Why the study?
The study evaluated the prognostic value of the triglyceride-glucose (TyG) index and its metabolic mediation pathways in patients with complex coronary lesions undergoing PCI.
Does a higher Triglyceride-glucose (TyG) index predict cardiovascular events in patients with complex coronary lesions undergoing PCI?
Does a higher Triglyceride-glucose (TyG) index predict cardiovascular events in patients with complex coronary lesions undergoing PCI?
The TyG index is an independent predictor of cardiovascular events in patients with complex coronary lesions undergoing PCI, with metabolic comorbidities mediating half of its prognostic impact.
May refine post-PCI risk stratification in complex lesions; hypothesis-generating for TyG-targeted trials.
This prospective cohort study evaluated the prognostic value of the triglyceride-glucose (TyG) index and its metabolic mediation pathways in 16 499 patients with complex coronary lesions (American College of Cardiology/American Heart Association type B2/C) undergoing percutaneous coronary intervention (PCI). Over a median 3-year follow-up, 535 patients (3.2%) experienced cardiovascular (CV) events. Patients in the highest TyG tertile (T3: >9.10) demonstrated a 2.442-fold increased CV risk compared with the lowest tertile (T1: <8.63; 95% CI 1.923-3.102, P < .001), with a significant dose-response relationship ( P -trend < .001). Structural equation modeling revealed that metabolic burden (hypertension, dyslipidemia, type 2 diabetes mellitus) mediated 50.0% of TyG-associated risk (indirect effect P = .038). TyG index exhibited superior predictive accuracy for CV events compared with the TG/HDL-C ratio (area under the curve [AUC] 0.617 vs 0.577, P = .004), though their combination did not significantly improve discrimination over TyG alone (△AUC = 0.001, P = .694). Type 2 diabetes mellitus accounted for 62.3% of the mediation effect, surpassing hypertension (20.8%), and dyslipidemia (16.9%). These findings establish the TyG index as an independent predictor of CV outcomes in complex coronary lesions, with metabolic comorbidities explaining half its prognostic impact. Integration of TyG-driven metabolic phenotyping may optimize risk stratification and targeted interventions in high-risk PCI populations.
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He et al. (2025) studied this question.
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