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      Metabolic disturbances and inflammatory dysfunction predict severity of coronavirus disease 2019 (COVID-19): a retrospective study

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      medRxiv

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          Abstract

          Background: The coronavirus disease 2019 (COVID-19) is spreading worldwide with 16,558 deaths till date. Serum albumin, high-density lipoprotein (HDL-C), and C-reactive protein have been known to be associated with the severity and mortality of community-acquired pneumonia. However, the characteristics and role of metabolic and inflammatory indicators in COVID-19 is unclear. Methods: We included 97 hospitalized patients with laboratory-confirmed COVID-19. Epidemiological, clinical, and laboratory indices; radiological features; and treatment were analysed. The differences in the clinical and laboratory parameters between mild and severe COVID-19 patients and the role of these indicators in severity prediction of COVID-19 were investigated. Results: All were Wuhan residents with contact with confirmed COVID-19 cases. The median age was 39 years (IQR: 30-59). The most common presenting symptoms were fever (58.8%), cough (55.7%), and fatigue (33%). Other features were lymphopenia, impaired fasting glucose, hypoproteinaemia, hypoalbuminemia, low high-density lipoproteinemia. Decrease in lymphocyte count, serum total protein, serum albumin, high-density lipoprotein cholesterol (HDL-C), ApoA1, CD3+T%, and CD8+T% were found to be valuable in predicting the transition of COVID-19 from mild to severe illness. Chest computed tomography (CT) images showed that the absorption of bilateral lung lesions synchronized with the recovery of metabolic and inflammatory indicators. Conclusions: Hypoproteinaemia, hypoalbuminemia, low high-density lipoproteinemia, and decreased ApoA1, CD3+T%, and CD8+T% could predict severity of COVID-19. Lymphocyte count, total serum protein, and HDL-C may be potentially useful for the evaluation of COVID-19.

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          Contributors
          Journal
          medRxiv
          March 26 2020
          Article
          10.1101/2020.03.24.20042283
          6acfbadf-c81e-42cf-98b7-f1277e970bfd
          © 2020
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