Biomarkers for predicting COVID-19 mortality: A study at Sulianti Saroso Infectious Disease Hospital, Indonesia.

The high transmissibility and mortality rates of the COVID-19 pandemic pose significant challenges. Patients can deteriorate rapidly, making it crucial to identify laboratory biomarkers for high-risk individuals. The aim of this study was to evaluate the predictive value of various laboratory parameters, including C-reactive protein (CRP), D-dimer, ferritin, neutrophil-to-lymphocyte ratio (NLR), prothrombin time (PT), and procalcitonin (PCT), in predicting COVID-19 mortality. A retrospective cohort study was conducted at Sulianti Saroso Infectious Disease Hospital, where COVID-19 patients were categorized into survivors and non-survivors. The Mann-Whitney test was used to assess group differences, while receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of each biomarker, with Youden's index (J) determining optimal cut-off values. Kaplan-Meier analysis was used to compare median survival times, and Cox regression assessed hazard rates and the relationship between biomarkers and mortality. A total of 1,598 patients were analyzed, the majority of whom were admitted with oxygen saturation levels >95% and classified as having mild to moderate disease severity. Among them, 216 patients died, resulting in a mortality rate of 13.52%. Significant variations in mortality rates were observed along the survival functions for NLR, ferritin, D-dimer, CRP, and PCT (<0.001). The survival curves for these biomarkers demonstrated distinct trends across tertiles over time. Among hematological markers, NLR was significantly associated with mortality (<0.001), with a 1.5-2.2% increased risk per unit increase. Biochemical markers (complete blood count) proved to be more effective than hematological parameters (NLR, ferritin, PT, D-dimer, CRP, PCT) when evaluating individual prognostic performance. Bivariate analysis of CRP, D-dimer, ferritin, NLR, PT, and PCT between survivors and non-survivors showed significant differences. Notably, NLR and PCT were highly relevant for predicting disease prognosis and mortality, with sensitivity and specificity values exceeding 80%.