4.7 Article

Prognostic value of baseline clinical and HRCT findings in 101 patients with severe COVID-19 in Wuhan, China

Journal

SCIENTIFIC REPORTS
Volume 10, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-020-74497-9

Keywords

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Funding

  1. Nation Science Foundation of China [82071921]
  2. Zhejiang University special scientific research fund for COVID-19 prevention and control
  3. Fundamental Research Funds for the Central Universities [2020kfyXGYJ019]

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The aim of this study was to assess the prognostic value of baseline clinical and high resolution CT (HRCT) findings in patients with severe COVID-19. In this retrospective, two-center study, we included two groups of inpatients with severe COVID-19 who had been discharged or died in Jin Yin-tan hospital and Wuhan union hospital between January 5, 2020, and February 22, 2020. Cases were confirmed by real-time polymerase chain reaction. Demographic, clinical, and laboratory data, and HRCT imaging were collected and compared between discharged and deceased patients. Univariable and multivariable logistic regression models were used to assess predictors of mortality risk in these patients. 101 patients were included in this study, of whom 66 were discharged and 35 died in the hospital. The mean age was 56.6 +/- 15.1 years and 67 (66.3%) were men. Of the 101 patients, hypertension (38, 37.6%), cardiovascular disease (21,20.8%), diabetes (18,17.8%), and chronic pulmonary disease (16,15.8%) were the most common coexisting conditions. The multivariable regression analysis showed older age (OR: 1.142, 95% CI 1.059-1.231, p<0.001), acute respiratory distress syndrome (ARDS) (OR: 10.142, 95% CI 1.611-63.853, p=0.014), reduced lymphocyte count (OR: 0.004, 95% CI 0.001-0.306, p=0.013), and elevated HRCT score (OR: 1.276, 95% CI 1.002-1.625, p=0.049) to be independent predictors of mortality risk on admission in severe COVID-19 patients. These findings may have important clinical implications for decision-making based on risk stratification of severe COVID-19 patients.

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