Role of Hemogram-Derived Ratios and Systemic-Immune Inflammation Index in Prediction of COVID-19 Progression in Egyptian Patients

Background: Early detection of COVID-19 patients with potentially severe disease is crucial for predicting the disease's course and prioritizing medical resources, lowering overall disease mortality. Objectives: To explore the role of hemogram-derived ratios and systemic-immune inflammation index (SII), in addition to C-reactive protein (CRP), in predicting COVID-19 severity and prognosis. Methods: In this retrospective study, data were collected from the medical records of 425 COVID-19 patients. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and SII, together with the CRP, were investigated and compared. Results: NLR, PLR, SII, and CRP increased significantly in severe cases and with ICU admission (p [≤] 0.001). But, in non-survivors only NLR and CRP were significantly elevated (p < 0.05). By interpreting area under the receiver operating characteristic curve (ROC-AUC), CRP and NLR were better predictors of disease severity (AUC: 0.7 for both), the need for ICU admission (AUC: 0.763 and 0.727, respectively) and in-hospital mortality (AUC: 0.812 and 0.75, respectively). SII was significantly associated with the risk of severe disease development (odds ratio (OR): 3.143; 95% confidence interval (CI): 1.101-8.976); CRP (OR: 2.902; CI95%: 1.342-6.273) and NLR (OR: 2.662; CI95%, 1.072-6.611) were significantly associated with ICU admission risk; and only CRP was significantly associated with in-hospital mortality risk (OR: 3.988; CI95%: 1.460-10.892). Conclusions: Values of CRP, SII, and NLR at the time of hospital admission could be independent prognostic biomarkers to predict COVID-19 progression. The integration of CRP, SII, and NLR into prognostic nomograms may lead to improved prediction.