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Assessment Of A Comparative Bayesian-Enhanced Population-Based Decision Model For Covid-19 Critical Care Prediction In The Dominican Republic Social Security Affiliates, Amado A. Baez, Oscar J. Lopez, Maria Martinez, Colyn White, Pedro Ramirez-Slaibe, Leticia Martinez, Pedro L. Castellanos
Assessment Of A Comparative Bayesian-Enhanced Population-Based Decision Model For Covid-19 Critical Care Prediction In The Dominican Republic Social Security Affiliates, Amado A. Baez, Oscar J. Lopez, Maria Martinez, Colyn White, Pedro Ramirez-Slaibe, Leticia Martinez, Pedro L. Castellanos
School of Medicine Publications and Presentations
Introduction: The novel coronavirus disease 2019 (COVID-19) has been a major health concern worldwide. This study aims to develop a Bayesian model to predict critical outcomes in patients with COVID-19.
Methods: Sensitivity and specificity were obtained from previous meta-analysis studies. The complex vulnerability index (IVC-COV2 index for its abbreviation in Spanish) was used to set the pretest probability. Likelihood ratios were integrated into a Fagan nomogram for posttest probabilities, and IVC-COV2 + National Early Warning Score (NEWS) values and CURB-65 scores were generated. Absolute and relative diagnostic gains (RDGs) were calculated based on pretest and posttest differences.
Results: The IVC-COV2 …