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将TyG指数添加到GRACE评分中可改善接受经皮冠状动脉介入治疗的非ST段抬高型急性冠状动脉综合征患者不良心血管结局的预测:一项回顾性研究。

Addition of TyG index to the GRACE score improves prediction of adverse cardiovascular outcomes in patients with non-ST-segment elevation acute coronary syndrome undergoing percutaneous coronary intervention: A retrospective study.

作者信息

Pang Shuo, Miao Guangrui, Zhou Yuanhang, Du Yang, Rui Ziao, Zhao Xiaoyan

机构信息

Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

出版信息

Front Cardiovasc Med. 2022 Aug 25;9:957626. doi: 10.3389/fcvm.2022.957626. eCollection 2022.

Abstract

BACKGROUND

The Global Registry of Acute Coronary Events (GRACE) score is a widely recognized tool for predicting adverse cardiovascular events in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS). The triglyceride-glucose index (TyG index) is a new biomarker of insulin resistance and has a close association with the occurrence of adverse cardiovascular events. We investigated whether the addition of the TyG index to the GRACE score could improve prognosis prediction in patients with NSTE-ACS undergoing percutaneous coronary intervention (PCI).

METHODS

In total, 515 patients with NSTE-ACS undergoing PCI were included in this retrospective study. Kaplan-Meier analysis was performed to describe the cumulative incidence of the primary endpoint based on the median TyG index. The relationship between the TyG index and GRACE score was analyzed using Spearman's rank correlation. Univariate and multivariate Cox proportional hazards analyses were used to identify independent risk factors. Based on the receiver operating characteristic curve, net reclassification improvement (NRI), integrated differentiation improvement (IDI), and decision curve analysis, the TyG index was evaluated for its predictive value when added to the GRACE score. ROC curve analyses, NRI, and IDI were used to compare the gain effect of the TyG index and the levels of HbA1C, FBG, TG, and LDL-C on the GRACE score for predicting adverse cardiovascular events.

RESULTS

The TyG index was an independent predictor of 2-year adverse cardiovascular events in patients with NSTE-ACS undergoing PCI. The addition of the TyG index to the GRACE score demonstrated an improved ability to predict 2-year adverse cardiovascular events compared with the GRACE score alone (AUCs: GRACE score 0.798 vs. GRACE score+TyG index 0.849, = 0.043; NRI = 0.718, < 0.001; IDI = 0.086, < 0.001). The decision curve analysis suggested that the clinical net benefit of the new model (GRACE score+TyG index) was superior to that of the GRACE score alone, with a probability range of 0.04 to 0.32. When including the TyG index, HbA1C, FBG, TG, and LDL-C in the GRACE score system, we found that the TyG index had a greater incremental impact on risk prediction and stratification compared to the other parameters.

CONCLUSION

Combining the TyG index and GRACE score could improve the prediction of 2-year adverse cardiovascular events. This new risk model could identify patients with NSTE-ACS at higher risk of adverse events following PCI so that they can be monitored more carefully.

摘要

背景

全球急性冠状动脉事件注册研究(GRACE)评分是预测非ST段抬高型急性冠状动脉综合征(NSTE-ACS)患者不良心血管事件的一种广泛认可的工具。甘油三酯-葡萄糖指数(TyG指数)是胰岛素抵抗的一种新生物标志物,与不良心血管事件的发生密切相关。我们研究了在GRACE评分中加入TyG指数是否能改善接受经皮冠状动脉介入治疗(PCI)的NSTE-ACS患者的预后预测。

方法

本回顾性研究共纳入515例接受PCI的NSTE-ACS患者。采用Kaplan-Meier分析根据TyG指数中位数描述主要终点的累积发生率。采用Spearman等级相关分析TyG指数与GRACE评分之间的关系。采用单因素和多因素Cox比例风险分析确定独立危险因素。基于受试者工作特征曲线、净重新分类改善(NRI)、综合鉴别改善(IDI)和决策曲线分析,评估TyG指数加入GRACE评分后的预测价值。采用ROC曲线分析、NRI和IDI比较TyG指数与糖化血红蛋白(HbA1C)、空腹血糖(FBG)、甘油三酯(TG)和低密度脂蛋白胆固醇(LDL-C)水平对GRACE评分预测不良心血管事件的增益效果。

结果

TyG指数是接受PCI的NSTE-ACS患者2年不良心血管事件的独立预测因子。与单独使用GRACE评分相比,在GRACE评分中加入TyG指数显示出更好的预测2年不良心血管事件的能力(曲线下面积:GRACE评分0.798 vs. GRACE评分+TyG指数0.849,P = 0.043;NRI = 0.718,P < 0.001;IDI = 0.086,P < 0.001)。决策曲线分析表明,新模型(GRACE评分+TyG指数)的临床净效益优于单独使用GRACE评分,概率范围为0.04至0.32。当在GRACE评分系统中纳入TyG指数、HbA1C、FBG、TG和LDL-C时,我们发现TyG指数对风险预测和分层的增量影响比其他参数更大。

结论

联合TyG指数和GRACE评分可改善对2年不良心血管事件的预测。这种新的风险模型可以识别出PCI术后发生不良事件风险较高的NSTE-ACS患者,以便对他们进行更密切的监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b136/9453480/f78111d6432a/fcvm-09-957626-g0001.jpg

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