Neutrophil-to-Lymphocyte Ratio as an Early Predictor of Severe COVID-19: A Retrospective Study

Abstract

Introduction: The ongoing pandemic Coronavirus disease-2019 (COVID-19) is posing a great challenge to the medical fraternity across the world. The disease has an unpredictable complex clinical course. Despite intermittent lockdowns of varying lengths and several containment procedures including personal behavioural changes observed, the virus persists with continuing mutations and surges in infection being reported in many countries. With existing limited knowledge about post infection immunity and efficacy of the newer vaccines currently, there is a need to identify risk factors and early predictors of severe COVID19 that could help timely risk stratification and prompt initiation of appropriate treatment to reduce morbidity and mortality. Aim: To identify the risk factors associated with severe COVID19 and to analyse the significance of neutrophil-to-lymphocyte ratio (NLR) in detecting severe COVID-19 early. Materials and Methods: This was a retrospective observational study conducted in Government Medical College Hospital, Omandurar Government Estate, Chennai, a tertiary care hospital in Tamil Nadu, India from July 2020-September 2020. The study included 300 COVID-19 patients admitted during the study time period. The clinical, demographic and laboratory profile were compared between the patients with severe and non severe disease to analyse the role of baseline NLR and other risk factors associated with severe COVID-19. Results: Majority of the patients were males (69%), with median age of 55 years. Older age and co-morbidities, diabetes mellitus and hypertension showed increased association with severe COVID-19. Complete Blood Count (CBC) examination at admission demonstrated significant elevation of total count, neutrophil count, NLR and reduction of lymphocyte count, platelet count in patients with severe and critical illness. Logistic regression identified NLR at admission, age, co-existing diabetes mellitus, serum ferritin and Computed Tomography (CT) chest lung involvement as independent risk factors for severe COVID-19. NLR had the largest Area Under the Curve (AUC) of 0.901; 95% Confidence Interval (CI), 0.867-0.935 followed by CT chest lung involvement with AUC of 0.887; 95% CI, 0.851-0.923 and serum ferritin with AUC of 0.818; 95% CI, 0.762-0.874 in Receiver Operating Characteristic (ROC) curve analysis. Conclusion: This study demonstrated NLR at admission as an early predictor of severe COVID-19. Increased baseline NLR, older age, co-existing diabetes mellitus, elevated serum ferritin and higher CT chest lung involvement percentage were independent risk factors associated with severe and critical illness.

Keywords

• complete blood count
• coronavirus disease-2019
• pandemic
• risk factors
• severe acute respiratory syndrome coronavirus-2