Selected article for: "early stage and model prediction"
Author: Lijiao Zeng; Jialu Li; Mingfeng Liao; Rui Hua; Pilai Huang; Mingxia Zhang; Youlong Zhang; Qinlang Shi; Zhaohua Xia; Xinzhong Ning; Dandan Liu; Jiu Mo; Ziyuan Zhou; Zigang Li; Yu Fu; Yuhui Liao; Jing Yuan; Lifei Wang; Qing He; Lei Liu; Kun Qiao
Title: Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study
  • Document date: 2020_3_30
    • ID: 8n3q30hy_35
    Snippet: The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.25.20043166 doi: medRxiv preprint although not ideal, difference between the two groups upon admission. Consistent with previous studies 2, 5, 6, 14, 15 , the severe group of this cohort demonstrated, at an early stage, a substantial increase in inflammatory factors such as C-reactive protein and interleukin-6, and dysfunction of coagulat.....
    Document: The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.25.20043166 doi: medRxiv preprint although not ideal, difference between the two groups upon admission. Consistent with previous studies 2, 5, 6, 14, 15 , the severe group of this cohort demonstrated, at an early stage, a substantial increase in inflammatory factors such as C-reactive protein and interleukin-6, and dysfunction of coagulation. Incorporating laboratory biomarkers tested at an early stage can also significantly improve risk prediction performance as compared to the best model without considering them (mean AUC = 0.884 versus 0.813).

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