Predictive value of the FIB-4 index in ST-elevation myocardial infarction patients: from admission to follow-up.

Abstract

Background: ST-elevation myocardial infarction (STEMI) remains a leading cause of global mortality despite advancements in primary percutaneous coronary intervention (PCI). The fibrosis-4 (FIB-4) index, a non-invasive marker of liver fibrosis, has been associated with cardiovascular outcomes. However, its predictive value for in-hospital and post-discharge all-cause mortality in STEMI patients undergoing PCI remains uncertain. This study aimed to evaluate the prognostic utility of the FIB-4 index in this high-risk population.

Methods: This retrospective study analysed 2186 STEMI patients who underwent PCI. Patients were categorised into three groups based on FIB-4 tertiles: Group 1 (FIB-4 < 4.52), group 2 (4.52 ≤ FIB-4 < 6.07), and group 3 (FIB-4 ≥ 6.07). Logistic regression assessed predictors of in-hospital mortality, while Kaplan-Meier's survival analysis and Cox proportional hazards models were used to evaluate post-discharge mortality.

Results: In-hospital mortality was significantly higher in group 3 (4.3%) compared to group 2 and group 1 (p = .016). The FIB-4 index was an independent predictor of in-hospital mortality (OR: 1.105, 95% CI: 1.011-1.207, p = .028), alongside Killip class ≥ II, diabetes mellitus and reduced eGFR < 76.8 mL/min. During a median follow-up of 21 months post-discharge, all-cause mortality occurred in 8% of patients (n = 178), with rates highest in group 3 (10%, n = 74) compared to group 2 and group 1 (p = .002). Kaplan-Meier's survival analysis demonstrated significantly lower cumulative survival in group 3 (log-rank test, p = .003). Multivariable Cox analysis confirmed an increased post-discharge mortality risk in group 3 (HR: 1.862, 95% CI: 1.254-2.764, p = .002) compared to group 1.

Conclusions: The FIB-4 index independently predicts in-hospital and post-discharge all-cause mortality in STEMI patients undergoing PCI. Its integration into clinical practice could improve risk stratification and patient management.