Model Prediction for In-Hospital Mortality in Patients with COVID-19: A Case-Control Study in Isfahan, Iran.

ABSTRACT: The COVID-19 pandemic has now imposed an enormous global burden as well as a large mortality in a short time period. Although there is no promising treatment, identification of early predictors of in-hospital mortality would be critically important in reducing its worldwide mortality. We aimed to suggest a prediction model for in-hospital mortality of COVID-19. In this case-control study, we recruited 513 confirmed patients with COVID-19 from February 18 to March 26, 2020 from Isfahan COVID-19 registry. Based on extracted laboratory, clinical, and demographic data, we created an in-hospital mortality predictive model using gradient boosting. We also determined the diagnostic performance of the proposed model including sensitivity, specificity, and area under the curve (AUC) as well as their

SUBMITTER: Abdollahpour I 

PROVIDER: S-EPMC8045635 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature