Development and validation of a risk score using complete blood count to predict in-hospital mortality in COVID-19 patients.

ABSTRACT:

Background

To develop a sensitive risk score predicting the risk of mortality in patients with coronavirus disease 2019 (COVID-19) using complete blood count (CBC).

Methods

We performed a retrospective cohort study from a total of 13,138 inpatients with COVID-19 in Hubei, China, and Milan, Italy. Among them, 9,810 patients with ≥2 CBC records from Hubei were assigned to the training cohort. CBC parameters were analyzed as potential predictors for all-cause mortality and were selected by the generalized linear mixed model (GLMM).

Findings

Five risk factors were derived to construct a composite score (PAWNN score) using the Cox regression model, including platelet counts, age, white blood cell counts, neutrophil counts, and neutrophil:lymphocyte ratio. The PAWNN

SUBMITTER: Liu H 

PROVIDER: S-EPMC7831644 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature