4.8 Article

Association between the systemic immune-inflammation index and kidney stone: A cross-sectional study of NHANES 2007-2018

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FRONTIERS IN IMMUNOLOGY
卷 14, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2023.1116224

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systemic immune-inflammatory index; kidney stone; neutrophil; lymphocyte; platelet; National Health and Nutrition Examination Survey

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This study analyzed the impact of systemic immune-inflammatory index (SII) on kidney stones. The results showed that in US adults aged 20-50, high levels of SII (>330 x 10(9)/L) were positively associated with the risk of kidney stones. However, no difference was found in the elderly subgroup. This finding compensates for previous studies and further validation is needed through larger prospective cohorts.
BackgroundThe incidence rate of kidney stones increased over the past decades globally, which brought medical expenditure and social burden. The systemic immune-inflammatory index (SII) was initially identified as a prognosis of multiple diseases. We performed an updated analysis on the impact of SII on kidney stones. MethodsThis compensatory cross-sectional study enrolled participants from the National Health and Nutrition Examination Survey 2007-2018. Univariate and multivariate logistic regression analyses were performed to investigate the association between SII and kidney stones. ResultsOf the 22220 participants, the mean (SD) age was 49.45 +/- 17.36 years old, with a 9.87% incidence rate of kidney stones. A fully adjusted model showed that SII higher than 330 x 10(9)/L was parallel associated with kidney stones (Odds ratio [OR] = 1.282, 95% Confidence interval [CI] = 1.023 to 1.608, P = 0.034) in adults aged 20-50. However, no difference was found in the elderly subgroup. Multiple imputation analyses confirmed the robustness of our results. ConclusionsOur findings suggested SII was positively associated with a high risk of kidney stones in US adults aged less than 50. The outcome compensated for previous studies that still needed more large-scale prospective cohorts for validation.

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