Prognostic value of the inflammatory burden index in predicting 1-year mortality in patients undergoing cardiac resynchronization therapy for heart failure

Background/objectives Heart failure (HF) is one of the leading causes of death and impairs quality of life worldwide. Systemic inflammation has been increasingly recognized as a major contributor to adverse outcomes in patients with heart failure. The Inflammatory Burden Index (IBI), a composite marker integrating C-reactive protein (CRP), neutrophils, and lymphocytes, may offer improved prognostic value over traditional inflammatory markers. This study aimed to evaluate the prognostic significance of IBI in predicting one-year mortality among patients undergoing Cardiac Resynchronization Therapy (CRT). Methods This retrospective observational study included 525 heart failure patients who received CRT between January 2020 and January 2024. Patients were grouped based on 1-year survival status. Continuous variables were compared using Student's t-test or Mann–Whitney U test based on normality assessment, and presented as mean ± SD or median [interquartile range, IQR]. To handle right-skewness and ensure linearity in the logit, inflammatory markers were logarithmically transformed [Log(IBI) and Log(CRP)]. Multivariable logistic regression models were constructed using a standardized baseline clinical model. Incremental prognostic value was evaluated using Integrated Discrimination Improvement (IDI), continuous Net Reclassification Improvement (NRI), and DeLong's test. Results Baseline CRP (median [IQR]: 20.90 [11.95–33.00] vs. 6.56 [3.37–13.80] mg/dL, p < 0.001) and IBI (median [IQR]: 81.15 [36.56–230.90] vs. 18.61 [7.76–44.46], p < 0.001) were significantly higher in non-survivors. In multivariable analysis, both Log(IBI) (OR: 1.983; 95% CI: 1.463–2.687; p < 0.001) and Log(CRP) (OR: 3.265; 95% CI: 2.278–4.678; p < 0.001) independently predicted 1-year mortality. Incorporating Log(IBI) or Log(CRP) significantly improved model discrimination over baseline clinical risk (AUC increased from 0.684 to 0.778 and 0.795, respectively; DeLong p < 0.001), yielding substantial IDI (0.0953 and 0.1118, p < 0.001) and continuous NRI (67.1% and 80.6%, p < 0.001) gains. Head-to-head comparison showed comparable discriminative performance between Log(IBI) and Log(CRP) models (DeLong p = 0.307). Conclusions Both Log(IBI) and Log(CRP) are independent predictors of 1-year mortality in HF patients undergoing CRT, offering comparable incremental prognostic utility over standard clinical risk factors. Incorporating these inflammatory biomarkers into routine risk stratification may refine the identification of high-risk candidates.