Identification and Prediction of Novel Clinical Phenotypes for Intensive Care Patients With SARS-CoV-2 Pneumonia: An Observational Cohort Study

Frontiers in Medicine

Jinghui Yang¹  Jun Wang²  Hui Chen²  Lei Xu³  Baodi Sun⁴  Zhu Zhu⁵  Yongsheng Li⁶  Shu Lu⁷  Jiangtao Yin⁸  Jun Gu⁹  Xiangrong Shao^1,10  Li Zhang^1,11  Xuesong Chen^1,12  Nan Su^1,13 

[1] Department of Critical Care Medicine, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China;Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, China;Department of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China;Department of Emergency, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China;Department of General Surgery, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou, China;Department of Intensive Care Medicine, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China;Department of Intensive Care Unit, Affiliated Hospital of Nantong University, Nantong, China;Department of Intensive Care Unit, The Affiliated Hospital of Jiangsu University, Zhenjiang, China;Department of Respiratory Medicine, Affiliated Hospital of Nantong University, Nantong, China;Department of Respiratory Medicine, The Affliliation Hospital of Yangzhou University, Yangzhou, China;Department of Respiratory Medicine, Zhongda Hospital Southeast University, Nanjing, China;Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China;Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, China;

关键词: COVID-19;    phenotypes;    machine learning;    intensive care unit;    28-day mortality;   

DOI  :  10.3389/fmed.2021.681336

来源: Frontiers

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