Abstract
OBJECTIVE: Coronavirus disease 2019 is an ongoing disease with high morbidity and mortality. We aimed to investigate the relationship between demographics, lymphocytes, eosinophils, and the coronavirus disease 2019 severity at hospital admission. MATERIAL AND METHODS: A retrospective, observational cross-sectional study was carried out with 5828 coronavirus disease 2019 patients between March 11, 2020, and November 30, 2020. Patients were divided into 3 groups according to where they were followed up as an indicator of disease severity, namely outpatients, inpatients, and critically ill patients. The patients' demographics and hemogram values on admission were recorded. The predictive accuracies of lymphocyte count, lymphocyte percentage, eosinophil count, and eosinophil percentage for predicting severity were determined using receiver operating characteristic curves. Logistic regression analysis was used to predict intensive care unit demand according to lymphocyte and eosinophil values. RESULTS: Of the 5828 coronavirus disease 2019 patients, 4050 were followed up as outpatients, 1581 were hospitalized in a ward, and 197 were hospitalized in the intensive care unit. Lymphocyte count and lymphocyte percentage were significantly different between the groups, but the difference for eosinophil count and eosinophil percentage was not significant as it was for lymphocytes. Cutoff values for lymphocyte count (1.0 × 109 /L), lymphocyte percentage (22%), eosinophil count (0.052 × 109 /L), and eosinophil percentage (0.08%) were found to indicate a high risk for intensive care unit admission. Coronavirus disease 2019 patients >55 years of age, with a lymphocyte count <1.0 × 109 /L, a lymphocyte percentage <22%, and an eosinophil percentage <0.08% had a 2-fold higher risk of requiring intensive care unit management. CONCLUSION: Lymphocyte counts and percentages are quick and reliable biomarkers for predicting coronavirus disease 2019 severity and may guide physicians for proper management earlier.