Author: Yabing Guo; Yingxia Liu; Jiatao Lu; Rong Fan; Fuchun Zhang; Xueru Yin; Zhihong Liu; Qinglang Zeng; Jing Yuan; Shufang Hu; Qiongya Wang; Baolin Liao; Mingxing Huang; Sichun Yin; Xilin Zhang; Rui Xin; Zhanzhou Lin; Changzheng Hu; Boliang Zhao; Ridong He; Minfeng Liang; Zheng Zhang; Li Liu; Jian Sun; Lu Tang; Lisi Deng; Jinyu Xia; Xiaoping Tang; Lei Liu; Jinlin Hou
Title: Development and validation of an early warning score (EWAS) for predicting clinical deterioration in patients with coronavirus disease 2019 Document date: 2020_4_21
ID: e2wevpi6_34
Snippet: Our study has several strengths, including the use of two independent cohorts with large sample sizes, which increase the reliability of the results. Nonetheless, the study also has certain limitations. First, the patients in the training cohort were enrolled from more than 30 hospitals in Guangdong Province, and their disease status, exposure history, and treatment strategy were relatively heterogeneous; however, this heterogeneity strengthens t.....
Document: Our study has several strengths, including the use of two independent cohorts with large sample sizes, which increase the reliability of the results. Nonetheless, the study also has certain limitations. First, the patients in the training cohort were enrolled from more than 30 hospitals in Guangdong Province, and their disease status, exposure history, and treatment strategy were relatively heterogeneous; however, this heterogeneity strengthens the reliability of our scoring methodology, which shows similar predictive ability in different patient populations. Secondly, the EWAS was based on artificially defined All rights reserved. No reuse allowed without permission.
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