RESUMO
BACKGROUND: Biomarkers that are cost-effective and accurate for predicting severe coronavirus disease 2019 (COVID-19) are urgently needed. We would like to assess the role of various inflammatory biomarkers on admission as disease severity predictors and determine the optimal cut-off of the neutrophile-to-lymphocyte ratio (NLR) for predicting severe COVID-19. METHODS: We conducted a cross-sectional study in six hospitals in Bali and recruited real-time PCR-confirmed COVID-19 patients aged >18 y from June to August 2020. Data collection included each patient's demographic, clinical, disease severity and hematological data. Multivariate and receiver operating characteristic curve analyses were performed. RESULTS: A total of 95 Indonesian COVID-19 patients were included. The highest NLR among severe patients was 11.5±6.2, followed by the non-severe group at 3.3±2.8. The lowest NLR was found in the asymptomatic group (1.9±1.1). The CD4+ and CD8+ values were lowest in the critical and severe disease groups. The area under the curve of NLR was 0.959. Therefore, the optimal NLR cut-off value for predicting severe COVID-19 was ≥3.55, with sensitivity at 90.9% and a specificity of 16.7%. CONCLUSIONS: Lower CD4+ and CD8+ and higher NLR values on admission are reliable predictors of severe COVID-19 among Indonesian people. NLR cut-off ≥3.55 is the optimal value for predicting severe COVID-19.
