A risk score based on baseline risk factors for predicting mortality in COVID-19 patients.

ABSTRACT:

Background

To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This model would assist frontline clinicians in optimizing medical treatment with limited resources.

Methods

6415 patients from seven hospitals in Wuhan city were assigned to the training and testing cohorts. A total of 6351 patients from another three hospitals in Wuhan, 2169 patients from outside of Wuhan, and 553 patients from Milan, Italy were assigned to three independent validation cohorts. A total of 64 candidate clinical variables at hospital admission were analyzed by random forest and least absolute shrinkage and selection operator (LASSO) analyses.

Results

Eight factors

SUBMITTER: Chen Z 

PROVIDER: S-EPMC8054492 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature