单位：[1]Department of Orthopedics, General Hospital of Chinese PLA Central Theater Command, Wuhan 430070, China.[2]Southern Medical University, Guangzhou 510515, China.[3]Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, Institute of Environment and Health, Jianghan University, Wuhan 430056, China.[4]Department of Scientific Research Training, General Hospital of Chinese PLA Central Theater Command, Wuhan 430070, China.[5]Department of Neurology, General Hospital of Chinese PLA Central Theater Command, Wuhan 430070, China.[6]Department of Radiology, General Hospital of Chinese PLA Central Theater Command, Wuhan 430070, China.[7]State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.[8]Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China‑Japan Friendship Hospital. Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing 100029, China.
Early classification and risk assessment for COVID-19 patients are critical for improving their terminal prognosis, and preventing the patients deteriorate into severe or critical situation. We performed a retrospective study on 222 COVID-19 patients in Wuhan treated between January 23rd and February 28th, 2020. A decision tree algorithm has been established including multiple factor logistic for cluster analyses that were performed to assess the predictive value of presumptive clinical diagnosis and features including characteristic signs and symptoms of COVID-19 patients. Therapeutic efficacy was evaluated by adopting Kaplan-Meier survival curve analysis and cox risk regression. The 222 patients were then clustered into two groups: cluster I (common type) and cluster II (high-risk type). High-risk cases can be judged from their clinical characteristics, including: age>50 years, chest CT images with multiple ground glass or wetting shadows, etc. Based on the classification analysis and risk factor analysis, a decision tree algorithm and management flow chart were established, which can help well recognize individuals who needs hospitalization and improve the clinical prognosis of the COVID-19 patients. Our risk factor analysis and management process suggestions are useful for improving the overall clinical prognosis and optimize the utilization of public health resources during treatment of COVID-19 patients.
基金：
National Natural Science FoundationNational Natural Science Foundation of China (NSFC) [21906069]; Foundation from Health Commission of Hubei Province Scientific Research Project [WJ2019H110]
第一作者单位：[1]Department of Orthopedics, General Hospital of Chinese PLA Central Theater Command, Wuhan 430070, China.[2]Southern Medical University, Guangzhou 510515, China.
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推荐引用方式(GB/T 7714)：
Zhi Li,Ling Wang,Lv‑shuai Huang,et al.Efficient management strategy of COVID-19 patients based on cluster analysis and clinical decision tree classification[J].SCIENTIFIC REPORTS.2021,11(1):doi:10.1038/s41598-021-89187-3.
APA：
Zhi Li,Ling Wang,Lv‑shuai Huang,Meng Zhang,Xianhua Cai...&Guoliang Liu.(2021).Efficient management strategy of COVID-19 patients based on cluster analysis and clinical decision tree classification.SCIENTIFIC REPORTS,11,(1)
MLA：
Zhi Li,et al."Efficient management strategy of COVID-19 patients based on cluster analysis and clinical decision tree classification".SCIENTIFIC REPORTS 11..1(2021)
