Evaluating Immune-Inflammatory Indices for Risk Stratification in Cardiovascular Disease: An Umbrella Review of...

Background/Objectives: Although systematic reviews and meta-analyses have examined immune-inflammatory indices in cardiovascular disease (CVD), the evidence remains scattered and inconsistent. This umbrella review aims to synthesize findings and evaluate the overall predictive value of these indices for clinical outcomes. Methods: We systematically searched PubMed, Cochrane Library, Web of Science, Embase, Scopus, and Medline for systematic reviews with meta-analyses assessing neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and systemic inflammation response index (SIRI) in patients with CVD. Study quality and certainty of evidence were appraised using AMSTAR-2 and GRADE, respectively. Results: A total of 35 meta-analyses covering 106 unique outcomes were included, of which 87 showed significant associations. Elevated NLR and SII were consistently linked to higher risks of CVD mortality, major adverse cardiovascular events, myocardial infarction, heart failure, and stroke. PLR and SIRI were primarily associated with poor recovery from stroke and increased mortality in ST-elevation myocardial infarction. Specifically, the methodological quality of the included reviews was generally moderate to high according to AMSTAR-2, whereas none of the associations reached high certainty based on GRADE, with most rated as low or very low and about one-quarter as moderate certainty. Conclusions: The overall certainty of evidence remains limited according to GRADE, alongside methodological heterogeneity, population variability, and inconsistent thresholds that further restrict the direct applicability of these findings in clinical practice. Nevertheless, available evidence indicates that elevated immune-inflammatory indices are likely associated with worse clinical outcomes in patients with CVD. Future research should prioritize establishing standardized cutoffs, improving methodological consistency, and validating these indices across diverse populations to support their integration into clinical risk-stratification frameworks.