Abstract
INTRODUCTION: COVID-19 infection has a myriad of presentation. Rural India and other developing nations are relatively resource poor, not having access to modern specialized investigations. In this study, we tried to evaluate only biochemical parameters in predicting the severity of the infection. The aim of this study was to find a cost-effective means to predict the clinical course at the time of admission and thereby to reduce mortality and, if possible, morbidity by timely intervention. MATERIALS AND METHODS: All COVID-19-positive cases admitted at our hospital from March 21 to December 31, 2020, were recruited in this study. The same acted as sham control at recovery. RESULTS: We observed a significant difference in biochemical parameters at the time of admission and discharge, between mild/moderate disease and severe disease. We found slightly deranged liver function tests at admission, which becomes normal at the time of discharge. Urea, C-reactive protein (CRP), procalcitonin, lactate dehydrogenase, and ferritin concentrations in severe/critical patients were significantly higher than that in the mild/moderate group. Receiver operating characteristic curves were plotted to predict the severity on the basis of biochemical parameters independently, of the patients based on these values. CONCLUSION: We proposed cutoff values of certain biochemical parameters, which will help in judging the severity of the infection at admission. We developed a predictive model with a significant predictive capability for CRP and ferritin values, using normal available biochemical parameters, routinely done in resource-poor centers. Clinicians working in resource-poor situations will be benefitted by having an idea of the severity of the disease. Timely intervention will reduce mortality and severe morbidity.