• Medicine · Jun 2021

    Multicenter Study Observational Study

    Multicenter analysis and a rapid screening model to predict early novel coronavirus pneumonia using a random forest algorithm.

    • Suxia Bao, Hong-Yi Pan, Wei Zheng, Qing-Qing Wu, Yi-Ning Dai, Nan-Nan Sun, Tian-Chen Hui, Wen-Hao Wu, Yi-Cheng Huang, Guo-Bo Chen, Qiao-Qiao Yin, Li-Juan Wu, Rong Yan, Ming-Shan Wang, Mei-Juan Chen, Jia-Jie Zhang, Li-Xia Yu, Ji-Chan Shi, Nian Fang, Yue-Fei Shen, Xin-Sheng Xie, Chun-Lian Ma, Wan-Jun Yu, Wen-Hui Tu, Bin Ju, Hai-Jun Huang, Yong-Xi Tong, and Hong-Ying Pan.
    • Department of Infectious Diseases, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014.
    • Medicine (Baltimore). 2021 Jun 18; 100 (24): e26279e26279.

    AbstractEarly determination of coronavirus disease 2019 (COVID-19) pneumonia from numerous suspected cases is critical for the early isolation and treatment of patients.The purpose of the study was to develop and validate a rapid screening model to predict early COVID-19 pneumonia from suspected cases using a random forest algorithm in China.A total of 914 initially suspected COVID-19 pneumonia in multiple centers were prospectively included. The computer-assisted embedding method was used to screen the variables. The random forest algorithm was adopted to build a rapid screening model based on the training set. The screening model was evaluated by the confusion matrix and receiver operating characteristic (ROC) analysis in the validation.The rapid screening model was set up based on 4 epidemiological features, 3 clinical manifestations, decreased white blood cell count and lymphocytes, and imaging changes on chest X-ray or computed tomography. The area under the ROC curve was 0.956, and the model had a sensitivity of 83.82% and a specificity of 89.57%. The confusion matrix revealed that the prospective screening model had an accuracy of 87.0% for predicting early COVID-19 pneumonia.Here, we developed and validated a rapid screening model that could predict early COVID-19 pneumonia with high sensitivity and specificity. The use of this model to screen for COVID-19 pneumonia have epidemiological and clinical significance.Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.

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