Higher insulin resistance indices (TyG, AIP, METS-IR) independently predicted major adverse cardiovascular events with a composite model achieving AUC 0.82 over 48 months.
Do insulin resistance indices predict high-risk coronary plaque characteristics and major adverse cardiovascular events in patients evaluated for coronary artery disease?
Integrating insulin resistance indices with coronary imaging markers significantly improves residual risk stratification and prediction of major adverse cardiovascular events in patients with coronary artery disease.
Absolute Event Rate: 0% vs 0%
ABSTRACT Significant residual cardiovascular risk persists in patients diagnosed with coronary artery disease despite intensive lipid‐lowering therapy. Although insulin resistance (IR) is an established epidemiological risk factor, the biological mechanisms by which it promotes plaque destabilization remain poorly understood. This single‐center retrospective study, involving 1271 patients, investigated the relationships between four validated IR indices—triglyceride‐glucose (TyG), TyG–body mass index (TyG–BMI), metabolic score for insulin resistance (METS‐IR), and atherogenic index of plasma (AIP)—and high‐risk coronary plaque characteristics quantified by coronary computed‐tomography angiography. Patients with coronary atherosclerosis demonstrated significantly higher IR indices than plaque‐free controls, with all indices exhibiting strong correlations with a high‐risk plaque burden. During follow‐up, 41 patients experienced major adverse cardiovascular events (MACEs), and higher TyG index, AIP, and METS–IR independently predicted MACE after multivariable adjustment, whereas TyG–BMI exhibited a similar but non‐significant trend. A composite model integrating high‐risk plaque burden, pericoronary fat attenuation index, and the four IR indices achieved superior prognostic accuracy, substantially outperforming individual biomarkers. These findings provide novel mechanistic insights into how metabolic dysfunction promotes coronary plaque vulnerability and identify a promising integrated approach for residual risk stratification in patients with coronary artery disease. In this study, IR indices (TyG, TyG‐BMI, AIP, and METS‐IR) correlated high‐risk coronary plaque features in 1271 patients. During 48‐month follow‐up, all indices independently predicted MACEs. Combined with coronary imaging markers, the composite model achieved AUC 0.82, revealing metabolic dysfunction drives plaque destabilization in coronary disease.
Yu et al. (Sun,) reported a other. Higher insulin resistance indices (TyG, AIP, METS-IR) independently predicted major adverse cardiovascular events with a composite model achieving AUC 0.82 over 48 months.