WorldWideScience

Sample records for demonstrated predictive validity

  1. Job Embeddedness Demonstrates Incremental Validity When Predicting Turnover Intentions for Australian University Employees

    Science.gov (United States)

    Heritage, Brody; Gilbert, Jessica M.; Roberts, Lynne D.

    2016-01-01

    Job embeddedness is a construct that describes the manner in which employees can be enmeshed in their jobs, reducing their turnover intentions. Recent questions regarding the properties of quantitative job embeddedness measures, and their predictive utility, have been raised. Our study compared two competing reflective measures of job embeddedness, examining their convergent, criterion, and incremental validity, as a means of addressing these questions. Cross-sectional quantitative data from 246 Australian university employees (146 academic; 100 professional) was gathered. Our findings indicated that the two compared measures of job embeddedness were convergent when total scale scores were examined. Additionally, job embeddedness was capable of demonstrating criterion and incremental validity, predicting unique variance in turnover intention. However, this finding was not readily apparent with one of the compared job embeddedness measures, which demonstrated comparatively weaker evidence of validity. We discuss the theoretical and applied implications of these findings, noting that job embeddedness has a complementary place among established determinants of turnover intention. PMID:27199817

  2. Marketing Plan for Demonstration and Validation Assets

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    2008-05-30

    The National Security Preparedness Project (NSPP), is to be sustained by various programs, including technology demonstration and evaluation (DEMVAL). This project assists companies in developing technologies under the National Security Technology Incubator program (NSTI) through demonstration and validation of technologies applicable to national security created by incubators and other sources. The NSPP also will support the creation of an integrated demonstration and validation environment. This report documents the DEMVAL marketing and visibility plan, which will focus on collecting information about, and expanding the visibility of, DEMVAL assets serving businesses with national security technology applications in southern New Mexico.

  3. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  4. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  5. Verification, validation, and reliability of predictions

    International Nuclear Information System (INIS)

    Pigford, T.H.; Chambre, P.L.

    1987-04-01

    The objective of predicting long-term performance should be to make reliable determinations of whether the prediction falls within the criteria for acceptable performance. Establishing reliable predictions of long-term performance of a waste repository requires emphasis on valid theories to predict performance. The validation process must establish the validity of the theory, the parameters used in applying the theory, the arithmetic of calculations, and the interpretation of results; but validation of such performance predictions is not possible unless there are clear criteria for acceptable performance. Validation programs should emphasize identification of the substantive issues of prediction that need to be resolved. Examples relevant to waste package performance are predicting the life of waste containers and the time distribution of container failures, establishing the criteria for defining container failure, validating theories for time-dependent waste dissolution that depend on details of the repository environment, and determining the extent of congruent dissolution of radionuclides in the UO 2 matrix of spent fuel. Prediction and validation should go hand in hand and should be done and reviewed frequently, as essential tools for the programs to design and develop repositories. 29 refs

  6. Validation of Sizewell ''B'' ultrasonic inspections -- Messages for performance demonstration

    International Nuclear Information System (INIS)

    Conroy, P.J.; Leyland, K.S.; Waites, C.

    1994-01-01

    At the time that the decisions leading to the construction of the Sizewell ''B'' plant were being made, public concern over the potential hazards of nuclear power was increasing. This concern was heightened by the accident at USA's Three Mile Island plant. The result of this and public pressure was that an extensive public inquiry was held in addition to the UK's normal licensing process. Part of the evidence to the inquiry supporting the safety case relied upon the ability of ultrasonic inspections to demonstrate that the Reactor Pressure Vessel (RPV) and other key components were free from defects that could threaten structural integrity. Evidence from a variety of trials designed to investigate the performance capability of ultrasonic inspection revealed that although ultrasonic inspection had the potential to satisfy this requirement its performance in practice was heavily dependent upon the details of application. It was therefore generally recognized that some form of inspection validation was required to provide assurance that the equipment, procedures and operators to be employed were adequate for purpose. The concept of inspection validation was therefore included in the safety case for the licensing of Sizewell ''B''. The UK validation trials covering the ultrasonic inspections of the Sizewell ''B'' PWR Reactor Pressure Vessel are now nearing completion. This paper summarizes the results of the RPV validations and considers some of the implications for ASME 11 Appendix 8 the US code covering performance demonstration

  7. Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project

    Energy Technology Data Exchange (ETDEWEB)

    Stottler, Gary

    2012-02-08

    General Motors, LLC and energy partner Shell Hydrogen, LLC, deployed a system of hydrogen fuel cell electric vehicles integrated with a hydrogen fueling station infrastructure to operate under real world conditions as part of the U.S. Department of Energy's Controlled Hydrogen Fleet and Infrastructure Validation and Demonstration Project. This technical report documents the performance and describes the learnings from progressive generations of vehicle fuel cell system technology and multiple approaches to hydrogen generation and delivery for vehicle fueling.

  8. SP-100 from ground demonstration to flight validation

    International Nuclear Information System (INIS)

    Buden, D.

    1989-01-01

    The SP-100 program is in the midst of developing and demonstrating the technology of a liquid-metal-cooled fast reactor using thermoelectric thermal-to-electric conversion devices for space power applications in the range of tens to hundreds of kilowatts. The current ground engineering system (GES) design and development phase will demonstrate the readiness of the technology building blocks and the system to proceed to flight system validation. This phase includes the demonstration of a 2.4-MW(thermal) reactor in the nuclear assembly test (NAT) and aerospace subsystem in the integrated assembly test (IAT). The next phase in the SP-100 development, now being planned, is to be a flight demonstration of the readiness of the technology to be incorporated into future military and civilian missions. This planning will answer questions concerning the logical progression of the GES to the flight validation experiment. Important issues in planning the orderly transition include answering the need to plan for a second reactor ground test, the method to be used to test the SP-100 for acceptance for flight, the need for the IAT prior to the flight-test configuration design, the efficient use of facilities for GES and the flight experiment, and whether the NAT should be modified based on flight experiment planning

  9. Darcy Tools version 3.4. Verification, validation and demonstration

    International Nuclear Information System (INIS)

    Svensson, Urban

    2010-12-01

    DarcyTools is a computer code for simulation of flow and transport in porous and/or fractured media. The fractured media in mind is a fractured rock and the porous media the soil cover on the top of the rock; it is hence groundwater flows, which is the class of flows in mind. A number of novel methods and features form the present version of DarcyTools. In the verification studies, these methods are evaluated by comparisons with analytical solutions for idealized situations. The five verification groups (see Table 3-1 below), thus reflect the scope of DarcyTools. The present report will focus on the Verification, Validation and Demonstration of DarcyTools. Two accompanying reports cover other aspects: - Concepts, Methods and Equations, /Svensson et al. 2010/ (Hereafter denoted Report 1). - User's Guide, /Svensson and Ferry 2010/ (Hereafter denoted Report 2)

  10. Darcy Tools version 3.4. Verification, validation and demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Urban (Computer-aided Fluid Engineering AB, Lyckeby (Sweden))

    2010-12-15

    DarcyTools is a computer code for simulation of flow and transport in porous and/or fractured media. The fractured media in mind is a fractured rock and the porous media the soil cover on the top of the rock; it is hence groundwater flows, which is the class of flows in mind. A number of novel methods and features form the present version of DarcyTools. In the verification studies, these methods are evaluated by comparisons with analytical solutions for idealized situations. The five verification groups (see Table 3-1 below), thus reflect the scope of DarcyTools. The present report will focus on the Verification, Validation and Demonstration of DarcyTools. Two accompanying reports cover other aspects: - Concepts, Methods and Equations, /Svensson et al. 2010/ (Hereafter denoted Report 1). - User's Guide, /Svensson and Ferry 2010/ (Hereafter denoted Report 2)

  11. The Predictive Validity of Projective Measures.

    Science.gov (United States)

    Suinn, Richard M.; Oskamp, Stuart

    Written for use by clinical practitioners as well as psychological researchers, this book surveys recent literature (1950-1965) on projective test validity by reviewing and critically evaluating studies which shed light on what may reliably be predicted from projective test results. Two major instruments are covered: the Rorschach and the Thematic…

  12. Pulsatile fluidic pump demonstration and predictive model application

    International Nuclear Information System (INIS)

    Morgan, J.G.; Holland, W.D.

    1986-04-01

    Pulsatile fluidic pumps were developed as a remotely controlled method of transferring or mixing feed solutions. A test in the Integrated Equipment Test facility demonstrated the performance of a critically safe geometry pump suitable for use in a 0.1-ton/d heavy metal (HM) fuel reprocessing plant. A predictive model was developed to calculate output flows under a wide range of external system conditions. Predictive and experimental flow rates are compared for both submerged and unsubmerged fluidic pump cases

  13. Predictive validity of the Slovene Matura

    Directory of Open Access Journals (Sweden)

    Valentin Bucik

    2001-09-01

    Full Text Available Passing Matura is the last step of the secondary school graduation, but it is also the entrance ticket for the university. Besides, the summary score of Matura exam takes part in the selection process for the particular university studies in case of 'numerus clausus'. In discussing either aim of Matura important dilemmas arise, namely, is the Matura examination sufficiently exact and rightful procedure to, firstly, use its results for settling starting studying conditions and, secondly, to select validly, reliably and sensibly the best candidates for university studies. There are some questions concerning predictive validity of Matura that should be answered, e.g. (i does Matura as an enrollment procedure add to the qualitaty of the study; (ii is it a better selection tool than entrance examinations formerly used in different faculties in the case of 'numerus clausus'; and (iii is it reasonable to expect high predictive validity of Matura results for success at the university at all. Recent results show that in the last few years the dropout-rate is lower than before, the pass-rate between the first and the second year is higher and the average duration of study per student is shorter. It is clear, however, that it is not possible to simply predict the study success from the Matura results. There are too many factors influencing the success in the university studies. In most examined study programs the correlation between Matura results and study success is positive but moderate, therefore it can not be said categorically that only candidates accepted according to the Matura results are (or will be the best students. Yet it has been shown that Matura is a standardized procedure, comparable across different candidates entering university, and that – when compared entrance examinations – it is more objective, reliable, and hen ce more valid and fair a procedure. In addition, comparable procedures of university recruiting and selection can be

  14. The predictive validity of safety climate.

    Science.gov (United States)

    Johnson, Stephen E

    2007-01-01

    Safety professionals have increasingly turned their attention to social science for insight into the causation of industrial accidents. One social construct, safety climate, has been examined by several researchers [Cooper, M. D., & Phillips, R. A. (2004). Exploratory analysis of the safety climate and safety behavior relationship. Journal of Safety Research, 35(5), 497-512; Gillen, M., Baltz, D., Gassel, M., Kirsch, L., & Vacarro, D. (2002). Perceived safety climate, job Demands, and coworker support among union and nonunion injured construction workers. Journal of Safety Research, 33(1), 33-51; Neal, A., & Griffin, M. A. (2002). Safety climate and safety behaviour. Australian Journal of Management, 27, 66-76; Zohar, D. (2000). A group-level model of safety climate: Testing the effect of group climate on microaccidents in manufacturing jobs. Journal of Applied Psychology, 85(4), 587-596; Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628] who have documented its importance as a factor explaining the variation of safety-related outcomes (e.g., behavior, accidents). Researchers have developed instruments for measuring safety climate and have established some degree of psychometric reliability and validity. The problem, however, is that predictive validity has not been firmly established, which reduces the credibility of safety climate as a meaningful social construct. The research described in this article addresses this problem and provides additional support for safety climate as a viable construct and as a predictive indicator of safety-related outcomes. This study used 292 employees at three locations of a heavy manufacturing organization to complete the 16 item Zohar Safety Climate Questionnaire (ZSCQ) [Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group

  15. CFD Validation Studies for Hypersonic Flow Prediction

    Science.gov (United States)

    Gnoffo, Peter A.

    2001-01-01

    A series of experiments to measure pressure and heating for code validation involving hypersonic, laminar, separated flows was conducted at the Calspan-University at Buffalo Research Center (CUBRC) in the Large Energy National Shock (LENS) tunnel. The experimental data serves as a focus for a code validation session but are not available to the authors until the conclusion of this session. The first set of experiments considered here involve Mach 9.5 and Mach 11.3 N2 flow over a hollow cylinder-flare with 30 degree flare angle at several Reynolds numbers sustaining laminar, separated flow. Truncated and extended flare configurations are considered. The second set of experiments, at similar conditions, involves flow over a sharp, double cone with fore-cone angle of 25 degrees and aft-cone angle of 55 degrees. Both sets of experiments involve 30 degree compressions. Location of the separation point in the numerical simulation is extremely sensitive to the level of grid refinement in the numerical predictions. The numerical simulations also show a significant influence of Reynolds number on extent of separation. Flow unsteadiness was easily introduced into the double cone simulations using aggressive relaxation parameters that normally promote convergence.

  16. Cross-Validation of Aerobic Capacity Prediction Models in Adolescents.

    Science.gov (United States)

    Burns, Ryan Donald; Hannon, James C; Brusseau, Timothy A; Eisenman, Patricia A; Saint-Maurice, Pedro F; Welk, Greg J; Mahar, Matthew T

    2015-08-01

    Cardiorespiratory endurance is a component of health-related fitness. FITNESSGRAM recommends the Progressive Aerobic Cardiovascular Endurance Run (PACER) or One mile Run/Walk (1MRW) to assess cardiorespiratory endurance by estimating VO2 Peak. No research has cross-validated prediction models from both PACER and 1MRW, including the New PACER Model and PACER-Mile Equivalent (PACER-MEQ) using current standards. The purpose of this study was to cross-validate prediction models from PACER and 1MRW against measured VO2 Peak in adolescents. Cardiorespiratory endurance data were collected on 90 adolescents aged 13-16 years (Mean = 14.7 ± 1.3 years; 32 girls, 52 boys) who completed the PACER and 1MRW in addition to a laboratory maximal treadmill test to measure VO2 Peak. Multiple correlations among various models with measured VO2 Peak were considered moderately strong (R = .74-0.78), and prediction error (RMSE) ranged from 5.95 ml·kg⁻¹,min⁻¹ to 8.27 ml·kg⁻¹.min⁻¹. Criterion-referenced agreement into FITNESSGRAM's Healthy Fitness Zones was considered fair-to-good among models (Kappa = 0.31-0.62; Agreement = 75.5-89.9%; F = 0.08-0.65). In conclusion, prediction models demonstrated moderately strong linear relationships with measured VO2 Peak, fair prediction error, and fair-to-good criterion referenced agreement with measured VO2 Peak into FITNESSGRAM's Healthy Fitness Zones.

  17. Validated predictive modelling of the environmental resistome.

    Science.gov (United States)

    Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

    2015-06-01

    Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

  18. Automatically explaining machine learning prediction results: a demonstration on type 2 diabetes risk prediction.

    Science.gov (United States)

    Luo, Gang

    2016-01-01

    Predictive modeling is a key component of solutions to many healthcare problems. Among all predictive modeling approaches, machine learning methods often achieve the highest prediction accuracy, but suffer from a long-standing open problem precluding their widespread use in healthcare. Most machine learning models give no explanation for their prediction results, whereas interpretability is essential for a predictive model to be adopted in typical healthcare settings. This paper presents the first complete method for automatically explaining results for any machine learning predictive model without degrading accuracy. We did a computer coding implementation of the method. Using the electronic medical record data set from the Practice Fusion diabetes classification competition containing patient records from all 50 states in the United States, we demonstrated the method on predicting type 2 diabetes diagnosis within the next year. For the champion machine learning model of the competition, our method explained prediction results for 87.4 % of patients who were correctly predicted by the model to have type 2 diabetes diagnosis within the next year. Our demonstration showed the feasibility of automatically explaining results for any machine learning predictive model without degrading accuracy.

  19. Predicting risk behaviors: development and validation of a diagnostic scale.

    Science.gov (United States)

    Witte, K; Cameron, K A; McKeon, J K; Berkowitz, J M

    1996-01-01

    The goal of this study was to develop and validate the Risk Behavior Diagnosis (RBD) Scale for use by health care providers and practitioners interested in promoting healthy behaviors. Theoretically guided by the Extended Parallel Process Model (EPPM; a fear appeal theory), the RBD scale was designed to work in conjunction with an easy-to-use formula to determine which types of health risk messages would be most appropriate for a given individual or audience. Because some health risk messages promote behavior change and others backfire, this type of scale offers guidance to practitioners on how to develop the best persuasive message possible to motivate healthy behaviors. The results of the study demonstrate the RBD scale to have a high degree of content, construct, and predictive validity. Specific examples and practical suggestions are offered to facilitate use of the scale for health practitioners.

  20. Laboratory Validation and Demonstrations of Non-Hexavalent Chromium Conversion Coatings for Steel Substrates (Briefing Charts)

    Science.gov (United States)

    2011-02-01

    UNCLASSIFIED: Approved for public release; distribution unlimited. Laboratory Validation and Demonstrations of Non- Hexavalent Chromium Conversion...00-00-2011 4. TITLE AND SUBTITLE Laboratory Validation and Demonstrations of Non- Hexavalent Chromium Conversion Coatings for Steel Substrates 5a...to MRAP II Acquisition Pretreatment /conversion coatings omitted: • Hex- chrome pretreatments prohibited for new ground vehicles • Hydrogen

  1. A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration.

    Science.gov (United States)

    Upton, J; Murphy, M; Shalloo, L; Groot Koerkamp, P W G; De Boer, I J M

    2014-01-01

    Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat

  2. Brief implicit association test: Validity and utility in prediction of voting behavior

    Directory of Open Access Journals (Sweden)

    Pavlović Maša D.

    2013-01-01

    Full Text Available We employed the Brief Implicit Association Test (a recently developed short version of IAT to measure implicit political attitudes toward four political parties running for Serbian parliament. To test its criterion validity, we measured voting intention and actual voting behavior. In addition, we introduced political involvement as a potential moderator of the BIAT’s predictive and incremental validity. The BIAT demonstrated good internal and predictive validity, but lacked incremental validity over self-report measures. Predictive power of the BIAT was moderated by political involvement - the BIAT scores were stronger predictors of voting intention and behavior among voters highly involved in politics. [Projekat Ministarstva nauke Republike Srbije, br. 179018

  3. Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

    Science.gov (United States)

    Zabor, Emily C; Coit, Daniel; Gershenwald, Jeffrey E; McMasters, Kelly M; Michaelson, James S; Stromberg, Arnold J; Panageas, Katherine S

    2018-02-22

    Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

  4. Evaluating the Predictive Validity of Graduate Management Admission Test Scores

    Science.gov (United States)

    Sireci, Stephen G.; Talento-Miller, Eileen

    2006-01-01

    Admissions data and first-year grade point average (GPA) data from 11 graduate management schools were analyzed to evaluate the predictive validity of Graduate Management Admission Test[R] (GMAT[R]) scores and the extent to which predictive validity held across sex and race/ethnicity. The results indicated GMAT verbal and quantitative scores had…

  5. The Predictive Validity of Teacher Candidate Letters of Reference

    Science.gov (United States)

    Mason, Richard W.; Schroeder, Mark P.

    2014-01-01

    Letters of reference are widely used as an essential part of the hiring process of newly licensed teachers. While the predictive validity of these letters of reference has been called into question it has never been empirically studied. The current study examined the predictive validity of the quality of letters of reference for forty-one student…

  6. 76 FR 81991 - National Spectrum Sharing Research Experimentation, Validation, Verification, Demonstration and...

    Science.gov (United States)

    2011-12-29

    ... NATIONAL SCIENCE FOUNDATION National Spectrum Sharing Research Experimentation, Validation... requirements of national level spectrum research, development, demonstration, and field trial facilities... to determine the optimal way to manage and use the radio spectrum. During Workshop I held at Boulder...

  7. MO-FG-303-03: Demonstration of Universal Knowledge-Based 3D Dose Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Shiraishi, S; Moore, K L [University of California, San Diego, La Jolla, CA (United States)

    2015-06-15

    Purpose: To demonstrate a knowledge-based 3D dose prediction methodology that can accurately predict achievable radiotherapy distributions. Methods: Using previously treated plans as input, an artificial neural network (ANN) was trained to predict 3D dose distributions based on 14 patient-specific anatomical parameters including the distance (r) to planning target volume (PTV) boundary, organ-at-risk (OAR) boundary distances, and angular position ( θ,φ). 23 prostate and 49 stereotactic radiosurgery (SRS) cases with ≥1 nearby OARs were studied. All were planned with volumetric-modulated arc therapy (VMAT) to prescription doses of 81Gy for prostate and 12–30Gy for SRS. Site-specific ANNs were trained using all prostate 23 plans and using a 24 randomly-selected subset for the SRS model. The remaining 25 SRS plans were used to validate the model. To quantify predictive accuracy, the dose difference between the clinical plan and prediction were calculated on a voxel-by-voxel basis δD(r,θ,φ)=Dclin(r,θ,φ)-Dpred(r, θ,φ). Grouping voxels by boundary distance, the mean <δ Dr>=(1/N)Σ -θ,φ D(r,θ,φ) and inter-quartile range (IQR) quantified the accuracy of this method for deriving DVH estimations. The standard deviation (σ) of δ D quantified the 3D dose prediction error on a voxel-by-voxel basis. Results: The ANNs were highly accurate in predictive ability for both prostate and SRS plans. For prostate, <δDr> ranged from −0.8% to +0.6% (max IQR=3.8%) over r=0–32mm, while 3D dose prediction accuracy averaged from σ=5–8% across the same range. For SRS, from r=0–34mm the training set <δDr> ranged from −3.7% to +1.5% (max IQR=4.4%) while the validation set <δDr> ranged from −2.2% to +5.8% (max IQR=5.3%). 3D dose prediction accuracy averaged σ=2.5% for the training set and σ=4.0% over the same interval. Conclusion: The study demonstrates this technique’s ability to predict achievable 3D dose distributions for VMAT SRS and prostate. Future

  8. MO-FG-303-03: Demonstration of Universal Knowledge-Based 3D Dose Prediction

    International Nuclear Information System (INIS)

    Shiraishi, S; Moore, K L

    2015-01-01

    Purpose: To demonstrate a knowledge-based 3D dose prediction methodology that can accurately predict achievable radiotherapy distributions. Methods: Using previously treated plans as input, an artificial neural network (ANN) was trained to predict 3D dose distributions based on 14 patient-specific anatomical parameters including the distance (r) to planning target volume (PTV) boundary, organ-at-risk (OAR) boundary distances, and angular position ( θ,φ). 23 prostate and 49 stereotactic radiosurgery (SRS) cases with ≥1 nearby OARs were studied. All were planned with volumetric-modulated arc therapy (VMAT) to prescription doses of 81Gy for prostate and 12–30Gy for SRS. Site-specific ANNs were trained using all prostate 23 plans and using a 24 randomly-selected subset for the SRS model. The remaining 25 SRS plans were used to validate the model. To quantify predictive accuracy, the dose difference between the clinical plan and prediction were calculated on a voxel-by-voxel basis δD(r,θ,φ)=Dclin(r,θ,φ)-Dpred(r, θ,φ). Grouping voxels by boundary distance, the mean =(1/N)Σ -θ,φ D(r,θ,φ) and inter-quartile range (IQR) quantified the accuracy of this method for deriving DVH estimations. The standard deviation (σ) of δ D quantified the 3D dose prediction error on a voxel-by-voxel basis. Results: The ANNs were highly accurate in predictive ability for both prostate and SRS plans. For prostate, ranged from −0.8% to +0.6% (max IQR=3.8%) over r=0–32mm, while 3D dose prediction accuracy averaged from σ=5–8% across the same range. For SRS, from r=0–34mm the training set ranged from −3.7% to +1.5% (max IQR=4.4%) while the validation set ranged from −2.2% to +5.8% (max IQR=5.3%). 3D dose prediction accuracy averaged σ=2.5% for the training set and σ=4.0% over the same interval. Conclusion: The study demonstrates this technique’s ability to predict achievable 3D dose distributions for VMAT SRS and prostate. Future investigations will attempt to

  9. Error analysis in predictive modelling demonstrated on mould data.

    Science.gov (United States)

    Baranyi, József; Csernus, Olívia; Beczner, Judit

    2014-01-17

    The purpose of this paper was to develop a predictive model for the effect of temperature and water activity on the growth rate of Aspergillus niger and to determine the sources of the error when the model is used for prediction. Parallel mould growth curves, derived from the same spore batch, were generated and fitted to determine their growth rate. The variances of replicate ln(growth-rate) estimates were used to quantify the experimental variability, inherent to the method of determining the growth rate. The environmental variability was quantified by the variance of the respective means of replicates. The idea is analogous to the "within group" and "between groups" variability concepts of ANOVA procedures. A (secondary) model, with temperature and water activity as explanatory variables, was fitted to the natural logarithm of the growth rates determined by the primary model. The model error and the experimental and environmental errors were ranked according to their contribution to the total error of prediction. Our method can readily be applied to analysing the error structure of predictive models of bacterial growth models, too. © 2013.

  10. Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Daan Nieboer

    Full Text Available External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting.We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1 the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2 the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury.The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples and heterogeneous in scenario 2 (in 17%-39% of simulated samples. Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2.The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

  11. Validation of a tuber blight (Phytophthora infestans) prediction model

    Science.gov (United States)

    Potato tuber blight caused by Phytophthora infestans accounts for significant losses in storage. There is limited published quantitative data on predicting tuber blight. We validated a tuber blight prediction model developed in New York with cultivars Allegany, NY 101, and Katahdin using independent...

  12. Development and demonstration of a validation methodology for vehicle lateral dynamics simulation models

    Energy Technology Data Exchange (ETDEWEB)

    Kutluay, Emir

    2013-02-01

    In this thesis a validation methodology to be used in the assessment of the vehicle dynamics simulation models is presented. Simulation of vehicle dynamics is used to estimate the dynamic responses of existing or proposed vehicles and has a wide array of applications in the development of vehicle technologies. Although simulation environments, measurement tools and mathematical theories on vehicle dynamics are well established, the methodical link between the experimental test data and validity analysis of the simulation model is still lacking. The developed validation paradigm has a top-down approach to the problem. It is ascertained that vehicle dynamics simulation models can only be validated using test maneuvers although they are aimed for real world maneuvers. Test maneuvers are determined according to the requirements of the real event at the start of the model development project and data handling techniques, validation metrics and criteria are declared for each of the selected maneuvers. If the simulation results satisfy these criteria, then the simulation is deemed ''not invalid''. If the simulation model fails to meet the criteria, the model is deemed invalid, and model iteration should be performed. The results are analyzed to determine if the results indicate a modeling error or a modeling inadequacy; and if a conditional validity in terms of system variables can be defined. Three test cases are used to demonstrate the application of the methodology. The developed methodology successfully identified the shortcomings of the tested simulation model, and defined the limits of application. The tested simulation model is found to be acceptable but valid only in a certain dynamical range. Several insights for the deficiencies of the model are reported in the analysis but the iteration step of the methodology is not demonstrated. Utilizing the proposed methodology will help to achieve more time and cost efficient simulation projects with

  13. Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose

    Directory of Open Access Journals (Sweden)

    You Wang

    2016-07-01

    Full Text Available In the application of electronic noses (E-noses, probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used to discriminate nine kinds of ginsengs of different species or production places. A flexible machine learning framework, Venn machine (VM was introduced to make probabilistic predictions for each prediction. Three Venn predictors were developed based on three classical probabilistic prediction methods (Platt’s method, Softmax regression and Naive Bayes. Three Venn predictors and three classical probabilistic prediction methods were compared in aspect of classification rate and especially the validity of estimated probability. A best classification rate of 88.57% was achieved with Platt’s method in offline mode, and the classification rate of VM-SVM (Venn machine based on Support Vector Machine was 86.35%, just 2.22% lower. The validity of Venn predictors performed better than that of corresponding classical probabilistic prediction methods. The validity of VM-SVM was superior to the other methods. The results demonstrated that Venn machine is a flexible tool to make precise and valid probabilistic prediction in the application of E-nose, and VM-SVM achieved the best performance for the probabilistic prediction of ginseng samples.

  14. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  15. Predictive Validity And Usefulness Of Visual Scanning Task In Hiv ...

    African Journals Online (AJOL)

    The visual scanning task is a useful screening tool for brain damage in HIV/AIDS by inference from impairment of visual information processing and disturbances in perceptual mental strategies. There is progressive neuro-cognitive decline as the disease worsens. Keywords: brain, cognition, HIV/AIDS, predictive validity, ...

  16. A robust approach to QMU, validation, and conservative prediction.

    Energy Technology Data Exchange (ETDEWEB)

    Segalman, Daniel Joseph; Paez, Thomas Lee; Bauman, Lara E

    2013-01-01

    A systematic approach to defining margin in a manner that incorporates statistical information and accommodates data uncertainty, but does not require assumptions about specific forms of the tails of distributions is developed. This approach extends to calculations underlying validation assessment and quantitatively conservative predictions.

  17. Validation of a multi-objective, predictive urban traffic model

    NARCIS (Netherlands)

    Wilmink, I.R.; Haak, P. van den; Woldeab, Z.; Vreeswijk, J.

    2013-01-01

    This paper describes the results of the verification and validation of the ecoStrategic Model, which was developed, implemented and tested in the eCoMove project. The model uses real-time and historical traffic information to determine the current, predicted and desired state of traffic in a

  18. Predicting the ungauged basin : Model validation and realism assessment

    NARCIS (Netherlands)

    Van Emmerik, T.H.M.; Mulder, G.; Eilander, D.; Piet, M.; Savenije, H.H.G.

    2015-01-01

    The hydrological decade on Predictions in Ungauged Basins (PUB) led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of

  19. Predicting the ungauged basin: model validation and realism assessment

    NARCIS (Netherlands)

    van Emmerik, Tim; Mulder, Gert; Eilander, Dirk; Piet, Marijn; Savenije, Hubert

    2015-01-01

    The hydrological decade on Predictions in Ungauged Basins (PUB) led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of

  20. A mechanistic model for electricity consumption on dairy farms: Definition, validation, and demonstration

    OpenAIRE

    Upton, J.R.; Murphy, M.; Shallo, L.; Groot Koerkamp, P.W.G.; Boer, de, I.J.M.

    2014-01-01

    Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical d...

  1. Approaches to Demonstrating the Reliability and Validity of Core Diagnostic Criteria for Chronic Pain.

    Science.gov (United States)

    Bruehl, Stephen; Ohrbach, Richard; Sharma, Sonia; Widerstrom-Noga, Eva; Dworkin, Robert H; Fillingim, Roger B; Turk, Dennis C

    2016-09-01

    The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks-American Pain Society Pain Taxonomy (AAPT) is designed to be an evidence-based multidimensional chronic pain classification system that will facilitate more comprehensive and consistent chronic pain diagnoses, and thereby enhance research, clinical communication, and ultimately patient care. Core diagnostic criteria (dimension 1) for individual chronic pain conditions included in the initial version of AAPT will be the focus of subsequent empirical research to evaluate and provide evidence for their reliability and validity. Challenges to validating diagnostic criteria in the absence of clear and identifiable pathophysiological mechanisms are described. Based in part on previous experience regarding the development of evidence-based diagnostic criteria for psychiatric disorders, headache, and specific chronic pain conditions (fibromyalgia, complex regional pain syndrome, temporomandibular disorders, pain associated with spinal cord injuries), several potential approaches for documentation of the reliability and validity of the AAPT diagnostic criteria are summarized. The AAPT is designed to be an evidence-based multidimensional chronic pain classification system. Conceptual and methodological issues related to demonstrating the reliability and validity of the proposed AAPT chronic pain diagnostic criteria are discussed. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

  2. Validating spatiotemporal predictions of an important pest of small grains.

    Science.gov (United States)

    Merrill, Scott C; Holtzer, Thomas O; Peairs, Frank B; Lester, Philip J

    2015-01-01

    Arthropod pests are typically managed using tactics applied uniformly to the whole field. Precision pest management applies tactics under the assumption that within-field pest pressure differences exist. This approach allows for more precise and judicious use of scouting resources and management tactics. For example, a portion of a field delineated as attractive to pests may be selected to receive extra monitoring attention. Likely because of the high variability in pest dynamics, little attention has been given to developing precision pest prediction models. Here, multimodel synthesis was used to develop a spatiotemporal model predicting the density of a key pest of wheat, the Russian wheat aphid, Diuraphis noxia (Kurdjumov). Spatially implicit and spatially explicit models were synthesized to generate spatiotemporal pest pressure predictions. Cross-validation and field validation were used to confirm model efficacy. A strong within-field signal depicting aphid density was confirmed with low prediction errors. Results show that the within-field model predictions will provide higher-quality information than would be provided by traditional field scouting. With improvements to the broad-scale model component, the model synthesis approach and resulting tool could improve pest management strategy and provide a template for the development of spatially explicit pest pressure models. © 2014 Society of Chemical Industry.

  3. Gene prediction validation and functional analysis of redundant pathways

    DEFF Research Database (Denmark)

    Sønderkær, Mads

    2011-01-01

    have employed a large mRNA-seq data set to improve and validate ab initio predicted gene models. This direct experimental evidence also provides reliable determinations of UTR regions and polyadenylation sites, which are not easily predicted in plants. Furthermore, once an annotated genome sequence...... is available, gene expression by mRNA-Seq enables acquisition of a more complete overview of gene isoform usage in complex enzymatic pathways enabling the identification of key genes. Metabolism in potatoes This information is useful e.g. for crop improvement based on manipulation of agronomically important...

  4. Validating Inertial Confinement Fusion (ICF) predictive capability using perturbed capsules

    Science.gov (United States)

    Schmitt, Mark; Magelssen, Glenn; Tregillis, Ian; Hsu, Scott; Bradley, Paul; Dodd, Evan; Cobble, James; Flippo, Kirk; Offerman, Dustin; Obrey, Kimberly; Wang, Yi-Ming; Watt, Robert; Wilke, Mark; Wysocki, Frederick; Batha, Steven

    2009-11-01

    Achieving ignition on NIF is a monumental step on the path toward utilizing fusion as a controlled energy source. Obtaining robust ignition requires accurate ICF models to predict the degradation of ignition caused by heterogeneities in capsule construction and irradiation. LANL has embarked on a project to induce controlled defects in capsules to validate our ability to predict their effects on fusion burn. These efforts include the validation of feature-driven hydrodynamics and mix in a convergent geometry. This capability is needed to determine the performance of capsules imploded under less-than-optimum conditions on future IFE facilities. LANL's recently initiated Defect Implosion Experiments (DIME) conducted at Rochester's Omega facility are providing input for these efforts. Recent simulation and experimental results will be shown.

  5. High-Lift Propeller Noise Prediction for a Distributed Electric Propulsion Flight Demonstrator

    Science.gov (United States)

    Nark, Douglas M.; Buning, Pieter G.; Jones, William T.; Derlaga, Joseph M.

    2017-01-01

    Over the past several years, the use of electric propulsion technologies within aircraft design has received increased attention. The characteristics of electric propulsion systems open up new areas of the aircraft design space, such as the use of distributed electric propulsion (DEP). In this approach, electric motors are placed in many different locations to achieve increased efficiency through integration of the propulsion system with the airframe. Under a project called Scalable Convergent Electric Propulsion Technology Operations Research (SCEPTOR), NASA is designing a flight demonstrator aircraft that employs many "high-lift propellers" distributed upstream of the wing leading edge and two cruise propellers (one at each wingtip). As the high-lift propellers are operational at low flight speeds (take-off/approach flight conditions), the impact of the DEP configuration on the aircraft noise signature is also an important design consideration. This paper describes efforts toward the development of a mulit-fidelity aerodynamic and acoustic methodology for DEP high-lift propeller aeroacoustic modeling. Specifically, the PAS, OVERFLOW 2, and FUN3D codes are used to predict the aerodynamic performance of a baseline high-lift propeller blade set. Blade surface pressure results from the aerodynamic predictions are then used with PSU-WOPWOP and the F1A module of the NASA second generation Aircraft NOise Prediction Program to predict the isolated high-lift propeller noise source. Comparisons of predictions indicate that general trends related to angle of attack effects at the blade passage frequency are captured well with the various codes. Results for higher harmonics of the blade passage frequency appear consistent for the CFD based methods. Conversely, evidence of the need for a study of the effects of increased azimuthal grid resolution on the PAS based results is indicated and will be pursued in future work. Overall, the results indicate that the computational

  6. Validation of Solar Sail Simulations for the NASA Solar Sail Demonstration Project

    Science.gov (United States)

    Braafladt, Alexander C.; Artusio-Glimpse, Alexandra B.; Heaton, Andrew F.

    2014-01-01

    NASA's Solar Sail Demonstration project partner L'Garde is currently assembling a flight-like sail assembly for a series of ground demonstration tests beginning in 2015. For future missions of this sail that might validate solar sail technology, it is necessary to have an accurate sail thrust model. One of the primary requirements of a proposed potential technology validation mission will be to demonstrate solar sail thrust over a set time period, which for this project is nominally 30 days. This requirement would be met by comparing a L'Garde-developed trajectory simulation to the as-flown trajectory. The current sail simulation baseline for L'Garde is a Systems Tool Kit (STK) plug-in that includes a custom-designed model of the L'Garde sail. The STK simulation has been verified for a flat plate model by comparing it to the NASA-developed Solar Sail Spaceflight Simulation Software (S5). S5 matched STK with a high degree of accuracy and the results of the validation indicate that the L'Garde STK model is accurate enough to meet the potential future mission requirements. Additionally, since the L'Garde sail deviates considerably from a flat plate, a force model for a non-flat sail provided by L'Garde sail was also tested and compared to a flat plate model in S5. This result will be used in the future as a basis of comparison to the non-flat sail model being developed for STK.

  7. The Predictive Validity of the ABFM's In-Training Examination.

    Science.gov (United States)

    O'Neill, Thomas R; Li, Zijia; Peabody, Michael R; Lybarger, Melanie; Royal, Kenneth; Puffer, James C

    2015-05-01

    Our objective was to examine the predictive validity of the American Board of Family Medicine's (ABFM) In-Training Examination (ITE) with regard to predicting outcomes on the ABFM certification examination. This study used a repeated measures design across three levels of medical training (PGY1--PGY2, PGY2--PGY3, and PGY3--initial certification) with three different cohorts (2010--2011, 2011--2012, and 2012--2013) to examine: (1) how well the residents' ITE scores correlated with their test scores in the following year, (2) what the typical score increase was across training years, and (3) what was the sensitivity, specificity, positive predictive value, and negative predictive value of the PGY3 scores with regard to predicting future results on the MC-FP Examination. ITE scores generally correlate at about .7 with the following year's ITE or with the following year's certification examination. The mean growth from PGY1 to PGY2 was 52 points, from PGY2 to PGY3 was 34 points, and from PGY3 to initial certification was 27 points. The sensitivity, specificity, positive predictive value, and negative predictive value were .91, .47, .96, and .27, respectively. The ITE is a useful predictor of future ITE and initial certification examination performance.

  8. Dynamic Modeling and Validation of a Biomass Hydrothermal Pretreatment Process - A Demonstration Scale Study

    DEFF Research Database (Denmark)

    Prunescu, Remus Mihail; Blanke, Mogens; Jakobsen, Jon Geest

    2015-01-01

    for the enzymatic hydrolysis process. Several by-products are also formed, which disturb and act as inhibitors downstream. The objective of this study is to formulate and validate a large scale hydrothermal pretreatment dynamic model based on mass and energy balances, together with a complex conversion mechanism......Hydrothermal pretreatment of lignocellulosic biomass is a cost effective technology for second generation biorefineries. The process occurs in large horizontal and pressurized thermal reactors where the biomatrix is opened under the action of steam pressure and temperature to expose cellulose...... and kinetics. The study includes a comprehensive sensitivity and uncertainty analysis, with parameter estimation from real-data in the 178-185° range. To highlight the application utility of the model, a state estimator for biomass composition is developed. The predictions capture well the dynamic trends...

  9. Slip Validation and Prediction for Mars Exploration Rovers

    Directory of Open Access Journals (Sweden)

    Jeng Yen

    2008-04-01

    Full Text Available This paper presents a novel technique to validate and predict the rover slips on Martian surface for NASA’s Mars Exploration Rover mission (MER. Different from the traditional approach, the proposed method uses the actual velocity profile of the wheels and the digital elevation map (DEM from the stereo images of the terrain to formulate the equations of motion. The six wheel speed from the empirical encoder data comprises the vehicle's velocity, and the rover motion can be estimated using mixed differential and algebraic equations. Applying the discretization operator to these equations, the full kinematics state of the rover is then resolved by the configuration kinematics solution in the Rover Sequencing and Visualization Program (RSVP. This method, with the proper wheel slip and sliding factors, produces accurate simulation of the Mars Exploration rovers, which have been validated with the earth-testing vehicle. This computational technique has been deployed to the operation of the MER rovers in the extended mission period. Particularly, it yields high quality prediction of the rover motion on high slope areas. The simulated path of the rovers has been validated using the telemetry from the onboard Visual Odometry (VisOdom. Preliminary results indicate that the proposed simulation is very effective in planning the path of the rovers on the high-slope areas.

  10. Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

    Science.gov (United States)

    Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

    2018-02-01

    To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

  11. Validation and Inter-comparison Against Observations of GODAE Ocean View Ocean Prediction Systems

    Science.gov (United States)

    Xu, J.; Davidson, F. J. M.; Smith, G. C.; Lu, Y.; Hernandez, F.; Regnier, C.; Drevillon, M.; Ryan, A.; Martin, M.; Spindler, T. D.; Brassington, G. B.; Oke, P. R.

    2016-02-01

    For weather forecasts, validation of forecast performance is done at the end user level as well as by the meteorological forecast centers. In the development of Ocean Prediction Capacity, the same level of care for ocean forecast performance and validation is needed. Herein we present results from a validation against observations of 6 Global Ocean Forecast Systems under the GODAE OceanView International Collaboration Network. These systems include the Global Ocean Ice Forecast System (GIOPS) developed by the Government of Canada, two systems PSY3 and PSY4 from the French Mercator-Ocean Ocean Forecasting Group, the FOAM system from UK met office, HYCOM-RTOFS from NOAA/NCEP/NWA of USA, and the Australian Bluelink-OceanMAPS system from the CSIRO, the Australian Meteorological Bureau and the Australian Navy.The observation data used in the comparison are sea surface temperature, sub-surface temperature, sub-surface salinity, sea level anomaly, and sea ice total concentration data. Results of the inter-comparison demonstrate forecast performance limits, strengths and weaknesses of each of the six systems. This work establishes validation protocols and routines by which all new prediction systems developed under the CONCEPTS Collaborative Network will be benchmarked prior to approval for operations. This includes anticipated delivery of CONCEPTS regional prediction systems over the next two years including a pan Canadian 1/12th degree resolution ice ocean prediction system and limited area 1/36th degree resolution prediction systems. The validation approach of comparing forecasts to observations at the time and location of the observation is called Class 4 metrics. It has been adopted by major international ocean prediction centers, and will be recommended to JCOMM-WMO as routine validation approach for operational oceanography worldwide.

  12. Preventing patient absenteeism: validation of a predictive overbooking model.

    Science.gov (United States)

    Reid, Mark W; Cohen, Samuel; Wang, Hank; Kaung, Aung; Patel, Anish; Tashjian, Vartan; Williams, Demetrius L; Martinez, Bibiana; Spiegel, Brennan M R

    2015-12-01

    To develop a model that identifies patients at high risk for missing scheduled appointments ("no-shows" and cancellations) and to project the impact of predictive overbooking in a gastrointestinal endoscopy clinic-an exemplar resource-intensive environment with a high no-show rate. We retrospectively developed an algorithm that uses electronic health record (EHR) data to identify patients who do not show up to their appointments. Next, we prospectively validated the algorithm at a Veterans Administration healthcare network clinic. We constructed a multivariable logistic regression model that assigned a no-show risk score optimized by receiver operating characteristic curve analysis. Based on these scores, we created a calendar of projected open slots to offer to patients and compared the daily performance of predictive overbooking with fixed overbooking and typical "1 patient, 1 slot" scheduling. Data from 1392 patients identified several predictors of no-show, including previous absenteeism, comorbid disease burden, and current diagnoses of mood and substance use disorders. The model correctly classified most patients during the development (area under the curve [AUC] = 0.80) and validation phases (AUC = 0.75). Prospective testing in 1197 patients found that predictive overbooking averaged 0.51 unused appointments per day versus 6.18 for typical booking (difference = -5.67; 95% CI, -6.48 to -4.87; P < .0001). Predictive overbooking could have increased service utilization from 62% to 97% of capacity, with only rare clinic overflows. Information from EHRs can accurately predict whether patients will no-show. This method can be used to overbook appointments, thereby maximizing service utilization while staying within clinic capacity.

  13. Discrete fracture modelling for the Stripa tracer validation experiment predictions

    International Nuclear Information System (INIS)

    Dershowitz, W.; Wallmann, P.

    1992-02-01

    Groundwater flow and transport through three-dimensional networks of discrete fractures was modeled to predict the recovery of tracer from tracer injection experiments conducted during phase 3 of the Stripa site characterization and validation protect. Predictions were made on the basis of an updated version of the site scale discrete fracture conceptual model used for flow predictions and preliminary transport modelling. In this model, individual fractures were treated as stochastic features described by probability distributions of geometric and hydrologic properties. Fractures were divided into three populations: Fractures in fracture zones near the drift, non-fracture zone fractures within 31 m of the drift, and fractures in fracture zones over 31 meters from the drift axis. Fractures outside fracture zones are not modelled beyond 31 meters from the drift axis. Transport predictions were produced using the FracMan discrete fracture modelling package for each of five tracer experiments. Output was produced in the seven formats specified by the Stripa task force on fracture flow modelling. (au)

  14. A Reliable and Valid Survey to Predict a Patient’s Gagging Intensity

    Directory of Open Access Journals (Sweden)

    Casey M. Hearing

    2014-07-01

    Full Text Available Objectives: The aim of this study was to devise a reliable and valid survey to predict the intensity of someone’s gag reflex. Material and Methods: A 10-question Predictive Gagging Survey was created, refined, and tested on 59 undergraduate participants. The questions focused on risk factors and experiences that would indicate the presence and strength of someone’s gag reflex. Reliability was assessed by administering the survey to a group of 17 participants twice, with 3 weeks separating the two administrations. Finally, the survey was given to 25 dental patients. In these cases, patients completed an informed consent form, filled out the survey, and then had a maxillary impression taken while their gagging response was quantified from 1 to 5 on the Fiske and Dickinson Gagging Intensity Index. Results: There was a moderate positive correlation between the Predictive Gagging Survey and Fiske and Dickinson’s Gagging Severity Index, r = +0.64, demonstrating the survey’s validity. Furthermore, the test-retest reliability was r = +0.96, demonstrating the survey’s reliability. Conclusions: The Predictive Gagging Survey is a 10-question survey about gag-related experiences and behaviours. We established that it is a reliable and valid method to assess the strength of someone’s gag reflex.

  15. The Reliability and Predictive Validity of the Stalking Risk Profile.

    Science.gov (United States)

    McEwan, Troy E; Shea, Daniel E; Daffern, Michael; MacKenzie, Rachel D; Ogloff, James R P; Mullen, Paul E

    2018-03-01

    This study assessed the reliability and validity of the Stalking Risk Profile (SRP), a structured measure for assessing stalking risks. The SRP was administered at the point of assessment or retrospectively from file review for 241 adult stalkers (91% male) referred to a community-based forensic mental health service. Interrater reliability was high for stalker type, and moderate-to-substantial for risk judgments and domain scores. Evidence for predictive validity and discrimination between stalking recidivists and nonrecidivists for risk judgments depended on follow-up duration. Discrimination was moderate (area under the curve = 0.66-0.68) and positive and negative predictive values good over the full follow-up period ( Mdn = 170.43 weeks). At 6 months, discrimination was better than chance only for judgments related to stalking of new victims (area under the curve = 0.75); however, high-risk stalkers still reoffended against their original victim(s) 2 to 4 times as often as low-risk stalkers. Implications for the clinical utility and refinement of the SRP are discussed.

  16. Sensory and cognitive neurophysiology in rats. Part 2: Validation and demonstration.

    Science.gov (United States)

    Dimitriadis, George; Fransen, Anne M M; Maris, Eric

    2014-07-30

    We have developed a novel setup for rats that allows for controlled sensory input to an animal engaged in a task while recording both electrophysiological signals and behavioral output. Our setup is described in a companion paper. We validate our setup by replicating (1) the functionally nonspecific spread of neural activity following tactile stimulation, and (2) the effects of anesthesia on the tactile evoked responses. We also demonstrate for the first time that the ECoG can be used to record evoked responses in a signal that reflects neural output (spiking activity), and illustrate the usefulness of our setup by demonstrating that these evoked responses are modulated by both the phase of pre-stimulus oscillations and by expectation. Compared with high-density wire recordings, micro-ECoG offers a much more stable signal without readjustments, and a much better scalability. Compared with extracranial and regular ECoG recordings, micro-ECoG allows us to measure signals that reflect both neural input and neural output. For sensory and cognitive research, our setup provides a unique combination of possibilities that cannot be achieved in other setups for rodents. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Predicting the ungauged basin: Model validation and realism assessment

    Directory of Open Access Journals (Sweden)

    Tim evan Emmerik

    2015-10-01

    Full Text Available The hydrological decade on Predictions in Ungauged Basins (PUB led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of model outcome has not been discussed to a great extent. With this paper we aim to contribute to the discussion on how one can determine the value and validity of a hydrological model developed for an ungauged basin. As in many cases no local, or even regional, data are available, alternative methods should be applied. Using a PUB case study in a genuinely ungauged basin in southern Cambodia, we give several examples of how one can use different types of soft data to improve model design, calibrate and validate the model, and assess the realism of the model output. A rainfall-runoff model was coupled to an irrigation reservoir, allowing the use of additional and unconventional data. The model was mainly forced with remote sensing data, and local knowledge was used to constrain the parameters. Model realism assessment was done using data from surveys. This resulted in a successful reconstruction of the reservoir dynamics, and revealed the different hydrological characteristics of the two topographical classes. This paper does not present a generic approach that can be transferred to other ungauged catchments, but it aims to show how clever model design and alternative data acquisition can result in a valuable hydrological model for an ungauged catchment.

  18. External validation of the Cairns Prediction Model (CPM) to predict conversion from laparoscopic to open cholecystectomy.

    Science.gov (United States)

    Hu, Alan Shiun Yew; Donohue, Peter O'; Gunnarsson, Ronny K; de Costa, Alan

    2018-03-14

    Valid and user-friendly prediction models for conversion to open cholecystectomy allow for proper planning prior to surgery. The Cairns Prediction Model (CPM) has been in use clinically in the original study site for the past three years, but has not been tested at other sites. A retrospective, single-centred study collected ultrasonic measurements and clinical variables alongside with conversion status from consecutive patients who underwent laparoscopic cholecystectomy from 2013 to 2016 in The Townsville Hospital, North Queensland, Australia. An area under the curve (AUC) was calculated to externally validate of the CPM. Conversion was necessary in 43 (4.2%) out of 1035 patients. External validation showed an area under the curve of 0.87 (95% CI 0.82-0.93, p = 1.1 × 10 -14 ). In comparison with most previously published models, which have an AUC of approximately 0.80 or less, the CPM has the highest AUC of all published prediction models both for internal and external validation. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

  19. Disentangling the Predictive Validity of High School Grades for Academic Success in University

    Science.gov (United States)

    Vulperhorst, Jonne; Lutz, Christel; de Kleijn, Renske; van Tartwijk, Jan

    2018-01-01

    To refine selective admission models, we investigate which measure of prior achievement has the best predictive validity for academic success in university. We compare the predictive validity of three core high school subjects to the predictive validity of high school grade point average (GPA) for academic achievement in a liberal arts university…

  20. Predicting child maltreatment: A meta-analysis of the predictive validity of risk assessment instruments.

    Science.gov (United States)

    van der Put, Claudia E; Assink, Mark; Boekhout van Solinge, Noëlle F

    2017-11-01

    Risk assessment is crucial in preventing child maltreatment since it can identify high-risk cases in need of child protection intervention. Despite widespread use of risk assessment instruments in child welfare, it is unknown how well these instruments predict maltreatment and what instrument characteristics are associated with higher levels of predictive validity. Therefore, a multilevel meta-analysis was conducted to examine the predictive accuracy of (characteristics of) risk assessment instruments. A literature search yielded 30 independent studies (N=87,329) examining the predictive validity of 27 different risk assessment instruments. From these studies, 67 effect sizes could be extracted. Overall, a medium significant effect was found (AUC=0.681), indicating a moderate predictive accuracy. Moderator analyses revealed that onset of maltreatment can be better predicted than recurrence of maltreatment, which is a promising finding for early detection and prevention of child maltreatment. In addition, actuarial instruments were found to outperform clinical instruments. To bring risk and needs assessment in child welfare to a higher level, actuarial instruments should be further developed and strengthened by distinguishing risk assessment from needs assessment and by integrating risk assessment with case management. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Validation of morphing wing methodologies on an unmanned aerial system and a wind tunnel technology demonstrator

    Science.gov (United States)

    Gabor, Oliviu Sugar

    To increase the aerodynamic efficiency of aircraft, in order to reduce the fuel consumption, a novel morphing wing concept has been developed. It consists in replacing a part of the wing upper and lower surfaces with a flexible skin whose shape can be modified using an actuation system placed inside the wing structure. Numerical studies in two and three dimensions were performed in order to determine the gains the morphing system achieves for the case of an Unmanned Aerial System and for a morphing technology demonstrator based on the wing tip of a transport aircraft. To obtain the optimal wing skin shapes in function of the flight condition, different global optimization algorithms were implemented, such as the Genetic Algorithm and the Artificial Bee Colony Algorithm. To reduce calculation times, a hybrid method was created by coupling the population-based algorithm with a fast, gradient-based local search method. Validations were performed with commercial state-of-the-art optimization tools and demonstrated the efficiency of the proposed methods. For accurately determining the aerodynamic characteristics of the morphing wing, two new methods were developed, a nonlinear lifting line method and a nonlinear vortex lattice method. Both use strip analysis of the span-wise wing section to account for the airfoil shape modifications induced by the flexible skin, and can provide accurate results for the wing drag coefficient. The methods do not require the generation of a complex mesh around the wing and are suitable for coupling with optimization algorithms due to the computational time several orders of magnitude smaller than traditional three-dimensional Computational Fluid Dynamics methods. Two-dimensional and three-dimensional optimizations of the Unmanned Aerial System wing equipped with the morphing skin were performed, with the objective of improving its performances for an extended range of flight conditions. The chordwise positions of the internal actuators

  2. A strategy for developing representative germplasm sets for systematic QTL validation, demonstrated for apple, peach, and sweet cherry

    NARCIS (Netherlands)

    Peace, C.P.; Luby, J.; Weg, van de W.E.; Bink, M.C.A.M.; Iezzoni, A.F.

    2014-01-01

    Horticultural crop improvement would benefit from a standardized, systematic, and statistically robust procedure for validating quantitative trait loci (QTLs) in germplasm relevant to breeding programs. Here, we describe and demonstrate a strategy for developing reference germplasm sets of

  3. Development, Demonstration and Validation of the Deep Space Orbit Determination Software Using Lunar Prospector Tracking Data

    Directory of Open Access Journals (Sweden)

    Eunji Lee

    2017-09-01

    Full Text Available The deep space orbit determination software (DSODS is a part of a flight dynamic subsystem (FDS for the Korean Pathfinder Lunar Orbiter (KPLO, a lunar exploration mission expected to launch after 2018. The DSODS consists of several sub modules, of which the orbit determination (OD module employs a weighted least squares algorithm for estimating the parameters related to the motion and the tracking system of the spacecraft, and subroutines for performance improvement and detailed analysis of the orbit solution. In this research, DSODS is demonstrated and validated at lunar orbit at an altitude of 100 km using actual Lunar Prospector tracking data. A set of a priori states are generated, and the robustness of DSODS to the a priori error is confirmed by the NASA planetary data system (PDS orbit solutions. Furthermore, the accuracy of the orbit solutions is determined by solution comparison and overlap analysis as about tens of meters. Through these analyses, the ability of the DSODS to provide proper orbit solutions for the KPLO are proved.

  4. Site characterization and validation. Stage 2 - Preliminary predictions

    International Nuclear Information System (INIS)

    Olsson, O.; Black, J.H.; Gale, J.E.; Holmes, D.C.

    1989-05-01

    The Site Characterization and Validation (SCV) project is designed to assess how well we can characterize a volume of rock prior to using it as a repository. The programme of work focuses on the validation of the techniques used in site characterization. The SCV project contains 5 stages of work arranged in two 'cycles' of data-gathering, prediction, and validation. The first stage of work has included drilling of 6 boreholes (N2, N3, N4, W1, W2 and V3) and measurements of geology, fracture characteristics, stess, single borehole geophysical logging, radar, seismics and hydrogeology. The rock at the SCV site is granite with small lithological variations. Based essentially on radar and seismic results 5 'fracture zones' have been identified, named GA, GB, GC, GH and GI. They all extend acroos the entire SCV site. They aer basically in in two groups (GA, GB, GC and GH, GI). The first group are aligned N40 degree E with a dip of 35 degree to the south. The second group are aligned approximately N10 degree W dipping 60 degree E. From the stochastic analysis of the joint data it was possible to identify three main fracture orientation clusters. The orientation of two of these clusters agree roughly with orientation of the main features. Cluster B has roughly the same orientation as GH and GI, while features GA, GB and GC have an orientation similar to the more loosely defined cluster C. The orientation of the third cluster (A) is northwest with a dip to northeast. It is found that 94% of all measured hydraulic transmissivity is accounted for by 4% of the tested rock, not all of this 'concentrated' transmissivity is with the major features defined by geophysics. When the hydraulic connections across the site are examied they show that there are several welldefined zones which permit rapid transmission of hydraulic signals. These are essentially from the northeast to the southwest. (66 figs., 21 tabs., 33 refs.)

  5. The predictive validity of the BioMedical Admissions Test for pre-clinical examination performance.

    Science.gov (United States)

    Emery, Joanne L; Bell, John F

    2009-06-01

    Some medical courses in the UK have many more applicants than places and almost all applicants have the highest possible previous and predicted examination grades. The BioMedical Admissions Test (BMAT) was designed to assist in the student selection process specifically for a number of 'traditional' medical courses with clear pre-clinical and clinical phases and a strong focus on science teaching in the early years. It is intended to supplement the information provided by examination results, interviews and personal statements. This paper reports on the predictive validity of the BMAT and its predecessor, the Medical and Veterinary Admissions Test. Results from the earliest 4 years of the test (2000-2003) were matched to the pre-clinical examination results of those accepted onto the medical course at the University of Cambridge. Correlation and logistic regression analyses were performed for each cohort. Section 2 of the test ('Scientific Knowledge') correlated more strongly with examination marks than did Section 1 ('Aptitude and Skills'). It also had a stronger relationship with the probability of achieving the highest examination class. The BMAT and its predecessor demonstrate predictive validity for the pre-clinical years of the medical course at the University of Cambridge. The test identifies important differences in skills and knowledge between candidates, not shown by their previous attainment, which predict their examination performance. It is thus a valid source of additional admissions information for medical courses with a strong scientific emphasis when previous attainment is very high.

  6. Achievement Motivation Revisited: New Longitudinal Data to Demonstrate Its Predictive Power

    Science.gov (United States)

    Hustinx, Paul W. J.; Kuyper, Hans; van der Werf, Margaretha P. C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary school students. Two measures of achievement…

  7. Achievement motivation revisited : New longitudinal data to demonstrate its predictive power

    NARCIS (Netherlands)

    Hustinx, P.W.J.; Kuyper, H.; Van der Werf, M.P.C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary

  8. Validation of an Acoustic Impedance Prediction Model for Skewed Resonators

    Science.gov (United States)

    Howerton, Brian M.; Parrott, Tony L.

    2009-01-01

    An impedance prediction model was validated experimentally to determine the composite impedance of a series of high-aspect ratio slot resonators incorporating channel skew and sharp bends. Such structures are useful for packaging acoustic liners into constrained spaces for turbofan noise control applications. A formulation of the Zwikker-Kosten Transmission Line (ZKTL) model, incorporating the Richards correction for rectangular channels, is used to calculate the composite normalized impedance of a series of six multi-slot resonator arrays with constant channel length. Experimentally, acoustic data was acquired in the NASA Langley Normal Incidence Tube over the frequency range of 500 to 3500 Hz at 120 and 140 dB OASPL. Normalized impedance was reduced using the Two-Microphone Method for the various combinations of channel skew and sharp 90o and 180o bends. Results show that the presence of skew and/or sharp bends does not significantly alter the impedance of a slot resonator as compared to a straight resonator of the same total channel length. ZKTL predicts the impedance of such resonators very well over the frequency range of interest. The model can be used to design arrays of slot resonators that can be packaged into complex geometries heretofore unsuitable for effective acoustic treatment.

  9. Developing and Validating a Predictive Model for Stroke Progression

    Directory of Open Access Journals (Sweden)

    L.E. Craig

    2011-12-01

    discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice.

  10. Developing and validating a predictive model for stroke progression.

    Science.gov (United States)

    Craig, L E; Wu, O; Gilmour, H; Barber, M; Langhorne, P

    2011-01-01

    sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice.

  11. Developing and Validating a Predictive Model for Stroke Progression

    Science.gov (United States)

    Craig, L.E.; Wu, O.; Gilmour, H.; Barber, M.; Langhorne, P.

    2011-01-01

    calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice. PMID:22566988

  12. The Validity of Conscientiousness Is Overestimated in the Prediction of Job Performance.

    Science.gov (United States)

    Kepes, Sven; McDaniel, Michael A

    2015-01-01

    Sensitivity analyses refer to investigations of the degree to which the results of a meta-analysis remain stable when conditions of the data or the analysis change. To the extent that results remain stable, one can refer to them as robust. Sensitivity analyses are rarely conducted in the organizational science literature. Despite conscientiousness being a valued predictor in employment selection, sensitivity analyses have not been conducted with respect to meta-analytic estimates of the correlation (i.e., validity) between conscientiousness and job performance. To address this deficiency, we reanalyzed the largest collection of conscientiousness validity data in the personnel selection literature and conducted a variety of sensitivity analyses. Publication bias analyses demonstrated that the validity of conscientiousness is moderately overestimated (by around 30%; a correlation difference of about .06). The misestimation of the validity appears to be due primarily to suppression of small effects sizes in the journal literature. These inflated validity estimates result in an overestimate of the dollar utility of personnel selection by millions of dollars and should be of considerable concern for organizations. The fields of management and applied psychology seldom conduct sensitivity analyses. Through the use of sensitivity analyses, this paper documents that the existing literature overestimates the validity of conscientiousness in the prediction of job performance. Our data show that effect sizes from journal articles are largely responsible for this overestimation.

  13. Radar investigations at the Saltsjoetunnel - predictions and validation

    International Nuclear Information System (INIS)

    Olsson, Olle; Palmqvist, Kai

    1989-01-01

    Borehole radar investigations have been performed in two boreholes drilled along the extent of the Saltsjoe tunnel in Stockholm, Sweden. The objective of the project was to test investigate the capabilities of the borehole radar technique to predict geological structures prior to tunnel excavation. Singlehole and crosshole radar measurements were made in the two boreholes which outlined and equilateral triangle. The crosshole data was used to produce tomograms showing the distribution of radar attenuation and slowness (inverse of velocity) in the plane between the boreholes. The radar model of the site contained one major feature which was identified as a fracture zone. The intersection of the fracture zone with the tunnel was extrapolated from the radar data and found to be in agreement with observations in the tunnel. At the intersection of the fracture zone with the tunnel grouting had to be applied. It has also been found that the radar identifies a number of smaller features which are of practically no significance with respect to tunnel construction. There is general agreement between the radar model of the site and the geologic-tectonic model of the site. This project has demonstrated the capability of the boreholes radar technique to predict the existence, location, and orientation of geologic features (e.g. fracture zones) which can be of significance to the cost and safety when excavating a tunnel. However, further development is needed to be able to use the technique cost effectively for continuous prediction ahead of the tunnel front. (authors) (17 figs., 1 tab.)

  14. Recurrent epistaxis: predicting risk of 30-day readmission, derivation and validation of RHINO-ooze score.

    Science.gov (United States)

    Addison, A; Paul, C; Kuo, R; Lamyman, A; Martinez-Devesa, P; Hettige, R

    2017-06-01

    To derive and validate a predictive scoring tool (RHINO-ooze score) with good sensitivity and specificity in identifying patients with epistaxis at high risk of 30 day readmission and to enable risk stratification for possible definitive intervention. Using medical databases, we searched for factors influencing recurrent epistaxis. The information ascertained together with our analysis of retrospective data on patients admitted with epistaxis between October 2013 and September 2014, was used as the derivation cohort to develop the predictive scoring model (RHINO-ooze score). The tool was validated by performing statistical analysis on the validation cohort of patients admitted with epistaxis between October 2014 and October 2015. Multiple linear regressions with backwards elimination was used to derive the predictive model. The area under the curve (AUC), sensitivity and specificity were calculated. 834 admissions were encountered within the study period. Using the derivative cohort (n= 302) the RHINO-ooze score with a maximum score of 8 from five variables (Recent admission, Haemorrhage point unidentified, Increasing age over 70, posterior Nasal packing, Oral anticoagulant) was developed. The RHINO-ooze score had a chi-square value of 99.72 with a significance level of smaller than 0.0001 and hence an overall good model fit. Comparison between the derivative and validation groups revealed similar rates of 30-day readmission between the cohorts. The sensitivity and specificity of predicting 30-day readmission in high risk patients with recurrent epistaxis (RHINO-ooze score equal/larger than 6) was 81% and 84%, respectively. The RHINO-ooze scoring tool demonstrates good specificity and sensitivity in predicting the risk of 30 day readmission in patients with epistaxis and can be used as an adjunct to clinical decision making with regards to timing of operative intervention in order to reduce readmission rates.

  15. Comorbidity predicts poor prognosis in nasopharyngeal carcinoma: Development and validation of a predictive score model

    International Nuclear Information System (INIS)

    Guo, Rui; Chen, Xiao-Zhong; Chen, Lei; Jiang, Feng; Tang, Ling-Long; Mao, Yan-Ping; Zhou, Guan-Qun; Li, Wen-Fei; Liu, Li-Zhi; Tian, Li; Lin, Ai-Hua; Ma, Jun

    2015-01-01

    Background and purpose: The impact of comorbidity on prognosis in nasopharyngeal carcinoma (NPC) is poorly characterized. Material and methods: Using the Adult Comorbidity Evaluation-27 (ACE-27) system, we assessed the prognostic value of comorbidity and developed, validated and confirmed a predictive score model in a training set (n = 658), internal validation set (n = 658) and independent set (n = 652) using area under the receiver operating curve analysis. Results: Comorbidity was present in 40.4% of 1968 patients (mild, 30.1%; moderate, 9.1%; severe, 1.2%). Compared to an ACE-27 score ⩽1, patients with an ACE-27 score >1 in the training set had shorter overall survival (OS) and disease-free survival (DFS) (both P < 0.001), similar results were obtained in the other sets (P < 0.05). In multivariate analysis, ACE-27 score was a significant independent prognostic factor for OS and DFS. The combined risk score model including ACE-27 had superior prognostic value to TNM stage alone in the internal validation set (0.70 vs. 0.66; P = 0.02), independent set (0.73 vs. 0.67; P = 0.002) and all patients (0.71 vs. 0.67; P < 0.001). Conclusions: Comorbidity significantly affects prognosis, especially in stages II and III, and should be incorporated into the TNM staging system for NPC. Assessment of comorbidity may improve outcome prediction and help tailor individualized treatment

  16. Prediction and validation of hemodialysis duration in acute methanol poisoning.

    Science.gov (United States)

    Lachance, Philippe; Mac-Way, Fabrice; Desmeules, Simon; De Serres, Sacha A; Julien, Anne-Sophie; Douville, Pierre; Ghannoum, Marc; Agharazii, Mohsen

    2015-11-01

    The duration of hemodialysis (HD) in methanol poisoning (MP) is dependent on the methanol concentration, the operational parameters used during HD, and the presence and severity of metabolic acidosis. However, methanol assays are not easily available, potentially leading to undue extension or premature termination of treatment. Here we provide a prediction model for the duration of high-efficiency HD in MP. In a retrospective cohort study, we identified 71 episodes of MP in 55 individuals who were treated with alcohol dehydrogenase inhibition and HD. Four patients had residual visual abnormality at discharge and only one patient died. In 46 unique episodes of MP with high-efficiency HD the mean methanol elimination half-life (T1/2) during HD was 108 min in women, significantly different from the 129 min in men. In a training set of 28 patients with MP, using the 90th percentile of gender-specific elimination T1/2 (147 min in men and 141 min in women) and a target methanol concentration of 4 mmol/l allowed all cases to reach a safe methanol of under 6 mmol/l. The prediction model was confirmed in a validation set of 18 patients with MP. High-efficiency HD time in hours can be estimated using 3.390 × (Ln (MCi/4)) for women and 3.534 × (Ln (MCi/4)) for men, where MCi is the initial methanol concentration in mmol/l, provided that metabolic acidosis is corrected.

  17. Validity of one-repetition maximum predictive equations in men with spinal cord injury.

    Science.gov (United States)

    Ribeiro Neto, F; Guanais, P; Dornelas, E; Coutinho, A C B; Costa, R R G

    2017-10-01

    Cross-sectional study. The study aimed (a) to test the cross-validation of current one-repetition maximum (1RM) predictive equations in men with spinal cord injury (SCI); (b) to compare the current 1RM predictive equations to a newly developed equation based on the 4- to 12-repetition maximum test (4-12RM). SARAH Rehabilitation Hospital Network, Brasilia, Brazil. Forty-five men aged 28.0 years with SCI between C6 and L2 causing complete motor impairment were enrolled in the study. Volunteers were tested, in a random order, in 1RM test or 4-12RM with 2-3 interval days. Multiple regression analysis was used to generate an equation for predicting 1RM. There were no significant differences between 1RM test and the current predictive equations. ICC values were significant and were classified as excellent for all current predictive equations. The predictive equation of Lombardi presented the best Bland-Altman results (0.5 kg and 12.8 kg for mean difference and interval range around the differences, respectively). The two created equation models for 1RM demonstrated the same and a high adjusted R 2 (0.971, Ppredictive equations are accurate to assess individuals with SCI at the bench press exercise. However, the predictive equation of Lombardi presented the best associated cross-validity results. A specific 1RM prediction equation was also elaborated for individuals with SCI. The created equation should be tested in order to verify whether it presents better accuracy than the current ones.

  18. Predicting Relapse among Young Adults: Psychometric Validation of the Advanced Warning of Relapse (AWARE) Scale

    Science.gov (United States)

    Kelly, John F.; Hoeppner, Bettina B.; Urbanoski, Karen A.; Slaymaker, Valerie

    2011-01-01

    Objective Failure to maintain abstinence despite incurring severe harm is perhaps the key defining feature of addiction. Relapse prevention strategies have been developed to attenuate this propensity to relapse, but predicting who will, and who will not, relapse has stymied attempts to more efficiently tailor treatments according to relapse risk profile. Here we examine the psychometric properties of a promising relapse risk measure - the Advance WArning of RElapse scale (AWARE) scale (Miller and Harris, 2000) in an understudied but clinically important sample of young adults. Method Inpatient youth (N=303; Age 18-24; 26% female) completed the AWARE scale and the Brief Symptom Inventory-18 (BSI) at the end of residential treatment, and at 1-, 3-, and 6-months following discharge. Internal and convergent validity was tested for each of these four timepoints using confirmatory factor analysis and correlations (with BSI scores). Predictive validity was tested for relapse 1, 3, and 6 months following discharge, as was incremental utility, where AWARE scores were used as predictors of any substance use while controlling for treatment entry substance use severity and having spent time in a controlled environment following treatment. Results Confirmatory factor analysis revealed a single, internally consistent, 25-item factor that demonstrated convergent validity and predicted subsequent relapse alone and when controlling for other important relapse risk predictors. Conclusions The AWARE scale may be a useful and efficient clinical tool for assessing short-term relapse risk among young people and, thus, could serve to enhance the effectiveness of relapse prevention efforts. PMID:21700396

  19. Predicting relapse among young adults: psychometric validation of the Advanced WArning of RElapse (AWARE) scale.

    Science.gov (United States)

    Kelly, John F; Hoeppner, Bettina B; Urbanoski, Karen A; Slaymaker, Valerie

    2011-10-01

    Failure to maintain abstinence despite incurring severe harm is perhaps the key defining feature of addiction. Relapse prevention strategies have been developed to attenuate this propensity to relapse, but predicting who will, and who will not, relapse has stymied attempts to more efficiently tailor treatments according to relapse risk profile. Here we examine the psychometric properties of a promising relapse risk measure-the Advance WArning of RElapse (AWARE) scale (Miller & Harris, 2000) in an understudied but clinically important sample of young adults. Inpatient youth (N=303; Ages 18-24; 26% female) completed the AWARE scale and the Brief Symptom Inventory-18 (BSI) at the end of residential treatment, and at 1-, 3-, and 6-months following discharge. Internal and convergent validity was tested for each of these four timepoints using confirmatory factor analysis and correlations (with BSI scores). Predictive validity was tested for relapse 1, 3, and 6 months following discharge, as was incremental utility, where AWARE scores were used as predictors of any substance use while controlling for treatment entry substance use severity and having spent time in a controlled environment following treatment. Confirmatory factor analysis revealed a single, internally consistent, 25-item factor that demonstrated convergent validity and predicted subsequent relapse alone and when controlling for other important relapse risk predictors. The AWARE scale may be a useful and efficient clinical tool for assessing short-term relapse risk among young people and, thus, could serve to enhance the effectiveness of relapse prevention efforts. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Development of Demonstrably Predictive Models for Emissions from Alternative Fuels Based Aircraft Engines

    Science.gov (United States)

    2017-05-01

    Engineering Chemistry Fundamentals, Vol. 5, No. 3, 1966, pp. 356–363. [14] Burns, R. A., Development of scalar and velocity imaging diagnostics...in an Aero- Engine Model Combustor at Elevated Pressure Using URANS and Finite- Rate Chemistry ,” 50th AIAA/ASME/SAE/ASEE Joint Propulsion Conference...FINAL REPORT Development of Demonstrably Predictive Models for Emissions from Alternative Fuels Based Aircraft Engines SERDP Project WP-2151

  1. Validation of resting metabolic rate prediction equations for teenagers

    Directory of Open Access Journals (Sweden)

    Paulo Henrique Santos da Fonseca

    2007-09-01

    Full Text Available The resting metabolic rate (RMR can be defi ned as the minimum rate of energy spent and represents the main component of the energetic outlay. The purpose of this study is to validate equations to predict the resting metabolic rate in teenagers (103 individuals, being 51 girls and 52 boys, with age between 10 and 17 years from Florianópolis – SC – Brazil. It was measured: the body weight, body height, skinfolds and obtained the lean and body fat mass through bioimpedance. The nonproteic RMR was measured by Weir’s equation (1949, utilizing AeroSport TEEM-100 gas analyzer. The studied equations were: Harry and Benedict (1919, Schofi eld (1985, WHO/FAO/UNU (1985, Henry and Rees (1991, Molnár et al. (1998, Tverskaya et al. (1998 and Müller et al. (2004. In order to study the cross-validation of the RMR prediction equations and its standard measure (Weir 1949, the following statistics procedure were calculated: Pearson’s correlation (r ≥ 0.70, the “t” test with the signifi cance level of p0.05 in relation to the standard measure, with exception of the equations suggested for Tverskaya et al. (1998, and the two models of Müller et al (2004. Even though there was not a signifi cant difference, only the models considered for Henry and Rees (1991, and Molnár et al. (1995 had gotten constant error variation under 5%. All the equations analyzed in the study in girls had not reached criterion of correlation values of 0.70 with the indirect calorimetry. Analyzing the prediction equations of RMR in boys, all of them had moderate correlation coeffi cients with the indirect calorimetry, however below 0.70. Only the equation developed for Tverskaya et al. (1998 presented differences (p ABSTRACT0,05 em relação à medida padrão (Weir 1949, com exceção das equações sugeridas por Tverskaya et al. (1998 e os dois modelos de Müller et al (2004. Mesmo não havendo diferença signifi cativa, somente os modelos propostos por Henry e Rees (1991

  2. Developing a model for validation and prediction of bank customer ...

    African Journals Online (AJOL)

    Credit risk is the most important risk of banks. The main approaches of the bank to reduce credit risk are correct validation using the final status and the validation model parameters. High fuel of bank reserves and lost or outstanding facilities of banks indicate the lack of appropriate validation models in the banking network.

  3. Systematic validation of predicted microRNAs for cyclin D1

    International Nuclear Information System (INIS)

    Jiang, Qiong; Feng, Ming-Guang; Mo, Yin-Yuan

    2009-01-01

    MicroRNAs are the endogenous small non-coding RNA molecules capable of silencing protein coding genes at the posttranscriptional level. Based on computer-aided predictions, a single microRNA could have over a hundred of targets. On the other hand, a single protein-coding gene could be targeted by many potential microRNAs. However, only a relatively small number of these predicted microRNA/mRNA interactions are experimentally validated, and no systematic validation has been carried out using a reporter system. In this study, we used luciferease reporter assays to validate microRNAs that can silence cyclin D1 (CCND1) because CCND1 is a well known proto-oncogene implicated in a variety of types of cancers. We chose miRanda (http://www.microRNA.org) as a primary prediction method. We then cloned 51 of 58 predicted microRNA precursors into pCDH-CMV-MCS-EF1-copGFP and tested for their effect on the luciferase reporter carrying the 3'-untranslated region (UTR) of CCND1 gene. Real-time PCR revealed the 45 of 51 cloned microRNA precursors expressed a relatively high level of the exogenous microRNAs which were used in our validation experiments. By an arbitrary cutoff of 35% reduction, we identified 7 microRNAs that were able to suppress Luc-CCND1-UTR activity. Among them, 4 of them were previously validated targets and the rest 3 microRNAs were validated to be positive in this study. Of interest, we found that miR-503 not only suppressed the luciferase activity, but also suppressed the endogenous CCND1 both at protein and mRNA levels. Furthermore, we showed that miR-503 was able to reduce S phase cell populations and caused cell growth inhibition, suggesting that miR-503 may be a putative tumor suppressor. This study provides a more comprehensive picture of microRNA/CCND1 interactions and it further demonstrates the importance of experimental target validation

  4. Predicting the need for institutional care shortly after admission to rehabilitation: Rasch analysis and predictive validity of the BRASS Index.

    Science.gov (United States)

    Panella, L; La Porta, F; Caselli, S; Marchisio, S; Tennant, A

    2012-09-01

    Effective discharge planning is increasingly recognised as a critical component of hospital-based Rehabilitation. The BRASS index is a risk screening tool for identification, shortly after hospital admission, of patients who are at risk of post-discharge problems. To evaluate the internal construct validity and reliability of the Blaylock Risk Assessment Screening Score (BRASS) within the rehabilitation setting. Observational prospective study. Rehabilitation ward of an Italian district hospital. One hundred and four consecutively admitted patients. Using classical psychometric methods and Rasch analysis (RA), the internal construct validity and reliability of the BRASS were examined. Also, external and predictive validity of the Rasch-modified BRASS (RMB) score were determined. Reliability of the original BRASS was low (Cronbach's alpha=0.595) and factor analyses showed that it was clearly multidimensional. A RA, based on a reduced 7-BRASS item set (RMB), satisfied model's expectations. Reliability was 0.777. The RMB scores strongly correlated with the original BRASS (rho=0.952; P28 days (RR=7.6, 95%CI=1.8-31.9). This study demonstrated that the original BRASS was multidimensional and unreliable. However, the RMB holds adequate internal construct validity and is sufficiently reliable as a predictor of discharge problems for group, but not individual use. The application of tools and methods (such as the BRASS Index) developed under the biomedical paradigm in a Physical and Rehabilitation Medicine setting may have limitations. Further research is needed to develop, within the rehabilitation setting, a valid measuring tool of risk of post-discharge problems at the individual level.

  5. Validation of Model-Based Prognostics for Pneumatic Valves in a Demonstration Testbed

    Science.gov (United States)

    2014-10-02

    predict end of life ( EOL ) and remaining useful life (RUL). The approach still follows the general estimation-prediction framework devel- oped in the...atmosphere, with linearly increasing leak area. kA2leak = Cleak (16) We define valve end of life ( EOL ) through open/close time limits of the valves, as in...represents end of life ( EOL ), and ∆kE represents remaining useful life (RUL). For valves, timing requirements are provided that de- fine the maximum

  6. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

    Science.gov (United States)

    Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

    2017-05-22

    PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age

  7. Proactive, Reactive, and Romantic Relational Aggression in Adulthood: Measurement, Predictive Validity, Gender Differences, and Association with Intermittent Explosive Disorder

    OpenAIRE

    Murray-Close, Dianna; Ostrov, Jamie M.; Nelson, David A.; Crick, Nicki R.; Coccaro, Emil F.

    2009-01-01

    The psychometric properties of a recently introduced adult self-report of relational aggression are presented. Specifically, the predictive utility of proactive and reactive peer-directed relational aggression, as well as romantic relational aggression, are explored in a large (N = 1387) study of adults. The measure had adequate reliability and validity and the subscales demonstrated unique predictive abilities for a number of dependent variables. In particular, reactive but not proactive rel...

  8. Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

    Science.gov (United States)

    Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

    2017-10-01

    Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (PLearning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that

  9. Validation of the mortality prediction equation for damage control ...

    African Journals Online (AJOL)

    , preoperative lowest pH and lowest core body temperature to derive an equation for the purpose of predicting mortality in damage control surgery. It was shown to reliably predict death despite damage control surgery. The equation derivation ...

  10. Predictive validity of the Sødring Motor Evaluation of Stroke Patients (SMES).

    Science.gov (United States)

    Wyller, T B; Sødring, K M; Sveen, U; Ljunggren, A E; Bautz-Holter, E

    1996-12-01

    The Sødring Motor Evaluation of Stroke Patients (SMES) has been developed as an instrument for the evaluation by physiotherapists of motor function and activities in stroke patients. The predictive validity of the instrument was studied in a consecutive sample of 93 acute stroke patients, assessed in the acute phase and after one year. The outcome measures were: survival, residence at home or in institution, the Barthel ADL index (dichotomized at 19/20), and the Frenchay Activities Index (FAI) (dichotomized at 9/10). The SMES, scored in the acute phase, demonstrated a marginally significant predictive power regarding survival, but was a highly significant predictor regarding the other outcomes. The adjusted odds ratio for a good versus a poor outcome for patients in the upper versus the lower tertile of the SMES arm subscore was 5.4 (95% confidence interval 0.9-59) for survival, 11.5 (2.1-88) for living at home, 86.3 (11-infinity) for a high Barthel score, and 31.4 (5.2-288) for a high FAI score. We conclude that SMES has high predictive validity.

  11. Predictive Simulation of Material Failure Using Peridynamics -- Advanced Constitutive Modeling, Verification and Validation

    Science.gov (United States)

    2016-03-31

    AFRL-AFOSR-VA-TR-2016-0309 Predictive simulation of material failure using peridynamics- advanced constitutive modeling, verification , and validation... Self -explanatory. 8. PERFORMING ORGANIZATION REPORT NUMBER. Enter all unique alphanumeric report numbers assigned by the performing organization, e.g...for public release. Predictive simulation of material failure using peridynamics-advanced constitutive modeling, verification , and validation John T

  12. Basic Modelling principles and Validation of Software for Prediction of Collision Damage

    DEFF Research Database (Denmark)

    Simonsen, Bo Cerup

    2000-01-01

    This report describes basic modelling principles, the theoretical background and validation examples for the collision damage prediction module in the ISESO stand-alone software.......This report describes basic modelling principles, the theoretical background and validation examples for the collision damage prediction module in the ISESO stand-alone software....

  13. Predictive Validity of Curriculum-Based Measures for English Learners at Varying English Proficiency Levels

    Science.gov (United States)

    Kim, Jennifer Sun; Vanderwood, Michael L.; Lee, Catherine Y.

    2016-01-01

    This study examined the predictive validity of curriculum-based measures in reading for Spanish-speaking English learners (ELs) at various levels of English proficiency. Third-grade Spanish-speaking EL students were screened during the fall using DIBELS Oral Reading Fluency (DORF) and Daze. Predictive validity was examined in relation to spring…

  14. A mechanistic model for electricity consumption on dairy farms: Definition, validation, and demonstration

    NARCIS (Netherlands)

    Upton, J.R.; Murphy, M.; Shallo, L.; Groot Koerkamp, P.W.G.; Boer, de I.J.M.

    2014-01-01

    Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on

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

    Science.gov (United States)

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

    2011-01-01

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

  16. On the short circuit resilience of organic solar cells: prediction and validation.

    Science.gov (United States)

    Oostra, A Jolt; Smits, Edsger C P; de Leeuw, Dago M; Blom, Paul W M; Michels, Jasper J

    2015-09-07

    The operational characteristics of organic solar cells manufactured with large area processing methods suffers from the occurrence of short-circuits due to defects in the photoactive thin film stack. In this work we study the effect of a shunt resistance on an organic solar cell and demonstrate that device performance is not affected negatively as long as the shunt resistance is higher than approximately 1000 Ohm. By studying charge transport across PSS-lithium fluoride/aluminum (LiF/Al) shunting junctions we show that this prerequisite is already met by applying a sufficiently thick (>1.5 nm) LiF layer. We demonstrate that this remarkable shunt-resilience stems from the formation of a significant charge transport barrier at the PSS-LiF/Al interface. We validate our predictions by fabricating devices with deliberately severed photoactive layers and find an excellent agreement between the calculated and experimental current-voltage characteristics.

  17. Ford Plug-In Project: Bringing PHEVs to Market Demonstration and Validation Project

    Energy Technology Data Exchange (ETDEWEB)

    D' Annunzio, Julie [Ford Motor Company, Dearborn, MI (United States); Slezak, Lee [U.S. DOE Office of Energy Efficiency & Renewable Energy, Washington, DC (United States); Conley, John Jason [National Energy Technology Lab. (NETL), Albany, OR (United States)

    2014-03-26

    This project is in support of our national goal to reduce our dependence on fossil fuels. By supporting efforts that contribute toward the successful mass production of plug-in hybrid electric vehicles, our nation’s transportation-related fuel consumption can be offset with energy from the grid. Over four and a half years ago, when this project was originally initiated, plug-in electric vehicles were not readily available in the mass marketplace. Through the creation of a 21 unit plug-in hybrid vehicle fleet, this program was designed to demonstrate the feasibility of the technology and to help build cross-industry familiarity with the technology and interface of this technology with the grid. Ford Escape PHEV Demonstration Fleet 3 March 26, 2014 Since then, however, plug-in vehicles have become increasingly more commonplace in the market. Ford, itself, now offers an all-electric vehicle and two plug-in hybrid vehicles in North America and has announced a third plug-in vehicle offering for Europe. Lessons learned from this project have helped in these production vehicle launches and are mentioned throughout this report. While the technology of plugging in a vehicle to charge a high voltage battery with energy from the grid is now in production, the ability for vehicle-to-grid or bi-directional energy flow was farther away than originally expected. Several technical, regulatory and potential safety issues prevented progressing the vehicle-to-grid energy flow (V2G) demonstration and, after a review with the DOE, V2G was removed from this demonstration project. Also proving challenging were communications between a plug-in vehicle and the grid or smart meter. While this project successfully demonstrated the vehicle to smart meter interface, cross-industry and regulatory work is still needed to define the vehicle-to-grid communication interface.

  18. On Validation of Directional Wave Predictions: Review and Discussion

    National Research Council Canada - National Science Library

    Rogers, W. E; Wang, David W

    2006-01-01

    This report consists of supplementary materials for an article, accepted for publication in the "Journal of Atmospheric and Oceanic Technology," dealing with directional wave model validation by the same authors...

  19. Status self-validation of a multifunctional sensor using a multivariate relevance vector machine and predictive filters

    International Nuclear Information System (INIS)

    Shen, Zhengguang; Wang, Qi

    2013-01-01

    A novel strategy by using a multivariable relevance vector machine coupled with predictive filters for status self-validation of a multifunctional sensor is proposed. The working principle and online updating algorithm of predictive filters are emphasized for multiple fault detection, isolation and recovery (FDIR), and the incorrect sensor measurements are validated online. The multivariable relevance vector machine is then employed for the signal reconstruction of the multifunctional sensor to generate the final validated measurement values (VMV) of multiple measured components, in which its advantages of sparse models and multivariable simultaneous outputs are fully used. With all likely uncertainty sources of the multifunctional self-validating sensor taken into account, the uncertainty propagation model is deduced in detail to evaluate the online validated uncertainty (VU) under a fault-free situation while a qualitative uncertainty component is appended to indicate the accuracy changes of VMV under different types of fault. A real experimental system of a multifunctional self-validating sensor is designed to verify the performance of the proposed strategy. From the real-time capacity and fault recovery accuracy of FDIR, and runtime of signal reconstruction under small samples, a performance comparison among different methods is made. Results demonstrate that the proposed scheme provides a better solution to the status self-validation of a multifunctional self-validating sensor under both normal and abnormal situations. (paper)

  20. An approach to model validation and model-based prediction -- polyurethane foam case study.

    Energy Technology Data Exchange (ETDEWEB)

    Dowding, Kevin J.; Rutherford, Brian Milne

    2003-07-01

    analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model

  1. Final Technical Report: Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project

    Energy Technology Data Exchange (ETDEWEB)

    Ronald Grasman

    2011-12-31

    This report summarizes the work conducted under U.S. Department of Energy (DOE) under contract DE-FC36-04GO14285 by Mercedes-Benz & Research Development, North America (MBRDNA), Chrysler, Daimler, Mercedes Benz USA (MBUSA), BP, DTE Energy and NextEnergy to validate fuel cell technologies for infrastructure, transportation as well as assess technology and commercial readiness for the market. The Mercedes Team, together with its partners, tested the technology by operating and fueling hydrogen fuel cell vehicles under real world conditions in varying climate, terrain and driving conditions. Vehicle and infrastructure data was collected to monitor the progress toward the hydrogen vehicle and infrastructure performance targets of $2.00 to 3.00/gge hydrogen production cost and 2,000-hour fuel cell durability. Finally, to prepare the public for a hydrogen economy, outreach activities were designed to promote awareness and acceptance of hydrogen technology. DTE, BP and NextEnergy established hydrogen filling stations using multiple technologies for on-site hydrogen generation, storage and dispensing. DTE established a hydrogen station in Southfield, Michigan while NextEnergy and BP worked together to construct one hydrogen station in Detroit. BP constructed another fueling station in Burbank, California and provided a full-time hydrogen trailer at San Francisco, California and a hydrogen station located at Los Angeles International Airport in Southern, California. Stations were operated between 2005 and 2011. The Team deployed 30 Gen I Fuel Cell Vehicles (FCVs) in the beginning of the project. While 28 Gen I F-CELLs used the A-Class platform, the remaining 2 were Sprinter delivery vans. Fuel cell vehicles were operated by external customers for real-world operations in various regions (ecosystems) to capture various driving patterns and climate conditions (hot, moderate and cold). External operators consisted of F-CELL partner organizations in California and Michigan

  2. The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: Introduction and forensic developmental validation.

    Science.gov (United States)

    Chaitanya, Lakshmi; Breslin, Krystal; Zuñiga, Sofia; Wirken, Laura; Pośpiech, Ewelina; Kukla-Bartoszek, Magdalena; Sijen, Titia; Knijff, Peter de; Liu, Fan; Branicki, Wojciech; Kayser, Manfred; Walsh, Susan

    2018-07-01

    Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces. Here we introduce and forensically validate the HIrisPlex-S DNA test system (S for skin) for the simultaneous prediction of eye, hair, and skin colour from trace DNA. This FDP system consists of two SNaPshot-based multiplex assays targeting a total of 41 SNPs via a novel multiplex assay for 17 skin colour predictive SNPs and the previous HIrisPlex assay for 24 eye and hair colour predictive SNPs, 19 of which also contribute to skin colour prediction. The HIrisPlex-S system further comprises three statistical prediction models, the previously developed IrisPlex model for eye colour prediction based on 6 SNPs, the previous HIrisPlex model for hair colour prediction based on 22 SNPs, and the recently introduced HIrisPlex-S model for skin colour prediction based on 36 SNPs. In the forensic developmental validation testing, the novel 17-plex assay performed in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, as previously shown for the 24-plex assay. Sensitivity testing of the 17-plex assay revealed complete SNP profiles from as little as 63 pg of input DNA, equalling the previously demonstrated sensitivity threshold of the 24-plex HIrisPlex assay. Testing of simulated forensic casework samples such as blood, semen, saliva stains, of inhibited DNA samples, of low quantity touch (trace) DNA samples, and of artificially degraded DNA samples as well as

  3. Validation test for CAP88 predictions of tritium dispersion at Los Alamos National Laboratory.

    Science.gov (United States)

    Michelotti, Erika; Green, Andrew; Whicker, Jeffrey; Eisele, William; Fuehne, David; McNaughton, Michael

    2013-08-01

    Gaussian plume models, such as CAP88, are used regularly for estimating downwind concentrations from stack emissions. At many facilities, the U.S. Environmental Protection Agency (U.S. EPA) requires that CAP88 be used to demonstrate compliance with air quality regulations for public protection from emissions of radionuclides. Gaussian plume models have the advantage of being relatively simple and their use pragmatic; however, these models are based on simplifying assumptions and generally they are not capable of incorporating dynamic meteorological conditions or complex topography. These limitations encourage validation tests to understand the capabilities and limitations of the model for the specific application. Los Alamos National Laboratory (LANL) has complex topography but is required to use CAP88 for compliance with the Clean Air Act Subpart H. The purpose of this study was to test the accuracy of the CAP88 predictions against ambient air measurements using released tritium as a tracer. Stack emissions of tritium from two LANL stacks were measured and the dispersion modeled with CAP88 using local meteorology. Ambient air measurements of tritium were made at various distances and directions from the stacks. Model predictions and ambient air measurements were compared over the course of a full year's data. Comparative results were consistent with other studies and showed the CAP88 predictions of downwind tritium concentrations were on average about three times higher than those measured, and the accuracy of the model predictions were generally more consistent for annual averages than for bi-weekly data.

  4. Validation of stress prediction during solidification of cast components

    CSIR Research Space (South Africa)

    Paine, AP

    2007-07-01

    Full Text Available to solidify and undergoes changes in phases where different material laws are valid. In the fluid state the metal is almost stress free but as the part starts to solidify and shrink, stresses are induced in the casting due to constraints from the mould. Some...

  5. Validation and prediction of traditional Chinese physical operation on spinal disease using multiple deformation models.

    Science.gov (United States)

    Pan, Lei; Yang, Xubo; Gu, Lixu; Lu, Wenlong; Fang, Min

    2011-03-01

    Traditional Chinese medical massage is a physical manipulation that achieves satisfactory results on spinal diseases, according to its advocates. However, the method relies on an expert's experience. Accurate analysis and simulation of massage are essential for validation of traditional Chinese physical treatment. The objective of this study is to provide analysis and simulation that can reproducibly verify and predict treatment efficacy. An improved physical multi-deformation model for simulating human cervical spine is proposed. First, the human spine, which includes muscle, vertebrae and inter- vertebral disks, are segmented and reconstructed from clinical CT and MR images. Homogeneous landmark registration is employed to align the spine models before and after the massage manipulation. Central line mass spring and contact FEM deformation models are used to individually evaluate spinal anatomy variations. The response of the human spine during the massage process is simulated based on specific clinical cases. Ten sets of patient data, including muscle-force relationships, displacement of vertebrae, strain and stress distribution on inter-vertebral disks were collected, including the pre-operation, post-operation and the 3-month follow-up. The simulation results demonstrate that traditional Chinese massage could significantly affect and treat most mild spinal disease. A new method that simulates a traditional Chinese medical massage operation on the human spine may be a useful tool to scientifically validate and predict treatment efficacy.

  6. [Reliability and validity of the Braden Scale for predicting pressure sore risk].

    Science.gov (United States)

    Boes, C

    2000-12-01

    For more accurate and objective pressure sore risk assessment various risk assessment tools were developed mainly in the USA and Great Britain. The Braden Scale for Predicting Pressure Sore Risk is one such example. By means of a literature analysis of German and English texts referring to the Braden Scale the scientific control criteria reliability and validity will be traced and consequences for application of the scale in Germany will be demonstrated. Analysis of 4 reliability studies shows an exclusive focus on interrater reliability. Further, even though examination of 19 validity studies occurs in many different settings, such examination is limited to the criteria sensitivity and specificity (accuracy). The range of sensitivity and specificity level is 35-100%. The recommended cut off points rank in the field of 10 to 19 points. The studies prove to be not comparable with each other. Furthermore, distortions in these studies can be found which affect accuracy of the scale. The results of the here presented analysis show an insufficient proof for reliability and validity in the American studies. In Germany, the Braden scale has not yet been tested under scientific criteria. Such testing is needed before using the scale in different German settings. During the course of such testing, construction and study procedures of the American studies can be used as a basis as can the problems be identified in the analysis presented below.

  7. Validation of Individual Non-Linear Predictive Pharmacokinetic ...

    African Journals Online (AJOL)

    3Department of Veterinary Medicine, Faculty of Agriculture, University of Novi Sad, Novi Sad, Republic of Serbia ... Purpose: To evaluate the predictive performance of phenytoin multiple dosing non-linear pharmacokinetic ... status epilepticus affects an estimated 152,000 ..... causal factors, i.e., infection, inflammation, tissue.

  8. Validation of an internal hardwood log defect prediction model

    Science.gov (United States)

    R. Edward. Thomas

    2011-01-01

    The type, size, and location of internal defects dictate the grade and value of lumber sawn from hardwood logs. However, acquiring internal defect knowledge with x-ray/computed-tomography or magnetic-resonance imaging technology can be expensive both in time and cost. An alternative approach uses prediction models based on correlations among external defect indicators...

  9. Cost prediction following traumatic brain injury: model development and validation.

    Science.gov (United States)

    Spitz, Gershon; McKenzie, Dean; Attwood, David; Ponsford, Jennie L

    2016-02-01

    The ability to predict costs following a traumatic brain injury (TBI) would assist in planning treatment and support services by healthcare providers, insurers and other agencies. The objective of the current study was to develop predictive models of hospital, medical, paramedical, and long-term care (LTC) costs for the first 10 years following a TBI. The sample comprised 798 participants with TBI, the majority of whom were male and aged between 15 and 34 at time of injury. Costing information was obtained for hospital, medical, paramedical, and LTC costs up to 10 years postinjury. Demographic and injury-severity variables were collected at the time of admission to the rehabilitation hospital. Duration of PTA was the most important single predictor for each cost type. The final models predicted 44% of hospital costs, 26% of medical costs, 23% of paramedical costs, and 34% of LTC costs. Greater costs were incurred, depending on cost type, for individuals with longer PTA duration, obtaining a limb or chest injury, a lower GCS score, older age at injury, not being married or defacto prior to injury, living in metropolitan areas, and those reporting premorbid excessive or problem alcohol use. This study has provided a comprehensive analysis of factors predicting various types of costs following TBI, with the combination of injury-related and demographic variables predicting 23-44% of costs. PTA duration was the strongest predictor across all cost categories. These factors may be used for the planning and case management of individuals following TBI. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  10. Baseline social amotivation predicts 1-year functioning in UHR subjects: A validation and prospective investigation.

    Science.gov (United States)

    Lam, Max; Abdul Rashid, Nur Amirah; Lee, Sara-Ann; Lim, Jeanette; Foussias, George; Fervaha, Gagan; Ruhrman, Stephan; Remington, Gary; Lee, Jimmy

    2015-12-01

    Social amotivation and diminished expression have been reported to underlie negative symptomatology in schizophrenia. In the current study we sought to establish and validate these negative symptom domains in a large cohort of schizophrenia subjects (n=887) and individuals who are deemed to be Ultra-High Risk (UHR) for psychosis. Confirmatory factor analysis conducted on PANSS item domains demonstrate that the dual negative symptom domains exist in schizophrenia and UHR subjects. We further sought to examine if these negative symptom domains were associated with functioning in UHR subjects. Linear regression analyses confirmed that social amotivation predicted functioning in UHR subjects prospectively at 1 year follow up. Results suggest that the association between social amotivation and functioning is generalisable beyond schizophrenia populations to those who are at-risk of developing psychosis. Social amotivation may be an important dimensional clinical construct to be studied across a range of psychiatric conditions. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

  11. Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation: The Maugeri Model.

    Science.gov (United States)

    Scrutinio, Domenico; Lanzillo, Bernardo; Guida, Pietro; Mastropasqua, Filippo; Monitillo, Vincenzo; Pusineri, Monica; Formica, Roberto; Russo, Giovanna; Guarnaschelli, Caterina; Ferretti, Chiara; Calabrese, Gianluigi

    2017-12-01

    Prediction of outcome after stroke rehabilitation may help clinicians in decision-making and planning rehabilitation care. We developed and validated a predictive tool to estimate the probability of achieving improvement in physical functioning (model 1) and a level of independence requiring no more than supervision (model 2) after stroke rehabilitation. The models were derived from 717 patients admitted for stroke rehabilitation. We used multivariable logistic regression analysis to build each model. Then, each model was prospectively validated in 875 patients. Model 1 included age, time from stroke occurrence to rehabilitation admission, admission motor and cognitive Functional Independence Measure scores, and neglect. Model 2 included age, male gender, time since stroke onset, and admission motor and cognitive Functional Independence Measure score. Both models demonstrated excellent discrimination. In the derivation cohort, the area under the curve was 0.883 (95% confidence intervals, 0.858-0.910) for model 1 and 0.913 (95% confidence intervals, 0.884-0.942) for model 2. The Hosmer-Lemeshow χ 2 was 4.12 ( P =0.249) and 1.20 ( P =0.754), respectively. In the validation cohort, the area under the curve was 0.866 (95% confidence intervals, 0.840-0.892) for model 1 and 0.850 (95% confidence intervals, 0.815-0.885) for model 2. The Hosmer-Lemeshow χ 2 was 8.86 ( P =0.115) and 34.50 ( P =0.001), respectively. Both improvement in physical functioning (hazard ratios, 0.43; 0.25-0.71; P =0.001) and a level of independence requiring no more than supervision (hazard ratios, 0.32; 0.14-0.68; P =0.004) were independently associated with improved 4-year survival. A calculator is freely available for download at https://goo.gl/fEAp81. This study provides researchers and clinicians with an easy-to-use, accurate, and validated predictive tool for potential application in rehabilitation research and stroke management. © 2017 American Heart Association, Inc.

  12. Development and validation of outcome prediction models for aneurysmal subarachnoid haemorrhage : The SAHIT multinational cohort study

    NARCIS (Netherlands)

    Jaja, Blessing N R; Saposnik, Gustavo; Lingsma, Hester F.; Macdonald, Erin; Thorpe, Kevin E.; Mamdani, Muhammed; Steyerberg, Ewout W.; Molyneux, Andrew; Manoel, Airton Leonardo De Oliveira; Schatlo, Bawarjan; Hanggi, Daniel; Hasan, David M.; Wong, George K C; Etminan, Nima; Fukuda, Hitoshi; Torner, James C.; Schaller, Karl L.; Suarez, Jose I.; Stienen, Martin N.; Vergouwen, Mervyn D.I.; Rinkel, Gabriel J.E.; Spears, Julian; Cusimano, Michael D.; Todd, Michael; Le Roux, Peter; Kirkpatrick, Peter J.; Pickard, John; Van Den Bergh, Walter M.; Murray, Gordon D; Johnston, S. Claiborne; Yamagata, Sen; Mayer, Stephan A.; Schweizer, Tom A.; Macdonald, R. Loch

    2018-01-01

    Objective To develop and validate a set of practical prediction tools that reliably estimate the outcome of subarachnoid haemorrhage from ruptured intracranial aneurysms (SAH). Design Cohort study with logistic regression analysis to combine predictors and treatment modality. Setting Subarachnoid

  13. Prediction and Validation of Mars Pathfinder Hypersonic Aerodynamic Data Base

    Science.gov (United States)

    Gnoffo, Peter A.; Braun, Robert D.; Weilmuenster, K. James; Mitcheltree, Robert A.; Engelund, Walter C.; Powell, Richard W.

    1998-01-01

    Postflight analysis of the Mars Pathfinder hypersonic, continuum aerodynamic data base is presented. Measured data include accelerations along the body axis and axis normal directions. Comparisons of preflight simulation and measurements show good agreement. The prediction of two static instabilities associated with movement of the sonic line from the shoulder to the nose and back was confirmed by measured normal accelerations. Reconstruction of atmospheric density during entry has an uncertainty directly proportional to the uncertainty in the predicted axial coefficient. The sensitivity of the moment coefficient to freestream density, kinetic models and center-of-gravity location are examined to provide additional consistency checks of the simulation with flight data. The atmospheric density as derived from axial coefficient and measured axial accelerations falls within the range required for sonic line shift and static stability transition as independently determined from normal accelerations.

  14. DSM-5 antisocial personality disorder: predictive validity in a prison sample.

    Science.gov (United States)

    Edens, John F; Kelley, Shannon E; Lilienfeld, Scott O; Skeem, Jennifer L; Douglas, Kevin S

    2015-04-01

    Symptoms of antisocial personality disorder (ASPD), particularly remorselessness, are frequently introduced in legal settings as a risk factor for future violence in prison, despite a paucity of research on the predictive validity of this disorder. We examined whether an ASPD diagnosis or symptom-criteria counts could prospectively predict any form of institutional misconduct, as well as aggressive and violent infractions among newly admitted prisoners. Adult male (n = 298) and female (n = 55) offenders were recruited from 4 prison systems across the United States. At the time of study enrollment, diagnostic information was collected using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; APA, 1994) Axis II Personality Disorders (SCID-II; First, Gibbon, Spitzer, Williams, & Benjamin, 1997) supplemented by a detailed review of official records. Disciplinary records were obtained from inmates' respective prisons covering a 1-year period following study enrollment and misconduct was categorized hierarchically as any (general), aggressive (verbal/physical), or violent (physical). Dichotomous ASPD diagnoses and adult symptom-criteria counts did not significantly predict institutional misconduct across our 3 outcome variables, with effect sizes being close to 0 in magnitude. The symptom of remorselessness in particular showed no relation to future misconduct in prison. Childhood symptom counts of conduct disorder demonstrated modest predictive utility. Our results offer essentially no support for the claim that ASPD diagnoses can predict institutional misconduct in prison, regardless of the number of adult symptoms present. In forensic contexts, testimony that an ASPD diagnosis identifies defendants who will pose a serious threat while incarcerated in prison presently lacks any substantial scientific foundation. (c) 2015 APA, all rights reserved).

  15. Validation of predicted exponential concentration profiles of chemicals in soils

    International Nuclear Information System (INIS)

    Hollander, Anne; Baijens, Iris; Ragas, Ad; Huijbregts, Mark; Meent, Dik van de

    2007-01-01

    Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d p ) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d p -values should estimated be either based on local conditions or on a fixed d p -value, which we recommend to be 10 cm for chemicals with a log K ow > 3. - Multimedia mass model predictions will improve when taking into account depth dependent soil concentrations

  16. Validity of a Manual Soft Tissue Profile Prediction Method Following Mandibular Setback Osteotomy

    OpenAIRE

    Kolokitha, Olga-Elpis

    2007-01-01

    Objectives The aim of this study was to determine the validity of a manual cephalometric method used for predicting the post-operative soft tissue profiles of patients who underwent mandibular setback surgery and compare it to a computerized cephalometric prediction method (Dentofacial Planner). Lateral cephalograms of 18 adults with mandibular prognathism taken at the end of pre-surgical orthodontics and approximately one year after surgery were used. Methods To test the validity of the manu...

  17. Investigating Postgraduate College Admission Interviews: Generalizability Theory Reliability and Incremental Predictive Validity

    Science.gov (United States)

    Arce-Ferrer, Alvaro J.; Castillo, Irene Borges

    2007-01-01

    The use of face-to-face interviews is controversial for college admissions decisions in light of the lack of availability of validity and reliability evidence for most college admission processes. This study investigated reliability and incremental predictive validity of a face-to-face postgraduate college admission interview with a sample of…

  18. Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

    NARCIS (Netherlands)

    P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We

  19. Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study

    NARCIS (Netherlands)

    Onland, Wes; Debray, Thomas P.; Laughon, Matthew M.; Miedema, Martijn; Cools, Filip; Askie, Lisa M.; Asselin, Jeanette M.; Calvert, Sandra A.; Courtney, Sherry E.; Dani, Carlo; Durand, David J.; Marlow, Neil; Peacock, Janet L.; Pillow, J. Jane; Soll, Roger F.; Thome, Ulrich H.; Truffert, Patrick; Schreiber, Michael D.; van Reempts, Patrick; Vendettuoli, Valentina; Vento, Giovanni; van Kaam, Anton H.; Moons, Karel G.; Offringa, Martin

    2013-01-01

    Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical

  20. A Cross-Validation Study of Police Recruit Performance as Predicted by the IPI and MMPI.

    Science.gov (United States)

    Shusman, Elizabeth J.; And Others

    Validation and cross-validation studies were conducted using the Minnesota Multiphasic Personality Inventory (MMPI) and Inwald Personality Inventory (IPI) to predict job performance for 698 urban male police officers who completed a six-month training academy. Job performance criteria evaluated included absence, lateness, derelictions, negative…

  1. Performance Prediction and Validation: Data, Frameworks, and Considerations

    Energy Technology Data Exchange (ETDEWEB)

    Tinnesand, Heidi

    2017-05-19

    Improving the predictability and reliability of wind power generation and operations will reduce costs and potentially establish a framework to attract new capital into the distributed wind sector, a key cost reduction requirement highlighted in results from the distributed wind future market assessment conducted with dWind. Quantifying and refining the accuracy of project performance estimates will also directly address several of the key challenges identified by industry stakeholders in 2015 as part of the distributed wind resource assessment workshop and be cross-cutting for several other facets of the distributed wind portfolio. This presentation covers the efforts undertaken in 2016 to address these topics.

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

    International Nuclear Information System (INIS)

    Dehing-Oberije, Cary; De Ruysscher, Dirk; Petit, Steven; Van Meerbeeck, Jan; Vandecasteele, Katrien; De Neve, Wilfried; Dingemans, Anne Marie C.; El Naqa, Issam; Deasy, Joseph; Bradley, Jeff; Huang, Ellen; Lambin, Philippe

    2010-01-01

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

  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. External Validation of a Prediction Model for Successful External Cephalic Version

    NARCIS (Netherlands)

    de Hundt, Marcella; Vlemmix, Floortje; Kok, Marjolein; van der Steeg, Jan W.; Bais, Joke M.; Mol, Ben W.; van der Post, Joris A.

    2012-01-01

    We sought external validation of a prediction model for the probability of a successful external cephalic version (ECV). We evaluated the performance of the prediction model with calibration and discrimination. For clinical practice, we developed a score chart to calculate the probability of a

  5. Experimental validation of the twins prediction program for rolling noise. Pt.2: results

    NARCIS (Netherlands)

    Thompson, D.J.; Fodiman, P.; Mahé, H.

    1996-01-01

    Two extensive measurement campaigns have been carried out to validate the TWINS prediction program for rolling noise, as described in part 1 of this paper. This second part presents the experimental results of vibration and noise during train pass-bys and compares them with predictions from the

  6. Test-Retest Reliability and Predictive Validity of the Implicit Association Test in Children

    Science.gov (United States)

    Rae, James R.; Olson, Kristina R.

    2018-01-01

    The Implicit Association Test (IAT) is increasingly used in developmental research despite minimal evidence of whether children's IAT scores are reliable across time or predictive of behavior. When test-retest reliability and predictive validity have been assessed, the results have been mixed, and because these studies have differed on many…

  7. Validation of models that predict Cesarean section after induction of labor

    NARCIS (Netherlands)

    Verhoeven, C. J. M.; Oudenaarden, A.; Hermus, M. A. A.; Porath, M. M.; Oei, S. G.; Mol, B. W. J.

    2009-01-01

    Objective Models for the prediction of Cesarean delivery after induction of labor can be used to improve clinical decision-making. The objective of this study was to validate two existing models, published by Peregrine et al. and Rane et al., for the prediction of Cesarean section after induction of

  8. Bayesian Calibration, Validation and Uncertainty Quantification for Predictive Modelling of Tumour Growth: A Tutorial.

    Science.gov (United States)

    Collis, Joe; Connor, Anthony J; Paczkowski, Marcin; Kannan, Pavitra; Pitt-Francis, Joe; Byrne, Helen M; Hubbard, Matthew E

    2017-04-01

    In this work, we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example, we calibrate the model against experimental data that are subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model.

  9. Predicting the 6-month risk of severe hypoglycemia among adults with diabetes: Development and external validation of a prediction model.

    Science.gov (United States)

    Schroeder, Emily B; Xu, Stan; Goodrich, Glenn K; Nichols, Gregory A; O'Connor, Patrick J; Steiner, John F

    2017-07-01

    To develop and externally validate a prediction model for the 6-month risk of a severe hypoglycemic event among individuals with pharmacologically treated diabetes. The development cohort consisted of 31,674 Kaiser Permanente Colorado members with pharmacologically treated diabetes (2007-2015). The validation cohorts consisted of 38,764 Kaiser Permanente Northwest members and 12,035 HealthPartners members. Variables were chosen that would be available in electronic health records. We developed 16-variable and 6-variable models, using a Cox counting model process that allows for the inclusion of multiple 6-month observation periods per person. Across the three cohorts, there were 850,992 6-month observation periods, and 10,448 periods with at least one severe hypoglycemic event. The six-variable model contained age, diabetes type, HgbA1c, eGFR, history of a hypoglycemic event in the prior year, and insulin use. Both prediction models performed well, with good calibration and c-statistics of 0.84 and 0.81 for the 16-variable and 6-variable models, respectively. In the external validation cohorts, the c-statistics were 0.80-0.84. We developed and validated two prediction models for predicting the 6-month risk of hypoglycemia. The 16-variable model had slightly better performance than the 6-variable model, but in some practice settings, use of the simpler model may be preferred. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Can preventable adverse events be predicted among hospitalized older patients? The development and validation of a predictive model.

    NARCIS (Netherlands)

    Steeg, L. van de; Langelaan, M.; Wagner, C.

    2014-01-01

    Objective: To develop and validate a predictive model for preventable adverse events (AEs) in hospitalized older patients, using clinically important risk factors that are readily available on admission. Design: Data from two retrospective patient record review studies on AEs were used. Risk factors

  11. Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population

    NARCIS (Netherlands)

    Maaren, M.C. van; Steenbeek, C.D. van; Pharoah, P.D.; Witteveen, A.; Sonke, G.S.; Strobbe, L.J.A.; Poortmans, P.; Siesling, S.

    2017-01-01

    BACKGROUND: PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. METHODS: All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected

  12. Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population

    NARCIS (Netherlands)

    van Maaren, M. C.; van Steenbeek, C. D.; Pharoah, P. D.P.; Witteveen, A.; Sonke, Gabe S.; Strobbe, L.J.A.; Poortmans, P.M.P.; Siesling, S.

    2017-01-01

    Background PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. Methods All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected from

  13. A Demonstration of Mobility Prediction as a Service in Cloudified LTE Networks

    NARCIS (Netherlands)

    Zhao, Zhongliang; Karimzadeh Motallebi Azar, Morteza; Braun, Torsten; Pras, Aiko; van den Berg, Hans Leo

    2015-01-01

    Location prediction has attracted a significant amount of research effort. Being able to predict users’ movement benefits a wide range of communication systems, including location-based service/applications, mobile access control, mobile QoS provision, and resource management for mobile computation

  14. Predicting interactions from mechanistic information: Can omic data validate theories?

    International Nuclear Information System (INIS)

    Borgert, Christopher J.

    2007-01-01

    To address the most pressing and relevant issues for improving mixture risk assessment, researchers must first recognize that risk assessment is driven by both regulatory requirements and scientific research, and that regulatory concerns may expand beyond the purely scientific interests of researchers. Concepts of 'mode of action' and 'mechanism of action' are used in particular ways within the regulatory arena, depending on the specific assessment goals. The data requirements for delineating a mode of action and predicting interactive toxicity in mixtures are not well defined from a scientific standpoint due largely to inherent difficulties in testing certain underlying assumptions. Understanding the regulatory perspective on mechanistic concepts will be important for designing experiments that can be interpreted clearly and applied in risk assessments without undue reliance on extrapolation and assumption. In like fashion, regulators and risk assessors can be better equipped to apply mechanistic data if the concepts underlying mechanistic research and the limitations that must be placed on interpretation of mechanistic data are understood. This will be critically important for applying new technologies to risk assessment, such as functional genomics, proteomics, and metabolomics. It will be essential not only for risk assessors to become conversant with the language and concepts of mechanistic research, including new omic technologies, but also, for researchers to become more intimately familiar with the challenges and needs of risk assessment

  15. Testing the Predictive Validity of the Hendrich II Fall Risk Model.

    Science.gov (United States)

    Jung, Hyesil; Park, Hyeoun-Ae

    2018-03-01

    Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators. In addition, logistic regression analysis was used to identify factors that significantly affect the occurrence of a fall. Among the different time points, the maximum fall-risk score assessed between admission and falling or discharge showed the best predictive performance. Confusion or disorientation and having a poor ability to rise from a sitting position were significant risk factors for a fall.

  16. Validating health impact assessment: Prediction is difficult (especially about the future)

    International Nuclear Information System (INIS)

    Petticrew, Mark; Cummins, Steven; Sparks, Leigh; Findlay, Anne

    2007-01-01

    Health impact assessment (HIA) has been recommended as a means of estimating how policies, programmes and projects may impact on public health and on health inequalities. This paper considers the difference between predicting health impacts and measuring those impacts. It draws upon a case study of the building of a new hypermarket in a deprived area of Glasgow, which offered an opportunity to reflect on the issue of the predictive validity of HIA, and to consider the difference between potential and actual impacts. We found that the actual impacts of the new hypermarket on diet differed from that which would have been predicted based on previous studies. Furthermore, they challenge current received wisdom about the impact of food retail outlets in poorer areas. These results are relevant to the validity of HIA as a process and emphasise the importance of further research on the predictive validity of HIA, which should help improve its value to decision-makers

  17. The Prediction of Training Proficiency in Firefighters: A Study of Predictive Validity in Spain

    Directory of Open Access Journals (Sweden)

    Alfredo Berges

    2018-02-01

    Full Text Available The present study provides results of criterion validity in the selection of firefighters in Spain. The predictors were cognitive skills, job knowledge, and physical aptitudes, and the criterion was training proficiency. The process involves 639 candidates, but only 44 complete successfully the selection process. Our results support previous evidence showing that general cognitive ability is the best predictor of training proficiency, with an operational validity of .57. With respect to the other predictors, job knowledge presented an operational validity of .55 and physical tests of .49. In addition, multiple regression analysis showed that cognitive aptitude explains 33% of the variance, but when physical aptitudes are included the explained variance increases to 50%. If we also add job knowledge, explained variance increases to 55%. Our study offers recent results of criterion validity in a barely investigated job, gathered in a country other than the one where prior research had been carried out.

  18. CAN UPPER EXTREMITY FUNCTIONAL TESTS PREDICT THE SOFTBALL THROW FOR DISTANCE: A PREDICTIVE VALIDITY INVESTIGATION

    Science.gov (United States)

    Hanney, William J.; Kolber, Morey J.; Davies, George J.; Riemann, Bryan

    2011-01-01

    Introduction: Understanding the relationships between performance tests and sport activity is important to the rehabilitation specialist. The purpose of this study was two- fold: 1) To identify if relationships exist between tests of upper body strength and power (Single Arm Seated Shot Put, Timed Push-Up, Timed Modified Pull-Up, and The Davies Closed Kinetic Chain Upper Extremity Stability Test, and the softball throw for distance), 2) To determine which variable or group of variables best predicts the performance of a sport specific task (the softball throw for distance). Methods: One hundred eighty subjects (111 females and 69 males, aged 18-45 years) performed the 5 upper extremity tests. The Pearson product moment correlation and a stepwise regression were used to determine whether relationships existed between performance on the tests and which upper extremity test result best explained the performance on the softball throw for distance. Results: There were significant correlations (r=.33 to r=.70, p=0.001) between performance on all of the tests. The modified pull-up test was the best predictor of the performance on the softball throw for distance (r2= 48.7), explaining 48.7% of variation in performance. When weight, height, and age were added to the regression equation the r2 values increased to 64.5, 66.2, and 67.5 respectively. Conclusion: The results of this study indicate that several upper extremity tests demonstrate significant relationships with one another and with the softball throw for distance. The modified pull up test was the best predictor of performance on the softball throw for distance. PMID:21712942

  19. Validity of a simple Internet-based outcome-prediction tool in patients with total hip replacement: a pilot study.

    Science.gov (United States)

    Stöckli, Cornel; Theiler, Robert; Sidelnikov, Eduard; Balsiger, Maria; Ferrari, Stephen M; Buchzig, Beatus; Uehlinger, Kurt; Riniker, Christoph; Bischoff-Ferrari, Heike A

    2014-04-01

    We developed a user-friendly Internet-based tool for patients undergoing total hip replacement (THR) due to osteoarthritis to predict their pain and function after surgery. In the first step, the key questions were identified by statistical modelling in a data set of 375 patients undergoing THR. Based on multiple regression, we identified the two most predictive WOMAC questions for pain and the three most predictive WOMAC questions for functional outcome, while controlling for comorbidity, body mass index, age, gender and specific comorbidities relevant to the outcome. In the second step, a pilot study was performed to validate the resulting tool against the full WOMAC questionnaire among 108 patients undergoing THR. The mean difference between observed (WOMAC) and model-predicted value was -1.1 points (95% confidence interval, CI -3.8, 1.5) for pain and -2.5 points (95% CI -5.3, 0.3) for function. The model-predicted value was within 20% of the observed value in 48% of cases for pain and in 57% of cases for function. The tool demonstrated moderate validity, but performed weakly for patients with extreme levels of pain and extreme functional limitations at 3 months post surgery. This may have been partly due to early complications after surgery. However, the outcome-prediction tool may be useful in helping patients to become better informed about the realistic outcome of their THR.

  20. Demonstration of Linked UAV Observations and Atmospheric Model Predictions in Chem/Bio Attack Response

    National Research Council Canada - National Science Library

    Davidson, Kenneth

    2003-01-01

    ... meteorological data, and the means for linking the UAV data to real-time dispersion prediction. The primary modeling effort focused on an adaptation of the 'Wind On Constant Streamline Surfaces...

  1. External validation of multivariable prediction models: a systematic review of methodological conduct and reporting

    Science.gov (United States)

    2014-01-01

    Background Before considering whether to use a multivariable (diagnostic or prognostic) prediction model, it is essential that its performance be evaluated in data that were not used to develop the model (referred to as external validation). We critically appraised the methodological conduct and reporting of external validation studies of multivariable prediction models. Methods We conducted a systematic review of articles describing some form of external validation of one or more multivariable prediction models indexed in PubMed core clinical journals published in 2010. Study data were extracted in duplicate on design, sample size, handling of missing data, reference to the original study developing the prediction models and predictive performance measures. Results 11,826 articles were identified and 78 were included for full review, which described the evaluation of 120 prediction models. in participant data that were not used to develop the model. Thirty-three articles described both the development of a prediction model and an evaluation of its performance on a separate dataset, and 45 articles described only the evaluation of an existing published prediction model on another dataset. Fifty-seven percent of the prediction models were presented and evaluated as simplified scoring systems. Sixteen percent of articles failed to report the number of outcome events in the validation datasets. Fifty-four percent of studies made no explicit mention of missing data. Sixty-seven percent did not report evaluating model calibration whilst most studies evaluated model discrimination. It was often unclear whether the reported performance measures were for the full regression model or for the simplified models. Conclusions The vast majority of studies describing some form of external validation of a multivariable prediction model were poorly reported with key details frequently not presented. The validation studies were characterised by poor design, inappropriate handling

  2. Validation of new prognostic and predictive scores by sequential testing approach

    International Nuclear Information System (INIS)

    Nieder, Carsten; Haukland, Ellinor; Pawinski, Adam; Dalhaug, Astrid

    2010-01-01

    Background and Purpose: For practitioners, the question arises how their own patient population differs from that used in large-scale analyses resulting in new scores and nomograms and whether such tools actually are valid at a local level and thus can be implemented. A recent article proposed an easy-to-use method for the in-clinic validation of new prediction tools with a limited number of patients, a so-called sequential testing approach. The present study evaluates this approach in scores related to radiation oncology. Material and Methods: Three different scores were used, each predicting short overall survival after palliative radiotherapy (bone metastases, brain metastases, metastatic spinal cord compression). For each scenario, a limited number of consecutive patients entered the sequential testing approach. The positive predictive value (PPV) was used for validation of the respective score and it was required that the PPV exceeded 80%. Results: For two scores, validity in the own local patient population could be confirmed after entering 13 and 17 patients, respectively. For the third score, no decision could be reached even after increasing the sample size to 30. Conclusion: In-clinic validation of new predictive tools with sequential testing approach should be preferred over uncritical adoption of tools which provide no significant benefit to local patient populations. Often the necessary number of patients can be reached within reasonable time frames even in small oncology practices. In addition, validation is performed continuously as the data are collected. (orig.)

  3. Validation of new prognostic and predictive scores by sequential testing approach

    Energy Technology Data Exchange (ETDEWEB)

    Nieder, Carsten [Radiation Oncology Unit, Nordland Hospital, Bodo (Norway); Inst. of Clinical Medicine, Univ. of Tromso (Norway); Haukland, Ellinor; Pawinski, Adam; Dalhaug, Astrid [Radiation Oncology Unit, Nordland Hospital, Bodo (Norway)

    2010-03-15

    Background and Purpose: For practitioners, the question arises how their own patient population differs from that used in large-scale analyses resulting in new scores and nomograms and whether such tools actually are valid at a local level and thus can be implemented. A recent article proposed an easy-to-use method for the in-clinic validation of new prediction tools with a limited number of patients, a so-called sequential testing approach. The present study evaluates this approach in scores related to radiation oncology. Material and Methods: Three different scores were used, each predicting short overall survival after palliative radiotherapy (bone metastases, brain metastases, metastatic spinal cord compression). For each scenario, a limited number of consecutive patients entered the sequential testing approach. The positive predictive value (PPV) was used for validation of the respective score and it was required that the PPV exceeded 80%. Results: For two scores, validity in the own local patient population could be confirmed after entering 13 and 17 patients, respectively. For the third score, no decision could be reached even after increasing the sample size to 30. Conclusion: In-clinic validation of new predictive tools with sequential testing approach should be preferred over uncritical adoption of tools which provide no significant benefit to local patient populations. Often the necessary number of patients can be reached within reasonable time frames even in small oncology practices. In addition, validation is performed continuously as the data are collected. (orig.)

  4. Predictive validity of the comprehensive basic science examination mean score for assessment of medical students' performance

    Directory of Open Access Journals (Sweden)

    Firouz Behboudi

    2002-04-01

    Full Text Available Background Medical education curriculum improvements can be achieved bye valuating students performance. Medical students have to pass two undergraduate comprehensive examinations, basic science and preinternship, in Iran. Purpose To measure validity of the students' mean score in comprehensive basic science exam (CBSE for predicting their performance in later curriculum phases. Methods This descriptive cross-sectional study was conducted on 95 (38 women and 55 men Guilan medical university students. Their admission to the university was 81% by regional quota and 12% by shaheed and other organizations' share. They first enrolled in 1994 and were able to pass CBS£ at first try. Data on gender, regional quota, and average grades of CBS£, PC, and CPIE were collected by a questionnaire. The calculations were done by SPSS package. Results The correlation coefficient between CBS£ and CPIE mean scores (0.65 was higher than correlation coefficient between CBS£ and PC mean scores (0.49. The predictive validity of CBS£ average grade was significant for students' performance in CPIE; however, the predictive validity of CBSE mean scores for students I pe1jormance in PC was lower. Conclusion he students' mean score in CBSE can be a good denominator for their further admission. We recommend further research to assess the predictive validity for each one of the basic courses. Keywords predictive validity, comprehensive basic exam

  5. Demonstration Exercise of a Validated Sample Collection Method for Powders Suspected of Being Biological Agents in Georgia 2006

    International Nuclear Information System (INIS)

    Marsh, B.

    2007-01-01

    August 7, 2006 the state of Georgia conducted a collaborative sampling exercise between the Georgia National Guard 4th Civil Support Team Weapons of Mass Destruction (CST-WMD) and the Georgia Department of Human Resources Division of Public Health demonstrating a recently validated bulk powder sampling method. The exercise was hosted at the Federal Law Enforcement Training Center (FLETC) at Glynn County, Georgia and involved the participation of the Georgia Emergency Management Agency (GEMA), Georgia National Guard, Georgia Public Health Laboratories, the Federal Bureau of Investigation Atlanta Office, Georgia Coastal Health District, and the Glynn County Fire Department. The purpose of the exercise was to demonstrate a recently validated national sampling standard developed by the American Standards and Test Measures (ASTM) International; ASTM E2458 S tandard Practice for Bulk Sample Collection and Swab Sample Collection of Visible Powders Suspected of Being Biological Agents from Nonporous Surfaces . The intent of the exercise was not to endorse the sampling method, but to develop a model for exercising new sampling methods in the context of existing standard operating procedures (SOPs) while strengthening operational relationships between response teams and analytical laboratories. The exercise required a sampling team to respond real-time to an incident cross state involving a clandestine bio-terrorism production lab found within a recreational vehicle (RV). Sample targets consisted of non-viable gamma irradiated B. anthracis Sterne spores prepared by Dugway Proving Ground. Various spore concentration levels were collected by the ASTM method, followed by on- and off-scene analysis utilizing the Center for Disease Control (CDC) Laboratory Response Network (LRN) and National Guard Bureau (NGB) CST mobile Analytical Laboratory Suite (ALS) protocols. Analytical results were compared and detailed surveys of participant evaluation comments were examined. I will

  6. Implicit and explicit preferences for physical attractiveness in a romantic partner: a double dissociation in predictive validity.

    Science.gov (United States)

    Eastwick, Paul W; Eagly, Alice H; Finkel, Eli J; Johnson, Sarah E

    2011-11-01

    Five studies develop and examine the predictive validity of an implicit measure of the preference for physical attractiveness in a romantic partner. Three hypotheses were generally supported. First, 2 variants of the go/no-go association task revealed that participants, on average, demonstrate an implicit preference (i.e., a positive spontaneous affective reaction) for physical attractiveness in a romantic partner. Second, these implicit measures were not redundant with a traditional explicit measure: The correlation between these constructs was .00 on average, and the implicit measures revealed no reliable sex differences, unlike the explicit measure. Third, explicit and implicit measures exhibited a double dissociation in predictive validity. Specifically, explicit preferences predicted the extent to which attractiveness was associated with participants' romantic interest in opposite-sex photographs but not their romantic interest in real-life opposite-sex speed-daters or confederates. Implicit preferences showed the opposite pattern. This research extends prior work on implicit processes in romantic relationships and offers the first demonstration that any measure of a preference for a particular characteristic in a romantic partner (an implicit measure of physical attractiveness, in this case) predicts individuals' evaluation of live potential romantic partners.

  7. Predictive value and construct validity of the work functioning screener-healthcare (WFS-H)

    Science.gov (United States)

    Boezeman, Edwin J.; Nieuwenhuijsen, Karen; Sluiter, Judith K.

    2016-01-01

    Objectives: To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Methods: Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. Results: The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (pvalue and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers. PMID:27010085

  8. Predictive value and construct validity of the work functioning screener-healthcare (WFS-H).

    Science.gov (United States)

    Boezeman, Edwin J; Nieuwenhuijsen, Karen; Sluiter, Judith K

    2016-05-25

    To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (ppredictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers.

  9. Development and validation of a predictive model for excessive postpartum blood loss: A retrospective, cohort study.

    Science.gov (United States)

    Rubio-Álvarez, Ana; Molina-Alarcón, Milagros; Arias-Arias, Ángel; Hernández-Martínez, Antonio

    2018-03-01

    postpartum haemorrhage is one of the leading causes of maternal morbidity and mortality worldwide. Despite the use of uterotonics agents as preventive measure, it remains a challenge to identify those women who are at increased risk of postpartum bleeding. to develop and to validate a predictive model to assess the risk of excessive bleeding in women with vaginal birth. retrospective cohorts study. "Mancha-Centro Hospital" (Spain). the elaboration of the predictive model was based on a derivation cohort consisting of 2336 women between 2009 and 2011. For validation purposes, a prospective cohort of 953 women between 2013 and 2014 were employed. Women with antenatal fetal demise, multiple pregnancies and gestations under 35 weeks were excluded METHODS: we used a multivariate analysis with binary logistic regression, Ridge Regression and areas under the Receiver Operating Characteristic curves to determine the predictive ability of the proposed model. there was 197 (8.43%) women with excessive bleeding in the derivation cohort and 63 (6.61%) women in the validation cohort. Predictive factors in the final model were: maternal age, primiparity, duration of the first and second stages of labour, neonatal birth weight and antepartum haemoglobin levels. Accordingly, the predictive ability of this model in the derivation cohort was 0.90 (95% CI: 0.85-0.93), while it remained 0.83 (95% CI: 0.74-0.92) in the validation cohort. this predictive model is proved to have an excellent predictive ability in the derivation cohort, and its validation in a latter population equally shows a good ability for prediction. This model can be employed to identify women with a higher risk of postpartum haemorrhage. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Predictive validity of the Biomedical Admissions Test: an evaluation and case study.

    Science.gov (United States)

    McManus, I C; Ferguson, Eamonn; Wakeford, Richard; Powis, David; James, David

    2011-01-01

    There has been an increase in the use of pre-admission selection tests for medicine. Such tests need to show good psychometric properties. Here, we use a paper by Emery and Bell [2009. The predictive validity of the Biomedical Admissions Test for pre-clinical examination performance. Med Educ 43:557-564] as a case study to evaluate and comment on the reporting of psychometric data in the field of medical student selection (and the comments apply to many papers in the field). We highlight pitfalls when reliability data are not presented, how simple zero-order associations can lead to inaccurate conclusions about the predictive validity of a test, and how biases need to be explored and reported. We show with BMAT that it is the knowledge part of the test which does all the predictive work. We show that without evidence of incremental validity it is difficult to assess the value of any selection tests for medicine.

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

    Science.gov (United States)

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

    2014-05-01

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

  12. Test-retest reliability and predictive validity of the Implicit Association Test in children.

    Science.gov (United States)

    Rae, James R; Olson, Kristina R

    2018-02-01

    The Implicit Association Test (IAT) is increasingly used in developmental research despite minimal evidence of whether children's IAT scores are reliable across time or predictive of behavior. When test-retest reliability and predictive validity have been assessed, the results have been mixed, and because these studies have differed on many factors simultaneously (lag-time between testing administrations, domain, etc.), it is difficult to discern what factors may explain variability in existing test-retest reliability and predictive validity estimates. Across five studies (total N = 519; ages 6- to 11-years-old), we manipulated two factors that have varied in previous developmental research-lag-time and domain. An internal meta-analysis of these studies revealed that, across three different methods of analyzing the data, mean test-retest (rs of .48, .38, and .34) and predictive validity (rs of .46, .20, and .10) effect sizes were significantly greater than zero. While lag-time did not moderate the magnitude of test-retest coefficients, whether we observed domain differences in test-retest reliability and predictive validity estimates was contingent on other factors, such as how we scored the IAT or whether we included estimates from a unique sample (i.e., a sample containing gender typical and gender diverse children). Recommendations are made for developmental researchers that utilize the IAT in their research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  13. Longitudinal prediction and concurrent functioning of adolescent girls demonstrating various profiles of dating violence and victimization.

    Science.gov (United States)

    Chiodo, Debbie; Crooks, Claire V; Wolfe, David A; McIsaac, Caroline; Hughes, Ray; Jaffe, Peter G

    2012-08-01

    Adolescent girls are involved in physical dating violence as both perpetrators and victims, and there are negative consequences associated with each of these behaviors. This article used a prospective design with 519 girls dating in grade 9 to predict profiles of dating violence in grade 11 based on relationships with families of origin (child maltreatment experiences, harsh parenting), and peers (harassment, delinquency, relational aggression). In addition, dating violence profiles were compared on numerous indices of adjustment (school connectedness, grades, self-efficacy and community connectedness) and maladjustment (suicide attempts, distress, delinquency, sexual behavior) for descriptive purposes. The most common profile was no dating violence (n = 367) followed by mutual violence (n = 81). Smaller numbers of girls reported victimization or perpetration only (ns = 39 and 32, respectively). Predicting grade 11 dating violence profile membership from grade 9 relationships was limited, although delinquency, parental rejection, and sexual harassment perpetration predicted membership to the mutually violent group, and delinquency predicted the perpetrator-only group. Compared to the non-violent group, the mutually violent girls in grade 11 had lower grades, poorer self-efficacy, and lower school connectedness and community involvement. Furthermore, they had higher rates of peer aggression and delinquency, were less likely to use condoms and were much more likely to have considered suicide. There were fewer differences among the profiles for girls involved with dating violence. In addition, the victims-only group reported higher rates of sexual intercourse, comparable to the mutually violent group and those involved in nonviolent relationships. Implications for prevention and intervention are highlighted.

  14. Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting, and Benchmarking

    Science.gov (United States)

    Daetwyler, Hans D.; Calus, Mario P. L.; Pong-Wong, Ricardo; de los Campos, Gustavo; Hickey, John M.

    2013-01-01

    The genomic prediction of phenotypes and breeding values in animals and plants has developed rapidly into its own research field. Results of genomic prediction studies are often difficult to compare because data simulation varies, real or simulated data are not fully described, and not all relevant results are reported. In addition, some new methods have been compared only in limited genetic architectures, leading to potentially misleading conclusions. In this article we review simulation procedures, discuss validation and reporting of results, and apply benchmark procedures for a variety of genomic prediction methods in simulated and real example data. Plant and animal breeding programs are being transformed by the use of genomic data, which are becoming widely available and cost-effective to predict genetic merit. A large number of genomic prediction studies have been published using both simulated and real data. The relative novelty of this area of research has made the development of scientific conventions difficult with regard to description of the real data, simulation of genomes, validation and reporting of results, and forward in time methods. In this review article we discuss the generation of simulated genotype and phenotype data, using approaches such as the coalescent and forward in time simulation. We outline ways to validate simulated data and genomic prediction results, including cross-validation. The accuracy and bias of genomic prediction are highlighted as performance indicators that should be reported. We suggest that a measure of relatedness between the reference and validation individuals be reported, as its impact on the accuracy of genomic prediction is substantial. A large number of methods were compared in example simulated and real (pine and wheat) data sets, all of which are publicly available. In our limited simulations, most methods performed similarly in traits with a large number of quantitative trait loci (QTL), whereas in traits

  15. Prediction of flow in mix-proof valve by use of CFD - Validation by LDA

    DEFF Research Database (Denmark)

    Jensen, Bo Boye Busk; Friis, Alan

    2004-01-01

    was done on a spherical shaped mix-proof valve (MPV). Flow were predicted by Computational Fluid Dynamics (CFD) and validated by data obtained from experiments using laser sheet visualization and laser Doppler anemometry. Correction of the measured velocities and probe location was required as refraction......-wall region is shown. Fully 3D flow patterns were identified and valuable information was obtained for further investigations concerning prediction of cleanability in the MPV based on knowledge of the hydrodynamics herein....

  16. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

    Science.gov (United States)

    Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

    2018-05-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

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

    LENUS (Irish Health Repository)

    Na, Xi

    2015-04-23

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

  18. The predictive and external validity of the STarT Back Tool in Danish primary care.

    Science.gov (United States)

    Morsø, Lars; Kent, Peter; Albert, Hanne B; Hill, Jonathan C; Kongsted, Alice; Manniche, Claus

    2013-08-01

    The STarT Back Tool (SBT) was recently translated into Danish and its concurrent validity described. This study tested the predictive validity of the Danish SBT. Danish primary care patients (n = 344) were compared to a UK cohort. SBT subgroup validity for predicting high activity limitation at 3 months' follow-up was assessed using descriptive proportions, relative risks, AUC and odds ratios. The SBT had a statistically similar predictive ability in Danish primary care as in UK primary care. Unadjusted relative risks for poor clinical outcome on activity limitation in the Danish cohort were 2.4 (1.7-3.4) for the medium-risk subgroup and 2.8 (1.8-3.8) for the high-risk subgroup versus 3.1 (2.5-3.9) and 4.5 (3.6-5.6) for the UK cohort. Adjusting for confounders appeared to explain the lower predictive ability of the Danish high-risk group. The Danish SBT distinguished between low- and medium-risk subgroups with a similar predictive ability of the UK SBT. That distinction is useful information for informing patients about their expected prognosis and may help guiding clinicians' choice of treatment. However, cross-cultural differences in the SBT psychosocial subscale may reduce the predictive ability of the high-risk subgroup in Danish primary care.

  19. Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

    Science.gov (United States)

    Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G M; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M

    2014-01-01

    In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

  20. Tent Preservation Project - Demonstration/Validation for Replacement of Aqueous Copper 8 Quinolinolate Treatment of Cotton Webbing With RO-59-WP

    National Research Council Canada - National Science Library

    Bosselman, Suzanne E

    2008-01-01

    .... This report describes a demonstration/validation study of an alternative coating, RO-59-WP, as a potential additive to or replacement for Copper 8, which has been taken off the market several times...

  1. Implementation and Validation of a Self-Consumption Maximization Energy Management Strategy in a Vanadium Redox Flow BIPV Demonstrator

    Directory of Open Access Journals (Sweden)

    Luis Fialho

    2016-06-01

    Full Text Available This paper presents the results of the implementation of a self-consumption maximization strategy tested in a real-scale Vanadium Redox Flow Battery (VRFB (5 kW, 60 kWh and Building Integrated Photovoltaics (BIPV demonstrator (6.74 kWp. The tested energy management strategy aims to maximize the consumption of energy generated by a BIPV system through the usage of a battery. Whenever possible, the residual load is either stored in the battery to be used later or is supplied by the energy stored previously. The strategy was tested over seven days in a real-scale VRF battery to assess the validity of this battery to implement BIPV-focused energy management strategies. The results show that it was possible to obtain a self-consumption ratio of 100.0%, and that 75.6% of the energy consumed was provided by PV power. The VRFB was able to perform the strategy, although it was noticed that the available power (either to charge or discharge varied with the state of charge.

  2. Predicting AKI in emergency admissions: an external validation study of the acute kidney injury prediction score (APS).

    Science.gov (United States)

    Hodgson, L E; Dimitrov, B D; Roderick, P J; Venn, R; Forni, L G

    2017-03-08

    Hospital-acquired acute kidney injury (HA-AKI) is associated with a high risk of mortality. Prediction models or rules may identify those most at risk of HA-AKI. This study externally validated one of the few clinical prediction rules (CPRs) derived in a general medicine cohort using clinical information and data from an acute hospitals electronic system on admission: the acute kidney injury prediction score (APS). External validation in a single UK non-specialist acute hospital (2013-2015, 12 554 episodes); four cohorts: adult medical and general surgical populations, with and without a known preadmission baseline serum creatinine (SCr). Performance assessed by discrimination using area under the receiver operating characteristic curves (AUCROC) and calibration. HA-AKI incidence within 7 days (kidney disease: improving global outcomes (KDIGO) change in SCr) was 8.1% (n=409) of medical patients with known baseline SCr, 6.6% (n=141) in those without a baseline, 4.9% (n=204) in surgical patients with baseline and 4% (n=49) in those without. Across the four cohorts AUCROC were: medical with known baseline 0.65 (95% CIs 0.62 to 0.67) and no baseline 0.71 (0.67 to 0.75), surgical with baseline 0.66 (0.62 to 0.70) and no baseline 0.68 (0.58 to 0.75). For calibration, in medicine and surgical cohorts with baseline SCr, Hosmer-Lemeshow p values were non-significant, suggesting acceptable calibration. In the medical cohort, at a cut-off of five points on the APS to predict HA-AKI, positive predictive value was 16% (13-18%) and negative predictive value 94% (93-94%). Of medical patients with HA-AKI, those with an APS ≥5 had a significantly increased risk of death (28% vs 18%, OR 1.8 (95% CI 1.1 to 2.9), p=0.015). On external validation the APS on admission shows moderate discrimination and acceptable calibration to predict HA-AKI and may be useful as a severity marker when HA-AKI occurs. Harnessing linked data from primary care may be one way to achieve more accurate

  3. Development and validation of a predictive equation for lean body mass in children and adolescents.

    Science.gov (United States)

    Foster, Bethany J; Platt, Robert W; Zemel, Babette S

    2012-05-01

    Lean body mass (LBM) is not easy to measure directly in the field or clinical setting. Equations to predict LBM from simple anthropometric measures, which account for the differing contributions of fat and lean to body weight at different ages and levels of adiposity, would be useful to both human biologists and clinicians. To develop and validate equations to predict LBM in children and adolescents across the entire range of the adiposity spectrum. Dual energy X-ray absorptiometry was used to measure LBM in 836 healthy children (437 females) and linear regression was used to develop sex-specific equations to estimate LBM from height, weight, age, body mass index (BMI) for age z-score and population ancestry. Equations were validated using bootstrapping methods and in a local independent sample of 332 children and in national data collected by NHANES. The mean difference between measured and predicted LBM was - 0.12% (95% limits of agreement - 11.3% to 8.5%) for males and - 0.14% ( - 11.9% to 10.9%) for females. Equations performed equally well across the entire adiposity spectrum, as estimated by BMI z-score. Validation indicated no over-fitting. LBM was predicted within 5% of measured LBM in the validation sample. The equations estimate LBM accurately from simple anthropometric measures.

  4. The Predictive Validity of CBM Writing Indices for Eighth-Grade Students

    Science.gov (United States)

    Amato, Janelle M.; Watkins, Marley W.

    2011-01-01

    Curriculum-based measurement (CBM) is an alternative to traditional assessment techniques. Technical work has begun to identify CBM writing indices that are psychometrically sound for monitoring older students' writing proficiency. This study examined the predictive validity of CBM writing indices in a sample of 447 eighth-grade students.…

  5. A predictive validity study of the Learning Style Questionnaire (LSQ) using multiple, specific learning criteria

    NARCIS (Netherlands)

    Kappe, F.R.; Boekholt, L.; den Rooyen, C.; van der Flier, H.

    2009-01-01

    Multiple and specific learning criteria were used to examine the predictive validity of the Learning Style Questionnaire (LSQ). Ninety-nine students in a college of higher learning in The Netherlands participated in a naturally occurring field study. The students were categorized into one of four

  6. Validation of lactate clearance at 6 h for mortality prediction in critically ill children

    OpenAIRE

    Rajeev Kumar; Nirmal Kumar

    2016-01-01

    Background and Aims: To validate the lactate clearance (LC) at 6 h for mortality prediction in Pediatric Intensive Care Unit (PICU)-admitted patients and its comparison with a pediatric index of mortality 2 (PIM 2) score. Design: A prospective, observational study in a tertiary care center. Materials and Methods: Children

  7. Validity of the Optometry Admission Test in Predicting Performance in Schools and Colleges of Optometry.

    Science.gov (United States)

    Kramer, Gene A.; Johnston, JoElle

    1997-01-01

    A study examined the relationship between Optometry Admission Test scores and pre-optometry or undergraduate grade point average (GPA) with first and second year performance in optometry schools. The test's predictive validity was limited but significant, and comparable to those reported for other admission tests. In addition, the scores…

  8. Multilevel Assessment of the Predictive Validity of Teacher Made Tests in the Zimbabwean Primary Education Sector

    Science.gov (United States)

    Machingambi, Zadzisai

    2017-01-01

    The principal focus of this study was to undertake a multilevel assessment of the predictive validity of teacher made tests in the Zimbabwean primary education sector. A correlational research design was adopted for the study, mainly to allow for statistical treatment of data and subsequent classical hypotheses testing using the spearman's rho.…

  9. Development and validation of a digital work simulation to predict workplace deviance

    NARCIS (Netherlands)

    Dubbelt, L.; Oostrom, J.K.; drs. Hiemstra, A.M.F.; Modderman, J.P.L.

    2015-01-01

    ”This paper describes a new and innovative measure that is developed to predict workplace deviance through the measurement of Machiavellianism and Compliant Behavior. Two field studies were conducted to study the validity of the digital work simulation. In Study 1, (N = 113) support was found for

  10. A Parsimonious Instrument for Predicting Students' Intent to Pursue a Sales Career: Scale Development and Validation

    Science.gov (United States)

    Peltier, James W.; Cummins, Shannon; Pomirleanu, Nadia; Cross, James; Simon, Rob

    2014-01-01

    Students' desire and intention to pursue a career in sales continue to lag behind industry demand for sales professionals. This article develops and validates a reliable and parsimonious scale for measuring and predicting student intention to pursue a selling career. The instrument advances previous scales in three ways. The instrument is…

  11. Predictive validity of proposed remission criteria in first-episode schizophrenic patients responding to antipsychotics

    NARCIS (Netherlands)

    Wunderink, Lex; Nienhuis, Fokko J.; Sytema, Sjoerd; Wiersma, Durk

    The objective of this study was to examine the predictive validity of the remission criteria proposed by Andreasen et all in first-episode patients responding to antipsychotics. Antipsychotic responsive patients with first-episode schizophrenia showing symptom remission (n = 60) were compared with

  12. Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failure

    NARCIS (Netherlands)

    Voors, Adriaan A.; Ouwerkerk, Wouter; Zannad, Faiez; van Veldhuisen, Dirk J.; Samani, Nilesh J.; Ponikowski, Piotr; Ng, Leong L.; Metra, Marco; ter Maaten, Jozine M.; Lang, Chim C.; Hillege, Hans L.; van der Harst, Pim; Filippatos, Gerasimos; Dickstein, Kenneth; Cleland, John G.; Anker, Stefan D.; Zwinderman, Aeilko H.

    Introduction From a prospective multicentre multicountry clinical trial, we developed and validated risk models to predict prospective all-cause mortality and hospitalizations because of heart failure (HF) in patients with HF. Methods and results BIOSTAT-CHF is a research programme designed to

  13. Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failure

    NARCIS (Netherlands)

    Voors, Adriaan A.; Ouwerkerk, Wouter; Zannad, Faiez; van Veldhuisen, Dirk J.; Samani, Nilesh J.; Ponikowski, Piotr; Ng, Leong L.; Metra, Marco; ter Maaten, Jozine M.; Lang, Chim C.; Hillege, Hans L.; van der Harst, Pim; Filippatos, Gerasimos; Dickstein, Kenneth; Cleland, John G.; Anker, Stefan D.; Zwinderman, Aeilko H.

    2017-01-01

    Introduction From a prospective multicentre multicountry clinical trial, we developed and validated risk models to predict prospective all-cause mortality and hospitalizations because of heart failure (HF) in patients with HF. Methods and results BIOSTAT-CHF is a research programme designed to

  14. Predictive Validity of Early Literacy Measures for Korean English Language Learners in the United States

    Science.gov (United States)

    Han, Jeanie Nam; Vanderwood, Michael L.; Lee, Catherine Y.

    2015-01-01

    This study examined the predictive validity of early literacy measures with first-grade Korean English language learners (ELLs) in the United States at varying levels of English proficiency. Participants were screened using Dynamic Indicators of Basic Early Literacy Skills (DIBELS) Phoneme Segmentation Fluency (PSF), DIBELS Nonsense Word Fluency…

  15. Predictive Validity and Accuracy of Oral Reading Fluency for English Learners

    Science.gov (United States)

    Vanderwood, Michael L.; Tung, Catherine Y.; Checca, C. Jason

    2014-01-01

    The predictive validity and accuracy of an oral reading fluency (ORF) measure for a statewide assessment in English language arts was examined for second-grade native English speakers (NESs) and English learners (ELs) with varying levels of English proficiency. In addition to comparing ELs with native English speakers, the impact of English…

  16. Validation of Occupants’ Behaviour Models for Indoor Quality Parameter and Energy Consumption Prediction

    DEFF Research Database (Denmark)

    Fabi, Valentina; Sugliano, Martina; Andersen, Rune Korsholm

    2015-01-01

    Occupants’ behaviour related to building control system plays a significant role to achieve thermal comfort and air quality in naturally-ventilated buildings. Generally, the published models of occupant's behavior are not validated, meaning that the predictive power has not yet been tested. For t...

  17. Incremental Validity of the WJ III COG: Limited Predictive Effects beyond the GIA-E

    Science.gov (United States)

    McGill, Ryan J.; Busse, R. T.

    2015-01-01

    This study is an examination of the incremental validity of Cattell-Horn-Carroll (CHC) broad clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III COG) for predicting scores on the Woodcock-Johnson III Tests of Achievement (WJ III ACH). The participants were children and adolescents, ages 6-18 (n = 4,722), drawn from the WJ…

  18. Validation of forcefields in predicting the physical and thermophysical properties of emeraldine base polyaniline

    NARCIS (Netherlands)

    Chen, X.P.; Yuan, C.A.; Wong, C.K.Y.; Koh, S.W.; Zhang, G.Q.

    2011-01-01

    We report a molecular modelling study to validate the forcefields [condensed-phase optimised molecular potentials for atomistic simulation studies (COMPASS) and polymer-consistent forcefield (PCFF)] in predicting the physical and thermophysical properties of polymers. This work comprises of two key

  19. Testing the Predictive Validity and Construct of Pathological Video Game Use

    Science.gov (United States)

    Groves, Christopher L.; Gentile, Douglas; Tapscott, Ryan L.; Lynch, Paul J.

    2015-01-01

    Three studies assessed the construct of pathological video game use and tested its predictive validity. Replicating previous research, Study 1 produced evidence of convergent validity in 8th and 9th graders (N = 607) classified as pathological gamers. Study 2 replicated and extended the findings of Study 1 with college undergraduates (N = 504). Predictive validity was established in Study 3 by measuring cue reactivity to video games in college undergraduates (N = 254), such that pathological gamers were more emotionally reactive to and provided higher subjective appraisals of video games than non-pathological gamers and non-gamers. The three studies converged to show that pathological video game use seems similar to other addictions in its patterns of correlations with other constructs. Conceptual and definitional aspects of Internet Gaming Disorder are discussed. PMID:26694472

  20. Testing the Predictive Validity and Construct of Pathological Video Game Use

    Directory of Open Access Journals (Sweden)

    Christopher L. Groves

    2015-12-01

    Full Text Available Three studies assessed the construct of pathological video game use and tested its predictive validity. Replicating previous research, Study 1 produced evidence of convergent validity in 8th and 9th graders (N = 607 classified as pathological gamers. Study 2 replicated and extended the findings of Study 1 with college undergraduates (N = 504. Predictive validity was established in Study 3 by measuring cue reactivity to video games in college undergraduates (N = 254, such that pathological gamers were more emotionally reactive to and provided higher subjective appraisals of video games than non-pathological gamers and non-gamers. The three studies converged to show that pathological video game use seems similar to other addictions in its patterns of correlations with other constructs. Conceptual and definitional aspects of Internet Gaming Disorder are discussed.

  1. Development and validation of a prediction model for loss of physical function in elderly hemodialysis patients.

    Science.gov (United States)

    Fukuma, Shingo; Shimizu, Sayaka; Shintani, Ayumi; Kamitani, Tsukasa; Akizawa, Tadao; Fukuhara, Shunichi

    2017-09-05

    Among aging hemodialysis patients, loss of physical function has become a major issue. We developed and validated a model of predicting loss of physical function among elderly hemodialysis patients. We conducted a cohort study involving maintenance hemodialysis patients  ≥65 years of age from the Dialysis Outcomes and Practice Pattern Study in Japan. The derivation cohort included 593 early phase (1996-2004) patients and the temporal validation cohort included 447 late-phase (2005-12) patients. The main outcome was the incidence of loss of physical function, defined as the 12-item Short Form Health Survey physical function score decreasing to 0 within a year. Using backward stepwise logistic regression by Akaike's Information Criteria, six predictors (age, gender, dementia, mental health, moderate activity and ascending stairs) were selected for the final model. Points were assigned based on the regression coefficients and the total score was calculated by summing the points for each predictor. In total, 65 (11.0%) and 53 (11.9%) hemodialysis patients lost their physical function within 1 year in the derivation and validation cohorts, respectively. This model has good predictive performance quantified by both discrimination and calibration. The proportion of the loss of physical function increased sequentially through low-, middle-, and high-score categories based on the model (2.5%, 11.7% and 22.3% in the validation cohort, respectively). The loss of physical function was strongly associated with 1-year mortality [adjusted odds ratio 2.48 (95% confidence interval 1.26-4.91)]. We developed and validated a risk prediction model with good predictive performance for loss of physical function in elderly hemodialysis patients. Our simple prediction model may help physicians and patients make more informed decisions for healthy longevity. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA.

  2. Development and validation of a CFD model predicting the backfill process of a nuclear waste gallery

    International Nuclear Information System (INIS)

    Gopala, Vinay Ramohalli; Lycklama a Nijeholt, Jan-Aiso; Bakker, Paul; Haverkate, Benno

    2011-01-01

    dynamics (CFD) tool box. Volume of fluid method (VOF) is used to track the interface between grout and air. The CFD model is validated and tested in three steps. First, the numerical implementation of the Bingham model is verified against an analytical solution for a channel flow. Second, the capability of the model for the prediction of the flow of grout is tested by means of a comparison of the simulations with experimental results from two standard flowability tests for concrete: the V-funnel flow time and slump flow tests. As a third step, the CFD model is compared with experiments in a transparent Plexiglas experimental test setup performed at Delft University of Technology, to test the model under more practical and realistic conditions. This experimental setup is a 1:12.5 scaled version of the setup of the full-scale mock-up test for backfilling of a waste gallery with emplaced canisters used in the European 6th framework project ESDRED (). Furthermore, the plexiglas setup is used to study the influence of different backfill parameters. The CFD results for a channel flow shows good comparison against the analytical solution, demonstrating the correct implementation of the Bingham model in OpenFOAM. Also, the CFD results for the flowability tests show very good comparison with the experimental results, thereby ensuring a good prediction of the flow of grout. The simulations of the backfill process show good qualitative comparison with the plexiglas experiment. However, occurrence of segregation and also varying rheological properties of the grout in the plexiglas experiment results in significant differences between the simulation and the experiment.

  3. Validations and improvements of airfoil trailing-edge noise prediction models using detailed experimental data

    DEFF Research Database (Denmark)

    Kamruzzaman, M.; Lutz, Th.; Würz, W.

    2012-01-01

    This paper describes an extensive assessment and a step by step validation of different turbulent boundary-layer trailing-edge noise prediction schemes developed within the European Union funded wind energy project UpWind. To validate prediction models, measurements of turbulent boundary-layer pr...... with measurements in the frequency region higher than 1 kHz, whereas they over-predict the sound pressure level in the low-frequency region. Copyright © 2011 John Wiley & Sons, Ltd.......-layer properties such as two-point turbulent velocity correlations, the spectra of the associated wall pressure fluctuations and the emitted trailing-edge far-field noise were performed in the laminar wind tunnel of the Institute of Aerodynamics and Gas Dynamics, University of Stuttgart. The measurements were...... carried out for a NACA 643-418 airfoil, at Re  =  2.5 ×106, angle of attack of −6° to 6°. Numerical results of different prediction schemes are extensively validated and discussed elaborately. The investigations on the TNO-Blake noise prediction model show that the numerical wall pressure fluctuation...

  4. External validation of the ability of the DRAGON score to predict outcome after thrombolysis treatment

    DEFF Research Database (Denmark)

    Ovesen, Christian Aavang; Christensen, Anders; Nielsen, J K

    2013-01-01

    Easy-to-perform and valid assessment scales for the effect of thrombolysis are essential in hyperacute stroke settings. Because of this we performed an external validation of the DRAGON scale proposed by Strbian et al. in a Danish cohort. All patients treated with intravenous recombinant plasmino......Easy-to-perform and valid assessment scales for the effect of thrombolysis are essential in hyperacute stroke settings. Because of this we performed an external validation of the DRAGON scale proposed by Strbian et al. in a Danish cohort. All patients treated with intravenous recombinant...... and their modified Rankin Scale (mRS) was assessed after 3 months. Three hundred and three patients were included in the analysis. The DRAGON scale proved to have a good discriminative ability for predicting highly unfavourable outcome (mRS 5-6) (area under the curve-receiver operating characteristic [AUC-ROC]: 0...

  5. Predictive Validity of Explicit and Implicit Threat Overestimation in Contamination Fear

    Science.gov (United States)

    Green, Jennifer S.; Teachman, Bethany A.

    2012-01-01

    We examined the predictive validity of explicit and implicit measures of threat overestimation in relation to contamination-fear outcomes using structural equation modeling. Undergraduate students high in contamination fear (N = 56) completed explicit measures of contamination threat likelihood and severity, as well as looming vulnerability cognitions, in addition to an implicit measure of danger associations with potential contaminants. Participants also completed measures of contamination-fear symptoms, as well as subjective distress and avoidance during a behavioral avoidance task, and state looming vulnerability cognitions during an exposure task. The latent explicit (but not implicit) threat overestimation variable was a significant and unique predictor of contamination fear symptoms and self-reported affective and cognitive facets of contamination fear. On the contrary, the implicit (but not explicit) latent measure predicted behavioral avoidance (at the level of a trend). Results are discussed in terms of differential predictive validity of implicit versus explicit markers of threat processing and multiple fear response systems. PMID:24073390

  6. Review and evaluation of performance measures for survival prediction models in external validation settings

    Directory of Open Access Journals (Sweden)

    M. Shafiqur Rahman

    2017-04-01

    Full Text Available Abstract Background When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. Methods An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Results Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell’s concordance measure which tended to increase as censoring increased. Conclusions We recommend that Uno’s concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller’s measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston’s D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive

  7. Predictive validity of pre-admission assessments on medical student performance.

    Science.gov (United States)

    Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

    2017-11-24

    To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

  8. Prediction of prostate cancer in unscreened men: external validation of a risk calculator.

    Science.gov (United States)

    van Vugt, Heidi A; Roobol, Monique J; Kranse, Ries; Määttänen, Liisa; Finne, Patrik; Hugosson, Jonas; Bangma, Chris H; Schröder, Fritz H; Steyerberg, Ewout W

    2011-04-01

    Prediction models need external validation to assess their value beyond the setting where the model was derived from. To assess the external validity of the European Randomized study of Screening for Prostate Cancer (ERSPC) risk calculator (www.prostatecancer-riskcalculator.com) for the probability of having a positive prostate biopsy (P(posb)). The ERSPC risk calculator was based on data of the initial screening round of the ERSPC section Rotterdam and validated in 1825 and 531 men biopsied at the initial screening round in the Finnish and Swedish sections of the ERSPC respectively. P(posb) was calculated using serum prostate specific antigen (PSA), outcome of digital rectal examination (DRE), transrectal ultrasound and ultrasound assessed prostate volume. The external validity was assessed for the presence of cancer at biopsy by calibration (agreement between observed and predicted outcomes), discrimination (separation of those with and without cancer), and decision curves (for clinical usefulness). Prostate cancer was detected in 469 men (26%) of the Finnish cohort and in 124 men (23%) of the Swedish cohort. Systematic miscalibration was present in both cohorts (mean predicted probability 34% versus 26% observed, and 29% versus 23% observed, both pscreened men, but overestimated the risk of a positive biopsy. Further research is necessary to assess the performance and applicability of the ERSPC risk calculator when a clinical setting is considered rather than a screening setting. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

    Science.gov (United States)

    Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

    2011-01-01

    We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

  10. Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers.

    Directory of Open Access Journals (Sweden)

    Andrew T Kwon

    2011-12-01

    Full Text Available We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions.

  11. Validity of childhood adiposity classification in predicting adolescent overweight and obesity.

    Science.gov (United States)

    Huerta, Michael; Zarka, Salman; Bibi, Haim; Haviv, Jacob; Scharf, Shimon; Gdalevich, Michael

    2010-05-03

    Identification of children at risk for adolescent overweight can assist in targeting interventions. Uncertainty remains regarding the validity of current body mass index (BMI) reference values in predicting future risk on a population basis. This study aimed to assess the validity of current childhood adiposity classifications in predicting adolescent overweight and obesity among Israeli youth. Historical cohort study. School-based childhood health studies and adolescent physical examinations. A total of 3 163 subjects surveyed first at age 8-15 and again at age 17-19. Age, sex, height, weight and BMI. Sensitivity, specificity, positive and negative predictive values, and relative risk of childhood adiposity classification. Childhood overweight and obesity showed low sensitivity and high specificity for predicting adolescent overweight and obesity. Positive predictive values were low and varied by age and sex, but negative predictive values were consistently high in both sexes and all ages (range 0.85-0.99). After adjusting for age and sex, both childhood overweight and obesity substantially increased the risk of adolescent overweight (relative risk [RR] 7.03 and 7.20, respectively) and adolescent obesity (RR 24.34 and 28.41, respectively). Childhood overweight and obesity are strong risk factors for adolescent overweight and obesity among Israeli youth. Normal weight children were at very low risk for adolescent overweight. These findings suggest that population-based health promotion aimed at maintaining normal weight among children should be given preference over risk-guided approaches targeting weight reduction among obese children.

  12. A prediction algorithm for first onset of major depression in the general population: development and validation.

    Science.gov (United States)

    Wang, JianLi; Sareen, Jitender; Patten, Scott; Bolton, James; Schmitz, Norbert; Birney, Arden

    2014-05-01

    Prediction algorithms are useful for making clinical decisions and for population health planning. However, such prediction algorithms for first onset of major depression do not exist. The objective of this study was to develop and validate a prediction algorithm for first onset of major depression in the general population. Longitudinal study design with approximate 3-year follow-up. The study was based on data from a nationally representative sample of the US general population. A total of 28 059 individuals who participated in Waves 1 and 2 of the US National Epidemiologic Survey on Alcohol and Related Conditions and who had not had major depression at Wave 1 were included. The prediction algorithm was developed using logistic regression modelling in 21 813 participants from three census regions. The algorithm was validated in participants from the 4th census region (n=6246). Major depression occurred since Wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions, assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule-diagnostic and statistical manual for mental disorders IV. A prediction algorithm containing 17 unique risk factors was developed. The algorithm had good discriminative power (C statistics=0.7538, 95% CI 0.7378 to 0.7699) and excellent calibration (F-adjusted test=1.00, p=0.448) with the weighted data. In the validation sample, the algorithm had a C statistic of 0.7259 and excellent calibration (Hosmer-Lemeshow χ(2)=3.41, p=0.906). The developed prediction algorithm has good discrimination and calibration capacity. It can be used by clinicians, mental health policy-makers and service planners and the general public to predict future risk of having major depression. The application of the algorithm may lead to increased personalisation of treatment, better clinical decisions and more optimal mental health service planning.

  13. French validation and adaptation of the Grobman nomogram for prediction of vaginal birth after cesarean delivery.

    Science.gov (United States)

    Haumonte, J-B; Raylet, M; Christophe, M; Mauviel, F; Bertrand, A; Desbriere, R; d'Ercole, C

    2018-03-01

    To validate Grobman nomogram for predicting vaginal birth after cesarean delivery (VBAC) in a French population and adapt it. Multicenter retrospective study of maternal and obstetric factors associated with VBAC between May 2012 and May 2013 in 6 maternity units. External validation and adaptation of the prenatal and intrapartum Grobman nomograms for vaginal birth prediction after cesarean delivery in a French cohort. The study included 523 women with previous cesarean deliveries; 70% underwent a trial of labor for a subsequent delivery (n=367) with a success rate of 65% (n=240). In the univariate analysis, 5 factors were associated with successful VBAC: previous vaginal delivery before the cesarean (P6 (P=0.03). A potentially recurrent indication (defined as arrest of dilation or descent as the indication for the previous cesarean) (P=0.039), a hypertensive disorder during pregnancy (P=0.05), and labor induction (P=0.017) were each associated with failed VBAC. External validation of the prenatal and intrapartum Grobman nomograms showed an area under the ROC curve of 69% (95% CI: 0.638, 0.736) and 65% (95% CI: 0.599, 0.700) respectively. Adaptation of the nomogram to the French cohort resulted in the inclusion of the following factors: maternal age, body mass index at last prenatal visit, hypertensive disorder, gestational age at delivery, recurring indication, cervical dilatation, and induction of labor. Its area under the curve to predict successful VBAC was 78% (95% CI: 0.738, 0.825). The nomogram to predict VBAC developed by Grobman et al. is validated in the French population. Adaptation to the French population, by excluding ethnicity, appeared to improve its performance. Impact of the nomogram use on the caesarean section rate has to be validated in a randomized control trial. Copyright © 2017. Published by Elsevier Masson SAS.

  14. Validity of a manual soft tissue profile prediction method following mandibular setback osteotomy.

    Science.gov (United States)

    Kolokitha, Olga-Elpis

    2007-10-01

    The aim of this study was to determine the validity of a manual cephalometric method used for predicting the post-operative soft tissue profiles of patients who underwent mandibular setback surgery and compare it to a computerized cephalometric prediction method (Dentofacial Planner). Lateral cephalograms of 18 adults with mandibular prognathism taken at the end of pre-surgical orthodontics and approximately one year after surgery were used. To test the validity of the manual method the prediction tracings were compared to the actual post-operative tracings. The Dentofacial Planner software was used to develop the computerized post-surgical prediction tracings. Both manual and computerized prediction printouts were analyzed by using the cephalometric system PORDIOS. Statistical analysis was performed by means of t-test. Comparison between manual prediction tracings and the actual post-operative profile showed that the manual method results in more convex soft tissue profiles; the upper lip was found in a more prominent position, upper lip thickness was increased and, the mandible and lower lip were found in a less posterior position than that of the actual profiles. Comparison between computerized and manual prediction methods showed that in the manual method upper lip thickness was increased, the upper lip was found in a more anterior position and the lower anterior facial height was increased as compared to the computerized prediction method. Cephalometric simulation of post-operative soft tissue profile following orthodontic-surgical management of mandibular prognathism imposes certain limitations related to the methods implied. However, both manual and computerized prediction methods remain a useful tool for patient communication.

  15. Validation of a risk prediction model for Barrett's esophagus in an Australian population.

    Science.gov (United States)

    Ireland, Colin J; Gordon, Andrea L; Thompson, Sarah K; Watson, David I; Whiteman, David C; Reed, Richard L; Esterman, Adrian

    2018-01-01

    Esophageal adenocarcinoma is a disease that has a high mortality rate, the only known precursor being Barrett's esophagus (BE). While screening for BE is not cost-effective at the population level, targeted screening might be beneficial. We have developed a risk prediction model to identify people with BE, and here we present the external validation of this model. A cohort study was undertaken to validate a risk prediction model for BE. Individuals with endoscopy and histopathology proven BE completed a questionnaire containing variables previously identified as risk factors for this condition. Their responses were combined with data from a population sample for analysis. Risk scores were derived for each participant. Overall performance of the risk prediction model in terms of calibration and discrimination was assessed. Scores from 95 individuals with BE and 636 individuals from the general population were analyzed. The Brier score was 0.118, suggesting reasonable overall performance. The area under the receiver operating characteristic was 0.83 (95% CI 0.78-0.87). The Hosmer-Lemeshow statistic was p =0.14. Minimizing false positives and false negatives, the model achieved a sensitivity of 74% and a specificity of 73%. This study has validated a risk prediction model for BE that has a higher sensitivity than previous models.

  16. A Supervised Learning Process to Validate Online Disease Reports for Use in Predictive Models.

    Science.gov (United States)

    Patching, Helena M M; Hudson, Laurence M; Cooke, Warrick; Garcia, Andres J; Hay, Simon I; Roberts, Mark; Moyes, Catherine L

    2015-12-01

    Pathogen distribution models that predict spatial variation in disease occurrence require data from a large number of geographic locations to generate disease risk maps. Traditionally, this process has used data from public health reporting systems; however, using online reports of new infections could speed up the process dramatically. Data from both public health systems and online sources must be validated before they can be used, but no mechanisms exist to validate data from online media reports. We have developed a supervised learning process to validate geolocated disease outbreak data in a timely manner. The process uses three input features, the data source and two metrics derived from the location of each disease occurrence. The location of disease occurrence provides information on the probability of disease occurrence at that location based on environmental and socioeconomic factors and the distance within or outside the current known disease extent. The process also uses validation scores, generated by disease experts who review a subset of the data, to build a training data set. The aim of the supervised learning process is to generate validation scores that can be used as weights going into the pathogen distribution model. After analyzing the three input features and testing the performance of alternative processes, we selected a cascade of ensembles comprising logistic regressors. Parameter values for the training data subset size, number of predictors, and number of layers in the cascade were tested before the process was deployed. The final configuration was tested using data for two contrasting diseases (dengue and cholera), and 66%-79% of data points were assigned a validation score. The remaining data points are scored by the experts, and the results inform the training data set for the next set of predictors, as well as going to the pathogen distribution model. The new supervised learning process has been implemented within our live site and is

  17. Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model

    Directory of Open Access Journals (Sweden)

    Meyfroidt Geert

    2011-10-01

    Full Text Available Abstract Background The intensive care unit (ICU length of stay (LOS of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP, a machine learning technique. Methods Non-interventional study. Predictive modeling, separate development (n = 461 and validation (n = 499 cohort. GP models were developed to predict the probability of ICU discharge the day after surgery (classification task, and to predict the day of ICU discharge as a discrete variable (regression task. GP predictions were compared with predictions by EuroSCORE, nurses and physicians. The classification task was evaluated using aROC for discrimination, and Brier Score, Brier Score Scaled, and Hosmer-Lemeshow test for calibration. The regression task was evaluated by comparing median actual and predicted discharge, loss penalty function (LPF ((actual-predicted/actual and calculating root mean squared relative errors (RMSRE. Results Median (P25-P75 ICU length of stay was 3 (2-5 days. For classification, the GP model showed an aROC of 0.758 which was significantly higher than the predictions by nurses, but not better than EuroSCORE and physicians. The GP had the best calibration, with a Brier Score of 0.179 and Hosmer-Lemeshow p-value of 0.382. For regression, GP had the highest proportion of patients with a correctly predicted day of discharge (40%, which was significantly better than the EuroSCORE (p Conclusions A GP model that uses PDMS data of the first 4 hours after admission in the ICU of scheduled adult cardiac surgery patients was able to predict discharge from the ICU as a

  18. Reliability and Validity of the Load-Velocity Relationship to Predict the 1RM Back Squat.

    Science.gov (United States)

    Banyard, Harry G; Nosaka, Kazunori; Haff, G Gregory

    2017-07-01

    Banyard, HG, Nosaka, K, and Haff, GG. Reliability and validity of the load-velocity relationship to predict the 1RM back squat. J Strength Cond Res 31(7): 1897-1904, 2017-This study investigated the reliability and validity of the load-velocity relationship to predict the free-weight back squat one repetition maximum (1RM). Seventeen strength-trained males performed three 1RM assessments on 3 separate days. All repetitions were performed to full depth with maximal concentric effort. Predicted 1RMs were calculated by entering the mean concentric velocity of the 1RM (V1RM) into an individualized linear regression equation, which was derived from the load-velocity relationship of 3 (20, 40, 60% of 1RM), 4 (20, 40, 60, 80% of 1RM), or 5 (20, 40, 60, 80, 90% of 1RM) incremental warm-up sets. The actual 1RM (140.3 ± 27.2 kg) was very stable between 3 trials (ICC = 0.99; SEM = 2.9 kg; CV = 2.1%; ES = 0.11). Predicted 1RM from 5 warm-up sets up to and including 90% of 1RM was the most reliable (ICC = 0.92; SEM = 8.6 kg; CV = 5.7%; ES = -0.02) and valid (r = 0.93; SEE = 10.6 kg; CV = 7.4%; ES = 0.71) of the predicted 1RM methods. However, all predicted 1RMs were significantly different (p ≤ 0.05; ES = 0.71-1.04) from the actual 1RM. Individual variation for the actual 1RM was small between trials ranging from -5.6 to 4.8% compared with the most accurate predictive method up to 90% of 1RM, which was more variable (-5.5 to 27.8%). Importantly, the V1RM (0.24 ± 0.06 m·s) was unreliable between trials (ICC = 0.42; SEM = 0.05 m·s; CV = 22.5%; ES = 0.14). The load-velocity relationship for the full depth free-weight back squat showed moderate reliability and validity but could not accurately predict 1RM, which was stable between trials. Thus, the load-velocity relationship 1RM prediction method used in this study cannot accurately modify sessional training loads because of large V1RM variability.

  19. Validation of a prediction model that allows direct comparison of the Oxford Knee Score and American Knee Society clinical rating system.

    Science.gov (United States)

    Maempel, J F; Clement, N D; Brenkel, I J; Walmsley, P J

    2015-04-01

    This study demonstrates a significant correlation between the American Knee Society (AKS) Clinical Rating System and the Oxford Knee Score (OKS) and provides a validated prediction tool to estimate score conversion. A total of 1022 patients were prospectively clinically assessed five years after TKR and completed AKS assessments and an OKS questionnaire. Multivariate regression analysis demonstrated significant correlations between OKS and the AKS knee and function scores but a stronger correlation (r = 0.68, p Society of Bone & Joint Surgery.

  20. Using deuterated PAH amendments to validate chemical extraction methods to predict PAH bioavailability in soils

    International Nuclear Information System (INIS)

    Gomez-Eyles, Jose L.; Collins, Chris D.; Hodson, Mark E.

    2011-01-01

    Validating chemical methods to predict bioavailable fractions of polycyclic aromatic hydrocarbons (PAHs) by comparison with accumulation bioassays is problematic. Concentrations accumulated in soil organisms not only depend on the bioavailable fraction but also on contaminant properties. A historically contaminated soil was freshly spiked with deuterated PAHs (dPAHs). dPAHs have a similar fate to their respective undeuterated analogues, so chemical methods that give good indications of bioavailability should extract the fresh more readily available dPAHs and historic more recalcitrant PAHs in similar proportions to those in which they are accumulated in the tissues of test organisms. Cyclodextrin and butanol extractions predicted the bioavailable fraction for earthworms (Eisenia fetida) and plants (Lolium multiflorum) better than the exhaustive extraction. The PAHs accumulated by earthworms had a larger dPAH:PAH ratio than that predicted by chemical methods. The isotope ratio method described here provides an effective way of evaluating other chemical methods to predict bioavailability. - Research highlights: → Isotope ratios can be used to evaluate chemical methods to predict bioavailability. → Chemical methods predicted bioavailability better than exhaustive extractions. → Bioavailability to earthworms was still far from that predicted by chemical methods. - A novel method using isotope ratios to assess the ability of chemical methods to predict PAH bioavailability to soil biota.

  1. Using deuterated PAH amendments to validate chemical extraction methods to predict PAH bioavailability in soils

    Energy Technology Data Exchange (ETDEWEB)

    Gomez-Eyles, Jose L., E-mail: j.l.gomezeyles@reading.ac.uk [University of Reading, School of Human and Environmental Sciences, Soil Research Centre, Reading, RG6 6DW Berkshire (United Kingdom); Collins, Chris D.; Hodson, Mark E. [University of Reading, School of Human and Environmental Sciences, Soil Research Centre, Reading, RG6 6DW Berkshire (United Kingdom)

    2011-04-15

    Validating chemical methods to predict bioavailable fractions of polycyclic aromatic hydrocarbons (PAHs) by comparison with accumulation bioassays is problematic. Concentrations accumulated in soil organisms not only depend on the bioavailable fraction but also on contaminant properties. A historically contaminated soil was freshly spiked with deuterated PAHs (dPAHs). dPAHs have a similar fate to their respective undeuterated analogues, so chemical methods that give good indications of bioavailability should extract the fresh more readily available dPAHs and historic more recalcitrant PAHs in similar proportions to those in which they are accumulated in the tissues of test organisms. Cyclodextrin and butanol extractions predicted the bioavailable fraction for earthworms (Eisenia fetida) and plants (Lolium multiflorum) better than the exhaustive extraction. The PAHs accumulated by earthworms had a larger dPAH:PAH ratio than that predicted by chemical methods. The isotope ratio method described here provides an effective way of evaluating other chemical methods to predict bioavailability. - Research highlights: > Isotope ratios can be used to evaluate chemical methods to predict bioavailability. > Chemical methods predicted bioavailability better than exhaustive extractions. > Bioavailability to earthworms was still far from that predicted by chemical methods. - A novel method using isotope ratios to assess the ability of chemical methods to predict PAH bioavailability to soil biota.

  2. Predictive Validity of the Columbia-Suicide Severity Rating Scale for Short-Term Suicidal Behavior

    DEFF Research Database (Denmark)

    Conway, Paul Maurice; Erlangsen, Annette; Teasdale, Thomas William

    2017-01-01

    adolescents (90.6% females) who participated at follow-up (85.9%) out of the 99 (49.7%) baseline respondents. All adolescents were recruited from a specialized suicide-prevention clinic in Denmark. Through multivariate logistic regression analyses, we examined whether baseline suicidal behavior predicted......Using the Columbia-Suicide Severity Rating Scale (C-SSRS), we examined the predictive and incremental predictive validity of past-month suicidal behavior and ideation for short-term suicidal behavior among adolescents at high risk of suicide. The study was conducted in 2014 on a sample of 85...... subsequent suicidal behavior (actual attempts and suicidal behavior of any type, including preparatory acts, aborted, interrupted and actual attempts; mean follow-up of 80.8 days, SD = 52.4). Furthermore, we examined whether suicidal ideation severity and intensity incrementally predicted suicidal behavior...

  3. Broadband Fan Noise Prediction System for Turbofan Engines. Volume 3; Validation and Test Cases

    Science.gov (United States)

    Morin, Bruce L.

    2010-01-01

    Pratt & Whitney has developed a Broadband Fan Noise Prediction System (BFaNS) for turbofan engines. This system computes the noise generated by turbulence impinging on the leading edges of the fan and fan exit guide vane, and noise generated by boundary-layer turbulence passing over the fan trailing edge. BFaNS has been validated on three fan rigs that were tested during the NASA Advanced Subsonic Technology Program (AST). The predicted noise spectra agreed well with measured data. The predicted effects of fan speed, vane count, and vane sweep also agreed well with measurements. The noise prediction system consists of two computer programs: Setup_BFaNS and BFaNS. Setup_BFaNS converts user-specified geometry and flow-field information into a BFaNS input file. From this input file, BFaNS computes the inlet and aft broadband sound power spectra generated by the fan and FEGV. The output file from BFaNS contains the inlet, aft and total sound power spectra from each noise source. This report is the third volume of a three-volume set documenting the Broadband Fan Noise Prediction System: Volume 1: Setup_BFaNS User s Manual and Developer s Guide; Volume 2: BFaNS User s Manual and Developer s Guide; and Volume 3: Validation and Test Cases. The present volume begins with an overview of the Broadband Fan Noise Prediction System, followed by validation studies that were done on three fan rigs. It concludes with recommended improvements and additional studies for BFaNS.

  4. Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

    Directory of Open Access Journals (Sweden)

    Hui Miao

    Full Text Available BACKGROUND: In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. MATERIALS AND METHODS: We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic. RESULTS: We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53 to 0.63 (95% CI, 0.60-0.66. CONCLUSION: The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

  5. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    Science.gov (United States)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  6. Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer.

    Science.gov (United States)

    Yu, Ami; Woo, Sang Myung; Joo, Jungnam; Yang, Hye-Ryung; Lee, Woo Jin; Park, Sang-Jae; Nam, Byung-Ho

    2016-01-01

    There is no reliable screening tool to identify people with high risk of developing pancreatic cancer even though pancreatic cancer represents the fifth-leading cause of cancer-related death in Korea. The goal of this study was to develop an individualized risk prediction model that can be used to screen for asymptomatic pancreatic cancer in Korean men and women. Gender-specific risk prediction models for pancreatic cancer were developed using the Cox proportional hazards model based on an 8-year follow-up of a cohort study of 1,289,933 men and 557,701 women in Korea who had biennial examinations in 1996-1997. The performance of the models was evaluated with respect to their discrimination and calibration ability based on the C-statistic and Hosmer-Lemeshow type χ2 statistic. A total of 1,634 (0.13%) men and 561 (0.10%) women were newly diagnosed with pancreatic cancer. Age, height, BMI, fasting glucose, urine glucose, smoking, and age at smoking initiation were included in the risk prediction model for men. Height, BMI, fasting glucose, urine glucose, smoking, and drinking habit were included in the risk prediction model for women. Smoking was the most significant risk factor for developing pancreatic cancer in both men and women. The risk prediction model exhibited good discrimination and calibration ability, and in external validation it had excellent prediction ability. Gender-specific risk prediction models for pancreatic cancer were developed and validated for the first time. The prediction models will be a useful tool for detecting high-risk individuals who may benefit from increased surveillance for pancreatic cancer.

  7. Parent- and Self-Reported Dimensions of Oppositionality in Youth: Construct Validity, Concurrent Validity, and the Prediction of Criminal Outcomes in Adulthood

    Science.gov (United States)

    Aebi, Marcel; Plattner, Belinda; Metzke, Christa Winkler; Bessler, Cornelia; Steinhausen, Hans-Christoph

    2013-01-01

    Background: Different dimensions of oppositional defiant disorder (ODD) have been found as valid predictors of further mental health problems and antisocial behaviors in youth. The present study aimed at testing the construct, concurrent, and predictive validity of ODD dimensions derived from parent- and self-report measures. Method: Confirmatory…

  8. Advanced validation of CFD-FDTD combined method using highly applicable solver for reentry blackout prediction

    International Nuclear Information System (INIS)

    Takahashi, Yusuke

    2016-01-01

    An analysis model of plasma flow and electromagnetic waves around a reentry vehicle for radio frequency blackout prediction during aerodynamic heating was developed in this study. The model was validated based on experimental results from the radio attenuation measurement program. The plasma flow properties, such as electron number density, in the shock layer and wake region were obtained using a newly developed unstructured grid solver that incorporated real gas effect models and could treat thermochemically non-equilibrium flow. To predict the electromagnetic waves in plasma, a frequency-dependent finite-difference time-domain method was used. Moreover, the complicated behaviour of electromagnetic waves in the plasma layer during atmospheric reentry was clarified at several altitudes. The prediction performance of the combined model was evaluated with profiles and peak values of the electron number density in the plasma layer. In addition, to validate the models, the signal losses measured during communication with the reentry vehicle were directly compared with the predicted results. Based on the study, it was suggested that the present analysis model accurately predicts the radio frequency blackout and plasma attenuation of electromagnetic waves in plasma in communication. (paper)

  9. Predicting surgical site infection after spine surgery: a validated model using a prospective surgical registry.

    Science.gov (United States)

    Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

    2014-09-01

    The impact of surgical site infection (SSI) is substantial. Although previous study has determined relative risk and odds ratio (OR) values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of SSI, rather than relative risk or OR values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of SSI after spine surgery. This study performs a multivariate analysis of SSI after spine surgery using a large prospective surgical registry. Using the results of this analysis, this study will then create and validate a predictive model for SSI after spine surgery. The patient sample is from a high-quality surgical registry from our two institutions with prospectively collected, detailed demographic, comorbidity, and complication data. An SSI that required return to the operating room for surgical debridement. Using a prospectively collected surgical registry of more than 1,532 patients with extensive demographic, comorbidity, surgical, and complication details recorded for 2 years after the surgery, we identified several risk factors for SSI after multivariate analysis. Using the beta coefficients from those regression analyses, we created a model to predict the occurrence of SSI after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created a predictive model based on our beta coefficients from our multivariate analysis. The final predictive model for SSI had a receiver-operator curve characteristic of 0.72, considered to be a fair measure. The final model has been uploaded for use on SpineSage.com. We present a validated model for predicting SSI after spine surgery. The value in this model is that it gives

  10. Predictive Validity of a Student Self-Report Screener of Behavioral and Emotional Risk in an Urban High School

    Science.gov (United States)

    Dowdy, Erin; Harrell-Williams, Leigh; Dever, Bridget V.; Furlong, Michael J.; Moore, Stephanie; Raines, Tara; Kamphaus, Randy W.

    2016-01-01

    Increasingly, schools are implementing school-based screening for risk of behavioral and emotional problems; hence, foundational evidence supporting the predictive validity of screening instruments is important to assess. This study examined the predictive validity of the Behavior Assessment System for Children-2 Behavioral and Emotional Screening…

  11. Six factors of adult dyslexia assesed by cognitive tests and self-report questions: Very high predictive validity

    NARCIS (Netherlands)

    Tamboer, P.; Vorst, H.C.M.; de Jong, P.F.

    2017-01-01

    The Multiple Diagnostic Digital Dyslexia Test for Adults (MDDDT-A) consists of 12 newly developed tests and self-report questions in the Dutch language. Predictive validity and construct validity were investigated and compared with validity of a standard test battery of dyslexia (STB) in a sample of

  12. Assessment and validation of the CAESAR predictive model for bioconcentration factor (BCF in fish

    Directory of Open Access Journals (Sweden)

    Milan Chiara

    2010-07-01

    Full Text Available Abstract Background Bioconcentration factor (BCF describes the behaviour of a chemical in terms of its likelihood of concentrating in organisms in the environment. It is a fundamental property in recent regulations, such as the European Community Regulation on chemicals and their safe use or the Globally Harmonized System for classification, labelling and packaging. These new regulations consider the possibility of reducing or waiving animal tests using alternative methods, such as in silico methods. This study assessed and validated the CAESAR predictive model for BCF in fish. Results To validate the model, new experimental data were collected and used to create an external set, as a second validation set (a first validation exercise had been done just after model development. The performance of the model was compared with BCFBAF v3.00. For continuous values and for classification purposes the CAESAR BCF model gave better results than BCFBAF v3.00 for the chemicals in the applicability domain of the model. R2 and Q2 were good and accuracy in classification higher than 90%. Applying an offset of 0.5 to the compounds predicted with BCF close to the thresholds, the number of false negatives (the most dangerous errors dropped considerably (less than 0.6% of chemicals. Conclusions The CAESAR model for BCF is useful for regulatory purposes because it is robust, reliable and predictive. It is also fully transparent and documented and has a well-defined applicability domain, as required by REACH. The model is freely available on the CAESAR web site and easy to use. The reliability of the model reporting the six most similar compounds found in the CAESAR dataset, and their experimental and predicted values, can be evaluated.

  13. External Validation of Prediction Models for Pneumonia in Primary Care Patients with Lower Respiratory Tract Infection

    DEFF Research Database (Denmark)

    Schierenberg, Alwin; Minnaard, Margaretha C; Hopstaken, Rogier M

    2016-01-01

    BACKGROUND: Pneumonia remains difficult to diagnose in primary care. Prediction models based on signs and symptoms (S&S) serve to minimize the diagnostic uncertainty. External validation of these models is essential before implementation into routine practice. In this study all published S&S mode...... discriminative accuracy coupled with reasonable to good calibration across the IPD of different study populations. This model is therefore the main candidate for primary care use....

  14. Prediction and Validation of Heat Release Direct Injection Diesel Engine Using Multi-Zone Model

    Science.gov (United States)

    Anang Nugroho, Bagus; Sugiarto, Bambang; Prawoto; Shalahuddin, Lukman

    2014-04-01

    The objective of this study is to develop simulation model which capable to predict heat release of diesel combustion accurately in efficient computation time. A multi-zone packet model has been applied to solve the combustion phenomena inside diesel cylinder. The model formulations are presented first and then the numerical results are validated on a single cylinder direct injection diesel engine at various engine speed and timing injections. The model were found to be promising to fulfill the objective above.

  15. Reliability, Validity, and Predictive Utility of the 25-Item Criminogenic Cognitions Scale (CCS)

    OpenAIRE

    Tangney, June Price; Stuewig, Jeffrey; Furukawa, Emi; Kopelovich, Sarah; Meyer, Patrick; Cosby, Brandon

    2012-01-01

    Theory, research, and clinical reports suggest that moral cognitions play a role in initiating and sustaining criminal behavior. The 25 item Criminogenic Cognitions Scale (CCS) was designed to tap 5 dimensions: Notions of entitlement; Failure to Accept Responsibility; Short-Term Orientation; Insensitivity to Impact of Crime; and Negative Attitudes Toward Authority. Results from 552 jail inmates support the reliability, validity, and predictive utility of the measure. The CCS was linked to cri...

  16. Predictive validity of examinations at the Secondary Education Certificate (SEC) level

    OpenAIRE

    Farrugia, Josette; Ventura, Frank

    2007-01-01

    This paper presents the predictive validity of results obtained by 16-year-old Maltese students in the May 2004 Secondary Education Certificate (SEC) examinations in Biology, Chemistry, Physics, Mathematics, Computing, English and Maltese for the Advanced level examinations in these subjects taken by the same students two years later. The study checks whether the SEC level is a good foundation for the higher level, the likelihood of obtaining a high grade at A-level from particular SEC result...

  17. The East London glaucoma prediction score: web-based validation of glaucoma risk screening tool

    Science.gov (United States)

    Stephen, Cook; Benjamin, Longo-Mbenza

    2013-01-01

    AIM It is difficult for Optometrists and General Practitioners to know which patients are at risk. The East London glaucoma prediction score (ELGPS) is a web based risk calculator that has been developed to determine Glaucoma risk at the time of screening. Multiple risk factors that are available in a low tech environment are assessed to provide a risk assessment. This is extremely useful in settings where access to specialist care is difficult. Use of the calculator is educational. It is a free web based service. Data capture is user specific. METHOD The scoring system is a web based questionnaire that captures and subsequently calculates the relative risk for the presence of Glaucoma at the time of screening. Three categories of patient are described: Unlikely to have Glaucoma; Glaucoma Suspect and Glaucoma. A case review methodology of patients with known diagnosis is employed to validate the calculator risk assessment. RESULTS Data from the patient records of 400 patients with an established diagnosis has been captured and used to validate the screening tool. The website reports that the calculated diagnosis correlates with the actual diagnosis 82% of the time. Biostatistics analysis showed: Sensitivity = 88%; Positive predictive value = 97%; Specificity = 75%. CONCLUSION Analysis of the first 400 patients validates the web based screening tool as being a good method of screening for the at risk population. The validation is ongoing. The web based format will allow a more widespread recruitment for different geographic, population and personnel variables. PMID:23550097

  18. External validation of the NUn score for predicting anastomotic leakage after oesophageal resection.

    Science.gov (United States)

    Paireder, Matthias; Jomrich, Gerd; Asari, Reza; Kristo, Ivan; Gleiss, Andreas; Preusser, Matthias; Schoppmann, Sebastian F

    2017-08-29

    Early detection of anastomotic leakage (AL) after oesophageal resection for malignancy is crucial. This retrospective study validates a risk score, predicting AL, which includes C-reactive protein, albumin and white cell count in patients undergoing oesophageal resection between 2003 and 2014. For validation of the NUn score a receiver operating characteristic (ROC) curve is estimated. Area under the ROC curve (AUC) is reported with 95% confidence interval (CI). Among 258 patients (79.5% male) 32 patients showed signs of anastomotic leakage (12.4%). NUn score in our data has a median of 9.3 (range 6.2-17.6). The odds ratio for AL was 1.31 (CI 1.03-1.67; p = 0.028). AUC for AL was 0.59 (CI 0.47-0.72). Using the original cutoff value of 10, the sensitivity was 45.2% an the specificity was 73.8%. This results in a positive predictive value of 19.4% and a negative predictive value of 90.6%. The proportion of variation in AL occurrence, which is explained by the NUn score, was 2.5% (PEV = 0.025). This study provides evidence for an external validation of a simple risk score for AL after oesophageal resection. In this cohort, the NUn score is not useful due to its poor discrimination.

  19. Incremental Validity of Personality Measures in Predicting Underwater Performance and Adaptation.

    Science.gov (United States)

    Colodro, Joaquín; Garcés-de-Los-Fayos, Enrique J; López-García, Juan J; Colodro-Conde, Lucía

    2015-03-17

    Intelligence and personality traits are currently considered effective predictors of human behavior and job performance. However, there are few studies about their relevance in the underwater environment. Data from a sample of military personnel performing scuba diving courses were analyzed with regression techniques, testing the contribution of individual differences and ascertaining the incremental validity of the personality in an environment with extreme psychophysical demands. The results confirmed the incremental validity of personality traits (ΔR 2 = .20, f 2 = .25) over the predictive contribution of general mental ability (ΔR 2 = .07, f 2 = .08) in divers' performance. Moreover, personality (R(L)2 = .34) also showed a higher validity to predict underwater adaptation than general mental ability ( R(L)2 = .09). The ROC curve indicated 86% of the maximum possible discrimination power for the prediction of underwater adaptation, AUC = .86, p personality traits as predictors of an effective response to the changing circumstances of military scuba diving. They also may improve the understanding of the behavioral effects and psychophysiological complications of diving and can also provide guidance for psychological intervention and prevention of risk in this extreme environment.

  20. Measurement of predictive validity in violence risk assessment studies: a second-order systematic review.

    Science.gov (United States)

    Singh, Jay P; Desmarais, Sarah L; Van Dorn, Richard A

    2013-01-01

    The objective of the present review was to examine how predictive validity is analyzed and reported in studies of instruments used to assess violence risk. We reviewed 47 predictive validity studies published between 1990 and 2011 of 25 instruments that were included in two recent systematic reviews. Although all studies reported receiver operating characteristic curve analyses and the area under the curve (AUC) performance indicator, this methodology was defined inconsistently and findings often were misinterpreted. In addition, there was between-study variation in benchmarks used to determine whether AUCs were small, moderate, or large in magnitude. Though virtually all of the included instruments were designed to produce categorical estimates of risk - through the use of either actuarial risk bins or structured professional judgments - only a minority of studies calculated performance indicators for these categorical estimates. In addition to AUCs, other performance indicators, such as correlation coefficients, were reported in 60% of studies, but were infrequently defined or interpreted. An investigation of sources of heterogeneity did not reveal significant variation in reporting practices as a function of risk assessment approach (actuarial vs. structured professional judgment), study authorship, geographic location, type of journal (general vs. specialized audience), sample size, or year of publication. Findings suggest a need for standardization of predictive validity reporting to improve comparison across studies and instruments. Copyright © 2013 John Wiley & Sons, Ltd.

  1. In-Hospital Risk Prediction for Post-stroke Depression. Development and Validation of the Post-stroke Depression Prediction Scale

    NARCIS (Netherlands)

    Thóra Hafsteinsdóttir; Roelof G.A. Ettema; Diederick Grobbee; Prof. Dr. Marieke J. Schuurmans; Janneke van Man-van Ginkel; Eline Lindeman

    2013-01-01

    Background and Purpose—The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early

  2. Validation of the ureteral diameter ratio for predicting early spontaneous resolution of primary vesicoureteral reflux.

    Science.gov (United States)

    Arlen, Angela M; Kirsch, Andrew J; Leong, Traci; Cooper, Christopher S

    2017-08-01

    Management of primary vesicoureteral reflux (VUR) remains controversial, and reflux grade currently constitutes an important prognostic factor. Previous reports have demonstrated that distal ureteral diameter ratio (UDR) may be more predictive of outcome than vesicoureteral reflux (VUR) grade. We performed an external validation study in young children, evaluating early spontaneous resolution rates relative to reflux grade and UDR. Voiding cystourethrograms (VCUGs) were reviewed. UDR was computed by measuring largest ureteral diameter within the pelvis and dividing by the distance between the L1 and L3 vertebral bodies (Figure). VUR grade and UDR were tested in univariate and multivariable analyses. Primary outcome was status of VUR at last clinical follow-up (i.e. resolution, persistence, or surgical intervention). Demographics, VUR timing, laterality, and imaging indication were also assessed. One-hundred and forty-seven children (98 girls, 49 boys) were diagnosed with primary VUR at a mean age of 5.5 ± 4.7 months. Sixty-seven (45.6%) resolved spontaneously, 55 (37.4%) had persistent disease, and 25 (17%) were surgically corrected. Patients who spontaneously resolved had significantly lower VUR grade, refluxed later during bladder filling, and had significantly lower UDR. In a multivariable model, grade of VUR (p = 0.001), age early spontaneous resolution than grade alone. Furthermore, unlike traditional VUR grading where children with grade 1-5 may outgrow reflux depending on other factors, there appears to be a consistent UDR cutoff whereby patients are unlikely to resolve. In the present study, no child with a UDR greater than 0.43 experienced early spontaneous resolution, and only three (4.5%) of those with spontaneous resolution had a UDR above 0.35. UDR correlates with reflux grade, and is predictive of early resolution in children with primary VUR. UDR is an objective measurement of VUR, and provides valuable prognostic information about spontaneous

  3. Chemotherapy effectiveness and mortality prediction in surgically treated osteosarcoma dogs: A validation study.

    Science.gov (United States)

    Schmidt, A F; Nielen, M; Withrow, S J; Selmic, L E; Burton, J H; Klungel, O H; Groenwold, R H H; Kirpensteijn, J

    2016-03-01

    Canine osteosarcoma is the most common bone cancer, and an important cause of mortality and morbidity, in large purebred dogs. Previously we constructed two multivariable models to predict a dog's 5-month or 1-year mortality risk after surgical treatment for osteosarcoma. According to the 5-month model, dogs with a relatively low risk of 5-month mortality benefited most from additional chemotherapy treatment. In the present study, we externally validated these results using an independent cohort study of 794 dogs. External performance of our prediction models showed some disagreement between observed and predicted risk, mean difference: -0.11 (95% confidence interval [95% CI]-0.29; 0.08) for 5-month risk and 0.25 (95%CI 0.10; 0.40) for 1-year mortality risk. After updating the intercept, agreement improved: -0.0004 (95%CI-0.16; 0.16) and -0.002 (95%CI-0.15; 0.15). The chemotherapy by predicted mortality risk interaction (P-value=0.01) showed that the chemotherapy compared to no chemotherapy effectiveness was modified by 5-month mortality risk: dogs with a relatively lower risk of mortality benefited most from additional chemotherapy. Chemotherapy effectiveness on 1-year mortality was not significantly modified by predicted risk (P-value=0.28). In conclusion, this external validation study confirmed that our multivariable risk prediction models can predict a patient's mortality risk and that dogs with a relatively lower risk of 5-month mortality seem to benefit most from chemotherapy. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Predictive validity of childhood oppositional defiant disorder and conduct disorder: implications for the DSM-V.

    Science.gov (United States)

    Burke, Jeffrey D; Waldman, Irwin; Lahey, Benjamin B

    2010-11-01

    Data are presented from 3 studies of children and adolescents to evaluate the predictive validity of childhood oppositional defiant disorder (ODD) and conduct disorder (CD) as defined in the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV; American Psychiatric Association, 1994) and the International Classification of Diseases, Version 10 (ICD-10; World Health Organization, 1992). The present analyses strongly support the predictive validity of these diagnoses by showing that they predict both future psychopathology and enduring functional impairment. Furthermore, the present findings generally support the hierarchical developmental hypothesis in DSM-IV that some children with ODD progress to childhood-onset CD, and some youth with CD progress to antisocial personality disorder (APD). Nonetheless, they reveal that CD does not always co-occur with ODD, particularly during adolescence. Importantly, the present findings suggest that ICD-10 diagnostic criteria for ODD, which treat CD symptoms as ODD symptoms when diagnostic criteria for CD are not met, identify more functionally impaired children than the more restrictive DSM-IV definition of ODD. Filling this "hole" in the DSM-IV criteria for ODD should be a priority for the DSM-V. In addition, the present findings suggest that although the psychopathic trait of interpersonal callousness in childhood independently predicts future APD, these findings do not confirm the hypothesis that callousness distinguishes a subset of children with CD with an elevated risk for APD. PsycINFO Database Record (c) 2010 APA, all rights reserved

  5. Computational prediction and experimental validation of Ciona intestinalis microRNA genes

    Directory of Open Access Journals (Sweden)

    Pasquinelli Amy E

    2007-11-01

    Full Text Available Abstract Background This study reports the first collection of validated microRNA genes in the sea squirt, Ciona intestinalis. MicroRNAs are processed from hairpin precursors to ~22 nucleotide RNAs that base pair to target mRNAs and inhibit expression. As a member of the subphylum Urochordata (Tunicata whose larval form has a notochord, the sea squirt is situated at the emergence of vertebrates, and therefore may provide information about the evolution of molecular regulators of early development. Results In this study, computational methods were used to predict 14 microRNA gene families in Ciona intestinalis. The microRNA prediction algorithm utilizes configurable microRNA sequence conservation and stem-loop specificity parameters, grouping by miRNA family, and phylogenetic conservation to the related species, Ciona savignyi. The expression for 8, out of 9 attempted, of the putative microRNAs in the adult tissue of Ciona intestinalis was validated by Northern blot analyses. Additionally, a target prediction algorithm was implemented, which identified a high confidence list of 240 potential target genes. Over half of the predicted targets can be grouped into the gene ontology categories of metabolism, transport, regulation of transcription, and cell signaling. Conclusion The computational techniques implemented in this study can be applied to other organisms and serve to increase the understanding of the origins of non-coding RNAs, embryological and cellular developmental pathways, and the mechanisms for microRNA-controlled gene regulatory networks.

  6. Smartphone App-Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability.

    Science.gov (United States)

    Manor, Brad; Yu, Wanting; Zhu, Hao; Harrison, Rachel; Lo, On-Yee; Lipsitz, Lewis; Travison, Thomas; Pascual-Leone, Alvaro; Zhou, Junhong

    2018-01-30

    . Across all detected strides in the laboratory, stride times derived from the app and GAITRite mat were highly correlated (Ptime dual-task costs were also highly correlated (Ptimes (mean 16.9, SD 9.0 ms) was unaffected by the magnitude of stride time, walking condition, or pocket tightness. For both normal and dual-task trials, average stride times derived from app walking trials demonstrated excellent test-retest reliability within and between both laboratory and home-based assessments (intraclass correlation coefficient range .82-.94). The iPhone app we created enabled valid and reliable assessment of stride timing-with the smartphone in the pocket-during both normal and dual-task walking and within both laboratory and nonlaboratory environments. Additional work is warranted to expand the functionality of this tool to older adults and other patient populations. ©Brad Manor, Wanting Yu, Hao Zhu, Rachel Harrison, On-Yee Lo, Lewis Lipsitz, Thomas Travison, Alvaro Pascual-Leone, Junhong Zhou. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 30.01.2018.

  7. Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

    Science.gov (United States)

    Hunter, H. E.

    1972-01-01

    The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

  8. Perioperative Respiratory Adverse Events in Pediatric Ambulatory Anesthesia: Development and Validation of a Risk Prediction Tool.

    Science.gov (United States)

    Subramanyam, Rajeev; Yeramaneni, Samrat; Hossain, Mohamed Monir; Anneken, Amy M; Varughese, Anna M

    2016-05-01

    Perioperative respiratory adverse events (PRAEs) are the most common cause of serious adverse events in children receiving anesthesia. Our primary aim of this study was to develop and validate a risk prediction tool for the occurrence of PRAE from the onset of anesthesia induction until discharge from the postanesthesia care unit in children younger than 18 years undergoing elective ambulatory anesthesia for surgery and radiology. The incidence of PRAE was studied. We analyzed data from 19,059 patients from our department's quality improvement database. The predictor variables were age, sex, ASA physical status, morbid obesity, preexisting pulmonary disorder, preexisting neurologic disorder, and location of ambulatory anesthesia (surgery or radiology). Composite PRAE was defined as the presence of any 1 of the following events: intraoperative bronchospasm, intraoperative laryngospasm, postoperative apnea, postoperative laryngospasm, postoperative bronchospasm, or postoperative prolonged oxygen requirement. Development and validation of the risk prediction tool for PRAE were performed using a split sampling technique to split the database into 2 independent cohorts based on the year when the patient received ambulatory anesthesia for surgery and radiology using logistic regression. A risk score was developed based on the regression coefficients from the validation tool. The performance of the risk prediction tool was assessed by using tests of discrimination and calibration. The overall incidence of composite PRAE was 2.8%. The derivation cohort included 8904 patients, and the validation cohort included 10,155 patients. The risk of PRAE was 3.9% in the development cohort and 1.8% in the validation cohort. Age ≤ 3 years (versus >3 years), ASA physical status II or III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) significantly predicted the occurrence of PRAE in a multivariable logistic regression

  9. Computational Prediction and Rationalization, and Experimental Validation of Handedness Induction in Helical Aromatic Oligoamide Foldamers.

    Science.gov (United States)

    Liu, Zhiwei; Hu, Xiaobo; Abramyan, Ara M; Mészáros, Ádám; Csékei, Márton; Kotschy, András; Huc, Ivan; Pophristic, Vojislava

    2017-03-13

    Metadynamics simulations were used to describe the conformational energy landscapes of several helically folded aromatic quinoline carboxamide oligomers bearing a single chiral group at either the C or N terminus. The calculations allowed the prediction of whether a helix handedness bias occurs under the influence of the chiral group and gave insight into the interactions (sterics, electrostatics, hydrogen bonds) responsible for a particular helix sense preference. In the case of camphanyl-based and morpholine-based chiral groups, experimental data confirming the validity of the calculations were already available. New chiral groups with a proline residue were also investigated and were predicted to induce handedness. This prediction was verified experimentally through the synthesis of proline-containing monomers, their incorporation into an oligoamide sequence by solid phase synthesis and the investigation of handedness induction by NMR spectroscopy and circular dichroism. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. DES Prediction of Cavitation Erosion and Its Validation for a Ship Scale Propeller

    Science.gov (United States)

    Ponkratov, Dmitriy, Dr

    2015-12-01

    Lloyd's Register Technical Investigation Department (LR TID) have developed numerical functions for the prediction of cavitation erosion aggressiveness within Computational Fluid Dynamics (CFD) simulations. These functions were previously validated for a model scale hydrofoil and ship scale rudder [1]. For the current study the functions were applied to a cargo ship's full scale propeller, on which the severe cavitation erosion was reported. The performed Detach Eddy Simulation (DES) required a fine computational mesh (approximately 22 million cells), together with a very small time step (2.0E-4 s). As the cavitation for this type of vessel is primarily caused by a highly non-uniform wake, the hull was also included in the simulation. The applied method under predicted the cavitation extent and did not fully resolve the tip vortex; however, the areas of cavitation collapse were captured successfully. Consequently, the developed functions showed a very good prediction of erosion areas, as confirmed by comparison with underwater propeller inspection results.

  11. Validation of water sorption-based clay prediction models for calcareous soils

    DEFF Research Database (Denmark)

    Arthur, Emmanuel; Razzaghi, Fatemeh; Moosavi, Ali

    2017-01-01

    on prediction accuracy. The soils had clay content ranging from 9 to 61% and CaCO3 from 24 to 97%. The three water sorption models considered showed a reasonably fair prediction of the clay content from water sorption at 28% relative humidity (RMSE and ME values ranging from 10.6 to 12.1 and −8.1 to −4......Soil particle size distribution (PSD), particularly the active clay fraction, mediates soil engineering, agronomic and environmental functions. The tedious and costly nature of traditional methods of determining PSD prompted the development of water sorption-based models for determining the clay...... fraction. The applicability of such models to semi-arid soils with significant amounts of calcium carbonate and/or gypsum is unknown. The objective of this study was to validate three water sorption-based clay prediction models for 30 calcareous soils from Iran and identify the effect of CaCO3...

  12. Development and validation of a predictive technology for creep closure of underground rooms in salt

    International Nuclear Information System (INIS)

    Munson, D.E.; DeVries, K.L.

    1991-07-01

    Because of the concern for public health and safety, when compared to normal engineering practice, radioactive waste repositories have quite unusual requirements governing performance assessment. In part, performance assessment requires prediction of time-dependent or creep response of the repository hundreds to thousands of years into the future. In salt, one specific need is to predict, with confidence, the time at which the repository rooms creep closed sufficiently to encapsulate the waste and seal the repository. Thus, a major task of the Waste Isolation Pilot Plant (WIPP) Program is to develop and validate this predictive technology to calculate creep of repository rooms in the bedded salt deposits of Southeastern New Mexico. 19 refs., 15 figs., 2 tabs

  13. Development and validation of multivariable predictive model for thromboembolic events in lymphoma patients.

    Science.gov (United States)

    Antic, Darko; Milic, Natasa; Nikolovski, Srdjan; Todorovic, Milena; Bila, Jelena; Djurdjevic, Predrag; Andjelic, Bosko; Djurasinovic, Vladislava; Sretenovic, Aleksandra; Vukovic, Vojin; Jelicic, Jelena; Hayman, Suzanne; Mihaljevic, Biljana

    2016-10-01

    Lymphoma patients are at increased risk of thromboembolic events but thromboprophylaxis in these patients is largely underused. We sought to develop and validate a simple model, based on individual clinical and laboratory patient characteristics that would designate lymphoma patients at risk for thromboembolic event. The study population included 1,820 lymphoma patients who were treated in the Lymphoma Departments at the Clinics of Hematology, Clinical Center of Serbia and Clinical Center Kragujevac. The model was developed using data from a derivation cohort (n = 1,236), and further assessed in the validation cohort (n = 584). Sixty-five patients (5.3%) in the derivation cohort and 34 (5.8%) patients in the validation cohort developed thromboembolic events. The variables independently associated with risk for thromboembolism were: previous venous and/or arterial events, mediastinal involvement, BMI>30 kg/m(2) , reduced mobility, extranodal localization, development of neutropenia and hemoglobin level 3). For patients classified at risk (intermediate and high-risk scores), the model produced negative predictive value of 98.5%, positive predictive value of 25.1%, sensitivity of 75.4%, and specificity of 87.5%. A high-risk score had positive predictive value of 65.2%. The diagnostic performance measures retained similar values in the validation cohort. Developed prognostic Thrombosis Lymphoma - ThroLy score is more specific for lymphoma patients than any other available score targeting thrombosis in cancer patients. Am. J. Hematol. 91:1014-1019, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  14. Validation of CRIB II for prediction of mortality in premature babies.

    Science.gov (United States)

    Rastogi, Pallav Kumar; Sreenivas, V; Kumar, Nirmal

    2010-02-01

    Validation of Clinical Risk Index for Babies (CRIB II) score in predicting the neonatal mortality in preterm neonates < or = 32 weeks gestational age. Prospective cohort study. Tertiary care neonatal unit. 86 consecutively born preterm neonates with gestational age < or = 32 weeks. The five variables related to CRIB II were recorded within the first hour of admission for data analysis. The receiver operating characteristics (ROC) curve was used to check the accuracy of the mortality prediction. HL Goodness of fit test was used to see the discrepancy between observed and expected outcomes. A total of 86 neonates (males 59.6% mean birthweight: 1228 +/- 398 grams; mean gestational age: 28.3 +/- 2.4 weeks) were enrolled in the study, of which 17 (19.8%) left hospital against medical advice (LAMA) before reaching the study end point. Among 69 neonates completing the study, 24 (34.8%) had adverse outcome during hospital stay and 45 (65.2%) had favorable outcome. CRIB II correctly predicted adverse outcome in 90.3% (Hosmer Lemeshow goodness of fit test P=0.6). Area under curve (AUC) for CRIB II was 0.9032. In intention to treat analysis with LAMA cases included as survivors, the mortality prediction was 87%. If these were included as having died then mortality prediction was 83.1%. The CRIB II score was found to be a good predictive instrument for mortality in preterm infants < or = 32 weeks gestation.

  15. Positive predictive value of infective endocarditis in the Danish National Patient Registry: a validation study.

    Science.gov (United States)

    Østergaard, Lauge; Adelborg, Kasper; Sundbøll, Jens; Pedersen, Lars; Loldrup Fosbøl, Emil; Schmidt, Morten

    2018-05-30

    The positive predictive value of an infective endocarditis diagnosis is approximately 80% in the Danish National Patient Registry. However, since infective endocarditis is a heterogeneous disease implying long-term intravenous treatment, we hypothesiszed that the positive predictive value varies by length of hospital stay. A total of 100 patients with first-time infective endocarditis in the Danish National Patient Registry were identified from January 2010 - December 2012 at the University hospital of Aarhus and regional hospitals of Herning and Randers. Medical records were reviewed. We calculated the positive predictive value according to admission length, and separately for patients with a cardiac implantable electronic device and a prosthetic heart valve using the Wilson score method. Among the 92 medical records available for review, the majority of the patients had admission length ⩾2 weeks. The positive predictive value increased with length of admission. In patients with admission length value was 65% while it was 90% for admission length ⩾2 weeks. The positive predictive value was 81% for patients with a cardiac implantable electronic device and 87% for patients with a prosthetic valve. The positive predictive value of the infective endocarditis diagnosis in the Danish National Patient Registry is high for patients with admission length ⩾2 weeks. Using this algorithm, the Danish National Patient Registry provides a valid source for identifying infective endocarditis for research.

  16. A pilot validation of a modified Illness Perceptions Questionnaire designed to predict response to cognitive therapy for psychosis.

    Science.gov (United States)

    Marcus, Elena; Garety, Philippa; Weinman, John; Emsley, Richard; Dunn, Graham; Bebbington, Paul; Freeman, Daniel; Kuipers, Elizabeth; Fowler, David; Hardy, Amy; Waller, Helen; Jolley, Suzanne

    2014-12-01

    Clinical responsiveness to cognitive behavioural therapy for psychosis (CBTp) varies. Recent research has demonstrated that illness perceptions predict active engagement in therapy, and, thereby, better outcomes. In this study, we aimed to investigate the psychometric properties of a modification of the Illness Perceptions Questionnaire (M-IPQ) designed to predict response following CBTp. Fifty-six participants with persistent, distressing delusions completed the M-IPQ; forty before a brief CBT intervention targeting persecutory ideation and sixteen before and after a control condition. Additional predictors of outcome (delusional conviction, symptom severity and belief inflexibility) were assessed at baseline. Outcomes were assessed at baseline and at follow-up four to eight weeks later. The M-IPQ comprised two factors measuring problem duration and therapy-specific perceptions of Cure/Control. Associated subscales, formed by summing the relevant items for each factor, were reliable in their structure. The Cure/Control subscale was also reliable over time; showed convergent validity with other predictors of outcome; predicted therapy outcomes; and differentially predicted treatment effects. We measured outcome without an associated measure of engagement, in a small sample. Findings are consistent with hypothesis and existing research, but require replication in a larger, purposively recruited sample. The Cure/Control subscale of the M-IPQ shows promise as a predictor of response to therapy. Specifically targeting these illness perceptions in the early stages of cognitive behavioural therapy may improve engagement and, consequently, outcomes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. Evaluation of the phototoxicity of unsubstituted and alkylated polycyclic aromatic hydrocarbons to mysid shrimp (Americamysis bahia): Validation of predictive models.

    Science.gov (United States)

    Finch, Bryson E; Marzooghi, Solmaz; Di Toro, Dominic M; Stubblefield, William A

    2017-08-01

    Crude oils are composed of an assortment of hydrocarbons, some of which are polycyclic aromatic hydrocarbons (PAHs). Polycyclic aromatic hydrocarbons are of particular interest due to their narcotic and potential phototoxic effects. Several studies have examined the phototoxicity of individual PAHs and fresh and weathered crude oils, and several models have been developed to predict PAH toxicity. Fingerprint analyses of oils have shown that PAHs in crude oils are predominantly alkylated. However, current models for estimating PAH phototoxicity assume toxic equivalence between unsubstituted (i.e., parent) and alkyl-substituted compounds. This approach may be incorrect if substantial differences in toxic potency exist between unsubstituted and substituted PAHs. The objective of the present study was to examine the narcotic and photo-enhanced toxicity of commercially available unsubstituted and alkylated PAHs to mysid shrimp (Americamysis bahia). Data were used to validate predictive models of phototoxicity based on the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap approach and to develop relative effect potencies. Results demonstrated that photo-enhanced toxicity increased with increasing methylation and that phototoxic PAH potencies vary significantly among unsubstituted compounds. Overall, predictive models based on the HOMO-LUMO gap were relatively accurate in predicting phototoxicity for unsubstituted PAHs but are limited to qualitative assessments. Environ Toxicol Chem 2017;36:2043-2049. © 2017 SETAC. © 2017 SETAC.

  18. Western Validation of a Novel Gastric Cancer Prognosis Prediction Model in US Gastric Cancer Patients.

    Science.gov (United States)

    Woo, Yanghee; Goldner, Bryan; Son, Taeil; Song, Kijun; Noh, Sung Hoon; Fong, Yuman; Hyung, Woo Jin

    2018-03-01

    A novel prediction model for accurate determination of 5-year overall survival of gastric cancer patients was developed by an international collaborative group (G6+). This prediction model was created using a single institution's database of 11,851 Korean patients and included readily available and clinically relevant factors. Already validated using external East Asian cohorts, its applicability in the American population was yet to be determined. Using the Surveillance, Epidemiology, and End Results (SEER) dataset, 2014 release, all patients diagnosed with gastric adenocarcinoma who underwent surgical resection between 2002 and 2012, were selected. Characteristics for analysis included: age, sex, depth of tumor invasion, number of positive lymph nodes, total lymph nodes retrieved, presence of distant metastasis, extent of resection, and histology. Concordance index (C-statistic) was assessed using the novel prediction model and compared with the prognostic index, the seventh edition of the TNM staging system. Of the 26,019 gastric cancer patients identified from the SEER database, 15,483 had complete datasets. Validation of the novel prediction tool revealed a C-statistic of 0.762 (95% CI 0.754 to 0.769) compared with the seventh TNM staging model, C-statistic 0.683 (95% CI 0.677 to 0.689), (p prediction model for gastric cancer in the American patient population. Its superior prediction of the 5-year survival of gastric cancer patients in a large Western cohort strongly supports its global applicability. Importantly, this model allows for accurate prognosis for an increasing number of gastric cancer patients worldwide, including those who received inadequate lymphadenectomy or underwent a noncurative resection. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  19. 3D conformal MRI-controlled transurethral ultrasound prostate therapy: validation of numerical simulations and demonstration in tissue-mimicking gel phantoms.

    Science.gov (United States)

    Burtnyk, Mathieu; N'Djin, William Apoutou; Kobelevskiy, Ilya; Bronskill, Michael; Chopra, Rajiv

    2010-11-21

    MRI-controlled transurethral ultrasound therapy uses a linear array of transducer elements and active temperature feedback to create volumes of thermal coagulation shaped to predefined prostate geometries in 3D. The specific aims of this work were to demonstrate the accuracy and repeatability of producing large volumes of thermal coagulation (>10 cc) that conform to 3D human prostate shapes in a tissue-mimicking gel phantom, and to evaluate quantitatively the accuracy with which numerical simulations predict these 3D heating volumes under carefully controlled conditions. Eleven conformal 3D experiments were performed in a tissue-mimicking phantom within a 1.5T MR imager to obtain non-invasive temperature measurements during heating. Temperature feedback was used to control the rotation rate and ultrasound power of transurethral devices with up to five 3.5 × 5 mm active transducer elements. Heating patterns shaped to human prostate geometries were generated using devices operating at 4.7 or 8.0 MHz with surface acoustic intensities of up to 10 W cm(-2). Simulations were informed by transducer surface velocity measurements acquired with a scanning laser vibrometer enabling improved calculations of the acoustic pressure distribution in a gel phantom. Temperature dynamics were determined according to a FDTD solution to Pennes' BHTE. The 3D heating patterns produced in vitro were shaped very accurately to the prostate target volumes, within the spatial resolution of the MRI thermometry images. The volume of the treatment difference falling outside ± 1 mm of the target boundary was, on average, 0.21 cc or 1.5% of the prostate volume. The numerical simulations predicted the extent and shape of the coagulation boundary produced in gel to within (mean ± stdev [min, max]): 0.5 ± 0.4 [-1.0, 2.1] and -0.05 ± 0.4 [-1.2, 1.4] mm for the treatments at 4.7 and 8.0 MHz, respectively. The temperatures across all MRI thermometry images were predicted within -0.3 ± 1.6 °C and 0

  20. Validation and uncertainty analysis of a pre-treatment 2D dose prediction model

    Science.gov (United States)

    Baeza, Jose A.; Wolfs, Cecile J. A.; Nijsten, Sebastiaan M. J. J. G.; Verhaegen, Frank

    2018-02-01

    Independent verification of complex treatment delivery with megavolt photon beam radiotherapy (RT) has been effectively used to detect and prevent errors. This work presents the validation and uncertainty analysis of a model that predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The prediction model is based on an exponential point dose model with separable primary and secondary photon fluence components. The model includes a scatter kernel, off-axis ratio map, transmission values and penumbra kernels for beam-delimiting components. These parameters were derived through a model fitting procedure supplied with point dose and dose profile measurements of radiation fields. The model was validated against a treatment planning system (TPS; Eclipse) and radiochromic film measurements for complex clinical scenarios, including volumetric modulated arc therapy (VMAT). Confidence limits on fitted model parameters were calculated based on simulated measurements. A sensitivity analysis was performed to evaluate the effect of the parameter uncertainties on the model output. For the maximum uncertainty, the maximum deviating measurement sets were propagated through the fitting procedure and the model. The overall uncertainty was assessed using all simulated measurements. The validation of the prediction model against the TPS and the film showed a good agreement, with on average 90.8% and 90.5% of pixels passing a (2%,2 mm) global gamma analysis respectively, with a low dose threshold of 10%. The maximum and overall uncertainty of the model is dependent on the type of clinical plan used as input. The results can be used to study the robustness of the model. A model for predicting accurate 2D pre-treatment PDIs in complex RT scenarios can be used clinically and its uncertainties can be taken into account.

  1. Development and validation of a nomogram predicting recurrence risk in women with symptomatic urinary tract infection.

    Science.gov (United States)

    Cai, Tommaso; Mazzoli, Sandra; Migno, Serena; Malossini, Gianni; Lanzafame, Paolo; Mereu, Liliana; Tateo, Saverio; Wagenlehner, Florian M E; Pickard, Robert S; Bartoletti, Riccardo

    2014-09-01

    To develop and externally validate a novel nomogram predicting recurrence risk probability at 12 months in women after an episode of urinary tract infection. The study included 768 women from Santa Maria Annunziata Hospital, Florence, Italy, affected by urinary tract infections from January 2005 to December 2009. Another 373 women with the same criteria enrolled at Santa Chiara Hospital, Trento, Italy, from January 2010 to June 2012 were used to externally validate and calibrate the nomogram. Univariate and multivariate Cox regression models tested the relationship between urinary tract infection recurrence risk, and patient clinical and laboratory characteristics. The nomogram was evaluated by calculating concordance probabilities, as well as testing calibration of predicted urinary tract infection recurrence with observed urinary tract infections. Nomogram variables included: number of partners, bowel function, type of pathogens isolated (Gram-positive/negative), hormonal status, number of previous urinary tract infection recurrences and previous treatment of asymptomatic bacteriuria. Of the original development data, 261 out of 768 women presented at least one episode of recurrence of urinary tract infection (33.9%). The nomogram had a concordance index of 0.85. The nomogram predictions were well calibrated. This model showed high discrimination accuracy and favorable calibration characteristics. In the validation group (373 women), the overall c-index was 0.83 (P = 0.003, 95% confidence interval 0.51-0.99), whereas the area under the receiver operating characteristic curve was 0.85 (95% confidence interval 0.79-0.91). The present nomogram accurately predicts the recurrence risk of urinary tract infection at 12 months, and can assist in identifying women at high risk of symptomatic recurrence that can be suitable candidates for a prophylactic strategy. © 2014 The Japanese Urological Association.

  2. The predictive and discriminant validity of the zone of proximal development.

    Science.gov (United States)

    Meijer, J; Elshout, J J

    2001-03-01

    Dynamic measurement procedures are supposed to uncover the zone of proximal development and to increase predictive validity in comparison to conventional, static measurement procedures. Two alternative explanations for the discrepancies between static and dynamic measurements were investigated. The first focuses on Vygotsky's learning potential theory, the second considers the role of anxiety tendency during test taking. If test anxious tendencies are mitigated by dynamic testing procedures, in particular the availability of assistance, the concept of the zone of proximal development may be superfluous in explaining the differences between the outcomes of static and dynamic measurement. Participants were students from secondary education in the Netherlands. They were tested repeatedly in grade three as well as in grade four. Participants were between 14 and 17 years old; their average age was 15.4 years with a standard deviation of .52. Two types of mathematics tests were used in a longitudinal experiment. The first type of test consisted of open-ended items, which participants had to solve completely on their own. With the second type of test, assistance was available to participants during the test. The latter so-called learning test was conceived of as a dynamic testing procedure. Furthermore, a test anxiety questionnaire was administered repeatedly. Structural equation modelling was used to analyse the data. Apart from emotionality and worry, lack of self-confidence appears to be an important constituent of test anxiety. The learning test appears to contribute to the predictive validity of conventional tests and thus a part of Vygotsky's claims were substantiated. Moreover, the mere inclusion of a test anxiety factor into an explanatory model for the gathered data is not sufficient. Apart from test anxiety and mathematical ability it is necessary to assume a factor which may be construed as mathematics learning potential. The results indicate that the observed

  3. External validation of the ability of the DRAGON score to predict outcome after thrombolysis treatment.

    Science.gov (United States)

    Ovesen, C; Christensen, A; Nielsen, J K; Christensen, H

    2013-11-01

    Easy-to-perform and valid assessment scales for the effect of thrombolysis are essential in hyperacute stroke settings. Because of this we performed an external validation of the DRAGON scale proposed by Strbian et al. in a Danish cohort. All patients treated with intravenous recombinant plasminogen activator between 2009 and 2011 were included. Upon admission all patients underwent physical and neurological examination using the National Institutes of Health Stroke Scale along with non-contrast CT scans and CT angiography. Patients were followed up through the Outpatient Clinic and their modified Rankin Scale (mRS) was assessed after 3 months. Three hundred and three patients were included in the analysis. The DRAGON scale proved to have a good discriminative ability for predicting highly unfavourable outcome (mRS 5-6) (area under the curve-receiver operating characteristic [AUC-ROC]: 0.89; 95% confidence interval [CI] 0.81-0.96; pDRAGON scale provided good discriminative capability (AUC-ROC: 0.89; 95% CI 0.78-1.0; p=0.003) for highly unfavourable outcome. We confirmed the validity of the DRAGON scale in predicting outcome after thrombolysis treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. The design organization test: further demonstration of reliability and validity as a brief measure of visuospatial ability.

    Science.gov (United States)

    Killgore, William D S; Gogel, Hannah

    2014-01-01

    Neuropsychological assessments are frequently time-consuming and fatiguing for patients. Brief screening evaluations may reduce test duration and allow more efficient use of time by permitting greater attention toward neuropsychological domains showing probable deficits. The Design Organization Test (DOT) was initially developed as a 2-min paper-and-pencil alternative for the Block Design (BD) subtest of the Wechsler scales. Although initially validated for clinical neurologic patients, we sought to further establish the reliability and validity of this test in a healthy, more diverse population. Two alternate versions of the DOT and the Wechsler Abbreviated Scale of Intelligence (WASI) were administered to 61 healthy adult participants. The DOT showed high alternate forms reliability (r = .90-.92), and the two versions yielded equivalent levels of performance. The DOT was highly correlated with BD (r = .76-.79) and was significantly correlated with all subscales of the WASI. The DOT proved useful when used in lieu of BD in the calculation of WASI IQ scores. Findings support the reliability and validity of the DOT as a measure of visuospatial ability and suggest its potential worth as an efficient estimate of intellectual functioning in situations where lengthier tests may be inappropriate or unfeasible.

  5. Validation of a risk prediction model for Barrett’s esophagus in an Australian population

    Directory of Open Access Journals (Sweden)

    Ireland CJ

    2018-03-01

    Full Text Available Colin J Ireland,1 Andrea L Gordon,2 Sarah K Thompson,3 David I Watson,4 David C Whiteman,5 Richard L Reed,6 Adrian Esterman1,7 1School of Nursing and Midwifery, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia; 2School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia; 3Discipline of Surgery, University of Adelaide, Adelaide, SA, Australia; 4Department of Surgery, Flinders University, Bedford Park, SA, Australia; 5Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia; 6Discipline of General Practice, Flinders University, Bedford Park, SA, Australia; 7Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia Background: Esophageal adenocarcinoma is a disease that has a high mortality rate, the only known precursor being Barrett’s esophagus (BE. While screening for BE is not cost-effective at the population level, targeted screening might be beneficial. We have developed a risk prediction model to identify people with BE, and here we present the external validation of this model. Materials and methods: A cohort study was undertaken to validate a risk prediction model for BE. Individuals with endoscopy and histopathology proven BE completed a questionnaire containing variables previously identified as risk factors for this condition. Their responses were combined with data from a population sample for analysis. Risk scores were derived for each participant. Overall performance of the risk prediction model in terms of calibration and discrimination was assessed. Results: Scores from 95 individuals with BE and 636 individuals from the general population were analyzed. The Brier score was 0.118, suggesting reasonable overall performance. The area under the receiver operating characteristic was 0.83 (95% CI 0.78–0.87. The Hosmer–Lemeshow statistic was p=0

  6. Multisite external validation of a risk prediction model for the diagnosis of blood stream infections in febrile pediatric oncology patients without severe neutropenia.

    Science.gov (United States)

    Esbenshade, Adam J; Zhao, Zhiguo; Aftandilian, Catherine; Saab, Raya; Wattier, Rachel L; Beauchemin, Melissa; Miller, Tamara P; Wilkes, Jennifer J; Kelly, Michael J; Fernbach, Alison; Jeng, Michael; Schwartz, Cindy L; Dvorak, Christopher C; Shyr, Yu; Moons, Karl G M; Sulis, Maria-Luisa; Friedman, Debra L

    2017-10-01

    Pediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/μL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness. A 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables. From the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI. The results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017;123:3781-3790. © 2017 American Cancer Society. © 2017 American Cancer Society.

  7. Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.

    Science.gov (United States)

    Woodward, S J

    2001-09-01

    The Pasture Quality (PQ) model is a simple, mechanistic, dynamical system model that was designed to capture the essential biological processes in grazed grass-clover pasture, and to be optimised to derive improved grazing strategies for New Zealand dairy farms. While the individual processes represented in the model (photosynthesis, tissue growth, flowering, leaf death, decomposition, worms) were based on experimental data, this did not guarantee that the assembled model would accurately predict the behaviour of the system as a whole (i.e., pasture growth and quality). Validation of the whole model was thus a priority, since any strategy derived from the model could impact a farm business in the order of thousands of dollars per annum if adopted. This paper describes the process of defining performance criteria for the model, obtaining suitable data to test the model, and carrying out the validation analysis. The validation process highlighted a number of weaknesses in the model, which will lead to the model being improved. As a result, the model's utility will be enhanced. Furthermore, validation was found to have an unexpected additional benefit, in that despite the model's poor initial performance, support was generated for the model among field scientists involved in the wider project.

  8. Prediction of flow and drawdown for the site characterization and validation site in the Stripa Mine

    International Nuclear Information System (INIS)

    Long, J.C.S.; Mauldon, A.D.; Nelson, K.; Martel, S.; Fuller, P.; and Karasaki, K.

    1992-01-01

    Geophysical and hydrologic data from a location in the Stripa Mine in Sweden, called the Site Characterization and Validation (SCV) block, has been used to create a series of models for flow through the fracture network. The models can be characterized as ''equivalent discontinuum'' models. Equivalent discontinuum models are derived starting from a specified lattice or 6 ''template''. An inverse analysis called ''Simulated Annealing'' is used to make a random search through the elements of the lattice to find a configuration that can reproduce the measured responses. Evidence at Stripa points to hydrology which is dominated by fracture zones. These have been identified and located through extensive characterization efforts. Lattice templates were arranged to lie on the fracture zones identified by Black and Olsson. The fundamental goal of this project was to build a fracture flow model based an initial data set, and use this model to make predictions of the flow behavior during a new test. Then given data from the new test, predict a second test, etc. The first data set was an interference test called C1-2. Both a two-dimensional and a three-dimensional model were annealed to the C1-2 data and use this model to predict the behavior of the Simulated Drift Experiment (SDE). The SDE measured the flow into, and drawdown due to reducing the pressure in a group of 6 parallel boreholes. Then both the C1-2 and SDE data were used to predict the flow into and drawdown due to an excavation, the Validation Drift (VD), made through the boreholes. Finally, all the data was used to predict the hydrologic response to opening another hole, T1

  9. Predictive Validity of National Basketball Association Draft Combine on Future Performance.

    Science.gov (United States)

    Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

    2018-02-01

    Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

  10. A Critical Analysis and Validation of the Accuracy of Wave Overtopping Prediction Formulae for OWECs

    Directory of Open Access Journals (Sweden)

    David Gallach-Sánchez

    2018-01-01

    Full Text Available The development of wave energy devices is growing in recent years. One type of device is the overtopping wave energy converter (OWEC, for which the knowledge of the wave overtopping rates is a basic and crucial aspect in their design. In particular, the most interesting range to study is for OWECs with steep slopes to vertical walls, and with very small freeboards and zero freeboards where the overtopping rate is maximized, and which can be generalized as steep low-crested structures. Recently, wave overtopping prediction formulae have been published for this type of structures, although their accuracy has not been fully assessed, as the overtopping data available in this range is scarce. We performed a critical analysis of the overtopping prediction formulae for steep low-crested structures and the validation of the accuracy of these formulae, based on new overtopping data for steep low-crested structures obtained at Ghent University. This paper summarizes the existing knowledge about average wave overtopping, describes the physical model tests performed, analyses the results and compares them to existing prediction formulae. The new dataset extends the wave overtopping data towards vertical walls and zero freeboard structures. In general, the new dataset validated the more recent overtopping formulae focused on steep slopes with small freeboards, although the formulae are underpredicting the average overtopping rates for very small and zero relative crest freeboards.

  11. An integrated computational validation approach for potential novel miRNA prediction

    Directory of Open Access Journals (Sweden)

    Pooja Viswam

    2017-12-01

    Full Text Available MicroRNAs (miRNAs are short, non-coding RNAs between 17bp-24bp length that regulate gene expression by targeting mRNA molecules. The regulatory functions of miRNAs are known to be majorly associated with disease phenotypes such as cancer, cell signaling, cell division, growth and other metabolisms. Novel miRNAs are defined as sequences which does not have any similarity with the existing known sequences and void of any experimental evidences. In recent decades, the advent of next-generation sequencing allows us to capture the small RNA molecules form the cells and developing methods to estimate their expression levels. Several computational algorithms are available to predict the novel miRNAs from the deep sequencing data. In this work, we integrated three novel miRNA prediction programs miRDeep, miRanalyzer and miRPRo to compare and validate their prediction efficiency. The dicer cleavage sites, alignment density, seed conservation, minimum free energy, AU-GC percentage, secondary loop scores, false discovery rates and confidence scores will be considered for comparison and evaluation. Efficiency to identify isomiRs and base pair mismatches in a strand specific manner will also be considered for the computational validation. Further, the criteria and parameters for the identification of the best possible novel miRNA with minimal false positive rates were deduced.

  12. Validation of model predictions of pore-scale fluid distributions during two-phase flow

    Science.gov (United States)

    Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

    2018-05-01

    Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

  13. Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

    Science.gov (United States)

    Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

    2011-12-01

    This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

  14. External validation of structure-biodegradation relationship (SBR) models for predicting the biodegradability of xenobiotics.

    Science.gov (United States)

    Devillers, J; Pandard, P; Richard, B

    2013-01-01

    Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.

  15. Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data

    Directory of Open Access Journals (Sweden)

    Hendrik Treutler

    2016-10-01

    Full Text Available Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92 % of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0.

  16. An Experimental Simulation to Validate FEM to Predict Transverse Young’s Modulus of FRP Composites

    Directory of Open Access Journals (Sweden)

    V. S. Sai

    2013-01-01

    Full Text Available Finite element method finds application in the analysis of FRP composites due to its versatility in getting the solution for complex cases which are not possible by exact classical analytical approaches. The finite element result is questionable unless it is obtained from converged mesh and properly validated. In the present work specimens are prepared with metallic materials so that the arrangement of fibers is close to hexagonal packing in a matrix as similar arrangement in case of FRP is complex due to the size of fibers. Transverse Young’s moduli of these specimens are determined experimentally. Equivalent FE models are designed and corresponding transverse Young’s moduli are compared with the experimental results. It is observed that the FE values are in good agreement with the experimental results, thus validating FEM for predicting transverse modulus of FRP composites.

  17. A new approach to predicting environmental transfer of radionuclides to wildlife: A demonstration for freshwater fish and caesium

    Energy Technology Data Exchange (ETDEWEB)

    Beresford, N.A., E-mail: nab@ceh.ac.uk [NERC Centre for Ecology and Hydrology, Lancaster Environment Centre, Library Av. Bailrigg, Lancaster LA1 4AP (United Kingdom); Yankovich, T.L. [Saskatchewan Research Council, Environment and Forestry, 125, 15 Innovation Blvd., Saskatoon, SK S7N 2X8 (Canada); Wood, M.D. [School of Environment and Life Sciences, Room 323, Peel Building, University of Salford, Manchester, M5 4WT (United Kingdom); Fesenko, S. [International Atomic Energy Agency, 1400 Vienna (Austria); Andersson, P. [Strålsäkerhetsnymdigheten, Swedish Radiation Safety Authority, SE-171 16 Stockholm (Sweden); Muikku, M. [STUK, P.O. Box 14, 00881 Helsinki (Finland); Willey, N.J. [Centre for Research in Biosciences, University of the West of England, Coldharbour Lane, Frenchay, Bristol BS16 1QY (United Kingdom)

    2013-10-01

    The application of the concentration ratio (CR) to predict radionuclide activity concentrations in wildlife from those in soil or water has become the widely accepted approach for environmental assessments. Recently both the ICRP and IAEA have produced compilations of CR values for application in environmental assessment. However, the CR approach has many limitations, most notably, that the transfer of most radionuclides is largely determined by site-specific factors (e.g. water or soil chemistry). Furthermore, there are few, if any, CR values for many radionuclide-organism combinations. In this paper, we propose an alternative approach and, as an example, demonstrate and test this for caesium and freshwater fish. Using a Residual Maximum Likelihood (REML) mixed-model regression we analysed a dataset comprising 597 entries for 53 freshwater fish species from 67 sites. The REML analysis generated a mean value for each species on a common scale after REML adjustment taking account of the effect of the inter-site variation. Using an independent dataset, we subsequently test the hypothesis that the REML model outputs can be used to predict radionuclide, in this case radiocaesium, activity concentrations in unknown species from the results of a species which has been sampled at a specific site. The outputs of the REML analysis accurately predicted {sup 137}Cs activity concentrations in different species of fish from 27 Finnish lakes; these data had not been used in our initial analyses. We recommend that this alternative approach be further investigated for other radionuclides and ecosystems. - Highlights: • An alternative approach to estimating radionuclide transfer to wildlife is presented. • Analysed a dataset comprising 53 freshwater fish species collected from 67 sites. • Residual Maximum Likelihood mixed model regression is used. • Model output takes account of the effect of inter-site variation. • Successfully predicted {sup 137}Cs concentrations in

  18. Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone App

    Directory of Open Access Journals (Sweden)

    Min Soo Choo

    2017-04-01

    Full Text Available Purpose We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. Methods Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. Results A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179 and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. Conclusions External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.

  19. Screening for frailty in community-dwelling elderly subjects: Predictive validity of the modified SEGA instrument.

    Science.gov (United States)

    Oubaya, N; Dramé, M; Novella, J-L; Quignard, E; Cunin, C; Jolly, D; Mahmoudi, R

    2017-11-01

    To study the capacity of the SEGAm instrument to predict loss of independence among elderly community-dwelling subjects. The study was performed in four French departments (Ardennes, Marne, Meurthe-et-Moselle, Meuse). Subjects aged 65 years or more, living at home, who could read and understand French, with a degree of autonomy corresponding to groups 5 or 6 in the AGGIR autonomy evaluation scale were included. Assessment included demographic characteristics, comprehensive geriatric assessment, and the SEGAm instrument at baseline. Subjects had follow-up visits at home at 6 and 12 months. During follow-up, vital status and level of independence were recorded. Logistic regression was used to study predictive validity of the SEGAm instrument. Among the 116 subjects with complete follow-up, 84 (72.4%) were classed as not very frail at baseline, 23 (19.8%) as frail, and 9 (7.8%) as very frail; 63 (54.3%) suffered loss of at least one ADL or IADL at 12 months. By multivariable analysis, frailty status at baseline was significantly associated with loss of independence during the 12 months of follow-up (OR=4.52, 95% CI=1.40-14.68; p=0.01). We previously validated the SEGAm instrument in terms of feasibility, acceptability, internal structure validity, reliability, and discriminant validity. This instrument appears to be a suitable tool for screening frailty among community-dwelling elderly subjects, and could be used as a basis to plan early targeted interventions for subjects at risk of adverse outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

    Directory of Open Access Journals (Sweden)

    Elisa Passini

    2017-09-01

    (fast/late Na+ and Ca2+ currents exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca2+-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

  1. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity.

    Science.gov (United States)

    Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca

    2017-01-01

    (fast/late Na + and Ca 2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca 2+ -transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

  2. Validated Loads Prediction Models for Offshore Wind Turbines for Enhanced Component Reliability

    DEFF Research Database (Denmark)

    Koukoura, Christina

    To improve the reliability of offshore wind turbines, accurate prediction of their response is required. Therefore, validation of models with site measurements is imperative. In the present thesis a 3.6MW pitch regulated-variable speed offshore wind turbine on a monopole foundation is built...... are used for the modification of the sub-structure/foundation design for possible material savings. First, the background of offshore wind engineering, including wind-wave conditions, support structure, blade loading and wind turbine dynamics are presented. Second, a detailed description of the site...

  3. Reliability, Validity, and Predictive Utility of the 25-Item Criminogenic Cognitions Scale (CCS).

    Science.gov (United States)

    Tangney, June Price; Stuewig, Jeffrey; Furukawa, Emi; Kopelovich, Sarah; Meyer, Patrick; Cosby, Brandon

    2012-10-01

    Theory, research, and clinical reports suggest that moral cognitions play a role in initiating and sustaining criminal behavior. The 25 item Criminogenic Cognitions Scale (CCS) was designed to tap 5 dimensions: Notions of entitlement; Failure to Accept Responsibility; Short-Term Orientation; Insensitivity to Impact of Crime; and Negative Attitudes Toward Authority. Results from 552 jail inmates support the reliability, validity, and predictive utility of the measure. The CCS was linked to criminal justice system involvement, self-report measures of aggression, impulsivity, and lack of empathy. Additionally, the CCS was associated with violent criminal history, antisocial personality, and clinicians' ratings of risk for future violence and psychopathy (PCL:SV). Furthermore, criminogenic thinking upon incarceration predicted subsequent official reports of inmate misconduct during incarceration. CCS scores varied somewhat by gender and race. Research and applied uses of CCS are discussed.

  4. Development and validation of the 3-D CFD model for CANDU-6 moderator temperature predictions

    International Nuclear Information System (INIS)

    Yoon, Churl; Rhee, Bo Wook; Min, Byung Joo

    2003-03-01

    A computational fluid dynamics model for predicting the moderator circulation inside the CANada Deuterium Uranium (CANDU) reactor vessel has been developed to estimate the local subcooling of the moderator in the vicinity of the Calandria tubes. The buoyancy effect induced by internal heating is accounted for by Boussinesq approximation. The standard κ-ε turbulence model associated with logarithmic wall treatment is applied to predict the turbulent jet flows from the inlet nozzles. The matrix of the Calandria tubes in the core region is simplified to porous media, in which an-isotropic hydraulic impedance is modeled using an empirical correlation of the frictional pressure loss. The governing equations are solved by CFX-4.4, a commercial CFD code developed by AEA technology. The CFD model has been successfully verified and validated against experimental data obtained in the Stern Laboratories Inc. (SLI) in Hamilton, Ontario

  5. A six-factor model of brand personality and its predictive validity

    Directory of Open Access Journals (Sweden)

    Živanović Marko

    2017-01-01

    Full Text Available The study examines applicability and usefulness of HEXACO-based model in the description of brand personality. Following contemporary theoretical developments in human personality research, Study 1 explored the latent personality structure of 120 brands using descriptors of six personality traits as defined in HEXACO model: Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness. The results of exploratory factor analyses have supported HEXACO personality six-factor structure to a large extent. In Study 2 we addressed the question of predictive validity of HEXACO-based brand personality. Brand personality traits, but predominantly Honesty-Humility, accounted for substantial amount of variance in prediction of important aspects of consumer-brand relationship: attitude toward brand, perceived quality of a brand, and brand loyalty. The implications of applying HEXACO-based brand personality in marketing research are discussed. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 179018 and Grant no. 175012

  6. A Validation of Subchannel Based CHF Prediction Model for Rod Bundles

    International Nuclear Information System (INIS)

    Hwang, Dae-Hyun; Kim, Seong-Jin

    2015-01-01

    A large number of CHF data base were procured from various sources which included square and non-square lattice test bundles. CHF prediction accuracy was evaluated for various models including CHF lookup table method, empirical correlations, and phenomenological DNB models. The parametric effect of the mass velocity and unheated wall has been investigated from the experimental result, and incorporated into the development of local parameter CHF correlation applicable to APWR conditions. According to the CHF design criterion, the CHF should not occur at the hottest rod in the reactor core during normal operation and anticipated operational occurrences with at least a 95% probability at a 95% confidence level. This is accomplished by assuring that the minimum DNBR (Departure from Nucleate Boiling Ratio) in the reactor core is greater than the limit DNBR which accounts for the accuracy of CHF prediction model. The limit DNBR can be determined from the inverse of the lower tolerance limit of M/P that is evaluated from the measured-to-predicted CHF ratios for the relevant CHF data base. It is important to evaluate an adequacy of the CHF prediction model for application to the actual reactor core conditions. Validation of CHF prediction model provides the degree of accuracy inferred from the comparison of solution and data. To achieve a required accuracy for the CHF prediction model, it may be necessary to calibrate the model parameters by employing the validation results. If the accuracy of the model is acceptable, then it is applied to the real complex system with the inferred accuracy of the model. In a conventional approach, the accuracy of CHF prediction model was evaluated from the M/P statistics for relevant CHF data base, which was evaluated by comparing the nominal values of the predicted and measured CHFs. The experimental uncertainty for the CHF data was not considered in this approach to determine the limit DNBR. When a subchannel based CHF prediction model

  7. Predicting medical complications after spine surgery: a validated model using a prospective surgical registry.

    Science.gov (United States)

    Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

    2014-02-01

    The possibility and likelihood of a postoperative medical complication after spine surgery undoubtedly play a major role in the decision making of the surgeon and patient alike. Although prior study has determined relative risk and odds ratio values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of medical complication, rather than relative risk or odds ratio values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of medical complication during and after spine surgery. Statistical analysis using a prospective surgical spine registry that recorded extensive demographic, surgical, and complication data. Outcomes examined are medical complications that were specifically defined a priori. This analysis is a continuation of statistical analysis of our previously published report. Using a prospectively collected surgical registry of more than 1,476 patients with extensive demographic, comorbidity, surgical, and complication detail recorded for 2 years after surgery, we previously identified several risk factor for medical complications. Using the beta coefficients from those log binomial regression analyses, we created a model to predict the occurrence of medical complication after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created two predictive models: one predicting the occurrence of any medical complication and the other predicting the occurrence of a major medical complication. The final predictive model for any medical complications had a receiver operator curve characteristic of 0.76, considered to be a fair measure. The final predictive model for any major medical complications had

  8. Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury.

    Science.gov (United States)

    James, Matthew T; Pannu, Neesh; Hemmelgarn, Brenda R; Austin, Peter C; Tan, Zhi; McArthur, Eric; Manns, Braden J; Tonelli, Marcello; Wald, Ron; Quinn, Robert R; Ravani, Pietro; Garg, Amit X

    2017-11-14

    Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Demographic, laboratory, and comorbidity variables measured prior to discharge. Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher

  9. Development and Validation of Computational Fluid Dynamics Models for Prediction of Heat Transfer and Thermal Microenvironments of Corals

    Science.gov (United States)

    Ong, Robert H.; King, Andrew J. C.; Mullins, Benjamin J.; Cooper, Timothy F.; Caley, M. Julian

    2012-01-01

    We present Computational Fluid Dynamics (CFD) models of the coupled dynamics of water flow, heat transfer and irradiance in and around corals to predict temperatures experienced by corals. These models were validated against controlled laboratory experiments, under constant and transient irradiance, for hemispherical and branching corals. Our CFD models agree very well with experimental studies. A linear relationship between irradiance and coral surface warming was evident in both the simulation and experimental result agreeing with heat transfer theory. However, CFD models for the steady state simulation produced a better fit to the linear relationship than the experimental data, likely due to experimental error in the empirical measurements. The consistency of our modelling results with experimental observations demonstrates the applicability of CFD simulations, such as the models developed here, to coral bleaching studies. A study of the influence of coral skeletal porosity and skeletal bulk density on surface warming was also undertaken, demonstrating boundary layer behaviour, and interstitial flow magnitude and temperature profiles in coral cross sections. Our models compliment recent studies showing systematic changes in these parameters in some coral colonies and have utility in the prediction of coral bleaching. PMID:22701582

  10. Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

    Science.gov (United States)

    King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

    2011-01-01

    Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

  11. Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

    Directory of Open Access Journals (Sweden)

    Michael King

    Full Text Available Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL for the development of hazardous drinking in safe drinkers.A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women.69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873. The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51. External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846 and Hedge's g of 0.68 (95% CI 0.57, 0.78.The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

  12. An Automated Defect Prediction Framework using Genetic Algorithms: A Validation of Empirical Studies

    Directory of Open Access Journals (Sweden)

    Juan Murillo-Morera

    2016-05-01

    Full Text Available Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding software practitioners. With timely and accurate defect predictions, practitioners can focus their limited testing resources on higher risk areas. This paper reports the results of three empirical studies that uses an automated genetic defect prediction framework. This framework generates and compares different learning schemes (preprocessing + attribute selection + learning algorithms and selects the best one using a genetic algorithm, with the objective to estimate the defect proneness of a software module. The first empirical study is a performance comparison of our framework with the most important framework of the literature. The second empirical study is a performance and runtime comparison between our framework and an exhaustive framework. The third empirical study is a sensitivity analysis. The last empirical study, is our main contribution in this paper. Performance of the software development defect prediction models (using AUC, Area Under the Curve was validated using NASA-MDP and PROMISE data sets. Seventeen data sets from NASA-MDP (13 and PROMISE (4 projects were analyzed running a NxM-fold cross-validation. A genetic algorithm was used to select the components of the learning schemes automatically, and to assess and report the results. Our results reported similar performance between frameworks. Our framework reported better runtime than exhaustive framework. Finally, we reported the best configuration according to sensitivity analysis.

  13. Validation of the DRAGON Score in a Chinese Population to Predict Functional Outcome of Intravenous Thrombolysis-Treated Stroke Patients.

    Science.gov (United States)

    Zhang, Xinmiao; Liao, Xiaoling; Wang, Chunjuan; Liu, Liping; Wang, Chunxue; Zhao, Xingquan; Pan, Yuesong; Wang, Yilong; Wang, Yongjun

    2015-08-01

    The DRAGON score predicts functional outcome of ischemic stroke patients treated with intravenous thrombolysis. Our aim was to evaluate its utility in a Chinese stroke population. Patients with acute ischemic stroke treated with intravenous thrombolysis were prospectively registered in the Thrombolysis Implementation and Monitor of acute ischemic Stroke in China. We excluded patients with basilar artery occlusion and missing data, leaving 970 eligible patients. We calculated the DRAGON score, and the clinical outcome was measured by the modified Rankin Scale at 3 months. Model discrimination was quantified by calculating the C statistic. Calibration was assessed using Pearson correlation coefficient. The C statistic was .73 (.70-.76) for good outcome and .75 (.70-.79) for miserable outcome. Proportions of patients with good outcome were 94%, 83%, 70%, and 0% for 0 to 1, 2, 3, and 8 to 10 score points, respectively. Proportions of patients with miserable outcome were 0%, 3%, 9%, and 50% for 0 to 1, 2, 3, and 8 to 10 points, respectively. There was high correlation between predicted and observed probability of 3-month favorable and miserable outcome in the external validation cohort (Pearson correlation coefficient, .98 and .98, respectively, both P DRAGON score showed good performance to predict functional outcome after tissue-type plasminogen activator treatment in the Chinese population. This study demonstrated the accuracy and usability of the DRAGON score in the Chinese population in daily practice. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  14. Validating the Galerkin least-squares finite element methods in predicting mixing flows in stirred tank reactors

    International Nuclear Information System (INIS)

    Johnson, K.; Bittorf, K.J.

    2002-01-01

    A novel approach for computer aided modeling and optimizing mixing process has been developed using Galerkin least-squares finite element technology. Computer aided mixing modeling and analysis involves Lagrangian and Eulerian analysis for relative fluid stretching, and energy dissipation concepts for laminar and turbulent flows. High quality, conservative, accurate, fluid velocity, and continuity solutions are required for determining mixing quality. The ORCA Computational Fluid Dynamics (CFD) package, based on a finite element formulation, solves the incompressible Reynolds Averaged Navier Stokes (RANS) equations. Although finite element technology has been well used in areas of heat transfer, solid mechanics, and aerodynamics for years, it has only recently been applied to the area of fluid mixing. ORCA, developed using the Galerkin Least-Squares (GLS) finite element technology, provides another formulation for numerically solving the RANS based and LES based fluid mechanics equations. The ORCA CFD package is validated against two case studies. The first, a free round jet, demonstrates that the CFD code predicts the theoretical velocity decay rate, linear expansion rate, and similarity profile. From proper prediction of fundamental free jet characteristics, confidence can be derived when predicting flows in a stirred tank, as a stirred tank reactor can be considered a series of free jets and wall jets. (author)

  15. Validation of Heat-Flux Predictions on the Outer Air Seal of a Transonic Turbine Blade (Preprint)

    National Research Council Canada - National Science Library

    Clark, John P; Polanka, Marc D; Meininger, Matthew; Praisner, Thomas J

    2006-01-01

    .... So, a set of predictions of the heat flux on the Blade Outer Air Seal (BOAS) of a transonic turbine is here validated with time-resolved measurements obtained in a single-stage high pressure turbine rig...

  16. [Validation of a clinical prediction rule to distinguish bacterial from aseptic meningitis].

    Science.gov (United States)

    Agüero, Gonzalo; Davenport, María C; Del Valle, María de la P; Gallegos, Paulina; Kannemann, Ana L; Bokser, Vivian; Ferrero, Fernando

    2010-02-01

    Despite most meningitis are not bacterial, antibiotics are usually administered on admission because bacterial meningitis is difficult to be rule-out. Distinguishing bacterial from aseptic meningitis on admission could avoid inappropriate antibiotic use and hospitalization. We aimed to validate a clinical prediction rule to distinguish bacterial from aseptic meningitis in children, on arriving to the emergency room. This prospective study included patients aged or = 1000 cells/mm(3), CSF protein > or = 80 mg/dl, peripheral blood absolute neutrophil count > or = 10.000/mm(3), seizure = 1 point each. Sensitivity (S), specificity (E), positive and negative predictive values (PPV and NPV), positive and negative likelihood ratios (PLR and NLR) of the BMS to predict bacterial meningitis were calculated. Seventy patients with meningitis were included (14 bacterial meningitis). When BMS was calculated, 25 patients showed a BMS= 0 points, 11 BMS= 1 point, and 34 BMS > or = 2 points. A BMS = 0 showed S: 100%, E: 44%, VPP: 31%, VPN: 100%, RVP: 1,81 RVN: 0. A BMS > or = 2 predicted bacterial meningitis with S: 100%, E: 64%, VPP: 41%, VPN: 100%, PLR: 2.8, NLR:0. Using BMS was simple, and allowed identifying children with very low risk of bacterial meningitis. It could be a useful tool to assist clinical decision making.

  17. Modelling for the Stripa site characterization and validation drift inflow: prediction of flow through fractured rock

    International Nuclear Information System (INIS)

    Herbert, A.; Gale, J.; MacLeod, R.; Lanyon, G.

    1991-12-01

    We present our approach to predicting flow through a fractured rock site; the site characterization and validation region in the Stripa mine. Our approach is based on discrete fracture network modelling using the NAPSAC computer code. We describe the conceptual models and assumptions that we have used to interpret the geometry and flow properties of the fracture networks, from measurements at the site. These are used to investigate large scale properties of the network and we show that for flows on scales larger than about 10 m, porous medium approximation should be used. The porous medium groundwater flow code CFEST is used to predict the large scale flows through the mine and the SCV region. This, in turn, is used to provide boundary conditions for more detailed models, which predict the details of flow, using a discrete fracture network model, on scales of less than 10 m. We conclude that a fracture network approach is feasible and that it provides a better understanding of details of flow than conventional porous medium approaches and a quantification of the uncertainty associated with predictive flow modelling characterised from field measurement in fractured rock. (au)

  18. Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy.

    Science.gov (United States)

    Liu, Yan-De; Ying, Yi-Bin; Fu, Xia-Ping

    2005-03-01

    To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.

  19. Validation of prediction model for successful vaginal birth after Cesarean delivery based on sonographic assessment of hysterotomy scar.

    Science.gov (United States)

    Baranov, A; Salvesen, K Å; Vikhareva, O

    2018-02-01

    To validate a prediction model for successful vaginal birth after Cesarean delivery (VBAC) based on sonographic assessment of the hysterotomy scar, in a Swedish population. Data were collected from a prospective cohort study. We recruited non-pregnant women aged 18-35 years who had undergone one previous low-transverse Cesarean delivery at ≥ 37 gestational weeks and had had no other uterine surgery. Participants who subsequently became pregnant underwent transvaginal ultrasound examination of the Cesarean hysterotomy scar at 11 + 0 to 13 + 6 and at 19 + 0 to 21 + 6 gestational weeks. Thickness of the myometrium at the thinnest part of the scar area was measured. After delivery, information on pregnancy outcome was retrieved from hospital records. Individual probabilities of successful VBAC were calculated using a previously published model. Predicted individual probabilities were divided into deciles. For each decile, observed VBAC rates were calculated. To assess the accuracy of the prediction model, receiver-operating characteristics curves were constructed and the areas under the curves (AUC) were calculated. Complete sonographic data were available for 120 women. Eighty (67%) women underwent trial of labor after Cesarean delivery (TOLAC) with VBAC occurring in 70 (88%) cases. The scar was visible in all 80 women at the first-trimester scan and in 54 (68%) women at the second-trimester scan. AUC was 0.44 (95% CI, 0.28-0.60) among all women who underwent TOLAC and 0.51 (95% CI, 0.32-0.71) among those with the scar visible sonographically at both ultrasound examinations. The prediction model demonstrated poor accuracy for prediction of successful VBAC in our Swedish population. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

  20. Predictive validity of the Work Ability Index and its individual items in the general population.

    Science.gov (United States)

    Lundin, Andreas; Leijon, Ola; Vaez, Marjan; Hallgren, Mats; Torgén, Margareta

    2017-06-01

    This study assesses the predictive ability of the full Work Ability Index (WAI) as well as its individual items in the general population. The Work, Health and Retirement Study (WHRS) is a stratified random national sample of 25-75-year-olds living in Sweden in 2000 that received a postal questionnaire ( n = 6637, response rate = 53%). Current and subsequent sickness absence was obtained from registers. The ability of the WAI to predict long-term sickness absence (LTSA; ⩾ 90 consecutive days) during a period of four years was analysed by logistic regression, from which the Area Under the Receiver Operating Characteristic curve (AUC) was computed. There were 313 incident LTSA cases among 1786 employed individuals. The full WAI had acceptable ability to predict LTSA during the 4-year follow-up (AUC = 0.79; 95% CI 0.76 to 0.82). Individual items were less stable in their predictive ability. However, three of the individual items: current work ability compared with lifetime best, estimated work impairment due to diseases, and number of diagnosed current diseases, exceeded AUC > 0.70. Excluding the WAI item on number of days on sickness absence did not result in an inferior predictive ability of the WAI. The full WAI has acceptable predictive validity, and is superior to its individual items. For public health surveys, three items may be suitable proxies of the full WAI; current work ability compared with lifetime best, estimated work impairment due to diseases, and number of current diseases diagnosed by a physician.

  1. Anatomical Cystocele Recurrence: Development and Internal Validation of a Prediction Model.

    Science.gov (United States)

    Vergeldt, Tineke F M; van Kuijk, Sander M J; Notten, Kim J B; Kluivers, Kirsten B; Weemhoff, Mirjam

    2016-02-01

    To develop a prediction model that estimates the risk of anatomical cystocele recurrence after surgery. The databases of two multicenter prospective cohort studies were combined, and we performed a retrospective secondary analysis of these data. Women undergoing an anterior colporrhaphy without mesh materials and without previous pelvic organ prolapse (POP) surgery filled in a questionnaire, underwent translabial three-dimensional ultrasonography, and underwent staging of POP preoperatively and postoperatively. We developed a prediction model using multivariable logistic regression and internally validated it using standard bootstrapping techniques. The performance of the prediction model was assessed by computing indices of overall performance, discriminative ability, calibration, and its clinical utility by computing test characteristics. Of 287 included women, 149 (51.9%) had anatomical cystocele recurrence. Factors included in the prediction model were assisted delivery, preoperative cystocele stage, number of compartments involved, major levator ani muscle defects, and levator hiatal area during Valsalva. Potential predictors that were excluded after backward elimination because of high P values were age, body mass index, number of vaginal deliveries, and family history of POP. The shrinkage factor resulting from the bootstrap procedure was 0.91. After correction for optimism, Nagelkerke's R and the Brier score were 0.15 and 0.22, respectively. This indicates satisfactory model fit. The area under the receiver operating characteristic curve of the prediction model was 71.6% (95% confidence interval 65.7-77.5). After correction for optimism, the area under the receiver operating characteristic curve was 69.7%. This prediction model, including history of assisted delivery, preoperative stage, number of compartments, levator defects, and levator hiatus, estimates the risk of anatomical cystocele recurrence.

  2. Demonstration and Validation of a Waste-to-Energy Conversion System for Fixed DoD Installations

    Science.gov (United States)

    2013-08-01

    unique challenges , and the project experienced significant delays. The primary contributors to project delays were a state permitting process lacking...LESSONS LEARNED FROM THE DEMONSTRATION Implementation of the demonstration effort was a more significant challenge than had been anticipated at the...Ms  N  dP  Pb  Ps  Pstd  Qs(std) Ts  Vm Vm(std) Vw(std) Vlc T(std)  Tm  SQ.RT.dP y  Pstatic  Pstack  I  vs  Qs  O  % O2  % CO2  % CO  % N2  Zcf  Scf

  3. Validating computational predictions of night-time ventilation in Stanford's Y2E2 building

    Science.gov (United States)

    Chen, Chen; Lamberti, Giacomo; Gorle, Catherine

    2017-11-01

    Natural ventilation can significantly reduce building energy consumption, but robust design is a challenging task. We previously presented predictions of natural ventilation performance in Stanford's Y2E2 building using two models with different levels of fidelity, embedded in an uncertainty quantification framework to identify the dominant uncertain parameters and predict quantified confidence intervals. The results showed a slightly high cooling rate for the volume-averaged temperature, and the initial thermal mass temperature and window discharge coefficients were found to have an important influence on the results. To further investigate the potential role of these parameters on the observed discrepancies, the current study is performing additional measurements in the Y2E2 building. Wall temperatures are recorded throughout the nightflush using thermocouples; flow rates through windows are measured using hotwires; and spatial variability in the air temperature is explored. The measured wall temperatures are found the be within the range of our model assumptions, and the measured velocities agree reasonably well with our CFD predications. Considerable local variations in the indoor air temperature have been recorded, largely explaining the discrepancies in our earlier validation study. Future work will therefore focus on a local validation of the CFD results with the measurements. Center for Integrated Facility Engineering (CIFE).

  4. Validation of a CFD Analysis Model for Predicting CANDU-6 Moderator Temperature Against SPEL Experiments

    International Nuclear Information System (INIS)

    Churl Yoon; Bo Wook Rhee; Byung-Joo Min

    2002-01-01

    A validation of a 3D CFD model for predicting local subcooling of the moderator in the vicinity of calandria tubes in a CANDU-6 reactor is performed. The small scale moderator experiments performed at Sheridan Park Experimental Laboratory (SPEL) in Ontario, Canada[1] is used for the validation. Also a comparison is made between previous CFD analyses based on 2DMOTH and PHOENICS, and the current analysis for the same SPEL experiment. For the current model, a set of grid structures for the same geometry as the experimental test section is generated and the momentum, heat and continuity equations are solved by CFX-4.3, a CFD code developed by AEA technology. The matrix of calandria tubes is simplified by the porous media approach. The standard k-ε turbulence model associated with logarithmic wall treatment and SIMPLEC algorithm on the body fitted grid are used. Buoyancy effects are accounted for by the Boussinesq approximation. For the test conditions simulated in this study, the flow pattern identified is the buoyancy-dominated flow, which is generated by the interaction between the dominant buoyancy force by heating and inertial momentum forces by the inlet jets. As a result, the current CFD moderator analysis model predicts the moderator temperature reasonably, and the maximum error against the experimental data is kept at less than 2.0 deg. C over the whole domain. The simulated velocity field matches with the visualization of SPEL experiments quite well. (authors)

  5. External validation of the MRI-DRAGON score: early prediction of stroke outcome after intravenous thrombolysis.

    Science.gov (United States)

    Turc, Guillaume; Aguettaz, Pierre; Ponchelle-Dequatre, Nelly; Hénon, Hilde; Naggara, Olivier; Leclerc, Xavier; Cordonnier, Charlotte; Leys, Didier; Mas, Jean-Louis; Oppenheim, Catherine

    2014-01-01

    The aim of our study was to validate in an independent cohort the MRI-DRAGON score, an adaptation of the (CT-) DRAGON score to predict 3-month outcome in acute ischemic stroke patients undergoing MRI before intravenous thrombolysis (IV-tPA). We reviewed consecutive (2009-2013) anterior circulation stroke patients treated within 4.5 hours by IV-tPA in the Lille stroke unit (France), where MRI is the first-line pretherapeutic work-up. We assessed the discrimination and calibration of the MRI-DRAGON score to predict poor 3-month outcome, defined as modified Rankin Score >2, using c-statistic and the Hosmer-Lemeshow test, respectively. We included 230 patients (mean ±SD age 70.4±16.0 years, median [IQR] baseline NIHSS 8 [5]-[14]; poor outcome in 78(34%) patients). The c-statistic was 0.81 (95%CI 0.75-0.87), and the Hosmer-Lemeshow test was not significant (p = 0.54). The MRI-DRAGON score showed good prognostic performance in the external validation cohort. It could therefore be used to inform the patient's relatives about long-term prognosis and help to identify poor responders to IV-tPA alone, who may be candidates for additional therapeutic strategies, if they are otherwise eligible for such procedures based on the institutional criteria.

  6. External validation of the MRI-DRAGON score: early prediction of stroke outcome after intravenous thrombolysis.

    Directory of Open Access Journals (Sweden)

    Guillaume Turc

    Full Text Available The aim of our study was to validate in an independent cohort the MRI-DRAGON score, an adaptation of the (CT- DRAGON score to predict 3-month outcome in acute ischemic stroke patients undergoing MRI before intravenous thrombolysis (IV-tPA.We reviewed consecutive (2009-2013 anterior circulation stroke patients treated within 4.5 hours by IV-tPA in the Lille stroke unit (France, where MRI is the first-line pretherapeutic work-up. We assessed the discrimination and calibration of the MRI-DRAGON score to predict poor 3-month outcome, defined as modified Rankin Score >2, using c-statistic and the Hosmer-Lemeshow test, respectively.We included 230 patients (mean ±SD age 70.4±16.0 years, median [IQR] baseline NIHSS 8 [5]-[14]; poor outcome in 78(34% patients. The c-statistic was 0.81 (95%CI 0.75-0.87, and the Hosmer-Lemeshow test was not significant (p = 0.54.The MRI-DRAGON score showed good prognostic performance in the external validation cohort. It could therefore be used to inform the patient's relatives about long-term prognosis and help to identify poor responders to IV-tPA alone, who may be candidates for additional therapeutic strategies, if they are otherwise eligible for such procedures based on the institutional criteria.

  7. Predicting Hemorrhagic Transformation of Acute Ischemic Stroke: Prospective Validation of the HeRS Score.

    Science.gov (United States)

    Marsh, Elisabeth B; Llinas, Rafael H; Schneider, Andrea L C; Hillis, Argye E; Lawrence, Erin; Dziedzic, Peter; Gottesman, Rebecca F

    2016-01-01

    Hemorrhagic transformation (HT) increases the morbidity and mortality of ischemic stroke. Anticoagulation is often indicated in patients with atrial fibrillation, low ejection fraction, or mechanical valves who are hospitalized with acute stroke, but increases the risk of HT. Risk quantification would be useful. Prior studies have investigated risk of systemic hemorrhage in anticoagulated patients, but none looked specifically at HT. In our previously published work, age, infarct volume, and estimated glomerular filtration rate (eGFR) significantly predicted HT. We created the hemorrhage risk stratification (HeRS) score based on regression coefficients in multivariable modeling and now determine its validity in a prospectively followed inpatient cohort.A total of 241 consecutive patients presenting to 2 academic stroke centers with acute ischemic stroke and an indication for anticoagulation over a 2.75-year period were included. Neuroimaging was evaluated for infarct volume and HT. Hemorrhages were classified as symptomatic versus asymptomatic, and by severity. HeRS scores were calculated for each patient and compared to actual hemorrhage status using receiver operating curve analysis.Area under the curve (AUC) comparing predicted odds of hemorrhage (HeRS score) to actual hemorrhage status was 0.701. Serum glucose (P hemorrhages were more likely to be symptomatic and more severe.The HeRS score is a valid predictor of HT in patients with ischemic stroke and indication for anticoagulation.

  8. Demonstration/Validation of Incremental Sampling at Two Diverse Military Ranges and Development of an Incremental Sampling Tool

    Science.gov (United States)

    2010-06-01

    Sampling (MIS)? • Technique of combining many increments of soil from a number of points within exposure area • Developed by Enviro Stat (Trademarked...Demonstrating a reliable soil sampling strategy to accurately characterize contaminant concentrations in spatially extreme and heterogeneous...into a set of decision (exposure) units • One or several discrete or small- scale composite soil samples collected to represent each decision unit

  9. Predictive validity of the post-enrolment English language assessment tool for commencing undergraduate nursing students.

    Science.gov (United States)

    Glew, Paul J; Hillege, Sharon P; Salamonson, Yenna; Dixon, Kathleen; Good, Anthony; Lombardo, Lien

    2015-12-01

    Nursing students with English as an additional language (EAL) may underperform academically. The post-enrolment English language assessment (PELA) is used in literacy support, but its predictive validity in identifying those at risk of underperformance remains unknown. To validate a PELA, as a predictor of academic performance. Prospective survey design. The study was conducted at a university located in culturally and linguistically diverse areas of western Sydney, Australia. Commencing undergraduate nursing students who were Australian-born (n=1323, 49.6%) and born outside of Australia (n=1346, 50.4%) were recruited for this study. The 2669 (67% of 3957) participants provided consent and completed a first year nursing unit that focussed on developing literacy skills. Between 2010 and 2013, commencing students completed the PELA and English language acculturation scale (ELAS), a previously validated instrument. The grading levels of the PELA tool were: Level 1 (proficient), Level 2 (borderline), and Level 3 (poor, and requiring additional support). Participants with a PELA Level 2 or 3 were more likely to be: a) non-Australian-born (χ(2): 520.6, df: 2, pstudent (χ(2): 225.6, df: 2, pstudents who are at risk of academic underachievement. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  10. Validation and Refinement of Prediction Models to Estimate Exercise Capacity in Cancer Survivors Using the Steep Ramp Test

    NARCIS (Netherlands)

    Stuiver, Martijn M.; Kampshoff, Caroline S.; Persoon, Saskia; Groen, Wim; van Mechelen, Willem; Chinapaw, Mai J. M.; Brug, Johannes; Nollet, Frans; Kersten, Marie-José; Schep, Goof; Buffart, Laurien M.

    2017-01-01

    Objective: To further test the validity and clinical usefulness of the steep ramp test (SRT) in estimating exercise tolerance in cancer survivors by external validation and extension of previously published prediction models for peak oxygen consumption (Vo2(peak)) and peak power output (W-peak).&

  11. Short-Term Predictive Validity of Cluster Analytic and Dimensional Classification of Child Behavioral Adjustment in School

    Science.gov (United States)

    Kim, Sangwon; Kamphaus, Randy W.; Baker, Jean A.

    2006-01-01

    A constructive debate over the classification of child psychopathology can be stimulated by investigating the validity of different classification approaches. We examined and compared the short-term predictive validity of cluster analytic and dimensional classifications of child behavioral adjustment in school using the Behavior Assessment System…

  12. Multivariable prediction model for suspected giant cell arteritis: development and validation

    Directory of Open Access Journals (Sweden)

    Ing EB

    2017-11-01

    Full Text Available Edsel B Ing,1 Gabriela Lahaie Luna,2 Andrew Toren,3 Royce Ing,4 John J Chen,5 Nitika Arora,6 Nurhan Torun,7 Otana A Jakpor,8 J Alexander Fraser,9 Felix J Tyndel,10 Arun NE Sundaram,10 Xinyang Liu,11 Cindy TY Lam,1 Vivek Patel,12 Ezekiel Weis,13 David Jordan,14 Steven Gilberg,14 Christian Pagnoux,15 Martin ten Hove21Department of Ophthalmology and Vision Sciences, University of Toronto Medical School, Toronto, 2Department of Ophthalmology, Queen’s University, Kingston, ON, 3Department of Ophthalmology, University of Laval, Quebec, QC, 4Toronto Eyelid, Strabismus and Orbit Surgery Clinic, Toronto, ON, Canada; 5Mayo Clinic, Department of Ophthalmology and Neurology, 6Mayo Clinic, Department of Ophthalmology, Rochester, MN, 7Department of Surgery, Division of Ophthalmology, Harvard Medical School, Boston, MA, 8Harvard Medical School, Boston, MA, USA; 9Department of Clinical Neurological Sciences and Ophthalmology, Western University, London, 10Department of Medicine, University of Toronto Medical School, Toronto, ON, Canada; 11Department of Medicine, Fudan University Shanghai Medical College, Shanghai, People’s Republic of China; 12Roski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; 13Departments of Ophthalmology, Universities of Alberta and Calgary, Edmonton and Calgary, AB, 14Department of Ophthalmology, University of Ottawa, Ottawa, ON, 15Vasculitis Clinic, Mount Sinai Hospital, Toronto, ON, CanadaPurpose: To develop and validate a diagnostic prediction model for patients with suspected giant cell arteritis (GCA.Methods: A retrospective review of records of consecutive adult patients undergoing temporal artery biopsy (TABx for suspected GCA was conducted at seven university centers. The pathologic diagnosis was considered the final diagnosis. The predictor variables were age, gender, new onset headache, clinical temporal artery abnormality, jaw claudication, ischemic vision loss (VL, diplopia

  13. External validation of approaches to prediction of falls during hospital rehabilitation stays and development of a new simpler tool

    Directory of Open Access Journals (Sweden)

    Angela Vratsistas-Curto

    2017-12-01

    Full Text Available Objectives: To test the external validity of 4 approaches to fall prediction in a rehabilitation setting (Predict_FIRST, Ontario Modified STRATIFY (OMS, physiotherapists’ judgement of fall risk (PT_Risk, and falls in the past year (Past_Falls, and to develop and test the validity of a simpler tool for fall prediction in rehabilitation (Predict_CM2. Participants: A total of 300 consecutively-admitted rehabilitation inpatients. Methods: Prospective inception cohort study. Falls during the rehabilitation stay were monitored. Potential predictors were extracted from medical records. Results: Forty-one patients (14% fell during their rehabilitation stay. The external validity, area under the receiver operating characteristic curve (AUC, for predicting future fallers was: 0.71 (95% confidence interval (95% CI: 0.61–0.81 for OMS (Total_Score; 0.66 (95% CI: 0.57–0.74 for Predict_FIRST; 0.65 (95% CI 0.57–0.73 for PT_Risk; and 0.52 for Past_Falls (95% CI: 0.46–0.60. A simple 3-item tool (Predict_CM2 was developed from the most predictive individual items (impaired mobility/transfer ability, impaired cognition, and male sex. The accuracy of Predict_CM2 was 0.73 (95% CI: 0.66–0.81, comparable to OMS (Total_Score (p = 0.52, significantly better than Predict_FIRST (p = 0.04, and Past_Falls (p < 0.001, and approaching significantly better than PT_Risk (p = 0.09. Conclusion: Predict_CM2 is a simpler screening tool with similar accuracy for predicting fallers in rehabilitation to OMS (Total_Score and better accuracy than Predict_FIRST or Past_Falls. External validation of Predict_CM2 is required.

  14. Validity of bioelectrical impedance measurement in predicting fat-free mass of Chinese children and adolescents.

    Science.gov (United States)

    Wang, Lin; Hui, Stanley Sai-chuen; Wong, Stephen Heung-sang

    2014-11-15

    The current study aimed to examine the validity of various published bioelectrical impedance analysis (BIA) equations in estimating FFM among Chinese children and adolescents and to develop BIA equations for the estimation of fat-free mass (FFM) appropriate for Chinese children and adolescents. A total of 255 healthy Chinese children and adolescents aged 9 to 19 years old (127 males and 128 females) from Tianjin, China, participated in the BIA measurement at 50 kHz between the hand and the foot. The criterion measure of FFM was also employed using dual-energy X-ray absorptiometry (DEXA). FFM estimated from 24 published BIA equations was cross-validated against the criterion measure from DEXA. Multiple linear regression was conducted to examine alternative BIA equation for the studied population. FFM estimated from the 24 published BIA equations yielded high correlations with the directly measured FFM from DEXA. However, none of the 24 equations was statistically equivalent with the DEXA-measured FFM. Using multiple linear regression and cross-validation against DEXA measurement, an alternative prediction equation was determined as follows: FFM (kg)=1.613+0.742×height (cm)2/impedance (Ω)+0.151×body weight (kg); R2=0.95; SEE=2.45 kg; CV=6.5, 93.7% of the residuals of all the participants fell within the 95% limits of agreement. BIA was highly correlated with FFM in Chinese children and adolescents. When the new developed BIA equations are applied, BIA can provide a practical and valid measurement of body composition in Chinese children and adolescents.

  15. 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.

  16. Prediction of Curve Progression in Idiopathic Scoliosis: Validation of the Sanders Skeletal Maturity Staging System.

    Science.gov (United States)

    Sitoula, Prakash; Verma, Kushagra; Holmes, Laurens; Gabos, Peter G; Sanders, James O; Yorgova, Petya; Neiss, Geraldine; Rogers, Kenneth; Shah, Suken A

    2015-07-01

    Retrospective case series. This study aimed to validate the Sanders Skeletal Maturity Staging System and to assess its correlation to curve progression in idiopathic scoliosis. The Sanders Skeletal Maturity Staging System has been used to predict curve progression in idiopathic scoliosis. This study intended to validate that initial study with a larger sample size. We retrospectively reviewed 1100 consecutive patients with idiopathic scoliosis between 2005 and 2011. Girls aged 8 to 14 years (skeletal age and scoliosis curve magnitude were followed to skeletal maturity (Risser stage 5 or fully capped Risser stage 4), curve progression to 50° or greater, or spinal fusion. Patients with nonidiopathic curves were excluded. There were 161 patients: 131 girls (12.3 ± 1.2 yr) and 30 boys (13.9 ± 1.1 yr). The distribution of patients within Sanders stage (SS) 1 through 7 was 7, 28, 41, 45, 7, 31, and 2 patients, respectively; modified Lenke curve types 1 to 6 were 26, 12, 63, 5, 38, and 17 patients, respectively. All patients in SS2 with initial Cobb angles of 25° or greater progressed, and patients in SS1 and SS3 with initial Cobb angles of 35° or greater progressed. Similarly, all patients with initial Cobb angles of 40° or greater progressed except those in SS7. Conversely, none of the patients with initial Cobb angles of 15° or less or those in SS5, SS6, and SS7 with initial Cobb angles of 30° or less progressed. Predictive progression of 67%, 50%, 43%, 27%, and 60% was observed for subgroups SS1/30°, SS2/20°, SS3/30°, SS4/30°, and SS6/35° respectively. This larger cohort shows a strong predictive correlation between SS and initial Cobb angle for probability of curve progression in idiopathic scoliosis. 3.

  17. Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies.

    Science.gov (United States)

    Partin, Alan W; Van Neste, Leander; Klein, Eric A; Marks, Leonard S; Gee, Jason R; Troyer, Dean A; Rieger-Christ, Kimberly; Jones, J Stephen; Magi-Galluzzi, Cristina; Mangold, Leslie A; Trock, Bruce J; Lance, Raymond S; Bigley, Joseph W; Van Criekinge, Wim; Epstein, Jonathan I

    2014-10-01

    The DOCUMENT multicenter trial in the United States validated the performance of an epigenetic test as an independent predictor of prostate cancer risk to guide decision making for repeat biopsy. Confirming an increased negative predictive value could help avoid unnecessary repeat biopsies. We evaluated the archived, cancer negative prostate biopsy core tissue samples of 350 subjects from a total of 5 urological centers in the United States. All subjects underwent repeat biopsy within 24 months with a negative (controls) or positive (cases) histopathological result. Centralized blinded pathology evaluation of the 2 biopsy series was performed in all available subjects from each site. Biopsies were epigenetically profiled for GSTP1, APC and RASSF1 relative to the ACTB reference gene using quantitative methylation specific polymerase chain reaction. Predetermined analytical marker cutoffs were used to determine assay performance. Multivariate logistic regression was used to evaluate all risk factors. The epigenetic assay resulted in a negative predictive value of 88% (95% CI 85-91). In multivariate models correcting for age, prostate specific antigen, digital rectal examination, first biopsy histopathological characteristics and race the test proved to be the most significant independent predictor of patient outcome (OR 2.69, 95% CI 1.60-4.51). The DOCUMENT study validated that the epigenetic assay was a significant, independent predictor of prostate cancer detection in a repeat biopsy collected an average of 13 months after an initial negative result. Due to its 88% negative predictive value adding this epigenetic assay to other known risk factors may help decrease unnecessary repeat prostate biopsies. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  18. Factors associated with therapeutic inertia in hypertension: validation of a predictive model.

    Science.gov (United States)

    Redón, Josep; Coca, Antonio; Lázaro, Pablo; Aguilar, Ma Dolores; Cabañas, Mercedes; Gil, Natividad; Sánchez-Zamorano, Miguel Angel; Aranda, Pedro

    2010-08-01

    To study factors associated with therapeutic inertia in treating hypertension and to develop a predictive model to estimate the probability of therapeutic inertia in a given medical consultation, based on variables related to the consultation, patient, physician, clinical characteristics, and level of care. National, multicentre, observational, cross-sectional study in primary care and specialist (hospital) physicians who each completed a questionnaire on therapeutic inertia, provided professional data and collected clinical data on four patients. Therapeutic inertia was defined as a consultation in which treatment change was indicated (i.e., SBP >or= 140 or DBP >or= 90 mmHg in all patients; SBP >or= 130 or DBP >or= 80 in patients with diabetes or stroke), but did not occur. A predictive model was constructed and validated according to the factors associated with therapeutic inertia. Data were collected on 2595 patients and 13,792 visits. Therapeutic inertia occurred in 7546 (75%) of the 10,041 consultations in which treatment change was indicated. Factors associated with therapeutic inertia were primary care setting, male sex, older age, SPB and/or DBP values close to normal, treatment with more than one antihypertensive drug, treatment with an ARB II, and more than six visits/year. Physician characteristics did not weigh heavily in the association. The predictive model was valid internally and externally, with acceptable calibration, discrimination and reproducibility, and explained one-third of the variability in therapeutic inertia. Although therapeutic inertia is frequent in the management of hypertension, the factors explaining it are not completely clear. Whereas some aspects of the consultations were associated with therapeutic inertia, physician characteristics were not a decisive factor.

  19. Prostatectomy-based validation of combined urine and plasma test for predicting high grade prostate cancer.

    Science.gov (United States)

    Albitar, Maher; Ma, Wanlong; Lund, Lars; Shahbaba, Babak; Uchio, Edward; Feddersen, Søren; Moylan, Donald; Wojno, Kirk; Shore, Neal

    2018-03-01

    Distinguishing between low- and high-grade prostate cancers (PCa) is important, but biopsy may underestimate the actual grade of cancer. We have previously shown that urine/plasma-based prostate-specific biomarkers can predict high grade PCa. Our objective was to determine the accuracy of a test using cell-free RNA levels of biomarkers in predicting prostatectomy results. This multicenter community-based prospective study was conducted using urine/blood samples collected from 306 patients. All recruited patients were treatment-naïve, without metastases, and had been biopsied, designated a Gleason Score (GS) based on biopsy, and assigned to prostatectomy prior to participation in the study. The primary outcome measure was the urine/plasma test accuracy in predicting high grade PCa on prostatectomy compared with biopsy findings. Sensitivity and specificity were calculated using standard formulas, while comparisons between groups were performed using the Wilcoxon Rank Sum, Kruskal-Wallis, Chi-Square, and Fisher's exact test. GS as assigned by standard 10-12 core biopsies was 3 + 3 in 90 (29.4%), 3 + 4 in 122 (39.8%), 4 + 3 in 50 (16.3%), and > 4 + 3 in 44 (14.4%) patients. The urine/plasma assay confirmed a previous validation and was highly accurate in predicting the presence of high-grade PCa (Gleason ≥3 + 4) with sensitivity between 88% and 95% as verified by prostatectomy findings. GS was upgraded after prostatectomy in 27% of patients and downgraded in 12% of patients. This plasma/urine biomarker test accurately predicts high grade cancer as determined by prostatectomy with a sensitivity at 92-97%, while the sensitivity of core biopsies was 78%. © 2018 Wiley Periodicals, Inc.

  20. Validation and Demonstration of the NOAA Unique Combined Atmospheric Processing System (NUCAPS) in Support of User Applications

    Science.gov (United States)

    Nalli, N. R.; Gambacorta, A.; Tan, C.; Iturbide, F.; Barnet, C. D.; Reale, A.; Sun, B.; Liu, Q.

    2017-12-01

    This presentation overviews the performance of the operational SNPP NOAA Unique Combined Atmospheric Processing System (NUCAPS) environmental data record (EDR) products. The SNPP Cross-track Infrared Sounder and Advanced Technology Microwave Sounder (CrIS/ATMS) suite, the first of the Joint Polar Satellite System (JPSS) Program, is one of NOAA's major investments in our nation's future operational environmental observation capability. The NUCAPS algorithm is a world-class NOAA-operational IR/MW retrieval algorithm based upon the well-established AIRS science team algorithm for deriving temperature, moisture, ozone and carbon trace gas to provide users with state-of-the-art EDR products. Operational use of the products includes the NOAA National Weather Service (NWS) Advanced Weather Interactive Processing System (AWIPS), along with numerous science-user applications. NUCAPS EDR product assessments are made with reference to JPSS Level 1 global requirements, which provide the definitive metrics for assessing that the products have minimally met predefined global performance specifications. The NESDIS/STAR NUCAPS development and validation team recently delivered the Phase 4 algorithm which incorporated critical updates necessary for compatibility with full spectral-resolution (FSR) CrIS sensor data records (SDRs). Based on comprehensive analyses, the NUCAPS Phase 4 CrIS-FSR temperature, moisture and ozone profile EDRs, as well as the carbon trace gas EDRs (CO, CH4 and CO2), are shown o be meeting or close to meeting the JPSS program global requirements. Regional and temporal assessments of interest to EDR users (e.g., AWIPS) will also be presented.

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

    Directory of Open Access Journals (Sweden)

    Karacali Bilge

    2007-10-01

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

  2. Validation of a Methodology to Predict Micro-Vibrations Based on Finite Element Model Approach

    Science.gov (United States)

    Soula, Laurent; Rathband, Ian; Laduree, Gregory

    2014-06-01

    This paper presents the second part of the ESA R&D study called "METhodology for Analysis of structure- borne MICro-vibrations" (METAMIC). After defining an integrated analysis and test methodology to help predicting micro-vibrations [1], a full-scale validation test campaign has been carried out. It is based on a bread-board representative of typical spacecraft (S/C) platform consisting in a versatile structure made of aluminium sandwich panels equipped with different disturbance sources and a dummy payload made of a silicon carbide (SiC) bench. The bread-board has been instrumented with a large set of sensitive accelerometers and tests have been performed including back-ground noise measurement, modal characterization and micro- vibration tests. The results provided responses to the perturbation coming from a reaction wheel or cryo-cooler compressors, operated independently then simultaneously with different operation modes. Using consistent modelling and associated experimental characterization techniques, a correlation status has been assessed by comparing test results with predictions based on FEM approach. Very good results have been achieved particularly for the case of a wheel in sweeping rate operation with test results over-predicted within a reasonable margin lower than two. Some limitations of the methodology have also been identified for sources operating at a fixed rate or coming with a small number of dominant harmonics and recommendations have been issued in order to deal with model uncertainties and stay conservative.

  3. Incremental validity of positive orientation: predictive efficiency beyond the five-factor model

    Directory of Open Access Journals (Sweden)

    Łukasz Roland Miciuk

    2016-05-01

    Full Text Available Background The relation of positive orientation (a basic predisposition to think positively of oneself, one’s life and one’s future and personality traits is still disputable. The purpose of the described research was to verify the hypothesis that positive orientation has predictive efficiency beyond the five-factor model. Participants and procedure One hundred and thirty participants (at the mean age M = 24.84 completed the following questionnaires: the Self-Esteem Scale (SES, the Satisfaction with Life Scale (SWLS, the Life Orientation Test-Revised (LOT-R, the Positivity Scale (P-SCALE, the NEO Five Factor Inventory (NEO-FFI, the Self-Concept Clarity Scale (SCC, the Generalized Self-Efficacy Scale (GSES and the Life Engagement Test (LET. Results The introduction of positive orientation as an additional predictor in the second step of regression analyses led to better prediction of the following variables: purpose in life, self-concept clarity and generalized self-efficacy. This effect was the strongest for predicting purpose in life (i.e. 14% increment of the explained variance. Conclusions The results confirmed our hypothesis that positive orientation can be characterized by incremental validity – its inclusion in the regression model (in addition to the five main factors of personality increases the amount of explained variance. These findings may provide further evidence for the legitimacy of measuring positive orientation and personality traits separately.

  4. A comprehensive model for the prediction of vibrations due to underground railway traffic: formulation and validation

    International Nuclear Information System (INIS)

    Costa, Pedro Alvares; Cardoso Silva, Antonio; Calçada, Rui; Lopes, Patricia; Fernandez, Jesus

    2016-01-01

    n this communication, a numerical approach for the prediction of vibrations induced in buildings due to railway traffic in tunnels is presented. The numerical model is based on the concept of dynamic sub structuring, being composed by three autonomous models to simulate the following main parts of the problem: i) generation of vibrations (train-track interaction); ii) propagation of vibrations (track - tunnel-ground system); iii) reception of vibrations (building coupled to the ground). The methodology proposed allows dealing with the three-dimensional characteristics of the problem with a reasonable computational effort [ 1 , 2 ] . After the brief description of the model, its experimental validation is performed. For that, a case study about vibrations inside of a building close to a shallow railway tunnel in Madrid are simulated and the experimental data [ 3 ] is compared with the predicted results [ 4 ]. Finally, the communication finishes with some insights about the potentialities and challenges of this numerical modelling approach on the prediction of the behavior of ancient structures subjected to vibrations induced by human sources (railway and road traffic, pile driving, etc)

  5. Predictive Validity of Delay Discounting Behavior in Adolescence: A Longitudinal Twin Study

    Science.gov (United States)

    Isen, Joshua D.; Sparks, Jordan C.; Iacono, William G.

    2014-01-01

    A standard assumption in the delay discounting literature is that individuals who exhibit steeper discounting of hypothetical rewards also experience greater difficulty deferring gratification to real-world rewards. There is ample cross-sectional evidence that delay discounting paradigms reflect a variety of maladaptive psychosocial outcomes, including substance use pathology. We sought to determine whether a computerized assessment of hypothetical delay discounting (HDD) taps into behavioral impulsivity in a community sample of adolescent twins (N = 675). Using a longitudinal design, we hypothesized that greater HDD at age 14–15 predicts real-world impulsive choices and risk for substance use disorders in late adolescence. We also examined the genetic and environmental structure of HDD performance. Individual differences in HDD behavior showed moderate heritability, and were prospectively associated with real-world temporal discounting at age 17–18. Contrary to expectations, HDD was not consistently related to substance use or trait impulsivity. Although a significant association between HDD behavior and past substance use emerged in males, this effect was mediated by cognitive ability. In both sexes, HDD failed to predict a comprehensive index of substance use problems and behavioral disinhibition in late adolescence. In sum, we present some of the first evidence that HDD performance is heritable and predictive of real-world temporal discounting of rewards. Nevertheless, HDD might not serve as a valid marker of substance use disorder risk in younger adolescents, particularly females. PMID:24999868

  6. Validity of bacterial pneumonia score for predicting bacteremia in children with pneumonia

    Directory of Open Access Journals (Sweden)

    Rosalia Theodosia Daten Beyeng

    2011-12-01

    Full Text Available Background Bacteremia in children with pneumonia reflects a severe condition, with longer duration of hospital care and potentially lethal complications. Early detection of bacteremia in patients with pneumonia may reduce serious complications. Few bacteremia screening tools have been widely used in chidren with pneumonia. One of those tools is the bacterial pneumonia score (BPS. Objective To assess the validity of the bacterial pneumonia score for predicting bacteremia in pediatric patients with pneumonia. Methods A diagnostic test was conducted on children aged 1 to 60 months hospitalized with pneumonia from December 2009 to August 2010. Subjects were collected consecutively. Pneumonia was diagnosed using the World Healt Organization (WHO criteria. Subjects underwent complete blood counts and blood culture examinations at admission. Statistical analyses included sensitivity, specificity, positive and negative predictive value (PPV/NPV, positive and negative likelihood ratio (PLR/NLR, and post-test probability. Results Our study included 229 children. Based on BPS with a cut-off score of ≥ 4, the sensitivity was 83.3%, specificity 49.7%, PPV 8.4%, NPV 98.2%, PLR 1.66, NLR 0.31, and post-test probability 8.4% for detecting bacteremia in pediatric pneumonia patients. Conclusion BPS can not be used for predicting bacteremia in pediatric patients with pneumonia.

  7. External Validation and Update of a Prediction Rule for the Duration of Sickness Absence Due to Common Mental Disorders

    NARCIS (Netherlands)

    Norder, Giny; Roelen, Corne A. M.; van der Klink, Jac J. L.; Bultmann, Ute; Sluiter, J. K.; Nieuwenhuijsen, K.

    Purpose The objective of the present study was to validate an existing prediction rule (including age, education, depressive/anxiety symptoms, and recovery expectations) for predictions of the duration of sickness absence due to common mental disorders (CMDs) and investigate the added value of

  8. OR25: Validity of predictive equations for resting energy expenditure for overweight older adults with and without diabetes

    NARCIS (Netherlands)

    Verreijen, A. M.; Garrido, V.; Engberink, M.F.; Memelink, R. G.; Visser, M.; Weijs, P. J.

    2017-01-01

    Rationale: Predictive equations for resting energy expenditure (REE) are used in the treatment of overweight and obesity, but the validity of these equations in overweight older adults is unknown. This study evaluates which predictive REE equation is the best alternative to indirect calorimetry in

  9. A Study of the Predictive Validity of the Children's Depression Inventory for Major Depression Disorder in Puerto Rican Adolescents

    Science.gov (United States)

    Rivera-Medina, Carmen L.; Bernal, Guillermo; Rossello, Jeannette; Cumba-Aviles, Eduardo

    2010-01-01

    This study aims to evaluate the predictive validity of the Children's Depression Inventory items for major depression disorder (MDD) in an outpatient clinic sample of Puerto Rican adolescents. The sample consisted of 130 adolescents, 13 to 18 years old. The five most frequent symptoms of the Children's Depression Inventory that best predict the…

  10. Readmissions and death after ICU discharge: development and validation of two predictive models.

    Directory of Open Access Journals (Sweden)

    Omar Badawi

    Full Text Available INTRODUCTION: Early discharge from the ICU is desirable because it shortens time in the ICU and reduces care costs, but can also increase the likelihood of ICU readmission and post-discharge unanticipated death if patients are discharged before they are stable. We postulated that, using eICU® Research Institute (eRI data from >400 ICUs, we could develop robust models predictive of post-discharge death and readmission that may be incorporated into future clinical information systems (CIS to assist ICU discharge planning. METHODS: Retrospective, multi-center, exploratory cohort study of ICU survivors within the eRI database between 1/1/2007 and 3/31/2011. EXCLUSION CRITERIA: DNR or care limitations at ICU discharge and discharge to location external to hospital. Patients were randomized (2∶1 to development and validation cohorts. Multivariable logistic regression was performed on a broad range of variables including: patient demographics, ICU admission diagnosis, admission severity of illness, laboratory values and physiologic variables present during the last 24 hours of the ICU stay. Multiple imputation was used to address missing data. The primary outcomes were the area under the receiver operator characteristic curves (auROC in the validation cohorts for the models predicting readmission and death within 48 hours of ICU discharge. RESULTS: 469,976 and 234,987 patients representing 219 hospitals were in the development and validation cohorts. Early ICU readmission and death was experienced by 2.54% and 0.92% of all patients, respectively. The relationship between predictors and outcomes (death vs readmission differed, justifying the need for separate models. The models for early readmission and death produced auROCs of 0.71 and 0.92, respectively. Both models calibrated well across risk groups. CONCLUSIONS: Our models for death and readmission after ICU discharge showed good to excellent discrimination and good calibration. Although

  11. Development and validation of an ICD-10-based disability predictive index for patients admitted to hospitals with trauma.

    Science.gov (United States)

    Wada, Tomoki; Yasunaga, Hideo; Yamana, Hayato; Matsui, Hiroki; Fushimi, Kiyohide; Morimura, Naoto

    2018-03-01

    There was no established disability predictive measurement for patients with trauma that could be used in administrative claims databases. The aim of the present study was to develop and validate a diagnosis-based disability predictive index for severe physical disability at discharge using the International Classification of Diseases, 10th revision (ICD-10) coding. This retrospective observational study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to hospitals with trauma and discharged alive from 01 April 2010 to 31 March 2015 were included. Pediatric patients under 15 years old were excluded. Data for patients admitted to hospitals from 01 April 2010 to 31 March 2013 was used for development of a disability predictive index (derivation cohort), while data for patients admitted to hospitals from 01 April 2013 to 31 March 2015 was used for the internal validation (validation cohort). The outcome of interest was severe physical disability defined as the Barthel Index score of predictive index for each patient was defined as the sum of the scores. The predictive performance of the index was validated using the receiver operating characteristic curve analysis in the validation cohort. The derivation cohort included 1,475,158 patients, while the validation cohort included 939,659 patients. Of the 939,659 patients, 235,382 (25.0%) were discharged with severe physical disability. The c-statistics of the disability predictive index was 0.795 (95% confidence interval [CI] 0.794-0.795), while that of a model using the disability predictive index and patient baseline characteristics was 0.856 (95% CI 0.855-0.857). Severe physical disability at discharge may be well predicted with patient age, sex, CCI score, and the diagnosis-based disability predictive index in patients admitted to hospitals with trauma. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies

    Directory of Open Access Journals (Sweden)

    Dimitrov BD

    2015-04-01

    Full Text Available Borislav D Dimitrov,1,2 Nicola Motterlini,2,† Tom Fahey2 1Academic Unit of Primary Care and Population Sciences, University of Southampton, Southampton, United Kingdom; 2HRB Centre for Primary Care Research, Department of General Medicine, Division of Population Health Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland †Nicola Motterlini passed away on November 11, 2012 Objective: Estimating calibration performance of clinical prediction rules (CPRs in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. Study design and methods: Methodological study of systematic reviews of validation studies of CPRs: a ABCD2 rule for prediction of 7 day stroke; and b CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”. As confirmation, a logistic regression model (with derivation study coefficients was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs, 95% confidence intervals (CIs, and indexes of heterogeneity (I2 on forest plots (fixed and random effects models, with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. Results: Our simplified method, applied to ABCD2 rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points, indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82, however, calibration in some studies was low. In such cases with miscalibration, the under-prediction

  13. Development and validation of a novel predictive scoring model for microvascular invasion in patients with hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Zhao, Hui; Hua, Ye; Dai, Tu; He, Jian; Tang, Min; Fu, Xu; Mao, Liang; Jin, Huihan; Qiu, Yudong

    2017-01-01

    Highlights: • This study aimed to establish a novel predictive scoring model of MVI in HCC patients. • Preoperative imaging features on CECT, such as intratumoral arteries, non-nodule type and absence of radiological tumor capsule were independent predictors for MVI. • The predictive scoring model is of great value in prediction of MVI regardless of tumor size. - Abstract: Purpose: Microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) cannot be accurately predicted preoperatively. This study aimed to establish a predictive scoring model of MVI in solitary HCC patients without macroscopic vascular invasion. Methods: A total of 309 consecutive HCC patients who underwent curative hepatectomy were divided into the derivation (n = 206) and validation cohort (n = 103). A predictive scoring model of MVI was established according to the valuable predictors in the derivation cohort based on multivariate logistic regression analysis. The performance of the predictive model was evaluated in the derivation and validation cohorts. Results: Preoperative imaging features on CECT, such as intratumoral arteries, non-nodular type of HCC and absence of radiological tumor capsule were independent predictors for MVI. The predictive scoring model was established according to the β coefficients of the 3 predictors. Area under receiver operating characteristic (AUROC) of the predictive scoring model was 0.872 (95% CI, 0.817-0.928) and 0.856 (95% CI, 0.771-0.940) in the derivation and validation cohorts. The positive and negative predictive values were 76.5% and 88.0% in the derivation cohort and 74.4% and 88.3% in the validation cohort. The performance of the model was similar between the patients with tumor size ≤5 cm and >5 cm in AUROC (P = 0.910). Conclusions: The predictive scoring model based on intratumoral arteries, non-nodular type of HCC, and absence of the radiological tumor capsule on preoperative CECT is of great value in the prediction of MVI

  14. Development and validation of a novel predictive scoring model for microvascular invasion in patients with hepatocellular carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Hui [Department of Hepatopancreatobiliary Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu (China); Department of Hepatopancreatobiliary Surgery, Nanjing Medical University Affiliated Wuxi Second People' s Hospital, Wuxi, Jiangsu (China); Hua, Ye [Department of Neurology, Nanjing Medical University Affiliated Wuxi Second People’s Hospital, Wuxi, Jiangsu (China); Dai, Tu [Department of Hepatopancreatobiliary Surgery, Nanjing Medical University Affiliated Wuxi Second People' s Hospital, Wuxi, Jiangsu (China); He, Jian; Tang, Min [Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu (China); Fu, Xu; Mao, Liang [Department of Hepatopancreatobiliary Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu (China); Jin, Huihan, E-mail: 45687061@qq.com [Department of Hepatopancreatobiliary Surgery, Nanjing Medical University Affiliated Wuxi Second People' s Hospital, Wuxi, Jiangsu (China); Qiu, Yudong, E-mail: yudongqiu510@163.com [Department of Hepatopancreatobiliary Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu (China)

    2017-03-15

    Highlights: • This study aimed to establish a novel predictive scoring model of MVI in HCC patients. • Preoperative imaging features on CECT, such as intratumoral arteries, non-nodule type and absence of radiological tumor capsule were independent predictors for MVI. • The predictive scoring model is of great value in prediction of MVI regardless of tumor size. - Abstract: Purpose: Microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) cannot be accurately predicted preoperatively. This study aimed to establish a predictive scoring model of MVI in solitary HCC patients without macroscopic vascular invasion. Methods: A total of 309 consecutive HCC patients who underwent curative hepatectomy were divided into the derivation (n = 206) and validation cohort (n = 103). A predictive scoring model of MVI was established according to the valuable predictors in the derivation cohort based on multivariate logistic regression analysis. The performance of the predictive model was evaluated in the derivation and validation cohorts. Results: Preoperative imaging features on CECT, such as intratumoral arteries, non-nodular type of HCC and absence of radiological tumor capsule were independent predictors for MVI. The predictive scoring model was established according to the β coefficients of the 3 predictors. Area under receiver operating characteristic (AUROC) of the predictive scoring model was 0.872 (95% CI, 0.817-0.928) and 0.856 (95% CI, 0.771-0.940) in the derivation and validation cohorts. The positive and negative predictive values were 76.5% and 88.0% in the derivation cohort and 74.4% and 88.3% in the validation cohort. The performance of the model was similar between the patients with tumor size ≤5 cm and >5 cm in AUROC (P = 0.910). Conclusions: The predictive scoring model based on intratumoral arteries, non-nodular type of HCC, and absence of the radiological tumor capsule on preoperative CECT is of great value in the prediction of MVI

  15. External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.

    Science.gov (United States)

    Zhao, Zhiguo; Wickersham, Nancy; Kangelaris, Kirsten N; May, Addison K; Bernard, Gordon R; Matthay, Michael A; Calfee, Carolyn S; Koyama, Tatsuki; Ware, Lorraine B

    2017-08-01

    Mortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort. The validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied. The biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined. We validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.

  16. Predicting the success of IVF: external validation of the van Loendersloot's model.

    Science.gov (United States)

    Sarais, Veronica; Reschini, Marco; Busnelli, Andrea; Biancardi, Rossella; Paffoni, Alessio; Somigliana, Edgardo

    2016-06-01

    Is the predictive model for IVF success proposed by van Loendersloot et al. valid in a different geographical and cultural context? The model discriminates well but was less accurate than in the original context where it was developed. Several independent groups have developed models that combine different variables with the aim of estimating the chance of pregnancy with IVF but only four of them have been externally validated. One of these four, the van Loendersloot's model, deserves particular attention and further investigation for at least three reasons; (i) the reported area under the receiver operating characteristics curve (c-statistics) in the temporal validation setting was the highest reported to date (0.68), (ii) the perspective of the model is clinically wise since it includes variables obtained from previous failed cycles, if any, so it can be applied to any women entering an IVF cycle, (iii) the model lacks external validation in a geographically different center. Retrospective cohort study of women undergoing oocyte retrieval for IVF between January 2013 and December 2013 at the infertility unit of the Fondazione Ca' Granda, Ospedale Maggiore Policlinico of Milan, Italy. Only the first oocyte retrieval cycle performed during the study period was included in the study. Women with previous IVF cycles were excluded if the last one before the study cycle was in another center. The main outcome was the cumulative live birth rate per oocytes retrieval. Seven hundred seventy-two women were selected. Variables included in the van Loendersloot's model and the relative weights (beta) were used. The variable resulting from this combination (Y) was transformed into a probability. The discriminatory capacity was assessed using the c-statistics. Calibration was made using a logistic regression that included Y as the unique variable and live birth as the outcome. Data are presented using both the original and the calibrated models. Performance was evaluated

  17. Emotional Responses to Suicidal Patients: Factor Structure, Construct, and Predictive Validity of the Therapist Response Questionnaire-Suicide Form

    Directory of Open Access Journals (Sweden)

    Shira Barzilay

    2018-04-01

    Full Text Available BackgroundMental health professionals have a pivotal role in suicide prevention. However, they also often have intense emotional responses, or countertransference, during encounters with suicidal patients. Previous studies of the Therapist Response Questionnaire-Suicide Form (TRQ-SF, a brief novel measure aimed at probing a distinct set of suicide-related emotional responses to patients found it to be predictive of near-term suicidal behavior among high suicide-risk inpatients. The purpose of this study was to validate the TRQ-SF in a general outpatient clinic setting.MethodsAdult psychiatric outpatients (N = 346 and their treating mental health professionals (N = 48 completed self-report assessments following their first clinic meeting. Clinician measures included the TRQ-SF, general emotional states and traits, therapeutic alliance, and assessment of patient suicide risk. Patient suicidal outcomes and symptom severity were assessed at intake and one-month follow-up. Following confirmatory factor analysis of the TRQ-SF, factor scores were examined for relationships with clinician and patient measures and suicidal outcomes.ResultsFactor analysis of the TRQ-SF confirmed three dimensions: (1 affiliation, (2 distress, and (3 hope. The three factors also loaded onto a single general factor of negative emotional response toward the patient that demonstrated good internal reliability. The TRQ-SF scores were associated with measures of clinician state anger and anxiety and therapeutic alliance, independently of clinician personality traits after controlling for the state- and patient-specific measures. The total score and three subscales were associated in both concurrent and predictive ways with patient suicidal outcomes, depression severity, and clinicians’ judgment of patient suicide risk, but not with global symptom severity, thus indicating specifically suicide-related responses.ConclusionThe TRQ-SF is a brief and reliable measure with a

  18. Emotional Responses to Suicidal Patients: Factor Structure, Construct, and Predictive Validity of the Therapist Response Questionnaire-Suicide Form.

    Science.gov (United States)

    Barzilay, Shira; Yaseen, Zimri S; Hawes, Mariah; Gorman, Bernard; Altman, Rachel; Foster, Adriana; Apter, Alan; Rosenfield, Paul; Galynker, Igor

    2018-01-01

    Mental health professionals have a pivotal role in suicide prevention. However, they also often have intense emotional responses, or countertransference, during encounters with suicidal patients. Previous studies of the Therapist Response Questionnaire-Suicide Form (TRQ-SF), a brief novel measure aimed at probing a distinct set of suicide-related emotional responses to patients found it to be predictive of near-term suicidal behavior among high suicide-risk inpatients. The purpose of this study was to validate the TRQ-SF in a general outpatient clinic setting. Adult psychiatric outpatients ( N  = 346) and their treating mental health professionals ( N  = 48) completed self-report assessments following their first clinic meeting. Clinician measures included the TRQ-SF, general emotional states and traits, therapeutic alliance, and assessment of patient suicide risk. Patient suicidal outcomes and symptom severity were assessed at intake and one-month follow-up. Following confirmatory factor analysis of the TRQ-SF, factor scores were examined for relationships with clinician and patient measures and suicidal outcomes. Factor analysis of the TRQ-SF confirmed three dimensions: (1) affiliation, (2) distress, and (3) hope. The three factors also loaded onto a single general factor of negative emotional response toward the patient that demonstrated good internal reliability. The TRQ-SF scores were associated with measures of clinician state anger and anxiety and therapeutic alliance, independently of clinician personality traits after controlling for the state- and patient-specific measures. The total score and three subscales were associated in both concurrent and predictive ways with patient suicidal outcomes, depression severity, and clinicians' judgment of patient suicide risk, but not with global symptom severity, thus indicating specifically suicide-related responses. The TRQ-SF is a brief and reliable measure with a 3-factor structure. It demonstrates

  19. Proactive, reactive, and romantic relational aggression in adulthood: measurement, predictive validity, gender differences, and association with Intermittent Explosive Disorder.

    Science.gov (United States)

    Murray-Close, Dianna; Ostrov, Jamie M; Nelson, David A; Crick, Nicki R; Coccaro, Emil F

    2010-04-01

    The psychometric properties of a recently introduced adult self-report of relational aggression are presented. Specifically, the predictive utility of proactive and reactive peer-directed relational aggression, as well as romantic relational aggression, are explored in a large (N=1387) study of adults. The measure had adequate reliability and validity and the subscales demonstrated unique predictive abilities for a number of dependent variables. In particular, reactive but not proactive relational aggression was uniquely associated with history of abuse, hostile attribution biases, and feelings of distress regarding relational provocation situations. Reactive relational aggression was also more strongly related to anger and hostility than proactive aggression. In addition, relational aggression in the context of romantic relationships was uniquely related to anger, hostility, impulsivity, history of abuse, hostile attribution biases, and emotional sensitivity to relational provocations, even when controlling for peer-directed relational aggression. Gender differences in overall levels of relational aggression were not observed; however, males were most likely to engage in peer-directed proactive and reactive relational aggression whereas females were most likely to engage in romantic relational aggression. In a second study (N=150), relational aggression was higher in a sample of adults with Intermittent Explosive Disorder than in a sample of healthy controls or psychiatric controls. The findings highlight the importance of assessing subtypes of relational aggression in adult samples. Ways in which this measure may extend research in psychology and psychiatry are discussed. Copyright 2009 Elsevier Ltd. All rights reserved.

  20. CAMS prototype extension: Integration of data acquisition, signal validation, tracking simulator, predictive simulator, state identification, and probabilistic safety assessment

    International Nuclear Information System (INIS)

    Fantoni, Paolo; Iguchi, Yukihiro; Meyer, Geir; Soerensen, Aimar; Van Dyck, Claude

    1996-04-01

    CAMS (Computerized Accident Management Support) is a system that will provide assistance to the staff in the control room, in the technical support centre, and in a national safety centre. These three groups of users do not need the same type of support. Support is offered in identification of the plant state, in assessment of the future development of the accident, and in planning of accident mitigation strategies. Last year the predictive part of the system was tested at a safety exercise arranged by the Swedish Nuclear Inspectorate, and found to be a useful tool, with potential for further development. Now, new methods are added in signal validation, state identification, tracking simulation, predictive simulation, risk monitoring, and man-machine interface design. A prototype will be demonstrated at Loen in May 1996. This prototype is still under development. The purpose of this prototype is to test those methods in a simulated environment to verify that the developed functions, using different techniques, can work together producing the desired result in an efficient way. The plan is to test these techniques at power plants. During the CAMS design, a considerable effort has been given to maintain the generality of the CAMS concept; although the referenced process has been so far a BWR nuclear plant, the use of this structure and design can be applied to other processes, including non-nuclear processes. The research programme is carried out in close cooperation with member organizations (author)

  1. The Predictive Validity of using Admissions Testing and Multiple Mini-interviews in Undergraduate University Admissions

    DEFF Research Database (Denmark)

    Makransky, Guido; Havmose, Philip S.; Vang, Maria Louison

    2017-01-01

    The aim of this study was to evaluate the predictive validity of a two-step admissions procedure that included a cognitive ability test followed by multiple mini-interviews (MMI) used to assess non-cognitive skills compared to a grade-based admissions relative to subsequent drop-out rates...... and academic achievement after one and two years of study. The participants consisted of the entire population of 422 psychology students who were admitted to the University of Southern Denmark between 2010 and 2013. The results showed significantly lower drop-out rates after the first year of study, and non......-significant lower drop-out rates after the second year of study for the admission procedure that included the assessment of non-cognitive skills though the MMI. Furthermore, this admission procedure resulted in a significant lower risk of failing the final exam after the first and second year of study, compared...

  2. Validation of a multi-marker model for the prediction of incident type 2 diabetes mellitus

    DEFF Research Database (Denmark)

    Lyssenko, Valeriya; Jørgensen, Torben; Gerwien, Robert W

    2012-01-01

    Purpose: To assess performance of a biomarker-based score that predicts the five-year risk of diabetes (Diabetes Risk Score, DRS) in an independent cohort that included 15-year follow-up. Method: DRS was developed on the Inter99 cohort, and validated on the Botnia cohort. Performance...... was benchmarked against other risk-assessment tools comparing calibration, time to event analysis, and net reclassification. Results: The area under the receiver-operating characteristic curve (AUC) was 0.84 for the Inter99 cohort and 0.78 for the Botnia cohort. In the Botnia cohort, DRS provided better...... discrimination than fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance, oral glucose tolerance test or risk scores derived from Framingham or San Antonio Study cohorts. Overall reclassification with DRS was significantly better than using FPG and glucose tolerance status (p

  3. Validation Study of a Predictive Algorithm to Evaluate Opioid Use Disorder in a Primary Care Setting

    Science.gov (United States)

    Sharma, Maneesh; Lee, Chee; Kantorovich, Svetlana; Tedtaotao, Maria; Smith, Gregory A.

    2017-01-01

    Background: Opioid abuse in chronic pain patients is a major public health issue. Primary care providers are frequently the first to prescribe opioids to patients suffering from pain, yet do not always have the time or resources to adequately evaluate the risk of opioid use disorder (OUD). Purpose: This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm (“profile”) incorporating phenotypic and, more uniquely, genotypic risk factors. Methods and Results: In a validation study with 452 participants diagnosed with OUD and 1237 controls, the algorithm successfully categorized patients at high and moderate risk of OUD with 91.8% sensitivity. Regardless of changes in the prevalence of OUD, sensitivity of the algorithm remained >90%. Conclusion: The algorithm correctly stratifies primary care patients into low-, moderate-, and high-risk categories to appropriately identify patients in need for additional guidance, monitoring, or treatment changes. PMID:28890908

  4. Validation of the ORIGEN-S code for predicting radionuclide inventories in used CANDU Fuel

    International Nuclear Information System (INIS)

    Tait, J.C.; Gauld, I.; Kerr, A.H.

    1994-10-01

    The safety assessment being conducted by AECL Research for the concept of deep geological disposal of used CANDU UO 2 fuel requires the calculation of radionuclide inventories in the fuel to provide source terms for radionuclide release. This report discusses the validation of selected actinide and fission-product inventories calculated using the ORIGEN-S code coupled with the WIMS-AECL lattice code, using data from analytical measurements of radioisotope inventories in Pickering CANDU reactor fuel. The recent processing of new ENDF/B-VI cross-section data has allowed the ORIGEN-S calculations to be performed using the most up-to-date nuclear data available. The results indicate that the code is reliably predicting actinide and the majority of fission-product inventories to within the analytical uncertainty. 38 refs., 4 figs., 5 tabs

  5. Validation of the ORIGEN-S code for predicting radionuclide inventories in used CANDU fuel

    International Nuclear Information System (INIS)

    Tait, J.C.; Gauld, I.; Kerr, A.H.

    1995-01-01

    The safety assessment being conducted by AECL Research for the concept of deep geological disposal of used CANDU UO 2 fuel requires the calculation of radionuclide inventories in the fuel to provide source terms for radionuclide release. This report discusses the validation of selected actinide and fission-product inventories calculated using the ORIGEN-S code coupled with the WIMS-AECL lattice code, using data from analytical measurements of radioisotope inventories in Pickering CANDU reactor fuel. The recent processing of new ENDF/B-VI cross-section data has allowed the ORIGEN-S calculations to be performed using the most up-to-date nuclear data available. The results indicate that the code is reliably predicting actinide and the majority of fission-product inventories to within the analytical uncertainty. ((orig.))

  6. Angiographically demonstrated coronary collaterals predict residual viable myocardium in patients with chronic myocardial infarction. A regional metabolic study

    International Nuclear Information System (INIS)

    Fukai, Masumi; Ii, Masaaki; Nakakoji, Takahiro

    2000-01-01

    Angiographical demonstration of coronary collateral circulation may suggest the presence of residual viable myocardium. The development of coronary collaterals was judged according to Rentrop's classification in 37 patients with old anteroseptal myocardial infarction and 13 control patients with chest pain syndrome. The subjects with myocardial infarction were divided into 2 groups: 17 patients with the main branch of the left coronary artery clearly identified by collateral blood flow from the contralateral coronary artery [Coll (+) group, male/female 10/7, mean age 56.6 years] and 20 patients with obscure coronary trunk [Coll (-) group, male/female 16/4, mean age 54.9 years]. Thallium-201 myocardial scintigraphy and examination of local myocardial metabolism were carried out by measuring the flux of lactic acid under dipyridamole infusion load. Coronary stenosis of 99% or total occlusion was found in only 5 of 20 patients (25%) in the Coll (-) group but in 16 of 17 patients (94%) in the Coll (+) group (p<0.001). Redistribution of myocardial scintigraphy was found in 11 of 15 patients (73%) in the Coll (+) group, but only 3 of 18 patients (17%) in the Coll (-) group (p<0.01). The myocardial lactic acid extraction rate was -13.2±17.0% in the Coll (+) group, but 9.1±13.2% in the Coll (-) group (p<0.001). These results suggest that coronary collateral may contribute to minimizing the infarct area and to prediction of the presence of viable myocardium. (author)

  7. Predictive validity of the tobacco marketing receptivity index among non-smoking youth.

    Science.gov (United States)

    Braun, Sandra; Abad-Vivero, Erika Nayeli; Mejía, Raúl; Barrientos, Inti; Sargent, James D; Thrasher, James F

    2018-05-01

    In a previous cross-sectional study of early adolescents, we developed a marketing receptivity index (MRI) that integrates point-of-sale (PoS) marketing exposures, brand recall, and ownership of branded merchandise. The MRI had independent, positive associations with smoking susceptibility among never smokers and with current smoking behavior. The current longitudinal study assessed the MRI's predictive validity among adolescents who have never smoked cigarettes METHODS: Data come from a longitudinal, school-based survey of 33 secondary schools in Argentina. Students who had never smoked at baseline were followed up approximately 17months later (n=1700). Questions assessed: PoS marketing exposure by querying frequency of going to stores where tobacco is commonly sold; cued recall of brand names for 3 cigarette packages from dominant brands but with the brand name removed; and ownership of branded merchandise. A four-level MRI was derived: 1.low PoS marketing exposure only; 2. high PoS exposure or recall of 1 brand; 3. recall of 2 or more brands; and 4. ownership of branded merchandise. Logistic regression models regressed smoking initiation by follow up survey on the MRI, each of its components, and students' willingness to try a brand, adjusting for sociodemographics, social network smoking, and sensation seeking. The MRI had an independent positive association with smoking initiation. When analyzed separately, each MRI component was associated with outcomes except branded merchandise ownership. The MRI and its components were associated with smoking initiation, except for branded merchandise ownership, which may better predict smoking progression than initiation. The MRI appears valid and useful for future studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Predictive validity of the personal qualities assessment for selection of medical students in Scotland.

    Science.gov (United States)

    Dowell, Jon; Lumsden, Mary Ann; Powis, David; Munro, Don; Bore, Miles; Makubate, Boikanyo; Kumwenda, Ben

    2011-01-01

    The Personal Qualities Assessment (PQA) was developed to enhance medical student selection by measuring a range of non-cognitive attributes in the applicants to medical school. Applicants to the five Scottish medical schools were invited to pilot the test in 2001 and 2002. To evaluate the predictive validity of PQA for selecting medical students. A longitudinal cohort study was conducted in which PQA scores were compared with senior year medical school performance. Consent to access performance markers was obtained from 626 students (61.6% of 1017 entrants in 2002-2003). Linkable Foundation Year (4th) rankings were available for 411 (66%) students and objective structured clinical examination (OSCE) rankings for 335 (54%) of those consenting. Both samples were representative of the original cohort. No significant correlations were detected between separate elements of the PQA assessment and student performance. However, using the algorithm advocated by Powis et al. those defined as 'non-extreme' (libertarian-communitarian moral orientation scales were ranked higher in OSCEs (average of 7.5% or 25 out of 335, p = 0.049). This study was limited by high attrition and basic outcome markers which are insensitive to relevant non-cognitive characteristics. However, it is the largest currently available study of predictive validity for the PQA assessment. There was one finding of significance: that those students who were identified by PQA as 'not extreme' on the two personal characteristics scales performed better in an OSCE measure of professionalism. Futures studies are required since psychometric testing for both cognitive and non-cognitive attributes are increasingly used in admission process and these should include more and better measures of professionalism against which to correlate non-cognitive traits.

  9. Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

    Directory of Open Access Journals (Sweden)

    Eduardo Arrais Rocha

    2015-01-01

    Full Text Available Abstract Background: 30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes. Objective: This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx at different stages of cardiac resynchronization therapy (CRT. Methods: Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves. Results: The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD, ejection fraction < 25% and use of high doses of diuretics (HDD increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping. Conclusion: We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

  10. [The validity of proofs in demonstrating risk and in research into the causal connection of occupational diseases].

    Science.gov (United States)

    Bonetti, Daniela

    2014-01-01

    The verification of the occupational origin of a disease is a forensic medical activity requiring: the confirmation of the existence and of the exact nosographic identification of the disease, as well as the type of work really performed, and the actual exposure to an effective occupational hazard during an adequate time, and finally a reconstruction of the causal relationship based on objective data. Checking the disease is essentially documentary, corroborated by direct survey by medical examination. The assessment of exposure to the occupational hazard must be scrupulous also, not being acceptable the medical history alone: that is, it does require documentary evidence. Finally, the logical process of recognition of causation requires the application of rigorous forensic medical methodology, with references to current scientific knowledge, and the application of legal criteriology from the legal field of law in which you are moving. Indeed, forensic medical methodology is not the same of epidemiological one: probability of occurrence of an event is not a proof, but only a circumstantial element. A forensic medical doctor organizes every evidence and circumstantial evidence in a unique decision-making process, as a result of a logical process, and probabilistic data can be among circumstantial evidence, but they must suit the case in details, in order to reach the so called "logic probability". But this doesn't mean that you have "proven" the occupational origin of a disease. In the "demonstration" of a fact you use the same forensic medical methodology (thus referring to classic criteria: temporality, biological gradient and plausibility, topographical, exclusion, and phenomenal continuity if suitable, too), and also the same general scientific references, nevertheless the law can be different in causality principles admitted (the principles governing the causal link are the same in Criminal Code and Civil law both, but they differ in private insurance), and

  11. Serum Gamma-Glutamyl-Transferase Independently Predicts Outcome After Transarterial Chemoembolization of Hepatocellular Carcinoma: External Validation

    Energy Technology Data Exchange (ETDEWEB)

    Guiu, Boris, E-mail: boris.guiu@chu-dijon.fr; Deschamps, Frederic [Institut Gustave Roussy, Department of Interventional Radiology (France); Boulin, Mathieu [University Hospital, INSERM U866 (France); Boige, Valerie; Malka, David; Ducreux, Michel [Institut Gustave Roussy, Department of Digestive Oncology (France); Hillon, Patrick [University Hospital, INSERM U866 (France); Baere, Thierry de [Institut Gustave Roussy, Department of Interventional Radiology (France)

    2012-10-15

    Purpose: An Asian study showed that gamma glutamyl transpeptidase (GGT) can predict survival after transarterial chemoembolization (TACE) of hepatocellular carcinoma (HCC). This study was designed to validate in a European population this biomarker as an independent predictor of outcome after TACE of HCC and to determine a threshold value for clinical use. Methods: In 88 consecutive patients treated by TACE for HCC, the optimal threshold for GGT serum level was determined by a ROC analysis. Endpoints were time-to-treatment failure (TTTF) and overall survival (OS). All multivariate models were internally validated using bootstrapping (90 replications). Results: Median follow-up lasted 373 days, and median overall survival was 748 days. The optimal threshold for GGT was 165 U/L (sensitivity: 89.3%; specificity: 56.7%; area under the ROC curve: 0.7515). Median TTTF was shorter when GGT was {>=}165 U/L (281 days vs. 850 days; P < 0.001). GGT {>=}165 U/L (hazard ratio (HR) = 2.06; P = 0.02), WHO PS of 2 (HR = 5.4; P = 0.002), and tumor size (HR = 1.12; P = 0.014) were independently associated with shorter TTTF. Median OS was shorter when GGT was {>=}165 U/L (508 days vs. not reached; P < 0.001). GGT {>=} 165 U/L (HR = 3.05; P = 0.029), WHO PS of 2 (HR = 12.95; P < 0.001), alfa-fetoprotein (HR = 2.9; P = 0.01), and tumor size (HR = 1.096; P = 0.013) were independently associated with shorter OS. The results were confirmed by bootstrapping. Conclusions: Our results provide in a European population the external validation of GGT as an independent predictor of outcome after TACE of HCC. A serum level of GGT {>=} 165 U/L is independently associated with both shorter TTTF and OS.

  12. Serum Gamma-Glutamyl-Transferase Independently Predicts Outcome After Transarterial Chemoembolization of Hepatocellular Carcinoma: External Validation

    International Nuclear Information System (INIS)

    Guiu, Boris; Deschamps, Frédéric; Boulin, Mathieu; Boige, Valérie; Malka, David; Ducreux, Michel; Hillon, Patrick; Baère, Thierry de

    2012-01-01

    Purpose: An Asian study showed that gamma glutamyl transpeptidase (GGT) can predict survival after transarterial chemoembolization (TACE) of hepatocellular carcinoma (HCC). This study was designed to validate in a European population this biomarker as an independent predictor of outcome after TACE of HCC and to determine a threshold value for clinical use. Methods: In 88 consecutive patients treated by TACE for HCC, the optimal threshold for GGT serum level was determined by a ROC analysis. Endpoints were time-to-treatment failure (TTTF) and overall survival (OS). All multivariate models were internally validated using bootstrapping (90 replications). Results: Median follow-up lasted 373 days, and median overall survival was 748 days. The optimal threshold for GGT was 165 U/L (sensitivity: 89.3%; specificity: 56.7%; area under the ROC curve: 0.7515). Median TTTF was shorter when GGT was ≥165 U/L (281 days vs. 850 days; P < 0.001). GGT ≥165 U/L (hazard ratio (HR) = 2.06; P = 0.02), WHO PS of 2 (HR = 5.4; P = 0.002), and tumor size (HR = 1.12; P = 0.014) were independently associated with shorter TTTF. Median OS was shorter when GGT was ≥165 U/L (508 days vs. not reached; P < 0.001). GGT ≥ 165 U/L (HR = 3.05; P = 0.029), WHO PS of 2 (HR = 12.95; P < 0.001), alfa-fetoprotein (HR = 2.9; P = 0.01), and tumor size (HR = 1.096; P = 0.013) were independently associated with shorter OS. The results were confirmed by bootstrapping. Conclusions: Our results provide in a European population the external validation of GGT as an independent predictor of outcome after TACE of HCC. A serum level of GGT ≥ 165 U/L is independently associated with both shorter TTTF and OS.

  13. Validation of software components for the prediction of irradiation-induced damage of RPV steel

    International Nuclear Information System (INIS)

    Bergner, Frank; Birkenheuer, Uwe; Ulbricht, Andreas

    2010-04-01

    The modelling of irradiation-induced damage of RPV steels from primary cascades up to the change of mechanical properties bridging length scales from the atomic level up to the macro-scale and time scales up to years contributes essentially to an improved understanding of the phenomenon of neutron embrittlement. In future modelling may become a constituent of the procedure to evaluate RPV safety. The selected two-step approach is based upon the coupling of a rate-theory module aimed at simulating the evolution of the size distribution of defect-solute clusters with a hardening module aimed at predicting the yield stress increase. The scope of the investigation consists in the development and validation of corresponding numerical tools. In order to validate these tools, the output of representative simulations is compared with results from small-angle neutron scattering experiments and tensile tests performed for neutron-irradiated RPV steels. Using the developed rate-theory module it is possible to simulate the evolution of size, concentration and composition of mixed Cu-vacancy clusters over the relevant ranges of size up to 10.000 atoms and time up to tens of years. The connection between the rate-theory model and hardening is based upon both the mean spacing and the strength of obstacles for dislocation glide. As a result of the validation procedure of the numerical tools, we have found that essential trends of the irradiation-induced yield stress increase of Cu-bearing and low-Cu RPV steels are displayed correctly. First ideas on how to take into account the effect of Ni on both cluster evolution and hardening are worked out.

  14. A model to predict element redistribution in unsaturated soil: Its simplification and validation

    International Nuclear Information System (INIS)

    Sheppard, M.I.; Stephens, M.E.; Davis, P.A.; Wojciechowski, L.

    1991-01-01

    A research model has been developed to predict the long-term fate of contaminants entering unsaturated soil at the surface through irrigation or atmospheric deposition, and/or at the water table through groundwater. The model, called SCEMR1 (Soil Chemical Exchange and Migration of Radionuclides, Version 1), uses Darcy's law to model water movement, and the soil solid/liquid partition coefficient, K d , to model chemical exchange. SCEMR1 has been validated extensively on controlled field experiments with several soils, aeration statuses and the effects of plants. These validation results show that the model is robust and performs well. Sensitivity analyses identified soil K d , annual effective precipitation, soil type and soil depth to be the four most important model parameters. SCEMR1 consumes too much computer time for incorporation into a probabilistic assessment code. Therefore, we have used SCEMR1 output to derive a simple assessment model. The assessment model reflects the complexity of its parent code, and provides a more realistic description of containment transport in soils than would a compartment model. Comparison of the performance of the SCEMR1 research model, the simple SCEMR1 assessment model and the TERRA compartment model on a four-year soil-core experiment shows that the SCEMR1 assessment model generally provides conservative soil concentrations. (15 refs., 3 figs.)

  15. New tools and new ideas for HR practitioners. Structural and predictive validity of weighted satisfaction questionnaire

    Directory of Open Access Journals (Sweden)

    Lorenzo Revuelto Taboada

    2012-12-01

    Full Text Available One of the fundamental tasks for an Human Resource Management (HRM practitioner consists in designing a reward system that can be broadly understood and can influence the attitudes and, subsequently, the behavior of individuals to permit achievement of organizational objectives. To do so, appropriate tools are necessary to allow key actions to be identified in terms of motivating employees; thereby, avoiding opportunistic costs derived from allocating resources needed to close the gap in employee satisfaction, with regard to non-priority factors for workers in satisfying their own personal needs. This article, thus, presents a dual assessment scale consisting of 44 items, categorized into six dimensions, which firstly evaluates the importance of motivation and, secondly, the level of satisfaction with the current situation for each of the 44 factors considered. Using a sample of 801 individuals, we analyzedthe internal consistency, face validity, and predictive validity of the measuring scales, obtaining a series of results that were, to say the least, promising

  16. Validation of MATRA-S Low Flow Predictions Using PNL 2x6 Mixed Convection Test

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Kyong-Won; Kwon, Hyuk; Kim, Seong-Jin; Hwang, Dae-Hyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    The MATRA-S, a subchannel analysis code has been used to thermal-hydraulic design of SMART core. As the safety enhancement is getting important more and more, some features of the MATRA-S code are required to be validated in order to be applied to nonnominal operating conditions in addition to its applicability to reactor design under normal operating conditions. The MATRA-S code has two numerical schemes, SCHEME for implicit application and XSCHEM for explicit one. The implicit scheme had been developed under assumptions that the axial flow is larger enough than the crossflow. Under certain conditions, especially low flow and low pressure operating conditions, this implicit SCHEME oscillates or becomes unstable numerically and then MATRA-S fails to obtain good solution. These demerits were known as common in implicit schemes of many COBRA families. Efforts have been exerted to resolve these limitations in SCHEME of the MATRA-S such as a once through marching scheme against the multi-pass marching scheme and an adaptive multi-grid method. These remedies can reduce the numerically unstable range for SCHEME but some unstable regions still remain. The XSCHEM, an explicit scheme of MATRA-S was validated using the PNL 2x6 rod bundle flow transient test. The explicit scheme agreed with implicit scheme for steady state calculations. And it showed its capability to predict low flow conditions such as negative flow and recirculation flow.

  17. Predicting environmental aspects of CCSR leachates through the application of scientifically valid leaching protocols

    International Nuclear Information System (INIS)

    Hassett, D.J.

    1993-01-01

    The disposal of solid wastes from energy production, particularly solid wastes from coal conversion processes, requires a thorough understanding of the waste material as well as the disposal environment. Many coal conversion solid residues (CCSRs) have chemical, mineralogical, and physical properties advantageous for use as engineering construction materials and in other industrial applications. If disposal is to be the final disposition of CCSRs from any source, the very properties that can make ash useful also contribute to behavior that must be understood for scientifically logical and environmentally responsible disposal. This paper describes the application of scientifically valid leaching and characterization tests designed to predict field phenomena. The key to proper characterization of these unique materials is the recognition of and compensation for the hydration reactions that can occur during long-term leaching. Many of these reactions, such as the formation of the mineral ettringite, can have a profound effect on the concentration of potentially problematic trace elements such as boron, chromium, and selenium. The mobility of these elements, which may be concentrated in CCSRs due to the conversion process, must be properly evaluated for the formation of informed and scientifically sound decisions regarding safe disposal. Groundwater is an extremely important and relatively scarce resource. Contamination of this resource is a threat to life, which is highly dependent on it, so management of materials that can impact groundwater must be carefully planned and executed. The application of scientifically valid leaching protocols and complete testing are critical to proper waste management

  18. What is required for the validation of in vitro assays for predicting contaminant relative bioavailability? Considerations and criteria

    International Nuclear Information System (INIS)

    Juhasz, Albert L.; Basta, Nicholas T.; Smith, Euan

    2013-01-01

    A number of studies have shown the potential of in vitro assays to predict contaminant in vivo relative bioavailability in order to refine human health exposure assessment. Although the term ‘validated’ has been used to describe the goodness of fit between in vivo and in vitro observations, its misuse has arisen from semantic considerations in addition to the lack of defined criteria for establishing performance validation. While several internal validation methods may be utilised, performance validation should preferably focus on assessing the agreement of model predictions with a set of data which are independent of those used to construct the model. In order to achieve robust validated predictive models, a number of parameters (e.g. size of data set, source of independent soils, contaminant concentration range, animal model, relative bioavailability endpoint) need to be considered in addition to defined criteria for establishing performance validation which are currently lacking. -- Defined criteria for establishing in vivo–in vitro performance validation are required in order to ensure robust, defensible predictive models for human health exposure assessment

  19. Predictive validity of the Hendrich fall risk model II in an acute geriatric unit.

    Science.gov (United States)

    Ivziku, Dhurata; Matarese, Maria; Pedone, Claudio

    2011-04-01

    Falls are the most common adverse events reported in acute care hospitals, and older patients are the most likely to fall. The risk of falling cannot be completely eliminated, but it can be reduced through the implementation of a fall prevention program. A major evidence-based intervention to prevent falls has been the use of fall-risk assessment tools. Many tools have been increasingly developed in recent years, but most instruments have not been investigated regarding reliability, validity and clinical usefulness. This study intends to evaluate the predictive validity and inter-rater reliability of Hendrich fall risk model II (HFRM II) in order to identify older patients at risk of falling in geriatric units and recommend its use in clinical practice. A prospective descriptive design was used. The study was carried out in a geriatric acute care unit of an Italian University hospital. All over 65 years old patients consecutively admitted to a geriatric acute care unit of an Italian University hospital over 8-month period were enrolled. The patients enrolled were screened for the falls risk by nurses with the HFRM II within 24h of admission. The falls occurring during the patient's hospital stay were registered. Inter-rater reliability, area under the ROC curve, sensitivity, specificity, positive and negative predictive values and time for the administration were evaluated. 179 elderly patients were included. The inter-rater reliability was 0.87 (95% CI 0.71-1.00). The administration time was about 1min. The most frequently reported risk factors were depression, incontinence, vertigo. Sensitivity and specificity were respectively 86% and 43%. The optimal cut-off score for screening at risk patients was 5 with an area under the ROC curve of 0.72. The risk factors more strongly associated with falls were confusion and depression. As falls of older patients are a common problem in acute care settings it is necessary that the nurses use specific validate and reliable

  20. The validation and assessment of machine learning: a game of prediction from high-dimensional data.

    Directory of Open Access Journals (Sweden)

    Tune H Pers

    Full Text Available In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often implies that multiple methods are tested and compared on the same set of data. This is particularly difficult in situations that are prone to over-fitting where the number of subjects is low compared to the number of potential predictors. The article presents a game which provides some grounds for conducting a fair model comparison. Each player selects a modeling strategy for predicting individual response from potential predictors. A strictly proper scoring rule, bootstrap cross-validation, and a set of rules are used to make the results obtained with different strategies comparable. To illustrate the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively.

  1. Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

    Science.gov (United States)

    Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

    2007-08-01

    Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

  2. Validity of the Clock Drawing Test in predicting reports of driving problems in the elderly

    Directory of Open Access Journals (Sweden)

    Banou Evangelia

    2004-10-01

    Full Text Available Abstract Background This study examined the use of the Folstein Mini Mental Status Exam (MMSE and the Clock Drawing Test (CDT in predicting retrospective reports of driving problems among the elderly. The utility of existing scoring systems for the CDT was also examined. Methods Archival chart records of 325 patients of a geriatric outpatient clinic were reviewed, of which 162 had CDT results (including original clock drawings. T-test, correlation, and regression procedures were used to analyze the data. Results Both CDT and MMSE scores were significantly worse among non-drivers than individuals who were currently or recently driving. Among current or recent drivers, scores on both instruments correlated significantly with the total number of reported accidents or near misses, although the magnitude of the respective correlations was small. Only MMSE scores, however, significantly predicted whether or not any accidents or near misses were reported at all. Neither MMSE nor CDT scores predicted unique variance in the regressions. Conclusions The overall results suggest that both the MMSE and CDT have limited utility as potential indicators of driving problems in the elderly. The demonstrated predictive power for these instruments appears to be redundant, such that both appear to assess general cognitive function versus more specific abilities. Furthermore, the lack of robust prediction suggests that neither are sufficient to serve as stand-alone instruments on which to solely base decisions of driving capacity. Rather, individuals who evidence impairment should be provided a more thorough and comprehensive assessment than can be obtained through screening tools.

  3. Simple knowledge-based descriptors to predict protein-ligand interactions. Methodology and validation

    Science.gov (United States)

    Nissink, J. Willem M.; Verdonk, Marcel L.; Klebe, Gerhard

    2000-11-01

    A new type of shape descriptor is proposed to describe the spatial orientation for non-covalent interactions. It is built from simple, anisotropic Gaussian contributions that are parameterised by 10 adjustable values. The descriptors have been used to fit propensity distributions derived from scatter data stored in the IsoStar database. This database holds composite pictures of possible interaction geometries between a common central group and various interacting moieties, as extracted from small-molecule crystal structures. These distributions can be related to probabilities for the occurrence of certain interaction geometries among different functional groups. A fitting procedure is described that generates the descriptors in a fully automated way. For this purpose, we apply a similarity index that is tailored to the problem, the Split Hodgkin Index. It accounts for the similarity in regions of either high or low propensity in a separate way. Although dependent on the division into these two subregions, the index is robust and performs better than the regular Hodgkin index. The reliability and coverage of the fitted descriptors was assessed using SuperStar. SuperStar usually operates on the raw IsoStar data to calculate propensity distributions, e.g., for a binding site in a protein. For our purpose we modified the code to have it operate on our descriptors instead. This resulted in a substantial reduction in calculation time (factor of five to eight) compared to the original implementation. A validation procedure was performed on a set of 130 protein-ligand complexes, using four representative interacting probes to map the properties of the various binding sites: ammonium nitrogen, alcohol oxygen, carbonyl oxygen, and methyl carbon. The predicted `hot spots' for the binding of these probes were compared to the actual arrangement of ligand atoms in experimentally determined protein-ligand complexes. Results indicate that the version of SuperStar that applies to

  4. Validating severity of illness scoring systems in the prediction of outcomes in Staphylococcus aureus bacteremia.

    Science.gov (United States)

    Sharma, Mamta; Szpunar, Susan; Khatib, Riad

    2013-08-01

    Severity of illness scores are helpful in predicting mortality; however, no standardized scoring system has been validated in patients with Staphylococcus aureus bacteremia (SAB). The modified Rapid Emergency Medicine Score (REMS), the CURB-65 (confusion, urea, respiratory rate, blood pressure and age 65) and the Charlson weighted index of comorbidity (CWIC) were compared in predicting outcomes at the onset of SAB. All adult inpatients with SAB from July 15, 2008, to December 31, 2009, were prospectively assessed. The 3 scoring systems were applied: REMS, CURB-65 and CWIC. The end points were attributable and overall mortality. A total of 241 patients with SAB were reviewed during the study period. The all-cause mortality rate was 22.8% and attributable mortality 14.1%. Patients who died had higher mean CURB-65 score and REMS than those who lived, whereas the difference in the CWIC score was not significant. Two logistic regression models based on CURB-65 score or REMS, after controlling for CWIC, revealed that both scores were independent predictors of mortality, with an odds ratio of 3.38 (P < 0.0001) and 1.45 (P < 0.0001) for CURB-65 and REMS, respectively. Receiver operating characteristic analysis revealed that a cutoff point of 3.0 (CURB-65) and 6.0 (REMS) provided the highest sensitivity and specificity. The area under the curves for all-cause mortality were 0.832 and 0.806, and for attributable mortality 0.845 and 0.819, for CURB-65 and REMS, respectively. REMS and CURB-65 scores outperformed CWIC as predictors of mortality in SAB and may be effective in predicting the severity of illness at the onset of bacteremia.

  5. Predictive Validity and Adjustment of Ideal Partner Preferences Across the Transition Into Romantic Relationships.

    Science.gov (United States)

    Gerlach, Tanja M; Arslan, Ruben C; Schultze, Thomas; Reinhard, Selina K; Penke, Lars

    2017-09-18

    Although empirical research has investigated what we ideally seek in a romantic partner for decades, the crucial question of whether ideal partner preferences actually guide our mating decisions in real life has remained largely unanswered. One reason for this is the lack of designs that assess individuals' ideal partner preferences before entering a relationship and then follow up on them over an extended period. In the Göttingen Mate Choice Study (GMCS), a preregistered, large-scale online study, we used such a naturalistic prospective design. We investigated partner preferences across 4 preference domains in a large sample of predominantly heterosexual singles (N = 763, aged 18-40 years) and tracked these individuals across a period of 5 months upon a possible transition into romantic relationships. Attesting to their predictive validity, partner preferences prospectively predicted the characteristics of later partners. This was equally true for both sexes, except for vitality-attractiveness where men's preferences were more predictive of their later partners' standing on this dimension than women's. Self-perceived mate value did not moderate the preference-partner characteristics relations. Preferences proved to be relatively stable across the 5 months interval, yet were less stable for those who entered a relationship. Subgroup analyses using a newly developed indicator of preference adjustment toward (vs. away from) partner characteristics revealed that participants adjusted their preferences downward when partners fell short of initial preferences, but showed no consistent adjustment when partners exceeded them. Results and implications are discussed against the background of ongoing controversies in mate choice and romantic relationship research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  6. Predicting plant invasions under climate change: are species distribution models validated by field trials?

    Science.gov (United States)

    Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

    2014-09-01

    Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced

  7. Predictive validity of driving-simulator assessments following traumatic brain injury: a preliminary study.

    Science.gov (United States)

    Lew, Henry L; Poole, John H; Lee, Eun Ha; Jaffe, David L; Huang, Hsiu-Chen; Brodd, Edward

    2005-03-01

    To evaluate whether driving simulator and road test evaluations can predict long-term driving performance, we conducted a prospective study on 11 patients with moderate to severe traumatic brain injury. Sixteen healthy subjects were also tested to provide normative values on the simulator at baseline. At their initial evaluation (time-1), subjects' driving skills were measured during a 30-minute simulator trial using an automated 12-measure Simulator Performance Index (SPI), while a trained observer also rated their performance using a Driving Performance Inventory (DPI). In addition, patients were evaluated on the road by a certified driving evaluator. Ten months later (time-2), family members observed patients driving for at least 3 hours over 4 weeks and rated their driving performance using the DPI. At time-1, patients were significantly impaired on automated SPI measures of driving skill, including: speed and steering control, accidents, and vigilance to a divided-attention task. These simulator indices significantly predicted the following aspects of observed driving performance at time-2: handling of automobile controls, regulation of vehicle speed and direction, higher-order judgment and self-control, as well as a trend-level association with car accidents. Automated measures of simulator skill (SPI) were more sensitive and accurate than observational measures of simulator skill (DPI) in predicting actual driving performance. To our surprise, the road test results at time-1 showed no significant relation to driving performance at time-2. Simulator-based assessment of patients with brain injuries can provide ecologically valid measures that, in some cases, may be more sensitive than a traditional road test as predictors of long-term driving performance in the community.

  8. Prediction of low birth weight delivery by maternal status and its validation: Decision curve analysis

    Directory of Open Access Journals (Sweden)

    Mehri Rejali

    2017-01-01

    Full Text Available Background: In this study, we evaluated assessed elements connected with low birth weight (LBW and used decision curve analysis (DCA to define a scale to anticipate the probability of having a LBW newborn child. Methods: This hospital-based case–control study was led in Arak Hospital in Iran. The study included 470 mothers with LBW neonate and 470 mothers with natural neonates. Information were gathered by meeting moms utilizing preplanned organized questionnaire and from hospital records. The estimated probabilities of detecting LBW were calculated using the logistic regression and DCA to quantify the clinical consequences and its validation. Results: Factors significantly associated with LBW were premature membrane rupture (odds ratio [OR] = 3.18 [1.882–5.384], former LBW infants (OR = 2.99 [1.510–5.932], premature pain (OR = 2.70 [1.659–4.415], hypertension in pregnancy (OR = 2.39 [1.429–4.019], last trimester of pregnancy bleeding (OR = 2.58 [1.018–6.583], mother age >30 (OR = 2.17 [1.350–3.498]. However, with DCA, the prediction model made on these 15 variables has a net benefit (NB of 0.3110 is best predictive with the highest NB. NB has simple clinical interpretation and utilizing the model is what might as well be called a procedure that distinguished what might as well be called 31.1 LBW per 100 cases with no superfluous recognize. Conclusions: It is conceivable to foresee LBW utilizing a prediction model show in light of noteworthy hazard components connected with LBW. The majority of the hazard elements for LBW are preventable, and moms can be alluded amid early pregnancy to a middle which is furnished with facilities for administration of high hazard pregnancy and LBW infant.

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

    International Nuclear Information System (INIS)

    Chow, Edward; Abdolell, Mohamed; Panzarella, Tony; Harris, Kristin; Bezjak, Andrea; Warde, Padraig; Tannock, Ian

    2009-01-01

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

  10. Examining Predictive Validity of Oral Reading Fluency Slope in Upper Elementary Grades Using Quantile Regression.

    Science.gov (United States)

    Cho, Eunsoo; Capin, Philip; Roberts, Greg; Vaughn, Sharon

    2017-07-01

    Within multitiered instructional delivery models, progress monitoring is a key mechanism for determining whether a child demonstrates an adequate response to instruction. One measure commonly used to monitor the reading progress of students is oral reading fluency (ORF). This study examined the extent to which ORF slope predicts reading comprehension outcomes for fifth-grade struggling readers ( n = 102) participating in an intensive reading intervention. Quantile regression models showed that ORF slope significantly predicted performance on a sentence-level fluency and comprehension assessment, regardless of the students' reading skills, controlling for initial ORF performance. However, ORF slope was differentially predictive of a passage-level comprehension assessment based on students' reading skills when controlling for initial ORF status. Results showed that ORF explained unique variance for struggling readers whose posttest performance was at the upper quantiles at the end of the reading intervention, but slope was not a significant predictor of passage-level comprehension for students whose reading problems were the most difficult to remediate.

  11. Development and validation of risk prediction equations to estimate survival in patients with colorectal cancer: cohort study

    OpenAIRE

    Hippisley-Cox, Julia; Coupland, Carol

    2017-01-01

    Objective: To develop and externally validate risk prediction equations to estimate absolute and conditional survival in patients with colorectal cancer. \\ud \\ud Design: Cohort study.\\ud \\ud Setting: General practices in England providing data for the QResearch database linked to the national cancer registry.\\ud \\ud Participants: 44 145 patients aged 15-99 with colorectal cancer from 947 practices to derive the equations. The equations were validated in 15 214 patients with colorectal cancer ...

  12. Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis

    Science.gov (United States)

    Rutigliano, Grazia; Stahl, Daniel; Davies, Cathy; Bonoldi, Ilaria; Reilly, Thomas; McGuire, Philip

    2017-01-01

    Importance The overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined. Objective To measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health care. Design, Setting, and Participants Clinical register-based cohort study. Patients were drawn from electronic, real-world, real-time clinical records relating to 2008 to 2015 routine secondary mental health care in the South London and the Maudsley National Health Service Foundation Trust. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and the Maudsley National Health Service Foundation Trust in the period between January 1, 2008, and December 31, 2015. Data analysis began on September 1, 2016. Main Outcomes and Measures Risk of development of nonorganic International Statistical Classification of Diseases and Related Health Problems, Tenth Revision psychotic disorders. Results A total of 91 199 patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within South London and the Maudsley National Health Service Foundation Trust were included in the derivation (n = 33 820) or external validation (n = 54 716) data sets. The mean age was 32.97 years, 50.88% were men, and 61.05% were white race/ethnicity. The mean follow-up was 1588 days. The overall 6-year risk of psychosis in secondary mental health care was 3.02 (95% CI, 2.88-3.15), which is higher than the 6-year risk in the local general population (0.62). Compared with the ARMS designation, all of the International Statistical Classification of Diseases and Related Health Problems

  13. Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields.

    Science.gov (United States)

    Cunha, B C N; Belk, K E; Scanga, J A; LeValley, S B; Tatum, J D; Smith, G C

    2004-07-01

    This study was performed to validate previous equations and to develop and evaluate new regression equations for predicting lamb carcass fabrication yields using outputs from a lamb vision system-hot carcass component (LVS-HCC) and the lamb vision system-chilled carcass LM imaging component (LVS-CCC). Lamb carcasses (n = 149) were selected after slaughter, imaged hot using the LVS-HCC, and chilled for 24 to 48 h at -3 to 1 degrees C. Chilled carcasses yield grades (YG) were assigned on-line by USDA graders and by expert USDA grading supervisors with unlimited time and access to the carcasses. Before fabrication, carcasses were ribbed between the 12th and 13th ribs and imaged using the LVS-CCC. Carcasses were fabricated into bone-in subprimal/primal cuts. Yields calculated included 1) saleable meat yield (SMY); 2) subprimal yield (SPY); and 3) fat yield (FY). On-line (whole-number) USDA YG accounted for 59, 58, and 64%; expert (whole-number) USDA YG explained 59, 59, and 65%; and expert (nearest-tenth) USDA YG accounted for 60, 60, and 67% of the observed variation in SMY, SPY, and FY, respectively. The best prediction equation developed in this trial using LVS-HCC output and hot carcass weight as independent variables explained 68, 62, and 74% of the variation in SMY, SPY, and FY, respectively. Addition of output from LVS-CCC improved predictive accuracy of the equations; the combined output equations explained 72 and 66% of the variability in SMY and SPY, respectively. Accuracy and repeatability of measurement of LM area made with the LVS-CCC also was assessed, and results suggested that use of LVS-CCC provided reasonably accurate (R2 = 0.59) and highly repeatable (repeatability = 0.98) measurements of LM area. Compared with USDA YG, use of the dual-component lamb vision system to predict cut yields of lamb carcasses improved accuracy and precision, suggesting that this system could have an application as an objective means for pricing carcasses in a value

  14. Mortality after Spontaneous Subarachnoid Hemorrhage: Causality and Validation of a Prediction Model.

    Science.gov (United States)

    Abulhasan, Yasser B; Alabdulraheem, Najayeb; Simoneau, Gabrielle; Angle, Mark R; Teitelbaum, Jeanne

    2018-04-01

    To evaluate primary causes of death after spontaneous subarachnoid hemorrhage (SAH) and externally validate the HAIR score, a prognostication tool, in a single academic institution. We reviewed all patients with SAH admitted to our neuro-intensive care unit between 2010 and 2016. Univariate and multivariate logistic regressions were performed to identify predictors of in-hospital mortality. The HAIR score predictors were Hunt and Hess grade at treatment decision, age, intraventricular hemorrhage, and rebleeding within 24 hours. Validation of the HAIR score was characterized with the receiver operating curve, the area under the curve, and a calibration plot. Among 434 patients with SAH, in-hospital mortality was 14.1%. Of the 61 mortalities, 54 (88.5%) had a neurologic cause of death or withdrawal of care and 7 (11.5%) had cardiac death. Median time from SAH to death was 6 days. The main causes of death were effect of the initial hemorrhage (26.2%), rebleeding (23%) and refractory cerebral edema (19.7%). Factors significantly associated with in-hospital mortality in the multivariate analysis were age, Hunt and Hess grade, and intracerebral hemorrhage. Maximum lumen size was also a significant risk factor after aneurysmal SAH. The HAIR score had a satisfactory discriminative ability, with an area under the curve of 0.89. The in-hospital mortality is lower than in previous reports, attesting to the continuing improvement of our institutional SAH care. The major causes are the same as in previous reports. Despite a different therapeutic protocol, the HAIR score showed good discrimination and could be a useful tool for predicting mortality. Copyright © 2018 Elsevier Inc. All rights reserved.

  15. Methodology for experimental validation of a CFD model for predicting noise generation in centrifugal compressors

    International Nuclear Information System (INIS)

    Broatch, A.; Galindo, J.; Navarro, R.; García-Tíscar, J.

    2014-01-01

    Highlights: • A DES of a turbocharger compressor working at peak pressure point is performed. • In-duct pressure signals are measured in a steady flow rig with 3-sensor arrays. • Pressure spectra comparison is performed as a validation for the numerical model. • A suitable comparison methodology is developed, relying on pressure decomposition. • Whoosh noise at outlet duct is detected in experimental and numerical spectra. - Abstract: Centrifugal compressors working in the surge side of the map generate a broadband noise in the range of 1–3 kHz, named as whoosh noise. This noise is perceived at strongly downsized engines operating at particular conditions (full load, tip-in and tip-out maneuvers). A 3-dimensional CFD model of a centrifugal compressor is built to analyze fluid phenomena related to whoosh noise. A detached eddy simulation is performed with the compressor operating at the peak pressure point of 160 krpm. A steady flow rig mounted on an anechoic chamber is used to obtain experimental measurements as a means of validation for the numerical model. In-duct pressure signals are obtained in addition to standard averaged global variables. The numerical simulation provides global variables showing excellent agreement with experimental measurements. Pressure spectra comparison is performed to assess noise prediction capability of numerical model. The influence of the type and position of the virtual pressure probes is evaluated. Pressure decomposition is required by the simulations to obtain meaningful spectra. Different techniques for obtaining pressure components are analyzed. At the simulated conditions, a broadband noise in 1–3 kHz frequency band is detected in the experimental measurements. This whoosh noise is also captured by the numerical model

  16. Predictive validity of a brief antiretroviral adherence index: Retrospective cohort analysis under conditions of repetitive administration

    Directory of Open Access Journals (Sweden)

    Colwell Bradford

    2008-08-01

    Full Text Available Abstract Background Newer antiretroviral (ARV agents have improved pharmacokinetics, potency, and tolerability and have enabled the design of regimens with improved virologic outcomes. Successful antiretroviral therapy is dependent on patient adherence. In previous research, we validated a subset of items from the ACTG adherence battery as prognostic of virologic suppression at 6 months and correlated with adherence estimates from the Medication Event Monitoring System (MEMS. The objective of the current study was to validate the longitudinal use of the Owen Clinic adherence index in analyses of time to initial virologic suppression and maintenance of suppression. Results 278 patients (naïve n = 168, experienced n = 110 met inclusion criteria. Median [range] time on the first regimen during the study period was 286 (30 – 1221 days. 217 patients (78% achieved an undetectable plasma viral load (pVL at median 63 days. 8.3% (18/217 of patients experienced viral rebound (pVL > 400 after initial suppression. Adherence scores varied from 0 – 25 (mean 1.06, median 0. The lowest detectable adherence score cut point using this instrument was ≥ 5 for both initial suppression and maintenance of suppression. In the final Cox model of time to first undetectable pVL, controlling for prior treatment experience and baseline viral load, the adjusted hazard ratio for time updated adherence score was 0.36score ≥ 5 (95% CI: 0.19–0.69 [reference: score ≥ 5 (0.05–0.66 [reference: Conclusion A brief, longitudinally administered self report adherence instrument predicted both initial virologic suppression and maintenance of suppression in patients using contemporary ARV regimens. The survey can be used for identification of sub-optimal adherence with subsequent appropriate intervention.

  17. A demonstration of the 'isotope wind tunnel principle' in JET and its use in predicting reactor performance

    International Nuclear Information System (INIS)

    Cordey, J.; Alper, B.; Budny, R.

    2000-01-01

    ELMy H-mode pulses have been obtained with different hydrogenic isotopes (H and D) but having the same profiles of the dimensionless parameters ρ*, β*, ν* and q, to test whether the confinement scale invariance principle is valid in a tokamak. The fact that the confinement times, the ELM and sawtooth frequencies in the two pulses all scale as expected suggests that the invariance principle is satisfied through the plasma radial extent, in spite of the differing physical processes taking place in the plasma centre, core and edge regions. An application of this 'isotope windtunnel technique' to predicting D-T performance of next step devices is discussed. In tokamak discharges, such as the steady state ELMy H-mode, the physical processes change dramatically as one moves out in minor radius. In the central region the temperature gradient is controlled by MHD modes (sawteeth), whilst outside in what is known as the core confinement region the transport is thought to be due to small scale Larmor radius (r i ) size turbulence, such as that caused by the ion temperature gradient instability. Finally in the edge region the transport is almost neoclassical with intermittent MHD events (ELMs) controlling the steepness of the gradients in this region. From theoretical analysis, in particular the confinement scale invariance principle, it should be possible to describe the transport properties in all three regions in terms of the profiles of the basic dimensionless plasma physics parameters ρ*(∝(MT) 1/2 /aB), β(∝ nT/B 2 ), ν* (∝ na/T 2 ) and q (∝Bκ/Rj). The thermal diffusivity should have the form χ ∝ Ba 2 /M F(ρ*, β, ν*, q, ...) where the form of the function F will be different in each of the three regions. One method of checking whether the invariance principle is correct is to complete wind tunnel or identity experiments on different tokamaks. This involves setting up discharges on different tokamaks with the same profiles of ρ*, β, ν* and q and

  18. The predictive value of demonstrable stress incontinence during basic office evaluation and urodynamics in women without symptomatic urinary incontinence undergoing vaginal prolapse surgery

    NARCIS (Netherlands)

    van der Ploeg, J. Marinus; Zwolsman, Sandra E.; Posthuma, Selina; Wiarda, Hylco S.; van der Vaart, C. Huub; Roovers, Jan-Paul W. R.

    2017-01-01

    Women with pelvic organ prolapse without symptoms of urinary incontinence (UI) might demonstrate stress urinary incontinence (SUI) with or without prolapse reduction. We aimed to determine the value of demonstrable SUI during basic office evaluation or urodynamics in predicting SUI after vaginal

  19. An assessment of the validity of inelastic design analysis methods by comparisons of predictions with test results

    International Nuclear Information System (INIS)

    Corum, J.M.; Clinard, J.A.; Sartory, W.K.

    1976-01-01

    The use of computer programs that employ relatively complex constitutive theories and analysis procedures to perform inelastic design calculations on fast reactor system components introduces questions of validation and acceptance of the analysis results. We may ask ourselves, ''How valid are the answers.'' These questions, in turn, involve the concepts of verification of computer programs as well as qualification of the computer programs and of the underlying constitutive theories and analysis procedures. This paper addresses the latter - the qualification of the analysis methods for inelastic design calculations. Some of the work underway in the United States to provide the necessary information to evaluate inelastic analysis methods and computer programs is described, and typical comparisons of analysis predictions with inelastic structural test results are presented. It is emphasized throughout that rather than asking ourselves how valid, or correct, are the analytical predictions, we might more properly question whether or not the combination of the predictions and the associated high-temperature design criteria leads to an acceptable level of structural integrity. It is believed that in this context the analysis predictions are generally valid, even though exact correlations between predictions and actual behavior are not obtained and cannot be expected. Final judgment, however, must be reserved for the design analyst in each specific case. (author)

  20. External validation of a clinical prediction rule to predict full recovery and ongoing moderate/severe disability following acute whiplash injury.

    Science.gov (United States)

    Ritchie, Carrie; Hendrikz, Joan; Jull, Gwendolen; Elliott, James; Sterling, Michele

    2015-04-01

    Retrospective secondary analysis of data. To investigate the external validity of the whiplash clinical prediction rule (CPR). We recently derived a whiplash CPR to consolidate previously established prognostic factors for poor recovery from a whiplash injury and predicted 2 recovery pathways. Prognostic factors for full recovery were being less than 35 years of age and having an initial Neck Disability Index (NDI) score of 32% or less. Prognostic factors for ongoing moderate/severe pain and disability were being 35 years of age or older, having an initial NDI score of 40% or more, and the presence of hyperarousal symptoms. Validation is required to confirm the reproducibility and accuracy of this CPR. Clinician feedback on the usefulness of the CPR is also important to gauge acceptability. A secondary analysis of data from 101 individuals with acute whiplash-associated disorder who had previously participated in either a randomized controlled clinical trial or prospective cohort study was performed using accuracy statistics. Full recovery was defined as NDI score at 6 months of 10% or less, and ongoing moderate/severe pain and disability were defined as an NDI score at 6 months of 30% or greater. In addition, a small sample of physical therapists completed an anonymous survey on the clinical acceptability and usability of the tool. Results The positive predictive value of ongoing moderate/severe pain and disability was 90.9% in the validation cohort, and the positive predictive value of full recovery was 80.0%. Surveyed physical therapists reported that the whiplash CPR was simple, understandable, would be easy to use, and was an acceptable prognostic tool. External validation of the whiplash CPR confirmed the reproducibility and accuracy of this dual-pathway tool for individuals with acute whiplash-associated disorder. Further research is needed to assess prospective validation, the impact of inclusion on practice, and to examine the efficacy of linking treatment

  1. Validating predictions of evolving porosity and permeability in carbonate reservoir rocks exposed to CO2-brine

    Science.gov (United States)

    Smith, M. M.; Hao, Y.; Carroll, S.

    2017-12-01

    Improving our ability to better forecast the extent and impact of changes in porosity and permeability due to CO2-brine-carbonate reservoir interactions should lower uncertainty in long-term geologic CO2 storage capacity estimates. We have developed a continuum-scale reactive transport model that simulates spatial and temporal changes to porosity, permeability, mineralogy, and fluid composition within carbonate rocks exposed to CO2 and brine at storage reservoir conditions. The model relies on two primary parameters to simulate brine-CO2-carbonate mineral reaction: kinetic rate constant(s), kmineral, for carbonate dissolution; and an exponential parameter, n, relating porosity change to resulting permeability. Experimental data collected from fifteen core-flooding experiments conducted on samples from the Weyburn (Saskatchewan, Canada) and Arbuckle (Kansas, USA) carbonate reservoirs were used to calibrate the reactive-transport model and constrain the useful range of k and n values. Here we present the results of our current efforts to validate this model and the use of these parameter values, by comparing predictions of extent and location of dissolution and the evolution of fluid permeability against our results from new core-flood experiments conducted on samples from the Duperow Formation (Montana, USA). Agreement between model predictions and experimental data increase our confidence that these parameter ranges need not be considered site-specific but may be applied (within reason) at various locations and reservoirs. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  2. Performance prediction and validation of equilibrium modeling for gasification of cashew nut shell char

    Directory of Open Access Journals (Sweden)

    M. Venkata Ramanan

    2008-09-01

    Full Text Available Cashew nut shell, a waste product obtained during deshelling of cashew kernels, had in the past been deemed unfit as a fuel for gasification owing to its high occluded oil content. The oil, a source of natural phenol, oozes upon gasification, thereby clogging the gasifier throat, downstream equipment and associated utilities with oil, resulting in ineffective gasification and premature failure of utilities due to its corrosive characteristics. To overcome this drawback, the cashew shells were de-oiled by charring in closed chambers and were subsequently gasified in an autothermal downdraft gasifier. Equilibrium modeling was carried out to predict the producer gas composition under varying performance influencing parameters, viz., equivalence ratio (ER, reaction temperature (RT and moisture content (MC. The results were compared with the experimental output and are presented in this paper. The model is quite satisfactory with the experimental outcome at the ER applicable to gasification systems, i.e., 0.15 to 0.30. The results show that the mole fraction of (i H2, CO and CH4 decreases while (N2 + H2O and CO2 increases with ER, (ii H2 and CO increases while CH4, (N2 + H2O and CO2 decreases with reaction temperature, (iii H2, CH4, CO2 and (N2 + H2O increases while CO decreases with moisture content. However at an equivalence ratio less than 0.15, the model predicts an unrealistic composition and is observed to be non valid below this ER.

  3. On the Predictability of Computer simulations: Advances in Verification and Validation

    KAUST Repository

    Prudhomme, Serge

    2014-01-06

    We will present recent advances on the topics of Verification and Validation in order to assess the reliability and predictability of computer simulations. The first part of the talk will focus on goal-oriented error estimation for nonlinear boundary-value problems and nonlinear quantities of interest, in which case the error representation consists of two contributions: 1) a first contribution, involving the residual and the solution of the linearized adjoint problem, which quantifies the discretization or modeling error; and 2) a second contribution, combining higher-order terms that describe the linearization error. The linearization error contribution is in general neglected with respect to the discretization or modeling error. However, when nonlinear effects are significant, it is unclear whether ignoring linearization effects may produce poor convergence of the adaptive process. The objective will be to show how both contributions can be estimated and employed in an adaptive scheme that simultaneously controls the two errors in a balanced manner. In the second part of the talk, we will present novel approach for calibration of model parameters. The proposed inverse problem not only involves the minimization of the misfit between experimental observables and their theoretical estimates, but also an objective function that takes into account some design goals on specific design scenarios. The method can be viewed as a regularization approach of the inverse problem, one, however, that best respects some design goals for which mathematical models are intended. The inverse problem is solved by a Bayesian method to account for uncertainties in the data. We will show that it shares the same structure as the deterministic problem that one would obtain by multi-objective optimization theory. The method is illustrated on an example of heat transfer in a two-dimensional fin. The proposed approach has the main benefit that it increases the confidence in predictive

  4. Development and validation of a Luminex assay for detection of a predictive biomarker for PROSTVAC-VF therapy

    Science.gov (United States)

    Lucas, Julie L.; Tacheny, Erin A.; Ferris, Allison; Galusha, Michelle; Srivastava, Apurva K.; Ganguly, Aniruddha; Williams, P. Mickey; Sachs, Michael C.; Thurin, Magdalena; Tricoli, James V.; Ricker, Winnie; Gildersleeve, Jeffrey C.

    2017-01-01

    Cancer therapies can provide substantially improved survival in some patients while other seemingly similar patients receive little or no benefit. Strategies to identify patients likely to respond well to a given therapy could significantly improve health care outcomes by maximizing clinical benefits while reducing toxicities and adverse effects. Using a glycan microarray assay, we recently reported that pretreatment serum levels of IgM specific to blood group A trisaccharide (BG-Atri) correlate positively with overall survival of cancer patients on PROSTVAC-VF therapy. The results suggested anti-BG-Atri IgM measured prior to treatment could serve as a biomarker for identifying patients likely to benefit from PROSTVAC-VF. For continued development and clinical application of serum IgM specific to BG-Atri as a predictive biomarker, a clinical assay was needed. In this study, we developed and validated a Luminex-based clinical assay for measuring serum IgM specific to BG-Atri. IgM levels were measured with the Luminex assay and compared to levels measured using the microarray for 126 healthy individuals and 77 prostate cancer patients. This assay provided reproducible and consistent results with low %CVs, and tolerance ranges were established for the assay. IgM levels measured using the Luminex assay were found to be highly correlated to the microarray results with R values of 0.93–0.95. This assay is a Laboratory Developed Test (LDT) and is suitable for evaluating thousands of serum samples in CLIA certified laboratories that have validated the assay. In addition, the study demonstrates that discoveries made using neoglycoprotein-based microarrays can be readily migrated to a clinical assay. PMID:28771597

  5. Validity of Medical Student Questionnaire Data in Prediction of Rural Practice Choice and Its Association With Service Orientation.

    Science.gov (United States)

    Shannon, C Ken; Jackson, Jodie

    2015-01-01

    The validity of medical student projection of, and predictors for, rural practice and the association of a measure of service orientation, projected practice accessibility to the indigent, were investigated. West Virginia (WV) medical student online pre- and postrural rotation questionnaire data were collected during the time period 2001-2009. Of the 1,517 respondent students, submissions by 1,271 met the time interval criterion for inclusion in analyses. Subsequent WV licensing data were available for 461 in 2013. These 2 databases were used to assess for validity of projection of rural practice, for predictors of rural practice, and for student projected accessibility of the future practice to indigent patients. There were statistically significant associations between both pre- and postrotation projections of rural practice and subsequent rural practice. The most significant independent predictors of rural practice were student rural background, reported primary care intent, prediction of rural practice and projection of greater accessibility of the future practice to indigent patients. For scoring of practice access, there were trends for higher scoring by rural students and rural practitioners, with greater pre-post increases for those with urban hometowns. This study demonstrates the utility of medical student questionnaires for projections of numbers of future rural physicians. It suggests that students with a rural background, rural practice intent, or greater service orientation are more likely to enter rural practice. It also suggests that students, particularly those with urban hometowns, are influenced by rural rotation experiences in forecasting greater practice accessibility and in entering rural practice. © 2015 National Rural Health Association.

  6. Gene expression signatures predict outcome in non-muscle invasive bladder carcinoma - a multi-center validation study

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Zieger, Karsten; Real, Francisco X.

    2007-01-01

    and carcinoma in situ (CIS) and for predicting disease recurrence and progression. EXPERIMENTAL DESIGN: We analyzed tumors from 404 patients diagnosed with bladder cancer in hospitals in Denmark, Sweden, England, Spain, and France using custom microarrays. Molecular classifications were compared with pathologic....... CONCLUSION: This multicenter validation study confirms in an independent series the clinical utility of molecular classifiers to predict the outcome of patients initially diagnosed with non-muscle-invasive bladder cancer. This information may be useful to better guide patient treatment....

  7. Comparison of mortality prediction models and validation of SAPS II in critically ill burns patients.

    Science.gov (United States)

    Pantet, O; Faouzi, M; Brusselaers, N; Vernay, A; Berger, M M

    2016-06-30

    Specific burn outcome prediction scores such as the Abbreviated Burn Severity Index (ABSI), Ryan, Belgian Outcome of Burn Injury (BOBI) and revised Baux scores have been extensively studied. Validation studies of the critical care score SAPS II (Simplified Acute Physiology Score) have included burns patients but not addressed them as a cohort. The study aimed at comparing their performance in a Swiss burns intensive care unit (ICU) and to observe whether they were affected by a standardized definition of inhalation injury. We conducted a retrospective cohort study, including all consecutive ICU burn admissions (n=492) between 1996 and 2013: 5 epochs were defined by protocol changes. As required for SAPS II calculation, stays burned (TBSA) and inhalation injury (systematic standardized diagnosis since 2006). Study epochs were compared (χ2 test, ANOVA). Score performance was assessed by receiver operating characteristic curve analysis. SAPS II performed well (AUC 0.89), particularly in burns burns <40% TBSA. Ryan and BOBI scores were least accurate, as they heavily weight inhalation injury.

  8. A Validated Analytical Model for Availability Prediction of IPTV Services in VANETs

    Directory of Open Access Journals (Sweden)

    Bernd E. Wolfinger

    2014-12-01

    Full Text Available In vehicular ad hoc networks (VANETs, besides the original applications typically related to traffic safety, we nowadays can observe an increasing trend toward infotainment applications, such as IPTV services. Quality of experience (QoE, as observed by the end users of IPTV, is highly important to guarantee adequate user acceptance for the service. In IPTV, QoE is mainly determined by the availability of TV channels for the users. This paper presents an efficient and rather generally applicable analytical model that allows one to predict the blocking probability of TV channels, both for channel-switching-induced, as well as for handover-induced blocking events. We present the successful validation of the model by means of simulation, and we introduce a new measure for QoE. Numerous case studies illustrate how the analytical model and our new QoE measure can be applied successfully for the dimensioning of IPTV systems, taking into account the QoE requirements of the IPTV service users in strongly diverse traffic scenarios.

  9. Theory and validation of a liquid radiation filter greenhouse simulation for performance prediction

    International Nuclear Information System (INIS)

    Feuermann, D.; Kopel, R.; Zeroni, M.; Levi, S.; Gale, J.

    1997-01-01

    A greenhouse is described which has a selectively absorbing liquid radiation filter (LRF) circulating in double layered cladding. The filter removes much of the near infrared wave band of solar radiation (700 nm) while transmitting most of the photosynthetic radiation (400-700 nm). This greatly reduces the heat input to the greenhouse and, by transferring heat from day to night, facilitates better temperature control. This is particularly important for CO2 fertilization, which requires that the greenhouse should remain closed during daylight hours. A computer simulation model was developed to study the relationship between design parameters of such a LRF greenhouse and its thermal performance under different climatic conditions. The model was based on a small number of governing equations describing the major physical phenomena responsible for the greenhouse climate. Validation of the simulation was performed with data from a 330 m2 LRF greenhouse, operating in the Negev (Israel) desert highlands. The predicted greenhouse temperatures were found to agree with measured values to within one to two degrees Celsius. Performances of a LRF and a conventional greenhouse were compared using the simulation and hourly meteorological data for central Israel. For the summer season of May to October, the number of daylight hours during which the LRF greenhouse could remain closed was larger by about two-thirds than that of the conventional greenhouse

  10. Microcomputer-based tests for repeated-measures: Metric properties and predictive validities

    Science.gov (United States)

    Kennedy, Robert S.; Baltzley, Dennis R.; Dunlap, William P.; Wilkes, Robert L.; Kuntz, Lois-Ann

    1989-01-01

    A menu of psychomotor and mental acuity tests were refined. Field applications of such a battery are, for example, a study of the effects of toxic agents or exotic environments on performance readiness, or the determination of fitness for duty. The key requirement of these tasks is that they be suitable for repeated-measures applications, and so questions of stability and reliability are a continuing, central focus of this work. After the initial (practice) session, seven replications of 14 microcomputer-based performance tests (32 measures) were completed by 37 subjects. Each test in the battery had previously been shown to stabilize in less than five 90-second administrations and to possess retest reliabilities greater than r = 0.707 for three minutes of testing. However, all the tests had never been administered together as a battery and they had never been self-administered. In order to provide predictive validity for intelligence measurement, the Wechsler Adult Intelligence Scale-Revised and the Wonderlic Personnel Test were obtained on the same subjects.

  11. Regional variation in the predictive validity of self-rated health for mortality

    Directory of Open Access Journals (Sweden)

    Edward R. Berchick

    2017-12-01

    Full Text Available Self-rated health (SRH is a commonly used measure for assessing general health in surveys in the United States. However, individuals from different parts of the United States may vary in how they assess their health. Geographic differences in health care access and in the prevalence of illnesses may make it difficult to discern true regional differences in health when using SRH as a health measure. In this article, we use data from the 1986 and 1989–2006 National Health Interview Survey Linked Mortality Files and estimate Cox regression models to examine whether the relationship between SRH and five-year all-cause mortality differs by Census region. Contrary to hypotheses, there is no evidence of regional variation in the predictive validity of SRH for mortality. At all levels of SRH, and for both non-Hispanic white and non-Hispanic black respondents, SRH is equally and strongly associated with five-year mortality across regions. Our results suggest that differences in SRH across regions are not solely due to differences in how respondents assess their health across regions, but reflect true differences in health. Future research can, therefore, employ this common measure to investigate the geographic patterning of health in the United States.

  12. External validation of models predicting the individual risk of metachronous peritoneal carcinomatosis from colon and rectal cancer.

    Science.gov (United States)

    Segelman, J; Akre, O; Gustafsson, U O; Bottai, M; Martling, A

    2016-04-01

    To externally validate previously published predictive models of the risk of developing metachronous peritoneal carcinomatosis (PC) after resection of nonmetastatic colon or rectal cancer and to update the predictive model for colon cancer by adding new prognostic predictors. Data from all patients with Stage I-III colorectal cancer identified from a population-based database in Stockholm between 2008 and 2010 were used. We assessed the concordance between the predicted and observed probabilities of PC and utilized proportional-hazard regression to update the predictive model for colon cancer. When applied to the new validation dataset (n = 2011), the colon and rectal cancer risk-score models predicted metachronous PC with a concordance index of 79% and 67%, respectively. After adding the subclasses of pT3 and pT4 stage and mucinous tumour to the colon cancer model, the concordance index increased to 82%. In validation of external and recent cohorts, the predictive accuracy was strong in colon cancer and moderate in rectal cancer patients. The model can be used to identify high-risk patients for planned second-look laparoscopy/laparotomy for possible subsequent cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

  13. Development and validation of prediction models for endometrial cancer in postmenopausal bleeding.

    Science.gov (United States)

    Wong, Alyssa Sze-Wai; Cheung, Chun Wai; Fung, Linda Wen-Ying; Lao, Terence Tzu-Hsi; Mol, Ben Willem J; Sahota, Daljit Singh

    2016-08-01

    To develop and assess the accuracy of risk prediction models to diagnose endometrial cancer in women having postmenopausal bleeding (PMB). A retrospective cohort study of 4383 women in a One-stop PMB clinic from a university teaching hospital in Hong Kong. Clinical risk factors, transvaginal ultrasonic measurement of endometrial thickness (ET) and endometrial histology were obtained from consecutive women between 2002 and 2013. Two models to predict risk of endometrial cancer were developed and assessed, one based on patient characteristics alone and a second incorporated ET with patient characteristics. Endometrial histology was used as the reference standard. The split-sample internal validation and bootstrapping technique were adopted. The optimal threshold for prediction of endometrial cancer by the final models was determined using a receiver-operating characteristics (ROC) curve and Youden Index. The diagnostic gain was compared to a reference strategy of measuring ET only by comparing the AUC using the Delong test. Out of 4383 women with PMB, 168 (3.8%) were diagnosed with endometrial cancer. ET alone had an area under curve (AUC) of 0.92 (95% confidence intervals [CIs] 0.89-0.94). In the patient characteristics only model, independent predictors of cancer were age at presentation, age at menopause, body mass index, nulliparity and recurrent vaginal bleeding. The AUC and Youdens Index of the patient characteristic only model were respectively 0.73 (95% CI 0.67-0.80) and 0.72 (Sensitivity=66.5%; Specificity=68.9%; +ve LR=2.14; -ve LR=0.49). ET, age at presentation, nulliparity and recurrent vaginal bleeding were independent predictors in the patient characteristics plus ET model. The AUC and Youdens Index of the patient characteristic plus ET model where respectively 0.92 (95% CI 0.88-0.96) and 0.71 (Sensitivity=82.7%; Specificity=88.3%; +ve LR=6.38; -ve LR=0.2). Comparison of AUC indicated that a history alone model was inferior to a model using ET alone

  14. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

    NARCIS (Netherlands)

    Petersen, Japke F.; Stuiver, Martijn M.; Timmermans, Adriana J.; Chen, Amy; Zhang, Hongzhen; O'Neill, James P.; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T.; Koch, Wayne; van den Brekel, Michiel W. M.

    2017-01-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442

  15. Validation of Clinical Prediction Models: Theory and Applications in Testicular Germ Cell Cancer

    NARCIS (Netherlands)

    Y. Vergouwe (Yvonne)

    2003-01-01

    textabstractlinical prediction models combine patient characteristics to predict the probability of having a certain disease (diagnosis) or the probability that a particular disease state will occur (prognosis). The predicted probability of the diagnostic or prognostic outcome may assist the

  16. A systematic approach to obtain validated Partial Least Square models for predicting lipoprotein subclasses from serum NMR spectra

    NARCIS (Netherlands)

    Mihaleva, V.V.; van Schalkwijk, D.B.; de Graaf, A.A.; van Duynhoven, J.; van Dorsten, F.A.; Vervoort, J.; Smilde, A.; Westerhuis, J.A.; Jacobs, D.M.

    2014-01-01

    A systematic approach is described for building validated PLS models that predict cholesterol and triglyceride concentrations in lipoprotein subclasses in fasting serum from a normolipidemic, healthy population. The PLS models were built on diffusion-edited 1H NMR spectra and calibrated on

  17. A systematic approach to obtain validated partial least square models for predicting lipoprotein subclasses from serum NMR spectra

    NARCIS (Netherlands)

    Mihaleva, V.V.; Schalkwijk, van D.B.; Graaf, de A.A.; Duynhoven, van J.P.M.; Dorsten, van F.A.; Vervoort, J.J.M.; Smilde, A.K.; Westerhuis, J.A.; Jacobs, D.M.

    2014-01-01

    A systematic approach is described for building validated PLS models that predict cholesterol and triglyceride concentrations in lipoprotein subclasses in fasting serum from a normolipidemic, healthy population. The PLS models were built on diffusion-edited (1)H NMR spectra and calibrated on

  18. A systematic approach to obtain validated partial least square models for predicting lipoprotein subclasses from serum nmr spectra

    NARCIS (Netherlands)

    Mihaleva, V.V.; Schalkwijk, D.B. van; Graaf, A.A. de; Duynhoven, J. van; Dorsten, F.A. van; Vervoort, J.; Smilde, A.; Westerhuis, J.A.; Jacobs, D.M.

    2014-01-01

    A systematic approach is described for building validated PLS models that predict cholesterol and triglyceride concentrations in lipoprotein subclasses in fasting serum from a normolipidemic, healthy population. The PLS models were built on diffusion-edited 1H NMR spectra and calibrated on

  19. Differential Predictive Validity of High School GPA and College Entrance Test Scores for University Students in Yemen

    Science.gov (United States)

    Al-Hattami, Abdulghani Ali Dawod

    2012-01-01

    High school grade point average and college entrance test scores are two admission criteria that are currently used by most colleges in Yemen to select their prospective students. Given their widespread use, it is important to investigate their predictive validity to ensure the accuracy of the admission decisions in these institutions. This study…

  20. Using multiple and specific criteria to assess the predictive validity of the Big Five personality factors on academic performance.

    NARCIS (Netherlands)

    Kappe, F.R.; van der Flier, H.

    2010-01-01

    Multiple and specific academic performance criteria were used to examine the predictive validity of the Big Five personality traits. One hundred thirty-three students in a college of higher learning in The Netherlands participated in a naturally occurring field study. The results of the NEO-FFI were

  1. Validation of the ASSERT subchannel code for prediction of CHF in standard and non-standard CANDU bundle geometries

    International Nuclear Information System (INIS)

    Kiteley, J.C.; Carver, M.B.; Zhou, Q.N.

    1993-01-01

    The ASSERT code has been developed to address the three-dimensional computation of flow and phase distribution and fuel element surface temperatures within the horizontal subchannels of CANDU PHWR fuel channels, and to provide a detailed prediction of critical heat flux distribution throughout the bundle. The ASSERT subchannel code has been validated extensively against a wide repertoire of experiments; its combination of three-dimensional prediction of local flow conditions with a comprehensive method of predicting critical heat flux (CHF) at these local conditions makes it a unique tool for predicting CHF for situations outside the existing experimental data base. In particular, ASSERT is the only tool available to systematically investigate CHF under conditions of local geometric variations, such as pressure tube creep and fuel element strain. This paper discusses the numerical methodology used in ASSERT, the constitutive relationships incorporated, and the CHF assessment methodology. The evolutionary validation plan is discussed, and early validation exercises are summarized. The paper concentrates, however, on more recent validation exercises in standard and non-standard geometries. 28 refs., 12 figs

  2. Validation of the ASSERT subchannel code: Prediction of critical heat flux in standard and nonstandard CANDU bundle geometries

    International Nuclear Information System (INIS)

    Carver, M.B.; Kiteley, J.C.; Zhou, R.Q.N.; Junop, S.V.; Rowe, D.S.

    1995-01-01

    The ASSERT code has been developed to address the three-dimensional computation of flow and phase distribution and fuel element surface temperatures within the horizontal subchannels of Canada uranium deuterium (CANDU) pressurized heavy water reactor fuel channels and to provide a detailed prediction of critical heat flux (CHF) distribution throughout the bundle. The ASSERT subchannel code has been validated extensively against a wide repertoire of experiments; its combination of three-dimensional prediction of local flow conditions with a comprehensive method of predicting CHF at these local conditions makes it a unique tool for predicting CHF for situations outside the existing experimental database. In particular, ASSERT is an appropriate tool to systematically investigate CHF under conditions of local geometric variations, such as pressure tube creep and fuel element strain. The numerical methodology used in ASSERT, the constitutive relationships incorporated, and the CHF assessment methodology are discussed. The evolutionary validation plan is also discussed and early validation exercises are summarized. More recent validation exercises in standard and nonstandard geometries are emphasized

  3. On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design.

    Science.gov (United States)

    Roy, Kunal; Mitra, Indrani

    2011-07-01

    Quantitative structure-activity relationships (QSARs) have important applications in drug discovery research, environmental fate modeling, property prediction, etc. Validation has been recognized as a very important step for QSAR model development. As one of the important objectives of QSAR modeling is to predict activity/property/toxicity of new chemicals falling within the domain of applicability of the developed models and QSARs are being used for regulatory decisions, checking reliability of the models and confidence of their predictions is a very important aspect, which can be judged during the validation process. One prime application of a statistically significant QSAR model is virtual screening for molecules with improved potency based on the pharmacophoric features and the descriptors appearing in the QSAR model. Validated QSAR models may also be utilized for design of focused libraries which may be subsequently screened for the selection of hits. The present review focuses on various metrics used for validation of predictive QSAR models together with an overview of the application of QSAR models in the fields of virtual screening and focused library design for diverse series of compounds with citation of some recent examples.

  4. Prognosis of patients with nonspecific neck pain: development and external validation of a prediction rule for persistence of complaints

    NARCIS (Netherlands)

    Schellingerhout, J.M.; Heijmans, M.W.; Verhagen, A.P.; Lewis, M.; de Vet, H.C.W.; Koes, B.W.

    2010-01-01

    Study Design.: Reanalysis of data from 3 randomized controlled trials. Objective.: Development and validation of a prediction rule that estimates the probability of complaints persisting for at least 6 months in patients presenting with nonspecific neck pain in primary care. Sumary of Background

  5. Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

    Science.gov (United States)

    Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

    2013-01-01

    This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

  6. A Cross-Cultural Test of Sex Bias in the Predictive Validity of Scholastic Aptitude Examinations: Some Israeli Findings.

    Science.gov (United States)

    Zeidner, Moshe

    1987-01-01

    This study examined the cross-cultural validity of the sex bias contention with respect to standardized aptitude testing, used for academic prediction purposes in Israel. Analyses were based on the grade point average and scores of 1778 Jewish and 1017 Arab students who were administered standardized college entrance test batteries. (Author/LMO)

  7. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

    NARCIS (Netherlands)

    Roelen, Corne A. M.; Stapelfeldt, Christina M.; Heymans, Martijn W.; van Rhenen, Willem; Labriola, Merete; Nielsen, Claus V.; Bultmann, Ute; Jensen, Chris

    Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated. Methods 2,562 municipal eldercare

  8. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

    NARCIS (Netherlands)

    Roelen, C.A.M.; Stapelfeldt, C.M.; Heijmans, M.W.; van Rhenen, W.; Labriola, M.; Nielsen, C.V.; Bultmann, U.; Jensen, C.

    2015-01-01

    Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models’ risk discrimination was also investigated. Methods 2,562 municipal eldercare

  9. Determining the validity of exposure models for environmental epidemiology : predicting electromagnetic fields from mobile phone base stations

    NARCIS (Netherlands)

    Beekhuizen, Johan|info:eu-repo/dai/nl/34472641X

    2014-01-01

    One of the key challenges in environmental epidemiology is the exposure assessment of large populations. Spatial exposure models have been developed that predict exposure to the pollutant of interest for large study sizes. However, the validity of these exposure models is often unknown. In this

  10. Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables

    NARCIS (Netherlands)

    Roelen, Corne; Thorsen, Sannie; Heymans, Martijn; Twisk, Jos; Bultmann, Ute; Bjorner, Jakob

    2018-01-01

    Purpose: The purpose of this study is to develop and validate a prediction model for identifying employees at increased risk of long-term sickness absence (LTSA), by using variables commonly measured in occupational health surveys. Materials and methods: Based on the literature, 15 predictor

  11. Predicting asthma in preschool children with asthma-like symptoms : Validating and updating the PIAMA risk score

    NARCIS (Netherlands)

    Hafkamp-de Groen, Esther; Lingsma, Hester F.; Caudri, Daan; Levie, Deborah; Wijga, Alet; Koppelman, Gerard H.; Duijts, Liesbeth; Jaddoe, Vincent W. V.; Smit, Henriette A.; Kerkhof, Marjan; Moll, Henriette A.; Hofman, Albert; Steyerberg, Ewout W.; de Jongste, Johan C.; Raat, Hein

    2013-01-01

    Background: The Prevention and Incidence of Asthma and Mite Allergy (PIAMA) risk score predicts the probability of having asthma at school age among preschool children with suggestive symptoms. Objective: We sought to externally validate the PIAMA risk score at different ages and in ethnic and

  12. Incremental Criterion Validity of the WJ-III COG Clinical Clusters: Marginal Predictive Effects beyond the General Factor

    Science.gov (United States)

    McGill, Ryan J.

    2015-01-01

    The current study examined the incremental validity of the clinical clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ-III COG) for predicting scores on the Woodcock-Johnson III Tests of Achievement (WJ-III ACH). All participants were children and adolescents (N = 4,722) drawn from the nationally representative WJ-III…

  13. Predictive modeling of infrared radiative heating in tomato dry-peeling process: Part II. Model validation and sensitivity analysis

    Science.gov (United States)

    A predictive mathematical model was developed to simulate heat transfer in a tomato undergoing double sided infrared (IR) heating in a dry-peeling process. The aims of this study were to validate the developed model using experimental data and to investigate different engineering parameters that mos...

  14. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

    Energy Technology Data Exchange (ETDEWEB)

    Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)

    2012-05-01

    Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive

  15. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

    International Nuclear Information System (INIS)

    Valerio, Luis G.; Cross, Kevin P.

    2012-01-01

    Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.

  16. TECHNOLOGY DEMONSTRATION OF SLUDGE MASS REDUCTION VIA ALUMINUM DISSOLUTION: GLASS FORMULATION PROCESSING WINDOW PREDICTIONS FOR SB5

    International Nuclear Information System (INIS)

    Fox, K.; Tommy Edwards, T.; David Peeler, D.

    2007-01-01

    Composition projections for Sludge Batch 5 (SB5) were developed, based on a modeling approach at the Savannah River National Laboratory (SRNL), to evaluate possible impacts of the Al-dissolution process on the availability of viable frit compositions for vitrification at the Defense Waste Processing Facility (DWPF). The study included two projected SB5 compositions that bound potential outcomes (or degrees of effectiveness) of the Al-dissolution process, as well as a nominal SB5 composition projection based on the results of the recent Al-dissolution demonstration at SRNL. The three SB5 projections were the focus of a two-stage paper study assessment. A Nominal Stage assessment combined each of the SB5 composition projections with an array of 19,305 frit compositions over a wide range of waste loading (WL) values and evaluated them against the DWPF process control models. The Nominal Stage results allowed for the down-selection of a small number of frits that provided reasonable projected operating windows (typically 27 to 42 wt% WL). The frit/sludge systems were mostly limited by process related constraints, with only one system being limited by predictions of nepheline crystallization, a waste form affecting constraint. The criteria applied in selecting the frit compositions somewhat restricted the compositional flexibility of the candidate frits for each individual SB5 composition projection, which may limit the ability to further tailor the frit for improved melt rate. Variation Stage assessments were then performed using the down-selected frits and the three SB5 composition projections with variation applied to each sludge component. The Variation Stage results showed that the operating windows were reduced in width, as expected when variation in the sludge composition is applied. However, several of the down-selected frits exhibited a relatively high degree of robustness to the applied sludge variation, providing WL windows of approximately 30 to 39 wt%. The

  17. Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills

    Science.gov (United States)

    2012-07-01

    Previous research demonstrated that an empirically-keyed, response-option scored biographical data (biodata) : scale predicted supervisory ratings of air traffic control specialist (ATCS) job performance (Dean & Broach, : 2011). This research f...

  18. Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm.

    Science.gov (United States)

    Bellón, Juan Ángel; de Dios Luna, Juan; King, Michael; Nazareth, Irwin; Motrico, Emma; GildeGómez-Barragán, María Josefa; Torres-González, Francisco; Montón-Franco, Carmen; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Moreno-Peral, Patricia

    2017-04-01

    Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The 'predictAL-10' risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the 'predictAL-9'), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking. © British Journal of General Practice 2017.

  19. Predicting Environmental Suitability for a Rare and Threatened Species (Lao Newt, Laotriton laoensis) Using Validated Species Distribution Models

    Science.gov (United States)

    Chunco, Amanda J.; Phimmachak, Somphouthone; Sivongxay, Niane; Stuart, Bryan L.

    2013-01-01

    The Lao newt (Laotriton laoensis) is a recently described species currently known only from northern Laos. Little is known about the species, but it is threatened as a result of overharvesting. We integrated field survey results with climate and altitude data to predict the geographic distribution of this species using the niche modeling program Maxent, and we validated these predictions by using interviews with local residents to confirm model predictions of presence and absence. The results of the validated Maxent models were then used to characterize the environmental conditions of areas predicted suitable for L. laoensis. Finally, we overlaid the resulting model with a map of current national protected areas in Laos to determine whether or not any land predicted to be suitable for this species is coincident with a national protected area. We found that both area under the curve (AUC) values and interview data provided strong support for the predictive power of these models, and we suggest that interview data could be used more widely in species distribution niche modeling. Our results further indicated that this species is mostly likely geographically restricted to high altitude regions (i.e., over 1,000 m elevation) in northern Laos and that only a minute fraction of suitable habitat is currently protected. This work thus emphasizes that increased protection efforts, including listing this species as endangered and the establishment of protected areas in the region predicted to be suitable for L. laoensis, are urgently needed. PMID:23555808

  20. Tone Noise Predictions for a Spacecraft Cabin Ventilation Fan Ingesting Distorted Inflow and the Challenges of Validation

    Science.gov (United States)

    Koch, L. Danielle; Shook, Tony D.; Astler, Douglas T.; Bittinger, Samantha A.

    2012-01-01

    A fan tone noise prediction code has been developed at NASA Glenn Research Center that is capable of estimating duct mode sound power levels for a fan ingesting distorted inflow. This code was used to predict the circumferential and radial mode sound power levels in the inlet and exhaust duct of an axial spacecraft cabin ventilation fan. Noise predictions at fan design rotational speed were generated. Three fan inflow conditions were studied: an undistorted inflow, a circumferentially symmetric inflow distortion pattern (cylindrical rods inserted radially into the flowpath at 15deg, 135deg, and 255deg), and a circumferentially asymmetric inflow distortion pattern (rods located at 15deg, 52deg and 173deg). Noise predictions indicate that tones are produced for the distorted inflow cases that are not present when the fan operates with an undistorted inflow. Experimental data are needed to validate these acoustic predictions, as well as the aerodynamic performance predictions. Given the aerodynamic design of the spacecraft cabin ventilation fan, a mechanical and electrical conceptual design study was conducted. Design features of a fan suitable for obtaining detailed acoustic and aerodynamic measurements needed to validate predictions are discussed.

  1. New Perspectives on the Validity of the "GRE"® General Test for Predicting Graduate School Grades. ETS GRE® Board Research Report. ETS GRE®-14-03. ETS Research Report. RR-14-26

    Science.gov (United States)

    Klieger, David M.; Cline, Frederick A.; Holtzman, Steven L.; Minsky, Jennifer L.; Lorenz, Florian

    2014-01-01

    Given the serious consequences of making ill-fated admissions and funding decisions for applicants to graduate and professional school, it is important to rely on sound evidence to optimize such judgments. Previous meta-analytic research has demonstrated the generalizable validity of the "GRE"® General Test for predicting academic…

  2. On the incremental validity of irrational beliefs to predict subjective well-being while controlling for personality factors.

    Science.gov (United States)

    Spörrle, Matthias; Strobel, Maria; Tumasjan, Andranik

    2010-11-01

    This research examines the incremental validity of irrational thinking as conceptualized by Albert Ellis to predict diverse aspects of subjective well-being while controlling for the influence of personality factors. Rational-emotive behavior therapy (REBT) argues that irrational beliefs result in maladaptive emotions leading to reduced well-being. Although there is some early scientific evidence for this relation, it has never been investigated whether this connection would still persist when statistically controlling for the Big Five personality factors, which were consistently found to be important determinants of well-being. Regression analyses revealed significant incremental validity of irrationality over personality factors when predicting life satisfaction, but not when predicting subjective happiness. Results are discussed with respect to conceptual differences between these two aspects of subjective well-being.

  3. Predictive validity of endpoints used in electrophysiological modelling of migraine in the trigeminovascular system.

    Science.gov (United States)

    Farkas, Bence; Kardos, Péter; Orosz, Szabolcs; Tarnawa, István; Csekő, Csongor; Lévay, György; Farkas, Sándor; Lendvai, Balázs; Kovács, Péter

    2015-11-02

    The trigeminovascular system has a pivotal role in the pathomechanism of migraine. The aim of the present study was to further develop existing models of migraine making them more suitable for testing the effects of compounds with presumed antimigraine activity in anaesthetised rats. Simultaneous recording of ongoing activity of spontaneously active neurons in the trigeminocervical complex as well as their discharges evoked by electrical stimulation of the dura mater via activation of A- and C-sensory fibres were carried out. Effects of sumatriptan, propranolol and topiramate were evaluated prior to and after application of a mixture containing inflammatory mediators on the dura. Propranolol (10 mg/kg s.c) and topiramate (30 mg/kg s.c.) resulted in a tendency to decrease the level of both spontaneous and evoked activity, while sumatriptan (1 mg/kg s.c.) did not exhibit any effect on recorded parameters. Application of an inflammatory soup to the dura mater boosted up spontaneous activity, which could be significantly attenuated by propranolol and topiramate but not by sumatriptan. In addition, all compounds prevented the delayed increase of spontaneous firing. In contrast to the ongoing activity, evoked responses were not augmented by inflammatory mediators. Nevertheless, inhibitory effect of propranolol and topiramate was evident when considering A- or C-fibre responses. Findings do not support the view that electrically evoked responses are useful for the measurement of trigeminal sensitization. It is proposed however, that inhibition of enhanced firing (immediate and/or delayed) evoked by inflammatory mediators as an endpoint have higher predictive validity regarding the clinical effectiveness of compounds. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. A pediatric FOUR score coma scale: interrater reliability and predictive validity.

    Science.gov (United States)

    Czaikowski, Brianna L; Liang, Hong; Stewart, C Todd

    2014-04-01

    The Full Outline of UnResponsiveness (FOUR) Score is a coma scale that consists of four components (eye and motor response, brainstem reflexes, and respiration). It was originally validated among the adult population and recently in a pediatric population. To enhance clinical assessment of pediatric intensive care unit patients, including those intubated and/or sedated, at our children's hospital, we modified the FOUR Score Scale for this population. This modified scale would provide many of the same advantages as the original, such as interrater reliability, simplicity, and elimination of the verbal component that is not compatible with the Glasgow Coma Scale (GCS), creating a more valuable neurological assessment tool for the nursing community. Our goal was to potentially provide greater information than the formally used GCS when assessing critically ill, neurologically impaired patients, including those sedated and/or intubated. Experienced pediatric intensive care unit nurses were trained as "expert raters." Two different nurses assessed each subject using the Pediatric FOUR Score Scale (PFSS), GCS, and Richmond Agitation Sedation Scale at three different time points. Data were compared with the Pediatric Cerebral Performance Category (PCPC) assessed by another nurse. Our hypothesis was that the PFSS and PCPC should highly correlate and the GCS and PCPC should correlate lower. Study results show that the PFSS is excellent for interrater reliability for trained nurse-rater pairs and prediction of poor outcome and in-hospital mortality, under various situations, but there were no statistically significant differences between the PFSS and the GCS. However, the PFSS does have the potential to provide greater neurological assessment in the intubated and/or sedated patient based on the outcomes of our study.

  5. Prediction of proton chemical shifts in RNA - Their use in structure refinement and validation

    International Nuclear Information System (INIS)

    Cromsigt, Jenny A.M.T.C.; Hilbers, Cees W.; Wijmenga, Sybren S.

    2001-01-01

    An analysis is presented of experimental versus calculated chemical shifts of the non-exchangeable protons for 28 RNA structures deposited in the Protein Data Bank, covering a wide range of structural building blocks. We have used existing models for ring-current and magnetic-anisotropy contributions to calculate the proton chemical shifts from the structures. Two different parameter sets were tried: (i) parameters derived by Ribas-Prado and Giessner-Prettre (GP set) [(1981) J. Mol. Struct.,76, 81-92.]; (ii) parameters derived by Case [(1995) J. Biomol. NMR, 6, 341-346]. Both sets lead to similar results. The detailed analysis was carried using the GP set. The root-mean-square-deviation between the predicted and observed chemical shifts of the complete database is 0.16 ppm with a Pearson correlation coefficient of 0.79. For protons in the usually well-defined A-helix environment these numbers are, 0.08 ppm and 0.96, respectively. As a result of this good correspondence, a reliable analysis could be made of the structural dependencies of the 1 H chemical shifts revealing their physical origin. For example, a down-field shift of either H2' or H3' or both indicates a high-syn/syn χ-angle. In an A-helix it is essentially the 5'-neighbor that affects the chemical shifts of H5, H6 and H8 protons. The H5, H6 and H8 resonances can therefore be assigned in an A-helix on the basis of their observed chemical shifts. In general, the chemical shifts were found to be quite sensitive to structural changes. We therefore propose that a comparison between calculated and observed 1 H chemical shifts is a good tool for validation and refinement of structures derived from NOEs and J-couplings

  6. Clinical and angiographic predictors of haemodynamically significant angiographic lesions: development and validation of a risk score to predict positive fractional flow reserve.

    Science.gov (United States)

    Sareen, Nishtha; Baber, Usman; Kezbor, Safwan; Sayseng, Sonny; Aquino, Melissa; Mehran, Roxana; Sweeny, Joseph; Barman, Nitin; Kini, Annapoorna; Sharma, Samin K

    2017-04-07

    Coronary revascularisation based upon physiological evaluation of lesions improves clinical outcomes. Angiographic or visual stenosis assessment alone is insufficient in predicting haemodynamic stenosis severity by fractional flow reserve (FFR) and therefore cannot be used to guide revascularisation, particularly in the lesion subset system formulated. Of 1,023 consecutive lesions (883 patients), 314 (31%) were haemodynamically significant. Characteristics associated with FFR ≤0.8 include male gender, higher SYNTAX score, lesions ≥20 mm, stenosis >50%, bifurcation, calcification, absence of tortuosity and smaller reference diameter. A user-friendly integer score was developed with the five variables demonstrating the strongest association. On prospective validation (in 279 distinct lesions), the increasing value of the score correlated well with increasing haemodynamic significance (C-statistic 0.85). We identified several clinical and angiographic characteristics and formulated a scoring system to guide the approach to intermediate lesions. This may translate into cost savings. Larger studies with prospective validation are required to confirm our results.

  7. The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model.

    Science.gov (United States)

    Klemans, Rob J B; Otte, Dianne; Knol, Mirjam; Knol, Edward F; Meijer, Yolanda; Gmelig-Meyling, Frits H J; Bruijnzeel-Koomen, Carla A F M; Knulst, André C; Pasmans, Suzanne G M A

    2013-01-01

    A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values with 100% positive and negative predictive values could be calculated for both the updated model and sIgE to Ara h 2. In this way, the outcome of the food challenge could be predicted with 100% accuracy in 59% (updated model) and 50% (Ara h 2) of the patients. Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

  8. Predicting umbilical artery pH during labour: Development and validation of a nomogram using fetal heart rate patterns.

    Science.gov (United States)

    Ramanah, Rajeev; Omar, Sikiyah; Guillien, Alicia; Pugin, Aurore; Martin, Alain; Riethmuller, Didier; Mottet, Nicolas

    2018-06-01

    Nomograms are statistical models that combine variables to obtain the most accurate and reliable prediction for a particular risk. Fetal heart rate (FHR) interpretation alone has been found to be poorly predictive for fetal acidosis while other clinical risk factors exist. The aim of this study was to create and validate a nomogram based on FHR patterns and relevant clinical parameters to provide a non-invasive individualized prediction of umbilical artery pH during labour. A retrospective observational study was conducted on 4071 patients in labour presenting singleton pregnancies at >34 gestational weeks and delivering vaginally. Clinical characteristics, FHR patterns and umbilical cord gas of 1913 patients were used to construct a nomogram predicting an umbilical artery (Ua) pH <7.18 (10th centile of the study population) after an univariate and multivariate stepwise logistic regression analysis. External validation was obtained from an independent cohort of 2158 patients. Area under the receiver operating characteristics (ROC) curve, sensitivity, specificity, positive and negative predictive values of the nomogram were determined. Upon multivariate analysis, parity (p < 0.01), induction of labour (p = 0.01), a prior uterine scar (p = 0.02), maternal fever (p = 0.02) and the type of FHR (p < 0.01) were significantly associated with an Ua pH <7.18 (p < 0.05). Apgar score at 1, 5 and 10 min were significantly lower in the group with an Ua pH <7.18 (p < 0.01). The nomogram constructed had a Concordance Index of 0.75 (area under the curve) with a sensitivity of 57%, a specificity of 91%, a negative predictive value of 5% and a positive predictive value of 99%. Calibration found no difference between the predicted probabilities and the observed rate of Ua pH <7.18 (p = 0.63). The validation set had a Concordance Index of 0.72 and calibration with a p < 0.77. We successfully developed and validated a nomogram to predict Ua pH by

  9. Validation of the assert subchannel code: Prediction of CHF in standard and non-standard Candu bundle geometries

    International Nuclear Information System (INIS)

    Carver, M.B.; Kiteley, J.C.; Zhou, R.Q.N.; Junop, S.V.; Rowe, D.S.

    1993-01-01

    The ASSERT code has been developed to address the three-dimensional computation of flow and phase distribution and fuel element surface temperatures within the horizontal subchannels of CANDU PHWR fuel channels, and to provide a detailed prediction of critical heat flux (CHF) distribution throughout the bundle. The ASSERT subchannel code has been validated extensively against a wide repertoire of experiments; its combination of three-dimensional prediction of local flow conditions with a comprehensive method of prediting CHF at these local conditions, makes it a unique tool for predicting CHF for situations outside the existing experimental data base. In particular, ASSERT is an appropriate tool to systematically investigate CHF under conditions of local geometric variations, such as pressure tube creep and fuel element strain. This paper discusses the numerical methodology used in ASSERT, the constitutive relationships incorporated, and the CHF assessment methodology. The evolutionary validation plan is discussed, and early validation exercises are summarized. The paper concentrates, however, on more recent validation exercises in standard and non-standard geometries

  10. Post-bronchoscopy pneumonia in patients suffering from lung cancer: Development and validation of a risk prediction score.

    Science.gov (United States)

    Takiguchi, Hiroto; Hayama, Naoki; Oguma, Tsuyoshi; Harada, Kazuki; Sato, Masako; Horio, Yukihiro; Tanaka, Jun; Tomomatsu, Hiromi; Tomomatsu, Katsuyoshi; Takihara, Takahisa; Niimi, Kyoko; Nakagawa, Tomoki; Masuda, Ryota; Aoki, Takuya; Urano, Tetsuya; Iwazaki, Masayuki; Asano, Koichiro

    2017-05-01

    The incidence, risk factors, and consequences of pneumonia after flexible bronchoscopy in patients with lung cancer have not been studied in detail. We retrospectively analyzed the data from 237 patients with lung cancer who underwent diagnostic bronchoscopy between April 2012 and July 2013 (derivation sample) and 241 patients diagnosed between August 2013 and July 2014 (validation sample) in a tertiary referral hospital in Japan. A score predictive of post-bronchoscopy pneumonia was developed in the derivation sample and tested in the validation sample. Pneumonia developed after bronchoscopy in 6.3% and 4.1% of patients in the derivation and validation samples, respectively. Patients who developed post-bronchoscopy pneumonia needed to change or cancel their planned cancer therapy more frequently than those without pneumonia (56% vs. 6%, ppneumonia, which we added to develop our predictive score. The incidence of pneumonia associated with scores=0, 1, and ≥2 was 0, 3.7, and 13.4% respectively in the derivation sample (p=0.003), and 0, 2.9, and 9.7% respectively in the validation sample (p=0.016). The incidence of post-bronchoscopy pneumonia in patients with lung cancer was not rare and associated with adverse effects on the clinical course. A simple 3-point predictive score identified patients with lung cancer at high risk of post-bronchoscopy pneumonia prior to the procedure. Copyright © 2017 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

  11. Demonstration of a multiscale modeling technique: prediction of the stress–strain response of light activated shape memory polymers

    International Nuclear Information System (INIS)

    Beblo, Richard V; Weiland, Lisa Mauck

    2010-01-01

    Presented is a multiscale modeling method applied to light activated shape memory polymers (LASMPs). LASMPs are a new class of shape memory polymer (SMPs) being developed for adaptive structures applications where a thermal stimulus is undesirable. LASMP developmental emphasis is placed on optical manipulation of Young's modulus. A multiscale modeling approach is employed to anticipate the soft and hard state moduli solely on the basis of a proposed molecular formulation. Employing such a model shows promise for expediting down-selection of favorable formulations for synthesis and testing, and subsequently accelerating LASMP development. An empirical adaptation of the model is also presented which has applications in system design once a formulation has been identified. The approach employs rotational isomeric state theory to build a molecular scale model of the polymer chain yielding a list of distances between the predicted crosslink locations, or r-values. The r-values are then fitted with Johnson probability density functions and used with Boltzmann statistical mechanics to predict stress as a function of the strain of the phantom polymer network. Empirical adaptation for design adds junction constraint theory to the modeling process. Junction constraint theory includes the effects of neighboring chain interactions. Empirical fitting results in numerically accurate Young's modulus predictions. The system is modular in nature and thus lends itself well to being adapted to other polymer systems and development applications

  12. Long-Term Survival Prediction for Coronary Artery Bypass Grafting: Validation of the ASCERT Model Compared With The Society of Thoracic Surgeons Predicted Risk of Mortality.

    Science.gov (United States)

    Lancaster, Timothy S; Schill, Matthew R; Greenberg, Jason W; Ruaengsri, Chawannuch; Schuessler, Richard B; Lawton, Jennifer S; Maniar, Hersh S; Pasque, Michael K; Moon, Marc R; Damiano, Ralph J; Melby, Spencer J

    2018-05-01

    The recently developed American College of Cardiology Foundation-Society of Thoracic Surgeons (STS) Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) Long-Term Survival Probability Calculator is a valuable addition to existing short-term risk-prediction tools for cardiac surgical procedures but has yet to be externally validated. Institutional data of 654 patients aged 65 years or older undergoing isolated coronary artery bypass grafting between 2005 and 2010 were reviewed. Predicted survival probabilities were calculated using the ASCERT model. Survival data were collected using the Social Security Death Index and institutional medical records. Model calibration and discrimination were assessed for the overall sample and for risk-stratified subgroups based on (1) ASCERT 7-year survival probability and (2) the predicted risk of mortality (PROM) from the STS Short-Term Risk Calculator. Logistic regression analysis was performed to evaluate additional perioperative variables contributing to death. Overall survival was 92.1% (569 of 597) at 1 year and 50.5% (164 of 325) at 7 years. Calibration assessment found no significant differences between predicted and actual survival curves for the overall sample or for the risk-stratified subgroups, whether stratified by predicted 7-year survival or by PROM. Discriminative performance was comparable between the ASCERT and PROM models for 7-year survival prediction (p validated for prediction of long-term survival after coronary artery bypass grafting in all risk groups. The widely used STS PROM performed comparably as a predictor of long-term survival. Both tools provide important information for preoperative decision making and patient counseling about potential outcomes after coronary artery bypass grafting. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  13. Validation and Refinement of Prediction Models to Estimate Exercise Capacity in Cancer Survivors Using the Steep Ramp Test.

    Science.gov (United States)

    Stuiver, Martijn M; Kampshoff, Caroline S; Persoon, Saskia; Groen, Wim; van Mechelen, Willem; Chinapaw, Mai J M; Brug, Johannes; Nollet, Frans; Kersten, Marie-José; Schep, Goof; Buffart, Laurien M

    2017-11-01

    To further test the validity and clinical usefulness of the steep ramp test (SRT) in estimating exercise tolerance in cancer survivors by external validation and extension of previously published prediction models for peak oxygen consumption (Vo 2peak ) and peak power output (W peak ). Cross-sectional study. Multicenter. Cancer survivors (N=283) in 2 randomized controlled exercise trials. Not applicable. Prediction model accuracy was assessed by intraclass correlation coefficients (ICCs) and limits of agreement (LOA). Multiple linear regression was used for model extension. Clinical performance was judged by the percentage of accurate endurance exercise prescriptions. ICCs of SRT-predicted Vo 2peak and W peak with these values as obtained by the cardiopulmonary exercise test were .61 and .73, respectively, using the previously published prediction models. 95% LOA were ±705mL/min with a bias of 190mL/min for Vo 2peak and ±59W with a bias of 5W for W peak . Modest improvements were obtained by adding body weight and sex to the regression equation for the prediction of Vo 2peak (ICC, .73; 95% LOA, ±608mL/min) and by adding age, height, and sex for the prediction of W peak (ICC, .81; 95% LOA, ±48W). Accuracy of endurance exercise prescription improved from 57% accurate prescriptions to 68% accurate prescriptions with the new prediction model for W peak . Predictions of Vo 2peak and W peak based on the SRT are adequate at the group level, but insufficiently accurate in individual patients. The multivariable prediction model for W peak can be used cautiously (eg, supplemented with a Borg score) to aid endurance exercise prescription. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  14. The Smoking Consequences Questionnaire: Factor structure and predictive validity among Spanish-speaking Latino smokers in the United States.

    Science.gov (United States)

    Vidrine, Jennifer Irvin; Vidrine, Damon J; Costello, Tracy J; Mazas, Carlos; Cofta-Woerpel, Ludmila; Mejia, Luz Maria; Wetter, David W

    2009-11-01

    Much of the existing research on smoking outcome expectancies has been guided by the Smoking Consequences Questionnaire (SCQ ). Although the original version of the SCQ has been modified over time for use in different populations, none of the existing versions have been evaluated for use among Spanish-speaking Latino smokers in the United States. The present study evaluated the factor structure and predictive validity of the 3 previously validated versions of the SCQ--the original, the SCQ-Adult, and the SCQ-Spanish, which was developed with Spanish-speaking smokers in Spain--among Spanish-speaking Latino smokers in Texas. The SCQ-Spanish represented the least complex solution. Each of the SCQ-Spanish scales had good internal consistency, and the predictive validity of the SCQ-Spanish was partially supported. Nearly all the SCQ-Spanish scales predicted withdrawal severity even after controlling for demographics and dependence. Boredom Reduction predicted smoking relapse across the 5- and 12-week follow-up assessments in a multivariate model that also controlled for demographics and dependence. Our results support use of the SCQ-Spanish with Spanish-speaking Latino smokers in the United States.

  15. Bayesian maximum entropy integration of ozone observations and model predictions: an application for attainment demonstration in North Carolina.

    Science.gov (United States)

    de Nazelle, Audrey; Arunachalam, Saravanan; Serre, Marc L

    2010-08-01

    States in the USA are required to demonstrate future compliance of criteria air pollutant standards by using both air quality monitors and model outputs. In the case of ozone, the demonstration tests aim at relying heavily on measured values, due to their perceived objectivity and enforceable quality. Weight given to numerical models is diminished by integrating them in the calculations only in a relative sense. For unmonitored locations, the EPA has suggested the use of a spatial interpolation technique to assign current values. We demonstrate that this approach may lead to erroneous assignments of nonattainment and may make it difficult for States to establish future compliance. We propose a method that combines different sources of information to map air pollution, using the Bayesian Maximum Entropy (BME) Framework. The approach gives precedence to measured values and integrates modeled data as a function of model performance. We demonstrate this approach in North Carolina, using the State's ozone monitoring network in combination with outputs from the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. We show that the BME data integration approach, compared to a spatial interpolation of measured data, improves the accuracy and the precision of ozone estimations across the state.

  16. Acute Kidney Injury in Trauma Patients Admitted to Critical Care: Development and Validation of a Diagnostic Prediction Model.

    Science.gov (United States)

    Haines, Ryan W; Lin, Shih-Pin; Hewson, Russell; Kirwan, Christopher J; Torrance, Hew D; O'Dwyer, Michael J; West, Anita; Brohi, Karim; Pearse, Rupert M; Zolfaghari, Parjam; Prowle, John R

    2018-02-26

    Acute Kidney Injury (AKI) complicating major trauma is associated with increased mortality and morbidity. Traumatic AKI has specific risk factors and predictable time-course facilitating diagnostic modelling. In a single centre, retrospective observational study we developed risk prediction models for AKI after trauma based on data around intensive care admission. Models predicting AKI were developed using data from 830 patients, using data reduction followed by logistic regression, and were independently validated in a further 564 patients. AKI occurred in 163/830 (19.6%) with 42 (5.1%) receiving renal replacement therapy (RRT). First serum creatinine and phosphate, units of blood transfused in first 24 h, age and Charlson score discriminated need for RRT and AKI early after trauma. For RRT c-statistics were good to excellent: development: 0.92 (0.88-0.96), validation: 0.91 (0.86-0.97). Modelling AKI stage 2-3, c-statistics were also good, development: 0.81 (0.75-0.88) and validation: 0.83 (0.74-0.92). The model predicting AKI stage 1-3 performed moderately, development: c-statistic 0.77 (0.72-0.81), validation: 0.70 (0.64-0.77). Despite good discrimination of need for RRT, positive predictive values (PPV) at the optimal cut-off were only 23.0% (13.7-42.7) in development. However, PPV for the alternative endpoint of RRT and/or death improved to 41.2% (34.8-48.1) highlighting death as a clinically relevant endpoint to RRT.

  17. A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation

    Directory of Open Access Journals (Sweden)

    Luis Cláudio Lemos Correia

    Full Text Available Abstract Background: Currently, there is no validated multivariate model to predict probability of obstructive coronary disease in patients with acute chest pain. Objective: To develop and validate a multivariate model to predict coronary artery disease (CAD based on variables assessed at admission to the coronary care unit (CCU due to acute chest pain. Methods: A total of 470 patients were studied, 370 utilized as the derivation sample and the subsequent 100 patients as the validation sample. As the reference standard, angiography was required to rule in CAD (stenosis ≥ 70%, while either angiography or a negative noninvasive test could be used to rule it out. As predictors, 13 baseline variables related to medical history, 14 characteristics of chest discomfort, and eight variables from physical examination or laboratory tests were tested. Results: The prevalence of CAD was 48%. By logistic regression, six variables remained independent predictors of CAD: age, male gender, relief with nitrate, signs of heart failure, positive electrocardiogram, and troponin. The area under the curve (AUC of this final model was 0.80 (95% confidence interval [95%CI] = 0.75 - 0.84 in the derivation sample and 0.86 (95%CI = 0.79 - 0.93 in the validation sample. Hosmer-Lemeshow's test indicated good calibration in both samples (p = 0.98 and p = 0.23, respectively. Compared with a basic model containing electrocardiogram and troponin, the full model provided an AUC increment of 0.07 in both derivation (p = 0.0002 and validation (p = 0.039 samples. Integrated discrimination improvement was 0.09 in both derivation (p < 0.001 and validation (p < 0.0015 samples. Conclusion: A multivariate model was derived and validated as an accurate tool for estimating the pretest probability of CAD in patients with acute chest pain.

  18. External Validation Study of First Trimester Obstetric Prediction Models (Expect Study I): Research Protocol and Population Characteristics.

    Science.gov (United States)

    Meertens, Linda Jacqueline Elisabeth; Scheepers, Hubertina Cj; De Vries, Raymond G; Dirksen, Carmen D; Korstjens, Irene; Mulder, Antonius Lm; Nieuwenhuijze, Marianne J; Nijhuis, Jan G; Spaanderman, Marc Ea; Smits, Luc Jm

    2017-10-26

    A number of first-trimester prediction models addressing important obstetric outcomes have been published. However, most models have not been externally validated. External validation is essential before implementing a prediction model in clinical practice. The objective of this paper is to describe the design of a study to externally validate existing first trimester obstetric prediction models, based upon maternal characteristics and standard measurements (eg, blood pressure), for the risk of pre-eclampsia (PE), gestational diabetes mellitus (GDM), spontaneous preterm birth (PTB), small-for-gestational-age (SGA) infants, and large-for-gestational-age (LGA) infants among Dutch pregnant women (Expect Study I). The results of a pilot study on the feasibility and acceptability of the recruitment process and the comprehensibility of the Pregnancy Questionnaire 1 are also reported. A multicenter prospective cohort study was performed in The Netherlands between July 1, 2013 and December 31, 2015. First trimester obstetric prediction models were systematically selected from the literature. Predictor variables were measured by the Web-based Pregnancy Questionnaire 1 and pregnancy outcomes were established using the Postpartum Questionnaire 1 and medical records. Information about maternal health-related quality of life, costs, and satisfaction with Dutch obstetric care was collected from a subsample of women. A pilot study was carried out before the official start of inclusion. External validity of the models will be evaluated by assessing discrimination and calibration. Based on the pilot study, minor improvements were made to the recruitment process and online Pregnancy Questionnaire 1. The validation cohort consists of 2614 women. Data analysis of the external validation study is in progress. This study will offer insight into the generalizability of existing, non-invasive first trimester prediction models for various obstetric outcomes in a Dutch obstetric population

  19. A Demonstration using Low-kt Fatigue Specimens of a Method for Predicting the Fatigue Behaviour of Corroded Aircraft Components

    Science.gov (United States)

    2013-03-01

    predictions of infinite life, i.e. runouts . For this reason the NASGRO dataset was not used in the Criticality Model. UNCLASSIFIED DSTO-RR-0390...JSM-6490 SEM at DSTO. The fracture surfaces of the specimens were removed using an abrasive cut-off wheel , cleaned using water and analytical grade...Pitting Bolthole in NASA Space Shuttle wheels 7075-T6 EDM EDM Low-kt fatigue specimen Wei [133] 2024-T3/Thickness not stated 500 h in 0.5M

  20. Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models

    Directory of Open Access Journals (Sweden)

    Testa Antonia C

    2010-10-01

    Full Text Available Abstract Background Hitherto, risk prediction models for preoperative ultrasound-based diagnosis of ovarian tumors were dichotomous (benign versus malignant. We develop and validate polytomous models (models that predict more than two events to diagnose ovarian tumors as benign, borderline, primary invasive or metastatic invasive. The main focus is on how different types of models perform and compare. Methods A multi-center dataset containing 1066 women was used for model development and internal validation, whilst another multi-center dataset of 1938 women was used for temporal and external validation. Models were based on standard logistic regression and on penalized kernel-based algorithms (least squares support vector machines and kernel logistic regression. We used true polytomous models as well as combinations of dichotomous models based on the 'pairwise coupling' technique to produce polytomous risk estimates. Careful variable selection was performed, based largely on cross-validated c-index estimates. Model performance was assessed with the dichotomous c-index (i.e. the area under the ROC curve and a polytomous extension, and with calibration graphs. Results For all models, between 9 and 11 predictors were selected. Internal validation was successful with polytomous c-indexes between 0.64 and 0.69. For the best model dichotomous c-indexes were between 0.73 (primary invasive vs metastatic and 0.96 (borderline vs metastatic. On temporal and external validation, overall discrimination performance was good with polytomous c-indexes between 0.57 and 0.64. However, discrimination between primary and metastatic invasive tumors decreased to near random levels. Standard logistic regression performed well in comparison with advanced algorithms, and combining dichotomous models performed well in comparison with true polytomous models. The best model was a combination of dichotomous logistic regression models. This model is available online

  1. Validation of a predictive model for smart control of electrical energy storage

    NARCIS (Netherlands)

    Homan, Bart; van Leeuwen, Richard Pieter; Smit, Gerardus Johannes Maria; Zhu, Lei; de Wit, Jan B.

    2016-01-01

    The purpose of this paper is to investigate the applicability of a relatively simple model which is based on energy conservation for model predictions as part of smart control of thermal and electric storage. The paper reviews commonly used predictive models. Model predictions of charging and

  2. Predicting Rehabilitation Success Rate Trends among Ethnic Minorities Served by State Vocational Rehabilitation Agencies: A National Time Series Forecast Model Demonstration Study

    Science.gov (United States)

    Moore, Corey L.; Wang, Ningning; Washington, Janique Tynez

    2017-01-01

    Purpose: This study assessed and demonstrated the efficacy of two select empirical forecast models (i.e., autoregressive integrated moving average [ARIMA] model vs. grey model [GM]) in accurately predicting state vocational rehabilitation agency (SVRA) rehabilitation success rate trends across six different racial and ethnic population cohorts…

  3. The reliability, validity, sensitivity, specificity and predictive values of the Chinese version of the Rowland Universal Dementia Assessment Scale.

    Science.gov (United States)

    Chen, Chia-Wei; Chu, Hsin; Tsai, Chia-Fen; Yang, Hui-Ling; Tsai, Jui-Chen; Chung, Min-Huey; Liao, Yuan-Mei; Chi, Mei-Ju; Chou, Kuei-Ru

    2015-11-01

    The purpose of this study was to translate the Rowland Universal Dementia Assessment Scale into Chinese and to evaluate the psychometric properties (reliability and validity) and the diagnostic properties (sensitivity, specificity and predictive values) of the Chinese version of the Rowland Universal Dementia Assessment Scale. The accurate detection of early dementia requires screening tools with favourable cross-cultural linguistic and appropriate sensitivity, specificity, and predictive values, particularly for Chinese-speaking populations. This was a cross-sectional, descriptive study. Overall, 130 participants suspected to have cognitive impairment were enrolled in the study. A test-retest for determining reliability was scheduled four weeks after the initial test. Content validity was determined by five experts, whereas construct validity was established by using contrasted group technique. The participants' clinical diagnoses were used as the standard in calculating the sensitivity, specificity, positive predictive value and negative predictive value. The study revealed that the Chinese version of the Rowland Universal Dementia Assessment Scale exhibited a test-retest reliability of 0.90, an internal consistency reliability of 0.71, an inter-rater reliability (kappa value) of 0.88 and a content validity index of 0.97. Both the patients and healthy contrast group exhibited significant differences in their cognitive ability. The optimal cut-off points for the Chinese version of the Rowland Universal Dementia Assessment Scale in the test for mild cognitive impairment and dementia were 24 and 22, respectively; moreover, for these two conditions, the sensitivities of the scale were 0.79 and 0.76, the specificities were 0.91 and 0.81, the areas under the curve were 0.85 and 0.78, the positive predictive values were 0.99 and 0.83 and the negative predictive values were 0.96 and 0.91 respectively. The Chinese version of the Rowland Universal Dementia Assessment Scale

  4. Demonstration and validation of automated agricultural field extraction from multi-temporal Landsat data for the majority of United States harvested cropland

    Science.gov (United States)

    Yan, L.; Roy, D. P.

    2014-12-01

    The spatial distribution of agricultural fields is a fundamental description of rural landscapes and the location and extent of fields is important to establish the area of land utilized for agricultural yield prediction, resource allocation, and for economic planning, and may be indicative of the degree of agricultural capital investment, mechanization, and labor intensity. To date, field objects have not been extracted from satellite data over large areas because of computational constraints, the complexity of the extraction task, and because consistently processed appropriate resolution data have not been available or affordable. A recently published automated methodology to extract agricultural crop fields from weekly 30 m Web Enabled Landsat data (WELD) time series was refined and applied to 14 states that cover 70% of harvested U.S. cropland (USDA 2012 Census). The methodology was applied to 2010 combined weekly Landsat 5 and 7 WELD data. The field extraction and quantitative validation results are presented for the following 14 states: Iowa, North Dakota, Illinois, Kansas, Minnesota, Nebraska, Texas, South Dakota, Missouri, Indiana, Ohio, Wisconsin, Oklahoma and Michigan (sorted by area of harvested cropland). These states include the top 11 U.S states by harvested cropland area. Implications and recommendations for systematic application to global coverage Landsat data are discussed.

  5. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields.

    Science.gov (United States)

    Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin; Strawn, Laura K

    2016-02-01

    Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  6. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

    Science.gov (United States)

    Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin

    2015-01-01

    Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

  7. Validation of adult height prediction based on automated bone age determination in the Paris Longitudinal Study of healthy children

    Energy Technology Data Exchange (ETDEWEB)

    Martin, David D. [Tuebingen University Children' s Hospital, Tuebingen (Germany); Filderklinik, Filderstadt (Germany); Schittenhelm, Jan [Tuebingen University Children' s Hospital, Tuebingen (Germany); Thodberg, Hans Henrik [Visiana, Holte (Denmark)

    2016-02-15

    An adult height prediction model based on automated determination of bone age was developed and validated in two studies from Zurich, Switzerland. Varied living conditions and genetic backgrounds might make the model less accurate. To validate the adult height prediction model on children from another geographical location. We included 51 boys and 58 girls from the Paris Longitudinal Study of children born 1953 to 1958. Radiographs were obtained once or twice a year in these children from birth to age 18. Bone age was determined using the BoneXpert method. Radiographs in children with bone age greater than 6 years were considered, in total 1,124 images. The root mean square deviation between the predicted and the observed adult height was 2.8 cm for boys in the bone age range 6-15 years and 3.1 cm for girls in the bone age range 6-13 years. The bias (the average signed difference) was zero, except for girls below bone age 12, where the predictions were 0.8 cm too low. The accuracy of the BoneXpert method in terms of root mean square error was as predicted by the model, i.e. in line with what was observed in the Zurich studies. (orig.)

  8. Validation of adult height prediction based on automated bone age determination in the Paris Longitudinal Study of healthy children

    International Nuclear Information System (INIS)

    Martin, David D.; Schittenhelm, Jan; Thodberg, Hans Henrik

    2016-01-01

    An adult height prediction model based on automated determination of bone age was developed and validated in two studies from Zurich, Switzerland. Varied living conditions and genetic backgrounds might make the model less accurate. To validate the adult height prediction model on children from another geographical location. We included 51 boys and 58 girls from the Paris Longitudinal Study of children born 1953 to 1958. Radiographs were obtained once or twice a year in these children from birth to age 18. Bone age was determined using the BoneXpert method. Radiographs in children with bone age greater than 6 years were considered, in total 1,124 images. The root mean square deviation between the predicted and the observed adult height was 2.8 cm for boys in the bone age range 6-15 years and 3.1 cm for girls in the bone age range 6-13 years. The bias (the average signed difference) was zero, except for girls below bone age 12, where the predictions were 0.8 cm too low. The accuracy of the BoneXpert method in terms of root mean square error was as predicted by the model, i.e. in line with what was observed in the Zurich studies. (orig.)

  9. 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.

  10. Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry.

    Science.gov (United States)

    Wang, Shengfeng; Qian, Frank; Zheng, Yonglan; Ogundiran, Temidayo; Ojengbede, Oladosu; Zheng, Wei; Blot, William; Nathanson, Katherine L; Hennis, Anselm; Nemesure, Barbara; Ambs, Stefan; Olopade, Olufunmilayo I; Huo, Dezheng

    2018-04-01

    Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models. We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC). Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512-0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506-0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532-0.640). We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.

  11. Predicting DMS-IV cluster B personality disorder criteria from MMPI-2 and Rorschach data: a test of incremental validity.

    Science.gov (United States)

    Blais, M A; Hilsenroth, M J; Castlebury, F; Fowler, J C; Baity, M R

    2001-02-01

    Despite their frequent conjoint clinical use, the incremental validity of Rorschach (Rorschach, 1921/1942) and MMPI (Hathaway & McKinley, 1943) data has not been adequately established, nor has any study to date explored the incremental validity of these tests for predicting Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) personality disorders (PDs). In a reanalysis of existing data, we used select Rorschach variables and the MMPI PD scales to predict DSM-IV antisocial, borderline, histrionic, and narcissistic PD criteria in a sample of treatment-seeking outpatients. The correlational findings revealed alimited relation between Rorschach and MMPI-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) variables, with only 5 of 30 correlations reaching significance (p psychological characteristics of the DSM-IV Cluster B PDs.

  12. Construction, internal validation and implementation in a mobile application of a scoring system to predict nonadherence to proton pump inhibitors

    Directory of Open Access Journals (Sweden)

    Emma Mares-García

    2017-06-01

    Full Text Available Background Other studies have assessed nonadherence to proton pump inhibitors (PPIs, but none has developed a screening test for its detection. Objectives To construct and internally validate a predictive model for nonadherence to PPIs. Methods This prospective observational study with a one-month follow-up was carried out in 2013 in Spain, and included 302 patients with a prescription for PPIs. The primary variable was nonadherence to PPIs (pill count. Secondary variables were gender, age, antidepressants, type of PPI, non-guideline-recommended prescription (NGRP of PPIs, and total number of drugs. With the secondary variables, a binary logistic regression model to predict nonadherence was constructed and adapted to a points system. The ROC curve, with its area (AUC, was calculated and the optimal cut-off point was established. The points system was internally validated through 1,000 bootstrap samples and implemented in a mobile application (Android. Results The points system had three prognostic variables: total number of drugs, NGRP of PPIs, and antidepressants. The AUC was 0.87 (95% CI [0.83–0.91], p < 0.001. The test yielded a sensitivity of 0.80 (95% CI [0.70–0.87] and a specificity of 0.82 (95% CI [0.76–0.87]. The three parameters were very similar in the bootstrap validation. Conclusions A points system to predict nonadherence to PPIs has been constructed, internally validated and implemented in a mobile application. Provided similar results are obtained in external validation studies, we will have a screening tool to detect nonadherence to PPIs.

  13. Reading the Road Signs: The Utility of the MMPI-2 Restructured Form Validity Scales in Prediction of Premature Termination.

    Science.gov (United States)

    Anestis, Joye C; Finn, Jacob A; Gottfried, Emily; Arbisi, Paul A; Joiner, Thomas E

    2015-06-01

    This study examined the utility of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) Validity Scales in prediction of premature termination in a sample of 511 individuals seeking services from a university-based psychology clinic. Higher scores on True Response Inconsistency-Revised and Infrequent Psychopathology Responses increased the risk of premature termination, whereas higher scores on Adjustment Validity lowered the risk of premature termination. Additionally, when compared with individuals who did not prematurely terminate, individuals who prematurely terminated treatment had lower Global Assessment of Functioning scores at both intake and termination and made fewer improvements. Implications of these findings for the use of the MMPI-2-RF Validity Scales in promoting treatment compliance are discussed. © The Author(s) 2014.

  14. Validation of a Dutch risk score predicting poor outcome in adults with bacterial meningitis in Vietnam and Malawi.

    Directory of Open Access Journals (Sweden)

    Ewout S Schut

    Full Text Available We have previously developed and validated a prognostic model to predict the risk for unfavorable outcome in Dutch adults with bacterial meningitis. The aim of the current study was to validate this model in adults with bacterial meningitis from two developing countries, Vietnam and Malawi. Demographic and clinical characteristics of Vietnamese (n = 426, Malawian patients (n = 465 differed substantially from those of Dutch patients (n = 696. The Dutch model underestimated the risk of poor outcome in both Malawi and Vietnam. The discrimination of the original model (c-statistic [c] 0.84; 95% confidence interval 0.81 to 0.86 fell considerably when re-estimated in the Vietnam cohort (c = 0.70 or in the Malawian cohort (c = 0.68. Our validation study shows that new prognostic models have to be developed for these countries in a sufficiently large series of unselected patients.

  15. The fairness, predictive validity and acceptability of multiple mini interview in an internationally diverse student population- a mixed methods study

    OpenAIRE

    Kelly, Maureen E.; Dowell, Jon; Husbands, Adrian; Newell, John; O'Flynn, Siun; Kropmans, Thomas; Dunne, Fidelma P.; Murphy, Andrew W.

    2014-01-01

    Background International medical students, those attending medical school outside of their country of citizenship, account for a growing proportion of medical undergraduates worldwide. This study aimed to establish the fairness, predictive validity and acceptability of Multiple Mini Interview (MMI) in an internationally diverse student population. Methods This was an explanatory sequential, mixed methods study. All students in First Year Medicine, National University of Ireland Galway 2012 we...

  16. Development and validation of a multivariate prediction model for patients with acute pancreatitis in Intensive Care Medicine.

    Science.gov (United States)

    Zubia-Olaskoaga, Felix; Maraví-Poma, Enrique; Urreta-Barallobre, Iratxe; Ramírez-Puerta, María-Rosario; Mourelo-Fariña, Mónica; Marcos-Neira, María-Pilar; García-García, Miguel Ángel

    2018-03-01

    Development and validation of a multivariate prediction model for patients with acute pancreatitis (AP) admitted in Intensive Care Units (ICU). A prospective multicenter observational study, in 1 year period, in 46 international ICUs (EPAMI study). adults admitted to an ICU with AP and at least one organ failure. Development of a multivariate prediction model, using the worst data of the stay in ICU, based in multivariate analysis, simple imputation in a development cohort. The model was validated in another cohort. 374 patients were included (mortality of 28.9%). Variables with statistical significance in multivariate analysis were age, no alcoholic and no biliary etiology, development of shock, development of respiratory failure, need of continuous renal replacement therapy, and intra-abdominal pressure. The model created with these variables presented an AUC of ROC curve of 0.90 (CI 95% 0.81-0.94) in the validation cohort. We developed a multivariable prediction model, and AP cases could be classified as low mortality risk (between 2 and 9.5 points, mortality of 1.35%), moderate mortality risk (between 10 and 12.5 points, 28.92% of mortality), and high mortality risk (13 points of more, mortality of 88.37%). Our model presented better AUC of ROC curve than APACHE II (0.91 vs 0.80) and SOFA in the first 24 h (0.91 vs 0.79). We developed and validated a multivariate prediction model, which can be applied in any moment of the stay in ICU, with better discriminatory power than APACHE II and SOFA in the first 24 h. Copyright © 2018 IAP and EPC. Published by Elsevier B.V. All rights reserved.

  17. Prediction of dissolved reactive phosphorus losses from small agricultural catchments: calibration and validation of a parsimonious model

    Directory of Open Access Journals (Sweden)

    C. Hahn

    2013-10-01

    Full Text Available Eutrophication of surface waters due to diffuse phosphorus (P losses continues to be a severe water quality problem worldwide, causing the loss of ecosystem functions of the respective water bodies. Phosphorus in runoff often originates from a small fraction of a catchment only. Targeting mitigation measures to these critical source areas (CSAs is expected to be most efficient and cost-effective, but requires suitable tools. Here we investigated the capability of the parsimonious Rainfall-Runoff-Phosphorus (RRP model to identify CSAs in grassland-dominated catchments based on readily available soil and topographic data. After simultaneous calibration on runoff data from four small hilly catchments on the Swiss Plateau, the model was validated on a different catchment in the same region without further calibration. The RRP model adequately simulated the discharge and dissolved reactive P (DRP export from the validation catchment. Sensitivity analysis showed that the model predictions were robust with respect to the classification of soils into "poorly drained" and "well drained", based on the available soil map. Comparing spatial hydrological model predictions with field data from the validation catchment provided further evidence that the assumptions underlying the model are valid and that the model adequately accounts for the dominant P export processes in the target region. Thus, the parsimonious RRP model is a valuable tool that can be used to determine CSAs. Despite the considerable predictive uncertainty regarding the spatial extent of CSAs, the RRP can provide guidance for the implementation of mitigation measures. The model helps to identify those parts of a catchment where high DRP losses are expected or can be excluded with high confidence. Legacy P was predicted to be the dominant source for DRP losses and thus, in combination with hydrologic active areas, a high risk for water quality.

  18. Psychometric properties and convergent and predictive validity of an executive function test battery for two-year-olds

    Directory of Open Access Journals (Sweden)

    Hanna eMulder

    2014-07-01

    Full Text Available Executive function (EF is an important predictor of numerous developmental outcomes, such as academic achievement and behavioral adjustment. Although a plethora of measurement instruments exists to assess executive function in children, only few of these are suitable for toddlers, and even fewer have undergone psychometric evaluation. The present study evaluates the psychometric properties and validity of an assessment battery for measuring EF in two-year-olds. A sample of 2437 children were administered the assessment battery at a mean age of 2;4 years (SD = 0;3 years in a large-scale field study. Measures of both hot EF (snack and gift delay tasks and cool EF (six boxes, memory for location, and visual search task were included. Confirmatory Factor Analyses showed that a two-factor hot and cool EF model fitted the data better than a one-factor model. Measurement invariance was supported across groups differing in age, gender, socioeconomic status (SES, home language, and test setting. Criterion and convergent validity were evaluated by examining relationships between EF and age, gender, SES, home language, and parent and teacher reports of children’s attention and inhibitory control. Predictive validity of the test battery was investigated by regressing children’s pre-academic skills and behavioral problems at age three on the latent hot and cool EF factors at age two years. The test battery showed satisfactory psychometric quality and criterion, convergent, and predictive validity. Whereas cool EF predicted both pre-academic skills and behavior problems one year later, hot EF predicted behavior problems only. These results show that EF can be assessed with psychometrically sound instruments in children as young as two years, and that EF tasks can be reliably applied in large scale field research. The current instruments offer new opportunities for investigating EF in early childhood, and for evaluating interventions targeted at improving

  19. Development and internal validation of a side-specific, multiparametric magnetic resonance imaging-based nomogram for the prediction of extracapsular extension of prostate cancer.

    Science.gov (United States)

    Martini, Alberto; Gupta, Akriti; Lewis, Sara C; Cumarasamy, Shivaram; Haines, Kenneth G; Briganti, Alberto; Montorsi, Francesco; Tewari, Ashutosh K

    2018-04-19

    To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve-sparing radical prostatectomy. We retrospectively analysed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: prostate-specific antigen; highest ipsilateral biopsy Gleason grade; highest ipsilateral percentage core involvement; and ECE on multiparametric magnetic resonance imaging (mpMRI). A multivariable logistic regression analysis was fitted to predict side-specific ECE. A nomogram was built based on the coefficients of the logit function. Internal validation was performed using 'leave-one-out' cross-validation. Calibration was graphically investigated. The decision curve analysis was used to evaluate the net clinical benefit. The study population consisted of 829 side-specific cases, after excluding negative biopsy observations (n = 293). ECE was reported on mpMRI and final pathology in 115 (14%) and 142 (17.1%) cases, respectively. Among these, mpMRI was able to predict ECE correctly in 57 (40.1%) cases. All variables in the model except highest percentage core involvement were predictors of ECE (all P ≤ 0.006). All variables were considered for inclusion in the nomogram. After internal validation, the area under the curve was 82.11%. The model demonstrated excellent calibration and improved clinical risk prediction, especially when compared with relying on mpMRI prediction of ECE alone. When retrospectively applying the nomogram-derived probability, using a 20% threshold for performing nerve-sparing, nine out of 14 positive surgical margins (PSMs) at the site of ECE resulted above the threshold. We developed an easy-to-use model for the prediction of side-specific ECE, and hope it serves as a tool for planning nerve-sparing radical prostatectomy and in the reduction of PSM in

  20. Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.

    Science.gov (United States)

    Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng

    2015-09-22

    The increasing rate of health care expenditures in the United States has placed a significant burden on the nation's economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. In the HealthInfoNet, Maine's health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient's next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree-based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

  1. Predictive validity of the GOSLON Yardstick index in patients with unilateral cleft lip and palate: A systematic review.

    Directory of Open Access Journals (Sweden)

    Cindy Buj-Acosta

    Full Text Available Among the various indices developed for measuring the results of treatment in patients born with unilateral cleft lip and palate (UCLP, the GOSLON Yardstick index is the most widely used to assess the efficacy of treatment and treatment outcomes, which in UCLP cases are closely linked to jaw growth. The aim of this study was to conduct a systematic review to validate the predictability of growth using the GOSLON Yardstick in patients born with UCLP. A systematic literature review was conducted in four Internet databases: Medline, Cochrane Library, Scopus and Embase, complemented by a manual search and a further search in the databases of the leading journals that focus on this topic. An electronic search was also conducted among grey literature. The search identified a total of 131 articles. Duplicated articles were excluded and after reading titles and abstracts, any articles not related to the research objective were excluded, leaving a total of 21 texts. After reading the complete text, only three articles fulfilled the inclusion criteria. The results showed a predictive validity of between 42.2% and 64.7%, which points to a lack of evidence in the literature for the predictive validity of the GOSLON Yardstick index used in children born with UCLP.

  2. Assessing the reliability, predictive and construct validity of historical, clinical and risk management-20 (HCR-20) in Mexican psychiatric inpatients.

    Science.gov (United States)

    Sada, Andrea; Robles-García, Rebeca; Martínez-López, Nicolás; Hernández-Ramírez, Rafael; Tovilla-Zarate, Carlos-Alfonso; López-Munguía, Fernando; Suárez-Alvarez, Enrique; Ayala, Xochitl; Fresán, Ana

    2016-08-01

    Assessing dangerousness to gauge the likelihood of future violent behaviour has become an integral part of clinical mental health practice in forensic and non-forensic psychiatric settings, one of the most effective instruments for this being the Historical, Clinical and Risk Management-20 (HCR-20). To examine the HCR-20 factor structure in Mexican psychiatric inpatients and to obtain its predictive validity and reliability for use in this population. In total, 225 patients diagnosed with psychotic, affective or personality disorders were included. The HCR-20 was applied at hospital admission and violent behaviours were assessed during psychiatric hospitalization using the Overt Aggression Scale (OAS). Construct validity, predictive validity and internal consistency were determined. Violent behaviour remains more severe in patients classified in the high-risk group during hospitalization. Fifteen items displayed adequate communalities in the original designated domains of the HCR-20 and internal consistency of the instruments was high. The HCR-20 is a suitable instrument for predicting violence risk in Mexican psychiatric inpatients.

  3. Validity of resting energy expenditure predictive equations before and after an energy-restricted diet intervention in obese women.

    Directory of Open Access Journals (Sweden)

    Jonatan R Ruiz

    Full Text Available BACKGROUND: We investigated the validity of REE predictive equations before and after 12-week energy-restricted diet intervention in Spanish obese (30 kg/m(2>BMI<40 kg/m(2 women. METHODS: We measured REE (indirect calorimetry, body weight, height, and fat mass (FM and fat free mass (FFM, dual X-ray absorptiometry in 86 obese Caucasian premenopausal women aged 36.7±7.2 y, before and after (n = 78 women the intervention. We investigated the accuracy of ten REE predictive equations using weight, height, age, FFM and FM. RESULTS: At baseline, the most accurate equation was the Mifflin et al. (Am J Clin Nutr 1990; 51: 241-247 when using weight (bias:-0.2%, P = 0.982, 74% of accurate predictions. This level of accuracy was not reached after the diet intervention (24% accurate prediction. After the intervention, the lowest bias was found with the Owen et al. (Am J Clin Nutr 1986; 44: 1-19 equation when using weight (bias:-1.7%, P = 0.044, 81% accurate prediction, yet it provided 53% accurate predictions at baseline. CONCLUSIONS: There is a wide variation in the accuracy of REE predictive equations before and after weight loss in non-morbid obese women. The results acquire especial relevance in the context of the challenging weight regain phenomenon for the overweight/obese population.

  4. Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.).

    Science.gov (United States)

    Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K; Sandeep, I S; Mohanty, Sujata; Naik, Pradeep K; Mishra, Antaryami; Nayak, Sanghamitra

    2016-01-01

    The drug yielding potential of turmeric ( Curcuma longa L.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R 2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.

  5. Development of prediction model and experimental validation in predicting the curcumin content of turmeric (Curcuma longa L.

    Directory of Open Access Journals (Sweden)

    Abdul Akbar

    2016-10-01

    Full Text Available The drug yielding potential of turmeric (Curcuma longa L. is largely due to the presence of phyto-constituent ‘curcumin’. Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8 was the most suitable one with R2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.

  6. The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

    Science.gov (United States)

    Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

    2013-11-01

    The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

  7. Development and validation of a prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults.

    Science.gov (United States)

    Mathioudakis, Nestoras Nicolas; Everett, Estelle; Routh, Shuvodra; Pronovost, Peter J; Yeh, Hsin-Chieh; Golden, Sherita Hill; Saria, Suchi

    2018-01-01

    To develop and validate a multivariable prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults. We collected pharmacologic, demographic, laboratory, and diagnostic data from 128 657 inpatient days in which at least 1 unit of subcutaneous insulin was administered in the absence of intravenous insulin, total parenteral nutrition, or insulin pump use (index days). These data were used to develop multivariable prediction models for biochemical and clinically significant hypoglycemia (blood glucose (BG) of ≤70 mg/dL and model development and validation, respectively. Using predictors of age, weight, admitting service, insulin doses, mean BG, nadir BG, BG coefficient of variation (CV BG ), diet status, type 1 diabetes, type 2 diabetes, acute kidney injury, chronic kidney disease (CKD), liver disease, and digestive disease, our model achieved a c-statistic of 0.77 (95% CI 0.75 to 0.78), positive likelihood ratio (+LR) of 3.5 (95% CI 3.4 to 3.6) and negative likelihood ratio (-LR) of 0.32 (95% CI 0.30 to 0.35) for prediction of biochemical hypoglycemia. Using predictors of sex, weight, insulin doses, mean BG, nadir BG, CV BG , diet status, type 1 diabetes, type 2 diabetes, CKD stage, and steroid use, our model achieved a c-statistic of 0.80 (95% CI 0.78 to 0.82), +LR of 3.8 (95% CI 3.7 to 4.0) and -LR of 0.2 (95% CI 0.2 to 0.3) for prediction of clinically significant hypoglycemia. Hospitalized patients at risk of insulin-associated hypoglycemia can be identified using validated prediction models, which may support the development of real-time preventive interventions.

  8. On the safety and performance demonstration tests of Prototype Gen-IV Sodium-Cooled Fast Reactor and validation and verification of computational codes

    International Nuclear Information System (INIS)

    Kim, Jong Bum; Jeong, Ji Young; Lee, Tae Ho; Kim, Sung Kyun; Euh, Dong Jin; Joo, Hyung Kook

    2016-01-01

    The design of Prototype Gen-IV Sodium-Cooled Fast Reactor (PGSFR) has been developed and the validation and verification (V and V) activities to demonstrate the system performance and safety are in progress. In this paper, the current status of test activities is described briefly and significant results are discussed. The large-scale sodium thermal-hydraulic test program, Sodium Test Loop for Safety Simulation and Assessment-1 (STELLA-1), produced satisfactory results, which were used for the computer codes V and V, and the performance test results of the model pump in sodium showed good agreement with those in water. The second phase of the STELLA program with the integral effect tests facility, STELLA-2, is in the detailed design stage of the design process. The sodium thermal-hydraulic experiment loop for finned-tube sodium-to-air heat exchanger performance test, the intermediate heat exchanger test facility, and the test facility for the reactor flow distribution are underway. Flow characteristics test in subchannels of a wire-wrapped rod bundle has been carried out for safety analysis in the core and the dynamic characteristic test of upper internal structure has been performed for the seismic analysis model for the PGSFR. The performance tests for control rod assemblies (CRAs) have been conducted for control rod drive mechanism driving parts and drop tests of the CRA under scram condition were performed. Finally, three types of inspection sensors under development for the safe operation of the PGSFR were explained with significant results

  9. On the safety and performance demonstration tests of Prototype Gen-IV Sodium-Cooled Fast Reactor and validation and verification of computational codes

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Bum; Jeong, Ji Young; Lee, Tae Ho; Kim, Sung Kyun; Euh, Dong Jin; Joo, Hyung Kook [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    The design of Prototype Gen-IV Sodium-Cooled Fast Reactor (PGSFR) has been developed and the validation and verification (V and V) activities to demonstrate the system performance and safety are in progress. In this paper, the current status of test activities is described briefly and significant results are discussed. The large-scale sodium thermal-hydraulic test program, Sodium Test Loop for Safety Simulation and Assessment-1 (STELLA-1), produced satisfactory results, which were used for the computer codes V and V, and the performance test results of the model pump in sodium showed good agreement with those in water. The second phase of the STELLA program with the integral effect tests facility, STELLA-2, is in the detailed design stage of the design process. The sodium thermal-hydraulic experiment loop for finned-tube sodium-to-air heat exchanger performance test, the intermediate heat exchanger test facility, and the test facility for the reactor flow distribution are underway. Flow characteristics test in subchannels of a wire-wrapped rod bundle has been carried out for safety analysis in the core and the dynamic characteristic test of upper internal structure has been performed for the seismic analysis model for the PGSFR. The performance tests for control rod assemblies (CRAs) have been conducted for control rod drive mechanism driving parts and drop tests of the CRA under scram condition were performed. Finally, three types of inspection sensors under development for the safe operation of the PGSFR were explained with significant results.

  10. The accuracy of Internet search engines to predict diagnoses from symptoms can be assessed with a validated scoring system.

    Science.gov (United States)

    Shenker, Bennett S

    2014-02-01

    To validate a scoring system that evaluates the ability of Internet search engines to correctly predict diagnoses when symptoms are used as search terms. We developed a five point scoring system to evaluate the diagnostic accuracy of Internet search engines. We identified twenty diagnoses common to a primary care setting to validate the scoring system. One investigator entered the symptoms for each diagnosis into three Internet search engines (Google, Bing, and Ask) and saved the first five webpages from each search. Other investigators reviewed the webpages and assigned a diagnostic accuracy score. They rescored a random sample of webpages two weeks later. To validate the five point scoring system, we calculated convergent validity and test-retest reliability using Kendall's W and Spearman's rho, respectively. We used the Kruskal-Wallis test to look for differences in accuracy scores for the three Internet search engines. A total of 600 webpages were reviewed. Kendall's W for the raters was 0.71 (psearch engines is a valid and reliable instrument. The scoring system may be used in future Internet research. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  11. A physical function test for use in the intensive care unit: validity, responsiveness, and predictive utility of the physical function ICU test (scored).

    Science.gov (United States)

    Denehy, Linda; de Morton, Natalie A; Skinner, Elizabeth H; Edbrooke, Lara; Haines, Kimberley; Warrillow, Stephen; Berney, Sue

    2013-12-01

    Several tests have recently been developed to measure changes in patient strength and functional outcomes in the intensive care unit (ICU). The original Physical Function ICU Test (PFIT) demonstrates reliability and sensitivity. The aims of this study were to further develop the original PFIT, to derive an interval score (the PFIT-s), and to test the clinimetric properties of the PFIT-s. A nested cohort study was conducted. One hundred forty-four and 116 participants performed the PFIT at ICU admission and discharge, respectively. Original test components were modified using principal component analysis. Rasch analysis examined the unidimensionality of the PFIT, and an interval score was derived. Correlations tested validity, and multiple regression analyses investigated predictive ability. Responsiveness was assessed using the effect size index (ESI), and the minimal clinically important difference (MCID) was calculated. The shoulder lift component was removed. Unidimensionality of combined admission and discharge PFIT-s scores was confirmed. The PFIT-s displayed moderate convergent validity with the Timed "Up & Go" Test (r=-.60), the Six-Minute Walk Test (r=.41), and the Medical Research Council (MRC) sum score (rho=.49). The ESI of the PFIT-s was 0.82, and the MCID was 1.5 points (interval scale range=0-10). A higher admission PFIT-s score was predictive of: an MRC score of ≥48, increased likelihood of discharge home, reduced likelihood of discharge to inpatient rehabilitation, and reduced acute care hospital length of stay. Scoring of sit-to-stand assistance required is subjective, and cadence cutpoints used may not be generalizable. The PFIT-s is a safe and inexpensive test of physical function with high clinical utility. It is valid, responsive to change, and predictive of key outcomes. It is recommended that the PFIT-s be adopted to test physical function in the ICU.

  12. Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking

    NARCIS (Netherlands)

    Daetwyler, H.D.; Calus, M.P.L.; Pong-Wong, R.; Los Campos, De G.; Hickey, J.M.

    2013-01-01

    The genomic prediction of phenotypes and breeding values in animals and plants has developed rapidly into its own research field. Results of genomic prediction studies are often difficult to compare because data simulation varies, real or simulated data are not fully described, and not all relevant

  13. Exacerbations in adults with asthma: A systematic review and external validation of prediction models

    NARCIS (Netherlands)

    Loymans, Rik J. B.; Debray, Thomas P. A.; Honkoop, Persijn J.; Termeer, Evelien H.; Snoeck-Stroband, Jiska B.; Schermer, Tjard R. J.; Assendelft, Willem J. J.; Timp, Merel; Chung, Kian Fan; Sousa, Ana R.; Sont, Jaap K.; Sterk, Peter J.; Reddel, Helen K.; ter Riet, Gerben

    2018-01-01

    Several prediction models assessing future risk of exacerbations in adult patients with asthma have been published. Applicability of these models is uncertain because their predictive performance has often not been assessed beyond the population in which they were derived. This study aimed to

  14. Driving and Low Vision: Validity of Assessments for Predicting Performance of Drivers

    Science.gov (United States)

    Strong, J. Graham; Jutai, Jeffrey W.; Russell-Minda, Elizabeth; Evans, Mal

    2008-01-01

    The authors conducted a systematic review to examine whether vision-related assessments can predict the driving performance of individuals who have low vision. The results indicate that measures of visual field, contrast sensitivity, cognitive and attention-based tests, and driver screening tools have variable utility for predicting real-world…

  15. External validation of prediction models for time to death in potential donors after circulatory death

    NARCIS (Netherlands)

    Kotsopoulos, A.M.M.; Böing-Messing, F.; Jansen, N.E.; Vos, P.; Abdo, W.F.

    2018-01-01

    Predicting time to death in controlled donation after circulatory death (cDCD) donors following withdrawal of life‐sustaining treatment (WLST) is important but poses a major challenge. The aim of this study is to determine factors predicting time to circulatory death within 60 minutes after WSLT and

  16. Predicting the peak growth velocity in the individual child: validation of a new growth model.

    NARCIS (Netherlands)

    Busscher, I.; Kingma, I.; de Bruin, R.; Wapstra, F.H.; Verkerke, G.J.; Veldhuizen, A.G.

    2012-01-01

    Predicting the peak growth velocity in an individual patient with adolescent idiopathic scoliosis is essential or determining the prognosis of the disorder and timing of the (surgical) treatment. Until the present time, no accurate method has been found to predict the timing and magnitude of the

  17. Predicting the peak growth velocity in the individual child : validation of a new growth model

    NARCIS (Netherlands)

    Busscher, Iris; Kingma, Idsart; de Bruin, Rob; Wapstra, Frits Hein; Verkerke, Gijsvertus J.; Veldhuizen, Albert G.

    Predicting the peak growth velocity in an individual patient with adolescent idiopathic scoliosis is essential or determining the prognosis of the disorder and timing of the (surgical) treatment. Until the present time, no accurate method has been found to predict the timing and magnitude of the

  18. Predicting the peak growth velocity in the individual child: validation of a new growth model

    NARCIS (Netherlands)

    Busscher, I.; Kingma, I.; Bruin, R.; Wapstra, F.H.; Verkerke, Gijsbertus Jacob; Veldhuizen, A.G.

    2012-01-01

    Predicting the peak growth velocity in an individual patient with adolescent idiopathic scoliosis is essential or determining the prognosis of the disorder and timing of the (surgical) treatment. Until the present time, no accurate method has been found to predict the timing and magnitude of the

  19. Prediction model of RSV-hospitalization in late preterm infants : An update and validation study

    NARCIS (Netherlands)

    Korsten, Koos; Blanken, Maarten O; Nibbelke, Elisabeth E; Moons, Karel G M; Bont, Louis

    BACKGROUND: New vaccines and RSV therapeutics have been developed in the past decade. With approval of these new pharmaceuticals on the horizon, new challenges lie ahead in selecting the appropriate target population. We aimed to improve a previously published prediction model for prediction of

  20. Prediction model of RSV-hospitalization in late preterm infants: An update and validation study

    NARCIS (Netherlands)

    Korsten, K.; Blanken, M.O.; Nibbelke, E.E.; Moons, K.G.; Bont, L.; Liem, K.D.; et al.,

    2016-01-01

    BACKGROUND: New vaccines and RSV therapeutics have been developed in the past decade. With approval of these new pharmaceuticals on the horizon, new challenges lie ahead in selecting the appropriate target population. We aimed to improve a previously published prediction model for prediction of

  1. GMAT versus Alternatives: Predictive Validity Evidence from Central Europe and the Middle East

    Science.gov (United States)

    Koys, Daniel

    2010-01-01

    The author found that the GPA at the end of the MBA program is most accurately predicted by the Graduate Management Admission Test (GMAT) and the Test of English as a Foreign Language (TOEFL). MBA GPA is also predicted, though less accurately, by the Scholastic Level Exam, a mathematics test, undergraduate GPA, and previous career progression. If…

  2. An efficient numerical target strength prediction model: Validation against analysis solutions

    NARCIS (Netherlands)

    Fillinger, L.; Nijhof, M.J.J.; Jong, C.A.F. de

    2014-01-01

    A decade ago, TNO developed RASP (Rapid Acoustic Signature Prediction), a numerical model for the prediction of the target strength of immersed underwater objects. The model is based on Kirchhoff diffraction theory. It is currently being improved to model refraction, angle dependent reflection and

  3. The risk of severe postoperative pain: Modification and validation of a clinical prediction rule

    NARCIS (Netherlands)

    Janssen, Kristel J. M.; Kalkman, Cor J.; Grobbee, Diederick E.; Bonsel, Gouke J.; Moons, Karel G. M.; Vergouwe, Yvonne

    2008-01-01

    BACKGROUND: Recently, a prediction rule was developed to preoperatively predict the risk of severe pain in the first postoperative hour in surgical inpatients. We aimed to modify the rule to enhance its use in both surgical inpatients and outpatients (ambulatory patients). Subsequently, we

  4. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions

    Directory of Open Access Journals (Sweden)

    Quentin Noirhomme

    2014-01-01

    Full Text Available Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with cross-validation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the cross-validation was further illustrated on real-data from a brain–computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson's disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation.

  5. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions.

    Science.gov (United States)

    Noirhomme, Quentin; Lesenfants, Damien; Gomez, Francisco; Soddu, Andrea; Schrouff, Jessica; Garraux, Gaëtan; Luxen, André; Phillips, Christophe; Laureys, Steven

    2014-01-01

    Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with cross-validation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the cross-validation was further illustrated on real-data from a brain-computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson's disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation.

  6. Exploring the Predictive Validity of the Susceptibility to Smoking Construct for Tobacco Cigarettes, Alternative Tobacco Products, and E-Cigarettes.

    Science.gov (United States)

    Cole, Adam G; Kennedy, Ryan David; Chaurasia, Ashok; Leatherdale, Scott T

    2017-12-06

    Within tobacco prevention programming, it is useful to identify youth that are at risk for experimenting with various tobacco products and e-cigarettes. The susceptibility to smoking construct is a simple method to identify never-smoking students that are less committed to remaining smoke-free. However, the predictive validity of this construct has not been tested within the Canadian context or for the use of other tobacco products and e-cigarettes. This study used a large, longitudinal sample of secondary school students that reported never using tobacco cigarettes and non-current use of alternative tobacco products or e-cigarettes at baseline in Ontario, Canada. The sensitivity, specificity, and positive and negative predictive values of the susceptibility construct for predicting tobacco cigarette, e-cigarette, cigarillo or little cigar, cigar, hookah, and smokeless tobacco use one and two years after baseline measurement were calculated. At baseline, 29.4% of the sample was susceptible to future tobacco product or e-cigarette use. The sensitivity of the construct ranged from 43.2% (smokeless tobacco) to 59.5% (tobacco cigarettes), the specificity ranged from 70.9% (smokeless tobacco) to 75.9% (tobacco cigarettes), and the positive predictive value ranged from 2.6% (smokeless tobacco) to 32.2% (tobacco cigarettes). Similar values were calculated for each measure of the susceptibility construct. A significant number of youth that did not currently use tobacco products or e-cigarettes at baseline reported using tobacco products and e-cigarettes over a two-year follow-up period. The predictive validity of the susceptibility construct was high and the construct can be used to predict other tobacco product and e-cigarette use among youth. This study presents the predictive validity of the susceptibility construct for the use of tobacco cigarettes among secondary school students in Ontario, Canada. It also presents a novel use of the susceptibility construct for

  7. Structural refinement and prediction of potential CCR2 antagonists through validated multi-QSAR modeling studies.

    Science.gov (United States)

    Amin, Sk Abdul; Adhikari, Nilanjan; Baidya, Sandip Kumar; Gayen, Shovanlal; Jha, Tarun

    2018-01-03

    Chemokines trigger numerous inflammatory responses and modulate the immune system. The interaction between monocyte chemoattractant protein-1 and chemokine receptor 2 (CCR2) may be the cause of atherosclerosis, obesity, and insulin resistance. However, CCR2 is also implicated in other inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, asthma, and neuropathic pain. Therefore, there is a paramount importance of designing potent and selective CCR2 antagonists despite a number of drug candidates failed in clinical trials. In this article, 83 CCR2 antagonists by Jhonson and Jhonson Pharmaceuticals have been considered for robust validated multi-QSAR modeling studies to get an idea about the structural and pharmacophoric requirements for designing more potent CCR2 antagonists. All these QSAR models were validated and statistically reliable. Observations resulted from different modeling studies correlated and validated results of other ones. Finally, depending on these QSAR observations, some new molecules were proposed that may exhibit higher activity against CCR2.

  8. Prediction and validation of burnout curves for Goettelborn char using reaction kinetics determined in shock tube experiments

    Energy Technology Data Exchange (ETDEWEB)

    Moors, J.H.J.; Banin, V.E.; Haas, J.H.P.; Weber, R.; Veefkind, A. [Eindhoven University of Technology, Eindhoven (Netherlands). Dept. of Applied Physics

    1999-01-01

    Using a shock tube facility the combustion characteristics of pulverised char ({lt} 10 {mu}m) were measured. A prediction was made for the burnout behaviour of a commercial sized char particle (75-90 {mu}m) in different ambient conditions using a `pseudo kinetic` approach. In this approach the kinetic rate of a surface containing micro pores is determined and these `pseudo kinetics` are then applied to the larger particle not taking into account the micro pores. Comparison of the predictions with measurements done with an isothermal plug flow reactor showed this approach to be valid within experimental error for low burnout. A linear decrease of the kinetic reaction rate with burnout is shown to predict the burnout behaviour in the complete range of burnout. A possible explanation for this linear decrease could be a growing fraction of non-combustible material in the char particles during burnout. 11 refs., 6 figs., 2 tabs.

  9. Prediction of arterial oxygen partial pressure after changes in FIO₂: validation and clinical application of a novel formula.

    Science.gov (United States)

    Al-Otaibi, H M; Hardman, J G

    2011-11-01

    Existing methods allow prediction of Pa(O₂) during adjustment of Fi(O₂). However, these are cumbersome and lack sufficient accuracy for use in the clinical setting. The present studies aim to extend the validity of a novel formula designed to predict Pa(O₂) during adjustment of Fi(O₂) and to compare it with the current methods. Sixty-seven new data sets were collected from 46 randomly selected, mechanically ventilated patients. Each data set consisted of two subsets (before and 20 min after Fi(O₂) adjustment) and contained ventilator settings, pH, and arterial blood gas values. We compared the accuracy of Pa(O₂) prediction using a new formula (which utilizes only the pre-adjustment Pa(O₂) and pre- and post-adjustment Fi(O₂) with prediction using assumptions of constant Pa(O₂)/Fi(O₂) or constant Pa(O₂)/Pa(O₂). Subsequently, 20 clinicians predicted Pa(O₂) using the new formula and using Nunn's isoshunt diagram. The accuracy of the clinician's predictions was examined. The 95% limits of agreement (LA(95%)) between predicted and measured Pa(O₂) in the patient group were: new formula 0.11 (2.0) kPa, Pa(O₂)/Fi(O₂) -1.9 (4.4) kPa, and Pa(O₂)/Pa(O₂) -1.0 (3.6) kPa. The LA(95%) of clinicians' predictions of Pa(O₂) were 0.56 (3.6) kPa (new formula) and -2.7 (6.4) kPa (isoshunt diagram). The new formula's prediction of changes in Pa(O₂) is acceptably accurate and reliable and better than any other existing method. Its use by clinicians appears to improve accuracy over the most popular existing method. The simplicity of the new method may allow its regular use in the critical care setting.

  10. Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model

    Science.gov (United States)

    Gustafson, David H; Hawkins, Robert P; Brennan, Patricia F; Dinauer, Susan; Johnson, Pauley R; Siegler, Tracy

    2010-01-01

    Objective To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements. Design Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases. Measurements Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes. Results Two of the seven factors, ‘organizational motivation’ and ‘meeting user needs,’ were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome. Limitations The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study. Conclusion The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term. PMID:20962135

  11. Development and validation of clinical prediction models for mortality, functional outcome and cognitive impairment after stroke: a study protocol.</