Publication

Abstract : Background: COVID-19 being a pandemic, differentiating severe from non-severe cases and predicting the disease progression by better use of the commonly available laboratory parameters would help reduce the mortality, morbidity, healthcare expenditure. At present, there is no single marker that can convincingly predict the severity of COVID in an individual. Several studies have demonstrated the usefulness of individual hemogram parameters in the prediction and risk stratification of COVID-19 infections, however there is a lack of consistency of data across these studies and there are no studies done hitherto in the south Indian population. Our study was done with the primary objective to analyze the effectiveness of admission hemogram parameters as a panel in differentiating severe from non-severe cases and in predicting the disease progression and with the secondary objective to look for the cut-off point of the variables to differentiate these groups. Materials And Methods: It is a single-centre prospective observational study. Independent sample t-test, Mann Whitney, Chi-square and ROC analysis were done using IBM SPSS software. Results: The mean age of subjects in the severe group was 63.5±14.55 and in the non-severe group was 48.6±16.61 (p <0.001). NLR, d-NLR, LMR, PLR, RDW and LCR in the severe group were 14.35±13.86, 6.3±4.84, 6.03±20.17, 263.98±246.27, 15.39 ±4.26 and 388.75±2074.63 and in the non-severe group were 3.5±2.92, 2.2±1.59, 3.15±1.76, 148.98±78.45, 13.88±1.77 and 636.04±1846.14 respectively, which were all statistically significant. Conclusion: We conclude by saying that severity of COVID-19 and the probability of ICU admission can be better predicted by using admission hemogram panel than individual hemogram parameters