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Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study

Authors :
Yalan Yu
Tao Liu
Liang Shao
Xinyi Li
Colin K. He
Muhammad Jamal
Yi Luo
Yingying Wang
Yanan Liu
Yufeng Shang
Yunbao Pan
Xinghuan Wang
Fuling Zhou
Source :
Virulence, Vol 11, Iss 1, Pp 1569-1581 (2020)
Publication Year :
2020
Publisher :
Taylor & Francis Group, 2020.

Abstract

A pandemic designated as Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. Up to date, there is no efficient biomarker for the timely prediction of the disease progression in patients. To analyze the inflammatory profiles of COVID-19 patients and demonstrate their implications for the illness progression of COVID-19. Retrospective analysis of 3,265 confirmed COVID-19 cases hospitalized between 10 January 2020, and 26 March 2020 in three medical centers in Wuhan, China. Patients were diagnosed as COVID-19 and hospitalized in Leishenshan Hospital, Zhongnan Hospital of Wuhan University and The Seventh Hospital of Wuhan, China. Univariable and multivariable logistic regression models were used to determine the possible risk factors for disease progression. Moreover, cutoff values, the sensitivity and specificity of inflammatory parameters for disease progression were determined by MedCalc Version 19.2.0. Age (95%CI, 1.017 to 1.048; P

Details

Language :
English
ISSN :
21505594 and 21505608
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Virulence
Publication Type :
Academic Journal
Accession number :
edsdoj.50ee6d614fe1a96874fcbbb71bde
Document Type :
article
Full Text :
https://doi.org/10.1080/21505594.2020.1840108