Department of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Graduate School, Beijing University of Chinese Medicine, Beijing, 100029, China.
Cardiovasc Diabetol. 2024 Oct 14;23(1):359. doi: 10.1186/s12933-024-02446-1.
Triglyceride (TG) and its related metabolic indices are recognized as important biomarker gauging cardiovascular diseases. This study aimed to explore the association between multiple TG-derived metabolic indices including the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes to identify valuable predictors for cardiovascular prognosis in patients with type 2 diabetes (T2DM) and coronary heart disease (CHD).
Data of 1034 patients with T2DM and CHD from China-Japan Friendship Hospital between January 2019 and March 2022 were collected and analyzed. Multivariate Cox proportional hazards models and restricted cubic spline (RCS) analysis were conducted to examine the associations between AIP, TyG index, TyG-BMI and major adverse cardiac and cerebrovascular events (MACCEs). The area under the receiver operating characteristic (ROC) curve (AUC) was used to screen the most valuable predictor. Kaplan-Meier curve analysis was employed to examine the relationship between the predictor and prognosis. The goodness-of-fit of models was evaluated using the calibration curve and χ likelihood ratio test. Subgroup analysis and interaction test were performed to control for confounding factors.
The overall incidence of MACCEs was 31.04% during a median of 13.3 months of follow-up. The results showed that AIP, TyG index and TyG-BMI were all positively correlated with the risk of MACCEs in patients with T2DM and CHD (P < 0.05). Furthermore, ROC (AUC = 0.899) suggested that AIP had the strongest ability to predict the risk of MACCEs, and the highest AIP values enhanced the risk by 83.5% in the population. RCS model demonstrated that AIP was nonlinearly associated with the incident cardiovascular outcomes (P for nonlinear = 0.0118). The Kaplan-Meier analysis for MACCEs grouped by the AIP tertiles indicated that the probability of cumulative incidences of MACCEs was significantly higher in patients with a higher AIP (all Log rank P < 0.001). Meanwhile, the calibration curve demonstrated an excellent goodness-of-fit of the multivariate model (χ = 13.210, P = 0.105). Subgroup analysis revealed that the trend of positive association of AIP with cardiovascular risk was similar across subgroups except in non-hypertensive individuals.
Our study, for the first time, may provide valuable information that multiple TG-derived metabolic indices play a crucial role in the risk of MACCEs and it is recommended to monitor the AIP for lipid management in patients with established T2DM and CHD.
甘油三酯（TG）及其相关代谢指标已被认为是衡量心血管疾病的重要生物标志物。本研究旨在探讨多种 TG 衍生的代谢指标与心血管结局之间的关系，包括血浆致动脉粥样硬化指数（AIP）、甘油三酯-葡萄糖（TyG）指数、甘油三酯-葡萄糖-体重指数（TyG-BMI），以确定 2 型糖尿病（T2DM）和冠心病（CHD）患者心血管预后的有价值预测因子。
本研究纳入了 2019 年 1 月至 2022 年 3 月期间在中国中日友好医院就诊的 1034 例 T2DM 和 CHD 患者，采用多变量 Cox 比例风险模型和限制性立方样条（RCS）分析，探讨 AIP、TyG 指数、TyG-BMI 与主要不良心脑血管事件（MACCEs）之间的关联。采用受试者工作特征（ROC）曲线下面积（AUC）筛选最有价值的预测因子。Kaplan-Meier 曲线分析预测因子与预后的关系。通过校准曲线和 χ 似然比检验评估模型的拟合优度。采用亚组分析和交互检验控制混杂因素。
在中位随访 13.3 个月期间，总体 MACCE 发生率为 31.04%。结果表明，AIP、TyG 指数和 TyG-BMI 与 T2DM 和 CHD 患者的 MACCE 风险均呈正相关（P<0.05）。此外，ROC（AUC=0.899）表明 AIP 对预测 MACCE 风险的能力最强，在人群中 AIP 值越高，风险增加 83.5%。RCS 模型显示 AIP 与心血管结局呈非线性相关（P<0.0118）。根据 AIP 三分位组的 MACCE Kaplan-Meier 分析，AIP 较高的患者累积 MACCE 发生率明显更高（所有 Log rank P<0.001）。同时，校准曲线表明多变量模型拟合良好（χ=13.210，P=0.105）。亚组分析显示，AIP 与心血管风险的正相关趋势在除非高血压个体以外的各亚组中相似。
本研究首次提供了有价值的信息，即多种 TG 衍生的代谢指标在 MACCE 风险中起关键作用，建议在患有已确诊的 T2DM 和 CHD 的患者中监测 AIP 以进行血脂管理。
