Cao Bi-Fei, Liu Kuan, Chen Hao-Wen, Xu Zheng-Yun, Wang Shi-Ao, Zhang Chen-Yu, Liu Yu-Jing, Li Qiu-Rong, Shao Zhan-Hui, Liao Kai-Yue, Zhong Qi, Jin Hao-Yuan, Du Shan-Tong, Huang Ze-Jun, Wu Xian-Bo
Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou, 510515, China.
Public Health Division, Hospital of Zhongluotan Town, Baiyun District, Guangzhou, 510515, China.
Atherosclerosis. 2025 Aug;407:120407. doi: 10.1016/j.atherosclerosis.2025.120407. Epub 2025 Jun 18.
For patients with type 2 diabetes (T2D), the triglyceride-glucose (TyG) index, the atherogenic index of plasma (AIP) and the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) are recognized as reliable predictors of cardiovascular diseases. However, the association of these predictors with microvascular complications (MVCs) in T2D remains controversial and warrants further investigation.
Using data from the Action to Control Cardiovascular Risk in Diabetes study, we examined the association of cardiometabolic indices with the risk of incident microvascular outcomes, including diabetic kidney disease (DKD), diabetic neuropathy (DN) and diabetic retinopathy (DR). Group-based trajectory models were used to determine cardiometabolic indices trajectories during the 24-month follow-up period. Restricted cubic spline analysis were conducted to assess the non-linear relationship between baseline indices and MVCs, and Cox proportional hazards regression models were employed to evaluate the associations of baseline and trajectory indices with MVCs.
During a median follow-up of 3.69, 3.69 and 3.78 years, 2289 DKD, 2227 DN and 2420 DR events were recorded. Elevated TyG index, AIP, NHHR were significantly associated with an increased risk of DKD (P < 0.05), and AIP demonstrated superior predictive capacity. The fully-adjusted HR (95 % CI) for the highest quartile of TyG index, AIP and NHHR for DKD risk were 1.307 (1.174-1.455), 1.341 (1.202-1.496) and 1.341 (1.202-1.496), respectively. Three distinct trajectories of Tyg index, AIP, NHHR were identified: low-stable, moderate-stable and high-stable. The incidence of DKD in the TyG index, AIP and NHHR with high-stable trajectory increased by 41.3 %, 47.3 % and 20.7 %, respectively, whereas the incidence of DN in the AIP increased by 19.3 % compared with low-stable trajectory.
The baseline levels and trajectories of cardiometabolic indices are associated with an increase in the risk of MVCs in patients with T2D. Regular monitoring and sustained stabilization of these indicators at low levels are vital for preventing and managing MVCs. The graphical abstract is shown in Figure S1.
对于2型糖尿病（T2D）患者，甘油三酯-葡萄糖（TyG）指数、血浆致动脉粥样硬化指数（AIP）以及非高密度脂蛋白胆固醇与高密度脂蛋白胆固醇之比（NHHR）被认为是心血管疾病的可靠预测指标。然而，这些预测指标与T2D微血管并发症（MVCs）之间的关联仍存在争议，值得进一步研究。
利用糖尿病心血管风险控制行动研究的数据，我们研究了心脏代谢指标与新发微血管结局风险之间的关联，这些结局包括糖尿病肾病（DKD）、糖尿病神经病变（DN）和糖尿病视网膜病变（DR）。基于组的轨迹模型用于确定24个月随访期内的心脏代谢指标轨迹。进行受限立方样条分析以评估基线指标与MVCs之间的非线性关系，并采用Cox比例风险回归模型评估基线指标和轨迹指标与MVCs之间的关联。
在中位随访3.69年、3.69年和3.78年期间，分别记录了2289例DKD、2227例DN和2420例DR事件。TyG指数、AIP、NHHR升高与DKD风险增加显著相关（P<0.05），且AIP显示出更好的预测能力。TyG指数、AIP和NHHR最高四分位数的DKD风险的完全调整后HR（95%CI）分别为1.307（1.174-1.455）、1.341（1.202-1.496）和1.341（1.202-1.496）。确定了TyG指数、AIP、NHHR的三种不同轨迹：低稳定、中稳定和高稳定。TyG指数、AIP和NHHR高稳定轨迹的DKD发病率分别增加41.3%、47.3%和20.7%，而AIP的DN发病率与低稳定轨迹相比增加了19.3%。
心脏代谢指标的基线水平和轨迹与T2D患者MVCs风险增加相关。定期监测并将这些指标持续稳定在低水平对于预防和管理MVCs至关重要。图形摘要见图S1。
