Prognostic Performance of the Pan-Immune-Inflammation Value in Critically Ill Patients with Crimean-Congo Hemorrhagic Fever

Objective: The Pan-Immune-Inflammation Value (PIV) has recently emerged as a promising inflammation-based biomarker in several malignant and inflammatory diseases. However, its prognostic significance in Crimean-Congo hemorrhagic fever (CCHF) has not previously been investigated. This study evaluated the prognostic value of admission PIV in critically ill patients with CCHF and compared its performance with established disease-specific severity scores and other inflammatory biomarkers.Methods: This retrospective observational cohort study included 110 adult patients with laboratory-confirmed CCHF admitted to the intensive care unit of a tertiary referral hospital between 2014 and 2025. Admission PIV, Systemic Immune-Inflammation Index (SII), Systemic Inflammation Response Index (SIRI), fibrinogen-to-albumin ratio (FAR), and Severity Grading Score (SGS) were evaluated. Receiver operating characteristic (ROC) analysis, Spearman correlation, Kaplan–Meier survival analysis, and multivariable logistic regression were performed to assess their association with in-hospital mortality.Results: PIV showed poor discriminatory ability for predicting in-hospital mortality (AUC=0.508) and was not independently associated with mortality in multivariable analysis (OR=1.199, 95% CI 0.80–1.79; p=0.373). In contrast, SGS demonstrated the highest predictive performance (AUC=0.739) and remained the only independent predictor of mortality (OR=1.382, 95% CI 1.11–1.71; p=0.003). FAR showed high sensitivity (91.7%) but limited specificity (40.0%). PIV correlated significantly with APACHE II, SIRI, SII, blood urea nitrogen, creatinine, and SGS but not with SOFA.Conclusion: Admission PIV has limited prognostic utility in critically ill patients with CCHF and does not provide incremental prognostic value beyond established disease-specific severity scores. SGS remains the most reliable predictor of mortality in this patient population.