Background: Cardiovascular disease (CVD) is a leading cause of death in older adults and is closely associated with inflammation. The aggregate index of systemic inflammation (AISI), a novel biomarker, may predict CVD mortality in this population. To analyze the association between AISI levels and CVD mortality in the older population.

Methods: This study was based on the National Health and Nutrition Examination Survey (NHANES) database. By constructing weighted Kaplan–Meier (K-M) survival curves and Cox proportional hazards models, the link between AISI levels and CVD mortality rate were analyzed in the elderly. The restricted cubic spline (RCS) was applied to elucidate the non-linear link. A random survival forest model was constructed to assess the predictive value of multiple variables.

Results: One thousand three hundred nineteen CVD death events were recorded. The weighted K-M survival curve manifested that the CVD mortality risk was considerably higher in the highest tertile group than in the lowest tertile. In the model with full adjustments, each one-unit increase in AISI was associated with a 1.52-fold higher risk of death
(HR = 1.52, 95% CI: 1.30-1.76, P < .001), and a non-linear relationship was detected (P-non-linear = .0001). When AISI was above the threshold of 263.43, the CVD mortality risk was significantly elevated (HR = 1.99, 95% CI: 1.59-2.49, P < .001). No significance was observed below this threshold. AISI had the highest predictive value for CVD mortality in the elderly.

Conclusion: The AISI is an effective indicator for predicting the CVD mortality risk in the elderly, especially when AISI reaches high levels.

#This work was equally contributed to by the authors.