Inflammatory indices AISI and SIRI in atherosclerosis risk stratification: validation across community and intensive care populations.

BACKGROUND

Systemic inflammation plays a key role in atherosclerosis development. This study evaluated the predictive performance of two composite inflammatory indices-the Aggregate Index of Systemic Inflammation (AISI) and the Systemic Inflammation Response Index (SIRI)-across community and intensive care populations. The Systemic Immune-Inflammation Index (SII) was also assessed in univariate analysis.

METHODS

Data were obtained from a health examination cohort ( = 23,516) diagnosed with carotid atherosclerosis ultrasound, and the MIMIC-IV database ( = 15,000) classified using ICD codes. Individuals were included based on complete demographic, laboratory, and diagnostic data, with strict exclusion of those with recent acute events or missing values. Logistic regression models were constructed and evaluated with smoothed ROC curves. Non-linear associations were examined using restricted cubic splines (RCS), and subgroup analyses were performed by sex, metabolic status, and ethnicity.

RESULTS

SIRI was consistently associated with atherosclerosis in both cohorts and showed stronger predictive power in men and individuals with metabolic syndrome ( < 0.01). AISI showed opposite trends across populations. SII did not show significant associations in univariate analysis and was not included in further modeling. Model performance improved with additional covariates (AUC increased from 0.56 to 0.79). RCS revealed non-linear relationships for both indices. Subgroup effects of SIRI were more prominent in the health examination cohort, while predictive power remained significant across critically ill patients regardless of gender or ethnicity.

CONCLUSION

SIRI is a robust and consistent predictor of atherosclerosis risk in diverse populations, supporting its utility in routine health assessments and personalized screening. In contrast, AISI's predictive value is population-dependent. These results support the use of SIRI in personalized screening strategies and suggest its potential utility in routine health assessments.