WorldWideScience

Sample records for strongly predicted outcome

  1. Combination of 24-Hour and 7-Day Relative Neurological Improvement Strongly Predicts 90-Day Functional Outcome of Endovascular Stroke Therapy.

    Science.gov (United States)

    Pu, Jie; Wang, Huaiming; Tu, Mingyi; Zi, Wenjie; Hao, Yonggang; Yang, Dong; Liu, Wenhua; Wan, Yue; Geng, Yu; Lin, Min; Jin, Ping; Xiong, Yunyun; Xu, Gelin; Yin, Qin; Liu, Xinfeng

    2018-01-03

    Early judgment of long-term prognosis is the key to making medical decisions in acute anterior circulation large-vessel occlusion stroke (LVOS) after endovascular treatment (EVT). We aimed to investigate the relationship between the combination of 24-hour and 7-day relative neurological improvement (RNI) and 90-day functional outcome. We selected the target population from a multicenter ischemic stroke registry. The National Institutes of Health Stroke Scale (NIHSS) scores at baseline, 24 hours, and 7 days were collected. RNI was calculated by the following equation: (baseline NIHSS - 24-hour/7-day NIHSS)/baseline NIHSS × 100%. A modified Rankin Scale score of 0-2 at 90 days was defined as a favorable outcome. Multivariable logistic regression analysis was used to evaluate the relationship between RNI and 90-day outcome. Receiver operator characteristic curve analysis was performed to identify the predictive power and cutoff point of RNI for functional outcome. A total of 568 patients were enrolled. Both 24-hour and 7-day RNI were independent predictors of 90-day outcome. The best cutoff points of 24-hour and 7-day RNI were 28% and 42%, respectively. Compared with those with 24-hour RNI of less than 28% and 7-day RNI of less than 42%, patients with 24-hour RNI of 28% or greater and 7-day RNI of 42% or greater had a 39.595-fold (95% confidence interval 22.388-70.026) increased probability of achieving 90-day favorable outcome. The combination of 24-hour and 7-day RNI very strongly predicts 90-day functional outcome in patients with acute anterior circulation LVOS who received EVT, and it can be used as an early accurate surrogate of long-term outcome. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  2. Right Heart End-Systolic Remodeling Index Strongly Predicts Outcomes in Pulmonary Arterial Hypertension: Comparison With Validated Models.

    Science.gov (United States)

    Amsallem, Myriam; Sweatt, Andrew J; Aymami, Marie C; Kuznetsova, Tatiana; Selej, Mona; Lu, HongQuan; Mercier, Olaf; Fadel, Elie; Schnittger, Ingela; McConnell, Michael V; Rabinovitch, Marlene; Zamanian, Roham T; Haddad, Francois

    2017-06-01

    Right ventricular (RV) end-systolic dimensions provide information on both size and function. We investigated whether an internally scaled index of end-systolic dimension is incremental to well-validated prognostic scores in pulmonary arterial hypertension. From 2005 to 2014, 228 patients with pulmonary arterial hypertension were prospectively enrolled. RV end-systolic remodeling index (RVESRI) was defined by lateral length divided by septal height. The incremental values of RV free wall longitudinal strain and RVESRI to risk scores were determined. Mean age was 49±14 years, 78% were female, 33% had connective tissue disease, 52% were in New York Heart Association class ≥III, and mean pulmonary vascular resistance was 11.2±6.4 WU. RVESRI and right atrial area were strongly connected to the other right heart metrics. Three zones of adaptation (adapted, maladapted, and severely maladapted) were identified based on the RVESRI to RV systolic pressure relationship. During a mean follow-up of 3.9±2.4 years, the primary end point of death, transplant, or admission for heart failure was reached in 88 patients. RVESRI was incremental to risk prediction scores in pulmonary arterial hypertension, including the Registry to Evaluate Early and Long-Term PAH Disease Management score, the Pulmonary Hypertension Connection equation, and the Mayo Clinic model. Using multivariable analysis, New York Heart Association class III/IV, RVESRI, and log NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) were retained (χ 2 , 62.2; P right heart metrics, RVESRI demonstrated the best test-retest characteristics. RVESRI is a simple reproducible prognostic marker in patients with pulmonary arterial hypertension. © 2017 American Heart Association, Inc.

  3. Midregional-proAtrial Natriuretic Peptide and High Sensitive Troponin T Strongly Predict Adverse Outcome in Patients Undergoing Percutaneous Repair of Mitral Valve Regurgitation.

    Directory of Open Access Journals (Sweden)

    Jochen Wöhrle

    Full Text Available It is not known whether biomarkers of hemodynamic stress, myocardial necrosis, and renal function might predict adverse outcome in patients undergoing percutaneous repair of severe mitral valve insufficiency. Thus, we aimed to assess the predictive value of various established and emerging biomarkers for major adverse cardiovascular events (MACE in these patients.Thirty-four patients with symptomatic severe mitral valve insufficiency with a mean STS-Score for mortality of 12.6% and a mean logistic EuroSCORE of 19.7% undergoing MitraClip therapy were prospectively included in this study. Plasma concentrations of mid regional-proatrial natriuretic peptide (MR-proANP, Cystatin C, high-sensitive C-reactive protein (hsCRP, high-sensitive troponin T (hsTnT, N-terminal B-type natriuretic peptide (NT-proBNP, galectin-3, and soluble ST-2 (interleukin 1 receptor-like 1 were measured directly before procedure. MACE was defined as cardiovascular death and hospitalization for heart failure (HF.During a median follow-up of 211 days (interquartile range 133 to 333 days, 9 patients (26.5% experienced MACE (death: 7 patients, rehospitalization for HF: 2 patients. Thirty day MACE-rate was 5.9% (death: 2 patients, no rehospitalization for HF. Baseline concentrations of hsTnT (Median 92.6 vs 25.2 ng/L, NT-proBNP (Median 11251 vs 1974 pg/mL and MR-proANP (Median 755.6 vs 318.3 pmol/L, all p<0.001 were clearly higher in those experiencing an event vs event-free patients, while other clinical variables including STS-Score and logistic EuroSCORE did not differ significantly. In Kaplan-Meier analyses, NT-proBNP and in particular hsTnT and MR-proANP above the median discriminated between those experiencing an event vs event-free patients. This was further corroborated by C-statistics where areas under the ROC curve for prediction of MACE using the respective median values were 0.960 for MR-proANP, 0.907 for NT-proBNP, and 0.822 for hsTnT.MR-proANP and hsTnT strongly

  4. Strong ground motion prediction using virtual earthquakes.

    Science.gov (United States)

    Denolle, M A; Dunham, E M; Prieto, G A; Beroza, G C

    2014-01-24

    Sedimentary basins increase the damaging effects of earthquakes by trapping and amplifying seismic waves. Simulations of seismic wave propagation in sedimentary basins capture this effect; however, there exists no method to validate these results for earthquakes that have not yet occurred. We present a new approach for ground motion prediction that uses the ambient seismic field. We apply our method to a suite of magnitude 7 scenario earthquakes on the southern San Andreas fault and compare our ground motion predictions with simulations. Both methods find strong amplification and coupling of source and structure effects, but they predict substantially different shaking patterns across the Los Angeles Basin. The virtual earthquake approach provides a new approach for predicting long-period strong ground motion.

  5. Strong earthquakes can be predicted: a multidisciplinary method for strong earthquake prediction

    Directory of Open Access Journals (Sweden)

    J. Z. Li

    2003-01-01

    Full Text Available The imminent prediction on a group of strong earthquakes that occurred in Xinjiang, China in April 1997 is introduced in detail. The prediction was made on the basis of comprehensive analyses on the results obtained by multiple innovative methods including measurements of crustal stress, observation of infrasonic wave in an ultra low frequency range, and recording of abnormal behavior of certain animals. Other successful examples of prediction are also enumerated. The statistics shows that above 40% of 20 total predictions jointly presented by J. Z. Li, Z. Q. Ren and others since 1995 can be regarded as effective. With the above methods, precursors of almost every strong earthquake around the world that occurred in recent years were recorded in our laboratory. However, the physical mechanisms of the observed precursors are yet impossible to explain at this stage.

  6. Is It Possible to Predict Strong Earthquakes?

    Science.gov (United States)

    Polyakov, Y. S.; Ryabinin, G. V.; Solovyeva, A. B.; Timashev, S. F.

    2015-07-01

    The possibility of earthquake prediction is one of the key open questions in modern geophysics. We propose an approach based on the analysis of common short-term candidate precursors (2 weeks to 3 months prior to strong earthquake) with the subsequent processing of brain activity signals generated in specific types of rats (kept in laboratory settings) who reportedly sense an impending earthquake a few days prior to the event. We illustrate the identification of short-term precursors using the groundwater sodium-ion concentration data in the time frame from 2010 to 2014 (a major earthquake occurred on 28 February 2013) recorded at two different sites in the southeastern part of the Kamchatka Peninsula, Russia. The candidate precursors are observed as synchronized peaks in the nonstationarity factors, introduced within the flicker-noise spectroscopy framework for signal processing, for the high-frequency component of both time series. These peaks correspond to the local reorganizations of the underlying geophysical system that are believed to precede strong earthquakes. The rodent brain activity signals are selected as potential "immediate" (up to 2 weeks) deterministic precursors because of the recent scientific reports confirming that rodents sense imminent earthquakes and the population-genetic model of K irshvink (Soc Am 90, 312-323, 2000) showing how a reliable genetic seismic escape response system may have developed over the period of several hundred million years in certain animals. The use of brain activity signals, such as electroencephalograms, in contrast to conventional abnormal animal behavior observations, enables one to apply the standard "input-sensor-response" approach to determine what input signals trigger specific seismic escape brain activity responses.

  7. Mechanical Ventilation-induced Diaphragm Atrophy Strongly Impacts Clinical Outcomes.

    Science.gov (United States)

    Goligher, Ewan C; Dres, Martin; Fan, Eddy; Rubenfeld, Gordon D; Scales, Damon C; Herridge, Margaret S; Vorona, Stefannie; Sklar, Michael C; Rittayamai, Nuttapol; Lanys, Ashley; Murray, Alistair; Brace, Deborah; Urrea, Cristian; Reid, W Darlene; Tomlinson, George; Slutsky, Arthur S; Kavanagh, Brian P; Brochard, Laurent J; Ferguson, Niall D

    2018-01-15

    Diaphragm dysfunction worsens outcomes in mechanically ventilated patients, but the clinical impact of potentially preventable changes in diaphragm structure and function caused by mechanical ventilation is unknown. To determine whether diaphragm atrophy developing during mechanical ventilation leads to prolonged ventilation. Diaphragm thickness was measured daily by ultrasound in adults requiring invasive mechanical ventilation; inspiratory effort was assessed by thickening fraction. The primary outcome was time to liberation from ventilation. Secondary outcomes included complications (reintubation, tracheostomy, prolonged ventilation, or death). Associations were adjusted for age, severity of illness, sepsis, sedation, neuromuscular blockade, and comorbidity. Of 211 patients enrolled, 191 had two or more diaphragm thickness measurements. Thickness decreased more than 10% in 78 patients (41%) by median Day 4 (interquartile range, 3-5). Development of decreased thickness was associated with a lower daily probability of liberation from ventilation (adjusted hazard ratio, 0.69; 95% confidence interval [CI], 0.54-0.87; per 10% decrease), prolonged ICU admission (adjusted duration ratio, 1.71; 95% CI, 1.29-2.27), and a higher risk of complications (adjusted odds ratio, 3.00; 95% CI, 1.34-6.72). Development of increased thickness (n = 47; 24%) also predicted prolonged ventilation (adjusted duration ratio, 1.38; 95% CI, 1.00-1.90). Decreasing thickness was related to abnormally low inspiratory effort; increasing thickness was related to excessive effort. Patients with thickening fraction between 15% and 30% (similar to breathing at rest) during the first 3 days had the shortest duration of ventilation. Diaphragm atrophy developing during mechanical ventilation strongly impacts clinical outcomes. Targeting an inspiratory effort level similar to that of healthy subjects at rest might accelerate liberation from ventilation.

  8. Predicting outcome after appendicectomy.

    LENUS (Irish Health Repository)

    Kell, M R

    2012-02-03

    AIM: To validate an intraoperative appendicitis severity score (IASS) and examine outcome following emergency appendectomy. METHODS: A prospective study was undertaken, enrolling consecutive patients undergoing emergency appendicectomy. Data were obtained independently on preoperative Alvarado scores, IASS (0-3: 0 no inflammation, 1 engorged appendix\\/no peritonitis, 2 peritoneal reaction\\/exudate or 3 evidence of perforation\\/abscess) and postoperative outcome parameters. RESULTS: There were 149 patients identified with a mean age of 20.7 years. There was no association between Alvarado score and length of hospital stay, septic complication, patient sex or duration of symptoms (p>0.05). IASS was found to be an independent risk factor for septic complication, wound infection (p<0.05) and length of hospital stay (p<0.001). There was no correlation between preoperative duration of symptoms or time until surgery and intraoperative score. CONCLUSIONS: This simple scoring system can identify patients more likely to suffer morbidity following emergency appendicectomy. Specifically, this system identifies patients who have a high risk of sepsis and therefore could be of use when comparing healthcare performance.

  9. Predicting outcome of status epilepticus.

    Science.gov (United States)

    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

  10. Prediction of the occurrence of related strong earthquakes in Italy

    International Nuclear Information System (INIS)

    Vorobieva, I.A.; Panza, G.F.

    1993-06-01

    In the seismic flow it is often observed that a Strong Earthquake (SE), is followed by Related Strong Earthquakes (RSEs), which occur near the epicentre of the SE with origin time rather close to the origin time of the SE. The algorithm for the prediction of the occurrence of a RSE has been developed and applied for the first time to the seismicity data of the California-Nevada region and has been successfully tested in several regions of the World, the statistical significance of the result being 97%. So far, it has been possible to make five successful forward predictions, with no false alarms or failures to predict. The algorithm is applied here to the Italian territory, where the occurrence of RSEs is a particularly rare phenomenon. Our results show that the standard algorithm is successfully directly applicable without any adjustment of the parameters. Eleven SEs are considered. Of them, three are followed by a RSE, as predicted by the algorithm, eight SEs are not followed by a RSE, and the algorithm predicts this behaviour for seven of them, giving rise to only one false alarm. Since, in Italy, quite often the series of strong earthquakes are relatively short, the algorithm has been extended to handle such situation. The result of this experiment indicates that it is possible to attempt to test a SE, for the occurrence of a RSE, soon after the occurrence of the SE itself, performing timely ''preliminary'' recognition on reduced data sets. This fact, the high confidence level of the retrospective analysis, and the first successful forward predictions, made in different parts of the World, indicates that, even if additional tests are desirable, the algorithm can already be considered for routine application to Civil Defence. (author). Refs, 3 figs, 7 tabs

  11. What Factors Predict Who Will Have a Strong Social Network Following a Stroke?

    Science.gov (United States)

    Northcott, Sarah; Marshall, Jane; Hilari, Katerina

    2016-01-01

    Purpose: Measures of social networks assess the number and nature of a person's social contacts, and strongly predict health outcomes. We explored how social networks change following a stroke and analyzed concurrent and baseline predictors of social networks 6 months poststroke. Method: We conducted a prospective longitudinal observational study.…

  12. Associations Between Participant Ratings of PREP for Strong Bonds and Marital Outcomes 1 Year Postintervention.

    Science.gov (United States)

    Allen, Elizabeth S; Post, Kristina M; Markman, Howard J; Rhoades, Galena K; Stanley, Scott M

    2017-07-01

    After completing a relationship education program, collecting participant evaluations of the program is common practice. These are generally used as an index of "consumer satisfaction" with the program, with implications for feasibility and quality. Rarely have these ratings been used as predictors of changes in marital quality, although such feedback may be the only data providers collect or have immediate access to when considering the success of their efforts. To better understand the utility of such ratings to predict outcomes, we evaluated links between participant ratings and changes in self-reported marital satisfaction and communication scores one year later for a sample of 191 Army couples who had participated in a relationship education program delivered by Army chaplains (PREP for Strong Bonds). Overall ratings of general satisfaction with the program and the leader did not predict changes in marital outcomes one year later, whereas higher ratings of how much was learned, program helpfulness, increased similarity in outlook regarding Army life, and helpfulness of communication skills training predicted greater change in communication skills one year later. Higher ratings of items reflecting intent to invest more time in the relationship, and increased confidence in constructive communication and working as a team with the spouse predicted greater increases in both marital satisfaction and communication skills one year later. The constructs of intention and confidence (akin to perceived behavioral control) suggest that the Theory of Planned Behavior may be particularly useful when considering which Army couples will show ongoing benefit after relationship education.

  13. Predicting the outcome of ankylosing spondylitis therapy

    Science.gov (United States)

    Vastesaeger, Nathan; van der Heijde, Désirée; Inman, Robert D; Wang, Yanxin; Deodhar, Atul; Hsu, Benjamin; Rahman, Mahboob U; Dijkmans, Ben; Geusens, Piet; Vander Cruyssen, Bert; Collantes, Eduardo; Sieper, Joachim; Braun, Jürgen

    2011-01-01

    Objectives To create a model that provides a potential basis for candidate selection for anti-tumour necrosis factor (TNF) treatment by predicting future outcomes relative to the current disease profile of individual patients with ankylosing spondylitis (AS). Methods ASSERT and GO–RAISE trial data (n=635) were analysed to identify baseline predictors for various disease-state and disease-activity outcome instruments in AS. Univariate, multivariate, receiver operator characteristic and correlation analyses were performed to select final predictors. Their associations with outcomes were explored. Matrix and algorithm-based prediction models were created using logistic and linear regression, and their accuracies were compared. Numbers needed to treat were calculated to compare the effect size of anti-TNF therapy between the AS matrix subpopulations. Data from registry populations were applied to study how a daily practice AS population is distributed over the prediction model. Results Age, Bath ankylosing spondylitis functional index (BASFI) score, enthesitis, therapy, C-reactive protein (CRP) and HLA-B27 genotype were identified as predictors. Their associations with each outcome instrument varied. However, the combination of these factors enabled adequate prediction of each outcome studied. The matrix model predicted outcomes as well as algorithm-based models and enabled direct comparison of the effect size of anti-TNF treatment outcome in various subpopulations. The trial populations reflected the daily practice AS population. Conclusion Age, BASFI, enthesitis, therapy, CRP and HLA-B27 were associated with outcomes in AS. Their combined use enables adequate prediction of outcome resulting from anti-TNF and conventional therapy in various AS subpopulations. This may help guide clinicians in making treatment decisions in daily practice. PMID:21402563

  14. Emotion suppression, not reappraisal, predicts psychotherapy outcome.

    Science.gov (United States)

    Scherer, Anne; Boecker, Maren; Pawelzik, Markus; Gauggel, Siegfried; Forkmann, Thomas

    2017-03-01

    The aim of this study was to identify whether trait emotion regulation strategies predict successful or unsuccessful psychotherapy outcomes in cognitive behaviour therapy. Three emotion regulation strategies (reappraisal, suppression, and externalizing behaviour) were assessed in 358 in- and outpatients. Patients were then grouped by therapy outcome. Emotion regulation strategies and confounding variables were entered as predictors in multinomial logistic regression analyses. Emotion suppression, but not reappraisal, was found to predict therapy outcomes for in- and outpatients, with patients high in suppression experiencing worse outcomes. Externalizing behaviour was only relevant in inpatient treatment. High suppression might be detrimental to psychotherapy outcome and should be assessed early on. Further research should investigate the influence of suppression on the mechanisms that facilitate change in psychotherapy.

  15. Promoting Strong ISO 50001 Outcomes with Supportive National Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee, T.; Siciliano, Graziella; de los Reyes, Pamela

    2015-08-04

    The ISO 50001 standard is a key mechanism for reducing greenhouse gas emissions and improving energy efficiency globally. An increasing number of companies are seeking certification, creating the need for personnel that are competent to conduct ISO 50001 certification audits. The growth of ISO 50001 is expected to accelerate as more companies integrate ISO 50001 into their corporate sustainability strategies and supplier requirements. Robust implementation of ISO 50001 represents an important tool for countries with climate change mitigation goals. Because of its dual focus on continual improvement of an organization’s energy management system (EnMS) and its energy performance improvement, ISO 50001 requires skills of both implementers and certification auditors that are not well-supported by current credentials and training. This paper describes an effort to address skill gaps of certification auditors, a critical factor to ensure that ISO 50001 implementations are robust and result in continued energy performance improvement. A collaboration of governments through the Energy Management Working Group (EMWG), formerly under Global Superior Energy Performance (GSEP), has formed to build workforce capacity for ISO 50001 certification audits. The EMWG is leading the development of an internationally-relevant certification scheme for ISO 50001 Lead Auditor that meets requirements for ISO/IEC 17024 accreditation and ISO 50003 for defining ISO 50001 Lead Auditor competency. Wider availability of competent ISO 50001 Lead Auditors will ultimately increase the impact and market value of ISO 50001 certification and improve consistency of ISO 50001 certification outcomes by establishing a standardized and high level of knowledge and skills globally.

  16. Macaques can predict social outcomes from facial expressions.

    Science.gov (United States)

    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.

  17. Early Adolescent Affect Predicts Later Life Outcomes.

    Science.gov (United States)

    Kansky, Jessica; Allen, Joseph P; Diener, Ed

    2016-07-01

    Subjective well-being as a predictor for later behavior and health has highlighted its relationship to health, work performance, and social relationships. However, the majority of such studies neglect the developmental nature of well-being in contributing to important changes across the transition to adulthood. To examine the potential role of subjective well-being as a long-term predictor of critical life outcomes, we examined indicators of positive and negative affect at age 14 as predictors of relationship, adjustment, self-worth, and career outcomes a decade later at ages 23 to 25, controlling for family income and gender. We utilised multi-informant methods including reports from the target participant, close friends, and romantic partners in a demographically diverse community sample of 184 participants. Early adolescent positive affect predicted fewer relationship problems (less self-reported and partner-reported conflict, and greater friendship attachment as rated by close peers) and healthy adjustment to adulthood (lower levels of depression, anxiety, and loneliness). It also predicted positive work functioning (higher levels of career satisfaction and job competence) and increased self-worth. Negative affect did not significantly predict any of these important life outcomes. In addition to predicting desirable mean levels of later outcomes, early positive affect predicted beneficial changes across time in many outcomes. The findings extend early research on the beneficial outcomes of subjective well-being by having an earlier assessment of well-being, including informant reports in measuring a large variety of outcome variables, and by extending the findings to a lower socioeconomic group of a diverse and younger sample. The results highlight the importance of considering positive affect as an important component of subjective well-being distinct from negative affect. © 2016 The International Association of Applied Psychology.

  18. Outcome manipulation in corporate prediction markets

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2007-01-01

    This paper presents a framework for applying prediction markets to corporate decision-making. The analysis is motivated by the recent surge of interest in markets as information aggregation devices and their potential use within firms. We characterize the amount of outcome manipulation that results...... in equilibrium and the impact of this manipulation on market prices...

  19. Predicting Clinical Outcomes Using Molecular Biomarkers

    Directory of Open Access Journals (Sweden)

    Harry B. Burke

    2016-01-01

    Full Text Available Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician–patient interaction, they will be an integral part of physician–patient-shared decision-making, and they will improve clinical care and patient outcomes.

  20. Predicting Severe Pneumonia Outcomes in Children.

    Science.gov (United States)

    Williams, Derek J; Zhu, Yuwei; Grijalva, Carlos G; Self, Wesley H; Harrell, Frank E; Reed, Carrie; Stockmann, Chris; Arnold, Sandra R; Ampofo, Krow K; Anderson, Evan J; Bramley, Anna M; Wunderink, Richard G; McCullers, Jonathan A; Pavia, Andrew T; Jain, Seema; Edwards, Kathryn M

    2016-10-01

    Substantial morbidity and excessive care variation are seen with pediatric pneumonia. Accurate risk-stratification tools to guide clinical decision-making are needed. We developed risk models to predict severe pneumonia outcomes in children (<18 years) by using data from the Etiology of Pneumonia in the Community Study, a prospective study of community-acquired pneumonia hospitalizations conducted in 3 US cities from January 2010 to June 2012. In-hospital outcomes were organized into an ordinal severity scale encompassing severe (mechanical ventilation, shock, or death), moderate (intensive care admission only), and mild (non-intensive care hospitalization) outcomes. Twenty predictors, including patient, laboratory, and radiographic characteristics at presentation, were evaluated in 3 models: a full model included all 20 predictors, a reduced model included 10 predictors based on expert consensus, and an electronic health record (EHR) model included 9 predictors typically available as structured data within comprehensive EHRs. Ordinal regression was used for model development. Predictive accuracy was estimated by using discrimination (concordance index). Among the 2319 included children, 21% had a moderate or severe outcome (14% moderate, 7% severe). Each of the models accurately identified risk for moderate or severe pneumonia (concordance index across models 0.78-0.81). Age, vital signs, chest indrawing, and radiologic infiltrate pattern were the strongest predictors of severity. The reduced and EHR models retained most of the strongest predictors and performed as well as the full model. We created 3 risk models that accurately estimate risk for severe pneumonia in children. Their use holds the potential to improve care and outcomes. Copyright © 2016 by the American Academy of Pediatrics.

  1. Network information improves cancer outcome prediction.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

    2014-07-01

    Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. Predicting radiotherapy outcomes using statistical learning techniques

    Energy Technology Data Exchange (ETDEWEB)

    El Naqa, Issam; Bradley, Jeffrey D; Deasy, Joseph O [Washington University, Saint Louis, MO (United States); Lindsay, Patricia E; Hope, Andrew J [Department of Radiation Oncology, Princess Margaret Hospital, Toronto, ON (Canada)

    2009-09-21

    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among

  3. Predicting radiotherapy outcomes using statistical learning techniques

    Science.gov (United States)

    El Naqa, Issam; Bradley, Jeffrey D.; Lindsay, Patricia E.; Hope, Andrew J.; Deasy, Joseph O.

    2009-09-01

    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

  4. Predicting radiotherapy outcomes using statistical learning techniques

    International Nuclear Information System (INIS)

    El Naqa, Issam; Bradley, Jeffrey D; Deasy, Joseph O; Lindsay, Patricia E; Hope, Andrew J

    2009-01-01

    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

  5. Do illness perceptions predict health outcomes in primary care patients?

    DEFF Research Database (Denmark)

    Frostholm, Lisbeth; Oernboel, Eva; Christensen, Kaj S

    2007-01-01

    OBJECTIVE: Little is known about whether illness perceptions affect health outcomes in primary care patients. The aim of this study was to examine if patients' illness perceptions were associated with their self-rated health in a 2-year follow-up period. METHODS: One thousand seven hundred eighty......-five primary care patients presenting a new or recurrent health problem completed an adapted version of the illness perception questionnaire and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) at baseline and 3, 12, and 24 months' follow-up. Linear regressions were performed for (1) all...... patients, (2) patients without chronic disorders presenting physical disease, and (3) patients presenting medically unexplained symptoms (MUS). RESULTS: Negative illness perceptions were associated with poor physical and mental health at baseline. They most strongly predicted changes in health status...

  6. Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes

    Directory of Open Access Journals (Sweden)

    Sakanyan Vehary

    2008-05-01

    Full Text Available Abstract Background Bacterial promoters, which increase the efficiency of gene expression, differ from other promoters by several characteristics. This difference, not yet widely exploited in bioinformatics, looks promising for the development of relevant computational tools to search for strong promoters in bacterial genomes. Results We describe a new triad pattern algorithm that predicts strong promoter candidates in annotated bacterial genomes by matching specific patterns for the group I σ70 factors of Escherichia coli RNA polymerase. It detects promoter-specific motifs by consecutively matching three patterns, consisting of an UP-element, required for interaction with the α subunit, and then optimally-separated patterns of -35 and -10 boxes, required for interaction with the σ70 subunit of RNA polymerase. Analysis of 43 bacterial genomes revealed that the frequency of candidate sequences depends on the A+T content of the DNA under examination. The accuracy of in silico prediction was experimentally validated for the genome of a hyperthermophilic bacterium, Thermotoga maritima, by applying a cell-free expression assay using the predicted strong promoters. In this organism, the strong promoters govern genes for translation, energy metabolism, transport, cell movement, and other as-yet unidentified functions. Conclusion The triad pattern algorithm developed for predicting strong bacterial promoters is well suited for analyzing bacterial genomes with an A+T content of less than 62%. This computational tool opens new prospects for investigating global gene expression, and individual strong promoters in bacteria of medical and/or economic significance.

  7. Predicting outcome after stroke: the role of basic activities of daily living predicting outcome after stroke.

    Science.gov (United States)

    Gialanella, B; Santoro, R; Ferlucci, C

    2013-10-01

    Very few studies have investigated the influence of single activities of daily living (ADL) at admission as possible predictors of functional outcome after rehabilitation. The aim of the current study was to investigate admission functional status and performance of basic ADLs as assessed by Functional Independence Measure (FIM) scale as possible predictors of motor and functional outcome after stroke during inpatient rehabilitation. This is a prospective and observational study. Inpatients of our Department of Physical Medicine and Rehabilitation. Two hundred sixty consecutive patients with primary diagnosis of stroke were enrolled and 241 patients were used in the final analyses. Two backward stepwise regression analyses were applied to predict outcome. The first backward stepwise regression had age, gender, stroke type, stroke-lesion size, aphasia, neglect, onset to admission interval, Cumulative Illness Rating Scale, National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Scale, Trunk Control Test, and FIM (total, motor and cognitive scores) as independent variables. The second analyses included the above variables plus FIM items as an independent variable. The dependent variables were the discharge scores and effectiveness in total and motor-FIM, and discharge destination. The first multivariate analysis showed that admission Fugl-Meyer, neglect, total, motor and cognitive FIM scores were the most important predictors of FIM outcomes, while admission NIHSS score was the only predictor of discharge destination. Conversely, when admission single FIM items were included in the statistical model, admission Fugl-Meyer, neglect, grooming, dressing upper body, and social interaction scores were the most important predictors of FIM outcomes, while admission memory and bowel control scores were the only predictors of discharge destination. Our study indicates that performances of basic ADLs are important stroke outcome predictors and among which social

  8. Prediction of strong earthquake motions on rock surface using evolutionary process models

    International Nuclear Information System (INIS)

    Kameda, H.; Sugito, M.

    1984-01-01

    Stochastic process models are developed for prediction of strong earthquake motions for engineering design purposes. Earthquake motions with nonstationary frequency content are modeled by using the concept of evolutionary processes. Discussion is focused on the earthquake motions on bed rocks which are important for construction of nuclear power plants in seismic regions. On this basis, two earthquake motion prediction models are developed, one (EMP-IB Model) for prediction with given magnitude and epicentral distance, and the other (EMP-IIB Model) to account for the successive fault ruptures and the site location relative to the fault of great earthquakes. (Author) [pt

  9. Prediction and discovery of extremely strong hydrodynamic instabilities due to a velocity jump: theory and experiments

    International Nuclear Information System (INIS)

    Fridman, A M

    2008-01-01

    The theory and the experimental discovery of extremely strong hydrodynamic instabilities are described, viz. the Kelvin-Helmholtz, centrifugal, and superreflection instabilities. The discovery of the last two instabilities was predicted and the Kelvin-Helmholtz instability in real systems was revised by us. (reviews of topical problems)

  10. Machine learning landscapes and predictions for patient outcomes

    Science.gov (United States)

    Das, Ritankar; Wales, David J.

    2017-07-01

    The theory and computational tools developed to interpret and explore energy landscapes in molecular science are applied to the landscapes defined by local minima for neural networks. These machine learning landscapes correspond to fits of training data, where the inputs are vital signs and laboratory measurements for a database of patients, and the objective is to predict a clinical outcome. In this contribution, we test the predictions obtained by fitting to single measurements, and then to combinations of between 2 and 10 different patient medical data items. The effect of including measurements over different time intervals from the 48 h period in question is analysed, and the most recent values are found to be the most important. We also compare results obtained for neural networks as a function of the number of hidden nodes, and for different values of a regularization parameter. The predictions are compared with an alternative convex fitting function, and a strong correlation is observed. The dependence of these results on the patients randomly selected for training and testing decreases systematically with the size of the database available. The machine learning landscapes defined by neural network fits in this investigation have single-funnel character, which probably explains why it is relatively straightforward to obtain the global minimum solution, or a fit that behaves similarly to this optimal parameterization.

  11. Prediction of strong ground motion based on scaling law of earthquake

    International Nuclear Information System (INIS)

    Kamae, Katsuhiro; Irikura, Kojiro; Fukuchi, Yasunaga.

    1991-01-01

    In order to predict more practically strong ground motion, it is important to study how to use a semi-empirical method in case of having no appropriate observation records for actual small-events as empirical Green's functions. We propose a prediction procedure using artificially simulated small ground motions as substitute for the actual motions. First, we simulate small-event motion by means of stochastic simulation method proposed by Boore (1983) in considering pass effects such as attenuation, and broadening of waveform envelope empirically in the objective region. Finally, we attempt to predict the strong ground motion due to a future large earthquake (M 7, Δ = 13 km) using the same summation procedure as the empirical Green's function method. We obtained the results that the characteristics of the synthetic motion using M 5 motion were in good agreement with those by the empirical Green's function method. (author)

  12. Risperidone and Venlafaxine Metabolic Ratios Strongly Predict a CYP2D6 Poor Metabolizing Genotype.

    Science.gov (United States)

    Mannheimer, Buster; Haslemo, Tore; Lindh, Jonatan D; Eliasson, Erik; Molden, Espen

    2016-02-01

    To investigate the predictive value of the risperidone and venlafaxine metabolic ratios and CYP2D6 genotype. The determination of risperidone, 9-hydroxyrisperidone, and venlafaxine, O-desmethylvenlafaxine, N-desmethylvenlafaxine and CYP2D6 genotype was performed in 425 and 491 patients, respectively. The receiver operator characteristic method and the area under the receiver operator characteristic curve were used to illustrate the predictive value of risperidone metabolic ratio for the individual CYP2D6 genotype. To evaluate the proposed cutoff levels of >1 to identify individuals with a poor CYP2D6 genotype, the sensitivity, specificity, positive predictive values, and negative predictive values were calculated. Area under the receiver operator characteristic curve to predict poor metabolizers for risperidone/9-hydroxyrisperidone and N-desmethylvenlafaxine/O-desmethylvenlafaxine ratios was 93% and 99%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value (confidence interval) of a risperidone/9-hydroxyrisperidone ratio >1 to predict a CYP2D6 poor metabolizer genotype were 91% (76%-97%), 86% (83%-89%), 35% (26%-46%), and 99% (97%-100%), respectively. The corresponding measures for N-desmethylvenlafaxine/O-desmethylvenlafaxine were 93% (76%-97%), 87% (83%-89%), 40% (32%-51%), and 99% (98%-100%). Risperidone/9-hydroxyrisperidone and N-desmethylvenlafaxine/O-desmethylvenlafaxine metabolic ratios >1 strongly predict individuals with poor metabolizer genotype, which could guide psychotropic drug treatment to avoid adverse drug reactions and to increase their therapeutic efficacy in patients prescribed these drugs.

  13. Diffusion changes predict cognitive and functional outcome

    DEFF Research Database (Denmark)

    Jokinen, Hanna; Schmidt, Reinhold; Ropele, Stefan

    2013-01-01

    A study was undertaken to determine whether diffusion-weighted imaging (DWI) abnormalities in normal-appearing brain tissue (NABT) and in white matter hyperintensities (WMH) predict longitudinal cognitive decline and disability in older individuals independently of the concomitant magnetic...

  14. Monitoring of the future strong Vrancea events by using the CN formal earthquake prediction algorithm

    International Nuclear Information System (INIS)

    Moldoveanu, C.L.; Novikova, O.V.; Panza, G.F.; Radulian, M.

    2003-06-01

    The preparation process of the strong subcrustal events originating in Vrancea region, Romania, is monitored using an intermediate-term medium-range earthquake prediction method - the CN algorithm (Keilis-Borok and Rotwain, 1990). We present the results of the monitoring of the preparation of future strong earthquakes for the time interval from January 1, 1994 (1994.1.1), to January 1, 2003 (2003.1.1) using the updated catalogue of the Romanian local network. The database considered for the CN monitoring of the preparation of future strong earthquakes in Vrancea covers the period from 1966.3.1 to 2003.1.1 and the geographical rectangle 44.8 deg - 48.4 deg N, 25.0 deg - 28.0 deg E. The algorithm correctly identifies, by retrospective prediction, the TJPs for all the three strong earthquakes (Mo=6.4) that occurred in Vrancea during this period. The cumulated duration of the TIPs represents 26.5% of the total period of time considered (1966.3.1-2003.1.1). The monitoring of current seismicity using the algorithm CN has been carried out since 1994. No strong earthquakes occurred from 1994.1.1 to 2003.1.1 but the CN declared an extended false alarm from 1999.5.1 to 2000.11.1. No alarm has currently been declared in the region (on January 1, 2003), as can be seen from the TJPs diagram shown. (author)

  15. Prediction of unfavorable outcomes in cryptococcal meningitis

    DEFF Research Database (Denmark)

    Hakyemez, I N; Erdem, H; Beraud, G

    2018-01-01

    Cryptococcal meningitis (CM) is mostly seen in immunocompromised patients, particularly human immunodeficiency virus (HIV)-positive patients, but CM may also occur in apparently immunocompetent individuals. Outcome analyses have been performed in such patients but, due to the high prevalence of HIV...

  16. Sonographic prediction of outcome of vacuum deliveries

    DEFF Research Database (Denmark)

    Kahrs, Birgitte H; Usman, Sana; Ghi, Tullio

    2017-01-01

    outcome in nulliparous women with prolonged second stage of labor. STUDY DESIGN: We performed a prospective cohort study in nulliparous women at term with prolonged second stage of labor in 7 European maternity units from 2013 through 2016. Fetal head position and station were determined using...

  17. Factors predicting the outcome of acute renal failure in pregnancy

    International Nuclear Information System (INIS)

    Khana, N.; Akhtar, F.

    2010-01-01

    To determine the factors predicting renal outcome in patients developing acute renal failure in pregnancy. Study Design: Descriptive cohort study. Place and Duration of Study: Study was conducted at Nephrology Unit of Sindh Institute of Urology and Transplantation, Karachi, from October 2006 to March 2007. Methodology: Patients with acute renal failure due to complications of pregnancy, with normal size of both the kidneys on ultrasound were enrolled, and followed for a period of 60 days or until recovery of renal function. Patient's age and parity, presence of antenatal care, type of complication of pregnancy, foetal outcome and duration of oliguria were compared between patients who remained dialysis dependent and those who recovered renal function. Chi-square/Fisher's exact test and student's t-test, were used for determining the association of categorical and continuous variables with dialysis dependency. Results: The mean age was 29 +- 6 years. Most patients came from rural areas of interior Sindh. Sixty eight percent did not have antenatal checkups. Antepartum haemorrhage (p=0.002) and prolonged duration of oliguria (35 +- 15.7 days, p= < 0.001) were associated with dialysis dependency, which was observed in 50% of the study group. Conclusion: Ante-partum haemorrhage and prolonged oliguria were strong predictors of irreversible renal failure. This highlights the need for early recognition and referral, and the importance of trained birth attendants and antenatal care. (author)

  18. [Scales for predicting outcome after severe trauma].

    Science.gov (United States)

    Ali Ali, B; Fortún Moral, M; Belzunegui Otano, T; Reyero Díez, D; Castro Neira, M

    2017-04-30

    In this article we review the development of the most-used scales for severe trauma patients over the past 40 years. It is well known that anatomical scales are effective for measuring the severity of injuries and for predicting results. Physiological scales measure the dynamic component after trauma, with a great influence on the prognosis of injured patients. Metabolic scales, both lactate and base deficit, are reflections of tissue hypoperfusion states and therefore shock. The combined scales are used for prediction and comparative assessment of results. The inclusion of factors that influence the prognosis of trauma patients has led to the development of new scales. However, they lack external validation studies for their widespread use. Until these validation studies are conducted caution should be taken with the use of existing scales.

  19. Protein-Based Urine Test Predicts Kidney Transplant Outcomes

    Science.gov (United States)

    ... News Releases News Release Thursday, August 22, 2013 Protein-based urine test predicts kidney transplant outcomes NIH- ... supporting development of noninvasive tests. Levels of a protein in the urine of kidney transplant recipients can ...

  20. Predicting couple therapy outcomes based on speech acoustic features.

    Directory of Open Access Journals (Sweden)

    Md Nasir

    Full Text Available 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

  1. Low plasma bicarbonate predicts poor outcome of cerebral malaria ...

    African Journals Online (AJOL)

    Malaria remains a major cause of morbidity and mortality in many sub Saharan countries and cerebral malaria is widely recognised as one of its most fatal forms. We studied the predictive value of routine biochemical laboratory indices in predicting the outcome of cerebral malaria in 50 Nigerian children ages 9 months to 6 ...

  2. Outcome Prediction after Radiotherapy with Medical Big Data.

    Science.gov (United States)

    Magome, Taiki

    2016-01-01

    Data science is becoming more important in many fields. In medical physics field, we are facing huge data every day. Treatment outcomes after radiation therapy are determined by complex interactions between clinical, biological, and dosimetrical factors. A key concept of recent radiation oncology research is to predict the outcome based on medical big data for personalized medicine. Here, some reports, which are analyzing medical databases with machine learning techniques, were reviewed and feasibility of outcome prediction after radiation therapy was discussed. In addition, some strategies for saving manual labors to analyze huge data in medical physics were discussed.

  3. Using predictive analytics and big data to optimize pharmaceutical outcomes.

    Science.gov (United States)

    Hernandez, Inmaculada; Zhang, Yuting

    2017-09-15

    The steps involved, the resources needed, and the challenges associated with applying predictive analytics in healthcare are described, with a review of successful applications of predictive analytics in implementing population health management interventions that target medication-related patient outcomes. In healthcare, the term big data typically refers to large quantities of electronic health record, administrative claims, and clinical trial data as well as data collected from smartphone applications, wearable devices, social media, and personal genomics services; predictive analytics refers to innovative methods of analysis developed to overcome challenges associated with big data, including a variety of statistical techniques ranging from predictive modeling to machine learning to data mining. Predictive analytics using big data have been applied successfully in several areas of medication management, such as in the identification of complex patients or those at highest risk for medication noncompliance or adverse effects. Because predictive analytics can be used in predicting different outcomes, they can provide pharmacists with a better understanding of the risks for specific medication-related problems that each patient faces. This information will enable pharmacists to deliver interventions tailored to patients' needs. In order to take full advantage of these benefits, however, clinicians will have to understand the basics of big data and predictive analytics. Predictive analytics that leverage big data will become an indispensable tool for clinicians in mapping interventions and improving patient outcomes. Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

  4. Uncertainties in model-based outcome predictions for treatment planning

    International Nuclear Information System (INIS)

    Deasy, Joseph O.; Chao, K.S. Clifford; Markman, Jerry

    2001-01-01

    Purpose: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. Methods and Materials: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ('noise') is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. Results: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment

  5. CN earthquake prediction algorithm and the monitoring of the future strong Vrancea events

    International Nuclear Information System (INIS)

    Moldoveanu, C.L.; Radulian, M.; Novikova, O.V.; Panza, G.F.

    2002-01-01

    The strong earthquakes originating at intermediate-depth in the Vrancea region (located in the SE corner of the highly bent Carpathian arc) represent one of the most important natural disasters able to induce heavy effects (high tool of casualties and extensive damage) in the Romanian territory. The occurrence of these earthquakes is irregular, but not infrequent. Their effects are felt over a large territory, from Central Europe to Moscow and from Greece to Scandinavia. The largest cultural and economical center exposed to the seismic risk due to the Vrancea earthquakes is Bucharest. This metropolitan area (230 km 2 wide) is characterized by the presence of 2.5 million inhabitants (10% of the country population) and by a considerable number of high-risk structures and infrastructures. The best way to face strong earthquakes is to mitigate the seismic risk by using the two possible complementary approaches represented by (a) the antiseismic design of structures and infrastructures (able to support strong earthquakes without significant damage), and (b) the strong earthquake prediction (in terms of alarm intervals declared for long, intermediate or short-term space-and time-windows). The intermediate term medium-range earthquake prediction represents the most realistic target to be reached at the present state of knowledge. The alarm declared in this case extends over a time window of about one year or more, and a space window of a few hundreds of kilometers. In the case of Vrancea events the spatial uncertainty is much less, being of about 100 km. The main measures for the mitigation of the seismic risk allowed by the intermediate-term medium-range prediction are: (a) verification of the buildings and infrastructures stability and reinforcement measures when required, (b) elaboration of emergency plans of action, (c) schedule of the main actions required in order to restore the normality of the social and economical life after the earthquake. The paper presents the

  6. Gesture Performance in Schizophrenia Predicts Functional Outcome After 6 Months.

    Science.gov (United States)

    Walther, Sebastian; Eisenhardt, Sarah; Bohlhalter, Stephan; Vanbellingen, Tim; Müri, René; Strik, Werner; Stegmayer, Katharina

    2016-11-01

    The functional outcome of schizophrenia is heterogeneous and markers of the course are missing. Functional outcome is associated with social cognition and negative symptoms. Gesture performance and nonverbal social perception are critically impaired in schizophrenia. Here, we tested whether gesture performance or nonverbal social perception could predict functional outcome and the ability to adequately perform relevant skills of everyday function (functional capacity) after 6 months. In a naturalistic longitudinal study, 28 patients with schizophrenia completed tests of nonverbal communication at baseline and follow-up. In addition, functional outcome, social and occupational functioning, as well as functional capacity at follow-up were assessed. Gesture performance and nonverbal social perception at baseline predicted negative symptoms, functional outcome, and functional capacity at 6-month follow-up. Gesture performance predicted functional outcome beyond the baseline measure of functioning. Patients with gesture deficits at baseline had stable negative symptoms and experienced a decline in social functioning. While in patients without gesture deficits, negative symptom severity decreased and social functioning remained stable. Thus, a simple test of hand gesture performance at baseline may indicate favorable outcomes in short-term follow-up. The results further support the importance of nonverbal communication skills in subjects with schizophrenia. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

  7. Clinical Outcome Prediction Using Single-Cell Data.

    Science.gov (United States)

    Pouyan, Maziyar Baran; Jindal, Vasu; Nourani, Mehrdad

    2016-10-01

    Single-cell technologies like flow cytometry (FCM) provide valuable biological data for knowledge discovery in complex cellular systems like tissues and organs. FCM data contains multi-dimensional information about the cellular heterogeneity of intricate cellular systems. It is possible to correlate single-cell markers with phenotypic properties of those systems. Cell population identification and clinical outcome prediction from single-cell measurements are challenging problems in the field of single cell analysis. In this paper, we propose a hybrid learning approach to predict clinical outcome using samples' single-cell FCM data. The proposed method is efficient in both i) identification of cellular clusters in each sample's FCM data and ii) predict clinical outcome (healthy versus unhealthy) for each subject. Our method is robust and the experimental results indicate promising performance.

  8. Trial Vocal Fold Injection Predicts Thyroplasty Outcomes in Nonparalytic Glottic Incompetence.

    Science.gov (United States)

    Dumberger, Lukas D; Overton, Lewis; Buckmire, Robert A; Shah, Rupali N

    2017-04-01

    Trial vocal fold injection (TVFI) may be used prior to permanent medialization when voice outcome is uncertain. We aimed to determine whether voice outcomes of TVFI are predictive of, or correlate with outcomes after type I Gore-Tex medialization thyroplasty (GMT) in patients with nonparalytic glottic incompetence (GI). Thirty-five patients with nonparalytic GI who underwent TVFI followed by GMT were retrospectively reviewed. Change in voice-related quality of life (VRQOL) after TVFI was compared to change in VRQOL 3 to 9 months after GMT. Similar comparisons were made for change in glottal function index (GFI) and change in grade, roughness, breathiness, asthenia, and strain (GRBAS). Sample correlation coefficients were calculated. Change in VRQOL after TVFI showed good correlation with change in VRQOL after GMT, r = 0.55. Change in GFI after TVFI showed strong correlation with change in GFI after GMT, r = 0.74. Change in GRBAS after TVFI showed excellent correlation with change in GRBAS after GMT, r = 0.90. The TVFI is a useful tool in nonparalytic GI when outcomes from glottic closure procedures are not clear. Voice outcome measures after TVFI strongly correlate with outcomes from GMT. These data may be used to more confidently counsel patients regarding their predicted outcomes of permanent medialization.

  9. Prediction for Major Adverse Outcomes in Cardiac Surgery: Comparison of Three Prediction Models

    Directory of Open Access Journals (Sweden)

    Cheng-Hung Hsieh

    2007-09-01

    Conclusion: The Parsonnet score performed as well as the logistic regression models in predicting major adverse outcomes. The Parsonnet score appears to be a very suitable model for clinicians to use in risk stratification of cardiac surgery.

  10. Seismic rupture modelling, strong motion prediction and seismic hazard assessment: fundamental and applied approaches

    International Nuclear Information System (INIS)

    Berge-Thierry, C.

    2007-05-01

    The defence to obtain the 'Habilitation a Diriger des Recherches' is a synthesis of the research work performed since the end of my Ph D. thesis in 1997. This synthesis covers the two years as post doctoral researcher at the Bureau d'Evaluation des Risques Sismiques at the Institut de Protection (BERSSIN), and the seven consecutive years as seismologist and head of the BERSSIN team. This work and the research project are presented in the framework of the seismic risk topic, and particularly with respect to the seismic hazard assessment. Seismic risk combines seismic hazard and vulnerability. Vulnerability combines the strength of building structures and the human and economical consequences in case of structural failure. Seismic hazard is usually defined in terms of plausible seismic motion (soil acceleration or velocity) in a site for a given time period. Either for the regulatory context or the structural specificity (conventional structure or high risk construction), seismic hazard assessment needs: to identify and locate the seismic sources (zones or faults), to characterize their activity, to evaluate the seismic motion to which the structure has to resist (including the site effects). I specialized in the field of numerical strong-motion prediction using high frequency seismic sources modelling and forming part of the IRSN allowed me to rapidly working on the different tasks of seismic hazard assessment. Thanks to the expertise practice and the participation to the regulation evolution (nuclear power plants, conventional and chemical structures), I have been able to work on empirical strong-motion prediction, including site effects. Specific questions related to the interface between seismologists and structural engineers are also presented, especially the quantification of uncertainties. This is part of the research work initiated to improve the selection of the input ground motion in designing or verifying the stability of structures. (author)

  11. Prediction and design of first super-strong liquid-crystalline polymers

    International Nuclear Information System (INIS)

    Dowell, F.

    1989-01-01

    This paper presents the details of the theoretical prediction and design (atom by atom, bond by bond) of the molecule chemical structures of the first candidate super-strong liquid-crystalline polymers (SS LCPs). These LCPs are the first LCPs designed to have good compressive strengths, as well as to have tensile strengths and tensile moduli significantly larger than those of existing strong LCPs (such as Kevlar). The key feature of this new class of LCPs is that the exceptional strength is three dimensional on a microscopic, molecular level (thus, on a macroscopic level), in contrast to present LCPs (such as Kevlar) with their one-dimensional exceptional strength. These SS LCPs also have some solubility and processing advantages over existing strong LCPs. These SS LCPs are specially-designed combined LCPs such that the side chains of a molecule interdigitate with the side chains of other molecules. This paper also presents other essential general and specific features required for SS LCPs. Considerations in the design of SS LCPs include the spacing distance between side chains along the backbone, the need for rigid sections in the backbone and side chains, the degree of polymerization, the length of the side chains, the regularity of spacing of the side chains along the backbone, the interdigitation of side chains in submolecular strips, the packing of the side chains on one or two sides of the backbone, the symmetry of the side chains, the points of attachment of the side chains to the backbone, the flexibility and size of the chemical group connecting each side chain to the backbone, the effect of semiflexible sections in the backbone and side chains, and the choice of types of dipolar and/or hydrogen bonding forces in the backbones and side chains for easy alignment

  12. Learning Approaches, Demographic Factors to Predict Academic Outcomes

    Science.gov (United States)

    Nguyen, Tuan Minh

    2016-01-01

    Purpose: The purpose of this paper is to predict academic outcome in math and math-related subjects using learning approaches and demographic factors. Design/Methodology/Approach: ASSIST was used as the instrumentation to measure learning approaches. The study was conducted in the International University of Vietnam with 616 participants. An…

  13. Predicting Social Anxiety Treatment Outcome based on Therapeutic Email Conversations

    NARCIS (Netherlands)

    Hoogendoorn, M.; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

    2016-01-01

    Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more

  14. Prediction of Outcome Using the Mannheim peritonitis Index in ...

    African Journals Online (AJOL)

    Background: Successful management of peritonitis has, for decades, presented a challenge to surgeons despite advancements in medicine. This led to the development of disease severity grading systems that would aid in stratifying patients by individual risk factors and hence appropriately predict possible outcome.

  15. Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes

    Science.gov (United States)

    2015-05-01

    COVERED 15Apr2014 - 14Apr2015 4. TITLE AND SUBTITLE Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes 5a. CONTRACT...al., 1982; Kram & Taylor, 1990) that the mass- specific metabolic cost of locomotion varies in a systematic manner with the linear dimensions of the

  16. Prediction of outcome in patients with low back pain

    DEFF Research Database (Denmark)

    Kongsted, Alice; Andersen, Cathrine Hedegaard; Mørk Hansen, Martin

    2016-01-01

    intensity (0-10) and disability (RMDQ) after 2-weeks, 3-months, and 12-months. The course of LBP in 859 patients was predicted to be short (54%), prolonged (36%), or chronic (7%). Clinicians' expectations were most strongly associated with education, LBP history, radiating pain, and neurological signs...

  17. Lack of Early Improvement Predicts Poor Outcome Following Acute Intracerebral Hemorrhage.

    Science.gov (United States)

    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

  18. [Gastroschisis: Prenatal ultrasonography and obstetrical criteria for predicting neonatal outcome].

    Science.gov (United States)

    Ducellier, G; Moussy, P; Sahmoune, L; Bonneau, S; Alanio, E; Bory, J-P

    2016-09-01

    Prenatal diagnosis of complex laparoschisis is difficult and yet it is associated with a significantly increased morbidity and mortality. The aim of the study was to define ultrasonographic factor and obstetrical criteria to predicting adverse neonatal outcome. Retrospective cohort study over 10 years, of 35 gastroschisis cases in CHU of Reims (France). The primary outcome was the neonatal death due to gastroschisis. The sonographic markers was bowel dilatation intra- or extra-abdominale, amniotic fluid, intra-uterin growth. The obstetrical criteria was fetal vitality, fetal heart rate, type of delivery, the weight and the term of birth. There were 28 live births, 16 children with favorable outcome, 8 children with adverse perinatal outcome and 4 deaths. There were any sonographic criteria to predicting adverse neonatal outcome. Only the birth weight less than 2000g was associated with an increase gastrointestinal complications (P=0.049). The type of the delivery was not associated with an adverse prenatal outcome. The birth weight less than 2000g seems to be associate with an increase gastrointestinal complications. It is important to fight against prematurity in case of gastroschisis. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  19. Oxygenation Saturation Index Predicts Clinical Outcomes in ARDS.

    Science.gov (United States)

    DesPrez, Katherine; McNeil, J Brennan; Wang, Chunxue; Bastarache, Julie A; Shaver, Ciara M; Ware, Lorraine B

    2017-12-01

    Traditional measures of ARDS severity such as Pao 2 /Fio 2 may not reliably predict clinical outcomes. The oxygenation index (OI [Fio 2  × mean airway pressure × 100)/Pao 2 ]) may more accurately reflect ARDS severity but requires arterial blood gas measurement. We hypothesized that the oxygenation saturation index (OSI [Fio 2  × mean airway pressure × 100)/oxygen saturation by pulse oximetry (Spo 2 )]) is a reliable noninvasive surrogate for the OI that is associated with hospital mortality and ventilator-free days (VFDs) in patients with ARDS. Critically ill patients enrolled in a prospective cohort study were eligible if they developed ARDS (Berlin criteria) during the first 4 ICU days and had mean airway pressure, Spo 2 /Fio 2 , and Pao 2 /Fio 2 values recorded on the first day of ARDS (N = 329). The highest mean airway pressure and lowest Spo 2 /Fio 2 and Pao 2 /Fio 2 values were used to calculate OI and OSI. The association between OI or OSI and hospital mortality or VFD was analyzed by using logistic regression and linear regression, respectively. The area under the receiver-operating characteristic curve (AUC) for mortality was compared among OI, OSI, Spo 2 /Fio 2 , Pao 2 /Fio 2 , and Acute Physiology and Chronic Health Evaluation II scores. OI and OSI were strongly correlated (rho = 0.862; P OSI was independently associated with hospital mortality (OR per 5-point increase in OSI, 1.228 [95% CI, 1.056-1.429]; P = .008). OI and OSI were each associated with a reduction in VFD (OI, P = .023; OSI, P = .005). The AUC for mortality prediction was greatest for Acute Physiology and Chronic Health Evaluation II scores (AUC, 0.695; P OSI (AUC, 0.602; P = .007). The AUC for OSI was substantially better in patients aged OSI was correlated with the OI. The OSI on the day of ARDS diagnosis was significantly associated with increased mortality and fewer VFDs. The findings suggest that OSI is a reliable surrogate for OI that can noninvasively provide

  20. Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review.

    Science.gov (United States)

    Senders, Joeky T; Staples, Patrick C; Karhade, Aditya V; Zaki, Mark M; Gormley, William B; Broekman, Marike L D; Smith, Timothy R; Arnaout, Omar

    2018-01-01

    Accurate measurement of surgical outcomes is highly desirable to optimize surgical decision-making. An important element of surgical decision making is identification of the patient cohort that will benefit from surgery before the intervention. Machine learning (ML) enables computers to learn from previous data to make accurate predictions on new data. In this systematic review, we evaluate the potential of ML for neurosurgical outcome prediction. A systematic search in the PubMed and Embase databases was performed to identify all potential relevant studies up to January 1, 2017. Thirty studies were identified that evaluated ML algorithms used as prediction models for survival, recurrence, symptom improvement, and adverse events in patients undergoing surgery for epilepsy, brain tumor, spinal lesions, neurovascular disease, movement disorders, traumatic brain injury, and hydrocephalus. Depending on the specific prediction task evaluated and the type of input features included, ML models predicted outcomes after neurosurgery with a median accuracy and area under the receiver operating curve of 94.5% and 0.83, respectively. Compared with logistic regression, ML models performed significantly better and showed a median absolute improvement in accuracy and area under the receiver operating curve of 15% and 0.06, respectively. Some studies also demonstrated a better performance in ML models compared with established prognostic indices and clinical experts. In the research setting, ML has been studied extensively, demonstrating an excellent performance in outcome prediction for a wide range of neurosurgical conditions. However, future studies should investigate how ML can be implemented as a practical tool supporting neurosurgical care. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease

    Science.gov (United States)

    Horn, Andreas; Reich, Martin; Vorwerk, Johannes; Li, Ningfei; Wenzel, Gregor; Fang, Qianqian; Schmitz-Hübsch, Tanja; Nickl, Robert; Kupsch, Andreas; Volkmann, Jens; Kühn, Andrea A.; Fox, Michael D.

    2018-01-01

    Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p<0.001). This same connectivity profile predicted response in an independent patient cohort (p<0.01). Structural and functional connectivity were independent predictors of clinical improvement (p<0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. Interpretation Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. PMID:28586141

  2. Relative size predicts competitive outcome through 2 million years.

    Science.gov (United States)

    Liow, Lee Hsiang; Di Martino, Emanuela; Krzeminska, Malgorzata; Ramsfjell, Mali; Rust, Seabourne; Taylor, Paul D; Voje, Kjetil L

    2017-08-01

    Competition is an important biotic interaction that influences survival and reproduction. While competition on ecological timescales has received great attention, little is known about competition on evolutionary timescales. Do competitive abilities change over hundreds of thousands to millions of years? Can we predict competitive outcomes using phenotypic traits? How much do traits that confer competitive advantage and competitive outcomes change? Here we show, using communities of encrusting marine bryozoans spanning more than 2 million years, that size is a significant determinant of overgrowth outcomes: colonies with larger zooids tend to overgrow colonies with smaller zooids. We also detected temporally coordinated changes in average zooid sizes, suggesting that different species responded to a common external driver. Although species-specific average zooid sizes change over evolutionary timescales, species-specific competitive abilities seem relatively stable, suggesting that traits other than zooid size also control overgrowth outcomes and/or that evolutionary constraints are involved. © 2017 John Wiley & Sons Ltd/CNRS.

  3. Regional Characterization of the Crust in Metropolitan Areas for Prediction of Strong Ground Motion

    Science.gov (United States)

    Hirata, N.; Sato, H.; Koketsu, K.; Umeda, Y.; Iwata, T.; Kasahara, K.

    2003-12-01

    Introduction: After the 1995 Kobe earthquake, the Japanese government increased its focus and funding of earthquake hazards evaluation, studies of man-made structures integrity, and emergency response planning in the major urban centers. A new agency, the Ministry of Education, Science, Sports and Culture (MEXT) has started a five-year program titled as Special Project for Earthquake Disaster Mitigation in Urban Areas (abbreviated to Dai-dai-toku in Japanese) since 2002. The project includes four programs: I. Regional characterization of the crust in metropolitan areas for prediction of strong ground motion. II. Significant improvement of seismic performance of structure. III. Advanced disaster management system. IV. Investigation of earthquake disaster mitigation research results. We will present the results from the first program conducted in 2002 and 2003. Regional Characterization of the Crust in Metropolitan Areas for Prediction of Strong Ground Motion: A long-term goal is to produce map of reliable estimations of strong ground motion. This requires accurate determination of ground motion response, which includes a source process, an effect of propagation path, and near surface response. The new five-year project was aimed to characterize the "source" and "propagation path" in the Kanto (Tokyo) region and Kinki (Osaka) region. The 1923 Kanto Earthquake is one of the important targets to be addressed in the project. The proximity of the Pacific and Philippine Sea subducting plates requires study of the relationship between earthquakes and regional tectonics. This project focuses on identification and geometry of: 1) Source faults, 2) Subducting plates and mega-thrust faults, 3) Crustal structure, 4) Seismogenic zone, 5) Sedimentary basins, 6) 3D velocity properties We have conducted a series of seismic reflection and refraction experiment in the Kanto region. In 2002 we have completed to deploy seismic profiling lines in the Boso peninsula (112 km) and the

  4. Hemizona Assay and Sperm Penetration Assay in the Prediction of IVF Outcome: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Paraskevi Vogiatzi

    2013-01-01

    Full Text Available The limited predictive value of semen analysis in achieving natural conception or in IVF outcome confirms the need for sperm function tests to determine optimal management. We reviewed HZA and SPA predictive power in IVF outcome, with statistical significance of diagnostic power of the assays. HZA was readily efficient in predicting IVF outcome, while evident inconsistency among the studies analysed framed the SPA’s role in male fertility evaluation. Considerable variation was noted in the diagnostic accuracy values of SPA with wide sensitivity (52–100%, specificity (0–100%, and PPV (18–100% and NPV (0–100% together with fluctuation and notable differentiation in methodology and cutoff values employed by each group. HZA methodology was overall consistent with minor variation in cutoff values and oocyte source, while data analysis reported strong correlation between HZA results with IVF outcome, high sensitivity (75–100%, good specificity (57–100%, and high PPV (79–100% and NPV (68–100%. HZA correlated well with IVF outcome and demonstrated better sensitivity/specificity and positive/negative predictive power. Males with normal or slightly abnormal semen profiles could benefit by this intervention and could be evaluated prior to referral to assisted reproduction. HZA should be used in a sequential fashion with semen analysis and potentially other bioassays in an IVF setting.

  5. Prediction of Functional Outcome in Axonal Guillain-Barre Syndrome.

    Science.gov (United States)

    Sung, Eun Jung; Kim, Dae Yul; Chang, Min Cheol; Ko, Eun Jae

    2016-06-01

    To identify the factors that could predict the functional outcome in patients with the axonal type of Guillain-Barre syndrome (GBS). Two hundred and two GBS patients admitted to our university hospital between 2003 and 2014 were reviewed retrospectively. We defined a good outcome as being "able to walk independently at 1 month after onset" and a poor outcome as being "unable to walk independently at 1 month after onset". We evaluated the factors that differed between the good and poor outcome groups. Twenty-four patients were classified into the acute motor axonal neuropathy type. There was a statistically significant difference between the good and poor outcome groups in terms of the GBS disability score at admission, and GBS disability score and Medical Research Council sum score at 1 month after admission. In an electrophysiologic analysis, the good outcome group showed greater amplitude of median, ulnar, deep peroneal, and posterior tibial nerve compound muscle action potentials (CMAP) and greater amplitude of median, ulnar, and superficial peroneal sensory nerve action potentials (SNAP) than the poor outcome group. A lower GBS disability score at admission, high amplitude of median, ulnar, deep peroneal, and posterior tibial CMAPs, and high amplitude of median, ulnar, and superficial peroneal SNAPs were associated with being able to walk at 1 month in patients with axonal GBS.

  6. Preoperative prediction model of outcome after cholecystectomy for symptomatic gallstones

    DEFF Research Database (Denmark)

    Borly, L; Anderson, I B; Bardram, Linda

    1999-01-01

    and sonography evaluated gallbladder motility, gallstones, and gallbladder volume. Preoperative variables in patients with or without postcholecystectomy pain were compared statistically, and significant variables were combined in a logistic regression model to predict the postoperative outcome. RESULTS: Eighty...... and by the absence of 'agonizing' pain and of symptoms coinciding with pain (P model 15 of 18 predicted patients had postoperative pain (PVpos = 0.83). Of 62 patients predicted as having no pain postoperatively, 56 were pain-free (PVneg = 0.90). Overall accuracy...... was 89%. CONCLUSION: From this prospective study a model based on preoperative symptoms was developed to predict postcholecystectomy pain. Since intrastudy reclassification may give too optimistic results, the model should be validated in future studies....

  7. Neonatal Sleep-Wake Analyses Predict 18-month Neurodevelopmental Outcomes.

    Science.gov (United States)

    Shellhaas, Renée A; Burns, Joseph W; Hassan, Fauziya; Carlson, Martha D; Barks, John D E; Chervin, Ronald D

    2017-11-01

    The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved

  8. WHY WE CANNOT PREDICT STRONG EARTHQUAKES IN THE EARTH’S CRUST

    Directory of Open Access Journals (Sweden)

    Iosif L. Gufeld

    2011-01-01

    Full Text Available In the past decade, earthquake disasters caused multiple fatalities and significant economic losses and challenged the modern civilization. The wellknown achievements and growing power of civilization are backstrapped when facing the Nature. The question arises, what hinders solving a problem of earthquake prediction, while longterm and continuous seismic monitoring systems are in place in many regions of the world. For instance, there was no forecast of the Japan Great Earthquake of March 11, 2011, despite the fact that monitoring conditions for its prediction were unique. Its focal zone was 100–200 km away from the monitoring network installed in the area of permanent seismic hazard, which is subject to nonstop and longterm seismic monitoring. Lesson should be learned from our common fiasco in forecasting, taking into account research results obtained during the past 50–60 years. It is now evident that we failed to identify precursors of the earthquakes. Prior to the earthquake occurrence, the observed local anomalies of various fields reflected other processes that were mistakenly viewed as processes of preparation for largescale faulting. For many years, geotectonic situations were analyzed on the basis of the physics of destruction of laboratory specimens, which was applied to the lithospheric conditions. Many researchers realize that such an approach is inaccurate. Nonetheless, persistent attempts are being undertaken with application of modern computation to detect anomalies of various fields, which may be interpreted as earthquake precursors. In our opinion, such illusory intentions were smashed by the Great Japan Earthquake (Figure 6. It is also obvious that sufficient attention has not been given yet to fundamental studies of seismic processes.This review presents the authors’ opinion concerning the origin of the seismic process and strong earthquakes, being part of the process. The authors realize that a wide discussion is

  9. Perceived Masculinity Predicts U.S. Supreme Court Outcomes.

    Science.gov (United States)

    Chen, Daniel; Halberstam, Yosh; Yu, Alan C L

    2016-01-01

    Previous studies suggest a significant role of language in the court room, yet none has identified a definitive correlation between vocal characteristics and court outcomes. This paper demonstrates that voice-based snap judgments based solely on the introductory sentence of lawyers arguing in front of the Supreme Court of the United States predict outcomes in the Court. In this study, participants rated the opening statement of male advocates arguing before the Supreme Court between 1998 and 2012 in terms of masculinity, attractiveness, confidence, intelligence, trustworthiness, and aggressiveness. We found significant correlation between vocal characteristics and court outcomes and the correlation is specific to perceived masculinity even when judgment of masculinity is based only on less than three seconds of exposure to a lawyer's speech sample. Specifically, male advocates are more likely to win when they are perceived as less masculine. No other personality dimension predicts court outcomes. While this study does not aim to establish any causal connections, our findings suggest that vocal characteristics may be relevant in even as solemn a setting as the Supreme Court of the United States.

  10. Cephalometry and prediction of oral appliance treatment outcome.

    Science.gov (United States)

    Ng, Andrew Tze Ming; Darendeliler, M Ali; Petocz, Peter; Cistulli, Peter A

    2012-03-01

    Predicting which patients with obstructive sleep apnea (OSA) will be successfully treated with mandibular advancement splints (MAS) remains elusive. Developing simple daytime measurements and tests to predict treatment outcome would enhance MAS treatment. The purpose of this study was to assess the clinical utility of anthropomorphic measurements and cephalometric X-rays in the prediction of MAS treatment outcome in OSA. Anthropomorphic measurements and cephalometric X-rays from 72 OSA patients who had presented to a tertiary referral sleep clinic were analyzed retrospectively. Treatment response was defined as ≥50% reduction in Apnea/Hypopnea Index (AHI; criterion 1); ≥50% reduction and residual AHI less than 20/h (criterion 2); ≥50% reduction in AHI and residual AHI less than 10/h (criterion 3); and ≥50% reduction in AHI and residual AHI less than 5/h (criterion 4). This was done to reflect the differences in the clinical definition of treatment success in the literature. A good response occurred in 56% (40 patients) according to criterion 1; 54% (39 patients) according to criterion 2; 46% (33 patients) according to criterion 3; or 39% (28 patients) according to criterion 4. Age and gender were found to be significant predictors for criteria 1 and 2. Age and soft palate length were found to be significant predictors for criteria 3 and 4. Equations to predict MAS treatment response were derived as equations were to predict final AHI. Certain cephalometric and anthropomorphic measurements impact on MAS treatment outcome. This study adds to the current literature and implies that MAS success is (to some degree) related to anatomical characteristics.

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

    Science.gov (United States)

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

    2013-09-01

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

  12. Six-month changes in spirituality and religiousness in alcoholics predict drinking outcomes at nine months.

    Science.gov (United States)

    Robinson, Elizabeth A R; Krentzman, Amy R; Webb, Jon R; Brower, Kirk J

    2011-07-01

    Although spiritual change is hypothesized to contribute to recovery from alcohol dependence, few studies have used prospective data to investigate this hypothesis. Prior studies have also been limited to treatment-seeking and Alcoholics Anonymous (AA) samples. This study included alcohol-dependent individuals, both in treatment and not, to investigate the effect of spiritual and religious (SR) change on subsequent drinking outcomes, independent of AA involvement. Alcoholics (N = 364) were recruited for a panel study from two abstinence-based treatment centers, a moderation drinking program, and untreated individuals from the local community. Quantitative measures of SR change between baseline and 6 months were used to predict 9-month drinking outcomes, controlling for baseline drinking and AA involvement. Significant 6-month changes in 8 of 12 SR measures were found, which included private SR practices, beliefs, daily spiritual experiences, three measures of forgiveness, negative religious coping, and purpose in life. Increases in private SR practices and forgiveness of self were the strongest predictors of improvements in drinking outcomes. Changes in daily spiritual experiences, purpose in life, a general measure of forgiveness, and negative religious coping also predicted favorable drinking outcomes. SR change predicted good drinking outcomes in alcoholics, even when controlling for AA involvement. SR variables, broadly defined, deserve attention in fostering change even among those who do not affiliate with AA or religious institutions. Last, future research should include SR variables, particularly various types of forgiveness, given the strong effects found for forgiveness of self.

  13. Predictive efficacy of radioisotope voiding cystography for renal outcome

    International Nuclear Information System (INIS)

    Kim, Seok Ki; Lee, Dong Soo; Kim, Kwang Myeung; Choi, Whang; Chung, June Key; Lee, Myung Chul

    2000-01-01

    As vesicoureteral reflux (VUR) could lead to renal functional deterioration when combined with urinary tract infection, we need to decide whether operative anti-reflux treatment should be performed at the time of diagnosis of VUR. Predictive value of radioisotope voiding cystography (RIVCG) for renal outcome was tested. In 35 children (18 males, 17 females), radiologic voiding cystoure-thrography (VCU), RIVCG and DMSA scan were performed. Change in renal function was evaluated using the follow-up DMSA scan, ultrasonography, and clinical information. Discriminant analysis was performed using individual or integrated variables such as reflux amount and extent at each phase of voiding on RIVCG, in addition to age, gender and cortical defect on DMSA scan at the time of diagnosis. Discriminant function was composed and its performance was examined. Reflux extent at the filling phase and reflux amount and extent at postvoiding phase had a significant prognostic value. Total reflux amount was a composite variable to predict prognosis. Discriminant function composed of reflux extent at the filling phase and reflux amount and extent at postvoiding phase showed better positive predictive value and specificity than conventional reflux grading. RIVCG could predict renal outcome by disclosing characteristic reflux pattern during various voiding phases.=20

  14. A new nomogram to predict pathologic outcome following radical prostatectomy

    Directory of Open Access Journals (Sweden)

    Alexandre Crippa

    2006-04-01

    Full Text Available OBJECTIVE: To develop a preoperative nomogram to predict pathologic outcome in patients submitted to radical prostatectomy for clinical localized prostate cancer. MATERIALS AND METHODS: Nine hundred and sixty patients with clinical stage T1 and T2 prostate cancer were evaluated following radical prostatectomy, and 898 were included in the study. Following a multivariate analysis, nomograms were developed incorporating serum PSA, biopsy Gleason score, and percentage of positive biopsy cores in order to predict the risks of extraprostatic tumor extension, and seminal vesicle involvement. RESULTS: In univariate analysis there was a significant association between percentage of positive biopsy cores (p < 0.001, serum PSA (p = 0.001 and biopsy Gleason score (p < 0.001 with extraprostatic tumor extension. A similar pathologic outcome was seen among tumors with Gleason score 7, and Gleason score 8 to 10. In multivariate analysis, the 3 preoperative variables showed independent significance to predict tumor extension. This allowed the development of nomogram-1 (using Gleason scores in 3 categories - 2 to 6, 7 and 8 to 10 and nomogram-2 (using Gleason scores in 2 categories - 2 to 6 and 7 to 10 to predict disease extension based on these 3 parameters. In the validation analysis, 87% and 91.1% of the time the nomograms-1 and 2, correctly predicted the probability of a pathological stage to within 10% respectively. CONCLUSION: Incorporating percent of positive biopsy cores to a nomogram that includes preoperative serum PSA and biopsy Gleason score, can accurately predict the presence of extraprostatic disease extension in patients with clinical localized prostate cancer.

  15. Short ECG segments predict defibrillation outcome using quantitative waveform measures.

    Science.gov (United States)

    Coult, Jason; Sherman, Lawrence; Kwok, Heemun; Blackwood, Jennifer; Kudenchuk, Peter J; Rea, Thomas D

    2016-12-01

    Quantitative waveform measures of the ventricular fibrillation (VF) electrocardiogram (ECG) predict defibrillation outcome. Calculation requires an ECG epoch without chest compression artifact. However, pauses in CPR can adversely affect survival. Thus the potential use of waveform measures is limited by the need to pause CPR. We sought to characterize the relationship between the length of the CPR-free epoch and the ability to predict outcome. We conducted a retrospective investigation using the CPR-free ECG prior to first shock among out-of-hospital VF cardiac arrest patients in a large metropolitan region (n=442). Amplitude Spectrum Area (AMSA) and Median Slope (MS) were calculated using ECG epochs ranging from 5s to 0.2s. The relative ability of the measures to predict return of organized rhythm (ROR) and neurologically-intact survival was evaluated at different epoch lengths by calculating the area under the receiver operating characteristic curve (AUC) using the 5-s epoch as the referent group. Compared to the 5-s epoch, AMSA performance declined significantly only after reducing epoch length to 0.2s for ROR (AUC 0.77-0.74, p=0.03) and with epochs of ≤0.6s for neurologically-intact survival (AUC 0.72-0.70, p=0.04). MS performance declined significantly with epochs of ≤0.8s for ROR (AUC 0.78-0.77, p=0.04) and with epochs ≤1.6s for neurologically-intact survival (AUC 0.72-0.71, p=0.04). Waveform measures predict defibrillation outcome using very brief ECG epochs, a quality that may enable their use in current resuscitation algorithms designed to limit CPR interruption. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. Problematic Eating Behaviors Predict Outcomes After Bariatric Surgery.

    Science.gov (United States)

    Miller-Matero, Lisa R; Bryce, Kelly; Saulino, Caroline K; Dykhuis, Kate E; Genaw, Jeffrey; Carlin, Arthur M

    2018-02-07

    There are no clear psychosocial predictors of weight loss following bariatric surgery. The purpose of this study was to investigate whether preoperative problematic eating behaviors predict weight loss outcomes following bariatric surgery. Clinical records were utilized to examine outcomes of 101 patients who completed a pre-surgical psychosocial evaluation and underwent gastric bypass or sleeve gastrectomy. Information analyzed included binge eating history and scores from the Hospital Anxiety and Depression Scale, Yale Food Addiction Scale, and Emotional Eating Scale. Measures of weight loss 1 year post-surgery were compared to pre-surgical assessments. One-year follow-up data were available for 60 patients. Patients with higher levels of eating in response to anger/frustration (p = .02), anxiety (p = .01), or depression (p = .05) were more likely to miss the 1-year follow-up appointment. Eating in response to anger/frustration and depression were related to poorer weight loss outcomes. There was a trend for binge eating to predict greater %EWL (p = .06). A higher number of food addiction symptoms increased the likelihood that patients would experience less weight loss (p = .01). Psychiatric symptoms were not related to weight loss outcomes. Patients who endorsed higher levels of pre-surgical emotional eating and food addiction symptoms had poorer weight loss 1 year post-surgery. Providers should consider screening patients for these behaviors during the pre-surgical psychosocial evaluation which would allow opportunities for psychotherapy and potential improvement in weight loss outcomes. Future research should examine which interventions are successful at improving problematic eating behaviors.

  17. Cluster analysis as a prediction tool for pregnancy outcomes.

    Science.gov (United States)

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  18. Writing abilities longitudinally predict academic outcomes of adolescents with ADHD.

    Science.gov (United States)

    Molitor, Stephen J; Langberg, Joshua M; Bourchtein, Elizaveta; Eddy, Laura D; Dvorsky, Melissa R; Evans, Steven W

    2016-09-01

    Students with attention-deficit/hyperactivity disorder (ADHD) often experience a host of negative academic outcomes, and deficits in reading and mathematics abilities contribute to these academic impairments. Students with ADHD may also have difficulties with written expression, but there has been minimal research in this area and it is not clear whether written expression abilities uniquely contribute to the academic functioning of students with ADHD. The current study included a sample of 104 middle school students diagnosed with ADHD (Grades 6-8). Participants were followed longitudinally to evaluate whether written expression abilities at baseline predicted student grade point average (GPA) and parent ratings of academic impairment 18 months later, after controlling for reading ability and additional relevant covariates. Written expression abilities longitudinally predicted both academic outcomes above and beyond ADHD and oppositional defiant disorder symptoms, medication use, reading ability, and baseline values of GPA and parent-rated academic impairment. Follow-up analyses revealed that no single aspect of written expression was demonstrably more impactful on academic outcomes than the others, suggesting that writing as an entire process should be the focus of intervention. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  19. Writing Abilities Longitudinally Predict Academic Outcomes of Adolescents with ADHD

    Science.gov (United States)

    Molitor, Stephen J.; Langberg, Joshuah M.; Bourchtein, Elizaveta; Eddy, Laura D.; Dvorsky, Melissa R.; Evans, Steven W.

    2016-01-01

    Students with ADHD often experience a host of negative academic outcomes and deficits in reading and mathematics abilities contribute to these academic impairments. Students with ADHD may also have difficulties with written expression but there has been minimal research in this area and it is not clear whether written expression abilities uniquely contribute to the academic functioning of students with ADHD. The current study included a sample of 104 middle school students diagnosed with ADHD (grades 6–8). Participants were followed longitudinally to evaluate whether written expression abilities at baseline predicted student GPA and parent ratings of academic impairment 18 months later, after controlling for reading ability and additional relevant covariates. Written expression abilities longitudinally predicted both academic outcomes above and beyond ADHD and ODD symptoms, medication use, reading ability, and baseline values of GPA and parent-rated academic impairment. Follow-up analyses revealed that no single aspect of written expression was demonstrably more impactful on academic outcomes than the others, suggesting that writing as an entire process should be the focus of intervention. PMID:26783650

  20. Predicting outcome in clinically isolated syndrome using machine learning

    Science.gov (United States)

    Wottschel, V.; Alexander, D.C.; Kwok, P.P.; Chard, D.T.; Stromillo, M.L.; De Stefano, N.; Thompson, A.J.; Miller, D.H.; Ciccarelli, O.

    2014-01-01

    We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clinically isolated syndrome (CIS), on the basis of single patient's lesion features and clinical/demographic characteristics. Seventy-four patients at onset of CIS were scanned and clinically reviewed after one and three years. CDMS was used as the gold standard against which SVM classification accuracy was tested. Radiological features related to lesional characteristics on conventional MRI were defined a priori and used in combination with clinical/demographic features in an SVM. Forward recursive feature elimination with 100 bootstraps and a leave-one-out cross-validation was used to find the most predictive feature combinations. 30 % and 44 % of patients developed CDMS within one and three years, respectively. The SVMs correctly predicted the presence (or the absence) of CDMS in 71.4 % of patients (sensitivity/specificity: 77 %/66 %) at 1 year, and in 68 % (60 %/76 %) at 3 years on average over all bootstraps. Combinations of features consistently gave a higher accuracy in predicting outcome than any single feature. Machine-learning-based classifications can be used to provide an “individualised” prediction of conversion to MS from subjects' baseline scans and clinical characteristics, with potential to be incorporated into routine clinical practice. PMID:25610791

  1. Pretreatment biomarkers predicting PTSD psychotherapy outcomes: A systematic review.

    Science.gov (United States)

    Colvonen, Peter J; Glassman, Lisa H; Crocker, Laura D; Buttner, Melissa M; Orff, Henry; Schiehser, Dawn M; Norman, Sonya B; Afari, Niloofar

    2017-04-01

    Although our understanding of the relationship between posttraumatic stress disorder (PTSD), brain structure and function, neural networks, stress-related systems, and genetics is growing, there is considerably less attention given to which biological markers predict evidence-based PTSD psychotherapy outcomes. Our systematic PRISMA-informed review of 20 studies examined biomarkers as predictors of evidence-based PTSD psychotherapy outcomes. Results provide preliminary evidence that specific structural and functional neural systems (involved in information processing), glucocorticoid sensitivity and metabolism (part of the hypothalamic-pituitary-adrenal axis and the response to stress), heart rate (involved with fear habituation), gene methylation, and certain genotypes (associated with serotonin and glucocorticoids) predicted positive response to PTSD treatment. These pre-treatment biomarkers are associated with processes integral to PTSD treatment, such as those affecting fear learning and extinction, cognitive restructuring, information processing, emotional processing, and interoceptive monitoring. Identifying pre-treatment biomarkers that predict treatment response may offer insight into the mechanisms of psychological treatment, provide a foundation for improving the pharmaceutical augmentation of treatment, and inform treatment matching. Published by Elsevier Ltd.

  2. Immunophenotype predicts outcome in pediatric acute liver failure.

    Science.gov (United States)

    Bucuvalas, John; Filipovich, Lisa; Yazigi, Nada; Narkewicz, Michael R; Ng, Vicky; Belle, Steven H; Zhang, Song; Squires, Robert H

    2013-03-01

    We sought to determine whether markers of T-cell immune activation, including soluble interleukin 2 receptor alpha (sIL2Rα) levels predict outcome in pediatric acute liver failure and may target potential candidates for immunomodulatory therapy. We analyzed markers of immune activation in 77 patients with pediatric acute liver failure enrolled in a multinational, multicenter study. The outcomes were survival with native liver, liver transplantation (LT), and death without transplantation within 21 days after enrollment. Adjusting for multiple comparisons, only normalized serum sIL2Rα level differed significantly among the 3 outcomes, and was significantly higher in patients who died (P=0.02) or underwent LT (P=0.01) compared with those who survived with their native liver. The 37 patients with normal sIL2Rα levels all lived, 30 with their native liver. Of the 15 subjects with markedly high sIL2Rα (≥5000 IU/mL), 5 survived with their native liver, 2 died, and 8 underwent LT. Evidence of immune activation is present in some patients who die or undergo LT. Patients with higher sIL2Rα levels were more likely to die or undergo LT within 21 days than those with lower levels. Identifying a subset of patients at risk for poor outcome may form the foundation for targeted clinical trials with immunomodulatory drugs.

  3. Prediction and Outcome of Intensive Care Unit-Acquired Paresis.

    Science.gov (United States)

    Peñuelas, Oscar; Muriel, Alfonso; Frutos-Vivar, Fernando; Fan, Eddy; Raymondos, Konstantinos; Rios, Fernando; Nin, Nicolás; Thille, Arnaud W; González, Marco; Villagomez, Asisclo J; Davies, Andrew R; Du, Bin; Maggiore, Salvatore M; Matamis, Dimitrios; Abroug, Fekri; Moreno, Rui P; Kuiper, Michael A; Anzueto, Antonio; Ferguson, Niall D; Esteban, Andrés

    2018-01-01

    Intensive care unit-acquired paresis (ICUAP) is associated with poor outcomes. Our objective was to evaluate predictors for ICUAP and the short-term outcomes associated with this condition. A secondary analysis of a prospective study including 4157 mechanically ventilated adults in 494 intensive care units from 39 countries. After sedative interruption, patients were screened for ICUAP daily, which was defined as the presence of symmetric and flaccid quadriparesis associated with decreased or absent deep tendon reflexes. A multinomial logistic regression was used to create a predictive model for ICUAP. Propensity score matching was used to estimate the relationship between ICUAP and short-term outcomes (ie, weaning failure and intensive care unit [ICU] mortality). Overall, 114 (3%) patients had ICUAP. Variables associated with ICUAP were duration of mechanical ventilation (relative risk ratio [RRR] per day, 1.10; 95% confidence interval [CI] 1.08-1.12), steroid therapy (RRR 1.8; 95% CI, 1.2-2.8), insulin therapy (RRR 1.8; 95% CI 1.2-2.7), sepsis (RRR 1.9; 95% CI: 1.2 to 2.9), acute renal failure (RRR 2.2; 95% CI 1.5-3.3), and hematological failure (RRR 1.9; 95% CI: 1.2-2.9). Coefficients were used to generate a weighted scoring system to predict ICUAP. ICUAP was significantly associated with both weaning failure (paired rate difference of 22.1%; 95% CI 9.8-31.6%) and ICU mortality (paired rate difference 10.5%; 95% CI 0.1-24.0%). Intensive care unit-acquired paresis is relatively uncommon but is significantly associated with weaning failure and ICU mortality. We constructed a weighted scoring system, with good discrimination, to predict ICUAP in mechanically ventilated patients at the time of awakening.

  4. Predictive macrosomia birthweight thresholds for adverse maternal and neonatal outcomes.

    Science.gov (United States)

    Wang, Dan; Zhu, Li; Zhang, Shulian; Wu, Xueqin; Wang, Xiaoli; Lv, Qin; Gan, Dongmei; Liu, Ling; Li, Wen; Zhou, Qin; Lu, Jiarong; He, Haiying; Wang, Jimei; Xin, Hua; Li, Zhankui; Chen, Chao

    2016-12-01

    We examined the predictive macrosomia birthweight thresholds for adverse maternal and neonatal outcomes. This was a multicenter, retrospective cohort study conducted in China. We selected 178 709 singletons weighing ≥2500 g with gestational age 37-44 weeks. We categorized macrosomia with two gradations (4000-4499 g and ≥4500 g) and compared them with a normosomic reference group of infants with birthweight 2500-3999 g. The risks of obstetric and neonatal complications increased when infants had a birthweight of ≥4000 g. The rates of infant mortality, Apgar score ≤3 at 5 min, respiratory and neurological disorders rose significantly among neonates weighing ≥4500 g. A definition of macrosomia as birthweight ≥4000 g could be beneficial as an indicator of obstetric and newborn complications, and birthweight ≥4500 g might be predictive of severe infant morbidity and mortality risk.

  5. Executive function processes predict mobility outcomes in older adults.

    Science.gov (United States)

    Gothe, Neha P; Fanning, Jason; Awick, Elizabeth; Chung, David; Wójcicki, Thomas R; Olson, Erin A; Mullen, Sean P; Voss, Michelle; Erickson, Kirk I; Kramer, Arthur F; McAuley, Edward

    2014-02-01

    To examine the relationship between performance on executive function measures and subsequent mobility outcomes in community-dwelling older adults. Randomized controlled clinical trial. Champaign-Urbana, Illinois. Community-dwelling older adults (N = 179; mean age 66.4). A 12-month exercise trial with two arms: an aerobic exercise group and a stretching and strengthening group. Established cognitive tests of executive function (flanker task, task switching, and a dual-task paradigm) and the Wisconsin card sort test. Mobility was assessed using the timed 8-foot up and go test and times to climb up and down a flight of stairs. Participants completed the cognitive tests at baseline and the mobility measures at baseline and after 12 months of the intervention. Multiple regression analyses were conducted to determine whether baseline executive function predicted postintervention functional performance after controlling for age, sex, education, cardiorespiratory fitness, and baseline mobility levels. Selective baseline executive function measurements, particularly performance on the flanker task (β = 0.15-0.17) and the Wisconsin card sort test (β = 0.11-0.16) consistently predicted mobility outcomes at 12 months. The estimates were in the expected direction, such that better baseline performance on the executive function measures predicted better performance on the timed mobility tests independent of intervention. Executive functions of inhibitory control, mental set shifting, and attentional flexibility were predictive of functional mobility. Given the literature associating mobility limitations with disability, morbidity, and mortality, these results are important for understanding the antecedents to poor mobility function that well-designed interventions to improve cognitive performance can attenuate. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

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

    Science.gov (United States)

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

    2017-11-15

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

  7. Endoscopic Mucosal Healing Predicts Favorable Clinical Outcomes in Inflammatory Bowel Disease: A Meta-analysis.

    Science.gov (United States)

    Reinink, Andrew R; Lee, Terrence C; Higgins, Peter D R

    2016-08-01

    Mucosal healing (MH) in inflammatory bowel disease has been associated with improved long-term clinical outcomes. Uncertainty remains as to the magnitude of this effect and to how this association changes with time and degree of healing. PubMed, EMBASE, and Web of Science searches identified 1570 citations. Screening of abstracts identified 155 articles for full-text review, of which 19 met inclusion criteria. For 3 outcomes of interest (surgeries, hospitalizations, remission), weighted random-effects meta-analysis was performed. In pooled analysis, MH predicted fewer major abdominal surgeries (relative risk [RR], 0.34; 95% confidence interval [CI], 0.26-0.46), increased remission (RR, 1.84; 95% CI, 1.43-2.36), and fewer hospitalizations (RR, 0.58; 95% CI, 0.42-0.78). Complete MH and partial MH both showed significantly higher rates of favorable outcomes. Separate analyses for Crohn's disease and ulcerative colitis showed identical patterns for surgeries and remission. When subjects with no healing were excluded, and complete versus partial healing was compared, rates of surgery were not significantly different (RR, 0.82; 95% CI, 0.46-1.44). However, complete healing was superior in predicting corticosteroid-free remission (RR, 1.71; 95% CI, 1.24-2.34). Meta-regression found that the predictive power of this complete versus partial healing distinction was strongly associated with the duration of follow-up after endoscopy. MH is a strong predictor of fewer surgeries, long-term clinical remission, and fewer hospitalizations. Complete healing is not significantly more favorable than partial healing for predicting surgeries or hospitalizations, but it did predict higher rates of clinical remission. This benefit of complete MH over partial healing increases with follow-up time.

  8. Stroke scale score and early prediction of outcome after stroke

    International Nuclear Information System (INIS)

    Ahmed, R.; Zuberi, F.Z.; Afsar, S.

    2004-01-01

    Objective: To evaluate the baseline National Institute of Health Stroke Scale (NIHSS) score as a predictor of functional outcome after ischemic stroke. Subjects and Methods: The study included 50 patients who presented to Civil Hospital, Karachi, during the study period with acute stroke and were evaluated with CT scan of brain. Only those patients were enrolled in the study that had acute ischemic stroke. The enrolled subjects were then evaluated for the neurological impairment using National Institute of Health Stroke Scale (NIHSS). The subjects were followed-up and their functional outcome was assessed using Barthel index (BI) on the 7th day of their admission. Results: Of the fifty patients enrolled in the study, 31 (62%) were males and 19 (38%) were females, with age ranging from 45 years to 95 years and a mean age of 59.9 years. Neurological impairment at presentation was assessed by NIHSS. The score ranged between 2 and 28. The functional outcome was evaluated on the 7th day using Barthel index (BI), which ranged from 0 to 80. NIHSS score was found to be a good predictor of functional outcome in patients with ischemic stroke (p<0.001). Other factors like gender, hypertension and heart disease did not affect the functional recovery in such patients. Various factors were found to be significant for early prediction of stroke recovery. The NIHSS score was the strongest predictor of outcome after ischemic stroke. Age at the time of the event was also found to be an important predictor for stroke recovery. Conclusion: The NIHSS score is a good predictor of patient's recovery after stroke. Assessing the patient's neurological impairment at first presentation of ischemic stroke can guide the physician regarding the prognosis and management plan. (author)

  9. Fronto-Temporal Connectivity Predicts ECT Outcome in Major Depression

    Directory of Open Access Journals (Sweden)

    Amber M. Leaver

    2018-03-01

    Full Text Available BackgroundElectroconvulsive therapy (ECT is arguably the most effective available treatment for severe depression. Recent studies have used MRI data to predict clinical outcome to ECT and other antidepressant therapies. One challenge facing such studies is selecting from among the many available metrics, which characterize complementary and sometimes non-overlapping aspects of brain function and connectomics. Here, we assessed the ability of aggregated, functional MRI metrics of basal brain activity and connectivity to predict antidepressant response to ECT using machine learning.MethodsA radial support vector machine was trained using arterial spin labeling (ASL and blood-oxygen-level-dependent (BOLD functional magnetic resonance imaging (fMRI metrics from n = 46 (26 female, mean age 42 depressed patients prior to ECT (majority right-unilateral stimulation. Image preprocessing was applied using standard procedures, and metrics included cerebral blood flow in ASL, and regional homogeneity, fractional amplitude of low-frequency modulations, and graph theory metrics (strength, local efficiency, and clustering in BOLD data. A 5-repeated 5-fold cross-validation procedure with nested feature-selection validated model performance. Linear regressions were applied post hoc to aid interpretation of discriminative features.ResultsThe range of balanced accuracy in models performing statistically above chance was 58–68%. Here, prediction of non-responders was slightly higher than for responders (maximum performance 74 and 64%, respectively. Several features were consistently selected across cross-validation folds, mostly within frontal and temporal regions. Among these were connectivity strength among: a fronto-parietal network [including left dorsolateral prefrontal cortex (DLPFC], motor and temporal networks (near ECT electrodes, and/or subgenual anterior cingulate cortex (sgACC.ConclusionOur data indicate that pattern classification of multimodal f

  10. Predicting academic outcomes in an Australian graduate entry medical programme.

    Science.gov (United States)

    Puddey, Ian B; Mercer, Annette

    2014-02-15

    Predictive validity studies for selection criteria into graduate entry courses in Australia have been inconsistent in their outcomes. One of the reasons for this inconsistency may have been failure to have adequately considered background disciplines of the graduates as well as other potential confounding socio-demographic variables that may influence academic performance. Graduate entrants into the MBBS at The University of Western Australia between 2005 and 2012 were studied (N = 421). They undertook a 6-month bridging course, before joining the undergraduate-entry students for Years 3 through 6 of the medical course. Students were selected using their undergraduate Grade Point Average (GPA), Graduate Australian Medical School Admissions Test scores (GAMSAT) and a score from a standardised interview. Students could apply from any background discipline and could also be selected through an alternative rural entry pathway again utilising these 3 entry scores. Entry scores, together with age, gender, discipline background, rural entry status and a socioeconomic indicator were entered into linear regression models to determine the relative influence of each predictor on subsequent academic performance in the course. Background discipline, age, gender and selection through the rural pathway were variously related to each of the 3 entry criteria. Their subsequent inclusion in linear regression models identified GPA at entry, being from a health/allied health background and total GAMSAT score as consistent independent predictors of stronger academic performance as measured by the weighted average mark for the core units completed throughout the course. The Interview score only weakly predicted performance later in the course and mainly in clinically-based units. The association of total GAMSAT score with academic performance was predominantly dictated by the score in GAMSAT Section 3 (Reasoning in the biological and physical sciences) with Section 1 (Reasoning in the

  11. Acute Appendicitis in Pregnancy: Predictive Clinical Factors and Pregnancy Outcomes.

    Science.gov (United States)

    Theilen, Lauren H; Mellnick, Vincent M; Shanks, Anthony L; Tuuli, Methodius G; Odibo, Anthony O; Macones, George A; Cahill, Alison G

    2017-05-01

    Objective  The objective of this study was to identify clinical factors predictive of appendicitis in pregnant women and associated obstetric outcomes. Study Design  We performed a single-center, retrospective cohort study of pregnant women who underwent magnetic resonance imaging for suspected appendicitis from 2007 to 2012. Rates and odds of appendicitis based on presenting signs and symptoms were estimated. We also estimated rates and odds of adverse obstetric outcomes among women with a diagnosis of appendicitis. Results  Of 171 pregnant women evaluated, 14 (8.2%) had pathology-confirmed appendicitis. White blood cell (WBC) count on admission was moderately predictive of appendicitis (area under the receiver operating characteristic curve, 0.74). A WBC count > 18,000 made the diagnosis of appendicitis more than 10 times more likely (adjusted odds ratio, 10.51; 95% confidence interval, 1.67-43.1). Of 127 women with complete pregnancy follow-up, women with appendicitis had a higher rate of pregnancy loss appendicitis. Appendicitis diagnosed in the first trimester was associated with increased risk of pregnancy loss  18,000 on admission is significantly associated with appendicitis in pregnant women undergoing evaluation for appendicitis. Appendicitis during the first trimester of pregnancy is associated with previable pregnancy loss. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  12. Module-based outcome prediction using breast cancer compendia.

    Directory of Open Access Journals (Sweden)

    Martin H van Vliet

    Full Text Available BACKGROUND: The availability of large collections of microarray datasets (compendia, or knowledge about grouping of genes into pathways (gene sets, is typically not exploited when training predictors of disease outcome. These can be useful since a compendium increases the number of samples, while gene sets reduce the size of the feature space. This should be favorable from a machine learning perspective and result in more robust predictors. METHODOLOGY: We extracted modules of regulated genes from gene sets, and compendia. Through supervised analysis, we constructed predictors which employ modules predictive of breast cancer outcome. To validate these predictors we applied them to independent data, from the same institution (intra-dataset, and other institutions (inter-dataset. CONCLUSIONS: We show that modules derived from single breast cancer datasets achieve better performance on the validation data compared to gene-based predictors. We also show that there is a trend in compendium specificity and predictive performance: modules derived from a single breast cancer dataset, and a breast cancer specific compendium perform better compared to those derived from a human cancer compendium. Additionally, the module-based predictor provides a much richer insight into the underlying biology. Frequently selected gene sets are associated with processes such as cell cycle, E2F regulation, DNA damage response, proteasome and glycolysis. We analyzed two modules related to cell cycle, and the OCT1 transcription factor, respectively. On an individual basis, these modules provide a significant separation in survival subgroups on the training and independent validation data.

  13. Indocyanine green video angiography predicts outcome of extravasation injuries.

    Directory of Open Access Journals (Sweden)

    Werner Haslik

    Full Text Available BACKGROUND: Extravasation of cytotoxic drugs is a serious complication of systemic cancer treatment. Still, a reliable method for early assessment of tissue damage and outcome prediction is missing. Here, we demonstrate that the evaluation of blood flow by indocyanine green (ICG angiography in the extravasation area predicts for the need of surgical intervention. METHODS: Twenty-nine patients were evaluated by ICG angiography after extravasation of vesicant or highly irritant cytotoxic drugs administered by peripheral i.v. infusion. Tissue perfusion as assessed by this standardized method was correlated with clinical outcome. RESULTS: The perfusion index at the site of extravasation differed significantly between patients with reversible tissue damage and thus healing under conservative management (N = 22 versus those who needed surgical intervention due to the development of necrosis (N = 7; P = 0.0001. Furthermore, in patients benefiting from conservative management, the perfusion index was significantly higher in the central extravasation area denoting hyperemia, when compared with the peripheral area (P = 0.0001. CONCLUSIONS: In this patient cohort, ICG angiography as indicator of local perfusion within the extravasation area was of prognostic value for tissue damage. ICG angiography could thus be used for the early identification of patients at risk for irreversible tissue damage after extravasation of cytotoxic drugs.

  14. Personality characteristics predict outcome of eating disorders in adolescents: a 4-year prospective study.

    Science.gov (United States)

    van der Ham, T; van Strien, D C; van Engeland, H

    1998-06-01

    Results of studies on predictive factors in eating disorders have not been very clear until now. Attention has focused primarily on the predictive value of eating behaviour, duration of illness, comorbidity, and population characteristics for groups with mixed eating disorders, but lately several studies have concentrated on the influence of psychological and personality characteristics. In this 4-year prospective follow-up study of 49 eating-disordered adolescent patients, the predictive value of psychological factors and personality characteristics for the course of eating disorders is determined and discussed. The prognostic power of psychological variables measured by means of the Eating Disorder Inventory and the Dutch Personality Questionnaire is found to be stronger than that of behavioral factors and population characteristics and is different for anorectic and bulimic patients. For restricting anorectics, strong maturity fears predict poor outcome after four years, while for bulimic anorectics a longer duration of illness is related to poor prognosis. For patients with bulimic characteristics low self-esteem at admission is predictive of poor outcome.

  15. FRAIL-NH Predicts Outcomes in Long Term Care.

    Science.gov (United States)

    Kaehr, E W; Pape, L C; Malmstrom, T K; Morley, J E

    2016-02-01

    To investigate the predictive validity of the short, simple FRAIL-NH frailty screening tool in the long term care population and to then compare the predictive validity with the frailty index (FI) for 6-month adverse health outcomes. Retrospective study using the Minimum Data Set (MDS) 3.0 and chart review from June-December 2014. Two Long Term Care Facilities in Saint Louis, MO. 270 patients ages ≥ 65 years old residing in long term care. Frailty was measured using the FRAIL-NH and Frailty Index (FI) criteria. Adverse outcomes measured at 6-month follow-up included falls, hospitalizations, and hospice enrollment/mortality. Based on screening tool used frailty prevalence was 48.7% for FRAIL-NH and 30.3% for FI. The FRAIL-NH pre-frail (Adjusted Odds Ratio [AOR]=2.62; 95% Confidence Interval [CI]=1.25-5.54; p=0.11) classification was associated with 6 month risk of falling and mortality/hospice enrollment was associated with the frail classification, AOR=3.96 (1.44-10.87, p=0.007). Combining the pre-frail and frail categories both measures predicted 6 month mortality with the FRAIL-NH being the strongest predictor (AOR=3.36; 95%CI=1.26-8.98; p=0.016) and the FI was a more modest predictor with an AOR of 2.28; 95%CI=1.01-5.15; p=0.047. When directly comparing the FRAIL-NH to the FI, the FRAIL-NH pre-frail were at increased risk of falling, AOR=2.42 (1.11-5.92, p=0.027) and the FRAIL-NH frail were at increased risk of hospice enrollment/death, OR=3.25 (1.04- 10.86) p=0.044. In comparison to the FI, the FRAIL-NH preformed just as well at screening for frailty and was a slightly better predictor of adverse outcomes. The FRAIL-NH is a brief, easy-to-administer frailty screening tool appropriate for long term care patients and predicts increased risk of falls in the pre-frail and mortality/hospice enrollment in the frail.

  16. Right Atrial Deformation in Predicting Outcomes in Pediatric Pulmonary Hypertension.

    Science.gov (United States)

    Jone, Pei-Ni; Schäfer, Michal; Li, Ling; Craft, Mary; Ivy, D Dunbar; Kutty, Shelby

    2017-12-01

    Elevated right atrial (RA) pressure is a risk factor for mortality, and RA size is prognostic of adverse outcomes in pulmonary hypertension (PH). There is limited data on phasic RA function (reservoir, conduit, and pump) in pediatric PH. We sought to evaluate (1) the RA function in pediatric PH patients compared with controls, (2) compare the RA deformation indices with Doppler indices of diastolic dysfunction, functional capacity, biomarkers, invasive hemodynamics, and right ventricular functional indices, and (3) evaluate the potential of RA deformation indices to predict clinical outcomes. Sixty-six PH patients (mean age 7.9±4.7 years) were compared with 36 controls (7.7±4.4 years). RA and right ventricular deformation indices were obtained using 2-dimensional speckle tracking (2DCPA; TomTec, Germany). RA strain, strain rates, emptying fraction, and right ventricular longitudinal strain were measured. RA function was impaired in PH patients versus controls ( P right ventricular diastolic dysfunction. RA reservoir function, pump function, the rate of atrial filling, and atrial minimum volume emerged as outcome predictors in pediatric PH. © 2017 American Heart Association, Inc.

  17. The neural basis of predicting the outcomes of planned actions

    Directory of Open Access Journals (Sweden)

    Andrew eJahn

    2011-11-01

    Full Text Available A key feature of human intelligence is the ability to predict the outcomes of one’s own actions prior to executing them. Action values are thought to be represented in part in the dorsal and ventral medial prefrontal cortex, yet current studies have focused on the value of executed actions rather than the anticipated value of a planned action. Thus, little is known about the neural basis of how individuals think (or fail to think about their actions and the potential consequences before they act. We scanned individuals with fMRI while they thought about performing actions that they knew would likely be correct or incorrect. Here we show that merely imagining an error, as opposed to imagining a correct outcome, increases activity in the dorsal anterior cingulate cortex, independently of subsequent actions. This activity overlaps with regions that respond to actual error commission. The findings show a distinct network that signals the prospective outcomes of one’s planned actions. A number of clinical disorders such as schizophrenia and drug abuse involve a failure to take the potential consequences of an action into account prior to acting. Our results thus suggest how dysfunctions of the medial prefrontal cortex may contribute to such failures.

  18. Predicting outcomes of mood, anxiety and somatoform disorders: the Leiden routine outcome monitoring study.

    Science.gov (United States)

    van Noorden, Martijn S; van Fenema, Esther M; van der Wee, Nic J A; van Rood, Yanda R; Carlier, Ingrid V E; Zitman, Frans G; Giltay, Erik J

    2012-12-15

    Mood, anxiety and somatoform (MAS) disorders are highly prevalent disorders with substantial mutual comorbidity and a large disease burden. Early identification of patients at risk for poor outcome in routine clinical practice is of clinical importance. The purpose of this study was to predict outcomes in outpatients with MAS disorders using routine outcome monitoring (ROM) data. We conducted a cohort study of 892 adult MAS patients in a naturalistic outpatient psychiatric specialty care setting and validated our results in a replication cohort of 1392 patients. Poor outcome was defined as a <50% reduction (compared to baseline) on the self-report brief symptom inventory (BSI) or a score of ≥3 on the observer-rated clinical global impression severity scale (CGI-S). During a follow-up of up to 2 years, Cox regression models were used to analyze the independent baseline predictors for poor outcome. In multivariable Cox regression models, independent and replicated predictors for poor outcome were higher age (overall p<0.001 for combined cohorts in multivariable Cox regression model), having comorbid MAS disorders or a somatoform disorder (<0.001), dysfunctional personality traits (i.e., tendency to self-harm [p<0.001], intimacy problems [p<0.001] and affective lability [p<0.001]), and a low reported general health status (p<0.001). Detailed treatment information was not available. MAS patients meeting the profile of being elderly, suffering from comorbid MAS disorders or a somatoform disorder, with cluster B personality traits, and a poor reported general health may need special preventive measures to minimise the risk of poor outcome. Copyright © 2012 Elsevier B.V. All rights reserved.

  19. Departures from predicted type II behavior in dirty strong-coupling superconductors

    International Nuclear Information System (INIS)

    Park, J.C.; Neighbor, J.E.; Shiffman, C.A.

    1976-01-01

    Calorimetric measurements of the Ginsburg-Landau parameters for Pb-Sn and Pb-Bi alloys show good agreement with the calculations of Rainer and Bergmann for kappa 1 (t)/kappa 1 (1). However, the calculations of Rainer and Usadel for kappa 2 (t)/kappa 2 (1) substantially underestimate the enhancements due to strong-coupling. (Auth.)

  20. Predicting outcome of depression using the depressive symptom profile: the Leiden Routine Outcome Monitoring Study.

    Science.gov (United States)

    van Noorden, Martijn S; van Fenema, Esther M; van der Wee, Nic J A; Zitman, Frans G; Giltay, Erik J

    2012-06-01

    To investigate the predictive value of items for individual depressive symptoms measured with the self-rated Beck Depression Inventory-Revised (BDI-II) self-report scale on outcome in a large naturalistic cohort of depressive outpatients. We used a cohort of 1,489 adult patients aged 18-65 years with major depressive disorder or dysthymic disorder established with the MINI-Plus diagnostic interview. All patients had a routine outcome monitoring baseline measurement in 2004-2009, with a maximum of 2 years follow-up. We used multivariable Cox regression models to predict remission (MADRS < 10; where MADRS stands for Montgomery-Åsberg Depression Rating Scale) and response (≥50% improvement), and adjusted for clinical and demographic characteristics (i.e. marital status, level of education, working status, comorbid anxiety, avoidant and borderline personality traits, and suicidality) that were identified as predictors in earlier studies. Of the 21 BDI-II items, the items "pessimism" and "loss of energy" independently predicted for both remission and response. For pessimism, the hazard ratio (HR) for remission was 0.81 (95% confidence interval [CI]: 0.73-0.89, P < .001) and for loss of energy, the HR was 0.81 (95% CI: 0.72-0.92, P = .001). These findings of robust prediction of poor outcome by baseline items of "pessimism" and "loss of energy" in a naturalistic treatment setting may help clinicians to identify depressive patients in need for additional or alternative therapeutic approaches. © 2012 Wiley Periodicals, Inc.

  1. Leptomeningeal collateral status predicts outcome after middle cerebral artery occlusion.

    Science.gov (United States)

    Madelung, C F; Ovesen, C; Trampedach, C; Christensen, A; Havsteen, I; Hansen, C K; Christensen, H

    2018-01-01

    Perfusion through leptomeningeal collateral vessels is a likely pivotal factor in the outcome of stroke patients. We aimed to investigate the effect of collateral status on outcome in a cohort of unselected, consecutive stroke patients with middle cerebral artery occlusion undergoing reperfusion therapy. This retrospectively planned analysis was passed on prospectively collected data from 187 consecutive patients with middle cerebral artery occlusion admitted within 4.5 hours to one center and treated with intravenous thrombolysis alone (N = 126), mechanical thrombectomy alone (N = 5), or both (N = 56) from May 2009 to April 2014. Non-contrast CT (NCCT) and computed tomography angiography (CTA) were provided on admission and NCCT repeated at 24 hours. Collateral status was assessed based on the initial CTA. Hemorrhagic transformation was evaluated on the 24-hour NCCT and according to European Cooperative Acute Stroke Study (ECASS) criteria. Modified Rankin Scale score was assessed at 90 days, and mortality at 1 year. At 90 days, median (IQR) modified Rankin Scale score in patients with poor collateral status was 4 (3-6) compared to 2 (1-4) in patients with good collateral status (P collateral status were less likely to achieve a good 90-day outcome (modified Rankin Scale score 0-2) (Adjusted odds ratio 0.27, 95% CI: 0.09-0.86). During the first year, 40.9% of patients with poor collateral status died vs 18.2% of the remaining population (P = .001). Leptomeningeal collateral status predicts functional outcome, mortality, and hemorrhagic transformation following middle cerebral artery occlusion. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Patient classification and outcome prediction in IgA nephropathy.

    Science.gov (United States)

    Diciolla, M; Binetti, G; Di Noia, T; Pesce, F; Schena, F P; Vågane, A M; Bjørneklett, R; Suzuki, H; Tomino, Y; Naso, D

    2015-11-01

    clinical practitioners in medicine. The proposed comparative study of several data mining models for the outcome prediction in IgAN patients, using a large dataset of clinical records from three different countries, provides an insight into the relative prediction ability of the considered methods applied to such a disease. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Psychiatric comorbidity and aspects of cognitive coping negatively predict outcome in cognitive behavioral treatment of psychophysiological insomnia.

    Science.gov (United States)

    van de Laar, Merijn; Pevernagie, Dirk; van Mierlo, Petra; Overeem, Sebastiaan

    2015-01-01

    Cognitive behavioral treatment is the gold standard treatment for insomnia, although a substantial group does not respond. We examined possible predictors for treatment outcome in psychophysiological insomniacs, with a focus on the presence of clearly defined psychiatric comorbidity. This was a longitudinal uncontrolled case series study comprising 60 patients with chronic psychophysiological insomnia consecutively referred to a tertiary sleep medicine center, to receive cognitive behavioral treatment for insomnia (CBT-I). Remission of insomnia was defined as a posttreatment Insomnia Severity Index score below 8. As an alternative outcome, we used a clinically relevant decrease on the Insomnia Severity Index (drop of > 7 points). Personality, coping, and social support questionnaires were assessed before the start of the treatment and were compared between treatment responders and nonresponders. To examine whether these variables were predictive for negative treatment outcome, logistic regression analyses were applied. Treatment nonresponders had a significantly higher prevalence of psychiatric comorbidity. Logistic regression analyses showed that the presence of psychiatric comorbidity was strongly predictive for negative treatment outcome (odds ratios: 20.6 and 10.3 for the 2 outcome definitions). Additionally, higher scores on the cognitive coping strategy called "refocus on planning" were associated with worse CBT-I outcome. Current psychiatric comorbidity is strongly predictive for negative treatment outcome. The presence of a psychiatric disorder must therefore be one of the leading arguments in the choice of treatment modalities that are being proposed to patients with insomnia.

  4. Serum MHPG Strongly Predicts Conversion to Alzheimer's Disease in Behaviorally Characterized Subjects with Down Syndrome

    NARCIS (Netherlands)

    Dekker, Alain D.; Coppus, Antonia M. W.; Vermeiren, Yannick; Aerts, Tony; van Duijn, Cornelia M.; Kremer, Berry P.; Naude, Pieter J. W.; Van Dam, Debby; De Deyn, Peter P.

    2015-01-01

    Background: Down syndrome (DS) is the most prevalent genetic cause of intellectual disability. Early-onset Alzheimer's disease (AD) frequently develops in DS and is characterized by progressive memory loss and behavioral and psychological signs and symptoms of dementia (BPSD). Predicting and

  5. Enhanced outage prediction modeling for strong extratropical storms and hurricanes in the Northeastern United States

    Science.gov (United States)

    Cerrai, D.; Anagnostou, E. N.; Wanik, D. W.; Bhuiyan, M. A. E.; Zhang, X.; Yang, J.; Astitha, M.; Frediani, M. E.; Schwartz, C. S.; Pardakhti, M.

    2016-12-01

    The overwhelming majority of human activities need reliable electric power. Severe weather events can cause power outages, resulting in substantial economic losses and a temporary worsening of living conditions. Accurate prediction of these events and the communication of forecasted impacts to the affected utilities is necessary for efficient emergency preparedness and mitigation. The University of Connecticut Outage Prediction Model (OPM) uses regression tree models, high-resolution weather reanalysis and real-time weather forecasts (WRF and NCAR ensemble), airport station data, vegetation and electric grid characteristics and historical outage data to forecast the number and spatial distribution of outages in the power distribution grid located within dense vegetation. Recent OPM improvements consist of improved storm classification and addition of new predictive weather-related variables and are demonstrated using a leave-one-storm-out cross-validation based on 130 severe extratropical storms and two hurricanes (Sandy and Irene) in the Northeast US. We show that it is possible to predict the number of trouble spots causing outages in the electric grid with a median absolute percentage error as low as 27% for some storm types, and at most around 40%, in a scale that varies between four orders of magnitude, from few outages to tens of thousands. This outage information can be communicated to the electric utility to manage allocation of crews and equipment and minimize the recovery time for an upcoming storm hazard.

  6. Strong homing does not predict high site fidelity in juvenile reef fishes

    Science.gov (United States)

    Streit, Robert P.; Bellwood, David R.

    2018-03-01

    After being displaced, juvenile reef fishes are able to return home over large distances. This strong homing behaviour is extraordinary and may allow insights into the longer-term spatial ecology of fish communities. For example, it appears intuitive that strong homing behaviour should be indicative of long-term site fidelity. However, this connection has rarely been tested. We quantified the site fidelity of juvenile fishes of four species after returning home following displacement. Two species, parrotfishes and Pomacentrus moluccensis, showed significantly reduced site fidelity after returning home. On average, they disappeared from their home sites almost 3 d earlier than expected. Mortality or competitive exclusion does not seem to be the main reasons for their disappearance. Rather, we suggest an increased propensity to relocate after encountering alternative reef locations while homing. It appears that some juvenile fishes may have a higher innate spatial flexibility than their strict homing drive suggests.

  7. Surgical Skill in Bariatric Surgery: Does Skill in One Procedure Predict Outcomes for Another?

    Science.gov (United States)

    Varban, Oliver A.; Greenberg, Caprice C.; Schram, Jon; Ghaferi, Amir A.; Thumma, Joythi R.; Carlin, Arthur M.; Dimick, Justin B.

    2016-01-01

    STRUCTURED ABSTRACT Background Recent data establishes a strong link between peer video ratings of surgical skill and clinical outcomes with laparoscopic gastric bypass. Whether skill for one bariatric procedure can predict outcomes for another, related procedure is unknown. Methods Twenty surgeons voluntarily submitted videos of a standard laparoscopic gastric bypass procedure, which was blindly rated by 10 or more peers using a modified version of the Objective Structured Assessment of Technical Skills (OSATS). Surgeons were divided into quartiles for skill in performing gastric bypass and their outcomes within 30 days after sleeve gastrectomy were compared. Multivariate logistic regression analysis was utilized to adjust for patient risk factors. Results Surgeons with skill ratings in the top (n=5), middle (n=10, middle two combined), and bottom (n=5) quartiles for laparoscopic gastric bypass had similar rates of surgical and medical complications following laparoscopic sleeve gastrectomy (top 5.7%, middle 6.4%, bottom 5.5%, p=0.13). Furthermore, surgeon skill ratings did not correlate with rates of reoperation, readmission and emergency department visits. Top rated surgeons had significantly faster operating room times for sleeve gastrectomy (top 76 min, middle 90 min, bottom 88 min; plaparoscopic gastric bypass do not predict outcomes with laparoscopic sleeve gastrectomy. Evaluation of surgical skill with one procedure may not apply to other related procedures and may require independent assessment of surgical technical proficiency. PMID:27324569

  8. Productive procrastination: academic procrastination style predicts academic and alcohol outcomes

    Science.gov (United States)

    Westgate, Erin C.; Wormington, Stephanie V.; Oleson, Kathryn C.; Lindgren, Kristen P.

    2017-01-01

    Productive procrastination replaces one adaptive behavior with another adaptive—albeit less important—behavior (e.g., organizing notes instead of studying for an exam). We identified adaptive and maladaptive procrastination styles associated with academic and alcohol outcomes in 1106 college undergraduates. Cluster analysis identified five academic procrastination styles—non-procrastinators, academic productive procrastinators, non-academic productive procrastinators, non-academic procrastinators, and classic procrastinators. Procrastination style differentially predicted alcohol-related problems, cravings, risk of alcohol use disorders, and GPA (all ps procrastination and academic productive procrastination were most adaptive overall; non-academic productive procrastination, non-academic procrastination, and classic procrastination were least adaptive. Productive procrastination differed from other procrastination strategies, and maladaptive procrastination styles may be a useful risk indicator for preventative and intervention efforts. PMID:28804158

  9. Productive procrastination: academic procrastination style predicts academic and alcohol outcomes.

    Science.gov (United States)

    Westgate, Erin C; Wormington, Stephanie V; Oleson, Kathryn C; Lindgren, Kristen P

    2017-03-01

    Productive procrastination replaces one adaptive behavior with another adaptive-albeit less important-behavior (e.g., organizing notes instead of studying for an exam). We identified adaptive and maladaptive procrastination styles associated with academic and alcohol outcomes in 1106 college undergraduates. Cluster analysis identified five academic procrastination styles- non-procrastinators , academic productive procrastinators , non-academic productive procrastinators, non-academic procrastinators , and classic procrastinators . Procrastination style differentially predicted alcohol-related problems, cravings, risk of alcohol use disorders, and GPA (all ps procrastination and academic productive procrastination were most adaptive overall; non-academic productive procrastination, non-academic procrastination, and classic procrastination were least adaptive. Productive procrastination differed from other procrastination strategies, and maladaptive procrastination styles may be a useful risk indicator for preventative and intervention efforts.

  10. Predicting Dental Caries Outcomes in Children: A "Risky" Concept.

    Science.gov (United States)

    Divaris, K

    2016-03-01

    In recent years, unprecedented gains in the understanding of the biology and mechanisms underlying human health and disease have been made. In the domain of oral health, although much remains to be learned, the complex interactions between different systems in play have begun to unravel: host genome, oral microbiome with its transcriptome, proteome and metabolome, and more distal influences, including relevant behaviors and environmental exposures. A reasonable expectation is that this emerging body of knowledge can help improve the oral health and optimize care for individuals and populations. These goals are articulated by the National Institutes of Health as "precision medicine" and the elimination of health disparities. Key processes in these efforts are the discovery of causal factors or mechanistic pathways and the identification of individuals or population segments that are most likely to develop (any or severe forms of) oral disease. This article critically reviews the fundamental concepts of risk assessment and outcome prediction, as they relate to early childhood caries (ECC)-a common complex disease with significant negative impacts on children, their families, and the health system. The article highlights recent work and advances in methods available to estimate caries risk and derive person-level caries propensities. It further discusses the reasons for their limited utility in predicting individual ECC outcomes and informing clinical decision making. Critical issues identified include the misconception of defining dental caries as a tooth or surface-level condition versus a person-level disease; the fallacy of applying population-level parameters to individuals, termed privatization of risk; and the inadequacy of using frequentist versus Bayesian modeling approaches to derive individual disease propensity estimates. The article concludes with the notion that accurate caries risk assessment at the population level and "precision dentistry" at the

  11. Incorporating Persistent Pain in Phenotypic Frailty Measurement and Prediction of Adverse Health Outcomes.

    Science.gov (United States)

    Lohman, Matthew C; Whiteman, Karen L; Greenberg, Rebecca L; Bruce, Martha L

    2017-02-01

    Frailty, a syndrome of physiological deficits, is prevalent among older adults and predicts elevated risk of adverse health outcomes. Although persistent pain predicts similar risk, it is seldom considered in frailty measurement. This article evaluated the construct and predictive validity of including persistent pain in phenotypic frailty measurement. Frailty and persistent pain were operationalized using data from the Health and Retirement Study (2006-2012 waves). Among a subset of adults aged 65 and older (n = 3,652), we used latent class analysis to categorize frailty status and to evaluate construct validity. Using Cox proportional hazards models, we compared time to incident adverse outcomes (death, fall, hospitalization, institutionalization, and functional disability) between frailty classes determined by either including or excluding persistent pain as a frailty component. In latent class models, persistent pain occurred with other frailty components in patterns consistent with a medical syndrome. Frail and intermediately frail classes determined by including persistent pain were more strongly associated with all adverse outcomes compared with frail and intermediately frail classes determined excluding persistent pain. Frail respondents had significantly greater risk of death compared with nonfrail respondents when frailty models included rather than excluded persistent pain (respectively, hazard ratio [HR] = 3.87, 95% confidence interval [CI] = 2.99-5.00 (including pain); HR = 2.10, 95% CI = 1.71-2.59 (excluding pain). Findings support consideration of persistent pain as a component of the frailty phenotype. Persistent pain assessment may provide an expedient method to enhance frailty measurement and improve prediction of adverse outcomes. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Advanced analytics for outcome prediction in intensive care units.

    Science.gov (United States)

    Jalali, Ali; Bender, Dieter; Rehman, Mohamed; Nadkanri, Vinay; Nataraj, C

    2016-08-01

    In this paper we present a new expert knowledge based clinical decision support system for prediction of intensive care units outcome based on the physiological measurements collected during the first 48 hours of the patient's admission to the ICU. The developed CDSS algorithm is composed of several stages. First, we categorize the collected data based on the physiological organ that they represent. We then extract clinically relevant features from each data category and then rank these features based on their mutual information with the outcome. Then, we design an artificial neural network to serve as a classifier to detect patients at high risk of critical deterioration. We use the eight-fold cross validation method to test the developed CDSS classifier. The results from the classification show that the newly designed CDSS outperforms the widely used acuity scoring systems, SOFA and SAPS-III. The F-score classification result of our developed algorithms is 42% while the F-score results for SOFA and SAPS-III are 26% and 29% respectively.

  13. CT Measured Psoas Density Predicts Outcomes After Enterocutaneous Fistula Repair

    Science.gov (United States)

    Lo, Wilson D.; Evans, David C.; Yoo, Taehwan

    2018-01-01

    Background Low muscle mass and quality are associated with poor surgical outcomes. We evaluated CT measured psoas muscle density as a marker of muscle quality and physiologic reserve, and hypothesized that it would predict outcomes after enterocutaneous fistula repair (ECF). Methods We conducted a retrospective cohort study of patients 18 – 90 years old with ECF failing non-operative management requiring elective operative repair at Ohio State University from 2005 – 2016 that received a pre-operative abdomen/pelvis CT with intravenous contrast within 3 months of their operation. Psoas Hounsfield Unit average calculation (HUAC) were measured at the L3 level. 1 year leak rate, 90 day, 1 year, and 3 year mortality, complication risk, length of stay, dependent discharge, and 30 day readmission were compared to HUAC. Results 100 patients met inclusion criteria. Patients were stratified into interquartile (IQR) ranges based on HUAC. The lowest HUAC IQR was our low muscle quality (LMQ) cutoff, and was associated with 1 year leak (OR 3.50, p < 0.01), 1 year (OR 2.95, p < 0.04) and 3 year mortality (OR 3.76, p < 0.01), complication risk (OR 14.61, p < 0.01), and dependent discharge (OR 4.07, p < 0.01) compared to non-LMQ patients. Conclusions Psoas muscle density is a significant predictor of poor outcomes in ECF repair. This readily available measure of physiologic reserve can identify patients with ECF on pre-operative evaluation that have significantly increased risk that may benefit from additional interventions and recovery time to mitigate risk before operative repair. PMID:29505144

  14. Predictive Models of Cognitive Outcomes of Developmental Insults

    Science.gov (United States)

    Chan, Yupo; Bouaynaya, Nidhal; Chowdhury, Parimal; Leszczynska, Danuta; Patterson, Tucker A.; Tarasenko, Olga

    2010-04-01

    Representatives of Arkansas medical, research and educational institutions have gathered over the past four years to discuss the relationship between functional developmental perturbations and their neurological consequences. We wish to track the effect on the nervous system by developmental perturbations over time and across species. Except for perturbations, the sequence of events that occur during neural development was found to be remarkably conserved across mammalian species. The tracking includes consequences on anatomical regions and behavioral changes. The ultimate goal is to develop a predictive model of long-term genotypic and phenotypic outcomes that includes developmental insults. Such a model can subsequently be fostered into an educated intervention for therapeutic purposes. Several datasets were identified to test plausible hypotheses, ranging from evoked potential datasets to sleep-disorder datasets. An initial model may be mathematical and conceptual. However, we expect to see rapid progress as large-scale gene expression studies in the mammalian brain permit genome-wide searches to discover genes that are uniquely expressed in brain circuits and regions. These genes ultimately control behavior. By using a validated model we endeavor to make useful predictions.

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

    Science.gov (United States)

    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

  16. Diabetic Retinopathy Is Strongly Predictive of Cardiovascular Autonomic Neuropathy in Type 2 Diabetes.

    Science.gov (United States)

    Huang, Chih-Cheng; Lee, Jong-Jer; Lin, Tsu-Kung; Tsai, Nai-Wen; Huang, Chi-Ren; Chen, Shu-Fang; Lu, Cheng-Hsien; Liu, Rue-Tsuan

    2016-01-01

    A well-established, comprehensive, and simple test battery was used here to re-evaluate risk factors for cardiovascular autonomic neuropathy (CAN) in type 2 diabetes. One hundred and seventy-four patients with type 2 diabetes were evaluated through the methods of deep breathing and Valsalva maneuver for correlation with factors that might influence the presence and severity of CAN. The Composite Autonomic Scoring Scale (CASS) was used to grade the severity of autonomic impairment, and CAN was defined as a CASS score ≥2. Results showed that nephropathy, duration of diabetes, blood pressure, uric acid, and the presence of retinopathy and metabolic syndrome significantly correlated with the CASS score. Age may not be a risk factor for diabetic CAN. However, the effects of diabetes on CAN are more prominent in younger patients than in older ones. Diabetic retinopathy is the most significant risk factor predictive of the presence of CAN in patients with type 2 diabetes.

  17. Predicting the biological variability of environmental rhythms: weak or strong anticipation for sensorimotor synchronization?

    Science.gov (United States)

    Torre, Kjerstin; Varlet, Manuel; Marmelat, Vivien

    2013-12-01

    The internal processes involved in synchronizing our movements with environmental stimuli have traditionally been addressed using regular metronomic sequences. Regarding real-life environments, however, biological rhythms are known to have intrinsic variability, ubiquitously characterized as fractal long-range correlations. In our research we thus investigate to what extent the synchronization processes drawn from regular metronome paradigms can be generalized to other (biologically) variable rhythms. Participants performed synchronized finger tapping under five conditions of long-range and/or short-range correlated, randomly variable, and regular auditory sequences. Combining experimental data analysis and numerical simulation, we found that synchronizing with biologically variable rhythms involves the same internal processes as with other variable rhythms (whether totally random or comprising lawful regularities), but different from those involved with a regular metronome. This challenges both the generalizability of conclusions drawn from regular-metronome paradigms, and recent research assuming that biologically variable rhythms may trigger specific strong anticipatory processes to achieve synchronization. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Acute post cessation smoking. A strong predictive factor for metabolic syndrome among adult Saudis

    International Nuclear Information System (INIS)

    AlDaghri, Nasser M.

    2009-01-01

    To determine the influence of tobacco exposure in the development of metabolic syndrome (MS) in the adult Saudi population. Six hundred and sixty-four adults (305 males and 359 females) aged 25-70 years were included in this cross-sectional study conducted at the King Abdul Aziz University Hospital, between June 2006 and May 2007. We classified the participants into non-smokers, smokers, and ex-smokers (defined as complete cessation for 1-2 years). All subjects were screened for the presence of MS using the modified American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), International Diabetes Federation (IDF) and World Health Organization (WHO) definitions. Metabolic syndrome was highest among ex-smokers regardless of definition used. Relative risk for ex-smokers (95% CI: 2.23, 1.06-4.73) was more than twice in harboring MS as compared to non-smokers (95% CI: 2.78, 1.57-4.92) (p=0.009). Acute post-cessation smoking is a strong predictor for MS among male and female Arabs. Smoking cessation programs should include a disciplined lifestyle and dietary intervention to counteract the MS-augmenting side-effect of smoking cessation. (author)

  19. Family Factors Predict Treatment Outcome for Pediatric Obsessive Compulsive Disorder

    Science.gov (United States)

    Peris, Tara S.; Sugar, Catherine A.; Bergman, R. Lindsey; Chang, Susanna; Langley, Audra; Piacentini, John

    2012-01-01

    Objective To examine family conflict, parental blame, and poor family cohesion as predictors of treatment outcome for youth receiving family-focused cognitive behavioral therapy (FCBT) for obsessive compulsive disorder (OCD). Methods We analyzed data from a sample of youth who were randomized to FCBT (n = 49; 59% male; mean age = 12.43 years) as part of a larger randomized clinical trial. Youngsters and their families were assessed by an independent evaluator (IE) pre- and post- FCBT using a standardized battery of measures evaluating family functioning and OCD symptom severity. Family conflict and cohesion were measured via parent self-report on the Family Environment Scale (FES; Moos & Moos, 1994) and parental blame was measured using parent self-report on the Parental Attitudes and Behaviors Scale (PABS; Peris, 2008b). Symptom severity was rated by IE’s using the Children’s Yale-Brown Obsessive Compulsive Scale (CY-BOCS; Scahill et al., 1997). Results Families with lower levels of parental blame and family conflict and higher levels of family cohesion at baseline were more likely to have a child who responded to FCBT treatment even after adjusting for baseline symptom severity compared to families who endorsed higher levels of dysfunction prior to treatment. In analyses using both categorical and continuous outcome measures, higher levels of family dysfunction and difficulty in higher number of domains of family functioning were associated with lower rates of treatment response. In addition, changes in family cohesion predicted response to FCBT controlling for baseline symptom severity. Conclusions Findings speak to the role of the family in treatment for childhood OCD and highlight potential targets for future family interventions. PMID:22309471

  20. Prediction of outcome after diagnosis of metachronous contralateral breast cancer

    Directory of Open Access Journals (Sweden)

    Fernö Mårten

    2011-03-01

    Full Text Available Abstract Background Although 2-20% of breast cancer patients develop a contralateral breast cancer (CBC, prognosis after CBC is still debated. Using a unique patient cohort, we have investigated whether time interval to second breast cancer (BC2 and mode of detection are associated to prognosis. Methods Information on patient-, tumour-, treatment-characteristics, and outcome was abstracted from patients' individual charts for all patients diagnosed with metachronous CBC in the Southern Healthcare Region of Sweden from 1977-2007. Distant disease-free survival (DDFS and risk of distant metastases were primary endpoints. Results The cohort included 723 patients with metachronous contralateral breast cancer as primary breast cancer event. Patients with less than three years to BC2 had a significantly impaired DDFS (p = 0.01, and in sub-group analysis, this effect was seen primarily in patients aged Conclusions In a large cohort of patients with CBC, we found the time interval to BC2 to be a strong prognostic factor for DDFS in young women and mode of detection to be related to risk of distant metastases. Future studies of tumour biology of BC2 in relation to prognostic factors found in the present study can hopefully provide biological explanations to these findings.

  1. Vegetative State: Difficulty in Identifying Consciousness and Predicting Outcome.

    Science.gov (United States)

    Kondratyeva, E A; Avdunina, I A; Kondratyev, A N; Ulitin, A U; Ivanova, N E; Petrova, M V; Luginina, E V; Grechko, A V

    Article consists of literature review, authors experience of the application of neurovisualization and neurophysiological research methods to predict the recovery of consciousness in patients in vegetative state (VS). According to the literature data PET with FDG has higher sensitivity in the detection of signs of consciousness, then functional MRI (fMRI). The method fMRI allows assessing the functional activity of the brain in a state of rest and in response to stimulation with different modalities ― visual, auditory, etc (with the application of active and passive paradigm). A higher specificity in the detection of signs of consciousness have the methodology of fMRI with the active paradigm, at the same time, the absence of signs of consciousness according to the fMRI can not be charged as a basis for the conclusion of a poor prognosis in a particular patient. Neurophysiological tests (EEG, TMS, EP, etc) are more readily available and quite effective. Based on the literature analysis, the authors comes to the conclusion that neurovisualization and neurophysiological tests used in the prediction of the outcome of VS reflects the residual functional activity of different brain areas, in a context of diffuse brain damage, and the recovery of consciousness is usually combined with the restoring of the functional activity off the thalamocortical tracts, which activity, indirectly, is evaluated using these methods. In the authors' opinions, the main disadvantage in the interpretation of the is the lack of a common pathophysiological concept of the organization of brain functions in VS patients. The authors offer for the discussion their concept of stable pathological states of the brain, which is based on the works of Russian pathophysiologists.

  2. Patient assessment: preparing for a predictable aesthetic outcome.

    Science.gov (United States)

    Mehta, Shamir B; Banerji, Subir; Aulakh, Raman

    2015-01-01

    The flux of patients seeking to make changes to the appearance of their smile zone appears to be on a pathway of continual increase. This is possibly due to an increase in awareness towards oral health, and perhaps social, peer and media pressures, respectively. Cohorts of dental practitioners have thus responded to the latter demands by attending a plethora of educational courses, often focusing on either restorative techniques or other disciplines, notably orthodontics and clear aligners in particular. Consequently, treatment planning and thus treatment provision may carry the risk of being biased or indeed 'outcome driven' whereby the skills and knowledge of any clinician towards a particular faculty may significantly influence the ultimate treatment plan, with the unfortunate tendency sometimes to overlook the role of the interdisciplinary approach of concomitant restorative and contemporary techniques. The role of orthodontics to facilitate the provision of such treatment, along with predictable enamel bonding, has the distinct advantage of providing an acceptable aesthetic result with minimal biological intervention. However, to achieve an optimal result in such cases requires meticulous treatment planning and patient selection to avoid pitfalls with regards to long-term stability and function. This article suggests a standardized approach to patient assessment, with an interdisciplinary perspective in mind. Clinical Relevance: With the growth of patient demand for improving the appearance of the smile, a meticulous assessment protocol is required along with effective interdisciplinary communication. This enables a comprehensive treatment plan to be developed with the correct priorities.

  3. Duration of Posttraumatic Amnesia Predicts Neuropsychological and Global Outcome in Complicated Mild Traumatic Brain Injury.

    Science.gov (United States)

    Hart, Tessa; Novack, Thomas A; Temkin, Nancy; Barber, Jason; Dikmen, Sureyya S; Diaz-Arrastia, Ramon; Ricker, Joseph; Hesdorffer, Dale C; Jallo, Jack; Hsu, Nancy H; Zafonte, Ross

    Examine the effects of posttraumatic amnesia (PTA) duration on neuropsychological and global recovery from 1 to 6 months after complicated mild traumatic brain injury (cmTBI). A total of 330 persons with cmTBI defined as Glasgow Coma Scale score of 13 to 15 in emergency department, with well-defined abnormalities on neuroimaging. Enrollment within 24 hours of injury with follow-up at 1, 3, and 6 months. Glasgow Outcome Scale-Extended, California Verbal Learning Test II, and Controlled Oral Word Association Test. Duration of PTA was retrospectively measured with structured interview at 30 days postinjury. Despite all having a Glasgow Coma Scale Score of 13 to 15, a quarter of the sample had a PTA duration of greater than 7 days; half had PTA duration of 1 of 7 days. Both cognitive performance and Extended Glasgow Outcome Scale outcomes were strongly associated with time since injury and PTA duration, with those with PTA duration of greater than 1 week showing residual moderate disability at 6-month assessment. Findings reinforce importance of careful measurement of duration of PTA to refine outcome prediction and allocation of resources to those with cmTBI. Future research would benefit from standardization in computed tomographic criteria and use of severity indices beyond Glasgow Coma Scale to characterize cmTBI.

  4. Prediction of en-route complications during interfacility transport by outcome predictive scores in ED.

    Science.gov (United States)

    Wong, Y K; Lui, C T; Li, K K; Wong, C Y; Lee, M M; Tong, W L; Ong, K L; Tang, S Y H

    2016-05-01

    The objective was to determine the accuracy of the outcome predictive scores (Modified Early Warning Score [MEWS]; Hypotension, Low Oxygen Saturation, Low Temperature, Abnormal ECG, Loss of Independence [HOTEL] score; and Simple Clinical Score [SCS]) in predicting en-route complications during interfacility transport (IFT) in emergency department. This was a retrospective cohort study. All IFT cases by ambulances with either nurse-led or physician-led escort, occurring between 1 January 2011 and 31 December 2012, were included. Obstetric and pediatric cases (age HOTEL, and SCS) at triage station and on ambulance departure. The accuracy of predictive scores was compared by the receiver operating characteristic (ROC) curves. A total of 659 cases were included. Seventeen cases had en-route complications (2.6%). The complication rate in physician-escorted transport (2.2%) was similar to that in nurse-escorted transport (2.6%). None of the 57 intubated cases had en-route complications. The area under the ROC curve for MEWS was 0.662 (triage) and 0.479 (departure). The accuracy of MEWS at triage was better than that at departure (P = .049). The area under the ROC curve for HOTEL was 0.613 (triage) and 0.597 (departure), and that for SCS was 0.6 (triage) and 0.568 (departure). In general, the predictive scores at triage were better than those on departure. None of the scores had good accuracy in prediction of en-route complications during IFT. MEWS at triage was among the best one already but was not ideal. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Fetal megacystis : prediction of spontaneous resolution and outcome

    NARCIS (Netherlands)

    Fontanella, F.; Duin, L.; Adama van Scheltema, P. N.; Cohen-Overbeek, T. E.; Pajkrt, E.; Bekker, M.; Willekes, C.; Bax, C. J.; Bilardo, C. M.

    2017-01-01

    Objectives: To investigate the natural history of fetal megacystis from diagnosis in utero to postnatal outcome, and to identify prognostic indicators of spontaneous resolution and postnatal outcome after resolution. Methods: This was a national retrospective cohort study. Fetal megacystis was

  6. Procedure to predict the storey where plastic drift dominates in two-storey building under strong ground motion

    DEFF Research Database (Denmark)

    Hibino, Y.; Ichinose, T.; Costa, J.L.D.

    2009-01-01

    A procedure is presented to predict the storey where plastic drift dominates in two-storey buildings under strong ground motion. The procedure utilizes the yield strength and the mass of each storey as well as the peak ground acceleration. The procedure is based on two different assumptions: (1......) the seismic force distribution is of inverted triangular form and (2) the rigid-plastic model represents the system. The first and the second assumptions, respectively, lead to lower and upper estimates of the base shear coefficient under which the drift of the first storey exceeds that of the second storey...

  7. Residual pulmonary vasodilative reserve predicts outcome in idiopathic pulmonary hypertension.

    Science.gov (United States)

    Leuchte, Hanno H; Baezner, Carlos; Baumgartner, Rainer A; Muehling, Olaf; Neurohr, Claus; Behr, Juergen

    2015-06-01

    Idiopathic pulmonary arterial hypertension (IPAH) remains a devastating and incurable, albeit treatable condition. Treatment response is not uniform and parameters that help to anticipate a rather benign or a malignant course of the disease are warranted. Acute pulmonary vasoreactivity testing during right heart catheterisation is recommended to identify a minority of patients with IPAH with sustained response to calcium channel blocker therapy. This study aimed to evaluate the prognostic significance of a residual pulmonary vasodilative reserve in patients with IPAH not meeting current vasoresponder criteria. Observational right heart catheter study in 66 (n=66) patients with IPAH not meeting current vasoresponse criteria. Pulmonary vasodilative reserve was assessed by inhalation of 5 µg iloprost-aerosol. Sixty-six (n=66) of 72 (n=72) patients with IPAH did not meet current definition criteria assessed during vasodilator testing to assess pulmonary vasodilatory reserve. In those, iloprost-aerosol caused a reduction of mean pulmonary artery pressure (Δ pulmonary artery pressure-11.4%; p<0.001) and increased cardiac output (Δ cardiac output +16.7%; p<0.001), resulting in a reduction of pulmonary vascular resistance (Δ pulmonary vascular resistance-25%; p<0.001). The magnitude of this response was pronounced in surviving patients. A pulmonary vascular resistance reduction of ≥30% turned out to predict outcome in patients with IPAH. Residual pulmonary vasodilative reserve during acute vasodilator testing is of prognostic relevance in patients with IPAH not meeting current definitions of acute vasoreactivity. Therefore vasoreactivity testing holds more information than currently used. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  8. The success of cardiotocography in predicting perinatal outcome

    Directory of Open Access Journals (Sweden)

    Alpaslan Kaban

    2012-06-01

    Full Text Available Objectives: The determination of the fetal condition duringlabor is important to minimize fetal death due to asphyxiaand the neurological sequelae of fetal hypoxia.This study evaluated the success of fetal cardiotocographyin predicting perinatal consequences.Materials and methods: This study enrolled 101 full-termpregnant women admitted for delivery to Vakif GurebaTraining and Research Hospital between October 2009and February 2010. Women were included if they wereaged 18-45 years and within 36-41 weeks of gestation.During a 20-min period of fetal monitoring, a change inFHR (fetal heart rate lasting for 15 s or two elevated runsof 15 beats was evaluated as a reactive NST (non-stresstest. The umbilical artery pH was used as the “gold standard”for assessing fetal asphyxia.Results: The mean age of the women included in thestudy was 27.82 ± 5.29 years, the average parity was1.09± 0.96. The pH was normal in 85 neonates, while 13 hadfetal asphyxia. No significant difference in umbilical cordblood pH, pO2, or pCO2 was observed between these twogroups (p = 0.497, p = 0.722, and p = 0.053, respectively.No significant difference in maternal age, parity, or birthweight was found between the group with fetal distressbased on CTG (cardiotocography and the normal group.Conclusion: Cardiotocography is an important test duringlabor for labor management, it is insufficient for predictingthe perinatal outcome. Therefore, labor should beevaluated on an individualized basis. J Clin Exp Invest2012; 3(2: 168-171

  9. Do infant vocabulary skills predict school-age language and literacy outcomes?

    Science.gov (United States)

    Duff, Fiona J; Reen, Gurpreet; Plunkett, Kim; Nation, Kate

    2015-08-01

    Strong associations between infant vocabulary and school-age language and literacy skills would have important practical and theoretical implications: Preschool assessment of vocabulary skills could be used to identify children at risk of reading and language difficulties, and vocabulary could be viewed as a cognitive foundation for reading. However, evidence to date suggests predictive ability from infant vocabulary to later language and literacy is low. This study provides an investigation into, and interpretation of, the magnitude of such infant to school-age relationships. Three hundred British infants whose vocabularies were assessed by parent report in the 2nd year of life (between 16 and 24 months) were followed up on average 5 years later (ages ranged from 4 to 9 years), when their vocabulary, phonological and reading skills were measured. Structural equation modelling of age-regressed scores was used to assess the strength of longitudinal relationships. Infant vocabulary (a latent factor of receptive and expressive vocabulary) was a statistically significant predictor of later vocabulary, phonological awareness, reading accuracy and reading comprehension (accounting for between 4% and 18% of variance). Family risk for language or literacy difficulties explained additional variance in reading (approximately 10%) but not language outcomes. Significant longitudinal relationships between preliteracy vocabulary knowledge and subsequent reading support the theory that vocabulary is a cognitive foundation of both reading accuracy and reading comprehension. Importantly however, the stability of vocabulary skills from infancy to later childhood is too low to be sufficiently predictive of language outcomes at an individual level - a finding that fits well with the observation that the majority of 'late talkers' resolve their early language difficulties. For reading outcomes, prediction of future difficulties is likely to be improved when considering family

  10. Unilateral hip osteoarthritis: can we predict the outcome of the other hip?

    Energy Technology Data Exchange (ETDEWEB)

    Vossinakis, I.C. [General Hospital of Volos, Orthopaedic Department, Volos (Greece); Georgiades, G. [General Hospital of Tripoli, Tripoli Greece, Orthopaedic Department, Athens (Greece); Hartofilakidis, G. [University of Athens Medical School, Department of Orthopaedics, Athens (Greece); Kafidas, D.

    2008-10-15

    The objective of this study was to define, in unilateral hip osteoarthritis (OA), factors predicting the outcome of the other hip. We examined the anteroposterior radiographs of the pelvis of 95 white patients with unilateral idiopathic (56 patients) or secondary to congenital hip diseases (39 patients) OA. The other hip was free from symptoms (pain or limping) at the initial examination and without radiographic evidence of OA; it was what we call a ''normal'' hip. Two parameters were evaluated: (1) the type of osteoarthritis of the involved hip and (2) the range of four radiographic indices of the contralateral hip: the sourcil inclination (weight-bearing surface), the acetabular angle, the Wiberg's center-edge angle, and the neck-shaft angle. Follow-up radiographs for the hips that remained OA-free were available for 10 to 35 years and for those that developed OA, at the time of initial symptoms, range 2 to 31 years. Logistic regression analysis showed that the presence of idiopathic OA in one hip had a statistically significant effect on the development of OA on the other hip (p<0.001). Minor deviations of radiographic indices of the contralateral hip is not a predictive factor for its outcome. When the radiographic indices are examined together with the pathology of the involved hip, only WBS was shown to have a significant effect to the development of OA and its type (p < 0.001). The following conclusions can be drawn from this study: 1. Patient with idiopathic OA of one hip is at increased risk of developing OA in the other hip. 2. The outcome of the other hip cannot be predicted only on the basis of the evaluation of its radiographic indices. 3. Among the different indices, WBS seems to have a strong influence toward the development of OA. (orig.)

  11. Intracranial EEG in predicting surgical outcome in frontal lobe epilepsy.

    Science.gov (United States)

    Holtkamp, Martin; Sharan, Ashwini; Sperling, Michael R

    2012-10-01

    Surgery in frontal lobe epilepsy (FLE) has a worse prognosis regarding seizure freedom than anterior lobectomy in temporal lobe epilepsy. The current study aimed to assess whether intracranial interictal and ictal EEG findings in addition to clinical and scalp EEG data help to predict outcome in a series of patients who needed invasive recording for FLE surgery. Patients with FLE who had resective surgery after chronic intracranial EEG recording were included. Outcome predictors were compared in patients with seizure freedom (group 1) and those with recurrent seizures (group 2) at 19-24 months after surgery. Twenty-five patients (16 female) were included in this study. Mean age of patients at epilepsy surgery was 32.3 ± 15.6 years (range 12-70); mean duration of epilepsy was 16.9 ± 13.4 years (range 1-48). In each outcome group, magnetic resonance imaging revealed frontal lobe lesions in three patients. Fifteen patients (60%) were seizure-free (Engel class 1), 10 patients (40%) continued to have seizures (two were class II, three were class III, and five were class IV). Lack of seizure freedom was seen more often in patients with epilepsy surgery on the left frontal lobe (group 1, 13%; group 2, 70%; p = 0.009) and on the dominant (27%; 70%; p = 0.049) hemisphere as well as in patients without aura (29%; 80%; p = 0.036), whereas sex, age at surgery, duration of epilepsy, and presence of an MRI lesion in the frontal lobe or extrafrontal structures were not different between groups. Electroencephalographic characteristics associated with lack of seizure freedom included presence of interictal epileptiform discharges in scalp recordings (31%; 90%; p = 0.01). Detailed analysis of intracranial EEG revealed widespread (>2 cm) (13%; 70%; p = 0.01) in contrast to focal seizure onset as well as shorter latency to onset of seizure spread (5.8 ± 6.1 s; 1.5 ± 2.3 s; p = 0.016) and to ictal involvement of brain structures beyond the frontal lobe (23.5 ± 22.4 s; 5.8 ± 5.4 s

  12. Are alcohol outlet densities strongly associated with alcohol-related outcomes? A critical review of recent evidence.

    Science.gov (United States)

    Gmel, Gerhard; Holmes, John; Studer, Joseph

    2015-06-29

    There have been reviews on the association between density of alcohol outlets and harm including studies published up to December 2008. Since then the number of publications has increased dramatically. The study reviews the more recent studies with regard to their utility to inform policy. A systematic review found more than 160 relevant studies (published between January 2009 and October 2014). The review focused on: (i) outlet density and assaultive or intimate partner violence; (ii) studies including individual level data; or (iii) 'natural experiments'. Despite overall evidence for an association between density and harm, there is little evidence on causal direction (i.e. whether demand leads to more supply or increased availability increases alcohol use and harm). When outlet types (e.g. bars, supermarkets) are analysed separately, studies are too methodologically diverse and partly contradictory to permit firm conclusions besides those pertaining to high outlet densities in areas such as entertainment districts. Outlet density commonly had little effect on individual-level alcohol use, and the few 'natural experiments' on restricting densities showed little or no effects. Although outlet densities are likely to be positively related to alcohol use and harm, few policy recommendations can be given as effects vary across study areas, outlet types and outlet cluster size. Future studies should examine in detail outlet types, compare different outcomes associated with different strengths of association with alcohol, analyse non-linear effects and compare different methodologies. Purely aggregate-level studies examining total outlet density only should be abandoned. [Gmel G, Holmes J, Studer J. Are alcohol outlet densities strongly associated with alcohol-related outcomes? A critical review of recent evidence. Drug Alcohol Rev 2015]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

  13. Predictive Capacity of Cloninger's temperament and character inventory (TCI-R) in alcohol use disorder outcomes.

    Science.gov (United States)

    Ávila Escribano, José Juan; Sánchez Barba, Mercedes; Álvarez Pedrero, Aida; López Villarreal, Ana; Recio Pérez, Joaquina; Rodríguez Rodilla, Manuela; Fraile García, Eulalia

    2016-06-14

    to investigate the ability to predict the outcome of alcohol use disorders through Cloninger's temperament and character inventory (TCI-R). this is a prospective study consisting of 237 outpatients with alcohol use disorders who underwent follow-up treatment for 6 months and whose personality traits were studied using TCI-R. At the end of that period, the scores of each TCI-R trait were analyzed in terms of those who remained in treatment and those who dropped out. The whole group scored highly in novelty seeking (NS) and harm avoidance (HA) and produced low scores in self-directedness (SD), these last traits are considered prominent. The drop-out group scored significantly (p=.004) higher in novelty seeking (NS) than the follow-up group. Also, when the score was higher than the 67 percentile the likelihood of abandoning the treatment was 1.07 times higher. Cloninger's temperament and character inventory is a good instrument to predict the outcome of treatment of patients with alcohol use disorders and the novelty seeking (NS) dimension is strongly related to therapeutic drop-out.

  14. Prediction of strong acceleration motion depended on focal mechanism; Shingen mechanism wo koryoshita jishindo yosoku ni tsuite

    Energy Technology Data Exchange (ETDEWEB)

    Kaneda, Y.; Ejiri, J. [Obayashi Corp., Tokyo (Japan)

    1996-10-01

    This paper describes simulation results of strong acceleration motion with varying uncertain fault parameters mainly for a fault model of Hyogo-ken Nanbu earthquake. For the analysis, based on the fault parameters, the strong acceleration motion was simulated using the radiation patterns and the breaking time difference of composite faults as parameters. A statistic waveform composition method was used for the simulation. For the theoretical radiation patterns, directivity was emphasized which depended on the strike of faults, and the maximum acceleration was more than 220 gal. While, for the homogeneous radiation patterns, the maximum accelerations were isotopically distributed around the fault as a center. For variations in the maximum acceleration and the predominant frequency due to the breaking time difference of three faults, the response spectral value of maximum/minimum was about 1.7 times. From the viewpoint of seismic disaster prevention, underground structures including potential faults and non-arranging properties can be grasped using this simulation. Significance of the prediction of strong acceleration motion was also provided through this simulation using uncertain factors, such as breaking time of composite faults, as parameters. 4 refs., 4 figs., 1 tab.

  15. Strong correlation between the 6-minute walk test and accelerometry functional outcomes in boys with Duchenne muscular dystrophy.

    Science.gov (United States)

    Davidson, Zoe E; Ryan, Monique M; Kornberg, Andrew J; Walker, Karen Z; Truby, Helen

    2015-03-01

    Accelerometry provides information on habitual physical capability that may be of value in the assessment of function in Duchenne muscular dystrophy. This preliminary investigation describes the relationship between community ambulation measured by the StepWatch activity monitor and the current standard of functional assessment, the 6-minute walk test, in ambulatory boys with Duchenne muscular dystrophy (n = 16) and healthy controls (n = 13). All participants completed a 6-minute walk test and wore the StepWatch™ monitor for 5 consecutive days. Both the 6-minute walk test and StepWatch accelerometry identified a decreased capacity for ambulation in boys with Duchenne compared to healthy controls. There were strong, significant correlations between 6-minute walk distance and all StepWatch parameters in affected boys only (r = 0.701-0.804). These data proffer intriguing observations that warrant further exploration. Specifically, accelerometry outcomes may compliment the 6-minute walk test in assessment of therapeutic interventions for Duchenne muscular dystrophy. © The Author(s) 2014.

  16. Nonlocal response functions for predicting shear flow of strongly inhomogeneous fluids. I. Sinusoidally driven shear and sinusoidally driven inhomogeneity.

    Science.gov (United States)

    Glavatskiy, Kirill S; Dalton, Benjamin A; Daivis, Peter J; Todd, B D

    2015-06-01

    We present theoretical expressions for the density, strain rate, and shear pressure profiles in strongly inhomogeneous fluids undergoing steady shear flow with periodic boundary conditions. The expressions that we obtain take the form of truncated functional expansions. In these functional expansions, the independent variables are the spatially sinusoidal longitudinal and transverse forces that we apply in nonequilibrium molecular-dynamics simulations. The longitudinal force produces strong density inhomogeneity, and the transverse force produces sinusoidal shear. The functional expansions define new material properties, the response functions, which characterize the system's nonlocal response to the longitudinal force and the transverse force. We find that the sinusoidal longitudinal force, which is mainly responsible for the generation of density inhomogeneity, also modulates the strain rate and shear pressure profiles. Likewise, we find that the sinusoidal transverse force, which is mainly responsible for the generation of sinusoidal shear flow, can also modify the density. These cross couplings between density inhomogeneity and shear flow are also characterized by nonlocal response functions. We conduct nonequilibrium molecular-dynamics simulations to calculate all of the response functions needed to describe the response of the system for weak shear flow in the presence of strong density inhomogeneity up to the third order in the functional expansion. The response functions are then substituted directly into the truncated functional expansions and used to predict the density, velocity, and shear pressure profiles. The results are compared to the directly evaluated profiles from molecular-dynamics simulations, and we find that the predicted profiles from the truncated functional expansions are in excellent agreement with the directly computed density, velocity, and shear pressure profiles.

  17. Nonlocal response functions for predicting shear flow of strongly inhomogeneous fluids. I. Sinusoidally driven shear and sinusoidally driven inhomogeneity

    Science.gov (United States)

    Glavatskiy, Kirill S.; Dalton, Benjamin A.; Daivis, Peter J.; Todd, B. D.

    2015-06-01

    We present theoretical expressions for the density, strain rate, and shear pressure profiles in strongly inhomogeneous fluids undergoing steady shear flow with periodic boundary conditions. The expressions that we obtain take the form of truncated functional expansions. In these functional expansions, the independent variables are the spatially sinusoidal longitudinal and transverse forces that we apply in nonequilibrium molecular-dynamics simulations. The longitudinal force produces strong density inhomogeneity, and the transverse force produces sinusoidal shear. The functional expansions define new material properties, the response functions, which characterize the system's nonlocal response to the longitudinal force and the transverse force. We find that the sinusoidal longitudinal force, which is mainly responsible for the generation of density inhomogeneity, also modulates the strain rate and shear pressure profiles. Likewise, we find that the sinusoidal transverse force, which is mainly responsible for the generation of sinusoidal shear flow, can also modify the density. These cross couplings between density inhomogeneity and shear flow are also characterized by nonlocal response functions. We conduct nonequilibrium molecular-dynamics simulations to calculate all of the response functions needed to describe the response of the system for weak shear flow in the presence of strong density inhomogeneity up to the third order in the functional expansion. The response functions are then substituted directly into the truncated functional expansions and used to predict the density, velocity, and shear pressure profiles. The results are compared to the directly evaluated profiles from molecular-dynamics simulations, and we find that the predicted profiles from the truncated functional expansions are in excellent agreement with the directly computed density, velocity, and shear pressure profiles.

  18. Strong ground motion prediction applying dynamic rupture simulations for Beppu-Haneyama Active Fault Zone, southwestern Japan

    Science.gov (United States)

    Yoshimi, M.; Matsushima, S.; Ando, R.; Miyake, H.; Imanishi, K.; Hayashida, T.; Takenaka, H.; Suzuki, H.; Matsuyama, H.

    2017-12-01

    We conducted strong ground motion prediction for the active Beppu-Haneyama Fault zone (BHFZ), Kyushu island, southwestern Japan. Since the BHFZ runs through Oita and Beppy cities, strong ground motion as well as fault displacement may affect much to the cities.We constructed a 3-dimensional velocity structure of a sedimentary basin, Beppu bay basin, where the fault zone runs through and Oita and Beppu cities are located. Minimum shear wave velocity of the 3d model is 500 m/s. Additional 1-d structure is modeled for sites with softer sediment: holocene plain area. We observed, collected, and compiled data obtained from microtremor surveys, ground motion observations, boreholes etc. phase velocity and H/V ratio. Finer structure of the Oita Plain is modeled, as 250m-mesh model, with empirical relation among N-value, lithology, depth and Vs, using borehole data, then validated with the phase velocity data obtained by the dense microtremor array observation (Yoshimi et al., 2016).Synthetic ground motion has been calculated with a hybrid technique composed of a stochastic Green's function method (for HF wave), a 3D finite difference (LF wave) and 1D amplification calculation. Fault geometry has been determined based on reflection surveys and active fault map. The rake angles are calculated with a dynamic rupture simulation considering three fault segments under a stress filed estimated from source mechanism of earthquakes around the faults (Ando et al., JpGU-AGU2017). Fault parameters such as the average stress drop, a size of asperity etc. are determined based on an empirical relation proposed by Irikura and Miyake (2001). As a result, strong ground motion stronger than 100 cm/s is predicted in the hanging wall side of the Oita plain.This work is supported by the Comprehensive Research on the Beppu-Haneyama Fault Zone funded by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

  19. Empirical equations for the prediction of PGA and pseudo spectral accelerations using Iranian strong-motion data

    Science.gov (United States)

    Zafarani, H.; Luzi, Lucia; Lanzano, Giovanni; Soghrat, M. R.

    2018-01-01

    A recently compiled, comprehensive, and good-quality strong-motion database of the Iranian earthquakes has been used to develop local empirical equations for the prediction of peak ground acceleration (PGA) and 5%-damped pseudo-spectral accelerations (PSA) up to 4.0 s. The equations account for style of faulting and four site classes and use the horizontal distance from the surface projection of the rupture plane as a distance measure. The model predicts the geometric mean of horizontal components and the vertical-to-horizontal ratio. A total of 1551 free-field acceleration time histories recorded at distances of up to 200 km from 200 shallow earthquakes (depth regression analysis using the random effects algorithm of Abrahamson and Youngs (Bull Seism Soc Am 82:505-510, 1992), which considers between-events as well as within-events errors. Due to the limited data used in the development of previous Iranian ground motion prediction equations (GMPEs) and strong trade-offs between different terms of GMPEs, it is likely that the previously determined models might have less precision on their coefficients in comparison to the current study. The richer database of the current study allows improving on prior works by considering additional variables that could not previously be adequately constrained. Here, a functional form used by Boore and Atkinson (Earthquake Spect 24:99-138, 2008) and Bindi et al. (Bull Seism Soc Am 9:1899-1920, 2011) has been adopted that allows accounting for the saturation of ground motions at close distances. A regression has been also performed for the V/H in order to retrieve vertical components by scaling horizontal spectra. In order to take into account epistemic uncertainty, the new model can be used along with other appropriate GMPEs through a logic tree framework for seismic hazard assessment in Iran and Middle East region.

  20. Self-Conscious Shyness: Growth during Toddlerhood, Strong Role of Genetics, and No Prediction from Fearful Shyness.

    Science.gov (United States)

    Eggum-Wilkens, Natalie D; Lemery-Chalfant, Kathryn; Aksan, Nazan; Goldsmith, H Hill

    2015-01-01

    Fearful and self-conscious subtypes of shyness have received little attention in the empirical literature. Study aims included: 1) determining if fearful shyness predicted self-conscious shyness, 2) describing development of self-conscious shyness, and 3) examining genetic and environmental contributions to fearful and self-conscious shyness. Observed self-conscious shyness was examined at 19, 22, 25, and 28 months in same-sex twins (MZ = 102, DZ = 111, missing zygosity = 3 pairs). Self-conscious shyness increased across toddlerhood, but onset was earlier than predicted by theory. Fearful shyness (observed [6 and 12 months] and parents' reports [12 and 22 months]) was not predictive of self-conscious shyness. Independent genetic factors made strong contributions to parent-reported (but not observed) fearful shyness (additive genetic influence = .69 and .72 at 12 and 22 months, respectively) and self-conscious shyness (additive genetic influence = .90 for the growth model intercept). Results encourage future investigation of patterns of change and interrelations in shyness subtypes.

  1. Predictive Modeling for Strongly Correlated f-electron Systems: A first-principles and database driven machine learning approach

    Science.gov (United States)

    Ahmed, Towfiq; Khair, Adnan; Abdullah, Mueen; Harper, Heike; Eriksson, Olle; Wills, John; Zhu, Jian-Xin; Balatsky, Alexander

    Data driven computational tools are being developed for theoretical understanding of electronic properties in f-electron based materials, e.g., Lanthanides and Actnides compounds. Here we show our preliminary work on Ce compounds. Due to a complex interplay among the hybridization of f-electrons to non-interacting conduction band, spin-orbit coupling, and strong coulomb repulsion of f-electrons, no model or first-principles based theory can fully explain all the structural and functional phases of f-electron systems. Motivated by the large need in predictive modeling of actinide compounds, we adopted a data-driven approach. We found negative correlation between the hybridization and atomic volume. Mutual information between these two features were also investigated. In order to extend our search space with more features and predictability of new compounds, we are currently developing electronic structure database. Our f-electron database will be potentially aided by machine learning (ML) algorithm to extract complex electronic, magnetic and structural properties in f-electron system, and thus, will open up new pathways for predictive capabilities and design principles of complex materials. NSEC, IMS at LANL.

  2. Predicting long-term recovery of a strongly acidified stream using MAGIC and climate models (Litavka, Czech Republic

    Directory of Open Access Journals (Sweden)

    D. W. Hardekopf

    2008-03-01

    Full Text Available Two branches forming the headwaters of a stream in the Czech Republic were studied. Both streams have similar catchment characteristics and historical deposition; however one is rain-fed and strongly affected by acid atmospheric deposition, the other spring-fed and only moderately acidified. The MAGIC model was used to reconstruct past stream water and soil chemistry of the rain-fed branch, and predict future recovery up to 2050 under current proposed emissions levels. A future increase in air temperature calculated by a regional climate model was then used to derive climate-related scenarios to test possible factors affecting chemical recovery up to 2100. Macroinvertebrates were sampled from both branches, and differences in stream chemistry were reflected in the community structures. According to modelled forecasts, recovery of the rain-fed branch will be gradual and limited, and continued high levels of sulphate release from the soils will continue to dominate stream water chemistry, while scenarios related to a predicted increase in temperature will have little impact. The likelihood of colonization of species from the spring-fed branch was evaluated considering the predicted extent of chemical recovery. The results suggest that the possibility of colonization of species from the spring-fed branch to the rain-fed will be limited to only the acid-tolerant stonefly, caddisfly and dipteran taxa in the modelled period.

  3. Predicting Community College Outcomes: Does High School CTE Participation Have a Significant Effect?

    Science.gov (United States)

    Dietrich, Cecile; Lichtenberger, Eric; Kamalludeen, Rosemaliza

    2016-01-01

    This study explored the relative importance of participation in high school career and technical education (CTE) programs in predicting community college outcomes. A hierarchical generalized linear model (HGLM) was used to predict community college outcome attainment among a random sample of direct community college entrants. Results show that…

  4. An evolution of trauma care evaluation: A thesis on trauma registry and outcome prediction models

    NARCIS (Netherlands)

    Joosse, P.

    2013-01-01

    Outcome prediction models play an invaluable role in the evaluation and improvement of modern trauma care. Trauma registries underlying these outcome prediction models need to be accurate, complete and consistent. This thesis focused on the opportunities and limitations of trauma registries and

  5. Predicting outcome from coma : man-in-the-barrel syndrome as potential pitfall

    NARCIS (Netherlands)

    Elting, JW; Haaxma, R; De Keyser, J; Sulter, G.

    The Glasgow coma scale motor score is often used in predicting outcome after hypoxic ischemic coma. Judicious care should be exerted when using this variable in predicting outcome in patients with coma following hypotension since borderzone infarction can obscure the clinical picture. We describe a

  6. FERAL : Network-based classifier with application to breast cancer outcome prediction

    NARCIS (Netherlands)

    Allahyar, A.; De Ridder, J.

    2015-01-01

    Motivation: Breast cancer outcome prediction based on gene expression profiles is an important strategy for personalize patient care. To improve performance and consistency of discovered markers of the initial molecular classifiers, network-based outcome prediction methods (NOPs) have been proposed.

  7. Predicting Adolescent Drug Abuse Treatment Outcome with the Personal Experience Inventory (PEI)

    Science.gov (United States)

    Stinchfield, Randy; Winters, Ken C.

    2004-01-01

    The purposes of this study were to examine the clinical utility of the Personal Experience Inventory (PEI) Psychosocial scales to predict adolescent drug abuse treatment outcome. The role of psychosocial risk factors in predicting treatment outcome also has theoretical interest given that such factors have been associated with the development of…

  8. Comparison of hysterosalpingography and laparoscopy in predicting fertility outcome

    NARCIS (Netherlands)

    Mol, B. W.; Collins, J. A.; Burrows, E. A.; van der Veen, F.; Bossuyt, P. M.

    1999-01-01

    In this study, we compare the prognostic significance of hysterosalpingography (HSG) and laparoscopy for fertility outcome. In a prospective cohort study in 11 clinics participating in the Canadian Infertility Treatment Evaluation Study (CITES), consecutive couples who registered between 1 April

  9. Cast index in predicting outcome of proximal pediatric forearm fractures

    Directory of Open Access Journals (Sweden)

    Hassaan Qaiser Sheikh

    2015-01-01

    Conclusion: Cast index is useful in predicting redisplacement of manipulated distal forearm fractures. We found that in proximal half forearm fractures it is difficult to achieve a CI of <0.8, but increased CI does not predict loss of position in these fractures. We therefore discourage the use of CI in proximal half forearm fractures.

  10. Predicting The Outcome of Marketing Negotiations: Role-Playing versus Unaided Opinions

    OpenAIRE

    JS Armstrong; Philip D. Hutcherson

    2005-01-01

    Role -playing and unaided opinions were used to forecast the outcome of three negotiations. Consistent with prior re search, role-playing yielded more accurate predictions. In two studies on marketing negotiations, the predictions based on role-playing were correct for 53% of the predictions while unaided opinions were correct for only 7% (p

  11. Comparison of Two Embryo Scoring Systems for Prediction of Outcome in Assisted Reproductive Techniques Cycles

    Directory of Open Access Journals (Sweden)

    Navid Fotoohi Ghiam

    2011-12-01

    Full Text Available Cumulative embryo score (CES is one of the many embryo scoring methods which have been developed to help clinicians to transfer high quality embryos and predict pregnancy rate in assisted reproductive techniques (ART cycles. Regarding the existing difference in CES calculation this study was done to compare two methods in order to determine the more practical and preferable one. In a retrospective, cross sectional descriptive analytical study, a total of 508 ART cycles in infertile patients treated from November 2002 until March 2004, were evaluated using two methods of CES calculation in embryonic scoring to predict ART outcome. According to one method, CES was obtained by adding the individual scores of all transferred embryos. Whereas in the other reference method, CES was calculated by the sum of each embryo score multiplied by its number of blastomeres on the day of transfer. The mean score of transferred embryos (MSTE was referred to CES divided by the total number of embryos transferred in either method. A total of 109 clinical pregnancies (pregnancy rate 21.5% including 96 singletons, 10 twins and triplets occurred in the 508 ART cycles. The pregnancy rate was strongly correlated to CES & MSTE. According to one method, CES was 12.6±6.4 in pregnant versus 9.2±5.8 in non-pregnant group (P<0.0001. According to the other one, in the pregnant group CES was 86.7±48 versus 68.7±55 in the non-pregnant group (P<0.002. Both methods showed a significant difference. Regarding MSTE, using the first method, in the pregnant group it was 3±0.6 versus 2.8±0.7 in the non-pregnant group (P<0.011 whereas with the other approach it was 21.3±8.6 in the pregnant group versus 19.9±9.07 in non-pregnant (P<0.152 showing that the first method can also predict pregnancy outcome with MSTE. Considering that both MSTE and CES in the first method can significantly predict outcome in ART cycles, it seems this method is preferable and more useful in practice

  12. Predicting outcome in clinically isolated syndrome using machine learning

    Directory of Open Access Journals (Sweden)

    V. Wottschel

    2015-01-01

    Machine-learning-based classifications can be used to provide an “individualised” prediction of conversion to MS from subjects' baseline scans and clinical characteristics, with potential to be incorporated into routine clinical practice.

  13. Revolutionizing Toxicity Testing For Predicting Developmental Outcomes (DNT4)

    Science.gov (United States)

    Characterizing risk from environmental chemical exposure currently requires extensive animal testing; however, alternative approaches are being researched to increase throughput of chemicals screened, decrease reliance on animal testing, and improve accuracy in predicting adverse...

  14. Acoustic parameters of snoring sound to assess the effectiveness of sleep nasendoscopy in predicting surgical outcome.

    Science.gov (United States)

    Jones, Terry M; Walker, Paul; Ho, Meau-Shin; Earis, John E; Swift, Andrew C; Charters, Peter

    2006-08-01

    To assess the effectiveness of two grading systems used to predict surgical outcome in nonapneic snorers. A prospective observational study. Prior to undergoing palatal surgery, 20 patients completed a sleep nasendoscopic examination involving sequential steady-state sedation with intravenous propofol. Using a combination of acoustic parameters of snoring sound as an objective outcome measurement, and the answers to a specifically designed questionnaire as a subjective outcome measurement, the effectiveness of each grading system in predicting surgical outcome was examined. Depending on the outcome measurement used, sensitivity in predicting success of surgery for snoring varied from 16.7% to 50.0% and specificity from 38.5% to 62.5% for the Pringle and Croft system, while sensitivity varied from 91.7% to 100% and specificity from 30.8% to 31.5% for the Camilleri system. Sleep nasendoscopy using these classifications cannot be recommended as a reliable predictor of surgical outcome in nonapneic snorers. C-4.

  15. Professor-Student Rapport Scale: Six Items Predict Student Outcomes

    Science.gov (United States)

    Wilson, Janie H.; Ryan, Rebecca G.

    2013-01-01

    Rapport between students and teachers leads to numerous positive student outcomes, including attitudes toward the teacher and course, student motivation, and perceived learning. The recent development of a Professor-Student Rapport scale offers assessment of this construct. However, a Cronbach's [alpha] of 0.96 indicated item redundancy, and the…

  16. Using the Revised Trauma Score to Predict Outcome in Severely ...

    African Journals Online (AJOL)

    Conclusion: The results in this study revealed that though the weighted RTS was effective in determining mortality outcome in head injured patients, the mortality rate in this study was high because of delayed transfer of patients due to poor ambulance services, associated cervical spine injuries and gunshot injuries to the ...

  17. Outcome prediction in gastroschisis - The gastroschisis prognostic score (GPS) revisited.

    Science.gov (United States)

    Puligandla, Pramod S; Baird, Robert; Skarsgard, Eric D; Emil, Sherif; Laberge, Jean-Martin

    2017-05-01

    The GPS enables risk stratification for gastroschisis and helps discriminate low from high morbidity groups. The purpose of this study was to revalidate GPS's characterization of a high morbidity group and to quantify relationships between the GPS and outcomes. With REB approval, complete survivor data from a national gastroschisis registry was collected. GPS bowel injury scoring was revalidated excluding the initial inception/validation cohorts (>2011). Length of stay (LOS), 1st enteral feed days (dFPO), TPN days (dTPN), and aggregate complications (COMP) were compared between low and high morbidity risk groups. Mathematical relationships between outcomes and integer increases in GPS were explored using the entire cohort (2005-present). Median (range) LOS, dPO, and dTPN for the entire cohort (n=849) was 36 (26,62), 13 (9,18), and 27 (20,46) days, respectively. High-risk patients (GPS≥2; n=80) experienced significantly worse outcomes than low risk patients (n=263). Each integer increase in GPS was associated with increases in LOS and dTPN by 16.9 and 12.7days, respectively (pGPS effectively discriminates low from high morbidity risk groups. Within the high risk group, integer increases in GPS produce quantitatively differentiated outcomes which may guide initial counseling and resource allocation. IIb. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Module-Based Outcome Prediction Using Breast Cancer Compendia

    NARCIS (Netherlands)

    Van Vliet, M.H.; Klijn, C.N.; Wessels, L.F.; Reinders, M.J.T.

    2007-01-01

    Background. The availability of large collections of microarray datasets (compendia), or knowledge about grouping of genes into pathways (gene sets), is typically not exploited when training predictors of disease outcome. These can be useful since a compendium increases the number of samples, while

  19. Outcome Prediction of Neonatal Hypoxic-Ischemic Encephalopathy

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2006-12-01

    Full Text Available Data for 205 neonates from the multicenter National Institute of Child Health trial of hypothermia in hypoxic-ischemic encephalopathy (HIE were analyzed by using clinical and laboratory variables obtained in the NICUs within 6 hours of birth, with death or moderate/severe disability at 18-22 months or death as the outcomes.

  20. How much will the sea level rise? Outcome selection and subjective probability in climate change predictions.

    Science.gov (United States)

    Juanchich, Marie; Sirota, Miroslav

    2017-12-01

    We tested whether people focus on extreme outcomes to predict climate change and assessed the gap between the frequency of the predicted outcome and its perceived probability while controlling for climate change beliefs. We also tested 2 cost-effective interventions to reduce the preference for extreme outcomes and the frequency-probability gap by manipulating the probabilistic format: numerical or dual-verbal-numerical. In 4 experiments, participants read a scenario featuring a distribution of sea level rises, selected a sea rise to complete a prediction (e.g., "It is 'unlikely' that the sea level will rise . . . inches") and judged the likelihood of this sea rise occurring. Results showed that people have a preference for predicting extreme climate change outcomes in verbal predictions (59% in Experiments 1-4) and that this preference was not predicted by climate change beliefs. Results also showed an important gap between the predicted outcome frequency and participants' perception of the probability that it would occur. The dual-format reduced the preference for extreme outcomes for low and medium probability predictions but not for high ones, and none of the formats consistently reduced the frequency-probability gap. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  1. Leptomeningeal collateral status predicts outcome after middle cerebral artery occlusion

    DEFF Research Database (Denmark)

    Madelung, Christopher Fugl; Ovesen, C; Trampedach, C

    2017-01-01

    OBJECTIVES: Perfusion through leptomeningeal collateral vessels is a likely pivotal factor in the outcome of stroke patients. We aimed to investigate the effect of collateral status on outcome in a cohort of unselected, consecutive stroke patients with middle cerebral artery occlusion undergoing...... thrombectomy alone (N = 5), or both (N = 56) from May 2009 to April 2014. Non-contrast CT (NCCT) and computed tomography angiography (CTA) were provided on admission and NCCT repeated at 24 hours. Collateral status was assessed based on the initial CTA. Hemorrhagic transformation was evaluated on the 24-hour...... NCCT and according to European Cooperative Acute Stroke Study (ECASS) criteria. Modified Rankin Scale score was assessed at 90 days, and mortality at 1 year. RESULTS: At 90 days, median (IQR) modified Rankin Scale score in patients with poor collateral status was 4 (3-6) compared to 2 (1-4) in patients...

  2. Cord Blood DNA Methylation Biomarkers for Predicting Neurodevelopmental Outcomes

    Directory of Open Access Journals (Sweden)

    Nicolette A. Hodyl

    2016-12-01

    Full Text Available Adverse environmental exposures in pregnancy can significantly alter the development of the fetus resulting in impaired child neurodevelopment. Such exposures can lead to epigenetic alterations like DNA methylation, which may be a marker of poor cognitive, motor and behavioral outcomes in the infant. Here we review studies that have assessed DNA methylation in cord blood following maternal exposures that may impact neurodevelopment of the child. We also highlight some key studies to illustrate the potential for DNA methylation to successfully identify infants at risk for poor outcomes. While the current evidence is limited, in that observations to date are largely correlational, in time and with larger cohorts analyzed and longer term follow-up completed, we may be able to develop epigenetic biomarkers that not only indicate adverse early life exposures but can also be used to identify individuals likely to be at an increased risk of impaired neurodevelopment even in the absence of detailed information regarding prenatal environment.

  3. Predicting Later Language Outcomes from the Language Use Inventory

    Science.gov (United States)

    Pesco, Diane; O'Neill, Daniela K.

    2012-01-01

    Purpose: To examine the predictive validity of the Language Use Inventory (LUI), a parent report of language use by children 18-47 months old (O'Neill, 2009). Method: 348 children whose parents had completed the LUI were reassessed at 5-6 years old with standardized, norm-referenced language measures and parent report of developmental history. The…

  4. Nomogram for predicting the probability of the positive outcome of ...

    African Journals Online (AJOL)

    F.A. Yeboah

    Abstract. Introduction and objectives: Several existing models have been developed to predict positive prostate biopsy among men undergoing evaluation for prostate cancer (PCa). However, most of these models have come from industrialized countries. We therefore, developed a prostate disease nomogram model to ...

  5. Abdominal compartment syndrome in trauma patients: New insights for predicting outcomes

    Directory of Open Access Journals (Sweden)

    Aisha W Shaheen

    2016-01-01

    Full Text Available Context: Abdominal compartment syndrome (ACS is associated with high morbidity and mortality among trauma patients. Several clinical and laboratory findings have been suggested as markers for ACS, and these may point to different types of ACS and complications. Aims: This study aims to identify the strength of association of clinical and laboratory variables with specific adverse outcomes in trauma patients with ACS. Settings and Design: A 5-year retrospective chart review was conducted at three Level I Trauma Centers in the City of Chicago, IL, USA. Subjects and Methods:A complete set of demographic, pre-, intra- and post-operative variables were collected from 28 patient charts. Statistical Analysis:Pearson's correlation coefficient was used to determine the strength of association between 29 studied variables and eight end outcomes. Results: Thirty-day mortality was associated strongly with the finding of an initial intra-abdominal pressure >20 mmHg and moderately with blunt injury mechanism. A lactic acid >5 mmol/L on admission was moderately associated with increased blood transfusion requirements and with acute renal failure during the hospitalization. Developing ACS within 48 h of admission was moderately associated with increased length of stay in the Intensive Care Unit (ICU, more ventilator days, and longer hospital stay. Initial operative intervention lasting more than 2 h was moderately associated with risk of developing multi-organ failure. Hemoglobin level 7 days were moderately associated with a disposition to long-term support facility. Conclusions: Clinical and lab variables can predict specific adverse outcomes in trauma patients with ACS. These findings may be used to guide patient management, improve resource utilization, and build capacity within trauma centers.

  6. Predicting Low Back Pain Outcomes: Suggestions for Future Directions.

    Science.gov (United States)

    Boissoneault, Jeff; Mundt, Jennifer; Robinson, Michael; George, Steven Z

    2017-09-01

    Chronic low back pain (LBP) is a common and costly musculoskeletal pain condition, and effective treatment of LBP represents a significant goal of physical therapists. Establishing a targeted track of treatment for patients with LBP at high risk for chronicity that is focused on modifiable prognostic factors could have significant personal and societal benefit. Such an approach would require that clinicians accurately predict the patients who are at an elevated risk of developing chronic LBP in the early stages of the condition. In this Viewpoint, we consider the strengths and limitations of existing literature and propose suggestions that may lead to the development of parsimonious, cost-effective, and accurate predictive models of LBP chronicity. J Orthop Sports Phys Ther 2017;47(9):588-592. doi:10.2519/jospt.2017.0607.

  7. Prediction of stroke thrombolysis outcome using CT brain machine learning

    Directory of Open Access Journals (Sweden)

    Paul Bentley

    2014-01-01

    Full Text Available A critical decision-step in the emergency treatment of ischemic stroke is whether or not to administer thrombolysis — a treatment that can result in good recovery, or deterioration due to symptomatic intracranial haemorrhage (SICH. Certain imaging features based upon early computerized tomography (CT, in combination with clinical variables, have been found to predict SICH, albeit with modest accuracy. In this proof-of-concept study, we determine whether machine learning of CT images can predict which patients receiving tPA will develop SICH as opposed to showing clinical improvement with no haemorrhage. Clinical records and CT brains of 116 acute ischemic stroke patients treated with intravenous thrombolysis were collected retrospectively (including 16 who developed SICH. The sample was split into training (n = 106 and test sets (n = 10, repeatedly for 1760 different combinations. CT brain images acted as inputs into a support vector machine (SVM, along with clinical severity. Performance of the SVM was compared with established prognostication tools (SEDAN and HAT scores; original, or after adaptation to our cohort. Predictive performance, assessed as area under receiver-operating-characteristic curve (AUC, of the SVM (0.744 compared favourably with that of prognostic scores (original and adapted versions: 0.626–0.720; p < 0.01. The SVM also identified 9 out of 16 SICHs, as opposed to 1–5 using prognostic scores, assuming a 10% SICH frequency (p < 0.001. In summary, machine learning methods applied to acute stroke CT images offer automation, and potentially improved performance, for prediction of SICH following thrombolysis. Larger-scale cohorts, and incorporation of advanced imaging, should be tested with such methods.

  8. Extinction reveals that primary sensory cortex predicts reinforcement outcome.

    Science.gov (United States)

    Bieszczad, Kasia M; Weinberger, Norman M

    2012-02-01

    Primary sensory cortices are traditionally regarded as stimulus analysers. However, studies of associative learning-induced plasticity in the primary auditory cortex (A1) indicate involvement in learning, memory and other cognitive processes. For example, the area of representation of a tone becomes larger for stronger auditory memories and the magnitude of area gain is proportional to the degree that a tone becomes behaviorally important. Here, we used extinction to investigate whether 'behavioral importance' specifically reflects a sound's ability to predict reinforcement (reward or punishment) vs. to predict any significant change in the meaning of a sound. If the former, then extinction should reverse area gains as the signal no longer predicts reinforcement. Rats (n = 11) were trained to bar-press to a signal tone (5.0 kHz) for water-rewards, to induce signal-specific area gains in A1. After subsequent withdrawal of reward, A1 was mapped to determine representational areas. Signal-specific area gains, estimated from a previously established brain-behavior quantitative function, were reversed, supporting the 'reinforcement prediction' hypothesis. Area loss was specific to the signal tone vs. test tones, further indicating that withdrawal of reinforcement, rather than unreinforced tone presentation per se, was responsible for area loss. Importantly, the amount of area loss was correlated with the amount of extinction (r = 0.82, P reinforcement, and that the number of cells tuned to a stimulus can dictate its ability to command behavior. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  9. Predicting outcome in melanoma: where are we now?

    LENUS (Irish Health Repository)

    Jennings, L

    2009-09-01

    Melanoma incidence continues to rise in most countries. This is of grave concern, given the mortality rate in a relatively young population. Current staging tools are limited in their ability to predict accurately those at risk of metastatic disease, relapse and treatment failure. This overview comprehensively reviews relevant literature, with the focus on the last 5 years, and discusses the current state of traditional and emerging novel methods of staging for melanoma and their effect on prognosis in this population.

  10. Ruptured corpus luteal cyst: Prediction of clinical outcomes with CT

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Myoung Seok; Moon, Min Hoan; Woo, Hyun Sik; Sung, Chang Kyu; Jeon, Hye Won; Lee, Taek Sang [SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul (Korea, Republic of)

    2017-08-01

    To evaluate the determinant pretreatment CT findings that can predict surgical intervention for patients suffering from corpus luteal cyst rupture with hemoperitoneum. From January 2009 to December 2014, a total of 106 female patients (mean age, 26.1 years; range, 17–44 years) who visited the emergency room of our institute for acute abdominal pain and were subsequently diagnosed with ruptured corpus luteal cyst with hemoperitoneum were included in the retrospective study. The analysis of CT findings included cyst size, cyst shape, sentinel clot sign, ring of fire sign, hemoperitoneum depth, active bleeding in portal phase and attenuation of hemoperitoneum. The comparison of CT findings between the surgery and conservative management groups was performed with the Mann-Whitney U test or chi-square test. Logistic regression analysis was used to determine significant CT findings in predicting surgical intervention for a ruptured cyst. Comparative analysis revealed that the presence of active bleeding and the hemoperitoneum depth were significantly different between the surgery and conservative management groups and were confirmed as significant CT findings for predicting surgery, with adjusted odds ratio (ORs) of 3.773 and 1.318, respectively (p < 0.01). On the receiver-operating characteristic curve analysis for hemoperitoneum depth, the optimal cut-off value was 5.8 cm with 73.7% sensitivity and 58.6% specificity (Az = 0.711, p = 0.004). In cases with a hemoperitoneum depth > 5.8 cm and concurrent active bleeding, the OR for surgery increased to 5.786. The presence of active bleeding and the hemoperitoneum depth on a pretreatment CT scan can be predictive warning signs of surgery for a patient with a ruptured corpus luteal cyst with hemoperitoneum.

  11. Hamsi scoring in the prediction of unfavorable outcomes from tuberculous meningitis

    DEFF Research Database (Denmark)

    Erdem, Hakan; Ozturk-Engin, Derya; Tireli, Hulya

    2015-01-01

    Predicting unfavorable outcome is of paramount importance in clinical decision making. Accordingly, we designed this multinational study, which provided the largest case series of tuberculous meningitis (TBM). 43 centers from 14 countries (Albania, Croatia, Denmark, Egypt, France, Hungary, Iraq, ...

  12. Predicting mobility outcome in lower limb amputees with motor ability tests used in early rehabilitation

    NARCIS (Netherlands)

    Spaan, Matthijs H; Vrieling, Aline H; van de Berg, Pim; Dijkstra, Pieter U; van Keeken, Helco G

    STUDY DESIGN: Retrospective cohort study. BACKGROUND: Persons with a lower limb amputation can regain mobility using a prosthetic device. For fast and adequate prescription of prosthetic components, it is necessary to predict the mobility outcome early in rehabilitation. Currently, prosthetic

  13. Predicting Extubation Outcome by Cough Peak Flow Measured Using a Built-in Ventilator Flow Meter.

    Science.gov (United States)

    Gobert, Florent; Yonis, Hodane; Tapponnier, Romain; Fernandez, Raul; Labaune, Marie-Aude; Burle, Jean-François; Barbier, Jack; Vincent, Bernard; Cleyet, Maria; Richard, Jean-Christophe; Guérin, Claude

    2017-12-01

    Successful weaning from mechanical ventilation depends on the patient's ability to cough efficiently. Cough peak flow (CPF) could predict extubation success using a dedicated flow meter but required patient disconnection. We aimed to predict extubation outcome using an overall model, including cough performance assessed by a ventilator flow meter. This was a prospective observational study conducted from November 2014 to October 2015. Before and after a spontaneous breathing trial, subjects were encouraged to cough as strongly as possible before freezing the ventilator screen to assess CPF and tidal volume (V T ) in the preceding inspiration. Early extubation success rate was defined as the proportion of subjects not re-intubated 48 h after extubation. Diagnostic performance of CPF and V T was assessed by using the area under the curve of the receiver operating characteristic curve. Cut-off values for CPF and V T were defined according to median values and used to describe the performance of a predictive test combining them with risk factors of early extubation failure. Among 673 subjects admitted, 92 had a cough assessment before extubation. For the 81 subjects with early extubation success, the median CPF was -67.7 L/min, and median V T was 0.646 L. For the 11 subjects with early extubation failure, the median CPF was -57.3 L/min, and median V T was 0.448 L. Area under the curve was 0.61 (95% CI 0.37-0.83) for CPF and 0.64 (95% CI 0.42-0.84) for CPF/V T combined. After dichotomization (CPF 0.55 L), there was a synergistic effect to predict early extubation success ( P pH before extubation meter of an ICU ventilator was able to predict extubation success and to build a composite score to predict extubation failure. The results were close to that found in previous studies that used a dedicated flow meter. This could help to identify high-risk subjects to prevent extubation failure. (ClinicalTrials.gov registration NCT02847221.). Copyright © 2017 by Daedalus

  14. Prediction of surgical outcome in compressive cervical myelopathy: A novel clinicoradiological prognostic score

    Directory of Open Access Journals (Sweden)

    Rishi Anil Aggarwal

    2016-01-01

    Full Text Available Context: Preoperative severity of myelopathy, age, and duration of symptoms have been shown to be highly predictive of the outcome in compressive cervical myelopathy (CCM. The role of radiological parameters is still controversial. Aims: Define the prognostic factors in CCM and formulate a prognostic score to predict the outcome following surgery in CCM. Settings and Design: Retrospective. Materials and Methods: This study included 78 consecutive patients with CCM treated surgically. The modified Japanese Orthopaedic Association (mJOA scale was used to quantify severity of myelopathy at admission and at 12-month follow-up. The outcome was defined as "good" if the patient had mJOA score ≥16 and "poor" if the score was <16. Age, sex, duration of symptoms, comorbidities, intrinsic hand muscle wasting (IHMW, diagnosis, surgical technique, Torg ratio, instability on dynamic radiographs, and magnetic resonance imaging (MRI signal intensity changes were assessed. Statistics: Statistical Package for the Social Sciences (SPSS (version 20.0 was used for statistical analysis. The association was assessed amongst variables using logistic regression analysis. Parameters having a statistically significant correlation with the outcome were included in formulating a prognostic score. Results: Severity of myelopathy, IHMW, age, duration, diabetes, and instability on radiographs were predictive of the outcome with a P value <0.01. Genders, diagnosis, surgical procedure, Torg ratio, and intensity changes on MRI were not significantly related to the outcome. A 8-point scoring system was devised incorporating the significant clinicoradiological parameters, and it was found that nearly all patients (97.82% with a score below 5 had good outcome and all patients (100% with a score above 5 had poor outcome. The outcome is difficult to predict with a score of 5. Conclusions: Clinical parameters are better predictors of the outcome as compared to radiological findings

  15. An index predictive of cognitive outcome in retired professional American Football players with a history of sports concussion.

    Science.gov (United States)

    Wright, Mathew J; Woo, Ellen; Birath, J Brandon; Siders, Craig A; Kelly, Daniel F; Wang, Christina; Swerdloff, Ronald; Romero, Elizabeth; Kernan, Claudia; Cantu, Robert C; Guskiewicz, Kevin

    2016-01-01

    Various concussion characteristics and personal factors are associated with cognitive recovery in athletes. We developed an index based on concussion frequency, severity, and timeframe, as well as cognitive reserve (CR), and we assessed its predictive power regarding cognitive ability in retired professional football players. Data from 40 retired professional American football players were used in the current study. On average, participants had been retired from football for 20 years. Current neuropsychological performances, indicators of CR, concussion history, and play data were used to create an index for predicting cognitive outcome. The sample displayed a range of concussions, concussion severities, seasons played, CR, and cognitive ability. Many of the participants demonstrated cognitive deficits. The index strongly predicted global cognitive ability (R(2) = .31). The index also predicted the number of areas of neuropsychological deficit, which varied as a function of the deficit classification system used (Heaton: R(2) = .15; Wechsler: R(2) = .28). The current study demonstrated that a unique combination of CR, sports concussion, and game-related data can predict cognitive outcomes in participants who had been retired from professional American football for an average of 20 years. Such indices may prove to be useful for clinical decision making and research.

  16. Early Dynamics of P-selectin and Interleukin 6 Predicts Outcomes in Ischemic Stroke

    DEFF Research Database (Denmark)

    Pusch, Gabriella; Debrabant, Birgit; Molnar, Tihamer

    2015-01-01

    to poststroke infection, death, and functional outcome, and assessed the ability of the models to predict each outcome. RESULTS: Interleukin 6 (IL-6) levels and change of IL-6 concentrations by 72 hours correlated with the size of tissue damage indicated by S100B titers. Levels of IL-6 and P-selectin at 72...

  17. Pre-delivery fibrinogen predicts adverse maternal or neonatal outcomes in patients with placental abruption.

    Science.gov (United States)

    Wang, Liangcheng; Matsunaga, Shigetaka; Mikami, Yukiko; Takai, Yasushi; Terui, Katsuo; Seki, Hiroyuki

    2016-07-01

    Placental abruption is a severe obstetric complication of pregnancy that can cause disseminated intravascular coagulation and progress to massive post-partum hemorrhage. Coagulation disorder due to extreme consumption of fibrinogen is considered the main pathogenesis of disseminated intravascular coagulation in patients with placental abruption. The present study sought to determine if the pre-delivery fibrinogen level could predict adverse maternal or neonatal outcomes in patients with placental abruption. This retrospective medical chart review was conducted in a center for maternal, fetal, and neonatal medicine in Japan with 61 patients with placental abruption. Fibrinogen levels prior to delivery were collected and evaluated for the prediction of maternal and neonatal outcomes. The main outcome measures for maternal outcomes were disseminated intravascular coagulation and hemorrhage, and the main outcome measures for neonatal outcomes were Apgar score at 5 min, umbilical artery pH, and stillbirth. The receiver-operator curve and multivariate logistic regression analyses indicated that fibrinogen significantly predicted overt disseminated intravascular coagulation and the requirement of ≥6 red blood cell units, ≥10 fresh frozen plasma units, and ≥20 fresh frozen plasma units for transfusion. Moderate hemorrhage occurred in 71.5% of patients with a decrease in fibrinogen levels to 155 mg/dL. Fibrinogen could also predict neonatal outcomes. Umbilical artery pH neonatal outcomes with placental abruption. © 2016 Japan Society of Obstetrics and Gynecology. © 2016 Japan Society of Obstetrics and Gynecology.

  18. The role of attachment in predicting CBT treatment outcome in children with anxiety disorders

    DEFF Research Database (Denmark)

    Walczak, Monika Anna; Normann, Nicoline; Tolstrup, Marie

    2015-01-01

    Introduction: Child’s insecure attachment to parents and insecure parental attachment has been linked to childhood anxiety (Brumariu & Kerns, 2010; Manassis et al.,1994).Whether attachment patterns can predict treatment outcome, is yet to be investigated. We examined the role of children...... that it is important to consider the parental attachment insecurity as a possible outcome hindering factor....

  19. Mothers' labeling responses to infants' gestures predict vocabulary outcomes.

    Science.gov (United States)

    Olson, Janet; Masur, Elise Frank

    2015-11-01

    Twenty-nine infants aged 1;1 and their mothers were videotaped while interacting with toys for 18 minutes. Six experimental stimuli were presented to elicit infant communicative bids in two communicative intent contexts - proto-declarative and proto-imperative. Mothers' verbal responses to infants' gestural and non-gestural communicative bids were coded for object and action labels. Relations between maternal labeling responses and infants' vocabularies at 1;1 and 1;5 were examined. Mothers' labeling responses to infants' gestural communicative bids were concurrently and predictively related to infants' vocabularies, whereas responses to non-gestural communicative bids were not. Mothers' object labeling following gestures in the proto-declarative context mediated the association from infants' gesturing in the proto-declarative context to concurrent noun lexicons and was the strongest predictor of subsequent noun lexicons. Mothers' action labeling after infants' gestural bids in the proto-imperative context predicted infants' acquisition of action words at 1;5. Findings show that mothers' responsive labeling explain specific relations between infants' gestures and their vocabulary development.

  20. Prediction of labor induction outcome using different clinical parameters

    Directory of Open Access Journals (Sweden)

    Tatić-Stupar Žaklina

    2013-01-01

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

  1. Does motivation predict outcome of pelvic floor muscle retraining?

    Science.gov (United States)

    Te West, Nevine I D; Parkin, Katrina; Hayes, Wendy; Costa, Daniel S J; Kasparian, Nadine A; Moore, Kate H

    2017-02-01

    Although pelvic floor muscle training (PFMT) is effective for stress urinary incontinence (SUI), patients need to be motivated to obtain cure. An instrument to assess motivation in such patients was published in 2009: the Incontinence Treatment Motivation Questionnaire (ITMQ). The ITMQ consists of five domains: (i) positive attitudes toward PFMT; (ii) reasons for not doing PFMT; (iii) difficulties living with incontinence; (iv) desire for treatment; and (v) incontinence severity influencing motivation. The aim of the present study was to examine the relationship between ITMQ scores and treatment success. After referral for PFMT, women with SUI completed the ITMQ. Pre- and post-treatment outcomes were the International Consultation on Incontinence Questionnaire (ICIQ) score and a 24-hr pad test. Correlations between ITMQ scores and baseline, as well as post-treatment change in ICIQ scores and pad test results were examined. Additionally, the demographics of non-participants, participants, and patients lost to follow-up were compared. Of 85 recruits, 18 did not complete the ITMQ, 14 were lost to follow-up, thus 53 completed the PFMT programme and undertook either one or both outcomes. Pre-treatment, severity on ICIQ correlated with total ITMQ (ρ = 0.33, P = 0.01). Post-treatment change in pad test was inversely correlated with Domain 2 (ρ = -0.33, P = 0.03). The pre-treatment severity of incontinence was significantly associated with motivation for treatment. Unfortunately, post-treatment change correlated with only one domain of the questionnaire. Further modification of the ITMQ is envisaged. Neurourol. Urodynam. 36:316-321, 2017. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  2. Outcome Prediction of Eating Disorders: Can Admission Data Forecast Outcome Needs at Discharge

    National Research Council Canada - National Science Library

    Gouthro, Linda

    1997-01-01

    .... The purpose of this study was to determine if data collected for individuals during the initial assessment phase of an eating disorders program could predict the nature of discharge needs at the time...

  3. Vital Sign Prediction of Adverse Maternal Outcomes in Women with Hypovolemic Shock: The Role of Shock Index.

    Directory of Open Access Journals (Sweden)

    Alison M El Ayadi

    Full Text Available To determine the optimal vital sign predictor of adverse maternal outcomes in women with hypovolemic shock secondary to obstetric hemorrhage and to develop thresholds for referral/intensive monitoring and need for urgent intervention to inform a vital sign alert device for low-resource settings.We conducted secondary analyses of a dataset of pregnant/postpartum women with hypovolemic shock in low-resource settings (n = 958. Using receiver-operating curve analysis, we evaluated the predictive ability of pulse, systolic blood pressure, diastolic blood pressure, shock index, mean arterial pressure, and pulse pressure for three adverse maternal outcomes: (1 death, (2 severe maternal outcome (death or severe end organ dysfunction morbidity; and (3 a combined severe maternal and critical interventions outcome comprising death, severe end organ dysfunction morbidity, intensive care admission, blood transfusion ≥ 5 units, or emergency hysterectomy. Two threshold parameters with optimal rule-in and rule-out characteristics were selected based on sensitivities, specificities, and positive and negative predictive values.Shock index was consistently among the top two predictors across adverse maternal outcomes. Its discriminatory ability was significantly better than pulse and pulse pressure for maternal death (p<0.05 and p<0.01, respectively, diastolic blood pressure and pulse pressure for severe maternal outcome (p<0.01, and systolic and diastolic blood pressure, mean arterial pressure and pulse pressure for severe maternal outcome and critical interventions (p<0.01. A shock index threshold of ≥ 0.9 maintained high sensitivity (100.0 with clinical practicality, ≥ 1.4 balanced specificity (range 70.0-74.8 with negative predictive value (range 93.2-99.2, and ≥ 1.7 further improved specificity (range 80.7-90.8 without compromising negative predictive value (range 88.8-98.5.For women with hypovolemic shock from obstetric hemorrhage, shock index was

  4. Predicting workplace outcomes from the ability to eavesdrop on feelings.

    Science.gov (United States)

    Elfenbein, Hillary Anger; Ambady, Nalini

    2002-10-01

    Emotion recognition, the most reliably validated component within the construct of emotional intelligence, is a complicated skill. Although emotion recognition skill is generally valued in the workplace, "eavesdropping," or relatively better recognition ability with emotions expressed through the less controllable "leaky" nonverbal channels, can have detrimental social and workplace consequences. In light of theory regarding positive emotion in organizations, as well as research on the consequences of perceiving negative information, the authors hypothesized and found an interaction between nonverbal channel and emotional valence in predicting workplace ratings from colleagues and supervisors. Ratings were higher for eavesdropping ability with positive emotion and lower for eavesdropping ability with negative emotion. The authors discuss implications for the complexity of interventions associated with emotional intelligence in workplace settings.

  5. Early Seizure Frequency and Aetiology Predict Long-Term Medical Outcome in Childhood-Onset Epilepsy

    Science.gov (United States)

    Sillanpaa, Matti; Schmidt, Dieter

    2009-01-01

    In clinical practice, it is important to predict as soon as possible after diagnosis and starting treatment, which children are destined to develop medically intractable seizures and be at risk of increased mortality. In this study, we determined factors predictive of long-term seizure and mortality outcome in a population-based cohort of 102…

  6. Expression profiling to predict outcome in breast cancer: the influence of sample selection

    International Nuclear Information System (INIS)

    Gruvberger, Sofia K; Ringnér, Markus; Edén, Patrik; Borg, Åke; Fernö, Mårten; Peterson, Carsten; Meltzer, Paul S

    2003-01-01

    Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor-α status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor-α-positive and estrogen receptor-α-negative tumors

  7. Hypoalbuminaemia predicts outcome in adult patients with congenital heart disease

    Science.gov (United States)

    Kempny, Aleksander; Diller, Gerhard-Paul; Alonso-Gonzalez, Rafael; Uebing, Anselm; Rafiq, Isma; Li, Wei; Swan, Lorna; Hooper, James; Donovan, Jackie; Wort, Stephen J; Gatzoulis, Michael A; Dimopoulos, Konstantinos

    2015-01-01

    Background In patients with acquired heart failure, hypoalbuminaemia is associated with increased risk of death. The prevalence of hypoproteinaemia and hypoalbuminaemia and their relation to outcome in adult patients with congenital heart disease (ACHD) remains, however, unknown. Methods Data on patients with ACHD who underwent blood testing in our centre within the last 14 years were collected. The relation between laboratory, clinical or demographic parameters at baseline and mortality was assessed using Cox proportional hazards regression analysis. Results A total of 2886 patients with ACHD were included. Mean age was 33.3 years (23.6–44.7) and 50.1% patients were men. Median plasma albumin concentration was 41.0 g/L (38.0–44.0), whereas hypoalbuminaemia (disease complexity, hypoalbuminaemia remained a significant predictor of death. Conclusions Hypoalbuminaemia is common in patients with ACHD and is associated with a threefold increased risk of risk of death. Hypoalbuminaemia, therefore, should be included in risk-stratification algorithms as it may assist management decisions and timing of interventions in the growing ACHD population. PMID:25736048

  8. Do Patient Characteristics Predict Outcome of Psychodynamic Psychotherapy for Social Anxiety Disorder?

    Directory of Open Access Journals (Sweden)

    Jörg Wiltink

    Full Text Available Little is known about patient characteristics as predictors for outcome in manualized short term psychodynamic psychotherapy (PDT. No study has addressed which patient variables predict outcome of PDT for social anxiety disorder.In the largest multicenter trial on psychotherapy of social anxiety (SA to date comparing cognitive therapy, PDT and wait list condition N = 230 patients were assigned to receive PDT, of which N = 166 completed treatment. Treatment outcome was assessed based on diverse parameters such as endstate functioning, remission, response, and drop-out. The relationship between patient characteristics (demographic variables, mental co-morbidity, personality, interpersonal problems and outcome was analysed using logistic and linear regressions.Pre-treatment SA predicted up to 39 percent of variance of outcome. Only few additional baseline characteristics predicted better treatment outcome (namely, lower comorbidity and interpersonal problems with a limited proportion of incremental variance (5.5 to 10 percent, while, e.g., shame, self-esteem or harm avoidance did not.We argue that the central importance of pre-treatment symptom severity for predicting outcomes should advocate alternative treatment strategies (e.g. longer treatments, combination of psychotherapy and medication in those who are most disturbed. Given the relatively small amount of variance explained by the other patient characteristics, process variables and patient-therapist interaction should additionally be taken into account in future research.Controlled-trials.com/ISRCTN53517394.

  9. Do Patient Characteristics Predict Outcome of Psychodynamic Psychotherapy for Social Anxiety Disorder?

    Science.gov (United States)

    Wiltink, Jörg; Hoyer, Jürgen; Beutel, Manfred E; Ruckes, Christian; Herpertz, Stephan; Joraschky, Peter; Koranyi, Susan; Michal, Matthias; Nolting, Björn; Pöhlmann, Karin; Salzer, Simone; Strauss, Bernhard; Leibing, Eric; Leichsenring, Falk

    2016-01-01

    Little is known about patient characteristics as predictors for outcome in manualized short term psychodynamic psychotherapy (PDT). No study has addressed which patient variables predict outcome of PDT for social anxiety disorder. In the largest multicenter trial on psychotherapy of social anxiety (SA) to date comparing cognitive therapy, PDT and wait list condition N = 230 patients were assigned to receive PDT, of which N = 166 completed treatment. Treatment outcome was assessed based on diverse parameters such as endstate functioning, remission, response, and drop-out. The relationship between patient characteristics (demographic variables, mental co-morbidity, personality, interpersonal problems) and outcome was analysed using logistic and linear regressions. Pre-treatment SA predicted up to 39 percent of variance of outcome. Only few additional baseline characteristics predicted better treatment outcome (namely, lower comorbidity and interpersonal problems) with a limited proportion of incremental variance (5.5 to 10 percent), while, e.g., shame, self-esteem or harm avoidance did not. We argue that the central importance of pre-treatment symptom severity for predicting outcomes should advocate alternative treatment strategies (e.g. longer treatments, combination of psychotherapy and medication) in those who are most disturbed. Given the relatively small amount of variance explained by the other patient characteristics, process variables and patient-therapist interaction should additionally be taken into account in future research. Controlled-trials.com/ISRCTN53517394.

  10. Radiological predictive factors for the outcome of surgically treated calcaneus fractures.

    Science.gov (United States)

    Baptista, Mário; Pinto, Rui; Torres, João

    2015-06-01

    Calcaneus fractures are fairly common and clinically relevant due to their poor outcome. Thus, solving the controversy regarding treatment and outcome prediction should be a target. This study intends to evaluate the predictive ability of common radiologic tools for the surgical outcome of calcaneus fractures, regardless of treatment modality. 44 patients' records, with operated calcaneus fractures between 2008 and 2013, were retrospectively assessed and imagiology was blindly evaluated. Patients were submitted to percutaneous or open lateral approach. No relevant correlations were found between the measurements on the plain lateral radiograph and the outcome. Fractures were also graded according to the Sanders classification. Type 4 fractures predicted the occurrence of any hazard, such as skin or pain related complications and need for secondary surgery (p=0.051, odds=14.00 [CI=1.30-150.89]). However, it's still not possible to accurately target patients with high risk of postoperative complications. Until then, follow-up protocols should be maintained indiscriminately.

  11. Predicting outcome in term neonates with hypoxic-ischaemic encephalopathy using simplified MR criteria

    Energy Technology Data Exchange (ETDEWEB)

    Jyoti, Rajeev; O' Neil, Ross [Canberra Hospital, Medical Imaging, Canberra, ACT (Australia)

    2006-01-01

    MRI is an established investigation in the evaluation of neonates with suspected hypoxic-ischaemic encephalopathy (HIE). However, its role as a predictor of neurodevelopmental outcome remains complex. To establish reproducible simplified MR criteria and evaluate their role in predicting neurodevelopmental outcome in term neonates with HIE. Term neonates with suspected HIE had MRI at 7-10 days of age. MR scans were interpreted according to new simplified criteria by two radiologists blinded to the clinical course and outcome. The new simplified criteria allocated grade 1 to cases with no central and less than 10% peripheral change, grade 2 to those with less than 30% central and/or 10-30% peripheral area change, and grade 3 to those with more than 30% central or peripheral change. MRI changes were compared with clinical neurodevelopmental outcome evaluated prospectively at 1 year of age. Neurodevelopmental outcome was based upon the DQ score (revised Griffith's) and cerebral palsy on neurological assessment. Of 20 subjects, all those showing severe (grade 3) MR changes (35%) died or had poor neurodevelopmental outcome. Subjects with a normal MR scan or with scans showing only mild (grade 1) MR changes (55%) had normal outcomes. One subject showing moderate (grade 2) changes on MRI had a moderate outcome (5%), while another had an atypical pattern of MR changes with a normal outcome (5%). Assessment of full-term neonates with suspected HIE using the simplified MR criteria is highly predictive of neurodevelopmental outcome. (orig.)

  12. Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomes

    Directory of Open Access Journals (Sweden)

    Chris L. Smith

    2016-06-01

    Full Text Available Glioblastoma multiforme is a heterogeneous and infiltrative cancer with dismal prognosis. Studying the migratory behavior of tumor-derived cell populations can be informative, but it places a high premium on the precision of in vitro methods and the relevance of in vivo conditions. In particular, the analysis of 2D cell migration may not reflect invasion into 3D extracellular matrices in vivo. Here, we describe a method that allows time-resolved studies of primary cell migration with single-cell resolution on a fibrillar surface that closely mimics in vivo 3D migration. We used this platform to screen 14 patient-derived glioblastoma samples. We observed that the migratory phenotype of a subset of cells in response to platelet-derived growth factor was highly predictive of tumor location and recurrence in the clinic. Therefore, migratory phenotypic classifiers analyzed at the single-cell level in a patient-specific way can provide high diagnostic and prognostic value for invasive cancers.

  13. Accept or Reject? Predicting Ideation Outcomes through Enterprise Social Media

    Directory of Open Access Journals (Sweden)

    Rozaidi Nik Ahmad

    2017-01-01

    Full Text Available Implementing social media in the workplace may make it easier for employees to participate in knowledge sharing activities such as Q&A and ideation. However, vetting the quality of answers and ideas becomes more complex when anyone in the company can contribute. Research on the use of social media for Q&A has shown that certain characteristics and reputation algorithms can help determine the best answers. Less is known about the ideation process and the way it plays out in social media. This paper explores the use of enterprise social media (ESM for ideation by employees in a large Russian organization distributed across nine time zones. In particular, we explore which characteristics of both ideas and their contributors predict whether ideas get accepted or rejected. Our analysis is based on logistic regression analysis of a sample of 488 ideas contributed in an ESM tool used in the organization as well as a content analysis of the types of ideas generated. Our results suggest that rather than being truly democratic and decentralized, ideation in ESM is driven by those in (or proximate to positions of organizational power.

  14. Management outcome of acute urinary retention: model of prediction.

    LENUS (Irish Health Repository)

    Daly, Padraig

    2012-01-31

    OBJECTIVES: To assess for predictors of outcome in patients presenting with acute urinary retention (AUR). METHODS: A study was performed in our unit to evaluate trial without catheter (TWOC) and successive management. We assessed for predictors of surgical or medical management, which included: age, volume drained at time of catheterisation, cause of retention, serum creatinine, success of trial of voiding, co-morbidities, prostate-specific antigen (PSA) and prostate size on digital rectal examination (DRE). RESULTS: 72 men were entered into the study over an 18-month period: 27 had a successful first TWOC, 20 patients had a second TWOC, and 6 were successful. In total, 31 of the 33 patients with a successful TWOC remained on alpha-blockers without a further episode of AUR within a minimum of 6 months\\' follow-up. Patients failing TWOC were managed by transurethral resection of the prostate (n = 22), long-term catheterisation (n = 15) or prostatic stents (n = 3), and 1 patient died prior to intervention. Three predictors were significant on multivariate analysis: PSA (>2.9 ng\\/ml), prostate size on DRE (large) and volume drained at time of catheterisation (>or=1,000 ml). CONCLUSION: Patients with elevated PSA (>2.9 ng\\/ml), a large prostate size on DRE and a volume drained at time of catheterisation >1,000 ml are best managed by surgical intervention, while those with volumes drained at time of catheterisation of <1,000 ml, a PSA

  15. Parental stress predicts functional outcome in pediatric cancer survivors.

    Science.gov (United States)

    Hile, Sarah; Erickson, Sarah J; Agee, Brittany; Annett, Robert D

    2014-10-01

    Childhood cancer survivors are at risk for long-term neurocognitive and psychosocial morbidities. Research has seldom examined the relationship between these morbidities; thus, little empirical evidence exists concerning overall salience and how morbidities converge to impair day-to-day functioning. An increased understanding of functional impairment resulting from the pediatric cancer experience can inform early risk identification as well as sources for intervention. The purpose of this study was to characterize the frequency/severity of functional impairment and identify significant neurocognitive and psychosocial determinants of functional impairment. Fifty child-parent dyads were enrolled. Children were aged 7-19 years who were at least 2 years postdiagnosis with leukemia/lymphoma and were recruited through a pediatric oncology late effects clinic. Parents completed questionnaires, rating their own adjustment to their child's illness as well as their child's level of functional impairment, while a brief neuropsychological exam was administered to children. Twenty-six percent of the sample evidenced clinically significant functional impairment. Regression analyses indicated that neurocognitive deficits did not predict functional impairment, whereas parental stress was a significant predictor. Although children demonstrated both neurocognitive deficits and functional impairments, results favor psychosocial factors, such as parental stress, as a predictor of overall functional impairment. The implications of this study suggest that late effects aggregate to impact day-to-day functioning in pediatric cancer survivor populations and parental stress may serve as a marker for heightened risk. The results suggest that broader functional domains, especially school and self-care domains, should be evaluated and considered when identifying potential targets for psychosocial interventions. Copyright © 2014 John Wiley & Sons, Ltd.

  16. Serum uric acid level predicts adverse outcomes after myocardial revascularization or cardiac valve surgery.

    Science.gov (United States)

    Lazzeroni, Davide; Bini, Matteo; Camaiora, Umberto; Castiglioni, Paolo; Moderato, Luca; Bosi, Davide; Geroldi, Simone; Ugolotti, Pietro T; Brambilla, Lorenzo; Brambilla, Valerio; Coruzzi, Paolo

    2018-01-01

    Background High levels of serum uric acid have been associated with adverse outcomes in cardiovascular diseases such as myocardial infarction and heart failure. The aim of the current study was to evaluate the prognostic role of serum uric acid levels in patients undergoing cardiac rehabilitation after myocardial revascularization and/or cardiac valve surgery. Design We performed an observational prospective cohort study. Methods The study included 1440 patients with available serum uric acid levels, prospectively followed for 50 ± 17 months. Mean age was 67 ± 11 years; 781 patients (54%) underwent myocardial revascularization, 474 (33%) cardiac valve surgery and 185 (13%) valve-plus-coronary artery by-pass graft surgery. The primary endpoints were overall and cardiovascular mortality while secondary end-points were combined major adverse cardiac and cerebrovascular events. Results Serum uric acid level mean values were 286 ± 95 µmol/l and elevated serum uric acid levels (≥360 µmol/l or 6 mg/dl) were found in 275 patients (19%). Overall mortality (hazard ratio = 2.1; 95% confidence interval: 1.5-3.0; p uric acid levels, even after adjustment for age, gender, arterial hypertension, diabetes, glomerular filtration rate, atrial fibrillation and medical therapy. Moreover, strong positive correlations between serum uric acid level and probability of overall mortality ( p uric acid levels predict mortality and adverse cardiovascular outcome in patients undergoing myocardial revascularization and/or cardiac valve surgery even after the adjustment for age, gender, arterial hypertension, diabetes, glomerular filtration rate and medical therapy.

  17. TREATMENT OUTCOME WITH IMPLANT-RETAINED OVERDENTURES .1. CLINICAL FINDINGS AND PREDICTABILITY OF CLINICAL TREATMENT OUTCOME

    NARCIS (Netherlands)

    CUNE, MS; DEPUTTER, C; HOOGSTRATEN, J

    This nationwide study was conducted to clinically evaluate treatment with implant-retained overdentures when applied on a large scale and to determine to what degree treatment results could be predicted from patient and treatment characteristics at baseline. A total of 429 patients who had received

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

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-10-20

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

  20. Predictive factors for long-term outcome in polymyositis/dermatomyositis-associated interstitial lung diseases.

    Science.gov (United States)

    Fujisawa, Tomoyuki; Hozumi, Hironao; Kono, Masato; Enomoto, Noriyuki; Nakamura, Yutaro; Inui, Naoki; Nakashima, Ran; Imura, Yoshitaka; Mimori, Tsuneyo; Suda, Takafumi

    2017-03-01

    Interstitial lung disease (ILD) is strongly associated with polymyositis (PM), dermatomyositis (DM), and clinically amyopathic dermatomyositis (CADM). It is also related to mortality. Previous studies have highlighted that the acute form of PM/DM/CADM-associated ILD (PM/DM/CADM-ILD) has a poor short-term prognosis. However, little is known about the long-term clinical features of patients with PM/DM/CADM-ILD. The aim of the present study is to clarify the clinical characteristics and the predictive factors for long-term outcomes in patients with PM/DM/CADM-ILD. Thirty-four patients with PM/DM/CADM-ILD who were followed up for more than 12 months were analyzed retrospectively. The patients were classified as "stable" or "deterioration" according to respiratory symptoms, serial changes in forced vital capacity (FVC) or arterial oxygen pressure, and radiologic findings during the follow-up period. Twenty-six patients (76%) were in the stable group and eight patients (24%) were in the deterioration group. Home oxygen therapy was performed in six cases in the deterioration group because of chronic respiratory failure due to progression of ILD. The deterioration group, in comparison to the stable group, had a significantly lower %FVC and a higher positive rate for the anti-PL-7 antibody. Multivariate logistic regression analysis revealed that a positive anti-PL-7 antibody test and a lower %FVC were independently associated with deterioration during long-term follow-up. Patients with PM/DM/CADM-ILD are at risk for chronic respiratory failure due to the deterioration of ILD during long-term follow-up. The presence of anti-PL-7 antibody and a lower %FVC at initial diagnosis may predict long-term deterioration in patients with PM/DM/CADM-ILD. Copyright © 2016 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

  1. Helsinki Computed Tomography Scoring System Can Independently Predict Long-Term Outcome in Traumatic Brain Injury.

    Science.gov (United States)

    Yao, Shun; Song, Jian; Li, Shun; Cao, Chenglong; Fang, Li; Wang, Chaohu; Xu, Guozheng

    2017-05-01

    The Helsinki computed tomography (CT) scoring system was developed to predict long-term outcome in patients with traumatic brain injury (TBI) 2 years ago; however, it has not yet been external validated. This study aimed to determine whether this system could be used as an independent predictor for TBI. This retrospective cohort study was performed on 302 consecutive patients with TBI. Univariate and multivariate logistic regressions and receiver operating characteristic curve analyses were used to determine the relationship between initial Helsinki CT scores and mortality and unfavorable neurologic outcome at 6 months after injury. Outcomes were assessed using the Glasgow Outcome Scale (scores of 1-3 defined as unfavorable outcome). Of all patients, mortality was 17.9% and unfavorable outcome was 41.4%. The Helsinki CT score was significantly associated with the 6-month outcome in univariate analyses (P < 0.05). After adjustment for other factors in the multivariate regression analysis, the Helsinki CT score remained an independent predictor for mortality (odds ratio [OR], 1.22; 95% confidence interval [CI], 1.08-1.39; P = 0.002) and unfavorable outcome (OR, 1.14; 95% CI, 1.04-1.26; P = 0.007). Receiver operating characteristic curve analyses showed that the Helsinki CT score possessed good discrimination ability for mortality (area under the curve, 0.81; 95% CI, 0.75-0.87; P < 0.001) and moderate discrimination ability for unfavorable outcome (area under the curve, 0.74; 95% CI, 0.69-0.80; P < 0.001). Moreover, at 1.9 hours after TBI, the Helsinki CT score was most accurate for predicting mortality (accuracy, 74.5%) and unfavorable outcome (accuracy, 71.5%). The Helsinki CT score showed good prognostic discrimination and can be used as an independent predictor for long-term outcome prediction in patients with TBI. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle

    Directory of Open Access Journals (Sweden)

    Ge Cheng

    2016-12-01

    Full Text Available Predicting the outcome of National Basketball Association (NBA matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that the model is able to predict the winning team with 74.4% accuracy, outperforming other classical machine learning algorithms that could only afford a maximum prediction accuracy of 70.6% in the experiments that we performed.

  3. Methodological Challenges in Examining the Impact of Healthcare Predictive Analytics on Nursing-Sensitive Patient Outcomes.

    Science.gov (United States)

    Jeffery, Alvin D

    2015-06-01

    The expansion of real-time analytic abilities within current electronic health records has led to innovations in predictive modeling and clinical decision support systems. However, the ability of these systems to influence patient outcomes is currently unknown. Even though nurses are the largest profession within the healthcare workforce, little research has been performed to explore the impact of clinical decision support on their decisions and the patient outcomes associated with them. A scoping literature review explored the impact clinical decision support systems containing healthcare predictive analytics have on four nursing-sensitive patient outcomes (pressure ulcers, failure to rescue, falls, and infections). While many articles discussed variable selection and predictive model development/validation, only four articles examined the impact on patient outcomes. The novelty of predictive analytics and the inherent methodological challenges in studying clinical decision support impact are likely responsible for this paucity of literature. Major methodological challenges include (1) multilevel nature of intervention, (2) treatment fidelity, and (3) adequacy of clinicians' subsequent behavior. There is currently insufficient evidence to demonstrate efficacy of healthcare predictive analytics-enhanced clinical decision support systems on nursing-sensitive patient outcomes. Innovative research methods and a greater emphasis on studying this phenomenon are needed.

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

    Science.gov (United States)

    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 = 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.

  5. Rapid Acute Physiology Score versus Rapid Emergency Medicine Score in Trauma Outcome Prediction; a Comparative Study

    Directory of Open Access Journals (Sweden)

    Babak Nakhjavan-Shahraki

    2017-01-01

    Full Text Available Introduction: Rapid acute physiology score (RAPS and rapid emergency medicine score (REMS are two physiologic models for measuring injury severity in emergency settings. The present study was designed to compare the two models in outcome prediction of trauma patients presenting to emergency department (ED.Methods: In this prospective cross-sectional study, the two models of RAPS and REMS were compared regarding prediction of mortality and poor outcome (severe disability based on Glasgow outcome scale of trauma patients presenting to the EDs of 5 educational hospitals in Iran (Tehran, Tabriz, Urmia, Jahrom and Ilam from May to October 2016. The discriminatory power and calibration of the models were calculated and compared using STATA 11.Results: 2148 patients with the mean age of 39.50±17.27 years were studied (75.56% males. The area under the curve of REMS and RAPS in predicting in-hospital mortality were calculated to be 0.93 (95% CI: 0.92-0.95 and 0.899 (95% CI: 0.86-0.93, respectively (p=0.02. These measures were 0.92 (95% CI: 0.90-0.94 and 0.86 (95% CI: 0.83-0.90, respectively, regarding poor outcome (p=0.001. The optimum cut-off point in predicting outcome was found to be 3 for REMS model and 2 for RAPS model. The sensitivity and specificity of REMS and RAPS in the mentioned cut offs were 95.93 vs. 85.37 and 77.63 vs. 83.51, respectively, in predicting mortality. Calibration and overall performance of the two models were acceptable.Conclusion: The present study showed that adding age and level of arterial oxygen saturation to the variables included in RAPS model can increase its predictive value. Therefore, it seems that REMS could be used for predicting mortality and poor outcome of trauma patients in emergency settings

  6. Comparison of TMS and DTT for predicting motor outcome in intracerebral hemorrhage.

    Science.gov (United States)

    Jang, Sung Ho; Ahn, Sang Ho; Sakong, Joon; Byun, Woo Mok; Choi, Byung Yun; Chang, Chul Hoon; Bai, Daiseg; Son, Su Min

    2010-03-15

    TMS (transcranial magnetic stimulation) and DTT (diffusion tensor tractography) have different advantages in evaluating stroke patients. TMS has good clinical accessibility and economical benefit. On the contrary, DTT has a unique advantage to visualize neural tracts three-dimensionally although it requires an expensive and large MRI machine. Many studies have demonstrated that TMS and DTT have predictive values for motor outcome in stroke patients. However, there has been no study on the comparison of these two evaluation tools. In the current study, we compared the abilities of TMS and DTT to predict upper motor outcome in patients with ICH (intracerebral hemorrhage). Fifty-three consecutive patients with severe motor weakness were evaluated by TMS and DTT at the early stage (7-28 days) of ICH. Modified Brunnstrom classification (MBC) and the motricity index of upper extremity (UMI) were evaluated at onset and 6 months after onset. Patients with the presence of a motor evoked potential (MEP) in TMS or a preserved corticospinal tract (CST) in DTT showed better motor outcomes than those without (p=0.000). TMS showed higher positive predictive value than DTT. In contrast, DTT showed higher negative predictive value than TMS. TMS and DTT had different advantages in predicting motor outcome, and this result could be a reference to predict final neurological deficit at the early stage of ICH.

  7. PREDICTING THE MATCH OUTCOME IN ONE DAY INTERNATIONAL CRICKET MATCHES, WHILE THE GAME IS IN PROGRESS

    Directory of Open Access Journals (Sweden)

    Michael Bailey

    2006-12-01

    Full Text Available Millions of dollars are wagered on the outcome of one day international (ODI cricket matches, with a large percentage of bets occurring after the game has commenced. Using match information gathered from all 2200 ODI matches played prior to January 2005, a range of variables that could independently explain statistically significant proportions of variation associated with the predicted run totals and match outcomes were created. Such variables include home ground advantage, past performances, match experience, performance at the specific venue, performance against the specific opposition, experience at the specific venue and current form. Using a multiple linear regression model, prediction variables were numerically weighted according to statistical significance and used to predict the match outcome. With the use of the Duckworth-Lewis method to determine resources remaining, at the end of each completed over, the predicted run total of the batting team could be updated to provide a more accurate prediction of the match outcome. By applying this prediction approach to a holdout sample of matches, the efficiency of the "in the run" wagering market could be assessed. Preliminary results suggest that the market is prone to overreact to events occurring throughout the course of the match, thus creating brief inefficiencies in the wagering market

  8. Prediction of outcome in the psychosis prodrome using neuroanatomical pattern classification.

    Science.gov (United States)

    Kambeitz-Ilankovic, Lana; Meisenzahl, Eva M; Cabral, Carlos; von Saldern, Sebastian; Kambeitz, Joseph; Falkai, Peter; Möller, Hans-Jürgen; Reiser, Maximilian; Koutsouleris, Nikolaos

    2016-06-01

    To date, research into the biomarker-aided early recognition of psychosis has focused on predicting the transition likelihood of clinically defined individuals with different at-risk mental states (ARMS) based on structural (and functional) brain changes. However, it is currently unknown whether neuroimaging patterns could be identified to facilitate the individualized prediction of symptomatic and functional recovery. Therefore, we investigated whether cortical surface alterations analyzed by means of multivariate pattern recognition methods could enable the single-subject identification of functional outcomes in twenty-seven ARMS individuals. Subjects were dichotomized into 'good' vs. 'poor' outcome groups on average 4years after the baseline MRI scan using a Global Assessment of Functioning (GAF) threshold of 70. Cortical surface-based pattern classification predicted good (N=14) vs. poor outcome status (N=13) at follow-up with an accuracy of 82% as determined by nested leave-one-cross-validation. Neuroanatomical prediction involved cortical area reductions in superior temporal, inferior frontal and inferior parietal areas and was not confounded by functional impairment at baseline, or antipsychotic medication and transition status over the follow-up period. The prediction model's decision scores were correlated with positive and general symptom scores in the ARMS group at follow-up, whereas negative symptoms were not linked to predicted poorer functional outcome. These findings suggest that poorer functional outcomes are associated with non-resolving attenuated psychosis and could be predicted at the single-subject level using multivariate neuroanatomical risk stratification methods. However, the generalizability and specificity of the suggested prediction model should be thoroughly investigated in future large-scale and cross-diagnostic MRI studies. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Normal preoperative white blood cell count is predictive of outcomes for endovascular procedures.

    Science.gov (United States)

    Amaranto, Daniel J; Wang, Edward C; Eskandari, Mark K; Morasch, Mark D; Rodriguez, Heron E; Pearce, William H; Kibbe, Melina R

    2011-11-01

    An abnormally elevated preoperative white blood cell count (WBC) has been associated with postoperative morbidity and mortality. However, it is unknown if a normal WBC is predictive of postoperative outcomes following vascular interventions. Thus, the objective of this study is to determine if a WBC within the normal range is predictive of outcomes following vascular interventions. The medical records of patients undergoing endovascular and open repair of carotid stenosis, aortic aneurysm, and peripheral arterial disease from 1999 to 2009 were retrospectively reviewed. Major adverse events (MAE) were defined as death, stroke, and myocardial infarction. Of 1773 cases with normal preoperative WBC (3.5-10.5 K/μL), there were 804 [45.3%] endovascular and 969 [54.7%] open vascular surgeries. Patients with complications (55) or MAE (19) after endovascular intervention had higher preoperative WBC compared with patients without complications (WBC 7.7 ± 1.47 vs 7.1 ± 1.57, respectively, P = .002) or MAE (WBC 8.3 ± 1.26 vs 7.1 ± 0.06, respectively, P = .001). No difference was observed for patients who received open surgery. Patients undergoing endovascular intervention were 2.3, 4.8, and 22 times more likely to experience complications (P = .004), MAE (P = .003), or death (P = .036) when WBC exceeded 7.5 K/μL. Multivariate analysis showed that preoperative normal WBC was an independent predictor of complications, MAE, and death in patients after endovascular procedures but only for death in patients after open vascular procedures. This study demonstrates a strong linear correlation between an increasing preoperative WBC within the normal range and an increased risk for postoperative complications and death following endovascular interventions. The study also found a significant curvilinear U-shaped relation between a normal preoperative WBC and death in the open surgical cohort, with patients in the very low and very high normal WBC range at an increased risk of death

  10. Development and validation of a dynamic outcome prediction model for paracetamol-induced acute liver failure

    DEFF Research Database (Denmark)

    Bernal, William; Wang, Yanzhong; Maggs, James

    2016-01-01

    BACKGROUND: Early, accurate prediction of survival is central to management of patients with paracetamol-induced acute liver failure to identify those needing emergency liver transplantation. Current prognostic tools are confounded by recent improvements in outcome independent of emergency liver...... transplantation, and constrained by static binary outcome prediction. We aimed to develop a simple prognostic tool to reflect current outcomes and generate a dynamic updated estimation of risk of death. METHODS: Patients with paracetamol-induced acute liver failure managed at intensive care units in the UK...... normalised ratio (INR), and cardiovascular failure were used to derive an initial predictive model, with a second (day 2) model including additional changes in INR and lactate. FINDINGS: We developed and validated new high-performance statistical models to support decision making in patients with paracetamol...

  11. The Clinical Added Value of Imaging: A Perspective From Outcome Prediction.

    Science.gov (United States)

    Jollans, Lee; Whelan, Robert

    2016-09-01

    Objective measures of psychiatric health would be of benefit in clinical practice. Despite considerable research in the area of psychiatric neuroimaging outcome prediction, translating putative neuroimaging markers (neuromarkers) of a disorder into clinical practice has proven challenging. We reviewed studies that used neuroimaging measures to predict treatment response and disease outcomes in major depressive disorder, substance use, autism spectrum disorder, psychosis, and dementia. The majority of studies sought to predict psychiatric outcomes rather than develop a specific biological index of future disease trajectory. Studies varied widely with respect to sample size and quantification of out-of-sample prediction model performance. Many studies were able to predict psychiatric outcomes with moderate accuracy, with neuroimaging data often augmenting the prediction compared to clinical or psychometric data alone. We make recommendations for future research with respect to methods that can increase the generalizability and reproducibility of predictions. Large sample sizes in conjunction with machine learning methods, such as feature selection, cross-validation, and random label permutation, provide significant improvement to and quantification of generalizability. Further refinement of neuroimaging protocols and analysis methods will likely facilitate the clinical applicability of predictive imaging markers in psychiatry. Such clinically relevant neuromarkers need not necessarily be grounded in the pathophysiology of the disease, but identifying these neuromarkers may suggest targets for future research into disease mechanisms. The ability of imaging prediction models to augment clinical judgments will ultimately depend on the personal and economic costs and benefits to the patient. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Pekka Kuittinen

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

  13. Functional Outcome Prediction after Traumatic Spinal Cord Injury Based on Acute Clinical Factors.

    OpenAIRE

    Kaminski, Ludovic; Cordemans, Virginie; Cernat, Eduard; M'Bra, Kouamé Innocent; Mac-Thiong, Jean-Marc

    2017-01-01

    Spinal cord injury (SCI) is a devastating condition that affects patients on both a personal and societal level. The objective of the study is to improve the prediction of long-term functional outcome following SCI based on the acute clinical findings. A total of 76 patients with acute traumatic SCI were prospectively enrolled in a cohort study in a single Level I trauma center. Spinal Cord Independence Measure (SCIM) at 1 year after the trauma was the primary outcome. Potential predictors of...

  14. Do Patient Characteristics Predict Outcome of Psychodynamic Psychotherapy for Social Anxiety Disorder?

    OpenAIRE

    Wiltink, Jörg; Hoyer, Jürgen; Beutel, Manfred E.; Ruckes, Christian; Herpertz, Stephan; Joraschky, Peter; Koranyi, Susan; Michal, Matthias; Nolting, Björn; Pöhlmann, Karin; Salzer, Simone; Strauss, Bernhard; Leibing, Eric; Leichsenring, Falk

    2016-01-01

    OBJECTIVES: Little is known about patient characteristics as predictors for outcome in manualized short term psychodynamic psychotherapy (PDT). No study has addressed which patient variables predict outcome of PDT for social anxiety disorder. RESEARCH DESIGN AND METHODS: In the largest multicenter trial on psychotherapy of social anxiety (SA) to date comparing cognitive therapy, PDT and wait list condition N = 230 patients were assigned to receive PDT, of which N = 166 completed treatmen...

  15. A Comparison of Rational Versus Empirical Methods in the Prediction of Psychotherapy Outcome

    OpenAIRE

    Spielmans, Glen I.

    2004-01-01

    Several systems have been designed to monitor psychotherapy outcome, in which feedback is generated based on how a client's rate of progress compares to an expected level of progress. Clients who progress at a much lesser rate than the average client are referred to as signal-alarm cases. Recent studies have shown that providing feedback to therapists based on comparing their clients' progress to a set of rational, clinically derived algorithms has enhanced outcomes for clients predicted to s...

  16. Do personality traits predict outcome of psychodynamically oriented psychosomatic inpatient treatment beyond initial symptoms?

    Science.gov (United States)

    Steinert, Christiane; Klein, Susanne; Leweke, Frank; Leichsenring, Falk

    2015-03-01

    Whether personality characteristics have an impact on treatment outcome is an important question in psychotherapy research. One of the most common approaches for the description of personality is the five-factor model of personality. Only few studies investigated whether patient personality as measured with the NEO-Five-Factor Inventory (NEO-FFI, Costa & McCrae [1992b]. Revised NEO-PI-R and NEO-FFI. Professional manual. Odessa, FL: Psychological Assessment Recources) predicts outcome. Results were inconsistent. Studies reporting personality to be predictive of outcome did not control for baseline symptoms, while studies controlling initial symptoms could not support these findings. We hypothesized that after taking into account baseline symptoms, the NEO-FFI would not predict outcome and tested this in a large sample of inpatients at a psychosomatic clinic. Naturalistic, non-controlled study using patients' data for multiple regression analysis to identify predictors of outcome. Data of 254 inpatients suffering primarily from depressive, anxiety, stress, and somatoform disorders were analysed. Personality was assessed at the beginning of therapy. For psychotherapy outcome, changes in anxiety and depression (Hospital Anxiety and Depression Scale; HADS), overall psychopathology (Symptom Checklist-90-R Global Severity Index [GSI]), and interpersonal problems (Inventory of Interpersonal Problems; IIP) were measured. The treatment resulted in significant decreases on all outcome measures corresponding to moderate to large effect sizes (HADS: d = 1.03; GSI: d = 0.90; IIP: d = 0.38). Consistent with our hypothesis, none of the personality domains predicted outcome when baseline symptoms were controlled for. Personality assessment at baseline does not seem to have an added value in the prediction of inpatient psychotherapy outcome beyond initial symptoms. Clinical implications Personality dimensions overlap with symptomatic distress. Rather than serve as predictors of

  17. Statistical aspects of radiogenomics: can radiogenomics models be used to aid prediction of outcomes in cancer patients?

    Science.gov (United States)

    Ren, Boya; Mazurowski, Maciej A.

    2017-03-01

    Radiogenomics is a new direction in cancer research that aims at identifying the relationship between tumor genomics and its appearance in imaging (i.e. its radiophenotype). Recent years brought multiple radiogenomic discoveries in brain, breast, lung, and other cancers. With development of this new field we believe that it important to investigate in which setting radiogenomics could be useful to better direct research effort. One of the general applications of radiogenomics is to generate imaging-based models for prediction of outcomes and doing so through modeling the relationship between imaging and genomics and the relationship between genomics and outcomes. We believe that this is an important potential application of radiogenomic as it could advance imaging-based precision medicine. We show a preliminary simulation study evaluation whether such approach results in improved models. We investigate different setting in terms of the strengths of the radiogenomic relationship, prognostic power of the imaging and genomic descriptors, and availability and quality of data. Our experiments indicated that the following parameters have impact on usefulness of the radiogenomic approach: predictive power of genomic features and imaging features, strength of the radiogenomic relationship as well as number and follow up time for the genomic data. Overall, we found that there are some situations in which radiogenomics approach is beneficial but only when the radiogenomic relationship is strong and low number of imaging cases with outcomes data are available.

  18. Predicting Paris: Multi-Method Approaches to Forecast the Outcomes of Global Climate Negotiations

    Directory of Open Access Journals (Sweden)

    Detlef F. Sprinz

    2016-09-01

    Full Text Available We examine the negotiations held under the auspices of the United Nations Framework Convention of Climate Change in Paris, December 2015. Prior to these negotiations, there was considerable uncertainty about whether an agreement would be reached, particularly given that the world’s leaders failed to do so in the 2009 negotiations held in Copenhagen. Amid this uncertainty, we applied three different methods to predict the outcomes: an expert survey and two negotiation simulation models, namely the Exchange Model and the Predictioneer’s Game. After the event, these predictions were assessed against the coded texts that were agreed in Paris. The evidence suggests that combining experts’ predictions to reach a collective expert prediction makes for significantly more accurate predictions than individual experts’ predictions. The differences in the performance between the two different negotiation simulation models were not statistically significant.

  19. Predicting outcome

    African Journals Online (AJOL)

    events, preoperative brain natriuretic peptide (BNP) may be a better predictor of postoperative cardiac complications, than troponins.8 Preoperative BNP elevation identifies a vulnerable ventricle at risk of a major adverse cardiac event, while troponin elevations most commonly reflect myocyte necrosis as a final common ...

  20. Strong subjective recovery as a protective factor against the effects of positive symptoms on quality of life outcomes in schizophrenia.

    Science.gov (United States)

    Kukla, Marina; Lysaker, Paul H; Roe, David

    2014-08-01

    Interest in recovery from schizophrenia has been growing steadily, with much of the focus on remission from psychotic symptoms and a return to functioning. Less is known about the experience of subjective recovery and its relationships with other important outcomes, such as quality of life and the formation and sustenance of social connections. This study sought to address this gap in knowledge by examining the links between self perceived recovery, symptoms, and the social components of quality of life. Sixty eight veterans with schizophrenia-spectrum disorders who were participating in a study of cognitive remediation and work were concurrently administered the Recovery Assessment Scale, Positive and Negative Syndrome Scale, and the Heinrichs-Carpenter Quality of Life Scale (QLS). Linear regression analyses demonstrated that subjective recovery moderated the relationship between positive symptoms and both QLS intrapsychic foundations scores and QLS instrumental role functioning after controlling for negative symptoms. Further examination of this interaction revealed that for individuals with substantial positive symptoms, higher levels of subjective recovery were associated with better instrumental role functioning and intrapsychic foundational abilities. Greater self perceived recovery is linked with stronger quality of life, both in regards to the cognitive and affective bases for socialization and active community involvement, even in the presence of substantial psychotic symptoms. Clinical implications of these findings are discussed. Published by Elsevier Inc.

  1. Decompressive craniectomy for hemispheric infarction: predictive factors for six month rehabilitation outcome.

    Science.gov (United States)

    Wong, G K; Kung, J; Ng, S C; Zhu, X L; Poon, W S

    2008-01-01

    Decompressive craniectomy after hemispheric infarction has been shown to reduce mortality and functional outcome in selected patients. However, the optimal timing for surgery and patient most likely to benefit from this procedures was not known. We aimed to determine possible factors predictive of outcome following decompressive craniectomy for ischemic infarction from review of oneurological outcome in our patients at six months. We retrospectively reviewed 21 patients who underwent decompressive craniectomy for hemispheric infarction over a three year period in a regional neurosurgical center in Hong Kong. All patients were recruited subsequently for active in-patient rehabilitation, when suitable. The median age was 53 and the male to female ration was 1:3. Four patients (19%) achieved independent activity of daily living at six months after rehabilitation. Neither early surgery, within 24-48 hours after admission, nor side of infarction correlated with six month neurological outcome. All four patients with favourable neurological outcome at six month demonstrated favourable clinical improvement even at one month. Early decompressive hemicraniectomy is not predictive of neurological outcome, determined by Glasgow outcome score, at six months (P = 1.00, NS).

  2. Sustain talk predicts poorer outcomes among mandated college student drinkers receiving a brief motivational intervention.

    Science.gov (United States)

    Apodaca, Timothy R; Borsari, Brian; Jackson, Kristina M; Magill, Molly; Longabaugh, Richard; Mastroleo, Nadine R; Barnett, Nancy P

    2014-09-01

    Within-session client language that represents a movement toward behavior change (change talk) has been linked to better treatment outcomes in the literature on motivational interviewing (MI). There has been somewhat less study of the impact of client language against change (sustain talk) on outcomes following an MI session. This study examined the role of both client change talk and sustain talk, as well as therapist language, occurring during a brief motivational intervention (BMI) session with college students who had violated college alcohol policy (N = 92). Audiotapes of these sessions were coded using a therapy process coding system. A series of hierarchical regressions were used to examine the relationships among therapist MI-consistent and MI-inconsistent language, client change talk and sustain talk, as well as global measures of relational variables, and drinking outcomes. Contrary to prior research, sustain talk, but not change talk, predicted poorer alcohol use outcomes following the BMI at 3- and 12-month follow-up assessments. Higher levels of client self-exploration during the session also predicted improved drinking outcomes. Therapist measures of MI-consistent and MI-inconsistent language, and global measures of therapist acceptance and MI spirit were unrelated to client drinking outcomes. Results suggest that client sustain talk and self-exploration during the session play an important role in determining drinking outcomes among mandated college students receiving a BMI addressing alcohol use.

  3. Methods for prediction of strong earthquake ground motion. Final technical report, October 1, 1976--September 30, 1977

    International Nuclear Information System (INIS)

    Trifunac, M.D.

    1977-09-01

    The purpose of this report is to summarize the results of the work on characterization of strong earthquake ground motion. The objective of this effort has been to initiate presentation of simple yet detailed methodology for characterization of strong earthquake ground motion for use in licensing and evaluation of operating Nuclear Power Plants. This report will emphasize the simplicity of the methodology by presenting only the end results in a format that may be useful for the development of the site specific criteria in seismic risk analysis, for work on the development of modern standards and regulatory guides, and for re-evaluation of the existing power plant sites

  4. Predicting mobility outcome in lower limb amputees with motor ability tests used in early rehabilitation.

    Science.gov (United States)

    Spaan, Matthijs H; Vrieling, Aline H; van de Berg, Pim; Dijkstra, Pieter U; van Keeken, Helco G

    2017-04-01

    Retrospective cohort study. Persons with a lower limb amputation can regain mobility using a prosthetic device. For fast and adequate prescription of prosthetic components, it is necessary to predict the mobility outcome early in rehabilitation. Currently, prosthetic prescription is primarily based on empirical knowledge of rehabilitation professionals. In this study, we explored motor ability tests, to be completed without a prosthetic device, which have predictive value for mobility outcome at the end of rehabilitation. For this study, data of 82 patients with a lower limb amputation were included. The Single-limb standing balance test (Balance test), the Lower-Extremity Motor Coordination Test and the Amputee Mobility Predictor Assessment Tool (AMPnoPRO) were used as measures for motor ability. Mobility outcome was measured using the Timed Up and Go Test, the Two-Minute Walking Test and K levels were used. The explained variance of the Balance test, the Lower-Extremity Motor Coordination Test and the AMPnoPRO was, respectively, 0.603, 0.534 and 0.649 on the Two-Minute Walking Test (linear regression); 0.597, 0.431 and 0.624 on the Timed Up and Go Test (linear regression); and 0.432, 0.420 and 0.526 on the K levels (logistic regression). The AMPnoPRO predicted mobility outcome statistically (largest amount of explained variance). Clinical relevance This study explored the possibility of statistically predicting mobility outcome in lower limb amputees at the end of rehabilitation, using motor ability tests conducted in early rehabilitation. This study suggests the use of the AMPnoPRO to predict mobility outcome in lower limb amputees.

  5. Has growth mixture modeling improved our understanding of how early change predicts psychotherapy outcome?

    Science.gov (United States)

    Koffmann, Andrew

    2017-03-02

    Early change in psychotherapy predicts outcome. Seven studies have used growth mixture modeling [GMM; Muthén, B. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class-latent growth modeling. In L. M. Collins & A. G. Sawyers (Eds.), New methods for the analysis of change (pp. 291-322). Washington, DC: American Psychological Association] to identify patient classes based on early change but have yielded conflicting results. Here, we review the earlier studies and apply GMM to a new data set. In a university-based training clinic, 251 patients were administered the Outcome Questionnaire-45 [Lambert, M. J., Hansen, N. B., Umphress, V., Lunnen, K., Okiishi, J., Burlingame, G., … Reisinger, C. W. (1996). Administration and scoring manual for the Outcome Questionnaire (OQ 45.2). Wilmington, DE: American Professional Credentialing Services] at each psychotherapy session. We used GMM to identify class structure based on change in the first six sessions and examined trajectories as predictors of outcome. The sample was best described as a single class. There was no evidence of autoregressive trends in the data. We achieved better fit to the data by permitting latent variables some degree of kurtosis, rather than to assume multivariate normality. Treatment outcome was predicted by the amount of early improvement, regardless of initial level of distress. The presence of sudden early gains or losses did not further improve outcome prediction. Early improvement is an easily computed, powerful predictor of psychotherapy outcome. The use of GMM to investigate the relationship between change and outcome is technically complex and computationally intensive. To date, it has not been particularly informative.

  6. Factors predicting outcome of cardiopulmonary resuscitation in a developing country: the Siriraj cardiopulmonary resuscitation registry.

    Science.gov (United States)

    Krittayaphong, Rungroj; Saengsung, Panisara; Chawaruechai, Tanawin; Yindeengam, Ahthit; Udompunturak, Suthipol

    2009-05-01

    Outcomes of cardiac arrest and cardiopulmonary resuscitation (CPR) are not usually evaluated or monitored extensively in developing countries. To determine the outcome of CPR and the factors predicting its outcome. Siriraj Hospital is a 2,400-bed, 17-building, university hospital. Data were analyzed from the Siriraj CPR registry which was modified from the Utstein template. Data entry consisted of demographic data, reason for cardiac arrest, rhythm causing cardiac arrest, type of ward, type of department, status of patients before the event as well as sequence of action including the use of medications and outcome of CPR. The primary outcomes were rated to return of spontaneous circulation (ROSC) and survival to discharge. Univariate and multivariable logistic regression analysis were performed. Approximately 95,000 patients were admitted to the hospital each year. There were a total of 2,747 CPR reports during the time frame from January 2003 to December 2006. Of these 57.9% were males. The average age was 53.3 +/- 25.2 years. Most cardiac arrests occurred in the medicine, surgery and pediatric wards. Basic life support (BLS) was started within 1 minute in 83.1% and advanced life support (ALS) was started within 4 minutes in 78.6%. Of 516 (18.8%) patients were terminal cases. Outcomes of CPR were as follows: 49.8% had ROSC, 21% survived at 24 hours, and 7.4% survived to discharge. From a logistic regression analysis, predicting factors for both ROSC and survival to discharge included non-terminal cases, witnessed arrest, non-cardiac, non-sepsis causes, and arrest during daytime. The rate of ROSC and survival to discharge from the Siriraj CPR registry were 49.8% and 7.4% respectively. Several factors can be used to predict the immediate outcome of CPR. The present analysis should help monitor the quality of CPR and post-resuscitation care and aid in the strategic planning to improve CPR outcomes.

  7. Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy.

    Science.gov (United States)

    Asadi, Hamed; Dowling, Richard; Yan, Bernard; Mitchell, Peter

    2014-01-01

    Stroke is a major cause of death and disability. Accurately predicting stroke outcome from a set of predictive variables may identify high-risk patients and guide treatment approaches, leading to decreased morbidity. Logistic regression models allow for the identification and validation of predictive variables. However, advanced machine learning algorithms offer an alternative, in particular, for large-scale multi-institutional data, with the advantage of easily incorporating newly available data to improve prediction performance. Our aim was to design and compare different machine learning methods, capable of predicting the outcome of endovascular intervention in acute anterior circulation ischaemic stroke. We conducted a retrospective study of a prospectively collected database of acute ischaemic stroke treated by endovascular intervention. Using SPSS®, MATLAB®, and Rapidminer®, classical statistics as well as artificial neural network and support vector algorithms were applied to design a supervised machine capable of classifying these predictors into potential good and poor outcomes. These algorithms were trained, validated and tested using randomly divided data. We included 107 consecutive acute anterior circulation ischaemic stroke patients treated by endovascular technique. Sixty-six were male and the mean age of 65.3. All the available demographic, procedural and clinical factors were included into the models. The final confusion matrix of the neural network, demonstrated an overall congruency of ∼ 80% between the target and output classes, with favourable receiving operative characteristics. However, after optimisation, the support vector machine had a relatively better performance, with a root mean squared error of 2.064 (SD: ± 0.408). We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter datasets, likely further improving prediction. Finally, we

  8. Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy.

    Directory of Open Access Journals (Sweden)

    Hamed Asadi

    Full Text Available INTRODUCTION: Stroke is a major cause of death and disability. Accurately predicting stroke outcome from a set of predictive variables may identify high-risk patients and guide treatment approaches, leading to decreased morbidity. Logistic regression models allow for the identification and validation of predictive variables. However, advanced machine learning algorithms offer an alternative, in particular, for large-scale multi-institutional data, with the advantage of easily incorporating newly available data to improve prediction performance. Our aim was to design and compare different machine learning methods, capable of predicting the outcome of endovascular intervention in acute anterior circulation ischaemic stroke. METHOD: We conducted a retrospective study of a prospectively collected database of acute ischaemic stroke treated by endovascular intervention. Using SPSS®, MATLAB®, and Rapidminer®, classical statistics as well as artificial neural network and support vector algorithms were applied to design a supervised machine capable of classifying these predictors into potential good and poor outcomes. These algorithms were trained, validated and tested using randomly divided data. RESULTS: We included 107 consecutive acute anterior circulation ischaemic stroke patients treated by endovascular technique. Sixty-six were male and the mean age of 65.3. All the available demographic, procedural and clinical factors were included into the models. The final confusion matrix of the neural network, demonstrated an overall congruency of ∼ 80% between the target and output classes, with favourable receiving operative characteristics. However, after optimisation, the support vector machine had a relatively better performance, with a root mean squared error of 2.064 (SD: ± 0.408. DISCUSSION: We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter

  9. Overgeneral memory predicts stability of short-term outcome of electroconvulsive therapy for depression.

    Science.gov (United States)

    Raes, Filip; Sienaert, Pascal; Demyttenaere, Koen; Peuskens, Joseph; Williams, J Mark G; Hermans, Dirk

    2008-03-01

    To investigate the predictive value of overgeneral memory (OGM) for outcome of electroconvulsive therapy (ECT) for depression. The Autobiographical Memory Test was used to measure OGM in 25 patients with depression before ECT. The Hamilton Rating Scale for Depression (HRSD) was administered weekly to 1 week posttreatment. Overgeneral memory did not predict HRSD scores from the last ECT treatment, but did predict HRSD change scores from the last treatment to 1-week follow-up: patients high in OGM experienced a relatively greater increase in HRSD scores after the last treatment. Results further extend the status of OGM as a predictor of an unfavorable course of depression to a previously unstudied ECT population.

  10. The predictive value of childhood subthreshold manic symptoms for adolescent and adult psychiatric outcomes

    NARCIS (Netherlands)

    Papachristou, Efstathios; Oldehinkel, Albertine J.; Ormel, Johan; Raven, Dennis; Hartman, Catharina A.; Frangou, Sophia; Reichenberg, Abraham

    2017-01-01

    Background: Childhood subthreshold manic symptoms may represent a state of developmental vulnerability to Bipolar Disorder (BD) and may also be associated with other adverse psychiatric outcomes. To test this hypothesis we examined the structure and predictive value of childhood subthreshold manic

  11. Can the outcome of pelvic-floor rehabilitation in patients with fecal incontinence be predicted?

    NARCIS (Netherlands)

    M.P. Terra (Maaike); M. Deutekom (Marije); A.C. Dobben (Annette); C.G.M.I. Baeten; L.W.M. Janssen (Lucas); G.E. Boeckxstaens (Guy); A.F. Engel (Alexander); R.J.F. Felt-Bersma; J.F.W. Slors; M.F. Gerhards (Michael); A.B. Bijnen (Bart); E. Everhardt; W.R. Schouten (Ruud); B. Berghmans; P.M.M. Bossuyt (Patrick); J. Stoker (Jacob)

    2008-01-01

    textabstractPurpose: Pelvic-floor rehabilitation does not provide the same degree of relief in all fecal incontinent patients. We aimed at studying prospectively the ability of tests to predict the outcome of pelvic-floor rehabilitation in patients with fecal incontinence. Materials and methods: Two

  12. Overview of data-synthesis in systematic reviews of studies on outcome prediction models

    NARCIS (Netherlands)

    T. van den Berg (Tobias); M.W. Heymans (Martijn); O. Leone; D. Vergouw (David); J. Hayden (Jill); A.P. Verhagen (Arianne); H.C. de Vet (Henrica C)

    2013-01-01

    textabstractBackground: Many prognostic models have been developed. Different types of models, i.e. prognostic factor and outcome prediction studies, serve different purposes, which should be reflected in how the results are summarized in reviews. Therefore we set out to investigate how authors of

  13. Does ultrasonographic foetal head position prior to induction of labour predict the outcome of delivery?

    NARCIS (Netherlands)

    Verhoeven, Corine J. M.; Mulders, Leon G. M.; Oei, S. Guid; Mol, Ben Willem J.

    2012-01-01

    Objective: To examine the capacity of pre-induction sonographic assessment of occipital position of the foetal head to predict the outcome of delivery, and to assess whether sonographic foetal head position before induction of labour is related to foetal presentation at delivery. Study design: A

  14. Combining biological gene expression signatures in predicting outcome in breast cancer: An alternative to supervised classification

    NARCIS (Netherlands)

    Nuyten, Dimitry S. A.; Hastie, Trevor; Chi, Jen-Tsan Ashley; Chang, Howard Y.; van de Vijver, Marc J.

    2008-01-01

    INTRODUCTION: Gene expression profiling has been extensively used to predict outcome in breast cancer patients. We have previously reported on biological hypothesis-driven analysis of gene expression profiling data and we wished to extend this approach through the combinations of various gene

  15. Could Learning Outcomes of the First Course in Accounting Predict Overall Academic Performance?

    Science.gov (United States)

    Alanzi, Khalid A.; Alfraih, Mishari M.

    2017-01-01

    Purpose: This study aims to question whether learning outcomes of the first course in accounting could predict the overall academic performance of accounting students as measured by their graduating grade point average (GPA). Design/methodology/approach The sample of the present study was drawn from accounting students who were graduated during…

  16. Predicting outcome after cardiac surgery : comparison of global haemodynamic and tonometric variables

    NARCIS (Netherlands)

    Bams, JL; Mariani, MA; Groeneveld, ABJ

    To compare how outcome can be predicted from global haemodynamic compared with regional perfusion-related variables (gastric intramucosal pH (pHi) and intramucosal-arterial PCO2 difference (Delta PCO2)), we measured global haemodynamics, gastric pHi and Delta PCO2 in 68 haemodynamically compromised

  17. Persistent Hypogonadotropic Hypogonadism in Men After Severe Traumatic Brain Injury: Temporal Hormone Profiles and Outcome Prediction.

    Science.gov (United States)

    Barton, David J; Kumar, Raj G; McCullough, Emily H; Galang, Gary; Arenth, Patricia M; Berga, Sarah L; Wagner, Amy K

    2016-01-01

    To (1) examine relationships between persistent hypogonadotropic hypogonadism (PHH) and long-term outcomes after severe traumatic brain injury (TBI); and (2) determine whether subacute testosterone levels can predict PHH. Level 1 trauma center at a university hospital. Consecutive sample of men with severe TBI between 2004 and 2009. Prospective cohort study. Post-TBI blood samples were collected during week 1, every 2 weeks until 26 weeks, and at 52 weeks. Serum hormone levels were measured, and individuals were designated as having PHH if 50% or more of samples met criteria for hypogonadotropic hypogonadism. At 6 and 12 months postinjury, we assessed global outcome, disability, functional cognition, depression, and quality of life. We recruited 78 men; median (interquartile range) age was 28.5 (22-42) years. Thirty-four patients (44%) had PHH during the first year postinjury. Multivariable regression, controlling for age, demonstrated PHH status predicted worse global outcome scores, more disability, and reduced functional cognition at 6 and 12 months post-TBI. Two-step testosterone screening for PHH at 12 to 16 weeks postinjury yielded a sensitivity of 79% and specificity of 100%. PHH status in men predicts poor outcome after severe TBI, and PHH can accurately be predicted at 12 to 16 weeks.

  18. Persistent hypogonadotropic hypogonadism in men after severe traumatic brain injury: temporal hormone profiles and outcome prediction

    Science.gov (United States)

    Barton, David J.; Kumar, Raj G.; McCullough, Emily H.; Galang, Gary; Arenth, Patricia M.; Berga, Sarah L.; Wagner, Amy K.

    2015-01-01

    Objective (1) Examine relationships between persistent hypogonadotropic hypogonadism (PHH) and long-term outcomes after severe traumatic brain injury (TBI); (2) determine if sub-acute testosterone levels can predict PHH. Setting Level 1 trauma center at a university hospital. Participants Consecutive sample of men with severe TBI between 2004 and 2009. Design Prospective cohort study. Main Measures Post-TBI blood samples were collected during week 1, every 2 weeks until 26 weeks, and at 52 weeks. Serum hormone levels were measured, and individuals were designated as having PHH if ≥50% of samples met criteria for hypogonadotropic hypogonadism. At 6 and 12 months post-injury, we assessed global outcome, disability, functional cognition, depression, and quality-of-life. Results We recruited 78 men; median (IQR) age was 28.5 (22–42) years. 34 patients (44%) had PHH during the first year post-injury. Multivariable regression, controlling for age, demonstrated PHH status predicted worse global outcome scores, more disability, and reduced functional cognition at 6 and 12 months post-TBI. Two-step testosterone screening for PHH at 12–16 weeks post-injury yielded a sensitivity of 79% and specificity of 100%. Conclusion PHH status in men predicts poor outcome after severe TBI, and PHH can accurately be predicted at 12–16 weeks. PMID:26360007

  19. Prediction of outcome in mild to moderate head injury : A review

    NARCIS (Netherlands)

    van der Naalt, J

    2001-01-01

    This paper reviews the functional outcome of patients sustaining mild and moderate head injury (HI). Discrepancies across studies in the definition of minor, mild, and moderate HI are discussed in terms of hindering the interpretation of recovery. The predictive value of acute severity indices,

  20. Prognostic factors for predicting outcomes after intramedullary nailing of the tibia

    NARCIS (Netherlands)

    Schemitsch, Emil H.; Bhandari, Mohit; Guyatt, Gordon; Sanders, David W.; Swiontkowski, Marc; Tornetta, Paul; Walter, Stephen D.; Zdero, Rad; Goslings, J. C.; Teague, David; Jeray, Kyle; McKee, Michael D.; Sprague, Sheila; Heels-Ansdell, Diane; Buckingham, Lisa; Leece, Pamela; Viveiros, Helena; Mignott, Tashay; Ansell, Natalie; Sidorkewicz, Natalie; Agel, Julie; Bombardier, Claire; Berlin, Jesse A.; Bosse, Michael; Browner, Bruce; Gillespie, Brenda; Jones, Alan; O'Brien, Peter; Poolman, Rudolf; Kreder, Hans J.; Stephen, David J. G.; Axelrod, Terry S.; Yee, Albert J. M.; Richards, Robin R.; Finkelstein, Joel; Gofton, Wade; Murnaghan, John; Schatztker, Joseph; Ford, Michael; Bulmer, Beverly; Conlan, Lisa; Laflamme, G. Yves; Berry, Gregory; Beaumont, Pierre; Ranger, Pierre; Laflamme, Georges-Henri; Gagnon, Sylvain; Malo, Michel; Fernandes, Julio; Poirier, Marie-France; Waddell, James P.; Bogoch, Earl R.; Daniels, Timothy R.; McBroom, Robert R.; Vicente, Milena R.; Storey, Wendy; Wild, Lisa M.; McCormack, Robert; Perey, Bertrand; Goetz, Thomas J.; Pate, Graham; Penner, Murray J.; Panagiotopoulos, Kostas; Pirani, Shafique; Dommisse, Ian G.; Loomer, Richard L.; Stone, Trevor; Moon, Karyn; Zomar, Mauri; Webb, Lawrence X.; Teasdall, Robert D.; Birkedal, John Peter; Martin, David Franklin; Ruch, David S.; Kilgus, Douglas J.; Pollock, David C.; Harris, Mitchel Brion; Wiesler, Ethan Ron; Ward, William G.; Shilt, Jeffrey Scott; Koman, Andrew L.; Poehling, Gary G.; Kulp, Brenda; Creevy, William R.; Stein, Andrew B.; Bono, Christopher T.; Einhorn, Thomas A.; Brown, Desmond; Pacicca, Donna; Sledge, John B.; Foster, Timothy E.; Voloshin, Ilva; Bolton, Jill; Carlisle, Hope; Shaughnessy, Lisa; Obremskey, William T.; LeCroy, C. Michael; Meinberg, Eric G.; Messer, Terry M.; Craig, William L.; Dirschl, Douglas R.; Caudle, Robert; Harris, Tim; Elhert, Kurt; Hage, William; Jones, Robert; Piedrahita, Luis; Schricker, Paul O.; Driver, Robin; Godwin, Jean; Kregor, Philip James; Tennent, Gregory; Truchan, Lisa M.; Sciadini, Marcus; Shuler, Franklin D.; Driver, Robin E.; Nading, Mary Alice; Neiderstadt, Jacky; Vap, Alexander R.; Vallier, Heather A.; Patterson, Brendan M.; Wilber, John H.; Wilber, Roger G.; Sontich, John K.; Moore, Timothy Alan; Brady, Drew; Cooperman, Daniel R.; Davis, John A.; Cureton, Beth Ann; Mandel, Scott; Orr, R. Douglas; Sadler, John T. S.; Hussain, Tousief; Rajaratnam, Krishan; Petrisor, Bradley; Drew, Brian; Bednar, Drew A.; Kwok, Desmond C. H.; Pettit, Shirley; Hancock, Jill; Cole, Peter A.; Smith, Joel J.; Brown, Gregory A.; Lange, Thomas A.; Stark, John G.; Levy, Bruce A.; Swiontkowski, Marc F.; Garaghty, Mary J.; Salzman, Joshua G.; Schutte, Carol A.; Tastad, Linda; Vang, Sandy; Seligson, David; Roberts, Craig S.; Malkani, Arthur L.; Sanders, Laura; Dyer, Carmen; Heinsen, Jessica; Smith, Langan; Madanagopal, Sudhakar; Frantz-Bush, Linda; Coupe, Kevin J.; Tucker, Jeffrey J.; Criswell, Allen R.; Buckle, Rosemary; Rechter, Alan Jeffrey; Sheth, Dhiren Shaskikant; Urquart, Brad; Trotscher, Thea; Anders, Mark J.; Kowalski, Joseph M.; Fineberg, Marc S.; Bone, Lawrence B.; Phillips, Matthew J.; Rohrbacher, Bernard; Stegemann, Philip; Mihalko, William M.; Buyea, Cathy; Augustine, Stephen J.; Jackson, William Thomas; Solis, Gregory; Ero, U.; Segina, Daniel N.; Berrey, Hudson B.; Agnew, Samuel G.; Fitzpatrick, Michael; Campbell, Lakina C.; Derting, Lynn; McAdams, June; Ponsen, Kees Jan; Kloen, Peter; Joosse, Pieter; Winkelhagen, Jasper; Duivenvoorden, Raphaël; Teague, David C.; Davey, Joseph; Sullivan, J. Andy; Ertl, William J. J.; Puckett, Timothy A.; Pasque, Charles B.; Tompkins, John F.; Gruel, Curtis R.; Kammerlocher, Paul; Lehman, Thomas P.; Puffinbarger, William R.; Carl, Kathy L.; Weber, Donald W.; Jomha, Nadr M.; Goplen, Gordon R.; Masson, Edward; A, Lauren; Schaump, Lori N.; Jeray, Kyle J.; Goetz, David R.; Westberry, David E.; Broderick, J. Scott; Moon, Bryan S.; Tanner, Stephanie L.; Powell, James N.; Buckley, Richard E.; Elves, Leslie; John, Saint; Connolly, Stephen; Abraham, Edward P.; Steele, Trudy; Ellis, Thomas; Herzberg, Alex; Brown, George A.; Crawford, Dennis E.; Hart, Robert; Hayden, James; Orfaly, Robert M.; Vigland, Theodore; Vivekaraj, Maharani; Bundy, Gina L.; Miclau, Theodore; Matityahu, Amir; Coughlin, R. Richard; Kandemir, Utku; McClellan, R. Trigg; Lin, Cindy Hsin-Hua; Karges, David; Cramer, Kathryn; Watson, J. Tracy; Moed, Berton; Scott, Barbara; Beck, Dennis J.; Orth, Carolyn; Puskas, David; Clark, Russell; Jones, Jennifer; Egol, Kenneth A.; Paksima, Nader; Wai, Eugene K.; Johnson, Garth; Wilkinson, Ross; Gruszczynski, Adam T.; Vexler, Liisa

    2012-01-01

    Prediction of negative postoperative outcomes after long-bone fracture treatment may help to optimize patient care. We recently completed the Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT), a large, multicenter trial of reamed and unreamed

  1. Outcome Prediction in Moderate and Severe Traumatic Brain Injury: A Focus on Computed Tomography Variables

    NARCIS (Netherlands)

    Jacobs, Bram; Beems, Tjemme; van der Vliet, Ton M.; van Vugt, Arie B.; Hoedemaekers, Cornelia; Horn, Janneke; Franschman, Gaby; Haitsma, Ian; van der Naalt, Joukje; Andriessen, Teuntje M. J. C.; Borm, George F.; Vos, Pieter E.

    2013-01-01

    With this study we aimed to design validated outcome prediction models in moderate and severe traumatic brain injury (TBI) using demographic, clinical, and radiological parameters. Seven hundred consecutive moderate or severe TBI patients were included in this observational prospective cohort study.

  2. Early Prediction of Outcome of Activities of Daily Living After Stroke A Systematic Review

    NARCIS (Netherlands)

    Veerbeek, Janne M.; Kwakkel, Gert; van Wegen, Erwin E. H.; Ket, Johannes C. F.; Heymans, Martijn W.

    Background and Purpose-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables

  3. Pain drawings predict outcome of surgical treatment for degenerative disc disease in the cervical spine.

    Science.gov (United States)

    MacDowall, Anna; Robinson, Yohan; Skeppholm, Martin; Olerud, Claes

    2017-08-01

    Pain drawings have been frequently used in the preoperative evaluation of spine patients. For lumbar conditions comprehensive research has established both the reliability and predictive value, but for the cervical spine most of this knowledge is lacking. The aims of this study were to validate pain drawings for the cervical spine, and to investigate the predictive value for treatment outcome of four different evaluation methods. We carried out a post hoc analysis of a randomized controlled trial, comparing cervical disc replacement to fusion for radiculopathy related to degenerative disc disease. A pain drawing together with Neck Disability Index (NDI) was completed preoperatively, after 2 and 5 years. The inter- and intraobserver reliability of four evaluation methods was tested using κ statistics, and its predictive value investigated by correlation to change in NDI. Included were 151 patients, mean age of 47 years, female/male: 78/73. The interobserver reliability was fair for the modified Ransford and Udén methods, good for the Gatchel method, and very good for the modified Ohnmeiss method. Markings in the shoulder and upper arm region on the pain drawing were positive predictors of outcome after 2 years of follow-up, and markings in the upper arm region remained a positive predictor of outcome even after 5 years of follow-up. Pain drawings were a reliable tool to interpret patients' pain prior to cervical spine surgery and were also to some extent predictive for treatment outcome.

  4. Intratumoral genome diversity parallels progression and predicts outcome in pediatric cancer

    NARCIS (Netherlands)

    Mengelbier, Linda Holmquist; Karlsson, Jenny; Lindgren, David; Valind, Anders; Lilljebjörn, Henrik; Jansson, Caroline; Bexell, Daniel; Braekeveldt, Noémie; Ameur, Adam; Jonson, Tord; Kultima, Hanna Göransson; Isaksson, Anders; Asmundsson, Jurate; Versteeg, Rogier; Rissler, Marianne; Fioretos, Thoas; Sandstedt, Bengt; Börjesson, Anna; Backman, Torbjörn; Pal, Niklas; Øra, Ingrid; Mayrhofer, Markus; Gisselsson, David

    2015-01-01

    Genetic differences among neoplastic cells within the same tumour have been proposed to drive cancer progression and treatment failure. Whether data on intratumoral diversity can be used to predict clinical outcome remains unclear. We here address this issue by quantifying genetic intratumoral

  5. A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

    NARCIS (Netherlands)

    C. Staiger (Christine); S. Cadot; R Kooter; M. Dittrich (Marcus); T. Müller (Tobias); G.W. Klau (Gunnar); L.F.A. Wessels (Lodewyk)

    2011-01-01

    htmlabstractRecently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically

  6. A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer

    NARCIS (Netherlands)

    C. Staiger (Christine); S. Cadot; R Kooter; M. Dittrich (Marcus); T. Müller (Tobias); G.W. Klau (Gunnar); L.F.A. Wessels (Lodewyk)

    2012-01-01

    htmlabstractRecently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically

  7. What predicts a poor outcome in older stroke survivors? A systematic review of the literature

    NARCIS (Netherlands)

    van Almenkerk, S.; Smalbrugge, M.; Depla, M.F.I.A.; Eefsting, J.A.; Hertogh, C.M.P.M.

    2013-01-01

    Purpose: To identify factors in the early post-stroke period that have a predictive value for a poor outcome, defined as institutionalization or severe disability. Methods: MEDLINE, PSYCINFO, EMBASE and CINAHL were systematically searched for observational cohort studies in which adult and/or

  8. Comparison of HIV-1 genotypic resistance test interpretation systems in predicting virological outcomes over time

    NARCIS (Netherlands)

    D. Frentz (Dineke); C.A.B. Boucher (Charles); M. Assel (Matthias); A. de Luca (Andrea); M. Fabbiani (Massimiliano); F. Incardona (Francesca); P. Libin (Pieter); N. Manca (Nino); V. Müller (Viktor); B.O. Nualláin (Breanndán); R. Paredes (Roger); M. Prosperi (Mattia); E. Quiros-Roldan (Eugenia); L. Ruiz (Lidia); P.M.A. Sloot (Peter); C. Torti (Carlo); A.M. Vandamme (Anne Mieke); K. Laethem (Kristel); M. Zazzi (Maurizio); D.A.M.C. van de Vijver (David)

    2010-01-01

    textabstractBackground: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks.

  9. Early Intervention for Young Children with Attention Deficit Hyperactivity Disorder: Prediction of Academic and Behavioral Outcomes

    Science.gov (United States)

    DuPaul, George J.; Kern, Lee; Caskie, Grace I. L.; Volpe, Robert J.

    2015-01-01

    We examined the degree to which child, family, and treatment variables predicted treatment outcomes for reading and math achievement and oppositional behavior in a sample of 135 young children (105 boys and 30 girls). All of the participants met "Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision"…

  10. EEG Estimates of Cognitive Workload and Engagement Predict Math Problem Solving Outcomes

    Science.gov (United States)

    Beal, Carole R.; Galan, Federico Cirett

    2012-01-01

    In the present study, the authors focused on the use of electroencephalography (EEG) data about cognitive workload and sustained attention to predict math problem solving outcomes. EEG data were recorded as students solved a series of easy and difficult math problems. Sequences of attention and cognitive workload estimates derived from the EEG…

  11. Can Assessment Reactivity Predict Treatment Outcome among Adolescents with Alcohol and Other Substance Use Disorders?

    Science.gov (United States)

    Kaminer, Yifrah; Burleson, Joseph A.; Burke, Rebecca H.

    2008-01-01

    The objectives of this paper are two-fold: to examine first, if the change from positive to negative alcohol and any other substance use status from baseline assessment to the onset of the first session (i.e., pre-treatment phase) occurs in adolescents, that is, Assessment Reactivity (AR); second, whether AR predicts treatment outcome.…

  12. Collateral flow predicts outcome after basilar artery occlusion : The posterior circulation collateral score

    NARCIS (Netherlands)

    van der Hoeven, Erik J R J; McVerry, Ferghal; Vos, Jan Albert; Algra, Ale; Puetz, Volker; Kappelle, L. Jaap; Schonewille, Wouter J.

    2016-01-01

    BACKGROUND AND AIM: Our aim was to assess the prognostic value of a semiquantitative computed tomography angiography-based grading system, for the prediction of outcome in patients with acute basilar artery occlusion, based on the presence of potential collateral pathways on computed tomography

  13. Predicting mobility outcome one year after stroke: a prospective cohort study.

    NARCIS (Netherlands)

    Port, I.G. van de; Kwakkel, G.; Schepers, V.P.; Lindeman, E.

    2006-01-01

    OBJECTIVE: To develop a prognostic model to predict mobility outcome one year post-stroke. DESIGN: Prospective cohort study in patients with a first-ever stroke admitted for inpatient rehabilitation. PATIENTS: A total of 217 patients with stroke (mean age 58 years) following inpatient rehabilitation

  14. Early prediction of outcome of activities of daily living after stroke: a systematic review

    NARCIS (Netherlands)

    Veerbeek, J.M.; Kwakkel, G.; van Wegen, E.E.H.; Ket, J.C.F.; Heijmans, M.W.

    2011-01-01

    BACKGROUND AND PURPOSE-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables

  15. And yet they correlate: psychophysiological activation predicts self-report outcomes of exposure therapy in claustrophobia.

    Science.gov (United States)

    Alpers, Georg W; Sell, Roxane

    2008-10-01

    The study examines whether self-reported fear and physiological activation are concordant when claustrophobic patients are exposed to small spaces, whether the measures change in synchrony for individual patients and whether initial activation of measures can predict the outcome of an exposure treatment. Ten patients with claustrophobia participated in six in-vivo exposure sessions with continuous monitoring of self-reported fear and their EKG. Partial pressure of carbon dioxide (pCO(2)), a measure of hyperventilation, was available in a subsample of patients. While evidence for concordance of self-reported fear and heart rate was limited, the measures changed synchronously within subjects. Most importantly, higher heart rate at the beginning of the first exposure session predicted better treatment outcome. Because self-reported fear turned out not to be a reliable predictor of the outcome, this is interpreted as evidence for the incremental validity of physiological measures of fear.

  16. Cerebrospinal fluid neurofilament light chain levels predict visual outcome after optic neuritis

    DEFF Research Database (Denmark)

    Modvig, Signe; Degn, M; Sander, B

    2016-01-01

    BACKGROUND: Optic neuritis is a good model for multiple sclerosis relapse, but currently no tests can accurately predict visual outcome. OBJECTIVE: The purpose of this study was to examine whether cerebrospinal fluid (CSF) biomarkers of tissue damage and remodelling (neurofilament light chain (NF......-L), myelin basic protein, osteopontin and chitinase-3-like-1) predict visual outcome after optic neuritis. METHODS: We included 47 patients with optic neuritis as a first demyelinating episode. Patients underwent visual tests, optical coherence tomography (OCT), magnetic resonance imaging (MRI) and lumbar...... puncture. Biomarkers were measured in CSF by enzyme-linked immunosorbent assay (ELISA). Patients were followed up six months after onset and this included visual tests and OCT. Outcome measures were inter-ocular differences in low contrast visual acuity (LCVA), retinal nerve fibre layer (RNFL) and ganglion...

  17. Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

    Directory of Open Access Journals (Sweden)

    Rubén Armañanzas

    Full Text Available Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE. Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery.

  18. Trait body shame predicts health outcomes in college women: A longitudinal investigation.

    Science.gov (United States)

    Lamont, Jean M

    2015-12-01

    Trait body shame impacts psychological health, but its influence on physical health heretofore has not been examined. While body shame may be expected to impact physical health through many mechanisms, this investigation tested whether trait body shame predicts physical health outcomes by promoting negative attitudes toward bodily processes, thereby diminishing health evaluation and ultimately impacting physical health. Correlational (Study 1, N = 177) and longitudinal (Study 2, N = 141) studies tested hypotheses that trait body shame would predict infections, self-rated health, and symptoms, and that body responsiveness and health evaluation would mediate these relationships. In Study 1, trait body shame predicted all three poor health outcomes, and body responsiveness and health evaluation mediated these relationships. Study 2 partially replicated these results while controlling for depression, smoking, and BMI, and longitudinal analyses supported the temporal precedence of trait body shame in the proposed model. Limitations and alternative pathways are discussed.

  19. Learning stochastic finite-state transducer to predict individual patient outcomes.

    Science.gov (United States)

    Ordoñez, Patricia; Schwarz, Nelson; Figueroa-Jiménez, Adnel; Garcia-Lebron, Leonardo A; Roche-Lima, Abiel

    2016-01-01

    The high frequency data in intensive care unit is flashed on a screen for a few seconds and never used again. However, this data can be used by machine learning and data mining techniques to predict patient outcomes. Learning finite-state transducers (FSTs) have been widely used in problems where sequences need to be manipulated and insertions, deletions and substitutions need to be modeled. In this paper, we learned the edit distance costs of a symbolic univariate time series representation through a stochastic finite-state transducer to predict patient outcomes in intensive care units. The Nearest-Neighbor method with these learned costs was used to classify the patient status within an hour after 10 h of data. Several experiments were developed to estimate the parameters that better fit the model regarding the prediction metrics. Our best results are compared with published works, where most of the metrics (i.e., Accuracy, Precision and F-measure) were improved.

  20. First-trimester sonographic prediction of obstetric and neonatal outcomes in monochorionic diamniotic twin pregnancies.

    Science.gov (United States)

    Allaf, M Baraa; Vintzileos, Anthony M; Chavez, Martin R; Wax, Joseph A; Ravangard, Samadh F; Figueroa, Reinaldo; Borgida, Adam; Shamshirsaz, Amir; Markenson, Glenn; Davis, Sarah; Habenicht, Rebecca; Haeri, Sina; Ozhand, Ali; Johnson, Jeffery; Sangi-Haghpeykar, Haleh; Spiel, Melissa; Ruano, Rodrigo; Meyer, Marjorie; Belfort, Michael A; Ogburn, Paul; Campbell, Winston A; Shamshirsaz, Alireza A

    2014-01-01

    The purpose of this study was to investigate whether discordant nuchal translucency and crown-rump length measurements in monochorionic diamniotic twins are predictive of adverse obstetric and neonatal outcomes. We conducted a multicenter retrospective cohort study including all monochorionic diamniotic twin pregnancies with two live fetuses at the 11-week to 13-week 6-day sonographic examination who had serial follow-up sonography until delivery. Isolated nuchal translucency, crown-rump length, and combined discordances were correlated with adverse obstetric outcomes, individually and in composite, including the occurrence of 1 or more of the following in either fetus: intrauterine growth restriction (IUGR), twin-twin transfusion syndrome (TTTS), intrauterine fetal death (IUFD), growth discordance (≥ 20%), and preterm birth before 28 weeks' gestation. Correlations with adverse composite neonatal outcomes were also studied. A receiver operating characteristic curve analysis and a logistic regression analysis with a generalized estimating equation were conducted. Fifty-four of the 177 pregnancies included (31%) had an adverse composite obstetric outcome, with TTTS in 19 (11%), IUGR in 21 (12%), discordant growth in 14 (8%), IUFD in 14 (8%), and preterm birth before 28 weeks in 10 (6%). Of the 254 neonates included in the study, 69 (27%) were complicated by adverse composite neonatal outcomes, with respiratory distress syndrome being the most common (n = 59 [23%]). The areas under the curve for the combined discordances to predict composite obstetric and neonatal outcomes were 0.62 (95% confidence interval, 0.52-0.72), and 0.54 (95% confidence interval, 0.46-0.61), respectively. In our population, nuchal translucency, crown-rump length, and combined discordances in monochorionic diamniotic twin pregnancies were not predictive of adverse composite obstetric and neonatal outcomes.

  1. Chronic health conditions and depressive symptoms strongly predict persistent food insecurity among rural low-income families.

    Science.gov (United States)

    Hanson, Karla L; Olson, Christine M

    2012-08-01

    Longitudinal studies of food insecurity have not considered the unique circumstances of rural families. This study identified factors predictive of discontinuous and persistent food insecurity over three years among low-income families with children in rural counties in 13 U.S. states. Respondents reported substantial knowledge of community resources, food and finance skills, and use of formal public food assistance, yet 24% had persistent food insecurity, and another 41% were food insecure for one or two years. Multivariate multinomial regression models tested relationships between human capital, social support, financial resources, expenses, and food insecurity. Enduring chronic health conditions increased the risk of both discontinuous and persistent food insecurity. Lasting risk for depression predicted only persistent food insecurity. Education beyond high school was the only factor found protective against persistent food insecurity. Access to quality physical and mental health care services are essential to ameliorate persistent food insecurity among rural, low-income families.

  2. Self-Conscious Shyness: Growth during Toddlerhood, Strong Role of Genetics, and No Prediction from Fearful Shyness

    OpenAIRE

    Eggum-Wilkens, Natalie D.; Lemery-Chalfant, Kathryn; Aksan, Nazan; Goldsmith, H. Hill

    2014-01-01

    Fearful and self-conscious subtypes of shyness have received little attention in the empirical literature. Study aims included: 1) determining if fearful shyness predicted self-conscious shyness, 2) describing development of self-conscious shyness, and 3) examining genetic and environmental contributions to fearful and self-conscious shyness. Observed self-conscious shyness was examined at 19, 22, 25, and 28 months in same-sex twins (MZ = 102, DZ = 111, missing zygosity = 3 pairs). Self-consc...

  3. Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients

    Directory of Open Access Journals (Sweden)

    Saeed Safari

    2016-01-01

    Full Text Available Background: Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL, Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE score clinical decision rules in predicting the short-term serious outcome of syncope patients. Materials and Methods: The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI, and cerebrovascular accidents (CVAs were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC curve analysis was done. Results: A total of 187 patients (mean age: 64.2 ΁ 17.2 years were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%, 12 (6.4%, and 36 (19.2% patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models (P > 0.05. The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others (P > 0.05. Conclusion: This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

  4. Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients.

    Science.gov (United States)

    Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

    2016-01-01

    Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models ( P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others ( P > 0.05). This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

  5. Comparison of risk-scoring systems in the prediction of outcome after liver resection

    Directory of Open Access Journals (Sweden)

    S. Ulyett

    2017-11-01

    Full Text Available Abstract Background Risk prediction techniques commonly used in liver surgery include the American Society of Anesthesiologists (ASA grading, Charlson Comorbidity Index (CCI and cardiopulmonary exercise tests (CPET. This study compares the utility of these techniques along with the number of segments resected as predictive tools in liver surgery. Methods A review of a unit database of patients undergoing liver resection between February 2008 and January 2015 was undertaken. Patient demographics, ASA, CCI and CPET variables were recorded along with resection size. Clavien-Dindo grade III–V complications were used as a composite outcome in analyses. Association between predictive variables and outcome was assessed by univariate and multivariate techniques. Results One hundred and seventy-two resections in 168 patients were identified. Grade III–V complications occurred after 42 (24.4% liver resections. In univariate analysis of CPET variables, ventilatory equivalents for CO2 (VEqCO2 was associated with outcome. CCI score, but not ASA grade, was also associated with outcome. In multivariate analysis, the odds ratio of developing grade III–V complications for incremental increases in VEqCO2, CCI and number of liver segments resected were 1.09, 1.49 and 2.94, respectively. Conclusions Of the techniques evaluated, resection size provides the simplest and most discriminating predictor of significant complications following liver surgery.

  6. Noninvasive Bioelectrical Impedance for Predicting Clinical Outcomes in Outpatients With Heart Failure.

    Science.gov (United States)

    Lyons, Kristin J; Bischoff, Michelle K; Fonarow, Gregg C; Horwich, Tamara B

    2017-03-01

    Noninvasive bioelectrical impedance analysis (BIA) has shown promise in acute heart failure (HF) management. To our knowledge, its use in predicting outcomes in outpatients with chronic HF patients has not been well described. BIA assessment of edema index was performed in 359 outpatients with HF using the InBody 520 scale. Edema index was calculated by dividing extracellular by total body water. Patients were stratified into those with low (≤0.39) and high (>0.39) edema indices. The outcome of interest was death, urgent transplant, or ventricular assist device over 2-year follow up. Patients with a high edema index were older, had higher B-type natriuretic peptide values and New York Heart Association Class. Patients with a high edema index had poorer outcomes (unadjusted hazard ratio 1.90, 95% confidence intervals 1.05-3.56). However, in multivariate analyses, a high edema index was not an independent predictor of outcomes (adjusted hazard ratio 1.21, 95% confidence interval 0.51-2.90). A high edema index using a bioimpedance scale in a HF clinic correlated with patient outcomes in unadjusted analyses, but was not a predictor of outcomes once other measures of HF severity are accounted for. As a noninvasive measure of volume status, use of BIA in a HF clinic may be beneficial in determining patient prognosis and treatment when other outcome predictors are not immediately available.

  7. Role of nutritional status in predicting quality of life outcomes in cancer--a systematic review of the epidemiological literature.

    Science.gov (United States)

    Lis, Christopher G; Gupta, Digant; Lammersfeld, Carolyn A; Markman, Maurie; Vashi, Pankaj G

    2012-04-24

    Malnutrition is a significant factor in predicting cancer patients' quality of life (QoL). We systematically reviewed the literature on the role of nutritional status in predicting QoL in cancer. We searched MEDLINE database using the terms "nutritional status" in combination with "quality of life" together with "cancer". Human studies published in English, having nutritional status as one of the predictor variables, and QoL as one of the outcome measures were included. Of the 26 included studies, 6 investigated head and neck cancer, 8 gastrointestinal, 1 lung, 1 gynecologic and 10 heterogeneous cancers. 24 studies concluded that better nutritional status was associated with better QoL, 1 study showed that better nutritional status was associated with better QoL only in high-risk patients, while 1 study concluded that there was no association between nutritional status and QoL. Nutritional status is a strong predictor of QoL in cancer patients. We recommend that more providers implement the American Society of Parenteral and Enteral Nutrition (ASPEN) guidelines for oncology patients, which includes nutritional screening, nutritional assessment and intervention as appropriate. Correcting malnutrition may improve QoL in cancer patients, an important outcome of interest to cancer patients, their caregivers, and families.

  8. Role of nutritional status in predicting quality of life outcomes in cancer – a systematic review of the epidemiological literature

    Science.gov (United States)

    2012-01-01

    Malnutrition is a significant factor in predicting cancer patients’ quality of life (QoL). We systematically reviewed the literature on the role of nutritional status in predicting QoL in cancer. We searched MEDLINE database using the terms “nutritional status” in combination with “quality of life” together with “cancer”. Human studies published in English, having nutritional status as one of the predictor variables, and QoL as one of the outcome measures were included. Of the 26 included studies, 6 investigated head and neck cancer, 8 gastrointestinal, 1 lung, 1 gynecologic and 10 heterogeneous cancers. 24 studies concluded that better nutritional status was associated with better QoL, 1 study showed that better nutritional status was associated with better QoL only in high-risk patients, while 1 study concluded that there was no association between nutritional status and QoL. Nutritional status is a strong predictor of QoL in cancer patients. We recommend that more providers implement the American Society of Parenteral and Enteral Nutrition (ASPEN) guidelines for oncology patients, which includes nutritional screening, nutritional assessment and intervention as appropriate. Correcting malnutrition may improve QoL in cancer patients, an important outcome of interest to cancer patients, their caregivers, and families. PMID:22531478

  9. A predictive scoring instrument for tuberculosis lost to follow-up outcome

    Science.gov (United States)

    2012-01-01

    Background Adherence to tuberculosis (TB) treatment is troublesome, due to long therapy duration, quick therapeutic response which allows the patient to disregard about the rest of their treatment and the lack of motivation on behalf of the patient for improved. The objective of this study was to develop and validate a scoring system to predict the probability of lost to follow-up outcome in TB patients as a way to identify patients suitable for directly observed treatments (DOT) and other interventions to improve adherence. Methods Two prospective cohorts, were used to develop and validate a logistic regression model. A scoring system was constructed, based on the coefficients of factors associated with a lost to follow-up outcome. The probability of lost to follow-up outcome associated with each score was calculated. Predictions in both cohorts were tested using receiver operating characteristic curves (ROC). Results The best model to predict lost to follow-up outcome included the following characteristics: immigration (1 point value), living alone (1 point) or in an institution (2 points), previous anti-TB treatment (2 points), poor patient understanding (2 points), intravenous drugs use (IDU) (4 points) or unknown IDU status (1 point). Scores of 0, 1, 2, 3, 4 and 5 points were associated with a lost to follow-up probability of 2,2% 5,4% 9,9%, 16,4%, 15%, and 28%, respectively. The ROC curve for the validation group demonstrated a good fit (AUC: 0,67 [95% CI; 0,65-0,70]). Conclusion This model has a good capacity to predict a lost to follow-up outcome. Its use could help TB Programs to determine which patients are good candidates for DOT and other strategies to improve TB treatment adherence. PMID:22938040

  10. Black Hole Sign Predicts Poor Outcome in Patients with Intracerebral Hemorrhage.

    Science.gov (United States)

    Li, Qi; Yang, Wen-Song; Chen, Sheng-Li; Lv, Fu-Rong; Lv, Fa-Jin; Hu, Xi; Zhu, Dan; Cao, Du; Wang, Xing-Chen; Li, Rui; Yuan, Liang; Qin, Xin-Yue; Xie, Peng

    2018-01-01

    In spontaneous intracerebral hemorrhage (ICH), black hole sign has been proposed as a promising imaging marker that predicts hematoma expansion in patients with ICH. The aim of our study was to investigate whether admission CT black hole sign predicts hematoma growth in patients with ICH. From July 2011 till February 2016, patients with spontaneous ICH who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan were recruited into the study. The presence of black hole sign on admission non-enhanced CT was independently assessed by 2 readers. The functional outcome was assessed using the modified Rankin Scale (mRS) at 90 days. Univariate and multivariable logistic regression analyses were performed to assess the association between the presence of the black hole sign and functional outcome. A total of 225 patients (67.6% male, mean age 60.3 years) were included in our study. Black hole sign was identified in 32 of 225 (14.2%) patients on admission CT scan. The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, baseline ICH volume, admission Glasgow Coma Scale score, and presence of black hole sign on baseline CT independently predict poor functional outcome at 90 days. There are significantly more patients with a poor functional outcome (defined as mRS ≥4) among patients with black hole sign than those without (84.4 vs. 32.1%, p black hole sign independently predicts poor outcome in patients with ICH. Early identification of black hole sign is useful in prognostic stratification and may serve as a potential therapeutic target for anti-expansion clinical trials. © 2018 S. Karger AG, Basel.

  11. Predictive models of objective oropharyngeal OSA surgery outcomes: Success rate and AHI reduction ratio.

    Science.gov (United States)

    Choi, Ji Ho; Lee, Jae Yong; Cha, Jaehyung; Kim, Kangwoo; Hong, Seung-No; Lee, Seung Hoon

    2017-01-01

    The aim of this study was to develop a predictive model of objective oropharyngeal obstructive sleep apnea (OSA) surgery outcomes including success rate and apnea-hypopnea index (AHI) reduction ratio in adult OSA patients. Retrospective outcome research. All subjects with OSA who underwent oropharyngeal and/or nasal surgery and were followed for at least 3 months were enrolled in this study. Demographic, anatomical [tonsil size (TS) and palate-tongue position (PTP) grade (Gr)], and polysomnographic parameters were analyzed. The AHI reduction ratio (%) was defined as [(postoperative AHI-preoperative AHI) x 100 / postoperative AHI], and surgical success was defined as a ≥ 50% reduction in preoperative AHI with a postoperative AHI predictive equation by Forward Selection likelihood ratio (LR) logistic regression analysis was: [Formula: see text]The best predictive equation according to stepwise multiple linear regression analysis was: [Formula: see text] (TS/PTP Gr = 1 if TS/PTP Gr 3 or 4, TS/PTP Gr = 0 if TS/PTP Gr 1 or 2). The predictive models for oropharyngeal surgery described in this study may be useful for planning surgical treatments and improving objective outcomes in adult OSA patients.

  12. Predictive models of objective oropharyngeal OSA surgery outcomes: Success rate and AHI reduction ratio.

    Directory of Open Access Journals (Sweden)

    Ji Ho Choi

    Full Text Available The aim of this study was to develop a predictive model of objective oropharyngeal obstructive sleep apnea (OSA surgery outcomes including success rate and apnea-hypopnea index (AHI reduction ratio in adult OSA patients.Retrospective outcome research.All subjects with OSA who underwent oropharyngeal and/or nasal surgery and were followed for at least 3 months were enrolled in this study. Demographic, anatomical [tonsil size (TS and palate-tongue position (PTP grade (Gr], and polysomnographic parameters were analyzed. The AHI reduction ratio (% was defined as [(postoperative AHI-preoperative AHI x 100 / postoperative AHI], and surgical success was defined as a ≥ 50% reduction in preoperative AHI with a postoperative AHI < 20.A total of 156 consecutive OSAS adult patients (mean age ± SD = 38.9 ± 9.6, M / F = 149 / 7 were included in this study. The best predictive equation by Forward Selection likelihood ratio (LR logistic regression analysis was: [Formula: see text]The best predictive equation according to stepwise multiple linear regression analysis was: [Formula: see text] (TS/PTP Gr = 1 if TS/PTP Gr 3 or 4, TS/PTP Gr = 0 if TS/PTP Gr 1 or 2.The predictive models for oropharyngeal surgery described in this study may be useful for planning surgical treatments and improving objective outcomes in adult OSA patients.

  13. The role of attachment in predicting CBT treatment outcome in children with anxiety disorders

    DEFF Research Database (Denmark)

    Walczak, Monika Anna; Normann, Nicoline; Tolstrup, Marie

    2015-01-01

    Introduction: Child’s insecure attachment to parents and insecure parental attachment has been linked to childhood anxiety (Brumariu & Kerns, 2010; Manassis et al.,1994).Whether attachment patterns can predict treatment outcome, is yet to be investigated. We examined the role of children’s attach......Introduction: Child’s insecure attachment to parents and insecure parental attachment has been linked to childhood anxiety (Brumariu & Kerns, 2010; Manassis et al.,1994).Whether attachment patterns can predict treatment outcome, is yet to be investigated. We examined the role of children......’s attachment to parents, and parental attachment in predicting treatment outcome in anxious children receiving cognitive-behavioral treatment. Method: A total of 69 children aged 7-13 years were diagnosed at intake and post-treatment, using Anxiety Disorders Interview Schedule for DSM-IV (Silverman and Albano...... style in responders and non-responders in the present sample. We found a significant difference in maternal attachment anxiety scale (p=.011), with mothers of non-responders showing significantly higher attachment anxiety. Binominal logistic regression analysis was used to measure a predictive value...

  14. Communication abnormalities predict functional outcomes in chronic schizophrenia: differential associations with social and adaptive functions.

    Science.gov (United States)

    Bowie, Christopher R; Harvey, Philip D

    2008-08-01

    Communication abnormalities are hallmark features of schizophrenia. Despite the prevalence and persistence of these symptoms, little is known about their functional implications. In this study, we examined, in a sample of chronically institutionalized schizophrenia patients (N=317), whether two types of communication abnormalities (i.e., verbal underproductivity and disconnected speech) had differential relationships with social and adaptive outcomes. Baseline ratings of verbal underproductivity, disconnected speech, global cognitive performance, and clinical symptoms, were entered into stepwise regression analyses to examine their relationship with 2.5 year social and adaptive outcomes. At baseline, disconnected speech was significantly associated with socially impolite behavior, while verbal underproductivity was associated with social disengagement and impaired friendships. Both types of communication abnormalities were significantly associated with other types of social skills. Verbal underproductivity predicted follow-up social skills, social engagement, and friendships, accounting for more variance than. cognition or symptoms. In contrast to social outcomes, adaptive outcomes were predicted by baseline neurocognition and clinical symptoms, but not communication abnormalities. These findings provide evidence for specific relationships of communication disorder subtypes with diverse impairments in social functions. In this chronically institutionalized sample, communication disorder was a stronger predictor of social, but not adaptive, outcomes than neurocognition or clinical symptoms.

  15. Predicting Outcome after Pediatric Traumatic Brain Injury by Early Magnetic Resonance Imaging Lesion Location and Volume

    Science.gov (United States)

    Smitherman, Emily; Hernandez, Ana; Stavinoha, Peter L.; Huang, Rong; Kernie, Steven G.; Diaz-Arrastia, Ramon

    2016-01-01

    Abstract Brain lesions after traumatic brain injury (TBI) are heterogeneous, rendering outcome prognostication difficult. The aim of this study is to investigate whether early magnetic resonance imaging (MRI) of lesion location and lesion volume within discrete brain anatomical zones can accurately predict long-term neurological outcome in children post-TBI. Fluid-attenuated inversion recovery (FLAIR) MRI hyperintense lesions in 63 children obtained 6.2±5.6 days postinjury were correlated with the Glasgow Outcome Scale Extended-Pediatrics (GOS-E Peds) score at 13.5±8.6 months. FLAIR lesion volume was expressed as hyperintensity lesion volume index (HLVI)=(hyperintensity lesion volume / whole brain volume)×100 measured within three brain zones: zone A (cortical structures); zone B (basal ganglia, corpus callosum, internal capsule, and thalamus); and zone C (brainstem). HLVI-total and HLVI-zone C predicted good and poor outcome groups (pCompared to patients with lesions in zone A alone or in zones A and B, patients with lesions in all three zones had a significantly higher odds ratio (4.38; 95% confidence interval, 1.19–16.0) for developing an unfavorable outcome. PMID:25808802

  16. Using the presurgical psychological evaluation to predict 5-year weight loss outcomes in bariatric surgery patients.

    Science.gov (United States)

    Marek, Ryan J; Ben-Porath, Yossef S; Dulmen, Manfred H M van; Ashton, Kathleen; Heinberg, Leslie J

    2017-03-01

    Psychosocial factors contribute to poorer weight loss outcomes following bariatric surgery; however, findings on associations between preoperative psychiatric diagnoses, psychological testing, and weight loss are inconsistent. Examine associations between presurgical psychiatric diagnoses derived from a semi-structured clinical interview and test scores from the Minnesota Multiphasic Personality-Inventory-2 - Restructured Form (MMPI-2-RF) and 5-year Body Mass Index (BMI) outcomes. Cleveland Clinic Bariatric and Metabolic Institute METHODS: 446 consecutively consented patients who underwent a Roux-en-Y gastric bypass (RYGB) at least 5 years prior were included in the study. A majority were women (74.2%) and Caucasian (66.2%). Patients' mean presurgical BMI was 49.14 kg/m 2 [SD = 9.50 kg/m 2 ]. Psychiatric diagnoses were obtained from a presurgical, semi-structured clinical interview and all participants were administered the MMPI-2-RF at their presurgical evaluations. BMIs were collected at 4 postoperative time points across a 5-year trajectory. This prospective design utilized latent growth curve modeling. Older patients evidenced a slower rate of BMI reduction over time. A presurgical diagnosis of Binge Eating Disorder predicted higher BMIs at the 5-year outcome. Scores on MMPI-2-RF measures of emotional and behavioral dysfunction domains incrementally predicted poorer weight loss outcomes. Preoperative indicators of psychopathology, notably indicators that are dimensional in nature, are important in predicting postoperative outcomes. Closer follow-up with patients who evidence presurgical psychological factors, both before and after surgery, may help improve outcomes. Copyright © 2017 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  18. Prediction of functional outcomes in stroke patients: the role of motor patterns according to limb synergies.

    Science.gov (United States)

    Gialanella, Bernardo; Santoro, Raffaele

    2015-10-01

    To address the relationships among motor patterns evaluated according to the limb synergies and functional outcomes in stroke patients and clarify which motor pattern was the most important predictor of functional outcomes. The study was conducted on 208 patients with primary diagnosis of stroke admitted for in-hospital rehabilitation. At entry, the Fugl-Meyer Scale was administered to assess motor function according to limb synergies. Pearson's correlation was used to assess the relationship between variables, and backward stepwise regression analysis was used to identify the outcome determinants. Final functional independence measure (FIM) scores and length of in-hospital stay were the outcome measures. At the end of rehabilitation, motor-FIM scores of patients with extensor and flexor synergies, mixing synergies, and no dependence from the synergies were higher than those of no movements and flexor synergy. Multivariate regression analysis showed that extensor synergy of upper limb was an independent predictor of final motor-FIM, personal care and mobility, extensor synergy of lower limb of locomotion, while mixing synergies of upper limb was an independent predictor of length of in-hospital stay. In stroke rehabilitation, the patients' motor patterns according to the synergies strongly relate with functional outcomes and are important outcome predictors.

  19. Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury.

    Science.gov (United States)

    Wu, Xuehai; Zou, Qihong; Hu, Jin; Tang, Weijun; Mao, Ying; Gao, Liang; Zhu, Jianhong; Jin, Yi; Wu, Xin; Lu, Lu; Zhang, Yaojun; Zhang, Yao; Dai, Zhengjia; Gao, Jia-Hong; Weng, Xuchu; Zhou, Liangfu; Northoff, Georg; Giacino, Joseph T; He, Yong; Yang, Yihong

    2015-09-16

    For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological

  20. Artificial Neural Network System to Predict the Postoperative Outcome of Percutaneous Nephrolithotomy.

    Science.gov (United States)

    Aminsharifi, Alireza; Irani, Dariush; Pooyesh, Shima; Parvin, Hamid; Dehghani, Sakineh; Yousofi, Khalilolah; Fazel, Ebrahim; Zibaie, Fatemeh

    2017-05-01

    To construct, train, and apply an artificial neural network (ANN) system for prediction of different outcome variables of percutaneous nephrolithotomy (PCNL). We calculated predictive accuracy, sensitivity, and precision for each outcome variable. During the study period, all adult patients who underwent PCNL at our institute were enrolled in the study. Preoperative and postoperative variables were recorded, and stone-free status was assessed perioperatively with computed tomography scans. MATLAB software was used to design and train the network in a feed forward back-propagation error adjustment scheme. Preoperative and postoperative data from 200 patients (training set) were used to analyze the effect and relative relevance of preoperative values on postoperative parameters. The validated adequately trained ANN was used to predict postoperative outcomes in the subsequent 254 adult patients (test set) whose preoperative values were serially fed into the system. To evaluate system accuracy in predicting each postoperative variable, predicted values were compared with actual outcomes. Two hundred fifty-four patients (155 [61%] males) were considered the test set. Mean stone burden was 6702.86 ± 381.6 mm 3 . Overall stone-free rate was 76.4%. Fifty-four out of 254 patients (21.3%) required ancillary procedures (shockwave lithotripsy 5.9%, transureteral lithotripsy 10.6%, and repeat PCNL 4.7%). The accuracy and sensitivity of the system in predicting different postoperative variables ranged from 81.0% to 98.2%. As a complex nonlinear mathematical model, our ANN system is an interconnected data mining tool, which prospectively analyzes and "learns" the relationships between variables. The accuracy and sensitivity of the system for predicting the stone-free rate, the need for blood transfusion, and post-PCNL ancillary procedures ranged from 81.0% to 98.2%.The stone burden and the stone morphometry were among the most significant preoperative characteristics that

  1. Predicting gambling problems from gambling outcome expectancies in college student-athletes.

    Science.gov (United States)

    St-Pierre, Renée A; Temcheff, Caroline E; Gupta, Rina; Derevensky, Jeffrey; Paskus, Thomas S

    2014-03-01

    While previous research has suggested the potential importance of gambling outcome expectancies in determining gambling behaviour among adolescents, the predictive ability of gambling outcome expectancies has not yet been clearly delineated for college-aged youth. The current study aims to explore the relationships between gender and outcome expectancies in the prediction of gambling severity among college student-athletes. Data from the National Collegiate Athletic Association (NCAA) study assessing gambling behaviours and problems among U.S. college student-athletes were utilized. Complete data was available for 7,517 student-athletes. As expected, male college student-athletes reported more gambling participation as well as greater gambling problems than their female counterparts. Findings showed positive relationships between the outcome expectancies of financial gain, and negative emotional impacts and gambling problems. That is, those who endorsed more items on the outcome expectancy scales for financial gain and negative emotional impacts also tended to endorse more gambling-related problems. Findings also showed a negative relationship between outcome expectancies of fun and enjoyment, and gambling problems over and above the variance accounted for by gender. Those with gambling problems were less likely to have the expectation that gambling would be fun than those without gambling problems. Despite NCAA efforts to curb gambling activity, the results suggest that college student-athletes are at risk for over-involvement in gambling. Therefore, it is important to explore gambling outcome expectancies within this group since the motivations and reasons for gambling might be able to inform treatment initiatives.

  2. Frontal gray matter abnormalities predict seizure outcome in refractory temporal lobe epilepsy patients.

    Science.gov (United States)

    Doucet, Gaelle E; He, Xiaosong; Sperling, Michael; Sharan, Ashwini; Tracy, Joseph I

    2015-01-01

    Developing more reliable predictors of seizure outcome following temporal lobe surgery for intractable epilepsy is an important clinical goal. In this context, we investigated patients with refractory temporal lobe epilepsy (TLE) before and after temporal resection. In detail, we explored gray matter (GM) volume change in relation with seizure outcome, using a voxel-based morphometry (VBM) approach. To do so, this study was divided into two parts. The first one involved group analysis of differences in regional GM volume between the groups (good outcome (GO), e.g., no seizures after surgery; poor outcome (PO), e.g., persistent postoperative seizures; and controls, N = 24 in each group), pre- and post-surgery. The second part of the study focused on pre-surgical data only (N = 61), determining whether the degree of GM abnormalities can predict surgical outcomes. For this second step, GM abnormalities were identified, within each lobe, in each patient when compared with an ad hoc sample of age-matched controls. For the first analysis, the results showed larger GM atrophy, mostly in the frontal lobe, in PO patients, relative to both GO patients and controls, pre-surgery. When comparing pre-to-post changes, we found relative GM gains in the GO but not in the PO patients, mostly in the non-resected hemisphere. For the second analysis, only the frontal lobe displayed reliable prediction of seizure outcome. 81% of the patients showing pre-surgical increased GM volume in the frontal lobe became seizure free, post-surgery; while 77% of the patients with pre-surgical reduced frontal GM volume had refractory seizures, post-surgery. A regression analysis revealed that the proportion of voxels with reduced frontal GM volume was a significant predictor of seizure outcome (p = 0.014). Importantly, having less than 1% of the frontal voxels with GM atrophy increased the likelihood of being seizure-free, post-surgery, by seven times. Overall, our results suggest that using pre

  3. Feature selection for outcome prediction in oesophageal cancer using genetic algorithm and random forest classifier.

    Science.gov (United States)

    Paul, Desbordes; Su, Ruan; Romain, Modzelewski; Sébastien, Vauclin; Pierre, Vera; Isabelle, Gardin

    2017-09-01

    The outcome prediction of patients can greatly help to personalize cancer treatment. A large amount of quantitative features (clinical exams, imaging, …) are potentially useful to assess the patient outcome. The challenge is to choose the most predictive subset of features. In this paper, we propose a new feature selection strategy called GARF (genetic algorithm based on random forest) extracted from positron emission tomography (PET) images and clinical data. The most relevant features, predictive of the therapeutic response or which are prognoses of the patient survival 3 years after the end of treatment, were selected using GARF on a cohort of 65 patients with a local advanced oesophageal cancer eligible for chemo-radiation therapy. The most relevant predictive results were obtained with a subset of 9 features leading to a random forest misclassification rate of 18±4% and an areas under the of receiver operating characteristic (ROC) curves (AUC) of 0.823±0.032. The most relevant prognostic results were obtained with 8 features leading to an error rate of 20±7% and an AUC of 0.750±0.108. Both predictive and prognostic results show better performances using GARF than using 4 other studied methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

    Science.gov (United States)

    Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

    2018-01-01

    The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

  5. Pretreatment clinical findings predict outcome for patients receiving preoperative radiation for rectal cancer

    International Nuclear Information System (INIS)

    Myerson, Robert J.; Singh, Anurag; Birnbaum, Elisa H.; Fry, Robert D.; Fleshman, James W.; Kodner, Ira J.; Lockett, Mary Ann; Picus, Joel; Walz, Bruce J.; Read, Thomas E.

    2001-01-01

    adverse clinical factors were present: 0 for none, 1 for one or two, 2 for three or four. This sorted outcome highly significantly (p≤0.002, Tarone Ware), with 5-year LC/FFR of 98%/85% (score 0), 90%/72% (score 1), and 74%/58% (score 2). The scoring system sorts the data for both subgroups of surgeons; however, there are substantial differences in LC on the basis of the surgeon's experience. For colorectal specialists (251 cases), the 5-year LC is 100%, 94%, and 78% for scores of 0, 1, and 2, respectively (p=0.004). For the more mixed group of nonspecialist surgeons (133 cases), LC is 98%, 80%, and 65% for scores of 0, 1, and 2 (p=0.008). In multivariate analysis, the clinical score and surgeon's background retained independent predictive value, even when pathologic stage was included. Conclusions: For many patients with rectal cancer, adjuvant treatment can be administered in a well-tolerated sequential fashion--moderate doses of preoperative radiation followed by surgery followed by postoperative chemotherapy to address the risk of occult metastatic disease. A clinical scoring system has been presented here that would suggest that the local control is excellent for lesions with a score of 0 or (if the surgeon is experienced) 1, and therefore sequential treatment could be considered. Cases with a clinical score of 2 should be strongly considered for protocols evaluating more aggressive preoperative treatment, such as combined modality preoperative treatment

  6. Functional Outcome Prediction after Traumatic Spinal Cord Injury Based on Acute Clinical Factors.

    Science.gov (United States)

    Kaminski, Ludovic; Cordemans, Virginie; Cernat, Eduard; M'Bra, Kouamé Innocent; Mac-Thiong, Jean-Marc

    2017-06-15

    Spinal cord injury (SCI) is a devastating condition that affects patients on both a personal and societal level. The objective of the study is to improve the prediction of long-term functional outcome following SCI based on the acute clinical findings. A total of 76 patients with acute traumatic SCI were prospectively enrolled in a cohort study in a single Level I trauma center. Spinal Cord Independence Measure (SCIM) at 1 year after the trauma was the primary outcome. Potential predictors of functional outcome were recorded during the acute hospitalization: age, sex, level and type of injury, comorbidities, American Spinal Injury Association (ASIA) Impairment Scale (AIS), ASIA Motor Score (AMS), ASIA Light Touch score (LT), ASIA Pin Prick score (PP), Injury Severity Score (ISS), traumatic brain injury, and delay from trauma to surgery. A linear regression model was created with the primary outcome modeled relative to the acute clinical findings. Only four variables were selected in the model, with performance averaging an R-square value of 0.57. In descending order, the best predictors for SCIM at 1 year were: LT, AIS grade, ISS, and AMS. One-year functional outcome (SCIM) can be estimated by a simple equation that takes into account four parameters of the initial physical examination. Estimating the patient long-term outcome early after traumatic SCI is important in order to define the management strategies that might diminish the costs and to give the patient and family a better view of the long-term expectations.

  7. What predicts outcome, response, and drop-out in CBT of depressive adults? a naturalistic study.

    Science.gov (United States)

    Schindler, Amrei; Hiller, Wolfgang; Witthöft, Michael

    2013-05-01

    The efficacy of CBT for unipolar depressive disorders is well established, yet not all patients improve or tolerate treatment. To identify factors associated with symptomatic outcome, response, and drop-out in depressive patients under naturalistic CBT. 193 patients with major depression or dysthymia were tested. Sociodemographic and clinical variables were entered as predictors in hierarchical regression analyses. A higher degree of pretreatment depression, early improvement, and completion of therapy were identified as predictors for symptomatic change and response. Drop-out was predicted by concurrent personality disorder, less positive outcome expectancies, and by failure to improve early in treatment. Our results highlight the importance of early response to predict improvement in routine CBT. Attempts to refine the quality of treatment programs should focus on avoiding premature termination (drop-out) and consider motivational factors in more depth. Routinely administered standardized assessments would enhance symptom monitoring and help to identify persons at risk of not improving under therapy.

  8. Mental health predicts better academic outcomes: a longitudinal study of elementary school students in Chile.

    Science.gov (United States)

    Murphy, J Michael; Guzmán, Javier; McCarthy, Alyssa E; Squicciarini, Ana María; George, Myriam; Canenguez, Katia M; Dunn, Erin C; Baer, Lee; Simonsohn, Ariela; Smoller, Jordan W; Jellinek, Michael S

    2015-04-01

    The world's largest school-based mental health program, Habilidades para la Vida [Skills for Life (SFL)], has been operating on a national scale in Chile for 15 years. SFL's activities include using standardized measures to screen elementary school students and providing preventive workshops to students at risk for mental health problems. This paper used SFL's data on 37,397 students who were in first grade in 2009 and third grade in 2011 to ascertain whether first grade mental health predicted subsequent academic achievement and whether remission of mental health problems predicted improved academic outcomes. Results showed that mental health was a significant predictor of future academic performance and that, overall, students whose mental health improved between first and third grade made better academic progress than students whose mental health did not improve or worsened. Our findings suggest that school-based mental health programs like SFL may help improve students' academic outcomes.

  9. Associations between young children's emotion attributions and prediction of outcome in differing social situations.

    Science.gov (United States)

    Eivers, Areana R; Brendgen, Mara; Borge, Anne I H

    2010-06-01

    Associations between young children's attributions of emotion at different points in a story, and with regard to their own prediction about the story's outcome, were investigated using two hypothetical scenarios of social and emotional challenge (social entry and negative event). First grade children (N = 250) showed an understanding that emotions are tied to situational cues by varying the emotions they attributed both between and within scenarios. Furthermore, emotions attributed to the main protagonist at the beginning of the scenarios were differentially associated with children's prediction of a positive or negative outcome and with the valence of the emotion attributed at the end of the scenario. Gender differences in responses to some items were also found.

  10. Electroencephalography Predicts Poor and Good Outcomes After Cardiac Arrest: A Two-Center Study.

    Science.gov (United States)

    Rossetti, Andrea O; Tovar Quiroga, Diego F; Juan, Elsa; Novy, Jan; White, Roger D; Ben-Hamouda, Nawfel; Britton, Jeffrey W; Oddo, Mauro; Rabinstein, Alejandro A

    2017-07-01

    The prognostic role of electroencephalography during and after targeted temperature management in postcardiac arrest patients, relatively to other predictors, is incompletely known. We assessed performances of electroencephalography during and after targeted temperature management toward good and poor outcomes, along with other recognized predictors. Cohort study (April 2009 to March 2016). Two academic hospitals (Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland; Mayo Clinic, Rochester, MN). Consecutive comatose adults admitted after cardiac arrest, identified through prospective registries. All patients were managed with targeted temperature management, receiving prespecified standardized clinical, neurophysiologic (particularly, electroencephalography during and after targeted temperature management), and biochemical evaluations. We assessed electroencephalography variables (reactivity, continuity, epileptiform features, and prespecified "benign" or "highly malignant" patterns based on the American Clinical Neurophysiology Society nomenclature) and other clinical, neurophysiologic (somatosensory-evoked potential), and biochemical prognosticators. Good outcome (Cerebral Performance Categories 1 and 2) and mortality predictions at 3 months were calculated. Among 357 patients, early electroencephalography reactivity and continuity and flexor or better motor reaction had greater than 70% positive predictive value for good outcome; reactivity (80.4%; 95% CI, 75.9-84.4%) and motor response (80.1%; 95% CI, 75.6-84.1%) had highest accuracy. Early benign electroencephalography heralded good outcome in 86.2% (95% CI, 79.8-91.1%). False positive rates for mortality were less than 5% for epileptiform or nonreactive early electroencephalography, nonreactive late electroencephalography, absent somatosensory-evoked potential, absent pupillary or corneal reflexes, presence of myoclonus, and neuron-specific enolase greater than 75 µg/L; accuracy was highest for

  11. Goal commitment predicts treatment outcome for adolescents with alcohol use disorder.

    Science.gov (United States)

    Kaminer, Yifrah; Ohannessian, Christine McCauley; McKay, James R; Burke, Rebecca H; Flannery, Kaitlin

    2018-01-01

    Commitment to change is an innovative potential mediator and mechanism of behavior change (MOBC) that has not been examined in adolescents with substance use disorders (SUD). The Adolescent Substance Abuse Goal Commitment (ASAGC) questionnaire is a reliable and valid 2-scale measure developed to assess the adolescent's commitment to either abstinence or harm reduction (HR) that includes consumption reduction as a stated treatment goal. The objective of this study was to examine the ASAGC's ability to predict alcohol use treatment outcome. During sessions three and nine of a 10-week treatment program, therapists completed the ASAGC for 170 adolescents 13-18years of age with alcohol use disorder (AUD). Drinking behaviors were assessed during and after a continued-care phase until 12-month from study onset. Analysis of Variance results indicated that adolescents who reported no alcohol use had significantly higher scores on the commitment to abstinence scale than adolescents who reported alcohol use. None of the ANOVA models were significant for commitment to HR. When treatment outcome was examined, commitment to abstinence consistently predicted number of drinking days, number of heavy drinking days, and the maximum number of drinks post-treatment. In contrast, commitment to HR did not predict any of the drinking outcomes. These results suggest that the more adolescents were committed to abstinence during treatment, the less they used and abused alcohol after treatment completion. In addition to the ASAGC's ability to differentiate between commitment to abstinence and commitment to HR, study findings demonstrate that goal commitment consistently predicts AUD treatment outcome. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Early Prediction and Outcome of Septic Encephalopathy in Acute Stroke Patients With Nosocomial Coma

    OpenAIRE

    Tong, Dao-Ming; Zhou, Ye-Ting; Wang, Guang-Sheng; Chen, Xiao-Dong; Yang, Tong-Hui

    2015-01-01

    Background Septic encephalopathy (SE) is the most common acute encephalopathy in ICU; however, little attention has been focused on risk of SE in the course of acute stroke. Our aim is to investigate the early prediction and outcome of SE in stroke patients with nosocomial coma (NC). Methods A retrospective cohort study was conducted in an ICU of the tertiary teaching hospital in China from January 2006 to December 2009. Ninety-four acute stroke patients with NC were grouped according to with...

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

    Directory of Open Access Journals (Sweden)

    Chika Sumiyoshi

    2015-09-01

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

  14. Cross-trial prediction of treatment outcome in depression: a machine learning approach.

    Science.gov (United States)

    Chekroud, Adam Mourad; Zotti, Ryan Joseph; Shehzad, Zarrar; Gueorguieva, Ralitza; Johnson, Marcia K; Trivedi, Madhukar H; Cannon, Tyrone D; Krystal, John Harrison; Corlett, Philip Robert

    2016-03-01

    Antidepressant treatment efficacy is low, but might be improved by matching patients to interventions. At present, clinicians have no empirically validated mechanisms to assess whether a patient with depression will respond to a specific antidepressant. We aimed to develop an algorithm to assess whether patients will achieve symptomatic remission from a 12-week course of citalopram. We used patient-reported data from patients with depression (n=4041, with 1949 completers) from level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D; ClinicalTrials.gov, number NCT00021528) to identify variables that were most predictive of treatment outcome, and used these variables to train a machine-learning model to predict clinical remission. We externally validated the model in the escitalopram treatment group (n=151) of an independent clinical trial (Combining Medications to Enhance Depression Outcomes [COMED]; ClinicalTrials.gov, number NCT00590863). We identified 25 variables that were most predictive of treatment outcome from 164 patient-reportable variables, and used these to train the model. The model was internally cross-validated, and predicted outcomes in the STAR*D cohort with accuracy significantly above chance (64·6% [SD 3·2]; pbuproprion treatment group in COMED (n=134; accuracy 59·7%, p=0·023), but not in a combined venlafaxine-mirtazapine group (n=140; accuracy 51·4%, p=0·53), suggesting specificity of the model to underlying mechanisms. Building statistical models by mining existing clinical trial data can enable prospective identification of patients who are likely to respond to a specific antidepressant. Yale University. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Comparison of models for predicting outcomes in patients with coronary artery disease focusing on microsimulation

    Directory of Open Access Journals (Sweden)

    Masoud Amiri

    2012-01-01

    Full Text Available Background: Physicians have difficulty to subjectively estimate the cardiovascular risk of their patients. Using an estimate of global cardiovascular risk could be more relevant to guide decisions than using binary representation (presence or absence of risk factors data. The main aim of the paper is to compare different models of predicting the progress of a coronary artery diseases (CAD to help the decision making of physician. Methods: There are different standard models for predicting risk factors such as models based on logistic regression model, Cox regression model, dynamic logistic regression model, and simulation models such as Markov model and microsimulation model. Each model has its own application which can or cannot use by physicians to make a decision on treatment of each patient. Results: There are five main common models for predicting of outcomes, including models based on logistic regression model (for short-term outcomes, Cox regression model (for intermediate-term outcomes, dynamic logistic regression model, and simulation models such as Markov and microsimulation models (for long-term outcomes. The advantages and disadvantages of these models have been discussed and summarized. Conclusion: Given the complex medical decisions that physicians face in everyday practice, the multiple interrelated factors that play a role in choosing the optimal treatment, and the continuously accumulating new evidence on determinants of outcome and treatment options for CAD, physicians may potentially benefit from a clinical decision support system that accounts for all these considerations. The microsimulation model could provide cardiologists, researchers, and medical students a user-friendly software, which can be used as an intelligent interventional simulator.

  16. Exposure and Response Prevention Process Predicts Treatment Outcome in Youth with OCD

    Science.gov (United States)

    Kircanski, Katharina; Peris, Tara S.

    2014-01-01

    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. PMID:25052626

  17. San Francisco Syncope Rule to predict short-term serious outcomes: a systematic review

    Science.gov (United States)

    Saccilotto, Ramon T.; Nickel, Christian H.; Bucher, Heiner C.; Steyerberg, Ewout W.; Bingisser, Roland; Koller, Michael T.

    2011-01-01

    Background: The San Francisco Syncope Rule has been proposed as a clinical decision rule for risk stratification of patients presenting to the emergency department with syncope. It has been validated across various populations and settings. We undertook a systematic review of its accuracy in predicting short-term serious outcomes. Methods: We identified studies by means of systematic searches in seven electronic databases from inception to January 2011. We extracted study data in duplicate and used a bivariate random-effects model to assess the predictive accuracy and test characteristics. Results: We included 12 studies with a total of 5316 patients, of whom 596 (11%) experienced a serious outcome. The prevalence of serious outcomes across the studies varied between 5% and 26%. The pooled estimate of sensitivity of the San Francisco Syncope Rule was 0.87 (95% confidence interval [CI] 0.79–0.93), and the pooled estimate of specificity was 0.52 (95% CI 0.43–0.62). There was substantial between-study heterogeneity (resulting in a 95% prediction interval for sensitivity of 0.55–0.98). The probability of a serious outcome given a negative score with the San Francisco Syncope Rule was 5% or lower, and the probability was 2% or lower when the rule was applied only to patients for whom no cause of syncope was identified after initial evaluation in the emergency department. The most common cause of false-negative classification for a serious outcome was cardiac arrhythmia. Interpretation: The San Francisco Syncope Rule should be applied only for patients in whom no cause of syncope is evident after initial evaluation in the emergency department. Consideration of all available electrocardiograms, as well as arrhythmia monitoring, should be included in application of the San Francisco Syncope Rule. Between-study heterogeneity was likely due to inconsistent classification of arrhythmia. PMID:21948723

  18. Does the Community of Inquiry Framework Predict Outcomes in Online MBA Courses?

    OpenAIRE

    J. B. Arbaugh

    2008-01-01

    While Garrison and colleagues’ (2000) Community of Inquiry (CoI) framework has generated substantial interest among online learning researchers, it has yet to be subjected to extensive quantitative verification or tested for external validity. Using a sample of students from 55 online MBA courses, the findings of this study suggest strong empirical support for the framework and its ability to predict both perceived learning and delivery medium satisfaction in online management education. The ...

  19. In silico and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

    Science.gov (United States)

    Schmidt, Julien; Guillaume, Philippe; Dojcinovic, Danijel; Karbach, Julia; Coukos, George; Luescher, Immanuel

    2017-07-14

    Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-specific T cells often are tumoricidal. However, identifying tumor-specific T-cell epitopes is a major challenge. A widely used strategy relies on initial prediction of human leukocyte antigen-binding peptides by in silico algorithms, but the predictive power of this approach is unclear. Here, we used the human tumor antigen NY-ESO-1 (ESO) and the human leukocyte antigen variant HLA-A*0201 (A2) as a model and predicted in silico the 41 highest-affinity, A2-binding 8-11-mer peptides and assessed their binding, kinetic complex stability, and immunogenicity in A2-transgenic mice and on peripheral blood mononuclear cells from ESO-vaccinated melanoma patients. We found that 19 of the peptides strongly bound to A2, 10 of which formed stable A2-peptide complexes and induced CD8 + T cells in A2-transgenic mice. However, only 5 of the peptides induced cognate T cells in humans; these peptides exhibited strong binding and complex stability and contained multiple large hydrophobic and aromatic amino acids. These results were not predicted by in silico algorithms and provide new clues to improving T-cell epitope identification. In conclusion, our findings indicate that only a small fraction of in silico -predicted A2-binding ESO peptides are immunogenic in humans, namely those that have high peptide-binding strength and complex stability. This observation highlights the need for improving in silico predictions of peptide immunogenicity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  20. Lower Serum Zinc and Higher CRP Strongly Predict Prenatal Depression and Physio-somatic Symptoms, Which All Together Predict Postnatal Depressive Symptoms.

    Science.gov (United States)

    Roomruangwong, Chutima; Kanchanatawan, Buranee; Sirivichayakul, Sunee; Mahieu, Boris; Nowak, Gabriel; Maes, Michael

    2017-03-01

    Pregnancy and delivery are associated with activation of immune-inflammatory pathways which may prime parturients to develop postnatal depression. There are, however, few data on the associations between immune-inflammatory pathways and prenatal depression and physio-somatic symptoms. This study examined the associations between serum zinc, C-reactive protein (CRP), and haptoglobin at the end of term and prenatal physio-somatic symptoms (fatigue, back pain, muscle pain, dyspepsia, obstipation) and prenatal and postnatal depressive and anxiety symptoms as measured using the Edinburgh Postnatal Depression Scale (EPDS), Beck Depression Inventory (BDI), Hamilton Depression Rating Scale (HAMD), and Spielberger's State Anxiety Inventory (STAI). Zinc and haptoglobin were significantly lower and CRP increased at the end of term as compared with non-pregnant women. Prenatal depression was predicted by lower zinc and lifetime history of depression, anxiety, and premenstrual tension syndrome (PMS). The latter histories were also significantly and inversely related to lower zinc. The severity of prenatal EDPS, HAMD, BDI, STAI, and physio-somatic symptoms was predicted by fatigue in the first and second trimesters, a positive life history of depression, anxiety, and PMS, and lower zinc and higher CRP. Postnatal depressive symptoms are predicted by prenatal depression, physio-somatic symptoms, zinc and CRP. Prenatal depressive and physio-somatic symptoms have an immune-inflammatory pathophysiology, while postnatal depressive symptoms are highly predicted by prenatal immune activation, prenatal depression, and a lifetime history of depression and PMS. Previous episodes of depression, anxiety disorders, and PMS may prime pregnant females to develop prenatal and postnatal depressive symptoms via activated immune pathways.

  1. Noninvasive work of breathing improves prediction of post-extubation outcome.

    Science.gov (United States)

    Banner, Michael J; Euliano, Neil R; Martin, A Daniel; Al-Rawas, Nawar; Layon, A Joseph; Gabrielli, Andrea

    2012-02-01

    We hypothesized that non-invasively determined work of breathing per minute (WOB(N)/min) (esophageal balloon not required) may be useful for predicting extubation outcome, i.e., appropriate work of breathing values may be associated with extubation success, while inappropriately increased values may be associated with failure. Adult candidates for extubation were divided into a training set (n = 38) to determine threshold values of indices for assessing extubation and a prospective validation set (n = 59) to determine the predictive power of the threshold values for patients successfully extubated and those who failed extubation. All were evaluated for extubation during a spontaneous breathing trial (5 cmH(2)O pressure support ventilation, 5 cmH(2)O positive end expiratory pressure) using routine clinical practice standards. WOB(N)/min data were blinded to attending physicians. Area under the receiver operating characteristic curves (AUC), sensitivity, specificity, and positive and negative predictive values of all extubation indices were determined. AUC for WOB(N)/min was 0.96 and significantly greater (p indices. WOB(N)/min had a specificity of 0.83, the highest sensitivity at 0.96, positive predictive value at 0.84, and negative predictive value at 0.96 compared to all indices. For 95% of those successfully extubated, WOB(N)/min was ≤10 J/min. WOB(N)/min had the greatest overall predictive accuracy for extubation compared to traditional indices. WOB(N)/min warrants consideration for use in a complementary manner with spontaneous breathing pattern data for predicting extubation outcome.

  2. The role of marshall and rotterdam score in predicting 30-day outcome of traumatic brain injury

    Science.gov (United States)

    Siahaan, A. M. P.; Akbar, T. Y. M.; Nasution, M. D.

    2018-03-01

    Traumatic brain injury (TBI) remains one of the leading causes of mortality and morbidity, especially in the young population. To predict the outcome of TBI, Marshall, and Rotterdam–CT Scan based scoring was mostly used. As many studies showed conflicting results regarding of the usage of both scoring, this study aims to determine the correlation between Rotterdam and Marshall scoring system with outcome in 30 days and found correlation among them. In 120 subjects with TBI that admitted to Adam Malik General Hospital, we found a significant association of both scorings with the 30-day Glasgow Outcome Score. Therefore, we recommend the use of Marshall and Rotterdam CT Score in initial assessment as a good predictor for patients with TBI.

  3. Interpreting the Strongly Lensed Supernova iPTF16geu: Time Delay Predictions, Microlensing, and Lensing Rates

    Energy Technology Data Exchange (ETDEWEB)

    More, Anupreeta; Oguri, Masamune; More, Surhud [Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU, WPI), University of Tokyo, Chiba 277-8583 (Japan); Suyu, Sherry H. [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, D-85748 Garching (Germany); Lee, Chien-Hsiu, E-mail: anupreeta.more@ipmu.jp [Subaru Telescope, National Astronomical Observatory of Japan, 650 North Aohoku Place, Hilo, HI 96720 (United States)

    2017-02-01

    We present predictions for time delays between multiple images of the gravitationally lensed supernova, iPTF16geu, which was recently discovered from the intermediate Palomar Transient Factory (iPTF). As the supernova is of Type Ia where the intrinsic luminosity is usually well known, accurately measured time delays of the multiple images could provide tight constraints on the Hubble constant. According to our lens mass models constrained by the Hubble Space Telescope F814W image, we expect the maximum relative time delay to be less than a day, which is consistent with the maximum of 100 hr reported by Goobar et al. but places a stringent upper limit. Furthermore, the fluxes of most of the supernova images depart from expected values suggesting that they are affected by microlensing. The microlensing timescales are small enough that they may pose significant problems to measure the time delays reliably. Our lensing rate calculation indicates that the occurrence of a lensed SN in iPTF is likely. However, the observed total magnification of iPTF16geu is larger than expected, given its redshift. This may be a further indication of ongoing microlensing in this system.

  4. Prediction of memory rehabilitation outcomes in traumatic brain injury by using functional magnetic resonance imaging.

    Science.gov (United States)

    Strangman, Gary E; O'Neil-Pirozzi, Therese M; Goldstein, Richard; Kelkar, Kalika; Katz, Douglas I; Burke, David; Rauch, Scott L; Savage, Cary R; Glenn, Mel B

    2008-05-01

    To evaluate the ability of functional magnetic resonance imaging (fMRI) measures collected from people with traumatic brain injury (TBI) to provide predictive value for rehabilitation outcomes over and above standard predictors. Prospective study. Academic medical center. Persons (N=54) with TBI greater than 1 year postinjury. A novel 12-session group rehabilitation program focusing on internal strategies to improve memory. The Hopkins Verbal Learning Test-Revised (HVLT-R) delayed recall score. fMRI measures were collected while participants performed a strategically directed word memorization task. Prediction models were multiple linear regressions with the following primary predictors of outcome: age, education, injury severity, preintervention HVLT-R, and task-related fMRI activation of the left dorsolateral and left ventrolateral prefrontal cortex (VLPFC). Baseline HVLT-R was a significant predictor of outcome (P=.007), as was injury severity (for severe vs mild, P=.049). We also found a significant quadratic (inverted-U) effect of fMRI in the VLPFC (P=.007). This study supports previous evidence that left prefrontal activity is related to strategic verbal learning, and the magnitude of this activation predicted success in response to cognitive memory rehabilitation strategies. Extreme under- or overactivation of VLPFC was associated with less successful learning after rehabilitation. Further study is necessary to clarify this relationship and to expand and optimize the possible uses of functional imaging to guide rehabilitation therapies.

  5. General and religious coping predict drinking outcomes for alcohol dependent adults in treatment.

    Science.gov (United States)

    Martin, Rosemarie A; Ellingsen, Victor J; Tzilos, Golfo K; Rohsenow, Damaris J

    2015-04-01

    Religiosity is associated with improved treatment outcomes among adults with alcohol dependence; however, it is unknown whether religious coping predicts drinking outcomes above and beyond the effects of coping in general, and whether gender differences exist. We assessed 116 alcohol-dependent adults (53% women; mean age = 37, SD = 8.6) for use of religious coping, general coping, and alcohol use within 2 weeks of entering outpatient treatment, and again 6 months after treatment. Religious coping at 6 months predicted fewer heavy alcohol use days and fewer drinks per day. This relationship was no longer significant after controlling for general coping at 6 months. The relationship between the use of religious coping strategies and drinking outcomes is not independent of general coping. Coping skills training that includes religious coping skills, as one of several coping methods, may be useful for a subset of adults early in recovery. This novel, prospective study assessed the relationship between religious coping strategies, general coping, and treatment outcomes for alcohol-dependent adults in treatment with results suggesting that the use of religious coping as one of several coping methods may be useful for a subset of adults early in recovery. © American Academy of Addiction Psychiatry.

  6. Does pre- and post-angioplasty Doppler ultrasound evaluation help in predicting vascular access outcome?

    Science.gov (United States)

    Guedes-Marques, Maria; Maia, Pedro A; Neves, Fernando; Ferreira, Aníbal; Cruz, João; Carvalho, Dulce; Oliveira, Carlos; Barreto, Carlos; Carvalho, Telmo; Ponce, Pedro

    2016-11-02

    Kidney Disease - Improving Global Outcomes (KDIGO) recommends post-percutaneous transluminal angioplasty (PTA) access blood flow (ABF) improvement predicts vascular access (VA) outcome. Secondary: compare Doppler ultrasound (DU) and angiography diagnostic accuracy; determine how other factors predict outcome. Eighty patients. DU evaluation performed pre- and post-PTA. Several parameters recorded. Secondary patency verified after 6 months. Initial ABF 537 ± 248 mL/min; final ABF 1013 ± 354 mL/min. Number and location of stenosis was highly correlated between DU and angiography (p30% associated to better survival, p 0.038. Initial ABF0.05). A >2-fold ABF increase had no significant impact on fistulas (p>0.05) but was significantly associated with worst outcomes in grafts (23.1% vs. 73.5%, p 0.009). Grafts had lower survival (HR 3.3, p 0.034). Although less accurate for central lesions, DU has a key role on VA surveillance, allowing a morphologic and hemodynamic assessment. Angioplasty is effective in preserving VA; however, it may increase restenosis due to accelerated neointimal hyperplasia. Current parameters are not useful. Trials addressing this issue are needed.

  7. Predictive Value of Frailty Indices for Adverse Outcomes in Older Adults.

    Science.gov (United States)

    Pérez-Zepeda, Mario Ulises; Cesari, Matteo; García-Peña, Carmen

    2016-01-01

    There are two widely used tools to classify frailty in older adults: the frailty phenotype and the frailty index. Both have been validated for prediction of adverse outcomes. To assess the ability of different frailty indices to predict a number of adverse outcomes (falls, disability, and mortality) by adding deficits in a fixed sequence (with the first five deficits as in the frailty phenotype: weakness, weight loss, slowness, exhaustion and low physical activity) or randomly. This is an analysis of the Costa-Rican Longevity and Healthy Aging Study in which ≥ 60-year-old adults were included and followed up for four years. Frailty indices were constructed, including the frailty phenotype components in the first five indices followed by the random addition of other deficits and estimating for each one the odds ratios for falls and disability and hazard ratios for mortality, adjusted for age and sex. We included 2,708 adults; mean age was 76.31 years, 54.28% were women. Indices with the highest number of deficits had the highest estimates for each adverse outcome, independent of the deficit. The higher the number of deficits in an index, the higher the estimates for adverse outcomes, independent of the type of deficit added.

  8. Otoacoustic emissions in the prediction of sudden sensorineural hearing loss outcome.

    Science.gov (United States)

    Shupak, Avi; Zeidan, Reem; Shemesh, Rafael

    2014-12-01

    To evaluate the role of otoacoustic emissions (OAEs) in the prediction of idiopathic sudden sensorineural hearing loss (ISSNHL) outcome. Open-label prospective study. Tertiary referral medical center. Fifteen ISSNHL patients (age: 57.6 ± 16.2 years) were prospectively followed 7 days, 14 days, and 3 months post-presentation and the commencement of treatment. Pure-tone audiometry, TEOAEs (Transient Evoked OAEs), and DPOAEs (Distortion Product OAEs) testing. The pure-tone threshold averages of the three most affected frequencies, detectability, and the signal-to-noise ratios (SNRs) values of the TEOAEs and DPOAEs were calculated. The main outcome measures were pure-tone hearing improvement, sensitivity, and specificity of the OAEs measures towards ISSNHL outcome. Patients having detectable TEOAEs on the first follow-up evaluation had average hearing improvement of 62 ± 41% whereas those with no response improved only by 11 ± 15% (P hearing improvement, results were 71 ± 37% and 10 ± 14%, respectively (P hearing improvement reached 71% and the specificity 100%. For the DPOAEs, the corresponding values were 83% and 100%. Univariate analysis showed significant contribution for the variance in hearing improvement by both TEOAEs and DPOAEs and their interaction (P values of 0.043, 0.005, and 0.009, respectively). The results suggest potential role of TEOAEs and DPOAEs evaluation in the early stage of treatment in the prediction of ISSNHL outcome.

  9. A model and scoring system to predict outcome of intrauterine pregnancies of uncertain viability.

    Science.gov (United States)

    Bottomley, C; Van Belle, V; Pexsters, A; Papageorghiou, A T; Mukri, F; Kirk, E; Van Huffel, S; Timmerman, D; Bourne, T

    2011-05-01

    To define the incidence and outcome of intrauterine pregnancy of uncertain viability (PUV) and to develop and assess the performance of a model and a scoring system to predict ongoing viability. Of 1881 consecutive women undergoing transvaginal ultrasonography, a cohort of 493 women with an empty gestational sac model and a 'simple' model in the prediction of viability at each outcome point, based on maternal demographics, ultrasound features and symptoms. The performance of each system was assessed by receiver-operating characteristics (ROC) curve analysis and calibration plots on a test dataset. The incidence of PUV in this population was 29.2% (549/1881). Of the 493 pregnancies with initial (7-14 days) follow-up available, 307 (62.3%) were viable at this time and of the 444 pregnancies with follow-up at the end of the first trimester, 225 (50.7%) were still viable. Initial (7-14-day) viability was predicted by the model with an area under the ROC curve (AUC) of 0.837 (95% CI, 0.791-0.884) in the training dataset and 0.821 (95% CI, 0.756-0.885) in the test dataset. First-trimester (11-14-week) viability was predicted by the model with an AUC of 0.788 (95% CI, 0.734-0.842) in the training dataset and 0.774 (95% CI, 0.701-0.848) in the test dataset. The scoring system performed slightly worse than did the model, but had the advantage of being easily applicable. When early pregnancy viability cannot be established immediately with ultrasound, use of either a logistic regression model or a scoring system allows an individualized prediction of first-trimester outcome. Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.

  10. Anorexic self-control and bulimic self-hate: differential outcome prediction from initial self-image.

    Science.gov (United States)

    Birgegård, Andreas; Björck, Caroline; Norring, Claes; Sohlberg, Staffan; Clinton, David

    2009-09-01

    The study investigated initial self-image (structural analysis of social behavior) and its relation to 36-month outcome, among patients with anorexia nervosa and bulimia nervosa. Hypotheses were that degree of different aspects of self-image would predict outcome in the groups. Participants were 52 patients with anorexia and 91 with bulimia from a longitudinal naturalistic database, and outcome measures included eating disorder and psychiatric symptoms and a general outcome index. Stepwise regression was used to investigate which self-image variables were related to outcome, and multiple regression contrasted the groups directly on each obtained predictor. Consistent with hypotheses, in bulimia degree of self-hate/self-love moderately predicted outcome, whereas self-control-related variables powerfully predicted outcome in anorexia. It is important to focus on self-image in the treatment of both diagnostic groups, but especially in anorexia nervosa, where control-submission interactions between patient and therapist should be handled with care.

  11. Prognostic Model to Predict Post-Autologous Stem-Cell Transplantation Outcomes in Classical Hodgkin Lymphoma.

    Science.gov (United States)

    Chan, Fong Chun; Mottok, Anja; Gerrie, Alina S; Power, Maryse; Nijland, Marcel; Diepstra, Arjan; van den Berg, Anke; Kamper, Peter; d'Amore, Francesco; d'Amore, Alexander Lindholm; Hamilton-Dutoit, Stephen; Savage, Kerry J; Shah, Sohrab P; Connors, Joseph M; Gascoyne, Randy D; Scott, David W; Steidl, Christian

    2017-11-10

    Purpose Our aim was to capture the biology of classical Hodgkin lymphoma (cHL) at the time of relapse and discover novel and robust biomarkers that predict outcomes after autologous stem-cell transplantation (ASCT). Materials and Methods We performed digital gene expression profiling on a cohort of 245 formalin-fixed, paraffin-embedded tumor specimens from 174 patients with cHL, including 71 with biopsies taken at both primary diagnosis and relapse, to investigate temporal gene expression differences and associations with post-ASCT outcomes. Relapse biopsies from a training cohort of 65 patients were used to build a gene expression-based prognostic model of post-ASCT outcomes (RHL30), and two independent cohorts were used for validation. Results Gene expression profiling revealed that 24% of patients exhibited poorly correlated expression patterns between their biopsies taken at initial diagnosis and relapse, indicating biologic divergence. Comparative analysis of the prognostic power of gene expression measurements in primary versus relapse specimens demonstrated that the biology captured at the time of relapse contained superior properties for post-ASCT outcome prediction. We developed RHL30, using relapse specimens, which identified a subset of high-risk patients with inferior post-ASCT outcomes in two independent external validation cohorts. The prognostic power of RHL30 was independent of reported clinical prognostic markers (both at initial diagnosis and at relapse) and microenvironmental components as assessed by immunohistochemistry. Conclusion We have developed and validated a novel clinically applicable prognostic assay that at the time of first relapse identifies patients with unfavorable post-ASCT outcomes. Moving forward, it will be critical to evaluate the clinical use of RHL30 in the context of positron emission tomography-guided response assessment and the evolving cHL treatment landscape.

  12. Measure of functional independence dominates discharge outcome prediction after inpatient rehabilitation for stroke.

    Science.gov (United States)

    Brown, Allen W; Therneau, Terry M; Schultz, Billie A; Niewczyk, Paulette M; Granger, Carl V

    2015-04-01

    Identifying clinical data acquired at inpatient rehabilitation admission for stroke that accurately predict key outcomes at discharge could inform the development of customized plans of care to achieve favorable outcomes. The purpose of this analysis was to use a large comprehensive national data set to consider a wide range of clinical elements known at admission to identify those that predict key outcomes at rehabilitation discharge. Sample data were obtained from the Uniform Data System for Medical Rehabilitation data set with the diagnosis of stroke for the years 2005 through 2007. This data set includes demographic, administrative, and medical variables collected at admission and discharge and uses the FIM (functional independence measure) instrument to assess functional independence. Primary outcomes of interest were functional independence measure gain, length of stay, and discharge to home. The sample included 148,367 people (75% white; mean age, 70.6±13.1 years; 97% with ischemic stroke) admitted to inpatient rehabilitation a mean of 8.2±12 days after symptom onset. The total functional independence measure score, the functional independence measure motor subscore, and the case-mix group were equally the strongest predictors for any of the primary outcomes. The most clinically relevant 3-variable model used the functional independence measure motor subscore, age, and walking distance at admission (r(2)=0.107). No important additional effect for any other variable was detected when added to this model. This analysis shows that a measure of functional independence in motor performance and age at rehabilitation hospital admission for stroke are predominant predictors of outcome at discharge in a uniquely large US national data set. © 2015 American Heart Association, Inc.

  13. Nonlocal response functions for predicting shear flow of strongly inhomogeneous fluids. II. Sinusoidally driven shear and multisinusoidal inhomogeneity.

    Science.gov (United States)

    Dalton, Benjamin A; Glavatskiy, Kirill S; Daivis, Peter J; Todd, B D

    2015-07-01

    We use molecular-dynamics computer simulations to investigate the density, strain-rate, and shear-pressure responses of a simple model atomic fluid to transverse and longitudinal external forces. We have previously introduced a response function formalism for describing the density, strain-rate, and shear-pressure profiles in an atomic fluid when it is perturbed by a combination of longitudinal and transverse external forces that are independent of time and have a simple sinusoidal spatial variation. In this paper, we extend the application of the previously introduced formalism to consider the case of a longitudinal force composed of multiple sinusoidal components in combination with a single-component sinusoidal transverse force. We find that additional harmonics are excited in the density, strain-rate, and shear-pressure profiles due to couplings between the force components. By analyzing the density, strain-rate, and shear-pressure profiles in Fourier space, we are able to evaluate the Fourier coefficients of the response functions, which now have additional components describing the coupling relationships. Having evaluated the Fourier coefficients of the response functions, we are then able to accurately predict the density, velocity, and shear-pressure profiles for fluids that are under the influence of a longitudinal force composed of two or three sinusoidal components combined with a single-component sinusoidal transverse force. We also find that in the case of a multisinusoidal longitudinal force, it is sufficient to include only pairwise couplings between different longitudinal force components. This means that it is unnecessary to include couplings between three or more force components in the case of a longitudinal force composed of many Fourier components, and this paves the way for a highly accurate but tractable treatment of nonlocal transport phenomena in fluids with density and strain-rate inhomogeneities on the molecular length scale.

  14. Prediction of outcome of extracorporeal shock wave lithotripsy in the management of ureteric calculi.

    Science.gov (United States)

    Wang, Mingqing; Shi, Qiduo; Wang, Xuguang; Yang, Kun; Yang, Rui

    2011-02-01

    The present study was designed to evaluate the clinical outcome of using extracorporeal shock wave lithotripsy (ESWL) in the treatment of ureteric calculi and to establish a predictive model for the stone-free rate in patients receiving the treatment. A total of 831 patients with ureteric calculi were accepted in this study. Several parameters, including stone site, stone number, stone size, history of urolithiasis, renal colic, hydronephrosis, and double-J ureteric stent, were analyzed using univariate and multivariate analyses. A prediction model was established based on the logistic regression analysis of the significant factors, and the goodness-of-fit of the model was evaluated by employing the Hosmer-Lemeshow test. At a 3-month follow-up after ESWL treatment, the overall stone-free rate was 96.8% (804/831) with no serious complications being found, while the treatment failed in 3.2% (27/831) of the patients. Five factors, including stone number, stone size, history of urolithiasis, renal colic, and double-J ureteric stent contributed significantly to the clinical outcome of the ESWL treatment. The prediction model had a sensitivity and overall accuracy of 99.8 and 96.9%, respectively. The results show that ESWL remains an effective method for treating ureteric calculi. The prediction model established in this study could be used as a method for estimating prognosis in patients following ESWL treatment.

  15. Computational Models for Predicting Outcomes of Neuroprosthesis Implantation: the Case of Cochlear Implants.

    Science.gov (United States)

    Ceresa, Mario; Mangado, Nerea; Andrews, Russell J; Gonzalez Ballester, Miguel A

    2015-10-01

    Electrical stimulation of the brain has resulted in the most successful neuroprosthetic techniques to date: deep brain stimulation (DBS) and cochlear implants (CI). In both cases, there is a lack of pre-operative measures to predict the outcomes after implantation. We argue that highly detailed computational models that are specifically tailored for a patient can provide useful information to improve the precision of the nervous system electrode interface. We apply our framework to the case of CI, showing how we can predict nerve response for patients with both intact and degenerated nerve fibers. Then, using the predicted response, we calculate a metric for the usefulness of the stimulation protocol and use this information to rerun the simulations with better parameters.

  16. Outcome prediction in a mathematical model of immune response to infection

    Science.gov (United States)

    Mai, Manuel; Wang, Kun; Kirby, Michael; Shattuck, Mark D.; O'Hern, Corey S.

    2014-03-01

    In clinical settings, it is of great importance to diagnose patients in the shortest amount of time and with the highest achievable accuracy. Current open questions concerning the modeling of the host response to infection include: How many measurements and with what frequency are needed to diagnose patients with a given accuracy? What is the effect of patient variation on the prediction accuracy? We employ machine-learning techniques to predict disease outcomes from data generated from a set of ordinary differential equations (ODE) used to model the immune response to infection. ODE models have the advantage that we can generate an unlimited amount of data, and we can easily simulate patient differences by varying model parameters. We explore the dependence of the prediction accuracy on data sets generated from the sets of ODEs as a function of the number of and spacing between measurements, number of measured variables, and the size of the patient variability.

  17. Do treatment quality indicators predict cardiovascular outcomes in patients with diabetes?

    Directory of Open Access Journals (Sweden)

    Grigory Sidorenkov

    Full Text Available BACKGROUND: Landmark clinical trials have led to optimal treatment recommendations for patients with diabetes. Whether optimal treatment is actually delivered in practice is even more important than the efficacy of the drugs tested in trials. To this end, treatment quality indicators have been developed and tested against intermediate outcomes. No studies have tested whether these treatment quality indicators also predict hard patient outcomes. METHODS: A cohort study was conducted using data collected from >10.000 diabetes patients in the Groningen Initiative to Analyze Type 2 Treatment (GIANTT database and Dutch Hospital Data register. Included quality indicators measured glucose-, lipid-, blood pressure- and albuminuria-lowering treatment status and treatment intensification. Hard patient outcome was the composite of cardiovascular events and all-cause death. Associations were tested using Cox regression adjusting for confounding, reporting hazard ratios (HR with 95% confidence intervals. RESULTS: Lipid and albuminuria treatment status, but not blood pressure lowering treatment status, were associated with the composite outcome (HR = 0.77, 0.67-0.88; HR = 0.75, 0.59-0.94. Glucose lowering treatment status was associated with the composite outcome only in patients with an elevated HbA1c level (HR = 0.72, 0.56-0.93. Treatment intensification with glucose-lowering but not with lipid-, blood pressure- and albuminuria-lowering drugs was associated with the outcome (HR = 0.73, 0.60-0.89. CONCLUSION: Treatment quality indicators measuring lipid- and albuminuria-lowering treatment status are valid quality measures, since they predict a lower risk of cardiovascular events and mortality in patients with diabetes. The quality indicators for glucose-lowering treatment should only be used for restricted populations with elevated HbA1c levels. Intriguingly, the tested indicators for blood pressure-lowering treatment did not predict patient

  18. Predicting work-related disability and medical cost outcomes: a comparison of injury severity scoring methods.

    Science.gov (United States)

    Sears, Jeanne M; Blanar, Laura; Bowman, Stephen M

    2014-01-01

    Acute work-related trauma is a leading cause of death and disability among U.S. workers. Occupational health services researchers have described the pressing need to identify valid injury severity measures for purposes such as case-mix adjustment and the construction of appropriate comparison groups in programme evaluation, intervention, quality improvement, and outcome studies. The objective of this study was to compare the performance of several injury severity scores and scoring methods in the context of predicting work-related disability and medical cost outcomes. Washington State Trauma Registry (WTR) records for injuries treated from 1998 to 2008 were linked with workers' compensation claims. Several Abbreviated Injury Scale (AIS)-based injury severity measures (ISS, New ISS, maximum AIS) were estimated directly from ICD-9-CM codes using two software packages: (1) ICDMAP-90, and (2) Stata's user-written ICDPIC programme (ICDPIC). ICDMAP-90 and ICDPIC scores were compared with existing WTR scores using the Akaike Information Criterion, amount of variance explained, and estimated effects on outcomes. Competing risks survival analysis was used to evaluate work disability outcomes. Adjusted total medical costs were modelled using linear regression. The linked sample contained 6052 work-related injury events. There was substantial agreement between WTR scores and those estimated by ICDMAP-90 (kappa=0.73), and between WTR scores and those estimated by ICDPIC (kappa=0.68). Work disability and medical costs increased monotonically with injury severity, and injury severity was a significant predictor of work disability and medical cost outcomes in all models. WTR and ICDMAP-90 scores performed better with regard to predicting outcomes than did ICDPIC scores, but effect estimates were similar. Of the three severity measures, maxAIS was usually weakest, except when predicting total permanent disability. Injury severity was significantly associated with work disability

  19. ROLE OF GLYCOSYLATED HAEMOGLOBIN IN PREDICTION OF FOETOMATERNAL OUTCOME IN GESTATIONAL DIABETES MELLITUS

    Directory of Open Access Journals (Sweden)

    Vinita Sarbhai

    2016-08-01

    Full Text Available OBJECTIVE To explore the role of Glycosylated Haemoglobin (HbA1c in predicting foetomaternal outcome in pregnant women with gestational diabetes mellitus (GDM. METHOD This was a prospective study of 100 women with singleton pregnancy with 140 mg/dL on glucose challenge test enrolled in Kasturba Hospital, Delhi, from 2012 to 2013. A detailed history, examination, routine obstetrical investigations including 75 g Oral Glucose Tolerance Test (OGTT and HbA1c level were done. Patients were managed accordingly and followed till delivery. Their obstetrical and perinatal outcomes were noted and the data was compared using chi-squared test and Fischer’s exact test with a two-tailed p-value 6% HbA1c level and those with abnormal OGTT. Adverse maternal outcomes in patients with >6% HbA1c included excessive weight gain (68% vs. 58.2%, preeclampsia (44% vs. 38.2%, polyhydramnios (44% vs. 35.2%, caesarean section (68% vs. 52.9%, wound sepsis (24% vs. 17.6% as compared to patients with abnormal GTT. Adverse foetal outcomes and neonatal complications in patients with >6% HbA1c included preterm delivery (36% vs. 32.3%, intrauterine death (12% vs. 8.8%, LGA babies (52% vs. 29.4%, congenital anomalies (13.6% vs. 9.6%, respiratory distress (27.3% vs. 16.1%, hypoglycaemia (36.8% vs. 25.8%, hyperbilirubinaemia (31.8% vs. 29%, and NICU admission >2 days (95.4% vs. 64.5%. A high HbA1c was found to be comparable to OGTT in predicting adverse maternal outcome in GDM patients while a poor foetal outcome was more commonly associated with HbA1c >6%. CONCLUSIONS HbA1c is a sensitive tool for prediction of foetomaternal outcomes in patients with abnormal blood glucose value; hence, it should be advised in all pregnant women.

  20. Prediction of Bladder Outcomes after Traumatic Spinal Cord Injury: A Longitudinal Cohort Study.

    Science.gov (United States)

    Pavese, Chiara; Schneider, Marc P; Schubert, Martin; Curt, Armin; Scivoletto, Giorgio; Finazzi-Agrò, Enrico; Mehnert, Ulrich; Maier, Doris; Abel, Rainer; Röhrich, Frank; Weidner, Norbert; Rupp, Rüdiger; Kessels, Alfons G; Bachmann, Lucas M; Kessler, Thomas M

    2016-06-01

    Neurogenic bladder dysfunction represents one of the most common and devastating sequelae of traumatic spinal cord injury (SCI). As early prediction of bladder outcomes is essential to counsel patients and to plan neurourological management, we aimed to develop and validate a model to predict urinary continence and complete bladder emptying 1 y after traumatic SCI. Using multivariate logistic regression analysis from the data of 1,250 patients with traumatic SCI included in the European Multicenter Spinal Cord Injury study, we developed two prediction models of urinary continence and complete bladder emptying 1 y after traumatic SCI and performed an external validation in 111 patients. As predictors, we evaluated age, gender, and all variables of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) and of the Spinal Cord Independence Measure (SCIM). Urinary continence and complete bladder emptying 1 y after SCI were assessed through item 6 of SCIM. The full model relies on lower extremity motor score (LEMS), light-touch sensation in the S3 dermatome of ISNCSI, and SCIM subscale respiration and sphincter management: the area under the receiver operating characteristics curve (aROC) was 0.936 (95% confidence interval [CI]: 0.922-0.951). The simplified model is based on LEMS only: the aROC was 0.912 (95% CI: 0.895-0.930). External validation of the full and simplified models confirmed the excellent predictive power: the aROCs were 0.965 (95% CI: 0.934-0.996) and 0.972 (95% CI 0.943-0.999), respectively. This study is limited by the substantial number of patients with a missing 1-y outcome and by differences between derivation and validation cohort. Our study provides two simple and reliable models to predict urinary continence and complete bladder emptying 1 y after traumatic SCI. Early prediction of bladder function might optimize counselling and patient-tailored rehabilitative interventions and improve patient stratification in

  1. Does impulsivity predict outcome in treatment for binge eating disorder? A multimodal investigation.

    Science.gov (United States)

    Manasse, Stephanie M; Espel, Hallie M; Schumacher, Leah M; Kerrigan, Stephanie G; Zhang, Fengqing; Forman, Evan M; Juarascio, Adrienne S

    2016-10-01

    Multiple dimensions of impulsivity (e.g., affect-driven impulsivity, impulsive inhibition - both general and food-specific, and impulsive decision-making) are associated with binge eating pathology cross-sectionally, yet the literature on whether impulsivity predicts treatment outcome is limited. The present pilot study explored impulsivity-related predictors of 20-week outcome in a small open trial (n = 17) of a novel treatment for binge eating disorder. Overall, dimensions of impulsivity related to emotions (i.e., negative urgency) and food cues emerged as predictors of treatment outcomes (i.e., binge eating frequency and global eating pathology as measured by the Eating Disorders Examination), while more general measures of impulsivity were statistically unrelated to global eating pathology or binge frequency. Specifically, those with higher levels of negative urgency at baseline experienced slower and less pronounced benefit from treatment, and those with higher food-specific impulsivity had more severe global eating pathology at baseline that was consistent at post-treatment and follow-up. These preliminary findings suggest that patients high in negative urgency and with poor response inhibition to food cues may benefit from augmentation of existing treatments to achieve optimal outcomes. Future research will benefit from replication with a larger sample, parsing out the role of different dimensions of impulsivity in treatment outcome for eating disorders, and identifying how treatment can be improved to accommodate higher levels of baseline impulsivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Serum tenascin-C predicts severity and outcome of acute intracerebral hemorrhage.

    Science.gov (United States)

    Wang, Lin-Guo; Huangfu, Xue-Qin; Tao, Bo; Zhong, Guan-Jin; Le, Zhou-Di

    2018-06-01

    Tenascin-C is a matricellular protein related to brain injury. We studied serum tenascin-C in acute intracerebral hemorrhage (ICH) and examined the associations with severity and outcome following the acute event. Tenascin-C samples were obtained from 162 patients with acute hemorrhagic stroke and 162 healthy controls. Poor 90-day functional outcome was defined as modified Rankin Scale score > 2. Early neurological deterioration (END) and hematoma growth (HG) were recorded at 24 h. Patients had higher tenascin-C levels than controls. Tenascin-C levels were positively correlated with hematoma volume or National Institutes of Health Stroke Scale score at baseline. Elevated tenascin-C levels were independently associated with END, HG, 90-day mortality and poor functional outcome. Moreover, tenascin-C levels significantly predicted END, HG and 90-day outcomes under receiver operating characteristic curves. An increase in serum tenascin-C level is associated with an adverse outcome in ICH patients, supporting the potential role of serum tenascin-C as a prognostic biomarker for hemorrhagic stroke. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes.

    Science.gov (United States)

    Ramchandani, Manisha; Siddiqui, Muniza; Kanwar, Raveena; Lakha, Manwinder; Phi, Linda; Giacomelli, Luca; Chiappelli, Francesco

    2011-01-06

    The rate of preterm birth is a public health concern worldwide because it is increasing and efforts to prevent it have failed. We report a Clinically Relevant Complex Systematic Review (CSCSR) designed to identify and evaluate the best available evidence in support of the association between periodontal status in women and pregnancy outcome of preterm low birth weight. We hypothesize that the traditional limits of research synthesis must be expanded to incorporate a translational component. As a proof-of-concept model, we propose that this CSCSR can yield greater validity of efficacy and effectiveness through supplementing its recommendations with data of the proteomic signature of periodontal disease in pregnancy, which can contribute to addressing specifically the predictive validity for adverse outcomes. For this CRCSR, systematic reviews were identified through The National Library of MedicinePubmed, The Cochrane library, CINAHL, Google Scholar, Web of Science, and the American Dental Association web library. Independent reviewers quantified the relevance and quality of this literature with R-AMSTAR. Homogeneity and inter-rater reliability testing were supplemented with acceptable sampling analysis. Research synthesis outcomes were analyzed qualitatively toward a Bayesian inference, and converge to demonstrate a definite association between maternal periodontal disease and pregnancy outcome. This CRCSR limits heterogeneity in terms of periodontal disease, outcome measure, selection bias, uncontrolled confounders and effect modifiers. Taken together, the translational CRCSR model we propose suggests that further research is advocated to explore the fundamental mechanisms underlying this association, from a molecular and proteomic perspective.

  4. Parkinsonian motor impairment predicts personality domains related to genetic risk and treatment outcomes in schizophrenia.

    Science.gov (United States)

    Molina, Juan L; Calvó, María; Padilla, Eduardo; Balda, Mara; Alemán, Gabriela González; Florenzano, Néstor V; Guerrero, Gonzalo; Kamis, Danielle; Rangeon, Beatriz Molina; Bourdieu, Mercedes; Strejilevich, Sergio A; Conesa, Horacio A; Escobar, Javier I; Zwir, Igor; Cloninger, C Robert; de Erausquin, Gabriel A

    2017-01-01

    Identifying endophenotypes of schizophrenia is of critical importance and has profound implications on clinical practice. Here we propose an innovative approach to clarify the mechanims through which temperament and character deviance relates to risk for schizophrenia and predict long-term treatment outcomes. We recruited 61 antipsychotic naïve subjects with chronic schizophrenia, 99 unaffected relatives, and 68 healthy controls from rural communities in the Central Andes. Diagnosis was ascertained with the Schedules of Clinical Assessment in Neuropsychiatry; parkinsonian motor impairment was measured with the Unified Parkinson's Disease Rating Scale; mesencephalic parenchyma was evaluated with transcranial ultrasound; and personality traits were assessed using the Temperament and Character Inventory. Ten-year outcome data was available for ~40% of the index cases. Patients with schizophrenia had higher harm avoidance and self-transcendence (ST), and lower reward dependence (RD), cooperativeness (CO), and self-directedness (SD). Unaffected relatives had higher ST and lower CO and SD. Parkinsonism reliably predicted RD, CO, and SD after correcting for age and sex. The average duration of untreated psychosis (DUP) was over 5 years. Further, SD was anticorrelated with DUP and antipsychotic dosing at follow-up. Baseline DUP was related to antipsychotic dose-years. Further, 'explosive/borderline', 'methodical/obsessive', and 'disorganized/schizotypal' personality profiles were associated with increased risk of schizophrenia. Parkinsonism predicts core personality features and treatment outcomes in schizophrenia. Our study suggests that RD, CO, and SD are endophenotypes of the disease that may, in part, be mediated by dopaminergic function. Further, SD is an important determinant of treatment course and outcome.

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

    Science.gov (United States)

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

    2018-03-01

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

  6. An evidence-based decision assistance model for predicting training outcome in juvenile guide dogs.

    Science.gov (United States)

    Harvey, Naomi D; Craigon, Peter J; Blythe, Simon A; England, Gary C W; Asher, Lucy

    2017-01-01

    Working dog organisations, such as Guide Dogs, need to regularly assess the behaviour of the dogs they train. In this study we developed a questionnaire-style behaviour assessment completed by training supervisors of juvenile guide dogs aged 5, 8 and 12 months old (n = 1,401), and evaluated aspects of its reliability and validity. Specifically, internal reliability, temporal consistency, construct validity, predictive criterion validity (comparing against later training outcome) and concurrent criterion validity (comparing against a standardised behaviour test) were evaluated. Thirty-nine questions were sourced either from previously published literature or created to meet requirements identified via Guide Dogs staff surveys and staff feedback. Internal reliability analyses revealed seven reliable and interpretable trait scales named according to the questions within them as: Adaptability; Body Sensitivity; Distractibility; Excitability; General Anxiety; Trainability and Stair Anxiety. Intra-individual temporal consistency of the scale scores between 5-8, 8-12 and 5-12 months was high. All scales excepting Body Sensitivity showed some degree of concurrent criterion validity. Predictive criterion validity was supported for all seven scales, since associations were found with training outcome, at at-least one age. Thresholds of z-scores on the scales were identified that were able to distinguish later training outcome by identifying 8.4% of all dogs withdrawn for behaviour and 8.5% of all qualified dogs, with 84% and 85% specificity. The questionnaire assessment was reliable and could detect traits that are consistent within individuals over time, despite juvenile dogs undergoing development during the study period. By applying thresholds to scores produced from the questionnaire this assessment could prove to be a highly valuable decision-making tool for Guide Dogs. This is the first questionnaire-style assessment of juvenile dogs that has shown value in predicting

  7. Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

    Science.gov (United States)

    Bychkov, Dmitrii; Turkki, Riku; Haglund, Caj; Linder, Nina; Lundin, Johan

    2016-03-01

    Recent advances in computer vision enable increasingly accurate automated pattern classification. In the current study we evaluate whether a convolutional neural network (CNN) can be trained to predict disease outcome in patients with colorectal cancer based on images of tumor tissue microarray samples. We compare the prognostic accuracy of CNN features extracted from the whole, unsegmented tissue microarray spot image, with that of CNN features extracted from the epithelial and non-epithelial compartments, respectively. The prognostic accuracy of visually assessed histologic grade is used as a reference. The image data set consists of digitized hematoxylin-eosin (H and E) stained tissue microarray samples obtained from 180 patients with colorectal cancer. The patient samples represent a variety of histological grades, have data available on a series of clinicopathological variables including long-term outcome and ground truth annotations performed by experts. The CNN features extracted from images of the epithelial tissue compartment significantly predicted outcome (hazard ratio (HR) 2.08; CI95% 1.04-4.16; area under the curve (AUC) 0.66) in a test set of 60 patients, as compared to the CNN features extracted from unsegmented images (HR 1.67; CI95% 0.84-3.31, AUC 0.57) and visually assessed histologic grade (HR 1.96; CI95% 0.99-3.88, AUC 0.61). As a conclusion, a deep-learning classifier can be trained to predict outcome of colorectal cancer based on images of H and E stained tissue microarray samples and the CNN features extracted from the epithelial compartment only resulted in a prognostic discrimination comparable to that of visually determined histologic grade.

  8. Heart rate variability predicts therapy outcome in pain-predominant multisomatoform disorder.

    Science.gov (United States)

    Angelovski, Angela; Sattel, Heribert; Henningsen, Peter; Sack, Martin

    2016-04-01

    Autonomic imbalance establishes an important model to understand organically unexplained physical complaints. Our study aimed to investigate whether the functioning of the autonomous nervous system corresponds with somatoform symptoms and predicts the outcome of brief psychotherapy in these patients. As a part of multicenter study assessing effects of brief psychodynamic interpersonal therapy on multisomatoform disorder (PISO-study), 106 patients participated in a stress experiment investigating autonomic reactivity during application of the Stroop-test. Patients were randomized receiving either enhanced medical care (EMC, N=49) or psychotherapy (N=57). Autonomic baseline functioning as well as stress reactivity of heart rate (HR) and heart rate variability (HRV) were analyzed in their relation to symptom measures and as potential predictors of the primary outcome (Physical Component Score of the SF-36) during 9-month follow-up. After therapy patients markedly and sustainably improved in physical quality of life, and this long-term improvement was predicted by baseline HR and HRV. HRV also predicted change in pain symptoms following psychotherapy. A responder analysis revealed a significant better treatment outcome in patients with high pre-treatment HRV (OR 3.4, CI: 1.2-9.9, p=.0035). No significant associations between HR or HRV and outcome measures were found in the EMC group. In our study, the adaptability of the autonomous nervous system as indicated by low pretreatment HR and high HRV was associated with a more pronounced benefit from psychotherapy. This finding can be explained by a possible association between autonomic self-regulation and emotional learning capacities. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Scoring Systems for Outcome Prediction in a Cardiac Surgical Intensive Care Unit: A Comparative Study.

    Science.gov (United States)

    Exarchopoulos, Themistocles; Charitidou, Efstratia; Dedeilias, Panagiotis; Charitos, Christos; Routsi, Christina

    2015-07-01

    Most scoring systems used to predict clinical outcome in critical care were not designed for application in cardiac surgery patients. To compare the predictive ability of the most widely used scoring systems (Acute Physiology and Chronic Health Evaluation [APACHE] II, Simplified Acute Physiology Score [SAPS] II, and Sequential Organ Failure Assessment [SOFA]) and of 2 specialized systems (European System for Cardiac Operative Risk Evaluation [EuroSCORE] II and the cardiac surgery score [CASUS]) for clinical outcome in patients after cardiac surgery. Consecutive patients admitted to a cardiac surgical intensive care unit (CSICU) were prospectively studied. Data on the preoperative condition, intraoperative parameters, and postoperative course were collected. EuroSCORE II, CASUS, and scores from 3 general severity-scoring systems (APACHE II, SAPS II, and SOFA) were calculated on the first postoperative day. Clinical outcome was defined as 30-day mortality and in-hospital morbidity. A total of 150 patients were included. Thirty-day mortality was 6%. CASUS was superior in outcome prediction, both in relation to discrimination (area under curve, 0.89) and calibration (Brier score = 0.043, χ(2) = 2.2, P = .89), followed by EuroSCORE II for 30-day mortality (area under curve, 0.87) and SOFA for morbidity (Spearman ρ= 0.37 and 0.35 for the CSICU length of stay and duration of mechanical ventilation, respectively; Wilcoxon W = 367.5, P = .03 for probability of readmission to CSICU). CASUS can be recommended as the most reliable and beneficial option for benchmarking and risk stratification in cardiac surgery patients. ©2015 American Association of Critical-Care Nurses.

  10. A comparative study of four intensive care outcome prediction models in cardiac surgery patients.

    Science.gov (United States)

    Doerr, Fabian; Badreldin, Akmal Ma; Heldwein, Matthias B; Bossert, Torsten; Richter, Markus; Lehmann, Thomas; Bayer, Ole; Hekmat, Khosro

    2011-03-01

    Outcome prediction scoring systems are increasingly used in intensive care medicine, but most were not developed for use in cardiac surgery patients. We compared the performance of four intensive care outcome prediction scoring systems (Acute Physiology and Chronic Health Evaluation II [APACHE II], Simplified Acute Physiology Score II [SAPS II], Sequential Organ Failure Assessment [SOFA], and Cardiac Surgery Score [CASUS]) in patients after open heart surgery. We prospectively included all consecutive adult patients who underwent open heart surgery and were admitted to the intensive care unit (ICU) between January 1st 2007 and December 31st 2008. Scores were calculated daily from ICU admission until discharge. The outcome measure was ICU mortality. The performance of the four scores was assessed by calibration and discrimination statistics. Derived variables (Mean- and Max- scores) were also evaluated. During the study period, 2801 patients (29.6% female) were included. Mean age was 66.9 ± 10.7 years and the ICU mortality rate was 5.2%. Calibration tests for SOFA and CASUS were reliable throughout (p-value not predicted and observed outcome for SAPS II (days 1, 2, 3 and 5) and APACHE II (days 2 and 3). CASUS, and its mean- and maximum-derivatives, discriminated better between survivors and non-survivors than the other scores throughout the study (area under curve ≥ 0.90). In order of best discrimination, CASUS was followed by SOFA, then SAPS II, and finally APACHE II. SAPS II and APACHE II derivatives had discrimination results that were superior to those of the SOFA derivatives. CASUS and SOFA are reliable ICU mortality risk stratification models for cardiac surgery patients. SAPS II and APACHE II did not perform well in terms of calibration and discrimination statistics.

  11. Automated prediction of tissue outcome after acute ischemic stroke in computed tomography perfusion images

    Science.gov (United States)

    Vos, Pieter C.; Bennink, Edwin; de Jong, Hugo; Velthuis, Birgitta K.; Viergever, Max A.; Dankbaar, Jan Willem

    2015-03-01

    Assessment of the extent of cerebral damage on admission in patients with acute ischemic stroke could play an important role in treatment decision making. Computed tomography perfusion (CTP) imaging can be used to determine the extent of damage. However, clinical application is hindered by differences among vendors and used methodology. As a result, threshold based methods and visual assessment of CTP images has not yet shown to be useful in treatment decision making and predicting clinical outcome. Preliminary results in MR studies have shown the benefit of using supervised classifiers for predicting tissue outcome, but this has not been demonstrated for CTP. We present a novel method for the automatic prediction of tissue outcome by combining multi-parametric CTP images into a tissue outcome probability map. A supervised classification scheme was developed to extract absolute and relative perfusion values from processed CTP images that are summarized by a trained classifier into a likelihood of infarction. Training was performed using follow-up CT scans of 20 acute stroke patients with complete recanalization of the vessel that was occluded on admission. Infarcted regions were annotated by expert neuroradiologists. Multiple classifiers were evaluated in a leave-one-patient-out strategy for their discriminating performance using receiver operating characteristic (ROC) statistics. Results showed that a RandomForest classifier performed optimally with an area under the ROC of 0.90 for discriminating infarct tissue. The obtained results are an improvement over existing thresholding methods and are in line with results found in literature where MR perfusion was used.

  12. 3 Tesla MRI-negative focal epilepsies: Presurgical evaluation, postoperative outcome and predictive factors.

    Science.gov (United States)

    Kogias, Evangelos; Klingler, Jan-Helge; Urbach, Horst; Scheiwe, Christian; Schmeiser, Barbara; Doostkam, Soroush; Zentner, Josef; Altenmüller, Dirk-Matthias

    2017-12-01

    To investigate presurgical diagnostic modalities, clinical and seizure outcome as well as predictive factors after resective epilepsy surgery in 3 Tesla MRI-negative focal epilepsies. This retrospective study comprises 26 patients (11 males/15 females, mean age 34±12years, range 13-50 years) with 3 Tesla MRI-negative focal epilepsies who underwent resective epilepsy surgery. Non-invasive and invasive presurgical diagnostic modalities, type and localization of resection, clinical and epileptological outcome with a minimum follow-up of 1year (range 1-11 years, mean 2.5±2.3years) after surgery as well as outcome predictors were evaluated. All patients underwent invasive video-EEG monitoring after implantation of intracerebral depth and/or subdural electrodes. Ten patients received temporal and 16 extratemporal or multilobar (n=4) resections. There was no perioperative death or permanent morbidity. Overall, 12 of 26 patients (46%) were completely seizure-free (Engel IA) and 65% had a favorable outcome (Engel I-II). In particular, seizure-free ratio was 40% in the temporal and 50% in the extratemporal group. In the temporal group, long duration of epilepsy correlated with poor seizure outcome, whereas congruent unilateral FDG-PET hypometabolism correlated with a favorable outcome. In almost two thirds of temporal and extratemporal epilepsies defined as "non-lesional" by 3 Tesla MRI criteria, a favorable postoperative seizure outcome (Engel I-II) can be achieved with accurate multimodal presurgical evaluation including intracranial EEG recordings. In the temporal group, most favorable results were obtained when FDG-PET displayed congruent unilateral hypometabolism. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Computed tomography of the brain in predicting outcome of traumatic intracranial haemorrhage in Malaysian patients

    International Nuclear Information System (INIS)

    Azian, A.A.; Nurulazman, A.A.; Shuaib, I.L.; Mahayidin, M.; Ariff, A.R.; Naing, N.N.; Abdullah, J.

    2001-01-01

    Head injury is a significant economic, social and medical problem all over the world. Road accidents are the most frequent cause of head injury in Malaysia which highest risk in the young (15 to 24 years old). The associated outcomes include good recovery, possibility of death for the severely injured, which may cause disruption of the lives of their family members. It is important to predict the outcome as it will provide sound information to assist clinicians in Malaysia in providing prognostic information to patients and their families, to assess the effectiveness of different modes of treatment in promoting recovery and to document the significance of head injury as a public health problem. Results. A total of 103 cases with intracranial hemorrhage i.e. intracerebral hemorrhage, extradural hemorrhage, subdural hemorrhage, intraventricular hemorrhage, hemorrhagic contusion and subarachnoid hemorrhage, following motor vehicle accidents was undertaken to study factors contributing to either good or poor outcome according to the Glasgow outcome scale. Patients below 12 years of age were excluded. The end point of the study was taken at 24 months post injury. The selected variables were incorporated into models generated by logistic regression techniques of multivariate analysis to see the significant predictors of outcome as well as the correlation between the CT findings with GCS. Conclusion. Significant predictors of outcome were GCS on arrival in the accident emergency department, pupillary reflex and the CT scan findings. The CT predictors of outcome include ICH, EDH, IVH, present of SAH, site of ICH, volumes of EDH and SDH as well as midline shift. (author)

  14. PET in infancy predicts long-term outcome during adolescence in cryptogenic West syndrome.

    Science.gov (United States)

    Natsume, J; Maeda, N; Itomi, K; Kidokoro, H; Ishihara, N; Takada, H; Okumura, A; Kubota, T; Miura, K; Aso, K; Morikawa, T; Kato, K; Negoro, T; Watanabe, K

    2014-08-01

    Developmental and seizure outcomes in patients with cryptogenic West syndrome are variable. Our aim was to clarify the relationship between FDG-PET findings in infancy and long-term seizure and developmental outcome in cryptogenic West syndrome. From 1991 to 1999, we prospectively performed FDG-PET from the onset of cryptogenic West syndrome in 27 patients. PET was performed at onset and at 10 months of age. In 2012, we evaluated the educational status, psychomotor development, and seizure outcome in 23 of the 27 patients (13-22 years of age). The correlation between PET findings and outcome was evaluated. At onset, PET showed hypometabolism in 13 patients (57%). The second PET after the initial treatment revealed cortical hypometabolism in 7 patients (30%). While hypometabolism at onset disappeared on the second PET in 9 patients, it was newly revealed in 3 patients on the second PET. In 2012, seven patients had persistent or recurrent seizures. Eight patients had intellectual impairment. The first PET did not correlate with seizure or developmental outcome. Five of 7 patients (71%) with hypometabolism seen on the second PET had persistent or recurrent seizures, while 14 of 16 (88%) patients with normal findings on the second PET were free of seizures. Five of 7 patients (71%) showing hypometabolism on the second PET had intellectual impairment. Thirteen of 16 (81%) patients with normal findings on the second PET showed normal intelligence. A significant correlation was found between the second PET and long-term seizure (P = .01) or developmental outcome (P = .03). Cortical hypometabolism is not permanent; it changes with clinical symptoms. Hypometabolism after initial treatment predicts long-term seizures and poor developmental outcome. © 2014 by American Journal of Neuroradiology.

  15. Pre-pregnancy high-risk factors at first antenatal visit: how predictive are these of pregnancy outcomes?

    Directory of Open Access Journals (Sweden)

    Tandu-Umba B

    2014-12-01

    , low birth weight, macrosomia, preeclampsia/eclampsia, cesarean section, premature rupture of membranes, and stillbirth, respectively. Outcomes that were significantly influenced by non-pathologic risk factors were also significantly influenced by pathologic risk factors.Conclusion: Pregnancy adverse outcomes are strongly influenced by either non-pathologic or pathologic pre-pregnancy risk factors at first antenatal visit booking. The recurrence potential of complications is one reason to establish the predictability and preventability of morbidity such that the most appropriate referrals and best options throughout the pregnancy can be determined.Keywords: pre-pregnancy risk factors, recurrence, maternal/perinatal outcomes, developing countries

  16. Developing and Testing a Model to Predict Outcomes of Organizational Change

    Science.gov (United States)

    Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

    2003-01-01

    Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

  17. Nucleated red blood cells and early EEG: predicting Sarnat stage and two year outcome.

    LENUS (Irish Health Repository)

    Walsh, B H

    2012-01-31

    AIMS: Hypoxic Ischaemic Encephalopathy (HIE) causes characteristic changes of the electroencephalogram (EEG), and a raised Nucleated Red Blood Cell (NRBC) count compared to controls. We wished to examine whether combining these markers could improve their ability to predict HIE severity in the first 24h. METHODS: Term infants with HIE were recruited. NRBC count and continuous multi-channel EEG were recorded within the first 24h. Neurological assessment was carried out at 24 months. A control population with NRBC counts in the first 24h was recruited. RESULTS: 44 infants with HIE and 43 control infants were recruited. Of the HIE population 39 completed a 2 year follow-up. The median NRBC count differed significantly between the controls and those with HIE (3\\/100 WBC [range of 0-11] vs 12.3\\/100 WBC [0-240]) (p<0.001). Within the HIE population the median NRBC count was significantly greater in infants with moderate\\/severe HIE than mild (16\\/100 WBC [range of 0-240] vs 8\\/100 WBC [1-23]) (p=0.016), and among infants with abnormal outcome compared to normal (21.3\\/100 WBC [1-239.8] vs 8.3\\/100 WBC [0-50])(p=0.03). The predictive ability of EEG changed with time post-delivery, therefore results are given at both 12 and 24h of age. At both time points the combined marker had a stronger correlation than EEG alone; with HIE severity (12h: r=0.661 vs r=0.622), (24h: r=0.645 vs r=0.598), and with outcome at 2 years (12h: r=0.756 vs r=0.652), (24h: r=0.802 vs r=0.746). CONCLUSION: Combining early EEG and NRBC count to predict HIE severity and neurological outcome, improved the predictive ability of either in isolation.

  18. An early, novel illness severity score to predict outcome after cardiac arrest.

    Science.gov (United States)

    Rittenberger, Jon C; Tisherman, Samuel A; Holm, Margo B; Guyette, Francis X; Callaway, Clifton W

    2011-11-01

    Illness severity scores are commonly employed in critically ill patients to predict outcome. To date, prior scores for post-cardiac arrest patients rely on some event-related data. We developed an early, novel post-arrest illness severity score to predict survival, good outcome and development of multiple organ failure (MOF) after cardiac arrest. Retrospective review of data from adults treated after in-hospital or out-of-hospital cardiac arrest in a single tertiary care facility between 1/1/2005 and 12/31/2009. In addition to clinical data, initial illness severity was measured using serial organ function assessment (SOFA) scores and full outline of unresponsiveness (FOUR) scores at hospital or intensive care unit arrival. Outcomes were hospital mortality, good outcome (discharge to home or rehabilitation) and development of multiple organ failure (MOF). Single-variable logistic regression followed by Chi-squared automatic interaction detector (CHAID) was used to determine predictors of outcome. Stepwise multivariate logistic regression was used to determine the independent association between predictors and each outcome. The Hosmer-Lemeshow test was used to evaluate goodness of fit. The n-fold method was used to cross-validate each CHAID analysis and the difference between the misclassification risk estimates was used to determine model fit. Complete data from 457/495 (92%) subjects identified distinct categories of illness severity using combined FOUR motor and brainstem subscales, and combined SOFA cardiovascular and respiratory subscales: I. Awake; II. Moderate coma without cardiorespiratory failure; III. Moderate coma with cardiorespiratory failure; and IV. Severe coma. Survival was independently associated with category (I: OR 58.65; 95% CI 27.78, 123.82; II: OR 14.60; 95% CI 7.34, 29.02; III: OR 10.58; 95% CI 4.86, 23.00). Category was also similarly associated with good outcome and development of MOF. The proportion of subjects in each category changed

  19. Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning.

    Science.gov (United States)

    Higaki, Akinori; Mogi, Masaki; Iwanami, Jun; Min, Li-Juan; Bai, Hui-Yu; Shan, Bao-Shuai; Kukida, Masayoshi; Kan-No, Harumi; Ikeda, Shuntaro; Higaki, Jitsuo; Horiuchi, Masatsugu

    2018-01-01

    The Morris water maze test (MWM) is one of the most popular and established behavioral tests to evaluate rodents' spatial learning ability. The conventional training period is around 5 days, but there is no clear evidence or guidelines about the appropriate duration. In many cases, the final outcome of the MWM seems predicable from previous data and their trend. So, we assumed that if we can predict the final result with high accuracy, the experimental period could be shortened and the burden on testers reduced. An artificial neural network (ANN) is a useful modeling method for datasets that enables us to obtain an accurate mathematical model. Therefore, we constructed an ANN system to estimate the final outcome in MWM from the previously obtained 4 days of data in both normal mice and vascular dementia model mice. Ten-week-old male C57B1/6 mice (wild type, WT) were subjected to bilateral common carotid artery stenosis (WT-BCAS) or sham-operation (WT-sham). At 6 weeks after surgery, we evaluated their cognitive function with MWM. Mean escape latency was significantly longer in WT-BCAS than in WT-sham. All data were collected and used as training data and test data for the ANN system. We defined a multiple layer perceptron (MLP) as a prediction model using an open source framework for deep learning, Chainer. After a certain number of updates, we compared the predicted values and actual measured values with test data. A significant correlation coefficient was derived form the updated ANN model in both WT-sham and WT-BCAS. Next, we analyzed the predictive capability of human testers with the same datasets. There was no significant difference in the prediction accuracy between human testers and ANN models in both WT-sham and WT-BCAS. In conclusion, deep learning method with ANN could predict the final outcome in MWM from 4 days of data with high predictive accuracy in a vascular dementia model.

  20. Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning.

    Directory of Open Access Journals (Sweden)

    Akinori Higaki

    Full Text Available The Morris water maze test (MWM is one of the most popular and established behavioral tests to evaluate rodents' spatial learning ability. The conventional training period is around 5 days, but there is no clear evidence or guidelines about the appropriate duration. In many cases, the final outcome of the MWM seems predicable from previous data and their trend. So, we assumed that if we can predict the final result with high accuracy, the experimental period could be shortened and the burden on testers reduced. An artificial neural network (ANN is a useful modeling method for datasets that enables us to obtain an accurate mathematical model. Therefore, we constructed an ANN system to estimate the final outcome in MWM from the previously obtained 4 days of data in both normal mice and vascular dementia model mice. Ten-week-old male C57B1/6 mice (wild type, WT were subjected to bilateral common carotid artery stenosis (WT-BCAS or sham-operation (WT-sham. At 6 weeks after surgery, we evaluated their cognitive function with MWM. Mean escape latency was significantly longer in WT-BCAS than in WT-sham. All data were collected and used as training data and test data for the ANN system. We defined a multiple layer perceptron (MLP as a prediction model using an open source framework for deep learning, Chainer. After a certain number of updates, we compared the predicted values and actual measured values with test data. A significant correlation coefficient was derived form the updated ANN model in both WT-sham and WT-BCAS. Next, we analyzed the predictive capability of human testers with the same datasets. There was no significant difference in the prediction accuracy between human testers and ANN models in both WT-sham and WT-BCAS. In conclusion, deep learning method with ANN could predict the final outcome in MWM from 4 days of data with high predictive accuracy in a vascular dementia model.

  1. Predictive outcome factors in the young patient treated with lumbar disc herniation surgery.

    Science.gov (United States)

    Strömqvist, Fredrik; Strömqvist, Björn; Jönsson, Bo; Gerdhem, Paul; Karlsson, Magnus K

    2016-10-01

    OBJECTIVE The aim of this study was to evaluate predictive factors for outcome after lumbar disc herniation surgery in young patients. METHODS In the national Swedish spine register, the authors identified 180 patients age 20 years or younger, in whom preoperative and 1-year postoperative data were available. The cohort was treated with primary open surgery due to lumbar disc herniation between 2000 and 2010. Before and 1 year after surgery, the patients graded their back and leg pain on a visual analog scale, quality of life by the 36-Item Short-Form Health Survey and EuroQol-5 Dimensions, and disability by the Oswestry Disability Index. Subjective satisfaction rate was registered on a Likert scale (satisfied, undecided, or dissatisfied). The authors evaluated if age, sex, preoperative level of leg and back pain, duration of leg pain, pain distribution, quality of life, mental status, and/or disability were associated with the outcome. The primary end point variable was the grade of patient satisfaction. RESULTS Lumbar disc herniation surgery in young patients normalizes quality of life according to the 36-Item Short-Form Health Survey, and only 4.5% of the patients were unsatisfied with the surgical outcome. Predictive factors for inferior postoperative patient-reported outcome measures (PROM) scores were severe preoperative leg or back pain, low preoperative mental health, and pronounced preoperative disability, but only low preoperative mental health was associated with inferiority in the subjective grade of satisfaction. No associations were found between preoperative duration of leg pain, distribution of pain, or health-related quality of life and the postoperative PROM scores or the subjective grade of satisfaction. CONCLUSIONS Lumbar disc herniation surgery in young patients generally yields a satisfactory outcome. Severe preoperative pain, low mental health, and severe disability increase the risk of reaching low postoperative PROM scores, but are only of

  2. Diffusion-weighted ASPECTS as an independent marker for predicting functional outcome.

    Science.gov (United States)

    Tei, Hideaki; Uchiyama, Sinichiro; Usui, Toru; Ohara, Kuniko

    2011-04-01

    Whether lesion volume on diffusion-weighted MRI imaging (DWI) can reliably predict functional outcome in acute ischemic stroke is controversial. The aim of our study was to assess whether the Alberta Stroke Program Early CT Score (ASPECTS) on DWI is useful for predicting functional outcome in patients with anterior circulation infarction with a broad range of severities. Three-hundred and fifty patients with first-ever ischemic stroke in the anterior circulation within 24 h of onset were enrolled. We compared background characteristics, vital signs, laboratory data, and MRI findings between favorable (F) and unfavorable (U) outcome groups at 3 months, according to the modified Rankin Scale (mRS). The F and U groups were defined as having a mRS of 0-2 and 3-6, respectively. DWI ASPECTS was scored by DWI obtained 3-24 h after onset. Two-hundred and eighteen patients (62.3%) were classified into the F group and 132 patients (37.7%) into the U group. On univariate analysis, the F group patients were younger, had lower score of the National Institutes of Health Stroke Scale (NIHSS) at entry (5.7 ± 3.3 vs. 14.2 ± 6.0), male predominance, longer time after onset, lower rate of prior antithrombotic therapy, higher hematocrit and lower fibrinogen than the U group patients. Stroke subtype was different between the two groups, and F group patients had higher DWI ASPECTS score, lower leukoaraiosis and medial temporal atrophy score, and lower rate of early neurological deterioration (END) than the U group patients. Multiple logistic regression analysis revealed that NIHSS (p < 0.001), prior antithrombotic therapy (p = 0.013), ASPECTS (p = 0.002), and END (p < 0.001) were independent predictors of functional outcome. DWI ASPECTS can be an independent predictor for functional outcome, along with other clinical variables.

  3. Predicting outcomes in patients with chronic myeloid leukemia at any time during tyrosine kinase inhibitor therapy.

    Science.gov (United States)

    Quintás-Cardama, Alfonso; Choi, Sangbum; Kantarjian, Hagop; Jabbour, Elias; Huang, Xuelin; Cortes, Jorge

    2014-08-01

    Current recommendations for monitoring patients with chronic myeloid leukemia (CML) provide recommendations for response assessment and treatment only at 3, 6, 12, and 18 months. These recommendations are based on clinical trial outcomes computed from treatment start. Conditional survival estimates take into account the changing hazard rates as time from treatment elapses as a continuum. We performed conditional survival analyses among patients with CML to improve prognostication at any time point during the course of therapy. We used 2 cohorts of patients with CML in chronic phase: 1 treated in the frontline DASISION (Dasatinib versus Imatinib Study in Treatment - Naïve CML) phase III study (n = 519) and another treated after imatinib treatment had failed in the dasatinib dose-optimization phase III CA180-034 study (n = 670). Conditional survival estimates were calculated. A modified Cox proportional hazards model was used to build a prognostic nomogram. As the time alive or free from events from commencement of treatment increased, conditional survival estimates changed. No differences were observed regarding future outcomes between patients treated with imatinib or dasatinib in the frontline setting for patients with the same breakpoint cluster region-abelson 1 (BCR-ABL1) transcript levels evaluated at the same time point. Age older than 60 years greatly affected future outcomes particularly in the short-term. Conditional survival-based nomograms allowed the prediction of future outcomes at any time point. In summary, we designed a calculator to predict future outcomes of patients with CML at any time point during the course of therapy. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Adolescent Eating Disorders Predict Psychiatric, High-Risk Behaviors and Weight Outcomes in Young Adulthood.

    Science.gov (United States)

    Micali, Nadia; Solmi, Francesca; Horton, Nicholas J; Crosby, Ross D; Eddy, Kamryn T; Calzo, Jerel P; Sonneville, Kendrin R; Swanson, Sonja A; Field, Alison E

    2015-08-01

    To investigate whether anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), and other specified feeding and eating disorders (OSFED), including purging disorder (PD), subthreshold BN, and BED at ages 14 and 16 years, are prospectively associated with later depression, anxiety disorders, alcohol and substance use, and self-harm. Eating disorders were ascertained at ages 14 and 16 years in 6,140 youth at age 14 (58% of those eligible) and 5,069 at age 16 (52% of those eligible) as part of the prospective Avon Longitudinal Study of Parents and Children (ALSPAC). Outcomes (depression, anxiety disorders, binge drinking, drug use, deliberate self-harm, weight status) were measured using interviews and questionnaires about 2 years after predictors. Generalized estimating equation models adjusting for gender, socio-demographic variables, and prior outcome were used to examine prospective associations between eating disorders and each outcome. All eating disorders were predictive of later anxiety disorders. AN, BN, BED, PD, and OSFED were prospectively associated with depression (respectively AN: odds ratio [OR] = 1.39, 95% CI = 1.00-1.94; BN: OR = 3.39, 95% CI = 1.25-9.20; BED: OR = 2.00, 95% CI = 1.06-3.75; and PD: OR = 2.56, 95% CI = 1.38-4.74). All eating disorders but AN predicted drug use and deliberate self-harm (BN: OR = 5.72, 95% CI = 2.22-14.72; PD: OR = 4.88, 95% CI = 2.78-8.57; subthreshold BN: OR = 3.97, 95% CI = 1.44-10.98; and subthreshold BED: OR = 2.32, 95% CI = 1.43-3.75). Although BED and BN predicted obesity (respectively OR = 3.58, 95% CI = 1.06-12.14 and OR = 6.42, 95% CI = 1.69-24.30), AN was prospectively associated with underweight. Adolescent eating disorders, including subthreshold presentations, predict negative outcomes, including mental health disorders, substance use, deliberate self-harm, and weight outcomes. This study highlights the high public health and clinical burden of eating disorders

  5. Adolescent Eating Disorders Predict Psychiatric, High-Risk Behaviors and Weight Outcomes in Young Adulthood

    Science.gov (United States)

    Micali, Nadia; Solmi, Francesca; Horton, Nicholas J.; Crosby, Ross D.; Eddy, Kamryn T.; Calzo, Jerel P.; Sonneville, Kendrin R.; Swanson, Sonja A.; Field, Alison E.

    2015-01-01

    Objective To investigate whether anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), and other specified feeding and eating disorders (OSFED), including purging disorder (PD), subthreshold BN, and BED at ages 14 and 16, are prospectively associated with later depression, anxiety disorders, alcohol and substance use, and self-harm. Method Eating disorders were ascertained at 14 and 16 years of age in 6,140 youth at age 14 (58% of those eligible) and 5,069 at age 16 (52% of those eligible) as part of the prospective Avon Longitudinal Study of Parents and Children (ALSPAC). Outcomes (depression, anxiety disorders, binge drinking, drug use, deliberate self-harm, weight status) were measured using interviews and questionnaires about 2 years following predictors. Generalized estimating equation models adjusting for gender, socio-demographic variables, and prior outcome were used to examine prospective associations between eating disorders and each outcome. Results All eating disorders were predictive of later anxiety disorders. AN, BN, BED, PD, and OSFED were prospectively associated with depression (respectively AN: odds ratio [OR]=1.39 [95% CIs: 1.00-1.94]; BN: OR=3.39[1.25-9.20]; BED: OR=2.00 [1.06-3.75]; PD: OR=2.56 [1.38-4.74]). All eating disorders but AN predicted drug use and deliberate self-harm (BN: OR=5.72[2.22-14.72], PD: OR=4.88[2.78-8.57], subthreshold BN: OR=3.97[1.44-10.98], subthreshold BED: OR=2.32[1.43-3.75]). Whilst BED and BN predicted obesity (respectively OR=3.58 [1.06-12.14] and OR=6.42 [1.69-24.30]), AN was prospectively associated with underweight. Conclusions Adolescent eating disorders, including subthreshold presentations, predict negative outcomes, including mental health disorders, substance use, deliberate self-harm, and weight outcomes. This study highlights the high public health and clinical burden of eating disorders among adolescents. PMID:26210334

  6. A comparative study of four intensive care outcome prediction models in cardiac surgery patients

    Directory of Open Access Journals (Sweden)

    Lehmann Thomas

    2011-03-01

    Full Text Available Abstract Background Outcome prediction scoring systems are increasingly used in intensive care medicine, but most were not developed for use in cardiac surgery patients. We compared the performance of four intensive care outcome prediction scoring systems (Acute Physiology and Chronic Health Evaluation II [APACHE II], Simplified Acute Physiology Score II [SAPS II], Sequential Organ Failure Assessment [SOFA], and Cardiac Surgery Score [CASUS] in patients after open heart surgery. Methods We prospectively included all consecutive adult patients who underwent open heart surgery and were admitted to the intensive care unit (ICU between January 1st 2007 and December 31st 2008. Scores were calculated daily from ICU admission until discharge. The outcome measure was ICU mortality. The performance of the four scores was assessed by calibration and discrimination statistics. Derived variables (Mean- and Max- scores were also evaluated. Results During the study period, 2801 patients (29.6% female were included. Mean age was 66.9 ± 10.7 years and the ICU mortality rate was 5.2%. Calibration tests for SOFA and CASUS were reliable throughout (p-value not Conclusions CASUS and SOFA are reliable ICU mortality risk stratification models for cardiac surgery patients. SAPS II and APACHE II did not perform well in terms of calibration and discrimination statistics.

  7. Relationships between genetic polymorphisms and transcriptional profiles for outcome prediction in anticancer agent treatment.

    Science.gov (United States)

    Paik, Hyojung; Lee, Eunjung; Lee, Doheon

    2010-12-01

    In the era of personal genomics, predicting the individual response to drug-treatment is a challenge of biomedical research. The aim of this study was to validate whether interaction information between genetic and transcriptional signatures are promising features to predict a drug response. Because drug resistance/susceptibilities result from the complex associations of genetic and transcriptional activities, we predicted the inter-relationships between genetic and transcriptional signatures. With this concept, captured genetic polymorphisms and transcriptional profiles were prepared in cancer samples. By splitting ninety-nine samples into a trial set (n = 30) and a test set (n = 69), the outperformance of relationship-focused model (0.84 of area under the curve in trial set, P = 2.90 x 10⁻⁴) was presented in the trial set and validated in the test set, respectively. The prediction results of modeling show that considering the relationships between genetic and transcriptional features is an effective approach to determine outcome predictions of drug-treatment.

  8. Setting the vision: applied patient-reported outcomes and smart, connected digital healthcare systems to improve patient-centered outcomes prediction in critical illness.

    Science.gov (United States)

    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.

  9. Sequential organ failure assessment scoring and prediction of patient's outcome in Intensive Care Unit of a tertiary care hospital.

    Science.gov (United States)

    Jain, Aditi; Palta, Sanjeev; Saroa, Richa; Palta, Anshu; Sama, Sonu; Gombar, Satinder

    2016-01-01

    The objective was to determine the accuracy of sequential organ failure assessment (SOFA) score in predicting outcome of patients in Intensive Care Unit (ICU). Forty-four consecutive patients between 15 and 80 years admitted to ICU over 8 weeks period were studied prospectively. Three patients were excluded. SOFA score was determined 24 h postadmission to ICU and subsequently every 48 h for the first 10 days. Patients were followed till discharge/death/transfer from the ICU. Initial SOFA score, highest and mean SOFA scores were calculated and correlated with mortality and duration of stay in ICU. The mortality rate was 39% and the mean duration of stay in the ICU was 9 days. The maximum score in survivors (3.92 ± 2.17) was significantly lower than nonsurvivors (8.9 ± 3.45). The initial SOFA score had a strong statistical correlation with mortality. Cardiovascular score on day 1 and 3, respiratory score on day 7, and coagulation profile on day 3 correlated significantly with the outcome. Duration of the stay did not correlate with the survival (P = 0.461). SOFA score is a simple, but effective prognostic indicator and evaluator for patient progress in ICU. Day 1 SOFA can triage the patients into risk categories. For further management, mean and maximum score help determine the severity of illness and can act as a guide for the intensity of therapy required for each patient.

  10. The ratio of the neutrophil leucocytes to the lymphocytes predicts the outcome after cardiac resynchronization therapy.

    Science.gov (United States)

    Boros, András Mihály; Széplaki, Gábor; Perge, Péter; Jenei, Zsigmond; Bagyura, Zsolt; Zima, Endre; Molnár, Levente; Apor, Astrid; Becker, Dávid; Gellér, László; Prohászka, Zoltán; Merkely, Béla

    2016-05-01

    The low lymphocyte counts and high neutrophil leucocyte fractions have been associated with poor prognosis in chronic heart failure. We hypothesized that the baseline ratio of the neutrophil leucocytes to the lymphocytes (NL ratio) would predict the outcome of chronic heart failure patients undergoing cardiac resynchronization therapy (CRT). The qualitative blood counts and the serum levels of N-terminal of the prohormone brain natriuretic peptide (NT-proBNP) of 122 chronic heart failure patients and 122 healthy controls were analysed prospectively in this observational study. The 2-year mortality was considered as primary endpoint and the 6-month reverse remodelling (≥15% decrease in the end-systolic volume) as secondary endpoint. Multivariable regression analyses were applied and net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated. The NL ratio was elevated in chronic heart failure patients when compared with the healthy controls [2.93 (2.12-4.05) vs. 2.21 (1.64-2.81), P chronic heart failure and predicts outcome after CRT. According to the reclassification analysis, 4% of the patients would have been better categorized in the prediction models by combining the NT-proBNP with the NL ratio. Thus, a single blood count measurement could facilitate the optimal patient selection for the CRT. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Cardiology.

  11. Therapeutic relationships: their specificity in predicting outcomes for people with psychosis using clinical and vocational services.

    Science.gov (United States)

    Catty, Jocelyn; Koletsi, Marsha; White, Sarah; Becker, Thomas; Fioritti, Angelo; Kalkan, Rana; Lauber, Christoph; Lissouba, Pascale; Rössler, Wulf; Tomov, Toma; van Busschbach, Jooske T; Wiersma, Durk; Burns, Tom

    2010-12-01

    To determine the distinctions between the client-keyworker relationship and the client-vocational worker relationship by assessing their impact on clinical outcomes and exploring the associations between the two. As part of an international randomised controlled trial of supported employment (n = 312), client-keyworker relationship and client-vocational worker relationship were each tested against clinical and social functioning 6 months later. Associations between the two relationships over time were explored. Client-keyworker relationship predicted quality of life, while client-vocational worker relationship, as rated by the client, did not predict any clinical or social functioning outcomes. Vocational worker-rated relationship predicted reduced depression. The client-keyworker and client-vocational worker relationships were correlated, but this did not change over time. The impact of the client-vocational worker is likely to be on the shared task of finding employment, rather than on clinical and social functioning. Good client-vocational worker relationships do not detract from client-keyworker relationships.

  12. Serum YKL-40 independently predicts outcome after transcatheter arterial chemoembolization of hepatocellular carcinoma.

    Directory of Open Access Journals (Sweden)

    Cheng-Bao Zhu

    Full Text Available Transcatheter arterial chemoembolization (TACE is the most widely used treatment option for unresectable hepatocellular carcinoma (HCC. Elevated serum YKL-40 level has been shown to predict poor prognosis in HCC patients undergoing resection. This study was designed to validate the prognostic significance of serum YKL-40 in patients with HCC undergoing TACE treatment.Serum YKL-40 level was determined by enzyme-linked immunosorbent assay. Overall survival (OS was evaluated with the Kaplan-Meier method and compared by the log-rank test. Multivariate study with Cox proportional hazard model was used to evaluate independent prognostic variables of OS.The median pretreatment serum YKL-40 in HCC patients with was significantly higher than that in healthy controls (P<0.001. The YKL-40 could predict survival precisely either in a dichotomized or continuous fashion (P<0.001 and P = 0.001, respectively. Multivariate Cox regression analysis indicated that serum YKL-40 was an independent prognostic factor for OS in HCC patients (P = 0.001. In further stratified analyses, YKL-40 could discriminate the outcomes of patients with low and high alpha-fetoprotein (AFP level (P = 0.006 and 0.016, respectively. Furthermore, the combination of serum YKL-40 and AFP had more capacity to predict patients' outcomes.Serum YKL-40 was demonstrated to be an independent prognostic biomarker in HCC patients treated with TACE. Our results need confirmation in an independent study.

  13. Predicting group cognitive-behavioral therapy outcome of binge eating disorder using empirical classification.

    Science.gov (United States)

    Peterson, Carol B; Crosby, Ross D; Wonderlich, Stephen A; Mitchell, James E; Crow, Scott J; Engel, Scott

    2013-09-01

    The purpose of this study was to use empirical classification based on Latent Profile Analysis to identify subgroups of binge eating disorder (BED) and to evaluate the extent to which these subgroups were predictive of treatment outcome in group cognitive-behavioral therapy (CBT). The Eating Disorder Examination (EDE), Structured Clinical Interview for DSM-IV, and Inventory of Depressive Symptomatology-Self-Report were administered to 259 participants at baseline in a 15-session CBT trial (190 of whom received active treatment). The best fitting model included three profiles: dietary restraint only (DRO; n = 96; 51%); low dietary restraint (LDR; n = 52; 27%); and dietary restraint plus psychopathology (DRP; n = 42; 22%). Regression analyses revealed that after controlling for baseline score and treatment condition, EDE Global scores were lower for the DRO compared to the LDR profile at one year follow-up (p = .047). Class assignment was not predictive of EDE binge eating frequency or abstinence at end of treatment or follow-up. These results suggest that meaningful empirical classes based on eating disorder symptoms, psychopathology, dietary restraint, and BMI can be identified in BED and that these classes may be useful in predicting long-term group CBT outcome. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Abnormal uterine artery Doppler velocimetry predicts adverse outcomes in patients with abnormal analytes.

    Science.gov (United States)

    Roeder, Hilary A; Dejbakhsh, Sheila Z; Parast, Mana M; Laurent, Louise C; Woelkers, Douglas A

    2014-10-01

    Our aim was to determine if uterine artery (UtA) Doppler studies would risk-stratify women with abnormal serum analytes on prenatal genetic screening into those at baseline and increased risk for preeclampsia and small-for-gestational age (SGA). This retrospective cohort study examined outcomes of patients with ⩾one abnormal analyte (PAPP-A3.0, AFP>2.5, inhibin>2.0, or unconjugated estriolUtA pulsatility index (PI). Preeclampsia, preterm preeclampsia, SGA (birthweight (BW) one abnormal analyte, UtA Doppler screening, and delivery outcomes. Twenty-four (18%) had an elevated UtA PI (PI>1.6); preeclampsia occurred in 16 (12%) and 26 (20%) delivered a SGA neonate. Abnormal UtA Doppler PI increased the likelihood of a composite outcome of preeclampsia or SGA from 27% to 71% (LR 6.48 (2.93, 14.30)); a negative UtA Doppler PI reduced the likelihood to 18% (LR 0.57 (0.42, 0.78)). Abnormal UtA Doppler PI increased the likelihood of a more severe composite outcome of preterm preeclampsia or IUGR from 11% to 39% (LR 5.49 (3.03, 9.97)); a negative UtA Doppler study reduced the likelihood to 4% (LR 0.35 (0.16, 0.80)). In patients with abnormal serum analytes, abnormal UtA Doppler PI is significantly associated with preeclampsia or SGA and improves the prediction of these adverse outcomes by 9-15-fold. Providers can incorporate UtA Doppler PI into an abbreviated surveillance regimen; they can be reassured that a normal study markedly decreases the risk of a severe early adverse outcome. Copyright © 2014 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

  15. Clinical elements that predict outcome after traumatic brain injury: a prospective multicenter recursive partitioning (decision-tree) analysis.

    Science.gov (United States)

    Brown, Allen W; Malec, James F; McClelland, Robyn L; Diehl, Nancy N; Englander, Jeffrey; Cifu, David X

    2005-10-01

    Traumatic brain injury (TBI) often presents clinicians with a complex combination of clinical elements that can confound treatment and make outcome prediction challenging. Predictive models have commonly used acute physiological variables and gross clinical measures to predict mortality and basic outcome endpoints. The primary goal of this study was to consider all clinical elements available concerning a survivor of TBI admitted for inpatient rehabilitation, and identify those factors that predict disability, need for supervision, and productive activity one year after injury. The Traumatic Brain Injury Model Systems (TBIMS) database was used for decision tree analysis using recursive partitioning (n = 3463). Outcome measures included the Functional Independence Measure(), the Disability Rating Scale, the Supervision Rating Scale, and a measure of productive activity. Predictor variables included all physical examination elements, measures of injury severity (initial Glasgow Coma Scale score, duration of post-traumatic amnesia [PTA], length of coma, CT scan pathology), gender, age, and years of education. The duration of PTA, age, and most elements of the physical examination were predictive of early disability. The duration of PTA alone was selected to predict late disability and independent living. The duration of PTA, age, sitting balance, and limb strength were selected to predict productive activity at 1 year. The duration of PTA was the best predictor of outcome selected in this model for all endpoints and elements of the physical examination provided additional predictive value. Valid and reliable measures of PTA and physical impairment after TBI are important for accurate outcome prediction.

  16. Thrombus length discrepancy on dual-phase CT can predict clinical outcome in acute ischemic stroke

    International Nuclear Information System (INIS)

    Park, Mina; Kim, Kyung-eun; Lee, Seung-Koo; Shin, Na-Young; Lim, Soo Mee; Song, Dongbeom; Heo, Ji Hoe; Kim, Jin Woo; Oh, Se Won

    2016-01-01

    The thrombus length may be overestimated on early arterial computed tomography angiography (CTA) depending on the collateral status. We evaluated the value of a grading system based on the thrombus length discrepancy on dual-phase CT in outcome prediction. Forty-eight acute ischemic stroke patients with M1 occlusion were included. Dual-phase CT protocol encompassed non-contrast enhanced CT, CTA with a bolus tracking technique, and delayed contrast enhanced CT (CECT) performed 40s after contrast injection. The thrombus length discrepancy between CTA and CECT was graded by using a three-point scale: G0 = no difference; G1 = no difference in thrombus length, but in attenuation distal to thrombus; G2 = difference in thrombus length. Univariate and multivariate analyses were performed to define independent predictors of poor clinical outcome at 3 months. The thrombus discrepancy grade showed significant linear relationships with both the collateral status (P = 0.008) and the presence of antegrade flow on DSA (P = 0.010) with good interobserver agreement (κ = 0.868). In a multivariate model, the presence of thrombus length discrepancy (G2) was an independent predictor of poor clinical outcome [odds ratio = 11.474 (1.350-97.547); P =0.025]. The presence of thrombus length discrepancy on dual-phase CT may be a useful predictor of unfavourable clinical outcome in acute M1 occlusion patients. (orig.)

  17. Do ictal EEG characteristics predict treatment outcomes in schizophrenic patients undergoing electroconvulsive therapy?

    Science.gov (United States)

    Simsek, Gulnihal Gokce; Zincir, Selma; Gulec, Huseyin; Eksioglu, Sevgin; Semiz, Umit Basar; Kurtulmus, Yasemin Sipka

    2015-08-01

    The aim of this study is to investigate the relationship between features of electroencephalography (EEG), including seizure time, energy threshold level and post-ictal suppression time, and clinical variables, including treatment outcomes and side-effects, among schizophrenia inpatients undergoing electroconvulsive therapy (ECT). This is a naturalistic follow-up study on schizophrenia patients, diagnosed using DSM-IV-TR criteria, treated by a psychosis inpatient service. All participants completed the Brief Psychiatric Rating Scale (BPRS), the Global Assessment of Functioning (GAF) scale, the Frontal Assessment Battery (FAB) and a Data Collection Form. Assessments were made before treatment, during ECT and after treatment. Statistically significant improvements in both clinical and cognitive outcome were noted after ECT in all patients. Predictors of improvement were sought by evaluating electrophysiological variables measured at three time points (after the third, fifth and seventh ECT sessions). Logistic regression analysis showed that clinical outcome/improvement did not differ by seizure duration, threshold energy level or post-ictal suppression time. We found that ictal EEG parameters measured at several ECT sessions did not predict clinical recovery/outcomes. This may be because our centre defensively engages in "very specific patient selection" when ECT is contemplated. ECT does not cause short-term cognitive functional impairment and indeed improves cognition, because symptoms of the schizophrenic episode are alleviated.

  18. Prediction of adverse outcomes of acute coronary syndrome using intelligent fusion of triage information with HUMINT

    Science.gov (United States)

    McCullough, Claire L.; Novobilski, Andrew J.; Fesmire, Francis M.

    2006-04-01

    Faculty from the University of Tennessee at Chattanooga and the University of Tennessee College of Medicine, Chattanooga Unit, have used data mining techniques and neural networks to examine a set of fourteen features, data items, and HUMINT assessments for 2,148 emergency room patients with symptoms possibly indicative of Acute Coronary Syndrome. Specifically, the authors have generated Bayesian networks describing linkages and causality in the data, and have compared them with neural networks. The data includes objective information routinely collected during triage and the physician's initial case assessment, a HUMINT appraisal. Both the neural network and the Bayesian network were used to fuse the disparate types of information with the goal of forecasting thirty-day adverse patient outcome. This paper presents details of the methods of data fusion including both the data mining techniques and the neural network. Results are compared using Receiver Operating Characteristic curves describing the outcomes of both methods, both using only objective features and including the subjective physician's assessment. While preliminary, the results of this continuing study are significant both from the perspective of potential use of the intelligent fusion of biomedical informatics to aid the physician in prescribing treatment necessary to prevent serious adverse outcome from ACS and as a model of fusion of objective data with subjective HUMINT assessment. Possible future work includes extension of successfully demonstrated intelligent fusion methods to other medical applications, and use of decision level fusion to combine results from data mining and neural net approaches for even more accurate outcome prediction.

  19. Negative affect combines with smoking outcome expectancies to predict smoking behavior over time.

    Science.gov (United States)

    Cohen, Lee M; McCarthy, Denis M; Brown, Sandra A; Myers, Mark G

    2002-06-01

    The present study examined whether the tendency to experience negative affective states combines with smoking outcome expectancies to predict smoking behavior over time. Participants were 121 young adults and resource people recruited from 3 alcohol and drug treatment programs and through community advertisements. Each participant completed 3 interviews over a 4-year period. Results indicated that dispositional negative affect and positive smoking expectancies were significantly correlated with smoking behavior both within and across time. Expectations of positive and negative reinforcement partially mediated negative affect's relation with smoking across time. Positive expectancies did not function as a moderator of negative affect's relation with smoking behavior. These results represent an important step in incorporating smoking outcome expectancies into multivariate models of smoking risk.

  20. Predicting IVF Outcome: A Proposed Web-based System Using Artificial Intelligence.

    Science.gov (United States)

    Siristatidis, Charalampos; Vogiatzi, Paraskevi; Pouliakis, Abraham; Trivella, Marialenna; Papantoniou, Nikolaos; Bettocchi, Stefano

    2016-01-01

    To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome. Construction and evaluation of an enhanced web-based system with a novel Artificial Neural Network (ANN) architecture and conformed input and output parameters according to the clinical and bibliographical standards, driven by a complete data set and "trained" by a network expert in an IVF setting. The system is capable to act as a routine information technology platform for the IVF unit and is capable of recalling and evaluating a vast amount of information in a rapid and automated manner to provide an objective indication on the outcome of an artificial reproductive cycle. ANNs are an exceptional candidate in providing the fertility specialist with numerical estimates to promote personalization of healthcare and adaptation of the course of treatment according to the indications. Copyright © 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  1. Automatic delirium prediction system and nursing-sensitive outcomes in the medical intensive care unit.

    Science.gov (United States)

    Cho, Ha-young; Song, Xianghua; Piao, Jinshi; Jin, Yinji; Lee, Sun-Mi

    2015-02-01

    In Korea, delirium risk screening has not been routinely implemented in intensive care units (ICUs). The purpose of this study was to implement an Automatic Prediction of Delirium in Intensive Care Units (APREDEL-ICU) system to investigate its impact on nursing-sensitive outcomes and to assess nurse satisfaction with the system. A pre-post research design was used. A total of 145 patients were involved prior to the system implementation and 172 were involved after implementation. Forty medical ICU nurses evaluated the system. The APREDEL-ICU system did not result in a reduction in the incidence of delirium. However, the nurses reported that their knowledge regarding delirium care increased after the system was introduced. The proposed system was successfully implemented without increasing the burden of nurses in their assessment of delirium risk. Long-term use of APREDEL-ICU could enhance preventive care and consequently result in positive patient outcomes. © The Author(s) 2014.

  2. Cognitive dysfunction at baseline predicts symptomatic 1-year outcome in first-episode schizophrenics.

    Science.gov (United States)

    Moritz, S; Krausz, M; Gottwalz, E; Lambert, M; Perro, C; Ganzer, S; Naber, D

    2000-01-01

    The present study addresses the consequences of cognitive disturbances on symptomatic outcome. Fifty-three first-episode schizophrenics were reassessed (n = 32) 1 year after admission. Simple regression analyses revealed that several self-perceived cognitive deficits at baseline as measured with the Frankfurt Complaint Questionnaire significantly predicted increased Brief Psychiatric Rating Scale global scores at follow-up (p = 0.05 to p = 0.005). A stepwise regression analysis proved memory dysfunction to be the strongest predictor of symptomatic worsening (p = 0.005). It is suggested that the exploration and treatment of neuropsychological deficits in schizophrenia is of great clinical importance with regard to its impact on both functional and symptomatic outcome in schizophrenia. Copyright 2000 S. Karger AG, Basel

  3. Fetuin A/nutritional status predicts cardiovascular outcomes and survival in hemodialysis patients.

    Science.gov (United States)

    Chen, Hung-Yuan; Chiu, Yen-Ling; Hsu, Shih-Ping; Pai, Mei-Fen; Yang, Ju-Yeh; Peng, Yu-Sen

    2014-01-01

    Fetuin A - a predictor of cardiovascular (CV) outcomes in dialysis patients - is correlated with over-nutrition in the general population. Whether fetuin A and nutritional status interact with each other to alter CV outcomes and survival in hemodialysis (HD) patients remains unknown. We performed a prospective study on 388 prevalent HD patients. We used the geriatric nutritional risk index (GNRI) for the evaluation of nutritional status. Study outcomes included the occurrence of CV event, CV death, and all-cause mortality during follow-up; interactions between parameters for predicting outcomes were assessed by the interaction terms in a Cox regression model. Overall, 131 patients experienced CV events and 92 patients died, with 51 CV deaths. HD patients with higher fetuin A levels had lower numbers of CV events (adjusted hazard ratio [HR], 0.9; 0.81-0.99) and all-cause mortality (adjusted HR, 0.97; 0.91-0.99). However, patients with higher GNRI had lower all-cause mortality (adjusted HR, 0.79; 0.51-0.98, for every 10-unit increase). Fetuin A levels and GNRI showed a significant interaction in the prediction of CV events (adjusted HR, 1.01; 1.008-1.02) but not for all-cause or CV mortality. In patients with poor nutritional status, higher fetuin A levels were associated with fewer CV events; however, in contrast, in subjects with better nutritional status, higher fetuin A levels appeared to lead to a higher number of CV events. Fetuin A showed a remarkable interaction with nutritional status in evaluating the risks of CV morbidities in prevalent HD patients. © 2014 S. Karger AG, Basel.

  4. Do Flow and Pulsatility Index within the Accepted Ranges Predict Long-Term Outcomes after Coronary Artery Bypass Grafting?

    Science.gov (United States)

    Leon, Maximiliano De; Stanham, Roberto; Soca, Gerardo; Dayan, Victor

    2017-04-12

    Background  Transit-time flow measurement (TTFM) is the gold standard for intraoperative detection of graft failure. Several reports show that TTFM and distal coronary bed quality (DCBQ) may also be useful for midterm detection of graft failure. Nonetheless, there are no data regarding their predictive role on long-term outcomes. Methods  Patients with three-vessel disease who underwent isolated coronary artery bypass grafting (CABG) in 2006 and received at least one graft to the left anterior descending artery (LAD) or to the first obtuse marginal (OM1) or posterior descending artery (PDA) were included. Baseline characteristics, mean graft flow, pulsatility index, and subjective impression of DCBQ for each coronary territory were collected. Long-term cardiovascular (CV) and overall survival, operative mortality, and new percutaneous coronary intervention (PCI) were evaluated. Results  A total of 177 patients underwent isolated CABG. The OM1 was grafted in 131 patients, the LAD in 169 patients, and the PDA in 100 patients. Neither DQCB nor TTFM were predictors for new PCI. Independent predictors for overall survival were age, previous acute myocardial infarction (AMI), and DQCB of OM1 (odds ratio [OR] = 2.97; 95% confidence interval [CI]: 1.15-7.71). Age, previous AMI, and DCBQ of OM1 (OR = 2.5; 95% CI: 1.39-4.81) were independent predictors for CV survival. Conclusions  TTFM on patients with functioning grafts does not predict long-term survival or performance of new PCI. Subjective evaluation of distal coronary bed, especially of the OM1, has a strong impact on long-term outcomes. Georg Thieme Verlag KG Stuttgart · New York.

  5. Prediction of extubation outcome in preterm infants by composite extubation indices.

    Science.gov (United States)

    Dimitriou, Gabriel; Fouzas, Sotirios; Vervenioti, Aggeliki; Tzifas, Sotirios; Mantagos, Stefanos

    2011-11-01

    To determine whether composite extubation indices can predict extubation outcome in preterm infants. Prospective observational study. Level III neonatal intensive care unit. Fifty-six preterm infants cared for in the neonatal intensive care unit of a tertiary teaching hospital during 2007 and 2008. None. The study consisted of two parts. In the first part, different extubation indices were evaluated in a group of 28 neonates (derivation group). These indices included the diaphragmatic pressure-time index, the respiratory muscle pressure-time index, the maximal transdiaphragmatic pressure, the maximal inspiratory pressure, the airway pressure generated 100 milliseconds after an occlusion/maximal transdiaphragmatic pressure ratio, the airway pressure generated 100 milliseconds after an occlusion/maximal inspiratory pressure ratio, the tidal volume, and the respiratory rate to tidal volume ratio. After exploratory analysis, the best performing indices and the optimal threshold values to predict extubation outcome were selected. In the second part of the study, these indices were validated at the predetermined threshold values in an additional group of 28 preterm neonates (validation group). Four infants (14.3%) in the derivation group and four in the validation group (14.3%) failed extubation. Receiver operator characteristic curve analysis revealed that a diaphragmatic pressure-time index of ≤0.12, a respiratory muscle pressure-time index ≤0.10, a airway pressure generated 100 milliseconds after an occlusion/maximal transdiaphragmatic pressure of ≤0.14, and a airway pressure generated 100 milliseconds after an occlusion/maximal inspiratory pressure of ≤0.09 were the most accurate predictors of extubation outcome in the derivation group. In the validation group, a diaphragmatic pressure-time index of ≤0.12 and a respiratory muscle pressure-time index of ≤0.10 both had zero false-positive results, predicting with accuracy successful extubation. Composite

  6. A simplified acute physiology score in the prediction of acute aluminum phosphide poisoning outcome

    OpenAIRE

    Shahin Shadnia; Omid Mehrpour; Kambiz Soltaninejad

    2010-01-01

    Background : Aluminum phosphide (AlP) is used as a fumigant. It produces phosphine gas, which is a mitochondrial poison. Unfortunately, there is no known antidote for AlP intoxication, and also, there are few data about its prognostic factors. AIMS: The aim of this study was to determine the impact of the Simplified Acute Physiology Score II (SAPS II ) in the prediction of outcome in patients with acute AlP poisoning requiring admission to the Intensive Care Unit (ICU). Materials and Methods ...

  7. Use of brain lactate levels to predict outcome after perinatal asphyxia

    DEFF Research Database (Denmark)

    Leth, H; Toft, P.B.; Peitersen, Birgit

    1996-01-01

    Perinatal asphyxia is an important cause of neurological disability, but early prediction of outcome can be difficult. We performed proton magnetic resonance spectroscopy (MRS) and global cerebral blood flow measurements by xenon-133 clearance in 16 infants with evidence of perinatal asphyxia....... Cerebral blood flow was determined daily in the first 3 days after birth in seven cases. Proton MRS was performed in 11 infants within the first week (mean 3.7 days), the rest within the first month (mean 22.2 days), and all had a scan around 3 months of age. Four infants died neonatally, three showed...

  8. Treatment of 817 patients with spontaneous supratentorial intracerebral hemorrhage: characteristics, predictive factors and outcome

    Directory of Open Access Journals (Sweden)

    Homajoun Maslehaty

    2012-05-01

    Full Text Available The aim of this study was to present the data of a large cohort of patients with spontaneous supratentorial intracerebral hemorrhage (ICH, who were treated in our department and give a current overview considering special clinical characteristics, performed therapy and different predictive factors for morbidity and mortality. We reviewed the data of all patients with spontaneous ICH, who were treated in our department in a time span of 11 years through an analysis of our prospective database. Patients with spontaneous supratentorial ICH were included in the study. Patients with hemorrhage associated to vascular malformation or to cerebral ischemic stroke were excluded. The clinical performance at time of admission and discharge were scored using the Glasgow coma scale (GCS and the Glasgow outcome scale (GOS respectively. The patients’ cohort was divided into surgically and conservatively treated groups. Statistical analysis [Analysis of Variance (ANOVA and ?²-test] was done for various parameters to analyze their impact on morbidity and mortality. In total, we analyzed the data of 817 patients (364 female and 453 male. Two hundred and sixty-nine patients (32% were treated conservatively and 556 patients (68% underwent surgical procedures, i.e. cerebrospinal fluid drainage in 110 (19.8%, craniotomy in 338 (60.7% and application of both methods in 108 patients (19.4%. Total mortality rate was estimated with 23.5%. GCS<8, age over 70 years, intraventricular and basal ganglia hemorrhage, coumadin medication, combination of co-morbidities, hypertensive hemorrhage and postoperative re-bleeding were statistically significant risk factors for worse outcome (GOS 1 and 2 in the operated group. Similar to the observations of the operated group, GCS<8, age over 70 years and coumadin medication were statistically significant for worse outcome in the conservative group. In contrast, lobar plus basal ganglia ICH and multi-lobar hemorrhages were the most

  9. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study.

    Science.gov (United States)

    Ho, Samuel M Y; Ho, Judy W C; Bonanno, George A; Chu, Annie T W; Chan, Emily M S

    2010-06-11

    Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline) and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 +/- 9.2 years) from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%), recovery (0% and 4.3%), delayed dysfunction (13% and 15.9%) and resilience (76.8% and 66.7%). Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression) were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant predictor of a resilience outcome trajectory for depression

  10. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

    Directory of Open Access Journals (Sweden)

    Chu Annie TW

    2010-06-01

    Full Text Available Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Results - Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 ± 9.2 years from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%, recovery (0% and 4.3%, delayed dysfunction (13% and 15.9% and resilience (76.8% and 66.7%. Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant

  11. Prediction of outcomes by early treatment responses in childhood T-cell acute lymphoblastic leukemia: a retrospective study in China.

    Science.gov (United States)

    Wei, Wei; Chen, Xiaojuan; Zou, Yao; Chang, Lixian; An, Wenbin; Wan, Yang; Liu, Tianfeng; Yang, Wenyu; Chen, Yumei; Guo, Ye; Zhu, Xiaofan

    2015-07-15

    Early treatment responses are important prognostic factors in childhood T-cell acute lymphoblastic leukemia (T-ALL) patients. The predictive values of early treatment responses in Chinese childhood T-ALL patients were still unknown. From January 2003 to December 2012, 74 consecutive patients aged ≤ 15 years with newly diagnosed T-ALL were treated with BCH-2003 protocol or CCLG-2008 protocol in the Department of Pediatric, Institute of Hematology and Blood Diseases Hospital in China. Predictive values of early treatment responses, including prednisone response, bone marrow morphology at day 15 and day 33 during induction chemotherapy, and minimal residual disease (MRD) monitored by flow cytometry after induction therapy (time point 1, TP1) and before consolidation therapy (time point 2, TP2), were analyzed. The 5-year event free survival (EFS) and overall survival (OS) rates for these patients were 62.5% (SE, 6.4) and 62.7% (SE, 6.6), respectively. Prednisone poor responder was strongly associated with increased chance of induction failure (14.8%) and decreased survival rate (5 year EFS rate, 51.1 % (SE, 10.5)). Patients with ≥ 25% blast cells in bone marrow at day 15 were more likely to have an inferior outcome. 93.2% of the T-ALL patients achieved complete remission at day 33 while patients with resistant disease all died of disease progression. MRD ≥ 10(-2) at TP1 or MRD ≥ 10(-3) at TP2 was significantly related to dismal prognosis. Risk groups classified by MRD at two time points could stratify patients into different groups: 29.0% of the patients were MRD standard risk (MRD time points) with 3-year EFS rate of 100%, 29.0% were MRD high risk (MRD ≥ 10(-2) at TP1 or MRD ≥ 10(-2) at TP2) with 3-year EFS rate of 55.6% (SE, 16.6) , and the rest of patients were defined as MRD intermediate risk with 3-year EFS rate of 85.7% (SE, 13.2). Our study demonstrated that MRD was the most powerful predictor of treatment outcome in childhood T-ALL patients and

  12. A 14-year retrospective maternal report of alcohol consumption in pregnancy predicts pregnancy and teen outcomes.

    Science.gov (United States)

    Hannigan, John H; Chiodo, Lisa M; Sokol, Robert J; Janisse, James; Ager, Joel W; Greenwald, Mark K; Delaney-Black, Virginia

    2010-01-01

    Detecting patterns of maternal drinking that place fetuses at risk for fetal alcohol spectrum disorders (FASDs) is critical to diagnosis, treatment, and prevention but is challenging because information on antenatal drinking collected during pregnancy is often insufficient or lacking. Although retrospective assessments have been considered less favored by many researchers due to presumed poor reliability, this perception may be inaccurate because of reduced maternal denial and/or distortion. The present study hypothesized that fetal alcohol exposure, as assessed retrospectively during child adolescence, would be related significantly to prior measures of maternal drinking and would predict alcohol-related behavioral problems in teens better than antenatal measures of maternal alcohol consumption. Drinking was assessed during pregnancy, and retrospectively about the same pregnancy, at a 14-year follow-up in 288 African-American women using well-validated semistructured interviews. Regression analysis examined the predictive validity of both drinking assessments on pregnancy outcomes and on teacher-reported teen behavior outcomes. Retrospective maternal self-reported drinking assessed 14 years postpartum was significantly higher than antenatal reports of consumption. Retrospective report identified 10.8 times more women as risk drinkers (≥ one drink per day) than the antenatal report. Antenatal and retrospective reports were moderately correlated and both were correlated with the Michigan Alcoholism Screening Test. Self-reported alcohol consumption during pregnancy based on retrospective report identified significantly more teens exposed prenatally to at-risk alcohol levels than antenatal, in-pregnancy reports. Retrospective report predicted more teen behavior problems (e.g., attention problems and externalizing behaviors) than the antenatal report. Antenatal report predicted younger gestational age at birth and retrospective report predicted smaller birth size

  13. Predicting Outcome in Patients with Rhabdomyosarcoma: Role of [18F]Fluorodeoxyglucose Positron Emission Tomography

    International Nuclear Information System (INIS)

    Casey, Dana L.; Wexler, Leonard H.; Fox, Josef J.; Dharmarajan, Kavita V.; Schoder, Heiko; Price, Alison N.; Wolden, Suzanne L.

    2014-01-01

    Purpose: To evaluate whether [ 18 F]fluorodeoxyglucose positron emission tomography (FDG-PET) response of the primary tumor after induction chemotherapy predicts outcomes in rhabdomyosarcoma (RMS). Methods and Materials: After excluding those with initial tumor resection, 107 patients who underwent FDG-PET after induction chemotherapy at Memorial Sloan Kettering Cancer Center from 2002 to 2013 were reviewed. Local control (LC), progression-free survival (PFS), and overall survival (OS) were calculated according to FDG-PET response and maximum standardized uptake value (SUV) at baseline (PET1/SUV1), after induction chemotherapy (PET2/SUV2), and after local therapy (PET3/SUV3). Receiver operator characteristic curves were used to determine the optimal cutoff for dichotomization of SUV1 and SUV2 values. Results: The SUV1 (<9.5 vs ≥9.5) was predictive of PFS (P=.02) and OS (P=.02), but not LC. After 12 weeks (median) of induction chemotherapy, 45 patients had negative PET2 scans and 62 had positive scans: 3-year PFS was 72% versus 44%, respectively (P=.01). The SUV2 (<1.5 vs ≥1.5) was similarly predictive of PFS (P=.005) and was associated with LC (P=.02) and OS (P=.03). A positive PET3 scan was predictive of worse PFS (P=.0009), LC (P=.05), and OS (P=.03). Conclusions: [ 18 F]fluorodeoxyglucose positron emission tomography is an early indicator of outcomes in patients with RMS. Future prospective trials may incorporate FDG-PET response data for risk-adapted therapy and early assessment of new treatment regimens

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

    Science.gov (United States)

    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.

  15. Predictions for Boson-Jet Observables and Fragmentation Function Ratios from a Hybrid Strong/Weak Coupling Model for Jet Quenching

    CERN Document Server

    Casalderrey-Solana, Jorge; Milhano, José Guilherme; Pablos, Daniel; Rajagopal, Krishna

    2016-01-01

    We have previously introduced a hybrid strong/weak coupling model for jet quenching in heavy ion collisions that describes the production and fragmentation of jets at weak coupling, using PYTHIA, and describes the rate at which each parton in the jet shower loses energy as it propagates through the strongly coupled plasma, dE/dx, using an expression computed holographically at strong coupling. The model has a single free parameter that we fit to a single experimental measurement. We then confront our model with experimental data on many other jet observables, focusing here on boson-jet observables, finding that it provides a good description of present jet data. Next, we provide the predictions of our hybrid model for many measurements to come, including those for inclusive jet, dijet, photon-jet and Z-jet observables in heavy ion collisions with energy $\\sqrt{s}=5.02$ ATeV coming soon at the LHC. As the statistical uncertainties on near-future measurements of photon-jet observables are expected to be much sm...

  16. Molecular similarity-based predictions of the Tox21 screening outcome

    Directory of Open Access Journals (Sweden)

    Malgorzata Natalia Drwal

    2015-07-01

    Full Text Available To assess the toxicity of new chemicals and drugs, regulatory agencies require in vivo testing for many toxic endpoints, resulting in millions of animal experiments conducted each year. However, following the Replace, Reduce, Refine (3R principle, the development and optimization of alternative methods, in particular in silico methods, has been put into focus in the recent years. It is generally acknowledged that the more complex a toxic endpoint, the more difficult it is to model. Therefore, computational toxicology is shifting from modelling general and complex endpoints to the investigation and modelling of pathways of toxicity and the underlying molecular effects.The U.S. Toxicology in the 21st Century (Tox21 initiative has screened a large library of compounds, including approximately 10K environmental chemicals and drugs, for different mechanisms responsible for eliciting toxic effects, and made the results publicly available. Through the Tox21 Data Challenge, the consortium has established a platform for computational toxicologists to develop and validate their predictive models.Here, we present a fast and successful method for the prediction of different outcomes of the nuclear receptor and stress response pathway screening from the Tox21 Data Challenge 2014. The method is based on the combination of molecular similarity calculations and a naïve Bayes machine learning algorithm and has been implemented as a KNIME pipeline. Molecules are represented as binary vectors consisting of a concatenation of common two-dimensional molecular fingerprint types with topological compound properties. The prediction method has been optimized individually for each modelled target and evaluated in a cross-validation as well as with the independent Tox21 validation set. Our results show that the method can achieve good prediction accuracies and rank among the top algorithms submitted to the prediction challenge, indicating its broad applicability in

  17. Fuzzy logic-based prognostic score for outcome prediction in esophageal cancer.

    Science.gov (United States)

    Wang, Chang-Yu; Lee, Tsair-Fwu; Fang, Chun-Hsiung; Chou, Jyh-Horng

    2012-11-01

    Given the poor prognosis of esophageal cancer and the invasiveness of combined modality treatment, improved prognostic scoring systems are needed. We developed a fuzzy logic-based system to improve the predictive performance of a risk score based on the serum concentrations of C-reactive protein (CRP) and albumin in a cohort of 271 patients with esophageal cancer before radiotherapy. Univariate and multivariate survival analyses were employed to validate the independent prognostic value of the fuzzy risk score. To further compare the predictive performance of the fuzzy risk score with other prognostic scoring systems, time-dependent receiver operating characteristic curve (ROC) analysis was used. Application of fuzzy logic to the serum values of CRP and albumin increased predictive performance for 1-year overall survival (AUC=0.773) compared with that of a single marker (AUC=0.743 and 0.700 for CRP and albumin, respectively), where the AUC denotes the area under curve. This fuzzy logic-based approach also performed consistently better than the Glasgow Prognostic Score (GPS) (AUC=0.745). Thus, application of fuzzy logic to the analysis of serum markers can more accurately predict the outcome for patients with esophageal cancer.

  18. Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Xiaoli Liu

    2018-01-01

    Full Text Available Alzheimer’s disease (AD has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer’s disease. Recently, the multitask learning (MTL methods with sparsity-inducing norm (e.g., l2,1-norm have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures. However, these previous works formulate the prediction tasks as a linear regression problem. The major limitation is that they assumed a linear relationship between the MRI features and the cognitive outcomes. Some multikernel-based MTL methods have been proposed and shown better generalization ability due to the nonlinear advantage. We quantify the power of existing linear and nonlinear MTL methods by evaluating their performance on cognitive score prediction of Alzheimer’s disease. Moreover, we extend the traditional l2,1-norm to a more general lql1-norm (q≥1. Experiments on the Alzheimer’s Disease Neuroimaging Initiative database showed that the nonlinear l2,1lq-MKMTL method not only achieved better prediction performance than the state-of-the-art competitive methods but also effectively fused the multimodality data.

  19. Prediction of medication non-adherence and associated outcomes in pediatric kidney transplant recipients.

    Science.gov (United States)

    Connelly, James; Pilch, N; Oliver, M; Jordan, C; Fleming, J; Meadows, H; Baliga, P; Nadig, S; Twombley, K; Shatat, I; Taber, D

    2015-08-01

    Studies have continued to evaluate risk factors associated with post-transplant non-adherence in pediatric patients. However, many of these studies fail to evaluate how risk factors can be utilized to predict MNA. The aims of this study were to (i) determine salient risk factors associated with MNA to develop an adequate predictive risk model and (ii) assess transplant outcomes based on the presence of MNA in a large, diverse cohort of pediatric KTX recipients. One hundred and seventy-five solitary pediatric KTX recipients transplanted from 1999 to 2013 were included. AA, males, older patients, those who lived in urban environments, had legal issues, and lived shorter distances from the transplant center were more likely to have MNA. Using logistic regression, a parsimonious model applying nine risk factors together was developed for predicting MNA, demonstrating a PPV of 69% and a NPV of 81%. Patients with MNA had more than twice the risk of biopsy proven acute rejection, 1.6 times the risk of hospitalization, and 1.8 times the risk of graft loss. Utilization of a predictive model to determine risk of MNA after pediatric KTX may offer clinicians the ability to efficiently and effectively monitor MNA following transplant. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. High aspartate aminotransferase level predicts poor neurodevelopmental outcome in infants with meconium aspiration syndrome.

    Science.gov (United States)

    Chen, I-Lun; Ou-Yang, Mei-Chen; Chen, Feng-Shun; Chung, Mei-Yung; Chen, Chih-Cheng; Huang, Hsin-Chun

    2014-11-01

    The aim of our study is to clarify the perinatal predictive factors of meconium aspiration syndrome (MAS) with neurodevelopmental delay (ND) in infants. In this retrospective study, data were collected from the infants born between 1990 and 2008. They all had primary diagnosis of MAS. Multivariable analyzed perinatal predictive factors of MAS with ND. The developmental status of these infants was followed at least 2 years with the Wechsler Intelligence Scale for Children. A total of 114 surviving babies met the criteria of MAS. Six babies were defined as ND group. Lower 5-minute Apgar score and diastolic blood pressure were significantly related to the ND group. Elevated asparatate aminotransferase (AST), nucleated red blood cells, and white blood cells at the time of admission were significantly high in ND group. Furthermore, AST had area under the receiver operating characteristic curve of 0.879, (95% confidence interval: 0.801, 0.934), p < 0.0001. At 96 mg/dL, it had 83.33% sensitivity, 80.81% specificity, and negative predictive value of 98.8. Multivariable logistic regression analysis revealed AST was the only significant predictive factor for MAS with ND. Early intervention should be recommended in infants having MAS with high AST level at birth for improving their neurodevelopmental outcomes. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  1. Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

    Science.gov (United States)

    Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

    2014-12-01

    This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

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

    International Nuclear Information System (INIS)

    Bilbao, Cristina; Lara, Pedro Carlos; Ramirez, Raquel; Henriquez-Hernandez, Luis Alberto; Rodriguez, German; Falcon, Orlando; Leon, Laureano; Perucho, Manuel

    2010-01-01

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

  3. Hearing outcomes of vestibular schwannoma patients managed with 'wait and scan': predictive value of hearing level at diagnosis

    DEFF Research Database (Denmark)

    Stangerup, S-E; Tos, M; Thomsen, J

    2010-01-01

    This study aimed to evaluate the predictive value of both hearing level (at various frequencies) and speech discrimination for forecasting hearing outcome after a period of observation, in patients with vestibular schwannoma....

  4. Patient Characteristics Predict Occurrence and Outcome of Complaints Against Physicians: A Study From a Medical Center in Central Taiwan

    Directory of Open Access Journals (Sweden)

    Chun-Ying Wu

    2009-02-01

    Conclusion: Patients with certain characteristics tend to file complaints, receive compensation, or bring a case to court. Understanding of patient characteristics may be useful for predicting occurrence and outcome of complaints against physicians.

  5. Elevated troponin predicts long-term adverse cardiovascular outcomes in hypertensive crisis: a retrospective study.

    Science.gov (United States)

    Pattanshetty, Deepak J; Bhat, Pradeep K; Aneja, Ashish; Pillai, Dilip P

    2012-12-01

    Hypertensive crisis is associated with poor clinical outcomes. Elevated troponin, frequently observed in hypertensive crisis, may be attributed to myocardial supply-demand mismatch or obstructive coronary artery disease (CAD). However, in patients presenting with hypertensive crisis and an elevated troponin, the prevalence of CAD and the long-term adverse cardiovascular outcomes are unknown. We sought to assess the impact of elevated troponin on cardiovascular outcomes and evaluate the role of troponin as a predictor of obstructive CAD in patients with hypertensive crisis. Patients who presented with hypertensive crisis (n = 236) were screened retrospectively. Baseline and follow-up data including the event rates were obtained using electronic patient records. Those without an assay for cardiac Troponin I (cTnI) (n = 65) were excluded. Of the remaining 171 patients, those with elevated cTnI (cTnI ≥ 0.12 ng/ml) (n = 56) were compared with those with normal cTnI (cTnI hypertensive crisis, pulmonary edema, stroke or transient ischemic attack). At 2 years, MACCE occurred in 40 (71.4%) patients with elevated cTnI compared with 44 (38.3%) patients with normal cTnI [hazard ratio: 2.77; 95% confidence interval (CI): 1.79-4.27; P hypertensive crisis, elevated cTnI confers a significantly greater risk of long-term MACCE, and is a strong predictor of obstructive CAD.

  6. Quality of life predicts outcome in a heart failure disease management program.

    LENUS (Irish Health Repository)

    O'Loughlin, Christina

    2012-02-01

    BACKGROUND: Chronic heart failure (HF) is associated with a poor Health Related Quality of Life (HRQoL). HRQoL has been shown to be a predictor of HF outcomes however, variability in the study designs make it difficult to apply these findings to a clinical setting. The aim of this study was to establish if HRQoL is a predictor of long-term mortality and morbidity in HF patients followed-up in a disease management program (DMP) and if a HRQoL instrument could be applied to aid in identifying high-risk patients within a clinical context. METHODS: This is a retrospective analysis of HF patients attending a DMP with 18+\\/-9 months follow-up. Clinical and biochemical parameters were recorded on discharge from index HF admission and HRQoL measures were recorded at 2 weeks post index admission. RESULTS: 225 patients were enrolled into the study (mean age=69+\\/-12 years, male=61%, and 78%=systolic HF). In multivariable analysis, all dimensions of HRQoL (measured by the Minnesota Living with HF Questionnaire) were independent predictors of both mortality and readmissions particularly in patients <80 years. A significant interaction between HRQoL and age (Total((HRQoL))age: p<0.001) indicated that the association of HRQoL with outcomes diminished as age increased. CONCLUSIONS: These data demonstrate that HRQoL is a predictor of outcome in HF patients managed in a DMP. Younger patients (<65 years) with a Total HRQoL score of > or =50 are at high risk of an adverse outcome. In older patients > or =80 years HRQoL is not useful in predicting outcome.

  7. Prediction of Bladder Outcomes after Traumatic Spinal Cord Injury: A Longitudinal Cohort Study.

    Directory of Open Access Journals (Sweden)

    Chiara Pavese

    2016-06-01

    Full Text Available Neurogenic bladder dysfunction represents one of the most common and devastating sequelae of traumatic spinal cord injury (SCI. As early prediction of bladder outcomes is essential to counsel patients and to plan neurourological management, we aimed to develop and validate a model to predict urinary continence and complete bladder emptying 1 y after traumatic SCI.Using multivariate logistic regression analysis from the data of 1,250 patients with traumatic SCI included in the European Multicenter Spinal Cord Injury study, we developed two prediction models of urinary continence and complete bladder emptying 1 y after traumatic SCI and performed an external validation in 111 patients. As predictors, we evaluated age, gender, and all variables of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI and of the Spinal Cord Independence Measure (SCIM. Urinary continence and complete bladder emptying 1 y after SCI were assessed through item 6 of SCIM. The full model relies on lower extremity motor score (LEMS, light-touch sensation in the S3 dermatome of ISNCSI, and SCIM subscale respiration and sphincter management: the area under the receiver operating characteristics curve (aROC was 0.936 (95% confidence interval [CI]: 0.922-0.951. The simplified model is based on LEMS only: the aROC was 0.912 (95% CI: 0.895-0.930. External validation of the full and simplified models confirmed the excellent predictive power: the aROCs were 0.965 (95% CI: 0.934-0.996 and 0.972 (95% CI 0.943-0.999, respectively. This study is limited by the substantial number of patients with a missing 1-y outcome and by differences between derivation and validation cohort.Our study provides two simple and reliable models to predict urinary continence and complete bladder emptying 1 y after traumatic SCI. Early prediction of bladder function might optimize counselling and patient-tailored rehabilitative interventions and improve patient

  8. MAGIC biomarkers predict long term outcomes for steroid-resistant acute GVHD.

    Science.gov (United States)

    Major-Monfried, Hannah; Renteria, Anne S; Pawarode, Attaphol; Reddy, Pavan; Ayuk, Francis; Holler, Ernst; Efebera, Yvonne A; Hogan, William J; Wölfl, Matthias; Qayed, Muna; Hexner, Elizabeth O; Wudhikarn, Kitsada; Ordemann, Rainer; Young, Rachel; Shah, Jay; Hartwell, Matthew J; Chaudhry, Mohammed; Aziz, Mina; Etra, Aaron; Yanik, Gregory A; Kröger, Nicolaus; Weber, Daniela; Chen, Yi-Bin; Nakamura, Ryotaro; Rösler, Wolf; Kitko, Carrie L; Harris, Andrew C; Pulsipher, Michael; Reshef, Ran; Kowalyk, Steven; Morales, George; Torres, Ivan; Özbek, Umut; Ferrara, James L M; Levine, John E

    2018-03-15

    Acute graft versus host disease (GVHD) is treated with systemic corticosteroid immunosuppression. Clinical response after one week of therapy often guides further treatment decisions, but long term outcomes vary widely between centers and more accurate predictive tests are urgently needed. We analyzed clinical data and blood samples taken after one week of systemic treatment for GVHD from 507 patients from 17 centers of the Mount Sinai Acute GVHD International Consortium (MAGIC), dividing them into test (n=236) and two validation cohorts separated in time (n = 142 and 129, respectively). Initial response to systemic steroids correlated with response at four weeks, one-year non-relapse mortality (NRM) and overall survival (OS). A previously validated algorithm of two MAGIC biomarkers (ST2 and REG3α) consistently separated steroid resistant patients into two groups with dramatically different NRM and OS (p<0.001 for all three cohorts). High biomarker probability, resistance to steroids and GVHD severity (Minnesota risk) were all significant predictors of NRM in multivariate analysis. A direct comparison of receiver operating curves showed the area under the curve for biomarker probability (0.82) was significantly greater than that for steroid response (0.68, p=0.004) and for Minnesota risk (0.72, p=0.005). In conclusion, MAGIC biomarker probabilities generated after one week of systemic treatment for GVHD predict long term outcomes in steroid resistant GVHD better than clinical criteria and should prove useful in developing better treatment strategies. Copyright © 2018 American Society of Hematology.

  9. Speech processor data logging helps in predicting early linguistic outcomes in implanted children.

    Science.gov (United States)

    Guerzoni, Letizia; Cuda, Domenico

    2017-10-01

    To analyse the value of listening-data logged in the speech processor on the prediction of the early auditory and linguistic skills in children who received a cochlear implant in their first 2 years of life. Prospective observational non-randomized study. Ten children with profound congenital sensorineural hearing loss were included in the study. The mean age at CI activation was 16.9 months (SD ± 7.2; range 10-24). The auditory skills were evaluated with the Infant Toddler Meaningful Inventory Scale and the Category of Auditory Performance. Lexical level was assessed with the MacArthur-Bates Communicative Development Inventory. The overall data of average daily use and acoustic scene-analyses were extracted from Data Logging system. The effect of the one-year cumulative listening time to speech (in quiet) and speech-in-noise on the auditory and lexical scores was analysed. A significant positive correlation was found between speech in quiet exposure time at low loudness level (80 dB). The Category of Auditory Performance was not related to the logged data. The listening environment can influence the early functional outcomes in younger implanted children. In this perspective, the data logging system is a promising tool in predicting early linguistic and auditory outcomes. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Parent-child math anxiety and math-gender stereotypes predict adolescents' math education outcomes

    Science.gov (United States)

    Casad, Bettina J.; Hale, Patricia; Wachs, Faye L.

    2015-01-01

    Two studies examined social determinants of adolescents' math anxiety including parents' own math anxiety and children's endorsement of math-gender stereotypes. In Study 1, parent-child dyads were surveyed and the interaction between parent and child math anxiety was examined, with an eye to same- and other-gender dyads. Results indicate that parent's math anxiety interacts with daughters' and sons' anxiety to predict math self-efficacy, GPA, behavioral intentions, math attitudes, and math devaluing. Parents with lower math anxiety showed a positive relationship to children's math outcomes when children also had lower anxiety. The strongest relationships were found with same-gender dyads, particularly Mother-Daughter dyads. Study 2 showed that endorsement of math-gender stereotypes predicts math anxiety (and not vice versa) for performance beliefs and outcomes (self-efficacy and GPA). Further, math anxiety fully mediated the relationship between gender stereotypes and math self-efficacy for girls and boys, and for boys with GPA. These findings address gaps in the literature on the role of parents' math anxiety in the effects of children's math anxiety and math anxiety as a mechanism affecting performance. Results have implications for interventions on parents' math anxiety and dispelling gender stereotypes in math classrooms. PMID:26579000

  11. Multiscale modeling and distributed computing to predict cosmesis outcome after a lumpectomy

    Science.gov (United States)

    Garbey, M.; Salmon, R.; Thanoon, D.; Bass, B. L.

    2013-07-01

    Surgery for early stage breast carcinoma is either total mastectomy (complete breast removal) or surgical lumpectomy (only tumor removal). The lumpectomy or partial mastectomy is intended to preserve a breast that satisfies the woman's cosmetic, emotional and physical needs. But in a fairly large number of cases the cosmetic outcome is not satisfactory. Today, predicting that surgery outcome is essentially based on heuristic. Modeling such a complex process must encompass multiple scales, in space from cells to tissue, as well as in time, from minutes for the tissue mechanics to months for healing. The goal of this paper is to present a first step in multiscale modeling of the long time scale prediction of breast shape after tumor resection. This task requires coupling very different mechanical and biological models with very different computing needs. We provide a simple illustration of the application of heterogeneous distributed computing and modular software design to speed up the model development. Our computational framework serves currently to test hypothesis on breast tissue healing in a pilot study with women who have been elected to undergo BCT and are being treated at the Methodist Hospital in Houston, TX.

  12. Sequential analysis of variable markers for predicting outcomes in pediatric patients with acute liver failure.

    Science.gov (United States)

    Uchida, Hajime; Sakamoto, Seisuke; Fukuda, Akinari; Sasaki, Kengo; Shigeta, Takanobu; Nosaka, Shunsuke; Kubota, Masaya; Nakazawa, Atsuko; Nakagawa, Satoshi; Kasahara, Mureo

    2017-11-01

    Our aim was to analyze serial changes in the predictive variables and a scoring system retrospectively adapted to evaluate outcomes in pediatric patients with acute liver failure (ALF). We retrospectively collected data on 65 patients with ALF. The 65 patients were divided into two groups according to the need for liver transplantation (LT) as follows: LT group (n = 54) and non-LT group (n = 11). The early determination scoring system of the indications for LT proposed by the Intractable Hepato-Biliary Diseases Study Group of Japan (JIHBDSG) was used in our study. The area under the receiver operating characteristic curve (AUROC) was calculated for the JIHBDSG score between the LT group and non-LT group at the time of diagnosis (day 0) and day 3, and day 5 after the diagnosis. A JIHBDSG score of >3 at day 5 was found to identify the patients requiring LT with 83.7% sensitivity, 81.8% specificity, and 83.3% diagnostic accuracy. Based on a comparison of AUROC values, the JIHBDSG score on day 5 (AUROC 0.91) was higher than that on day 0 (AUROC 0.75) and day 3 (AUROC 0.84). We showed that a serial analysis of the JIHBDSG score might be useful for predicting outcomes of ALF in pediatric patients who fulfilled the criteria of LT indication in our center. However, further studies are needed to validate our results. © 2016 The Japan Society of Hepatology.

  13. Two pathways through adversity: Predicting well-being and housing outcomes among homeless service users.

    Science.gov (United States)

    Walter, Zoe C; Jetten, Jolanda; Dingle, Genevieve A; Parsell, Cameron; Johnstone, Melissa

    2016-06-01

    People who experience homelessness face many challenges and disadvantages that negatively impact health and well-being and form barriers to achieving stable housing. Further, people who are homeless often have limited social connections and support. Building on previous research that has shown the beneficial effect of group identification on health and well-being, the current study explores the relationship between two social identity processes - multiple group memberships and service identification - and well-being and positive housing outcomes. Measures were collected from 76 participants while they were residing in a homeless accommodation service (T1) and again 2-4 weeks after leaving the service (or 3 months after T1 if participants had not left the service). Mediation analyses revealed that multiple group memberships and service identification at T1 independently predicted well-being at T2 indirectly, via social support. Further, both social identity processes also indirectly predicted housing outcomes via social support. The implications of these findings are twofold. First, while belonging to multiple social groups may provide a pathway to gaining social support and well-being, group belonging may not necessarily be beneficial to achieve stable housing. Second, fostering identification with homeless services may be particularly important as a source of support that contributes to well-being. © 2015 The British Psychological Society.

  14. A comparison of published multidimensional indices to predict outcome in idiopathic pulmonary fibrosis

    Directory of Open Access Journals (Sweden)

    Charles Sharp

    2017-03-01

    Full Text Available Idiopathic pulmonary fibrosis (IPF has an unpredictable course and prognostic factors are incompletely understood. We aimed to identify prognostic factors, including multidimensional indices from a significant IPF cohort at the Bristol Interstitial Lung Disease Centre in the UK. Patients diagnosed with IPF between 2007 and 2014 were identified. Longitudinal pulmonary physiology and exercise testing results were collated, with all-cause mortality used as the primary outcome. Factors influencing overall, 12- and 24-month survival were identified using Cox proportional hazards modelling and receiver operating characteristic curve analysis. We found in this real-world cohort of 167 patients, diffusing capacity for carbon monoxide (DLCO and initiation of long-term oxygen were independent markers of poor prognosis. Exercise testing results predicted 12-month mortality as well as DLCO, but did not perform as well for overall survival. The Composite Physiological Index was the best performing multidimensional index, but did not outperform DLCO. Our data confirmed that patients who experienced a fall in forced vital capacity (FVC >10% had significantly worse survival after that point (p=0.024. Our data from longitudinal follow-up in IPF show that DLCO is the best individual prognostic marker, outperforming FVC. Exercise testing is important in predicting early poor outcome. Regular and complete review should be conducted to ensure appropriate care is delivered in a timely fashion.

  15. Parent-Child Math Anxiety and Math-Gender Stereotypes Predict Adolescents’ Math Education Outcomes

    Directory of Open Access Journals (Sweden)

    Bettina J Casad

    2015-11-01

    Full Text Available Two studies examined social determinants of adolescents’ math anxiety including parents’ own math anxiety and children’s endorsement of math-gender stereotypes. In study 1, parent-child dyads were surveyed and the interaction between parent and child math anxiety was examined, with an eye to same- and other-gender dyads. Results indicate that parent’s math anxiety interacts with daughters’ and sons’ anxiety to predict math self-efficacy, GPA, behavioral intentions, math attitudes, and math devaluing. Parents with lower math anxiety showed a positive relationship to children’s math outcomes when children also had lower anxiety. The strongest relationships were found with same-gender dyads, particularly Mother-Daughter dyads. Study 2 showed that endorsement of math-gender stereotypes predicts math anxiety (and not vice versa for performance beliefs and outcomes (self-efficacy and GPA. Further, math anxiety fully mediated the relationship between gender stereotypes and math self-efficacy for girls and for boys, and for boys with GPA. These findings address gaps in the literature on the role of parents’ math anxiety in the effects of children’s math anxiety and math anxiety as a mechanism affecting performance. Results have implications for interventions on parents’ math anxiety and dispelling gender stereotypes in math classrooms.

  16. Diagnostic evaluation of uterine artery Doppler sonography for the prediction of adverse pregnancy outcomes

    Directory of Open Access Journals (Sweden)

    Mojgan Barati

    2014-01-01

    Full Text Available Background : Increased impedance to flow in the uterine arteries assessed by value of the Doppler is associated with adverse pregnancy outcomes, especially pre-eclampsia. We investigated the predictive value of a uterine artery Doppler in the identification of adverse pregnancy outcomes such as ′pre-eclampsia′ and ′small fetus for gestational age′ (SGA. Materials and Methods: Three hundred and seventy-nine women, with singleton pregnancy, between 18 and 40 years of age, without risk factors, randomly underwent Doppler interrogation of the uterine arteries, between 16-22 weeks of gestation. Those who had a mean pulsatility index (PI of >1.45 were considered to have an abnormal result, and were evaluated and compared with those who had normal results for adverse pregnancy outcomes, including pre-eclampsia and small for gestational age. The relationship between the variables was assessed with the use of the chi-square test. Results : There were 17 cases (4.5% of abnormal uterine artery Doppler results and 15 of them (88.2% developed pre-eclampsia and four cases (23.5% had neonates small for gestational age. For predicting pre-eclampsia, the mean uterine artery PI had to be >1.45, had to have a specificity of 95.5% (95% CI, 70-92%, a sensitivity of 79% (95% CI, 43-82%, a negative predictive value (NPV of 98.9% (95% CI, 72-96%, and a positive predictive value (PPV of 88.2% (95% CI, 68-98%. In the case of ′small for gestational age′ it had to have a specificity of 96.5% (95% CI, 42-68%, a sensitivity of 57% (95% CI, 53-76%, an NPV of 99.2% (95% CI, 70-92%, and a PPV of 23.5% (95% CI, 30-72%. Conclusion : Uterine artery Doppler evaluation at 16-22 weeks of gestation might be an appropriate tool for identifying pregnancies that may be at an increased risk for development of pre-eclampsia and small fetus for gestational age.

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

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

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

  18. Interrogating differences in expression of targeted gene sets to predict breast cancer outcome.

    Science.gov (United States)

    Andres, Sarah A; Brock, Guy N; Wittliff, James L

    2013-07-02

    Genomics provides opportunities to develop precise tests for diagnostics, therapy selection and monitoring. From analyses of our studies and those of published results, 32 candidate genes were identified, whose expression appears related to clinical outcome of breast cancer. Expression of these genes was validated by qPCR and correlated with clinical follow-up to identify a gene subset for development of a prognostic test. RNA was isolated from 225 frozen invasive ductal carcinomas,and qRT-PCR was performed. Univariate hazard ratios and 95% confidence intervals for breast cancer mortality and recurrence were calculated for each of the 32 candidate genes. A multivariable gene expression model for predicting each outcome was determined using the LASSO, with 1000 splits of the data into training and testing sets to determine predictive accuracy based on the C-index. Models with gene expression data were compared to models with standard clinical covariates and models with both gene expression and clinical covariates. Univariate analyses revealed over-expression of RABEP1, PGR, NAT1, PTP4A2, SLC39A6, ESR1, EVL, TBC1D9, FUT8, and SCUBE2 were all associated with reduced time to disease-related mortality (HR between 0.8 and 0.91, adjusted p data sets for the gene expression, clinical, and combined models were 0.65, 0.63, and 0.65 for disease mortality and 0.64, 0.63, and 0.66 for disease recurrence, respectively. Molecular signatures consisting of five genes (PGR, GABRP, TBC1D9, SLC39A6 and LRBA) for disease mortality and of six genes (PGR, ESR1, GABRP, TBC1D9, SLC39A6 and LRBA) for disease recurrence were identified. These signatures were as effective as standard clinical parameters in predicting recurrence/mortality, and when combined, offered some improvement relative to clinical information alone for disease recurrence (median difference in C-values of 0.03, 95% CI of -0.08 to 0.13). Collectively, results suggest that these genes form the basis for a clinical

  19. Interrogating differences in expression of targeted gene sets to predict breast cancer outcome

    International Nuclear Information System (INIS)

    Andres, Sarah A; Brock, Guy N; Wittliff, James L

    2013-01-01

    Genomics provides opportunities to develop precise tests for diagnostics, therapy selection and monitoring. From analyses of our studies and those of published results, 32 candidate genes were identified, whose expression appears related to clinical outcome of breast cancer. Expression of these genes was validated by qPCR and correlated with clinical follow-up to identify a gene subset for development of a prognostic test. RNA was isolated from 225 frozen invasive ductal carcinomas,and qRT-PCR was performed. Univariate hazard ratios and 95% confidence intervals for breast cancer mortality and recurrence were calculated for each of the 32 candidate genes. A multivariable gene expression model for predicting each outcome was determined using the LASSO, with 1000 splits of the data into training and testing sets to determine predictive accuracy based on the C-index. Models with gene expression data were compared to models with standard clinical covariates and models with both gene expression and clinical covariates. Univariate analyses revealed over-expression of RABEP1, PGR, NAT1, PTP4A2, SLC39A6, ESR1, EVL, TBC1D9, FUT8, and SCUBE2 were all associated with reduced time to disease-related mortality (HR between 0.8 and 0.91, adjusted p < 0.05), while RABEP1, PGR, SLC39A6, and FUT8 were also associated with reduced recurrence times. Multivariable analyses using the LASSO revealed PGR, ESR1, NAT1, GABRP, TBC1D9, SLC39A6, and LRBA to be the most important predictors for both disease mortality and recurrence. Median C-indexes on test data sets for the gene expression, clinical, and combined models were 0.65, 0.63, and 0.65 for disease mortality and 0.64, 0.63, and 0.66 for disease recurrence, respectively. Molecular signatures consisting of five genes (PGR, GABRP, TBC1D9, SLC39A6 and LRBA) for disease mortality and of six genes (PGR, ESR1, GABRP, TBC1D9, SLC39A6 and LRBA) for disease recurrence were identified. These signatures were as effective as standard clinical

  20. Evaluation of LRINEC Scale Feasibility for Predicting Outcomes of Fournier Gangrene.

    Science.gov (United States)

    Kincius, Marius; Telksnys, Titas; Trumbeckas, Darius; Jievaltas, Mindaugas; Milonas, Daimantas

    2016-08-01

    Fournier gangrene (FG) is a fulminant necrotizing infection of the perineal, perianal, and periurethral tissues. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) scale is used for diagnosis of necrotizing fasciitis. However, data on its relevance and usefulness in FG are lacking. The aim of this study was to evaluate the utility of the LRINEC scale in predicting the outcome of FG. This retrospective case study included 41 patents with FG treated at our institution from 2000 to 2013. The patients were divided into survivors and non-survivors. The mortality rate was 22%. The median age (75 vs. 62.5 y; p = 0.013), rate of co-existing diabetes mellitus (66.7% vs. 3.1%; p < 0.001), and median affected skin surface (4% vs. 1%; p < 0.001) were greater in the non-survivors. Seven of nine patients (77.8%) who did not survive (compared with 37.5% who survived) had a polymicrobial infection (p = 0.032). Of all the causative pathogens isolated, Proteus mirabilis was more common in non-survivors (55.6% vs. 6.3%; p = 0.001). The median calculated LRINEC score for survivors was 5 compared with 10 for the non-survivors (p < 0.001). Regression analysis showed that all the aforementioned variables, except for polymicrobial culture, were significant risk factors for predicting death. The area under the receiver operating characteristic curve for the LRINEC score was the highest, 0.976 (95% confidence interval 0.872-0.999; p < 0.0001), and the cut-off value was ≥9 with 93.7% specificity and 100% susceptibility for the prediction of a lethal outcome. The LRINEC score could be used for prediction of disease severity and outcomes. A threshold of 9 could be a high-value predictor of death during the initial evaluation of patients with FG.

  1. Evaluating a theory of stress and adjustment when predicting long-term psychosocial outcome after brain injury.

    Science.gov (United States)

    Rutterford, Neil A; Wood, Rodger L

    2006-05-01

    Kendall and Terry (1996) include many psychosocial predictors in their theoretical model that explains individual differences in psychosocial adjustment (Lazarus & Folkman, 1984). The model depicts appraisal and coping variables as mediating relationships between situation factors, environmental and personal resources, and multidimensional outcome. The aim of this study was to explore these theoretical relationships at very late stages of recovery from traumatic brain injury. A total of 131 participants who were more than 10 years post-injury (mean = 15.31 years) completed several psychosocial measures relating to outcome dimensions comprising employment, community integration, life satisfaction, quality of life (QoL), and emotion. There was no evidence that appraisal and coping variables mediated relationships between psychosocial and any of the outcome variables. However, when appraisal and coping variables were combined with psychosocial variables as direct predictors of outcome, every outcome except employment status was reliably predicted, accounting for between 31 and 46% of the variance. Personality significantly influenced all predicted outcomes. Self-efficacy contributed to the prediction of all outcomes except QoL. Data did not support for the theory of stress and adjustment as a framework for explaining the nature of predictive relationships between psychosocial variables and very long-term, multidimensional outcome after brain injury.

  2. How adverse outcome pathways can aid the development and use of computational prediction models for regulatory toxicology

    Science.gov (United States)

    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 accumu...

  3. T cell subpopulations in lymph nodes may not be predictive of patient outcome in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Yoon Han-Seung

    2011-08-01

    Full Text Available Abstract Background The immune response has been proposed to be an important factor in determining patient outcome in colorectal cancer (CRC. Previous studies have concentrated on characterizing T cell populations in the primary tumour where T cells with regulatory effect (Foxp3+ Tregs have been identified as both enhancing and diminishing anti-tumour immune responses. No previous studies have characterized the T cell response in the regional lymph nodes in CRC. Methods Immunohistochemistry was used to analyse CD4, CD8 or Foxp3+ T cell populations in the regional lymph nodes of patients with stage II CRC (n = 31, with (n = 13 or without (n = 18 cancer recurrence after 5 years of follow up, to determine if the priming environment for anti-tumour immunity was associated with clinical outcome. Results The proportions of CD4, CD8 or Foxp3+ cells in the lymph nodes varied widely between and within patients, and there was no association between T cell populations and cancer recurrence or other clinicopathological characteristics. Conclusions These data indicate that frequency of these T cell subsets in lymph nodes may not be a useful tool for predicting patient outcome.

  4. Factors for Predicting Favorable Outcome of Percutaneous Epidural Adhesiolysis for Lumbar Disc Herniation

    Directory of Open Access Journals (Sweden)

    Sang Ho Moon

    2017-01-01

    Full Text Available Background. Lower back pain is a common reason for disability and the most common cause is lumbar disc herniation. Percutaneous epidural adhesiolysis has been applied to relieve pain and increase the functional capacity of patients who present this condition. Objectives. In this study, we retrospectively evaluated the factors which predict the outcome of percutaneous epidural adhesiolysis in patients who were diagnosed with lumbar disc herniation. Methods. Electronic medical records of patients diagnosed with lumbar disc herniation who have received percutaneous epidural adhesiolysis treatment were reviewed. The primary outcome was the factors that were associated with substantial response of ≥4 points or ≥50% of pain relief in the numerical rating scale pain score 12 months after the treatment. Results. Multivariate logistic regression analysis demonstrated that the presence of high-intensity zone (HIZ at magnetic resonance imaging was a predictor of substantial response to percutaneous epidural adhesiolysis for 12 months (P=0.007. The presence of a condition involving the vertebral foramen was a predictor for unsuccessful response after 12 months (P=0.02. Discussion and Conclusion. The presence of HIZ was a predictor of favorable long-term outcome after percutaneous epidural adhesiolysis for the treatment of lower back pain with radicular pain caused by lumbar disc herniation.

  5. Radiologic findings for prediction of rehabilitation outcomes in patients with chronic symptomatic os subfibulare.

    Science.gov (United States)

    Kim, Beom Suk; Woo, Sungmin; Kim, Jae Young; Park, Chankue

    2017-10-01

    To retrospectively evaluate the radiologic findings for predicting rehabilitation outcomes in patients with chronic symptomatic os subfibulare. 38 patients with chronic lateral ankle pain and os subfibulare underwent a standardized rehabilitation program. Rehabilitation outcome was evaluated after ≥3 months of intervention as the following: good response group (n = 20) without the need for further treatment and poor response group (n = 18) who underwent surgery after rehabilitation. Size, shape and location of os subfibulare, anterior talofibular ligament abnormality and attachment to the os subfibulare, interposition of fluid signal intensity between the os subfibulare and the fibula, and bone marrow edema in the os subfibulare on radiographs and MRI were evaluated by two radiologists blinded to rehabilitation outcomes and were compared between the two groups. The mean size of os subfibulare was significantly different between good and poor response groups: 7 versus 12 mm (p os subfibulare and the fibula and bone marrow edema in the os subfibulare on MRI was significantly different between the two groups (p os subfibulare.

  6. Could infarct location predict the long-term functional outcome in childhood arterial ischemic stroke?

    Directory of Open Access Journals (Sweden)

    Mauricio López-Espejo

    Full Text Available ABSTRACT Objective: To explore the influence of infarct location on long-term functional outcome following a first-ever arterial ischemic stroke (AIS in non-neonate children. Method: The MRIs of 39 children with AIS (median age 5.38 years; 36% girls; mean follow-up time 5.87 years were prospectively evaluated. Infarct location was classified as the absence or presence of subcortical involvement. Functional outcome was measured using the modified Rankin scale (mRS for children after the follow-up assessment. We utilized multivariate logistic regression models to estimate the odds ratios (ORs for the outcome while adjusting for age, sex, infarct size and middle cerebral artery territory involvement (significance < 0.05. Results: Both infarcts ≥ 4% of total brain volume (OR 9.92; CI 1.76 – 55.9; p 0.009 and the presence of subcortical involvement (OR 8.36; CI 1.76 – 53.6; p 0.025 independently increased the risk of marked functional impairment (mRS 3 to 5. Conclusion: Infarct extension and location can help predict the extent of disability after childhood AIS.

  7. Distinctive cytokines as biomarkers predicting fatal outcome of severe Staphylococcus aureus bacteremia in mice.

    Science.gov (United States)

    van den Berg, Sanne; Laman, Jon D; Boon, Louis; ten Kate, Marian T; de Knegt, Gerjo J; Verdijk, Rob M; Verbrugh, Henri A; Nouwen, Jan L; Bakker-Woudenberg, Irma A J M

    2013-01-01

    Invasive Staphylococcus aureus infections are frequently associated with bacteraemia. To support clinical decisions on antibiotic therapy, there is an urgent need for reliable markers as predictors of infection outcome. In the present study in mice, bacteraemia was established by intravenous inoculation of a clinical S. aureus isolate at the LD50 inoculum. As potential biomarkers for fatal outcome, blood culture (qualitative and quantitative), serum levels of C-reactive protein (CRP), as well as 31 selected cytokines and chemokines were assessed during the first three days of infection. A positive S. aureus blood culture, the quantitative blood culture, CRP levels, and levels of eight cytokines were indicative for the presence of S. aureus bacteraemia. However, only tumor necrosis factor (TNF) α, interleukin (IL) 1α, and keratinocyte chemoattractant (KC; a functional homologue of human IL-8) were each significantly elevated in eventually non-surviving infected mice versus eventually surviving infected mice. In severe S. aureus bacteraemia in mice, TNF-α, IL-1α, and KC are biomarkers predicting fatal outcome of infection. KC was a biomarker elevated irrespective the progression of infection, which is very interesting regarding clinical application in view of the heterogeneity of patients experiencing bacteraemia in this respect.

  8. The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

    Directory of Open Access Journals (Sweden)

    Bradford A. Moffat

    2006-04-01

    Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

  9. Predicting clinical outcomes in chordoma patients receiving immunotherapy: a comparison between volumetric segmentation and RECIST

    International Nuclear Information System (INIS)

    Fenerty, Kathleen E.; Folio, Les R.; Patronas, Nicholas J.; Marté, Jennifer L.; Gulley, James L.; Heery, Christopher R.

    2016-01-01

    The Response Evaluation Criteria in Solid Tumors (RECIST) are the current standard for evaluating disease progression or therapy response in patients with solid tumors. RECIST 1.1 calls for axial, longest-diameter (or perpendicular short axis of lymph nodes) measurements of a maximum of five tumors, which limits clinicians’ ability to adequately measure disease burden, especially in patients with irregularly shaped tumors. This is especially problematic in chordoma, a disease for which RECIST does not always adequately capture disease burden because chordoma tumors are typically irregularly shaped and slow-growing. Furthermore, primary chordoma tumors tend to be adjacent to vital structures in the skull or sacrum that, when compressed, lead to significant clinical consequences. Volumetric segmentation is a newer technology that allows tumor burden to be measured in three dimensions on either MR or CT. Here, we compared the ability of RECIST measurements and tumor volumes to predict clinical outcomes in a cohort of 21 chordoma patients receiving immunotherapy. There was a significant difference in radiologic time to progression Kaplan-Meier curves between clinical outcome groups using volumetric segmentation (P = 0.012) but not RECIST (P = 0.38). In several cases, changes in volume were earlier and more sensitive reflections of clinical status. RECIST is a useful evaluation method when obvious changes are occurring in patients with chordoma. However, in many cases, RECIST does not detect small changes, and volumetric assessment was capable of detecting changes and predicting clinical outcome earlier than RECIST. Although this study was small and retrospective, we believe our results warrant further research in this area

  10. Acute liver failure in Japan: definition, classification, and prediction of the outcome.

    Science.gov (United States)

    Sugawara, Kayoko; Nakayama, Nobuaki; Mochida, Satoshi

    2012-08-01

    Acute liver failure is a clinical syndrome characterized by hepatic encephalopathy and a bleeding tendency due to severe impairment of liver function caused by massive or submassive liver necrosis. Viral hepatitis is the most important and frequent cause of acute liver failure in Japan. The diagnostic criteria for fulminant hepatitis, including that caused by viral infections, autoimmune hepatitis, and drug allergy induced-liver damage, were first established in 1981. Considering the discrepancies between the definition of fulminant hepatitis in Japan and the definitions of acute liver failure in the United States and Europe, the Intractable Hepato-Biliary Disease Study Group established the diagnostic criteria for "acute liver failure" for Japan in 2011, and performed a nationwide survey of patients seen in 2010 to clarify the demographic and clinical features and outcomes of these patients. According to the survey, the survival rates of patients receiving medical treatment alone were low, especially in those with hepatic encephalopathy, despite artificial liver support, consisting of plasma exchange and hemodiafiltration, being provided to almost all patients in Japan. Thus, liver transplantation is inevitable to rescue most patients with hepatic encephalopathy. The indications for liver transplantation had, until recently, been determined according to the guideline published by the Acute Liver Failure Study Group in 1996. Recently, however, the Intractable Hepato-Biliary Disease Study Group established a scoring system to predict the outcomes of acute liver failure patients. Algorithms for outcome prediction have also been developed based on data-mining analyses. These novel guidelines need further evaluation to determine their usefulness.

  11. Are patient-reported outcomes predictive of patient satisfaction 5 years after anterior cervical spine surgery?

    Science.gov (United States)

    Schroeder, Gregory D; Coric, Dom; Kim, Han Jo; Albert, Todd J; Radcliff, Kris E

    2017-07-01

    Patient satisfaction is becoming an increasing common proxy for surgical quality; however, the correlation between patient satisfaction and surgical outcomes 2 and 5 years after anterior cervical surgery has not been evaluated. The study aimed to determine if patient satisfaction is predicted by improvement in patient-reported outcomes (PRO) 2 and 5 years after anterior cervical spine surgery. This is a retrospective analysis of prospectively collected data. The sample included patients enrolled in the Food and Drug Administration investigational device exemption clinical trial comparing total disc replacement with Mobi-C cervical artificial disc and anterior cervical discectomy and fusion. The outcome measures were visual analog scale (VAS) neck pain score, Neck Disability Index (NDI), and Short-Form 12-Item scores, as well as patient satisfaction. Receiver operating characteristic curves were used to determine if improvement in different PRO metrics can accurately identify patient satisfaction. Additionally, a logistic regression analysis was performed on the results at 24 months and 60 months to identify independent predictors of patient satisfaction. This research was supported by LDR (Zimmer Biomet) 13785 Research Boulevard - Suite 200 Austin, TX 78750. Data were available for 512 patients at 60 months. At 24 months postoperatively, NDI score improvement (area under the curve [AUC]=0.806), absolute NDI score (AUC=0.823), and absolute VAS neck pain score (AUC=0.808) were all excellent predictors of patient satisfaction. At 60 months postoperatively, NDI score improvement (AUC=0.815), absolute NDI score (AUC=0.839), VAS neck pain score improvement (AUC=0.803), and absolute VAS neck pain score (AUC=0.861) were all excellent predictors of patient satisfaction. In patients undergoing one- and two-level anterior cervical spine surgery, between 2 and 5 years postoperatively, patient satisfaction is significantly predicted by PROs, including the VAS neck score and the

  12. Validation of the hospital outcome prediction equation (HOPE) model for monitoring clinical performance.

    Science.gov (United States)

    Duke, G J; Graco, M; Santamaria, J; Shann, F

    2009-05-01

    The aim of this study was to validate a risk-adjusted hospital outcome prediction equation (HOPE) using a statewide administrative dataset. Retrospective observational study using multivariate logistic regression modelling. Calibration and discrimination were assessed by standardized mortality ratio (SMR), area under the receiver operating characteristic plot (ROC AUC), Hosmer-Lemeshow contingency tables and goodness-of-fit statistic in an independent dataset, and in all 23 important tertiary, metropolitan and regional hospitals. The dependent variable was in-hospital death. All consecutive adult hospital separations between 1 July 2004 and 30 June 2006, excluding obstetric and day-case only admissions, from all acute health services within the State of Victoria, Australia were included. A total of 379 676 consecutive records (1 July 2004 to 30 June 2005) was used to derive the HOPE model. Six variables (age, male sex, admission diagnosis, emergency admission, aged-care resident and inter-hospital transfer) were selected for inclusion in the final model. It was validated in the 384 489 consecutive records from the following year (1 July 2005 to 30 June 2006). The 95% confidence interval for the SMR was 0.98-1.02, and for the ROC AUC, 0.87-0.88. Discrimination and (one or more) calibration criteria were achieved in 22 (96%) of the 23 hospitals. The HOPE model is a simple risk-adjusted outcome prediction tool, based on six variables from data that are routinely collected for administrative purposes and appears to be a reliable predictor of hospital outcome.

  13. Predicting Implantation Outcome of In Vitro Fertilization and Intracytoplasmic Sperm Injection Using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Pegah Hafiz

    2017-09-01

    Full Text Available Background In vitro fertilization (IVF and intracytoplasmic sperm injection (ICSI are two important subsets of the assisted reproductive techniques, used for the treatment of infertility. Predicting implantation outcome of IVF/ICSI or the chance of pregnancy is essential for infertile couples, since these treatments are complex and expensive with a low probability of conception. Materials and Methods In this cross-sectional study, the data of 486 patients were collected using census method. The IVF/ICSI dataset contains 29 variables along with an identifier for each patient that is either negative or positive. Mean accuracy and mean area under the receiver operating characteristic (ROC curve are calculated for the classifiers. Sensitivity, specificity, positive and negative predictive values, and likelihood ratios of classifiers are employed as indicators of performance. The state-of-art classifiers which are candidates for this study include support vector machines, recursive partitioning (RPART, random forest (RF, adaptive boosting, and one-nearest neighbor. Results RF and RPART outperform the other comparable methods. The results revealed the areas under the ROC curve (AUC as 84.23 and 82.05%, respectively. The importance of IVF/ICSI features was extracted from the output of RPART. Our findings demonstrate that the probability of pregnancy is low for women aged above 38. Conclusion Classifiers RF and RPART are better at predicting IVF/ICSI cases compared to other decision makers that were tested in our study. Elicited decision rules of RPART determine useful predictive features of IVF/ICSI. Out of 20 factors, the age of woman, number of developed embryos, and serum estradiol level on the day of human chorionic gonadotropin administration are the three best features for such prediction.

  14. Using intake and change in multiple psychosocial measures to predict functional status outcomes in people with lumbar spine syndromes: a preliminary analysis.

    Science.gov (United States)

    Hart, Dennis L; Werneke, Mark W; Deutscher, Daniel; George, Steven Z; Stratford, Paul W; Mioduski, Jerome E

    2011-12-01

    Managing patients with lumbar spine syndromes who are seeking outpatient physical therapy represents a complex problem where psychosocial constructs such as fear-avoidance beliefs regarding physical activities or work activities, somatization, and depressive symptoms may affect functional status (FS) outcomes. The purpose of this study was to determine whether intake or changes in fear-avoidance beliefs regarding physical or work activities, somatization, and depressive symptoms assessed simultaneously affect FS outcomes prediction. This study was a secondary analysis of prospectively collected, longitudinal, observational cohort data. Data analyzed were from adult patients (n=323) with lumbar syndromes classified as elevated versus not elevated on single-item screening instruments for fear-avoidance beliefs regarding physical or work activities, somatization, and depressive symptoms at intake and discharge. Prediction of minimal clinically important difference in FS was assessed separately for intake and change from intake to discharge classifications using logistic regression models controlling for important variables. Intake and change models were strong (McFadden rho-squared values=.31 and .49, respectively). Patients classified as not elevated in fear-avoidance beliefs regarding physical activities but elevated in fear-avoidance beliefs regarding work activities, somatization, and depressive symptoms at intake were 5 out of 100 times less likely to report clinically important outcomes compared with being elevated in each measure. Patients not elevated in fear-avoidance beliefs regarding work activities and somatization at intake and discharge were 8 to 14 times more likely to report clinically important outcomes compared with being elevated in each measure. Sample size was limited. Data analyses were retrospective with no control of missing data. Combinations of multiple psychosocial constructs were important predictors of FS outcomes and may assist patient

  15. Serum albumin levels predict clinical outcomes in chronic kidney disease (CKD) patients undergoing cardiac resynchronization therapy.

    Science.gov (United States)

    Uchikawa, Tomohiro; Shimano, Masayuki; Inden, Yasuya; Murohara, Toyoaki

    2014-01-01

    A low level of serum albumin is common in chronic kidney disease (CKD) patients with heart failure (HF). Cardiac resynchronization therapy (CRT), a novel therapeutic option, improves cardiac performance in patients with severe HF. In addition, CKD has recently been found to be associated with outcomes after CRT; however, the associations of the serum albumin levels with adverse events and the long-term prognosis in CKD patients who have undergone CRT are unknown. In this study, we investigated whether the albumin levels can be used to the predict mortality rate and incidence of cardiovascular events in CKD patients treated with CRT. A retrospective chart review was conducted in 102 consecutive CKD patients receiving a CRT device for the treatment of advanced HF. The long-term outcomes following device implantation were assessed according to the albumin levels. During a median follow-up of 2.6 years, 34 patients (33.3%) died and 66 patients (64.7%) experienced cardiovascular events. A Kaplan-Meier survival analysis revealed that the CKD patients with decreased albumin levels exhibited significantly higher rates of all-cause mortality and cardiovascular events, including hospitalization for progressive HF, than the CKD patients without hypoalbuminemia. Importantly, a multivariate Cox regression analysis of confounding factors showed a low serum albumin level to independently predict all-cause death and cardiovascular events. Hypoalbuminemia independently predicts cardiac morbidity and mortality in CKD patients receiving CRT. Assessing the albumin levels provides valuable information regarding the long-term prognosis in CKD patients who undergo CRT.

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

    Directory of Open Access Journals (Sweden)

    Unachukwu Chioma

    2009-03-01

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

  17. Same admissions tools, different outcomes: a critical perspective on predictive validity in three undergraduate medical schools.

    Science.gov (United States)

    Edwards, Daniel; Friedman, Tim; Pearce, Jacob

    2013-12-27

    Admission to medical school is one of the most highly competitive entry points in higher education. Considerable investment is made by universities to develop selection processes that aim to identify the most appropriate candidates for their medical programs. This paper explores data from three undergraduate medical schools to offer a critical perspective of predictive validity in medical admissions. This study examined 650 undergraduate medical students from three Australian universities as they progressed through the initial years of medical school (accounting for approximately 25 per cent of all commencing undergraduate medical students in Australia in 2006 and 2007). Admissions criteria (aptitude test score based on UMAT, school result and interview score) were correlated with GPA over four years of study. Standard regression of each of the three admissions variables on GPA, for each institution at each year level was also conducted. Overall, the data found positive correlations between performance in medical school, school achievement and UMAT, but not interview. However, there were substantial differences between schools, across year levels, and within sections of UMAT exposed. Despite this, each admission variable was shown to add towards explaining course performance, net of other variables. The findings suggest the strength of multiple admissions tools in predicting outcomes of medical students. However, they also highlight the large differences in outcomes achieved by different schools, thus emphasising the pitfalls of generalising results from predictive validity studies without recognising the diverse ways in which they are designed and the variation in the institutional contexts in which they are administered. The assumption that high-positive correlations are desirable (or even expected) in these studies is also problematised.

  18. Do symptom-specific stages of change predict eating disorder treatment outcome?

    Science.gov (United States)

    Ackard, Diann M; Cronemeyer, Catherine L; Richter, Sara; Egan, Amber

    2015-03-01

    Interview methods to assess stages of change (SOC) in eating disorders (ED) indicate that SOC are positively correlated with symptom improvement over time. However, interviews require significant time and staff training and global measures of SOC do not capture varying levels of motivation across ED symptoms. This study used a self-report, ED symptom-specific SOC measure to determine prevalence of stages across symptoms and identify if SOC predict treatment outcome. Participants [N = 182; age 13-58 years; 92% Caucasian; 96% female; average BMI 21.7 (SD = 5.9); 50% ED not otherwise specified (EDNOS), 30.8% bulimia nervosa (BN), 19.2% anorexia nervosa (AN)] seeking ED treatment at a diverse-milieu multi-disciplinary facility in the United States completed stages of change, behavioral (ED symptom use and frequency) and psychological (ED concerns, anxiety, depression) measures at intake assessment and at 3, 6 and 12 months thereafter. Descriptive summaries were generated using ANOVA or Kruskal-Wallis (continuous) and χ (2) (categorical) tests. Repeated measures linear regression models with autoregressive correlation structure predicted treatment outcome. At intake assessment, 53.3% of AN, 34.0% of BN and 18.1% of EDNOS patients were in Preparation/Action. Readiness to change specific symptoms was highest for binge-eating (57.8%) and vomiting (56.5%). Frequency of fasting and restricting behaviors, and scores on all eating disorder and psychological measures improved over time regardless of SOC at intake assessment. Symptom-specific SOC did not predict reductions in ED symptom frequency. Overall SOC predicted neither improvement in Eating Disorder Examination Questionnaire (EDE-Q) scores nor reduction in depression or trait anxiety; however, higher overall SOC predicted lower state anxiety across follow-up. Readiness to change ED behaviors varies considerably. Most patients reduced eating disorder behaviors and increased psychological functioning regardless of stages

  19. Utility of screening questionnaire and polysomnography to predict postoperative outcomes in children.

    Science.gov (United States)

    Kako, Hiromi; Tripi, Jennifer; Walia, Hina; Tumin, Dmitry; Splaingard, Mark; Jatana, Kris R; Tobias, Joseph D; Raman, Vidya T

    2017-11-01

    The prevalence of pediatric obstructive sleep apnea (OSA) has increased concurrently with the increasing prevalence of obesity. We have previously validated a short questionnaire predicting the occurrence of OSA on polysomnography (PSG). This follow-up study assessed the utility of the questionnaire in predicting postoperative outcomes. Children undergoing surgery and completing a sleep study were prospectively screened for OSA using a short questionnaire. Procedures within 1 year of PSG were included in the analysis. Questionnaires were scored according to a cutoff previously deemed optimal for predicting OSA (apnea-hypopnea index ≥ 5) on the sleep study. Postoperative outcomes included prolonged (>60 min) length of stay (LOS) in the post-anesthesia care unit (PACU) and oxygen requirement in the PACU. The study cohort included 185 patients (100/85 male/female) age 8 ± 4 years, undergoing adenotonsillectomy (n = 109), other ear, nose, and throat (ENT) procedures (n = 18), or non-ENT procedures (n = 58). There were 45 patients with OSA documented by PSG and 122 patients identified as likely to have OSA according to questionnaire responses (89% sensitivity, 41% specificity). PACU LOS was prolonged in 55/181 (30%) cases and supplemental oxygen was used in the PACU in 29/181 (16%) cases. In separate multivariable models, supplemental oxygen use in the PACU was more common if a patient scored ≥2/6 points on the short questionnaire scale (OR = 5.0; 95% CI: 1.3, 19.9; p = 0.023) or if the patient was diagnosed with OSA on PSG (OR = 4.6; 95% CI: 1.6, 13.5; p = 0.005). Neither OSA on PSG nor questionnaire score ≥2/6 were associated with prolonged PACU stay. Both OSA diagnosis based on the AHI and the questionnaire scale achieved comparable predictive value for the need for oxygen use in the PACU. The utility of the questionnaire in predicting rare adverse events (e.g., unplanned admission or rapid response team activation) remains to be determined

  20. Comparing frailty measures in their ability to predict adverse outcome among older residents of assisted living

    Directory of Open Access Journals (Sweden)

    Hogan David B

    2012-09-01

    Full Text Available Abstract Background Few studies have directly compared the competing approaches to identifying frailty in more vulnerable older populations. We examined the ability of two versions of a frailty index (43 vs. 83 items, the Cardiovascular Health Study (CHS frailty criteria, and the CHESS scale to accurately predict the occurrence of three outcomes among Assisted Living (AL residents followed over one year. Methods The three frailty measures and the CHESS scale were derived from assessment items completed among 1,066 AL residents (aged 65+ participating in the Alberta Continuing Care Epidemiological Studies (ACCES. Adjusted risks of one-year mortality, hospitalization and long-term care placement were estimated for those categorized as frail or pre-frail compared with non-frail (or at high/intermediate vs. low risk on CHESS. The area under the ROC curve (AUC was calculated for select models to assess the predictive accuracy of the different frailty measures and CHESS scale in relation to the three outcomes examined. Results Frail subjects defined by the three approaches and those at high risk for decline on CHESS showed a statistically significant increased risk for death and long-term care placement compared with those categorized as either not frail or at low risk for decline. The risk estimates for hospitalization associated with the frailty measures and CHESS were generally weaker with one of the frailty indices (43 items showing no significant association. For death and long-term care placement, the addition of frailty (however derived or CHESS significantly improved on the AUC obtained with a model including only age, sex and co-morbidity, though the magnitude of improvement was sometimes small. The different frailty/risk models did not differ significantly from each other in predicting mortality or hospitalization; however, one of the frailty indices (83 items showed significantly better performance over the other measures in predicting long

  1. Comparing frailty measures in their ability to predict adverse outcome among older residents of assisted living.

    Science.gov (United States)

    Hogan, David B; Freiheit, Elizabeth A; Strain, Laurel A; Patten, Scott B; Schmaltz, Heidi N; Rolfson, Darryl; Maxwell, Colleen J

    2012-09-14

    Few studies have directly compared the competing approaches to identifying frailty in more vulnerable older populations. We examined the ability of two versions of a frailty index (43 vs. 83 items), the Cardiovascular Health Study (CHS) frailty criteria, and the CHESS scale to accurately predict the occurrence of three outcomes among Assisted Living (AL) residents followed over one year. The three frailty measures and the CHESS scale were derived from assessment items completed among 1,066 AL residents (aged 65+) participating in the Alberta Continuing Care Epidemiological Studies (ACCES). Adjusted risks of one-year mortality, hospitalization and long-term care placement were estimated for those categorized as frail or pre-frail compared with non-frail (or at high/intermediate vs. low risk on CHESS). The area under the ROC curve (AUC) was calculated for select models to assess the predictive accuracy of the different frailty measures and CHESS scale in relation to the three outcomes examined. Frail subjects defined by the three approaches and those at high risk for decline on CHESS showed a statistically significant increased risk for death and long-term care placement compared with those categorized as either not frail or at low risk for decline. The risk estimates for hospitalization associated with the frailty measures and CHESS were generally weaker with one of the frailty indices (43 items) showing no significant association. For death and long-term care placement, the addition of frailty (however derived) or CHESS significantly improved on the AUC obtained with a model including only age, sex and co-morbidity, though the magnitude of improvement was sometimes small. The different frailty/risk models did not differ significantly from each other in predicting mortality or hospitalization; however, one of the frailty indices (83 items) showed significantly better performance over the other measures in predicting long-term care placement. Using different

  2. [Partial nephrectomy on solitary kidney: Renal function outcome and predictive factors of impairment].

    Science.gov (United States)

    Pierquet, G; Zongo, D; Robert, G; Pasticier, G; Maurice-Tison, S; Bensadoun, H; Ballanger, P; Rouget, B; Ferriere, J-M; Bernhard, J-C

    2016-01-01

    To assess the postoperative functional outcome of PN in solitary kidney and define some predictive factors of renal change. A monocentric series of 45 partial nephrectomies on solitary kidneys, performed between 1988 and 2014, was retrospectively analyzed. Pre-, per- and postoperative clinicopathological data were collected in the UroCCR database. The evolution of early, medium and long-term postoperative Glomerular Filtration Rate (GFR) was evaluated. Predictive factors of GFR decline and hemodialysis were assessed in multivariate analysis. Mean age was 61 years old (±10.8). Mean preoperative GFR and tumor size were respectively 59.6 mL/min (±18.7) and 3.9 cm (±2.6). Vascular clamping was performed in 41 cases (91%). Median time of warm ischemia was 20 minutes (2-60). Mean follow-up was 66 months (±47). Mean GFR at day 5, 1 month and last follow-up were respectively 46.4 mL/min, 50.3 mL/min and 53.1 mL/min. At day 5 and at last follow-up, a GFR decrease ≥ 20% was found in 20 patients (44.4%) and in 16 patients (35.5%), respectively. Five patients (11%) required definitive hemodialysis (HD) at last follow-up. At day 5, tumor size>4 cm (0.006) and operative time (P=0.003) were independent predictive factors of GFR decline. At 1 year, RENAL ns ≥ 10 was the only independent predictive factor of GFR alteration (P=0.0007). Preoperative GFR was significantly associated with final hemodialysis (P=0.023). Partial nephrectomy allows most of the patients presenting with renal cell carcinoma on solitary kidney to be free of hemodialysis. Tumor complexity, tumor size and preoperative GFR seems to play a determinant role on postoperative functional outcome. These non-modifiable predictive factors should be recognized and taken into account to better select patients with high risk of postoperative renal failure. 5. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  3. Gastroschisis with intestinal atresia--predictive value of antenatal diagnosis and outcome of postnatal treatment.

    Science.gov (United States)

    Ghionzoli, Marco; James, Catherine P; David, Anna L; Shah, Dimple; Tan, Aileen W C; Iskaros, Joseph; Drake, David P; Curry, Joseph I; Kiely, Edward M; Cross, Kate; Eaton, Simon; De Coppi, Paolo; Pierro, Agostino

    2012-02-01

    The purpose of this study is to evaluate (1) the predictive value of fetal bowel dilatation (FBD) for intestinal atresia in gastroschisis and (2) the postnatal management and outcome of this condition. A retrospective review of all gastroschisis cases diagnosed in our fetal medicine unit between 1992 and 2010 and treated postnatally in our center was performed. One hundred thirty cases had full postnatal data available. Intestinal atresia was found at surgery in 14 neonates (jejunum, n = 6; ileum, n = 3; ascending colon, n = 3; multiple, n = 2). Polyhydramnios and FBD were more likely in the atresia group compared with infants with no atresia (P = .0003 and P = .005, respectively). Fetal bowel dilatation had 99% negative predictive value (95% confidence interval, 0.9-0.99) and 17% positive predictive value (95% confidence interval, 0.1-0.3) for atresia. Treatment of intestinal atresia included primary anastomosis (n = 5), delayed anastomosis (n = 2), and stoma formation followed by anastomosis (n = 7). Infants with atresia had longer duration of parenteral nutrition, higher incidence of sepsis, and cholestasis compared with infants with no atresia (P = .0003). However, the presence of atresia did not increase mortality. Polyhydramnios and FBD are associated with atresia. Absence of FBD in gastroschisis excludes intestinal atresia. In our experience, atresia is associated with a longer duration of parenteral nutrition but does not influence mortality. These findings may be relevant for antenatal counseling. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Hyperdense basilar artery sign diagnoses acute posterior circulation stroke and predicts short-term outcome

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Xiaoping [Affiliated Hospital of China Medical University at Shenyang, Department of Neurology, Shengjing Hospital, Shenyang (China); Guo, Yang [Shengjing Hospital, Department of Neurology, Shenyang (China)

    2010-12-15

    It is well established that the hyperdense middle cerebral artery sign is a specific marker for early ischemia in anterior circulation. However, little is known about the hyperdense basilar artery sign (HDBA) in posterior circulation. Our aim was to determine whether the HDBA sign has utility in early diagnosis of acute posterior circulation stroke and prediction of short-term outcome. Three-blinded readers examined unenhanced computed tomography scans for the HDBA sign, and materials were classified into two groups according to this sign. Vascular risk factors, admission and discharge National Institute of Health Stroke Scale (NIHSS) scores, short-term outcome, and radiological findings between the two groups were compared. One hundred and twenty-six cases of acute posterior circulation stroke (PCS) were included in the study. No statistically significant differences were found in risk factors of ischemic stroke, except atrial fibrillation (P = 0.025). Admission and discharge NIHSS scores for the positive HDBA group were significantly higher than scores for the negative HDBA group (P = 0.001, 0.002, respectively). The infarction territory for the positive HDBA group was mainly multi-region in nature (51.6%, P < 0.001), while the negative HDBA group showed mainly middle territory infarction. Significant independent predictors of short-term outcome included the HDBA sign (P < 0.001) and admission NIHSS scores (P < 0.001). Approximately half of the HDBA patients showed multi-region infarction and a serious neurological symptom. Based on our results, this sign might not only be helpful in early diagnosis of acute PCS but also be able to correlate with a poor short-term outcome. (orig.)

  5. A new nomogram for prediction of outcome of pediatric shock-wave lithotripsy.

    Science.gov (United States)

    Dogan, Hasan Serkan; Altan, Mesut; Citamak, Burak; Bozaci, Ali Cansu; Karabulut, Erdem; Tekgul, Serdar

    2015-04-01

    Despite the fact that shock-wave lithotripsy (SWL) remains a very good treatment option for smaller stones, it is being challenged by endourologic treatment modalities, which offer similar or even higher success rates in a shorter time, with minimal morbidity and invasiveness. The present study aimed to bring a new and practical insight in order to predict the outcomes of pediatric SWL and to provide objective information about pediatric SWL outcomes. To design a nomogram for predicting the outcomes of pediatric shock-wave lithotripsy. The study was conducted with a retrospective design and included 402 renal units who underwent SWL between January 2009 and August 2013. Patients with known cystine stone disease and cystinuria, with internal or external urinary diversion, were excluded. Analysis was performed on 383 renal units. Postoperative imaging was performed by plain abdominal graphy and ultrasonography with 3-month intervals. Patients who were completely free of stones were considered to be a success and statistical analysis was done regardingly Multivariate analysis was conducted by logistic regression analysis and a nomogram was developed. The male/female distribution was 216/167, with a mean age of 48 ± 40 months and a mean stone size of 9 ± 3.5 mm. The overall stone-free rate was 70% (270/383) and efficacy quotient was 0.57. Mean follow-up was 11 ± 11 months (3-54 months). The number of shock waves and amplitude of energy were higher in failed cases. Multivariate analysis showed that gender, stone size, number of stones, age, location of the stone, and history of previous intervention were found to be the independent prognostic factors for assessing the stone clearance rates. A nomogram was developed using these parameters. In this nomogram, the points achieved from each parameter are summed and total points correspond to the risk of failure in percent. A previous nomogram study by Onal et al. showed that younger age (predicted stone-free rate after a

  6. Predictive factors determining outcomes in pulseless limb in paediatric supracondylar fractures of humerus.

    Science.gov (United States)

    Chaturvedi, Hemant; Khanna, Vikram; Bhargava, Rakesh; Vaishya, Raju

    2018-03-01

    Amongst all the complications associated with paediatric supracondylar humerus fractures, significant vascular injury is reported in only 1% cases, of which, less than 1% develop Volkmann's ischemic contracture. This study evaluates factors, like delay in presentation of the injury, limb perfusion and pulse, in determining functional outcome in a supracondylar humerus fractures with pulseless limb. Twenty-one paediatric patients with a pulseless supracondylar humerus fracture presenting from 2012 to 2014 were included. The patients were divided into 3 groups with Group A (pulse returned post-reduction, n = 13), Group B (pink pulseless hand, n = 7) and Group C (white pulseless hand, n = 1). 11 patients in group A and 4 patients in Group B presented within 6 h. of injury while the remaining patients presented after 6 h. The primary outcome was vascular status as indicated by radial pulse and perfusion, and secondary outcomes included functional parameters assessed with Mayo Elbow Performance Score and Flynn criteria. Mean peripheral SpO2 in Group A patients was higher than Group B and Group C had a non-recordable oxygen saturation. Mean capillary refill time was more in Group A than Group B whereas in Group C patient had blanching and no capillary refill was seen. Mean Mayo Elbow Performance Score of Group A patients was highest as compared to Group B and Group C. Patients presenting within 6 h. of injury had a higher mean Mayo Elbow Performance score as compared to the patients presenting after 6 h of injury. Functional outcome as measured by Flynn Criteria was excellent in 13 patients. 6 patients had a good, 2 had fair outcome. A moderate negative corrélation (R = -0.5798) was seen between the time elapsed from the injury and the Mayo Elbow Performance score. Duration to presentation since injury, limb perfusion and presence of peripheral pulses seem to be important predictive factors determining the outcomes in pulseless supracondylar fracture humerus.

  7. T2-relaxometry predicts outcome of DBS in idiopathic Parkinson's disease.

    Science.gov (United States)

    Lönnfors-Weitzel, Tarja; Weitzel, Thilo; Slotboom, Johannes; Kiefer, Claus; Pollo, Claudio; Schüpbach, Michael; Oertel, Markus; Kaelin, Alain; Wiest, Roland

    2016-01-01

    Deep brain stimulation (DBS) nowadays is a well-established treatment of motor symptoms in Parkinson's disease. The subthalamic nucleus (STN) is a common target for DBS, because motor improvements have been shown to be superior to best medical therapy, if DBS electrodes have been appropriately positioned. DBS target identification can be assisted by MRI beyond structural imaging by spatially resolved measurement of T2-relaxation times (T2r). We pose the question, whether T2r of the STN is linked to the severity of the disease and whether outcome of DBS may be correlated to an asymmetric manifestation of the disease. Further, we investigated if abnormal T2r in the STN may be predictive for outcome of DBS. Twelve patients underwent preoperative MR imaging including a multi echo relaxometry sequence (3 Tesla, Siemens Medical Systems, Erlangen, Germany) ahead of DBS. T2r were determined for STN, substantia nigra (SN), red nucleus (RN) and centrum semiovale (CSO). Unified Parkinson's disease Rating Scale (UPDRS) scores were tested before and after DBS. Patients' T2r and deduced values representing left-right asymmetry of measurements were correlated with UPDRS scores and measures for outcome of DBS. Furthermore, patients' T2r were compared with T2r measurements in 12 healthy controls (HC). Patients' T2r for SN (mean 45.4 ms ± 4.4 ms) and STN (mean 56.4 ms ± 3.8 ms) were significantly shorter than T2r in HCs for SN (mean 60.7 ± 4.6) and STN (mean 66.1 ms ± 4.0 ms). While no mean T2r asymmetry was found in the SN, patients' mean T2r for STN showed a weakened left-right correlation (Pearson correlation coefficient 0.19 versus 0.72 in HC) indicating asymmetric degeneration. T2r asymmetry was not linked to the more severely affected hemisphere. The respective lower T2r within the left or right target region was significantly correlated to the outcome in terms of UPDRS III improvement in "off" state (Pearson correlation 0.82 corresponding to p ≪ 0

  8. Activation of the tryptophan/serotonin pathway is associated with severity and predicts outcomes in pneumonia: results of a long-term cohort study.

    Science.gov (United States)

    Meier, Marc A; Ottiger, Manuel; Vögeli, Alaadin; Steuer, Christian; Bernasconi, Luca; Thomann, Robert; Christ-Crain, Mirjam; Henzen, Christoph; Hoess, Claus; Zimmerli, Werner; Huber, Andreas; Mueller, Beat; Schuetz, Philipp

    2017-06-27

    As part of the immune defense during infection, an increase in enzyme activity of indoleamine 2,3-dioxygenase (IDO) leads to a breakdown of tryptophan to kynurenine. In previous animal studies, therapeutic antagonism of IDO resulted in reduced sepsis mortality. We investigated the prognostic ability of tryptophan, serotonin, kynurenine and IDO (represented by the ratio of kynurenine/tryptophan) to predict adverse clinical outcomes in patients with community-acquired pneumonia (CAP). We measured tryptophan, serotonin and kynurenine on admission plasma samples from CAP patients included in a previous multicenter trial by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We studied their association with inflammation (C-reactive protein), infection (procalcitonin) and clinical outcome. Mortality in the 268 included patients was 45% within 6 years of follow-up. IDO and kynurenine showed a strong positive correlation with markers of infection (procalcitonin) and inflammation (C-reactive protein) as well as sepsis and CAP severity scores. Tryptophan showed similar, but negative correlations. In a multivariate regression analysis adjusted for age and comorbidities, higher IDO activity and lower tryptophan levels were strongly associated with short-term adverse outcome defined as death and/or ICU admission within 30 days with adjusted odds ratios of 9.1 [95% confidence interval (CI) 1.4-59.5, p=0.021] and 0.11 (95% CI 0.02-0.70, p=0.021). Multivariate analysis did not reveal significant associations for kynurenine and serotonin. In hospitalized CAP patients, higher IDO activity and lower tryptophan levels independently predicted disease severity and short-term adverse outcome. Whether therapeutic modulation of IDO has positive effects on outcome needs further investigation.

  9. Aurora-A overexpression and aneuploidy predict poor outcome in serous ovarian carcinoma.

    Science.gov (United States)

    Lassus, Heini; Staff, Synnöve; Leminen, Arto; Isola, Jorma; Butzow, Ralf

    2011-01-01

    Aurora-A is a potential oncogene and therapeutic target in ovarian carcinoma. It is involved in mitotic events and overexpression leads to centrosome amplification and chromosomal instability. The objective of this study was to evaluate the clinical significance of Aurora-A and DNA ploidy in serous ovarian carcinoma. Serous ovarian carcinomas were analysed for Aurora-A protein by immunohistochemistry (n=592), Aurora-A copy number by CISH (n=169), Aurora-A mRNA by real-time PCR (n=158) and DNA ploidy by flowcytometry (n=440). Overexpression of Aurora-A was found in 27% of the tumors, cytoplasmic overexpression in 11% and nuclear in 17%. The cytoplasmic and nuclear overexpression were nearly mutually exclusive. Both cytoplasmic and nuclear overexpression were associated with shorter survival, high grade, high proliferation index and aberrant p53. Interestingly, only cytoplasmic expression was associated with aneuploidy and expression of phosphorylated Aurora-A. DNA ploidy was associated with poor patient outcome as well as aggressive clinicopathological parameters. In multivariate analysis, Aurora-A overexpression appeared as an independent prognostic factor for disease-free survival, together with grade, stage and ploidy. Aurora-A protein expression is strongly linked with poor patient outcome and aggressive disease characteristics, which makes Aurora-A a promising biomarker and a potential therapeutic target in ovarian carcinoma. Cytoplasmic and nuclear Aurora-A protein may have different functions. DNA aneuploidy is a strong predictor of poor prognosis in serous ovarian carcinoma. Copyright © 2010 Elsevier Inc. All rights reserved.

  10. Toward an MRI-based nomogram for the prediction of transperineal prostate biopsy outcome: A physician and patient decision tool.

    Science.gov (United States)

    Lee, Su-Min; Liyanage, Sidath H; Wulaningsih, Wahyu; Wolfe, Konrad; Carr, Thomas; Younis, Choudhry; Van Hemelrijck, Mieke; Popert, Rick; Acher, Peter

    2017-11-01

    To develop and internally validate a nomogram using biparametric magnetic resonance imaging (B-MRI)-derived variables for the prediction of prostate cancer at transperineal sector-guided prostate biopsy (TPSB). Consecutive patients referred to our institution with raised prostate-specific antigen (PSA), abnormal prostate examination, or persistent suspicion of prostate cancer after previous transrectal biopsy between July 2012 and November 2015 were reviewed from a prospective database. All patients underwent prebiopsy B-MRI with T2-weighted and diffusion-weighted imaging sequences, followed by 24 to 40 core TPSB with additional targeted cores using cognitive registration. Univariable and multivariable logistic regression analysis was used to determine predictors of prostate cancer outcomes. Multivariable coefficients were used to construct 2 MRI-based nomograms to predict any and significant (Gleason 4 or maximum cancer core length ≥6mm) prostate cancer at TPSB. Bootstrap resamples were used for internal validation. Accuracy was assessed by calculating the concordance index. In total, 615 men were included in the study. Prostate cancer was diagnosed in 317 (51.5%) men with significant cancer diagnosed in 237 (38.5%) men. Age, Prostate Imaging Reporting and Data System (PI-RADS) score, PSA, PSA density, and primary biopsy were predictors of prostate cancer at TPSB on univariable analysis (PPSA showed strong correlation with PSA density and was excluded. The remaining variables were all independent predictors of prostate cancer on multivariable analysis (P<0.0001) and used to generate the nomograms. Both nomograms showed good discrimination for prostate cancer, with a concordance index of 87% for any cancer and 92% for significant disease. Using a nomogram-derived probability threshold of<15%, 111 (18.0%) biopsies can be saved, at the expense of 3 missed significant prostate cancers. These internally validated MR-based nomograms were able to accurately predict

  11. Use of artificial neural networks to predict biological outcomes for patients receiving radical radiotherapy of the prostate

    International Nuclear Information System (INIS)

    Gulliford, Sarah L.; Webb, Steve; Rowbottom, Carl G.; Corne, David W.; Dearnaley, David P.

    2004-01-01

    Background and purpose: This paper discusses the application of artificial neural networks (ANN) in predicting biological outcomes following prostate radiotherapy. A number of model-based methods have been developed to correlate the dose distributions calculated for a patient receiving radiotherapy and the radiobiological effect this will produce. Most widely used are the normal tissue complication probability and tumour control probability models. An alternative method for predicting specific examples of tumour control and normal tissue complications is to use an ANN. One of the advantages of this method is that there is no need for a priori information regarding the relationship between the data being correlated. Patients and methods: A set of retrospective clinical data from patients who received radical prostate radiotherapy was used to train ANNs to predict specific biological outcomes by learning the relationship between the treatment plan prescription, dose distribution and the corresponding biological effect. The dose and volume were included as a differential dose-volume histogram in order to provide a holistic description of the available data. Results: It was shown that the ANNs were able to predict biochemical control and specific bladder and rectum complications with sensitivity and specificity of above 55% when the outcomes were dichotomised. It was also possible to analyse information from the ANNs to investigate the effect of individual treatment parameters on the outcome. Conclusion: ANNs have been shown to learn something of the complex relationship between treatment parameters and outcome which, if developed further, may prove to be a useful tool in predicting biological outcomes

  12. Symptoms of Depression Predict Negative Birth Outcomes in African American Women: A Pilot Study.

    Science.gov (United States)

    Giurgescu, Carmen; Engeland, Christopher G; Templin, Thomas N

    2015-01-01

    African American women have higher rates of preterm birth and low-birth-weight infants compared with non-Hispanic white women. Symptoms of depression have also been related to these negative birth outcomes. Lower levels of social support and higher levels of avoidance coping and cortisol have been related to more symptoms of depression in pregnant women. The purpose of this pilot study was to examine the relationships among symptoms of depression, social support, avoidance coping, cortisol, and negative birth outcomes (ie, preterm birth, low-birth-weight infants) in a sample of African American women. This study used a prospective design. A convenience sample of 90 African American women completed questionnaires and had blood drawn in the second trimester of pregnancy. Birth data were collected from medical records. Based on the Center for Epidemiological Studies-Depression (CES-D) Scale scores, 28% of women were at increased risk for clinical depression (CES-D ≥ 16). Compared to women who gave birth at term, women who had preterm birth had higher CES-D scores (11.67 and 19.0, respectively) and used avoidance coping more often (7.98 and 13.14, respectively). Compared to women with normal-birth-weight infants, women with low-birth-weight infants had higher levels of cortisol (61.75 mcg/dL and 89.72 mcg/dL, respectively). Women at increased risk for clinical depression were 16 times more likely to have preterm birth and 4 times more likely to have low-birth-weight infants. Women with plasma cortisol levels in the top 25th percentile were 7 times more likely to have low-birth-weight infants. Preeclampsia during pregnancy also predicted preterm birth and low-birth-weight infants. Symptoms of depression in pregnancy may predict adverse birth outcomes. Interventions that have the potential to improve the mental health of pregnant women and ultimately birth outcomes need to be explored. © 2015 by the American College of Nurse-Midwives.

  13. Comparison of the APACHE II, GCS and MRC scores in predicting outcomes in patients with tuberculous meningitis.

    Science.gov (United States)

    Chou, C-H; Lin, G-M; Ku, C-H; Chang, F-Y

    2010-01-01

    To evaluate different scoring systems, including Acute Physiology and Chronic Health Evaluation (APACHE) II, the Glasgow Coma Scale (GCS) and the Medical Research Council (MRC) staging system, as well as other prognostic factors, in predicting the discharge outcomes of adult patients with tuberculous meningitis (TBM). We conducted a retrospective analysis of patients admitted with a diagnosis of TBM to a tertiary hospital in northern Taiwan from March 1996 to February 2006. We used APACHE II, GCS, MRC and a variety of factors within 24 h of admission to predict discharge outcomes recorded by the Glasgow Outcome Scale (GOS). Among 43 TBM patients, 33 had a favourable outcome (GOS 4-5), and 10 had an unfavourable outcome (GOS 1-3). The severity of APACHE II, GCS, MRC and presence of hydrocephalus correlated well with the neurological outcomes (P MRC in receiver operating characteristic analysis. Furthermore, in-hospital mortality could be predicted accurately with APACHE II and GCS. The APACHE II scoring system is at least as effective as GCS and superior to MRC in predicting the discharge outcomes of adult patients with TBM.

  14. Preschool speech intelligibility and vocabulary skills predict long-term speech and language outcomes following cochlear implantation in early childhood.

    Science.gov (United States)

    Castellanos, Irina; Kronenberger, William G; Beer, Jessica; Henning, Shirley C; Colson, Bethany G; Pisoni, David B

    2014-07-01

    Speech and language measures during grade school predict adolescent speech-language outcomes in children who receive cochlear implants (CIs), but no research has examined whether speech and language functioning at even younger ages is predictive of long-term outcomes in this population. The purpose of this study was to examine whether early preschool measures of speech and language performance predict speech-language functioning in long-term users of CIs. Early measures of speech intelligibility and receptive vocabulary (obtained during preschool ages of 3-6 years) in a sample of 35 prelingually deaf, early-implanted children predicted speech perception, language, and verbal working memory skills up to 18 years later. Age of onset of deafness and age at implantation added additional variance to preschool speech intelligibility in predicting some long-term outcome scores, but the relationship between preschool speech-language skills and later speech-language outcomes was not significantly attenuated by the addition of these hearing history variables. These findings suggest that speech and language development during the preschool years is predictive of long-term speech and language functioning in early-implanted, prelingually deaf children. As a result, measures of speech-language functioning at preschool ages can be used to identify and adjust interventions for very young CI users who may be at long-term risk for suboptimal speech and language outcomes.

  15. Highly accurate prediction of food challenge outcome using routinely available clinical data.

    Science.gov (United States)

    DunnGalvin, Audrey; Daly, Deirdre; Cullinane, Claire; Stenke, Emily; Keeton, Diane; Erlewyn-Lajeunesse, Mich; Roberts, Graham C; Lucas, Jane; Hourihane, Jonathan O'B

    2011-03-01

    Serum specific IgE or skin prick tests are less useful at levels below accepted decision points. We sought to develop and validate a model to predict food challenge outcome by using routinely collected data in a diverse sample of children considered suitable for food challenge. The proto-algorithm was generated by using a limited data set from 1 service (phase 1). We retrospectively applied, evaluated, and modified the initial model by using an extended data set in another center (phase 2). Finally, we prospectively validated the model in a blind study in a further group of children undergoing food challenge for peanut, milk, or egg in the second center (phase 3). Allergen-specific models were developed for peanut, egg, and milk. Phase 1 (N = 429) identified 5 clinical factors associated with diagnosis of food allergy by food challenge. In phase 2 (N = 289), we examined the predictive ability of 6 clinical factors: skin prick test, serum specific IgE, total IgE minus serum specific IgE, symptoms, sex, and age. In phase 3 (N = 70), 97% of cases were accurately predicted as positive and 94% as negative. Our model showed an advantage in clinical prediction compared with serum specific IgE only, skin prick test only, and serum specific IgE and skin prick test (92% accuracy vs 57%, and 81%, respectively). Our findings have implications for the improved delivery of food allergy-related health care, enhanced food allergy-related quality of life, and economized use of health service resources by decreasing the number of food challenges performed. Copyright © 2011 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

  16. Predictive markers of clinical outcome in the GRMD dog model of Duchenne muscular dystrophy

    Science.gov (United States)

    Barthélémy, Inès; Pinto-Mariz, Fernanda; Yada, Erica; Desquilbet, Loïc; Savino, Wilson; Silva-Barbosa, Suse Dayse; Faussat, Anne-Marie; Mouly, Vincent; Voit, Thomas; Blot, Stéphane; Butler-Browne, Gillian

    2014-01-01

    In the translational process of developing innovative therapies for DMD (Duchenne muscular dystrophy), the last preclinical validation step is often carried out in the most relevant animal model of this human disease, namely the GRMD (Golden Retriever muscular dystrophy) dog. The disease in GRMD dogs mimics human DMD in many aspects, including the inter-individual heterogeneity. This last point can be seen as a drawback for an animal model but is inherently related to the disease in GRMD dogs closely resembling that of individuals with DMD. In order to improve the management of this inter-individual heterogeneity, we have screened a combination of biomarkers in sixty-one 2-month-old GRMD dogs at the onset of the disease and a posteriori we addressed their predictive value on the severity of the disease. Three non-invasive biomarkers obtained at early stages of the disease were found to be highly predictive for the loss of ambulation before 6 months of age. An elevation in the number of circulating CD4+CD49dhi T cells and a decreased stride frequency resulting in a reduced spontaneous speed were found to be strongly associated with the severe clinical form of the disease. These factors can be used as predictive tests to screen dogs to separate them into groups with slow or fast disease progression before their inclusion into a therapeutic preclinical trial, and therefore improve the reliability and translational value of the trials carried out on this invaluable large animal model. These same biomarkers have also been described to be predictive for the time to loss of ambulation in boys with DMD, strengthening the relevance of GRMD dogs as preclinical models of this devastating muscle disease. PMID:25261568

  17. Fetal Stomach Position Predicts Neonatal Outcomes in Isolated Left-Sided Congenital Diaphragmatic Hernia.

    Science.gov (United States)

    Basta, Amaya M; Lusk, Leslie A; Keller, Roberta L; Filly, Roy A

    2016-01-01

    We sought to determine the relationship between the degree of stomach herniation by antenatal sonography and neonatal outcomes in fetuses with isolated left-sided congenital diaphragmatic hernia (CDH). We retrospectively reviewed neonatal medical records and antenatal sonography of fetuses with isolated left CDH cared for at a single institution (2000-2012). Fetal stomach position was classified on sonography as follows: intra-abdominal, anterior left chest, mid-to-posterior left chest, or retrocardiac (right chest). Ninety fetuses were included with 70% surviving to neonatal discharge. Stomach position was intra-abdominal in 14% (n = 13), anterior left chest in 19% (n = 17), mid-to-posterior left chest in 41% (n = 37), and retrocardiac in 26% (n = 23). Increasingly abnormal stomach position was linearly associated with an increased odds of death (OR 4.8, 95% CI 2.1-10.9), extracorporeal membrane oxygenation (ECMO; OR 5.6, 95% CI 1.9-16.7), nonprimary diaphragmatic repair (OR 2.7, 95% CI 1.4-5.5), prolonged mechanical ventilation (OR 5.9, 95% CI 2.3-15.6), and prolonged respiratory support (OR 4.0, 95% CI 1.6-9.9). All fetuses with intra-abdominal stomach position survived without substantial respiratory morbidity or need for ECMO. Fetal stomach position is strongly associated with neonatal outcomes in isolated left CDH. This objective tool may allow for accurate prognostication in a variety of clinical settings. © 2015 S. Karger AG, Basel.

  18. Predicting outcomes in glioblastoma patients using computerized analysis of tumor shape: preliminary data

    Science.gov (United States)

    Mazurowski, Maciej A.; Czarnek, Nicholas M.; Collins, Leslie M.; Peters, Katherine B.; Clark, Kal

    2016-03-01

    Glioblastoma (GBM) is the most common primary brain tumor characterized by very poor survival. However, while some patients survive only a few months, some might live for multiple years. Accurate prognosis of survival and stratification of patients allows for making more personalized treatment decisions and moves treatment of GBM one step closer toward the paradigm of precision medicine. While some molecular biomarkers are being investigated, medical imaging remains significantly underutilized for prognostication in GBM. In this study, we investigated whether computer analysis of tumor shape can contribute toward accurate prognosis of outcomes. Specifically, we implemented applied computer algorithms to extract 5 shape features from magnetic resonance imaging (MRI) for 22 GBM patients. Then, we determined whether each one of the features can accurately distinguish between patients with good and poor outcomes. We found that that one of the 5 analyzed features showed prognostic value of survival. The prognostic feature describes how well the 3D tumor shape fills its minimum bounding ellipsoid. Specifically, for low values (less or equal than the median) the proportion of patients that survived more than a year was 27% while for high values (higher than median) the proportion of patients with survival of more than 1 year was 82%. The difference was statistically significant (p < 0.05) even though the number of patients analyzed in this pilot study was low. We concluded that computerized, 3D analysis of tumor shape in MRI may strongly contribute to accurate prognostication and stratification of patients for therapy in GBM.

  19. Body image dissatisfaction in pregnant and non-pregnant females is strongly predicted by immune activation and mucosa-derived activation of the tryptophan catabolite (TRYCAT) pathway.

    Science.gov (United States)

    Roomruangwong, Chutima; Kanchanatawan, Buranee; Carvalho, André F; Sirivichayakul, Sunee; Duleu, Sebastien; Geffard, Michel; Maes, Michael

    2018-04-01

    The aim of the present study is to delineate the associations between body image dissatisfaction in pregnant women and immune-inflammatory biomarkers, i.e., C-reactive protein (CRP), zinc and IgA/IgM responses to tryptophan and tryptophan catabolites (TRYCATs). We assessed 49 pregnant and 24 non-pregnant females and assessed Body Image Satisfaction (BIS) scores at the end of term (T1), and 2-4 days (T2) and 4-6 weeks (T3) after delivery. Subjects were divided in those with a lowered BIS score (≤ 3) versus those with a higher score. Logistic regression analysis showed that a lowered T1 BIS score was predicted by CRP levels and IgA responses to tryptophan (negative) and TRYCATs (positive), perinatal depression, body mass index (BMI) and age. The sum of quinolinic acid, kynurenine, 3-OH-kynurenine and 3-OH-anthranilic acid (reflecting brain quinolinic acid contents) was the single best predictor. In addition, a large part of the variance in the T1, T2 and T3 BIS scores was explained by IgA responses to tryptophan and TRYCATs, especially quinolinic acid. Body image dissatisfaction is strongly associated with inflammation and mucosa-derived IDO activation independently from depression, pregnancy, BMI and age. IgA responses to peripheral TRYCATs, which determine brain quinolinic acid concentrations, also predict body image dissatisfaction.

  20. THE SYSTEMATICS OF STRONG LENS MODELING QUANTIFIED: THE EFFECTS OF CONSTRAINT SELECTION AND REDSHIFT INFORMATION ON MAGNIFICATION, MASS, AND MULTIPLE IMAGE PREDICTABILITY

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, Traci L.; Sharon, Keren, E-mail: tljohn@umich.edu [University of Michigan, Department of Astronomy, 1085 South University Avenue, Ann Arbor, MI 48109-1107 (United States)

    2016-11-20

    Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading as to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.

  1. Predictability of motor outcome according to the time of diffusion tensor imaging in patients with cerebral infarct

    International Nuclear Information System (INIS)

    Kwon, Yong Hyun; Jeoung, Yong Jae; Lee, Jun; Son, Su Min; Jang, Sung Ho; Kim, Saeyoon; Kim, Chulseung

    2012-01-01

    Predictability of diffusion tensor imaging tractography (DTT) for motor outcome can differ according to the time of DTT. We attempted to compare the predictability for motor outcome according to the time of diffusion tensor imaging (DTI) by analyzing the corticospinal tract (CST) integrity on DTT in patients with corona radiata (CR) infarct. Seventy-one consecutive hemiparetic patients with CR infarct were recruited. Motor function of the affected extremities was measured twice: at onset and at 6 months from onset. According to the time of DTI, patients were classified into two groups: the early scanning group (ES group) within 14 days since stroke onset; and the late scanning group (LS group) 15-28 days. Motor outcome was compared with the CST integrity on DTT. Motor prognosis was predicted from scan time of DTI and the CST integrity on DTT in the logistic regression model. According to separate regression analysis, the CST integrity of the late group was found to predict MI score (OR = 14.000, 95% CI = 3.194-61.362, p < 0.05), whereas the CST integrity of the early group was not found to predict MI score. In terms of both positive and negative predictabilities, we found that predictability of DTT for motor outcome was better in patients who were scanned later (15-28 days after onset) than in patients who were scanned earlier (1-14 days after onset). (orig.)

  2. Predictability of motor outcome according to the time of diffusion tensor imaging in patients with cerebral infarct

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Yong Hyun [Yeungnam College of Science and Technology, Department of Physical Therapy, Taegu (Korea, Republic of); Jeoung, Yong Jae [Yeungnam University, Department of Physical Medicine and Rehabilitation, College of Medicine, Taegu (Korea, Republic of); Lee, Jun [Yeungnam University, Department of Neurology, College of Medicine, Taegu (Korea, Republic of); Son, Su Min; Jang, Sung Ho [Yeungnam University 317-1, Department of Physical Medicine and Rehabilitation, College of Medicine, Taegu (Korea, Republic of); Kim, Saeyoon [Yeungnam University, Department of Pediatrics, College of Medicine, Taegu (Korea, Republic of); Kim, Chulseung [Medical Devices Clinical Trial Center of Yeungnam University Hospital, Taegu (Korea, Republic of)

    2012-07-15

    Predictability of diffusion tensor imaging tractography (DTT) for motor outcome can differ according to the time of DTT. We attempted to compare the predictability for motor outcome according to the time of diffusion tensor imaging (DTI) by analyzing the corticospinal tract (CST) integrity on DTT in patients with corona radiata (CR) infarct. Seventy-one consecutive hemiparetic patients with CR infarct were recruited. Motor function of the affected extremities was measured twice: at onset and at 6 months from onset. According to the time of DTI, patients were classified into two groups: the early scanning group (ES group) within 14 days since stroke onset; and the late scanning group (LS group) 15-28 days. Motor outcome was compared with the CST integrity on DTT. Motor prognosis was predicted from scan time of DTI and the CST integrity on DTT in the logistic regression model. According to separate regression analysis, the CST integrity of the late group was found to predict MI score (OR = 14.000, 95% CI = 3.194-61.362, p < 0.05), whereas the CST integrity of the early group was not found to predict MI score. In terms of both positive and negative predictabilities, we found that predictability of DTT for motor outcome was better in patients who were scanned later (15-28 days after onset) than in patients who were scanned earlier (1-14 days after onset). (orig.)

  3. Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes.

    Science.gov (United States)

    Tu, J V

    1996-11-01

    Artificial neural networks are algorithms that can be used to perform nonlinear statistical modeling and provide a new alternative to logistic regression, the most commonly used method for developing predictive models for dichotomous outcomes in medicine. Neural networks offer a number of advantages, including requiring less formal statistical training, ability to implicitly detect complex nonlinear relationships between dependent and independent variables, ability to detect all possible interactions between predictor variables, and the availability of multiple training algorithms. Disadvantages include its "black box" nature, greater computational burden, proneness to overfitting, and the empirical nature of model development. An overview of the features of neural networks and logistic regression is presented, and the advantages and disadvantages of using this modeling technique are discussed.

  4. A histopathological score on baseline biopsies from elderly donors predicts outcome 1 year after renal transplantation

    DEFF Research Database (Denmark)

    Toft, Birgitte G; Federspiel, Birgitte H; Sørensen, Søren S

    2012-01-01

    Kidneys from elderly deceased patients and otherwise marginal donors may be considered for transplantation and a pretransplantation histopathological score for prediction of postoperative outcome is warranted. In a retrospective design, 29 baseline renal needle biopsies from elderly deceased donors...... wall thickness of arteries and/or arterioles. Nineteen renal baseline biopsies from 15 donors (age: 64 ± 10 years) were included and following consensus the histopathological score was 4.3 ± 2.1 (intraclass correlation coefficient: 0.81; confidence interval: 0.66-0.92). The donor organs were used...... for single renal transplantation (recipient age: 47 ± 3 years). Two grafts were lost after the transplantation. In the remaining 17 recipients the 1-year creatinine clearance (54 ± 6 mL/min) correlated to the baseline histopathological score (r(2) = 0.59; p

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

    Science.gov (United States)

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

    2017-06-01

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

  6. Empirically derived pain-patient MMPI subgroups: prediction of treatment outcome.

    Science.gov (United States)

    Moore, J E; Armentrout, D P; Parker, J C; Kivlahan, D R

    1986-02-01

    Fifty-seven male chronic pain patients admitted to an inpatient multimodal pain treatment program at a Midwestern Veterans Administration hospital completed the MMPI, Profile of Mood States (POMS), Tennessee Self-Concept Scale (TSCS), Rathus Assertiveness Schedule (RAS), activity diaries, and an extensive pain questionnaire. All patients were assessed both before and after treatment, and most also were assessed 2-5 months prior to treatment. No significant changes occurred during the baseline period, but significant improvements were evident at posttreatment on most variables: MMPI, POMS, TSCS, RAS, pain severity, sexual functioning, and activity diaries. MMPI subgroup membership, based on a hierarchical cluster analysis in a larger sample, was not predictive of differential treatment outcome. Possible reasons for comparable treatment gains among these subgroups, which previously have been shown to differ on many psychological and behavioral factors, are discussed.

  7. Velocity ratio predicts outcomes in patients with low gradient severe aortic stenosis and preserved EF

    DEFF Research Database (Denmark)

    Jander, Nikolaus; Hochholzer, Willibald; Kaufmann, Beat A

    2014-01-01

    OBJECTIVE: To evaluate the usefulness of velocity ratio (VR) in patients with low gradient severe aortic stenosis (LGSAS) and preserved EF. BACKGROUND: LGSAS despite preserved EF represents a clinically challenging entity. Reliance on mean pressure gradient (MPG) may underestimate stenosis severity...... for severe stenosis. We hypothesised that VR may have conceptual advantages over MPG and AVA, predict clinical outcomes and thereby be useful in the management of patients with LGSAS. METHODS: Patients from the prospective Simvastatin and Ezetimibe in Aortic Stenosis (SEAS) study with an AVA....25 suggesting non-severe stenosis. Aortic valve-related events (mean follow-up 42±14 months) were more frequent in patients with VRanalysis, MPG was the strongest independent predictor...

  8. Symptomless Multi-Variable Apnea Prediction Index Assesses Obstructive Sleep Apnea Risk and Adverse