Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.

ABSTRACT: Background: Predicting the risk of progression to severe coronavirus disease 2019 (COVID-19) could facilitate personalized diagnosis and treatment options, thus optimizing the use of medical resources. Methods: In this prospective study, 206 patients with COVID-19 were enrolled from regional medical institutions between December 20, 2019, and April 10, 2020. We collated a range of data to derive and validate a predictive model for COVID-19 progression, including demographics, clinical characteristics, laboratory findings, and cytokine levels. Variation analysis, along with the least absolute shrinkage and selection operator (LASSO) and Boruta algorithms, was used for modeling. The performance of the derived models was evaluated by specificity, sensitivity, area under the rece

SUBMITTER: Meng Z 

PROVIDER: S-EPMC8185163 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature