Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China

• Published in: Engineering (Beijing, China) Vol. 8; no. 1; pp. 116 - 121
• Main Authors: Yuan, Ye, Sun, Chuan, Tang, Xiuchuan, Cheng, Cheng, Mombaerts, Laurent, Wang, Maolin, Hu, Tao, Sun, Chenyu, Guo, Yuqi, Li, Xiuting, Xu, Hui, Ren, Tongxin, Xiao, Yang, Xiao, Yaru, Zhu, Hongling, Wu, Honghan, Li, Kezhi, Chen, Chuming, Liu, Yingxia, Liang, Zhichao, Cao, Zhiguo, Zhang, Hai-Tao, Paschaldis, Ioannis Ch, Liu, Quanying, Goncalves, Jorge, Zhong, Qiang, Yan, Li
• Format: Journal Article
• Language: English
• Published: China Elsevier Ltd 01-01-2022; School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China%School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China%Luxembourg Centre for Systems Biomedicine,University of Luxembourg,Belval L-4367,Luxembourg%Department of Emergency,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China%AMITA Health Saint Joseph Hospital Chicago,Chicago,IL 60657,USA%Department of Anesthesiology,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China%Huazhong University of Science and Technology-Wuxi Research Institute,Wuxi 214174,China%Division of Cardiology,Department of Internal Medicine,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China%Institute of Health Informatics,University College London,London NW1 2DA,UK%Department of Biomedical Engineering,Southern University of Science and Technology,Shenzhen 518055,China%Department of Infectious Diseases,Shenzhen Key Laboratory of Pathogenic Microbiology and Immunology,National Clinical Research Center for Infectious Disease,The Third People's Hospital of Shenzhen(Second Hospital Affiliated with the Southern University of Science and Technology),Shenzhen 518055,China%Department of Electrical and Computer Engineering&Division of Systems Engineering&Department of Biomedical Engineering,Boston University,Boston,MA 02215,USA%Luxembourg Centre for Systems Biomedicine,University of Luxembourg,Belval L-4367,Luxembourg; Department of Plant Sciences,University of Cambridge,Cambridge CB2 1TN,UK; THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company; Elsevier
• Subjects: COVID-19; Mortality risk prediction; Research Coronavirus Disease 2019; Risk score; COVID-19; Mortality risk prediction; Risk score
• ISSN: 2095-8099; 2096-0026
• DOI: 10.1016/j.eng.2020.10.013

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital, Wuhan, China (validation cohort 1) and 432 inpatients from The Third People’s Hospital of Shenzhen, Shenzhen, China (validation cohort 2). The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 d in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan–Meier score shows that patients can be clearly differentiated upon admission as low, intermediate, or high risk, with an area under the curve (AUC) score of 0.9551. In summary, a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); it has also been validated in independent cohorts.