Predictive Value of Plasma Big Endothelin-1 in Adverse Events of Patients With Coronary Artery Restenosis and Diabetes Mellitus: Beyond Traditional and Angiographic Risk Factors.

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BackgroundPatients with diabetes are a high-risk group for coronary in-stent restenosis (ISR), so it would be valuable to identify biomarkers to predict their prognosis. The plasma big endothelin-1 (big ET-1) level is closely related to cardiovascular adverse events; however, for patients with ISR and diabetes who undergo percutaneous coronary intervention (PCI), whether big ET-1 is independently correlated with prognosis is still uncertain.MethodsPatients with drug-eluting stent (DES) restenosis who underwent successful re-PCI from January 2017 to December 2018 at the Chinese Academy of Medical Sciences Fuwai Hospital were enrolled and followed up for 3 years. The patients were divided into the tertiles of baseline big ET-1. The primary end points were major adverse cardiovascular events (MACEs): cardiac death, non-fatal myocardial infarction (MI), target lesion revascularization (TLR), and stroke. A Cox multivariate proportional hazard model and the C-statistic were used to evaluate the potential predictive value of big ET-1 beyond traditional and angiographic risk factors.ResultsA total of 1,574 patients with ISR were included in this study, of whom 795 were diabetic. In patients with ISR and diabetes, after an average follow-up of 2.96 ± 0.56 years, with the first tertile of big ET-1 as a reference, the hazard ratio [HR] (95% CI) of MACEs after adjustment for traditional and angiographic risk factors was 1.24 (0.51–3.05) for the second tertile and 2.60 (1.16–5.81) for the third. Big ET-1 improved the predictive value for MACEs over traditional risk factors (C-statistic: 0.64 vs. 0.60, p = 0.03). Big ET-1 was not significantly associated with the risk of MACEs in patients without diabetes.ConclusionIncreased plasma big ET-1 was associated with a higher risk of adverse cardiovascular prognosis independent of traditional and angiographic risk factors, and therefore, it might be used as a predictive biomarker, in patients with ISR and diabetes.