Background: Heart failure (HF) is a disease closely associated with inflammation, and the systemic immune-inflammation index (SII) is a novel inflammatory marker. Therefore, this study aims to explore the relationship between SII and HF.
Methods: We used National Health and Nutrition Examination Survey data from 1998 to 2018 to include adults who reported a diagnosis of HF and complete information on the calculation of SII. SII was calculated as platelet count × neutrophil count/lymphocyte count. We used multiple logistic regression models to examine the association between SII and HF and explored possible influencing factors by subgroup analysis. In addition, we performed smoothed curve fitting and threshold effect analysis to describe the nonlinear relationship.
Results: The population-based study involved a total of 48,155 adults ages 20-85. Multivariate logistic regression showed that participants with the highest SII had a statistically significant 32% increased risk of HF prevalence compared to those with the lowest SII (OR = 1.32; 95% CI, 1.06-1.65, P = 0.0144) in a fully adjusted model. Subgroup analysis revealed no significant interactions between SII and specific subgroups (p > 0.05 for all interactions). Furthermore, the association between SII and HF was non-linear; the inflection point was 1104.78 (1000 cells/μl).
Conclusions: Based on our findings, elevated SII levels were found to be strongly associated with the risk of HF, and SII was nonlinearly associated with HF. To validate these findings, a larger prospective investigation is needed to support the results of this study and investigate potential problems.
Keywords: Cross-sectional study; Heart failure; NHANES; Population-based study; Risk factors; Systemic immune-inflammation index.
Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.