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Metabolic disturbances and inflammatory dysfunction predict severity of coronavirus disease 2019 (COVID-19): a retrospective study
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20042283
ABSTRACT
BackgroundThe 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. MethodsWe 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. ResultsAll 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. ConclusionsHypoproteinaemia, 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.
cc_by_nc
Texto completo:
1
Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Experimental_studies
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Observational_studies
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Prognostic_studies
Idioma:
En
Año:
2020
Tipo del documento:
Preprint