Association of baseline and trajectory of triglyceride-glucose index with the incidence of cardiovascular autonomic neuropathy in type 2 diabetes mellitus.

Abstract

Background: Cardiovascular autonomic neuropathy (CAN), characterized by disrupted autonomic regulation of the cardiovascular system, is a frequent complication associated with diabetes. The triglyceride-glucose (TyG) index represents a precise insulin resistance indicator. However, the influence of baseline and prolonged TyG index patterns on CAN risk in type 2 diabetes remains unclear.

Methods: Based on the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, multivariate logistic regression models and restricted cubic splines (RCS) were deployed for elucidating the relation between baseline TyG index and the incidence of CAN. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to assess the diagnostic value of the TyG index in predicting the risk of CAN. The relationship between TyG trajectory and the occurrence of CAN in individuals with diabetes was examined using Kaplan-Meier curve and a multivariable Cox proportional hazards regression model. Subgroup analysis was used to assess the robustness of the results. Additionally, we explored the impact of intensive glycemia treatment on the relationship between trajectory of TyG index and CAN risk.

Results: In this study, these in the top quartile of the TyG index had a greater likelihood of developing CAN (TyG index Q4 vs. Q1 in Model II, OR = 1.29, 95% CI 1.03-1.62, P = 0.027). RCS indicated a rising trend in the TyG index in relation to the incidence of CAN. The AUC of the TyG index for predicting the occurrence of CAN was 0.636 (95% CI 0.620-0.651; P < 0.001), with the cut-off value of 0.208. During a 7-year follow-up period, three unique TyG trajectories were recognized: class 1 (n = 431, 23.26%), class 2 (n = 798, 27.57%), and class 3 (n = 293, 31.71%). Notable discrepancies in CAN risk across various trajectories were identified in Kaplan-Meier curve (P < 0.001). Cox regression analysis indicated that individuals in class 3 experienced a greater incidence of CAN in comparison to those in class 1 after adjusting for all covariates. Subgroup analysis found no significant effect modification in this relationship. Additionally, in the intensive glycemia group, class 2 had a reduced risk of CAN, while class 3 had an increased risk when compared to standard glycemia group.

Conclusion: Increased baseline levels and long-term trajectory of TyG index are associated with an increased incidence of CAN. Intensive glycemic therapy might influence the association between the trajectory of TyG index and the chance of developing CAN.