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Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China
Author(s) -
Ye Yuan,
Chuan Sun,
Xiuchuan Tang,
Cheng Cheng,
Laurent Mombaerts,
Maolin Wang,
Tao Hu,
Chenyu Sun,
Yuqi Guo,
Xiuting Li,
Hui Xu,
Tongxin Ren,
Yang Xiao,
Yaru Xiao,
Hongling Zhu,
Honghan Wu,
Kezhi Li,
Chuming Chen,
Yingxia Liu,
Zhichao Liang,
Zhiguo Cao,
HaiTao Zhang,
Ioannis Ch. Paschaldis,
Quanying Liu,
Jorge Gonçalves,
Qiang Zhong,
Yan Li
Publication year - 2020
Publication title -
engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.376
H-Index - 45
eISSN - 2096-0026
pISSN - 2095-8099
DOI - 10.1016/j.eng.2020.10.013
Subject(s) - medicine , cohort , retrospective cohort study , covid-19 , framingham risk score , cohort study , pandemic , emergency medicine , severity of illness , mortality rate , risk assessment , intensive care medicine , disease , infectious disease (medical specialty) , computer security , computer science
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.

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