Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio and Their Role as Predictors of Disease Severity of Coronavirus Disease 2019 (COVID-19).

Abstract

Context Due to the wide spectrum of clinical illness in coronavirus disease 2019 (COVID-19) patients, it is important to stratify patients into severe and nonsevere categories. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been evaluated rapidly by a few studies worldwide for its association with severe disease, but practically none have been conducted in the Indian population. This study was undertaken to examine the role of NLR and PLR in predicting severe disease in Indian patients. Objectives The objective was to study the association of NLR and PLR observed at the time of admission with maximum disease severity during hospitalization and to study their role in predicting disease severity. Material and Methods A total of 229 COVID-19 patients were admitted at the center during the study period. After applying inclusion and exclusion criteria, 191 patients were included in the study. The demographic, clinical, and laboratory (complete blood count, NLR, and PLR) data of all patients were obtained at the time of admission. Maximum disease severity of all patients was assessed during hospitalization. Statistical Analysis Chi-square and Mann–Whitney U tests were used to assess statistical significance. Receiver operating characteristic curve (ROC) was plotted for NLR and PLR to estimate the cutoff values and sensitivity and specificity using Youden’s index for predicting severe disease. Logistic regression analysis was used to estimate the odds ratios (OR) and 95% confidence intervals. Results Mean NLR and PLR were significantly higher in severe patients (NLR = 7.41; PLR = 204) compared with nonsevere patients (NLR = 3.30; PLR = 121). ROC analysis showed that NLR, in comparison to PLR, had a higher area under the curve (AUC) of 0.779, with a larger OR of 1.237 and cutoff of 4.1, and showed 69% sensitivity and 78% specificity in predicting severe disease. Cut off for PLR was 115.3, which showed 79% sensitivity and 62% specificity in predicting severe disease. Conclusion NLR and PLR, both showing acceptable AUCs, can be used as screening tools to predict disease severity. However, NLR was a better predictor of disease severity.