Key result
TyHGB index links to ~11% higher DKD odds in T2D, demonstrating superior discrimination over TyG.
Why the study?
The TyG index lacks integration of HDL-C and adiposity measures pivotal in diabetic kidney disease pathogenesis, so the associative value of the novel TyHGB index was evaluated in T2DM patients.
Does the TyHGB index provide superior associative value for diabetic kidney disease compared to the TyG index in adults with type 2 diabetes mellitus?
Cross-Sectional (n=1,382)
Yes
Does the TyHGB index provide superior associative value for diabetic kidney disease compared to the TyG index in adults with type 2 diabetes mellitus?
Answers are grounded in this paper and cite their sources.
The novel TyHGB index is a superior biomarker compared to the TyG index for identifying diabetic kidney disease in patients with type 2 diabetes.
Background: The triglyceride-glucose (TyG) index is a recognized surrogate marker of insulin resistance but lacks integration of high-density lipoprotein cholesterol (HDL-C) and adiposity measures, which are pivotal in the pathogenesis of diabetic kidney disease (DKD). The novel triglyceride-high-density lipoprotein-glucose-body (TyHGB) index, combining TG/HDL-C ratio, fasting blood glucose (FBG), and body mass index (BMI), may offer a more comprehensive metabolic profile. This study aimed to evaluate the associative value of TyHGB for DKD in type 2 diabetes mellitus (T2DM) patients. Methods: A retrospective cross-sectional analysis of 1,382 adults with T2DM was conducted. We employed multivariable logistic regression, restricted cubic spline (RCS) analysis, and subgroup analyses to assess the independent and non-linear association of the TyHGB index with DKD. Receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate and compare its associative performance against the TyG index. Results: Among the participants, 286 (20.7%) were diagnosed with DKD. After full adjustment for demographic, clinical, and biochemical confounders, TyHGB was independently associated with DKD (OR = 1.11, 95%CI:1.05-1.17, p<0.001). RCS analysis revealed a significant non-linear relationship, with a sharp increase in DKD risk beyond a TyHGB threshold of 8.74. The TyHGB index demonstrated superior discriminative ability (AUC = 0.775, 95% CI: 0.747-0.803) compared to the TyG index (AUC = 0.644, p<0.001). Incorporating TyHGB into a baseline clinical model significantly improved risk association (AUC increased from 0.715 to 0.788, p<0.001) and provided substantial reclassification improvement (NRI = 0.647, IDI = 0.067). Conclusion: The TyHGB index exhibits a robust, independent, and non-linear association with DKD risk in T2DM patients and outperforms the established TyG index. As a readily accessible composite metric, it holds significant promise as a superior tool for early identification and risk stratification of DKD in clinical practice.
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Yang et al. (2026) conducted a cross-sectional in Diabetic kidney disease in type 2 diabetes mellitus (n=1,382). TyHGB index vs. TyG index was evaluated on Presence of diabetic kidney disease (DKD) (OR 1.11, 95% CI 1.05-1.17, p=<0.001). The TyHGB index was independently associated with diabetic kidney disease in patients with type 2 diabetes (OR 1.11) and demonstrated superior discriminative ability compared to the TyG index.
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