The predictive and prognostic role of hematologic and biochemical parameters in the emergency department among coronavirus disease 2019 patients

Coronavirus disease 2019 (COVID-19) had caused a worldwide pandemic with public health emergencies since 2020. For the symptomatic patients, high mortality rate was observed if without timely and optimized management. In this study, we aimed to investigate the predictive and prognostic roles of hematologic and biochemical parameters obtained in the emergency department (ED) for COVID-19 patients. We conducted a retrospective study in a dedicated COVID-19 medical center, recruiting a total of 228 COVID-19 patients with 86 severe and 142 non-severe cases. Both the hematologic and biochemical parameters obtained in the ED upon arrival were analyzed to evaluate the association of the biomarkers with disease severity and prognosis among COVID-19 patients. Among these parameters, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), ferritin, and D-dimer were significantly higher in the severe group than the non-severe one, whereas the platelet count and lymphocyte-to-monocyte ratio were significantly lower. Receiver operating characteristic curve analysis revealed that the areas under curve of CRP, PCT, LDH, ferritin, D-dimer, and NLR for differentiating the severity of COVID-19 were 0.713, 0.755, 0.763, 0.741, 0.733, and 0.683, respectively, whereas the areas under curve of CRP, PCT, LDH, ferritin, D-dimer, and NLR for differentiating the mortality of COVID-19 were 0.678, 0.744, 0.680, 0.676, 0.755, and 0.572, respectively. Logistic regression analysis revealed that CRP, PCT, LDH, ferritin, D-dimer, and NLR were independent indicators for prediction of severe COVID-19, and LDH and ferritin were independent factors associated with the mortality in COVID-19. In conclusion, higher CRP, PCT, LDH, ferritin, D-dimer, and NLR were associated with severe COVID-19, whereas higher LDH and ferritin were associated with the mortality in COVID-19. These findings could help early risk stratification in the ED and contribute to optimized patient management.