The value of clinical parameters in predicting the severity of COVID-19.
J Med Virol. 2020 May 21;:
Authors: Shang W, Dong J, Ren Y, Tian M, Li W, Hu J, Li Y
OBJECTIVE: To study the relationship between clinical indexes and the severity of coronavirus disease 2019 (COVID-19), and to explore its role in predicting the severity of COVID-19.
METHODS: Clinical data of 443 patients with COVID-19 admitted to our hospital were retrospectively analyzed, which were divided into non-severe group (n=304) and severe group (n=139) according to their condition. Clinical indicators were compared between different groups.
RESULTS: The differences in gender, age, the proportion of patients with combined heart disease, leukocyte, neutrophil-to-lymphocyte ratio (NLR), neutrophil, lymphocyte, platelet, D-dimer, C-reactive protein (CRP), procalcitonin, lactate dehydrogenase and albumin on admission between the two groups were statistically significant (p<0.05). Multivariate logistic regression analysis showed NLR and CRP were independent risk factors for severe COVID-19. Platelets were independent protective factors for severe COVID-19. Receiver Operating Characteristic (ROC) curve analysis demonstrated area under the curve (AUC) of NLR, platelet, CRP and combination was 0.737, 0.634, 0.734 and 0.774, respectively.
CONCLUSIONS: NLR, CRP and platelets can effectively assess the severity of COVID-19, among which NLR is the best predictor of severe COVID-19, and the combination of three clinical indicators can further predict severe COVID-19. This article is protected by copyright. All rights reserved.
PMID: 32436996 [PubMed - as supplied by publisher]