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《工程(英文)》 >> 2022年 第8卷 第1期 doi: 10.1016/j.eng.2020.10.013

COVID-19住院患者预后风险评分系统的开发和验证——一项多中心回顾性研究

a School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
b School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
c Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, L-4367, Luxembourg
d Department of Plant Sciences, University of Cambridge, Cambridge CB2 1TN, UK
e Department of Emergency, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
f AMITA Health Saint Joseph Hospital Chicago, Chicago, IL 60657, USA
g Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
h Huazhong University of Science and Technology-Wuxi Research Institute, Wuxi 214000, China
i Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
j Institute of Health Informatics, University College London, London WC1E 6BT, UK
k Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, China
l 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
m Department of Electrical and Computer Engineering & Division of Systems Engineering & Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA

收稿日期: 2020-08-11 修回日期: 2020-09-04 录用日期: 2020-10-11 发布日期: 2020-11-28

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摘要

新冠病毒肺炎(COVID-19)已成为世界范围内的流行疾病。COVID-19 住院患者的死亡率较高,促使研究人员研发方便实用的方法,以便临床医生及时发现高危患者。在本研究中,我们利用武汉同济医院1479 名住院患者的临床数据(用于模型开发的群体)进行了风险评分,并利用其他两个中心的数据进行了外部验证:武汉金银潭医院的141 名住院患者(验证群体1)和深圳第三人民医院的432 名住院患者(验证群体2)。本文提出的风险评分方法是基于常规血液样本中现成的三个生物标记,能够快捷地转换为死亡概率,并且可提前12 天以上预测单个患者的死亡率,且在所有群体中准确率均超过90%。此外,Kaplan-Meier 分数表明,本方法在患者入院时即可判别低、中、高风险,并且受试者工作特征(ROC)曲线下方的面积大小(area under curve, AUC)达到0.9551。综上所述,一种简单的风险评分方法已在预测感染严重急性呼吸综合征冠状病毒2(SARS-CoV-2)患者的死亡概率任务中得到验证,同时也在多中心数据中进行了验证。

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