A Prognostic Model to Predict Recovery of COVID-19 Patients Based on Longitudinal Laboratory Findings.

ABSTRACT: The temporal change patterns of laboratory data may provide insightful clues into the whole course of COVID-19. This study aimed to evaluate longitudinal change patterns of key laboratory tests in patients with COVID-19, and identify independent prognostic factors by examining the associations between laboratory findings and outcomes of patients. This multicenter study included 56 patients with COVID-19 treated in Jilin Province, China, from January 21, 2020 to March 5, 2020. The laboratory findings, epidemiological characteristics and demographic data were extracted from electronic medical records. The average value of eosinophils and carbon dioxide combining power continued to significantly increase, while the average value of cardiac troponin I and mean platelet volume decreased through

SUBMITTER: Tian S 

PROVIDER: S-EPMC7652910 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature