Abstract
Background
The triglyceride-glucose index (TyG) and its related indices are predominantly utilized for the effective assessment of insulin resistance. However, their predictive value concerning type 2 diabetes-related complications remains uncertain. Therefore, this study aims to investigate the potential association between TyG-related indices and type 2 diabetes-related complications through a retrospective analysis of two distinct populations.
Methodss
Established in 2016, the National Metabolic Management Center (MMC) serves as a comprehensive platform designed for the standardized diagnosis, treatment, and long-term follow-up of metabolic diseases, encompassing nearly 300 hospitals across various regions of China. Out of 8,669 initially hospitalized patients, 2,194 were selected for subsequent analysis. Patients were stratified into three groups according to the tertiles of TyG-related indices, with circulatory abnormalities (CA), diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic peripheral neuropathy (DPN) serving as the primary outcomes. Logistic regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between TyG-related indices and complications associated with type 2 diabetes. Finally, a validation analysis was performed on 9,715 samples from the MIMIC-IV 3.0 database to bolster the reliability and generalizability of the findings.
Results
Logistic regression analysis of patients in the MMC database revealed that, in fully adjusted models, each 1 SD increase in TyG and TyG-WC was significantly associated with an elevated risk of DKD. Restricted cubic spline (RCS) analysis indicated a non-linear inverse L-shaped relationship between TyG and DKD risk, while TyG-WC demonstrated a distinct dose-response relationship with DKD risk. Validation analysis conducted in the MIMIC-IV database further corroborated the significant association between TyG-related indices and the risk of DKD.
Conclusions
The findings of this study, involving both Chinese and American populations, indicate that TyG-related indices may serve as robust and independent potential biomarkers for assessing the risk of DKD in individuals with type 2 diabetes.