The value of clinical parameters in predicting the severity of COVID-19

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. Clinical data of 443 patients with COVID-19 admitted to our hospital were retrospectively analyzed, which were divided into nonsevere group (n = 304) and severe group (n = 139) according to their condition. Clinical indicators were compared between different groups. The differences in sex, 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 < .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. The receiver operating characteristic (ROC) curve analysis demonstrated area under the curve of NLR, platelet, CRP, and combination was 0.737, 0.634, 0.734, and 0.774, respectively. 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.