Abstract
Purpose: The objective of this study is to investigate the potential of TyG in forecasting the onset of diabetic kidney disease (DKD) and diabetic peripheral neuropathy (DPN).
Methods: A total of 2048 patients were enrolled in this study. The primiary outcomes are DKD and DPN. Quantile regression analysis was employed to investigate the implicit factors of TyG quartiles. Subsequently, based on the implicit factors, logistic regression models were constructed to further examine the relationship between TyG and DKD and DPN.
Results:In the baseline, TyG exhibited higher values across patients with DKD, DPN, and co-existence of DKD and DPN (DKD+DPN) in T2DM. Univariate logistic regressions demonstrated a significant association between an elevated TyG and an increased risk of DKD (OR = 1.842, [95% CI] 1.317–2.578, P for trend < 0.01), DPN (OR = 1.516, [95% CI] 1.114–2.288, P for trend < 0.05), DKD+DPN (OR = 2.088, [95% CI] 1.429–3.052, P for trend < 0.05) . Multivariable logistic regression models suggested a statistically significant increase in the risk of DKD (OR = 1.581, [95% CI] 1.031–2.424, p<0.05) DKD+DPN (OR = 1.779, [95% CI] 1.091–2.903, p<0.05 ) after adjusting the implicit factors of TyG quartiles. However, no significant relationship was observed between TyG and DPN in the multivariable regression analysis.
Conclusion: Elevated TyG was significantly associated with an increased risk of DKD in T2DM, but no significant relationship was showed with DPN. This finding provided further evidence for the clinical significance of integrating the TyG index into the initial assessment of diabetic microvascular complications.