Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19
Wenhua Liang, MD1,2; Hengrui Liang, MD1,2; Limin Ou, MD1; et alBinfeng Chen, MD3; Ailan Chen, MD1,4; Caichen Li, MD1; Yimin Li, MD1,5; Weijie Guan, MD1; Ling Sang, MD1,5,6; Jiatao Lu, MD4; Yuanda Xu, MD1,5,7; Guoqiang Chen, MD8; Haiyan Guo, MD9; Jun Guo, MD10; Zisheng Chen, MD1,11; Yi Zhao, MD1,2; Shiyue Li, MD1; Nuofu Zhang, MD1,4; Nanshan Zhong, MD1; Jianxing He, MD1,2; for the China Medical Treatment Expert Group for COVID-19
Author Affiliations Article Information
JAMA Intern Med. Published online May 12, 2020. doi:10.1001/jamainternmed.2020.2033
Abstract
Importance Early identification of patients with novel corona virus disease 2019 (COVID-19) who may develop critical illness is of great importance and may aid in delivering proper treatment and optimizing use of resources.
Objective To develop and validate a clinical score at hospital admission for predicting which patients with COVID-19 will develop critical illness based on a nationwide cohort in China.
Design, Setting, and Participants Collaborating with the National Health Commission of China, we established a retrospective cohort of patients with COVID-19 from 575 hospitals in 31 provincial administrative regions as of January 31, 2020. Epidemiological, clinical, laboratory, and imaging variables ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive risk score (COVID-GRAM). The score provides an estimate of the risk that a hospitalized patient with COVID-19 will develop critical illness. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC). Data from 4 additional cohorts in China hospitalized with COVID-19 were used to validate the score. Data were analyzed between February 20, 2020 and March 17, 2020.
