Predictive value of the triglyceride-glucose index for no-reflow phenomenon after percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction complicated by metabolic syndrome.

Objective: Acute ST-segment elevation myocardial infarction (STEMI) remains a major contributor to morbidity and mortality worldwide. The no-reflow phenomenon following percutaneous coronary intervention (PCI) complicates the clinical outcome of STEMI. This study aimed to identify a valuable predictor for no-reflow phenomenon.

Methods: This retrospective study analyzed clinical data from 378 STEMI patients with metabolic syndrome who underwent PCI between January 2023 and December 2023. Patients were divided into normal reflow (n = 311) and no-reflow (n = 67) groups based on post-PCI coronary angiography results. Data collected included patient demographics, medication usage, lipid profiles, cardiac biomarkers, and the triglyceride-glucose (TyG) index.

Results: Patients in the no-reflow group were older (59.98 ± 3.45 vs. 58.69 ± 3.57 years, P = 0.007), with higher fasting glucose (118.57 ± 7.23 vs. 113.59 ± 7.62 mg/dL, P < 0.001) and triglycerides (185.36 ± 10.17 vs. 176.56 ± 10.38 mg/dL, P < 0.001). The TyG index was notably higher in the no-reflow group (8.97 ± 1.15 vs. 7.49 ± 1.17, P < 0.001), showing the strongest correlation with no-reflow (r = 0.420, P < 0.001). Receiver Operating Characteristic (ROC) analysis identified the TyG index as the best predictor, with an AUC of 0.818 at a threshold of 8.1. Multivariable logistic regression identified TyG index ≥ 8.1 as the strongest independent predictor of no-reflow (OR, 9.591; 95% CI, 4.469-20.587, P < 0.001). The AUC of the TyG for predicting no-reflow was 0.869, with specificity and sensitivity of 0.891 and 0.791, respectively.

Conclusion: The TyG index is a powerful predictor of the no-reflow phenomenon in STEMI patients with metabolic syndrome undergoing PCI. Its robust sensitivity and specificity underscore its utility for risk stratification, enabling clinicians to identify high-risk patients and tailor preventive strategies.