Utility of biomarkers in predicting the severity and mortality of coronavirus disease 2019 infection: A retrospective observational study

Context: The clinical course of Coronavirus Disease 2019 (COVID-19) infection is variable and subjective. Hence, there is a dire need for objective interpretation of severity. The utilization of biomarkers categorizes these patients into nonsevere, severe, or critical categories. Aim: This study aims to assess the role of different biomarkers in predicting the severity and mortality of COVID 19. Materials and Methods: Case records of 247 patients of a designated COVID center in Kolhapur, Maharashtra, India, were included in this observational study. Biomarkers such as total leukocyte count, C-reactive protein, lactate dehydrogenase, D-Dimer, interleukin-6 (IL-6), procalcitonin, and serum ferritin were studied in different categories of severity of the disease. Results: The median serum ferritin levels among nonsevere cases, severe, and critical cases were 187.95 ng/mL (interquartile range [IQR] = 93.05 ng/mL to 382.50 ng/mL), 230 ng/mL (156 ng/mL to 670 ng/mL), and 412.33 ng/mL (234 ng/mL to 689 ng/mL), respectively and this difference was statistically significant (P < 0.001). The average values of IL-6 were significantly higher (P < 0.001) among the patients who died (19.12 pg/mL) when compared to those which were alive (3.74 pg/mL). Based on the receiver operating characteristic analysis, the interpretation of the severity of the disease was excellent through the evaluation of levels of serum ferritin (Area under curve = 0.755 [95% confidence interval = 0.635–0.875; P = 0.001]). Conclusions: Serum ferritin among the biomarker panel studied was the best test that predicted the severity of COVID-19 infection. The IL-6 levels were significantly higher among the patient who succumbed when compared to those who survived the disease.