Evaluative performance of TyG-ABSI versus traditional indices in relation to cardiovascular disease and mortality: evidence from the U.S. NHANES.

IF 10.6 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Xin Zheng, Wenjing Zhang, Feng Yang, Leigang Wang, Bing Yu, Bin Liang
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引用次数: 0

Abstract

Background: Metabolic Syndrome (MetS) significantly increases the risk of cardiovascular disease (CVD), with central obesity and insulin resistance as major contributors. The TyG-ABSI index is a newly proposed composite measure that combines the TyG index and ABSI, aiming to assess both insulin resistance and central obesity simultaneously. Previous studies have shown that TyG-ABSI has potential in predicting cardiovascular mortality, but its applicability in MetS populations remains unclear. This study aims to explore the association between TyG-ABSI and cardiovascular events in individuals with MetS and compare its predictive value with the traditional TyG index in this specific population.

Methods: Participants from the National Health and Nutrition Examination Survey (NHANES) between 2001 and 2018 were selected, with all data weighted for sample design, clustering, and stratification to ensure national representativeness. Associations between TyG-ABSI and other TyG indices with cardiovascular mortality and all-cause mortality were assessed using weighted Cox proportional hazards models; CVD prevalence was analyzed using weighted logistic regression models. Additional analyses included Kaplan-Meier survival curves and restricted cubic spline regression. Model performance was compared between TyG-ABSI, TyG, and its derived indices using ROC curves, NRI, IDI, and DCA. E-value, subgroup analyses, and competing risks models were conducted to assess robustness.

Results: This study analyzed data from 12,813 individuals with metabolic syndrome in the NHANES cohort to systematically compare the performance of TyG-ABSI and other TyG-related indices in assessing CVD and mortality. The results revealed significant associations between TyG-ABSI and CVD, cardiovascular mortality, and all-cause mortality. Specifically, for each 1-unit increase in TyG-ABSI, the risk of CVD increased by 28%, cardiovascular mortality by 25%, and all-cause mortality by 28%. These associations showed a dose-response relationship in stratified analyses based on tertiles, and TyG-ABSI outperformed the traditional TyG index in overall analysis. Compared to other TyG-related indices, TyG-ABSI demonstrated superior predictive performance in metrics such as the ROC curve, NRI, and DCA. Further analyses, including competing risks models, E-value estimation, and RCS modeling, confirmed the robustness of these associations. Subgroup analyses also supported the stability of TyG-ABSI, with limited interaction effects.

Conclusion: Our study highlights the value of TyG-ABSI in assessing cardiovascular disease and mortality risk in populations with MetS, providing new evidence for medical practice and public health interventions.

TyG-ABSI与心血管疾病和死亡率相关的传统指标的评估性能:来自美国NHANES的证据
背景:代谢综合征(MetS)显著增加心血管疾病(CVD)的风险,中心型肥胖和胰岛素抵抗是主要因素。TyG-ABSI指数是一种新提出的将TyG指数和ABSI结合起来的复合指标,旨在同时评估胰岛素抵抗和中心性肥胖。先前的研究表明,TyG-ABSI在预测心血管死亡率方面具有潜力,但其在MetS人群中的适用性尚不清楚。本研究旨在探讨TyG- absi与MetS患者心血管事件的关系,并将其与传统的TyG指数在这一特定人群中的预测价值进行比较。方法:选取2001 - 2018年全国健康与营养检查调查(NHANES)的参与者,对所有数据进行加权,进行样本设计、聚类和分层,以确保全国代表性。使用加权Cox比例风险模型评估TyG- absi和其他TyG指数与心血管死亡率和全因死亡率之间的关系;采用加权logistic回归模型分析心血管疾病患病率。其他分析包括Kaplan-Meier生存曲线和限制性三次样条回归。采用ROC曲线、NRI、IDI和DCA比较TyG- absi、TyG及其衍生指标的模型性能。进行e值、亚组分析和竞争风险模型来评估稳健性。结果:本研究分析了NHANES队列中12813例代谢综合征患者的数据,系统地比较了TyG-ABSI和其他tyg相关指标在评估心血管疾病和死亡率方面的表现。结果显示TyG-ABSI与CVD、心血管死亡率和全因死亡率之间存在显著相关性。具体来说,TyG-ABSI每增加1个单位,CVD的风险增加28%,心血管死亡率增加25%,全因死亡率增加28%。这些关联在基于分位数的分层分析中显示出剂量-反应关系,TyG- absi在整体分析中优于传统的TyG指数。与其他tyg相关指标相比,TyG-ABSI在ROC曲线、NRI和DCA等指标上表现出优越的预测性能。进一步的分析,包括竞争风险模型、e值估计和RCS模型,证实了这些关联的稳健性。亚组分析也支持TyG-ABSI的稳定性,相互作用有限。结论:我们的研究强调了TyG-ABSI在评估MetS人群心血管疾病和死亡风险方面的价值,为医疗实践和公共卫生干预提供了新的证据。
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来源期刊
Cardiovascular Diabetology
Cardiovascular Diabetology 医学-内分泌学与代谢
CiteScore
12.30
自引率
15.10%
发文量
240
审稿时长
1 months
期刊介绍: Cardiovascular Diabetology is a journal that welcomes manuscripts exploring various aspects of the relationship between diabetes, cardiovascular health, and the metabolic syndrome. We invite submissions related to clinical studies, genetic investigations, experimental research, pharmacological studies, epidemiological analyses, and molecular biology research in this field.
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