Unknown

Dataset Information

A novel severity score to predict inpatient mortality in COVID-19 patients.


ABSTRACT: COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n = 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the deriv

SUBMITTER: Altschul DJ 

PROVIDER: S-EPMC7542454 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature