Hematological and Biochemical Parameters at Admission as Predictors for Mortality in Patients with Moderate to Severe COVID-19

BACKGROUND: Timely diagnosis and effective use of available resources are urgent to avoid the loss of time, medical, and technological resources, particularly in COVID-19 pandemic. This study aimed to identify the most dominant predicting factor for mortality in moderate-severe COVID-19 patients. METHODS: This retrospective cohort study included a total of 253 patients diagnosed with moderate-severe COVID-19. The primary outcome measure was mortality during hospitalization. The receiver operating characteristic (ROC) curve was used to determine cut-off points. The data were categorized according to the cut-off points in ROC curve and analyzed using Chi-square and by binary logistic regression test to identify the independent predictors associated with mortality. RESULTS: The mean number of leukocytes (/µL), neutrophils (%), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), C-reactive protein (CRP, mg/L), and D-dimer (mg/L) in the non-survived group was significantly higher than those of the survived group. Meanwhile, the mean number of platelet count/µL, absolute lymphocyte count (ALC), in the non-survived group was significantly lower than those of the survived group. CRP level predicted mortality with a cut-off point of ≥8.41 mg/L, sensitivity of 98.1%, and specificity of 72.0% (P = .000). CONCLUSIONS: High leukocyte count, low platelet count, high NLR, high CRP level, and high D-dimer on admission predicted mortality of COVID-19 patients. In addition, CRP was found to be the most dominant predicting factor of mortality in moderate-severe COVID-19 patients.