Differential Diagnostic Utility of Clinical Laboratory Data in Patients with Severe and Non-severe COVID-19

Abstract

Background: Coronavirus disease 2019 (COVID-19) is a coronavirus outbreak caused by severe acute respiratory syndrome coron-avirus 2 infection. Objectives: This study aimed to investigate the relationship between laboratory variables and COVID-19 severity. Methods: A total of 731 confirmed cases were included in this study. Based on the clinical course of the disease, the patients were divided into non-severe (n = 599) and severe (n = 132) groups. The area under the curve was estimated for each of the significant predictive factors by the receiver operating characteristic curve. Youden’s index was used to determine the optimal cut-off points to predict the severity of COVID-19. Results: Out of 731 patients, 407 (55.56%) cases were male. The mean age value and age range of the patients were 58.37 and 1-98 years, respectively. The age (OR = 1.03, 95% CI: 1.02-1.05), international normalized ratio (INR) (OR = 2.09, 95% CI: 1.11-3.96), lactate dehydrogenase (LDH) (OR = 1.003, 95% CI: 1.001-1.1.003), and neutrophil/lymphocyte ratio (NLR) (OR = 1.08, 95% CI: 1.02-1.14) were associated with the severity of COVID-19 in the multivariate analyses. The areas under the curve of LDH, NLR, and INR for the diagnosis of disease severity were 0.76, 0.69, and 0.62, respectively. Conclusions: The results of this study revealed that LDH, NLR, and INR could help to discriminate between non-severe and severe COVID-19 cases. Therefore, clinicians can use these variables to improve therapeutic effects and reduce disease severity.