Predictive Role of Biomarkers in COVID-19 Mortality

Abstract

Background The coronavirus disease 2019 (COVID-19) pandemic has resulted in high mortality among patients in critical intensive care units. Hence, identifying mortality markers in the follow-up and treatment of these patients is essential. This study aimed to evaluate the relationships between mortality rates in patients with COVID-19 and the neutrophil/lymphocyte ratio (NLR), derived NLR (dNLR), platelet/lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), systemic inflammation response index (SII), and systemic inflammatory response index (SIRI). Methodology In this study, we assessed 466 critically ill patients diagnosed with COVID-19 in the adult intensive care unit of Kastamonu Training and Research Hospital. Age, gender, and comorbidities were recorded at the time of admission along with NLR, dNLR, MLR, PLR, SII, and SIRI values from hemogram data. Acute Physiology and Chronic Health Evaluation II (APACHE II) scores and mortality rates over 28 days were recorded. Patients were divided into survival (n = 128) and non-survival (n = 338) groups according to 28-day mortality. Results A statistically significant difference was found between leukocyte, neutrophil, dNLR, APACHE II, and SIRI parameters between the surviving and non-surviving groups. A logistic regression analysis of independent variables of 28-day mortality identified significant associations between dNLR (p = 0.002) and APACHE II score (p < 0.001) and 28-day mortality. Conclusions Inflammatory biomarkers and APACHE II score appear to be good predictive values for mortality in COVID-19 infection. The dNLR value was more effective than other biomarkers in estimating mortality due to COVID-19. In our study, the cut-off value for dNLR was 3.64.