Why the study?
The combined impact of the triglyceride-glucose index and systemic inflammation index on all-cause and cardiovascular mortality remained unclear.
Does the combination of high TyG index and high SII predict increased all-cause and cardiovascular mortality in U.S. adults?
Does the combination of high TyG index and high SII predict increased all-cause and cardiovascular mortality in U.S. adults?
The combined assessment of the TyG index and SII significantly enhances the prediction of all-cause and cardiovascular mortality, highlighting the synergistic prognostic value of insulin resistance and systemic inflammation.
Supports combined TyG-SII assessment for mortality prediction; hypothesis-generating and requires prospective validation.
The triglyceride-glucose and systemic inflammation index have been linked to mortality outcomes. However, their combined impact on all-cause and cardiovascular mortality remains unclear. This study aimed to evaluate the individual and combined associations of the TyG index and SII with mortality using data from NHANES. Associations between TyG, SII, and mortality were assessed using multivariable Cox proportional hazards models and restricted cubic spline (RCS) regression models. Subgroup and sensitivity analyses were also conducted. Compared to individuals with low TyG and low SII, those with high TyG and high SII had a hazard ratio (HR) of 1.29 (95% CI, 1.16-1.44) for all-cause mortality, 1.54 (95% CI, 1.23-1.94) for cardiovascular mortality, 1.56 (95% CI, 1.20-2.04) for cardiac mortality, and 1.60 (95% CI, 0.83-3.08) for cerebrovascular mortality after full adjustment. The ROC curve analysis indicated that the combination of TyG and SII had an AUC of 0.599 for predicting all-cause mortality and 0.613 for cardiovascular mortality. Subgroup and sensitivity analyses yielded consistent findings. In conclusion, these results underscore the significant combined association of the TyG index and SII on all-cause and cardiovascular mortality, highlighting the importance of jointly assessing these indices to better predict mortality outcomes.
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Liu et al. (2025) studied this question.
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