Cardiovascular risk prediction in hemodialysis patients using the triglyceride-glucose index: a multicenter prospective cohort study.

利用甘油三酯-葡萄糖指数预测血液透析患者的心血管风险:一项多中心前瞻性队列研究

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作者:Lee Yu Ho, Kang Seok Hui, Kim Dae Kyu, Kim Jin Sug, Jeong Kyung Hwan, Kim Yang Gyun, Lee Dong-Young, Ahn Shin Young, Chung Sungjin, Sun In O, Lee Min-Jeong, Hwang Hyeon Seok
BACKGROUND: Triglyceride-glucose (TyG) index has recently been established as an indicator of insulin resistance and has predictive value for cardiovascular (CV) disease. However, the clinical significance of the TyG index in patients undergoing hemodialysis remains unknown. METHODS: We prospectively enrolled 759 patients undergoing maintenance hemodialysis. The participants were divided into tertiles based on their baseline TyG index. Echocardiographic parameters, vascular calcification scores, and several plasma biomarkers were obtained and compared using the TyG index. RESULTS: The TyG index was positively correlated with levels of circulating vascular pathologic markers, endostatin (ρ = 0.134, P = .025) and vascular adhesion protein-1 (ρ = 0.130, P = .012), but not with vascular calcification score. The TyG index was not correlated with any echocardiographic parameters. Patients in tertile 3 showed the highest cumulative event rates of CV and cardiac events (P < .001 and P = .001, respectively). In the multivariable Cox regression analysis, patients in the TyG index tertile 3 had a significantly increased risk of CV and cardiac events compared to those in the TyG index tertile 1 [adjusted hazard ratio (HR): 1.89, 95% confidence interval (CI): 1.08-3.30, and adjusted HR: 2.01, 95% CI: 1.05-3.82, respectively]. A 1 standard deviation increase in the TyG index was also associated with significantly higher risks of CV and cardiac events. CONCLUSIONS: The TyG index was associated with vascular pathology markers and an increased risk of adverse CV outcomes in patients undergoing hemodialysis. Our study suggests that the TyG index has the potential to assist clinicians in identifying a high CV risk in hemodialysis patients.

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