期刊论文详细信息
Virulence
Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study
Xinyi Li1  Yanan Liu2  Yingying Wang2  Fuling Zhou2  Liang Shao2  Yufeng Shang2  Yalan Yu2  Muhammad Jamal3  Yi Luo4  Yunbao Pan4  Tao Liu5  Xinghuan Wang6  Colin K. He7 
[1] Department of Anesthesiology, Zhongnan Hospital of Wuhan University, Wuhan, Chin;Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, Chin;Department of Immunology, School of Basic Medical Science, Wuhan University, Wuhan, Chin;Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Chin;Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, Chin;Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Chin;Orient Health Care, Stego Tech LLC, King of Prussia, PA, US;
关键词: COVID-19;    serum amyloid A protein;    disease progression;    risk factor;    predictor;    biomarker;   
DOI  :  10.1080/21505594.2020.1840108
来源: Taylor & Francis
PDF
【 摘 要 】

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 < 0.001), serum amyloid A protein (SAA) (95%CI, 1.216 to 1.396; P < 0.001) and erythrocyte sedimentation rate (ESR) (95%CI, 1.006 to 1.045; P < 0.001) were likely the risk factors for the disease progression. The Area under the curve (AUC) of SAA for the progression of COVID-19 was 0.923, with the best predictive cutoff value of SAA of 12.4 mg/L, with a sensitivity of 83.9% and a specificity of 97.67%. SAA-containing parameters are novel promising ones for predicting disease progression in COVID-19.

【 授权许可】

CC BY   

【 预 览 】
附件列表
Files Size Format View
RO202111269548000ZK.pdf 5646KB PDF download
  文献评价指标  
  下载次数:8次 浏览次数:21次