FIRE-MI score - focus on inflammatory response evaluation after myocardial infarction - a clinical risk score for predicting mortality following acute coronary syndrome

Introduction A pro-inflammatory status is known to increase the risk of cardiovascular events and mortality. Despite robust evidence supporting its deleterious effects, clinical recognition and interpretation of inflammatory activation remain limited in daily practice. This study aimed to develop a practical, clinically applicable risk score, based on routinely available laboratory markers, to predict in-hospital mortality following acute coronary syndrome (ACS). Methods This single-centre retrospective study included all patients admitted for ACS between January 2016 and December 2023. The newly developed FIRE-MI score (range: 0–5 points) was derived after identifying inflammatory biomarkers independently associated with in-hospital mortality (IHM) in multivariate analysis, with one point assigned per significant variable. The score incorporated the following parameters: C-reactive protein (CRP) > 1.5 mg/dL (p = 0.001), ferritin > 400 µg/L (p = 0.039), fibrinogen > 4.0 g/L (p = 0.021), uric acid (p = 0.041), and neutrophil percentage > 75% (p = 0.023). Patients scoring ≥ 3 were classified as high-risk. The score’s association with IHM was analysed using binary logistic regression and compared with the Killip–Kimball (KK) classification by receiver-operating characteristic (ROC) curve analysis. Results A total of 1714 patients were included; 70.4% (n = 1206) were male, with a mean age of 69.2 ± 13.0 years. STEMI was present in 44.7% (n = 765) and 82.6% (n = 1415) were in sinus rhythm; most patients presented as KK class I (69.0%, n = 1,183). Elevated CRP, uric acid, ferritin, fibrinogen, and neutrophilia were observed in 23.7%, 31.0%, 24.3%, 44.2%, and 50.9% of patients, respectively. IHM occurred in 7.2% (n = 124). The mean FIRE-MI score was 1.73 ± 1.14, with 26.5% (n = 454) classified as high-risk, figure 1. IHM was significantly more frequent among high-risk patients (66.9% vs 23.3%; χ² = 112.31; p = 0.001). On multivariate analysis, the FIRE-MI score was an independent predictor of IHM (OR = 5.87, 95% CI 3.94–8.76; p = 0.001). ROC analysis demonstrated a fair discriminative ability, superior to the KK classification (AUC = 0.715 vs 0.698; p = 0.047), figure 2. Conclusion The FIRE-MI score effectively stratifies patients according to their risk of in-hospital mortality following ACS, outperforming traditional clinical classification systems. Its simplicity and reliance on standard inflammatory biomarkers make it a promising tool for bedside risk assessment, reinforcing the pivotal role of systemic inflammation in adverse cardiovascular outcomes.