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

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

2020Virulence20 citationsDOIOpen Access PDF

Abstract

< 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.

Topics & Concepts

Internal medicineErythrocyte sedimentation rateMedicineRetrospective cohort studyLogistic regressionCoronavirus disease 2019 (COVID-19)BiomarkerDiseaseSerum amyloid AGastroenterologyProcalcitoninCutoffArea under the curveBiologyInflammationSepsisInfectious disease (medical specialty)BiochemistryQuantum mechanicsPhysicsCOVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 ResearchLong-Term Effects of COVID-19