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The association between triglyceride-glucose index and major adverse cardiovascular and cerebrovascular events in patients with heart failure

  • Ling Ren,
  • Dawei Liu,
  • Bo Zhou,
  • Jie Liu,
  • Changqing Yu

摘要

Objective

This study aimed to verify the association between triglyceride-glucose (TyG) and major adverse cardiovascular and cerebrovascular events (MACCE) in patients with heart failure (HF).

Methods

This single-center retrospective cohort study enrolled 927 patients with HF. Participants were categorized into four groups based on TyG index quartiles: Q1 (n = 227), Q2 (n = 237), Q3 (n = 234), and Q4 (n = 229). According to the occurrence of MACCE, they were further classified into non-MACCE (n = 847) and MACCE (n = 80) groups. Cox regression, subgroup analysis, receiver operating characteristic (ROC) curve analysis, Kaplan-Meier survival curves, and restricted cubic spline (RCS) plots were employed to evaluate the association between the TyG index and MACCE risk.

Results

Multivariable Cox regression analysis demonstrated that the TyG index remained independently associated with the risk of MACCE after adjusting for lifestyle factors, comorbidities, treatments, and key laboratory and echocardiographic parameters. Each 1-unit increase in TyG was associated with an 85.4% increase in MACCE risk (HR: 1.336–2.572, P < 0.001). Patients in the highest TyG quartile (Q4) had a 3.679-fold higher risk of MACCE compared to those in the lowest quartile (Q1) (HR: 1.702–7.956, P = 0.001). Subgroup analyses revealed that the association was more pronounced in females, patients aged > 75 years, those with chronic HF, hypertension, and those without chronic kidney disease (P for interaction = 0.021 and 0.035 for gender and hypertension, respectively). Sensitivity analyses addressing endpoint heterogeneity showed a stronger association between TyG and “hard endpoints” (HR per unit: 2.01, P < 0.001), with significant net reclassification improvement at 12 months. ROC analysis indicated a modest predictive value of TyG for MACCE (AUC = 0.587, 95% CI: 0.525–0.649, P = 0.010). Kaplan-Meier curves showed significant differences in cumulative event risk across TyG groups (Log-rank P = 0.025). RCS analysis indicated a significant positive linear dose-response relationship between TyG and MACCE risk (P for nonlinearity > 0.05).

Conclusion

The TyG index exhibits a significant positive linear association with the risk of MACCE in patients with HF. As a simple and readily accessible metabolic marker, the TyG index may provide supplementary prognostic information when considered alongside established clinical risk factors in this population.