Sex-adjusted approach to baseline variables demonstrated some improved predictive capabilities for disease severity and survival in patients with Coronavirus Disease 19

Introduction. The study was focused on comparing crude and sex-adjusted hazard ratio calculated by the baseline variables which may have contributed to the severity of the disease course and fatal outcomes in Coronavirus Disease-19 (COVID-19) patients. Method. The study enrolled 150 eligible adult patients with confirmed SARS-CoV-2 infection. There were 61 (40.7%) male patients, and 89 (59.3%) female patients. Baseline information of patients was collected from patient medical records and surveys that the patients had completed on admission to the hospital. Results. Considerable number of baseline variables stratified according to disease severity and outcomes showed different optimal cut-points (OCP) in men and women. Sex-adjusted baseline data categories such as age; BMI; systolic and diastolic blood pressure; peripheral RBC and platelet counts; haematocrit; percentage of neutrophils, lymphocytes, monocytes, and their ratio; percentage of eosinophils; titre of plasma IL-6, IL-8, IL-10, and IL-17; and CXCL10; and ratio of pro- and anti-inflammatory cytokines demonstrated significant impacts on the development of the severe stage and fatal outcomes by the mean hazard ratio in the Kaplan-Meier and Cox regression models. Conclusion. This study confirmed some improved predictive capabilities of the sex-adjusted approach in the analysis of the baseline predictive variables for severity and outcome of the COVID-19.