دورية أكاديمية
Designing optimal mortality risk prediction scores that preserve clinical knowledge.
| العنوان: | Designing optimal mortality risk prediction scores that preserve clinical knowledge. |
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| المؤلفون: | Arzeno NM; Department of Electrical and Computer Engineering, The University of Texas at Austin, 1 University Station C0803, Austin, TX 78712, USA. Electronic address: narzeno@utexas.edu., Lawson KA; Trauma Services, Dell Children's Medical Center of Central Texas, 4900 Mueller Blvd., Austin, TX 78723, USA. Electronic address: kalawson@seton.org., Duzinski SV; Trauma Services, Dell Children's Medical Center of Central Texas, 4900 Mueller Blvd., Austin, TX 78723, USA. Electronic address: svduzinski@seton.org., Vikalo H; Department of Electrical and Computer Engineering, The University of Texas at Austin, 1 University Station C0803, Austin, TX 78712, USA. Electronic address: hvikalo@ece.utexas.edu. |
| المصدر: | Journal of biomedical informatics [J Biomed Inform] 2015 Aug; Vol. 56, pp. 145-56. Date of Electronic Publication: 2015 Jun 06. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Country of Publication: United States NLM ID: 100970413 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-0480 (Electronic) Linking ISSN: 15320464 NLM ISO Abbreviation: J Biomed Inform Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Orlando : Elsevier Original Publication: San Diego, CA : Academic Press, c2001- |
| مواضيع طبية MeSH: | Hospital Mortality*, Medical Informatics/*methods , Risk Assessment/*methods, Adult ; Algorithms ; Brain Injuries/epidemiology ; Child ; Critical Care ; Databases, Factual ; Humans ; Intensive Care Units ; Intensive Care Units, Pediatric ; Models, Statistical ; Outcome Assessment, Health Care ; Predictive Value of Tests ; Prognosis ; ROC Curve ; Regression Analysis |
| مستخلص: | Many in-hospital mortality risk prediction scores dichotomize predictive variables to simplify the score calculation. However, hard thresholding in these additive stepwise scores of the form "add x points if variable v is above/below threshold t" may lead to critical failures. In this paper, we seek to develop risk prediction scores that preserve clinical knowledge embedded in features and structure of the existing additive stepwise scores while addressing limitations caused by variable dichotomization. To this end, we propose a novel score structure that relies on a transformation of predictive variables by means of nonlinear logistic functions facilitating smooth differentiation between critical and normal values of the variables. We develop an optimization framework for inferring parameters of the logistic functions for a given patient population via cyclic block coordinate descent. The parameters may readily be updated as the patient population and standards of care evolve. We tested the proposed methodology on two populations: (1) brain trauma patients admitted to the intensive care unit of the Dell Children's Medical Center of Central Texas between 2007 and 2012, and (2) adult ICU patient data from the MIMIC II database. The results are compared with those obtained by the widely used PRISM III and SOFA scores. The prediction power of a score is evaluated using area under ROC curve, Youden's index, and precision-recall balance in a cross-validation study. The results demonstrate that the new framework enables significant performance improvements over PRISM III and SOFA in terms of all three criteria. (Copyright © 2015 Elsevier Inc. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Continuous risk score; ICU; Nonlinear features; Optimizable risk score; PRISM III; Prognostic model; SOFA |
| تواريخ الأحداث: | Date Created: 20150610 Date Completed: 20160601 Latest Revision: 20191210 |
| رمز التحديث: | 20231215 |
| DOI: | 10.1016/j.jbi.2015.05.021 |
| PMID: | 26056073 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1532-0480 |
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| DOI: | 10.1016/j.jbi.2015.05.021 |