AUTHOR=Yin Xiaoshuang , Zou Jinmei , Yang Jing TITLE=The association between the aggregate index of systemic inflammation and risk of rheumatoid arthritis: retrospective analysis of NHANES 1999–2018 JOURNAL=Frontiers in Medicine VOLUME=11 YEAR=2024 URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2024.1446160 DOI=10.3389/fmed.2024.1446160 ISSN=2296-858X ABSTRACT=Objective

The investigation purpose was to examine the correlation between the aggregate index of systemic inflammation (AISI) and rheumatoid arthritis (RA) by utilizing the NHANES database from the years 1999 to 2018.

Methods

The NHANES database was utilized to extract data spanning from 1999 to 2018. AISI, comprising neutrophils (NEU), monocytes (MONO), platelets (PLT), and lymphocytes (LYM), was computed based on counts. The identification of RA patients was accomplished through questionnaire data. To investigate the connection between AISI and RA, a weighted multivariate regression and subgroup analysis were conducted. In addition, restricted cubic splines (RCS) were employed for examining non-linear associations.

Results

The study encompassed a total of 41,986 patients, among whom 2,642 (6.29%) were diagnosed with RA. Upon controlling for all covariates, the outcomes of the multivariate logistic regression assay demonstrated a statistically significant association between higher Ln(AISI) levels and elevated odds of RA (odds ratio [OR]: 1.097; 95% confidence interval [CI]: 1.096–1.099, p < 0.001). The interaction test findings indicate that there is no statistically significant impact within this particular association. The results of the RCS regression model revealed a non-linear pattern in the correlation between Ln(AISI) and RA. The threshold level of AISI for RA was determined as 298.9. The risk of RA rises steeply when AISI surpasses the threshold value.

Conclusion

Overall, a positive association has been observed between AISI and RA. This study highlights the potential of AISI as an innovative, vital, and appropriate inflammatory biomarker for predicting the risk of developing rheumatoid arthritis in older individuals residing in the United States.