorithm in predicting, were largely related to camera manipulation. To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

PubMed Central

Austin, Peter C; Lee, Douglas S

2011-01-01

Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

What predicts performance during clinical psychology training?

PubMed

Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

2014-06-01

While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Longitudinal cross-sectional study using prospective and retrospective data. Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. © 2013 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

Predictive factors for successful clinical outcome 1 year after an intensive combined physical and psychological programme for chronic low back pain.

PubMed

van Hooff, Miranda L; Spruit, Maarten; O'Dowd, John K; van Lankveld, Wim; Fairbank, Jeremy C T; van Limbeek, Jacques

2014-01-01

The aim of this longitudinal study is to determine the factors which predict a successful 1-year outcome from an intensive combined physical and psychological (CPP) programme in chronic low back pain (CLBP) patients. A prospective cohort of 524 selected consecutive CLBP patients was followed. Potential predictive factors included demographic characteristics, disability, pain and cognitive behavioural factors as measured at pre-treatment assessment. The primary outcome measure was the oswestry disability index (ODI). A successful 1-year follow-up outcome was defined as a functional status equivalent to 'normal' and healthy populations (ODI ≤22). The 2-week residential programme fulfills the recommendations in international guidelines. For statistical analysis we divided the database into two equal samples. A random sample was used to develop a prediction model with multivariate logistic regression. The remaining cases were used to validate this model. The final predictive model suggested being 'in employment' at pre-treatment [OR 3.61 (95 % CI 1.80-7.26)] and an initial 'disability score' [OR 0.94 (95 % CI 0.92-0.97)] as significant predictive factors for a successful 1-year outcome (R (2) = 22 %; 67 % correctly classified). There was no predictive value from measures of psychological distress. CLBP patients who are in work and mild to moderately disabled at the start of a CPP programme are most likely to benefit from it and to have a successful treatment outcome. In these patients, the disability score falls to values seen in healthy populations. This small set of factors is easily identified, allowing selection for programme entry and triage to alternative treatment regimes.

Predicting well-being longitudinally for mothers rearing offspring with intellectual and developmental disabilities.

PubMed

Grein, K A; Glidden, L M

2015-07-01

Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well-being. Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. These findings confirm that (1) characteristics of the child, mother and family during childhood can predict outcomes of maternal well-being 20 years later; and (2) different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent and family characteristics. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Developing a risk prediction model for the functional outcome after hip arthroscopy.

PubMed

Stephan, Patrick; Röling, Maarten A; Mathijssen, Nina M C; Hannink, Gerjon; Bloem, Rolf M

2018-04-19

Hip arthroscopic treatment is not equally beneficial for every patient undergoing this procedure. Therefore, the purpose of this study was to develop a clinical prediction model for functional outcome after surgery based on preoperative factors. Prospective data was collected on a cohort of 205 patients having undergone hip arthroscopy between 2011 and 2015. Demographic and clinical variables and patient reported outcome (PRO) scores were collected, and considered as potential predictors. Successful outcome was defined as either a Hip Outcome Score (HOS)-ADL score of over 80% or improvement of 23%, defined by the minimal clinical important difference, 1 year after surgery. The prediction model was developed using backward logistic regression. Regression coefficients were converted into an easy to use prediction rule. The analysis included 203 patients, of which 74% had a successful outcome. Female gender (OR: 0.37 (95% CI 0.17-0.83); p = 0.02), pincer impingement (OR: 0.47 (95% CI 0.21-1.09); p = 0.08), labral tear (OR: 0.46 (95% CI 0.20-1.06); p = 0.07), HOS-ADL score (IQR OR: 2.01 (95% CI 0.99-4.08); p = 0.05), WHOQOL physical (IQR OR: 0.43 (95% CI 0.22-0.87); p = 0.02) and WHOQOL psychological (IQR OR: 2.40 (95% CI 1.38-4.18); p = < 0.01) were factors in the final prediction model of successful functional outcome 1 year after hip arthroscopy. The model's discriminating accuracy turned out to be fair, as 71% (95% CI: 64-80%) of the patients were classified correctly. The developed prediction model can predict the functional outcome of patients that are considered for a hip arthroscopic intervention, containing six easy accessible preoperative risk factors. The model can be further improved trough external validation and/or adding additional potential predictors.

Intra-Operative Frozen Sections for Ovarian Tumors – A Tertiary Center Experience

PubMed Central

Arshad, Nur Zaiti Md; Ng, Beng Kwang; Paiman, Noor Asmaliza Md; Mahdy, Zaleha Abdullah; Noor, Rushdan Mohd

2018-01-01

Background: Accuracy of diagnosis with intra-operative frozen sections is extremely important in the evaluation of ovarian tumors so that appropriate surgical procedures can be selected. Study design: All patients who with intra-operative frozen sections for ovarian masses in a tertiary center over nine years from June 2008 until April 2017 were reviewed. Frozen section diagnosis and final histopathological reports were compared. Main outcome measures: Sensitivity, specificity, positive and negative predictive values of intra-operative frozen section as compared to final histopathological results for ovarian tumors. Results: A total of 92 cases were recruited for final evaluation. The frozen section diagnoses were comparable with the final histopathological reports in 83.7% of cases. The sensitivity, specificity, positive predictive value and negative predictive value for benign and malignant ovarian tumors were 95.6%, 85.1%, 86.0% and 95.2% and 69.2%, 100%, 100% and 89.2% respectively. For borderline ovarian tumors, the sensitivity and specificity were 76.2% and 88.7%, respectively; the positive predictive value was 66.7% and the negative predictive value was 92.7%. Conclusion: The accuracy of intra-operative frozen section diagnoses for ovarian tumors is high and this approach remains a reliable option in assessing ovarian masses intra-operatively. PMID:29373916

Prediction versus aetiology: common pitfalls and how to avoid them.

PubMed

van Diepen, Merel; Ramspek, Chava L; Jager, Kitty J; Zoccali, Carmine; Dekker, Friedo W

2017-04-01

Prediction research is a distinct field of epidemiologic research, which should be clearly separated from aetiological research. Both prediction and aetiology make use of multivariable modelling, but the underlying research aim and interpretation of results are very different. Aetiology aims at uncovering the causal effect of a specific risk factor on an outcome, adjusting for confounding factors that are selected based on pre-existing knowledge of causal relations. In contrast, prediction aims at accurately predicting the risk of an outcome using multiple predictors collectively, where the final prediction model is usually based on statistically significant, but not necessarily causal, associations in the data at hand.In both scientific and clinical practice, however, the two are often confused, resulting in poor-quality publications with limited interpretability and applicability. A major problem is the frequently encountered aetiological interpretation of prediction results, where individual variables in a prediction model are attributed causal meaning. This article stresses the differences in use and interpretation of aetiological and prediction studies, and gives examples of common pitfalls. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Long-term surgical outcomes of retinal detachment in patients with Stickler syndrome

PubMed Central

Reddy, Devasis N; Yonekawa, Yoshihiro; Thomas, Benjamin J; Nudleman, Eric D; Williams, George A

2016-01-01

Purpose The aim of the study was to present the long-term anatomical and visual outcomes of retinal detachment repair in patients with Stickler syndrome. Patients and methods This study is a retrospective, interventional, consecutive case series of patients with Stickler syndrome undergoing retinal reattachment surgery from 2009 to 2014 at the Associated Retinal Consultants, William Beaumont Hospital. Results Sixteen eyes from 13 patients were identified. Patients underwent a mean of 3.1 surgical interventions (range: 1–13) with a mean postoperative follow-up of 94 months (range: 5–313 months). Twelve eyes (75%) developed proliferative vitreoretinopathy. Retinal reattachment was achieved in 100% of eyes, with ten eyes (63%) requiring silicone oil tamponade at final follow-up. Mean preoperative visual acuity (VA) was 20/914, which improved to 20/796 at final follow-up (P=0.81). There was a significant correlation between presenting and final VA (P<0.001), and patients with poorer presenting VA were more likely to require silicone oil tamponade at final follow-up (P=0.04). Conclusion Repair of retinal detachment in patients with Stickler syndrome often requires multiple surgeries, and visual outcomes are variable. Presenting VA is significantly predictive of long-term VA outcomes. PMID:27574392

Predicting risky drinking outcomes longitudinally: what kind of advance notice can we get?

PubMed

Zucker, Robert A; Wong, Maria M; Clark, Duncan B; Leonard, Kenneth E; Schulenberg, John E; Cornelius, Jack R; Fitzgerald, Hiram E; Homish, Gregory G; Merline, Alicia; Nigg, Joel T; O'Malley, Patrick M; Puttler, Leon I

2006-02-01

This paper summarizes the proceedings of a symposium presented at the 2005 Research Society on Alcoholism meeting in Santa Barbara, California, that spans the interval from toddlerhood to early middle adulthood and addresses questions about how far ahead developmentally we can anticipate alcohol problems and related substance use disorder and how such work informs our understanding of the causes and course of alcohol problems and alcohol use disorder. The context of these questions both historically and developmentally is set by Robert Zucker in an introductory section. Next, Maria Wong and colleagues describe the developmental trajectories of behavioral and affective control from preschool to early adolescence in a high risk for alcoholism longitudinal study and demonstrate their ability to predict alcohol and drug outcomes in adolescence. Duncan Clark and Jack Cornelius follow with a report on the predictive utility of parental disruptive behavior disorders in predicting onset of alcohol problems in their adolescent offspring in late adolescence. Next, Kenneth Leonard and Gregory Homish report on adult development study findings relating baseline individual, spouse, and peer network drinking indicators at marriage onset that distinguish different patterns of stability and change in alcohol problems over the first 2 years of marriage. In the final paper, John Schulenberg and colleagues, utilizing national panel data from the Monitoring the Future Study, which cover the 18- to 35-year age span, show how trajectories of alcohol use in early adulthood predict differential alcohol abuse and dependence outcomes at age 35. Finally, Robert Zucker examines the degree to which the core symposium questions are answered and comments on next step research and clinical practice changes that are called for by these findings.

Predicting Risky Drinking Outcomes Longitudinally: What Kind of Advance Notice Can We Get?

PubMed Central

Zucker, Robert A.; Wong, Maria M.; Clark, Duncan B.; Leonard, Kenneth E.; Schulenberg, John E.; Cornelius, Jack R.; Fitzgerald, Hiram E.; Homish, Gregory G.; Merline, Alicia; Nigg, Joel T.; O’Malley, Patrick M.; Puttler, Leon I.

2006-01-01

This paper summarizes the proceedings of a symposium presented at the 2005 Research Society on Alcoholism meeting in Santa Barbara, California, that spans the interval from toddlerhood to early middle adulthood and addresses questions about how far ahead developmentally we can anticipate alcohol problems and related substance use disorder and how such work informs our understanding of the causes and course of alcohol problems and alcohol use disorder. The context of these questions both historically and developmentally is set by Robert Zucker in an introductory section. Next, Maria Wong and colleagues describe the developmental trajectories of behavioral and affective control from preschool to early adolescence in a high risk for alcoholism longitudinal study and demonstrate their ability to predict alcohol and drug outcomes in adolescence. Duncan Clark and Jack Cornelius follow with a report on the predictive utility of parental disruptive behavior disorders in predicting onset of alcohol problems in their adolescent offspring in late adolescence. Next, Kenneth Leonard and Gregory Homish report on adult development study findings relating baseline individual, spouse, and peer network drinking indicators at marriage onset that distinguish different patterns of stability and change in alcohol problems over the first 2 years of marriage. In the final paper, John Schulenberg and colleagues, utilizing national panel data from the Monitoring the Future Study, which cover the 18- to 35-year age span, show how trajectories of alcohol use in early adulthood predict differential alcohol abuse and dependence outcomes at age 35. Finally, Robert Zucker examines the degree to which the core symposium questions are answered and comments on next step research and clinical practice changes that are called for by these findings. PMID:16441273

Vital Signs: How Early Can Resident Evaluation Predict Acquisition of Competency in Surgical Pathology?

PubMed Central

Ducatman, Barbara S.; Williams, H. James; Hobbs, Gerald; Gyure, Kymberly A.

2009-01-01

Objectives To determine whether a longitudinal, case-based evaluation system can predict acquisition of competency in surgical pathology and how trainees at risk can be identified early. Design Data were collected for trainee performance on surgical pathology cases (how well their diagnosis agreed with the faculty diagnosis) and compared with training outcomes. Negative training outcomes included failure to complete the residency, failure to pass the anatomic pathology component of the American Board of Pathology examination, and/or failure to obtain or hold a position immediately following training. Findings Thirty-three trainees recorded diagnoses for 54 326 surgical pathology cases, with outcome data available for 15 residents. Mean case-based performance was significantly higher for those with positive outcomes, and outcome status could be predicted as early as postgraduate year-1 (P  =  .0001). Performance on the first postgraduate year-1 rotation was significantly associated with the outcome (P  =  .02). Although trainees with unsuccessful outcomes improved their performance more rapidly, they started below residents with successful outcomes and did not make up the difference during training. There was no significant difference in Step 1 or 2 United States Medical Licensing Examination (USMLE) scores when compared with performance or final outcomes (P  =  .43 and P  =  .68, respectively) and the resident in-service examination (RISE) had limited predictive ability. Discussion Differences between successful- and unsuccessful-outcome residents were most evident in early residency, ideal for designing interventions or counseling residents to consider another specialty. Conclusion Our longitudinal case-based system successfully identified trainees at risk for failure to acquire critical competencies for surgical pathology early in the program. PMID:21975705

Effects of laparoscopic myotomy on the esophageal motility pattern of esophageal achalasia as measured by high-resolution manometry.

PubMed

Salvador, Renato; Savarino, Edoardo; Pesenti, Elisa; Spadotto, Lorenzo; Voltarel, Guerrino; Capovilla, Giovanni; Cavallin, Francesco; Nicoletti, Loredana; Valmasoni, Michele; Ruol, Alberto; Merigliano, Stefano; Costantini, Mario

2017-09-01

Esophageal achalasia can be classified on the grounds of three distinct manometric patterns that correlate well with final outcome after laparoscopic Heller-Dor myotomy (LHM). No analytical data are available, however, on the postoperative picture and its possible correlation with final outcome. The aims of this study were: (a) to investigate whether manometric patterns change after LHM for achalasia; (b) to ascertain whether postoperative patterns and/or changes can predict final outcome; and (c) to test the hypothesis that the three known patterns represent different stages in the evolution of the disease. During the study period, we prospectively enlisted 206 consecutive achalasia patients who were assessed using high-resolution manometry (HRM) before undergoing LHM. Symptoms were scored using a detailed questionnaire. Barium swallow, endoscopy and HRM were performed, before and again 6 months after surgery. Preoperative HRM revealed the three known patterns with statistically different esophageal diameters (pattern I having the largest), and patients with pattern I had the highest symptom scores. The surgical treatment failed in 10 cases (4.9%). The only predictor of final outcome was the preoperative manometric pattern (p = 0.01). All patients with pattern I preoperatively had the same pattern afterward, whereas nearly 50% of patients with pattern III before LHM had patterns I or II after surgery. There were no cases showing the opposite trend. Neither a change of manometric pattern after surgery nor a patient's postoperative pattern was a predictor of final outcome, whereas preoperative pattern confirmed its prognostic significance. The three manometric patterns distinguishable in achalasia may represent different stages in the disease's evolution, pattern III and pattern I coinciding with the early and final stages of the disease, respectively.

Unavowed Abstention Can Overturn Poll Predictions

NASA Astrophysics Data System (ADS)

Galam, Serge

2018-03-01

I revisit the 2017 French Presidential election which opposed the far right National Front candidate Marine Le Pen against the center candidate Emmanuel Macron. While voting intentions for Le Pen stuck below 50% and polls kept predicting her failure, I warned on the emergence of a novel phenomenon I defined as unavowed abstention, which could suddenly reverse the ranking at Le Pen benefit on the voting day. My warning got a massive media coverage. She eventually lost the runoff at a score worse than predicted by the polls. Using a quantitative mathematical framing, which reveals the existence of tipping points in respective turnouts, I show that the predicted phenomenon of unavowed abstention did happen. But instead of shattering the expected outcome, against all odds it occurred at Le Pen expense, therefore without impact on the final outcome. The results shed a new light on other national cases such as Obama and Trump victories in the US.

Daily Autonomy Support and Sexual Identity Disclosure Predicts Daily Mental and Physical Health Outcomes.

PubMed

Legate, Nicole; Ryan, Richard M; Rogge, Ronald D

2017-06-01

Using a daily diary methodology, we examined how social environments support or fail to support sexual identity disclosure, and associated mental and physical health outcomes. Results showed that variability in disclosure across the diary period related to greater psychological well-being and fewer physical symptoms, suggesting potential adaptive benefits to selectively disclosing. A multilevel path model indicated that perceiving autonomy support in conversations predicted more disclosure, which in turn predicted more need satisfaction, greater well-being, and fewer physical symptoms that day. Finally, mediation analyses revealed that disclosure and need satisfaction explained why perceiving autonomy support in a conversation predicted greater well-being and fewer physical symptoms. That is, perceiving autonomy support in conversations indirectly predicted greater wellness through sexual orientation disclosure, along with feeling authentic and connected in daily interactions with others. Discussion highlights the role of supportive social contexts and everyday opportunities to disclose in affecting sexual minority mental and physical health.

Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds.

PubMed

Nagaraja, Sridevi; Chen, Lin; DiPietro, Luisa A; Reifman, Jaques; Mitrophanov, Alexander Y

2018-02-20

Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds. We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers. We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy. Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.

Expressions of positive emotion in women's college yearbook pictures and their relationship to personality and life outcomes across adulthood.

PubMed

Harker, L; Keltner, D

2001-01-01

To test hypotheses about positive emotion, the authors examined the relationship of positive emotional expression in women's college pictures to personality, observer ratings, and life outcomes. Consistent with the notion that positive emotions help build personal resources, positive emotional expression correlated with the self-reported personality traits of affiliation, competence, and low negative emotionality across adulthood and predicted changes in competence and negative emotionality. Observers rated women displaying more positive emotion more favorably on several personality dimensions and expected interactions with them to be more rewarding; thus, demonstrating the beneficial social consequences of positive emotions. Finally, positive emotional expression predicted favorable outcomes in marriage and personal well-being up to 30 years later. Controlling for physical attractiveness and social desirability had little impact on these findings.

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wittwehr, Clemens; Aladjov, Hristo; Ankley, Gerald

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework has emerged as a systematic approach for organizing knowledge that supports such inference. We argue that this systematic organization of knowledge can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment.more » Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment.« less

Prediction and uncertainty in human Pavlovian to instrumental transfer.

PubMed

Trick, Leanne; Hogarth, Lee; Duka, Theodora

2011-05-01

Attentional capture and behavioral control by conditioned stimuli have been dissociated in animals. The current study assessed this dissociation in humans. Participants were trained on a Pavlovian schedule in which 3 visual stimuli, A, B, and C, predicted the occurrence of an aversive noise with 90%, 50%, or 10% probability, respectively. Participants then went on to separate instrumental training in which a key-press response canceled the aversive noise with a .5 probability on a variable interval schedule. Finally, in the transfer phase, the 3 Pavlovian stimuli were presented in this instrumental schedule and were no longer differentially predictive of the outcome. Observing times and gaze dwell time indexed attention to these stimuli in both training and transfer. Aware participants acquired veridical outcome expectancies in training--that is, A > B > C, and these expectancies persisted into transfer. Most important, the transfer effect accorded with these expectancies, A > B > C. By contrast, observing times accorded with uncertainty--that is, they showed B > A = C during training, and B < A = C in the transfer phase. Dwell time bias supported this association between attention and uncertainty, although these data showed a slightly more complicated pattern. Overall, the study suggests that transfer is linked to outcome prediction and is dissociated from attention to conditioned stimuli, which is linked to outcome uncertainty.

Assessing Performance Outcomes of New Graduates Utilizing Simulation in a Military Transition Program

DTIC Science & Technology

2013-01-01

pretest and posttests ( p G .05). An additional analysis was conducted to determine if there were differences in outcomes based on whether par- ticipants...would be predicted based on FIGURE 1 Pretest and posttest mean performance scores for all 26 objectives of the anaphylaxis scenario. FIGURE 2 Pretest ...clinical practice. Another limitation of the study is the use of a pretest / posttest designwithout a control group for comparison of results. Finally

Decision making in a multidisciplinary cancer team: does team discussion result in better quality decisions?

PubMed

Kee, Frank; Owen, Tracy; Leathem, Ruth

2004-01-01

To establish whether treatment recommendations made by clinicians concur with the best outcomes predicted from their prognostic estimates and whether team discussion improves the quality or outcome of their decision making, the authors studied real-time decision making by a lung cancer team. Clinicians completed pre- and postdiscussion questionnaires for 50 newly diagnosed patients. For each patient/doctor pairing, a decision model determined the expected patient outcomes from the clinician's prognostic estimates. The difference between the expected utility of the recommended treatment and the maximum utility derived from the clinician's predictions of the outcomes (the net utility loss) following all potential treatment modalities was calculated as an indicator of quality of the decision. The proportion of treatment decisions changed by the multidisciplinary team discussion was also calculated. Insofar as the change in net utility loss brought about by multidisciplinary team discussion was not significantly different from zero, team discussion did not improve the quality of decision making overall. However, given the modest power of the study, these findings must be interpreted with caution. In only 23 of 87 instances (26%) in which an individual specialist's initial treatment preference differed from the final group judgment did the specialist finally concur with the group treatment choice after discussion. This study does not support the theory that team discussion improves decision making by closing a knowledge gap.

Perceptions of child sexual abuse in a hypothetical cybersexploitation case: the importance of perpetrator honesty, outcome type, and respondent gender.

PubMed

Davies, Michelle; Rogers, Paul; Hood, Paul A

2009-01-01

This study investigated perceptions of child sexual abuse in a hypothetical cybersexploitation case. Men were predicted to be more negative toward the victim than were women. Victims were predicted to be more negatively judged when they consented to sex than when they did not and when they were lied to than when they were not. Two hundred and seventy-six respondents read a sexual abuse depiction in which the perpetrator's disclosure about his age (being honest from the outset, lying, or refusing to disclose when questioned) and the final outcome of the meeting (consensual verses nonconsensual sexual intercourse) were varied between subjects. Respondents then completed a 17-item attribution scale. ANOVAs revealed broad support for the predictions. Results have implications for education about cybercrime.

Predicting the chance of live birth for women undergoing IVF: a novel pretreatment counselling tool.

PubMed

Dhillon, R K; McLernon, D J; Smith, P P; Fishel, S; Dowell, K; Deeks, J J; Bhattacharya, S; Coomarasamy, A

2016-01-01

Which pretreatment patient variables have an effect on live birth rates following assisted conception? The predictors in the final multivariate logistic regression model found to be significantly associated with reduced chances of IVF/ICSI success were increasing age (particularly above 36 years), tubal factor infertility, unexplained infertility and Asian or Black ethnicity. The two most widely recognized prediction models for live birth following IVF were developed on data from 1991 to 2007; pre-dating significant changes in clinical practice. These existing IVF outcome prediction models do not incorporate key pretreatment predictors, such as BMI, ethnicity and ovarian reserve, which are readily available now. In this cohort study a model to predict live birth was derived using data collected from 9915 women who underwent IVF/ICSI treatment at any CARE (Centres for Assisted Reproduction) clinic from 2008 to 2012. Model validation was performed on data collected from 2723 women who underwent treatment in 2013. The primary outcome for the model was live birth, which was defined as any birth event in which at least one baby was born alive and survived for more than 1 month. Data were collected from 12 fertility clinics within the CARE consortium in the UK. Multivariable logistic regression was used to develop the model. Discriminatory ability was assessed using the area under receiver operating characteristic (AUROC) curve, and calibration was assessed using calibration-in-the-large and the calibration slope test. The predictors in the final model were female age, BMI, ethnicity, antral follicle count (AFC), previous live birth, previous miscarriage, cause and duration of infertility. Upon assessing predictive ability, the AUROC curve for the final model and validation cohort was (0.62; 95% confidence interval (CI) 0.61-0.63) and (0.62; 95% CI 0.60-0.64) respectively. Calibration-in-the-large showed a systematic over-estimation of the predicted probability of live birth (Intercept (95% CI) = -0.168 (-0.252 to -0.084), P < 0.001). However, the calibration slope test was not significant (slope (95% CI) = 1.129 (0.893-1.365), P = 0.28). Due to the calibration-in-the-large test being significant we recalibrated the final model. The recalibrated model showed a much-improved calibration. Our model is unable to account for factors such as smoking and alcohol that can affect IVF/ICSI outcome and is somewhat restricted to representing the ethnic distribution and outcomes for the UK population only. We were unable to account for socioeconomic status and it may be that by having 75% of the population paying privately for their treatment, the results cannot be generalized to people of all socioeconomic backgrounds. In addition, patients and clinicians should understand this model is designed for use before treatment begins and does not include variables that become available (oocyte, embryo and endometrial) as treatment progresses. Finally, this model is also limited to use prior to first cycle only. To our knowledge, this is the first study to present a novel, up-to-date model encompassing three readily available prognostic factors; female BMI, ovarian reserve and ethnicity, which have not previously been used in prediction models for IVF outcome. Following geographical validation, the model can be used to build a user-friendly interface to aid decision-making for couples and their clinicians. Thereafter, a feasibility study of its implementation could focus on patient acceptability and quality of decision-making. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes.

PubMed

Wang, Yuanjia; Chen, Tianle; Zeng, Donglin

2016-01-01

Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse probability weighting or rank-based regression, which may be inefficient. In this paper, we develop a new support vector hazards machine (SVHM) approach to predict censored outcomes. Our method is based on predicting the counting process associated with the time-to-event outcomes among subjects at risk via a series of support vector machines. Introducing counting processes to represent time-to-event data leads to a connection between support vector machines in supervised learning and hazards regression in standard survival analysis. To account for different at risk populations at observed event times, a time-varying offset is used in estimating risk scores. The resulting optimization is a convex quadratic programming problem that can easily incorporate non-linearity using kernel trick. We demonstrate an interesting link from the profiled empirical risk function of SVHM to the Cox partial likelihood. We then formally show that SVHM is optimal in discriminating covariate-specific hazard function from population average hazard function, and establish the consistency and learning rate of the predicted risk using the estimated risk scores. Simulation studies show improved prediction accuracy of the event times using SVHM compared to existing machine learning methods and standard conventional approaches. Finally, we analyze two real world biomedical study data where we use clinical markers and neuroimaging biomarkers to predict age-at-onset of a disease, and demonstrate superiority of SVHM in distinguishing high risk versus low risk subjects.

Monitoring risk-adjusted outcomes in congenital heart surgery: does the appropriateness of a risk model change with time?

PubMed

Tsang, Victor T; Brown, Katherine L; Synnergren, Mats Johanssen; Kang, Nicholas; de Leval, Marc R; Gallivan, Steve; Utley, Martin

2009-02-01

Risk adjustment of outcomes in pediatric congenital heart surgery is challenging due to the great diversity in diagnoses and procedures. We have previously shown that variable life-adjusted display (VLAD) charts provide an effective graphic display of risk-adjusted outcomes in this specialty. A question arises as to whether the risk model used remains appropriate over time. We used a recently developed graphic technique to evaluate the performance of an existing risk model among those patients at a single center during 2000 to 2003 originally used in model development. We then compared the distribution of predicted risk among these patients with that among patients in 2004 to 2006. Finally, we constructed a VLAD chart of risk-adjusted outcomes for the latter period. Among 1083 patients between April 2000 and March 2003, the risk model performed well at predicted risks above 3%, underestimated mortality at 2% to 3% predicted risk, and overestimated mortality below 2% predicted risk. There was little difference in the distribution of predicted risk among these patients and among 903 patients between June 2004 and October 2006. Outcomes for the more recent period were appreciably better than those expected according to the risk model. This finding cannot be explained by any apparent bias in the risk model combined with changes in case-mix. Risk models can, and hopefully do, become out of date. There is scope for complacency in the risk-adjusted audit if the risk model used is not regularly recalibrated to reflect changing standards and expectations.

Predictive factors of open globe injury in patients requiring vitrectomy.

PubMed

Pimolrat, Weeraya; Choovuthayakorn, Janejit; Watanachai, Nawat; Patikulsila, Direk; Kunavisarut, Paradee; Chaikitmongkol, Voraporn; Ittipunkul, Nimitr

2014-01-01

To determine the outcomes and predictive factors of patients with open globe injury requiring pars plana vitrectomy (PPV). The medical records of 114 patients age 10 years or older who had undergone PPV due to ocular trauma, with at least 6 months follow up, were retrospectively reviewed. The mean age of the patients was 42 (SD14) years, with males accounting for 89% of the cases. Penetrating eye injury was the most common injury mechanism (43%) with most injuries occurring secondary to work related incidents (54%). After surgical interventions, 78% of the patients had visual improvement of one or more Snellen lines, while no light perception occurred in 10%. Anatomical attachment was achieved in 87% of eyes at the final follow up. Logistic regression analysis showed that the presence of a relative afferent pupillary defect (RAPD) was a significant predictive factor of visual outcome, while initial retinal detachment was a significant predictor of anatomical outcome. Pupillary reaction is an important presenting ocular sign in estimating the post-vitrectomy poor visual outcome for open globe injury. Vision was restored and improved in more than half of the patients in this study; however, long-term sequelae should be monitored. Copyright © 2013 Elsevier Ltd. All rights reserved.

Experiences of Discrimination among Chinese American Adolescents and the Consequences for Socioemotional and Academic Development

PubMed Central

Benner, Aprile D.; Kim, Su Yeong

2009-01-01

This longitudinal study examined the influences of discrimination on socioemotional adjustment and academic performance for a sample of 444 Chinese American adolescents. Using autoregressive and cross-lagged techniques, results indicate that discrimination in early adolescence predicted depressive symptoms, alienation, school engagement, and grades in middle adolescence, but early socioemotional adjustment and academic performance did not predict later experiences of discrimination. Further, our investigation of whether earlier or contemporaneous experiences of discrimination influenced developmental outcomes in middle adolescence indicated differential effects, with contemporaneous experiences of discrimination affecting socioemotional adjustment, while earlier discrimination was more influential for academic performance. Finally, we found a persistent negative effect of acculturation on the link between discrimination and adolescents’ developmental outcomes, such that those adolescents who were more acculturated (in this case, higher in American orientation) experienced more deleterious effects of discrimination on both socioemotional and academic outcomes. PMID:19899924

Exposure and response prevention process predicts treatment outcome in youth with OCD.

PubMed

Kircanski, Katharina; Peris, Tara S

2015-04-01

Recent research on the treatment of adults with anxiety disorders suggests that aspects of the in-session exposure therapy process are relevant to clinical outcomes. However, few comprehensive studies have been conducted with children and adolescents. In the present study, 35 youth diagnosed with primary obsessive-compulsive disorder (OCD; M age = 12.9 years, 49% male, 63% Caucasian) completed 12 sessions of exposure and response prevention (ERP) in one of two treatment conditions as part of a pilot randomized controlled testing of a family focused intervention for OCD. Key exposure process variables, including youth self-reported distress during ERP and the quantity and quality of ERP completed, were computed. These variables were examined as predictors of treatment outcomes assessed at mid-treatment, post-treatment, and three-month follow-up, partialing treatment condition. In general, greater variability of distress during ERP and completing a greater proportion of combined exposures (i.e., exposures targeting more than one OC symptom at once) were predictive of better outcomes. Conversely, greater distress at the end of treatment was generally predictive of poorer outcomes. Finally, several variables, including within- and between-session decreases in distress during ERP, were not consistently predictive of outcomes. Findings signal potentially important facets of exposure for youth with OCD and have implications for treatment. A number of results also parallel recent findings in the adult literature, suggesting that there may be some continuity in exposure processes from child to adult development. Future work should examine additional measures of exposure process, such as psychophysiological arousal during exposure, in youth.

Accuracy of SOFA score in prediction of 30-day outcome of critically ill patients.

PubMed

Safari, Saeed; Shojaee, Majid; Rahmati, Farhad; Barartloo, Alireza; Hahshemi, Behrooz; Forouzanfar, Mohammad Mehdi; Mohammadi, Elham

2016-12-01

Researchers have attempted to design various scoring systems to determine the severity and predict the outcome of critically ill patients. The present study aimed to evaluate the accuracy of SOFA score in predicting 1-month outcome of these patients in emergency department. The present study is a prospective cross-sectional study of >18 year old non-trauma critically ill patients presented to EDs of 3 hospitals, Tehran, Iran, during October 2014 to October 2015. Baseline characteristics, SOFA score variables, and 1-month outcome of patients were recorded and screening performance characteristics of the score were calculated using STATA 11 software. 140 patients with the mean age of 68.36 ± 18.62 years (18-95) were included (53.5% male). The most common complaints were decrease in level of consciousness (76.43%) and sepsis (60.0%), were the most frequent final diagnoses. Mean SOFA score of the patients was 7.13 ± 2.36 (minimum 2 and maximum 16). 72 (51.43%) patients died during the following 30 days and 16 (11.43%) patients were affected with multiple organ failure. Area under the ROC curve of SOFA score in predicting mortality of studied patients was 0.73 (95%CI: 0.65-0.81) (Fig. 2). Table 2 depicts screening performance characteristics of this scale in prediction of 1-month mortality in the best cut-off point of ≥7. At this cut-off point, sensitivity and specificity of SOFA in predicting 1-month mortality were 75% and 63.23%, respectively. Findings of the present study showed that SOFA scoring system has fair accuracy in predicting 1-month mortality of critically ill patients. However, until a more reliable scoring system is developed, SOFA might be useful for narrative prediction of patient outcome considering its acceptable likelihood ratios.

Free range users and one hit wonders: community users of an Internet-based cognitive behaviour therapy program.

PubMed

Christensen, Helen; Griffiths, Kathy; Groves, Chloe; Korten, Ailsa

2006-01-01

Little is known about the predictors of symptom change or the methods that might increase user 'compliance' on websites designed to improve mental health outcomes. The present paper: (i) examines predictors of expected final depression and anxiety scores on the MoodGYM website as a function of user characteristics; and (ii) compares the compliance rates of the original site with the new public version of the site (MoodGYM Mark II). The latter site requires compulsory completion of 'core' online assessments and may increase completion of site questionnaires. MoodGYM Mark I participants were 19,607 visitors (public registrants) between April 2001 and September 2003 plus 182 participants who had been randomly assigned to MoodGYM in an earlier trial (The BlueMood Trial). MoodGYM Mark II participants were 38,791 public registrants of the MoodGYM Mark II site collected between September 2003 and October 2004. Symptom assessments are repeated within the website intervention to allow the examination of change in symptoms. Outcome variables were gender, initial depression severity scores, number of assessments completed and final anxiety and depression scores. Men are predicted to be 0.19 units (SE=0.095) higher than women on depression, controlling for the initial depression level and number of modules completed. For initial depression scores above 2, it is predicted that the final score will indicate improvement relative to the initial score, the magnitude of the improvement increasing as a function of the number of modules attempted. For initial anxiety scores above 2, it is predicted that the final score will indicate improvement relative to the initial score, the magnitude of the improvement increasing as a function of the number of modules attempted. Mark II registrants were more likely than to Mark I registrants to complete onsite assessments. Visitors to the MoodGYM site are likely to have better psychological outcomes if they complete more of the site material. Compulsory completion of core sections increases assessment completion. There is a need to examine further the significance of attrition from online interventions, to develop methods of handling missing data, and to investigate strategies to improve visitor dropout.

Self-determination theory and diminished functioning: the role of interpersonal control and psychological need thwarting.

PubMed

Bartholomew, Kimberley J; Ntoumanis, Nikos; Ryan, Richard M; Bosch, Jos A; Thøgersen-Ntoumani, Cecilie

2011-11-01

Drawing from self-determination theory, three studies explored the social-environmental conditions that satisfy versus thwart psychological needs and, in turn, affect psychological functioning and well-being or ill-being. In cross-sectional Studies 1 and 2, structural equation modeling analyses supported latent factor models in which need satisfaction was predicted by athletes' perceptions of autonomy support, and need thwarting was better predicted by coach control. Athletes' perceptions of need satisfaction predicted positive outcomes associated with sport participation (vitality and positive affect), whereas need thwarting more consistently predicted maladaptive outcomes (disordered eating, burnout, depression, negative affect, and physical symptoms). In addition, athletes' perceptions of psychological need thwarting were significantly associated with perturbed physiological arousal (elevated levels of secretory immunoglobulin A) prior to training. The final study involved the completion of a diary and supported the relations observed in the cross-sectional studies at a daily level. These findings have important implications for the operationalization and measurement of interpersonal styles and psychological needs.

Visual outcome in Japanese patients with Acanthamoeba keratitis.

PubMed

Yamazoe, K; Yamamoto, Y; Shimazaki-Den, S; Shimazaki, J

2012-04-01

To identify prognostic factors affecting visual outcome in Acanthamoeba keratitis (AK) treated with topical chlorhexidine gluconate (CHG). A total of 35 eyes in 34 patients with AK were treated with 0.02% topical CHG. Patients were divided into two groups according to the final visual outcome: Group 1, final visual acuity (VA) of 20/25 or greater (22 eyes); Group 2, less than 20/25 (13 eyes). We compared these groups and evaluated the effectiveness of topical CHG compared with outcomes in previous reports. Ring infiltrate was observed more often in Group 2 (4.5% vs 61.5%, OR 33.6, 95% confidence interval (CI) 3.4-333.9, P<0.01). The duration between onset and diagnosis of AK was significantly longer (24.9 days vs 48.4 days, OR 1.03, 95% CI 1.00-1.06, P = 0.04) and VA at initial examination (log MAR) significantly lower (0.47 vs 1.59, OR 25.5, 95% CI 3.4-186.7, P<0.01) in Group 2 (visual outcome <20/25). Multivariate analysis revealed that only VA at initial examination was independently associated with worse visual outcome (adjusted OR 24.5, 95% CI 1.9-312.6, P=0.01). Seventeen (85.0%) of the 20 eyes diagnosed within 1 month and 24 (82.8%) of 29 eyes diagnosed within 2 months achieved a VA of 20/40 or greater. VA at initial examination was the most predictive factors for final visual outcome in AK. Topical CHG was comparably effective to other treatments, including polyhexamethyl biguanide and propamidine isethionate.

Predicting Long-Term Global Outcome after Traumatic Brain Injury: Development of a Practical Prognostic Tool Using the Traumatic Brain Injury Model Systems National Database.

PubMed

Walker, William C; Stromberg, Katharine A; Marwitz, Jennifer H; Sima, Adam P; Agyemang, Amma A; Graham, Kristin M; Harrison-Felix, Cynthia; Hoffman, Jeanne M; Brown, Allen W; Kreutzer, Jeffrey S; Merchant, Randall

2018-05-16

For patients surviving serious traumatic brain injury (TBI), families and other stakeholders often desire information on long-term functional prognosis, but accurate and easy-to-use clinical tools are lacking. We aimed to build utilitarian decision trees from commonly collected clinical variables to predict Glasgow Outcome Scale (GOS) functional levels at 1, 2, and 5 years after moderate-to-severe closed TBI. Flexible classification tree statistical modeling was used on prospectively collected data from the TBI-Model Systems (TBIMS) inception cohort study. Enrollments occurred at 17 designated, or previously designated, TBIMS inpatient rehabilitation facilities. Analysis included all participants with nonpenetrating TBI injured between January 1997 and January 2017. Sample sizes were 10,125 (year-1), 8,821 (year-2), and 6,165 (year-5) after cross-sectional exclusions (death, vegetative state, insufficient post-injury time, and unavailable outcome). In our final models, post-traumatic amnesia (PTA) duration consistently dominated branching hierarchy and was the lone injury characteristic significantly contributing to GOS predictability. Lower-order variables that added predictability were age, pre-morbid education, productivity, and occupational category. Generally, patient outcomes improved with shorter PTA, younger age, greater pre-morbid productivity, and higher pre-morbid vocational or educational achievement. Across all prognostic groups, the best and worst good recovery rates were 65.7% and 10.9%, respectively, and the best and worst severe disability rates were 3.9% and 64.1%. Predictability in test data sets ranged from C-statistic of 0.691 (year-1; confidence interval [CI], 0.675, 0.711) to 0.731 (year-2; CI, 0.724, 0.738). In conclusion, we developed a clinically useful tool to provide prognostic information on long-term functional outcomes for adult survivors of moderate and severe closed TBI. Predictive accuracy for GOS level was demonstrated in an independent test sample. Length of PTA, a clinical marker of injury severity, was by far the most critical outcome determinant.

MRI textures as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma

NASA Astrophysics Data System (ADS)

Langenhuizen, P. P. J. H.; Legters, M. J. W.; Zinger, S.; Verheul, H. B.; Leenstra, S.; de With, P. H. N.

2018-02-01

Vestibular schwannomas (VS) are benign brain tumors that can be treated with high-precision focused radiation with the Gamma Knife in order to stop tumor growth. Outcome prediction of Gamma Knife radiosurgery (GKRS) treatment can help in determining whether GKRS will be effective on an individual patient basis. However, at present, prognostic factors of tumor control after GKRS for VS are largely unknown, and only clinical factors, such as size of the tumor at treatment and pre-treatment growth rate of the tumor, have been considered thus far. This research aims at outcome prediction of GKRS by means of quantitative texture feature analysis on conventional MRI scans. We compute first-order statistics and features based on gray-level co- occurrence (GLCM) and run-length matrices (RLM), and employ support vector machines and decision trees for classification. In a clinical dataset, consisting of 20 tumors showing treatment failure and 20 tumors exhibiting treatment success, we have discovered that the second-order statistical metrics distilled from GLCM and RLM are suitable for describing texture, but are slightly outperformed by simple first-order statistics, like mean, standard deviation and median. The obtained prediction accuracy is about 85%, but a final choice of the best feature can only be made after performing more extensive analyses on larger datasets. In any case, this work provides suitable texture measures for successful prediction of GKRS treatment outcome for VS.

Motivational state controls the prediction error in Pavlovian appetitive-aversive interactions.

PubMed

Laurent, Vincent; Balleine, Bernard W; Westbrook, R Frederick

2018-01-01

Contemporary theories of learning emphasize the role of a prediction error signal in driving learning, but the nature of this signal remains hotly debated. Here, we used Pavlovian conditioning in rats to investigate whether primary motivational and emotional states interact to control prediction error. We initially generated cues that positively or negatively predicted an appetitive food outcome. We then assessed how these cues modulated aversive conditioning when a novel cue was paired with a foot shock. We found that a positive predictor of food enhances, whereas a negative predictor of that same food impairs, aversive conditioning. Critically, we also showed that the enhancement produced by the positive predictor is removed by reducing the value of its associated food. In contrast, the impairment triggered by the negative predictor remains insensitive to devaluation of its associated food. These findings provide compelling evidence that the motivational value attributed to a predicted food outcome can directly control appetitive-aversive interactions and, therefore, that motivational processes can modulate emotional processes to generate the final error term on which subsequent learning is based. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain connectivity changes occurring following cognitive behavioural therapy for psychosis predict long-term recovery.

PubMed

Mason, L; Peters, E; Williams, S C; Kumari, V

2017-01-17

Little is known about the psychobiological mechanisms of cognitive behavioural therapy for psychosis (CBTp) and which specific processes are key in predicting favourable long-term outcomes. Following theoretical models of psychosis, this proof-of-concept study investigated whether the long-term recovery path of CBTp completers can be predicted by the neural changes in threat-based social affective processing that occur during CBTp. We followed up 22 participants who had undergone a social affective processing task during functional magnetic resonance imaging along with self-report and clinician-administered symptom measures, before and after receiving CBTp. Monthly ratings of psychotic and affective symptoms were obtained retrospectively across 8 years since receiving CBTp, plus self-reported recovery at final follow-up. We investigated whether these long-term outcomes were predicted by CBTp-led changes in functional connections with dorsal prefrontal cortical and amygdala during the processing of threatening and prosocial facial affect. Although long-term psychotic symptoms were predicted by changes in prefrontal connections during prosocial facial affective processing, long-term affective symptoms were predicted by threat-related amygdalo-inferior parietal lobule connectivity. Greater increases in dorsolateral prefrontal cortex connectivity with amygdala following CBTp also predicted higher subjective ratings of recovery at long-term follow-up. These findings show that reorganisation occurring at the neural level following psychological therapy can predict the subsequent recovery path of people with psychosis across 8 years. This novel methodology shows promise for further studies with larger sample size, which are needed to better examine the sensitivity of psychobiological processes, in comparison to existing clinical measures, in predicting long-term outcomes.

Minimally invasive decompression surgery for lumbar spinal stenosis with degenerative scoliosis: Predictive factors of radiographic and clinical outcomes.

PubMed

Minamide, Akihito; Yoshida, Munehito; Iwahashi, Hiroki; Simpson, Andrew K; Yamada, Hiroshi; Hashizume, Hiroshi; Nakagawa, Yukihiro; Iwasaki, Hiroshi; Tsutsui, Shunji; Kagotani, Ryohei; Sonekatsu, Mayumi; Sasaki, Takahide; Shinto, Kazunori; Deguchi, Tsuyoshi

2017-05-01

There is ongoing controversy regarding the most appropriate surgical treatment for lumbar spinal stenosis (LSS) with concurrent degenerative lumbar scoliosis (DLS): decompression alone, decompression with limited spinal fusion, or long spinal fusion for deformity correction. The coexistence of degenerative stenosis and deformity is a common scenario; Nonetheless, selecting the appropriate surgical intervention requires thorough understanding of the patients clinical symptomatology as well as radiographic parameters. Minimally invasive (MIS) decompression surgery was performed for LSS patients with DLS. The aims of this study were (1) to investigate the clinical outcomes of MIS decompression surgery in LSS patients with DLS, and (2) to identify the predictive factors for both radiographic and clinical outcomes after MIS surgery. 438 consecutive patients were enrolled in this study. Inclusion criteria was evidence of LSS and DLS with coronal curvature measuring greater than 10°. The Japanese Orthopaedic Association (JOA) score, JOA recovery rate, low back pain (LBP), and radiographic features were evaluated preoperatively and at over 2 years postoperatively. Of the 438 patients, 122 were included in final analysis, with a mean follow-up of 2.4 years. The JOA recovery rate was 47.6%. LBP was significantly improved at final follow-up. Cobb angle was maintained for 2 years postoperatively (p = 0.159). Clinical outcomes in foraminal stenosis patients were significantly related to sex, preoperative high Cobb angle and progression of scoliosis (p = 0.008). In the severe scoliosis patients, the JOA recovery was 44%, and was significantly depended on progression of scoliosis (Cobb angle: preoperation 29.6°, 2-years follow-up 36.9°) and mismatch between the pelvic incidence (PI) and the lumbar lordosis (LL) (preoperative PI-LL 35.5 ± 21.2°) (p = 0.028). This study investigated clinical outcomes of MIS decompression surgery in LSS patients with DLS. The predictive risk factors of clinical outcomes were severe scoliosis, foramina stenosis, progressive scoliosis and large mismatch of PI-LL. Copyright © 2016 The Japanese Orthopaedic Association. All rights reserved.

Preoperative cow-side lactatemia measurement predicts negative outcome in Holstein dairy cattle with right abomasal disorders.

PubMed

Boulay, G; Francoz, D; Doré, E; Dufour, S; Veillette, M; Badillo, M; Bélanger, A-M; Buczinski, S

2014-01-01

The objectives of the current study were (1) to determine the gain in prognostic accuracy of preoperative l-lactate concentration (LAC) measured on farm on cows with right displaced abomasum (RDA) or abomasal volvulus (AV) for predicting negative outcome; and (2) to suggest clinically relevant thresholds for such use. A cohort of 102 cows with on-farm surgical diagnostic of RDA or AV was obtained from June 2009 through December 2011. Blood was drawn from coccygeal vessels before surgery and plasma LAC was immediately measured by using a portable clinical analyzer. Dairy producers were interviewed by phone 30 d following surgery and the outcome was determined: a positive outcome if the owner was satisfied of the overall evolution 30 d postoperatively, and a negative outcome if the cow was culled, died, or if the owner reported being unsatisfied 30 d postoperatively. The area under the curve of the receiver operating characteristic curve for LAC was 0.92 and was significantly greater than the area under the curve of the receiver operating characteristic curve of heart rate (HR; 0.77), indicating that LAC, in general, performed better than HR to predict a negative outcome. Furthermore, the ability to predict a negative outcome was significantly improved when LAC measurement was considered in addition to the already available HR data (area under the curve: 0.93 and 95% confidence interval: 0.87, 0.99). Important inflection points of the misclassification cost term function were noted at thresholds of 2 and 6 mmol/L, suggesting the potential utility of these cut-points. The 2 and 6 mmol/L thresholds had a sensitivity, specificity, positive predictive value, and negative predictive value for predicting a negative outcome of 76.2, 82.7, 53.3, and 93.1%, and of 28.6, 97.5, 75, and 84%, respectively. In terms of clinical interpretation, LAC ≤2 mmol/L appeared to be a good indicator of positive outcome and could be used to support a surgical treatment decision. The treatment decision for cows with LAC between 2 and 6 mmol/L, however, would depend on the economic context and the owner's attitude to risk in regard to potential return on its investment. Finally, performing a surgical correction on commercial cows with RDA or AV and a LAC ≥6 mmol/L appeared to be unjustified and these animals should be culled based on their high probability of negative outcome. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Application of the Novel Grading Scale (Lawton-Young Grading System) to Predict the Outcome of Brain Arteriovenous Malformation.

PubMed

Hafez, Ahmad; Koroknay-Pál, Päivi; Oulasvirta, Elias; Elseoud, Ahmed Abou; Lawton, Michael T; Niemelä, Mika; Laakso, Aki

2018-05-04

A supplementary grading scale (Supplemented Spetzler-Martin grade, Supp-SM) was introduced in 2010 as a refinement of the SM system to improve preoperative risk prediction of brain arteriovenous malformations (AVMs). To determine the ability to predict surgical outcomes using the Supp-SM grading scale. This retrospective study was conducted on 200 patients admitted to the Helsinki University Hospital between 2000 and 2014. The validity of the Supp-SM and SM grading systems was compared using the area under the receiver operating characteristic (AUROC) curves, with respect to the change between preoperative and early (3-4 mo) as well as final postoperative modified Rankin Scale (mRS) scores. The performance of the Supp-SM was superior to that of the SM grading scale in the early follow-up (3-4 mo): AUROC = 0.57 (95% confidence interval [CI]: 0.49-0.65) for SM and AUROC = 0.67 (95% CI: 0.60-0.75) for Supp-SM. The Supp-SM performance continued improving over SM at the late follow-up: AUROC = 0.63 (95% CI: 0.55-0.71) for SM and AUROC = 0.70 (95% CI: 0.62-0.77) for Supp-SM. The perforating artery supply, which is not part of either grading system, plays an important role in the early follow-up outcome (P = .008; odds ratio: 2.95; 95% CI: 1.32-6.55) and in the late follow-up outcome (P < .001; odds ratio: 5.89; 95% CI: 2.49-13.91). The Supp-SM grading system improves the outcome prediction accuracy and is a feasible alternative to the SMS, even for series with higher proportion of high-grade AVMs. However, perforators play important role on the outcome.

Magnetic Resonance Imaging Assessment of Squamous Cell Carcinoma of the Anal Canal Before and After Chemoradiation: Can MRI Predict for Eventual Clinical Outcome?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goh, Vicky, E-mail: vicky.goh@stricklandscanner.org.u; Gollub, Frank K.; Liaw, Jonathan

2010-11-01

Purpose: To describe the MRI appearances of squamous cell carcinoma of the anal canal before and after chemoradiation and to assess whether MRI features predict for clinical outcome. Methods and Materials: Thirty-five patients (15 male, 20 female; mean age 60.8 years) with histologically proven squamous cell cancer of the anal canal underwent MRI before and 6-8 weeks after definitive chemoradiation. Images were reviewed retrospectively by two radiologists in consensus blinded to clinical outcome: tumor size, signal intensity, extent, and TNM stage were recorded. Following treatment, patients were defined as responders by T and N downstaging and Response Evaluation Criteria inmore » Solid Tumors (RECIST). Final clinical outcome was determined by imaging and case note review: patients were divided into (1) disease-free and (2) with relapse and compared using appropriate univariate methods to identify imaging predictors; statistical significance was at 5%. Results: The majority of tumors were {<=}T2 (23/35; 65.7%) and N0 (21/35; 60%), mean size 3.75cm, and hyperintense (++ to +++, 24/35 patients; 68%). Following chemoradiation, there was a size reduction in all cases (mean 73.3%) and a reduction in signal intensity in 26/35 patients (74.2%). The majority of patients were classified as responders (26/35 (74.2%) patients by T and N downstaging; and 30/35 (85.7%) patients by RECIST). At a median follow-up of 33.5 months, 25 patients (71.4%) remained disease-free; 10 patients (28.6%) had locoregional or metastatic disease. Univariate analysis showed that no individual MRI features were predictive of eventual outcome. Conclusion: Early assessment of response by MRI at 6-8 weeks is unhelpful in predicting future clinical outcome.« less

Forecasts of Selected Social Indicators of Educational Outcomes and Recommended Policy Changes. (Final Report).

ERIC Educational Resources Information Center

Collazo, Andres; And Others

This report has three objectives: (1) to identify social indicators relating to policy concerns of the legislature, state board of education, and commissioner of education; (2) to predict the future status of selected social indicators, using the assumption that present policies will be continued; and (3) to recommend policy changes for achieving…

How adverse outcome pathways can aid the development and ...

EPA Pesticide Factsheets

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework has emerged as a systematic approach for organizing knowledge that supports such inference. We argue that this systematic organization of knowledge can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment. The present manuscript reports on expert opinion and case studies that came out of a European Commission, Joint Research Centre-sponsored work

Attributions and self-efficacy for physical activity in multiple sclerosis.

PubMed

Nickel, D; Spink, K; Andersen, M; Knox, K

2014-01-01

Self-efficacy is an important predictor of health-related physical activity in multiple sclerosis (MS). While past experiences are believed to influence efficacy beliefs, the explanations individuals provide for these experiences also may be critical. Our objective was to test the hypothesis that perceived success or failure to accumulate 150 min of physical activity in the previous week would moderate the relationship between the attributional dimension of stability and self-efficacy to exercise in the future. Forty-two adults with MS participated in this cross-sectional descriptive study. Participants completed questions assessing physical activity, perceived outcome for meeting the recommended level of endurance activity, attributions for the outcome, and exercise self-efficacy. Results from hierarchical multiple regression revealed a significant main effect for perceived outcome predicting self-efficacy that was qualified by a significant interaction. The final model, which included perceived outcome, stability, and the interaction term, predicted 37% of the variance in exercise self-efficacy, F (3, 38) = 7.27, p = .001. Our findings suggest that the best prediction of self-efficacy in the MS population may include the interaction of specific attributional dimensions with success/failure at meeting the recommended physical activity dose. Attributions may be another target for interventions aimed at increasing the physical activity in MS.

Validation of CRASH Model in Prediction of 14-day Mortality and 6-month Unfavorable Outcome of Head Trauma Patients.

PubMed

Hashemi, Behrooz; Amanat, Mahnaz; Baratloo, Alireza; Forouzanfar, Mohammad Mehdi; Rahmati, Farhad; Motamedi, Maryam; Safari, Saeed

2016-11-01

To date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. External validation of these models in different populations is of great importance for their generalization. The present study was designed, aiming to determine the value of CRASH prognostic model in prediction of 14-day mortality (14-DM) and 6-month unfavorable outcome (6-MUO) of patients with traumatic brain injury. In the present prospective diagnostic test study, calibration and discrimination of CRASH model were evaluated in head trauma patients referred to the emergency department. Variables required for calculating CRASH expected risks (ER), and observed 14-DM and 6-MUO were gathered. Then ER of 14-DM and 6-MUO were calculated. The patients were followed for 6 months and their 14-DM and 6-MUO were recorded. Finally, the correlation of CRASH ER and the observed outcome of the patients was evaluated. The data were analyzed using STATA version 11.0. In this study, 323 patients with the mean age of 34.0 ± 19.4 years were evaluated (87.3% male). Calibration of the basic and CT models in prediction of 14-day and 6-month outcome were in the desirable range (P < 0.05). Area under the curve in the basic model for prediction of 14-DM and 6-MUO were 0.92 (95% CI: 0.89-0.96) and 0.92 (95% CI: 0.90-0.95), respectively. In addition, area under the curve in the CT model for prediction of 14-DM and 6-MUO were 0.93 (95% CI: 0.91-0.97) and 0.93 (95% CI: 0.91-0.96), respectively. There was no significant difference between the discriminations of the two models in prediction of 14-DM (p = 0.11) and 6-MUO (p = 0.1). The results of the present study showed that CRASH prediction model has proper discrimination and calibration in predicting 14-DM and 6-MUO of head trauma patients. Since there was no difference between the values of the basic and CT models, using the basic model is recommended to simplify the risk calculations.

Individualized Prediction of Heat Stress in Firefighters: A Data-Driven Approach Using Classification and Regression Trees.

PubMed

Mani, Ashutosh; Rao, Marepalli; James, Kelley; Bhattacharya, Amit

2015-01-01

The purpose of this study was to explore data-driven models, based on decision trees, to develop practical and easy to use predictive models for early identification of firefighters who are likely to cross the threshold of hyperthermia during live-fire training. Predictive models were created for three consecutive live-fire training scenarios. The final predicted outcome was a categorical variable: will a firefighter cross the upper threshold of hyperthermia - Yes/No. Two tiers of models were built, one with and one without taking into account the outcome (whether a firefighter crossed hyperthermia or not) from the previous training scenario. First tier of models included age, baseline heart rate and core body temperature, body mass index, and duration of training scenario as predictors. The second tier of models included the outcome of the previous scenario in the prediction space, in addition to all the predictors from the first tier of models. Classification and regression trees were used independently for prediction. The response variable for the regression tree was the quantitative variable: core body temperature at the end of each scenario. The predicted quantitative variable from regression trees was compared to the upper threshold of hyperthermia (38°C) to predict whether a firefighter would enter hyperthermia. The performance of classification and regression tree models was satisfactory for the second (success rate = 79%) and third (success rate = 89%) training scenarios but not for the first (success rate = 43%). Data-driven models based on decision trees can be a useful tool for predicting physiological response without modeling the underlying physiological systems. Early prediction of heat stress coupled with proactive interventions, such as pre-cooling, can help reduce heat stress in firefighters.

Rostral anterior cingulate cortex activity and early symptom improvement during treatment for major depressive disorder

PubMed Central

Korb, Alexander S.; Hunter, Aimee M.; Cook, Ian A.; Leuchter, Andrew F.

2011-01-01

In treatment trials for Major Depressive Disorder (MDD), early symptom improvement is predictive of eventual clinical response. Clinical response may also be predicted by elevated pretreatment theta (4-7 Hz) current density in the rostral anterior cingulate (rACC) and medial orbitofrontal cortex (mOFC). We investigated the relationship between pretreatment EEG and early improvement in predicting clinical outcome in 72 MDD subjects across three placebo-controlled treatment trials. Subjects were randomized to receive fluoxetine, venlafaxine, or placebo. Theta current density in the rACC and mOFC was computed with Low-Resolution Brain Electromagnetic Tomography (LORETA). An ANCOVA, examining week 8 Hamilton Depression Rating Scale (HamD) percent change, showed a significant effect of week-2-HamD-percent-change, and a significant three-way interaction of week-2-HamD-percent-change × Treatment × rACC. Medication subjects with robust early improvement showed almost no relationship between rACC theta current density and final clinical outcome. However, in subjects with little early improvement, rACC activity showed a strong relationship with clinical outcome. The model examining mOFC showed a trend in the three-way interaction. A combination of pretreatment rACC activity and early symptom improvement may be useful for predicting treatment response. PMID:21546222

Cerebral Blood Volume ASPECTS Is the Best Predictor of Clinical Outcome in Acute Ischemic Stroke: A Retrospective, Combined Semi-Quantitative and Quantitative Assessment.

PubMed

Padroni, Marina; Bernardoni, Andrea; Tamborino, Carmine; Roversi, Gloria; Borrelli, Massimo; Saletti, Andrea; De Vito, Alessandro; Azzini, Cristiano; Borgatti, Luca; Marcello, Onofrio; d'Esterre, Christopher; Ceruti, Stefano; Casetta, Ilaria; Lee, Ting-Yim; Fainardi, Enrico

2016-01-01

The capability of CT perfusion (CTP) Alberta Stroke Program Early CT Score (ASPECTS) to predict outcome and identify ischemia severity in acute ischemic stroke (AIS) patients is still questioned. 62 patients with AIS were imaged within 8 hours of symptom onset by non-contrast CT, CT angiography and CTP scans at admission and 24 hours. CTP ASPECTS was calculated on the affected hemisphere using cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) maps by subtracting 1 point for any abnormalities visually detected or measured within multiple cortical circular regions of interest according to previously established thresholds. MTT-CBV ASPECTS was considered as CTP ASPECTS mismatch. Hemorrhagic transformation (HT), recanalization status and reperfusion grade at 24 hours, final infarct volume at 7 days and modified Rankin scale (mRS) at 3 months after onset were recorded. Semi-quantitative and quantitative CTP ASPECTS were highly correlated (p<0.00001). CBF, CBV and MTT ASPECTS were higher in patients with no HT and mRS ≤ 2 and inversely associated with final infarct volume and mRS (p values: from p<0.05 to p<0.00001). CTP ASPECTS mismatch was slightly associated with radiological and clinical outcomes (p values: from p<0.05 to p<0.02) only if evaluated quantitatively. A CBV ASPECTS of 9 was the optimal semi-quantitative value for predicting outcome. Our findings suggest that visual inspection of CTP ASPECTS recognizes infarct and ischemic absolute values. Semi-quantitative CBV ASPECTS, but not CTP ASPECTS mismatch, represents a strong prognostic indicator, implying that core extent is the main determinant of outcome, irrespective of penumbra size.

Cerebral Blood Volume ASPECTS Is the Best Predictor of Clinical Outcome in Acute Ischemic Stroke: A Retrospective, Combined Semi-Quantitative and Quantitative Assessment

PubMed Central

Padroni, Marina; Bernardoni, Andrea; Tamborino, Carmine; Roversi, Gloria; Borrelli, Massimo; Saletti, Andrea; De Vito, Alessandro; Azzini, Cristiano; Borgatti, Luca; Marcello, Onofrio; d’Esterre, Christopher; Ceruti, Stefano; Casetta, Ilaria; Lee, Ting-Yim; Fainardi, Enrico

2016-01-01

Introduction The capability of CT perfusion (CTP) Alberta Stroke Program Early CT Score (ASPECTS) to predict outcome and identify ischemia severity in acute ischemic stroke (AIS) patients is still questioned. Methods 62 patients with AIS were imaged within 8 hours of symptom onset by non-contrast CT, CT angiography and CTP scans at admission and 24 hours. CTP ASPECTS was calculated on the affected hemisphere using cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) maps by subtracting 1 point for any abnormalities visually detected or measured within multiple cortical circular regions of interest according to previously established thresholds. MTT-CBV ASPECTS was considered as CTP ASPECTS mismatch. Hemorrhagic transformation (HT), recanalization status and reperfusion grade at 24 hours, final infarct volume at 7 days and modified Rankin scale (mRS) at 3 months after onset were recorded. Results Semi-quantitative and quantitative CTP ASPECTS were highly correlated (p<0.00001). CBF, CBV and MTT ASPECTS were higher in patients with no HT and mRS≤2 and inversely associated with final infarct volume and mRS (p values: from p<0.05 to p<0.00001). CTP ASPECTS mismatch was slightly associated with radiological and clinical outcomes (p values: from p<0.05 to p<0.02) only if evaluated quantitatively. A CBV ASPECTS of 9 was the optimal semi-quantitative value for predicting outcome. Conclusions Our findings suggest that visual inspection of CTP ASPECTS recognizes infarct and ischemic absolute values. Semi-quantitative CBV ASPECTS, but not CTP ASPECTS mismatch, represents a strong prognostic indicator, implying that core extent is the main determinant of outcome, irrespective of penumbra size. PMID:26824672

Corrected ROC analysis for misclassified binary outcomes.

PubMed

Zawistowski, Matthew; Sussman, Jeremy B; Hofer, Timothy P; Bentley, Douglas; Hayward, Rodney A; Wiitala, Wyndy L

2017-06-15

Creating accurate risk prediction models from Big Data resources such as Electronic Health Records (EHRs) is a critical step toward achieving precision medicine. A major challenge in developing these tools is accounting for imperfect aspects of EHR data, particularly the potential for misclassified outcomes. Misclassification, the swapping of case and control outcome labels, is well known to bias effect size estimates for regression prediction models. In this paper, we study the effect of misclassification on accuracy assessment for risk prediction models and find that it leads to bias in the area under the curve (AUC) metric from standard ROC analysis. The extent of the bias is determined by the false positive and false negative misclassification rates as well as disease prevalence. Notably, we show that simply correcting for misclassification while building the prediction model is not sufficient to remove the bias in AUC. We therefore introduce an intuitive misclassification-adjusted ROC procedure that accounts for uncertainty in observed outcomes and produces bias-corrected estimates of the true AUC. The method requires that misclassification rates are either known or can be estimated, quantities typically required for the modeling step. The computational simplicity of our method is a key advantage, making it ideal for efficiently comparing multiple prediction models on very large datasets. Finally, we apply the correction method to a hospitalization prediction model from a cohort of over 1 million patients from the Veterans Health Administrations EHR. Implementations of the ROC correction are provided for Stata and R. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

PubMed Central

Aladjov, Hristo; Ankley, Gerald; Byrne, Hugh J.; de Knecht, Joop; Heinzle, Elmar; Klambauer, Günter; Landesmann, Brigitte; Luijten, Mirjam; MacKay, Cameron; Maxwell, Gavin; Meek, M. E. (Bette); Paini, Alicia; Perkins, Edward; Sobanski, Tomasz; Villeneuve, Dan; Waters, Katrina M.; Whelan, Maurice

2017-01-01

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24–25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment. PMID:27994170

An Exploration of the Associations of Alcohol-Related Social Media Use and Message Interpretation Outcomes to Problem Drinking Among College Students.

PubMed

Hoffman, Eric W; Austin, Erica Weintraub; Pinkleton, Bruce E; Austin, Bruce W

2017-07-01

College students' use of digital communication technology has led to a rapid expansion of digital alcohol marketing efforts. Two surveys (total usable n = 637) were conducted to explore college students' experiences with alcohol-related social media, their decision making related to alcohol use, and their problematic drinking behaviors. Study results indicated that students' use of alcohol-related social media predicted their problem drinking behaviors. In addition, students' wishful identification, perceived desirability, perceived similarity, and normative beliefs predicted their expectancies for drinking alcohol. Finally, students' expectancies for drinking alcohol predicted their problematic drinking behaviors.

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

The STarT Back Screening Tool and Individual Psychological Measures: Evaluation of Prognostic Capabilities for Low Back Pain Clinical Outcomes in Outpatient Physical Therapy Settings

PubMed Central

Bishop, Mark D.; Fritz, Julie M.; Robinson, Michael E.; Asal, Nabih R.; Nisenzon, Anne N.

2013-01-01

Background Psychologically informed practice emphasizes routine identification of modifiable psychological risk factors being highlighted. Objective The purpose of this study was to test the predictive validity of the STarT Back Screening Tool (SBT) in comparison with single-construct psychological measures for 6-month clinical outcomes. Design This was an observational, prospective cohort study. Methods Patients (n=146) receiving physical therapy for low back pain were administered the SBT and a battery of psychological measures (Fear-Avoidance Beliefs Questionnaire physical activity scale and work scale [FABQ-PA and FABQ-W, respectively], Pain Catastrophizing Scale [PCS], 11-item version of the Tampa Scale of Kinesiophobia [TSK-11], and 9-item Patient Health Questionnaire [PHQ-9]) at initial evaluation and 4 weeks later. Treatment was at the physical therapist's discretion. Clinical outcomes consisted of pain intensity and self-reported disability. Prediction of 6-month clinical outcomes was assessed for intake SBT and psychological measure scores using multiple regression models while controlling for other prognostic variables. In addition, the predictive capabilities of intake to 4-week changes in SBT and psychological measure scores for 6-month clinical outcomes were assessed. Results Intake pain intensity scores (β=.39 to .45) and disability scores (β=.47 to .60) were the strongest predictors in all final regression models, explaining 22% and 24% and 43% and 48% of the variance for the respective clinical outcome at 6 months. Neither SBT nor psychological measure scores improved prediction of 6-month pain intensity. The SBT overall scores (β=.22) and SBT psychosocial scores (β=.25) added to the prediction of disability at 6 months. Four-week changes in TSK-11 scores (β=−.18) were predictive of pain intensity at 6 months. Four-week changes in FABQ-PA scores (β=−.21), TSK-11 scores (β=−.20) and SBT overall scores (β=−.18) were predictive of disability at 6 months. Limitations Physical therapy treatment was not standardized or accounted for in the analysis. Conclusions Prediction of clinical outcomes by psychology-based measures was dependent upon the clinical outcome domain of interest. Similar to studies from the primary care setting, initial screening with the SBT provided additional prognostic information for 6-month disability and changes in SBT overall scores may provide important clinical decision-making information for treatment monitoring. PMID:23125279

Predictor characteristics necessary for building a clinically useful risk prediction model: a simulation study.

PubMed

Schummers, Laura; Himes, Katherine P; Bodnar, Lisa M; Hutcheon, Jennifer A

2016-09-21

Compelled by the intuitive appeal of predicting each individual patient's risk of an outcome, there is a growing interest in risk prediction models. While the statistical methods used to build prediction models are increasingly well understood, the literature offers little insight to researchers seeking to gauge a priori whether a prediction model is likely to perform well for their particular research question. The objective of this study was to inform the development of new risk prediction models by evaluating model performance under a wide range of predictor characteristics. Data from all births to overweight or obese women in British Columbia, Canada from 2004 to 2012 (n = 75,225) were used to build a risk prediction model for preeclampsia. The data were then augmented with simulated predictors of the outcome with pre-set prevalence values and univariable odds ratios. We built 120 risk prediction models that included known demographic and clinical predictors, and one, three, or five of the simulated variables. Finally, we evaluated standard model performance criteria (discrimination, risk stratification capacity, calibration, and Nagelkerke's r 2 ) for each model. Findings from our models built with simulated predictors demonstrated the predictor characteristics required for a risk prediction model to adequately discriminate cases from non-cases and to adequately classify patients into clinically distinct risk groups. Several predictor characteristics can yield well performing risk prediction models; however, these characteristics are not typical of predictor-outcome relationships in many population-based or clinical data sets. Novel predictors must be both strongly associated with the outcome and prevalent in the population to be useful for clinical prediction modeling (e.g., one predictor with prevalence ≥20 % and odds ratio ≥8, or 3 predictors with prevalence ≥10 % and odds ratios ≥4). Area under the receiver operating characteristic curve values of >0.8 were necessary to achieve reasonable risk stratification capacity. Our findings provide a guide for researchers to estimate the expected performance of a prediction model before a model has been built based on the characteristics of available predictors.

The Association between Outpatient Buprenorphine Detoxification Duration and Clinical Treatment Outcomes: A Review

PubMed Central

Sigmon, Stacey C.; Strain, Eric C.; Heil, Sarah H.; Higgins, Stephen T.

2011-01-01

Background The association between buprenorphine taper duration and treatment outcomes is not well understood. This review evaluated whether duration of outpatient buprenorphine taper is significantly associated with treatment outcomes. Methods Studies that were published in peer-reviewed journals, administered buprenorphine as an outpatient taper to opioid-dependent participants, and provided data on at least one of three primary treatment outcome measures (opioid abstinence, retention, peak withdrawal severity) were reviewed. Primary treatment outcomes were evaluated as a function of taper duration using hierarchical linear regressions using pre-taper maintenance as a cofactor. Results Twenty-eight studies were reviewed. Taper duration significantly predicted percent of opioid-negative samples provided during treatment, however pre-taper maintenance period predicted percent participants abstinent on the final day of treatment. High rates of relapse were reported. No significant association between taper duration and retention in treatment or peak withdrawal severity was observed. Conclusion The data reviewed here suggest taper duration is associated with opioid abstinence achieved during detoxification but not with other markers of treatment outcome. The reviewed studies varied widely on several parameters (e.g., frequency of urinalysis testing, provision of ancillary medications) that may influence treatment outcome and thus could have interfered with the ability to identify relationships between taper duration and outcomes. Future studies evaluating opioid detoxification should utilize rigorous experimental methods and report a wider range of outcome measures in order to help advance our understanding of the association between taper duration and treatment outcomes. PMID:21741781

Reminder Cues Modulate the Renewal Effect in Human Predictive Learning

PubMed Central

Bustamante, Javier; Uengoer, Metin; Lachnit, Harald

2016-01-01

Associative learning refers to our ability to learn about regularities in our environment. When a stimulus is repeatedly followed by a specific outcome, we learn to expect the outcome in the presence of the stimulus. We are also able to modify established expectations in the face of disconfirming information (the stimulus is no longer followed by the outcome). Both the change of environmental regularities and the related processes of adaptation are referred to as extinction. However, extinction does not erase the initially acquired expectations. For instance, following successful extinction, the initially learned expectations can recover when there is a context change – a phenomenon called the renewal effect, which is considered as a model for relapse after exposure therapy. Renewal was found to be modulated by reminder cues of acquisition and extinction. However, the mechanisms underlying the effectiveness of reminder cues are not well understood. The aim of the present study was to investigate the impact of reminder cues on renewal in the field of human predictive learning. Experiment I demonstrated that renewal in human predictive learning is modulated by cues related to acquisition or extinction. Initially, participants received pairings of a stimulus and an outcome in one context. These stimulus-outcome pairings were preceded by presentations of a reminder cue (acquisition cue). Then, participants received extinction in a different context in which presentations of the stimulus were no longer followed by the outcome. These extinction trials were preceded by a second reminder cue (extinction cue). During a final phase conducted in a third context, participants showed stronger expectations of the outcome in the presence of the stimulus when testing was accompanied by the acquisition cue compared to the extinction cue. Experiment II tested an explanation of the reminder cue effect in terms of simple cue-outcome associations. Therefore, acquisition and extinction cues were equated for their associative histories in Experiment II, which should abolish their impact on renewal if based on simple cue-outcome associations. In contrast to this prediction, Experiment II replicated the findings from Experiment I indicating that the effectiveness of reminder cues did not require direct reminder cue-outcome associations. PMID:28066293

Predicting consumer behavior with Web search.

PubMed

Goel, Sharad; Hofman, Jake M; Lahaie, Sébastien; Pennock, David M; Watts, Duncan J

2010-10-12

Recent work has demonstrated that Web search volume can "predict the present," meaning that it can be used to accurately track outcomes such as unemployment levels, auto and home sales, and disease prevalence in near real time. Here we show that what consumers are searching for online can also predict their collective future behavior days or even weeks in advance. Specifically we use search query volume to forecast the opening weekend box-office revenue for feature films, first-month sales of video games, and the rank of songs on the Billboard Hot 100 chart, finding in all cases that search counts are highly predictive of future outcomes. We also find that search counts generally boost the performance of baseline models fit on other publicly available data, where the boost varies from modest to dramatic, depending on the application in question. Finally, we reexamine previous work on tracking flu trends and show that, perhaps surprisingly, the utility of search data relative to a simple autoregressive model is modest. We conclude that in the absence of other data sources, or where small improvements in predictive performance are material, search queries provide a useful guide to the near future.

Predicting consumer behavior with Web search

PubMed Central

Goel, Sharad; Hofman, Jake M.; Lahaie, Sébastien; Pennock, David M.; Watts, Duncan J.

2010-01-01

Recent work has demonstrated that Web search volume can “predict the present,” meaning that it can be used to accurately track outcomes such as unemployment levels, auto and home sales, and disease prevalence in near real time. Here we show that what consumers are searching for online can also predict their collective future behavior days or even weeks in advance. Specifically we use search query volume to forecast the opening weekend box-office revenue for feature films, first-month sales of video games, and the rank of songs on the Billboard Hot 100 chart, finding in all cases that search counts are highly predictive of future outcomes. We also find that search counts generally boost the performance of baseline models fit on other publicly available data, where the boost varies from modest to dramatic, depending on the application in question. Finally, we reexamine previous work on tracking flu trends and show that, perhaps surprisingly, the utility of search data relative to a simple autoregressive model is modest. We conclude that in the absence of other data sources, or where small improvements in predictive performance are material, search queries provide a useful guide to the near future. PMID:20876140

MicroRNA based Pan-Cancer Diagnosis and Treatment Recommendation.

PubMed

Cheerla, Nikhil; Gevaert, Olivier

2017-01-13

The current state-of-the-art in cancer diagnosis and treatment is not ideal; diagnostic tests are accurate but invasive, and treatments are "one-size fits-all" instead of being personalized. Recently, miRNA's have garnered significant attention as cancer biomarkers, owing to their ease of access (circulating miRNA in the blood) and stability. There have been many studies showing the effectiveness of miRNA data in diagnosing specific cancer types, but few studies explore the role of miRNA in predicting treatment outcome. Here we go a step further, using tissue miRNA and clinical data across 21 cancers from the 'The Cancer Genome Atlas' (TCGA) database. We use machine learning techniques to create an accurate pan-cancer diagnosis system, and a prediction model for treatment outcomes. Finally, using these models, we create a web-based tool that diagnoses cancer and recommends the best treatment options. We achieved 97.2% accuracy for classification using a support vector machine classifier with radial basis. The accuracies improved to 99.9-100% when climbing up the embryonic tree and classifying cancers at different stages. We define the accuracy as the ratio of the total number of instances correctly classified to the total instances. The classifier also performed well, achieving greater than 80% sensitivity for many cancer types on independent validation datasets. Many miRNAs selected by our feature selection algorithm had strong previous associations to various cancers and tumor progression. Then, using miRNA, clinical and treatment data and encoding it in a machine-learning readable format, we built a prognosis predictor model to predict the outcome of treatment with 85% accuracy. We used this model to create a tool that recommends personalized treatment regimens. Both the diagnosis and prognosis model, incorporating semi-supervised learning techniques to improve their accuracies with repeated use, were uploaded online for easy access. Our research is a step towards the final goal of diagnosing cancer and predicting treatment recommendations using non-invasive blood tests.

Predictive validity of disability rating scale in determining functional outcome in patients with severe traumatic brain injury.

PubMed

Deepika, Akhil; Devi, B Indira; Shukla, Dhaval

2017-01-01

Most patients with severe traumatic brain injury (TBI) are discharged when they have still not recovered completely. Many such patients are not available for follow up. We conducted this study to determine whether the condition at discharge from acute care setting, as assessed with disability rating scale (DRS), correlates with functional outcome at follow up. This study was conducted at a Neurosurgical intensive care unit (ICU) of a tertiary care referral center. This was a prospective observational study. Patients admitted to ICU with a diagnosis of severe TBI were enrolled for the study. On the day of discharge, all patients underwent DRS assessment. A final assessment was performed using Glasgow outcome scale extended (GOSE) at 6 months after discharge from the hospital. The correlation between the DRS scores at the time of discharge with DRS scores and GOSE categories at 6 months after discharge was determined using Spearman's rho correlation coefficient. A total of 88 patients were recruited for the study. The correlation coefficient of DRS at discharge for DRS at 6 months was 0.536 and for GOSE was -0.553. The area under the curve of DRS score at discharge for predicting unfavorable outcome and mortality at 6 months was 0.770 and 0.820, respectively. The predictive validity of DRS is fair to good in determining GOSE at follow-up. Pending availability of a more accurate outcome assessment tool, DRS at discharge can be used as a surrogate outcome for GOSE at follow up.

Model‐Based Approach to Predict Adherence to Protocol During Antiobesity Trials

PubMed Central

Sharma, Vishnu D.; Combes, François P.; Vakilynejad, Majid; Lahu, Gezim; Lesko, Lawrence J.

2017-01-01

Abstract Development of antiobesity drugs is continuously challenged by high dropout rates during clinical trials. The objective was to develop a population pharmacodynamic model that describes the temporal changes in body weight, considering disease progression, lifestyle intervention, and drug effects. Markov modeling (MM) was applied for quantification and characterization of responder and nonresponder as key drivers of dropout rates, to ultimately support the clinical trial simulations and the outcome in terms of trial adherence. Subjects (n = 4591) from 6 Contrave® trials were included in this analysis. An indirect‐response model developed by van Wart et al was used as a starting point. Inclusion of drug effect was dose driven using a population dose‐ and time‐dependent pharmacodynamic (DTPD) model. Additionally, a population‐pharmacokinetic parameter‐ and data (PPPD)‐driven model was developed using the final DTPD model structure and final parameter estimates from a previously developed population pharmacokinetic model based on available Contrave® pharmacokinetic concentrations. Last, MM was developed to predict transition rate probabilities among responder, nonresponder, and dropout states driven by the pharmacodynamic effect resulting from the DTPD or PPPD model. Covariates included in the models and parameters were diabetes mellitus and race. The linked DTPD‐MM and PPPD‐MM was able to predict transition rates among responder, nonresponder, and dropout states well. The analysis concluded that body‐weight change is an important factor influencing dropout rates, and the MM depicted that overall a DTPD model‐driven approach provides a reasonable prediction of clinical trial outcome probabilities similar to a pharmacokinetic‐driven approach. PMID:28858397

Long-term outcomes of anterior spinal fusion for treating thoracic adolescent idiopathic scoliosis curves: average 15-year follow-up analysis.

PubMed

Sudo, Hideki; Ito, Manabu; Kaneda, Kiyoshi; Shono, Yasuhiro; Takahata, Masahiko; Abumi, Kuniyoshi

2013-05-01

Retrospective review. To assess the long-term outcomes of anterior spinal fusion (ASF) for treating thoracic adolescent idiopathic scoliosis (AIS). Although ASF is reported to provide good coronal and sagittal correction of the main thoracic (MT) AIS curves, the long-term outcomes of ASF is unknown. A consecutive series of 25 patients with Lenke 1 MT AIS were included. Outcome measures comprised radiographical measurements, pulmonary function, and Scoliosis Research Society outcome instrument (SRS-30) scores (preoperative SRS-30 scores were not documented). Postoperative surgical revisions and complications were recorded. Twenty-five patients were followed-up for 12 to 18 years (average, 15.2 yr). The average MT Cobb angle correction rate and the correction loss at the final follow-up were 56.7% and 9.2°, respectively. The average preoperative instrumented level of kyphosis was 8.3°, which significantly improved to 18.6° (P = 0.0003) at the final follow-up. The average percent-predicted forced vital capacity and forced expiratory volume in 1 second were significantly decreased during long-term follow-up measurements (73% and 69%; P = 0.0004 and 0.0016, respectively). However, no patient had complaints related to pulmonary function. The average total SRS-30 score was 4.0. Implant breakage was not observed. All patients, except 1 who required revision surgery, demonstrated solid fusion. Late instrumentation-related bronchial problems were observed in 1 patient who required implant removal and bronchial tube repair, 13 years after the initial surgery. Overall radiographical findings and patient outcome measures of ASF for Lenke 1 MT AIS were satisfactory at an average follow-up of 15 years. ASF provides significant sagittal correction of the main thoracic curve with long-term maintenance of sagittal profiles. Percent-predicted values of forced vital capacity and forced expiratory volume in 1 second were decreased in this cohort; however, no patient had complaints related to pulmonary function.

Acute postoperative seizures as predictors of seizure outcomes after epilepsy surgery.

PubMed

Giridharan, Nisha; Horn, Paul S; Greiner, Hansel M; Holland, Katherine D; Mangano, Francesco T; Arya, Ravindra

2016-11-01

This meta-analysis was performed to determine if acute postoperative seizures (APOS) predict epilepsy surgery outcomes. Additionally, we estimated pooled prevalence for APOS and explored if certain APOS characteristics predict surgical outcomes. A systematic literature search was performed for studies reporting seizure outcomes after epilepsy surgery in patients with and without APOS. APOS were defined as seizure(s) occurring within 30days of surgery. After data extraction, pooled Mantel-Haenszel odds ratio (OR) with 95% confidence intervals (CI) was calculated for 1-year seizure-free outcome in patients with and without APOS using random-effects meta-analysis. Sub-group meta-analysis for pediatric studies, time of occurrence, and APOS semiology were also performed. A meta-regression was performed to explore source(s) of heterogeneity. Seventeen studies were included in the final synthesis. Pooled prevalence of APOS was found to be 22.58%. A significantly higher proportion of patients without APOS within 30days of surgery (73.49%) were seizure-free at ≥1-year (OR 4.20, 95% CI 2.97-5.93, p<0.0001) compared to those with APOS (38.96%). Among the pediatric studies (n=6) 77.14% of patients without APOS were seizure-free at ≥1-year, compared to 35.94% of those with APOS (OR 5.71, 95% CI 3.32-9.80, p<0.0001). Patients having APOS within 24h of surgery and APOS semiology different from habitual pre-surgical seizures were more likely to achieve seizure-free outcomes, but these results failed to achieve statistical significance. APOS reliably predict 1-year seizure outcomes after epilepsy surgery. This information should help counsel patients and families. Copyright © 2016 Elsevier B.V. All rights reserved.

Prognostic factors of a favorable outcome following a supervised exercise program for soldiers with sub-acute and chronic low back pain.

PubMed

Perron, Marc; Gendron, Chantal; Langevin, Pierre; Leblond, Jean; Roos, Marianne; Roy, Jean-Sébastien

2018-04-02

Low back pain (LBP) encompasses heterogeneous patients unlikely to respond to a unique treatment. Identifying sub-groups of LBP may help to improve treatment outcomes. This is a hypothesis-setting study designed to create a clinical prediction rule (CPR) that will predict favorable outcomes in soldiers with sub-acute and chronic LBP participating in a multi-station exercise program. Military members with LBP participated in a supervised program comprising 7 stations each consisting of exercises of increasing difficulty. Demographic, impairment and disability data were collected at baseline. The modified Oswestry Disability Index (ODI) was administered at baseline and following the 6-week program. An improvement of 50% in the initial ODI score was considered the reference standard to determine a favorable outcome. Univariate associations with favorable outcome were tested using chi-square or paired t-tests. Variables that showed between-group (favorable/unfavorable) differences were entered into a logistic regression after determining the sampling adequacy. Finally, continuous variables were dichotomized and the sensitivity, specificity and positive and negative likelihood ratios were determined for the model and for each variable. A sample of 85 participants was included in analyses. Five variables contributed to prediction of a favorable outcome: no pain in lying down (p = 0.017), no use of antidepressants (p = 0.061), FABQ work score < 22.5 (p = 0.061), fewer than 5 physiotherapy sessions before entering the program (p = 0.144) and less than 6 months' work restriction (p = 0.161). This model yielded a sensitivity of 0.78, specificity of 0.80, LR+ of 3.88, and LR- of 0.28. A 77.5% probability of favorable outcome can be predicted by the presence of more than three of the five variables, while an 80% probability of unfavorable outcome can be expected if only three or fewer variables are present. The use of prognostic factors may guide clinicians in identifying soldiers with LBP most likely to have a favorable outcome. Further validation studies are needed to determine if the variables identified in our study are treatment effect modifiers that can predict success following participation in the multi-station exercise program. ClinicalTrials.gov Identifier: NCT03464877 registered retrospectively on 14 March 2018.

Long-term Follow-up of Cytomegalovirus Retinitis in Non-HIV Immunocompromised Patients: Clinical Features and Visual Prognosis.

PubMed

Iu, Lawrence P; Fan, Michelle C; Lau, Jordy K; Chan, Thomas S; Kwong, Yok-Lam; Wong, Ian Y

2016-05-01

To evaluate clinical features and long-term visual outcome of cytomegalovirus (CMV) retinitis in patients without human immunodeficiency virus (HIV) infection, and to determine factors that predict visual outcome. Retrospective cohort study. Consecutive patients with CMV retinitis without HIV infection were reviewed. Main outcome measures included clinical features, proportion of eyes with 6-month and final visual acuity (VA) <20/70 and <20/400, and odds ratios of factors associated with poor visual outcome. A total of 20 eyes from 13 patients were included with a median follow-up time of 17 months. All had at least 6 months of follow-up except 1 patient who died from sepsis at 1 month. At presentation, 50% of eyes had VA <20/70 and 25% had VA <20/400. Zone 1 involvement occurred in 55% and vitreous haze ≥grade 2+ occurred in 25%. Recurrence occurred in 33.3% at a mean time of 6.4 ± 3.3 weeks after discontinuation of anti-CMV therapy. The retinal detachment rate was 21.7% per eye-year and mortality rate was 11.7% per person-year. At final visit, 60% had VA <20/70 and 35% had VA <20/400. Macular involvement was significantly associated with poor final VA <20/400 (odds ratio = 25.00, P = .016). CMV retinitis without HIV infection was often aggressive at presentation. Significant intraocular inflammation was not uncommon. The long-term visual outcome was poor, especially in those with macular involvement. Copyright © 2016 Elsevier Inc. All rights reserved.

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.

PubMed

Wittwehr, Clemens; Aladjov, Hristo; Ankley, Gerald; Byrne, Hugh J; de Knecht, Joop; Heinzle, Elmar; Klambauer, Günter; Landesmann, Brigitte; Luijten, Mirjam; MacKay, Cameron; Maxwell, Gavin; Meek, M E Bette; Paini, Alicia; Perkins, Edward; Sobanski, Tomasz; Villeneuve, Dan; Waters, Katrina M; Whelan, Maurice

2017-02-01

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24-25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

Variance in predicted cup size by 2-dimensional vs 3-dimensional computerized tomography-based templating in primary total hip arthroplasty.

PubMed

Osmani, Feroz A; Thakkar, Savyasachi; Ramme, Austin; Elbuluk, Ameer; Wojack, Paul; Vigdorchik, Jonathan M

2017-12-01

Preoperative total hip arthroplasty templating can be performed with radiographs using acetate prints, digital viewing software, or with computed tomography (CT) images. Our hypothesis is that 3D templating is more precise and accurate with cup size prediction as compared to 2D templating with acetate prints and digital templating software. Data collected from 45 patients undergoing robotic-assisted total hip arthroplasty compared cup sizes templated on acetate prints and OrthoView software to MAKOplasty software that uses CT scan. Kappa analysis determined strength of agreement between each templating modality and the final size used. t tests compared mean cup-size variance from the final size for each templating technique. Interclass correlation coefficient (ICC) determined reliability of digital and acetate planning by comparing predictions of the operating surgeon and a blinded adult reconstructive fellow. The Kappa values for CT-guided, digital, and acetate templating with the final size was 0.974, 0.233, and 0.262, respectively. Both digital and acetate templating significantly overpredicted cup size, compared to CT-guided methods ( P < .001). There was no significant difference between digital and acetate templating ( P  = .117). Interclass correlation coefficient value for digital and acetate templating was 0.928 and 0.931, respectively. CT-guided planning more accurately predicts hip implant cup size when compared to the significant overpredictions of digital and acetate templating. CT-guided templating may also lead to better outcomes due to bone stock preservation from a smaller and more accurate cup size predicted than that of digital and acetate predictions.

Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli.

PubMed

Kumar, Neeraj; Mutha, Pratik K

2016-03-01

The prediction of the sensory outcomes of action is thought to be useful for distinguishing self- vs. externally generated sensations, correcting movements when sensory feedback is delayed, and learning predictive models for motor behavior. Here, we show that aspects of another fundamental function-perception-are enhanced when they entail the contribution of predicted sensory outcomes and that this enhancement relies on the adaptive use of the most stable predictions available. We combined a motor-learning paradigm that imposes new sensory predictions with a dynamic visual search task to first show that perceptual feature extraction of a moving stimulus is poorer when it is based on sensory feedback that is misaligned with those predictions. This was possible because our novel experimental design allowed us to override the "natural" sensory predictions present when any action is performed and separately examine the influence of these two sources on perceptual feature extraction. We then show that if the new predictions induced via motor learning are unreliable, rather than just relying on sensory information for perceptual judgments, as is conventionally thought, then subjects adaptively transition to using other stable sensory predictions to maintain greater accuracy in their perceptual judgments. Finally, we show that when sensory predictions are not modified at all, these judgments are sharper when subjects combine their natural predictions with sensory feedback. Collectively, our results highlight the crucial contribution of sensory predictions to perception and also suggest that the brain intelligently integrates the most stable predictions available with sensory information to maintain high fidelity in perceptual decisions. Copyright © 2016 the American Physiological Society.

Publication bias in animal research presented at the 2008 Society of Critical Care Medicine Conference.

PubMed

Conradi, Una; Joffe, Ari R

2017-07-07

To determine a direct measure of publication bias by determining subsequent full-paper publication (P) of studies reported in animal research abstracts presented at an international conference (A). We selected 100 random (using a random-number generator) A from the 2008 Society of Critical Care Medicine Conference. Using a data collection form and study manual, we recorded methodology and result variables from A. We searched PubMed and EMBASE to June 2015, and DOAJ and Google Scholar to May 2017 to screen for subsequent P. Methodology and result variables were recorded from P to determine changes in reporting from A. Predictors of P were examined using Fisher's Exact Test. 62% (95% CI 52-71%) of studies described in A were subsequently P after a median 19 [IQR 9-33.3] months from conference presentation. Reporting of studies in A was of low quality: randomized 27% (the method of randomization and allocation concealment not described), blinded 0%, sample-size calculation stated 0%, specifying the primary outcome 26%, numbers given with denominators 6%, and stating number of animals used 47%. Only being an orally presented (vs. poster presented) A (14/16 vs. 48/84, p = 0.025) predicted P. Reporting of studies in P was of poor quality: randomized 39% (the method of randomization and allocation concealment not described), likely blinded 6%, primary outcome specified 5%, sample size calculation stated 0%, numbers given with denominators 34%, and number of animals used stated 56%. Changes in reporting from A to P occurred: from non-randomized to randomized 19%, from non-blinded to blinded 6%, from negative to positive outcomes 8%, from having to not having a stated primary outcome 16%, and from non-statistically to statistically significant findings 37%. Post-hoc, using publication data, P was predicted by having positive outcomes (published 62/62, unpublished 33/38; p = 0.003), or statistically significant results (published 58/62, unpublished 20/38; p < 0.001). Only 62% (95% CI 52-71%) of animal research A are subsequently P; this was predicted by oral presentation of the A, finally having positive outcomes, and finally having statistically significant results. Publication bias is prevalent in critical care animal research.

Predicting drug hydrolysis based on moisture uptake in various packaging designs.

PubMed

Naversnik, Klemen; Bohanec, Simona

2008-12-18

An attempt was made to predict the stability of a moisture sensitive drug product based on the knowledge of the dependence of the degradation rate on tablet moisture. The moisture increase inside a HDPE bottle with the drug formulation was simulated with the sorption-desorption moisture transfer model, which, in turn, allowed an accurate prediction of the drug degradation kinetics. The stability prediction, obtained by computer simulation, was made in a considerably shorter time frame and required little resources compared to a conventional stability study. The prediction was finally upgraded to a stochastic Monte Carlo simulation, which allowed quantitative incorporation of uncertainty, stemming from various sources. The resulting distribution of the outcome of interest (amount of degradation product at expiry) is a comprehensive way of communicating the result along with its uncertainty, superior to single-value results or confidence intervals.

Validation of CRASH Model in Prediction of 14-day Mortality and 6-month Unfavorable Outcome of Head Trauma Patients

PubMed Central

Hashemi, Behrooz; Amanat, Mahnaz; Baratloo, Alireza; Forouzanfar, Mohammad Mehdi; Rahmati, Farhad; Motamedi, Maryam; Safari, Saeed

2016-01-01

Introduction: To date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. External validation of these models in different populations is of great importance for their generalization. The present study was designed, aiming to determine the value of CRASH prognostic model in prediction of 14-day mortality (14-DM) and 6-month unfavorable outcome (6-MUO) of patients with traumatic brain injury. Methods: In the present prospective diagnostic test study, calibration and discrimination of CRASH model were evaluated in head trauma patients referred to the emergency department. Variables required for calculating CRASH expected risks (ER), and observed 14-DM and 6-MUO were gathered. Then ER of 14-DM and 6-MUO were calculated. The patients were followed for 6 months and their 14-DM and 6-MUO were recorded. Finally, the correlation of CRASH ER and the observed outcome of the patients was evaluated. The data were analyzed using STATA version 11.0. Results: In this study, 323 patients with the mean age of 34.0 ± 19.4 years were evaluated (87.3% male). Calibration of the basic and CT models in prediction of 14-day and 6-month outcome were in the desirable range (P < 0.05). Area under the curve in the basic model for prediction of 14-DM and 6-MUO were 0.92 (95% CI: 0.89-0.96) and 0.92 (95% CI: 0.90-0.95), respectively. In addition, area under the curve in the CT model for prediction of 14-DM and 6-MUO were 0.93 (95% CI: 0.91-0.97) and 0.93 (95% CI: 0.91-0.96), respectively. There was no significant difference between the discriminations of the two models in prediction of 14-DM (p = 0.11) and 6-MUO (p = 0.1). Conclusion: The results of the present study showed that CRASH prediction model has proper discrimination and calibration in predicting 14-DM and 6-MUO of head trauma patients. Since there was no difference between the values of the basic and CT models, using the basic model is recommended to simplify the risk calculations. PMID:27800540

Refractive outcomes after multifocal intraocular lens exchange.

PubMed

Kim, Eric J; Sajjad, Ahmar; Montes de Oca, Ildamaris; Koch, Douglas D; Wang, Li; Weikert, Mitchell P; Al-Mohtaseb, Zaina N

2017-06-01

To evaluate the refractive outcomes after multifocal intraocular lens (IOL) exchange. Cullen Eye Institute, Baylor College of Medicine, Houston, Texas, USA. Retrospective case series. Patients had multifocal IOL explantation followed by IOL implantation. Outcome measures included type of IOL, surgical indication, corrected distance visual acuity (CDVA), and refractive prediction error. The study comprised 29 patients (35 eyes). The types of IOLs implanted after multifocal IOL explantation included in-the-bag IOLs (74%), iris-sutured IOLs (6%), sulcus-fixated IOLs with optic capture (9%), sulcus-fixated IOLs without optic capture (9%), and anterior chamber IOLs (3%). The surgical indication for exchange included blurred vision (60%), photic phenomena (57%), photophobia (9%), loss of contrast sensitivity (3%), and multiple complaints (29%). The CDVA was 20/40 or better in 94% of eyes before the exchange and 100% of eyes after the exchange (P = .12). The mean refractive prediction error significantly decreased from 0.22 ± 0.81 diopter (D) before the exchange to -0.09 ± 0.53 D after the exchange (P < .05). The median absolute refractive prediction error significantly decreased from 0.43 D before the exchange to 0.23 D after the exchange (P < .05). Multifocal IOL exchange can be performed safely with good visual outcomes using different types of IOLs. A lower refractive prediction error and a higher likelihood of 20/40 or better vision can be achieved with the implantation of the second IOL compared with the original multifocal IOL, regardless of the final IOL position. Copyright © 2017 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

The effect of user's perceived presence and promotion focus on usability for interacting in virtual environments.

PubMed

Sun, Huey-Min; Li, Shang-Phone; Zhu, Yu-Qian; Hsiao, Bo

2015-09-01

Technological advance in human-computer interaction has attracted increasing research attention, especially in the field of virtual reality (VR). Prior research has focused on examining the effects of VR on various outcomes, for example, learning and health. However, which factors affect the final outcomes? That is, what kind of VR system design will achieve higher usability? This question remains largely. Furthermore, when we look at VR system deployment from a human-computer interaction (HCI) lens, does user's attitude play a role in achieving the final outcome? This study aims to understand the effect of immersion and involvement, as well as users' regulatory focus on usability for a somatosensory VR learning system. This study hypothesized that regulatory focus and presence can effectively enhance user's perceived usability. Survey data from 78 students in Taiwan indicated that promotion focus is positively related to user's perceived efficiency, whereas involvement and promotion focus are positively related to user's perceived effectiveness. Promotion focus also predicts user satisfaction and overall usability perception. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

[Value of sepsis single-disease manage system in predicting mortality in patients with sepsis].

PubMed

Chen, J; Wang, L H; Ouyang, B; Chen, M Y; Wu, J F; Liu, Y J; Liu, Z M; Guan, X D

2018-04-03

Objective: To observe the effect of sepsis single-disease manage system on the improvement of sepsis treatment and the value in predicting mortality in patients with sepsis. Methods: A retrospective study was conducted. Patients with sepsis admitted to the Department of Surgical Intensive Care Unit of Sun Yat-Sen University First Affiliated Hospital from September 22, 2013 to May 5, 2015 were enrolled in this study. Sepsis single-disease manage system (Rui Xin clinical data manage system, China data, China) was used to monitor 25 clinical quality parameters, consisting of timeliness, normalization and outcome parameters. Based on whether these quality parameters could be completed or not, the clinical practice was evaluated by the system. The unachieved quality parameter was defined as suspicious parameters, and these suspicious parameters were used to predict mortality of patients with receiver operating characteristic curve (ROC). Results: A total of 1 220 patients with sepsis were enrolled, included 805 males and 415 females. The mean age was (59±17) years, and acute physiology and chronic health evaluation (APACHE Ⅱ) scores was 19±8. The area under ROC curve of total suspicious numbers for predicting 28-day mortality was 0.70; when the suspicious parameters number was more than 6, the sensitivity was 68.0% and the specificity was 61.0% for predicting 28-day mortality. In addition, the area under ROC curve of outcome suspicious number for predicting 28-day mortality was 0.89; when the suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 78.0% for predicting 28-day mortality. Moreover, the area under ROC curve of total suspicious number for predicting 90-day mortality was 0.73; when the total suspicious parameters number was more than 7, the sensitivity was 60.0% and the specificity was 74.0% for predicting 90-day mortality. Finally, the area under ROC curve of outcome suspicious numbers for predicting 90-day mortality was 0.92; when suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 81.0% for predicting 90-day mortality. Conclusion: The single center study suggests that this sepsis single-disease manage system could be used to monitor the completion of clinical practice for intensivist in managing sepsis, and the number of quality parameters failed to complete could be used to predict the mortality of the patients.

Neurologic examination at 24–48 hours predicts functional outcomes in basilar artery occlusion stroke

PubMed Central

Rangaraju, Srikant; Jovin, Tudor G.; Frankel, Michael; Schonewille, Wouter J.; Algra, Ale; Kappelle, L. Jaap; Nogueira, Raul G.

2016-01-01

Background and Purpose Accurate long-term outcome prognostication in basilar artery occlusion (BAO) strokes may guide clinical management in the subacute stage. We determine the prognostic value of the follow-up neurologic examination using the NIH stroke scale (NIHSS) and identify 24–48 hours NIHSS risk categories in BAO patients. Methods Participants of an observational registry of radiologically-confirmed acute BAO (BASICS) with prospectively collected 24–48 hours NIHSS and 1-month modified Rankin Scale (mRS) scores were included. Uni- and multivariable modeling were performed to identify independent predictors of poor outcome. Predictive powers of baseline and 24–48 hour NIHSS for poor outcome (mRS 4–6) and 1-month mortality were determined by Receiver Operating Characteristic analyses. Classification and regression tree (CART) analysis was performed to identify risk groups. Results 376 of 619 BASICS participants were included of whom 65.4% had poor outcome. In multivariable analyses, 24–48 hours NIHSS (OR=1.28 [1.21–1.35]), history of minor stroke (OR=2.64 [1.04–6.74], time to treatment >6 hours (OR=3.07 [1.35–6.99]) and age (OR 1.02 [0.99–1.04] were retained in the final model as predictors of poor outcome. Prognostic power of 24–48 hours NIHSS was higher than baseline NIHSS for 1-month poor outcome (AUC 0.92 vs. 0.75) and mortality (AUC 0.85 vs. 0.72). CART analysis identified five 24–48 hour NIHSS risk categories with poor outcome rates of 9.4% (NIHSS 0–4), 36% (NIHSS 5–11), 84.3% (NIHSS 12–22), 96.1% (NIHSS 23–27) and 100% (NIHSS≥28). Conclusion 24–48 hour NIHSS accurately predicts 1-month poor outcome and mortality and represents a clinically valuable prognostic tool for the care of BAO patients. PMID:27586683

Patient-Reported Outcomes of Periacetabular Osteotomy from the Prospective ANCHOR Cohort Study

PubMed Central

Clohisy, John C.; Ackerman, Jeffrey; Baca, Geneva; Baty, Jack; Beaulé, Paul E.; Kim, Young-Jo; Millis, Michael B.; Podeszwa, David A.; Schoenecker, Perry L.; Sierra, Rafael J.; Sink, Ernest L.; Sucato, Daniel J.; Trousdale, Robert T.; Zaltz, Ira

2017-01-01

Background: Current literature describing the periacetabular osteotomy (PAO) is mostly limited to retrospective case series. Larger, prospective cohort studies are needed to provide better clinical evidence regarding this procedure. The goals of the current study were to (1) report minimum 2-year patient-reported outcomes (pain, hip function, activity, overall health, and quality of life), (2) investigate preoperative clinical and disease characteristics as predictors of clinical outcomes, and (3) report the rate of early failures and reoperations in patients undergoing contemporary PAO surgery. Methods: A large, prospective, multicenter cohort of PAO procedures was established, and outcomes at a minimum of 2 years were analyzed. A total of 391 hips were included for analysis (79% of the patients were female, and the average patient age was 25.4 years). Patient-reported outcomes, conversion to total hip replacement, reoperations, and major complications were documented. Variables with a p value of ≤0.10 in the univariate linear regressions were included in the multivariate linear regression. The backward stepwise selection method was used to determine the final risk factors of clinical outcomes. Results: Clinical outcome analysis demonstrated major clinically important improvements in pain, function, quality of life, overall health, and activity level. Increasing age and a body mass index status of overweight or obese were predictive of improved results for certain outcome metrics. Male sex and mild acetabular dysplasia were predictive of lesser improvements in certain outcome measures. Three (0.8%) of the hips underwent early conversion to total hip arthroplasty, 12 (3%) required reoperation, and 26 (7%) experienced a major complication. Conclusions: This large, prospective cohort study demonstrated the clinical success of contemporary PAO surgery for the treatment of symptomatic acetabular dysplasia. Patient and disease characteristics demonstrated predictive value that should be considered in surgical decision-making. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence. PMID:28060231

Moments in time: metacognition, trust, and outcomes in dyadic negotiations.

PubMed

Olekalns, Mara; Smith, Philip L

2005-12-01

This research tested the relationships between turning points, cognitive and affective trust, and negotiation outcomes. After completing a simulated negotiation, participants identified turning points from videotape. Turning points were then classified as substantive (interest, offer), characterization (positive, negative), or procedural (positive, negative). Prenegotiation affective trust predicted subsequent turning points, whereas prenegotiation cognitive trust did not, suggesting that different cues influence the two types of trust. Postnegotiation cognitive trust was increased by the occurrence of interest, positive characterization, and positive procedural turning points and decreased by negative characterization turning points. Affective trust was increased by positive procedural turning points. Finally, interest turning points resulted in higher joint outcomes, whereas negative characterization turning points resulted in lower joint outcomes. We conclude that there are two paths to building trust and increasing joint gain, one through insight and one through signaling good faith intentions.

Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team.

PubMed

Harrison, David A; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B; Gwinnutt, Carl; Nolan, Jerry P; Rowan, Kathryn M

2014-08-01

The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Risk models for two outcomes-return of spontaneous circulation (ROSC) for greater than 20min and survival to hospital discharge-were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC>20min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC>20min (c index 0.81 versus 0.72). Validated risk models for ROSC>20min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

The upper respiratory pyramid: early factors and later treatment utilization in World Trade Center exposed firefighters.

PubMed

Niles, Justin K; Webber, Mayris P; Liu, Xiaoxue; Zeig-Owens, Rachel; Hall, Charles B; Cohen, Hillel W; Glaser, Michelle S; Weakley, Jessica; Schwartz, Theresa M; Weiden, Michael D; Nolan, Anna; Aldrich, Thomas K; Glass, Lara; Kelly, Kerry J; Prezant, David J

2014-08-01

We investigated early post 9/11 factors that could predict rhinosinusitis healthcare utilization costs up to 11 years later in 8,079 World Trade Center-exposed rescue/recovery workers. We used bivariate and multivariate analytic techniques to investigate utilization outcomes; we also used a pyramid framework to describe rhinosinusitis healthcare groups at early (by 9/11/2005) and late (by 9/11/2012) time points. Multivariate models showed that pre-9/11/2005 chronic rhinosinusitis diagnoses and nasal symptoms predicted final year healthcare utilization outcomes more than a decade after WTC exposure. The relative proportion of workers on each pyramid level changed significantly during the study period. Diagnoses of chronic rhinosinusitis within 4 years of a major inhalation event only partially explain future healthcare utilization. Exposure intensity, early symptoms and other factors must also be considered when anticipating future healthcare needs. © 2014 Wiley Periodicals, Inc.

Surgery applications of virtual reality

NASA Technical Reports Server (NTRS)

Rosen, Joseph

1994-01-01

Virtual reality is a computer-generated technology which allows information to be displayed in a simulated, bus lifelike, environment. In this simulated 'world', users can move and interact as if they were actually a part of that world. This new technology will be useful in many different fields, including the field of surgery. Virtual reality systems can be used to teach surgical anatomy, diagnose surgical problems, plan operations, simulate and perform surgical procedures (telesurgery), and predict the outcomes of surgery. The authors of this paper describe the basic components of a virtual reality surgical system. These components include: the virtual world, the virtual tools, the anatomical model, the software platform, the host computer, the interface, and the head-coupled display. In the chapter they also review the progress towards using virtual reality for surgical training, planning, telesurgery, and predicting outcomes. Finally, the authors present a training system being developed for the practice of new procedures in abdominal surgery.

The Upper Respiratory Pyramid: Early Factors and Later Treatment Utilization in World Trade Center Exposed Firefighters

PubMed Central

Niles, Justin K.; Webber, Mayris P.; Liu, Xiaoxue; Zeig-Owens, Rachel; Hall, Charles B.; Cohen, Hillel W.; Glaser, Michelle S.; Weakley, Jessica; Schwartz, Theresa M.; Weiden, Michael D.; Nolan, Anna; Aldrich, Thomas K.; Glass, Lara; Kelly, Kerry J.; Prezant, David J.

2015-01-01

Background We investigated early post 9/11 factors that could predict rhinosinusitis healthcare utilization costs up to 11 years later in 8,079 World Trade Center-exposed rescue/recovery workers. Methods We used bivariate and multivariate analytic techniques to investigate utilization outcomes; we also used a pyramid framework to describe rhinosinusitis healthcare groups at early (by 9/11/2005) and late (by 9/11/2012) time points. Results Multivariate models showed that pre-9/11/2005 chronic rhinosinusitis diagnoses and nasal symptoms predicted final year healthcare utilization outcomes more than a decade after WTC exposure. The relative proportion of workers on each pyramid level changed significantly during the study period. Conclusions Diagnoses of chronic rhinosinusitis within 4 years of a major inhalation event only partially explain future healthcare utilization. Exposure intensity, early symptoms and other factors must also be considered when anticipating future healthcare needs. PMID:24898816

Snoring intensity after a first session of soft palate radiofrequency: predictive value of the final result.

PubMed

Blumen, Marc Bernard; Vezina, Jean Philippe; Bequignon, Emilie; Chabolle, Frederic

2013-06-01

To determine whether snoring sound intensity measured after a first soft palate radiofrequency (RF) session for simple snoring helps predict the final result of the treatment. Observational retrospective study. We conducted a retrospective review of 105 subjects presenting with simple snoring or mild sleep apnea. All patients underwent two to three sessions of RF-assisted stiffening of the soft palate. In addition, uvulectomy was performed in case of a long uvula, and two paramedian trenches were created in the presence of palatal webbing. Snoring sound intensity was evaluated by the bed partner after each session. Eighty-six men and 19 women were included in the study. Mean age was 51.7 ± 9.8 years, and mean body mass index was 24.7 ± 4.4 kg/m(2) . The mean apnea/hypopnea index was 6.6 ± 4.2/h. The mean snoring sound intensity, as evaluated on a 10-cm visual analog scale (VAS), decreased from 8.2 ± 1.5 to 3.5 ± 2.2 after all sessions (P < .0001). A score of 3 was determined as being a score that satisfied the bed partner. Two groups were formed according to the final snoring sound intensity, using 3 as a threshold. Both groups had similar preoperative characteristics, but the snoring sound intensity was significantly lower after the first session in the group with final score <3 (P = .01). Similarly, a VAS score >7 after the first session was associated with a final score <3 in 30% of the cases. Snoring sound intensity after the first RF session helps predict the final outcome of RF-assisted stiffening of the soft palate for simple snoring. Copyright © 2012 The American Laryngological, Rhinological and Otological Society, Inc.

Examining the Predictive Validity of a Dynamic Assessment of Decoding to Forecast Response Tier 2 to Intervention

PubMed Central

Cho, Eunsoo; Compton, Donald L.; Fuchs, Doug; Fuchs, Lynn S.; Bouton, Bobette

2013-01-01

The purpose of this study was to examine the role of a dynamic assessment (DA) of decoding in predicting responsiveness to Tier 2 small group tutoring in a response-to-intervention model. First-grade students (n=134) who did not show adequate progress in Tier 1 based on 6 weeks of progress monitoring received Tier 2 small-group tutoring in reading for 14 weeks. Student responsiveness to Tier 2 was assessed weekly with word identification fluency (WIF). A series of conditional individual growth curve analyses were completed that modeled the correlates of WIF growth (final level of performance and growth). Its purpose was to examine the predictive validity of DA in the presence of 3 sets of variables: static decoding measures, Tier 1 responsiveness indicators, and pre-reading variables (phonemic awareness, rapid letter naming, oral vocabulary, and IQ). DA was a significant predictor of final level and growth, uniquely explaining 3% – 13% of the variance in Tier 2 responsiveness depending on the competing predictors in the model and WIF outcome (final level of performance or growth). Although the additional variances explained uniquely by DA were relatively small, results indicate the potential of DA in identifying Tier 2 nonresponders. PMID:23213050

Examining the predictive validity of a dynamic assessment of decoding to forecast response to tier 2 intervention.

PubMed

Cho, Eunsoo; Compton, Donald L; Fuchs, Douglas; Fuchs, Lynn S; Bouton, Bobette

2014-01-01

The purpose of this study was to examine the role of a dynamic assessment (DA) of decoding in predicting responsiveness to Tier 2 small-group tutoring in a response-to-intervention model. First grade students (n = 134) who did not show adequate progress in Tier 1 based on 6 weeks of progress monitoring received Tier 2 small-group tutoring in reading for 14 weeks. Student responsiveness to Tier 2 was assessed weekly with word identification fluency (WIF). A series of conditional individual growth curve analyses were completed that modeled the correlates of WIF growth (final level of performance and growth). Its purpose was to examine the predictive validity of DA in the presence of three sets of variables: static decoding measures, Tier 1 responsiveness indicators, and prereading variables (phonemic awareness, rapid letter naming, oral vocabulary, and IQ). DA was a significant predictor of final level and growth, uniquely explaining 3% to 13% of the variance in Tier 2 responsiveness depending on the competing predictors in the model and WIF outcome (final level of performance or growth). Although the additional variances explained uniquely by DA were relatively small, results indicate the potential of DA in identifying Tier 2 nonresponders. © Hammill Institute on Disabilities 2012.

Evaluation of functional outcome of the floating knee injury using multivariate analysis.

PubMed

Yokoyama, Kazuhiko; Tsukamoto, Tatsuro; Aoki, Shinichi; Wakita, Ryuji; Uchino, Masataka; Noumi, Takashi; Fukushima, Nobuaki; Itoman, Moritoshi

2002-11-01

The objective of this study is to evaluate significant contributing factors affecting the functional prognosis of floating knee injuries using multivariate analysis. A total of 68 floating knee injuries (67 patients) were treated at Kitasato University Hospital from 1986 to 1999. Both the femoral fractures and the tibial fractures were managed surgically by various methods. The functional results of these injuries were evaluated using the grading system of Karlström and Olerud. Follow-up periods ranged from 2 to 19 years (mean 50.2 months) after the original injury. We defined satisfactory (S) outcomes as those cases with excellent or good results and unsatisfactory (US) outcomes as those cases with acceptable or poor results. Logistic regression analysis was used as a multivariate analysis, and the dependent variables were defined as a satisfactory outcome or as an unsatisfactory outcome. The explanatory variables were predicting factors influencing the functional outcome such as age at trauma, gender, severity of soft-tissue injury in the femur and the tibia, AO fracture grade in the femur and the tibia, Fraser type (type I or type II), Injury Severity Score (ISS), and fixation time after injury (less than 1 week or more than 1 week) in the femur and the tibia. The final functional results were as follows: 25 cases had excellent results, 15 cases good results, 16 cases acceptable results, and 12 cases poor results. The predictive logistic regression equation was as follows: Log 1-p/p = 3.12-1.52 x Fraser type - 1.65 x severity of soft-tissue injury in the tibia - 1.31 x fixation time after injury in the tibia - 0.821 x AO fracture grade in the tibia + 1.025 x fixation time after injury in the femur - 0.687 x AO fracture grade in the femur ( p=0.01). Among the variables, Fraser type and the severity of soft-tissue injury in the tibia were significantly related to the final result. The multivariate analysis showed that both the involvement of the knee joint and the severity grade of soft-tissue injury in the tibia represented significant risk factors of poor outcome in floating knee injuries in this study.

Combination growth hormone and gonadotropin releasing hormone analog therapy in 11beta-hydroxylase deficiency.

PubMed

Bajpai, Anurag; Kabra, Madhulika; Menon, P S N

2006-06-01

Diagnosis of 11beta-hydroxylase deficiency was made in a boy at the age of 2 1/2 years on the basis of peripheral precocious puberty, growth acceleration (height standard deviation score +4.4) with advanced skeletal maturation (bone age 8.4 years) and elevated deoxycortisol levels. Glucocorticoid supplementation led to normalization of blood pressure but was associated with progression to central precocious puberty and increase in bone age resulting in decrease in predicted adult height to 133.7 cm (target height 163 cm). The child was started on GnRH analog (triptorelin 3.75 mg every 28 days), which led to improvement in predicted adult height by 3.1 cm over 15 months. Addition of growth hormone (0.1 IU/kg/day) resulted in improvement in predicted adult height (151 cm) and height deficit (12 cm) over the next 3.6 years. Final height (151 cm) exceeded predicted height at the initiation of GnRH analog treatment by 17.3 cm. This report suggests that combination GH and GnRH analog treatment may be useful in improving height outcome in children with 11beta-hydroxylase deficiency and compromised final height.

Protective factors can mitigate behavior problems after prenatal cocaine and other drug exposures.

PubMed

Bada, Henrietta S; Bann, Carla M; Whitaker, Toni M; Bauer, Charles R; Shankaran, Seetha; Lagasse, Linda; Lester, Barry M; Hammond, Jane; Higgins, Rosemary

2012-12-01

We determined the role of risk and protective factors on the trajectories of behavior problems associated with high prenatal cocaine exposure (PCE)/polydrug exposure. The Maternal Lifestyle Study enrolled 1388 children with or without PCE, assessed through age 15 years. Because most women using cocaine during pregnancy also used other substances, we analyzed for the effects of 4 categories of prenatal drug exposure: high PCE/other drugs (OD), some PCE/OD, OD/no PCE, and no PCE/no OD. Risks and protective factors at individual, family, and community levels that may be associated with behavior outcomes were entered stepwise into latent growth curve models, then replaced by cumulative risk and protective indexes, and finally by a combination of levels of risk and protective indexes. Main outcome measures were the trajectories of externalizing, internalizing, total behavior, and attention problems scores from the Child Behavior Checklist (parent). A total of 1022 (73.6%) children had known outcomes. High PCE/OD significantly predicted externalizing, total, and attention problems when considering the balance between risk and protective indexes. Some PCE/OD predicted externalizing and attention problems. OD/no PCE also predicted behavior outcomes except for internalizing behavior. High level of protective factors was associated with declining trajectories of problem behavior scores over time, independent of drug exposure and risk index scores. High PCE/OD is a significant risk for behavior problems in adolescence; protective factors may attenuate its detrimental effects. Clinical practice and public health policies should consider enhancing protective factors while minimizing risks to improve outcomes of drug-exposed children.

Impact of FAB classification on predicting outcome in acute myeloid leukemia, not otherwise specified, patients undergoing allogeneic stem cell transplantation in CR1: An analysis of 1690 patients from the acute leukemia working party of EBMT.

PubMed

Canaani, Jonathan; Beohou, Eric; Labopin, Myriam; Socié, Gerard; Huynh, Anne; Volin, Liisa; Cornelissen, Jan; Milpied, Noel; Gedde-Dahl, Tobias; Deconinck, Eric; Fegueux, Nathalie; Blaise, Didier; Mohty, Mohamad; Nagler, Arnon

2017-04-01

The French, American, and British (FAB) classification system for acute myeloid leukemia (AML) is extensively used and is incorporated into the AML, not otherwise specified (NOS) category in the 2016 WHO edition of myeloid neoplasm classification. While recent data proposes that FAB classification does not provide additional prognostic information for patients for whom NPM1 status is available, it is unknown whether FAB still retains a current prognostic role in predicting outcome of AML patients undergoing allogeneic stem cell transplantation. Using the European Society of Blood and Bone Marrow Transplantation registry we analyzed outcome of 1690 patients transplanted in CR1 to determine if FAB classification provides additional prognostic value. Multivariate analysis revealed that M6/M7 patients had decreased leukemia free survival (hazard ratio (HR) of 1.41, 95% confidence interval (CI), 1.01-1.99; P = .046) in addition to increased nonrelapse mortality (NRM) rates (HR, 1.79; 95% CI, 1.06-3.01; P = .028) compared with other FAB types. In the NPM1 wt AML, NOS cohort, FAB M6/M7 was also associated with increased NRM (HR, 2.17; 95% CI, 1.14-4.16; P = .019). Finally, in FLT3-ITD + patients, multivariate analyses revealed that specific FAB types were tightly associated with adverse outcome. In conclusion, FAB classification may predict outcome following transplantation in AML, NOS patients. © 2017 Wiley Periodicals, Inc.

Beating the news using social media: the case study of American Idol

NASA Astrophysics Data System (ADS)

Ciulla, Fabio; Mocanu, Delia; Baronchelli, Andrea; Goncalves, Bruno; Perra, Nicola; Vespignani, Alessandro

2013-03-01

We present a contribution to the debate on the predictability of social events using big data analytics. We focus on the elimination of contestants in the American Idol TV shows as an example of a well defined electoral phenomenon to assess the predictive power of twitter signals. We provide evidence that Twitter activity during the time span defined by the TV show airing and the voting period following it allows the anticipation of the voting outcome. Twitter data have been analyzed to attempt the winner prediction ahead of the airing of the official result. We also show that the fraction of Tweets that contain geolocation information allows us to map the fanbase of each contestant, both within the US and abroad, showing that strong regional polarizations occur. The geolocalized data are crucial for the correct prediction of the final outcome of the show, pointing out the importance of considering information beyond the aggregated twitter signal. Although American Idol voting is just a minimal and simplified version of complex societal phenomena, this work shows that the volume of information available in online systems permits the real time gathering of quantitative indicators that may be able to anticipate the future unfolding of opinion formation events.

Selection into medical school: from tools to domains.

PubMed

Wilkinson, Tom M; Wilkinson, Tim J

2016-10-03

Most research into the validity of admissions tools focuses on the isolated correlations of individual tools with later outcomes. Instead, looking at how domains of attributes, rather than tools, predict later success is likely to be more generalizable. We aim to produce a blueprint for an admissions scheme that is broadly relevant across institutions. We broke down all measures used for admissions at one medical school into the smallest possible component scores. We grouped these into domains on the basis of a multicollinearity analysis, and conducted a regression analysis to determine the independent validity of each domain to predict outcomes of interest. We identified four broad domains: logical reasoning and problem solving, understanding people, communication skills, and biomedical science. Each was independently and significantly associated with performance in final medical school examinations. We identified two potential errors in the design of admissions schema that can undermine their validity: focusing on tools rather than outcomes, and including a wide range of measures without objectively evaluating the independent contribution of each. Both could be avoided by following a process of programmatic assessment for selection.

Predictive value of neutrophil-to-lymphocyte ratio in diabetic wound healing.

PubMed

Vatankhah, Nasibeh; Jahangiri, Younes; Landry, Gregory J; McLafferty, Robert B; Alkayed, Nabil J; Moneta, Gregory L; Azarbal, Amir F

2017-02-01

The neutrophil-to-lymphocyte ratio (NLR) has been used as a surrogate marker of systemic inflammation. We sought to investigate the association between NLR and wound healing in diabetic wounds. The outcomes of 120 diabetic foot ulcers in 101 patients referred from August 2011 to December 2014 were examined retrospectively. Demographic, patient-specific, and wound-specific variables as well as NLR at baseline visit were assessed. Outcomes were classified as ulcer healing, minor amputation, major amputation, and chronic ulcer. The subjects' mean age was 59.4 ± 13.0 years, and 67 (66%) were male. Final outcome was complete healing in 24 ulcers (20%), minor amputation in 58 (48%) and major amputation in 16 (13%), and 22 chronic ulcers (18%) at the last follow-up (median follow-up time, 6.8 months). In multivariate analysis, higher NLR (odds ratio, 13.61; P = .01) was associated with higher odds of nonhealing. NLR can predict odds of complete healing in diabetic foot ulcers independent of wound infection and other factors. Copyright © 2016 Society for Vascular Surgery. All rights reserved.

A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks.

PubMed

Perisic, Ana; Bauch, Chris T

2009-05-28

Human behavior influences infectious disease transmission, and numerous "prevalence-behavior" models have analyzed this interplay. These previous analyses assumed homogeneously mixing populations without spatial or social structure. However, spatial and social heterogeneity are known to significantly impact transmission dynamics and are particularly relevant for certain diseases. Previous work has demonstrated that social contact structure can change the individual incentive to vaccinate, thus enabling eradication of a disease under a voluntary vaccination policy when the corresponding homogeneous mixing model predicts that eradication is impossible due to free rider effects. Here, we extend this work and characterize the range of possible behavior-prevalence dynamics on a network. We simulate transmission of a vaccine-preventable infection through a random, static contact network. Individuals choose whether or not to vaccinate on any given day according to perceived risks of vaccination and infection. We find three possible outcomes for behavior-prevalence dynamics on this type of network: small final number vaccinated and final epidemic size (due to rapid control through voluntary ring vaccination); large final number vaccinated and significant final epidemic size (due to imperfect voluntary ring vaccination), and little or no vaccination and large final epidemic size (corresponding to little or no voluntary ring vaccination). We also show that the social contact structure enables eradication under a broad range of assumptions, except when vaccine risk is sufficiently high, the disease risk is sufficiently low, or individuals vaccinate too late for the vaccine to be effective. For populations where infection can spread only through social contact network, relatively small differences in parameter values relating to perceived risk or vaccination behavior at the individual level can translate into large differences in population-level outcomes such as final size and final number vaccinated. The qualitative outcome of rational, self interested behaviour under a voluntary vaccination policy can vary substantially depending on interactions between social contact structure, perceived vaccine and disease risks, and the way that individual vaccination decision-making is modelled.

A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks

PubMed Central

2009-01-01

Background Human behavior influences infectious disease transmission, and numerous "prevalence-behavior" models have analyzed this interplay. These previous analyses assumed homogeneously mixing populations without spatial or social structure. However, spatial and social heterogeneity are known to significantly impact transmission dynamics and are particularly relevant for certain diseases. Previous work has demonstrated that social contact structure can change the individual incentive to vaccinate, thus enabling eradication of a disease under a voluntary vaccination policy when the corresponding homogeneous mixing model predicts that eradication is impossible due to free rider effects. Here, we extend this work and characterize the range of possible behavior-prevalence dynamics on a network. Methods We simulate transmission of a vaccine-prevetable infection through a random, static contact network. Individuals choose whether or not to vaccinate on any given day according to perceived risks of vaccination and infection. Results We find three possible outcomes for behavior-prevalence dynamics on this type of network: small final number vaccinated and final epidemic size (due to rapid control through voluntary ring vaccination); large final number vaccinated and significant final epidemic size (due to imperfect voluntary ring vaccination), and little or no vaccination and large final epidemic size (corresponding to little or no voluntary ring vaccination). We also show that the social contact structure enables eradication under a broad range of assumptions, except when vaccine risk is sufficiently high, the disease risk is sufficiently low, or individuals vaccinate too late for the vaccine to be effective. Conclusion For populations where infection can spread only through social contact network, relatively small differences in parameter values relating to perceived risk or vaccination behavior at the individual level can translate into large differences in population-level outcomes such as final size and final number vaccinated. The qualitative outcome of rational, self interested behaviour under a voluntary vaccination policy can vary substantially depending on interactions between social contact structure, perceived vaccine and disease risks, and the way that individual vaccination decision-making is modelled. PMID:19476616

Developmental outcomes of toddlers of young Latina mothers: Cultural, family, and parenting factors.

PubMed

Grau, Josefina M; Duran, Petra A; Castellanos, Patricia; Smith, Erin N; Silberman, Stephanie G; Wood, Lauren E

2015-11-01

Children of adolescent mothers are at risk for poor developmental outcomes. This study is among the first to examine how cultural, family, and parenting factors prospectively predict the cognitive and language development of children of young Latina mothers (N=170; Mage=17.9 years). Mothers were interviewed and observed interacting with their children at 18 months (W1). Children were tested at 18 (W1) and 24 (W2) months. Mothers' cultural orientation (W1) was related to aspects of the childrearing environment (W1), which in turn had implications for the children's development (W2). Specifically, a stronger orientation toward American culture was related to higher mother-reported engagement in parenting by their own mothers (grandmothers), which in turn predicted stronger gains in cognitive and expressive language functioning from W1 to W2. A stronger Latino orientation related to the display of more directiveness and greater mother-reported engagement by the children's biological fathers; directiveness, in turn, predicted fewer gains in cognitive functioning only when father engagement was low and did not predict expressive language development. Finally, mothers' display of more positive affect, a stronger American orientation, and higher grandmother engagement uniquely predicted gains in W2 expressive language functioning. Implications for intervention are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Developmental Outcomes of Toddlers of Young Latina Mothers: Cultural, Family, and Parenting Factors

PubMed Central

Grau, Josefina M.; Duran, Petra A.; Castellanos, Patricia; Smith, Erin N.; Silberman, Stephanie G.; Wood, Lauren

2015-01-01

Children of adolescent mothers are at risk for poor developmental outcomes. This study is among the first to examine how cultural, family, and parenting factors prospectively predict the cognitive and language development of children of young Latina mothers (N=170; Mage = 17.9 years). Mothers were interviewed and observed interacting with their children at 18 months (W1). Children were tested at 18 (W1) and 24 (W2) months. Mothers’ cultural orientation (W1) was related to aspects of the childrearing environment (W1), which in turn had implications for the children's development (W2). Specifically, a stronger orientation toward American culture was related to higher mother-reported engagement in parenting by their own mothers (grandmothers), which in turn predicted stronger gains in cognitive and expressive language functioning from W1 to W2. A stronger Latino orientation related to the display of more directiveness and greater mother-reported engagement by the children's biological fathers; directiveness, in turn, predicted fewer gains in cognitive functioning only when father engagement was low and did not predict expressive language development. Finally, mothers’ display of more positive affect, a stronger American orientation, and higher grandmother engagement uniquely predicted gains in W2 expressive language functioning. Implications for intervention are discussed. PMID:26454205

A Visual Language for Composable Simulation Scenarios

DTIC Science & Technology

2003-03-01

introduced by combining components of different levels of abstraction. However, the ideas presented in this research are applicable to all levels of...mission” [DMS95]. Finally, theater/campaign- level models predict the “outcomes of joint/ combined forces in a theatre/campaign level conflict” [DMS95...Other articles discussing composable simulation also gave more definitions and properties of components [DMS02d], [DMS02e], [BID00]. However, despite

Profile Similarity Metrics Increase Personality Scale Validity (Briefing Charts)

DTIC Science & Technology

2016-04-15

REPORT DATE (DD-MM-YYYY) April 2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) April 2015 – August 2015 4. TITLE AND SUBTITLE... temperament scales are used in employment settings to predict performance because they are generally valid and reduce adverse impact. This research...personality and temperament scales against job continuance outcomes. Analyses documented that: PSMs consistently accounted for over 90% of the variance in

MO-AB-BRA-10: Cancer Therapy Outcome Prediction Based On Dempster-Shafer Theory and PET Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lian, C; University of Rouen, QuantIF - EA 4108 LITIS, 76000 Rouen; Li, H

2015-06-15

Purpose: In cancer therapy, utilizing FDG-18 PET image-based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster-Shafer theory (DST) based approach, evidential low-dimensional transformation with feature selection (ELT-FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics. Methods: First, a specific loss function with sparse penalty was developed to learn an adaptive low-rank distance metric for representing themore » dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low-dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1-norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K-nearest-neighbor (EK- NN) classifier to predict treatment outcome. Results: Twenty-five patients with stage II–III non-small-cell lung cancer and thirty-six patients with esophageal squamous cell carcinomas treated with chemo-radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave-one-out cross-validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT-FS leads to higher prediction accuracy for the training and testing sets both for lung-cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal-cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT-FS also provides superior class separation in both test data sets. Conclusion: A novel DST- based approach has been proposed to predict cancer treatment outcome using PET image features and clinical characteristics. A specific loss function has been designed for robust accommodation of feature set incertitude and imprecision, facilitating adaptive learning of the dissimilarity metric for the EK-NN classifier.« less

Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.

PubMed

Sharma, Vishnu D; Combes, François P; Vakilynejad, Majid; Lahu, Gezim; Lesko, Lawrence J; Trame, Mirjam N

2018-02-01

Development of antiobesity drugs is continuously challenged by high dropout rates during clinical trials. The objective was to develop a population pharmacodynamic model that describes the temporal changes in body weight, considering disease progression, lifestyle intervention, and drug effects. Markov modeling (MM) was applied for quantification and characterization of responder and nonresponder as key drivers of dropout rates, to ultimately support the clinical trial simulations and the outcome in terms of trial adherence. Subjects (n = 4591) from 6 Contrave ® trials were included in this analysis. An indirect-response model developed by van Wart et al was used as a starting point. Inclusion of drug effect was dose driven using a population dose- and time-dependent pharmacodynamic (DTPD) model. Additionally, a population-pharmacokinetic parameter- and data (PPPD)-driven model was developed using the final DTPD model structure and final parameter estimates from a previously developed population pharmacokinetic model based on available Contrave ® pharmacokinetic concentrations. Last, MM was developed to predict transition rate probabilities among responder, nonresponder, and dropout states driven by the pharmacodynamic effect resulting from the DTPD or PPPD model. Covariates included in the models and parameters were diabetes mellitus and race. The linked DTPD-MM and PPPD-MM was able to predict transition rates among responder, nonresponder, and dropout states well. The analysis concluded that body-weight change is an important factor influencing dropout rates, and the MM depicted that overall a DTPD model-driven approach provides a reasonable prediction of clinical trial outcome probabilities similar to a pharmacokinetic-driven approach. © 2017, The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals, Inc. on behalf of American College of Clinical Pharmacology.

The predictive validity of ideal partner preferences: a review and meta-analysis.

PubMed

Eastwick, Paul W; Luchies, Laura B; Finkel, Eli J; Hunt, Lucy L

2014-05-01

A central element of interdependence theory is that people have standards against which they compare their current outcomes, and one ubiquitous standard in the mating domain is the preference for particular attributes in a partner (ideal partner preferences). This article reviews research on the predictive validity of ideal partner preferences and presents a new integrative model that highlights when and why ideals succeed or fail to predict relational outcomes. Section 1 examines predictive validity by reviewing research on sex differences in the preference for physical attractiveness and earning prospects. Men and women reliably differ in the extent to which these qualities affect their romantic evaluations of hypothetical targets. Yet a new meta-analysis spanning the attraction and relationships literatures (k = 97) revealed that physical attractiveness predicted romantic evaluations with a moderate-to-strong effect size (r = ∼.40) for both sexes, and earning prospects predicted romantic evaluations with a small effect size (r = ∼.10) for both sexes. Sex differences in the correlations were small (r difference = .03) and uniformly nonsignificant. Section 2 reviews research on individual differences in ideal partner preferences, drawing from several theoretical traditions to explain why ideals predict relational evaluations at different relationship stages. Furthermore, this literature also identifies alternative measures of ideal partner preferences that have stronger predictive validity in certain theoretically sensible contexts. Finally, a discussion highlights a new framework for conceptualizing the appeal of traits, the difference between live and hypothetical interactions, and the productive interplay between mating research and broader psychological theories.

Statistical Learning Theory for High Dimensional Prediction: Application to Criterion-Keyed Scale Development

PubMed Central

Chapman, Benjamin P.; Weiss, Alexander; Duberstein, Paul

2016-01-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in “big data” problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how three common SLT algorithms–Supervised Principal Components, Regularization, and Boosting—can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach—or perhaps because of them–SLT methods may hold value as a statistically rigorous approach to exploratory regression. PMID:27454257

Design of synthetic bacterial communities for predictable plant phenotypes

PubMed Central

Herrera Paredes, Sur; Gao, Tianxiang; Law, Theresa F.; Finkel, Omri M.; Mucyn, Tatiana; Teixeira, Paulo José Pereira Lima; Salas González, Isaí; Feltcher, Meghan E.; Powers, Matthew J.; Shank, Elizabeth A.; Jones, Corbin D.; Jojic, Vladimir; Dangl, Jeffery L.; Castrillo, Gabriel

2018-01-01

Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant–bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation–responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities. PMID:29462153

CD147/EMMPRIN overexpression and prognosis in cancer: A systematic review and meta-analysis

PubMed Central

Xin, Xiaoyan; Zeng, Xianqin; Gu, Huajian; Li, Min; Tan, Huaming; Jin, Zhishan; Hua, Teng; Shi, Rui; Wang, Hongbo

2016-01-01

CD147/EMMPRIN (extracellular matrix metalloproteinase inducer) plays an important role in tumor progression and a number of studies have suggested that it is an indicator of tumor prognosis. This current meta-analysis systematically reevaluated the predictive potential of CD147/EMMPRIN in various cancers. We searched PubMed and Embase databases to screen the literature. Fixed-effect and random-effect meta-analytical techniques were used to correlate CD147 expression with outcome measures. A total of 53 studies that included 68 datasets were eligible for inclusion in the final analysis. We found a significant association between CD147/EMMPRIN overexpression and adverse tumor outcomes, such as overall survival, disease-specific survival, progression-free survival, metastasis-free survival or recurrence-free survival, irrespective of the model analysis. In addition, CD147/EMMPRIN overexpression predicted a high risk for chemotherapy drugs resistance. CD147/EMMPRIN is a central player in tumor progression and predicts a poor prognosis, including in patients who have received chemo-radiotherapy. Our results provide the evidence that CD147/EMMPRIN could be a potential therapeutic target for cancers. PMID:27608940

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

PubMed

Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

2017-02-01

We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictive Validity of the HKT-R Risk Assessment Tool: Two and 5-Year Violent Recidivism in a Nationwide Sample of Dutch Forensic Psychiatric Patients.

PubMed

Bogaerts, Stefan; Spreen, Marinus; Ter Horst, Paul; Gerlsma, Coby

2018-06-01

This study has examined the predictive validity of the Historical Clinical Future [ Historisch Klinisch Toekomst] Revised risk assessment scheme in a cohort of 347 forensic psychiatric patients, which were discharged between 2004 and 2008 from any of 12 highly secure forensic centers in the Netherlands. Predictive validity was measured 2 and 5 years after release. Official reconviction data obtained from the Dutch Ministry of Security and Justice were used as outcome measures. Violent reoffending within 2 and 5 years after discharge was assessed. With regard to violent reoffending, results indicated that the predictive validity of the Historical domain was modest for 2 (area under the curve [AUC] = .75) and 5 (AUC = .74) years. The predictive validity of the Clinical domain was marginal for 2 (admission: AUC = .62; discharge: AUC = .63) and 5 (admission: AUC = .69; discharge: AUC = .62) years after release. The predictive validity of the Future domain was modest (AUC = .71) for 2 years and low for 5 (AUC = .58) years. The total score of the instrument was modest for 2 years (AUC = .78) and marginal for 5 (AUC = .68) years. Finally, the Final Risk Judgment was modest for 2 years (AUC = .78) and marginal for 5 (AUC = .63) years time at risk. It is concluded that this risk assessment instrument appears to be a satisfactory instrument for risk assessment.

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

Technical Performance as a Predictor of Clinical Outcomes in Laparoscopic Gastric Cancer Surgery.

PubMed

Fecso, Andras B; Bhatti, Junaid A; Stotland, Peter K; Quereshy, Fayez A; Grantcharov, Teodor P

2018-03-23

The purpose of this study was to evaluate the relationship between technical performance and patient outcomes in laparoscopic gastric cancer surgery. Laparoscopic gastrectomy for cancer is an advanced procedure with high rate of postoperative morbidity and mortality. Many variables including patient, disease, and perioperative management factors have been shown to impact postoperative outcomes; however, the role of surgical performance is insufficiently investigated. A retrospective review was performed for all patients who had undergone laparoscopic gastrectomy for cancer at 3 teaching institutions between 2009 and 2015. Patients with available, unedited video-recording of their procedure were included in the study. Video files were rated for technical performance, using Objective Structured Assessments of Technical Skills (OSATS) and Generic Error Rating Tool instruments. The main outcome variable was major short-term complications. The effect of technical performance on patient outcomes was assessed using logistic regression analysis with backward selection strategy. Sixty-one patients with available video recordings were included in the study. The overall complication rate was 29.5%. The mean Charlson comorbidity index, type of procedure, and the global OSATS score were included in the final predictive model. Lower performance score (OSATS ≤29) remained an independent predictor for major short-term outcomes (odds ratio 6.49), while adjusting for comorbidities and type of procedure. Intraoperative technical performance predicts major short-term outcomes in laparoscopic gastrectomy for cancer. Ongoing assessment and enhancement of surgical skills using modern, evidence-based strategies might improve short-term patient outcomes. Future work should focus on developing and studying the effectiveness of such interventions in laparoscopic gastric cancer surgery.

Interventions for reading difficulties: a comparison of response to intervention by ELL and EFL struggling readers.

PubMed

Lovett, Maureen W; De Palma, Maria; Frijters, Jan; Steinbach, Karen; Temple, Meredith; Benson, Nancy; Lacerenza, Léa

2008-01-01

This article explores whether struggling readers from different primary language backgrounds differ in response to phonologically based remediation. Following random assignment to one of three reading interventions or to a special education reading control program, reading and reading-related outcomes of 166 struggling readers were assessed before, during, and following 105 intervention hours. Struggling readers met criteria for reading disability, were below average in oral language and verbal skills, and varied in English as a first language (EFL) versus English-language learner (ELL) status. The research-based interventions proved superior to the special education control on both reading outcomes and rate of growth. No differences were revealed for children of EFL or ELL status in intervention outcomes or growth during intervention. Oral language abilities at entry were highly predictive of final outcomes and of reading growth during intervention, with greater language impairment being associated with greater growth.

Posterior cingulate cortex mediates outcome-contingent allocation of behavior

PubMed Central

Hayden, Benjamin Y.; Nair, Amrita C.; McCoy, Allison N.; Platt, Michael L.

2008-01-01

SUMMARY Adaptive decision making requires selecting an action and then monitoring its consequences to improve future decisions. The neuronal mechanisms supporting action evaluation and subsequent behavioral modification, however, remain poorly understood. To investigate the contribution of posterior cingulate cortex (CGp) to these processes, we recorded activity of single neurons in monkeys performing a gambling task in which the reward outcome of each choice strongly influenced subsequent choices. We found that CGp neurons signaled reward outcomes in a nonlinear fashion, and that outcome-contingent modulations in firing rate persisted into subsequent trials. Moreover, firing rate on any one trial predicted switching to the alternative option on the next trial. Finally, microstimulation in CGp following risky choices promoted a preference reversal for the safe option on the following trial. Collectively, these results demonstrate that CGp directly contributes to the evaluative processes that support dynamic changes in decision making in volatile environments. PMID:18940585

Predicting discharge mortality after acute ischemic stroke using balanced data.

PubMed

Ho, King Chung; Speier, William; El-Saden, Suzie; Liebeskind, David S; Saver, Jeffery L; Bui, Alex A T; Arnold, Corey W

2014-01-01

Several models have been developed to predict stroke outcomes (e.g., stroke mortality, patient dependence, etc.) in recent decades. However, there is little discussion regarding the problem of between-class imbalance in stroke datasets, which leads to prediction bias and decreased performance. In this paper, we demonstrate the use of the Synthetic Minority Over-sampling Technique to overcome such problems. We also compare state of the art machine learning methods and construct a six-variable support vector machine (SVM) model to predict stroke mortality at discharge. Finally, we discuss how the identification of a reduced feature set allowed us to identify additional cases in our research database for validation testing. Our classifier achieved a c-statistic of 0.865 on the cross-validated dataset, demonstrating good classification performance using a reduced set of variables.

Passion in sport: on the quality of the coach-athlete relationship.

PubMed

Lafrenière, Marc-André K; Jowett, Sophia; Vallerand, Robert J; Gonahue, Eric G; Lorimer, Ross

2008-10-01

Vallerand et al. (2003) developed a dualistic model of passion, wherein two types of passion are proposed: harmonious (HP) and obsessive (OP) passion that predict adaptive and less adaptive interpersonal outcomes, respectively. In the present research, we were interested in understanding the role of passion in the quality of coach-athlete relationships. Results of Study 1, conducted with athletes (N=157), revealed that HP positively predicts a high-quality coach-athlete relationship, whereas OP was largely unrelated to such relationships. Study 2 was conducted with coaches (N=106) and showed that only HP positively predicted the quality of the coach-athlete relationship. Furthermore, these effects were fully mediated by positive emotions. Finally, the quality of the coach-athlete relationship positively predicted coaches' subjective well-being. Future research directions are discussed in light of the dualistic model of passion.

Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

PubMed

Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

2018-05-22

To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p < 0.0001) and day 1-3 (p = 0.0012). The biparietal width and the transcerebellar diameter were related to Burdjalov Score on day 1 (p = 0.0111; p = 0.0002). The final multiple regression analysis revealed independent predictors of neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

The Surgical Apgar score combined with Comprehensive Geriatric Assessment improves short- but not long-term outcome prediction in older patients undergoing abdominal cancer surgery.

PubMed

Kenig, Jakub; Mastalerz, Kinga; Mitus, Jerzy; Kapelanczyk, Agata

2018-05-30

Frailty increases the risk of poor surgical outcomes in the older population. Some measurable intraoperative factors may also influence the final outcome. The Surgical Apgar Score (SAS) is a simple system predicting postoperative mortality and morbidity. However, the usefulness of the SAS remains unknown in fit and frail older patients. We aimed to test this, as well as investigate whether SAS can increase the predictive value of frailty in this group of patients. Consecutive patients ≥70 years of age, needing elective abdominal surgery for cancer were enrolled in a prospective study. Comprehensive Geriatric Assessment was used to determine frailty. Logistic regression was conducted investigating the association between the scores and 30-day postoperative outcomes and 1-year mortality. The study included 165 older patients with a median age of 77 (range 70-93) years. The prevalence of frailty was 38.2%. The most significant predictors of short-term morbidity and mortality were frailty [OR 6.2 (95%CI 2.9-13.4) and 14.9 (95%CI 5.9-38)] and the SAS [OR 12.5 (95%CI 2.8-45) and 29.5 (95%CI 6.3-125)]. At long-term follow-up frailty was the best predictor of mortality: OR 4.6 (95%CI 1.8-17.6). Frailty and the SAS, not age, were significant predictors of 30-day postoperative morbidity and mortality both in fit and frail older patients undergoing elective abdominal cancer surgery. At 1-yearfollow-up frailty, not the SAS, was an independent risk factor of mortality. The combination of frailty and the SAS increased predictive accuracy and may be a target of care. Copyright © 2018 Elsevier Inc. All rights reserved.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms

PubMed Central

Khan, Anzalee; Keefe, Richard S. E.

2017-01-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as “avolition and anhedonia,” specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes. PMID:29410933

Respiratory support in oncology ward setting: a prospective descriptive study.

PubMed

Mishra, Seema; Bhatnagar, Sushma; Gupta, Deepak; Goyal, Gaurav Nirvani; Agrawal, Ravi; Jain, Roopesh; Chauhan, Himanshu

2009-01-01

Mechanical ventilation in cancer patients is a critical issue The present prospective descriptive study was designed (1) to assess the patient population needing respirator support in ward setting at a premier state-run oncology institute in India, (2) to observe and analyze the course of their disease while on respirator, and (3) to coordinate better quality of life measures in cancer patients at the institute based on the present study's outcomes. Beginning from March 2005 to March 2006, all cancer patients who were connected to respirator in the wards were enrolled in the current study. Our anesthesiology department at the cancer institute also has primary responsibility for airway management and mechanical ventilation in high dependency units of oncology wards. Preventilation variables in cancer patients were assessed to judge the futility of mechanical ventilation in ward setting. Subsequently, patients were observed for disease course while on respirator. Final outcome with its etio-pathogenesis was correlated with predicted futility of mechanical ventilation. Over a period of 1 year, 132 (46 men and 86 women) cancer patients with median age 40 years (range 1-75 years) were connected to respirator in oncology wards. Based on the preventilation variables and indications for respirator support, right prediction of medical futility and hospital discharge was made in 77% of patients. Underestimation and overestimation of survival to hospital discharge was made in 10% cases and 13% cases, respectively. Based on preventilation variables, prediction of outcome in cancer patients needing respirator support can be made in 77% cases. This high probability of prediction can be used to educate patients, and their families and primary physicians, for well-informed and documented advance directives, formulated and regularly revised DNAR policies, and judicious use of respirator support for better quality-of-life outcomes.

Discrimination in measures of knowledge monitoring accuracy

PubMed Central

Was, Christopher A.

2014-01-01

Knowledge monitoring predicts academic outcomes in many contexts. However, measures of knowledge monitoring accuracy are often incomplete. In the current study, a measure of students’ ability to discriminate known from unknown information as a component of knowledge monitoring was considered. Undergraduate students’ knowledge monitoring accuracy was assessed and used to predict final exam scores in a specific course. It was found that gamma, a measure commonly used as the measure of knowledge monitoring accuracy, accounted for a small, but significant amount of variance in academic performance whereas the discrimination and bias indexes combined to account for a greater amount of variance in academic performance. PMID:25339979

Treatment expectancy affects the outcome of cognitive-behavioral interventions in chronic pain.

PubMed

Goossens, Mariëlle E J B; Vlaeyen, Johan W S; Hidding, Alita; Kole-Snijders, Ank; Evers, Silvia M A A

2005-01-01

Patients' initial beliefs about the success of a given pain treatment are shown to have an important influence on the final treatment outcome. The aims of the paper are to assess determinants of patients' treatment expectancy and to examine the extent to which treatment expectancy predicts the short-term and long-term outcome of cognitive-behavioral treatment of chronic pain. This study employs the data of 2 pooled randomized clinical trials evaluating the effectiveness of cognitive-behavioral interventions for 171 patients with fibromyalgia and chronic low back pain. Pretreatment and posttreatment expectancy were measured by a short questionnaire, which was based on the procedure by Borkovec and Nau. Four composite outcome variables (pain coping and control, motoric behavior, negative affect, and quality of life) were measured before and after the intervention and at 12 months follow-up. Furthermore, several patient characteristics were taken into account. Patients with higher treatment expectancies significantly received less disability compensation and were less fearful. A regression model of 3 factors (better pain coping and control, active and positive interpretation of pain, and less disability compensation) significantly explained 10% of the variance in pretreatment expectancy. Pretreatment expectancy significantly predicted each of the 4 outcome measures immediately after treatment and at 12 months follow-up. This study corroborates the importance of treatment expectation before entering a cognitive-behavioral intervention in patients with chronic musculoskeletal pain.

A Predictive Model of Weight Loss After Roux-en-Y Gastric Bypass up to 5 Years After Surgery: a Useful Tool to Select and Manage Candidates to Bariatric Surgery.

PubMed

Seyssel, Kevin; Suter, Michel; Pattou, François; Caiazzo, Robert; Verkindt, Helene; Raverdy, Violeta; Jolivet, Mathieu; Disse, Emmanuel; Robert, Maud; Giusti, Vittorio

2018-06-19

Different factors, such as age, gender, preoperative weight but also the patient's motivation, are known to impact outcomes after Roux-en-Y gastric bypass (RYGBP). Weight loss prediction is helpful to define realistic expectations and maintain motivation during follow-up, but also to select good candidates for surgery and limit failures. Therefore, developing a realistic predictive tool appears interesting. A Swiss cohort (n = 444), who underwent RYGBP, was used, with multiple linear regression models, to predict weight loss up to 60 months after surgery considering age, height, gender and weight at baseline. We then applied our model on two French cohorts and compared predicted weight to the one finally reached. Accuracy of our model was controlled using root mean square error (RMSE). Mean weight loss was 43.6 ± 13.0 and 40.8 ± 15.4 kg at 12 and 60 months respectively. The model was reliable to predict weight loss (0.37 < R 2  < 0.48) and RMSE between 5.0 and 12.2 kg. High preoperative weight and young age were positively correlated to weight loss, as well as male gender. Correlations between predicted weight and real weight were highly significant in both validation cohorts (R ≥ 0.7 and P < 0.01) and RMSE increased throughout follow-up between 6.2 and 15.4 kg. Our statistical model to predict weight loss outcomes after RYGBP seems accurate. It could be a valuable tool to define realistic weight loss expectations and to improve patient selection and outcomes during follow-up. Further research is needed to demonstrate the interest of this model in improving patients' motivation and results and limit the failures.

Selecting Policy Indicators and Developing Simulation Models for the National School Lunch and Breakfast Programs. Final Report. Special Nutrition Programs Report Series. Special Nutrition Programs Report No. CN-10-PRED

ERIC Educational Resources Information Center

Dragoset, Lisa; Gordon, Anne

2010-01-01

This report describes work using nationally representative 2005 data from the School Nutrition Dietary Assessment-III (SNDA-III) study to develop a simulation model to predict the potential implications of changes in policies or practices related to school meals and school food environments. The model focuses on three domains of outcomes: (1) the…

Effect of Adding McKenzie Syndrome, Centralization, Directional Preference, and Psychosocial Classification Variables to a Risk-Adjusted Model Predicting Functional Status Outcomes for Patients With Lumbar Impairments.

PubMed

Werneke, Mark W; Edmond, Susan; Deutscher, Daniel; Ward, Jason; Grigsby, David; Young, Michelle; McGill, Troy; McClenahan, Brian; Weinberg, Jon; Davidow, Amy L

2016-09-01

Study Design Retrospective cohort. Background Patient-classification subgroupings may be important prognostic factors explaining outcomes. Objectives To determine effects of adding classification variables (McKenzie syndrome and pain patterns, including centralization and directional preference; Symptom Checklist Back Pain Prediction Model [SCL BPPM]; and the Fear-Avoidance Beliefs Questionnaire subscales of work and physical activity) to a baseline risk-adjusted model predicting functional status (FS) outcomes. Methods Consecutive patients completed a battery of questionnaires that gathered information on 11 risk-adjustment variables. Physical therapists trained in Mechanical Diagnosis and Therapy methods classified each patient by McKenzie syndromes and pain pattern. Functional status was assessed at discharge by patient-reported outcomes. Only patients with complete data were included. Risk of selection bias was assessed. Prediction of discharge FS was assessed using linear stepwise regression models, allowing 13 variables to enter the model. Significant variables were retained in subsequent models. Model power (R(2)) and beta coefficients for model variables were estimated. Results Two thousand sixty-six patients with lumbar impairments were evaluated. Of those, 994 (48%), 10 (<1%), and 601 (29%) were excluded due to incomplete psychosocial data, McKenzie classification data, and missing FS at discharge, respectively. The final sample for analyses was 723 (35%). Overall R(2) for the baseline prediction FS model was 0.40. Adding classification variables to the baseline model did not result in significant increases in R(2). McKenzie syndrome or pain pattern explained 2.8% and 3.0% of the variance, respectively. When pain pattern and SCL BPPM were added simultaneously, overall model R(2) increased to 0.44. Although none of these increases in R(2) were significant, some classification variables were stronger predictors compared with some other variables included in the baseline model. Conclusion The small added prognostic capabilities identified when combining McKenzie or pain-pattern classifications with the SCL BPPM classification did not significantly improve prediction of FS outcomes in this study. Additional research is warranted to investigate the importance of classification variables compared with those used in the baseline model to maximize predictive power. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2016;46(9):726-741. Epub 31 Jul 2016. doi:10.2519/jospt.2016.6266.

Dynamic contrast-enhanced perfusion area-detector CT assessed with various mathematical models: Its capability for therapeutic outcome prediction for non-small cell lung cancer patients with chemoradiotherapy as compared with that of FDG-PET/CT.

PubMed

Ohno, Yoshiharu; Fujisawa, Yasuko; Koyama, Hisanobu; Kishida, Yuji; Seki, Shinichiro; Sugihara, Naoki; Yoshikawa, Takeshi

2017-01-01

To directly compare the capability of dynamic first-pass contrast-enhanced (CE-) perfusion area-detector CT (ADCT) and PET/CT for early prediction of treatment response, disease progression and overall survival of non-small cell carcinoma (NSCLC) patients treated with chemoradiotherapy. Fifty-three consecutive Stage IIIB NSCLC patients who had undergone PET/CT, dynamic first-pass CE-perfusion ADCT, chemoradiotherapy, and follow-up examination were enrolled in this study. They were divided into two groups: 1) complete or partial response (CR+PR) and 2) stable or progressive disease (SD+PD). Pulmonary arterial and systemic arterial perfusions and total perfusion were assessed at targeted lesions with the dual-input maximum slope method, permeability surface and distribution volume with the Patlak plot method, tumor perfusion with the single-input maximum slope method, and SUV max , and results were averaged to determine final values for each patient. Next, step-wise regression analysis was used to determine which indices were the most useful for predicting therapeutic effect. Finally, overall survival of responders and non-responders assessed by using the indices that had a significant effect on prediction of therapeutic outcome was statistically compared. The step-wise regression test showed that therapeutic effect (r 2 =0.63, p=0.01) was significantly affected by the following three factors in order of magnitude of impact: systemic arterial perfusion, total perfusion, and SUV max . Mean overall survival showed a significant difference for total perfusion (p=0.003) and systemic arterial perfusion (p=0.04). Dynamic first-pass CE-perfusion ADCT as well as PET/CT are useful for treatment response prediction in NSCLC patients treated with chemoradiotherapy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Variability in in vitro fertilization outcomes of prepubertal goat oocytes explained by basic semen analyses.

PubMed

Palomo, M J; Quintanilla, R; Izquierdo, M D; Mogas, T; Paramio, M T

2016-12-01

This work analyses the changes that caprine spermatozoa undergo during in vitro fertilization (IVF) of in vitro matured prepubertal goat oocytes and their relationship with IVF outcome, in order to obtain an effective model that allows prediction of in vitro fertility on the basis of semen assessment. The evolution of several sperm parameters (motility, viability and acrosomal integrity) during IVF and their relationship with three IVF outcome criteria (total penetration, normal penetration and cleavage rates) were studied in a total of 56 IVF replicates. Moderate correlation coefficients between some sperm parameters and IVF outcome were observed. In addition, stepwise multiple regression analyses were conducted that considered three grouping of sperm parameters as potential explanatory variables of the three IVF outcome criteria. The proportion of IVF outcome variation that can be explained by the fitted models ranged from 0.62 to 0.86, depending upon the trait analysed and the variables considered. Seven out of 32 sperm parameters were selected as partial covariates in at least one of the nine multiple regression models. Among these, progressive sperm motility assessed immediately after swim-up, the percentage of dead sperm with intact acrosome and the incidence of acrosome reaction both determined just before the gamete co-culture, and finally the proportion of viable spermatozoa at 17 h post-insemination were the most frequently selected sperm parameters. Nevertheless, the predictive ability of these models must be confirmed in a larger sample size experiment.

Ocular morbidities of juvenile idiopathic arthritis-associated uveitis in adulthood: results from a tertiary center study.

PubMed

Oray, Merih; Khachatryan, Naira; Ebrahimiadib, Nazanin; Abu Samra, Khawla; Lee, Stacey; Foster, C Stephen

2016-09-01

To describe the clinical and visual outcomes of juvenile idiopathic arthritis (JIA)-associated uveitis in adults and to examine risk factors for ongoing inflammation in adulthood. Medical records were reviewed for patients with JIA-associated uveitis who were >16 years old at the final visit (the last visit prior to data collection). In total, 135 eyes of 77 patients (70 female, 7 male) were included. The mean age of patients at the final visit was 29.72 ± 11.27 years. The number of eyes with visual acuity of ≤20/50 and ≤20/200 at the final visit was 37 (28 %) and 20 (15 %), respectively; at least one ocular complication was present in 72 % of eyes. Band keratopathy was the most frequent complication (42 %), followed by cataract (25 %), posterior synechiae (22 %), maculopathy (22 %), ocular hypertension (13 %), and hypotony (5 %). At the final visit, patients who were >16 years of age at presentation to the Massachusetts Eye Research and Surgery Institution had more ocular complications and a greater degree of vision loss than patients who were ≤16 years of age. Ongoing inflammation at the final visit was noted in 40 patients (52 %). The presence of posterior synechiae, hypotony, cataract at presentation, and a history of cataract surgery prior to presentation were predictive of ongoing inflammation in adulthood in univariate analysis. The presence of hypotony and posterior synechiae at the initial visit were predictive factors in multivariate analysis. JIA-associated uveitis may be associated with ongoing inflammation, ocular complications, and severe visual impairment in adulthood. The presence of posterior synechiae and hypotony at the initial visit is predictive of ongoing inflammation.

Predictive Factors and Treatment Outcomes of Tuberculous Pleural Effusion in Patients With Cancer and Pleural Effusion.

PubMed

Lee, Jaehee; Lee, Yong Dae; Lim, Jae Kwang; Lee, Deok Heon; Yoo, Seung Soo; Lee, Shin Yup; Cha, Seung Ick; Park, Jae Yong; Kim, Chang Ho

2017-08-01

Patients with cancer are at an increased risk of tuberculosis. As pleural effusion has great clinical significance in patients with cancer, the differential diagnosis between tuberculous pleural effusion (TPE) and malignant pleural effusion (MPE) is important. However, the predictive factors and treatment outcomes of TPE in patients with cancer have rarely been studied. Confirmed TPE cases identified at cancer diagnosis and during anticancer management from 2008-2015 were retrospectively investigated. Patients in the study included coexisting TPE and cancer (n = 20), MPE (n = 40) and TPE without cancer (n = 40). Control groups were patients with MPE, and patients with TPE without cancer. Clinical, laboratory and pleural fluid characteristics were compared among groups. Treatment outcomes were compared between patients with TPE with and without cancer. In the final analysis, serum C-reactive protein (S-CRP) ≥3.0mg/dL and pleural fluid adenosine deaminase (ADA) ≥40U/L were independent predictors for identifying TPE in patients with cancer having pleural effusion. The combination of S-CRP with pleural fluid ADA using an "or" rule achieved a sensitivity of 100%, whereas both parameters combined in an "and" rule had a specificity of 98%. Treatment outcomes were not different between the TPE groups with and without cancer. S-CRP and pleural fluid ADA levels may be helpful for predicting TPE in patients with cancer with pleural effusion. The combination of these biomarkers provides better information for distinguishing between TPE and MPE in these patients. Treatment outcomes of TPE in patients with cancer are comparable to those in patients without cancer. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

The preoperative manometric pattern predicts the outcome of surgical treatment for esophageal achalasia.

PubMed

Salvador, Renato; Costantini, Mario; Zaninotto, Giovanni; Morbin, Tiziana; Rizzetto, Christian; Zanatta, Lisa; Ceolin, Martina; Finotti, Elena; Nicoletti, Loredana; Da Dalt, Gianfranco; Cavallin, Francesco; Ancona, Ermanno

2010-11-01

A new manometric classification of esophageal achalasia has recently been proposed that also suggests a correlation with the final outcome of treatment. The aim of this study was to investigate this hypothesis in a large group of achalasia patients undergoing laparoscopic Heller-Dor myotomy. We evaluated 246 consecutive achalasia patients who underwent surgery as their first treatment from 2001 to 2009. Patients with sigmoid-shaped esophagus were excluded. Symptoms were scored and barium swallow X-ray, endoscopy, and esophageal manometry were performed before and again at 6 months after surgery. Patients were divided into three groups: (I) no distal esophageal pressurization (contraction wave amplitude <30 mmHg); (II) rapidly propagating compartmentalized pressurization (panesophageal pressurization >30 mmHg); and (III) rapidly propagating pressurization attributable to spastic contractions. Treatment failure was defined as a postoperative symptom score greater than the 10th percentile of the preoperative score (i.e., >7). Type III achalasia coincided with a longer overall lower esophageal sphincter (LES) length, a lower symptom score, and a smaller esophageal diameter. Treatment failure rates differed significantly in the three groups: I = 14.6% (14/96), II = 4.7% (6/127), and III = 30.4% (7/23; p = 0.0007). At univariate analysis, the manometric pattern, a low LES resting pressure, and a high chest pain score were the only factors predicting treatment failure. At multivariate analysis, the manometric pattern and a LES resting pressure <30 mmHg predicted a negative outcome. This is the first study by a surgical group to assess the outcome of surgery in 3 manometric achalasia subtypes: patients with panesophageal pressurization have the best outcome after laparoscopic Heller-Dor myotomy.

Can Preoperative Psychological Assessment Predict Outcomes After Temporomandibular Joint Arthroscopy?

PubMed

Bouloux, Gary F; Zerweck, Ashley G; Celano, Marianne; Dai, Tian; Easley, Kirk A

2015-11-01

Psychological assessment has been used successfully to predict patient outcomes after cardiothoracic and bariatric surgery. The purpose of this study was to determine whether preoperative psychological assessment could be used to predict patient outcomes after temporomandibular joint arthroscopy. Consecutive patients with temporomandibular dysfunction (TMD) who could benefit from arthroscopy were enrolled in a prospective cohort study. All patients completed the Millon Behavior Medicine Diagnostic survey before surgery. The primary predictor variable was the preoperative psychological scores. The primary outcome variable was the difference in pain between the pre- and postoperative periods. The Spearman rank correlation coefficient and the Pearson product-moment correlation were used to determine the association between psychological factors and change in pain. Univariable and multivariable analyses were performed using a mixed-effects linear model and multiple linear regression. A P value of .05 was considered significant. Eighty-six patients were enrolled in the study. Seventy-five patients completed the study and were included in the final analyses. The mean change in visual analog scale (VAS) pain score 1 month after arthroscopy was -15.4 points (95% confidence interval, -6.0 to -24.7; P < .001). Jaw function also improved after surgery (P < .001). No association between change in VAS pain score and each of the 5 preoperative psychological factors was identified with univariable correlation analyses. Multivariable analyses identified that a greater pain decrease was associated with a longer duration of preoperative symptoms (P = .054) and lower chronic anxiety (P = .064). This study has identified a weak association between chronic anxiety and the magnitude of pain decrease after arthroscopy for TMD. Further studies are needed to clarify the role of chronic anxiety in the outcome after surgical procedures for the treatment of TMD. Copyright © 2015. Published by Elsevier Inc.

Hippocampal Mismatch Signals Are Modulated by the Strength of Neural Predictions and Their Similarity to Outcomes.

PubMed

Long, Nicole M; Lee, Hongmi; Kuhl, Brice A

2016-12-14

The hippocampus is thought to compare predicted events with current perceptual input, generating a mismatch signal when predictions are violated. However, most prior studies have only inferred when predictions occur without measuring them directly. Moreover, an important but unresolved question is whether hippocampal mismatch signals are modulated by the degree to which predictions differ from outcomes. Here, we conducted a human fMRI study in which subjects repeatedly studied various word-picture pairs, learning to predict particular pictures (outcomes) from the words (cues). After initial learning, a subset of cues was paired with a novel, unexpected outcome, whereas other cues continued to predict the same outcome. Critically, when outcomes changed, the new outcome was either "near" to the predicted outcome (same visual category as the predicted picture) or "far" from the predicted outcome (different visual category). Using multivoxel pattern analysis, we indexed cue-evoked reactivation (prediction) within neocortical areas and related these trial-by-trial measures of prediction strength to univariate hippocampal responses to the outcomes. We found that prediction strength positively modulated hippocampal responses to unexpected outcomes, particularly when unexpected outcomes were close, but not identical, to the prediction. Hippocampal responses to unexpected outcomes were also associated with a tradeoff in performance during a subsequent memory test: relatively faster retrieval of new (updated) associations, but relatively slower retrieval of the original (older) associations. Together, these results indicate that hippocampal mismatch signals reflect a comparison between active predictions and current outcomes and that these signals are most robust when predictions are similar, but not identical, to outcomes. Although the hippocampus is widely thought to signal "mismatches" between memory-based predictions and outcomes, previous research has not linked hippocampal mismatch signals directly to neural measures of prediction strength. Here, we show that hippocampal mismatch signals increase as a function of the strength of predictions in neocortical regions. This increase in hippocampal mismatch signals was particularly robust when outcomes were similar, but not identical, to predictions. These results indicate that hippocampal mismatch signals are driven by both the active generation of predictions and the similarity between predictions and outcomes. Copyright © 2016 the authors 0270-6474/16/3612677-11$15.00/0.

Prediction of competitive diffusion on complex networks

NASA Astrophysics Data System (ADS)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2018-10-01

In this paper, we study the prediction problem of diffusion process on complex networks in competitive circumstances. With this problem solved, the competitors could timely intervene the diffusion process if needed such that an expected outcome might be obtained. We consider a model with two groups of competitors spreading opposite opinions on a network. A prediction method based on the mutual influences among the agents is proposed, called Influence Matrix (IM for short), and simulations on real-world networks show that the proposed IM method has quite high accuracy on predicting both the preference of any normal agent and the final competition result. For comparison purpose, classic centrality measures are also used to predict the competition result. It is shown that PageRank, Degree, Katz Centrality, and the IM method are suitable for predicting the competition result. More precisely, in undirected networks, the IM method performs better than these centrality measures when the competing group contains more than one agent; in directed networks, the IM method performs only second to PageRank.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience.

PubMed

Harvey, Philip D; Khan, Anzalee; Keefe, Richard S E

2017-12-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as "avolition and anhedonia," specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes.

Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model.

PubMed

Briggs, Andrew H; Baker, Timothy; Risebrough, Nancy A; Chambers, Mike; Gonzalez-McQuire, Sebastian; Ismaila, Afisi S; Exuzides, Alex; Colby, Chris; Tabberer, Maggie; Muellerova, Hana; Locantore, Nicholas; Rutten van Mölken, Maureen P M H; Lomas, David A

2017-05-01

The recent joint International Society for Pharmacoeconomics and Outcomes Research / Society for Medical Decision Making Modeling Good Research Practices Task Force emphasized the importance of conceptualizing and validating models. We report a new model of chronic obstructive pulmonary disease (COPD) (part of the Galaxy project) founded on a conceptual model, implemented using a novel linked-equation approach, and internally validated. An expert panel developed a conceptual model including causal relationships between disease attributes, progression, and final outcomes. Risk equations describing these relationships were estimated using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study, with costs estimated from the TOwards a Revolution in COPD Health (TORCH) study. Implementation as a linked-equation model enabled direct estimation of health service costs and quality-adjusted life years (QALYs) for COPD patients over their lifetimes. Internal validation compared 3 years of predicted cohort experience with ECLIPSE results. At 3 years, the Galaxy COPD model predictions of annual exacerbation rate and annual decline in forced expiratory volume in 1 second fell within the ECLIPSE data confidence limits, although 3-year overall survival was outside the observed confidence limits. Projections of the risk equations over time permitted extrapolation to patient lifetimes. Averaging the predicted cost/QALY outcomes for the different patients within the ECLIPSE cohort gives an estimated lifetime cost of £25,214 (undiscounted)/£20,318 (discounted) and lifetime QALYs of 6.45 (undiscounted/5.24 [discounted]) per ECLIPSE patient. A new form of model for COPD was conceptualized, implemented, and internally validated, based on a series of linked equations using epidemiological data (ECLIPSE) and cost data (TORCH). This Galaxy model predicts COPD outcomes from treatment effects on disease attributes such as lung function, exacerbations, symptoms, or exercise capacity; further external validation is required.

Neuropsychological and socio-occupational functioning in young psychiatric outpatients: a longitudinal investigation.

PubMed

Lee, Rico S C; Hermens, Daniel F; Redoblado-Hodge, M Antoinette; Naismith, Sharon L; Porter, Melanie A; Kaur, Manreena; White, Django; Scott, Elizabeth M; Hickie, Ian B

2013-01-01

Clinical symptoms and neuropsychological deficits are longitudinally associated with functional outcome in chronic psychiatric cohorts. The current study extended these findings to young and early-course psychiatric outpatients, with the aim of identifying cognitive markers that predict later socio-occupational functioning. At baseline, 183 young psychiatric outpatients were assessed. Ninety-three returned for follow-up (M = 21.6 years old; SD = 4.5) with an average re-assessment interval of 21.6 months (SD = 7.0), and primary diagnoses of major depressive disorder (n = 34), bipolar disorder (n = 29), or psychosis (n = 30). The primary outcome measure was cross-validated with various other functional measures and structural equation modelling was used to map out the interrelationships between predictors and later functional outcome. Good socio-occupational functioning at follow-up was associated with better quality of life, less disability, current employment and being in a romantic relationship. The final structural equation model explained 47.5% of the variability in functional outcome at follow-up, with baseline neuropsychological functioning (a composite of memory, working memory and attentional switching) the best independent predictor of later functional outcome. Notably, depressive and negative symptoms were only associated with functioning cross-sectionally. Diagnosis at follow-up was not associated with functional outcome. Neuropsychological functioning was the single best predictor of later socio-occupational outcome among young psychiatric outpatients. Therefore, framing psychiatric disorders along a neuropsychological continuum is likely to be more useful in predicting functional trajectory than traditional symptom-based classification systems. The current findings also have implications for early intervention utilising cognitive remediation approaches.

Definition of Failed Induction of Labor and Its Predictive Factors: Two Unsolved Issues of an Everyday Clinical Situation.

PubMed

Baños, Núria; Migliorelli, Federico; Posadas, Eduardo; Ferreri, Janisse; Palacio, Montse

2015-01-01

The objectives of this review were to identify the predictive factors of induction of labor (IOL) failure or success as well as to highlight the current heterogeneity regarding the definition and diagnosis of failed IOL. Only studies in which the main or secondary outcome was failed IOL, defined as not entering the active phase of labor after 24 h of prostaglandin administration ± 12 h of oxytocin infusion, were included in the review. The data collected were: study design, definition of failed IOL, induction method, IOL indications, failed IOL rate, cesarean section because of failed IOL and predictors of failed IOL. The database search detected 507 publications. The main reason for exclusion was that the primary or secondary outcomes were not the predetermined definition of failed IOL (not achieving active phase of labor). Finally, 7 studies were eligible. The main predictive factors identified in the review were cervical status, evaluated by the Bishop score or cervical length. Failed IOL should be defined as the inability to achieve the active phase of labor, considering that the definition of IOL is to enter the active phase of labor. A universal definition of failed IOL is an essential requisite to analyze and obtain solid results and conclusions on this issue. An important finding of this review is that only 7 of all the studies reviewed assessed achieving the active phase of labor as a primary or secondary IOL outcome. Another conclusion is that cervical status remains the most important predictor of IOL outcome, although the value of the parameters explored up to now is limited. To find or develop predictive tools to identify those women exposed to IOL who may not reach the active phase of labor is crucial to minimize the risks and costs associated with IOL failure while opening a great opportunity for investigation. Therefore, other predictive tools should be studied in order to improve IOL outcome in terms of health and economic burden. © 2015 S. Karger AG, Basel.

Mining manufacturing data for discovery of high productivity process characteristics.

PubMed

Charaniya, Salim; Le, Huong; Rangwala, Huzefa; Mills, Keri; Johnson, Kevin; Karypis, George; Hu, Wei-Shou

2010-06-01

Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 'trains' comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses. 2010 Elsevier B.V. All rights reserved.

Optimization of rotamers prior to template minimization improves stability predictions made by computational protein design.

PubMed

Davey, James A; Chica, Roberto A

2015-04-01

Computational protein design (CPD) predictions are highly dependent on the structure of the input template used. However, it is unclear how small differences in template geometry translate to large differences in stability prediction accuracy. Herein, we explored how structural changes to the input template affect the outcome of stability predictions by CPD. To do this, we prepared alternate templates by Rotamer Optimization followed by energy Minimization (ROM) and used them to recapitulate the stability of 84 protein G domain β1 mutant sequences. In the ROM process, side-chain rotamers for wild-type (WT) or mutant sequences are optimized on crystal or nuclear magnetic resonance (NMR) structures prior to template minimization, resulting in alternate structures termed ROM templates. We show that use of ROM templates prepared from sequences known to be stable results predominantly in improved prediction accuracy compared to using the minimized crystal or NMR structures. Conversely, ROM templates prepared from sequences that are less stable than the WT reduce prediction accuracy by increasing the number of false positives. These observed changes in prediction outcomes are attributed to differences in side-chain contacts made by rotamers in ROM templates. Finally, we show that ROM templates prepared from sequences that are unfolded or that adopt a nonnative fold result in the selective enrichment of sequences that are also unfolded or that adopt a nonnative fold, respectively. Our results demonstrate the existence of a rotamer bias caused by the input template that can be harnessed to skew predictions toward sequences displaying desired characteristics. © 2014 The Protein Society.

Statistical learning theory for high dimensional prediction: Application to criterion-keyed scale development.

PubMed

Chapman, Benjamin P; Weiss, Alexander; Duberstein, Paul R

2016-12-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in "big data" problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how 3 common SLT algorithms-supervised principal components, regularization, and boosting-can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach-or perhaps because of them-SLT methods may hold value as a statistically rigorous approach to exploratory regression. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

PubMed

Park, Seong Ho; Han, Kyunghwa

2018-03-01

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

The development of a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool for Better Outcomes in Labour Difficulty (BOLD): study protocol.

PubMed

Souza, João Paulo; Oladapo, Olufemi T; Bohren, Meghan A; Mugerwa, Kidza; Fawole, Bukola; Moscovici, Leonardo; Alves, Domingos; Perdona, Gleici; Oliveira-Ciabati, Livia; Vogel, Joshua P; Tunçalp, Özge; Zhang, Jim; Hofmeyr, Justus; Bahl, Rajiv; Gülmezoglu, A Metin

2015-05-26

The partograph is currently the main tool available to support decision-making of health professionals during labour. However, the rate of appropriate use of the partograph is disappointingly low. Apart from limitations that are associated with partograph use, evidence of positive impact on labour-related health outcomes is lacking. The main goal of this study is to develop a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool. The primary objectives are: to identify the essential elements of intrapartum monitoring that trigger the decision to use interventions aimed at preventing poor labour outcomes; to develop a simplified, monitoring-to-action algorithm for labour management; and to compare the diagnostic performance of SELMA and partograph algorithms as tools to identify women who are likely to develop poor labour-related outcomes. A prospective cohort study will be conducted in eight health facilities in Nigeria and Uganda (four facilities from each country). All women admitted for vaginal birth will comprise the study population (estimated sample size: 7,812 women). Data will be collected on maternal characteristics on admission, labour events and pregnancy outcomes by trained research assistants at the participating health facilities. Prediction models will be developed to identify women at risk of intrapartum-related perinatal death or morbidity (primary outcomes) throughout the course of labour. These predictions models will be used to assemble a decision-support tool that will be able to suggest the best course of action to avert adverse outcomes during the course of labour. To develop this set of prediction models, we will use up-to-date techniques of prognostic research, including identification of important predictors, assigning of relative weights to each predictor, estimation of the predictive performance of the model through calibration and discrimination, and determination of its potential for application using internal validation techniques. This research offers an opportunity to revisit the theoretical basis of the partograph. It is envisioned that the final product would help providers overcome the challenging tasks of promptly interpreting complex labour information and deriving appropriate clinical actions, and thus increase efficiency of the care process, enhance providers' competence and ultimately improve labour outcomes. Please see related articles ' http://dx.doi.org/10.1186/s12978-015-0027-6 ' and ' http://dx.doi.org/10.1186/s12978-015-0028-5 '.

Predictive model for risk of cesarean section in pregnant women after induction of labor.

PubMed

Hernández-Martínez, Antonio; Pascual-Pedreño, Ana I; Baño-Garnés, Ana B; Melero-Jiménez, María R; Tenías-Burillo, José M; Molina-Alarcón, Milagros

2016-03-01

To develop a predictive model for risk of cesarean section in pregnant women after induction of labor. A retrospective cohort study was conducted of 861 induced labors during 2009, 2010, and 2011 at Hospital "La Mancha-Centro" in Alcázar de San Juan, Spain. Multivariate analysis was used with binary logistic regression and areas under the ROC curves to determine predictive ability. Two predictive models were created: model A predicts the outcome at the time the woman is admitted to the hospital (before the decision to of the method of induction); and model B predicts the outcome at the time the woman is definitely admitted to the labor room. The predictive factors in the final model were: maternal height, body mass index, nulliparity, Bishop score, gestational age, macrosomia, gender of fetus, and the gynecologist's overall cesarean section rate. The predictive ability of model A was 0.77 [95% confidence interval (CI) 0.73-0.80] and model B was 0.79 (95% CI 0.76-0.83). The predictive ability for pregnant women with previous cesarean section with model A was 0.79 (95% CI 0.64-0.94) and with model B was 0.80 (95% CI 0.64-0.96). For a probability of estimated cesarean section ≥80%, the models A and B presented a positive likelihood ratio (+LR) for cesarean section of 22 and 20, respectively. Also, for a likelihood of estimated cesarean section ≤10%, the models A and B presented a +LR for vaginal delivery of 13 and 6, respectively. These predictive models have a good discriminative ability, both overall and for all subgroups studied. This tool can be useful in clinical practice, especially for pregnant women with previous cesarean section and diabetes.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

Prostate Gland Lengths and Iceball Dimensions Predict Micturition Functional Outcome Following Salvage Prostate Cryotherapy in Men with Radiation Recurrent Prostate Cancer

PubMed Central

Ahmad, Imran; Kalna, Gabriela; Ismail, Mohamed; Birrell, Fiona; Asterling, Sue; McCartney, Elaine; Greene, Damien; Davies, John; Leung, Hing Y.

2013-01-01

Introduction Tissue cryoablation is a potential curative option for solid malignancies, including radiation recurrent prostate cancer (RRPC). Case series of salvage cryotherapy (SCT) in RRPC have reported promising disease free survival (DFS) outcomes and acceptable toxicity profile. While many men receive SCT, no predictive factors for treatment induced side effects are known. The aim of this study is to validate the oncologic outcome of SCT in a large multi-centre patient cohort and to identify potential parameters associated with an increased risk of micturition symptoms. Patients and Methods In this retrospective analysis, we studied 283 consecutive patients with RRPC treated by SCT in three independent U.K. centres (between 2001 and 2011). Two freeze-thaw cycles of transperineal cryotherapy were performed under transrectal ultrasound guidance by a single surgeon in each of the 3 sites. We analysed clinico-pathological factors against tumour response. Functional outcomes were assessed by continence status and IPSS questionnaire. Predictive factors for SCT-induced micturition symptoms were analysed in a sub-group (n = 42) of consecutive cases. Results We found that nadir post-SCT PSA levels strongly associated with DFS. The DFS rates at 12- and 36-month were 84% and 67% for the ≤1 ng/ml group and 56% and 14% for the >1 ng/ml group, respectively (p<0.001). Correlative analysis revealed highly significant association between patients' post-SCT micturition status with prostate gland and iceball lengths following SCT. Finally, in a reduction model, both gland length and maximal length of iceball were highly associated with patients' IPSS outcome (p<0.001). Conclusion We report the largest European patient cohort treated with SCT for RRPC. Oncologic outcome guided by nadir PSA of <1 ng/ml is consistent with earlier single-centre series. For the first time, we identified physical parameters to predict micturition symptoms following SCT. Our data will directly assist on-going and future trial design in cryotherapy in prostate cancer. PMID:23950886

Outcomes assessment in the SPRINT multicenter tibial fracture trial: Adjudication committee size has trivial effect on trial results.

PubMed

Simunovic, Nicole; Walter, Stephen; Devereaux, P J; Sprague, Sheila; Guyatt, Gordon H; Schemitsch, Emil; Tornetta, Paul; Sanders, David; Swiontkowski, Marc; Bhandari, Mohit

2011-09-01

To evaluate how the size of an outcome adjudication committee, and the potential for dominance among its members, potentially impacts a trial's results. We conducted a retrospective analysis of data from the six-member adjudication committee in the Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT) Trial. We modeled the adjudication process, predicted the results and costs if smaller committees had been used, and tested for the presence of a dominant adjudicator. Use of smaller committee sizes (one to five members) would have had little impact on the final study results, although one analysis suggested that the benefit in reduction of reoperations with reamed nails in closed tibial fractures would have lost significance if committee sizes of three or less were used. We identified a significant difference between adjudicators in the number of times their original minority decisions became the final consensus decision (χ(2)=9.67, P=0.046), suggesting that dominant adjudicators were present. However, their impact on the final study results was trivial. Reducing the number of adjudicators from six to four would have led to little change in the final SPRINT study results irrespective of the significance of the original trial results, demonstrating the potential for savings in trial resources. Copyright © 2011 Elsevier Inc. All rights reserved.

The Meaning of Disease and Spiritual Responses to Stressors in Adults With Acute Leukemia Undergoing Hematopoietic Stem Cell Transplantation.

PubMed

Farsi, Zahra

2015-12-01

Some studies have shown that patients with cancer may experience significant spiritual distress as well as spiritual growth, that there is a positive association between spirituality and coping, and that positive religious coping predicts enhanced health outcomes. This study was designed to help explain how the meaning of disease and spiritual responses to threatening stressors influence the final experiential outcomes of adults with leukemia undergoing hematopoietic stem cell transplantation in Iran. This grounded theory study conducted in-depth interviews between 2009 and 2011 on 10 adults in Iran with leukemia undergoing hematopoietic stem cell transplantation. Recorded audio interviews were transcribed verbatim in Persian and coded and analyzed using Corbin and Strauss (2008)'s approach. Main categories that emerged from data included "experiencing the meaning of cancer"; "changing perceptions of death, life and health"; and "moving toward perfection and sublimity." "Finding meaning" was the main concept that defined the final outcome of the experience of participants. Understanding the meaning to patients of disease and treatments may help healthcare providers better appreciate the patients' perspective and improve the physician-patient relationship. Nurses are well positioned to play a decisive role in helping patients cope effectively with their treatment process and in helping ensure positive outcomes for treatments through their helping patients find the unique meaning of their experience.

Beta oscillations reflect supramodal information during perceptual judgment.

PubMed

Haegens, Saskia; Vergara, José; Rossi-Pool, Román; Lemus, Luis; Romo, Ranulfo

2017-12-26

Previous work on perceptual decision making in the sensorimotor system has shown population dynamics in the beta band, corresponding to the encoding of stimulus properties and the final decision outcome. Here, we asked how oscillatory dynamics in the medial premotor cortex (MPC) contribute to supramodal perceptual decision making. We recorded local field potentials (LFPs) and spikes in two monkeys trained to perform a tactile-acoustic frequency discrimination task, including both unimodal and crossmodal conditions. We studied the role of oscillatory activity as a function of stimulus properties (frequency and sensory modality), as well as decision outcome. We found that beta-band power correlated with relevant stimulus properties: there was a significant modulation by stimulus frequency during the working-memory (WM) retention interval, as well as modulation by stimulus modality-the latter was observed only in the case of a purely unimodal task, where modality information was relevant to prepare for the upcoming second stimulus. Furthermore, we found a significant modulation of beta power during the comparison and decision period, which was predictive of decision outcome. Finally, beta-band spike-field coherence (SFC) matched these LFP observations. In conclusion, we demonstrate that beta power in MPC is reflective of stimulus features in a supramodal, context-dependent manner, and additionally reflects the decision outcome. We propose that these beta modulations are a signature of the recruitment of functional neuronal ensembles, which encode task-relevant information.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

PubMed

Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

Prediction of two month modified Rankin Scale with an ordinal prediction model in patients with aneurysmal subarachnoid haemorrhage

PubMed Central

2010-01-01

Background Aneurysmal subarachnoid haemorrhage (aSAH) is a devastating event with a frequently disabling outcome. Our aim was to develop a prognostic model to predict an ordinal clinical outcome at two months in patients with aSAH. Methods We studied patients enrolled in the International Subarachnoid Aneurysm Trial (ISAT), a randomized multicentre trial to compare coiling and clipping in aSAH patients. Several models were explored to estimate a patient's outcome according to the modified Rankin Scale (mRS) at two months after aSAH. Our final model was validated internally with bootstrapping techniques. Results The study population comprised of 2,128 patients of whom 159 patients died within 2 months (8%). Multivariable proportional odds analysis identified World Federation of Neurosurgical Societies (WFNS) grade as the most important predictor, followed by age, sex, lumen size of the aneurysm, Fisher grade, vasospasm on angiography, and treatment modality. The model discriminated moderately between those with poor and good mRS scores (c statistic = 0.65), with minor optimism according to bootstrap re-sampling (optimism corrected c statistic = 0.64). Conclusion We presented a calibrated and internally validated ordinal prognostic model to predict two month mRS in aSAH patients who survived the early stage up till a treatment decision. Although generalizability of the model is limited due to the selected population in which it was developed, this model could eventually be used to support clinical decision making after external validation. Trial Registration International Standard Randomised Controlled Trial, Number ISRCTN49866681 PMID:20920243

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

PubMed

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

2016-01-01

To evaluate predictive factors for postoperative visual function of primary chronic rhegmatgenous retinal detachment (RRD) after sclera buckling (SB). Totally 48 patients (51 eyes) with primary chronic RRD were included in this prospective interventional clinical cases study, which underwent SB alone from June 2008 to December 2014. Age, sex, symptoms duration, detached extension, retinal hole position, size, type, fovea on/off, proliferative vitreoretinopathy (PVR), posterior vitreous detachment (PVD), baseline best corrected visual acuity (BCVA), operative duration, follow up duration, final BCVA were measured. Pearson correlation analysis, Spearman correlation analysis and multivariate linear stepwise regression were used to confirm predictive factors for better final visual acuity. Student's t-test, Wilcoxon two-sample test, Chi-square test and logistic stepwise regression were used to confirm predictive factors for better vision improvement. Baseline BCVA was 0.8313±0.6911 logMAR and final BCVA was 0.4761±0.4956 logMAR. Primary surgical success rate was 92.16% (47/51). Correlation analyses revealed shorter symptoms duration (r=0.3850, P=0.0053), less detached area (r=0.5489, P<0.0001), fovea (r=0.4605, P=0.0007), no PVR (r=0.3138, P=0.0250), better baseline BCVA (r=0.7291, P<0.0001), shorter operative duration (r=0.3233, P=0.0207) and longer follow up (r=-0.3358, P=0.0160) were related with better final BCVA, while independent predictive factors were better baseline BCVA [partial R-square (PR(2))=0.5316, P<0.0001], shorter symptoms duration (PR(2)=0.0609, P=0.0101), longer follow up duration (PR(2)=0.0278, P=0.0477) and shorter operative duration (PR(2)=0.0338, P=0.0350). Patients with vision improvement took up 49.02% (25/51). Univariate and multivariate analyses both revealed predictive factors for better vision improvement were better baseline vision [odds ratio (OR) =50.369, P=0.0041] and longer follow up duration (OR=1.144, P=0.0067). Independent predictive factors for better visual outcome of primary chronic RRD after SB are better baseline BCVA, shorter symptoms duration, shorter operative duration and longer follow up duration, while independent predictive factors for better vision improvement after operation are better baseline vision and longer follow up duration.

One-Dimensional Modelling of Internal Ballistics

NASA Astrophysics Data System (ADS)

Monreal-González, G.; Otón-Martínez, R. A.; Velasco, F. J. S.; García-Cascáles, J. R.; Ramírez-Fernández, F. J.

2017-10-01

A one-dimensional model is introduced in this paper for problems of internal ballistics involving solid propellant combustion. First, the work presents the physical approach and equations adopted. Closure relationships accounting for the physical phenomena taking place during combustion (interfacial friction, interfacial heat transfer, combustion) are deeply discussed. Secondly, the numerical method proposed is presented. Finally, numerical results provided by this code (UXGun) are compared with results of experimental tests and with the outcome from a well-known zero-dimensional code. The model provides successful results in firing tests of artillery guns, predicting with good accuracy the maximum pressure in the chamber and muzzle velocity what highlights its capabilities as prediction/design tool for internal ballistics.

Psychosocial safety climate, emotional demands, burnout, and depression: a longitudinal multilevel study in the Malaysian private sector.

PubMed

Idris, Mohd Awang; Dollard, Maureen F; Yulita

2014-07-01

This multilevel longitudinal study investigates a newly identified climate construct, psychosocial safety climate (PSC), as a precursor to job characteristics (e.g., emotional demands), and psychological outcomes (i.e., emotional exhaustion and depression). We argued that PSC, as an organizational climate construct, has cross-level effects on individually perceived job design and psychological outcomes. We hypothesized a mediation process between PSC and emotional exhaustion particularly through emotional demands. In sequence, we predicted that emotional exhaustion would predict depression. At Time 1, data were collected from employees in 36 Malaysian private sector organizations (80% responses rate), n = 253 (56%), and at Time 2 from 27 organizations (60%) and n = 117 (46%). Using hierarchical linear modeling (HLM), we found that there were cross-level effects of PSC Time 1 on emotional demands Time 2 and emotional exhaustion Time 2, but not on depression Time 2, across a 3-month time lag. We found evidence for a lagged mediated effect; emotional demands mediated the relationship between PSC and emotional exhaustion. Emotional exhaustion did not predict depression. Finally, our results suggest that PSC is an important organizational climate construct, and acts to reduce employee psychological problems in the workplace, via working conditions.

How radiologic/clinicopathologic features relate to compressive symptoms in benign thyroid disease.

PubMed

Siegel, Bianca; Ow, Thomas J; Abraham, Suzanne S; Loftus, Patricia A; Tassler, Andrew B; Smith, Richard V; Schiff, Bradley A

2017-04-01

To identify compressive symptomatology in a patient cohort with benign thyroid disease who underwent thyroidectomy. To determine radiographic/clinicopathologic features related to and predictive of a compressive outcome. Retrospective cohort study. Medical records of 232 patients with benign thyroid disease on fine needle aspiration who underwent thyroidectomy from 2009 to 2012 at an academic medical center were reviewed. Data collection and analyses involved subjects' demographics, compressive symptoms, preoperative airway encroachment, intubation complications, specimen weight, and final pathologic diagnosis. Subjects were ages 14 to 86 years (mean: 52.4 years). Ninety-six subjects (41.4%) reported compressive symptomatology of dysphagia (n =74; 32%), dyspnea (n = 39; 17%), and hoarseness (n = 24; 10%). Ninety-seven (42.2%) had preoperative airway encroachment. Dyspnea was significantly related to tracheal compression, tracheal deviation, and substernal extension. Dysphagia was related to tracheal compression and tracheal deviation. Compressive symptoms and preoperative airway encroachment were not related to intubation complications. Final pathologic diagnosis was not related to compressive symptoms, whereas specimen weight was significantly related to dyspnea and dysphagia. Final pathology revealed 74 subjects (32%) with malignant lesions. Malignant and benign nodular subject groups differed significantly in substernal extension, gland weight, tracheal deviation, and dyspnea. Logit modeling for dyspnea was significant for tracheal compression as a predictor for the likelihood of dyspnea. Dyspnea was closely related to preoperative airway encroachment and most indicative of a clinically relevant thyroid in our cohort with benign thyroid disease. Tracheal compression was found to have predictive value for the likelihood of a dyspneic outcome. 4. Laryngoscope, 127:993-997, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Prediction of insemination outcomes in Holstein dairy cattle using alternative machine learning algorithms.

PubMed

Shahinfar, Saleh; Page, David; Guenther, Jerry; Cabrera, Victor; Fricke, Paul; Weigel, Kent

2014-02-01

When making the decision about whether or not to breed a given cow, knowledge about the expected outcome would have an economic impact on profitability of the breeding program and net income of the farm. The outcome of each breeding can be affected by many management and physiological features that vary between farms and interact with each other. Hence, the ability of machine learning algorithms to accommodate complex relationships in the data and missing values for explanatory variables makes these algorithms well suited for investigation of reproduction performance in dairy cattle. The objective of this study was to develop a user-friendly and intuitive on-farm tool to help farmers make reproduction management decisions. Several different machine learning algorithms were applied to predict the insemination outcomes of individual cows based on phenotypic and genotypic data. Data from 26 dairy farms in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program were used, representing a 10-yr period from 2000 to 2010. Health, reproduction, and production data were extracted from on-farm dairy management software, and estimated breeding values were downloaded from the US Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory (Beltsville, MD) database. The edited data set consisted of 129,245 breeding records from primiparous Holstein cows and 195,128 breeding records from multiparous Holstein cows. Each data point in the final data set included 23 and 25 explanatory variables and 1 binary outcome for of 0.756 ± 0.005 and 0.736 ± 0.005 for primiparous and multiparous cows, respectively. The naïve Bayes algorithm, Bayesian network, and decision tree algorithms showed somewhat poorer classification performance. An information-based variable selection procedure identified herd average conception rate, incidence of ketosis, number of previous (failed) inseminations, days in milk at breeding, and mastitis as the most effective explanatory variables in predicting pregnancy outcome. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prognostic factors of arthroscopic pull-out repair for a posterior root tear of the medial meniscus.

PubMed

Moon, Hong-Kyo; Koh, Yong-Gon; Kim, Yong-Chan; Park, Young-Sik; Jo, Seung-Bae; Kwon, Sae-Kwang

2012-05-01

Repair of a posterior root tear of the medial meniscus (MRT) decreases peak contact pressure by restoring hoop tension and is expected to prevent progression to osteoarthritis. The purposes of this study were (1) to report the clinical and magnetic resonance imaging (MRI) results of arthroscopic pull-out repair of the MRT and (2) to identify prognostic factors of poor outcome. Case series; Level of evidence, 4. Fifty-one patients (47 women, 4 men) who underwent arthroscopic pull-out repair of the MRT by a single surgeon were enrolled. Mean follow-up after surgery was 33 months (range, 24-44 months). To identify factors affecting final outcome, patient-specific factors, such as gender, age, body mass index, meniscus extrusion, extrusion increase, subchondral edema, degree of varus alignment (<5° or >5°), and cartilage status in the medial compartment (Outerbridge grade 1 or 2 lesion vs grade 3 or 4 lesion), were investigated. Final clinical outcomes were determined using a visual analog scale (VAS) for pain and patient satisfaction scores, American Knee Society (AKS) scores, and Lysholm scores, and MRI outcomes were determined by evaluating meniscus extrusion and articular cartilage status. Multiple regression analysis was performed to identify variables that independently affected clinical and MRI-determined outcomes. All clinical outcome measures significantly improved after surgery. Patients with Outerbridge grade 3 or 4 chondral lesions had poorer results than those with grade 1 or 2 lesions in terms of AKS function and Lysholm scores. Patients with varus alignment of >5° had poorer results than those with varus alignment of <5° in terms of VAS satisfaction, AKS function, and Lysholm scores. Mean meniscus extrusion increased from 3.6 mm preoperatively to 5.0 mm postoperatively. Chondral lesions progressed in 3 (9.7%) of 31 patients. Preoperative meniscus extrusion was found to be positively correlated with final extrusion. At a mean follow-up of 33 months after pull-out repair, extrusion of the meniscus was found to have progressed. Nevertheless, this technique provided patients with a clinical benefit. Outerbridge grade 3 or 4 chondral lesions and varus alignment of >5° were found to independently predict an inferior clinical outcome.

Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team☆

PubMed Central

Harrison, David A.; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B.; Gwinnutt, Carl; Nolan, Jerry P.; Rowan, Kathryn M.

2014-01-01

Aim The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Methods Risk models for two outcomes—return of spontaneous circulation (ROSC) for greater than 20 min and survival to hospital discharge—were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. Results 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC > 20 min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC > 20 min (c index 0.81 versus 0.72). Conclusions Validated risk models for ROSC > 20 min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. PMID:24830872

Water Polo Game-Related Statistics in Women’s International Championships: Differences and Discriminatory Power

PubMed Central

Escalante, Yolanda; Saavedra, Jose M.; Tella, Victor; Mansilla, Mirella; García-Hermoso, Antonio; Dominguez, Ana M.

2012-01-01

The aims of this study were (i) to compare women’s water polo game-related statistics by match outcome (winning and losing teams) and phase (preliminary, classificatory, and semi-final/bronze medal/gold medal), and (ii) identify characteristics that discriminate performances for each phase. The game-related statistics of the 124 women’s matches played in five International Championships (World and European Championships) were analyzed. Differences between winning and losing teams in each phase were determined using the chi-squared. A discriminant analysis was then performed according to context in each of the three phases. It was found that the game-related statistics differentiate the winning from the losing teams in each phase of an international championship. The differentiating variables were both offensive (centre goals, power-play goals, counterattack goal, assists, offensive fouls, steals, blocked shots, and won sprints) and defensive (goalkeeper-blocked shots, goalkeeper-blocked inferiority shots, and goalkeeper-blocked 5-m shots). The discriminant analysis showed the game-related statistics to discriminate performance in all phases: preliminary, classificatory, and final phases (92%, 90%, and 83%, respectively). Two variables were discriminatory by match outcome (winning or losing teams) in all three phases: goals and goalkeeper-blocked shots. Key pointsThe preliminary phase that more than one variable was involved in this differentiation, including both offensive and defensive aspects of the game.The game-related statistics were found to have a high discriminatory power in predicting the result of matches with shots and goalkeeper-blocked shots being discriminatory variables in all three phases.Knowledge of the characteristics of women’s water polo game-related statistics of the winning teams and their power to predict match outcomes will allow coaches to take these characteristics into account when planning training and match preparation. PMID:24149356

Determinants of pediatric cataract program outcomes and follow-up in a large series in Mexico.

PubMed

Congdon, Nathan G; Ruiz, Sergio; Suzuki, Maki; Herrera, Veronica

2007-10-01

To report determinants of outcomes and follow-up in a large Mexican pediatric cataract project. Hospital Luis Sanchez Bulnes, Mexico City, Mexico. Data were collected prospectively from a pediatric cataract surgery program at the Hospital Luis Sanchez Bulnes, implemented by Helen Keller International. Preoperative data included age, sex, baseline visual acuity, type of cataract, laterality, and presence of conditions such as amblyopia. Surgical data included vitrectomy, capsulotomy, complications, and use of intraocular lenses (IOLs). Postoperative data included final visual acuity, refraction, number of follow-up visits, and program support for follow-up. Of 574 eyes of 415 children (mean age 7.1 years +/- 4.7 [SD]), IOLs were placed in 416 (87%). At least 1 follow-up was attended by 408 patients (98.3%) (mean total follow-up 3.5 +/- 1.8 months); 40% of eyes achieved a final visual acuity of 6/18 or better. Children living farther from the hospital had fewer postoperative visits (P = .04), while children receiving program support had more visits (P = .001). Factors predictive of better acuity included receiving an IOL during surgery (P = .04) and provision of postoperative spectacles (P = .001). Predictive of worse acuity were amblyopia (P = .003), postoperative complications (P = .0001), unilateral surgery (P = .0075), and female sex (P = .045). The results underscore the importance of surgical training in reducing complications, early intervention before amblyopia (observed in 40% of patients) can develop, and vigorous treatment if amblyopia is present. The positive impact of program support on follow-up is encouraging, although direct financial support may pose a problem for sustainability. More work is needed to understand reasons for worse outcomes in girls.

Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

PubMed

Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

2017-09-05

Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

A predictive mathematical model for the calculation of the final mass of Graves' disease thyroids treated with 131I

NASA Astrophysics Data System (ADS)

Traino, Antonio C.; Di Martino, Fabio; Grosso, Mariano; Monzani, Fabio; Dardano, Angela; Caraccio, Nadia; Mariani, Giuliano; Lazzeri, Mauro

2005-05-01

Substantial reductions in thyroid volume (up to 70-80%) after radioiodine therapy of Graves' hyperthyroidism are common and have been reported in the literature. A relationship between thyroid volume reduction and outcome of 131I therapy of Graves' disease has been reported by some authors. This important result could be used to decide individually the optimal radioiodine activity A0 (MBq) to administer to the patient, but a predictive model relating the change in gland volume to A0 is required. Recently, a mathematical model of thyroid mass reduction during the clearance phase (30-35 days) after 131I administration to patients with Graves' disease has been published and used as the basis for prescribing the therapeutic thyroid absorbed dose. It is well known that the thyroid volume reduction goes on until 1 year after therapy. In this paper, a mathematical model to predict the final mass of Graves' diseased thyroids submitted to 131I therapy is presented. This model represents a tentative explanation of what occurs macroscopically after the end of the clearance phase of radioiodine in the gland (the so-called second-order effects). It is shown that the final thyroid mass depends on its basal mass, on the radiation dose absorbed by the gland and on a constant value α typical of thyroid tissue. α has been evaluated based on a set of measurements made in 15 reference patients affected by Graves' disease and submitted to 131I therapy. A predictive equation for the calculation of the final mass of thyroid is presented. It is based on macroscopic parameters measurable after a diagnostic 131I capsule administration (0.37-1.85 MBq), before giving the therapy. The final mass calculated using this equation is compared to the final mass of thyroid measured 1 year after therapy administration in 22 Graves' diseased patients. The final masses calculated and measured 1 year after therapy are in fairly good agreement (R = 0.81). The possibility, for the physician, to decide a therapeutic activity based on the desired decrease of thyroid mass instead of on a fixed thyroid absorbed dose could be a new opportunity to cure Graves' disease.

A Self-determination Theory approach to the study of body image concerns, self-presentation and self-perceptions in a sample of aerobic instructors.

PubMed

Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos

2007-03-01

This study examined motivational predictors of body image concerns, self-presentation and self-perceptions using Self-determination Theory as a guiding framework. Aerobic instructors (N = 149) completed questionnaires measuring general need satisfaction, exercise motivational regulations, body image concerns, social physique anxiety and self-perceptions. Introjected regulation predicted all outcome variables in the expected direction. Intrinsic motivation positively predicted physical self-worth. Further, autonomy need satisfaction negatively predicted body image concerns. Finally, differences existed in need satisfaction, introjected regulation, self-perceptions and social physique anxiety between those at risk of developing eating disorders and those not at risk. The results underline the importance of overall and exercise-specific feelings of self-determination in dealing with body image concerns and low self-perceptions of aerobics instructors.

A Model to Predict Final Cost Growth in a Weapon System Development Program

DTIC Science & Technology

1975-08-01

Manual Calculation ..... .............. ... 117 11. Data and Results of 3 x 2 Manual Calculation .................... .. 119 12. Quarterly F-5E... manually calculated. The data and results are in Table 10. The computer program for these calculations is listed in Figure 12 with results in Figure...13. Table 10 Data and Results of 2 x 2 Manual Calculation Outcome Aspect Poor Acceptable 1 .5 .5 2 .3 .7 The total number of events possible are: (2)2

Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach

PubMed Central

Kang, Le; Chen, Weijie; Petrick, Nicholas A.; Gallas, Brandon D.

2014-01-01

The area under the receiver operating characteristic (ROC) curve (AUC) is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of AUC, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study. PMID:25399736

Leukoaraiosis predicts poor 90-day outcome after acute large cerebral artery occlusion.

PubMed

Henninger, Nils; Lin, Eugene; Baker, Stephen P; Wakhloo, Ajay K; Takhtani, Deepak; Moonis, Majaz

2012-01-01

To date limited information regarding outcome-modifying factors in patients with acute intracranial large artery occlusion (ILAO) in the anterior circulation is available. Leukoaraiosis (LA) is a common finding among patients with ischemic stroke and has been associated with poor post-stroke outcomes but its association with ILAO remains poorly characterized. This study sought to clarify the contribution of baseline LA and other common risk factors to 90-day outcome (modified Rankin Scale, mRS) after stroke due to acute anterior circulation ILAO. We retrospectively analyzed 1,153 consecutive patients with imaging-confirmed ischemic stroke during a 4-year period (2007-2010) at a single academic institution. The final study cohort included 87 patients with acute ILAO subjected to multimodal CT imaging within 24 h of symptom onset. LA severity was assessed using the van Swieten scale on non-contrast CT. Leptomeningeal collaterals were graded using CT angiogram source images. Hemorrhagic transformation (HT) was determined on follow-up CT. Multivariate logistic regression controlling for HT, treatment modality, demographic, as well as baseline clinical and imaging characteristics was used to identify independent predictors of a poor outcome (90-day mRS >2). The median National Institutes of Health Stroke Scale (NIHSS) at baseline was 15 (interquartile range 9-21). Twenty-four percent of the studied patients had severe LA. They were more likely to have hypertension (p = 0.028), coronary artery disease (p = 0.015), poor collaterals (p < 0.001), higher baseline NIHSS (p = 0.003), higher mRS at 90 days (p < 0.001), and were older (p = 0.002). Patients with severe LA had a uniformly poor outcome (p < 0.001) irrespective of treatment modality. Poor outcome was independently associated with higher baseline NIHSS (p < 0.001), worse LA (graded and dichotomized, p < 0.001), reduced leptomeningeal collaterals (graded and dichotomized, p < 0.001), presence of HT (p < 0.001), presence of parenchymal hemorrhages (p = 0.01), baseline mRS (p = 0.002), and older age (p = 0.043). The association between severe LA (p = 0.0056; OR 13.86; 95% CI 1.94-∞) and baseline NIHSS (p = 0.0001; OR 5.11; 95% CI 2.07-14.49 for each 10-point increase) with poor outcome maintained after adjustment for confounders in the final regression model. In this model, there was no significant association between presence of HT and poor outcome (p = 0.0572). Coexisting LA may predict poor functional outcome in patients with acute anterior circulation ILAO independent of other known important outcome predictors such as comorbid state, admission functional deficit, collateral status, hemorrhagic conversion, and treatment modality. Copyright © 2012 S. Karger AG, Basel.

Biomarker-Based Risk Model to Predict Cardiovascular Mortality in Patients With Stable Coronary Disease.

PubMed

Lindholm, Daniel; Lindbäck, Johan; Armstrong, Paul W; Budaj, Andrzej; Cannon, Christopher P; Granger, Christopher B; Hagström, Emil; Held, Claes; Koenig, Wolfgang; Östlund, Ollie; Stewart, Ralph A H; Soffer, Joseph; White, Harvey D; de Winter, Robbert J; Steg, Philippe Gabriel; Siegbahn, Agneta; Kleber, Marcus E; Dressel, Alexander; Grammer, Tanja B; März, Winfried; Wallentin, Lars

2017-08-15

Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This "ABC-CHD" model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts. This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial [STABILITY]; NCT00799903). Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Long-term visual outcomes in extremely low-birth-weight children (an American Ophthalmological Society thesis).

PubMed

Spencer, Rand

2006-01-01

The goal is to analyze the long-term visual outcome of extremely low-birth-weight children. This is a retrospective analysis of eyes of extremely low-birth-weight children on whom vision testing was performed. Visual outcomes were studied by analyzing acuity outcomes at >/=36 months of adjusted age, correlating early acuity testing with final visual outcome and evaluating adverse risk factors for vision. Data from 278 eyes are included. Mean birth weight was 731g, and mean gestational age at birth was 26 weeks. 248 eyes had grating acuity outcomes measured at 73 +/- 36 months, and 183 eyes had recognition acuity testing at 76 +/- 39 months. 54% had below normal grating acuities, and 66% had below normal recognition acuities. 27% of grating outcomes and 17% of recognition outcomes were /=3 years of age. A slower-than-normal rate of early visual development was predictive of abnormal grating acuity (P < .0001) and abnormal recognition acuity (P < .0001) at >/=3 years of age. Eyes diagnosed with maximal retinopathy of prematurity in zone I had lower acuity outcomes (P = .0002) than did those with maximal retinopathy of prematurity in zone II/III. Eyes of children born at 28 weeks gestational age. Eyes of children with poorer general health after premature birth had a 5.3 times greater risk of abnormal recognition acuity. Long-term visual development in extremely low-birth-weight infants is problematic and associated with a high risk of subnormal acuity. Early acuity testing is useful in identifying children at greatest risk for long-term visual abnormalities. Gestational age at birth of

A Simple Model Predicting Individual Weight Change in Humans

PubMed Central

Thomas, Diana M.; Martin, Corby K.; Heymsfield, Steven; Redman, Leanne M.; Schoeller, Dale A.; Levine, James A.

2010-01-01

Excessive weight in adults is a national concern with over 2/3 of the US population deemed overweight. Because being overweight has been correlated to numerous diseases such as heart disease and type 2 diabetes, there is a need to understand mechanisms and predict outcomes of weight change and weight maintenance. A simple mathematical model that accurately predicts individual weight change offers opportunities to understand how individuals lose and gain weight and can be used to foster patient adherence to diets in clinical settings. For this purpose, we developed a one dimensional differential equation model of weight change based on the energy balance equation is paired to an algebraic relationship between fat free mass and fat mass derived from a large nationally representative sample of recently released data collected by the Centers for Disease Control. We validate the model's ability to predict individual participants’ weight change by comparing model estimates of final weight data from two recent underfeeding studies and one overfeeding study. Mean absolute error and standard deviation between model predictions and observed measurements of final weights are less than 1.8 ± 1.3 kg for the underfeeding studies and 2.5 ± 1.6 kg for the overfeeding study. Comparison of the model predictions to other one dimensional models of weight change shows improvement in mean absolute error, standard deviation of mean absolute error, and group mean predictions. The maximum absolute individual error decreased by approximately 60% substantiating reliability in individual weight change predictions. The model provides a viable method for estimating individual weight change as a result of changes in intake and determining individual dietary adherence during weight change studies. PMID:24707319

Quantitative characterization of the progression of focal brain ischemia in a rat photochemical stroke model using in-vivo MRI

NASA Astrophysics Data System (ADS)

Van der Linden, Anne-Marie; Verhoye, Marleen; De Ryck, M.

2000-04-01

Stroke models, if used in drug evaluation studies, should have a predictable and reproducible course and outcome. While most drug trials focus on the lesion outcome, our study shows the importance of studying lesion growth instead of lesion outcome. In the study reported here, the time course of a photochemically induced neocortical infarct is studied in rats, using diffusion-weighted magnetic resonance imaging, while the rats were submitted to a rigorous control of physiological parameters, ensuring constant body temperature, blood gases (pO2 and pCO2), arterial pressure, heart rate and plasma glucose levels. Under such a stable physiological condition, rats were imaged as soon as possible after lesion up to 6 hours, which is the most important period to determine the slope of further lesion growth and final outcome. The data show that the initial size of the lesion is important for the further outcome of the stroke, both in lesion size and severity of the ischemic damage, as reflected by changes in the Apparent Diffusion Coefficient.

Child Abuse and Neglect, MAOA, and Mental Health Outcomes: A Prospective Examination

PubMed Central

Widom, Cathy Spatz; Brzustowicz, Linda M.

2012-01-01

Background Studies have examined the interaction of MAOA genotype with childhood maltreatment in relation to depressive symptomatology and alcohol abuse with conflicting findings. Both high and low activity allele combinations have been shown to be protective for maltreated children with direction of findings varying by study methodology and participant’s sex. Methods Participants in a prospective cohort design study involving court substantiated cases of child abuse and neglect and a matched comparison group were followed up into adulthood and interviewed (N = 802). Eighty-two percent consented to provide blood, 631 gave permission for DNA extraction and analyses, and 575 were included in the final sample. This sample included male, female, White, and Non-White (primarily Black) participants. Symptoms of dysthymia, major depression and alcohol abuse were assessed using the NIMH Diagnostic Interview Schedule-III-R. Results Significant three-way interactions, MAOA genotype by abuse by sex, predicted dysthymic symptoms. Low-activity MAOA genotype buffered against symptoms of dysthymia in physically abused and multiply maltreated women. Significant three-way interactions, MAOA genotype by sexual abuse by race, predicted all outcomes. Low-activity MAOA genotype buffered against symptoms of dysthymia, major depressive disorder and alcohol abuse for sexually abused White participants. The high-activity genotype was protective in the Non-White sexually abused group. Conclusions This prospective study provides evidence that MAOA interacts with child maltreatment to predict mental health outcomes. Reasons for sex differences and race findings are discussed. PMID:22030358

Attachment, Sexual Assertiveness, and Sexual Outcomes in Women with Provoked Vestibulodynia and Their Partners: A Mediation Model.

PubMed

Leclerc, Bianca; Bergeron, Sophie; Brassard, Audrey; Bélanger, Claude; Steben, Marc; Lambert, Bernard

2015-08-01

Provoked vestibulodynia (PVD) is a prevalent women's sexual pain disorder, which is associated with sexual function difficulties. Attachment theory has been used to understand adult sexual outcomes, providing a useful framework for examining sexual adaptation in couples confronted with PVD. Research to date indicates that anxious and avoidant attachment dimensions correlate with worse sexual outcomes in community and clinical samples. The present study examined the association between attachment, pain, sexual function, and sexual satisfaction in a sample of 101 couples in which the women presented with PVD. The actor-partner interdependence model was used in order to investigate both actor and partner effects. This study also examined the role of sexual assertiveness as a mediator of these associations via structural equation modeling. Women completed measures of pain intensity and both members of the couple completed measures of romantic attachment, sexual assertiveness, sexual function, and satisfaction. Results indicated that attachment dimensions did not predict pain intensity. Both anxious and avoidant attachment were associated with lower sexual satisfaction. Only attachment avoidance predicted lower sexual function in women. Partner effects indicated that higher sexual assertiveness in women predicted higher sexual satisfaction in men. Finally, women's sexual assertiveness was found to be a significant mediator of the relationship between their attachment dimensions, sexual function, and satisfaction. Findings highlight the importance of examining how anxious and avoidant attachment may lead to difficulties in sexual assertiveness and to less satisfying sexual interactions in couples where women suffer from PVD.

Universal school-based substance abuse prevention programs: Modeling targeted mediators and outcomes for adolescent cigarette, alcohol and marijuana use.

PubMed

Stephens, Peggy C; Sloboda, Zili; Stephens, Richard C; Teasdale, Brent; Grey, Scott F; Hawthorne, Richard D; Williams, Joseph

2009-06-01

We examined the relationships among targeted constructs of social influences and competence enhancement prevention curricula and cigarette, alcohol and marijuana use outcomes in a diverse sample of high school students. We tested the causal relationships of normative beliefs, perceptions of harm, attitudes toward use of these substances and refusal, communication, and decision-making skills predicting the self-reported use of each substance. In addition, we modeled the meditation of these constructs through the intentions to use each substance and tested the moderating effects of the skills variables on the relationships between intentions to use and self-reported use of each of these substances. Logistic regression path models were constructed for each of the drug use outcomes. Models were run using the Mplus 5.0 statistical application using the complex sample function to control for the sampling design of students nested within schools; full information maximum likelihood estimates (FIML) were utilized to address missing data. Relationships among targeted constructs and outcomes differed for each of the drugs with communication skills having a potentially iatrogenic effect on alcohol use. Program targets were mediated through the intentions to use these substances. Finally, we found evidence of a moderating effect of decision-making skills on perceptions of harm and attitudes toward use, depending upon the outcome. Prevention curricula may need to target specific drugs. In addition to normative beliefs, perceptions of harm, and refusal and decision-making skills, programs should directly target constructs proximal to behavioral outcomes such as attitudes and intentions. Finally, more research on the effects of communication skills on adolescent substance use should be examined.

Clinical experience with arthroscopically-assisted repair of peripheral triangular fibrocartilage complex tears in adolescents--technique and results.

PubMed

Farr, Sebastian; Zechmann, Ulrike; Ganger, Rudolf; Girsch, Werner

2015-08-01

The purpose of this study was to report our preliminary results after arthroscopically-assisted repair of peripheral triangular fibrocartilage complex (TFCC) tears in adolescent patients. All children and adolescents who underwent arthroscopically-assisted repair of a Palmer 1B tear were identified and prospectively evaluated after a mean follow-up of 1.3 years. The postoperative assessment included documentation of clinical parameters, pain score (visual analogue scale, VAS), grip strength and completion of validated outcome scores (Modified Mayo Wrist Score, MMWS; Disabilities of the Arm, Shoulder and Hand Inventory, DASH). A total of 12 patients (four males, eight females) with a mean age of 16.3 years at the time of surgery were evaluated. The mean VAS decreased significantly from 7.0 to 1.7 after the procedure. We observed a significant increase of the MMWS after surgery; however, MMWS was still significantly lower at final follow-up when compared to the contralateral side. A mean postoperative DASH score of 16 indicated an excellent outcome after the procedure. DASH Sports and Work Modules showed fair and good overall outcomes in the short-term, respectively. Grip strength averaged 86 % of the contralateral side at final follow-up, with no significant difference being found between both sides. Arthroscopically-assisted repair of peripheral TFCC tears in adolescents provided predictable pain relief and markedly improved functional outcome scores. Concomitant pathologies may have to be addressed at the same time to eventually achieve a satisfactory outcome. Sports participation, however, may be compromised in the short-term and should therefore be resumed six months postoperatively.

Weak Measurement and Quantum Smoothing of a Superconducting Qubit

NASA Astrophysics Data System (ADS)

Tan, Dian

In quantum mechanics, the measurement outcome of an observable in a quantum system is intrinsically random, yielding a probability distribution. The state of the quantum system can be described by a density matrix rho(t), which depends on the information accumulated until time t, and represents our knowledge about the system. The density matrix rho(t) gives probabilities for the outcomes of measurements at time t. Further probing of the quantum system allows us to refine our prediction in hindsight. In this thesis, we experimentally examine a quantum smoothing theory in a superconducting qubit by introducing an auxiliary matrix E(t) which is conditioned on information obtained from time t to a final time T. With the complete information before and after time t, the pair of matrices [rho(t), E(t)] can be used to make smoothed predictions for the measurement outcome at time t. We apply the quantum smoothing theory in the case of continuous weak measurement unveiling the retrodicted quantum trajectories and weak values. In the case of strong projective measurement, while the density matrix rho(t) with only diagonal elements in a given basis |n〉 may be treated as a classical mixture, we demonstrate a failure of this classical mixture description in determining the smoothed probabilities for the measurement outcome at time t with both diagonal rho(t) and diagonal E(t). We study the correlations between quantum states and weak measurement signals and examine aspects of the time symmetry of continuous quantum measurement. We also extend our study of quantum smoothing theory to the case of resonance fluorescence of a superconducting qubit with homodyne measurement and observe some interesting effects such as the modification of the excited state probabilities, weak values, and evolution of the predicted and retrodicted trajectories.

How do somatosensory deficits in the arm and hand relate to upper limb impairment, activity, and participation problems after stroke? A systematic review.

PubMed

Meyer, Sarah; Karttunen, Auli H; Thijs, Vincent; Feys, Hilde; Verheyden, Geert

2014-09-01

The association between somatosensory impairments and outcome after stroke remains unclear. The aim of this study was to systematically review the available literature on the relationship between somatosensory impairments in the upper limb and outcome after stroke. The electronic databases PubMed, CINAHL, EMBASE, Cochrane Library, PsycINFO, and Web of Science were systematically searched from inception until July 2013. Studies were included if adult patients with stroke (minimum n=10) were examined with reliable and valid measures of somatosensation in the upper limb to investigate the relationship with upper limb impairment, activity, and participation measures. Exclusion criteria included measures of somatosensation involving an overall score for upper and lower limb outcome and articles including only lower limb outcomes. Eligibility assessment, data extraction, and quality evaluation were completed by 2 independent reviewers. A cutoff score of ≥65% of the maximal quality score was used for further inclusion in this review. Six articles met all inclusion criteria. Two-point discrimination was shown to be predictive for upper limb dexterity, and somatosensory evoked potentials were shown to have predictive value in upper limb motor recovery. Proprioception was significantly correlated with perceived level of physical activity and social isolation and had some predictive value in functional movements of the upper limb. Finally, the combination of light touch and proprioception impairment was shown to be significantly related to upper limb motor recovery as well as handicap situations during activities of daily living. Heterogeneity of the included studies warrants caution when interpreting results. Large variation in results was found due to heterogeneity of the studies. However, somatosensory deficits were shown to have an important role in upper limb motor and functional performance after stroke. © 2014 American Physical Therapy Association.

Esophagogastric junction distensibility measurements during Heller myotomy and POEM for achalasia predict postoperative symptomatic outcomes

PubMed Central

Teitelbaum, Ezra N.; Soper, Nathaniel J.; Pandolfino, John E.; Kahrilas, Peter J.; Hirano, Ikuo; Boris, Lubomyr; Nicodème, Frédéric; Lin, Zhiyue; Hungness, Eric S.

2015-01-01

Background The functional lumen imaging probe (FLIP) is a novel diagnostic tool that can be used to measure esophagogastric junction (EGJ) distensibility. In this study we performed intraoperative FLIP measurements during laparoscopic Heller myotomy (LHM) and peroral esophageal myotomy (POEM) for treatment of achalasia and evaluated the relationship between EGJ distensibility and postoperative symptoms. Methods Distensibility index (DI) (defined as the minimum cross-sectional area at the EGJ divided by distensive pressure) was measured with FLIP at two time points during LHM and POEM: 1) at baseline after induction of anesthesia, and 2) after operation completion. Results Measurements were performed in 20 patients undergoing LHM and 36 undergoing POEM. Both operations resulted in an increase in DI, although this increase was larger with POEM (7±3.1 vs. 5.1±3.4mm2/mmHg, p<.05). The two patients (both LHM) with the smallest increases in DI (1 and 1.6mm2/mmHg) both had persistent symptoms postoperatively and, overall, LHM patients with larger increases in DI had lower postoperative Eckardt scores. In the POEM group, there was no correlation between change in DI and symptoms; however, all POEM patients experienced an increase in DI of >3mm2/mmHg. When all patients were divided into thirds based on final DI, none in the lowest DI group (<6mm2/mmHg) had symptoms suggestive of reflux (i.e., GerdQ score >7), as compared with 20% in the middle third (6–9mm2/mmHg) and 36% in the highest third (>9mm2/mmHg). Patients within an “ideal” final DI range (4.5–8.5 mm2/mmHg) had optimal symptomatic outcomes (i.e. Eckardt≤1 and GerdQ≤7) in 88% of cases, compared with 47% in those with a final DI above or below that range (p<.05). Conclusions Intraoperative EGJ distensibility measurements with FLIP were predictive of postoperative symptomatic outcomes. These results provide initial evidence that FLIP has the potential to act as a useful calibration tool during operations for achalasia. PMID:25055891

Reconceptualising the external validity of discrete choice experiments.

PubMed

Lancsar, Emily; Swait, Joffre

2014-10-01

External validity is a crucial but under-researched topic when considering using discrete choice experiment (DCE) results to inform decision making in clinical, commercial or policy contexts. We present the theory and tests traditionally used to explore external validity that focus on a comparison of final outcomes and review how this traditional definition has been empirically tested in health economics and other sectors (such as transport, environment and marketing) in which DCE methods are applied. While an important component, we argue that the investigation of external validity should be much broader than a comparison of final outcomes. In doing so, we introduce a new and more comprehensive conceptualisation of external validity, closely linked to process validity, that moves us from the simple characterisation of a model as being or not being externally valid on the basis of predictive performance, to the concept that external validity should be an objective pursued from the initial conceptualisation and design of any DCE. We discuss how such a broader definition of external validity can be fruitfully used and suggest innovative ways in which it can be explored in practice.

Printability of calcium phosphate powders for three-dimensional printing of tissue engineering scaffolds.

PubMed

Butscher, Andre; Bohner, Marc; Roth, Christian; Ernstberger, Annika; Heuberger, Roman; Doebelin, Nicola; von Rohr, Philipp Rudolf; Müller, Ralph

2012-01-01

Three-dimensional printing (3DP) is a versatile method to produce scaffolds for tissue engineering. In 3DP the solid is created by the reaction of a liquid selectively sprayed onto a powder bed. Despite the importance of the powder properties, there has to date been a relatively poor understanding of the relation between the powder properties and the printing outcome. This article aims at improving this understanding by looking at the link between key powder parameters (particle size, flowability, roughness, wettability) and printing accuracy. These powder parameters are determined as key factors with a predictive value for the final 3DP outcome. Promising results can be expected for mean particle size in the range of 20-35 μm, compaction rate in the range of 1.3-1.4, flowability in the range of 5-7 and powder bed surface roughness of 10-25 μm. Finally, possible steps and strategies in pushing the physical limits concerning improved quality in 3DP are addressed and discussed. Copyright © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

How to tell a happy from an unhappy schizotype: personality factors and mental health outcomes in individuals with psychotic experiences.

PubMed

Alminhana, Letícia O; Farias, Miguel; Claridge, Gordon; Cloninger, Claude R; Moreira-Almeida, Alexander

2017-01-01

It is unclear why some individuals reporting psychotic experiences have balanced lives while others go on to develop mental health problems. The objective of this study was to test if the personality traits of harm avoidance, self-directedness, and self-transcendence can be used as criteria to differentiate healthy from unhealthy schizotypal individuals. We interviewed 115 participants who reported a high frequency of psychotic experiences. The instruments used were the Temperament and Character Inventory (140), Structured Clinical Interview for DSM-IV, and the Oxford-Liverpool Inventory of Feelings and Experiences. Harm avoidance predicted cognitive disorganization (β = 0.319; t = 2.94), while novelty seeking predicted bipolar disorder (β = 0.136, Exp [β] = 1.146) and impulsive non-conformity (β = 0.322; t = 3.55). Self-directedness predicted an overall decrease in schizotypy, most of all in cognitive disorganization (β = -0.356; t = -2.95) and in impulsive non-conformity (β = -0.313; t = -2.83). Finally, self-transcendence predicted unusual experiences (β = 0.256; t = 2.32). Personality features are important criteria to distinguish between pathology and mental health in individuals presenting high levels of anomalous experiences (AEs). While self-directedness is a protective factor, both harm avoidance and novelty seeking were predictors of negative mental health outcomes. We suggest that the impact of AEs on mental health is moderated by personality factors.

Ex Vivo Perfusion Characteristics of Donation After Cardiac Death Kidneys Predict Long-Term Graft Survival.

PubMed

Sevinc, M; Stamp, S; Ling, J; Carter, N; Talbot, D; Sheerin, N

2016-12-01

Ex vivo perfusion is used in our unit for kidneys donated after cardiac death (DCD). Perfusion flow index (PFI), resistance, and perfusate glutathione S-transferase (GST) can be measured to assess graft viability. We assessed whether measurements taken during perfusion could predict long-term outcome after transplantation. All DCD kidney transplants performed from 2002 to 2014 were included in this study. The exclusion criteria were: incomplete data, kidneys not machine perfused, kidneys perfused in continuous mode, and dual transplantation. There were 155 kidney transplantations included in the final analysis. Demographic data, ischemia times, donor hypertension, graft function, survival and machine perfusion parameters after 3 hours were analyzed. Each perfusion parameter was divided into 3 groups as high, medium, and low. Estimated glomerular filtration rate was calculated at 12 months and then yearly after transplantation. There was a significant association between graft survival and PFI and GST (P values, .020 and .022, respectively). PFI was the only independent parameter to predict graft survival. A low PFI during ex vivo hypothermic perfusion is associated with inferior graft survival after DCD kidney transplantation. We propose that PFI is a measure of the health of the graft vasculature and that a low PFI indicates vascular disease and therefore predicts a worse long-term outcome. Copyright © 2016 Elsevier Inc. All rights reserved.

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions.

PubMed

White, B J; Amrine, D E; Larson, R L

2018-04-14

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive decisions in livestock production, health, and welfare. The predictive analytic process involves selecting a target variable, managing the data, partitioning the data, then creating algorithms, refining algorithms, and finally comparing accuracy of the created classifiers. The partitioning of the datasets allows model building and refining to occur prior to testing the predictive accuracy of the model with naive data to evaluate overall accuracy. Many different classification algorithms are available for predictive use and testing multiple algorithms can lead to optimal results. Application of a systematic process for predictive analytics using data that is currently collected or that could be collected on livestock operations will facilitate precision animal management through enhanced livestock operational decisions.

[Evolution of psychopathological alterations in patients with morbid obesity after bariatric surgery].

PubMed

Sánchez Zaldívar, Silvia; Arias Horcajadas, Francisco; Gorgojo Martínez, Juan José; Sánchez Romero, Sergio

2009-07-11

The aims of this study were to know the prevalence of the psychopathological alterations among patients with morbid obesity (MO) candidates for bariatric surgery in our centre, to analyze its predictive value on the surgical outcome and to study the evolution after weight stabilization was achieved. One hundred and forty five patients of the University Hospital Foundation Alcorcón (122 women) candidates for bariatric surgery (108 finally operated) were included in the study. A clinical interview was carried and several scales of psychopathology were applied before and after surgery: Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Maudsley Obsessive-compulsive Interview (MOCI), Barrat Impulsiveness Scale (BIS), Eating Disorder Inventory (EDI), Eating Attitudes Test (EAT), Bulimic Investigation Test Edinburg (BITE), and Body Shape Questionnaire (BSQ). A comparison of means between the initial and final scores of the psychometric tests and a logistic regression analysis to identify the predictive variables of positive evolution after surgery (defined as percentage of lost overweight> 50% and final IMC <35) were performed. An improvement in the scores of BDI, BAI and in the subscales of EDI, Impulse to the thinness (EDI-DT) and corporal Dissatisfaction (EDI-BD) was observed. The differences were not significant for the rest of the psychometric tests. The multivariate analysis identified 3 predictive factors for postsurgical evolution: BDI (OR 0.91, IC95% 0.82-1.02), BIS (OR 1.08, IC 95% 1.0-1.16) y EDI-DT (OR 1.18, IC 95% 1.0-1.39). In our study, the scales of depression, anxiety, impulse to thinness and corporal dissatisfaction improved in patients with MO after bariatric surgery. Some baseline psychometric variables may predict a favourable postsurgical evolution of these patients.

External validation of the DRAGON score in an elderly Spanish population: prediction of stroke prognosis after IV thrombolysis.

PubMed

Giralt-Steinhauer, Eva; Rodríguez-Campello, Ana; Cuadrado-Godia, Elisa; Ois, Ángel; Jiménez-Conde, Jordi; Soriano-Tárraga, Carolina; Roquer, Jaume

2013-01-01

Intravenous (i.v.) thrombolysis within 4.5 h of symptom onset has proven efficacy in acute ischemic stroke treatment, although half of all outcomes are unfavorable. The recently published DRAGON score aims to predict the 3-month outcome in stroke patients who have received i.v. alteplase. The purpose of this study was an external validation of the results of the DRAGON score in a Spanish cohort. Patients with acute stroke treated with alteplase were prospectively registered in our BasicMar database. We collected demographic characteristics, vascular risk factors, the time from stroke onset to treatment, baseline serum glucose levels and stroke severity for this population. We then reviewed hyperdense cerebral artery signs and signs of early infarct on the admission CT scan. We calculated the DRAGON score and used the developers' 3-month prognosis categories: good [modified Rankin Scale score (mRS) 0-2], poor (mRS 3-6) and miserable (mRS 5-6) outcome. Discrimination was tested using the area under the receiver operator curve (AUC-ROC). Calibration was assessed by the Hosmer-Lemeshow test. Our final cohort of 297 patients was older (median age 74 years, IQR 65-80) and had more risk factors and severe strokes [median National Institutes of Health Stroke Scale (NIHSS) points 13, IQR 7-19] than the original study population. Poor prognosis was observed in 143 (48.1%) patients. Higher DRAGON scores were associated with a higher risk of poor prognosis. None of our treated stroke patients with a DRAGON score ≥8 at admission experienced a favorable outcome after 3 months. All DRAGON variables were significantly associated with a worse outcome in the multivariate analysis except for onset-to-treatment time (p = 0.334). Discrimination to predict poor prognosis was very good (AUC-ROC 0.84) and the score had good Hosmer-Lemeshow calibration (p = 0.84). The DRAGON score is easy to perform and offers a rapid, reliable prediction of poor prognosis in acute-stroke patients treated with alteplase. This study replicates the original results in a different population. Copyright © 2013 S. Karger AG, Basel.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder

PubMed Central

Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant’s treatment outcome may help during antidepressant’s selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant’s treatment outcome for the MDD patients. PMID:28152063

Predicting Relapse in Patients With Medulloblastoma by Integrating Evidence From Clinical and Genomic Features

PubMed Central

Tamayo, Pablo; Cho, Yoon-Jae; Tsherniak, Aviad; Greulich, Heidi; Ambrogio, Lauren; Schouten-van Meeteren, Netteke; Zhou, Tianni; Buxton, Allen; Kool, Marcel; Meyerson, Matthew; Pomeroy, Scott L.; Mesirov, Jill P.

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 accuracy of treatment outcome prediction. Here, we show how integration of high-level clinical and genomic features or risk factors, including disease subtype, can yield more comprehensive, accurate, and biologically interpretable prediction models for relapse versus no-relapse classification. We also introduce a novel Bayesian nomogram indicating the amount of evidence that each feature contributes on a patient-by-patient basis. Patients and Methods A Bayesian cumulative log-odds model of outcome was developed from a training cohort of 96 children treated for medulloblastoma, starting with the evidence provided by clinical features of metastasis and histology (model A) and incrementally adding the evidence from gene-expression–derived features representing disease subtype–independent (model B) and disease subtype–dependent (model C) pathways, and finally high-level copy-number genomic abnormalities (model D). The models were validated on an independent test cohort (n = 78). Results On an independent multi-institutional test data set, models A to D attain an area under receiver operating characteristic (au-ROC) curve of 0.73 (95% CI, 0.60 to 0.84), 0.75 (95% CI, 0.64 to 0.86), 0.80 (95% CI, 0.70 to 0.90), and 0.78 (95% CI, 0.68 to 0.88), respectively, for predicting relapse versus no relapse. Conclusion The proposed models C and D outperform the current clinical classification schema (au-ROC, 0.68), our previously published eight-gene outcome signature (au-ROC, 0.71), and several new schemas recently proposed in the literature for medulloblastoma risk stratification. PMID:21357789

Psychosocial well-being and health-related quality of life in a UK population with Usher syndrome

PubMed Central

Dean, Gavin; Orford, Amy; Staines, Roy; McGee, Anna; Smith, Kimberley J

2017-01-01

Objectives To determine whether psychosocial well-being is associated with the health-related quality of life (HRQOL) of people with Usher syndrome. Setting The survey was advertised online and through deafblind-related charities, support groups and social groups throughout the UK. Participants 90 people with Usher syndrome took part in the survey. Inclusion criteria are having a diagnosis of Usher syndrome, being 18 or older and being a UK resident. Primary and secondary outcome measures All participants took part in a survey that measured depressive symptoms, loneliness and social support (predictors) and their physical and mental HRQOL (outcomes). Measured confounders included age-related, sex-related and health-related characteristics. Hierarchical multiple linear regression analyses examined the association of each psychosocial well-being predictor with the physical and mental HRQOL outcomes while controlling for confounders in a stepwise manner. Results After adjusting for all confounders, psychosocial well-being was shown to predict physical and mental HRQOL in our population with Usher syndrome. Increasing depressive symptoms were predictive of poorer physical (β=−0.36, p<0.01) and mental (β=−0.60, p<0.001) HRQOL. Higher levels of loneliness predicted poorer mental HRQOL (β=−0.20, p<0.05). Finally, increasing levels of social support predicted better mental HRQOL (β=0.19, p<0.05). Conclusions Depression, loneliness and social support all represent important issues that are linked with HRQOL in a UK population with Usher syndrome. Our results add to the growing body of evidence that psychosocial well-being is an important factor to consider in people with Usher syndrome alongside functional and physical impairment within research and clinical practice. PMID:28082366

Test selection, adaptation, and evaluation: a systematic approach to assess nutritional influences on child development in developing countries.

PubMed

Prado, Elizabeth L; Hartini, Sri; Rahmawati, Atik; Ismayani, Elfa; Hidayati, Astri; Hikmah, Nurul; Muadz, Husni; Apriatni, Mandri S; Ullman, Michael T; Shankar, Anuraj H; Alcock, Katherine J

2010-03-01

Evaluating the impact of nutrition interventions on developmental outcomes in developing countries can be challenging since most assessment tests have been produced in and for developed country settings. Such tests may not be valid measures of children's abilities when used in a new context. We present several principles for the selection, adaptation, and evaluation of tests assessing the developmental outcomes of nutrition interventions in developing countries where standard assessment tests do not exist. We then report the application of these principles for a nutrition trial on the Indonesian island of Lombok. Three hundred children age 22-55 months in Lombok participated in a series of pilot tests for the purpose of test adaptation and evaluation. Four hundred and eighty-seven 42-month-old children in Lombok were tested on the finalized test battery. The developmental assessment tests were adapted to the local context and evaluated for a number of psychometric properties, including convergent and discriminant validity, which were measured based on multiple regression models with maternal education, depression, and age predicting each test score. The adapted tests demonstrated satisfactory psychometric properties and the expected pattern of relationships with the three maternal variables. Maternal education significantly predicted all scores but one, maternal depression predicted socio-emotional competence, socio-emotional problems, and vocabulary, while maternal age predicted socio-emotional competence only. Following the methodological principles we present resulted in tests that were appropriate for children in Lombok and informative for evaluating the developmental outcomes of nutritional supplementation in the research context. Following this approach in future studies will help to determine which interventions most effectively improve child development in developing countries.

Erythropoietin in Predicting Prognosis in Patients with Acute-on-Chronic Liver Failure.

PubMed

Alempijevic, Tamara; Zec, Simon; Nikolic, Vladimir; Veljkovic, Aleksandar; Milivojevic, Vladimir; Dopsaj, Violeta; Stankovic, Sanja; Milosavljevic, Tomica

2016-12-01

Acute-on-chronic liver failure (ACLF) is characterized by a rapid progression to multiple organ failure and is associated with a very high mortality rate of 50-90%. Novel therapies are being investigated such as Erythropoietin (EPO). The aim of this prospective cohort study was to analyse the value of EPO in predicting prognosis and determine which patients may benefit most from EPO therapy. According to the EASL-CLIF criteria, 104 consecutive patients were diagnosed with ACLF, and separated into two groups based on the type of insult: bleeding (Group A=31) or non-bleeding (Group B=73). In addition to a complete biochemical work-up and calculation of relevant prognostic scores, levels of EPO were measured on admission and correlated to the type of insult and final outcome. Fifteen patients from Group A (mean age 60.32+/-9.29 years) had a lethal outcome and higher values of EPO on admission (319.26+/-326.58 mIU/ml) (p<0.005), compared to the 37 patients from Group B (mean age 59.9+/-10.19 years) with EPO levels at admission of 29.88+/-34.6 mIU/mL. In Group B, a cut-off EPO value of 30.65 mIU/mL had a sensitivity of 87.5% and a specificity 57.4% in predicting lethal outcome with an AUROC of 0.823. In Group A, a cut-off value of 229.95 mlU/mL had a sensitivity and specificity of 53.3% and 92.7%, respectively. The AUROC for this cut-off was 0.847. Erythropoietin is superior to the standard prognostic scores in predicting 28-day mortality. Lower levels of EPO were detected in patients without bleeding as an insult indicating a possible therapeutic benefit in these patients.

Tracing the source of numerical climate model uncertainties in precipitation simulations using a feature-oriented statistical model

NASA Astrophysics Data System (ADS)

Xu, Y.; Jones, A. D.; Rhoades, A.

2017-12-01

Precipitation is a key component in hydrologic cycles, and changing precipitation regimes contribute to more intense and frequent drought and flood events around the world. Numerical climate modeling is a powerful tool to study climatology and to predict future changes. Despite the continuous improvement in numerical models, long-term precipitation prediction remains a challenge especially at regional scales. To improve numerical simulations of precipitation, it is important to find out where the uncertainty in precipitation simulations comes from. There are two types of uncertainty in numerical model predictions. One is related to uncertainty in the input data, such as model's boundary and initial conditions. These uncertainties would propagate to the final model outcomes even if the numerical model has exactly replicated the true world. But a numerical model cannot exactly replicate the true world. Therefore, the other type of model uncertainty is related the errors in the model physics, such as the parameterization of sub-grid scale processes, i.e., given precise input conditions, how much error could be generated by the in-precise model. Here, we build two statistical models based on a neural network algorithm to predict long-term variation of precipitation over California: one uses "true world" information derived from observations, and the other uses "modeled world" information using model inputs and outputs from the North America Coordinated Regional Downscaling Project (NA CORDEX). We derive multiple climate feature metrics as the predictors for the statistical model to represent the impact of global climate on local hydrology, and include topography as a predictor to represent the local control. We first compare the predictors between the true world and the modeled world to determine the errors contained in the input data. By perturbing the predictors in the statistical model, we estimate how much uncertainty in the model's final outcomes is accounted for by each predictor. By comparing the statistical model derived from true world information and modeled world information, we assess the errors lying in the physics of the numerical models. This work provides a unique insight to assess the performance of numerical climate models, and can be used to guide improvement of precipitation prediction.

Relationship between Small Animal Intern Rank and Performance at a University Teaching Hospital.

PubMed

Hofmeister, Erik H; Saba, Corey; Kent, Marc; Creevy, Kate E

2015-01-01

The purpose of this study was to determine if there is a relationship between selection committee rankings of internship applicants and the performance of small animal interns. The hypothesis was that there would be a relationship between selection committee rank order and intern performance; the more highly an application was ranked, the better the intern's performance scores would be. In 2007, the Department of Small Animal Medicine and Surgery instituted a standardized approach to its intern selection process both to streamline the process and to track its effectiveness. At the end of intern years 2010-2014, every faculty member in the department was provided an intern assessment form for that year's class. There was no relationship between an individual intern's final rank by the selection committee and his/her performance either as a percentile score or a Likert-type score (p=.25, R2=0.04; p=0.31, R2=0.03, respectively). Likewise, when interns were divided into the top and bottom quartile based on their final rank by the selection committee, there was no relationship between their rank and their performance as a percentile score (median rank 15 vs. 20; p=.14) or Likert-type score (median rank 14 vs. 19; p=.27). Institutions that use a similar intern selection method may need to reconsider the time and effort being expended for an outcome that does not predict performance. Alternatively, specific criteria more predictive of performance outcomes should be identified and employed in the internship selection process.

[Arterial pressure curve and fluid status].

PubMed

Pestel, G; Fukui, K

2009-04-01

Fluid optimization is a major contributor to improved outcome in patients. Unfortunately, anesthesiologists are often in doubt whether an additional fluid bolus will improve the hemodynamics of the patient or not as excess fluid may even jeopardize the condition. This article discusses physiological concepts of liberal versus restrictive fluid management followed by a discussion on the respective capabilities of various monitors to predict fluid responsiveness. The parameter difference in pulse pressure (dPP), derived from heart-lung interaction in mechanically ventilated patients is discussed in detail. The dPP cutoff value of 13% to predict fluid responsiveness is presented together with several assessment techniques of dPP. Finally, confounding variables on dPP measurements, such as ventilation parameters, pneumoperitoneum and use of norepinephrine are also mentioned.

Toward a comprehensive model of antisocial development: a dynamic systems approach.

PubMed

Granic, Isabela; Patterson, Gerald R

2006-01-01

The purpose of this article is to develop a preliminary comprehensive model of antisocial development based on dynamic systems principles. The model is built on the foundations of behavioral research on coercion theory. First, the authors focus on the principles of multistability, feedback, and nonlinear causality to reconceptualize real-time parent-child and peer processes. Second, they model the mechanisms by which these real-time processes give rise to negative developmental outcomes, which in turn feed back to determine real-time interactions. Third, they examine mechanisms of change and stability in early- and late-onset antisocial trajectories. Finally, novel clinical designs and predictions are introduced. The authors highlight new predictions and present studies that have tested aspects of the model

Spring assisted cranioplasty: A patient specific computational model.

PubMed

Borghi, Alessandro; Rodriguez-Florez, Naiara; Rodgers, Will; James, Gregory; Hayward, Richard; Dunaway, David; Jeelani, Owase; Schievano, Silvia

2018-03-01

Implantation of spring-like distractors in the treatment of sagittal craniosynostosis is a novel technique that has proven functionally and aesthetically effective in correcting skull deformities; however, final shape outcomes remain moderately unpredictable due to an incomplete understanding of the skull-distractor interaction. The aim of this study was to create a patient specific computational model of spring assisted cranioplasty (SAC) that can help predict the individual overall final head shape. Pre-operative computed tomography images of a SAC patient were processed to extract a 3D model of the infant skull anatomy and simulate spring implantation. The distractors were modeled based on mechanical experimental data. Viscoelastic bone properties from the literature were tuned using the specific patient procedural information recorded during surgery and from x-ray measurements at follow-up. The model accurately captured spring expansion on-table (within 9% of the measured values), as well as at first and second follow-ups (within 8% of the measured values). Comparison between immediate post-operative 3D head scanning and numerical results for this patient proved that the model could successfully predict the final overall head shape. This preliminary work showed the potential application of computational modeling to study SAC, to support pre-operative planning and guide novel distractor design. Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Prognostic value of quantitative sensory testing in low back pain: a systematic review of the literature

PubMed Central

Marcuzzi, Anna; Dean, Catherine M; Wrigley, Paul J; Chakiath, Rosemary J; Hush, Julia M

2016-01-01

Quantitative sensory testing (QST) measures have recently been shown to predict outcomes in various musculoskeletal and pain conditions. The aim of this systematic review was to summarize the emerging body of evidence investigating the prognostic value of QST measures in people with low back pain (LBP). The protocol for this review was prospectively registered on the International Prospective Register of Systematic Reviews. An electronic search of six databases was conducted from inception to October 2015. Experts in the field were contacted to retrieve additional unpublished data. Studies were included if they were prospective longitudinal in design, assessed at least one QST measure in people with LBP, assessed LBP status at follow-up, and reported the association of QST data with LBP status at follow-up. Statistical pooling of results was not possible due to heterogeneity between studies. Of 6,408 references screened after duplicates removed, three studies were finally included. None of them reported a significant association between the QST measures assessed and the LBP outcome. Three areas at high risk of bias were identified which potentially compromise the validity of these results. Due to the paucity of available studies and the methodological shortcomings identified, it remains unknown whether QST measures are predictive of outcome in LBP. PMID:27660486

Prognostic value of quantitative sensory testing in low back pain: a systematic review of the literature.

PubMed

Marcuzzi, Anna; Dean, Catherine M; Wrigley, Paul J; Chakiath, Rosemary J; Hush, Julia M

2016-01-01

Quantitative sensory testing (QST) measures have recently been shown to predict outcomes in various musculoskeletal and pain conditions. The aim of this systematic review was to summarize the emerging body of evidence investigating the prognostic value of QST measures in people with low back pain (LBP). The protocol for this review was prospectively registered on the International Prospective Register of Systematic Reviews. An electronic search of six databases was conducted from inception to October 2015. Experts in the field were contacted to retrieve additional unpublished data. Studies were included if they were prospective longitudinal in design, assessed at least one QST measure in people with LBP, assessed LBP status at follow-up, and reported the association of QST data with LBP status at follow-up. Statistical pooling of results was not possible due to heterogeneity between studies. Of 6,408 references screened after duplicates removed, three studies were finally included. None of them reported a significant association between the QST measures assessed and the LBP outcome. Three areas at high risk of bias were identified which potentially compromise the validity of these results. Due to the paucity of available studies and the methodological shortcomings identified, it remains unknown whether QST measures are predictive of outcome in LBP.

Causal Rasch models.

PubMed

Stenner, A Jackson; Fisher, William P; Stone, Mark H; Burdick, Donald S

2013-01-01

Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.

Causal Rasch models

PubMed Central

Stenner, A. Jackson; Fisher, William P.; Stone, Mark H.; Burdick, Donald S.

2013-01-01

Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained. PMID:23986726

Computational discovery and in vivo validation of hnf4 as a regulatory gene in planarian regeneration.

PubMed

Lobo, Daniel; Morokuma, Junji; Levin, Michael

2016-09-01

Automated computational methods can infer dynamic regulatory network models directly from temporal and spatial experimental data, such as genetic perturbations and their resultant morphologies. Recently, a computational method was able to reverse-engineer the first mechanistic model of planarian regeneration that can recapitulate the main anterior-posterior patterning experiments published in the literature. Validating this comprehensive regulatory model via novel experiments that had not yet been performed would add in our understanding of the remarkable regeneration capacity of planarian worms and demonstrate the power of this automated methodology. Using the Michigan Molecular Interactions and STRING databases and the MoCha software tool, we characterized as hnf4 an unknown regulatory gene predicted to exist by the reverse-engineered dynamic model of planarian regeneration. Then, we used the dynamic model to predict the morphological outcomes under different single and multiple knock-downs (RNA interference) of hnf4 and its predicted gene pathway interactors β-catenin and hh Interestingly, the model predicted that RNAi of hnf4 would rescue the abnormal regenerated phenotype (tailless) of RNAi of hh in amputated trunk fragments. Finally, we validated these predictions in vivo by performing the same surgical and genetic experiments with planarian worms, obtaining the same phenotypic outcomes predicted by the reverse-engineered model. These results suggest that hnf4 is a regulatory gene in planarian regeneration, validate the computational predictions of the reverse-engineered dynamic model, and demonstrate the automated methodology for the discovery of novel genes, pathways and experimental phenotypes. michael.levin@tufts.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predictive value of the DASH tool for predicting return to work of injured workers with musculoskeletal disorders of the upper extremity.

PubMed

Armijo-Olivo, Susan; Woodhouse, Linda J; Steenstra, Ivan A; Gross, Douglas P

2016-12-01

To determine whether the Disabilities of the Arm, Shoulder, and Hand (DASH) tool added to the predictive ability of established prognostic factors, including patient demographic and clinical outcomes, to predict return to work (RTW) in injured workers with musculoskeletal (MSK) disorders of the upper extremity. A retrospective cohort study using a population-based database from the Workers' Compensation Board of Alberta (WCB-Alberta) that focused on claimants with upper extremity injuries was used. Besides the DASH, potential predictors included demographic, occupational, clinical and health usage variables. Outcome was receipt of compensation benefits after 3 months. To identify RTW predictors, a purposeful logistic modelling strategy was used. A series of receiver operating curve analyses were performed to determine which model provided the best discriminative ability. The sample included 3036 claimants with upper extremity injuries. The final model for predicting RTW included the total DASH score in addition to other established predictors. The area under the curve for this model was 0.77, which is interpreted as fair discrimination. This model was statistically significantly different than the model of established predictors alone (p<0.001). When comparing the DASH total score versus DASH item 23, a non-significant difference was obtained between the models (p=0.34). The DASH tool together with other established predictors significantly helped predict RTW after 3 months in participants with upper extremity MSK disorders. An appealing result for clinicians and busy researchers is that DASH item 23 has equal predictive ability to the total DASH score. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Awareness Programs and Change in Taste-Based Caste Prejudice

PubMed Central

Banerjee, Ritwik; Datta Gupta, Nabanita

2015-01-01

Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution - the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste. PMID:25902290

Home Environmental and Behavioral Risk Indices for Reading Achievement.

PubMed

Taylor, Jeanette; Ennis, Chelsea R; Hart, Sara A; Mikolajewski, Amy J; Schatschneider, Christopher

2017-07-01

The goal of this study was to identify home environmental and temperament/behavior variables that best predict standardized reading comprehension scores among school-aged children. Data from 269 children aged 9-16 ( M = 12.08; SD = 1.62) were used in discriminant function analyses to create the Home and Behavior indices. Family income was controlled in each index. The final Home and Behavior models each classified around 75% of cases correctly (reading comprehension at grade level vs. not). Each index was then used to predict other outcomes related to reading. Results showed that Home and/or Behavior accounted for 4-7% of the variance in reading fluency and spelling and 20-35% of the variance in parent-rated problems in math, social anxiety, and other dimensions. These metrics show promise as environmental and temperament/behavior risk scores that could be used to predict and potentially screen for further assessment of reading related problems.

Awareness programs and change in taste-based caste prejudice.

PubMed

Banerjee, Ritwik; Datta Gupta, Nabanita

2015-01-01

Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution--the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste.

Predictive model of third molar eruption after second molar extraction.

PubMed

De-la-Rosa-Gay, Cristina; Valmaseda-Castellón, Eduard; Gay-Escoda, Cosme

2010-03-01

Extraction of second permanent molars is an option for providing space in orthodontic treatment. Although many articles have described its impact on the outcome, there are few data on the prognosis of the eruption of the adjacent third molars. The aims of this investigation were to provide predictive models of eruption of third molars after second permanent molar extraction and to validate them. A total of 48 patients (ages, 11-23 years) who had 128 second permanent molars (54 maxillary, 74 mandibular) extracted during orthodontic treatment were followed until eruption of the third molars was complete. A lineal regression model predicted the final angle of the third molars with the permanent first molar by using the variables of initial angle, jaw, and the developmental stage of the third molar. A logistic regression model predicted the probability of correct eruption by using the variables of initial angle, jaw, sex, age, and the developmental stage of the third molar. 2010 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

The status of perineural invasion predicts the outcomes of postoperative radiotherapy in locally advanced esophageal squamous cell carcinoma.

PubMed

Ning, Zhong-Hua; Zhao, Wei; Li, Xiao-Dong; Chen, Lu-Jun; Xu, Bin; Gu, Wen-Dong; Shao, Ying-Jie; Xu, Yun; Huang, Jin; Pei, Hong-Lei; Jiang, Jing-Ting

2015-01-01

Prognosis of locally advanced esophageal squamous cell carcinoma (ESCC) remains dismal even after curative resection and adjuvant radiotherapy. New biomarkers for predicting prognosis and treatment outcomes are needed for improved treatment stratification of patients with locally advanced ESCC. The prognostic and treatment predictive significance of perineural invasion (PNI) in the locally advanced ESCC remains unclear. This study aimed to examine the effect of PNI on the outcomes of locally advanced ESCC patients after curative resection with or without postoperative radiotherapy (PORT). We retrospectively reviewed 262 consecutive locally advanced ESCC patients who underwent curative resection. Tumors sections were re-evaluated for PNI by an independent pathologist blinded to the patients' outcomes. Overall survival (OS) and disease-free survival (DFS) were determined using the Kaplan-Meier method; univariate log-rank test and multivariate Cox proportional hazard model were used to evaluate the prognostic value of PNI. Finally, 243 patients were analyzed and enrolled into this study, of which 132 received PORT. PNI was identified in 22.2% (54/243) of the pathologic sections. The 5-year DFS was favorable for PNI-negative patients versus PNI-positive patients (21.3% vs. 36.7%, respectively; P = 0.005). The 5-year OS was 40.3% for PNI-negative patients versus 21.7% for PNI-positive patients (P < 0.001). On multivariate analysis, PNI was an independent prognostic factor. In a subset analysis for patients received PORT, PNI was evaluated as a prognostic predictor as well (P < 0.05). In contrast to patients without PORT, PORT couldn't improve the disease recurrence and survival in locally advanced ESCC patients with PNI-positive (P > 0.05). PNI could serve as an independent prognostic factor and prognosticate treatment outcomes in locally advanced ESCC patients. The PNI status should be considered when stratifying high-risk locally advanced ESCC patients for adjuvant radiotherapy. Future prospective study is warranted to confirm our results.

Patient-reported outcomes as predictors of 10-year survival in women after acute myocardial infarction

PubMed Central

2010-01-01

Background Patient-reported outcomes are increasingly seen as complementary to biomedical measures. However, their prognostic importance has yet to be established, particularly in female long-term myocardial infarction (MI) survivors. We aimed to determine whether 10-year survival in older women after MI relates to patient-reported outcomes, and to compare their survival with that of the general female population. Methods We included all women aged 60-80 years suffering MI during 1992-1997, and treated at one university hospital in Norway. In 1998, 145 (60% of those alive) completed a questionnaire package including socio-demographics, the Sense of Coherence Scale (SOC-29), the World Health Organization Quality of Life Instrument Abbreviated (WHOQOL-BREF) and an item on positive effects of illness. Clinical information was based on self-reports and hospital medical records data. We obtained complete data on vital status. Results The all-cause mortality rate during the 1998-2008 follow-up of all patients was 41%. In adjusted analysis, the conventional predictors s-creatinine (HR 1.26 per 10% increase) and left ventricular ejection fraction below 30% (HR 27.38), as well as patient-reported outcomes like living alone (HR 6.24), dissatisfaction with self-rated health (HR 6.26), impaired psychological quality of life (HR 0.60 per 10 points difference), and experience of positive effects of illness (HR 6.30), predicted all-cause death. Major adverse cardiac and cerebral events were also significantly associated with both conventional predictors and patient-reported outcomes. Sense of coherence did not predict adverse events. Finally, 10-year survival was not significantly different from that of the general female population. Conclusion Patient-reported outcomes have long-term prognostic importance, and should be taken into account when planning aftercare of low-risk older female MI patients. PMID:21108810

Patient-reported outcomes as predictors of 10-year survival in women after acute myocardial infarction.

PubMed

Norekvål, Tone M; Fridlund, Bengt; Rokne, Berit; Segadal, Leidulf; Wentzel-Larsen, Tore; Nordrehaug, Jan Erik

2010-11-25

Patient-reported outcomes are increasingly seen as complementary to biomedical measures. However, their prognostic importance has yet to be established, particularly in female long-term myocardial infarction (MI) survivors. We aimed to determine whether 10-year survival in older women after MI relates to patient-reported outcomes, and to compare their survival with that of the general female population. We included all women aged 60-80 years suffering MI during 1992-1997, and treated at one university hospital in Norway. In 1998, 145 (60% of those alive) completed a questionnaire package including socio-demographics, the Sense of Coherence Scale (SOC-29), the World Health Organization Quality of Life Instrument Abbreviated (WHOQOL-BREF) and an item on positive effects of illness. Clinical information was based on self-reports and hospital medical records data. We obtained complete data on vital status. The all-cause mortality rate during the 1998-2008 follow-up of all patients was 41%. In adjusted analysis, the conventional predictors s-creatinine (HR 1.26 per 10% increase) and left ventricular ejection fraction below 30% (HR 27.38), as well as patient-reported outcomes like living alone (HR 6.24), dissatisfaction with self-rated health (HR 6.26), impaired psychological quality of life (HR 0.60 per 10 points difference), and experience of positive effects of illness (HR 6.30), predicted all-cause death. Major adverse cardiac and cerebral events were also significantly associated with both conventional predictors and patient-reported outcomes. Sense of coherence did not predict adverse events. Finally, 10-year survival was not significantly different from that of the general female population. Patient-reported outcomes have long-term prognostic importance, and should be taken into account when planning aftercare of low-risk older female MI patients.

Coordinating the effects of multiple variables: a skill fundamental to scientific thinking.

PubMed

Kuhn, Deanna; Pease, Maria; Wirkala, Clarice

2009-07-01

The skill of predicting outcomes based on simultaneous effects of multiple factors was examined. Over five sessions, 91 sixth graders engaged this task either individually or in pairs and either preceded or followed by six sessions on the more widely studied inquiry task that requires designing and interpreting experiments to identify individual effects. Final assessment, while indicating a high level of mastery on the inquiry task, showed progress but continuing conceptual challenges on the multivariable prediction task having to do with understanding of variables, variable levels, and consistency of a variable's operation across occasions. Task order had a significant but limited effect, and social collaboration conferred only a temporary benefit that disappeared in a final individual assessment. In a follow-up study, the lack of effect of social collaboration was confirmed, as was that of feedback on incorrect answers. Although fundamental to science, the concept that variables operate jointly and, under equivalent conditions, consistently across occasions is one that children appear to acquire only gradually and, therefore, one that cannot be assumed to be in place.

Happiness Unpacked: Positive Emotions Increase Life Satisfaction by Building Resilience

PubMed Central

Cohn, Michael A.; Fredrickson, Barbara L.; Brown, Stephanie L.; Mikels, Joseph A.; Conway, Anne M.

2011-01-01

Happiness – a composite of life satisfaction, coping resources, and positive emotions – predicts desirable life outcomes in many domains. The broaden-and-build theory suggests that this is because positive emotions help people build lasting resources. To test this hypothesis we measured emotions daily for one month in a sample of students (N=86) and assessed life satisfaction and trait resilience at the beginning and end of the month. Positive emotions predicted increases in both resilience and life satisfaction. Negative emotions had weak or null effects, and did not interfere with the benefits of positive emotions. Positive emotions also mediated the relation between baseline and final resilience, but life satisfaction did not. This suggests that it is in-the-moment positive emotions, and not more general positive evaluations of one’s life, that form the link between happiness and desirable life outcomes. Change in resilience mediated the relation between positive emotions and increased life satisfaction, suggesting that happy people become more satisfied not simply because they feel better, but because they develop resources for living well. PMID:19485613

The role of need fulfillment in relationship functioning and well-being: a self-determination theory perspective.

PubMed

Patrick, Heather; Knee, C Raymond; Canevello, Amy; Lonsbary, Cynthia

2007-03-01

Self-determination theory posits 3 basic psychological needs: autonomy (feeling uncoerced in one's actions), competence (feeling capable), and relatedness (feeling connected to others). Optimal well-being results when these needs are satisfied, though this research has traditionally focused on individual well-being outcomes (e.g., E. L. Deci & R. M. Ryan, 2000). Three studies examined the role of need fulfillment in relationship functioning and well-being. Study 1 found that fulfillment of each need individually predicted both individual and relationship well-being, with relatedness being the strongest unique predictor of relationship outcomes. Study 2 found that both partners' need fulfillment uniquely predicted one's own relationship functioning and well-being. Finally, in Study 3, the authors used a diary recording procedure and tested a model in which the association between need fulfillment and relationship quality was mediated by relationship motivation. Those who experienced greater need fulfillment enjoyed better postdisagreement relationship quality primarily because of their tendency to have more intrinsic or autonomous reasons for being in their relationship. 2007 APA, all rights reserved

When helping helps: autonomous motivation for prosocial behavior and its influence on well-being for the helper and recipient.

PubMed

Weinstein, Netta; Ryan, Richard M

2010-02-01

Self-determination theory posits that the degree to which a prosocial act is volitional or autonomous predicts its effect on well-being and that psychological need satisfaction mediates this relation. Four studies tested the impact of autonomous and controlled motivation for helping others on well-being and explored effects on other outcomes of helping for both helpers and recipients. Study 1 used a diary method to assess daily relations between prosocial behaviors and helper well-being and tested mediating effects of basic psychological need satisfaction. Study 2 examined the effect of choice on motivation and consequences of autonomous versus controlled helping using an experimental design. Study 3 examined the consequences of autonomous versus controlled helping for both helpers and recipients in a dyadic task. Finally, Study 4 manipulated motivation to predict helper and recipient outcomes. Findings support the idea that autonomous motivation for helping yields benefits for both helper and recipient through greater need satisfaction. Limitations and implications are discussed. Copyright 2009 APA, all rights reserved

Cognitive and emotional factors predicting decisional conflict among high-risk breast cancer survivors who receive uninformative BRCA1/2 results.

PubMed

Rini, Christine; O'Neill, Suzanne C; Valdimarsdottir, Heiddis; Goldsmith, Rachel E; Jandorf, Lina; Brown, Karen; DeMarco, Tiffani A; Peshkin, Beth N; Schwartz, Marc D

2009-09-01

To investigate high-risk breast cancer survivors' risk reduction decision making and decisional conflict after an uninformative BRCA1/2 test. Prospective, longitudinal study of 182 probands undergoing BRCA1/2 testing, with assessments 1-, 6-, and 12-months postdisclosure. Primary predictors were health beliefs and emotional responses to testing assessed 1-month postdisclosure. Main outcomes included women's perception of whether they had made a final risk management decision (decision status) and decisional conflict related to this issue. There were four patterns of decision making, depending on how long it took women to make a final decision and the stability of their decision status across assessments. Late decision makers and nondecision makers reported the highest decisional conflict; however, substantial numbers of women--even early and intermediate decision makers--reported elevated decisional conflict. Analyses predicting decisional conflict 1- and 12-months postdisclosure found that, after accounting for control variables and decision status, health beliefs and emotional factors predicted decisional conflict at different timepoints, with health beliefs more important 1 month after test disclosure and emotional factors more important 1 year later. Many of these women may benefit from decision making assistance. Copyright 2009 APA, all rights reserved.

Cognitive and Emotional Factors Predicting Decisional Conflict among High-Risk Breast Cancer Survivors Who Receive Uninformative BRCA1/2 Results

PubMed Central

Rini, Christine; O’Neill, Suzanne C.; Valdimarsdottir, Heiddis; Goldsmith, Rachel E.; DeMarco, Tiffani A.; Peshkin, Beth N.; Schwartz, Marc D.

2012-01-01

Objective To investigate high-risk breast cancer survivors’ risk reduction decision making and decisional conflict after an uninformative BRCA1/2 test. Design Prospective, longitudinal study of 182 probands undergoing BRCA1/2 testing, with assessments 1-, 6-, and 12-months post-disclosure. Measures Primary predictors were health beliefs and emotional responses to testing assessed 1-month post-disclosure. Main outcomes included women’s perception of whether they had made a final risk management decision (decision status) and decisional conflict related to this issue. Results There were four patterns of decision making, depending on how long it took women to make a final decision and the stability of their decision status across assessments. Late decision makers and non-decision makers reported the highest decisional conflict; however, substantial numbers of women—even early and intermediate decision makers—reported elevated decisional conflict. Analyses predicting decisional conflict 1- and 12-months post-disclosure found that, after accounting for controls and decision status, health beliefs and emotional factors predicted decisional conflict at different timepoints, with health beliefs more important one month after test disclosure and health beliefs more important one year later. Conclusion Many of these women may benefit from decision making assistance. PMID:19751083

Comparative Proteomic Analysis of Human Liver Tissue and Isolated Hepatocytes with a Focus on Proteins Determining Drug Exposure.

PubMed

Vildhede, Anna; Wiśniewski, Jacek R; Norén, Agneta; Karlgren, Maria; Artursson, Per

2015-08-07

Freshly isolated human hepatocytes are considered the gold standard for in vitro studies of liver functions, including drug transport, metabolism, and toxicity. For accurate predictions of the in vivo outcome, the isolated hepatocytes should reflect the phenotype of their in vivo counterpart, i.e., hepatocytes in human liver tissue. Here, we quantified and compared the membrane proteomes of freshly isolated hepatocytes and human liver tissue using a label-free shotgun proteomics approach. A total of 5144 unique proteins were identified, spanning over 6 orders of magnitude in abundance. There was a good global correlation in protein abundance. However, the expression of many plasma membrane proteins was lower in the isolated hepatocytes than in the liver tissue. This included transport proteins that determine hepatocyte exposure to many drugs and endogenous compounds. Pathway analysis of the differentially expressed proteins confirmed that hepatocytes are exposed to oxidative stress during isolation and suggested that plasma membrane proteins were degraded via the protein ubiquitination pathway. Finally, using pitavastatin as an example, we show how protein quantifications can improve in vitro predictions of in vivo liver clearance. We tentatively conclude that our data set will be a useful resource for improved hepatocyte predictions of the in vivo outcome.

Motor cortex guides selection of predictable movement targets

PubMed Central

Woodgate, Philip J.W.; Strauss, Soeren; Sami, Saber A.; Heinke, Dietmar

2016-01-01

The present paper asks whether the motor cortex contributes to prediction-based guidance of target selection. This question was inspired by recent evidence that suggests (i) recurrent connections from the motor system into the attentional system may extract movement-relevant perceptual information and (ii) that the motor cortex cannot only generate predictions of the sensory consequences of movements but may also operate as predictor of perceptual events in general. To test this idea we employed a choice reaching task requiring participants to rapidly reach and touch a predictable or unpredictable colour target. Motor cortex activity was modulated via transcranial direct current stimulation (tDCS). In Experiment 1 target colour repetitions were predictable. Under such conditions anodal tDCS facilitated selection versus sham and cathodal tDCS. This improvement was apparent for trajectory curvature but not movement initiation. Conversely, where no predictability of colour was embedded reach performance was unaffected by tDCS. Finally, the results of a key-press experiment suggested that motor cortex involvement is restricted to tasks where the predictable target colour is movement-relevant. The outcomes are interpreted as evidence that the motor system contributes to the top-down guidance of selective attention to movement targets. PMID:25835319

Learned predictiveness and outcome predictability effects are not simply two sides of the same coin.

PubMed

Thorwart, Anna; Livesey, Evan J; Wilhelm, Francisco; Liu, Wei; Lachnit, Harald

2017-10-01

The Learned Predictiveness effect refers to the observation that learning about the relationship between a cue and an outcome is influenced by the predictive relevance of the cue for other outcomes. Similarly, the Outcome Predictability effect refers to a recent observation that the previous predictability of an outcome affects learning about this outcome in new situations, too. We hypothesize that both effects may be two manifestations of the same phenomenon and stimuli that have been involved in highly predictive relationships may be learned about faster when they are involved in new relationships regardless of their functional role in predictive learning as cues and outcomes. Four experiments manipulated both the relationships and the function of the stimuli. While we were able to replicate the standard effects, they did not survive a transfer to situations where the functional role of the stimuli changed, that is the outcome of the first phase becomes a cue in the second learning phase or the cue of the first phase becomes the outcome of the second phase. Furthermore, unlike learned predictiveness, there was little indication that the distribution of overt attention in the second phase was influenced by previous predictability. The results suggest that these 2 very similar effects are not manifestations of a more general phenomenon but rather independent from each other. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Reducing unnecessary lab testing in the ICU with artificial intelligence.

PubMed

Cismondi, F; Celi, L A; Fialho, A S; Vieira, S M; Reti, S R; Sousa, J M C; Finkelstein, S N

2013-05-01

To reduce unnecessary lab testing by predicting when a proposed future lab test is likely to contribute information gain and thereby influence clinical management in patients with gastrointestinal bleeding. Recent studies have demonstrated that frequent laboratory testing does not necessarily relate to better outcomes. Data preprocessing, feature selection, and classification were performed and an artificial intelligence tool, fuzzy modeling, was used to identify lab tests that do not contribute an information gain. There were 11 input variables in total. Ten of these were derived from bedside monitor trends heart rate, oxygen saturation, respiratory rate, temperature, blood pressure, and urine collections, as well as infusion products and transfusions. The final input variable was a previous value from one of the eight lab tests being predicted: calcium, PTT, hematocrit, fibrinogen, lactate, platelets, INR and hemoglobin. The outcome for each test was a binary framework defining whether a test result contributed information gain or not. Predictive modeling was applied to recognize unnecessary lab tests in a real world ICU database extract comprising 746 patients with gastrointestinal bleeding. Classification accuracy of necessary and unnecessary lab tests of greater than 80% was achieved for all eight lab tests. Sensitivity and specificity were satisfactory for all the outcomes. An average reduction of 50% of the lab tests was obtained. This is an improvement from previously reported similar studies with average performance 37% by [1-3]. Reducing frequent lab testing and the potential clinical and financial implications are an important issue in intensive care. In this work we present an artificial intelligence method to predict the benefit of proposed future laboratory tests. Using ICU data from 746 patients with gastrointestinal bleeding, and eleven measurements, we demonstrate high accuracy in predicting the likely information to be gained from proposed future lab testing for eight common GI related lab tests. Future work will explore applications of this approach to a range of underlying medical conditions and laboratory tests. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Reducing unnecessary lab testing in the ICU with artificial intelligence

PubMed Central

Cismondi, F.; Celi, L.A.; Fialho, A.S.; Vieira, S.M.; Reti, S.R.; Sousa, J.M.C.; Finkelstein, S.N.

2017-01-01

Objectives To reduce unnecessary lab testing by predicting when a proposed future lab test is likely to contribute information gain and thereby influence clinical management in patients with gastrointestinal bleeding. Recent studies have demonstrated that frequent laboratory testing does not necessarily relate to better outcomes. Design Data preprocessing, feature selection, and classification were performed and an artificial intelligence tool, fuzzy modeling, was used to identify lab tests that do not contribute an information gain. There were 11 input variables in total. Ten of these were derived from bedside monitor trends heart rate, oxygen saturation, respiratory rate, temperature, blood pressure, and urine collections, as well as infusion products and transfusions. The final input variable was a previous value from one of the eight lab tests being predicted: calcium, PTT, hematocrit, fibrinogen, lactate, platelets, INR and hemoglobin. The outcome for each test was a binary framework defining whether a test result contributed information gain or not. Patients Predictive modeling was applied to recognize unnecessary lab tests in a real world ICU database extract comprising 746 patients with gastrointestinal bleeding. Main results Classification accuracy of necessary and unnecessary lab tests of greater than 80% was achieved for all eight lab tests. Sensitivity and specificity were satisfactory for all the outcomes. An average reduction of 50% of the lab tests was obtained. This is an improvement from previously reported similar studies with average performance 37% by [1–3]. Conclusions Reducing frequent lab testing and the potential clinical and financial implications are an important issue in intensive care. In this work we present an artificial intelligence method to predict the benefit of proposed future laboratory tests. Using ICU data from 746 patients with gastrointestinal bleeding, and eleven measurements, we demonstrate high accuracy in predicting the likely information to be gained from proposed future lab testing for eight common GI related lab tests. Future work will explore applications of this approach to a range of underlying medical conditions and laboratory tests. PMID:23273628

The PLAN score: a bedside prediction rule for death and severe disability following acute ischemic stroke.

PubMed

O'Donnell, Martin J; Fang, Jiming; D'Uva, Cami; Saposnik, Gustavo; Gould, Linda; McGrath, Emer; Kapral, Moira K

2012-11-12

We sought to develop and validate a simple clinical prediction rule for death and severe disability after acute ischemic stroke that can be used by general clinicians at the time of hospital admission. We analyzed data from a registry of 9847 patients (4943 in the derivation cohort and 4904 in the validation cohort) hospitalized with acute ischemic stroke and included in the Registry of the Canadian Stroke Network (July 1, 2003, to March 31, 2008; 11 regional stroke centers in Ontario, Canada). Outcome measures were 30-day and 1-year mortality and a modified Rankin score of 5 to 6 at discharge. Overall 30-day mortality was 11.5% (derivation cohort) and 13.5% (validation cohort). In the final multivariate model, we included 9 clinical variables that could be categorized as preadmission comorbidities (5 points for preadmission dependence [1.5], cancer [1.5], congestive heart failure [1.0], and atrial fibrillation [1.0]), level of consciousness (5 points for reduced level of consciousness), age (10 points, 1 point/decade), and neurologic focal deficit (5 points for significant/total weakness of the leg [2], weakness of the arm [2], and aphasia or neglect [1]). Maximum score is 25. In the validation cohort, the PLAN score (derived from preadmission comorbidities, level of consciousness, age, and neurologic deficit) predicted 30-day mortality (C statistic, 0.87), death or severe dependence at discharge (0.88), and 1-year mortality (0.84). The PLAN score also predicted favorable outcome (modified Rankin score, 0-2) at discharge (C statistic, 0.80). The PLAN clinical prediction rule identifies patients who will have a poor outcome after hospitalization for acute ischemic stroke. The score comprises clinical data available at the time of admission and may be determined by nonspecialist clinicians. Additional studies to independently validate the PLAN rule in different populations and settings are required.

Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample.

PubMed

Victor, Teresa A; Khalsa, Sahib S; Simmons, W Kyle; Feinstein, Justin S; Savitz, Jonathan; Aupperle, Robin L; Yeh, Hung-Wen; Bodurka, Jerzy; Paulus, Martin P

2018-01-24

Although neuroscience has made tremendous progress towards understanding the basic neural circuitry underlying important processes such as attention, memory and emotion, little progress has been made in applying these insights to psychiatric populations to make clinically meaningful treatment predictions. The overall aim of the Tulsa 1000 (T-1000) study is to use the NIMH Research Domain Criteria framework in order to establish a robust and reliable dimensional set of variables that quantifies the positive and negative valence, cognition and arousal domains, including interoception, to generate clinically useful treatment predictions. The T-1000 is a naturalistic study that will recruit, assess and longitudinally follow 1000 participants, including healthy controls and treatment-seeking individuals with mood, anxiety, substance use and eating disorders. Each participant will undergo interview, behavioural, biomarker and neuroimaging assessments over the course of 1 year. The study goal is to determine how disorders of affect, substance use and eating behaviour organise across different levels of analysis (molecules, genes, cells, neural circuits, physiology, behaviour and self-report) to predict symptom severity, treatment outcome and long-term prognosis. The data will be used to generate computational models based on Bayesian statistics. The final end point of this multilevel latent variable analysis will be standardised assessments that can be developed into clinical tools to help clinicians predict outcomes and select the best intervention for each individual, thereby reducing the burden of mental disorders, and taking psychiatry a step closer towards personalised medicine. Ethical approval was obtained from Western Institutional Review Board screening protocol #20101611. The dissemination plan includes informing health professionals of results for clinical practice, submitting results to journals for peer-reviewed publication, presenting results at national and international conferences and making the dataset available to researchers and mental health professionals. NCT02450240; Pre-results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Association between the high soluble fms-like tyrosine kinase-1 to placental growth factor ratio and adverse outcomes in asymptomatic women with early-onset fetal growth restriction.

PubMed

Shinohara, Satoshi; Uchida, Yuzo; Kasai, Mayuko; Sunami, Rei

2017-08-01

To assess whether the high soluble fms-like tyrosine kinase-1 (sFlt-1) to placental growth factor (PlGF) ratio is associated with adverse outcomes (e.g., HELLP syndrome [hemolysis, elevated liver enzymes, and low platelets], severe hypertension uncontrolled by medication, non-reassuring fetal status, placental abruption, pulmonary edema, growth arrest, maternal death, or fetal death) and a shorter duration to delivery in early-onset fetal growth restriction (FGR). Thirty-four women with FGR diagnosed at <34.0 weeks were recruited. Serum angiogenic marker levels were estimated within 6 hours of a diagnosis of FGR. A receiver operating characteristic curve was used to determine the threshold of the sFlt-1/PlGF ratio to predict adverse outcomes. We used multivariable logistic regression analysis to examine the association between the sFlt-1/PlGF ratio and adverse outcomes. Finally, we used Kaplan-Meier analysis and the log-rank test to assess the probability of delay in delivery. Women who developed adverse outcomes within a week had a significantly higher sFlt-1/PlGF ratio than did those who did not develop complications. A cutoff value of 86.2 for the sFlt-1/PlGF ratio predicted adverse outcomes, with a sensitivity and specificity of 77.8% and 80.0%, respectively. Moreover, 58.4% of women with an sFlt-1/PlGF ratio ≥86.2 versus 9.1% of those with an sFlt-1/PlGF ratio <86.2 delivered within a week of presentation (p < 0.001). In multivariate analyses, an sFlt-1/PlGF ratio ≥86.2 (adjusted odds ratio 9.52; 95% confidence interval, 1.25-72.8) was associated with adverse maternal and neonatal outcomes. A high sFlt-1/PlGF ratio was associated with adverse outcomes and a shorter duration to delivery in early-onset FGR.

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Predicting the math/science career goals of low-income prospective first-generation college students.

PubMed

Garriott, Patton O; Flores, Lisa Y; Martens, Matthew P

2013-04-01

The present study used social cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) to predict the math/science goal intentions of a sample of low-income prospective first-generation college students (N = 305). Structural equation modeling was used to test a model depicting relationships between contextual (i.e., social class, learning experiences, proximal supports and barriers) and person-cognitive (i.e., self-efficacy, outcome expectations, interests, goals) variables as hypothesized in SCCT and based on previous literature on low-income first-generation college students. Results indicated that the hypothesized model provided the best representation of the data. All paths in the model were statistically significant, with the exceptions of paths from self-efficacy to goals, outcome expectations to interests, and perceived barriers to self-efficacy. Bootstrapping procedures revealed that the relationships between social class, self-efficacy, and outcome expectations were mediated through learning experiences. Furthermore, the relationship between social supports and goals was mediated by self-efficacy and interests and the relationships between self-efficacy, outcome expectations, and goals were mediated by interests. Contrary to hypotheses, the relationship between barriers and goals was not mediated by self-efficacy and interests. The hypothesis that proximal contextual supports and barriers would moderate the relationship between interests and goals was not supported. The final model explained 66% and 55% of the variance in math/science interests and goals, respectively. Implications for future research and practice are discussed.

Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach.

PubMed

Kang, Le; Chen, Weijie; Petrick, Nicholas A; Gallas, Brandon D

2015-02-20

The area under the receiver operating characteristic curve is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of area under the receiver operating characteristic curve, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics-based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study. Copyright © 2014 John Wiley & Sons, Ltd.

Role of autofluorescence in inflammatory/infective diseases of the retina and choroid.

PubMed

Samy, Ahmed; Lightman, Sue; Ismetova, Filis; Talat, Lazha; Tomkins-Netzer, Oren

2014-01-01

Fundus autofluorescence (FAF) has recently emerged as a novel noninvasive imaging technique that uses the fluorescent properties of innate fluorophores accumulated in the retinal pigment epithelium (RPE) to assess the health and viability of the RPE/photoreceptor complex. Recent case reports suggest FAF as a promising tool for monitoring eyes with posterior uveitis helping to predict final visual outcome. In this paper we review the published literature on FAF in these disorders, specifically patterns in infectious and noninfectious uveitis, and illustrate some of these with short case histories.

Functional Manipulation of Root Endophyte Populations for Feedstock Improvement- Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dangl, Jeffery L.

This study provides a systemic analysis of the influence of the abiotic environment on the assembly of plant microbiomes. We show that under controlled conditions, community assembly cues are robust and predictable across multiple abiotic gradients. Plant colonization patterns are largely driven by phylogeny, and colonization phenotypes are ubiquitous across different specimens of the same phylogenetic class. Subsets of the full synthetic community were shown to induce different root morphologies, and the morphology observed with the full community is an outcome of epistasis between two functional guilds.

Autoimmunity in endocrine diseases.

PubMed

Rose, N R; Burek, C L

1982-01-01

The realization that autoimmunity underlies many endocrine disorders of previously unknown etiology has greatly broadened our understanding of the pathogenesis of these diseases. It has provided new explanations for their heredity and their association with particular HLA haplotypes. It has also offered new tools for diagnosing these diseases as well as monitoring their course or predicting their outcome. Finally, establishing the autoimmune basis of these diseases offers new potential for their treatment. The next quarter century of research into immunologic aspects of endocrine diseases promises to be as fruitful as the last.

Perceived threat and corroboration: key factors that improve a predictive model of trust in internet-based health information and advice.

PubMed

Harris, Peter R; Sillence, Elizabeth; Briggs, Pam

2011-07-27

How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ(2) (5) = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice.

Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

PubMed Central

Harris, Peter R; Briggs, Pam

2011-01-01

Background How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ2 5 = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Conclusions Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice. PMID:21795237

Endoscopic ultrasound evaluation in the surgical treatment of duodenal and peri-ampullary adenomas.

PubMed

Azih, Lilian C; Broussard, Brett L; Phadnis, Milind A; Heslin, Martin J; Eloubeidi, Mohamad A; Varadarajulu, Shayam; Arnoletti, Juan Pablo

2013-01-28

To investigate endoscopic ultrasound (EUS) for predicting depth of mucosal invasion and to analyze outcomes following endoscopic and transduodenal resection. Records of 111 patients seen at our institution from November 1999 to July 2011 with the post-operative pathological diagnosis of benign ampullary and duodenal adenomas were reviewed. Records of patients who underwent preoperative EUS for diagnostic purposes were identified. The accuracy of EUS in predicting the absence of muscular invasion was assessed by comparing EUS reports to the final surgical pathological results. In addition, the incidence of the post-operative complications over a period of 30 d and the subsequent long-term outcome (recurrence) over a period of 30 mo associated with endoscopic and transduodenal surgical resection was recorded, compared and analyzed. Among 111 patients with benign ampullary and duodenal adenomas, 47 underwent preoperative EUS for 29 peri-ampullary lesions and 18 duodenal lesions. In addition, computed tomography was performed in 18 patients, endoscopic retrograde cholangio-pancreatography in 10 patients and esophagogastroduodenoscopy in 22 patients. There were 43 patients with sporadic adenomas and 4 patients with familial adenomatous polyposis (FAP)/other polyposis syndromes. In 38 (81%, P < 0.05) patients, EUS reliably identified absence of submucosal and muscularis invasion. In 4 cases, EUS underestimated submucosal invasion that was proven by pathology. In the other 5 patients, EUS predicted muscularis invasion which could not be demonstrated in the resected specimen. EUS predicted tumor muscularis invasion with a specificity of 88% and negative predictive value of 90% (P < 0.05). Types of resection performed included endoscopic resection in 22 cases, partial duodenectomy in 9 cases, transduodenal ampullectomy with sphincteroplasty in 10 cases and pancreaticoduodenectomy in 6 cases. The main post-operative final pathological results included villous adenoma (n = 5), adenoma (n = 8), tubulovillous adenoma (n = 10), tubular adenoma (n = 20) and hyperplastic polyp (n = 2). Among the 47 patients who underwent resection, 8 (17%, 5 of which corresponded to surgical resection) developed post-procedural complications which included retroperitoneal hematoma, intra-abdominal abscess, wound infection, delayed gastric emptying and prolonged ileus. After median follow-up of 20 mo there were 6 local recurrences (13%, median follow-up = 20 mo) 4 of which were in patients with FAP. EUS accurately predicts the depth of mucosal invasion in suspected benign ampullary and duodenal adenomas. These patients can safely undergo endoscopic or local resection.

Posttreatment Variables Improve Outcome Prediction after Intra-Arterial Therapy for Acute Ischemic Stroke

PubMed Central

Prabhakaran, Shyam; Jovin, Tudor G.; Tayal, Ashis H.; Hussain, Muhammad S.; Nguyen, Thanh N.; Sheth, Kevin N.; Terry, John B.; Nogueira, Raul G.; Horev, Anat; Gandhi, Dheeraj; Wisco, Dolora; Glenn, Brenda A.; Ludwig, Bryan; Clemmons, Paul F.; Cronin, Carolyn A.; Tian, Melissa; Liebeskind, David; Zaidat, Osama O.; Castonguay, Alicia C.; Martin, Coleman; Mueller-Kronast, Nils; English, Joey D.; Linfante, Italo; Malisch, Timothy W.; Gupta, Rishi

2014-01-01

Background There are multiple clinical and radiographic factors that influence outcomes after endovascular reperfusion therapy (ERT) in acute ischemic stroke (AIS). We sought to derive and validate an outcome prediction score for AIS patients undergoing ERT based on readily available pretreatment and posttreatment factors. Methods The derivation cohort included 511 patients with anterior circulation AIS treated with ERT at 10 centers between September 2009 and July 2011. The prospective validation cohort included 223 patients with anterior circulation AIS treated in the North American Solitaire Acute Stroke registry. Multivariable logistic regression identified predictors of good outcome (modified Rankin score ≤2 at 3 months) in the derivation cohort; model β coefficients were used to assign points and calculate a risk score. Discrimination was tested using C statistics with 95% confidence intervals (CIs) in the derivation and validation cohorts. Calibration was assessed using the Hosmer-Lemeshow test and plots of observed to expected outcomes. We assessed the net reclassification improvement for the derived score compared to the Totaled Health Risks in Vascular Events (THRIVE) score. Subgroup analysis in patients with pretreatment Alberta Stroke Program Early CT Score (ASPECTS) and posttreatment final infarct volume measurements was also performed to identify whether these radiographic predictors improved the model compared to simpler models. Results Good outcome was noted in 186 (36.4%) and 100 patients (44.8%) in the derivation and validation cohorts, respectively. Combining readily available pretreatment and posttreatment variables, we created a score (acronym: SNARL) based on the following parameters: symptomatic hemorrhage [2 points: none, hemorrhagic infarction (HI)1–2 or parenchymal hematoma (PH) type 1; 0 points: PH2], baseline National Institutes of Health Stroke Scale score (3 points: 0–10; 1 point: 11–20; 0 points: >20), age (2 points: <60 years; 1 point: 60–79 years; 0 points: >79 years), reperfusion (3 points: Thrombolysis In Cerebral Ischemia score 2b or 3) and location of clot (1 point: M2; 0 points: M1 or internal carotid artery). The SNARL score demonstrated good discrimination in the derivation (C statistic 0.79, 95% CI 0.75–0.83) and validation cohorts (C statistic 0.74, 95% CI 0.68–0.81) and was superior to the THRIVE score (derivation cohort: C statistic 0.65, 95% CI 0.60–0.70; validation cohort: C-statistic 0.59, 95% CI 0.52–0.67; p < 0.01 in both cohorts) but was inferior to a score that included age, ASPECTS, reperfusion status and final infarct volume (C statistic 0.86, 95% CI 0.82–0.91; p = 0.04). Compared with the THRIVE score, the SNARL score resulted in a net reclassification improvement of 34.8%. Conclusions Among AIS patients treated with ERT, pretreatment scores such as the THRIVE score provide only fair prognostic information. Inclusion of posttreatment variables such as reperfusion and symptomatic hemorrhage greatly influences outcome and results in improved outcome prediction. PMID:24942008

Electrocardiogram findings in emergency department patients with syncope.

PubMed

Quinn, James; McDermott, Daniel

2011-07-01

To determine the sensitivity and specificity of the San Francisco Syncope Rule (SFSR) electrocardiogram (ECG) criteria for determining cardiac outcomes and to define the specific ECG findings that are the most important in patients with syncope. A consecutive cohort of emergency department (ED) patients with syncope or near syncope was considered. The treating emergency physicians assessed 50 predictor variables, including an ECG and rhythm assessment. For the ECG assessment, the physicians were asked to categorize the ECG as normal or abnormal based on any changes that were old or new. They also did a separate rhythm assessment and could use any of the ECGs or available monitoring strips, including prehospital strips, when making this assessment. All patients were followed up to determine a broad composite study outcome. The final ECG criterion for the SFSR was any nonsinus rhythm or new ECG changes. In this specific study, the initial assessments in the database were used to determine only cardiac-related outcomes (arrhythmia, myocardial infarction, structural, sudden death) based on set criteria, and the authors determined the sensitivity and specificity of the ECG criteria for cardiac outcomes only. All ECGs classified as "abnormal" by the study criteria were compared to the official cardiology reading to determine specific findings on the ECG. Univariate and multivariate analysis were used to determine important specific ECG and rhythm findings. A total of 684 consecutive patients were considered, with 218 having positive ECG criteria and 42 (6%) having important cardiac outcomes. ECG criteria predicted 36 of 42 patients with cardiac outcomes, with a sensitivity of 86% (95% confidence interval [CI] = 71% to 94%), a specificity of 70% (95% CI = 66% to 74%), and a negative predictive value of 99% (95% CI = 97% to 99%). Regarding specific ECG findings, any nonsinus rhythm from any source and any left bundle conduction problem (i.e., any left bundle branch block, left anterior fascicular block, left posterior fascicular block, or QRS widening) were 2.5 and 3.5 times more likely associated with significant cardiac outcomes. The ECG criteria from the SFSR are relatively simple, and if used correctly can help predict which patients are at risk of cardiac outcomes. Furthermore, any left bundle branch block conduction problems or any nonsinus rhythms found during the ED stay should be especially concerning for physicians caring for patients presenting with syncope. © 2011 by the Society for Academic Emergency Medicine.

Health-related quality-of-life parameters as independent prognostic factors in advanced or metastatic bladder cancer.

PubMed

Roychowdhury, D F; Hayden, A; Liepa, A M

2003-02-15

This retrospective analysis examined prognostic significance of health-related quality-of-life (HRQoL) parameters combined with baseline clinical factors on outcomes (overall survival, time to progressive disease, and time to treatment failure) in bladder cancer. Outcome and HRQoL (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30) data were collected prospectively in a phase III study assessing gemcitabine and cisplatin versus methotrexate, vinblastine, doxorubicin, and cisplatin in locally advanced or metastatic bladder cancer. Prespecified baseline clinical factors (performance status, tumor-node-metastasis staging, visceral metastases [VM], alkaline phosphatase [AP] level, number of metastatic sites, prior radiotherapy, disease measurability, sex, time from diagnosis, and sites of disease) and selected HRQoL parameters (global QoL; all functional scales; symptoms: pain, fatigue, insomnia, dyspnea, anorexia) were evaluated using Cox's proportional hazards model. Factors with individual prognostic value (P <.05) on outcomes in univariate models were assessed for joint prognostic value in a multivariate model. A final model was developed using a backward selection strategy. Patients with baseline HRQoL were included (364 of 405, 90%). The final model predicted longer survival with low/normal AP levels, no VM, high physical functioning, low role functioning, and no anorexia. Positive prognostic factors for time to progressive disease were good performance status, low/normal AP levels, no VM, and minimal fatigue; for time to treatment failure, they were low/normal AP levels, minimal fatigue, and no anorexia. Global QoL was a significant predictor of outcome in univariate analyses but was not retained in the multivariate model. HRQoL parameters are independent prognostic factors for outcome in advanced bladder cancer; their prognostic importance needs further evaluation.

The relationship between student engagement with online content and achievement in a blended learning anatomy course.

PubMed

Green, Rodney A; Whitburn, Laura Y; Zacharias, Anita; Byrne, Graeme; Hughes, Diane L

2017-12-13

Blended learning has become increasingly common in higher education. Recent findings suggest that blended learning achieves better student outcomes than traditional face-to-face teaching in gross anatomy courses. While face-to-face content is perceived as important to learning there is less evidence for the significance of online content in improving student outcomes. Students enrolled in a second-year anatomy course from the physiotherapy (PT), exercise physiology (EP), and exercise science (ES) programs across two campuses were included (n = 500). A structural equation model was used to evaluate the relationship of prior student ability (represented by grade in prerequisite anatomy course) and final course grade and whether the relationship was mediated by program, campus or engagement with the online elements of the learning management system (LMS; proportion of documents and video segments viewed and number of interactions with discussion forums). PT students obtained higher grades and were more likely to engage with online course materials than EP and ES students. Prerequisite grade made a direct contribution to course final grade (P < 0.001) but was also mediated by engagement with LMS videos and discussion forums (P < 0.001). Student learning outcomes in a blended anatomy course can be predicted the by level of engagement with online content. Anat Sci Educ. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

A Prospective Evaluation of High-Resolution CT Parameters in Predicting Extracorporeal Shockwave Lithotripsy Success for Upper Urinary Tract Calculi.

PubMed

Abdelhamid, Mahmoud; Mosharafa, Ashraf A; Ibrahim, Hamdy; Selim, Hany M; Hamed, Mohamed; Elghoneimy, Mohamed N; Salem, Hosny K; Abdelazim, Mohamed S; Badawy, Hesham

2016-11-01

To evaluate the ability of noncontrast CT parameters (stone size, stone attenuation, and skin-to-stone distance [SSD]) to predict the outcome of extracorporeal shockwave lithotripsy (SWL) in a prospective cohort of patients with renal and upper ureteric stones. Patients with stones 5 to 20 mm were prospectively enrolled from 2011 to 2014. Patients had NCCT with recording of stone size, stone mean attenuation, and SSD, as well as various stone and patient parameters. The numbers of needed sessions as well as the final outcome were determined, with SWL failure defined as residual fragments >3 mm. Predictors of SWL failure were assessed by multiple regression analysis. Two hundred twenty patients (mean ± standard deviation [SD] age 41.5 ± 12.4 years) underwent SWL. Mean ± SD stone size was 11.3 ± 4.1 mm, while mean ± SD stone attenuation was 795.1 ± 340.4 HU. Mean ± SD SSD was 9.4 ± 2.1 cm. The average number of sessions was 1.64. SWL was effective in 186 (84.5%) patients (group A), while 34 (15.5%) patients had significant residual fragments (>3 mm). On univariate analysis, predictors of SWL failure included stone attenuation >1000 HU, older age, higher body mass index, higher attenuation value, larger stone size, and longer SSD. Increased SSD and higher stone attenuation retained their significance as independent predictors of SWL failure (p < 0.05) on multiple regression analysis both after first session and as final SWL outcome. A positive correlation was found between number of SWL sessions and mean stone attenuation (r = 0.6, p < 0.001) and SSD (r = 4, p < 0.001). Stone mean attenuation and SSD on noncontrast CT are significant independent predictors of SWL outcome in patients with renal and ureteric stones. These parameters should be included in clinical decision algorithms for patients with urolithiasis. For patients with stones having mean attenuation of >1000 HU and/or large SSDs, alternatives to SWL should be considered.

[Application of digital design of orthodontic-prosthodontic multidisciplinary treatment plan in esthetic rehabilitation of anterior teeth].

PubMed

Liu, Y S; Li, Z; Zhao, Y J; Ye, H Q; Zhou, Y Q; Hu, W J; Liu, Y S; Xun, C L; Zhou, Y S

2018-02-18

To develop a digital workflow of orthodontic-prosthodontic multidisciplinary treatment plan which can be applied in complicated anterior teeth esthetic rehabilitation, in order to enhance the efficiency of communication between dentists and patients, and improve the predictability of treatment outcome. Twenty patients with the potential needs of orthodontic-prosthodontic multidisciplinary treatment to solve their complicated esthetic problems in anterior teeth were recruited in this study. Digital models of patients' both dental arches and soft tissues were captured using intra oral scanner. Direct prosthodontic (DP) treatment plan and orthodontic-prosthodontic (OP) treatment plan were carried out for each patient. For DP treatment plans, digital wax-up models were directly designed on original digital models using prosthodontic design system. For OP treatment plans, virtual-setups were performed using orthodontic analyze system according to orthodontic and esthetic criteria and imported to prosthodontic design system to finalize the digital wax-up models. These two treatment plans were shown to the patients and demonstrated elaborately. Each patient rated two treatment plans using visual analogue scales and the medians of scores of two treatment plans were analyzed using signed Wilcoxon test. Having taken into consideration various related factors, including time, costs of treatment, each patient chose a specific treatment plan. For the patients chose DP treatment plans, digital wax-up models were exported and printed into resin diagnostic models which would be utilized in the prosthodontic treatment process. For the patients chose OP treatment plans, virtual-setups were used to fabricate aligners or indirect bonding templates and digital wax-up models were also exported and printed into resin diagnostic models for prosthodontic treatment after orthodontic treatment completed. The medians of scores of DP treatment plan and OP treatment plan were calculated and analyzed by IBM SPSS 20. The median of scores of DP treatment plan was 8.4, the minimum value was 6.9 and the maximum value was 9.3. The median of scores of OP treatment plan was 9.0, the minimum value was 7.9 and the maximum value was 9.6. The median of scores of OP was significantly higher than that of DP (Z=-3.23, P<0.01). Finally, 12 patients chose OP treatment plans and 8 patients chose DP treatment plans. For cases with complex esthetic problems in anterior teeth, a digital workflow can demonstrate final treatment outcome and help patients make suitable treatment decisions. In our study, the orthodontic-prosthodontic multidisciplinary treatment plan is feasible which can provide predictions of treatment outcome and improve esthetic outcome with patients' satisfaction.

Assessing participation in community-based physical activity programs in Brazil.

PubMed

Reis, Rodrigo S; Yan, Yan; Parra, Diana C; Brownson, Ross C

2014-01-01

This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14-4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16-2.53), reporting a good health (OR = 1.58, 95% CI = 1.02-2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05-2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26-2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18-2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil.

Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted

PubMed Central

Røe, Cecilie; Skandsen, Toril; Manskow, Unn; Ader, Tiina; Anke, Audny

2015-01-01

The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI) and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury) model based prediction, from the Medical Research Council (MRC). Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic) (age, GCS score, and pupil reactivity to light), as well as with additional CT findings (CRASH CT). Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7) years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR) for mortality was 2.65. Unfavorable outcome (GOSE < 5) was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI. PMID:26688614

Influence of plasticity models upon the outcome of simulated hypervelocity impacts

NASA Astrophysics Data System (ADS)

Thomas, John N.

1994-07-01

This paper describes the results of numerical simulations of aluminum upon aluminum impacts which were performed with the CTH hydrocode to determine the effect plasticity formulations upon the final perforation size in the targets. The targets were 1 mm and 5 mm thick plates and the projectiles were 10 mm by 10 mm right circular cylinders. Both targets and projectiles were represented as 2024 aluminium alloy. The hydrocode simulations were run in a two-dimensional cylindrical geometry. Normal impacts at velocites between 5 and 15 km/s were simulated. Three isotropic yield stress models were explored in the simulations: an elastic-perfectly plastic model and the Johnson-Cook and Steinberg-Guinan-Lund viscoplastic models. The fracture behavior was modeled by a simple tensile pressure criterion. The simulations show that using the three strength models resulted in only minor differences in the final perforation diameter. The simulation results were used to construct an equation to predict the final hole size resulting from impacts on thin targets.

Interdependent Utilities: How Social Ranking Affects Choice Behavior

PubMed Central

Bault, Nadège; Coricelli, Giorgio; Rustichini, Aldo

2008-01-01

Organization in hierarchical dominance structures is prevalent in animal societies, so a strong preference for higher positions in social ranking is likely to be an important motivation of human social and economic behavior. This preference is also likely to influence the way in which we evaluate our outcome and the outcome of others, and finally the way we choose. In our experiment participants choose among lotteries with different levels of risk, and can observe the choice that others have made. Results show that the relative weight of gains and losses is the opposite in the private and social domain. For private outcomes, experience and anticipation of losses loom larger than gains, whereas in the social domain, gains loom larger than losses, as indexed by subjective emotional evaluations and physiological responses. We propose a theoretical model (interdependent utilities), predicting the implication of this effect for choice behavior. The relatively larger weight assigned to social gains strongly affects choices, inducing complementary behavior: faced with a weaker competitor, participants adopt a more risky and dominant behavior. PMID:18941538

LONG-TERM VISUAL OUTCOMES IN EXTREMELY LOW-BIRTH-WEIGHT CHILDREN (AN AMERICAN OPHTHALMOLOGICAL SOCIETY THESIS)

PubMed Central

Spencer, Rand

2006-01-01

Purpose The goal is to analyze the long-term visual outcome of extremely low-birth-weight children. Methods This is a retrospective analysis of eyes of extremely low-birth-weight children on whom vision testing was performed. Visual outcomes were studied by analyzing acuity outcomes at ≥36 months of adjusted age, correlating early acuity testing with final visual outcome and evaluating adverse risk factors for vision. Results Data from 278 eyes are included. Mean birth weight was 731g, and mean gestational age at birth was 26 weeks. 248 eyes had grating acuity outcomes measured at 73 ± 36 months, and 183 eyes had recognition acuity testing at 76 ± 39 months. 54% had below normal grating acuities, and 66% had below normal recognition acuities. 27% of grating outcomes and 17% of recognition outcomes were ≤20/200. Abnormal early grating acuity testing was predictive of abnormal grating (P < .0001) and recognition (P = .0001) acuity testing at ≥3 years of age. A slower-than-normal rate of early visual development was predictive of abnormal grating acuity (P < .0001) and abnormal recognition acuity (P < .0001) at ≥3 years of age. Eyes diagnosed with maximal retinopathy of prematurity in zone I had lower acuity outcomes (P = .0002) than did those with maximal retinopathy of prematurity in zone II/III. Eyes of children born at ≤28 weeks gestational age had 4.1 times greater risk for abnormal recognition acuity than did those of children born at >28 weeks gestational age. Eyes of children with poorer general health after premature birth had a 5.3 times greater risk of abnormal recognition acuity. Conclusions Long-term visual development in extremely low-birth-weight infants is problematic and associated with a high risk of subnormal acuity. Early acuity testing is useful in identifying children at greatest risk for long-term visual abnormalities. Gestational age at birth of ≤ 28 weeks was associated with a higher risk of an abnormal long-term outcome. PMID:17471358

An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment.

PubMed

Nassar, Matthew R; Wilson, Robert C; Heasly, Benjamin; Gold, Joshua I

2010-09-15

Maintaining appropriate beliefs about variables needed for effective decision making can be difficult in a dynamic environment. One key issue is the amount of influence that unexpected outcomes should have on existing beliefs. In general, outcomes that are unexpected because of a fundamental change in the environment should carry more influence than outcomes that are unexpected because of persistent environmental stochasticity. Here we use a novel task to characterize how well human subjects follow these principles under a range of conditions. We show that the influence of an outcome depends on both the error made in predicting that outcome and the number of similar outcomes experienced previously. We also show that the exact nature of these tendencies varies considerably across subjects. Finally, we show that these patterns of behavior are consistent with a computationally simple reduction of an ideal-observer model. The model adjusts the influence of newly experienced outcomes according to ongoing estimates of uncertainty and the probability of a fundamental change in the process by which outcomes are generated. A prior that quantifies the expected frequency of such environmental changes accounts for individual variability, including a positive relationship between subjective certainty and the degree to which new information influences existing beliefs. The results suggest that the brain adaptively regulates the influence of decision outcomes on existing beliefs using straightforward updating rules that take into account both recent outcomes and prior expectations about higher-order environmental structure.

Evaluating the Variations in the Flood Susceptibility Maps Accuracies due to the Alterations in the Type and Extent of the Flood Inventory

NASA Astrophysics Data System (ADS)

Tehrany, M. Sh.; Jones, S.

2017-10-01

This paper explores the influence of the extent and density of the inventory data on the final outcomes. This study aimed to examine the impact of different formats and extents of the flood inventory data on the final susceptibility map. An extreme 2011 Brisbane flood event was used as the case study. LR model was applied using polygon and point formats of the inventory data. Random points of 1000, 700, 500, 300, 100 and 50 were selected and susceptibility mapping was undertaken using each group of random points. To perform the modelling Logistic Regression (LR) method was selected as it is a very well-known algorithm in natural hazard modelling due to its easily understandable, rapid processing time and accurate measurement approach. The resultant maps were assessed visually and statistically using Area under Curve (AUC) method. The prediction rates measured for susceptibility maps produced by polygon, 1000, 700, 500, 300, 100 and 50 random points were 63 %, 76 %, 88 %, 80 %, 74 %, 71 % and 65 % respectively. Evidently, using the polygon format of the inventory data didn't lead to the reasonable outcomes. In the case of random points, raising the number of points consequently increased the prediction rates, except for 1000 points. Hence, the minimum and maximum thresholds for the extent of the inventory must be set prior to the analysis. It is concluded that the extent and format of the inventory data are also two of the influential components in the precision of the modelling.

Simple prediction scores predict good and devastating outcomes after stroke more accurately than physicians.

PubMed

Reid, John Michael; Dai, Dingwei; Delmonte, Susanna; Counsell, Carl; Phillips, Stephen J; MacLeod, Mary Joan

2017-05-01

physicians are often asked to prognosticate soon after a patient presents with stroke. This study aimed to compare two outcome prediction scores (Five Simple Variables [FSV] score and the PLAN [Preadmission comorbidities, Level of consciousness, Age, and focal Neurologic deficit]) with informal prediction by physicians. demographic and clinical variables were prospectively collected from consecutive patients hospitalised with acute ischaemic or haemorrhagic stroke (2012-13). In-person or telephone follow-up at 6 months established vital and functional status (modified Rankin score [mRS]). Area under the receiver operating curves (AUC) was used to establish prediction score performance. five hundred and seventy-five patients were included; 46% female, median age 76 years, 88% ischaemic stroke. Six months after stroke, 47% of patients had a good outcome (alive and independent, mRS 0-2) and 26% a devastating outcome (dead or severely dependent, mRS 5-6). The FSV and PLAN scores were superior to physician prediction (AUCs of 0.823-0.863 versus 0.773-0.805, P < 0.0001) for good and devastating outcomes. The FSV score was superior to the PLAN score for predicting good outcomes and vice versa for devastating outcomes (P < 0.001). Outcome prediction was more accurate for those with later presentations (>24 hours from onset). the FSV and PLAN scores are validated in this population for outcome prediction after both ischaemic and haemorrhagic stroke. The FSV score is the least complex of all developed scores and can assist outcome prediction by physicians. © The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

Rapid Prediction of Hematologic Acute Radiation Syndrome in Radiation Injury Patients Using Peripheral Blood Cell Counts.

PubMed

Port, M; Pieper, B; Knie, T; Dörr, H; Ganser, A; Graessle, D; Meineke, V; Abend, M

2017-08-01

Rapid clinical triage of radiation injury patients is essential for determining appropriate diagnostic and therapeutic interventions. We examined the utility of blood cell counts (BCCs) in the first three days postirradiation to predict clinical outcome, specifically for hematologic acute radiation syndrome (HARS). We analyzed BCC test samples from radiation accident victims (n = 135) along with their clinical outcome HARS severity scores (H1-4) using the System for Evaluation and Archiving of Radiation Accidents based on Case Histories (SEARCH) database. Data from nonirradiated individuals (H0, n = 132) were collected from an outpatient facility. We created binary categories for severity scores, i.e., 1 (H0 vs. H1-4), 2 (H0-1 vs. H2-4) and 3 (H0-2 vs. H3-4), to assess the discrimination ability of BCCs using unconditional logistic regression analysis. The test sample contained 454 BCCs from 267 individuals. We validated the discrimination ability on a second independent group comprised of 275 BCCs from 252 individuals originating from SEARCH (HARS 1-4), an outpatient facility (H0) and hospitals (e.g., leukemia patients, H4). Individuals with a score of H0 were easily separated from exposed individuals based on developing lymphopenia and granulocytosis. The separation of H0 and H1-4 became more prominent with increasing hematologic severity scores and time. On day 1, lymphocyte counts were most predictive for discriminating binary categories, followed by granulocytes and thrombocytes. For days 2 and 3, an almost complete separation was achieved when BCCs from different days were combined, supporting the measurement of sequential BCC. We found an almost complete discrimination of H0 vs. irradiated individuals during model validation (negative predictive value, NPV > 94%) for all three days, while the correct prediction of exposed individuals increased from day 1 (positive predictive value, PPV 78-89%) to day 3 (PPV > 90%). The models were unable to provide predictions for 10.9% of the test samples, because the PPVs or NPVs did not reach a 95% likelihood defined as the lower limit for a prediction. We developed a prediction model spreadsheet to provide early and prompt diagnostic predictions and therapeutic recommendations including identification of the worried well, requirement of hospitalization or development of severe hematopoietic syndrome. These results improve the provisional classification of HARS. For the final diagnosis, further procedures (sequential diagnosis, retrospective dosimetry, clinical follow-up, etc.) must be taken into account. Clinical outcome of radiation injury patients can be rapidly predicted within the first three days postirradiation using peripheral BCC.

Development and validation of a continuous measure of patient condition using the Electronic Medical Record.

PubMed

Rothman, Michael J; Rothman, Steven I; Beals, Joseph

2013-10-01

Patient condition is a key element in communication between clinicians. However, there is no generally accepted definition of patient condition that is independent of diagnosis and that spans acuity levels. We report the development and validation of a continuous measure of general patient condition that is independent of diagnosis, and that can be used for medical-surgical as well as critical care patients. A survey of Electronic Medical Record data identified common, frequently collected non-static candidate variables as the basis for a general, continuously updated patient condition score. We used a new methodology to estimate in-hospital risk associated with each of these variables. A risk function for each candidate input was computed by comparing the final pre-discharge measurements with 1-year post-discharge mortality. Step-wise logistic regression of the variables against 1-year mortality was used to determine the importance of each variable. The final set of selected variables consisted of 26 clinical measurements from four categories: nursing assessments, vital signs, laboratory results and cardiac rhythms. We then constructed a heuristic model quantifying patient condition (overall risk) by summing the single-variable risks. The model's validity was assessed against outcomes from 170,000 medical-surgical and critical care patients, using data from three US hospitals. Outcome validation across hospitals yields an area under the receiver operating characteristic curve(AUC) of ≥0.92 when separating hospice/deceased from all other discharge categories, an AUC of ≥0.93 when predicting 24-h mortality and an AUC of 0.62 when predicting 30-day readmissions. Correspondence with outcomes reflective of patient condition across the acuity spectrum indicates utility in both medical-surgical units and critical care units. The model output, which we call the Rothman Index, may provide clinicians with a longitudinal view of patient condition to help address known challenges in caregiver communication, continuity of care, and earlier detection of acuity trends. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Associations of perceived neighborhood environment on health status outcomes in persons with arthritis.

PubMed

Martin, Kathryn Remmes; Shreffler, Jack; Schoster, Britta; Callahan, Leigh F

2010-11-01

To examine the association between 4 aspects of perceived neighborhood environment (aesthetics, walkability, safety, and social cohesion) and health status outcomes in a cohort of North Carolinians with self-reported arthritis after adjustment for individual and neighborhood socioeconomic status covariates. In a telephone survey, 696 participants self-reported ≥1 types of arthritis or rheumatic conditions. Outcomes measured were physical and mental functioning (Short Form 12 health survey version 2 physical component and mental component summary [MCS]), functional disability (Health Assessment Questionnaire), and depressive symptomatology (Center for Epidemiologic Studies Depression Scale scores <16 versus ≥16). Multivariate regression and multivariate logistic regression analyses were conducted using Stata, version 11. Results from separate adjusted models indicated that measures of associations for perceived neighborhood characteristics were statistically significant (P ≤ 0.001 to P = 0.017) for each health status outcome (except walkability and MCS) after adjusting for covariates. Final adjusted models included all 4 perceived neighborhood characteristics simultaneously. A 1-point increase in perceiving worse neighborhood aesthetics predicted lower mental health (B = -1.81, P = 0.034). Individuals had increased odds of depressive symptoms if they perceived lower neighborhood safety (odds ratio [OR] 1.36, 95% confidence interval [95% CI] 1.04-1.78; P = 0.023) and lower neighborhood social cohesion (OR 1.42, 95% CI 1.03-1.96; P = 0.030). Study findings indicate that an individual's perception of neighborhood environment characteristics, especially aesthetics, safety, and social cohesion, is predictive of health outcomes among adults with self-reported arthritis, even after adjusting for key variables. Future studies interested in examining the role that community characteristics play on disability and mental health in individuals with arthritis might consider further examination of perceived neighborhood environment. Copyright © 2010 by the American College of Rheumatology.

Cerebrospinal fluid markers of neuronal and glial cell damage to monitor disease activity and predict long-term outcome in patients with autoimmune encephalitis.

PubMed

Constantinescu, R; Krýsl, D; Bergquist, F; Andrén, K; Malmeström, C; Asztély, F; Axelsson, M; Menachem, E B; Blennow, K; Rosengren, L; Zetterberg, H

2016-04-01

Clinical symptoms and long-term outcome of autoimmune encephalitis are variable. Diagnosis requires multiple investigations, and treatment strategies must be individually tailored. Better biomarkers are needed for diagnosis, to monitor disease activity and to predict long-term outcome. The value of cerebrospinal fluid (CSF) markers of neuronal [neurofilament light chain protein (NFL), and total tau protein (T-tau)] and glial cell [glial fibrillary acidic protein (GFAP)] damage in patients with autoimmune encephalitis was investigated. Demographic, clinical, magnetic resonance imaging, CSF and antibody-related data of 25 patients hospitalized for autoimmune encephalitis and followed for 1 year were retrospectively collected. Correlations between these data and consecutive CSF levels of NFL, T-tau and GFAP were investigated. Disability, assessed by the modified Rankin scale, was used for evaluation of disease activity and long-term outcome. The acute stage of autoimmune encephalitis was accompanied by high CSF levels of NFL and T-tau, whereas normal or significantly lower levels were observed after clinical improvement 1 year later. NFL and T-tau reacted in a similar way but at different speeds, with T-tau reacting faster. CSF levels of GFAP were initially moderately increased but did not change significantly later on. Final outcome (disability at 1 year) directly correlated with CSF-NFL and CSF-GFAP levels at all time-points and with CSF-T-tau at 3 ± 1 months. This correlation remained significant after age adjustment for CSF-NFL and T-tau but not for GFAP. In autoimmune encephalitis, CSF levels of neuronal and glial cell damage markers appear to reflect disease activity and long-term disability. © 2016 EAN.

Stochastic satisficing account of confidence in uncertain value-based decisions

PubMed Central

Bahrami, Bahador; Keramati, Mehdi

2018-01-01

Every day we make choices under uncertainty; choosing what route to work or which queue in a supermarket to take, for example. It is unclear how outcome variance, e.g. uncertainty about waiting time in a queue, affects decisions and confidence when outcome is stochastic and continuous. How does one evaluate and choose between an option with unreliable but high expected reward, and an option with more certain but lower expected reward? Here we used an experimental design where two choices’ payoffs took continuous values, to examine the effect of outcome variance on decision and confidence. We found that our participants’ probability of choosing the good (high expected reward) option decreased when the good or the bad options’ payoffs were more variable. Their confidence ratings were affected by outcome variability, but only when choosing the good option. Unlike perceptual detection tasks, confidence ratings correlated only weakly with decisions’ time, but correlated with the consistency of trial-by-trial choices. Inspired by the satisficing heuristic, we propose a “stochastic satisficing” (SSAT) model for evaluating options with continuous uncertain outcomes. In this model, options are evaluated by their probability of exceeding an acceptability threshold, and confidence reports scale with the chosen option’s thus-defined satisficing probability. Participants’ decisions were best explained by an expected reward model, while the SSAT model provided the best prediction of decision confidence. We further tested and verified the predictions of this model in a second experiment. Our model and experimental results generalize the models of metacognition from perceptual detection tasks to continuous-value based decisions. Finally, we discuss how the stochastic satisficing account of decision confidence serves psychological and social purposes associated with the evaluation, communication and justification of decision-making. PMID:29621325

Prognostic model for psychological outcomes in ambulatory surgery patients: A prospective study using a structural equation modeling framework.

PubMed

Mijderwijk, Hendrik-Jan; Stolker, Robert Jan; Duivenvoorden, Hugo J; Klimek, Markus; Steyerberg, Ewout W

2018-01-01

Surgical procedures are increasingly carried out in a day-case setting. Along with this increase, psychological outcomes have become prominent. The objective was to evaluate prospectively the prognostic effects of sociodemographic, medical, and psychological variables assessed before day-case surgery on psychological outcomes after surgery. The study was carried out between October 2010 and September 2011. We analyzed 398 mixed patients, from a randomized controlled trial, undergoing day-case surgery at a university medical center. Structural equation modeling was used to jointly study presurgical prognostic variables relating to sociodemographics (age, sex, nationality, marital status, having children, religion, educational level, employment), medical status (BMI, heart rate), and psychological status associated with anxiety (State-Trait Anxiety Inventory (STAI), Hospital Anxiety and Depression Scale (HADS-A)), fatigue (Multidimensional Fatigue Inventory (MFI)), aggression (State-Trait Anger Scale (STAS)), depressive moods (HADS-D), self-esteem, and self-efficacy. We studied psychological outcomes on day 7 after surgery, including anxiety, fatigue, depressive moods, and aggression regulation. The final prognostic model comprised the following variables: anxiety (STAI, HADS-A), fatigue (MFI), depression (HADS-D), aggression (STAS), self-efficacy, sex, and having children. The corresponding psychological variables as assessed at baseline were prominent (i.e. standardized regression coefficients ≥ 0.20), with STAI-Trait score being the strongest predictor overall. STAI-State (adjusted R2 = 0.44), STAI-Trait (0.66), HADS-A (0.45) and STAS-Trait (0.54) were best predicted. We provide a prognostic model that adequately predicts multiple postoperative outcomes in day-case surgery. Consequently, this enables timely identification of vulnerable patients who may require additional medical or psychological preventive treatment or-in a worst-case scenario-could be unselected for day-case surgery.

Risk of mortality after spinal cord injury: relationship with social support, education, and income.

PubMed

Krause, J S; Carter, R E

2009-08-01

Prospective cohort study. To identify the association of social support and socioeconomic factors with risk of early mortality among persons with spinal cord injury. Participants were identified from a large specialty hospital in the Southeastern United States. Data were collected by mailed survey, and mortality status was ascertained approximately 8 years later. The outcome was time from survey to mortality or censoring. Mortality status was determined using the National Death Index and the Social Security Death Index. There were 224 observed deaths (16.2%) in the full sample (n=1386). Because of missing data, the number of deaths used in the final analysis was 188 (out of 1249 participants). Cox proportional hazards modeling was used to build a comprehensive predictive model. After controlling for biographic and injury-related factors, two of four environmental predictors were retained in the final model including low income and general social support. Years of education and the upsets scale, another aspect of social support, were not retained in the final model. Inclusion of these variables resulted in only modest improvement in the prediction of survival compared with biographic and injury variables alone, as the pseudo-R(2) increased from 0.121 to 0.134 and the concordance from 0.730 to 0.751. Environmental factors are important predictors of mortality after spinal cord injury.

Final Technical Report for Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models, DE-FG02-07ER64429

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smyth, Padhraic

2013-07-22

This is the final report for a DOE-funded research project describing the outcome of research on non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. The main results consist of extensive development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies ofmore » climate variability in terms of the dynamics of atmospheric flow regimes.« less

Pre-clinical longitudinal monitoring of hemodynamic response to anti-vascular chemotherapy by hybrid diffuse optics.

PubMed

Farzam, Parisa; Johansson, Johannes; Mireles, Miguel; Jiménez-Valerio, Gabriela; Martínez-Lozano, Mar; Choe, Regine; Casanovas, Oriol; Durduran, Turgut

2017-05-01

The longitudinal effect of an anti-vascular endothelial growth factor receptor 2 (VEGFR-2) antibody (DC 101) therapy on a xenografted renal cell carcinoma (RCC) mouse model was monitored using hybrid diffuse optics. Two groups of immunosuppressed male nude mice (seven treated, seven controls) were measured. Tumor microvascular blood flow, total hemoglobin concentration and blood oxygenation were investigated as potential biomarkers for the monitoring of the therapy effect twice a week and were related to the final treatment outcome. These hemodynamic biomarkers have shown a clear differentiation between two groups by day four. Moreover, we have observed that pre-treatment values and early changes in hemodynamics are highly correlated with the therapeutic outcome demonstrating the potential of diffuse optics to predict the therapy response at an early time point.

Support Vector Machine-Based Prediction of Local Tumor Control After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klement, Rainer J., E-mail: rainer_klement@gmx.de; Department of Radiotherapy and Radiation Oncology, Leopoldina Hospital, Schweinfurt; Allgäuer, Michael

2014-03-01

Background: Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. Methods and Materials: We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performancemore » by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Results: Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED{sub ISO}) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED{sub ISO} and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED{sub ISO}, age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. Conclusions: These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are expected through a nonlinear combination of multiple features, eventually helping in the task of personalized treatment planning.« less

Support vector machine-based prediction of local tumor control after stereotactic body radiation therapy for early-stage non-small cell lung cancer.

PubMed

Klement, Rainer J; Allgäuer, Michael; Appold, Steffen; Dieckmann, Karin; Ernst, Iris; Ganswindt, Ute; Holy, Richard; Nestle, Ursula; Nevinny-Stickel, Meinhard; Semrau, Sabine; Sterzing, Florian; Wittig, Andrea; Andratschke, Nicolaus; Guckenberger, Matthias

2014-03-01

Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performance by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED(ISO)) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED(ISO) and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED(ISO), age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are expected through a nonlinear combination of multiple features, eventually helping in the task of personalized treatment planning. Copyright © 2014 Elsevier Inc. All rights reserved.

Action-outcome learning and prediction shape the window of simultaneity of audiovisual outcomes.

PubMed

Desantis, Andrea; Haggard, Patrick

2016-08-01

To form a coherent representation of the objects around us, the brain must group the different sensory features composing these objects. Here, we investigated whether actions contribute in this grouping process. In particular, we assessed whether action-outcome learning and prediction contribute to audiovisual temporal binding. Participants were presented with two audiovisual pairs: one pair was triggered by a left action, and the other by a right action. In a later test phase, the audio and visual components of these pairs were presented at different onset times. Participants judged whether they were simultaneous or not. To assess the role of action-outcome prediction on audiovisual simultaneity, each action triggered either the same audiovisual pair as in the learning phase ('predicted' pair), or the pair that had previously been associated with the other action ('unpredicted' pair). We found the time window within which auditory and visual events appeared simultaneous increased for predicted compared to unpredicted pairs. However, no change in audiovisual simultaneity was observed when audiovisual pairs followed visual cues, rather than voluntary actions. This suggests that only action-outcome learning promotes temporal grouping of audio and visual effects. In a second experiment we observed that changes in audiovisual simultaneity do not only depend on our ability to predict what outcomes our actions generate, but also on learning the delay between the action and the multisensory outcome. When participants learned that the delay between action and audiovisual pair was variable, the window of audiovisual simultaneity for predicted pairs increased, relative to a fixed action-outcome pair delay. This suggests that participants learn action-based predictions of audiovisual outcome, and adapt their temporal perception of outcome events based on such predictions. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Predicting cytotoxicity from heterogeneous data sources with Bayesian learning.

PubMed

Langdon, Sarah R; Mulgrew, Joanna; Paolini, Gaia V; van Hoorn, Willem P

2010-12-09

We collected data from over 80 different cytotoxicity assays from Pfizer in-house work as well as from public sources and investigated the feasibility of using these datasets, which come from a variety of assay formats (having for instance different measured endpoints, incubation times and cell types) to derive a general cytotoxicity model. Our main aim was to derive a computational model based on this data that can highlight potentially cytotoxic series early in the drug discovery process. We developed Bayesian models for each assay using Scitegic FCFP_6 fingerprints together with the default physical property descriptors. Pairs of assays that are mutually predictive were identified by calculating the ROC score of the model derived from one predicting the experimental outcome of the other, and vice versa. The prediction pairs were visualised in a network where nodes are assays and edges are drawn for ROC scores >0.60 in both directions. We observed that, if assay pairs (A, B) and (B, C) were mutually predictive, this was often not the case for the pair (A, C). The results from 48 assays connected to each other were merged in one training set of 145590 compounds and a general cytotoxicity model was derived. The model has been cross-validated as well as being validated with a set of 89 FDA approved drug compounds. We have generated a predictive model for general cytotoxicity which could speed up the drug discovery process in multiple ways. Firstly, this analysis has shown that the outcomes of different assay formats can be mutually predictive, thus removing the need to submit a potentially toxic compound to multiple assays. Furthermore, this analysis enables selection of (a) the easiest-to-run assay as corporate standard, or (b) the most descriptive panel of assays by including assays whose outcomes are not mutually predictive. The model is no replacement for a cytotoxicity assay but opens the opportunity to be more selective about which compounds are to be submitted to it. On a more mundane level, having data from more than 80 assays in one dataset answers, for the first time, the question - "what are the known cytotoxic compounds from the Pfizer compound collection?" Finally, having a predictive cytotoxicity model will assist the design of new compounds with a desired cytotoxicity profile, since comparison of the model output with data from an in vitro safety/toxicology assay suggests one is predictive of the other.

Limitations of ultrasonography for diagnosing white matter damage in preterm infants

PubMed Central

Debillon, T; N'Guyen, S; Muet, A; Quere, M; Moussaly, F; Roze, J

2003-01-01

Objectives: To compare the accuracy of ultrasonography (US) and magnetic resonance imaging (MRI) in diagnosing white matter abnormalities in preterm infants and to determine the specific indications for MRI. Design: Prospective cohort study. Setting: A neonatal intensive care unit in France. Patients: All preterm infants (≤ 33 weeks gestation) without severe respiratory distress syndrome precluding MRI. Main outcome measures: US and MRI performed contemporaneously during the third postnatal week were analysed by an independent observer. The findings were compared with those of a term MRI scan, the results of which were taken as the final diagnosis. Statistical analysis was performed to determine which early imaging study best predicted the term MRI findings. Results: The early US and MRI findings (79 infants) correlated closely for severe lesions (cystic periventricular leucomalacia and parenchymal infarction; κ coefficient = 0.86) but not for moderate lesions (non-cystic leucomalacia and parenchymal punctate haemorrhages; κ = 0.62). Overall, early MRI findings predicted late MRI findings in 98% of patients (95% confidence interval (CI) 89.5 to 99.9) compared with only 68% for early US (95% CI 52.1 to 79.2). Conclusions: US is highly effective in detecting severe lesions of the white matter in preterm infants, but MRI seems to be necessary for the diagnosis of less severe damage. MRI performed at about the third week of life is highly predictive of the final diagnosis at term. PMID:12819157

The effects of autonomy-supportive coaching, need satisfaction, and self-perceptions on initiative and identity in youth swimmers.

PubMed

Coatsworth, J Douglas; Conroy, David E

2009-03-01

This study tested a sequential process model linking youth sport coaching climates (perceived coach behaviors and perceived need satisfaction) to youth self-perceptions (perceived competence and global self-esteem) and youth development outcomes (initiative, identity reflection, identity exploration). A sample of 119 youth between the ages of 10 and 18 who participated in a community-directed summer swim league completed questionnaires over the course of the 7-week season. Results indicated that coaches' autonomy support, particularly via process-focused praise, predicted youth competence need satisfaction and relatedness need satisfaction in the coaching relationship. Youth competence need satisfaction predicted self-esteem indirectly via perceived competence. Finally, self-esteem predicted identity reflection, and perceived competence predicted both identity reflection and initiative. Effects of age, sex, and perceptions of direct contact with the coach were not significant. Findings suggest that the quality of the coaching climate is an important predictor of the developmental benefits of sport participation and that one pathway by which the coaching climate has its effect on initiative and identity reflection is through developing youth self-perceptions.

Can outcome of pancreatic pseudocysts be predicted? Proposal for a new scoring system.

PubMed

Şenol, Kazım; Akgül, Özgür; Gündoğdu, Salih Burak; Aydoğan, İhsan; Tez, Mesut; Coşkun, Faruk; Tihan, Deniz Necdet

2016-03-01

The spontaneous resolution rate of pancreatic pseudocysts (PPs) is 86%, and the serious complication rate is 3-9%. The aim of the present study was to develop a scoring system that would predict spontaneous resolution of PPs. Medical records of 70 patients were retrospectively reviewed. Two patients were excluded. Demographic data and laboratory measurements were obtained from patient records. Mean age of the 68 patients included was 56.6 years. Female:male ratio was 1.34:1. Causes of pancreatitis were stones (48.5%), alcohol consumption (26.5%), and unknown etiology (25%). Mean size of PP was 71 mm. Pseudocysts disappeared in 32 patients (47.1%). With univariate analysis, serum direct bilirubin level (>0.95 mg/dL), cyst carcinoembryonic antigen (CEA) level (>1.5), and cyst diameter (>55 mm) were found to be significantly different between patients with and without spontaneous resolution. In multivariate analysis, these variables were statistically significant. Scores were calculated with points assigned to each variable. Final scores predicted spontaneous resolution in approximately 80% of patients. The scoring system developed to predict resolution of PPs is simple and useful, but requires validation.

The Effects of Autonomy-supportive Coaching, Need Satisfaction and Self-Perceptions on Initiative and Identity in Youth Swimmers

PubMed Central

Coatsworth, J. Douglas; Conroy, David E.

2015-01-01

This study tested a sequential process model linking youth sport coaching climates (perceived coach behaviors and perceived need satisfaction) to youth self-perceptions (perceived competence and global self-esteem) and youth development outcomes (initiative, identity reflection, identity exploration). A sample of 119 youth between the ages 10–18 who participated in a community-directed summer swim league completed questionnaires over the course of the seven-week season. Results indicated that coaches’ autonomy support, particularly via process-focused praise, predicted youth competence and relatedness need satisfaction in the coaching relationship. Youth competence need satisfaction predicted self-esteem indirectly via perceived competence. Finally, self-esteem predicted identity reflection and perceived competence predicted both identity reflection and initiative. Effects of age, sex, and perceptions of direct contact with the coach were not significant. Findings suggest that the quality of the coaching climate is an important predictor of the developmental benefits of sport participation and that one pathway by which the coaching climate has its effect on initiative and identity reflection is through developing youth self-perceptions. PMID:19271821

Differentiating progress in a clinical group of fibromyalgia patients during and following a multicomponent treatment program.

PubMed

Van Den Houte, Maaike; Luyckx, Koen; Van Oudenhove, Lukas; Bogaerts, Katleen; Van Diest, Ilse; De Bie, Jozef; Van den Bergh, Omer

2017-07-01

Treatments including multiple nonpharmacological components have beneficial effects on the key symptoms of fibromyalgia, although effects are limited and often do not persist. In this study, we examined different patterns of clinical progress and the dynamic interplay between predictors and outcomes over time. Fibromyalgia patients (N=153; 135 women) followed a multidisciplinary group program spanning 12weeks, aimed at "regaining control over daily functioning". Anxiety, depression, pain coping and kinesiophobia were used as predictor variables. Outcome variables were pain severity, pain-related disability, physical functioning and functional interference. All variables were assessed at 3 moments: on the first and last day of treatment, and 12weeks after the last day of treatment. Overall treatment effects were analyzed using mixed model analyses. Latent class growth analysis identifying different treatment trajectory classes was used to investigate individual differences in treatment effects. Finally, cross-lagged structural equation models were used to investigate the dynamic interplay between predictors and outcomes over time. Only a fourth to a third of the total group showed improvement on the outcome variables. These patients had lower baseline anxiety, depression and kinesiophobia, and improved more on anxiety, depression and kinesiophobia. Physical well-being had a stronger effect on anxiety and depression than vice versa. Physical functioning predicted relative changes in kinesiophobia, while kinesiophobia predicted relative changes in pain-related disability. The results emphasize the importance of tailoring treatments to individual needs in order to improve overall effectiveness of treatment programs. Copyright © 2017. Published by Elsevier Inc.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other's Actions by Humans.

PubMed

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2017-01-01

The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants' ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert's abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert's self-estimation is explained only by considering a change in the individual's forward model, showing that an improvement in an expert's ability to predict outcomes of observed actions affects the individual's forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions.

Development and Validation of a Prediction Model for Pain and Functional Outcomes After Lumbar Spine Surgery.

PubMed

Khor, Sara; Lavallee, Danielle; Cizik, Amy M; Bellabarba, Carlo; Chapman, Jens R; Howe, Christopher R; Lu, Dawei; Mohit, A Alex; Oskouian, Rod J; Roh, Jeffrey R; Shonnard, Neal; Dagal, Armagan; Flum, David R

2018-03-07

Functional impairment and pain are common indications for the initiation of lumbar spine surgery, but information about expected improvement in these patient-reported outcome (PRO) domains is not readily available to most patients and clinicians considering this type of surgery. To assess population-level PRO response after lumbar spine surgery, and develop/validate a prediction tool for PRO improvement. This statewide multicenter cohort was based at 15 Washington state hospitals representing approximately 75% of the state's spine fusion procedures. The Spine Surgical Care and Outcomes Assessment Program and the survey center at the Comparative Effectiveness Translational Network prospectively collected clinical and PRO data from adult candidates for lumbar surgery, preoperatively and postoperatively, between 2012 and 2016. Prediction models were derived for PRO improvement 1 year after lumbar fusion surgeries on a random sample of 85% of the data and were validated in the remaining 15%. Surgical candidates from 2012 through 2015 were included; follow-up surveying continued until December 31, 2016, and data analysis was completed from July 2016 to April 2017. Functional improvement, defined as a reduction in Oswestry Disability Index score of 15 points or more; and back pain and leg pain improvement, defined a reduction in Numeric Rating Scale score of 2 points or more. A total of 1965 adult lumbar surgical candidates (mean [SD] age, 61.3 [12.5] years; 944 [59.6%] female) completed baseline surveys before surgery and at least 1 postoperative follow-up survey within 3 years. Of these, 1583 (80.6%) underwent elective lumbar fusion procedures; 1223 (77.3%) had stenosis, and 1033 (65.3%) had spondylolisthesis. Twelve-month follow-up participation rates for each outcome were between 66% and 70%. Improvements were reported in function, back pain, and leg pain at 12 months by 306 of 528 surgical patients (58.0%), 616 of 899 patients (68.5%), and 355 of 464 patients (76.5%), respectively, whose baseline scores indicated moderate to severe symptoms. Among nonoperative patients, 35 (43.8%), 47 (53.4%), and 53 (63.9%) reported improvements in function, back pain, and leg pain, respectively. Demographic and clinical characteristics included in the final prediction models were age, sex, race, insurance status, American Society of Anesthesiologists score, smoking status, diagnoses, prior surgery, prescription opioid use, asthma, and baseline PRO scores. The models had good predictive performance in the validation cohort (concordance statistic, 0.66-0.79) and were incorporated into a patient-facing, web-based interactive tool (https://becertain.shinyapps.io/lumbar_fusion_calculator). The PRO response prediction tool, informed by population-level data, explained most of the variability in pain reduction and functional improvement after surgery. Giving patients accurate information about their likelihood of outcomes may be a helpful component in surgery decision making.

Predictive value of clinical scoring and simplified gait analysis for acetabulum fractures.

PubMed

Braun, Benedikt J; Wrona, Julian; Veith, Nils T; Rollman, Mika; Orth, Marcel; Herath, Steven C; Holstein, Jörg H; Pohlemann, Tim

2016-12-01

Fractures of the acetabulum show a high, long-term complication rate. The aim of the present study was to determine the predictive value of clinical scoring and standardized, simplified gait analysis on the outcome after these fractures. Forty-one patients with acetabular fractures treated between 2008 and 2013 and available, standardized video recorded aftercare were identified from a prospective database. A visual gait score was used to determine the patients walking abilities 6-m postoperatively. Clinical (Merle d'Aubigne and Postel score, visual analogue scale pain, EQ5d) and radiological scoring (Kellgren-Lawrence score, postoperative computed tomography, and Matta classification) were used to perform correlation and multivariate regression analysis. The average patient age was 48 y (range, 15-82 y), six female patients were included in the study. Mean follow-up was 1.6 y (range, 1-2 y). Moderate correlation between the gait score and outcome (versus EQ5d: r s  = 0.477; versus Merle d'Aubigne: r s  = 0.444; versus Kellgren-Lawrence: r s  = -0.533), as well as high correlation between the Merle d'Aubigne score and outcome were seen (versus EQ5d: r s  = 0.575; versus Merle d'Aubigne: r s  = 0.776; versus Kellgren-Lawrence: r s  = -0.419). Using a multivariate regression model, the 6 m gait score (B = -0.299; P < 0.05) and early osteoarthritis development (B = 1.026; P < 0.05) were determined as predictors of final osteoarthritis. A good fit of the regression model was seen (R 2  = 904). Easy and available clinical scoring (gait score/Merle d'Aubigne) can predict short-term radiological and functional outcome after acetabular fractures with sufficient accuracy. Decisions on further treatment and interventions could be based on simplified gait analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies.

PubMed

McManus, I C; Dewberry, Chris; Nicholson, Sandra; Dowell, Jonathan S; Woolf, Katherine; Potts, Henry W W

2013-11-14

Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, 'dark matter' and 'dark energy' are posited to balance various theoretical equations, so medical student selection must also have its 'dark variance', whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

PubMed Central

2013-01-01

Background Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Methods Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Results Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Conclusions Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, ‘dark matter’ and ‘dark energy’ are posited to balance various theoretical equations, so medical student selection must also have its ‘dark variance’, whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills. PMID:24229353

On the design of learning outcomes for the undergraduate engineer's final year project

NASA Astrophysics Data System (ADS)

Thambyah, Ashvin

2011-03-01

The course for the final year project for engineering students, because of its strongly research-based, open-ended format, tends to not have well defined learning outcomes, which are also not aligned with any accepted pedagogical philosophy or learning technology. To address this problem, the revised Bloom's taxonomy table of Anderson and Krathwohl (2001) is utilised, as suggested previously by Lee and Lai (2007), to design new learning outcomes for the final year project course in engineering education. Based on the expectations of the engineering graduate, and integrating these graduate expectations into the six cognitive processes and four knowledge dimensions of the taxonomy table, 24 learning outcomes have been designed. It is proposed that these 24 learning outcomes be utilised as a suitable working template to inspire more critical evaluation of what is expected to be learnt by engineering students undertaking final year research or capstone projects.

Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

PubMed

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. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A critical appraisal of advances in the diagnosis of diverticular disease.

PubMed

Tursi, Antonio

2018-06-19

Diverticulosis of the colon is a common condition, and about one-fourth of those people develop symptoms, which is called 'diverticular disease' (DD). Since there are still some concerns about the diagnosis of DD, the aim of this review was to analyze current and evolving advances in its diagnosis. Area covered: Analysis of clinical, radiology, laboratory, and endoscopic tools to pose a correct diagnosis of DD was performed according to current PubMed literature. Expert commentary: A combination of clinical characteristic of the abdominal pain and fecal calprotectin expression may help to differentiate between symptomatic uncomplicated diverticular disease and irritable bowel syndrome. Abdominal computerized tomography (CT) scan is still the gold standard in diagnosing acute diverticulitis and its complications. CT-colonography may be useful as a predicting tool on the outcome of the disease. Diverticular Inflammation and Complications Assessment (DICA) endoscopic classification shows a significant relationship between severity of DICA score inflammatory indexes, as well as with severity of abdominal pain. Moreover, it seems to be predictive of the outcome of the disease in terms of acute diverticulitis occurrence/recurrence and surgery occurrence. Finally, preliminary data found intestinal microbiota analysis is a promising tool in diagnosing and monitoring this disease.

The role of colonoscopy in managing diverticular disease of the colon.

PubMed

Tursi, Antonio

2015-03-01

Diverticulosis of the colon is frequently found on routine colonoscopy, and the incidence of diverticular disease and its complications appears to be increasing. The role of colonoscopy in managing this disease is still controversial. Colonoscopy plays a key role in managing diverticular bleeding. Several techniques have been effectively used in this field, but band ligation seems to be the best in preventing rebleeding. Colonoscopy is also effective in posing a correct differential diagnosis with other forms of chronic colitis involving colon harbouring diverticula (in particular with Crohn's disease or Segmental Colitis Associated with Diverticulosis). The role of colonoscopy to confirm diagnosis of uncomplicated diverticulitis is still under debate, since the risk of advanced colonic neoplasia in patients admitted for acute uncomplicated diverticulitis is not increased as compared to the average-risk population. On the contrary, colonoscopy is mandatory if patients complain of persistent symptoms or after resolution of an episode of complicated diverticulitis. Finally, a recent endoscopic classification, called Diverticular Inflammation and Complications Assessment (DICA), has been developed and validated. This classification seems to be a promising tool for predicting the outcome of the colon harboring diverticula, but further, prospective studies have to confirm its predictive role on the outcome of the disease.

RFA Guardian: Comprehensive Simulation of Radiofrequency Ablation Treatment of Liver Tumors.

PubMed

Voglreiter, Philip; Mariappan, Panchatcharam; Pollari, Mika; Flanagan, Ronan; Blanco Sequeiros, Roberto; Portugaller, Rupert Horst; Fütterer, Jurgen; Schmalstieg, Dieter; Kolesnik, Marina; Moche, Michael

2018-01-15

The RFA Guardian is a comprehensive application for high-performance patient-specific simulation of radiofrequency ablation of liver tumors. We address a wide range of usage scenarios. These include pre-interventional planning, sampling of the parameter space for uncertainty estimation, treatment evaluation and, in the worst case, failure analysis. The RFA Guardian is the first of its kind that exhibits sufficient performance for simulating treatment outcomes during the intervention. We achieve this by combining a large number of high-performance image processing, biomechanical simulation and visualization techniques into a generalized technical workflow. Further, we wrap the feature set into a single, integrated application, which exploits all available resources of standard consumer hardware, including massively parallel computing on graphics processing units. This allows us to predict or reproduce treatment outcomes on a single personal computer with high computational performance and high accuracy. The resulting low demand for infrastructure enables easy and cost-efficient integration into the clinical routine. We present a number of evaluation cases from the clinical practice where users performed the whole technical workflow from patient-specific modeling to final validation and highlight the opportunities arising from our fast, accurate prediction techniques.

Screening of the aerodynamic and biophysical properties of barley malt

NASA Astrophysics Data System (ADS)

Ghodsvali, Alireza; Farzaneh, Vahid; Bakhshabadi, Hamid; Zare, Zahra; Karami, Zahra; Mokhtarian, Mohsen; Carvalho, Isabel. S.

2016-10-01

An understanding of the aerodynamic and biophysical properties of barley malt is necessary for the appropriate design of equipment for the handling, shipping, dehydration, grading, sorting and warehousing of this strategic crop. Malting is a complex biotechnological process that includes steeping; germination and finally, the dehydration of cereal grains under controlled temperature and humidity conditions. In this investigation, the biophysical properties of barley malt were predicted using two models of artificial neural networks as well as response surface methodology. Stepping time and germination time were selected as the independent variables and 1 000 kernel weight, kernel density and terminal velocity were selected as the dependent variables (responses). The obtained outcomes showed that the artificial neural network model, with a logarithmic sigmoid activation function, presents more precise results than the response surface model in the prediction of the aerodynamic and biophysical properties of produced barley malt. This model presented the best result with 8 nodes in the hidden layer and significant correlation coefficient values of 0.783, 0.767 and 0.991 were obtained for responses one thousand kernel weight, kernel density, and terminal velocity, respectively. The outcomes indicated that this novel technique could be successfully applied in quantitative and qualitative monitoring within the malting process.

Seasonal resource value and male size influence male aggressive interactions in the leaf footed cactus bug, Narnia femorata.

PubMed

Nolen, Zachary J; Allen, Pablo E; Miller, Christine W

2017-05-01

In animal contests, resource value (the quality of a given resource) and resource holding potential (a male's absolute fighting ability) are two important factors determining the level of engagement and outcome of contests. Few studies have tested these factors simultaneously. Here, we investigated whether natural, seasonal differences in cactus phenology (fruit quality) influence interactions between males in the leaf-footed cactus bug, Narnia femorata (Hemiptera: Coreidae). We also considered whether males were more likely to interact when they were similar in size, as predicted by theory. Finally, we examined if male size relative to the size of an opponent predicted competitive success. We found that males have more interactions on cactus with high value ripe fruit, as we predicted. Further, we found that males that were closer in size were more likely to interact, and larger males were more likely to become dominant. Copyright © 2017 Elsevier B.V. All rights reserved.

Connecting Athletes’ Self-Perceptions and Metaperceptions of Competence: a Structural Equation Modeling Approach

PubMed Central

Cecchini, Jose A.; Fernández-Rio, Javier; Méndez-Giménez, Antonio

2015-01-01

This study explored the relationships between athletes’ competence self-perceptions and metaperceptions. Two hundred and fifty one student-athletes (14.26 ± 1.89 years), members of twenty different teams (basketball, soccer) completed a questionnaire which included the Perception of Success Questionnaire, the Competence subscale of the Intrinsic Motivation Inventory, and modified versions of both questionnaires to assess athletes’ metaperceptions. Structural equation modelling analysis revealed that athletes’ task and ego metaperceptions positively predicted task and ego self-perceptions, respectively. Competence metaperceptions were strong predictors of competence self-perceptions, confirming the atypical metaperception formation in outcome-dependent contexts such as sport. Task and ego metaperceptions positively predicted athletes’ competence metaperceptions. How coaches value their athletes’ competence is more influential on what the athletes think of themselves than their own self-perceptions. Athletes’ ego and task metaperceptions influenced their competence metaperceptions (how coaches rate their competence). Therefore, athletes build their competence metaperceptions using all information available from their coaches. Finally, only task-self perfections positively predicted athletes’ competence self-perceptions. PMID:26240662

Comparison of classification methods for voxel-based prediction of acute ischemic stroke outcome following intra-arterial intervention

NASA Astrophysics Data System (ADS)

Winder, Anthony J.; Siemonsen, Susanne; Flottmann, Fabian; Fiehler, Jens; Forkert, Nils D.

2017-03-01

Voxel-based tissue outcome prediction in acute ischemic stroke patients is highly relevant for both clinical routine and research. Previous research has shown that features extracted from baseline multi-parametric MRI datasets have a high predictive value and can be used for the training of classifiers, which can generate tissue outcome predictions for both intravenous and conservative treatments. However, with the recent advent and popularization of intra-arterial thrombectomy treatment, novel research specifically addressing the utility of predictive classi- fiers for thrombectomy intervention is necessary for a holistic understanding of current stroke treatment options. The aim of this work was to develop three clinically viable tissue outcome prediction models using approximate nearest-neighbor, generalized linear model, and random decision forest approaches and to evaluate the accuracy of predicting tissue outcome after intra-arterial treatment. Therefore, the three machine learning models were trained, evaluated, and compared using datasets of 42 acute ischemic stroke patients treated with intra-arterial thrombectomy. Classifier training utilized eight voxel-based features extracted from baseline MRI datasets and five global features. Evaluation of classifier-based predictions was performed via comparison to the known tissue outcome, which was determined in follow-up imaging, using the Dice coefficient and leave-on-patient-out cross validation. The random decision forest prediction model led to the best tissue outcome predictions with a mean Dice coefficient of 0.37. The approximate nearest-neighbor and generalized linear model performed equally suboptimally with average Dice coefficients of 0.28 and 0.27 respectively, suggesting that both non-linearity and machine learning are desirable properties of a classifier well-suited to the intra-arterial tissue outcome prediction problem.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Evaluation of anatomic and morphologic nomogram to predict malignant and high-grade disease in a cohort of patients with small renal masses.

PubMed

Bagrodia, Aditya; Harrow, Brian; Liu, Zhuo-Wei; Olweny, Ephrem O; Faddegon, Stephen; Yin, Gang; Tan, Yung Khan; Han, Woong Kyu; Lotan, Yair; Margulis, Vitaly; Cadeddu, Jeffrey A

2014-01-01

To evaluate a nomogram using the RENAL Nephrometry Score (RENAL-NS) that was developed to characterize masses as benign vs. malignant and high vs. low grade in our patients with small renal masses treated with partial nephrectomy (PN). The nomogram was previously developed and validated in patients with widely variable tumor sizes. Retrospective review of PN performed between 1/2003 and 7/2011. Imaging was reviewed by a urologic surgeon for RENAL-NS. Final pathology was used to classify tumors as benign or malignant and low (I/II) or high (III/IV) Fuhrman grade. Patient age, gender, and RENAL score were entered into the nomogram described by Kutikov et al. to determine probabilities of cancer and high-grade disease. Area under the curve was determined to assess agreement between observed and expected outcomes for prediction of benign vs. malignant disease and for prediction of high- vs. low-grade or benign disease. A total of 250 patients with 252 masses underwent PN during the study period; 179/250 (71.6%) had preoperative imaging available. RENAL-NS was assigned to 181 masses. Twenty-two percent of tumors were benign. Eighteen percent of tumors were high grade. Area under the curve was 0.648 for predicting benign vs. malignant disease and 0.955 for predicting low-grade or benign vs. high-grade disease. The RENAL-NS score nomogram by Kutikov does not discriminate well between benign and malignant disease for small renal masses. The nomogram may potentially be useful in identifying high-grade tumors. Further validation is required where the nomogram probability and final pathologic specimen are available. Copyright © 2014 Elsevier Inc. All rights reserved.

Risk Matrix for Prediction of Disease Progression in a Referral Cohort of Patients with Crohn's Disease.

PubMed

Lakatos, Peter L; Sipeki, Nora; Kovacs, Gyorgy; Palyu, Eszter; Norman, Gary L; Shums, Zakera; Golovics, Petra A; Lovasz, Barbara D; Antal-Szalmas, Peter; Papp, Maria

2015-10-01

Early identification of patients with Crohn's disease (CD) at risk of subsequent complications is essential for adapting the treatment strategy. We aimed to develop a prediction model including clinical and serological markers for assessing the probability of developing advanced disease in a prospective referral CD cohort. Two hundred and seventy-one consecutive CD patients (42.4% males, median follow-up 108 months) were included and followed up prospectively. Anti-Saccharomyces cerevisiae antibodies (ASCA IgA/IgG) were determined by enzyme-linked immunosorbent assay. The final analysis was limited to patients with inflammatory disease behaviour at diagnosis. The final definition of advanced disease outcome was having intestinal resection or disease behaviour progression. Antibody (ASCA IgA and/or IgG) status, disease location and need for early azathioprine were included in a 3-, 5- and 7-year prediction matrix. The probability of advanced disease after 5 years varied from 6.2 to 55% depending on the combination of predictors. Similar findings were obtained in Kaplan-Meier analysis; the combination of ASCA, location and early use of azathioprine was associated with the probability of developing advanced disease (p < 0.001, log rank test). Our prediction models identified substantial differences in the probability of developing advanced disease in the early disease course of CD. Markers identified in this referral cohort were different from those previously published in a population-based cohort, suggesting that different prediction models should be used in the referral setting. Copyright © 2015 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

BICD1 expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas

PubMed Central

Huang, Shang-Pen; Chang, Yu-Chan; Low, Qie Hua; Wu, Alexander T.H.; Chen, Chi-Long; Lin, Yuan-Feng; Hsiao, Michael

2017-01-01

There is variation in the survival and therapeutic outcome of patients with glioblastomas (GBMs). Therapy resistance is an important challenge in the treatment of GBM patients. The aim of this study was to identify Temozolomide (TMZ) related genes and confirm their clinical relevance. The TMZ-related genes were discovered by analysis of the gene-expression profiling in our cell-based microarray. Their clinical relevance was verified by in silico meta-analysis of the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. Our results demonstrated that BICD1 expression could predict both prognosis and response to therapy in GBM patients. First, high BICD1 expression was correlated with poor prognosis in the TCGA GBM cohort (n=523) and in the CGGA glioma cohort (n=220). Second, high BICD1 expression predicted poor outcome in patients with TMZ treatment (n=301) and radiation therapy (n=405). Third, multivariable Cox regression analysis confirmed BICD1 expression as an independent factor affecting the prognosis and therapeutic response of TMZ and radiation in GBM patients. Additionally, age, MGMT and BICD1 expression were combinedly utilized to stratify GBM patients into more distinct risk groups, which may provide better outcome assessment. Finally, we observed a strong correlation between BICD1 expression and epithelial-mesenchymal transition (EMT) in GBMs, and proposed a possible mechanism of BICD1-associated survival or therapeutic resistance in GBMs accordingly. In conclusion, our study suggests that high BICD1 expression may result in worse prognosis and could be a predictor of poor response to TMZ and radiation therapies in GBM patients. PMID:29371945

Prognostic factors in prostate cancer.

PubMed

Braeckman, Johan; Michielsen, Dirk

2007-01-01

In the nineteenth century the main goal of medicine was predictive: diagnose the disease and achieve a satisfying prognosis of the patient's chances. Today the effort has shifted to cure the disease. Since the twentieth century, the word prognosis has also been used in nonmedical contexts, for example in corporate finance or elections. The most accurate form of prognosis is achieved statistically. Based on different prognostic factors it should be possible to tell patients how they are expected to do after prostate cancer has been diagnosed and how different treatments may change this outcome. A prognosis is a prediction. The word prognosis comes from the Greek word (see text) and means foreknowing. In the nineteenth century this was the main goal of medicine: diagnose the disease and achieve a satisfying prognosis of the patient's chances. Today the effort has shifted towards seeking a cure. Prognostic factors in (prostate) cancer are defined as "variables that can account for some of the heterogeneity associated with the expected course and outcome of a disease". Bailey defined prognosis as "a reasoned forecast concerning the course, pattern, progression, duration, and end of the disease. Prognostic factors are not only essential to understand the natural history and the course of the disease, but also to predict possible different outcomes of different treatments or perhaps no treatment at all. This is extremely important in a disease like prostate cancer where there is clear evidence that a substantial number of cases discovered by prostate-specific antigen (PSA) testing are unlikely ever to become clinically significant, not to mention mortal. Furthermore, prognostic factors are of paramount importance for correct interpretation of clinical trials and for the construction of future trials. Finally, according to WHO national screening committee criteria for implementing a national screening programme, widely accepted prognostic factors must be defined before assessing screening.

Which index should be used to measure primary surgical outcome for unilateral cleft lip and palate patients?

PubMed

Jones, Timothy; Leary, Sam; Atack, Nikki; Ireland, Tony; Sandy, Jonathan

2016-08-01

To determine the optimal dentoalveolar measure to assess unilateral cleft lip and palate (UCLP) patient plaster models. The models of 34 patients with UCLP taken at 5, 10, and 15-20 years of age were scored by two examiners on two separate occasions using five indices: the 5 Year Olds' (5YO), GOSLON, Modified Huddart/Bodenham (MHB), EUROCRAN, and Overjet. Reliability, validity, and ease of use were recorded for each index/examiner. All models were scored in either Bristol Dental Hospital or Derriford Hospital, Plymouth, United Kingdom by senior orthodontic clinicians. Highest overall reliability was seen with MHB (Kappa = 0.56-0.97). Predictive validity was similar for MHB, GOSLON, and 5YO with a 50-65 per cent prediction of final outcome from 5 and 10 years. EUROCRAN palatal index showed no clear predictive validity (Spearman's correlation = 0.20-0.21). Agreement to the gold standard 5YO score at the 5-year age group was high for MHB (Kappa = 0.83) and moderate for GOSLON (Kappa = 0.59). Agreement to the gold standard GOSLON score at 10 years was highest for 5YO (Kappa = 0.69), followed by Overjet (Kappa = 0.59) and MHB (Kappa = 0.46). Time to score 34 models per index (minutes): GOSLON (13.4) < Overjet (13.6) < 5YO (19.4) < EUROCRAN (24.8) < MHB (27.4). As an outcome measure of UCLP models, only MHB and 5YO indices can be recommended for use at 5 years of age and GOSLON at 10 years of age. © The Author 2016. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Which index should be used to measure primary surgical outcome for unilateral cleft lip and palate patients?

PubMed Central

Leary, Sam; Atack, Nikki; Ireland, Tony; Sandy, Jonathan

2016-01-01

Summary Objective: To determine the optimal dentoalveolar measure to assess unilateral cleft lip and palate (UCLP) patient plaster models. Design: The models of 34 patients with UCLP taken at 5, 10, and 15–20 years of age were scored by two examiners on two separate occasions using five indices: the 5 Year Olds’ (5YO), GOSLON, Modified Huddart/Bodenham (MHB), EUROCRAN, and Overjet. Reliability, validity, and ease of use were recorded for each index/examiner. Setting: All models were scored in either Bristol Dental Hospital or Derriford Hospital, Plymouth, United Kingdom by senior orthodontic clinicians. Results: Highest overall reliability was seen with MHB (Kappa = 0.56–0.97). Predictive validity was similar for MHB, GOSLON, and 5YO with a 50–65 per cent prediction of final outcome from 5 and 10 years. EUROCRAN palatal index showed no clear predictive validity (Spearman’s correlation = 0.20–0.21). Agreement to the gold standard 5YO score at the 5-year age group was high for MHB (Kappa = 0.83) and moderate for GOSLON (Kappa = 0.59). Agreement to the gold standard GOSLON score at 10 years was highest for 5YO (Kappa = 0.69), followed by Overjet (Kappa = 0.59) and MHB (Kappa = 0.46). Time to score 34 models per index (minutes): GOSLON (13.4) < Overjet (13.6) < 5YO (19.4) < EUROCRAN (24.8) < MHB (27.4). Conclusion: As an outcome measure of UCLP models, only MHB and 5YO indices can be recommended for use at 5 years of age and GOSLON at 10 years of age. PMID:26988992

The Family Life Project: an epidemiological and developmental study of young children living in poor rural communities.

PubMed

Vernon-Feagans, Lynne; Cox, Martha

2013-10-01

About 20% of children in the United States have been reported to live in rural communities, with child poverty rates higher and geographic isolation from resources greater than in urban communities. There have been surprisingly few studies of children living in rural communities, especially poor rural communities. The Family Life Project helped fill this gap by using an epidemiological design to recruit and study a representative sample of every baby born to a mother who resided in one of six poor rural counties over a 1-year period, oversampling for poverty and African American. 1,292 children were followed from birth to 36 months of age. This monograph described these children and used a cumulative risk model to examine the relation between social risk and children's executive functioning, language development, and behavioral competence at 36 months. Using both the Family Process Model of development and the Family Investment Model of development, observed parenting was examined over time in relation to child functioning at 36 months. Different aspects of observed parenting were examined as mediators/moderators of risk in predicting child outcomes. Results suggested that cumulative risk was important in predicting all three major domains of child outcomes and that positive and negative parenting and maternal language complexity were mediators of these relations. Maternal positive parenting was found to be a buffer for the most risky families in predicting behavioral competence. In a final model using both family process and investment measures, there was evidence of mediation but with little evidence of the specificity of parenting for particular outcomes. Discussion focused on the importance of cumulative risk and parenting in understanding child competence in rural poverty and the implications for possible intervention strategies that might be effective in maximizing the early development of these children.

Violence against teachers: prevalence and consequences.

PubMed

Wilson, Catherine M; Douglas, Kevin S; Lyon, David R

2011-08-01

Data collected from 731 teachers were used to examine the consequences of violence directed toward teachers while in the workplace. Analyses showed that the majority of respondents (n = 585, 80.0%) had experienced school-related violence—broadly defined—at one point in their careers. Serious violence (actual, attempted, or threatened physical violence) was less common, but still common enough to be of concern (n = 202, 27.6%). Violence predicted physical and emotional effects, as well as teaching-related functioning. In addition, a model with fear as a potential mediator revealed that both fear and violence were independently predictive of these negative outcomes. Finally, analyses showed that, in general, women reported higher levels of physical symptoms compared to men. We discuss the implications of violence against teachers in terms of personal consequences and the implications for mental health professionals working in an educational setting.

Frictionless segmented mechanics for controlled space closure

PubMed Central

Andrade, Ildeu

2017-01-01

ABSTRACT Extraction spaces may be needed to achieve specific orthodontic goals of positioning the dentition in harmony with the craniofacial complex. However, the fundamental reality that determines the occlusion final position is the control exerted by the orthodontist while closing the extraction spaces. A specific treatment objective may require the posterior teeth to remain in a constant position anteroposteriorly as well as vertically, while the anterior teeth occupy the entire extraction site. Another treatment objective may require the opposite, or any number of intentional alternatives of extraction site closure. The present case report describes a simple controlled segmented mechanic system that permitted definable and predictable force systems to be applied and allowed to predict the treatment outcome with confidence. This case was presented to the Brazilian Board of Orthodontics and Dentofacial Orthopedics (BBO) in partial fulfillment of the requirements for Diplomate certification. PMID:28444016

Effectiveness of late gadolinium enhancement to improve outcomes prediction in patients referred for cardiovascular magnetic resonance after echocardiography

PubMed Central

2013-01-01

Background Echocardiography (echo) is a first line test to assess cardiac structure and function. It is not known if cardiovascular magnetic resonance (CMR) with late gadolinium enhancement (LGE) ordered during routine clinical practice in selected patients can add additional prognostic information after routine echo. We assessed whether CMR improves outcomes prediction after contemporaneous echo, which may have implications for efforts to optimize processes of care, assess effectiveness, and allocate limited health care resources. Methods and results We prospectively enrolled 1044 consecutive patients referred for CMR. There were 38 deaths and 3 cardiac transplants over a median follow-up of 1.0 years (IQR 0.4-1.5). We first reproduced previous survival curve strata (presence of LGE and ejection fraction (EF) < 50%) for transplant free survival, to support generalizability of any findings. Then, in a subset (n = 444) with contemporaneous echo (median 3 days apart, IQR 1–9), EF by echo (assessed visually) or CMR were modestly correlated (R2 = 0.66, p < 0.001), and 30 deaths and 3 transplants occurred over a median follow-up of 0.83 years (IQR 0.29-1.40). CMR EF predicted mortality better than echo EF in univariable Cox models (Integrated Discrimination Improvement (IDI) 0.018, 95% CI 0.008-0.034; Net Reclassification Improvement (NRI) 0.51, 95% CI 0.11-0.85). Finally, LGE further improved prediction beyond EF as determined by hazard ratios, NRI, and IDI in all Cox models predicting mortality or transplant free survival, adjusting for age, gender, wall motion, and EF. Conclusions Among those referred for CMR after echocardiography, CMR with LGE further improves risk stratification of individuals at risk for death or death/cardiac transplant. PMID:23324403

Deriving a clinical prediction rule to target sexual healthcare to women attending British General Practices.

PubMed

Edelman, N L; Cassell, J A; Mercer, C H; Bremner, S A; Jones, C I; Gersten, A; deVisser, R O

2018-07-01

Some women attending General Practices (GPs) are at higher risk of unintended pregnancy (RUIP) and sexually transmitted infections (STI) than others. A clinical prediction rule (CPR) may help target resources using psychosocial questions as an acceptable, effective means of assessment. The aim was to derive a CPR that discriminates women who would benefit from sexual health discussion and intervention. Participants were recruited to a cross-sectional survey from six GPs in a city in South-East England in 2016. On arrival, female patients aged 16-44 years were invited to complete a questionnaire that addressed psychosocial factors, and the following self-reported outcomes: 2+ sexual partners in the last year (2PP) and RUIP. For each sexual risk, psychosocial questions were retained from logistic regression modelling which best discriminated women at risk using the C-statistic. Sensitivity and specificity were established in consultation with GP staff. The final sample comprised N = 1238 women. 2PP was predicted by 11 questions including age, binge-drinking weekly, ever having a partner who insulted you often, current smoking, and not cohabiting (C-statistic = 0.83, sensitivity = 73% and specificity = 77%). RUIP was predicted by 5 questions including sexual debut <16 years, and emergency contraception use in the last 6 months (C-statistic = 0.70, sensitivity = 69% and specificity = 57%). 2PP was better discriminated than RUIP but neither to a clinically-useful degree. The finding that different psychosocial factors predicted each outcome has implications for prevention strategies. Further research should investigate causal links between psychosocial factors and sexual risk. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The combination of indocyanine green clearance test and model for end-stage liver disease score predicts early graft outcome after liver transplantation.

PubMed

Yunhua, Tang; Weiqiang, Ju; Maogen, Chen; Sai, Yang; Zhiheng, Zhang; Dongping, Wang; Zhiyong, Guo; Xiaoshun, He

2018-06-01

Early allograft dysfunction (EAD) and early postoperative complications are two important clinical endpoints when evaluating clinical outcomes of liver transplantation (LT). We developed and validated two ICGR15-MELD models in 87 liver transplant recipients for predicting EAD and early postoperative complications after LT by incorporating the quantitative liver function tests (ICGR15) into the MELD score. Eighty seven consecutive patients who underwent LT were collected and divided into a training cohort (n = 61) and an internal validation cohort (n = 26). For predicting EAD after LT, the area under curve (AUC) for ICGR15-MELD score was 0.876, with a sensitivity of 92.0% and a specificity of 75.0%, which is better than MELD score or ICGR15 alone. The recipients with a ICGR15-MELD score ≥0.243 have a higher incidence of EAD than those with a ICGR15-MELD score <0.243 (P <0.001). For predicting early postoperative complications, the AUC of ICGR15-MELD score was 0.832, with a sensitivity of 90.9% and a specificity of 71.0%. Those recipients with an ICGR15-MELD score ≥0.098 have a higher incidence of early postoperative complications than those with an ICGR15-MELD score <0.098 (P < 0.001). Finally, application of the two ICGR15-MELD models in the validation cohort still gave good accuracy (AUC, 0.835 and 0.826, respectively) in predicting EAD and early postoperative complications after LT. The combination of quantitative liver function tests (ICGR15) and the preoperative MELD score is a reliable and effective predictor of EAD and early postoperative complications after LT, which is better than MELD score or ICGR15 alone.

Comparison of cell cycle progression score with two immunohistochemical markers (PTEN and Ki-67) for predicting outcome in prostate cancer after radical prostatectomy.

PubMed

Léon, Priscilla; Cancel-Tassin, Geraldine; Drouin, Sara; Audouin, Marie; Varinot, Justine; Comperat, Eva; Cathelineau, Xavier; Rozet, François; Vaessens, Christophe; Stone, Steven; Reid, Julia; Sangale, Zaina; Korman, Patrick; Rouprêt, Morgan; Fromond-Hankard, Gaelle; Cussenot, Olivier

2018-04-20

Previous studies of the cell cycle progression (CCP) score in surgical specimens of prostate cancer (PCa) in patients treated by radical prostatectomy (RP) demonstrated significant association with time to biochemical recurrence (BCR). In this study, we compared the ability of the CCP score and the expression of PTEN or Ki-67 to predict BCR in a cohort of patients treated by RP. Finally, we constructed the best predictive model for BCR, incorporating biomarkers and relevant clinical variables. The study population consisted of 652 PCa patients enrolled in a retrospective cohort and who had RP surgery in French urological centers from 2000 to 2007. Among the 652 patients with CCP scores and complete clinical data, BCR events occurred in 41%, and the median time from surgery to the last follow-up among BCR-free patients was 72 months. In univariate Cox analysis, the continuous CCP score and positive Ki-67 predicted recurrence with a HR of 1.44 (95% CI 1.17-1.75; p = 5.3 × 10 -4 ) and 1.89 (95% CI 1.38-2.57; p = 1.6 × 10 -4 ), respectively. In contrast, PTEN expression was not associated with BCR risk. Of the three biomarkers, only the CCP score remained significantly associated in a multivariable Cox model (p = 0.026). The best model incorporated CAPRA-S and CCP scores as predictors, with HRs of 1.32 and 1.24, respectively. The CCP score was superior to the two IHC markers (PTEN and Ki-67) for predicting outcome in PCa after RP.

Risk Prediction Models for Acute Kidney Injury in Critically Ill Patients: Opus in Progressu.

PubMed

Neyra, Javier A; Leaf, David E

2018-05-31

Acute kidney injury (AKI) is a complex systemic syndrome associated with high morbidity and mortality. Among critically ill patients admitted to intensive care units (ICUs), the incidence of AKI is as high as 50% and is associated with dismal outcomes. Thus, the development and validation of clinical risk prediction tools that accurately identify patients at high risk for AKI in the ICU is of paramount importance. We provide a comprehensive review of 3 clinical risk prediction tools that have been developed for incident AKI occurring in the first few hours or days following admission to the ICU. We found substantial heterogeneity among the clinical variables that were examined and included as significant predictors of AKI in the final models. The area under the receiver operating characteristic curves was ∼0.8 for all 3 models, indicating satisfactory model performance, though positive predictive values ranged from only 23 to 38%. Hence, further research is needed to develop more accurate and reproducible clinical risk prediction tools. Strategies for improved assessment of AKI susceptibility in the ICU include the incorporation of dynamic (time-varying) clinical parameters, as well as biomarker, functional, imaging, and genomic data. © 2018 S. Karger AG, Basel.

Evoked potentials recorded during routine EEG predict outcome after perinatal asphyxia.

PubMed

Nevalainen, Päivi; Marchi, Viviana; Metsäranta, Marjo; Lönnqvist, Tuula; Toiviainen-Salo, Sanna; Vanhatalo, Sampsa; Lauronen, Leena

2017-07-01

To evaluate the added value of somatosensory (SEPs) and visual evoked potentials (VEPs) recorded simultaneously with routine EEG in early outcome prediction of newborns with hypoxic-ischemic encephalopathy under modern intensive care. We simultaneously recorded multichannel EEG, median nerve SEPs, and flash VEPs during the first few postnatal days in 50 term newborns with hypoxic-ischemic encephalopathy. EEG background was scored into five grades and the worst two grades were considered to indicate poor cerebral recovery. Evoked potentials were classified as absent or present. Clinical outcome was determined from the medical records at a median age of 21months. Unfavorable outcome included cerebral palsy, severe mental retardation, severe epilepsy, or death. The accuracy of outcome prediction was 98% with SEPs compared to 90% with EEG. EEG alone always predicted unfavorable outcome when it was inactive (n=9), and favorable outcome when it was normal or only mildly abnormal (n=17). However, newborns with moderate or severe EEG background abnormality could have either favorable or unfavorable outcome, which was correctly predicted by SEP in all but one newborn (accuracy in this subgroup 96%). Absent VEPs were always associated with an inactive EEG, and an unfavorable outcome. However, presence of VEPs did not guarantee a favorable outcome. SEPs accurately predict clinical outcomes in newborns with hypoxic-ischemic encephalopathy and improve the EEG-based prediction particularly in those newborns with severely or moderately abnormal EEG findings. SEPs should be added to routine EEG recordings for early bedside assessment of newborns with hypoxic-ischemic encephalopathy. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Robotic laparoscopic radical prostatectomy for biopsy Gleason 8 to 10: prediction of favorable pathologic outcome with preoperative parameters.

PubMed

Shikanov, Sergey A; Thong, Alan; Gofrit, Ofer N; Zagaja, Gregory P; Steinberg, Gary D; Shalhav, Arieh L; Zorn, Kevin C

2008-07-01

We sought to evaluate the pathologic results and postoperative outcomes for men undergoing robot-assisted laparoscopic radical prostatectomy (RLRP) for biopsy Gleason score (GS) 8 to 10 disease. Stratification of these patients according to preoperative variables was also performed in an attempt to predict organ-confined cancer. A prospective RLRP database identified all patients with preoperative biopsy GS 8 to 10. Variables, including prostate-specific antigen (PSA), percent positive biopsy cores (%PBC), maximal percentage of cancer in biopsy core (%MCB), clinical stage, pathologic stage, pathologic GS, surgical margins status, lymph node status, time to biochemical recurrence, and recurrence rate, were evaluated. Preoperative variables were treated as continuous and categorical using PSA, %PBC and %MCB cutoffs of 10 ng/mL, 50%, and 30%, respectively. Between February 2003 and September 2007, a total of 1225 RLRPs were performed at the University of Chicago Medical Center. Seventy-two (5.9%) patients had preoperative biopsy GS 8 to 10. Two patients received neoadjuvant hormonal therapy and were excluded. Among 70 patients evaluated, 33 (47%) had organconfined (pT(2)N0) disease. Forty (60.6%) patients had pathologic downgrading to GS

Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics

NASA Astrophysics Data System (ADS)

Folkert, Michael R.; Setton, Jeremy; Apte, Aditya P.; Grkovski, Milan; Young, Robert J.; Schöder, Heiko; Thorstad, Wade L.; Lee, Nancy Y.; Deasy, Joseph O.; Oh, Jung Hun

2017-07-01

In this study, we investigate the use of imaging feature-based outcomes research (‘radiomics’) combined with machine learning techniques to develop robust predictive models for the risk of all-cause mortality (ACM), local failure (LF), and distant metastasis (DM) following definitive chemoradiation therapy (CRT). One hundred seventy four patients with stage III-IV oropharyngeal cancer (OC) treated at our institution with CRT with retrievable pre- and post-treatment 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans were identified. From pre-treatment PET scans, 24 representative imaging features of FDG-avid disease regions were extracted. Using machine learning-based feature selection methods, multiparameter logistic regression models were built incorporating clinical factors and imaging features. All model building methods were tested by cross validation to avoid overfitting, and final outcome models were validated on an independent dataset from a collaborating institution. Multiparameter models were statistically significant on 5 fold cross validation with the area under the receiver operating characteristic curve (AUC)  =  0.65 (p  =  0.004), 0.73 (p  =  0.026), and 0.66 (p  =  0.015) for ACM, LF, and DM, respectively. The model for LF retained significance on the independent validation cohort with AUC  =  0.68 (p  =  0.029) whereas the models for ACM and DM did not reach statistical significance, but resulted in comparable predictive power to the 5 fold cross validation with AUC  =  0.60 (p  =  0.092) and 0.65 (p  =  0.062), respectively. In the largest study of its kind to date, predictive features including increasing metabolic tumor volume, increasing image heterogeneity, and increasing tumor surface irregularity significantly correlated to mortality, LF, and DM on 5 fold cross validation in a relatively uniform single-institution cohort. The LF model also retained significance in an independent population.

Modeling and simulation of maintenance treatment in first-line non-small cell lung cancer with external validation.

PubMed

Han, Kelong; Claret, Laurent; Sandler, Alan; Das, Asha; Jin, Jin; Bruno, Rene

2016-07-13

Maintenance treatment (MTx) in responders following first-line treatment has been investigated and practiced for many cancers. Modeling and simulation may support interpretation of interim data and development decisions. We aimed to develop a modeling framework to simulate overall survival (OS) for MTx in NSCLC using tumor growth inhibition (TGI) data. TGI metrics were estimated using longitudinal tumor size data from two Phase III first-line NSCLC studies evaluating bevacizumab and erlotinib as MTx in 1632 patients. Baseline prognostic factors and TGI metric estimates were assessed in multivariate parametric models to predict OS. The OS model was externally validated by simulating a third independent NSCLC study (n = 253) based on interim TGI data (up to progression-free survival database lock). The third study evaluated pemetrexed + bevacizumab vs. bevacizumab alone as MTx. Time-to-tumor-growth (TTG) was the best TGI metric to predict OS. TTG, baseline tumor size, ECOG score, Asian ethnicity, age, and gender were significant covariates in the final OS model. The OS model was qualified by simulating OS distributions and hazard ratios (HR) in the two studies used for model-building. Simulations of the third independent study based on interim TGI data showed that pemetrexed + bevacizumab MTx was unlikely to significantly prolong OS vs. bevacizumab alone given the current sample size (predicted HR: 0.81; 95 % prediction interval: 0.59-1.09). Predicted median OS was 17.3 months and 14.7 months in both arms, respectively. These simulations are consistent with the results of the final OS analysis published 2 years later (observed HR: 0.87; 95 % confidence interval: 0.63-1.21). Final observed median OS was 17.1 months and 13.2 months in both arms, respectively, consistent with our predictions. A robust TGI-OS model was developed for MTx in NSCLC. TTG captures treatment effect. The model successfully predicted the OS outcomes of an independent study based on interim TGI data and thus may facilitate trial simulation and interpretation of interim data. The model was built based on erlotinib data and externally validated using pemetrexed data, suggesting that TGI-OS models may be treatment-independent. The results supported the use of longitudinal tumor size and TTG as endpoints in early clinical oncology studies.

The predictive value of external continuous lumbar drainage, with cerebrospinal fluid outflow controlled by medium pressure valve, in normal pressure hydrocephalus.

PubMed

Panagiotopoulos, V; Konstantinou, D; Kalogeropoulos, A; Maraziotis, T

2005-09-01

Although sporadic studies have described temporary external cerebrospinal fluid (CSF) lumbar drainage as a highly accurate test for predicting the outcome after ventricular shunting in normal pressure hydrocephalus (NPH) patients, a more recent study reports that the positive predictive value of external lumbar drainage (ELD) is high but the negative predictive value is deceptively low. Therefore, we conducted a prospective study in order to evaluate the predictive value of a continuous ELD, with CSF outflow controlled by medium pressure valve, in NPH patients. Twenty-seven patients with presumed NPH were admitted to our department and CSF drainage was carried out by a temporary (ELD) with CSF outflow controlled by a medium pressure valve for five days. All patients received a ventriculoperitoneal shunt using a medium pressure valve based upon preoperative clinical and radiographic criteria of NPH, regardless of ELD outcome. Clinical evaluation of gait disturbances, urinary incontinence and mental status, and radiological evaluation with brain CT was performed prior to and after ELD test, as well as three months after shunting. Twenty-two patients were finally shunted and included in this study. In a three-month follow-up, using a previously validated score system, overall improvement after permanent shunting correlated well to improvement after ELD test (Spearman's rho = 0.462, p = 0.03). When considering any degree of improvement as a positive response, ELD test yielded high positive predictive values for all individual parameters (gait disturbances 94%, 95% CI 71%-100%, urinary incontinence 100%, 95% CI 66%-100%, and mental status 100%, 95% CI 66%-100%) but negative predictive values were low (< 50%) except for cognitive impairment (85%, 95% CI 55%-98%). This study suggests that a positive ELD-valve system test should be considered a reliable criterion for preoperative selection of shunt-responsive NPH patients. In case of a negative ELD-valve system test, further investigation of the presumed NPH patients with additional tests should be performed.

Prediction of Drug-Drug Interactions with Crizotinib as the CYP3A Substrate Using a Physiologically Based Pharmacokinetic Model.

PubMed

Yamazaki, Shinji; Johnson, Theodore R; Smith, Bill J

2015-10-01

An orally available multiple tyrosine kinase inhibitor, crizotinib (Xalkori), is a CYP3A substrate, moderate time-dependent inhibitor, and weak inducer. The main objectives of the present study were to: 1) develop and refine a physiologically based pharmacokinetic (PBPK) model of crizotinib on the basis of clinical single- and multiple-dose results, 2) verify the crizotinib PBPK model from crizotinib single-dose drug-drug interaction (DDI) results with multiple-dose coadministration of ketoconazole or rifampin, and 3) apply the crizotinib PBPK model to predict crizotinib multiple-dose DDI outcomes. We also focused on gaining insights into the underlying mechanisms mediating crizotinib DDIs using a dynamic PBPK model, the Simcyp population-based simulator. First, PBPK model-predicted crizotinib exposures adequately matched clinically observed results in the single- and multiple-dose studies. Second, the model-predicted crizotinib exposures sufficiently matched clinically observed results in the crizotinib single-dose DDI studies with ketoconazole or rifampin, resulting in the reasonably predicted fold-increases in crizotinib exposures. Finally, the predicted fold-increases in crizotinib exposures in the multiple-dose DDI studies were roughly comparable to those in the single-dose DDI studies, suggesting that the effects of crizotinib CYP3A time-dependent inhibition (net inhibition) on the multiple-dose DDI outcomes would be negligible. Therefore, crizotinib dose-adjustment in the multiple-dose DDI studies could be made on the basis of currently available single-dose results. Overall, we believe that the crizotinib PBPK model developed, refined, and verified in the present study would adequately predict crizotinib oral exposures in other clinical studies, such as DDIs with weak/moderate CYP3A inhibitors/inducers and drug-disease interactions in patients with hepatic or renal impairment. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Predicting outcome in severe traumatic brain injury using a simple prognostic model.

PubMed

Sobuwa, Simpiwe; Hartzenberg, Henry Benjamin; Geduld, Heike; Uys, Corrie

2014-06-17

Several studies have made it possible to predict outcome in severe traumatic brain injury (TBI) making it beneficial as an aid for clinical decision-making in the emergency setting. However, reliable predictive models are lacking for resource-limited prehospital settings such as those in developing countries like South Africa. To develop a simple predictive model for severe TBI using clinical variables in a South African prehospital setting. All consecutive patients admitted at two level-one centres in Cape Town, South Africa, for severe TBI were included. A binary logistic regression model was used, which included three predictor variables: oxygen saturation (SpO₂), Glasgow Coma Scale (GCS) and pupil reactivity. The Glasgow Outcome Scale was used to assess outcome on hospital discharge. A total of 74.4% of the outcomes were correctly predicted by the logistic regression model. The model demonstrated SpO₂ (p=0.019), GCS (p=0.001) and pupil reactivity (p=0.002) as independently significant predictors of outcome in severe TBI. Odds ratios of a good outcome were 3.148 (SpO₂ ≥ 90%), 5.108 (GCS 6 - 8) and 4.405 (pupils bilaterally reactive). This model is potentially useful for effective predictions of outcome in severe TBI.

Development of a Conceptual Model of Disease Progression for Use in Economic Modeling of Chronic Obstructive Pulmonary Disease.

PubMed

Tabberer, Maggie; Gonzalez-McQuire, Sebastian; Muellerova, Hana; Briggs, Andrew H; Rutten-van Mölken, Maureen P M H; Chambers, Mike; Lomas, David A

2017-05-01

To develop and validate a new conceptual model (CM) of chronic obstructive pulmonary disease (COPD) for use in disease progression and economic modeling. The CM identifies and describes qualitative associations between disease attributes, progression and outcomes. A literature review was performed to identify any published CMs or literature reporting the impact and association of COPD disease attributes with outcomes. After critical analysis of the literature, a Steering Group of experts from the disciplines of health economics, epidemiology and clinical medicine was convened to develop a draft CM, which was refined using a Delphi process. The refined CM was validated by testing for associations between attributes using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). Disease progression attributes included in the final CM were history and occurrence of exacerbations, lung function, exercise capacity, signs and symptoms (cough, sputum, dyspnea), cardiovascular disease comorbidities, 'other' comorbidities (including depression), body composition (body mass index), fibrinogen as a biomarker, smoking and demographic characteristics (age, gender). Mortality and health-related quality of life were determined to be the most relevant final outcome measures for this model, intended to be the foundation of an economic model of COPD. The CM is being used as the foundation for developing a new COPD model of disease progression and to provide a framework for the analysis of patient-level data. The CM is available as a reference for the implementation of further disease progression and economic models.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other’s Actions by Humans

PubMed Central

Ganesh, Gowrishankar

2017-01-01

Abstract The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants’ ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert’s abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert’s self-estimation is explained only by considering a change in the individual’s forward model, showing that an improvement in an expert’s ability to predict outcomes of observed actions affects the individual’s forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. PMID:29340300

Watching novice action degrades expert motor performance: Causation between action production and outcome prediction of observed actions by humans

PubMed Central

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2014-01-01

Our social skills are critically determined by our ability to understand and appropriately respond to actions performed by others. However despite its obvious importance, the mechanisms enabling action understanding in humans have remained largely unclear. A popular but controversial belief is that parts of the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral paradigm, we investigated this belief by examining a causal relation between action production, and a component of action understanding - outcome prediction, the ability of a person to predict the outcome of observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert's ability to predict watched actions while controlling the other experimental factors, and exhibited that a change (improvement) in their outcome prediction ability results in a progressive and proportional deterioration in the expert's own darts performance. This causal relationship supports involvement of the motor system in outcome prediction by humans of actions observed in others. PMID:25384755

Is there more valuable information in PWI datasets for a voxel-wise acute ischemic stroke tissue outcome prediction than what is represented by typical perfusion maps?

NASA Astrophysics Data System (ADS)

Forkert, Nils Daniel; Siemonsen, Susanne; Dalski, Michael; Verleger, Tobias; Kemmling, Andre; Fiehler, Jens

2014-03-01

The acute ischemic stroke is a leading cause for death and disability in the industry nations. In case of a present acute ischemic stroke, the prediction of the future tissue outcome is of high interest for the clinicians as it can be used to support therapy decision making. Within this context, it has already been shown that the voxel-wise multi-parametric tissue outcome prediction leads to more promising results compared to single channel perfusion map thresholding. Most previously published multi-parametric predictions employ information from perfusion maps derived from perfusion-weighted MRI together with other image sequences such as diffusion-weighted MRI. However, it remains unclear if the typically calculated perfusion maps used for this purpose really include all valuable information from the PWI dataset for an optimal tissue outcome prediction. To investigate this problem in more detail, two different methods to predict tissue outcome using a k-nearest-neighbor approach were developed in this work and evaluated based on 18 datasets of acute stroke patients with known tissue outcome. The first method integrates apparent diffusion coefficient and perfusion parameter (Tmax, MTT, CBV, CBF) information for the voxel-wise prediction, while the second method employs also apparent diffusion coefficient information but the complete perfusion information in terms of the voxel-wise residue functions instead of the perfusion parameter maps for the voxel-wise prediction. Overall, the comparison of the results of the two prediction methods for the 18 patients using a leave-one-out cross validation revealed no considerable differences. Quantitatively, the parameter-based prediction of tissue outcome led to a mean Dice coefficient of 0.474, while the prediction using the residue functions led to a mean Dice coefficient of 0.461. Thus, it may be concluded from the results of this study that the perfusion parameter maps typically derived from PWI datasets include all valuable perfusion information required for a voxel-based tissue outcome prediction, while the complete analysis of the residue functions does not add further benefits for the voxel-wise tissue outcome prediction and is also computationally more expensive.

Can somatosensory and visual evoked potentials predict neurological outcome during targeted temperature management in post cardiac arrest patients?

PubMed

Choi, Seung Pill; Park, Kyu Nam; Wee, Jung Hee; Park, Jeong Ho; Youn, Chun Song; Kim, Han Joon; Oh, Sang Hoon; Oh, Yoon Sang; Kim, Soo Hyun; Oh, Joo Suk

2017-10-01

In cardiac arrest patients treated with targeted temperature management (TTM), it is not certain if somatosensory evoked potentials (SEPs) and visual evoked potentials (VEPs) can predict neurological outcomes during TTM. The aim of this study was to investigate the prognostic value of SEPs and VEPs during TTM and after rewarming. This retrospective cohort study included comatose patients resuscitated from cardiac arrest and treated with TTM between March 2007 and July 2015. SEPs and VEPs were recorded during TTM and after rewarming in these patients. Neurological outcome was assessed at discharge by the Cerebral Performance Category (CPC) Scale. In total, 115 patients were included. A total of 175 SEPs and 150 VEPs were performed. Five SEPs during treated with TTM and nine SEPs after rewarming were excluded from outcome prediction by SEPs due to an indeterminable N20 response because of technical error. Using 80 SEPs and 85 VEPs during treated with TTM, absent SEPs yielded a sensitivity of 58% and a specificity of 100% for poor outcome (CPC 3-5), and absent VEPs predicted poor neurological outcome with a sensitivity of 44% and a specificity of 96%. The AUC of combination of SEPs and VEPs was superior to either test alone (0.788 for absent SEPs and 0.713 for absent VEPs compared with 0.838 for the combination). After rewarming, absent SEPs and absent VEPs predicted poor neurological outcome with a specificity of 100%. When SEPs and VEPs were combined, VEPs slightly increased the prognostic accuracy of SEPs alone. Although one patient with absent VEP during treated with TTM had a good neurological outcome, none of the patients with good neurological outcome had an absent VEP after rewarming. Absent SEPs could predict poor neurological outcome during TTM as well as after rewarming. Absent VEPs may predict poor neurological outcome in both periods and VEPs may provide additional prognostic value in outcome prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing Participation in Community-Based Physical Activity Programs in Brazil

PubMed Central

REIS, RODRIGO S.; YAN, YAN; PARRA, DIANA C.; BROWNSON, ROSS C.

2015-01-01

Purpose This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. Methods We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. Results The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14–4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16–2.53), reporting a good health (OR = 1.58, 95% CI = 1.02–2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05–2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26–2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18–2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Conclusions Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil. PMID:23846162

Design of Biomedical Robots for Phenotype Prediction Problems

PubMed Central

deAndrés-Galiana, Enrique J.; Sonis, Stephen T.

2016-01-01

Abstract Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem. PMID:27347715

Design of Biomedical Robots for Phenotype Prediction Problems.

PubMed

deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Sonis, Stephen T

2016-08-01

Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem.

Can We Predict Functional Outcome in Neonates with Hypoxic Ischemic Encephalopathy by the Combination of Neuroimaging and Electroencephalography?

PubMed Central

Nanavati, Tania; Seemaladinne, Nirupama; Regier, Michael; Yossuck, Panitan; Pergami, Paola

2015-01-01

Background Neonatal hypoxic ischemic encephalopathy (HIE) is a major cause of mortality, morbidity, and long-term neurological deficits. Despite the availability of neuroimaging and neurophysiological testing, tools for accurate early diagnosis and prediction of developmental outcome are still lacking. The goal of this study was to determine if combined use of magnetic resonance imaging (MRI) and electroencephalography (EEG) findings could support outcome prediction. Methods We retrospectively reviewed records of 17 HIE neonates, classified brain MRI and EEG findings based on severity, and assessed clinical outcome up to 48 months. We determined the relation between MRI/EEG findings and clinical outcome. Results We demonstrated a significant relationship between MRI findings and clinical outcome (Fisher’s exact test, p = 0.017). EEG provided no additional information about the outcome beyond that contained in the MRI score. The statistical model for outcome prediction based on random forests suggested that EEG readings at 24 hours and 72 hours could be important variables for outcome prediction, but this needs to be investigated further. Conclusion Caution should be used when discussing prognosis for neonates with mild-to-moderate HIE based on early MR imaging and EEG findings. A robust, quantitative marker of HIE severity that allows for accurate prediction of long-term outcome, particularly for mild-to-moderate cases, is still needed. PMID:25862075

Resection of isolated pelvic recurrences after colorectal surgery: long-term results and predictors of improved clinical outcome.

PubMed

Henry, Leonard R; Sigurdson, Elin; Ross, Eric A; Lee, John S; Watson, James C; Cheng, Jonathan D; Freedman, Gary M; Konski, Andre; Hoffman, John P

2007-07-01

Recurrence in the pelvis after resection of a rectal or rectosigmoid cancer presents a dilemma. Resection offers the only reasonable probability for cure, but at the cost of perioperative morbidity and potential mortality. Clinical decision making remains difficult. Patients resected with curative intent for isolated pelvic recurrences after curative colorectal surgery from 1988 through 2003 were reviewed retrospectively. Clinical and pathologic factors, salvage operations, and complications were recorded. The primary measured outcome was overall survival. Univariate and multivariate analyses were conducted to identify prognostic factors of improved outcome. Ninety patients underwent an attempt at curative resection of a pelvic recurrence with median follow-up of 31 months. Complications occurred in 53% of patients. Operative mortality was 4.4% (4 of 90). Median overall survival was 38 months, and estimated 5-year survival was 40%. A total of 51 of 86 patients had known recurrences (15 local, 16 distant, 20 both). Multivariate analysis revealed that preoperative carcinoembryonic antigen level and final margin status were statistically significant predictors of outcome. The resection of pelvic recurrences after colorectal surgery for cancer can be performed with low mortality and good long-term outcome; however, morbidity from such procedures is high. Low preoperative carcinoembryonic antigen and negative margin of resection predict improved survival.

Resection of isolated pelvic recurrences after colorectal surgery: long-term results and predictors of improved clinical outcome.

PubMed

Henry, Leonard R; Sigurdson, Elin; Ross, Eric A; Lee, John S; Watson, James C; Cheng, Jonathan D; Freedman, Gary M; Konski, Andre; Hoffman, John P

2007-03-01

Recurrence in the pelvis after resection of a rectal or rectosigmoid cancer presents a dilemma. Resection offers the only reasonable probability for cure, but at the cost of marked perioperative morbidity and potential mortality. Clinical decision making remains difficult. Patients who underwent resection with curative intent for isolated pelvic recurrences after curative colorectal surgery from 1988 through 2003 were reviewed retrospectively. Clinical and pathological factors, salvage operations, and complications were recorded. The primary measured outcome was overall survival. Univariate and multivariate analyses were conducted to identify prognostic factors of improved outcome. Ninety patients underwent an attempt at curative resection of a pelvic recurrence; median follow-up was 31 months. Complications occurred in 53% of patients. Operative mortality occurred in 4 (4.4%) of 90 patients. Median overall survival was 38 months, and estimated 5-year survival was 40%. A total of 51 of 86 patients had known recurrences (15 local, 16 distant, 20 both). Multivariate analysis revealed that preoperative carcinoembryonic antigen level and final margin status were statistically significant predictors of outcome. The resection of pelvic recurrences after colorectal surgery for cancer can be performed with low mortality and good long-term outcome; however, morbidity from such procedures is high. Low preoperative carcinoembryonic antigen and negative margin of resection predict improved survival.

Prospective evaluation of a bivalirudin to warfarin transition nomogram.

PubMed

Hohlfelder, Benjamin; Sylvester, Katelyn W; Rimsans, Jessica; DeiCicchi, David; Connors, Jean M

2017-05-01

Bivalirudin may cause a falsely prolonged international normalized ratio (INR) that complicates the discontinuation of bivalirudin when used as a bridge to warfarin. To prospectively validate our novel bivalirudin to warfarin transition nomogram, adult patients who received bivalirudin as a bridge to warfarin between July 2015 and June 2016 were prospectively evaluated, utilizing our predictive nomogram. The major outcome of our analysis was the correlation between the predicted change in INR upon bivalirudin discontinuation based on the nomogram, and the actual change in INR upon bivalirudin discontinuation. The major outcome was analyzed using the Pearson's correlation test. A Pearson's correlation coefficient >0.6 was considered to be a strong correlation. Bivalirudin was used as a bridge to warfarin in 29 patients. The majority of patients (86%) included in the analysis had a ventricular assist device. The median initial bivalirudin rate was 0.07 mg/kg/h and the mean increase in INR when starting bivalirudin was 0.6. The mean final weight-based bivalirudin rate was 0.08 mg/kg/h and the mean change in INR after stopping bivalirudin was 0.7. The Pearson correlation coefficient between the predicted change in INR upon bivalirudin discontinuation and the actual change in INR upon bivalirudin discontinuation was 0.86 (p < 0.001). After bivalirudin discontinuation, 68% of patients had a therapeutic INR. The results of this prospective analysis successfully validated our novel bivalirudin to warfarin transition nomogram. There was a very strong correlation between the predicted change and actual change in INR upon bivalirudin discontinuation.

What Specific Facets of Executive Function are Associated with Academic Functioning in Youth with Attention-Deficit/Hyperactivity Disorder?

PubMed Central

Langberg, Joshua M.; Dvorsky, Melissa R.; Evans, Steven W.

2013-01-01

The purpose of the study was to evaluate the relation between ratings of Executive Function (EF) and academic functioning in a sample of 94 middle-school-aged youth with Attention-Deficit/Hyperactivity Disorder (ADHD; Mage = 11.9; 78% male; 21% minority). This study builds on prior work by evaluating associations between multiple specific aspects of EF (e.g., working memory, inhibition, and planning and organization) as rated by both parents and teachers on the Behavior Rating Inventory of Executive Function (BRIEF), with multiple academic outcomes, including school grades and homework problems. Further, this study examined the relationship between EF and academic outcomes above and beyond ADHD symptoms and controlled for a number of potentially important covariates, including intelligence and achievement scores. The EF Planning and Organization subscale as rated by both parents and teachers predicted school grades above and beyond symptoms of ADHD and relevant covariates. Parent ratings of youth’s ability to transition effectively between tasks/situations (Shift subscale) also predicted school grades. Parent-rated symptoms of inattention, hyperactivity/impulsivity, and planning and organization abilities were significant in the final model predicting homework problems. In contrast, only symptoms of inattention and the Organization of Materials subscale from the BRIEF were significant in the teacher model predicting homework problems. Organization and planning abilities are highly important aspects academic functioning for middle-school-aged youth with ADHD. Implications of these findings for the measurement of EF, and organization and planning abilities in particular, are discussed along with potential implications for intervention. PMID:23640285

Increasing Prediction the Original Final Year Project of Student Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Saragih, Rijois Iboy Erwin; Turnip, Mardi; Sitanggang, Delima; Aritonang, Mendarissan; Harianja, Eva

2018-04-01

Final year project is very important forgraduation study of a student. Unfortunately, many students are not seriouslydidtheir final projects. Many of studentsask for someone to do it for them. In this paper, an application of genetic algorithms to predict the original final year project of a studentis proposed. In the simulation, the data of the final project for the last 5 years is collected. The genetic algorithm has several operators namely population, selection, crossover, and mutation. The result suggest that genetic algorithm can do better prediction than other comparable model. Experimental results of predicting showed that 70% was more accurate than the previous researched.

Quality of courses evaluated by 'predictions' rather than opinions: Fewer respondents needed for similar results.

PubMed

Cohen-Schotanus, Janke; Schönrock-Adema, Johanna; Schmidt, Henk G

2010-01-01

A well-known problem with student surveys is a too low response rate. Experiences with predicting electoral outcomes, which required much smaller sample sizes, inspired us to adopt a similar approach to course evaluation. We expected that having respondents estimate the average opinions of their peers required fewer respondents for comparable outcomes than giving own opinions. Two course evaluation studies were performed among successive first-year medical students (N = 380 and 450, respectively). Study 1: Half the cohort gave opinions on nine questions, while the other half predicted the average outcomes. A prize was offered for the three best predictions (motivational remedy). Study 2: Half the cohort gave opinions, a quarter made predictions without a prize and a quarter made predictions with previous year's results as prior knowledge (cognitive remedy). The numbers of respondents required for stable outcomes were determined following an iterative process. Differences between numbers of respondents required and between average scores were analysed with ANOVA. In both studies, the prediction conditions required significantly fewer respondents (p < 0.001) for comparable outcomes. The informed prediction condition required the fewest respondents (N < 20). Problems with response rates can be reduced by asking respondents to predict evaluation outcomes rather than giving opinions.

Endoscopic ultrasound evaluation in the surgical treatment of duodenal and peri-ampullary adenomas

PubMed Central

Azih, Lilian C; Broussard, Brett L; Phadnis, Milind A; Heslin, Martin J; Eloubeidi, Mohamad A; Varadarajulu, Shayam; Arnoletti, Juan Pablo

2013-01-01

AIM: To investigate endoscopic ultrasound (EUS) for predicting depth of mucosal invasion and to analyze outcomes following endoscopic and transduodenal resection. METHODS: Records of 111 patients seen at our institution from November 1999 to July 2011 with the post-operative pathological diagnosis of benign ampullary and duodenal adenomas were reviewed. Records of patients who underwent preoperative EUS for diagnostic purposes were identified. The accuracy of EUS in predicting the absence of muscular invasion was assessed by comparing EUS reports to the final surgical pathological results. In addition, the incidence of the post-operative complications over a period of 30 d and the subsequent long-term outcome (recurrence) over a period of 30 mo associated with endoscopic and transduodenal surgical resection was recorded, compared and analyzed. RESULTS: Among 111 patients with benign ampullary and duodenal adenomas, 47 underwent preoperative EUS for 29 peri-ampullary lesions and 18 duodenal lesions. In addition, computed tomography was performed in 18 patients, endoscopic retrograde cholangio-pancreatography in 10 patients and esophagogastroduodenoscopy in 22 patients. There were 43 patients with sporadic adenomas and 4 patients with familial adenomatous polyposis (FAP)/other polyposis syndromes. In 38 (81%, P < 0.05) patients, EUS reliably identified absence of submucosal and muscularis invasion. In 4 cases, EUS underestimated submucosal invasion that was proven by pathology. In the other 5 patients, EUS predicted muscularis invasion which could not be demonstrated in the resected specimen. EUS predicted tumor muscularis invasion with a specificity of 88% and negative predictive value of 90% (P < 0.05). Types of resection performed included endoscopic resection in 22 cases, partial duodenectomy in 9 cases, transduodenal ampullectomy with sphincteroplasty in 10 cases and pancreaticoduodenectomy in 6 cases. The main post-operative final pathological results included villous adenoma (n = 5), adenoma (n = 8), tubulovillous adenoma (n = 10), tubular adenoma (n = 20) and hyperplastic polyp (n = 2). Among the 47 patients who underwent resection, 8 (17%, 5 of which corresponded to surgical resection) developed post-procedural complications which included retroperitoneal hematoma, intra-abdominal abscess, wound infection, delayed gastric emptying and prolonged ileus. After median follow-up of 20 mo there were 6 local recurrences (13%, median follow-up = 20 mo) 4 of which were in patients with FAP. CONCLUSION: EUS accurately predicts the depth of mucosal invasion in suspected benign ampullary and duodenal adenomas. These patients can safely undergo endoscopic or local resection. PMID:23382629

Evaluation of standardized and applied variables in predicting treatment outcomes of polytrauma patients.

PubMed

Aksamija, Goran; Mulabdic, Adi; Rasic, Ismar; Muhovic, Samir; Gavric, Igor

2011-01-01

Polytrauma is defined as an injury where they are affected by at least two different organ systems or body, with at least one life-threatening injuries. Given the multilevel model care of polytrauma patients within KCUS are inevitable weaknesses in the management of this category of patients. To determine the dynamics of existing procedures in treatment of polytrauma patients on admission to KCUS, and based on statistical analysis of variables applied to determine and define the factors that influence the final outcome of treatment, and determine their mutual relationship, which may result in eliminating the flaws in the approach to the problem. The study was based on 263 polytrauma patients. Parametric and non-parametric statistical methods were used. Basic statistics were calculated, based on the calculated parameters for the final achievement of research objectives, multicoleration analysis, image analysis, discriminant analysis and multifactorial analysis were used. From the universe of variables for this study we selected sample of n = 25 variables, of which the first two modular, others belong to the common measurement space (n = 23) and in this paper defined as a system variable methods, procedures and assessments of polytrauma patients. After the multicoleration analysis, since the image analysis gave a reliable measurement results, we started the analysis of eigenvalues, that is defining the factors upon which they obtain information about the system solve the problem of the existing model and its correlation with treatment outcome. The study singled out the essential factors that determine the current organizational model of care, which may affect the treatment and better outcome of polytrauma patients. This analysis has shown the maximum correlative relationships between these practices and contributed to development guidelines that are defined by isolated factors.

The Utility of Home-Practice in Mindfulness-Based Group Interventions: A Systematic Review.

PubMed

Lloyd, Annette; White, Ross; Eames, Catrin; Crane, Rebecca

2018-01-01

A growing body of research supports the efficacy of mindfulness-based interventions (MBIs). MBIs consider home-practice as essential to increasing the therapeutic effects of the treatment. To date however, the synthesis of the research conducted on the role of home-practice in controlled MBI studies has been a neglected area. This review aimed to conduct a narrative synthesis of published controlled studies, evaluating mindfulness-based group interventions, which have specifically measured home-practice. Empirical research literature published until June 2016 was searched using five databases. The search strategy focused on mindfulness-based stress reduction (MBSR), mindfulness-based cognitive therapy (MBCT), and home-practice. Included studies met the following criteria: controlled trials, participants 18 years and above, evaluations of MBSR or MBCT, utilised standardised quantitative outcome measures and monitored home-practice using a self-reported measure. Fourteen studies met the criteria and were included in the review. Across all studies, there was heterogeneity in the guidance and resources provided to participants and the approaches used for monitoring home-practice. In addition, the guidance on the length of home-practice was variable across studies, which indicates that research studies and teachers are not adhering to the published protocols. Finally, only seven studies examined the relationship between home-practice and clinical outcomes, of which four found that home-practice predicted improvements on clinical outcome measures. Future research should adopt a standardised approach for monitoring home-practice across MBIs. Additionally, studies should assess whether the amount of home-practice recommended to participants is in line with MBSR/MBCT manualised protocols. Finally, research should utilise experimental methodologies to explicitly explore the relationship between home-practice and clinical outcomes.

Natural history of multiple sclerosis from the Indian perspective: Experience from a tertiary care hospital.

PubMed

Jena, Subhransu S; Alexander, Mathew; Aaron, Sanjith; Mathew, Vivek; Thomas, Maya Mary; Patil, Anil K; Sivadasan, Ajith; Muthusamy, Karthik; Mani, Sunithi; Rebekah, J Grace

2015-01-01

Multiple sclerosis (MS) has a spectrum of heterogeneity, as seen in western and eastern hemispheres, in the clinical features, topography of involvement and differences in natural history. To study the clinical spectrum, imaging, and electrophysiological as well as cerebrospinal fluid (CSF) characteristics and correlate them with outcome. Retrospective analysis of MS patients during a period of 20 years. Cases were selected according to recent McDonald's criteria (2010), They were managed in the Department of Neurology, Christian Medical College, Vellore. Chi-square and Fisher's exact tests were used for categorical variables. Multiple binary logistic regressions were done to assess significance. Kaplan-Meier curves were drawn to estimate the time to irreversible disability. A total of 157 patients with female preponderance (55%) were included. The inter quartile range duration of follow-up was 9.1 (8.2, 11) years for 114 patients, who were included for final outcome analysis. Relapsing remitting MS (RRMS) (54.1%) was the most common type of MS seen. RRMS had a significantly better outcome (odds ratio: 0.12, 95% confidence interval: 0.02-0.57, P = 0.008) compared to progressive form of MS (primary progressive, secondary progressive). The Expanded Disability Status Scale score of patients at presentation and at final follow-up was 4.4 ± 1.31 and 4.1 ± 2.31, respectively. During the first presentation, polysymptomatic manifestations like motor and sphincteric involvement, incomplete recovery from the first attack; and, during the disease course, bowel, bladder, cerebellar and pyramidal affliction, predicted a worse outcome. A high incidence of optico-spinal presentation, predominance of RRMS and a low yield on cerebrospinal fluid (CSF) studies are the major findings of our study. A notable feature was the analysis of prognostic markers of disability.

Sexual experience among emotionally and behaviorally disordered students in therapeutic day schools: an ecological examination of adolescent risk.

PubMed

Donenberg, Geri R; Emerson, Erin; Brown, Larry K; Houck, Christopher; Mackesy-Amiti, Mary Ellen

2012-09-01

This study examined gender differences in family, peer, partner, and mental health characteristics related to sexual experience among emotionally and behaviorally disordered students in therapeutic day schools, a population at elevated risk for negative sexual health outcomes. A total of 417 13- to 20-year-old adolescents reported on their family functioning, peer and partner relationship characteristics, mental health problems, and self-reported sexual behavior. For boys and girls, peer influence and conduct problems predicted sexual experience, and family dysfunction was related to negative peer influence. Greater rejection sensitivity was related to less sexual experience for boys and girls. The final path model revealed indirect effects of family dysfunction on boys' but not girls' sexual experiences. Findings underscore the utility of an ecological approach to understand social and personal mechanisms that increase risk and mitigate negative outcomes among emotionally and behaviorally disordered boys and girls in therapeutic day schools.

EEG as an Indicator of Cerebral Functioning in Postanoxic Coma.

PubMed

Juan, Elsa; Kaplan, Peter W; Oddo, Mauro; Rossetti, Andrea O

2015-12-01

Postanoxic coma after cardiac arrest is one of the most serious acute cerebral conditions and a frequent cause of admission to critical care units. Given substantial improvement of outcome over the recent years, a reliable and timely assessment of clinical evolution and prognosis is essential in this context, but may be challenging. In addition to the classic neurologic examination, EEG is increasingly emerging as an important tool to assess cerebral functions noninvasively. Although targeted temperature management and related sedation may delay clinical assessment, EEG provides accurate prognostic information in the early phase of coma. Here, the most frequently encountered EEG patterns in postanoxic coma are summarized and their relations with outcome prediction are discussed. This article also addresses the influence of targeted temperature management on brain signals and the implication of the evolution of EEG patterns over time. Finally, the article ends with a view of the future prospects for EEG in postanoxic management and prognostication.

Predicting U.S. Army suicides after hospitalizations with psychiatric diagnoses in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

PubMed Central

Kessler, Ronald C.; Warner, LTC Christopher H.; Ivany, LTC Christopher; Petukhova, Maria V.; Rose, Sherri; Bromet, Evelyn J.; Brown, LTC Millard; Cai, Tianxi; Colpe, Lisa J.; Cox, Kenneth L.; Fullerton, Carol S.; Gilman, Stephen E.; Gruber, Michael J.; Heeringa, Steven G.; Lewandowski-Romps, Lisa; Li, Junlong; Millikan-Bell, Amy M.; Naifeh, James A.; Nock, Matthew K.; Rosellini, Anthony J.; Sampson, Nancy A.; Schoenbaum, Michael; Stein, Murray B.; Wessely, Simon; Zaslavsky, Alan M.; Ursano, Robert J.

2014-01-01

IMPORTANCE The U.S. Army experienced a sharp rise in suicides beginning in 2004. Administrative data show that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder. OBJECTIVE To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded post-hospital care. DESIGN, SETTING, AND PARTICIPANTS There were 53,769 hospitalizations of active duty soldiers in 2004–2009 with ICD-9-CM psychiatric admission diagnoses. Administrative data available prior to hospital discharge abstracted from a wide range of data systems (socio81 demographic, Army career, criminal justice, medical/pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees, penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations. MAIN OUTCOME Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge. RESULTS 68 soldiers died by suicide within 12 months of hospital discharge (12.0% of all Army suicides), equivalent to 263.9 suicides/100,000 person-years compared to 18.5 suicides/100,000 person-years in the total Army. Strongest predictors included socio-demographics (male, late age of enlistment), criminal offenses (verbal violence, weapons possession), prior suicidality, aspects of prior psychiatric inpatient and outpatient treatment, and disorders diagnosed during the focal hospitalizations. 52.9% of post-hospital suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3,824.1 suicides/100,000 person years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse post-hospital outcomes (unintentional injury deaths, suicide attempts, re-hospitalizations). CONCLUSIONS AND RELEVANCE The high concentration of risk of suicides and other adverse outcomes might justify targeting expanded post-hospital interventions to soldiers classified as having highest post-hospital suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects. PMID:25390793

Growth and development in children with classic congenital adrenal hyperplasia.

PubMed

Bonfig, Walter

2017-02-01

Final height outcome in classic congenital adrenal hyperplasia (CAH) has been of interest for many years. With analysis of growth patterns and used glucocorticoid regimens, enhanced treatment strategies have been developed and are still under development. Most of the current reports on final height outcome are confirmative of previous results. Final height data is still reported in cohorts that were diagnosed clinically and not by newborn screening. Clinical diagnosis of CAH leads to delayed diagnosis especially of simple virilizing CAH with significantly advanced bone age resulting in early pubertal development and reduced final height. In contrast salt-wasting CAH is diagnosed at an earlier stage in most cases resulting in better final height outcome in some cohorts. Nevertheless, final height outcome in patients with CAH treated with glucocorticoids is lower than the population norm and also at the lower end of genetic potential. Achievement of regular adult height is still a challenge with conventional glucocorticoid treatment in patients with CAH, which is why new hydrocortisone formulations and new treatment options for CAH are underway.

Differentiating neural systems mediating the acquisition versus expression of goal-directed and habitual behavioral control

PubMed Central

Liljeholm, Mimi; Dunne, Simon; O'Doherty, John P.

2015-01-01

Considerable behavioral data indicates that operant actions can become habitual, as evidenced by insensitivity to changes in the action-outcome contingency and in subjective outcome values. Notably, although several studies have investigated the neural substrates of habits, none has clearly differentiated the areas of the human brain that support habit formation from those that implement habitual control. We scanned participants with fMRI as they learned and performed an operant task in which the conditional structure of the environment encouraged either goal-directed encoding of the consequences of actions, or a habit-like mapping of actions to antecedent cues. Participants were also scanned during a subsequent assessment of insensitivity to outcome devaluation. We identified dissociable roles of the cerebellum and ventral striatum, across learning and test performance, in behavioral insensitivity to outcome devaluation. We also show that the inferior parietal lobule – an area previously implicated in several aspects of goal-directed action selection, including the attribution of intent and awareness of agency – predicts sensitivity to outcome devaluation. Finally, we reveal a potential functional homology between the human subgenual cortex and rodent infralimbic cortex in the implementation of habitual control. In summary, our findings suggest a broad systems division, at the cortical and subcortical levels, between brain areas mediating the encoding and expression of action-outcome and stimulus-response associations. PMID:25892332

New Medical and Surgical Insights Into Neonatal Necrotizing Enterocolitis: A Review.

PubMed

Frost, Brandy L; Modi, Biren P; Jaksic, Tom; Caplan, Michael S

2017-01-01

Necrotizing enterocolitis (NEC) has long remained a significant cause of morbidity and mortality in neonatal intensive care units. While the mainstay of treatment for this devastating condition remains largely supportive, research efforts continue to be directed toward understanding pathophysiology as well as how best to approach surgical management when indicated. In this review, we first examine recent medical observations, including overviews on the microbiome and a brief review of the use of probiotics. Next, we discuss the use of biomarkers and how clinicians may be able to use them in the future to predict the course of disease and, perhaps, the need for surgical intervention. We then provide an overview on the use of exclusive human milk feeding and the utility of this approach in preventing NEC. Finally, we discuss recent developments in the surgical management of NEC, beginning with indications for surgery and following with a section on technical surgical considerations, including peritoneal drain vs laparotomy. The review concludes with outcomes from infants with surgically treated NEC. Although medical treatment options for NEC are largely unchanged, understanding of the disease continues to evolve. As new research methods are developed, NEC pathophysiology can be more completely understood. In time, it is hoped that data from ongoing and planned clinical trials will allow us to routinely add targeted preventive measures in addition to human milk, such as prebiotics and probiotics, to the management of high-risk infants. In addition, the discovery of novel biomarkers may not only prove useful in predicting severity of illness but also will hopefully allow for identification of the disease prior to onset of clinical signs. Finally, continued investigation into optimizing surgical outcomes is essential in this population of infants, many of whom require long-term parenteral therapy and intestinal rehabilitation.

Role of Subdural Electrocorticography in Prediction of Long-Term Seizure Outcome in Epilepsy Surgery

ERIC Educational Resources Information Center

Asano, Eishi; Juhasz, Csaba; Shah, Aashit; Sood, Sandeep; Chugani, Harry T.

2009-01-01

Since prediction of long-term seizure outcome using preoperative diagnostic modalities remains suboptimal in epilepsy surgery, we evaluated whether interictal spike frequency measures obtained from extraoperative subdural electrocorticography (ECoG) recording could predict long-term seizure outcome. This study included 61 young patients (age…

Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

PubMed

Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

2018-05-15

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

Predicting couple therapy outcomes based on speech acoustic features

PubMed Central

Nasir, Md; Baucom, Brian Robert; Narayanan, Shrikanth

2017-01-01

Automated assessment and prediction of marital outcome in couples therapy is a challenging task but promises to be a potentially useful tool for clinical psychologists. Computational approaches for inferring therapy outcomes using observable behavioral information obtained from conversations between spouses offer objective means for understanding relationship dynamics. In this work, we explore whether the acoustics of the spoken interactions of clinically distressed spouses provide information towards assessment of therapy outcomes. The therapy outcome prediction task in this work includes detecting whether there was a relationship improvement or not (posed as a binary classification) as well as discerning varying levels of improvement or decline in the relationship status (posed as a multiclass recognition task). We use each interlocutor’s acoustic speech signal characteristics such as vocal intonation and intensity, both independently and in relation to one another, as cues for predicting the therapy outcome. We also compare prediction performance with one obtained via standardized behavioral codes characterizing the relationship dynamics provided by human experts as features for automated classification. Our experiments, using data from a longitudinal clinical study of couples in distressed relations, showed that predictions of relationship outcomes obtained directly from vocal acoustics are comparable or superior to those obtained using human-rated behavioral codes as prediction features. In addition, combining direct signal-derived features with manually coded behavioral features improved the prediction performance in most cases, indicating the complementarity of relevant information captured by humans and machine algorithms. Additionally, considering the vocal properties of the interlocutors in relation to one another, rather than in isolation, showed to be important for improving the automatic prediction. This finding supports the notion that behavioral outcome, like many other behavioral aspects, is closely related to the dynamics and mutual influence of the interlocutors during their interaction and their resulting behavioral patterns. PMID:28934302

Using social cognitive theory to explain discretionary, "leisure-time" physical exercise among high school students.

PubMed

Winters, Eric R; Petosa, Rick L; Charlton, Thomas E

2003-06-01

To examine whether knowledge of high school students' actions of self-regulation, and perceptions of self-efficacy to overcome exercise barriers, social situation, and outcome expectation will predict non-school related moderate and vigorous physical exercise. High school students enrolled in introductory Physical Education courses completed questionnaires that targeted selected Social Cognitive Theory variables. They also self-reported their typical "leisure-time" exercise participation using a standardized questionnaire. Bivariate correlation statistic and hierarchical regression were conducted on reports of moderate and vigorous exercise frequency. Each predictor variable was significantly associated with measures of moderate and vigorous exercise frequency. All predictor variables were significant in the final regression model used to explain vigorous exercise. After controlling for the effects of gender, the psychosocial variables explained 29% of variance in vigorous exercise frequency. Three of four predictor variables were significant in the final regression equation used to explain moderate exercise. The final regression equation accounted for 11% of variance in moderate exercise frequency. Professionals who attempt to increase the prevalence of physical exercise through educational methods should focus on the psychosocial variables utilized in this study.

Predicting the outcome of roulette

NASA Astrophysics Data System (ADS)

Small, Michael; Tse, Chi Kong

2012-09-01

There have been several popular reports of various groups exploiting the deterministic nature of the game of roulette for profit. Moreover, through its history, the inherent determinism in the game of roulette has attracted the attention of many luminaries of chaos theory. In this paper, we provide a short review of that history and then set out to determine to what extent that determinism can really be exploited for profit. To do this, we provide a very simple model for the motion of a roulette wheel and ball and demonstrate that knowledge of initial position, velocity, and acceleration is sufficient to predict the outcome with adequate certainty to achieve a positive expected return. We describe two physically realizable systems to obtain this knowledge both incognito and in situ. The first system relies only on a mechanical count of rotation of the ball and the wheel to measure the relevant parameters. By applying these techniques to a standard casino-grade European roulette wheel, we demonstrate an expected return of at least 18%, well above the -2.7% expected of a random bet. With a more sophisticated, albeit more intrusive, system (mounting a digital camera above the wheel), we demonstrate a range of systematic and statistically significant biases which can be exploited to provide an improved guess of the outcome. Finally, our analysis demonstrates that even a very slight slant in the roulette table leads to a very pronounced bias which could be further exploited to substantially enhance returns.

ChemProt-2.0: visual navigation in a disease chemical biology database

PubMed Central

Kim Kjærulff, Sonny; Wich, Louis; Kringelum, Jens; Jacobsen, Ulrik P.; Kouskoumvekaki, Irene; Audouze, Karine; Lund, Ole; Brunak, Søren; Oprea, Tudor I.; Taboureau, Olivier

2013-01-01

ChemProt-2.0 (http://www.cbs.dtu.dk/services/ChemProt-2.0) is a public available compilation of multiple chemical–protein annotation resources integrated with diseases and clinical outcomes information. The database has been updated to >1.15 million compounds with 5.32 millions bioactivity measurements for 15 290 proteins. Each protein is linked to quality-scored human protein–protein interactions data based on more than half a million interactions, for studying diseases and biological outcomes (diseases, pathways and GO terms) through protein complexes. In ChemProt-2.0, therapeutic effects as well as adverse drug reactions have been integrated allowing for suggesting proteins associated to clinical outcomes. New chemical structure fingerprints were computed based on the similarity ensemble approach. Protein sequence similarity search was also integrated to evaluate the promiscuity of proteins, which can help in the prediction of off-target effects. Finally, the database was integrated into a visual interface that enables navigation of the pharmacological space for small molecules. Filtering options were included in order to facilitate and to guide dynamic search of specific queries. PMID:23185041

Research priorities for gender nonconforming/transgender youth: gender identity development and biopsychosocial outcomes.

PubMed

Olson-Kennedy, Johanna; Cohen-Kettenis, Peggy T; Kreukels, Baudewijntje P C; Meyer-Bahlburg, Heino F L; Garofalo, Robert; Meyer, Walter; Rosenthal, Stephen M

2016-04-01

The review summarizes relevant research focused on prevalence and natural history of gender nonconforming/transgender youth, and outcomes of currently recommended clinical practice guidelines. This review identifies gaps in knowledge, and provides recommendations foci for future research. Increasing numbers of gender nonconforming youth are presenting for care. Clinically useful information for predicting individual psychosexual development pathways is lacking. Transgender youth are at high risk for poor medical and psychosocial outcomes. Longitudinal data examining the impact of early social transition and medical interventions are sparse. Existing tools to understand gender identity and quantify gender dysphoria need to be reconfigured to study a more diverse cohort of transgender individuals. Increasingly, biomedical data are beginning to change the trajectory of scientific investigation. Extensive research is needed to improve understanding of gender dysphoria, and transgender experience, particularly among youth. Recommendations include identification of predictors of persistence of gender dysphoria from childhood into adolescence, and a thorough investigation into the impact of interventions for transgender youth. Finally, examining the social environments of transgender youth is critical for the development of appropriate interventions necessary to improve the lives of transgender people.

A unified procedure for meta-analytic evaluation of surrogate end points in randomized clinical trials

PubMed Central

Dai, James Y.; Hughes, James P.

2012-01-01

The meta-analytic approach to evaluating surrogate end points assesses the predictiveness of treatment effect on the surrogate toward treatment effect on the clinical end point based on multiple clinical trials. Definition and estimation of the correlation of treatment effects were developed in linear mixed models and later extended to binary or failure time outcomes on a case-by-case basis. In a general regression setting that covers nonnormal outcomes, we discuss in this paper several metrics that are useful in the meta-analytic evaluation of surrogacy. We propose a unified 3-step procedure to assess these metrics in settings with binary end points, time-to-event outcomes, or repeated measures. First, the joint distribution of estimated treatment effects is ascertained by an estimating equation approach; second, the restricted maximum likelihood method is used to estimate the means and the variance components of the random treatment effects; finally, confidence intervals are constructed by a parametric bootstrap procedure. The proposed method is evaluated by simulations and applications to 2 clinical trials. PMID:22394448

Combining Spot Sign and Intracerebral Hemorrhage Score to Estimate Functional Outcome: Analysis From the PREDICT Cohort.

PubMed

Schneider, Hauke; Huynh, Thien J; Demchuk, Andrew M; Dowlatshahi, Dar; Rodriguez-Luna, David; Silva, Yolanda; Aviv, Richard; Dzialowski, Imanuel

2018-06-01

The intracerebral hemorrhage (ICH) score is the most commonly used grading scale for stratifying functional outcome in patients with acute ICH. We sought to determine whether a combination of the ICH score and the computed tomographic angiography spot sign may improve outcome prediction in the cohort of a prospective multicenter hemorrhage trial. Prospectively collected data from 241 patients from the observational PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign) were analyzed. Functional outcome at 3 months was dichotomized using the modified Rankin Scale (0-3 versus 4-6). Performance of (1) the ICH score and (2) the spot sign ICH score-a scoring scale combining ICH score and spot sign number-was tested. Multivariable analysis demonstrated that ICH score (odds ratio, 3.2; 95% confidence interval, 2.2-4.8) and spot sign number (n=1: odds ratio, 2.7; 95% confidence interval, 1.1-7.4; n>1: odds ratio, 3.8; 95% confidence interval, 1.2-17.1) were independently predictive of functional outcome at 3 months with similar odds ratios. Prediction of functional outcome was not significantly different using the spot sign ICH score compared with the ICH score alone (spot sign ICH score area under curve versus ICH score area under curve: P =0.14). In the PREDICT cohort, a prognostic score adding the computed tomographic angiography-based spot sign to the established ICH score did not improve functional outcome prediction compared with the ICH score. © 2018 American Heart Association, Inc.

How outcome prediction could affect patient decision making in knee replacements: a qualitative study.

PubMed

Barlow, Timothy; Scott, Patricia; Griffin, Damian; Realpe, Alba

2016-07-22

There is approximately a 17 % dissatisfaction rate with knee replacements. Calls for tools that can pre-operatively identify patients at risk of being dissatisfied have been widespread. However, it is not known how to present such information to patients, how it would affect their decision making process, and at what part of the pathway such a tool should be used. Using focus groups involving 12 participants and in-depth interviews with 10 participants, we examined how individual predictions of outcome could affect patients' decision making by providing fictitious predictions to patients at different stages of treatment. A thematic analysis was used to analyse the data. Our results demonstrate several interesting findings. Firstly, patients who have received information from friends and family are unwilling to adjust their expectation of outcome down (i.e. to a worse outcome), but highly willing to adjust it up (to a better outcome). This is an example of the optimism bias, and suggests that the effect on expectation of a poor outcome prediction would be blunted. Secondly, patients generally wanted a "bottom line" outcome, rather than lots of detail. Thirdly, patients who were earlier in their treatment for osteoarthritis were more likely to find the information useful, and it was more likely to affect their decision, than patients later in their treatment pathway. This research suggest that an outcome prediction tool would have most effect targeted towards people at the start of their treatment pathway, with a "bottom line" prediction of outcome. However, any effect on expectation and decision making of a poor outcome prediction is likely to be blunted by the optimism bias. These findings merit replication in a larger sample size.

Can we predict failure in couple therapy early enough to enhance outcome?

PubMed

Pepping, Christopher A; Halford, W Kim; Doss, Brian D

2015-02-01

Feedback to therapists based on systematic monitoring of individual therapy progress reliably enhances therapy outcome. An implicit assumption of therapy progress feedback is that clients unlikely to benefit from therapy can be detected early enough in the course of therapy for corrective action to be taken. To explore the possibility of using feedback of therapy progress to enhance couple therapy outcome, the current study tested whether weekly therapy progress could detect off-track clients early in couple therapy. In an effectiveness trial of couple therapy, 136 couples were monitored weekly on relationship satisfaction and an expert derived algorithm was used to attempt to predict eventual therapy outcome. As expected, the algorithm detected a significant proportion of couples who did not benefit from couple therapy at Session 3, but prediction was substantially improved at Session 4 so that eventual outcome was accurately predicted for 70% of couples, with little improvement of prediction thereafter. More sophisticated algorithms might enhance prediction accuracy, and a trial of the effects of therapy progress feedback on couple therapy outcome is needed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Termination of Resuscitation Rules to Predict Neurological Outcomes in Out-of-Hospital Cardiac Arrest for an Intermediate Life Support Prehospital System.

PubMed

Cheong, Randy Wang Long; Li, Huihua; Doctor, Nausheen Edwin; Ng, Yih Yng; Goh, E Shaun; Leong, Benjamin Sieu-Hon; Gan, Han Nee; Foo, David; Tham, Lai Peng; Charles, Rabind; Ong, Marcus Eng Hock

2016-01-01

Futile resuscitation can lead to unnecessary transports for out-of-hospital cardiac arrest (OHCA). The Basic Life Support (BLS) and Advanced Life Support (ALS) termination of resuscitation (TOR) guidelines have been validated with good results in North America. This study aims to evaluate the performance of these two rules in predicting neurological outcomes of OHCA patients in Singapore, which has an intermediate life support Emergency Medical Services (EMS) system. A retrospective cohort study was carried out on Singapore OHCA data collected from April 2010 to May 2012 for the Pan-Asian Resuscitation Outcomes Study (PAROS). The outcomes of each rule were compared to the actual neurological outcomes of the patients. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and predicted transport rates of each test were evaluated. A total of 2,193 patients had cardiac arrest of presumed cardiac etiology. TOR was recommended for 1,411 patients with the BLS-TOR rule, with a specificity of 100% (91.9, 100.0) for predicting poor neurological outcomes, PPV 100% (99.7, 100.0), sensitivity 65.7% (63.6, 67.7), NPV 5.6% (4.1, 7.5), and transportation rate 35.6%. Using the ALS-TOR rule, TOR was recommended for 587 patients, specificity 100% (91.9, 100.0) for predicting poor neurological outcomes, PPV 100% (99.4, 100.0), sensitivity 27.3% (25.4, 29.3), NPV 2.7% (2.0, 3.7), and transportation rate 73.2%. BLS-TOR predicted survival (any neurological outcome) with specificity 93.4% (95% CI 85.3, 97.8) versus ALS-TOR 98.7% (95% CI 92.9, 99.8). Both the BLS and ALS-TOR rules had high specificities and PPV values in predicting neurological outcomes, the BLS-TOR rule had a lower predicted transport rate while the ALS-TOR rule was more accurate in predicting futility of resuscitation. Further research into unique local cultural issues would be useful to evaluate the feasibility of any system-wide implementation of TOR.

Client Predictors of Short-term Psychotherapy Outcomes among Asian and White American Outpatients

PubMed Central

Kim, Jin E.; Zane, Nolan W.; Blozis, Shelley A.

2015-01-01

Purpose To examine predictors of psychotherapy outcomes, focusing on client characteristics that are especially salient for culturally diverse clients. Method Sixty clients (31 women; 27 White Americans, 33 Asian Americans) participated in this treatment study. Client characteristics were measured at pre-treatment, and outcomes were measured post-fourth session via therapist ratings of functioning and symptomatology. Regression analyses were utilized to test for predictors of outcomes, and bootstrap analyses were utilized to test for mediators. Results Higher levels of somatic symptoms predicted lower psychosocial functioning at post-treatment. Avoidant coping style predicted more negative symptoms and more psychological discomfort. Non-English language preference predicted worse outcomes; this effect was mediated by an avoidant coping style. Conclusions Language preference, avoidant coping style, and somatic symptoms predicted treatment outcome in a culturally diverse sample. Findings suggest that race/ethnicity-related variables may function through mediating proximal variables to affect outcomes. PMID:22836681

Laser-assisted subepithelial keratectomy versus epipolis laser in situ keratomileusis for myopia: a meta-analysis of clinical outcomes.

PubMed

Wen, Daizong; Huang, Jinhai; Li, Xuexi; Savini, Giacomo; Feng, Yifan; Lin, Qiaoya; Wang, Qinmei

2014-01-01

To identify possible differences between laser-assisted subepithelial keratectomy and epipolis laser in situ keratomileusis for myopia. Meta-analysis. Patients from previously reported comparative studies treated by laser-assisted subepithelial keratectomy versus epipolis laser in situ keratomileusis. A systematic literature retrieval was conducted in the MEDLINE, EMBASE and Cochrane Library, up to January 2013. The included studies were subject to a meta-analysis using a RevMan 5.1 version software. The differences in efficacy, predictability, safety, epithelial healing time, pain perception and corneal haze formation. A total of six studies involving 517 eyes were included. There were no statistically significant differences in the final proportion of eyes with uncorrected visual acuity of 6/6 or better (P = 0.43), mean postoperative uncorrected visual acuity (P = 0.53), final proportion of eyes with refraction within ± 0.50 D (P = 0.62) and ± 1.00 D (P = 0.16) of target, final proportion of eyes losing two or more lines of best spectacle-corrected visual acuity (P = 1.00), healing time of corneal epithelium (P = 0.58), final proportion of eyes with corneal haze grade 0.5 or higher (P = 0.26), and corneal haze levels (P = 0.36). There were no significant differences in efficacy, predictability, safety, epithelial healing time and corneal haze formation between laser-assisted subepithelial keratectomy and epipolis laser in situ keratomileusis, but the result was limited. Future more data are required to detect the potential differences between the two procedures. © 2013 Royal Australian and New Zealand College of Ophthalmologists.

Percutaneous internal fixation of proximal fifth metatarsal jones fractures (Zones II and III) with Charlotte Carolina screw and bone marrow aspirate concentrate: an outcome study in athletes.

PubMed

Murawski, Christopher D; Kennedy, John G

2011-06-01

Internal fixation is a popular first-line treatment method for proximal fifth metatarsal Jones fractures in athletes; however, nonunions and screw breakage can occur, in part because of nonspecific fixation hardware and poor blood supply. To report the results from 26 patients who underwent percutaneous internal fixation with a specialized screw system of a proximal fifth metatarsal Jones fracture (zones II and III) and bone marrow aspirate concentrate. Case series; Level of evidence, 4. Percutaneous internal fixation for a proximal fifth metatarsal Jones fracture (zones II and III) was performed on 26 athletic patients (mean age, 27.47 years; range, 18-47). All patients were competing at some level of sport and were assessed preoperatively and postoperatively using the Foot and Ankle Outcome Score and SF-12 outcome scores. The mean follow-up time was 20.62 months (range, 12-28). Of the 26 fractures, 17 were traditional zone II Jones fractures, and the remaining 9 were zone III proximal diaphyseal fractures. The mean Foot and Ankle Outcome Score significantly increased, from 51.15 points preoperatively (range, 14-69) to 90.91 at final follow-up (range, 71-100; P < .01). The mean physical component of the SF-12 score significantly improved, from 25.69 points preoperatively (range, 6-39) to 54.62 at final follow-up (range, 32-62; P < .01). The mean mental component of the SF-12 score also significantly improved, from 28.20 points preoperatively (range, 14-45) to 58.41 at final follow-up (range, 36-67; P < .01). The mean time to fracture healing on standard radiographs was 5 weeks after surgery (range, 4-24). Two patients did not return to their previous levels of sporting activity. One patient experienced a delayed union, and 1 healed but later refractured. Percutaneous internal fixation of proximal fifth metatarsal Jones fractures, with a Charlotte Carolina screw and bone marrow aspirate concentrate, provides more predictable results while permitting athletes a return to sport at their previous levels of competition, with few complications.

More than resisting temptation: Beneficial habits mediate the relationship between self-control and positive life outcomes.

PubMed

Galla, Brian M; Duckworth, Angela L

2015-09-01

Why does self-control predict such a wide array of positive life outcomes? Conventional wisdom holds that self-control is used to effortfully inhibit maladaptive impulses, yet this view conflicts with emerging evidence that self-control is associated with less inhibition in daily life. We propose that one of the reasons individuals with better self-control use less effortful inhibition, yet make better progress on their goals is that they rely on beneficial habits. Across 6 studies (total N = 2,274), we found support for this hypothesis. In Study 1, habits for eating healthy snacks, exercising, and getting consistent sleep mediated the effect of self-control on both increased automaticity and lower reported effortful inhibition in enacting those behaviors. In Studies 2 and 3, study habits mediated the effect of self-control on reduced motivational interference during a work-leisure conflict and on greater ability to study even under difficult circumstances. In Study 4, homework habits mediated the effect of self-control on classroom engagement and homework completion. Study 5 was a prospective longitudinal study of teenage youth who participated in a 5-day meditation retreat. Better self-control before the retreat predicted stronger meditation habits 3 months after the retreat, and habits mediated the effect of self-control on successfully accomplishing meditation practice goals. Finally, in Study 6, study habits mediated the effect of self-control on homework completion and 2 objectively measured long-term academic outcomes: grade point average and first-year college persistence. Collectively, these results suggest that beneficial habits-perhaps more so than effortful inhibition-are an important factor linking self-control with positive life outcomes. (c) 2015 APA, all rights reserved).

More than Resisting Temptation: Beneficial Habits Mediate the Relationship between Self-Control and Positive Life Outcomes

PubMed Central

Galla, Brian M.; Duckworth, Angela L.

2015-01-01

Why does self-control predict such a wide array of positive life outcomes? Conventional wisdom holds that self-control is used to effortfully inhibit maladaptive impulses, yet this view conflicts with emerging evidence that self-control is associated with less inhibition in daily life. We propose that one of the reasons individuals with better self-control use less effortful inhibition, yet make better progress on their goals is that they rely on beneficial habits. Across six studies (total N = 2,274), we found support for this hypothesis. In Study 1, habits for eating healthy snacks, exercising, and getting consistent sleep mediated the effect of self-control on both increased automaticity and lower reported effortful inhibition in enacting those behaviors. In Studies 2 and 3, study habits mediated the effect of self-control on reduced motivational interference during a work-leisure conflict and on greater ability to study even under difficult circumstances. In Study 4, homework habits mediated the effect of self-control on classroom engagement and homework completion. Study 5 was a prospective longitudinal study of teenage youth who participated in a five-day meditation retreat. Better self-control before the retreat predicted stronger meditation habits three months after the retreat, and habits mediated the effect of self-control on successfully accomplishing meditation practice goals. Finally, in Study 6, study habits mediated the effect of self-control on homework completion and two objectively measured long-term academic outcomes: grade point average and first-year college persistence. Collectively, these results suggest that beneficial habits--perhaps more so than effortful inhibition--are an important factor linking self-control with positive life outcomes. PMID:25643222

Breast cancer treatment decision making among Latinas and non-Latina Whites: a communication model predicting decisional outcomes and quality of life.

PubMed

Yanez, Betina; Stanton, Annette L; Maly, Rose C

2012-09-01

Deciding among medical treatment options is a pivotal event following cancer diagnosis, a task that can be particularly daunting for individuals uncomfortable with communication in a medical context. Few studies have explored the surgical decision-making process and associated outcomes among Latinas. We propose a model to elucidate pathways through which acculturation (indicated by language use) and reports of communication effectiveness specific to medical decision making contribute to decisional outcomes (i.e., congruency between preferred and actual involvement in decision making, treatment satisfaction) and quality of life among Latinas and non-Latina White women with breast cancer. Latinas (N = 326) and non-Latina Whites (N = 168) completed measures six months after breast cancer diagnosis, and quality of life was assessed 18 months after diagnosis. Structural equation modeling was used to examine relationships between language use, communication effectiveness, and outcomes. Among Latinas, 63% reported congruency in decision making, whereas 76% of non-Latina Whites reported congruency. In Latinas, greater use of English was related to better reported communication effectiveness. Effectiveness in communication was not related to congruency in decision making, but several indicators of effectiveness in communication were related to greater treatment satisfaction, as was greater congruency in decision making. Greater treatment satisfaction predicted more favorable quality of life. The final model fit the data well only for Latinas. Differences in quality of life and effectiveness in communication were observed between racial/ethnic groups. Findings underscore the importance of developing targeted interventions for physicians and Latinas with breast cancer to enhance communication in decision making. PsycINFO Database Record (c) 2012 APA, all rights reserved.

How clients "change emotion with emotion": A programme of research on emotional processing.

PubMed

Pascual-Leone, Antonio

2018-03-01

This paper reviews a body of research that has examined Pascual-Leone and Greenberg's sequential model of emotional processing or used its accompanying measure (the Classification of Affective Meaning States). Research from 24 studies using a plurality of methods examined process-outcome relationships from micro to macro levels of observation and builds support for emotional transformation as a possible causal mechanism of change in psychotherapy. A pooled sample of 310 clinical and 130 sub-clinical cases have been studied, reflecting the process of 7 different treatment approaches in addressing over 5 different presenting clinical problems (including depression, anxiety, relational trauma, and personality disorders). The initial findings on this model support the hypothesis that emotional transformation occurs in specific canonical sequences and these show large effects in the prediction of positive treatment outcomes. This model is the first in the field of psychotherapy to show how non-linear temporal patterns of moment-by-moment process relate to the unfolding of increasingly larger changes to create good psychotherapy treatment outcomes. Finally, clinical application of the model is also considered as a template for case formulations focused on emotion. Clinical or methodological significance of this article: This review article examines research on a specific model of emotional processing. (i) Experiencing certain key emotions during psychotherapy seems to predict good treatment outcomes, at both the session and treatment levels. (ii) There is also evidence to suggest that these productive emotional experiences unfold in an ordered pattern. Moreover, (iii) support for this way of understanding emotional processing comes from a number of very different treatment approaches and for several kinds of major disorders.

Effect of Geometric Parameters on Formability and Strain Path During Tube Hydrforming Process

NASA Astrophysics Data System (ADS)

Omar, A.; Harisankar, K. R.; Tewari, Asim; Narasimhan, K.

2016-08-01

Forming limit diagram (FLD) is an important tool to measure the material's formability for metal forming processes. In order to successfully manufacture a component through tube hydroforming process it is very important to know the effect of material properties, process and geometrical parameters on the outcome of finished product. This can be obtained by running a finite element code which not only saves time and money but also gives a result with considerable accuracy. Therefore, in this paper the mutual effect of diameter as well as thickness has been studied. Firstly the finite element based prediction is carried out to assess the formability of seamless and welded tubes with varying thickness. Later on, effect of varying diameter and thickness on strain path is predicted using statistical based regression analysis. Finally, the mutual effect of varying material property alongwith varying thickness and diameter on constraint factor is studied.

Assessment of patients for orthognathic surgery.

PubMed

Bailey, L J; Proffit, W R; White, R

1999-12-01

Rapid advances in orthognathic surgery now allow the clinician to treat severe dentofacial deformities that were once only manageable by orthodontic camouflage. These cases were often compromised with unacceptable facial esthetics and unstable occlusal results. Over the past 25 years, there have been numerous improvements in technology and the surgical management of dentofacial deformities. These progressions now allow more predictable surgical outcomes, which ensure patient satisfaction. Not all patients are candidates for surgical treatment; therefore, patient assessment and selection remains paramount in the process of diagnosing and treatment planning for this type of irreversible treatment. The inclusion of patients in the decision-making process increases their awareness and acceptance of the final result. The past three decades indicate an increased usage of orthodontic treatment by both children and adults. Patient demographic profiles for severe occlusal and facial characteristics are presented in an effort to understand the epidemiological factors of malocclusion and predict the population's need for this service.

Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring

PubMed Central

Nigam, Aastha; Dambanemuya, Henry K.; Joshi, Madhav; Chawla, Nitesh V.

2017-01-01

Abstract Peace processes are complex, protracted, and contentious involving significant bargaining and compromising among various societal and political stakeholders. In civil war terminations, it is pertinent to measure the pulse of the nation to ensure that the peace process is responsive to citizens' concerns. Social media yields tremendous power as a tool for dialogue, debate, organization, and mobilization, thereby adding more complexity to the peace process. Using Colombia's final peace agreement and national referendum as a case study, we investigate the influence of two important indicators: intergroup polarization and public sentiment toward the peace process. We present a detailed linguistic analysis to detect intergroup polarization and a predictive model that leverages Tweet structure, content, and user-based features to predict public sentiment toward the Colombian peace process. We demonstrate that had proaccord stakeholders leveraged public opinion from social media, the outcome of the Colombian referendum could have been different. PMID:29235916

When can employees have a family life? The effects of daily workload and affect on work-family conflict and social behaviors at home.

PubMed

Ilies, Remus; Schwind, Kelly M; Wagner, David T; Johnson, Michael D; DeRue, D Scott; Ilgen, Daniel R

2007-09-01

This article presents a longitudinal examination of antecedents and outcomes of work-to-family conflict. A total of 106 employees participating in an experience-sampling study were asked to respond to daily surveys both at work and at home, and their spouses were interviewed daily via telephone for a period of 2 weeks. Intraindividual analyses revealed that employees' perceptions of workload predicted work-to-family conflict over time, even when controlling for the number of hours spent at work. Workload also influenced affect at work, which in turn influenced affect at home. Finally, perhaps the most interesting finding in this study was that employees' behaviors in the family domain (reported by spouses) were predicted by the employees' perceptions of work-to-family conflict and their positive affect at home. (c) 2007 APA.

Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring.

PubMed

Nigam, Aastha; Dambanemuya, Henry K; Joshi, Madhav; Chawla, Nitesh V

2017-12-01

Peace processes are complex, protracted, and contentious involving significant bargaining and compromising among various societal and political stakeholders. In civil war terminations, it is pertinent to measure the pulse of the nation to ensure that the peace process is responsive to citizens' concerns. Social media yields tremendous power as a tool for dialogue, debate, organization, and mobilization, thereby adding more complexity to the peace process. Using Colombia's final peace agreement and national referendum as a case study, we investigate the influence of two important indicators: intergroup polarization and public sentiment toward the peace process. We present a detailed linguistic analysis to detect intergroup polarization and a predictive model that leverages Tweet structure, content, and user-based features to predict public sentiment toward the Colombian peace process. We demonstrate that had proaccord stakeholders leveraged public opinion from social media, the outcome of the Colombian referendum could have been different.

Algorithm for predicting death among older adults in the home care setting: study protocol for the Risk Evaluation for Support: Predictions for Elder-life in the Community Tool (RESPECT)

PubMed Central

Manuel, Douglas G; Taljaard, Monica; Chalifoux, Mathieu; Bennett, Carol; Costa, Andrew P; Bronskill, Susan; Kobewka, Daniel; Tanuseputro, Peter

2016-01-01

Introduction Older adults living in the community often have multiple, chronic conditions and functional impairments. A challenge for healthcare providers working in the community is the lack of a predictive tool that can be applied to the broad spectrum of mortality risks observed and may be used to inform care planning. Objective To predict survival time for older adults in the home care setting. The final mortality risk algorithm will be implemented as a web-based calculator that can be used by older adults needing care and by their caregivers. Design Open cohort study using the Resident Assessment Instrument for Home Care (RAI-HC) data in Ontario, Canada, from 1 January 2007 to 31 December 2013. Participants The derivation cohort will consist of ∼437 000 older adults who had an RAI-HC assessment between 1 January 2007 and 31 December 2012. A split sample validation cohort will include ∼122 000 older adults with an RAI-HC assessment between 1 January and 31 December 2013. Main outcome measures Predicted survival from the time of an RAI-HC assessment. All deaths (n≈245 000) will be ascertained through linkage to a population-based registry that is maintained by the Ministry of Health in Ontario. Statistical analysis Proportional hazards regression will be estimated after assessment of assumptions. Predictors will include sociodemographic factors, social support, health conditions, functional status, cognition, symptoms of decline and prior healthcare use. Model performance will be evaluated for 6-month and 12-month predicted risks, including measures of calibration (eg, calibration plots) and discrimination (eg, c-statistics). The final algorithm will use combined development and validation data. Ethics and dissemination Research ethics approval has been granted by the Sunnybrook Health Sciences Centre Review Board. Findings will be disseminated through presentations at conferences and in peer-reviewed journals. Trial registration number NCT02779309, Pre-results. PMID:27909039

Presurgery resting-state local graph-theory measures predict neurocognitive outcomes after brain surgery in temporal lobe epilepsy.

PubMed

Doucet, Gaelle E; Rider, Robert; Taylor, Nathan; Skidmore, Christopher; Sharan, Ashwini; Sperling, Michael; Tracy, Joseph I

2015-04-01

This study determined the ability of resting-state functional connectivity (rsFC) graph-theory measures to predict neurocognitive status postsurgery in patients with temporal lobe epilepsy (TLE) who underwent anterior temporal lobectomy (ATL). A presurgical resting-state functional magnetic resonance imaging (fMRI) condition was collected in 16 left and 16 right TLE patients who underwent ATL. In addition, patients received neuropsychological testing pre- and postsurgery in verbal and nonverbal episodic memory, language, working memory, and attention domains. Regarding the functional data, we investigated three graph-theory properties (local efficiency, distance, and participation), measuring segregation, integration and centrality, respectively. These measures were only computed in regions of functional relevance to the ictal pathology, or the cognitive domain. Linear regression analyses were computed to predict the change in each neurocognitive domain. Our analyses revealed that cognitive outcome was successfully predicted with at least 68% of the variance explained in each model, for both TLE groups. The only model not significantly predictive involved nonverbal episodic memory outcome in right TLE. Measures involving the healthy hippocampus were the most common among the predictors, suggesting that enhanced integration of this structure with the rest of the brain may improve cognitive outcomes. Regardless of TLE group, left inferior frontal regions were the best predictors of language outcome. Working memory outcome was predicted mostly by right-sided regions, in both groups. Overall, the results indicated our integration measure was the most predictive of neurocognitive outcome. In contrast, our segregation measure was the least predictive. This study provides evidence that presurgery rsFC measures may help determine neurocognitive outcomes following ATL. The results have implications for refining our understanding of compensatory reorganization and predicting cognitive outcome after ATL. The results are encouraging with regard to the clinical relevance of using graph-theory measures in presurgical algorithms in the setting of TLE. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Lack of Early Improvement Predicts Poor Outcome Following Acute Intracerebral Hemorrhage.

PubMed

Yogendrakumar, Vignan; Smith, Eric E; Demchuk, Andrew M; Aviv, Richard I; Rodriguez-Luna, David; Molina, Carlos A; Silva Blas, Yolanda; Dzialowski, Imanuel; Kobayashi, Adam; Boulanger, Jean-Martin; Lum, Cheemun; Gubitz, Gord; Padma, Vasantha; Roy, Jayanta; Kase, Carlos S; Bhatia, Rohit; Ali, Myzoon; Lyden, Patrick; Hill, Michael D; Dowlatshahi, Dar

2018-04-01

There are limited data as to what degree of early neurologic change best relates to outcome in acute intracerebral hemorrhage. We aimed to derive and validate a threshold for early postintracerebral hemorrhage change that best predicts 90-day outcomes. Derivation: retrospective analysis of collated clinical stroke trial data (Virtual International Stroke Trials Archive). retrospective analysis of a prospective multicenter cohort study (Prediction of haematoma growth and outcome in patients with intracerebral haemorrhage using the CT-angiography spot sign [PREDICT]). Neurocritical and ICUs. Patients with acute intracerebral hemorrhage presenting less than 6 hours. Derivation: 552 patients; validation: 275 patients. None. We generated a receiver operating characteristic curve for the association between 24-hour National Institutes of Health Stroke Scale change and clinical outcome. The primary outcome was a modified Rankin Scale score of 4-6 at 90 days; secondary outcomes were other modified Rankin Scale score ranges (modified Rankin Scale, 2-6, 3-6, 5-6, 6). We employed Youden's J Index to select optimal cut points and calculated sensitivity, specificity, and predictive values. We determined independent predictors via multivariable logistic regression. The derived definitions were validated in the PREDICT cohort. Twenty-four-hour National Institutes of Health Stroke Scale change was strongly associated with 90-day outcome with an area under the receiver operating characteristic curve of 0.75. Youden's method showed an optimum cut point at -0.5, corresponding to National Institutes of Health Stroke Scale change of greater than or equal to 0 (a lack of clinical improvement), which was seen in 46%. Early neurologic change accurately predicted poor outcome when defined as greater than or equal to 0 (sensitivity, 65%; specificity, 73%; positive predictive value, 70%; adjusted odds ratio, 5.05 [CI, 3.25-7.85]) or greater than or equal to 4 (sensitivity, 19%; specificity, 98%; positive predictive value, 91%; adjusted odds ratio, 12.24 [CI, 4.08-36.66]). All definitions reproduced well in the validation cohort. Lack of clinical improvement at 24 hours robustly predicted poor outcome and showed good discrimination for individual patients who would do poorly. These findings are useful for prognostication and may also present as a potential early surrogate outcome for future intracerebral hemorrhage treatment trials.

Predicting use of effective vegetable parenting practices with the Model of Goal Directed Behavior.

PubMed

Diep, Cassandra S; Beltran, Alicia; Chen, Tzu-An; Thompson, Debbe; O'Connor, Teresia; Hughes, Sheryl; Baranowski, Janice; Baranowski, Tom

2015-06-01

To model effective vegetable parenting practices using the Model of Goal Directed Vegetable Parenting Practices construct scales. An Internet survey was conducted with parents of pre-school children to assess their agreement with effective vegetable parenting practices and Model of Goal Directed Vegetable Parenting Practices items. Block regression modelling was conducted using the composite score of effective vegetable parenting practices scales as the outcome variable and the Model of Goal Directed Vegetable Parenting Practices constructs as predictors in separate and sequential blocks: demographics, intention, desire (intrinsic motivation), perceived barriers, autonomy, relatedness, self-efficacy, habit, anticipated emotions, perceived behavioural control, attitudes and lastly norms. Backward deletion was employed at the end for any variable not significant at P<0·05. Houston, TX, USA. Three hundred and seven parents (mostly mothers) of pre-school children. Significant predictors in the final model in order of relationship strength included habit of active child involvement in vegetable selection, habit of positive vegetable communications, respondent not liking vegetables, habit of keeping a positive vegetable environment and perceived behavioural control of having a positive influence on child's vegetable consumption. The final model's adjusted R 2 was 0·486. This was the first study to test scales from a behavioural model to predict effective vegetable parenting practices. Further research needs to assess these Model of Goal Directed Vegetable Parenting Practices scales for their (i) predictiveness of child consumption of vegetables in longitudinal samples and (ii) utility in guiding design of vegetable parenting practices interventions.

Using GPS, GIS, and Accelerometer Data to Predict Transportation Modes.

PubMed

Brondeel, Ruben; Pannier, Bruno; Chaix, Basile

2015-12-01

Active transportation is a substantial source of physical activity, which has a positive influence on many health outcomes. A survey of transportation modes for each trip is challenging, time-consuming, and requires substantial financial investments. This study proposes a passive collection method and the prediction of modes at the trip level using random forests. The RECORD GPS study collected real-life trip data from 236 participants over 7 d, including the transportation mode, global positioning system, geographical information systems, and accelerometer data. A prediction model of transportation modes was constructed using the random forests method. Finally, we investigated the performance of models on the basis of a limited number of participants/trips to predict transportation modes for a large number of trips. The full model had a correct prediction rate of 90%. A simpler model of global positioning system explanatory variables combined with geographical information systems variables performed nearly as well. Relatively good predictions could be made using a model based on the 991 trips of the first 30 participants. This study uses real-life data from a large sample set to test a method for predicting transportation modes at the trip level, thereby providing a useful complement to time unit-level prediction methods. By enabling predictions on the basis of a limited number of observations, this method may decrease the workload for participants/researchers and provide relevant trip-level data to investigate relations between transportation and health.

The Predictive Validity of the Short-Term Assessment of Risk and Treatability (START) for Multiple Adverse Outcomes in a Secure Psychiatric Inpatient Setting.

PubMed

O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

2016-04-01

The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict. © The Author(s) 2015.

Examination of Predictors and Moderators for Self-help Treatments of Binge Eating Disorder

PubMed Central

Masheb, Robin M.; Grilo, Carlos M.

2008-01-01

Predictors and moderators of outcomes were examined in 75 overweight patients with binge eating disorder (BED) who participated in a randomized clinical trial of guided self-help treatments. Age variables, psychiatric and personality disorder comorbidity and clinical characteristics were tested as predictors and moderators of treatment outcomes. Current age and age of BED onset did not predict outcomes. Key dimensional outcomes (binge frequency, eating psychopathology, and negative affect) were predominately predicted, but not moderated, by their respective pretreatment levels. Presence of personality disorders, particularly Cluster C, predicted both post-treatment negative affect and eating disorder psychopathology. Negative affect, but not major depressive disorder, predicted attrition, and post-treatment negative affect and eating disorder psychopathology. Despite the prognostic significance of these findings for dimensional outcomes, none of the variables tested were predictive of binge remission (i.e., a categorical outcome). No moderator effects were found. The present study found poorer prognosis for patients with negative affect and personality disorders suggesting that treatment outcomes may be enhanced by attending to the cognitive and personality styles of these patients. PMID:18837607

Predicting reading outcomes with progress monitoring slopes among middle grade students

PubMed Central

Tolar, Tammy D.; Barth, Amy E.; Fletcher, Jack M.; Francis, David J.; Vaughn, Sharon

2013-01-01

Effective implementation of response-to-intervention (RTI) frameworks depends on efficient tools for monitoring progress. Evaluations of growth (i.e., slope) may be less efficient than evaluations of status at a single time point, especially if slopes do not add to predictions of outcomes over status. We examined progress monitoring slope validity for predicting reading outcomes among middle school students by evaluating latent growth models for different progress monitoring measure-outcome combinations. We used multi-group modeling to evaluate the effects of reading ability, reading intervention, and progress monitoring administration condition on slope validity. Slope validity was greatest when progress monitoring was aligned with the outcome (i.e., word reading fluency slope was used to predict fluency outcomes in contrast to comprehension outcomes), but effects varied across administration conditions (viz., repeated reading of familiar vs. novel passages). Unless the progress monitoring measure is highly aligned with outcome, slope may be an inefficient method for evaluating progress in an RTI context. PMID:24659899

Macaques can predict social outcomes from facial expressions.

PubMed

Waller, Bridget M; Whitehouse, Jamie; Micheletta, Jérôme

2016-09-01

There is widespread acceptance that facial expressions are useful in social interactions, but empirical demonstration of their adaptive function has remained elusive. Here, we investigated whether macaques can use the facial expressions of others to predict the future outcomes of social interaction. Crested macaques (Macaca nigra) were shown an approach between two unknown individuals on a touchscreen and were required to choose between one of two potential social outcomes. The facial expressions of the actors were manipulated in the last frame of the video. One subject reached the experimental stage and accurately predicted different social outcomes depending on which facial expressions the actors displayed. The bared-teeth display (homologue of the human smile) was most strongly associated with predicted friendly outcomes. Contrary to our predictions, screams and threat faces were not associated more with conflict outcomes. Overall, therefore, the presence of any facial expression (compared to neutral) caused the subject to choose friendly outcomes more than negative outcomes. Facial expression in general, therefore, indicated a reduced likelihood of social conflict. The findings dispute traditional theories that view expressions only as indicators of present emotion and instead suggest that expressions form part of complex social interactions where individuals think beyond the present.

The transition from medical student to doctor: perceptions of final year students and preregistration house officers related to expected learning outcomes.

PubMed

Lempp, H; Seabrook, M; Cochrane, M; Rees, J

2005-03-01

In this prospective qualitative study over 12 months, we evaluated the educational and clinical effectiveness of a new final year undergraduate programme in a London medical school (Guy's, King's and St Thomas'). A stratified sample of 17/360 final year students were interviewed four times, and the content was assessed against 32 amalgamated learning outcomes identified in 1997 in The New Doctor. At the beginning of the preregistration year, eight of the learning outcomes were already met, 10 partly, eight remained to be attained and for six, insufficient evidence existed. Preregistration house officers who have been through the final year student house officer programme expressed competence in many of the outcomes of the General Medical Council's New Doctor. The study identified areas such as prescribing where further developments are needed and will help in planning the new foundation programme.

The functional neuroanatomy of decision-making.

PubMed

Rosenbloom, Michael H; Schmahmann, Jeremy D; Price, Bruce H

2012-01-01

Decision-making is a complex executive function that draws on past experience, present goals, and anticipation of outcome, and which is influenced by prevailing and predicted emotional tone and cultural context. Functional imaging investigations and focal lesion studies identify the orbitofrontal, anterior cingulate, and dorsolateral prefrontal cortices as critical to decision-making. The authors review the connections of these prefrontal regions with the neocortex, limbic system, basal ganglia, and cerebellum, highlight current ideas regarding the cognitive processes of decision-making that these networks subserve, and present a novel integrated neuroanatomical model for decision-making. Finally, clinical relevance of this circuitry is illustrated through a discussion of frontotemporal dementia, traumatic brain injury, and sociopathy.

Positive and negative adjustment and social support of sexual assault survivors.

PubMed

Borja, Susan E; Callahan, Jennifer L; Long, Patricia J

2006-12-01

The roles of positive (i.e., growth) and negative (i.e., posttraumatic stress symptoms and general symptomatology) adjustment following adult sexual assault experience(s) were examined using a standardized definition of abuse. These reactions were explored in association with positive and negative support from formal and informal providers. Finally, using standardized measures, the collective impact of positive and negative support, formal and informal support were investigated in predicting positive and negative psychological adjustment. Both forms of informal support were found to be associated with positive outcomes. Only negative informal support was associated with posttraumatic stress symptoms. First responders should consider whether support resources are appropriate to victims' needs.

Predictive value of cognition for different domains of outcome in recent-onset schizophrenia.

PubMed

Holthausen, Esther A E; Wiersma, Durk; Cahn, Wiepke; Kahn, René S; Dingemans, Peter M; Schene, Aart H; van den Bosch, Robert J

2007-01-15

The aim of this study was to see whether and how cognition predicts outcome in recent-onset schizophrenia in a large range of domains such as course of illness, self-care, interpersonal functioning, vocational functioning and need for care. At inclusion, 115 recent-onset patients were tested on a cognitive battery and 103 patients participated in the follow-up 2 years after inclusion. Differences in outcome between cognitively normal and cognitively impaired patients were also analysed. Cognitive measures at inclusion did not predict number of relapses, activities of daily living and interpersonal functioning. Time in psychosis or in full remission, as well as need for care, were partly predicted by specific cognitive measures. Although statistically significant, the predictive value of cognition with regard to clinical outcome was limited. There was a significant difference between patients with and without cognitive deficits in competitive employment status and vocational functioning. The predictive value of cognition for different social outcome domains varies. It seems that cognition most strongly predicts work performance, where having a cognitive deficit, regardless of the nature of the deficit, acts as a rate-limiting factor.

Proton MRS in acute traumatic brain injury: role for glutamate/glutamine and choline for outcome prediction.

PubMed

Shutter, Lori; Tong, Karen A; Holshouser, Barbara A

2004-12-01

Proton magnetic resonance spectroscopy (MRS) is being used to evaluate individuals with acute traumatic brain injury and several studies have shown that changes in certain brain metabolites (N-acetylaspartate, choline) are associated with poor neurologic outcomes. The majority of previous MRS studies have been obtained relatively late after injury and none have examined the role of glutamate/ glutamine (Glx). We conducted a prospective MRS study of 42 severely injured adults to measure quantitative metabolite changes early (7 days) after injury in normal appearing brain. We used these findings to predict long-term neurologic outcome and to determine if MRS data alone or in combination with clinical outcome variables provided better prediction of long-term outcomes. We found that glutamate/glutamine (Glx) and choline (Cho) were significantly elevated in occipital gray and parietal white matter early after injury in patients with poor long-term (6-12-month) outcomes. Glx and Cho ratios predicted long-term outcome with 94% accuracy and when combined with the motor Glasgow Coma Scale score provided the highest predictive accuracy (97%). Somatosensory evoked potentials were not as accurate as MRS data in predicting outcome. Elevated Glx and Cho are more sensitive indicators of injury and predictors of poor outcome when spectroscopy is done early after injury. This may be a reflection of early excitotoxic injury (i.e., elevated Glx) and of injury associated with membrane disruption (i.e., increased Cho) secondary to diffuse axonal injury.

Child, parent and family dysfunction as predictors of outcome in cognitive-behavioral treatment of antisocial children.

PubMed

Kazdin, A E

1995-03-01

The present study examined factors that predicted favorable treatment outcomes among clinically referred conduct problem children (N = 105, ages 7-13) who received cognitive-behavioral treatment. Three domains (severity and breadth of child impairment, parent stress and psychopathology and family dysfunction) assessed at pretreatment were predicted to affect treatment outcome. The results only partially supported the prediction. Less dysfunction in each of the domains predicted who responded favorably to treatment on parent ratings of deviance and prosocial functioning but not on teacher ratings of these outcomes. The findings have implications for identifying youths who respond to available treatments. The results also underscore fundamental questions about the assessment of treatment effects and the criteria for evaluating outcome.

Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches

PubMed Central

Memarian, Negar; Torre, Jared B.; Haltom, Kate E.; Stanton, Annette L.

2017-01-01

Abstract Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. PMID:28992270

EEG, evoked potentials and pulsed Doppler in asphyxiated term infants.

PubMed

Julkunen, Mia K; Himanen, Sari-Leena; Eriksson, Kai; Janas, Martti; Luukkaala, Tiina; Tammela, Outi

2014-09-01

To evaluate electroencephalograms (EEG), evoked potentials (EPs) and Doppler findings in the cerebral arteries as predictors of a 1-year outcome in asphyxiated newborn infants. EEG and EPs (brain stem auditory (BAEP), somatosensory (SEP), visual (VEP) evoked potentials) were assessed in 30 asphyxiated and 30 healthy term infants during the first days (range 1-8). Cerebral blood flow velocities (CBFV) were measured from the cerebral arteries using pulsed Doppler at ∼24h of age. EEG, EPs, Doppler findings, symptoms of hypoxic ischemic encephalopathy (HIE) and their combination were evaluated in predicting a 1-year outcome. An abnormal EEG background predicted poor outcome in the asphyxia group with a sensitivity of 67% and 81% specificity, and an abnormal SEP with 75% and 79%, respectively. Combining increased systolic CBFV (mean+3SD) with abnormal EEG or SEP improved the specificity, but not the sensitivity. The predictive values of abnormal BAEP and VEP were poor. Normal EEG and SEP predicted good outcome in the asphyxia group with sensitivities from 79% to 81%. The combination of normal EEG, normal SEP and systolic CBFV<3SD predicted good outcome with a sensitivity of 74% and 100% specificity. Combining abnormal EEG or EPs findings with increased systolic CBFV did not improve prediction of a poor 1-year outcome of asphyxiated infants. Normal EEG and normal SEP combined with systolic CBFV<3SD at about 24 h can be valuable in the prediction of normal 1-year outcome. Combining systolic CBFV at 24 h with EEG and SEP examinations can be of use in the prediction of normal 1-year outcome among asphyxiated infants. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Historical maintenance relevant information road-map for a self-learning maintenance prediction procedural approach

NASA Astrophysics Data System (ADS)

Morales, Francisco J.; Reyes, Antonio; Cáceres, Noelia; Romero, Luis M.; Benitez, Francisco G.; Morgado, Joao; Duarte, Emanuel; Martins, Teresa

2017-09-01

A large percentage of transport infrastructures are composed of linear assets, such as roads and rail tracks. The large social and economic relevance of these constructions force the stakeholders to ensure a prolonged health/durability. Even though, inevitable malfunctioning, breaking down, and out-of-service periods arise randomly during the life cycle of the infrastructure. Predictive maintenance techniques tend to diminish the appearance of unpredicted failures and the execution of needed corrective interventions, envisaging the adequate interventions to be conducted before failures show up. This communication presents: i) A procedural approach, to be conducted, in order to collect the relevant information regarding the evolving state condition of the assets involved in all maintenance interventions; this reported and stored information constitutes a rich historical data base to train Machine Learning algorithms in order to generate reliable predictions of the interventions to be carried out in further time scenarios. ii) A schematic flow chart of the automatic learning procedure. iii) Self-learning rules from automatic learning from false positive/negatives. The description, testing, automatic learning approach and the outcomes of a pilot case are presented; finally some conclusions are outlined regarding the methodology proposed for improving the self-learning predictive capability.

Learning and Motivational Processes Contributing to Pavlovian-Instrumental Transfer and Their Neural Bases: Dopamine and Beyond.

PubMed

Corbit, Laura H; Balleine, Bernard W

2016-01-01

Pavlovian stimuli exert a range of effects on behavior from simple conditioned reflexes, such as salivation, to altering the vigor and direction of instrumental actions. It is currently accepted that these distinct behavioral effects stem from two sources (i) the various associative connections between predictive stimuli and the component features of the events that these stimuli predict and (ii) the distinct motivational and cognitive functions served by cues, particularly their arousing and informational effects on the selection and performance of specific actions. Here, we describe studies that have assessed these latter phenomena using a paradigm that has come to be called Pavlovian-instrumental transfer. We focus first on behavioral experiments that have described distinct sources of stimulus control derived from the general affective and outcome-specific predictions of conditioned stimuli, referred to as general transfer and specific transfer, respectively. Subsequently, we describe research efforts attempting to establish the neural bases of these transfer effects, largely in the afferent and efferent connections of the nucleus accumbens (NAc) core and shell. Finally, we examine the role of predictive cues in examples of aberrant stimulus control associated with psychiatric disorders and addiction.

Using spatio-temporal modeling to predict long-term exposure to black smoke at fine spatial and temporal scale

NASA Astrophysics Data System (ADS)

Dadvand, Payam; Rushton, Stephen; Diggle, Peter J.; Goffe, Louis; Rankin, Judith; Pless-Mulloli, Tanja

2011-01-01

Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055 km 2) over a 12 year period (1985-1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology. The first stage separates the temporal trend in BS for the region as a whole from within-region spatial variation and the second stage is a linear model which predicts BS levels at all locations in the region using spatially referenced covariate data as predictors and the regional predicted temporal trend as an offset. Traffic and land cover predictors were included in the final model, which predicted 70% of the spatio-temporal variation in BS across the study region over the study period. This modeling approach appears to provide a robust way of estimating exposure to BS at an inter-urban scale.

Artificial neural networks in gynaecological diseases: current and potential future applications.

PubMed

Siristatidis, Charalampos S; Chrelias, Charalampos; Pouliakis, Abraham; Katsimanis, Evangelos; Kassanos, Dimitrios

2010-10-01

Current (and probably future) practice of medicine is mostly associated with prediction and accurate diagnosis. Especially in clinical practice, there is an increasing interest in constructing and using valid models of diagnosis and prediction. Artificial neural networks (ANNs) are mathematical systems being used as a prospective tool for reliable, flexible and quick assessment. They demonstrate high power in evaluating multifactorial data, assimilating information from multiple sources and detecting subtle and complex patterns. Their capability and difference from other statistical techniques lies in performing nonlinear statistical modelling. They represent a new alternative to logistic regression, which is the most commonly used method for developing predictive models for outcomes resulting from partitioning in medicine. In combination with the other non-algorithmic artificial intelligence techniques, they provide useful software engineering tools for the development of systems in quantitative medicine. Our paper first presents a brief introduction to ANNs, then, using what we consider the best available evidence through paradigms, we evaluate the ability of these networks to serve as first-line detection and prediction techniques in some of the most crucial fields in gynaecology. Finally, through the analysis of their current application, we explore their dynamics for future use.

The role of helplessness, outcome expectation for exercise and literacy in predicting disability and symptoms in older adults with arthritis.

PubMed

Bhat, Anita A; DeWalt, Darren A; Zimmer, Catherine R; Fried, Bruce J; Callahan, Leigh F

2010-10-01

To examine the effect of outcome expectation for exercise (OEE), helplessness, and literacy on arthritis outcomes in 2 community-based lifestyle randomized controlled trials (RCTs) conducted in urban and rural communities with older adults with arthritis. Data from 391 participants in 2 RCTs were combined to examine associations of 2 psychosocial variables: helplessness and OEE, and literacy with arthritis outcomes. Arthritis outcomes namely, the Health Assessment Questionnaire-Disability Index (HAQ-DI) and arthritis symptoms pain, fatigue and stiffness Visual Analogue Scales (VAS), were measured at baseline and at the end of the interventions. Complete baseline and post-intervention data were analyzed using STATA version 9. Disability after intervention was not predicted by helplessness, literacy, or OEE in the adjusted model. Arthritis symptoms after the intervention were all significantly predicted by helplessness at various magnitudes in adjusted models, but OEE and literacy were not significant predictors. When literacy, helplessness, and OEE were examined as predictors of arthritis outcomes in intervention trials, they did not predict disability. However, helplessness predicted symptoms of pain, fatigue, and stiffness, but literacy did not predict symptoms. Future sustainable interventions may include self-management components that address decreasing helplessness to improve arthritis outcomes. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Do the same factors predict outcome in schizophrenia and non-schizophrenia syndromes after first-episode psychosis? A two-year follow-up study.

PubMed

Peña, Javier; Segarra, Rafael; Ojeda, Natalia; García, Jon; Eguiluz, José I; Gutiérrez, Miguel

2012-06-01

The aim of this two-year longitudinal study was to identify the best baseline predictors of functional outcome in first-episode psychosis (FEP). We tested whether the same factors predict functional outcomes in two different subsamples of FEP patients: schizophrenia and non-schizophrenia syndrome groups. Ninety-five patients with FEP underwent a full clinical evaluation (i.e., PANSS, Mania, Depression and Insight). Functional outcome measurements included the WHO Disability Assessment Schedule (DAS-WHO), Global Assessment of Functioning (GAF) and Clinical Global Impression (CGI). Estimation of cognition was obtained by a neuropsychological battery which included attention, processing speed, language, memory and executive functioning. Greater severity of visuospatial functioning at baseline predicted poorer functional outcome as measured by the three functional scales (GAF, CGI and DAS-WHO) in the pooled FEP sample (explaining ut to the 12%, 9% and 10% of the variance, respectively). Negative symptoms also effectively contributed to predict GAF scores (8%). However, we obtained different predictive values after differentiating sample diagnoses. Processing speed significantly predicted most functional outcome measures in patients with schizophrenia, whereas visuospatial functioning was the only significant predictor of functional outcomes in the non-schizophrenia subgroup. Our results suggest that processing speed, visuospatial functioning and negative symptoms significantly (but differentially) predict outcomes in patients with FEP, depending on their clinical progression. For patients without a schizophrenia diagnosis, visuospatial functioning was the best predictor of functional outcome. The performance on processing speed seemed to be a key factor in more severe syndromes. However, only a small proportion of the variance could be explained by the model, so there must be many other factors that have to be considered. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clinical Value of Dorsal Medulla Oblongata Involvement Detected with Conventional MRI for Prediction of Outcome in Children with Enterovirus 71-related Brainstem Encephalitis.

PubMed

Liu, Kun; Zhou, Yongjin; Cui, Shihan; Song, Jiawen; Ye, Peipei; Xiang, Wei; Huang, Xiaoyan; Chen, Yiping; Yan, Zhihan; Ye, Xinjian

2018-04-05

Brainstem encephalitis is the most common neurologic complication after enterovirus 71 infection. The involvement of brainstem, especially the dorsal medulla oblongata, can cause severe sequelae or death in children with enterovirus 71 infection. We aimed to determine the prevalence of dorsal medulla oblongata involvement in children with enterovirus 71-related brainstem encephalitis (EBE) by using conventional MRI and to evaluate the value of dorsal medulla oblongata involvement in outcome prediction. 46 children with EBE were enrolled in the study. All subjects underwent a 1.5 Tesla MR examination of the brain. The disease distribution and clinical data were collected. Dichotomized outcomes (good versus poor) at longer than 6 months were available for 28 patients. Logistic regression was used to determine whether the MRI-confirmed dorsal medulla oblongata involvement resulted in improved clinical outcome prediction when compared with other location involvement. Of the 46 patients, 35 had MRI evidence of dorsal medulla oblongata involvement, 32 had pons involvement, 10 had midbrain involvement, and 7 had dentate nuclei involvement. Patients with dorsal medulla oblongata involvement or multiple area involvement were significantly more often in the poor outcome group than in the good outcome group. Logistic regression analysis showed that dorsal medulla oblongata involvement was the most significant single variable in outcome prediction (predictive accuracy, 90.5%), followed by multiple area involvement, age, and initial glasgow coma scale score. Dorsal medulla oblongata involvement on conventional MRI correlated significantly with poor outcomes in EBE children, improved outcome prediction when compared with other clinical and disease location variables, and was most predictive when combined with multiple area involvement, glasgow coma scale score and age.

Neurophysiological prediction of neurological good and poor outcome in post-anoxic coma.

PubMed

Grippo, A; Carrai, R; Scarpino, M; Spalletti, M; Lanzo, G; Cossu, C; Peris, A; Valente, S; Amantini, A

2017-06-01

Investigation of the utility of association between electroencephalogram (EEG) and somatosensory-evoked potentials (SEPs) for the prediction of neurological outcome in comatose patients resuscitated after cardiac arrest (CA) treated with therapeutic hypothermia, according to different recording times after CA. Glasgow Coma Scale, EEG and SEPs performed at 12, 24 and 48-72 h after CA were assessed in 200 patients. Outcome was evaluated by Cerebral Performance Category 6 months after CA. Within 12 h after CA, grade 1 EEG predicted good outcome and bilaterally absent (BA) SEPs predicted poor outcome. Because grade 1 EEG and BA-SEPs were never found in the same patient, the recording of both EEG and SEPs allows us to correctly prognosticate a greater number of patients with respect to the use of a single test within 12 h after CA. At 48-72 h after CA, both grade 2 EEG and BA-SEPs predicted poor outcome with FPR=0.0%. When these neurophysiological patterns are both present in the same patient, they confirm and strengthen their prognostic value, but because they also occurred independently in eight patients, poor outcome is predictable in a greater number of patients. The combination of EEG/SEP findings allows prediction of good and poor outcome (within 12 h after CA) and of poor outcome (after 48-72 h). Recording of EEG and SEPs in the same patients allows always an increase in the number of cases correctly classified, and an increase of the reliability of prognostication in a single patient due to concordance of patterns. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Tumor Necrosis Factor-α, Interleukins-12(p40), 6, and 10 levels in cerebrospinal fluid and outcome prediction in Ossimi sheep with encephalitic listeriosis.

PubMed

Abdlla, Ossama A; Elboshy, Mohamed E; Reisha, Engy F; Gadlla, Hossam A; El-Khodery, Sabry A

2015-06-01

Encephalitic listeriosis in sheep is a life-threatening disease. However, little is known about the cytokine response and their predictive value in this disease. The aim of present study was to assess the prognostic significance of Tumor Necrosis Factor-α (TNF-α), Interleukin-12(p40) (IL-12 p40), Interleukin-6 (IL-6), and Interleukin 10 (IL-10) levels in cerebrospinal fluid (CSF) in sheep with encephalitic listeriosis. Fifty-nine ewes in 14 flocks were diagnosed clinically as having listeriosis. CSF was collected and subjected to bacteriological examination and estimation of selected cytokines. Twenty-eight ewes were confirmed to be infected with Listeria monocytogenes. Based on antimicrobial sensitivity test, sheep were treated and the outcome was recorded as survivors (n=10) and non-survivors (n=18). Cutoff points for CSF cytokines were determined by Receiver operating characteristic analysis (ROC). Association between levels of CSF cytokines and outcome of listeriosis was assessed by logistic regression. TNF-α, IL-6 and IL-12(p40) levels as well as TNF-α/IL-10 ratio were significantly higher in non-survivors than survivors (p=0.002, 0.0021, 0.0033, and 0.001, respectively). However, IL-10 level was significantly lower in non-survivors than survivors (p=0.0058). ROC analysis revealed that IL-6 and TNF-α/IL-10 ratio had the highest AUC values (0.98, 0.984, respectively). Final multivariate logistic regression model showed that TNF-α/IL-10 ratio was the only variable that has predictive value for mortality in diseased sheep (p: 0.001; OR: 7.2; 95% CI: 5.7-9.8). TNF-α showed a positive correlation with IL-12β (r=0.917) and IL-6 (r=0.965). IL-12 (p40) showed also a positive correlation with IL-6 (r=0.906). However, IL-10 showed a negative correlation with TNF-α (r=-0.915), IL-12(p40) (r=-0.790), and IL-6 (r=-0.902). In conclusion, TNF-α/IL-10 ratio may provide predictive information about outcome of encephalitic listeriosis in sheep. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural-scaled entropy predicts the effects of nonlinear frequency compression on speech perception

PubMed Central

Rallapalli, Varsha H.; Alexander, Joshua M.

2015-01-01

The Neural-Scaled Entropy (NSE) model quantifies information in the speech signal that has been altered beyond simple gain adjustments by sensorineural hearing loss (SNHL) and various signal processing. An extension of Cochlear-Scaled Entropy (CSE) [Stilp, Kiefte, Alexander, and Kluender (2010). J. Acoust. Soc. Am. 128(4), 2112–2126], NSE quantifies information as the change in 1-ms neural firing patterns across frequency. To evaluate the model, data from a study that examined nonlinear frequency compression (NFC) in listeners with SNHL were used because NFC can recode the same input information in multiple ways in the output, resulting in different outcomes for different speech classes. Overall, predictions were more accurate for NSE than CSE. The NSE model accurately described the observed degradation in recognition, and lack thereof, for consonants in a vowel-consonant-vowel context that had been processed in different ways by NFC. While NSE accurately predicted recognition of vowel stimuli processed with NFC, it underestimated them relative to a low-pass control condition without NFC. In addition, without modifications, it could not predict the observed improvement in recognition for word final /s/ and /z/. Findings suggest that model modifications that include information from slower modulations might improve predictions across a wider variety of conditions. PMID:26627780

Increasing maternal healthcare use in Rwanda: implications for child nutrition and survival.

PubMed

Pierce, Hayley; Heaton, Tim B; Hoffmann, John

2014-04-01

Rwanda has made great progress in improving maternal utilization of health care through coordination of external aid and more efficient health policy. Using data from the 2005 and 2010 Rwandan Demographic and Health Surveys, we examine three related questions regarding the impact of expansion of health care in Rwanda. First, did the increased use of health center deliveries apply to women across varying levels of education, economic status, and area of residency? Second, did the benefits associated with being delivered at a health center diminish as utilization became more widespread? Finally, did inequality in child outcomes decline as a result of increased health care utilization? Propensity score matching was used to address the selectivity that arises when choosing to deliver at a hospital. In addition, the regression models include a linear model to predict child nutritional status and Cox regression to predict child survival. The analysis shows that the largest increases in delivery at a health center occur among less educated, less wealthy, and rural Rwandan women. In addition, delivery at a health center is associated with better nutritional status and survival and the benefit is not diminished following the dramatic increase in use of health centers. Finally, educational, economic and residential inequality in child survival and nutrition did not decline. Copyright © 2014 Elsevier Ltd. All rights reserved.

Task constraints distinguish perspective inferences from perspective use during discourse interpretation in a false belief task.

PubMed

Ferguson, Heather J; Apperly, Ian; Ahmad, Jumana; Bindemann, Markus; Cane, James

2015-06-01

Interpreting other peoples' actions relies on an understanding of their current mental states (e.g. beliefs, desires and intentions). In this paper, we distinguish between listeners' ability to infer others' perspectives and their explicit use of this knowledge to predict subsequent actions. In a visual-world study, two groups of participants (passive observers vs. active participants) watched short videos, depicting transfer events, where one character ('Jane') either held a true or false belief about an object's location. We tracked participants' eye-movements around the final visual scene, time-locked to related auditory descriptions (e.g. "Jane will look for the chocolates in the container on the left".). Results showed that active participants had already inferred the character's belief in the 1s preview period prior to auditory onset, before it was possible to use this information to predict an outcome. Moreover, they used this inference to correctly anticipate reference to the object's initial location on false belief trials at the earliest possible point (i.e. from "Jane" onwards). In contrast, passive observers only showed evidence of a belief inference from the onset of "Jane", and did not show reliable use of this inference to predict Jane's behaviour on false belief trials until much later, when the location ("left/right") was auditorily available. These results show that active engagement in a task activates earlier inferences about others' perspectives, and drives immediate use of this information to anticipate others' actions, compared to passive observers, who are susceptible to influences from egocentric or reality biases. Finally, we review evidence that using other peoples' perspectives to predict their behaviour is more cognitively effortful than simply using one's own. Copyright © 2015 Elsevier B.V. All rights reserved.

Newberry Volcano EGS Demonstration Stimulation Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trenton T. Cladouhos, Matthew Clyne, Maisie Nichols,; Susan Petty, William L. Osborn, Laura Nofziger

2011-10-23

As a part of Phase I of the Newberry Volcano EGS Demonstration project, several data sets were collected to characterize the rock volume around the well. Fracture, fault, stress, and seismicity data has been collected by borehole televiewer, LiDAR elevation maps, and microseismic monitoring. Well logs and cuttings from the target well (NWG 55-29) and core from a nearby core hole (USGS N-2) have been analyzed to develop geothermal, geochemical, mineralogical and strength models of the rock matrix, altered zones, and fracture fillings (see Osborn et al., this volume). These characterization data sets provide inputs to models used to planmore » and predict EGS reservoir creation and productivity. One model used is AltaStim, a stochastic fracture and flow software model developed by AltaRock. The software's purpose is to model and visualize EGS stimulation scenarios and provide guidance for final planning. The process of creating an AltaStim model requires synthesis of geologic observations at the well, the modeled stress conditions, and the stimulation plan. Any geomechanical model of an EGS stimulation will require many assumptions and unknowns; thus, the model developed here should not be considered a definitive prediction, but a plausible outcome given reasonable assumptions. AltaStim is a tool for understanding the effect of known constraints, assumptions, and conceptual models on plausible outcomes.« less

Predictors of psychological well-being amongst Korean immigrants to the United States: a structured interview survey.

PubMed

Shin, Hye Sook; Han, Hae-Ra; Kim, Miyong T

2007-03-01

As international migration becomes a common phenomenon in many countries, the health issues of immigrants are becoming an important area of concern among health care professionals worldwide. Adopting the stress-health outcome framework, this study examined risks and resources of both positive and negative affect (i.e., happiness and depression) among Korean Americans who experienced acculturative and recent life stresses. Hierarchical multiple regression analyses were performed to examine correlates of positive and negative outcomes in the stress process on a final sample of 147 Korean immigrants from a cross-sectional study. For happiness, lower levels of acculturative stress and recent life stress, a greater sense of mastery, and greater social support were associated with an increased level of happiness. None of the individual characteristics were significant. R(2) for the full model was .53. For negative affect, acculturative stress and recent life stress explained a significant portion (41%) of the total variance associated with depression (R(2)=.51). As with the happiness variable, individual characteristics failed to add to the predictiveness of the equation, while sense of mastery and social support functioned as significant resources in reducing depression. Increased mastery and greater social support were consistently predictive of greater happiness and less depression. Implications for future immigrant research are discussed.

Development and validation of the ORACLE score to predict risk of osteoporosis.

PubMed

Richy, Florent; Deceulaer, Fréderic; Ethgen, Olivier; Bruyère, Olivier; Reginster, Jean-Yves

2004-11-01

To develop and validate a composite index, the Osteoporosis Risk Assessment by Composite Linear Estimate (ORACLE), that includes risk factors and ultrasonometric outcomes to screen for osteoporosis. Two cohorts of postmenopausal women aged 45 years and older participated in the development (n = 407) and the validation (n = 202) of ORACLE. Their bone mineral density was determined by dual energy x-ray absorptiometry and quantitative ultrasonometry (QUS), and their historical and clinical risk factors were assessed (January to June 2003). Logistic regression analysis was used to select significant predictors of bone mineral density, whereas receiver operating characteristic (ROC) analysis was used to assess the discriminatory performance of ORACLE. The final logistic regression model retained 4 biometric or historical variables and 1 ultrasonometric outcome. The ROC areas under the curves (AUCs) for ORACLE were 84% for the prediction of osteoporosis and 78% for low bone mass. A sensitivity of 90% corresponded to a specificity of 50% for identification of women at risk of developing osteoporosis. The corresponding positive and negative predictive values were 86% and 54%, respectively, in the development cohort. In the validation cohort, the AUCs for identification of osteoporosis and low bone mass were 81% and 76% for ORACLE, 69% and 64% for QUS T score, 71% and 68% for QUS ultrasonometric bone profile index, and 76% and 75% for Osteoporosis Self-assessment Tool, respectively. ORACLE had the best discriminatory performance in identifying osteoporosis compared with the other approaches (P < .05). ORACLE exhibited the highest discriminatory properties compared with ultrasonography alone or other previously validated risk indices. It may be helpful to enhance the predictive value of QUS.

Psychosocial well-being and health-related quality of life in a UK population with Usher syndrome.

PubMed

Dean, Gavin; Orford, Amy; Staines, Roy; McGee, Anna; Smith, Kimberley J

2017-01-12

To determine whether psychosocial well-being is associated with the health-related quality of life (HRQOL) of people with Usher syndrome. The survey was advertised online and through deafblind-related charities, support groups and social groups throughout the UK. 90 people with Usher syndrome took part in the survey. Inclusion criteria are having a diagnosis of Usher syndrome, being 18 or older and being a UK resident. All participants took part in a survey that measured depressive symptoms, loneliness and social support (predictors) and their physical and mental HRQOL (outcomes). Measured confounders included age-related, sex-related and health-related characteristics. Hierarchical multiple linear regression analyses examined the association of each psychosocial well-being predictor with the physical and mental HRQOL outcomes while controlling for confounders in a stepwise manner. After adjusting for all confounders, psychosocial well-being was shown to predict physical and mental HRQOL in our population with Usher syndrome. Increasing depressive symptoms were predictive of poorer physical (β=-0.36, p<0.01) and mental (β=-0.60, p<0.001) HRQOL. Higher levels of loneliness predicted poorer mental HRQOL (β=-0.20, p<0.05). Finally, increasing levels of social support predicted better mental HRQOL (β=0.19, p<0.05). Depression, loneliness and social support all represent important issues that are linked with HRQOL in a UK population with Usher syndrome. Our results add to the growing body of evidence that psychosocial well-being is an important factor to consider in people with Usher syndrome alongside functional and physical impairment within research and clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Development and external validation of a prediction rule for an unfavorable course of late-life depression: A multicenter cohort study.

PubMed

Maarsingh, O R; Heymans, M W; Verhaak, P F; Penninx, B W J H; Comijs, H C

2018-08-01

Given the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. For development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60-90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50-66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. 111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). The model was developed and validated in The Netherlands, which could affect the cross-country generalizability. Based on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDD patients and identifying those at risk of an unfavourable outcome. Copyright © 2018 Elsevier B.V. All rights reserved.

Personality and mental health treatment: Traits as predictors of presentation, usage, and outcome.

PubMed

Thalmayer, Amber Gayle

2018-03-08

Self-report scores on personality inventories predict important life outcomes, including health and longevity, marital outcomes, career success, and mental health problems, but the ways they predict mental health treatment have not been widely explored. Psychotherapy is sought for diverse problems, but about half of those who begin therapy drop out, and only about half who complete therapy experience lasting improvements. Several authors have argued that understanding how personality traits relate to treatment could lead to better targeted, more successful services. Here self-report scores on Big Five and Big Six personality dimensions are explored as predictors of therapy presentation, usage, and outcomes in a sample of community clinic clients (N = 306). Participants received evidence-based treatments in the context of individual-, couples-, or family-therapy sessions. One measure of initial functioning and three indicators of outcome were used. All personality trait scores except Openness associated with initial psychological functioning. Higher Conscientiousness scores predicted more sessions attended for family therapy but fewer for couples-therapy clients. Higher Honesty-Propriety and Extraversion scores predicted fewer sessions attended for family-therapy clients. Better termination outcome was predicted by higher Conscientiousness scores for family- and higher Extraversion scores for individual-therapy clients. Higher Honesty-Propriety and Neuroticism scores predicted more improvement in psychological functioning in terms of successive Outcome Questionnaire-45 administrations. Taken together, the results provide some support for the role of personality traits in predicting treatment usage and outcome and for the utility of a 6-factor model in this context. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Setting the vision: applied patient-reported outcomes and smart, connected digital healthcare systems to improve patient-centered outcomes prediction in critical illness.

PubMed

Wysham, Nicholas G; Abernethy, Amy P; Cox, Christopher E

2014-10-01

Prediction models in critical illness are generally limited to short-term mortality and uncommonly include patient-centered outcomes. Current outcome prediction tools are also insensitive to individual context or evolution in healthcare practice, potentially limiting their value over time. Improved prognostication of patient-centered outcomes in critical illness could enhance decision-making quality in the ICU. Patient-reported outcomes have emerged as precise methodological measures of patient-centered variables and have been successfully employed using diverse platforms and technologies, enhancing the value of research in critical illness survivorship and in direct patient care. The learning health system is an emerging ideal characterized by integration of multiple data sources into a smart and interconnected health information technology infrastructure with the goal of rapidly optimizing patient care. We propose a vision of a smart, interconnected learning health system with integrated electronic patient-reported outcomes to optimize patient-centered care, including critical care outcome prediction. A learning health system infrastructure integrating electronic patient-reported outcomes may aid in the management of critical illness-associated conditions and yield tools to improve prognostication of patient-centered outcomes in critical illness.

Mucosal Perforation During Laparoscopic Heller Myotomy Has No Influence on Final Treatment Outcome.

PubMed

Salvador, Renato; Spadotto, Lorenzo; Capovilla, Giovanni; Voltarel, Guerrino; Pesenti, Elisa; Longo, Cristina; Cavallin, Francesco; Nicoletti, Loredana; Ruol, Alberto; Valmasoni, Michele; Merigliano, Stefano; Costantini, Mario

2016-12-01

The aims of the study were (a) to examine the final outcome in patients experiencing accidental mucosal perforation during laparoscopic Heller myotomy with Dor fundoplication (LHD) and (b) to evaluate whether perforation episodes might influence the way in which surgeons subsequently approached the LHD procedure. We studied all consecutive patients that underwent LHD between 1992 and 2015. Patients were divided into two main groups: those who experienced an intraoperative mucosal perforation (group P) and those whose LHD was uneventful (group NP). Two additional groups were compared: group A, which consisted of patients operated by a given surgeon immediately before a perforation episode occurred, and group B, which included those operated immediately afterwards. Eight hundred seventy-five patients underwent LHD; a mucosal perforation was detected in 25 patients (2.9 %), which was found unrelated to patients' symptom's score and age, radiological stage, manometric pattern, or the surgeon's experience. The median postoperative symptom score was similar for the two groups as the failure rate: 92 failures in group NP (10.8 %) and 4 in group P (16 %) (p = 0.34); moreover, symptoms recurred in 2 patients of group A (10 %) and 3 patients of group B (15 %) (p = 0.9). Accidental perforation during LHD is infrequent and impossible to predict on the grounds of preoperative therapy or the surgeon's personal experience. Despite a longer surgical procedure and hospital stay, the outcome of LHD is much the same as for patients undergoing uneventful myotomy. A recent mucosal perforation does not influence the surgeon's subsequent performance.

Characterizing the relationship between in-hospital measures and workers' compensation outcomes among severely injured construction workers using a data linkage strategy.

PubMed

Ruestow, Peter S; Friedman, Lee S

2013-10-01

To characterize the relationship between acute measures of severity and three important workers' compensation outcomes associated with a worker's ability to return to work and the cost of a work-related injury. Probabilistic data linkage of workers' compensation claims made by injured construction workers from 2000 to 2005 with two Illinois medical record registries. Multivariable robust regression models were built to assess the relationship between three in-hospital measures and three outcomes captured in the Workers' Compensation data. In the final multivariable models, a categorical increase in injury severity was associated with an extra $7,830 (95% CI: $4,729-$10,930) of monetary compensation awarded, though not with temporary total disability (TTD) or permanent partial disability (PPD). Our models also predicted that every extra day spent in the hospital results in an increase of 0.51 (95% CI: 0.23-0.80) weeks of TTD and an extra $1,248 (95% CI: $810-$1,686) in monetary compensation. Discharge to an intermediate care facility following the initial hospitalization was associated with an increase of 8.15 (95% CI: 4.03-12.28) weeks of TTD and an increase of $23,440 (95% CI: $17,033-$29,847) in monetary compensation. We were able to link data from the initial hospitalization for an injured worker with the final workers' compensation claims decision or settlement. The in-hospital measures of injury severity were associated with total monetary compensation as captured in the workers' compensation process. Copyright © 2013 Wiley Periodicals, Inc.

Radioiodine therapy in Graves' disease based on tissue-absorbed dose calculations: effect of pre-treatment thyroid volume on clinical outcome.

PubMed

Reinhardt, Michael J; Brink, Ingo; Joe, Alexius Y; Von Mallek, Dirk; Ezziddin, Samer; Palmedo, Holger; Krause, Thomas M

2002-09-01

This study was performed with three aims. The first was to analyse the effectiveness of radioiodine therapy in Graves' disease patients with and without goitres under conditions of mild iodine deficiency using several tissue-absorbed doses. The second aim was to detect further parameters which might be predictive for treatment outcome. Finally, we wished to determine the deviation of the therapeutically achieved dose from that intended. Activities of 185-2,220 MBq radioiodine were calculated by means of Marinelli's formula to deliver doses of 150, 200 or 300 Gy to the thyroids of 224 patients with Graves' disease and goitres up to 130 ml in volume. Control of hyperthyroidism, change in thyroid volume and thyrotropin-receptor antibodies were evaluated 15+/-9 months after treatment for each dose. The results were further evaluated with respect to pre-treatment parameters which might be predictive for therapy outcome. Thyroidal radioiodine uptake was measured every day during therapy to determine the therapeutically achieved target dose and its coefficient of variation. There was a significant dose dependency in therapeutic outcome: frequency of hypothyroidism increased from 27.4% after 150 Gy to 67.7% after 300 Gy, while the frequency of persistent hyperthyroidism decreased from 27.4% after 150 Gy to 8.1% after 300 Gy. Patients who became hypothyroid had a maximum thyroid volume of 42 ml and received a target dose of 256+/-80 Gy. The coefficient of variation for the achieved target dose ranged between 27.7% for 150 Gy and 17.8% for 300 Gy. When analysing further factors which might influence therapeutic outcome, only pre-treatment thyroid volume showed a significant relationship to the result of treatment. It is concluded that a target dose of 250 Gy is essential to achieve hypothyroidism within 1 year after radioiodine therapy in Graves' disease patients with goitres up to 40 ml in volume. Patients with larger goitres might need higher doses.

Mental health indicator interaction in predicting substance abuse treatment outcomes in nevada.

PubMed

Greenfield, Lawrence; Wolf-Branigin, Michael

2009-01-01

Indicators of co-occurring mental health and substance abuse problems routinely collected at treatment admission in 19 State substance abuse treatment systems include a dual diagnosis and a State mental health (cognitive impairment) agency referral. These indicators have yet to be compared as predictors of treatment outcomes. 1. Compare both indices as outcomes predictors individually and interactively. 2. Assess relationship of both indices to other client risk factors, e.g., physical/sexual abuse. Client admission and discharge records from the Nevada substance abuse treatment program, spanning 1995-2001 were reviewed (n = 17,591). Logistic regression analyses predicted treatment completion with significant improvement (33%) and treatment readmission following discharge (21%). Using Cox regression, the number of days from discharge to treatment readmission was predicted. Examined as predictors were two mental health indicators and their interaction with other admission and treatment variables controlled. Neither mental health indicator alone significantly predicted any of the three outcomes; however, the interaction between the two indicators significantly predicted each outcome (p < .05). Having both indices was highly associated with physical/sexual abuse, domestic violence, homelessness, out of labor force and prior treatment. Indicator interactions may help improve substance abuse treatment outcomes prediction.

Changes in need satisfaction and motivation orientation as predictors of psychological and behavioural outcomes in exercise referral.

PubMed

Rahman, Rachel Jane; Thogersen-Ntoumani, Cecilie; Thatcher, Joanne; Doust, Jonathan

2011-11-01

Employing Self-Determination Theory (Deci & Ryan, 1985) as a theoretical framework, this study examined psychological need satisfaction and motivational regulations as predictors of psychological and behavioural outcomes in exercise referral (ER). ER patients (N = 293; mean age 54.49) completed the measures of motivational regulations, psychological need satisfaction, health-related quality of life, life satisfaction, anxiety, depression and physical activity at entry, exit and 6 months following the end of a supervised exercise programme. Change in (Δ) intrinsic motivation during the scheme significantly predicted adherence and Δ habitual physical activity. Δ psychological need satisfaction from entry to exit significantly predicted Δ habitual physical activity from exit to 6-month follow-up. Δ psychological need satisfaction significantly predicted Δ motivational regulation and Δ psychological outcomes. Contrary to expectations, Δ self-determined regulation did not significantly predict Δ psychological outcomes during the structured part of the scheme, however, it did significantly predict Δ in psychological outcomes from exit to 6-month follow-up. These findings expand on cross-sectional research to demonstrate that psychological need satisfaction during supervised ER longitudinally predicts motivational regulation and psychological outcomes up to 6 months after a structured programme.

Muscle Mass Depletion Associated with Poor Outcome of Sepsis in the Emergency Department.

PubMed

Lee, YoonJe; Park, Hyun Kyung; Kim, Won Young; Kim, Myung Chun; Jung, Woong; Ko, Byuk Sung

2018-05-08

Muscle mass depletion has been suggested to predict morbidity and mortality in various diseases. However, it is not well known whether muscle mass depletion is associated with poor outcome in sepsis. We hypothesized that muscle mass depletion is associated with poor outcome in sepsis. Retrospective observational study was conducted in an emergency department during a 9-year period. Medical records of 627 patients with sepsis were reviewed. We divided the patients into 2 groups according to 28-day mortality and compared the presence of muscle mass depletion assessed by the cross-sectional area of the psoas muscle at the level of the third lumbar vertebra on abdomen CT scans. Univariate and multivariate logistic regression analyses were conducted to examine the association of scarcopenia on the outcome of sepsis. A total of 274 patients with sepsis were finally included in the study: 45 (16.4%) did not survive on 28 days and 77 patients (28.1%) were identified as having muscle mass depletion. The presence of muscle mass depletion was independently associated with 28-day mortality on multivariate logistic analysis (OR 2.79; 95% CI 1.35-5.74, p = 0.01). Muscle mass depletion evaluated by CT scan was associated with poor outcome of sepsis patients. Further studies on the appropriateness of specific treatment for muscle mass depletion with sepsis are needed. © 2018 S. Karger AG, Basel.

Authoritative Parenting Among Immigrant Chinese Mothers of Preschoolers

PubMed Central

Cheah, Charissa S. L.; Leung, Christy Y. Y.; Tahseen, Madiha; Schultz, David

2013-01-01

The goals of this study were: (a) to examine authoritative parenting style among Chinese immigrant mothers of young children, (b) to test the mediational mechanism between authoritative parenting style and children’s outcomes; and (c) to evaluate 3 predictors of authoritative parenting style (psychological well-being, perceived support in the parenting role, parenting stress). Participants included 85 Chinese immigrant mothers and their preschool children. Mothers reported on their parenting style, psychological well-being, perceived parenting support and stress, and children’s hyperactivity/attention. Teacher ratings of child adjustment were also obtained. Results revealed that Chinese immigrant mothers of preschoolers strongly endorsed the authoritative parenting style. Moreover, authoritative parenting predicted increased children’s behavioral/attention regulation abilities (lower hyperactivity/inattention), which then predicted decreased teacher rated child difficulties. Finally, mothers with greater psychological well-being or parenting support engaged in more authoritative parenting, but only under conditions of low parenting stress. Neither well-being nor parenting support predicted authoritative parenting when parenting hassles were high. Findings were discussed in light of cultural- and immigration-related issues facing immigrant Chinese mothers of young children. PMID:19586194

Authoritative parenting among immigrant Chinese mothers of preschoolers.

PubMed

Cheah, Charissa S L; Leung, Christy Y Y; Tahseen, Madiha; Schultz, David

2009-06-01

The goals of this study were: (a) to examine authoritative parenting style among Chinese immigrant mothers of young children, (b) to test the mediational mechanism between authoritative parenting style and children's outcomes; and (c) to evaluate 3 predictors of authoritative parenting style (psychological well-being, perceived support in the parenting role, parenting stress). Participants included 85 Chinese immigrant mothers and their preschool children. Mothers reported on their parenting style, psychological well-being, perceived parenting support and stress, and children's hyperactivity/attention. Teacher ratings of child adjustment were also obtained. Results revealed that Chinese immigrant mothers of preschoolers strongly endorsed the authoritative parenting style. Moreover, authoritative parenting predicted increased children's behavioral/attention regulation abilities (lower hyperactivity/inattention), which then predicted decreased teacher rated child difficulties. Finally, mothers with greater psychological well-being or parenting support engaged in more authoritative parenting, but only under conditions of low parenting stress. Neither well-being nor parenting support predicted authoritative parenting when parenting hassles were high. Findings were discussed in light of cultural- and immigration-related issues facing immigrant Chinese mothers of young children. Copyright 2009 APA, all rights reserved.

[Methodological approach to the use of artificial neural networks for predicting results in medicine].

PubMed

Trujillano, Javier; March, Jaume; Sorribas, Albert

2004-01-01

In clinical practice, there is an increasing interest in obtaining adequate models of prediction. Within the possible available alternatives, the artificial neural networks (ANN) are progressively more used. In this review we first introduce the ANN methodology, describing the most common type of ANN, the Multilayer Perceptron trained with backpropagation algorithm (MLP). Then we compare the MLP with the Logistic Regression (LR). Finally, we show a practical scheme to make an application based on ANN by means of an example with actual data. The main advantage of the RN is its capacity to incorporate nonlinear effects and interactions between the variables of the model without need to include them a priori. As greater disadvantages, they show a difficult interpretation of their parameters and large empiricism in their process of construction and training. ANN are useful for the computation of probabilities of a given outcome based on a set of predicting variables. Furthermore, in some cases, they obtain better results than LR. Both methodologies, ANN and LR, are complementary and they help us to obtain more valid models.

Psychological Considerations in the Assessment and Treatment of Pain in Neurorehabilitation and Psychological Factors Predictive of Therapeutic Response: Evidence and Recommendations from the Italian Consensus Conference on Pain in Neurorehabilitation

PubMed Central

Castelnuovo, Gianluca; Giusti, Emanuele M.; Manzoni, Gian Mauro; Saviola, Donatella; Gatti, Arianna; Gabrielli, Samantha; Lacerenza, Marco; Pietrabissa, Giada; Cattivelli, Roberto; Spatola, Chiara A. M.; Corti, Stefania; Novelli, Margherita; Villa, Valentina; Cottini, Andrea; Lai, Carlo; Pagnini, Francesco; Castelli, Lorys; Tavola, Mario; Torta, Riccardo; Arreghini, Marco; Zanini, Loredana; Brunani, Amelia; Capodaglio, Paolo; D'Aniello, Guido E.; Scarpina, Federica; Brioschi, Andrea; Priano, Lorenzo; Mauro, Alessandro; Riva, Giuseppe; Repetto, Claudia; Regalia, Camillo; Molinari, Enrico; Notaro, Paolo; Paolucci, Stefano; Sandrini, Giorgio; Simpson, Susan G.; Wiederhold, Brenda; Tamburin, Stefano

2016-01-01

Background: In order to provide effective care to patients suffering from chronic pain secondary to neurological diseases, health professionals must appraise the role of the psychosocial factors in the genesis and maintenance of this condition whilst considering how emotions and cognitions influence the course of treatment. Furthermore, it is important not only to recognize the psychological reactions to pain that are common to the various conditions, but also to evaluate how these syndromes differ with regards to the psychological factors that may be involved. As an extensive evaluation of these factors is still lacking, the Italian Consensus Conference on Pain in Neurorehabilitation (ICCPN) aimed to collate the evidence available across these topics. Objectives: To determine the psychological factors which are associated with or predictive of pain secondary to neurological conditions and to assess the influence of these aspects on the outcome of neurorehabilitation. Methods: Two reviews were performed. In the first, a PUBMED search of the studies assessing the association between psychological factors and pain or the predictive value of these aspects with respect to chronic pain was conducted. The included papers were then rated with regards to their methodological quality and recommendations were made accordingly. In the second study, the same methodology was used to collect the available evidence on the predictive role of psychological factors on the therapeutic response to pain treatments in the setting of neurorehabilitation. Results: The first literature search identified 1170 results and the final database included 189 articles. Factors such as depression, anxiety, pain catastrophizing, coping strategies, and cognitive functions were found to be associated with pain across the various conditions. However, there are differences between chronic musculoskeletal pain, migraine, neuropathy, and conditions associated with complex disability with regards to the psychological aspects that are involved. The second PUBMED search yielded 252 studies, which were all evaluated. Anxiety, depression, pain catastrophizing, coping strategies, and pain beliefs were found to be associated to different degrees with the outcomes of multidisciplinary programs, surgery, physical therapies, and psychological interventions. Finally, sense of presence was found to be related to the effectiveness of virtual reality as a distraction tool. Conclusions: Several psychological factors are associated with pain secondary to neurological conditions and should be acknowledged and addressed in order to effectively treat this condition. These factors also predict the therapeutic response to the neurorehabilitative interventions. PMID:27148104

An MEG signature corresponding to an axiomatic model of reward prediction error.

PubMed

Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

2012-01-02

Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

Magnetic resonance spectroscopic determination of a neuronal and axonal marker in white matter predicts reversibility of deficits in secondary normal pressure hydrocephalus

PubMed Central

Shiino, A; Nishida, Y; Yasuda, H; Suzuki, M; Matsuda, M; Inubushi, T

2004-01-01

Background: Normal pressure hydrocephalus (NPH) is considered to be a treatable form of dementia, because cerebrospinal fluid (CSF) shunting can lessen symptoms. However, neuroimaging has failed to predict when shunting will be effective. Objective: To investigate whether 1H (proton) magnetic resonance (MR) spectroscopy could predict functional outcome in patients after shunting. Methods: Neurological state including Hasegawa's dementia scale, gait, continence, and the modified Rankin scale were evaluated in 21 patients with secondary NPH who underwent ventriculo-peritoneal shunting. Outcomes were measured postoperatively at one and 12 months and were classified as excellent, fair, or poor. MR spectra were obtained from left hemispheric white matter. Results: Significant preoperative differences in N-acetyl aspartate (NAA)/creatine (Cr) and NAA/choline (Cho) were noted between patients with excellent and poor outcome at one month (p = 0.0014 and 0.0036, respectively). Multiple regression analysis linked higher preoperative NAA/Cr ratio, gait score, and modified Rankin scale to better one month outcome. Predictive value, sensitivity, and specificity for excellent outcome following shunting were 95.2%, 100%, and 87.5%. Multiple regression analysis indicated that NAA/Cho had the best predictive value for one year outcome (p = 0.0032); predictive value, sensitivity, and specificity were 89.5%, 90.0%, and 88.9%. Conclusions: MR spectroscopy predicted long term post-shunting outcomes in patients with secondary NPH, and it would be a useful assessment tool before lumbar drainage. PMID:15258216

Predicting in-treatment performance and post-treatment outcomes in methamphetamine users.

PubMed

Hillhouse, Maureen P; Marinelli-Casey, Patricia; Gonzales, Rachel; Ang, Alfonso; Rawson, Richard A

2007-04-01

This study examines the utility of individual drug use and treatment characteristics for predicting in-treatment performance and post-treatment outcomes over a 1-year period. Data were collected from 420 adults who participated in the Methamphetamine Treatment Project (MTP), a multi-site study of randomly assigned treatment for methamphetamine dependence. Interviews were conducted at baseline, during treatment and during three follow-up time-points: treatment discharge and at 6 and 12 months following admission. The Addiction Severity Index (ASI); the Craving, Frequency, Intensity and Duration Estimate (CFIDE); and laboratory urinalysis results were used in the current study. Analyses addressed both in-treatment performance and post-treatment outcomes. The most consistent finding is that pre-treatment methamphetamine use predicts in-treatment performance and post-treatment outcomes. No one variable predicted all in-treatment performance measures; however, gender, route of administration and pre-treatment methamphetamine use were significant predictors. Similarly, post-treatment outcomes were predicted by a range of variables, although pre-treatment methamphetamine use was significantly associated with each post-treatment outcome. These findings provide useful empirical information about treatment outcomes for methamphetamine abusers, and highlight the utility of assessing individual and in-treatment characteristics in the development of appropriate treatment plans.

The mathematics of morality for neonatal resuscitation.

PubMed

Meadow, William; Lagatta, Joanne; Andrews, Bree; Lantos, John

2012-12-01

This article discusses the ethical issues surrounding the resuscitation of infants who are at great risk to die or survive with significant morbidity. Data are introduced regarding money, outcomes, and prediction. Gestational age influences some of the outcomes after birth more than others do. Prediction is possible at four stages of the resuscitation process. Data suggest that antenatal and delivery room predictions are inadequate, and prediction at the time of discharge is too late. The predictive value (>95%) for the outcome of death or survival with neurodevelopmental impairment is discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

The EXCITE Trial: Predicting a Clinically Meaningful Motor Activity Log Outcome

PubMed Central

Park, Si-Woon; Wolf, Steven L.; Blanton, Sarah; Winstein, Carolee; Nichols-Larsen, Deborah S.

2013-01-01

Background and Objective This study determined which baseline clinical measurements best predicted a predefined clinically meaningful outcome on the Motor Activity Log (MAL) and developed a predictive multivariate model to determine outcome after 2 weeks of constraint-induced movement therapy (CIMT) and 12 months later using the database from participants in the Extremity Constraint Induced Therapy Evaluation (EXCITE) Trial. Methods A clinically meaningful CIMT outcome was defined as achieving higher than 3 on the MAL Quality of Movement (QOM) scale. Predictive variables included baseline MAL, Wolf Motor Function Test (WMFT), the sensory and motor portion of the Fugl-Meyer Assessment (FMA), spasticity, visual perception, age, gender, type of stroke, concordance, and time after stroke. Significant predictors identified by univariate analysis were used to develop the multivariate model. Predictive equations were generated and odds ratios for predictors were calculated from the multivariate model. Results Pretreatment motor function measured by MAL QOM, WMFT, and FMA were significantly associated with outcome immediately after CIMT. Pretreatment MAL QOM, WMFT, proprioception, and age were significantly associated with outcome after 12 months. Each unit of higher pretreatment MAL QOM score and each unit of faster pretreatment WMFT log mean time improved the probability of achieving a clinically meaningful outcome by 7 and 3 times at posttreatment, and 5 and 2 times after 12 months, respectively. Patients with impaired proprioception had a 20% probability of achieving a clinically meaningful outcome compared with those with intact proprioception. Conclusions Baseline clinical measures of motor and sensory function can be used to predict a clinically meaningful outcome after CIMT. PMID:18780883

The EXCITE Trial: Predicting a clinically meaningful motor activity log outcome.

PubMed

Park, Si-Woon; Wolf, Steven L; Blanton, Sarah; Winstein, Carolee; Nichols-Larsen, Deborah S

2008-01-01

This study determined which baseline clinical measurements best predicted a predefined clinically meaningful outcome on the Motor Activity Log (MAL) and developed a predictive multivariate model to determine outcome after 2 weeks of constraint-induced movement therapy (CIMT) and 12 months later using the database from participants in the Extremity Constraint Induced Therapy Evaluation (EXCITE) Trial. A clinically meaningful CIMT outcome was defined as achieving higher than 3 on the MAL Quality of Movement (QOM) scale. Predictive variables included baseline MAL, Wolf Motor Function Test (WMFT), the sensory and motor portion of the Fugl-Meyer Assessment (FMA), spasticity, visual perception, age, gender, type of stroke, concordance, and time after stroke. Significant predictors identified by univariate analysis were used to develop the multivariate model. Predictive equations were generated and odds ratios for predictors were calculated from the multivariate model. Pretreatment motor function measured by MAL QOM, WMFT, and FMA were significantly associated with outcome immediately after CIMT. Pretreatment MAL QOM, WMFT, proprioception, and age were significantly associated with outcome after 12 months. Each unit of higher pretreatment MAL QOM score and each unit of faster pretreatment WMFT log mean time improved the probability of achieving a clinically meaningful outcome by 7 and 3 times at posttreatment, and 5 and 2 times after 12 months, respectively. Patients with impaired proprioception had a 20% probability of achieving a clinically meaningful outcome compared with those with intact proprioception. Baseline clinical measures of motor and sensory function can be used to predict a clinically meaningful outcome after CIMT.

Newcomer Immigrant Adolescents: A Mixed-Methods Examination of Family Stressors and School Outcomes

ERIC Educational Resources Information Center

Patel, Sita G.; Clarke, Annette V.; Eltareb, Fazia; Macciomei, Erynn E.; Wickham, Robert E.

2016-01-01

Family stressors predict negative psychological outcomes for immigrant adolescents, yet little is known about how such stressors interact to predict school outcomes. The purpose of this study was to explore the interactive role of family stressors on school outcomes for newcomer adolescent immigrants. Using a convergent parallel mixed-methods…

Predicting and understanding law-making with word vectors and an ensemble model.

PubMed

Nay, John J

2017-01-01

Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015, only 2,513 were enacted. We developed a machine learning approach to forecasting the probability that any bill will become law. Starting in 2001 with the 107th Congress, we trained models on data from previous Congresses, predicted all bills in the current Congress, and repeated until the 113th Congress served as the test. For prediction we scored each sentence of a bill with a language model that embeds legislative vocabulary into a high-dimensional, semantic-laden vector space. This language representation enables our investigation into which words increase the probability of enactment for any topic. To test the relative importance of text and context, we compared the text model to a context-only model that uses variables such as whether the bill's sponsor is in the majority party. To test the effect of changes to bills after their introduction on our ability to predict their final outcome, we compared using the bill text and meta-data available at the time of introduction with using the most recent data. At the time of introduction context-only predictions outperform text-only, and with the newest data text-only outperforms context-only. Combining text and context always performs best. We conducted a global sensitivity analysis on the combined model to determine important variables predicting enactment.

Predicting and understanding law-making with word vectors and an ensemble model

PubMed Central

Nay, John J.

2017-01-01

Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015, only 2,513 were enacted. We developed a machine learning approach to forecasting the probability that any bill will become law. Starting in 2001 with the 107th Congress, we trained models on data from previous Congresses, predicted all bills in the current Congress, and repeated until the 113th Congress served as the test. For prediction we scored each sentence of a bill with a language model that embeds legislative vocabulary into a high-dimensional, semantic-laden vector space. This language representation enables our investigation into which words increase the probability of enactment for any topic. To test the relative importance of text and context, we compared the text model to a context-only model that uses variables such as whether the bill’s sponsor is in the majority party. To test the effect of changes to bills after their introduction on our ability to predict their final outcome, we compared using the bill text and meta-data available at the time of introduction with using the most recent data. At the time of introduction context-only predictions outperform text-only, and with the newest data text-only outperforms context-only. Combining text and context always performs best. We conducted a global sensitivity analysis on the combined model to determine important variables predicting enactment. PMID:28489868

Clavicle Chest Cage Angle Difference: Is It a Radiographic and Clinical Predictor of Postoperative Shoulder Imbalance in Lenke I Adolescent Idiopathic Scoliosis?

PubMed

Han, Xiao; Liu, Zhen; Qiu, Yong; Sha, Shifu; Yan, Huang; Jin, Mengran; Zhu, Zezhang

2016-09-01

A retrospective study. To evaluate the effect of preoperative clavicle chest cage angle difference (CCAD) on postoperative radiographic shoulder imbalance, cosmetic shoulder balance, patient's satisfaction, and surgeon's fulfillment in Lenke I adolescent idiopathic scoliosis (AIS). CCAD is a novel predictor of postoperative radiographic shoulder imbalance in AIS. However, radiographic shoulder balance does not always correspond to cosmetic shoulder balance. Forty-four Lenke I AIS patients treated with posterior spinal fusion with a minimum 2-year follow-up were analyzed. Shoulder height difference (SHD) and CCAD were measured on anteroposterior standing radiographs. The inner shoulder height (SHi) and the outer shoulder height (SHo) were measured using the patients' photographs. The patients' satisfaction and the surgeons' fulfillment were evaluated using a questionnaire. A receiver operative characteristic curve analysis was performed to explore the threshold values of preoperative CCAD in the prediction of the final follow-up radiographic shoulder imbalance, patients' satisfaction, and surgeons' fulfillment. At the final follow-up, the preoperative CCAD was significantly greater in patients with unbalanced shoulders (SHD ≥1 cm). For cosmetic shoulder balance at the final follow-up, there was no significant difference in preoperative CCAD between Group 1i (SHi ≥1 cm, n = 14) and Group 2i (SHi <1 cm, n = 30), and the preoperative CCAD was also similar between Group 1o (SHo ≥1 cm, n = 17) and Group 2o (SHo <1 cm, n = 27). For patients' satisfaction and surgeons' fulfillment, the preoperative CCAD was significantly greater in patients with unsatisfied outcomes. The threshold value of preoperative CCAD to predict the final follow-up radiographic shoulder imbalance, patients' satisfaction, and surgeons' fulfillment was 5.5°. CCAD is a good radiographic predictor for postoperative radiographic shoulder imbalance in Lenke I AIS patients. Moreover, it is also associated with the patients' satisfaction and surgeons' fulfillment postoperatively. However, CCAD cannot predict postoperative cosmetic shoulder balance. 4.

Comparison of the outcome of burn patients using acute-phase plasma base deficit.

PubMed

Salehi, S H; As'adi, K; Mousavi, J

2011-12-31

Background. In recent years, plasma base deficit has been used as a marker to determine the status of tissue perfusion in trauma patients and also to predict the outcome of these patients. This study was performed to investigate the effect of plasma base deficit in predicting burn patient outcome. Methods. This prospective cohort study was performed from October 2009 to October 2010 in the acute phase of burn patients who were admitted within 6 h post-injury to Motahari Burn Hospital in Iran. The patients were divided into two groups based on the plasma base deficit in the first 24 h post-injury: group A, in which the mean plasma base deficit was less than or equal to -6 (more negative), and group B, in which the mean plasma base deficit greater than -6. Statistical analysis was performed using SPSS v.16 software. Results. Thirty-eight patients were enrolled in each group. The mean plasma base deficit in group A (-7.76 ± 2.18 mmol) was significantly less than that in group B (-1.19 ± 2.82) mmol (p < 0.05). Although there was no significant difference between the mean of fluid resuscitation and urine output in the first 24 h after injury between the two groups (p > 0.05) and despite removal of interfering factors, there were significant differences between the systemic inflammatory response syndrome and the multiple organ dysfunction syndrome score and the percentage of sepsis between the two groups (p < 0.05). The mortality rate in group A (63.2%) was significantly higher than that in group B (36.8%) (p > 0.05). Conclusion. The plasma base deficit can be used as a valuable marker in the resuscitation of burn patients, along with clinical criteria. Physiological indicators (burn percentage, age, and mucosal burns) are not sufficient to predict mortality and morbidity in burn patients, and it is necessary to investigate the role of biochemical markers such as base deficit in determining the final outcome of burn patients.

Does the 6-minute walk test predict the prognosis in patients with NYHA class II or III chronic heart failure?

PubMed

Roul, G; Germain, P; Bareiss, P

1998-09-01

We prospectively evaluated the potential of the 6-minute walk test compared with peak VO2 in predicting outcome of patients with New York Heart Association (NYHA) class II or III heart failure. Patients with a history of heart failure caused by systolic dysfunction were included. The combined final outcome (death or hospitalization for heart failure) was used as the judgment criterion. One hundred twenty-one patients (age 59+/-11 years; left ventricular ejection fraction 29.6%+/-13%) were included and followed for 1.53+/-0.98 years. Patients were separated into two groups according to outcome: group 1 (G1, 74 patients), without events, and group 2 (G2, 47 patients), who reached the combined end point. Peak VO2 was clearly different between G1 and G2 (18.5+/-4 vs. 13.9+/-4 ml/kg/min, p=0.0001) but not the distance walked (448+/-92 vs 410+/-126 m; p=0.084, not significant). Survival analysis showed that unlike peak VO2, the distance covered was barely distinguishable between the groups (p < 0.08). However, receiver operating characteristic curves revealed that the best performances for the 6-minute walk test were obtained for subjects walking < or =300 m. These patients had a worse prognosis than those walking farther (p=0.013). In this subset of patients, there was a significant correlation between distance covered and peak VO2 (r=0.65, p=0.011). Thus it appears that the more severely affected patients have a daily activity level relatively close to their maximal exercise capacity. Nevertheless, the 300 m threshold suggested by this study needs to be validated in an independent population. A distance walked in 6 minutes < or =300 m can predict outcome. Moreover, in these cases there is a significant correlation between the 6-minute walk test and peak VO2 demonstrating the potential of this simple procedure as a first-line screening test for this subset of patients.

Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

PubMed

Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

2017-09-01

Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

Sensory predictions during action support perception of imitative reactions across suprasecond delays.

PubMed

Yon, Daniel; Press, Clare

2018-04-01

Perception during action is optimized by sensory predictions about the likely consequences of our movements. Influential theories in social cognition propose that we use the same predictions during interaction, supporting perception of similar reactions in our social partners. However, while our own action outcomes typically occur at short, predictable delays after movement execution, the reactions of others occur at longer, variable delays in the order of seconds. To examine whether we use sensorimotor predictions to support perception of imitative reactions, we therefore investigated the temporal profile of sensory prediction during action in two psychophysical experiments. We took advantage of an influence of prediction on apparent intensity, whereby predicted visual stimuli appear brighter (more intense). Participants performed actions (e.g., index finger lift) and rated the brightness of observed outcomes congruent (index finger lift) or incongruent (middle finger lift) with their movements. Observed action outcomes could occur immediately after execution, or at longer delays likely reflective of those in natural social interaction (1800 or 3600 ms). Consistent with the previous literature, Experiment 1 revealed that congruent action outcomes were rated as brighter than incongruent outcomes. Importantly, this facilitatory perceptual effect was found irrespective of whether outcomes occurred immediately or at delay. Experiment 2 replicated this finding and demonstrated that it was not the result of response bias. These findings therefore suggest that visual predictions generated during action are sufficiently general across time to support our perception of imitative reactions in others, likely generating a range of benefits during social interaction. Copyright © 2017 Elsevier B.V. All rights reserved.

Feedback-related negativity codes outcome valence, but not outcome expectancy, during reversal learning.

PubMed

von Borries, A K L; Verkes, R J; Bulten, B H; Cools, R; de Bruijn, E R A

2013-12-01

Optimal behavior depends on the ability to assess the predictive value of events and to adjust behavior accordingly. Outcome processing can be studied by using its electrophysiological signatures--that is, the feedback-related negativity (FRN) and the P300. A prominent reinforcement-learning model predicts an FRN on negative prediction errors, as well as implying a role for the FRN in learning and the adaptation of behavior. However, these predictions have recently been challenged. Notably, studies so far have used tasks in which the outcomes have been contingent on the response. In these paradigms, the need to adapt behavioral responses is present only for negative, not for positive feedback. The goal of the present study was to investigate the effects of positive as well as negative violations of expectancy on FRN amplitudes, without the usual confound of behavioral adjustments. A reversal-learning task was employed in which outcome value and outcome expectancy were orthogonalized; that is, both positive and negative outcomes were equally unexpected. The results revealed a double dissociation, with effects of valence but not expectancy on the FRN and, conversely, effects of expectancy but not valence on the P300. While FRN amplitudes were largest for negative-outcome trials, irrespective of outcome expectancy, P300 amplitudes were largest for unexpected-outcome trials, irrespective of outcome valence. These FRN effects were interpreted to reflect an evaluation along a good-bad dimension, rather than reflecting a negative prediction error or a role in behavioral adaptation. By contrast, the P300 reflects the updating of information relevant for behavior in a changing context.

Impact of associated injuries in the Floating knee: A retrospective study

PubMed Central

Rethnam, Ulfin; Yesupalan, Rajam S; Nair, Rajagopalan

2009-01-01

Background Floating knee injuries are usually associated with other significant injuries. Do these injuries have implications on the management of the floating knee and the final outcome of patients? Our study aims to assess the implications of associated injuries in the management and final outcome of floating knee. Methods 29 patients with floating knees were assessed in our institution. A retrospective analysis of medical records and radiographs were done and all associated injuries were identified. The impact of associated injuries on delay in initial surgical management, delay in rehabilitation & final outcome of the floating knee were assessed. Results 38 associated injuries were noted. 7 were associated with ipsilateral knee injuries. Lower limb injuries were most commonly associated with the floating knee. Patients with some associated injuries had a delay in surgical management and others a delay in post-operative rehabilitation. Knee ligament and vascular injuries were associated with poor outcome. Conclusion The associated injuries were quite frequent with the floating knee. Some of the associated injuries caused a delay in surgical management and post-operative rehabilitation. In assessment of the final outcome, patients with associated knee and vascular injuries had a poor prognosis. Majority of the patients with associated injuries had a good or excellent outcome. PMID:19144197

Somatic symptoms: an important index in predicting the outcome of depression at six-month and two-year follow-up points among outpatients with major depressive disorder.

PubMed

Hung, Ching-I; Liu, Chia-Yih; Wang, Shuu-Jiun; Juang, Yeong-Yuh; Yang, Ching-Hui

2010-09-01

Few studies have simultaneously compared the ability of depression, anxiety, and somatic symptoms to predict the outcome of major depressive disorder (MDD). This study aimed to compare the MDD outcome predictive ability of depression, anxiety, and somatic severity at 6-month and 2-year follow-ups. One-hundred and thirty-five outpatients (men/women=34/101) with MDD were enrolled. Depression and anxiety were evaluated by the Hamilton Depression Rating Scale, Hospital Anxiety and Depression Scale, and depression subscale of the Depression and Somatic Symptoms Scale (DSSS). Somatic severity was evaluated by the somatic subscale of the DSSS. Subjects undergoing pharmacotherapy in the follow-up month were categorized into the treatment group; the others were categorized into the no-treatment group. Multiple linear regressions were used to identify the scales most powerful in predicting MDD outcome. Among the 135 subjects, 119 and 106 completed the 6-month and 2-year follow-ups, respectively. Somatic severity at baseline was correlated with the outcomes of the three scales at the two follow-ups. After controlling for demographic variables, somatic severity independently predicted most outcomes of the three scales at the two follow-ups in the no-treatment group and the cost of pharmacotherapy and DSSS score at the 6-month follow-up in the treatment group. Division of the subjects into treatment and no-treatment groups was not based on randomization and bias might have been introduced. Somatic severity was the most powerful index in predicting MDD outcome. Psychometric scales with appropriate somatic symptom items may be more accurate in predicting MDD outcome. 2010 Elsevier B.V. All rights reserved.

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

'What will I be like' after my diagnosis of head and neck cancer?

PubMed

Rogers, S N; Hogg, E S; Cheung, W K A; Lai, L K L; Jassal, P; Lowe, D; Kanatas, A

2015-09-01

Consequences of treating head and neck cancer are reflected in health-related quality of life (HRQOL) patient-reported outcomes. HRQOL is an important outcome alongside survival and recurrence. However, relatively little HRQOL information is in a format that patients and oncology teams can easily interpret as a guide to likely outcomes following curative treatment. The study aim was to collate University of Washington Quality of Life (UW-QOL) questionnaires collected 1995-2012 at the Regional Head and Neck Surgical Unit with a view of summarizing key clinical-demographic influences on HRQOL outcomes at 2 years following diagnosis. Patients completing UW-QOL questionnaires at 9-60 months had their record closest to 2 years selected for cross-sectional analyses, while all questionnaires were analyzed to assess temporal trends. 65 % (1,134) of survivors to 9 months had a UW-QOL record in the cross-sectional analysis (median 23 months). Overall 1,349 completed 5,573 UW-QOL questionnaires. Various associations were seen, notably late overall clinical staging and treatment adversely associated with UW-QOL physical functioning domains. Logistic regression was used to better understand the predictive factors of UW-QOL outcome and determined the final formatting of tables for results. These tables provide important reference data about UW-QOL outcome at 2 years relevant to patients at the outset of their cancer journey. The increasing amount of HRQOL data allows for quite detailed subgroup analysis, which can help give patients and the clinical team a better understanding of likely long-term HRQOL outcomes. How this is best utilized in clinical care needs further evaluation.

Validation of the CRASH model in the prediction of 18-month mortality and unfavorable outcome in severe traumatic brain injury requiring decompressive craniectomy.

PubMed

Honeybul, Stephen; Ho, Kwok M; Lind, Christopher R P; Gillett, Grant R

2014-05-01

The goal in this study was to assess the validity of the corticosteroid randomization after significant head injury (CRASH) collaborators prediction model in predicting mortality and unfavorable outcome at 18 months in patients with severe traumatic brain injury (TBI) requiring decompressive craniectomy. In addition, the authors aimed to assess whether this model was well calibrated in predicting outcome across a wide spectrum of severity of TBI requiring decompressive craniectomy. This prospective observational cohort study included all patients who underwent a decompressive craniectomy following severe TBI at the two major trauma hospitals in Western Australia between 2004 and 2012 and for whom 18-month follow-up data were available. Clinical and radiological data on initial presentation were entered into the Web-based model and the predicted outcome was compared with the observed outcome. In validating the CRASH model, the authors used area under the receiver operating characteristic curve to assess the ability of the CRASH model to differentiate between favorable and unfavorable outcomes. The ability of the CRASH 6-month unfavorable prediction model to differentiate between unfavorable and favorable outcomes at 18 months after decompressive craniectomy was good (area under the receiver operating characteristic curve 0.85, 95% CI 0.80-0.90). However, the model's calibration was not perfect. The slope and the intercept of the calibration curve were 1.66 (SE 0.21) and -1.11 (SE 0.14), respectively, suggesting that the predicted risks of unfavorable outcomes were not sufficiently extreme or different across different risk strata and were systematically too high (or overly pessimistic), respectively. The CRASH collaborators prediction model can be used as a surrogate index of injury severity to stratify patients according to injury severity. However, clinical decisions should not be based solely on the predicted risks derived from the model, because the number of patients in each predicted risk stratum was still relatively small and hence the results were relatively imprecise. Notwithstanding these limitations, the model may add to a clinician's ability to have better-informed conversations with colleagues and patients' relatives about prognosis.

Predicting medical complications after spine surgery: a validated model using a prospective surgical registry.

PubMed

Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

2014-02-01

The possibility and likelihood of a postoperative medical complication after spine surgery undoubtedly play a major role in the decision making of the surgeon and patient alike. Although prior study has determined relative risk and odds ratio values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of medical complication, rather than relative risk or odds ratio values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of medical complication during and after spine surgery. Statistical analysis using a prospective surgical spine registry that recorded extensive demographic, surgical, and complication data. Outcomes examined are medical complications that were specifically defined a priori. This analysis is a continuation of statistical analysis of our previously published report. Using a prospectively collected surgical registry of more than 1,476 patients with extensive demographic, comorbidity, surgical, and complication detail recorded for 2 years after surgery, we previously identified several risk factor for medical complications. Using the beta coefficients from those log binomial regression analyses, we created a model to predict the occurrence of medical complication after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created two predictive models: one predicting the occurrence of any medical complication and the other predicting the occurrence of a major medical complication. The final predictive model for any medical complications had a receiver operator curve characteristic of 0.76, considered to be a fair measure. The final predictive model for any major medical complications had receiver operator curve characteristic of 0.81, considered to be a good measure. The final model has been uploaded for use on SpineSage.com. We present a validated model for predicting medical complications after spine surgery. The value in this model is that it gives the user an absolute percent likelihood of complication after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Patients are far more likely to understand an absolute percentage, rather than relative risk and confidence interval values. A model such as this is of paramount importance in counseling patients and enhancing the safety of spine surgery. In addition, a tool such as this can be of great use particularly as health care trends toward pay-for-performance, quality metrics, and risk adjustment. To facilitate the use of this model, we have created a website (SpineSage.com) where users can enter in patient data to determine likelihood of medical complications after spine surgery. Copyright © 2014 Elsevier Inc. All rights reserved.

Prediction of outcome of bright light treatment in patients with seasonal affective disorder: Discarding the early response, confirming a higher atypical balance, and uncovering a higher body mass index at baseline as predictors of endpoint outcome.

PubMed

Dimitrova, Tzvetelina D; Reeves, Gloria M; Snitker, Soren; Lapidus, Manana; Sleemi, Aamar R; Balis, Theodora G; Manalai, Partam; Tariq, Muhammad M; Cabassa, Johanna A; Karim, Naila N; Johnson, Mary A; Langenberg, Patricia; Rohan, Kelly J; Miller, Michael; Stiller, John W; Postolache, Teodor T

2017-11-01

We tested the hypothesis that the early improvement in mood after the first hour of bright light treatment compared to control dim-red light would predict the outcome at six weeks of bright light treatment for depressed mood in patients with Seasonal Affective Disorder (SAD). We also analyzed the value of Body Mass Index (BMI) and atypical symptoms of depression at baseline in predicting treatment outcome. Seventy-eight adult participants were enrolled. The first treatment was controlled crossover, with randomized order, and included one hour of active bright light treatment and one hour of control dim-red light, with one-hour washout. Depression was measured on the Structured Interview Guide for the Hamilton Rating Scale for Depression-SAD version (SIGH-SAD). The predictive association of depression scores changes after the first session. BMI and atypical score balance with treatment outcomes at endpoint were assessed using multivariable linear and logistic regressions. No significant prediction by changes in depression scores after the first session was found. However, higher atypical balance scores and BMI positively predicted treatment outcome. Absence of a control intervention for the six-weeks of treatment (only the first session in the laboratory was controlled). Exclusion of patients with comorbid substance abuse, suicidality and bipolar I disorder, and patients on antidepressant medications, reducing the generalizability of the study. Prediction of outcome by early response to light treatment was not replicated, and the previously reported prediction of baseline atypical balance was confirmed. BMI, a parameter routinely calculated in primary care, was identified as a novel predictor, and calls for replication and then exploration of possible mediating mechanisms. Published by Elsevier B.V.

A Prediction Model for Functional Outcomes in Spinal Cord Disorder Patients Using Gaussian Process Regression.

PubMed

Lee, Sunghoon Ivan; Mortazavi, Bobak; Hoffman, Haydn A; Lu, Derek S; Li, Charles; Paak, Brian H; Garst, Jordan H; Razaghy, Mehrdad; Espinal, Marie; Park, Eunjeong; Lu, Daniel C; Sarrafzadeh, Majid

2016-01-01

Predicting the functional outcomes of spinal cord disorder patients after medical treatments, such as a surgical operation, has always been of great interest. Accurate posttreatment prediction is especially beneficial for clinicians, patients, care givers, and therapists. This paper introduces a prediction method for postoperative functional outcomes by a novel use of Gaussian process regression. The proposed method specifically considers the restricted value range of the target variables by modeling the Gaussian process based on a truncated Normal distribution, which significantly improves the prediction results. The prediction has been made in assistance with target tracking examinations using a highly portable and inexpensive handgrip device, which greatly contributes to the prediction performance. The proposed method has been validated through a dataset collected from a clinical cohort pilot involving 15 patients with cervical spinal cord disorder. The results show that the proposed method can accurately predict postoperative functional outcomes, Oswestry disability index and target tracking scores, based on the patient's preoperative information with a mean absolute error of 0.079 and 0.014 (out of 1.0), respectively.

A multivariate analysis of pre-, peri-, and post-transplant factors affecting outcome after pediatric liver transplantation.

PubMed

McDiarmid, Sue V; Anand, Ravinder; Martz, Karen; Millis, Michael J; Mazariegos, George

2011-07-01

The purpose of this study was to identify significant, independent factors that predicted 6 month patient and graft survival after pediatric liver transplantation. The Studies of Pediatric Liver Transplantation (SPLIT) is a multicenter database established in 1995, of currently more than 4000 US and Canadian children undergoing liver transplantation. Previous published analyses from this data have examined specific factors influencing outcome. This study analyzes a comprehensive range of factors that may influence outcome from the time of listing through the peri- and postoperative period. A total of 42 pre-, peri- and posttransplant variables evaluated in 2982 pediatric recipients of a first liver transplant registered in SPLIT significant at the univariate level were included in multivariate models. In the final model combining all baseline and posttransplant events, posttransplant complications had the highest relative risk of death or graft loss. Reoperation for any cause increased the risk for both patient and graft loss by 11 fold and reoperation exclusive of specific complications by 4 fold. Vascular thromboses, bowel perforation, septicemia, and retransplantation, each independently increased the risk of patient and graft loss by 3 to 4 fold. The only baseline factor with a similarly high relative risk for patient and graft loss was recipient in the intensive care unit (ICU) intubated at transplant. A significant center effect was also found but did not change the impact of the highly significant factors already identified. We conclude that the most significant factors predicting patient and graft loss at 6 months in children listed for transplant are posttransplant surgical complications.

Early language delay phenotypes and correlation with later linguistic abilities.

PubMed

Petinou, Kakia; Spanoudis, George

2014-01-01

The present study focused on examining the continuity and directionality of language skills in late talkers (LTs) and identifying factors which might contribute to language outcomes at the age of 3 years. Subjects were 23 Cypriot-Greek-speaking toddlers classified as LTs and 24 age-matched typically developing peers (TDs). Participants were assessed at 28, 32 and 36 months, using various linguistic measures such as size of receptive and expressive vocabulary, mean length of utterance (MLU) of words and number of consonants produced. Data on otitis media familial history were also analyzed. The ANOVA results indicated parallel developmental profiles between the two groups, with a language lag characterizing LTs. Concurrent correlations between measures showed that poor phonetic inventories in the LT group at 28 months predicted poor MLU at the ages of 32 and 36 months. Significant cross-lagged correlations supported the finding that poor phonetic inventories at 28 months served as a good predictor for MLU and expressive vocabulary at the age of 32 and for MLU at 36 months. The results highlight the negative effect of early language delay on language skills up to the age of 3 years and lend support to the current literature regarding the universal linguistic picture of early and persistent language delay. Based on the current results, poor phonetic inventories at the age of intake might serve as a predictive factor for language outcomes at the age of 36 months. Finally, the findings are discussed in view of the need for further research with a focus on more language-sensitive tools in testing later language outcomes. © 2014 S. Karger AG, Basel.

Academic adjustment across middle school: the role of public regard and parenting.

PubMed

McGill, Rebecca Kang; Hughes, Diane; Alicea, Stacey; Way, Niobe

2012-07-01

In the current longitudinal study, we examined associations between Black and Latino youths' perceptions of the public's opinion of their racial/ethnic group (i.e., public regard) and changes in academic adjustment outcomes across middle school. We also tested combinations of racial/ethnic socialization and parent involvement in academic activities as moderators of this association. We used a 2nd-order latent trajectory model to test changes in academic adjustment outcomes in a sample of 345 Black and Latino urban youth across 6th, 7th, and 8th grades (51% female). Results revealed a significant average linear decline in academic adjustment from 6th to 8th grade, as well as significant variation around this decline. We found that parenting moderated the association between public regard and the latent trajectory of academic adjustment. Specifically, for youth who reported high racial/ethnic socialization and low parent academic involvement, lower public regard predicted lower academic adjustment in 6th grade. For youth who reported both low racial/ethnic socialization and low parent academic involvement, lower public regard predicted a steeper decline in academic adjustment over time. Finally, among youth who reported high racial/ethnic socialization and high parent academic involvement, public regard was not associated with either the intercept or the slope of academic adjustment. Thus, the combination of high racial/ethnic socialization and parent academic involvement may protect youths' academic motivation and performance from the negative effects of believing the public has low opinions of one's racial/ethnic group. Implications for protecting Black and Latino youths' academic outcomes from decline during middle school are discussed.

Does improvement in maternal attachment representations predict greater maternal sensitivity, child attachment security and lower rates of relapse to substance use? A second test of Mothering from the Inside Out treatment mechanisms.

PubMed

Suchman, Nancy E; DeCoste, Cindy; Borelli, Jessica L; McMahon, Thomas J

2018-02-01

In this study, we replicated a rigorous test of the proposed mechanisms of change associated with Mothering from the Inside out (MIO), an evidence-based parenting therapy that aims to enhance maternal reflective functioning and mental representations of caregiving in mothers enrolled in addiction treatment and caring for young children. First, using data from 84 mothers who enrolled in our second randomized controlled trial, we examined whether therapist fidelity to core MIO treatment components predicted improvement in maternal reflective functioning and mental representations of caregiving, even after taking fidelity to non-MIO components into account. Next, we examined whether improvement in directly targeted outcomes (e.g., maternal mentalizing and mental representations of caregiving) led to improvements in the indirectly targeted outcome of maternal caregiving sensitivity, even after controlling for other plausible competing mechanisms (e.g., improvement in maternal psychiatric distress and substance use). Third, we examined whether improvement in targeted parenting outcomes (e.g., maternal mentalizing, mental representations of caregiving and caregiving sensitivity) was associated in improvement in child attachment status, even after controlling for competing mechanisms (e.g., improvement in maternal psychiatric distress and substance use). Finally, we examined whether improvement in maternal mentalizing and caregiving representations was associated with a reduction in relapse to substance use. Support was found for the first three tests of mechanisms but not the fourth. Implications for future research and intervention development are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting adverse neonatal outcomes in fetuses with abdominal wall defects using prenatal risk factors.

PubMed

Nicholas, Sara S; Stamilio, David M; Dicke, Jeffery M; Gray, Diana L; Macones, George A; Odibo, Anthony O

2009-10-01

The aim of this study was to determine whether prenatal variables can predict adverse neonatal outcomes in fetuses with abdominal wall defects. A retrospective cohort study that used ultrasound and neonatal records for all cases of gastroschisis and omphalocele seen over a 16-year period. Cases with adverse neonatal outcomes were compared with noncases for multiple candidate predictive factors. Univariable and multivariable statistical methods were used to develop the prediction models, and effectiveness was evaluated using the area under the receiver operating characteristic curve. Of 80 fetuses with gastroschisis, 29 (36%) had the composite adverse outcome, compared with 15 of 33 (47%) live neonates with omphalocele. Intrauterine growth restriction was the only significant variable in gastroschisis, whereas exteriorized liver was the only predictor in omphalocele. The areas under the curve for the prediction models with gastroschisis and omphalocele are 0.67 and 0.74, respectively. Intrauterine growth restriction and exteriorization of the liver are significant predictors of adverse neonatal outcome with gastroschisis and omphalocele.

Goal-directed EEG activity evoked by discriminative stimuli in reinforcement learning.

PubMed

Luque, David; Morís, Joaquín; Rushby, Jacqueline A; Le Pelley, Mike E

2015-02-01

In reinforcement learning (RL), discriminative stimuli (S) allow agents to anticipate the value of a future outcome, and the response that will produce that outcome. We examined this processing by recording EEG locked to S during RL. Incentive value of outcomes and predictive value of S were manipulated, allowing us to discriminate between outcome-related and response-related activity. S predicting the correct response differed from nonpredictive S in the P2. S paired with high-value outcomes differed from those paired with low-value outcomes in a frontocentral positivity and in the P3b. A slow negativity then distinguished between predictive and nonpredictive S. These results suggest that, first, attention prioritizes detection of informative S. Activation of mental representations of these informative S then retrieves representations of outcomes, which in turn retrieve representations of responses that previously produced those outcomes. © 2014 Society for Psychophysiological Research.

The Effect of Cognitive Load and Outcome Congruency on the Learned Predictiveness Effect in Human Predictive Learning

ERIC Educational Resources Information Center

Jorge A. Pinto,; Vogel, Edgar H.; Núñez, Daniel E.

2017-01-01

The learned predictiveness effect or LPE is the finding that when people learn that certain cues are reliable predictors of an outcome in an initial stage of training (phase 1), they exhibit a learning bias in favor of these cues in a subsequent training involving new outcomes (phase 2) despite all cues being equally reliable in phase 2. In…

Center of Excellence for Individuation of Therapy for Breast Cancer

DTIC Science & Technology

2012-03-01

Sledge, B. Leyland-Jones (2011) Gene copy number and expression of TYMP and TYMS are predictive of outcome in breast cancer patients treated with... Gene copy number and expression of TYMP and TYMS are predictive of outcome in breast cancer patients treated with capecitabine. R. Audet, C...determine if a specific gene expression signature could be used as predictive marker for treatment outcome . Results summary for Cohort A: doxorubicin

Using mean duration and variation of procedure times to plan a list of surgical operations to fit into the scheduled list time.

PubMed

Pandit, Jaideep J; Tavare, Aniket

2011-07-01

It is important that a surgical list is planned to utilise as much of the scheduled time as possible while not over-running, because this can lead to cancellation of operations. We wished to assess whether, theoretically, the known duration of individual operations could be used quantitatively to predict the likely duration of the operating list. In a university hospital setting, we first assessed the extent to which the current ad-hoc method of operating list planning was able to match the scheduled operating list times for 153 consecutive historical lists. Using receiver operating curve analysis, we assessed the ability of an alternative method to predict operating list duration for the same operating lists. This method uses a simple formula: the sum of individual operation times and a pooled standard deviation of these times. We used the operating list duration estimated from this formula to generate a probability that the operating list would finish within its scheduled time. Finally, we applied the simple formula prospectively to 150 operating lists, 'shadowing' the current ad-hoc method, to confirm the predictive ability of the formula. The ad-hoc method was very poor at planning: 50% of historical operating lists were under-booked and 37% over-booked. In contrast, the simple formula predicted the correct outcome (under-run or over-run) for 76% of these operating lists. The calculated probability that a planned series of operations will over-run or under-run was found useful in developing an algorithm to adjust the planned cases optimally. In the prospective series, 65% of operating lists were over-booked and 10% were under-booked. The formula predicted the correct outcome for 84% of operating lists. A simple quantitative method of estimating operating list duration for a series of operations leads to an algorithm (readily created on an Excel spreadsheet, http://links.lww.com/EJA/A19) that can potentially improve operating list planning.

Predicting recovery of voluntary upper extremity movement in subacute stroke patients with severe upper extremity paresis.

PubMed

Koh, Chia-Lin; Pan, Shin-Liang; Jeng, Jiann-Shing; Chen, Bang-Bin; Wang, Yen-Ho; Hsueh, I-Ping; Hsieh, Ching-Lin

2015-01-01

Prediction of voluntary upper extremity (UE) movement recovery is largely unknown in patients with little voluntary UE movement at admission. The present study aimed to investigate (1) the extent and variation of voluntary UE movement recovery, and (2) the best predictive model of the recovery of voluntary UE movement by clinical variables in patients with severe UE paresis. Prospective cohort study. 140 (out of 590) stroke patients with severe UE paresis completed all assessments. Voluntary UE movement was assessed using the UE subscale of the Stroke Rehabilitation Assessment of Movement (STREAM-UE). Two outcome measures, STREAM-UE scores at discharge (DC(STREAM-UE)) and changes between admission and discharge (Δ(STREAM-UE)), were investigated to represent the final states and improvement of the recovery of voluntary UE movement. Stepwise regression analyses were used to investigate 19 clinical variables and to find the best predictive models of the two outcome measures. The participants showed wide variation in both DC(STREAM-UE) and Δ(STREAM-UE). 3.6% of the participants almost fully recovered at discharge (DC(STREAM-UE) > 15). A large improvement (Δ(STREAM-UE) >= 10) occurred in 16.4% of the participants, while 32.9% of the participants did not have any improvement. The four predictors for the DC(STREAM-UE) (R(2) = 35.0%) were 'baseline STREAM-UE score', 'hemorrhagic stroke', 'baseline National Institutes of Health Stroke Scale (NIHSS) score', and 'cortical lesion excluding primary motor cortex'. The three predictors for the Δ(STREAM-UE) (R(2) = 22.0%) were 'hemorrhagic stroke', 'baseline NIHSS score', and 'cortical lesion excluding primary motor cortex'. Recovery of voluntary UE movement varied widely in patients with severe UE paresis after stroke. The predictive power of clinical variables was poor. Both results indicate the complex nature of voluntary UE movement recovery in patients with severe UE paresis after stroke.

One wouldn't expect an expert bowler to hit only two pins: Hierarchical predictive processing of agent-caused events.

PubMed

Heil, Lieke; Kwisthout, Johan; van Pelt, Stan; van Rooij, Iris; Bekkering, Harold

2018-01-01

Evidence is accumulating that our brains process incoming information using top-down predictions. If lower level representations are correctly predicted by higher level representations, this enhances processing. However, if they are incorrectly predicted, additional processing is required at higher levels to "explain away" prediction errors. Here, we explored the potential nature of the models generating such predictions. More specifically, we investigated whether a predictive processing model with a hierarchical structure and causal relations between its levels is able to account for the processing of agent-caused events. In Experiment 1, participants watched animated movies of "experienced" and "novice" bowlers. The results are in line with the idea that prediction errors at a lower level of the hierarchy (i.e., the outcome of how many pins fell down) slow down reporting of information at a higher level (i.e., which agent was throwing the ball). Experiments 2 and 3 suggest that this effect is specific to situations in which the predictor is causally related to the outcome. Overall, the study supports the idea that a hierarchical predictive processing model can account for the processing of observed action outcomes and that the predictions involved are specific to cases where action outcomes can be predicted based on causal knowledge.

Phosphorylated tau/amyloid beta 1-42 ratio in ventricular cerebrospinal fluid reflects outcome in idiopathic normal pressure hydrocephalus

PubMed Central

2012-01-01

Background Idiopathic normal pressure hydrocephalus (iNPH) is a potentially reversible cause of dementia and gait disturbance that is typically treated by operative placement of a ventriculoperitoneal shunt. The outcome from shunting is variable, and some evidence suggests that the presence of comorbid Alzheimer's disease (AD) may impact shunt outcome. Evidence also suggests that AD biomarkers in cerebrospinal fluid (CSF) may predict the presence of AD. The aim of this study was to investigate the relationship between the phosphorylated tau/amyloid beta 1-42 (ptau/Aβ1-42) ratio in ventricular CSF and shunt outcome in patients with iNPH. Methods We conducted a prospective trial with a cohort of 39 patients with suspected iNPH. Patients were clinically and psychometrically assessed prior to and approximately 4 months after ventriculoperitoneal shunting. Lumbar and ventricular CSF obtained intraoperatively, and tissue from intraoperative cortical biopsies were analyzed for AD biomarkers. Outcome measures included performance on clinical symptom scales, supplementary gait measures, and standard psychometric tests. We investigated relationships between the ptau/Aβ1-42 ratio in ventricular CSF and cortical AD pathology, initial clinical features, shunt outcome, and lumbar CSF ptau/Aβ1-42 ratios in the patients in our cohort. Results We found that high ptau/Aβ1-42 ratios in ventricular CSF correlated with the presence of cortical AD pathology. At baseline, iNPH patients with ratio values most suggestive of AD presented with better gait performance but poorer cognitive performance. Patients with high ptau/Aβ1-42 ratios also showed a less robust response to shunting on both gait and cognitive measures. Finally, in a subset of 18 patients who also underwent lumbar puncture, ventricular CSF ratios were significantly correlated with lumbar CSF ratios. Conclusions Levels of AD biomarkers in CSF correlate with the presence of cortical AD pathology and predict aspects of clinical presentation in iNPH. Moreover, preliminary evidence suggests that CSF biomarkers of AD may prove useful for stratifying shunt prognosis in patients being evaluated and treated for this condition. PMID:22444461

Use of a machine learning framework to predict substance use disorder treatment success

PubMed Central

Kelmansky, Diana; van der Laan, Mark; Sahker, Ethan; Jones, DeShauna; Arndt, Stephan

2017-01-01

There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitates this decision by combining all identified prediction algorithms pertinent for a particular prediction problem. SL generates a final model that is at least as good as any of the other models considered for predicting the outcome. The overarching aim of this work is to introduce SL to analysts and practitioners. This work compares the performance of logistic regression, penalized regression, random forests, deep learning neural networks, and SL to predict successful substance use disorders (SUD) treatment. A nationwide database including 99,013 SUD treatment patients was used. All algorithms were evaluated using the area under the receiver operating characteristic curve (AUC) in a test sample that was not included in the training sample used to fit the prediction models. AUC for the models ranged between 0.793 and 0.820. SL was superior to all but one of the algorithms compared. An explanation of SL steps is provided. SL is the first step in targeted learning, an analytic framework that yields double robust effect estimation and inference with fewer assumptions than the usual parametric methods. Different aspects of SL depending on the context, its function within the targeted learning framework, and the benefits of this methodology in the addiction field are discussed. PMID:28394905

Use of a machine learning framework to predict substance use disorder treatment success.

PubMed

Acion, Laura; Kelmansky, Diana; van der Laan, Mark; Sahker, Ethan; Jones, DeShauna; Arndt, Stephan

2017-01-01

There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitates this decision by combining all identified prediction algorithms pertinent for a particular prediction problem. SL generates a final model that is at least as good as any of the other models considered for predicting the outcome. The overarching aim of this work is to introduce SL to analysts and practitioners. This work compares the performance of logistic regression, penalized regression, random forests, deep learning neural networks, and SL to predict successful substance use disorders (SUD) treatment. A nationwide database including 99,013 SUD treatment patients was used. All algorithms were evaluated using the area under the receiver operating characteristic curve (AUC) in a test sample that was not included in the training sample used to fit the prediction models. AUC for the models ranged between 0.793 and 0.820. SL was superior to all but one of the algorithms compared. An explanation of SL steps is provided. SL is the first step in targeted learning, an analytic framework that yields double robust effect estimation and inference with fewer assumptions than the usual parametric methods. Different aspects of SL depending on the context, its function within the targeted learning framework, and the benefits of this methodology in the addiction field are discussed.

Contrasting cue-density effects in causal and prediction judgments.

PubMed

Vadillo, Miguel A; Musca, Serban C; Blanco, Fernando; Matute, Helena

2011-02-01

Many theories of contingency learning assume (either explicitly or implicitly) that predicting whether an outcome will occur should be easier than making a causal judgment. Previous research suggests that outcome predictions would depart from normative standards less often than causal judgments, which is consistent with the idea that the latter are based on more numerous and complex processes. However, only indirect evidence exists for this view. The experiment presented here specifically addresses this issue by allowing for a fair comparison of causal judgments and outcome predictions, both collected at the same stage with identical rating scales. Cue density, a parameter known to affect judgments, is manipulated in a contingency learning paradigm. The results show that, if anything, the cue-density bias is stronger in outcome predictions than in causal judgments. These results contradict key assumptions of many influential theories of contingency learning.

Is the AIMS65 score useful in predicting outcomes in peptic ulcer bleeding?

PubMed

Jung, Sung Hoon; Oh, Jung Hwan; Lee, Hye Yeon; Jeong, Joon Won; Go, Se Eun; You, Chan Ran; Jeon, Eun Jung; Choi, Sang Wook

2014-02-21

To evaluate the applicability of AIMS65 scores in predicting outcomes of peptic ulcer bleeding. This was a retrospective study in a single center between January 2006 and December 2011. We enrolled 522 patients with upper gastrointestinal haemorrhage who visited the emergency room. High-risk patients were regarded as those who had re-bleeding within 30 d from the first endoscopy as well as those who died within 30 d of visiting the Emergency room. A total of 149 patients with peptic ulcer bleeding were analysed, and the AIMS65 score was used to retrospectively predict the high-risk patients. A total of 149 patients with peptic ulcer bleeding were analysed. The poor outcome group comprised 28 patients [male: 23 (82.1%) vs female: 5 (10.7%)] while the good outcome group included 121 patients [male: 93 (76.9%) vs female: 28 (23.1%)]. The mean age in each group was not significantly different. The mean serum albumin levels in the poor outcome group were slightly lower than those in the good outcome group (P = 0.072). For the prediction of poor outcome, the AIMS65 score had a sensitivity of 35.5% (95%CI: 27.0-44.8) and a specificity of 82.1% (95%CI: 63.1-93.9) at a score of 0. The AIMS65 score was insufficient for predicting outcomes in peptic ulcer bleeding (area under curve = 0.571; 95%CI: 0.49-0.65). The AIMS65 score may therefore not be suitable for predicting clinical outcomes in peptic ulcer bleeding. Low albumin levels may be a risk factor associated with high mortality in peptic ulcer bleeding.

Predicting outcome of status epilepticus.

PubMed

Leitinger, M; Kalss, G; Rohracher, A; Pilz, G; Novak, H; Höfler, J; Deak, I; Kuchukhidze, G; Dobesberger, J; Wakonig, A; Trinka, E

2015-08-01

Status epilepticus (SE) is a frequent neurological emergency complicated by high mortality and often poor functional outcome in survivors. The aim of this study was to review available clinical scores to predict outcome. Literature review. PubMed Search terms were "score", "outcome", and "status epilepticus" (April 9th 2015). Publications with abstracts available in English, no other language restrictions, or any restrictions concerning investigated patients were included. Two scores were identified: "Status Epilepticus Severity Score--STESS" and "Epidemiology based Mortality score in SE--EMSE". A comprehensive comparison of test parameters concerning performance, options, and limitations was performed. Epidemiology based Mortality score in SE allows detailed individualization of risk factors and is significantly superior to STESS in a retrospective explorative study. In particular, EMSE is very good at detection of good and bad outcome, whereas STESS detecting bad outcome is limited by a ceiling effect and uncertainty of correct cutoff value. Epidemiology based Mortality score in SE can be adapted to different regions in the world and to advances in medicine, as new data emerge. In addition, we designed a reporting standard for status epilepticus to enhance acquisition and communication of outcome relevant data. A data acquisition sheet used from patient admission in emergency room, from the EEG lab to intensive care unit, is provided for optimized data collection. Status Epilepticus Severity Score is easy to perform and predicts bad outcome, but has a low predictive value for good outcomes. Epidemiology based Mortality score in SE is superior to STESS in predicting good or bad outcome but needs marginally more time to perform. Epidemiology based Mortality score in SE may prove very useful for risk stratification in interventional studies and is recommended for individual outcome prediction. Prospective validation in different cohorts is needed for EMSE, whereas STESS needs further validation in cohorts with a wider range of etiologies. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015. Published by Elsevier Inc.

Additional diagnostic and prognostic value of copeptin ultra-sensitive for diagnosis of non-ST-elevation myocardial infarction in older patients presenting to the emergency department.

PubMed

Bahrmann, Philipp; Bahrmann, Anke; Breithardt, Ole-A; Daniel, Werner G; Christ, Michael; Sieber, Cornel C; Bertsch, Thomas

2013-06-01

Identifying older patients with non-ST- elevation myocardial infarction (NSTEMI) within the very large proportion with elevated high-sensitive cardiac troponin T (hs-cTnT) is a diagnostic challenge because they often present without clear symptoms or electrocardiographic features of acute coronary syndrome to the emergency department (ED). We prospectively investigated the diagnostic and prognostic performance of copeptin ultra-sensitive (copeptin-us) and hs-cTnT compared to hs-cTnT alone for NSTEMI at prespecified cut-offs in unselected older patients. We consecutively enrolled 306 non-surgical patients ≥70 years presenting to the ED. In addition to clinical examination, copeptin-us and hs-cTnT were measured at admission. Two cardiologists independently adjudicated the final diagnosis of NSTEMI after reviewing all available data. All patients were followed up for cardiovascular-related death within the following 12 months. NSTEMI was diagnosed in 38 (12%) patients (age 81±6 years). The combination of copeptin-us ≥14 pmol/L and hs-cTnT ≥0.014 µg/L compared to hs-cTnT ≥0.014 µg/L alone had a positive predictive value of 21% vs. 19% to rule in NSTEMI. The combination of copeptin-us <14 pmol/L and hs-cTnT <0.014 µg/L compared to hs-cTnT <0.014 µg/L alone had a negative predictive value of 100% vs. 99% to rule out NSTEMI. Hs-cTnT ≥0.014 µg/L alone was significantly associated with outcome. When copeptin-us ≥14 pmol/L was added, the net reclassification improvement for outcome was not significant (p=0.809). In unselected older patients presenting to the ED, the additional use of copeptin-us at predefined cut-offs may help to reliably rule out NSTEMI but may not help to increase predicted risk for outcome compared to hs-cTnT alone.

Five-year outcome of normal pressure hydrocephalus with or without a shunt: predictive value of the clinical signs, neuropsychological evaluation and infusion test.

PubMed

Savolainen, S; Hurskainen, H; Paljärvi, L; Alafuzoff, I; Vapalahti, M

2002-06-01

Between 1993-1995, 51 patients under 75 years of age with clinical symptoms and CT-based diagnosis of normal pressure hydrocephalus were investigated prospectively in order to clarify the value of neuropsychological tests, clinical symptoms and signs and infusion test in the differential diagnosis and prediction of outcome in normal pressure hydrocephalus. Patients had a thorough neurological examination, and neuropsychological evaluation. A 24-hour intraventricular ICP-measurement, infusion test, neurophysiological investigations and MRI study were performed, and a cortical biopsy was obtained. The ICP measurement defined the need for a shunt. All 51 patients were re-examined three and twelve months later. The final follow-up was accomplished five years postoperatively. 25 of the patients needed a shunt operation. One year after a shunt placement 72% of these patients had a good recovery concerning activities of daily living, 58% benefited in their urinary incontinence and 57% walked better. During the 5 years of follow-up 8 patients with shunt and 9 without shunt had died. Positive effect of shunting remained. Only one neuropsychological test, recognition of words test, distinguishes the patients with the need for a shunt. Simple mini mental examination test was not different in those who improved. In the postoperative follow-up patients with shunt showed no change in neuropsychological tests even if they were subjectively better. The infusion test was of no value in diagnosing NPH. The 16 patients with Alzheimer's disease did worse after one year than those without pathological changes, but the mortality was not increased. Specific neuropsychological tests are of little value in diagnosing NPH. Mini-Mental status examination was neither of value in diagnosing NPH nor in prediction of the outcome. In this study the infusion test did not improve diagnostic accuracy of NPH, but shunt placement relieves urinary incontinence and walking disability in patients with increased ICP. The patients with positive Alzheimer diagnosis on biopsy did not improve.

Clinical prediction of functional outcome after ischemic stroke: the surprising importance of periventricular white matter disease and race.

PubMed

Kissela, Brett; Lindsell, Christopher J; Kleindorfer, Dawn; Alwell, Kathleen; Moomaw, Charles J; Woo, Daniel; Flaherty, Matthew L; Air, Ellen; Broderick, Joseph; Tsevat, Joel

2009-02-01

We sought to build models that address questions of interest to patients and families by predicting short- and long-term mortality and functional outcome after ischemic stroke, while allowing for risk restratification as comorbid events accumulate. A cohort of 451 ischemic stroke subjects in 1999 were interviewed during hospitalization, at 3 months, and at approximately 4 years. Medical records from the acute hospitalization were abstracted. All hospitalizations for 3 months poststroke were reviewed to ascertain medical and psychiatric comorbidities, which were categorized for analysis. Multivariable models were derived to predict mortality and functional outcome (modified Rankin Scale) at 3 months and 4 years. Comorbidities were included as modifiers of the 3-month models, and included in 4-year predictions. Poststroke medical and psychiatric comorbidities significantly increased short-term poststroke mortality and morbidity. Severe periventricular white matter disease (PVWMD) was significantly associated with poor functional outcome at 3 months, independent of other factors, such as diabetes and age; inclusion of this imaging variable eliminated other traditional risk factors often found in stroke outcomes models. Outcome at 3 months was a significant predictor of long-term mortality and functional outcome. Black race was a predictor of 4-year mortality. We propose that predictive models for stroke outcome, as well as analysis of clinical trials, should include adjustment for comorbid conditions. The effects of PVWMD on short-term functional outcomes and black race on long-term mortality are findings that require confirmation.

Boys with a simple delayed puberty reach their target height.

PubMed

Cools, B L M; Rooman, R; Op De Beeck, L; Du Caju, M V L

2008-01-01

Final height in boys with delayed puberty is thought to be below target height. This conclusion, however, is based on studies that included patients with genetic short stature. We therefore studied final height in a group of 33 untreated boys with delayed puberty with a target height >-1.5 SDS. Standing height, sitting height, weight and arm span width were measured in each patient. Final height was predicted by the method of Greulich and Pyle using the tables of Bailey and Pinneau for retarded boys at their bone age (PAH1) and the tables of Bailey and Pinneau for average boys plus six months (PAH2). Mean final height (175.8 +/- 6.5 cm) was appropriate for the mean target height (174.7 +/- 4.5 cm). The prediction method of Bailey and Pinneau overestimated the final height by 1.4 cm and the modified prediction method slightly underestimated the final height (-0.15 cm). Boys with untreated delayed puberty reach a final height appropriate for their target height. Final height was best predicted by the method of Bailey and Pinneau using the tables for average boys at their bone age plus six months. Copyright 2008 S. Karger AG, Basel.

A Risk Prediction Model for the Assessment and Triage of Women with Hypertensive Disorders of Pregnancy in Low-Resourced Settings: The miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) Multi-country Prospective Cohort Study

PubMed Central

Payne, Beth A.; Hutcheon, Jennifer A.; Ansermino, J. Mark; Hall, David R.; Bhutta, Zulfiqar A.; Bhutta, Shereen Z.; Biryabarema, Christine; Grobman, William A.; Groen, Henk; Li, Jing; Magee, Laura A.; Merialdi, Mario; Nakimuli, Annettee; Qu, Ziguang; Sikandar, Rozina; Sass, Nelson; Sawchuck, Diane; Steyn, D. Wilhelm; Widmer, Mariana; Zhou, Jian; von Dadelszen, Peter

2014-01-01

Background Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. Methods and Findings From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735–0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658–0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. Conclusions The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care. Please see later in the article for the Editors' Summary PMID:24465185

Functional outcomes of child and adolescent mental disorders. Current disorder most important but psychiatric history matters as well.

PubMed

Ormel, J; Oerlemans, A M; Raven, D; Laceulle, O M; Hartman, C A; Veenstra, R; Verhulst, F C; Vollebergh, W; Rosmalen, J G M; Reijneveld, S A; Oldehinkel, A J

2017-05-01

Various sources indicate that mental disorders are the leading contributor to the burden of disease among youth. An important determinant of functioning is current mental health status. This study investigated whether psychiatric history has additional predictive power when predicting individual differences in functional outcomes. We used data from the Dutch TRAILS study in which 1778 youths were followed from pre-adolescence into young adulthood (retention 80%). Of those, 1584 youths were successfully interviewed, at age 19, using the World Health Organization Composite International Diagnostic Interview (CIDI 3.0) to assess current and past CIDI-DSM-IV mental disorders. Four outcome domains were assessed at the same time: economic (e.g. academic achievement, social benefits, financial difficulties), social (early motherhood, interpersonal conflicts, antisocial behavior), psychological (e.g. suicidality, subjective well-being, loneliness), and health behavior (e.g. smoking, problematic alcohol, cannabis use). Out of the 19 outcomes, 14 were predicted by both current and past disorders, three only by past disorders (receiving social benefits, psychiatric hospitalization, adolescent motherhood), and two only by current disorder (absenteeism, obesity). Which type of disorders was most important depended on the outcome. Adjusted for current disorder, past internalizing disorders predicted in particular psychological outcomes while externalizing disorders predicted in particular health behavior outcomes. Economic and social outcomes were predicted by a history of co-morbidity of internalizing and externalizing disorder. The risk of problematic cannabis use and alcohol consumption dropped with a history of internalizing disorder. To understand current functioning, it is necessary to examine both current and past psychiatric status.

Patient and team communication in the iPad era - a practical appraisal.

PubMed

Imburgia, Mario

2014-01-01

Communication with the patient and within the team is a critical factor that can influence the treatment outcome, especially in complex and multidisciplinary dental treatments. Indeed, effective communication, not focused on marketing but on proper information of the patient's intraoral situation, can encourage greater acceptance of treatment and also greater treatment satisfaction. Better communication within the dental team is also a very important factor to improve the final result and reduce the time needed to reach it. Thanks to new technological devices widely available, such as tablets, we can use visual communication and interaction with the clinical images of the patient in order to improve communication with the patient, and especially within the dental team. The use of this method allows us to obtain a facial, dentolabial and dental esthetic analysis of the patient that can be used in various clinical steps, improving the predictability of the esthetic outcome and at the same time reducing the number of clinical sessions usually required.

Biomechanical assessment and clinical analysis of different intramedullary nailing systems for oblique fractures.

PubMed

Alierta, J A; Pérez, M A; Seral, B; García-Aznar, J M

2016-09-01

The aim of this study is to evaluate the fracture union or non-union for a specific patient that presented oblique fractures in tibia and fibula, using a mechanistic-based bone healing model. Normally, this kind of fractures can be treated through an intramedullary nail using two possible configurations that depends on the mechanical stabilisation: static and dynamic. Both cases are simulated under different fracture geometries in order to understand the effect of the mechanical stabilisation on the fracture healing outcome. The results of both simulations are in good agreement with previous clinical experience. From the results, it is demonstrated that the dynamization of the fracture improves healing in comparison with a static or rigid fixation of the fracture. This work shows the versatility and potential of a mechanistic-based bone healing model to predict the final outcome (union, non-union, delayed union) of realistic 3D fractures where even more than one bone is involved.

Breadth of Extracurricular Participation and Adolescent Adjustment Among African-American and European-American Youth

PubMed Central

Fredricks, Jennifer A.; Eccles, Jacquelynne S.

2012-01-01

We examined the linear and nonlinear relations between breadth of extracurricular participation in 11th grade and developmental outcomes at 11th grade and 1 year after high school in an economically diverse sample of African-American and European-American youth. In general, controlling for demographic factors, children's motivation, and the dependent variable measured 3 years earlier, breadth was positively associated with indicators of academic adjustment at 11th grade and at 1 year after high school. In addition, for the three academic outcomes (i.e., grades, educational expectations, and educational status) the nonlinear function was significant; at high levels of involvement the well-being of youth leveled off or declined slightly. In addition, breadth of participation at 11th grade predicted lower internalizing behavior, externalizing behavior, alcohol use, and marijuana use at 11th grade. Finally, the total number of extracurricular activities at 11th grade was associated with civic engagement 2 years later. PMID:22837637

Breadth of Extracurricular Participation and Adolescent Adjustment Among African-American and European-American Youth.

PubMed

Fredricks, Jennifer A; Eccles, Jacquelynne S

2010-06-01

We examined the linear and nonlinear relations between breadth of extracurricular participation in 11th grade and developmental outcomes at 11th grade and 1 year after high school in an economically diverse sample of African-American and European-American youth. In general, controlling for demographic factors, children's motivation, and the dependent variable measured 3 years earlier, breadth was positively associated with indicators of academic adjustment at 11th grade and at 1 year after high school. In addition, for the three academic outcomes (i.e., grades, educational expectations, and educational status) the nonlinear function was significant; at high levels of involvement the well-being of youth leveled off or declined slightly. In addition, breadth of participation at 11th grade predicted lower internalizing behavior, externalizing behavior, alcohol use, and marijuana use at 11th grade. Finally, the total number of extracurricular activities at 11th grade was associated with civic engagement 2 years later.

Merger of Two Neutron Stars: Predictions from the Two-families Scenario

NASA Astrophysics Data System (ADS)

Drago, Alessandro; Pagliara, Giuseppe

2018-01-01

If only one family of “neutron stars” exists, their maximum mass must be equal to or larger than 2{M}ȯ and then, only in less than about 18% of cases, the outcome of the merger of two neutron stars is a prompt collapse to a black hole, since the newly formed system can avoid the collapse at least until differential rotation is present. In the so-called two-families scenario, stars made of hadrons are stable only up to about (1.5{--}1.6){M}ȯ , while the most massive compact stars are entirely made of strange quark matter. We show that in this scenario the outcome of the merger of two compact stars, entirely composed by hadrons, is a prompt collapse in at least 34% of the cases. It will therefore be easy to discriminate between the two scenarios once the gravitational waves emitted at the moment of the merger are detected. Finally, we shortly discuss the implications of GW170817‑GRB 170817A.

Physiologically based pharmacokinetic model of amphotericin B disposition in rats following administration of deoxycholate formulation (Fungizone®): pooled analysis of published data.

PubMed

Kagan, Leonid; Gershkovich, Pavel; Wasan, Kishor M; Mager, Donald E

2011-06-01

The time course of tissue distribution of amphotericin B (AmB) has not been sufficiently characterized despite its therapeutic importance and an apparent disconnect between plasma pharmacokinetics and clinical outcomes. The goals of this work were to develop and evaluate a physiologically based pharmacokinetic (PBPK) model to characterize the disposition properties of AmB administered as deoxycholate formulation in healthy rats and to examine the utility of the PBPK model for interspecies scaling of AmB pharmacokinetics. AmB plasma and tissue concentration-time data, following single and multiple intravenous administration of Fungizone® to rats, from several publications were combined for construction of the model. Physiological parameters were fixed to literature values. Various structural models for single organs were evaluated, and the whole-body PBPK model included liver, spleen, kidney, lung, heart, gastrointestinal tract, plasma, and remainder compartments. The final model resulted in a good simultaneous description of both single and multiple dose data sets. Incorporation of three subcompartments for spleen and kidney tissues was required for capturing a prolonged half-life in these organs. The predictive performance of the final PBPK model was assessed by evaluating its utility in predicting pharmacokinetics of AmB in mice and humans. Clearance and permeability-surface area terms were scaled with body weight. The model demonstrated good predictions of plasma AmB concentration-time profiles for both species. This modeling framework represents an important basis that may be further utilized for characterization of formulation- and disease-related factors in AmB pharmacokinetics and pharmacodynamics.

Relationship between Mental Health and Burden among Primary Caregivers of Outpatients with Schizophrenia.

PubMed

Yu, Wenjun; Chen, Jia; Hu, Jize; Hu, JingChu

2018-01-24

There is growing recognition that caring for a patient with schizophrenia often results in high levels of perceived burden and poorer overall mental health for caregivers. A quantitative cross-sectional design and standardized instruments were used to collect data from 355 primary caregivers of adults in outpatient care with schizophrenia in China. Structural equation modeling was used to examine the association between caregiver burden and mental health among primary caregivers and whether this association is influenced by personality, coping style, and family functioning, based on a diathesis-stress perspective. Goodness-of-fit indices (χ 2 /df = 1.406, GFI = 0.919, CFI = 0.957, etc.) confirmed that the modified model fit the data well. In line with the diathesis-stress model, and with this study's hypotheses, we found that caregiver burden was significantly related to mental health outcomes directly. The final model showed that personality traits, coping style, and family function influenced the relationship between caregiver burden and mental health. The neuroticism personality traits have a direct effect on caregiver burden and family functioning in this sample. Coping style had a direct effect on the caregiver burden, and family functioning had a direct effect on the caregiver burden. Our final model about primary caregivers can be applied clinically to predict mental health outcomes from caregiver burden. © 2018 Family Process Institute.

Targeting aspirin in acute disabling ischemic stroke: an individual patient data meta-analysis of three large randomized trials.

PubMed

Thompson, Douglas D; Murray, Gordon D; Candelise, Livia; Chen, Zhengming; Sandercock, Peter A G; Whiteley, William N

2015-10-01

Aspirin is of moderate overall benefit for patients with acute disabling ischemic stroke. It is unclear whether functional outcome could be improved after stroke by targeting aspirin to patients with a high risk of recurrent thrombosis or a low risk of haemorrhage. We aimed to determine whether patients at higher risk of thrombotic events or poor functional outcome, or lower risk of major haemorrhage had a greater absolute risk reduction of poor functional outcome with aspirin than the average patient. We used data on individual ischemic stroke patients from three large trials of aspirin vs. placebo in acute ischemic stroke: the first International Stroke Trial (n = 18,372), the Chinese Acute Stroke Trial (n = 20,172) and the Multicentre Acute Stroke Trial (n = 622). We developed and evaluated clinical prediction models for the following: early thrombotic events (myocardial infarction, ischemic stroke, deep vein thrombosis and pulmonary embolism); early haemorrhagic events (significant intracranial haemorrhage, major extracranial haemorrhage, or haemorrhagic transformation of an infarct); and late poor functional outcome. We calculated the absolute risk reduction of poor functional outcome (death or dependence) at final follow-up in: quartiles of early thrombotic risk; quartiles of early haemorrhagic risk; and deciles of poor functional outcome risk. Ischemic stroke patients who were older, had lower blood pressure, computerized tomography evidence of infarct or more severe deficits due to stroke had increased risk of thrombotic and haemorrhagic events and poor functional outcome. Prediction models built with all baseline variables (including onset to treatment time) discriminated weakly between patients with and without recurrent thrombotic events (area under the receiver operating characteristic curve 0·56, 95% CI:0·53-0·59) and haemorrhagic events (0·57, 0·52-0·64), though well between patients with and without poor functional outcome (0·77, 0·76-0·78) in the International Stroke Trial. We found no evidence that the net benefit of aspirin increased with increasing risk of thrombosis, haemorrhage or poor functional outcome in all three trials. Using simple clinical variables to target aspirin to patients after acute disabling stroke by risk of thrombosis, haemorrhage or poor functional outcome does not lead to greater net clinical benefit. We suggest future risk stratification schemes include new risk factors for thrombosis and intracranial haemorrhage. © 2015 The Authors. International Journal of Stroke published by John Wiley & Sons Ltd on behalf of World Stroke Organization.

Ureteral wall thickness at the impacted ureteral stone site: a critical predictor for success rates after SWL.

PubMed

Sarica, Kemal; Kafkasli, Alper; Yazici, Özgür; Çetinel, Ali Cihangir; Demirkol, Mehmet Kutlu; Tuncer, Murat; Şahin, Cahit; Eryildirim, Bilal

2015-02-01

The aim of the study was to determine the possible predictive value of certain patient- and stone-related factors on the stone-free rates and auxiliary procedures after extracorporeal shock wave lithotripsy in patients with impacted proximal ureteral calculi. A total of 111 patients (86 male, 25 females M/F: 3.44/1) with impacted proximal ureteral stones treated with shock wave lithotripsy were evaluated. Cases were retrieved from a departmental shock wave lithotripsy database. Variables analyzed included BMI of the case, diameter of proximal ureter and renal pelvis, stone size and Hounsfield unit, ureteral wall thickness at the impacted stone site. Stone-free status on follow-up imaging at 3 months was considered a successful outcome. All patients had a single impacted proximal ureteral stone. While the mean age of the cases was 46 ± 13 years (range 26-79 years), mean stone size was 8.95 mm (5.3-15.1 mm). Following shock wave lithotripsy although 87 patients (78.4%) were completely stone-free at 3-month follow-up visit, 24 (21.6%) cases had residual fragments requiring further repeat procedures. Prediction of the final outcome of SWL in patients with impacted proximal ureteral stones is a challenging issue and our data did clearly indicate a highly significant relationship between ureteral wall thickness and the success rates of shock wave lithotripsy particularly in cases requiring additional procedures. Of all the evaluated stone- and patient-related factors, only ureteral wall thickness at the impacted stone site independently predicted shock wave lithotripsy success.

Multiscale Mechano-Biological Finite Element Modelling of Oncoplastic Breast Surgery—Numerical Study towards Surgical Planning and Cosmetic Outcome Prediction

PubMed Central

Eiben, Bjoern; Hipwell, John H.; Williams, Norman R.; Keshtgar, Mo; Hawkes, David J.

2016-01-01

Surgical treatment for early-stage breast carcinoma primarily necessitates breast conserving therapy (BCT), where the tumour is removed while preserving the breast shape. To date, there have been very few attempts to develop accurate and efficient computational tools that could be used in the clinical environment for pre-operative planning and oncoplastic breast surgery assessment. Moreover, from the breast cancer research perspective, there has been very little effort to model complex mechano-biological processes involved in wound healing. We address this by providing an integrated numerical framework that can simulate the therapeutic effects of BCT over the extended period of treatment and recovery. A validated, three-dimensional, multiscale finite element procedure that simulates breast tissue deformations and physiological wound healing is presented. In the proposed methodology, a partitioned, continuum-based mathematical model for tissue recovery and angiogenesis, and breast tissue deformation is considered. The effectiveness and accuracy of the proposed numerical scheme is illustrated through patient-specific representative examples. Wound repair and contraction numerical analyses of real MRI-derived breast geometries are investigated, and the final predictions of the breast shape are validated against post-operative follow-up optical surface scans from four patients. Mean (standard deviation) breast surface distance errors in millimetres of 3.1 (±3.1), 3.2 (±2.4), 2.8 (±2.7) and 4.1 (±3.3) were obtained, demonstrating the ability of the surgical simulation tool to predict, pre-operatively, the outcome of BCT to clinically useful accuracy. PMID:27466815

Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD

PubMed Central

Galatzer-Levy, I R; Ma, S; Statnikov, A; Yehuda, R; Shalev, A Y

2017-01-01

To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the complex interactions between biological and environmental factors that underlay post-traumatic psychopathology. Further, using symptom-based diagnostic status as the group outcome overlooks the inherent heterogeneity of PTSD, potentially contributing to failures to replicate. To examine the potential yield of novel analytic tools, we reanalyzed data from a large longitudinal study of individuals identified following trauma in the general emergency room (ER) that failed to find a linear association between cortisol response to traumatic events and subsequent PTSD. First, latent growth mixture modeling empirically identified trajectories of post-traumatic symptoms, which then were used as the study outcome. Next, support vector machines with feature selection identified sets of features with stable predictive accuracy and built robust classifiers of trajectory membership (area under the receiver operator characteristic curve (AUC)=0.82 (95% confidence interval (CI)=0.80–0.85)) that combined clinical, neuroendocrine, psychophysiological and demographic information. Finally, graph induction algorithms revealed a unique path from childhood trauma via lower cortisol during ER admission, to non-remitting PTSD. Traditional general linear modeling methods then confirmed the newly revealed association, thereby delineating a specific target population for early endocrine interventions. Advanced computational approaches offer innovative ways for uncovering clinically significant, non-shared biological signals in heterogeneous samples. PMID:28323285

Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD.

PubMed

Galatzer-Levy, I R; Ma, S; Statnikov, A; Yehuda, R; Shalev, A Y

2017-03-21

To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the complex interactions between biological and environmental factors that underlay post-traumatic psychopathology. Further, using symptom-based diagnostic status as the group outcome overlooks the inherent heterogeneity of PTSD, potentially contributing to failures to replicate. To examine the potential yield of novel analytic tools, we reanalyzed data from a large longitudinal study of individuals identified following trauma in the general emergency room (ER) that failed to find a linear association between cortisol response to traumatic events and subsequent PTSD. First, latent growth mixture modeling empirically identified trajectories of post-traumatic symptoms, which then were used as the study outcome. Next, support vector machines with feature selection identified sets of features with stable predictive accuracy and built robust classifiers of trajectory membership (area under the receiver operator characteristic curve (AUC)=0.82 (95% confidence interval (CI)=0.80-0.85)) that combined clinical, neuroendocrine, psychophysiological and demographic information. Finally, graph induction algorithms revealed a unique path from childhood trauma via lower cortisol during ER admission, to non-remitting PTSD. Traditional general linear modeling methods then confirmed the newly revealed association, thereby delineating a specific target population for early endocrine interventions. Advanced computational approaches offer innovative ways for uncovering clinically significant, non-shared biological signals in heterogeneous samples.

[Can Psychometric Tests Predict Success in the Selection Interview for Medical School? A Cross-Sectional Study at One German Medical School].

PubMed

Kötter, T; Obst, K U; Brüheim, L; Eisemann, N; Voltmer, E; Katalinic, A

2017-07-01

Background The final exam grade is the main selection criterion for medical school application in Germany. For academic success, it seems to be a reliable predictor. Its use as the only selection criterion is, however, criticised. At some universities, personal interviews are part of the selection process. However, these are very time consuming and are of doubtful validity. The (additional) use of appropriate psychometric instruments could reduce the cost and increase the validity. This study investigates the extent to which psychometric instruments can predict the outcome of a personal selection interview. Methods This is a cross-sectional study on the correlation of the results of psychometric instruments with those of the personal selection interview as part of the application process. As the outcome, the score of the selection interview was used. The NEO - Five Factor Inventory, the Hospital Anxiety and Depression Scale (HADS) and the questionnaire to identify work-related behaviour and experience patterns (AVEM) were used as psychometric interviews. Results There was a statistically significant correlation with the results of the personal selection interview for the sum score of the depression scale from the HADS and the sum score for the dimension of life satisfaction of the AVEM. In addition, those participants who did not previously complete an application training achieved a better result in the selection interview. Conclusion The instruments used measure different aspects than the interviews and cannot replace them. It remains to be seen whether the selected parameters are able to predict academic success. © Georg Thieme Verlag KG Stuttgart · New York.

Big data and computational biology strategy for personalized prognosis.

PubMed

Ow, Ghim Siong; Tang, Zhiqun; Kuznetsov, Vladimir A

2016-06-28

The era of big data and precision medicine has led to accumulation of massive datasets of gene expression data and clinical information of patients. For a new patient, we propose that identification of a highly similar reference patient from an existing patient database via similarity matching of both clinical and expression data could be useful for predicting the prognostic risk or therapeutic efficacy.Here, we propose a novel methodology to predict disease/treatment outcome via analysis of the similarity between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). Our analyses revealed that Euclidean distance rather correlation distance measure was effective in defining an unbiased similarity measure calculated between two PSVs.We implemented our methods to high-grade serous ovarian cancer (HGSC) based on a 36-mRNA predictor that was previously shown to stratify patients into 3 distinct prognostic subgroups. We studied and revealed that patient's age, when converted into binary variable, was positively correlated with the overall risk of succumbing to the disease. When applied to an independent testing dataset, the inclusion of age into the molecular predictor provided more robust personalized prognosis of overall survival correlated with the therapeutic response of HGSC and provided benefit for treatment targeting of the tumors in HGSC patients.Finally, our method can be generalized and implemented in many other diseases to accurately predict personalized patients' outcomes.

Motivated reasoning in the prediction of sports outcomes and the belief in the "hot hand".

PubMed

Braga, João P N; Mata, André; Ferreira, Mário B; Sherman, Steven J

2017-12-01

The present paper explores the role of motivation to observe a certain outcome in people's predictions, causal attributions, and beliefs about a streak of binary outcomes (basketball scoring shots). In two studies we found that positive streaks (points scored by the participants' favourite team) lead participants to predict the streak's continuation (belief in the hot hand), but negative streaks lead to predictions of its end (gambler's fallacy). More importantly, these wishful predictions are supported by strategic attributions and beliefs about how and why a streak might unfold. Results suggest that the effect of motivation on predictions is mediated by a serial path via causal attributions to the teams at play and belief in the hot hand.

Research Priorities for Gender Nonconforming/Transgender Youth: Gender Identity Development and Biopsychosocial Outcomes

PubMed Central

Olson-Kennedy, J; Cohen-Kettenis, P. T.; Kreukels, B.P.C; Meyer-Bahlburg, H.F.L; Garofalo, R; Meyer, W; Rosenthal, S.M.

2016-01-01

This review summarizes relevant research focused on prevalence and natural history of gender non-conforming / transgender youth, and outcomes of currently recommended clinical practice guidelines. This review identifies gaps in knowledge, and provides recommendations foci for future research. Recent findings Increasing numbers of gender nonconforming youth are presenting for care. Clinically useful information for predicting individual psychosexual development pathways is lacking. Transgender youth are at high risk for poor medical and psychosocial outcomes. Longitudinal data examining the impact of early social transition and medical interventions are sparse. Existing tools to understand gender identity and quantify gender dysphoria need to be reconfigured in order to study a more diverse cohort of transgender individuals. Increasingly, biomedical data are beginning to change the trajectory of scientific investigation. Summary Extensive research is needed to improve understanding of gender dysphoria, and transgender experience, particularly among youth. Recommendations include identification of predictors of persistence of gender dysphoria from childhood into adolescence, and a thorough investigation into the impact of interventions for transgender youth. Finally, examining the social environments of transgender youth is critical for the development of appropriate interventions necessary to improve the lives of transgender people. PMID:26825472

On the costs and benefits of emotional labor: a meta-analysis of three decades of research.

PubMed

Hülsheger, Ute R; Schewe, Anna F

2011-07-01

This article provides a quantitative review of the link of emotional labor (emotion-rule dissonance, surface acting, and deep acting) with well-being and performance outcomes. The meta-analysis is based on 494 individual correlations drawn from a final sample of 95 independent studies. Results revealed substantial relationships of emotion-rule dissonance and surface acting with indicators of impaired well-being (ρs between .39 and .48) and job attitudes (ρs between -.24 and -.40) and a small negative relationship with performance outcomes (ρs between -.20 and -.05). Overall, deep acting displayed weak relationships with indicators of impaired well-being and job attitudes but positive relationships with emotional performance and customer satisfaction (ρs .18 and .37). A meta-analytic regression analysis provides information on the unique contribution of emotion-rule dissonance, surface acting, and deep acting in statistically predicting well-being and performance outcomes. Furthermore, a mediation analysis confirms theoretical models of emotional labor which suggest that surface acting partially mediates the relationship of emotion-rule dissonance with well-being. Implications for future research as well as pragmatic ramifications for organizational practices are discussed in conclusion.

Predicting Recovery Potential for Individual Stroke Patients Increases Rehabilitation Efficiency.

PubMed

Stinear, Cathy M; Byblow, Winston D; Ackerley, Suzanne J; Barber, P Alan; Smith, Marie-Claire

2017-04-01

Several clinical measures and biomarkers are associated with motor recovery after stroke, but none are used to guide rehabilitation for individual patients. The objective of this study was to evaluate the implementation of upper limb predictions in stroke rehabilitation, by combining clinical measures and biomarkers using the Predict Recovery Potential (PREP) algorithm. Predictions were provided for patients in the implementation group (n=110) and withheld from the comparison group (n=82). Predictions guided rehabilitation therapy focus for patients in the implementation group. The effects of predictive information on clinical practice (length of stay, therapist confidence, therapy content, and dose) were evaluated. Clinical outcomes (upper limb function, impairment and use, independence, and quality of life) were measured 3 and 6 months poststroke. The primary clinical practice outcome was inpatient length of stay. The primary clinical outcome was Action Research Arm Test score 3 months poststroke. Length of stay was 1 week shorter for the implementation group (11 days; 95% confidence interval, 9-13 days) than the comparison group (17 days; 95% confidence interval, 14-21 days; P =0.001), controlling for upper limb impairment, age, sex, and comorbidities. Therapists were more confident ( P =0.004) and modified therapy content according to predictions for the implementation group ( P <0.05). The algorithm correctly predicted the primary clinical outcome for 80% of patients in both groups. There were no adverse effects of algorithm implementation on patient outcomes at 3 or 6 months poststroke. PREP algorithm predictions modify therapy content and increase rehabilitation efficiency after stroke without compromising clinical outcome. URL: http://anzctr.org.au. Unique identifier: ACTRN12611000755932. © 2017 American Heart Association, Inc.

Editorial Commentary: Role of Synovial Biomarkers in Patient Outcomes After Knee Arthroscopy.

PubMed

Brand, Jefferson C

2016-03-01

Humans are notably poor at predicting event outcomes. In "Correlation of Synovial Fluid Biomarkers With Cartilage Pathology and Associated Outcomes in Knee Arthroscopy," Cuellar, Cuellar, Kirsch, and Strauss show that some synovial fluid biomarkers (20 were sampled for the investigation) may predict operative findings at the time of arthroscopy and patient-reported outcome measures at follow-up. Further research will clarify the role of synovial biomarkers in knee pathology and, hopefully, narrow the choices to one or two pertinent markers that can be used to improve our ability to predict outcomes from arthroscopic knee surgery. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Ford Class Aircraft Carrier: Poor Outcomes Are the Predictable Consequences of the Prevalent Acquisition Culture

DTIC Science & Technology

2015-10-01

FORD CLASS AIRCRAFT CARRIER Poor Outcomes Are the Predictable Consequences of the Prevalent Acquisition Culture...2. REPORT TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Ford Class Aircraft Carrier: Poor Outcomes Are the Predictable...This Study The Navy set ambitious goals for the Ford -class program, including an array of new technologies and design features that were intended

Aortic stiffness predicts functional outcome in patients after ischemic stroke.

PubMed

Gasecki, Dariusz; Rojek, Agnieszka; Kwarciany, Mariusz; Kubach, Marlena; Boutouyrie, Pierre; Nyka, Walenty; Laurent, Stephane; Narkiewicz, Krzysztof

2012-02-01

Increased aortic stiffness (measured by carotid-femoral pulse wave velocity) and central augmentation index have been shown to independently predict cardiovascular events, including stroke. We studied whether pulse wave velocity and central augmentation index predict functional outcome after ischemic stroke. In a prospective study, we enrolled 99 patients with acute ischemic stroke (age 63.7 ± 12.4 years, admission National Institutes of Health Stroke Scale score 6.6 ± 6.6, mean ± SD). Carotid-femoral pulse wave velocity and central augmentation index (SphygmoCor) were measured 1 week after stroke onset. Functional outcome was evaluated 90 days after stroke using the modified Rankin Scale with modified Rankin Scale score of 0 to 1 considered an excellent outcome. In univariate analysis, low carotid-femoral pulse wave velocity (P=0.000001) and low central augmentation index (P=0.028) were significantly associated with excellent stroke outcome. Age, severity of stroke, presence of previous stroke, diabetes, heart rate, and peripheral pressures also predicted stroke functional outcome. In multivariate analysis, the predictive value of carotid-femoral pulse wave velocity (<9.4 m/s) remained significant (OR, 0.21; 95% CI, 0.06-0.79; P=0.02) after adjustment for age, National Institutes of Health Stroke Scale score on admission, and presence of previous stroke. By contrast, central augmentation index had no significant predictive value after adjustment. This study indicates that aortic stiffness is an independent predictor of functional outcome in patients with acute ischemic stroke.

Artificial neural network classifier predicts neuroblastoma patients' outcome.

PubMed

Cangelosi, Davide; Pelassa, Simone; Morini, Martina; Conte, Massimo; Bosco, Maria Carla; Eva, Alessandra; Sementa, Angela Rita; Varesio, Luigi

2016-11-08

More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Assessment of general movements and heart rate variability in prediction of neurodevelopmental outcome in preterm infants.

PubMed

Dimitrijević, Lidija; Bjelaković, Bojko; Čolović, Hristina; Mikov, Aleksandra; Živković, Vesna; Kocić, Mirjana; Lukić, Stevo

2016-08-01

Adverse neurologic outcome in preterm infants could be associated with abnormal heart rate (HR) characteristics as well as with abnormal general movements (GMs) in the 1st month of life. To demonstrate to what extent GMs assessment can predict neurological outcome in preterm infants in our clinical setting; and to assess the clinical usefulness of time-domain indices of heart rate variability (HRV) in improving predictive value of poor repertoire (PR) GMs in writhing period. Qualitative assessment of GMs at 1 and 3 months corrected age; 24h electrocardiography (ECG) recordings and analyzing HRV at 1 month corrected age. Seventy nine premature infants at risk of neurodevelopmental impairments were included prospectively. Neurodevelopmental outcome was assessed at the age of 2 years corrected. Children were classified as having normal neurodevelopmental status, minor neurologic dysfunction (MND), or cerebral palsy (CP). We found that GMs in writhing period (1 month corrected age) predicted CP at 2 years with sensitivity of 100%, and specificity of 72.1%. Our results demonstrated the excellent predictive value of cramped synchronized (CS) GMs, but not of PR pattern. Analyzing separately a group of infants with PR GMs we found significantly lower values of HRV parameters in infants who later developed CP or MND vs. infants with PR GMs who had normal outcome. The quality of GMs was predictive for neurodevelopmental outcome at 2 years. Prediction of PR GMs was significantly enhanced with analyzing HRV parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Early Adolescent Relationship Predictors of Emerging Adult Outcomes: Youth with and without Type 1 Diabetes

PubMed Central

Helgeson, Vicki S.; Palladino, Dianne K.; Reynolds, Kerry A.; Becker, Dorothy; Escobar, Oscar; Siminerio, Linda

2013-01-01

Background Emerging adulthood is a high-risk period for mental health problems and risk behaviors for youth generally and for physical health problems among those with type 1 diabetes. Purpose To examine whether adolescents’ relationships with parents and friends predict health and risk behaviors during emerging adulthood. Method Youth with and without diabetes were enrolled at average age 12 and followed for 7 years. Parent and friend relationship variables, measured during adolescence, were used to predict emerging adulthood outcomes: depression, risk behavior, and, for those with diabetes, diabetes outcomes. Results Parent relationship quality predicted decreased depressive symptoms and, for those with diabetes, decreased alcohol use. Parent control predicted increased smoking, reduced college attendance, and, for control participants, increased depressive symptoms. For those with diabetes, parent control predicted decreased depressive symptoms and better self-care. Friend relationship variables predicted few outcomes. Conclusions Adolescent parent relationships remain an important influence on emerging adults’ lives. PMID:24178509

"As soon as the bat met the ball, I knew it was gone": outcome prediction, hindsight bias, and the representation and control of action in expert and novice baseball players.

PubMed

Gray, Rob; Beilock, Sun L; Carr, Thomas H

2007-08-01

A virtual-reality batting task compared novice and expert baseball players' ability to predict the outcomes of their swings as well as the susceptibility of these outcome predictions to hindsight bias--a measure of strength and resistance to distortion of memory for predicted action outcomes. During each swing the simulation stopped when the bat met the ball. Batters marked where on the field they thought the ball would land. Correct feedback was then displayed, after which batters attempted to remark the location they had indicated prior to feedback. Expert batters were more accurate than less-skilled individuals in the initial marking and showed less hindsight bias in the postfeedback marking. Furthermore, experts' number of hits in the previous block of trials was positively correlated with prediction accuracy and negatively correlated with hindsight bias. The reverse was true for novices. Thus the ability to predict the outcome of one's performance before such information is available in the environment is not only based on one's overall skill level, but how one is performing at a given moment.

Questions regarding the predictive value of one evolved complex adaptive system for a second: exemplified by the SOD1 mouse.

PubMed

Greek, Ray; Hansen, Lawrence A

2013-11-01

We surveyed the scientific literature regarding amyotrophic lateral sclerosis, the SOD1 mouse model, complex adaptive systems, evolution, drug development, animal models, and philosophy of science in an attempt to analyze the SOD1 mouse model of amyotrophic lateral sclerosis in the context of evolved complex adaptive systems. Humans and animals are examples of evolved complex adaptive systems. It is difficult to predict the outcome from perturbations to such systems because of the characteristics of complex systems. Modeling even one complex adaptive system in order to predict outcomes from perturbations is difficult. Predicting outcomes to one evolved complex adaptive system based on outcomes from a second, especially when the perturbation occurs at higher levels of organization, is even more problematic. Using animal models to predict human outcomes to perturbations such as disease and drugs should have a very low predictive value. We present empirical evidence confirming this and suggest a theory to explain this phenomenon. We analyze the SOD1 mouse model of amyotrophic lateral sclerosis in order to illustrate this position. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Basolateral amygdala rapid glutamate release encodes an outcome-specific representation vital for reward-predictive cues to selectively invigorate reward-seeking actions

PubMed Central

Malvaez, Melissa; Greenfield, Venuz Y.; Wang, Alice S.; Yorita, Allison M.; Feng, Lili; Linker, Kay E.; Monbouquette, Harold G.; Wassum, Kate M.

2015-01-01

Environmental stimuli have the ability to generate specific representations of the rewards they predict and in so doing alter the selection and performance of reward-seeking actions. The basolateral amygdala participates in this process, but precisely how is unknown. To rectify this, we monitored, in near-real time, basolateral amygdala glutamate concentration changes during a test of the ability of reward-predictive cues to influence reward-seeking actions (Pavlovian-instrumental transfer). Glutamate concentration was found to be transiently elevated around instrumental reward seeking. During the Pavlovian-instrumental transfer test these glutamate transients were time-locked to and correlated with only those actions invigorated by outcome-specific motivational information provided by the reward-predictive stimulus (i.e., actions earning the same specific outcome as predicted by the presented CS). In addition, basolateral amygdala AMPA, but not NMDA glutamate receptor inactivation abolished the selective excitatory influence of reward-predictive cues over reward seeking. These data the hypothesis that transient glutamate release in the BLA can encode the outcome-specific motivational information provided by reward-predictive stimuli. PMID:26212790

Predictions of Cockpit Simulator Experimental Outcome Using System Models

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Goka, T.

1984-01-01

This study involved predicting the outcome of a cockpit simulator experiment where pilots used cockpit displays of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. The experiments were run on the NASA Ames Research Center multicab cockpit simulator facility. Prior to the experiments, a mathematical model of the pilot/aircraft/CDTI flight system was developed which included relative in-trail and vertical dynamics between aircraft in the approach string. This model was used to construct a digital simulation of the string dynamics including response to initial position errors. The model was then used to predict the outcome of the in-trail following cockpit simulator experiments. Outcome included performance and sensitivity to different separation criteria. The experimental results were then used to evaluate the model and its prediction accuracy. Lessons learned in this modeling and prediction study are noted.

Studies in Bilingual Evaluation, Work Unit I: Bilingual Prediction Project. Final Report.

ERIC Educational Resources Information Center

de Porcel, Antonio; And Others

The final report of the Bilingual Prediction Project presents a review of the project from its inception in 1975 through completion in 1979. The main goal was to predict a student's academic ability in English. A prediction index was constructed in two stages. The first stage was a description of the target population and their school setting, as…

Independent and combined influence of homeownership, occupation, education, income, and community poverty on physical health in persons with arthritis.

PubMed

Callahan, Leigh F; Martin, Kathryn Remmes; Shreffler, Jack; Kumar, Deepak; Schoster, Britta; Kaufman, Jay S; Schwartz, Todd A

2011-05-01

To examine the independent and combined influence of individual- and community-level socioeconomic status (SES) measures on physical health status outcomes in people with self-reported arthritis. From 2004-2005, 968 participants completed a telephone survey assessing health status, chronic conditions, community characteristics, and sociodemographic variables. Individual-level SES measures used included homeownership, occupation (professional or not), educational attainment (less than high school, high school degree, and more than high school), and income (<$15,000, $15,000-$45,000, and >$45,000). Community poverty (2000 US Census block group percentage of individuals living below the poverty line [low, medium, and high]) was used as a community-level SES measure. Outcomes were physical functioning (Medical Outcomes Study Short Form 12 version 2 physical component summary [PCS]), functional disability (Health Assessment Questionnaire [HAQ]), and the Centers for Disease Control and Prevention (CDC) Health-Related Quality of Life (HRQOL) Healthy Days physical and limited activity days, and were analyzed via multivariable regressions. When entered separately, all individual-level SES variables were significantly (P < 0.01) associated with poorer PCS, HAQ, and CDC HRQOL scores. A higher magnitude of effect was seen for household income, specifically <$15,000 per year in final models with all 4 individual SES measures and community poverty. The magnitude of effect for education is reduced and marginally significant for the PCS and number of physically unhealthy days. No effects were seen for occupation, homeownership, and community poverty. Findings confirm that after adjusting for important covariates, lower individual- and community-level SES measures are associated with poorer physical health outcomes, while household income is the strongest predictor (as measured by both significance and effect) of poorer health status in final models. Studies not having participant-reported income available should make use of other SES measures, as they do independently predict physical health. Copyright © 2011 by the American College of Rheumatology.

Final anatomic and visual outcomes appear independent of duration of silicone oil intraocular tamponade in complex retinal detachment surgery.

PubMed

Rhatigan, Maedbh; McElnea, Elizabeth; Murtagh, Patrick; Stephenson, Kirk; Harris, Elaine; Connell, Paul; Keegan, David

2018-01-01

To report anatomic and visual outcomes following silicone oil removal in a cohort of patients with complex retinal detachment, to determine association between duration of tamponade and outcomes and to compare patients with oil removed and those with oil in situ in terms of demographic, surgical and visual factors. We reported a four years retrospective case series of 143 patients with complex retinal detachments who underwent intraocular silicone oil tamponade. Analysis between anatomic and visual outcomes, baseline demographics, duration of tamponade and number of surgical procedures were carried out using Fisher's exact test and unpaired two-tailed t -test. One hundred and six patients (76.2%) had undergone silicone oil removal at the time of review with 96 patients (90.6%) showing retinal reattachment following oil removal. Duration of tamponade was not associated with final reattachment rate or with a deterioration in best corrected visual acuity (BCVA). Patients with oil removed had a significantly better baseline and final BCVA compared to those under oil tamponade ( P =0.0001, <0.0001 respectively). Anatomic and visual outcomes in this cohort are in keeping with those reported in the literature. Favorable outcomes were seen with oil removal but duration of oil tamponade does not affect final attachment rate with modern surgical techniques and should be managed on a case by case basis.

Neurocognition and community outcome in schizophrenia: long-term predictive validity.

PubMed

Fujii, Daryl E; Wylie, A Michael

2003-02-01

The present study examined the predictive validity of neuropsychological measures to functional outcome in 26 schizophrenic patients 15-plus year post-testing. Outcome measures included score on the Resource Associated Functional Level Scale (RAFLS), number of state hospital admissions, and total duration of state hospital inpatient stay. Results of several stepwise multiple regressions revealed that verbal memory significantly predicted RAFLS score, accounting for nearly half of the variance. Trails B significantly predicted duration of state hospital inpatient status. Discussion focused on the utility of these measures for clinicians and system planners. Copyright 2002 Elsevier Science B.V.

Predictive performance of four frailty measures in an older Australian population

PubMed Central

Widagdo, Imaina S.; Pratt, Nicole; Russell, Mary; Roughead, Elizabeth E.

2015-01-01

Background: there are several different frailty measures available for identifying the frail elderly. However, their predictive performance in an Australian population has not been examined. Objective: to examine the predictive performance of four internationally validated frailty measures in an older Australian population. Methods: a retrospective study in the Australian Longitudinal Study of Ageing (ALSA) with 2,087 participants. Frailty was measured at baseline using frailty phenotype (FP), simplified frailty phenotype (SFP), frailty index (FI) and prognostic frailty score (PFS). Odds ratios (OR) were calculated to measure the association between frailty and outcomes at Wave 3 including mortality, hospitalisation, nursing home admission, fall and a combination of all outcomes. Predictive performance was measured by assessing sensitivity, specificity, positive and negative predictive values (PPV and NPV) and likelihood ratio (LR). Area under the curve (AUC) of dichotomised and the multilevel or continuous model of the measures was examined. Results: prevalence of frailty varied from 2% up to 49% between the measures. Frailty was significantly associated with an increased risk of any outcome, OR (95% confidence interval) for FP: 1.9 (1.4–2.8), SFP: 3.6 (1.5–8.8), FI: 3.4 (2.7–4.3) and PFS: 2.3 (1.8–2.8). PFS had high sensitivity across all outcomes (sensitivity: 55.2–77.1%). The PPV for any outcome was highest for SFP and FI (70.8 and 69.7%, respectively). Only FI had acceptable accuracy in predicting outcomes, AUC: 0.59–0.70. Conclusions: being identified as frail by any of the four measures was associated with an increased risk of outcomes; however, their predictive accuracy varied. PMID:26504118

Poor outcome prediction by burst suppression ratio in adults with post-anoxic coma without hypothermia.

PubMed

Yang, Qinglin; Su, Yingying; Hussain, Mohammed; Chen, Weibi; Ye, Hong; Gao, Daiquan; Tian, Fei

2014-05-01

Burst suppression ratio (BSR) is a quantitative electroencephalography (qEEG) parameter. The purpose of our study was to compare the accuracy of BSR when compared to other EEG parameters in predicting poor outcomes in adults who sustained post-anoxic coma while not being subjected to therapeutic hypothermia. EEG was registered and recorded at least once within 7 days of post-anoxic coma onset. Electrodes were placed according to the international 10-20 system, using a 16-channel layout. Each EEG expert scored raw EEG using a grading scale adapted from Young and scored amplitude-integrated electroencephalography tracings, in addition to obtaining qEEG parameters defined as BSR with a defined threshold. Glasgow outcome scales of 1 and 2 at 3 months, determined by two blinded neurologists, were defined as poor outcome. Sixty patients with Glasgow coma scale score of 8 or less after anoxic accident were included. The sensitivity (97.1%), specificity (73.3%), positive predictive value (82.5%), and negative prediction value (95.0%) of BSR in predicting poor outcome were higher than other EEG variables. BSR1 and BSR2 were reliable in predicting death (area under the curve > 0.8, P < 0.05), with the respective cutoff points being 39.8% and 61.6%. BSR1 was reliable in predicting poor outcome (area under the curve  =  0.820, P < 0.05) with a cutoff point of 23.9%. BSR1 was also an independent predictor of increased risk of death (odds ratio  =  1.042, 95% confidence intervals: 1.012-1.073, P  =  0.006). BSR may be a better predictor in prognosticating poor outcomes in patients with post-anoxic coma who do not undergo therapeutic hypothermia when compared to other qEEG parameters.