单位：[1]Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning Province, China[2]Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University,Shenyang, Liaoning Province, China中国医科大学附属盛京医院[3]Department of Respiratory and Critical Care Medicine, National Clinical Research Center of Respiratory Disease, TongjiHospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China[4]Department of Respiratory Disease, Second Affiliated Hospital, Zhejiang University College of Medicine,Hangzhou, Zhejiang Province, China[5]Department of Pulmonary and Critical Care Medicine, Second Xiangya Hospital, Central South University,Changsha, Hunan Province, China[6]Department of Emergency Medicine, Shengjing Hospital of China Medical University, Shenyang, LiaoningProvince, China中国医科大学附属盛京医院[7]Department of Pulmonary and Critical Care Medicine, First Hospital of China Medical University, Shenyang, LiaoningProvince, China[8]Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, HuazhongUniversity of Science and Technology, Wuhan, Hubei Province, China华中科技大学同济医学院附属协和医院[9]Department of Respiratory Disease, The Second Affiliated Hospital of Baotou Medical College, Baotou, China内蒙古科技大学包头医学院[10]Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan FriendshipHospital, Beijing, China[11]National Center for Respiratory Medicine, Beijing, China[12]Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Beijing, China[13]National Clinical Research Center for Respiratory Diseases, Beijing, China[14]Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Peking UnionMedical College, Beijing, China
Background and Objectives: The majority of coronavirus disease 2019 (COVID-19) cases are nonsevere, but severe cases have high mortality and need early detection and treatment. We aimed to develop a nomogram to predict the disease progression of nonsevere COVID-19 based on simple data that can be easily obtained even in primary medical institutions. Methods: In this retrospective, multicenter cohort study, we extracted data from initial simple medical evaluations of 495 COVID-19 patients randomized (2:1) into a development cohort and a validation cohort. The progression of nonsevere COVID-19 was recorded as the primary outcome. We built a nomogram with the development cohort and tested its performance in the validation cohort. Results: The nomogram was developed with the nine factors included in the final model. The area under the curve (AUC) of the nomogram scoring system for predicting the progression of nonsevere COVID-19 into severe COVID-19 was 0.875 and 0.821 in the development cohort and validation cohort, respectively. The nomogram achieved a good concordance index for predicting the progression of nonsevere COVID-19 cases in the development and validation cohorts (concordance index of 0.875 in the development cohort and 0.821 in the validation cohort) and had well-fitted calibration curves showing good agreement between the estimates and the actual endpoint events. Conclusions: The proposed nomogram built with a simplified index might help to predict the progression of nonsevere COVID-19; thus, COVID-19 with a high risk of disease progression could be identified in time, allowing an appropriate therapeutic choice according to the potential disease severity.
基金：
China Medical UniversityChina Medical University [02]
第一作者单位：[1]Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning Province, China
共同第一作者：
通讯作者：
通讯机构：[9]Department of Respiratory Disease, The Second Affiliated Hospital of Baotou Medical College, Baotou, China[10]Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan FriendshipHospital, Beijing, China[11]National Center for Respiratory Medicine, Beijing, China[12]Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Beijing, China[13]National Clinical Research Center for Respiratory Diseases, Beijing, China[14]Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Peking UnionMedical College, Beijing, China[*1]Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of China Medical University, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China[*2]National Center for Respiratory Medicine, Beijing, China[*3]National Clinical Research Center for Respiratory Diseases, Beijing, China[*4]Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.[*5]Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Beijing, China
推荐引用方式(GB/T 7714)：
Li Xue-lian,Wu Cen,Xie Jun-gang,et al.Development and validation of a nomogram for predicting the disease progression of nonsevere coronavirus disease 2019[J].JOURNAL of TRANSLATIONAL INTERNAL MEDICINE.2021,9(2):131-142.doi:10.2478/jtim-2021-0030.
APA：
Li, Xue-lian,Wu, Cen,Xie, Jun-gang,Zhang, Bin,Kui, Xiao...&Hou, Gang.(2021).Development and validation of a nomogram for predicting the disease progression of nonsevere coronavirus disease 2019.JOURNAL of TRANSLATIONAL INTERNAL MEDICINE,9,(2)
MLA：
Li, Xue-lian,et al."Development and validation of a nomogram for predicting the disease progression of nonsevere coronavirus disease 2019".JOURNAL of TRANSLATIONAL INTERNAL MEDICINE 9..2(2021):131-142
