Early predictors of severe COVID-19 among hospitalized patients.

ABSTRACT:

Background

Limited research has been conducted on early laboratory biomarkers to identify patients with severe coronavirus disease (COVID-19). This study fills this gap to ensure appropriate treatment delivery and optimal resource utilization.

Methods

In this retrospective, multicentre, cohort study, 52 and 64 participants with severe and mild cases of COVID-19, respectively, were enrolled during January-March 2020. Least absolute shrinkage and selection operator and binary forward stepwise logistic regression were used to construct a predictive risk score. A prediction model was then developed and verified using data from four hospitals.

Results

Of the 50 variables assessed, eight were independent predictors of COVID-19 and used to calculate risk scores for severe CO

SUBMITTER: Zhao Q 

PROVIDER: S-EPMC8841178 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature