Abstract
BACKGROUND: Hyperuricemia is the underlying condition of gout. Previous studies have indicated that specific strategies may be effective in preventing the progression of hyperuricemia to gout. However, there is a lack of widely applicable methods for identifying high-risk populations for gout. Gout is linked to inflammation, especially in the hyperuricemic population. Systemic inflammation response index (SIRI) is a novel method for evaluating an individual's systemic inflammatory activity. However, the association between SIRI and gout in the hyperuricemic population has not been studied. METHODS: The study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2007-2018.SIRI was log2-transformed before analysis. Multivariable logistic regression, subgroup analysis, and smooth curve fitting were employed to comprehensively evaluate the correlation between SIRI and gout prevalence in the hyperuricemic population. Additionally, we compared SIRI with other inflammatory markers. RESULT: A total of 6,732 hyperuricemic patients were included, of which 3,764 were men. After adjusting for all covariates, SIRI was found to be significantly positively correlated with gout prevalence in the female group ([OR = 1.385, 95% CI (1.187, 1.615), p < 0.001]), and its diagnostic performance was superior to other inflammatory markers. In the male group, the correlation between log2-SIRI and gout prevalence was not significant ([OR = 0.994, 95% CI (0.892, 1.108), p = 0.916]). But there were significant positive correlations in the 20-45 age group ([OR = 1.362, 95% CI (1.021, 1.818), p = 0.036]). Subgroup analyses revealed that the results were largely consistent when the individuals were divided into different subgroups (FDR adjusted p for interaction >0.05 for all). CONCLUSION: Our study suggests that the Systemic Inflammation Response Index (SIRI) has potential as a predictive marker for gout risk in hyperuricemic women. However, given the higher gout prevalence in men, the potential of SIRI as a predictive marker for gout risk in this population may be limited. Subgroup analyses, however, indicated that the relationship between SIRI and gout prevalence, as well as its statistical significance, varied across different age groups. Future research could further explore this association by investigating the relationship between SIRI and gout prevalence in different age cohorts.