Non-linear association of triglyceride-glucose index with cardiovascular and all-cause mortality in T2DM patients with diabetic kidney disease: NHANES 2001–2018 retrospective cohort study

The triglyceride glucose (TyG) index is a cutting-edge and highly effective marker of insulin resistance, a crucial factor in the development and exacerbation of diabetic kidney disease (DKD). To date, there has been limited research on how the triglyceride-glucose (TyG) index affects the outlook for patients suffering from DKD. In this multicenter retrospective cohort study, the analysis recruited 2,203 DKD patients from the National Health and Nutrition Examination Survey (NHANES) dataset, which covers the US from 2001 to 2018. The research applied a Cox proportional hazards model with multiple variables to investigate the association of the TyG index with mortality outcomes. Restricted cubic splines (RCS) and methods for analyzing threshold effects were employed to identify possible non-linear relationships. Over nearly 19 years of follow-up, this study captured data on 753 all-cause and 231 cardiovascular disease-specific fatalities. Sophisticated statistical methods, including RCS and smoothing curve adjustments via penalized splines, helped identify distinctive patterns: The baseline TyG index was observed to have a U-shaped pattern related to overall mortality and an L-shape with cardiovascular diseases(CVD) mortality among individuals with DKD. Notably, TyG index below 9.15 for overall mortality and 9.27 for CVD mortality were linked to reduced death rates (HR = 0.65, 95% CI = 0.52–0.82 for all-cause; HR = 0.58, 95% CI = 0.43–0.83 for CVD). On the other hand, TyG index exceeding these benchmarks (greater than 9.15 for all-cause and 9.27 for CVD) correlated with increased all-cause mortality risks (HR = 1.21, 95% CI = 1.02–1.43) and showed a non-significant change in CVD mortality risks (HR = 1.07, 95% CI = 0.83–1.38). This study emphasizes the non-linear linkage involving the TyG index and death rates due to CVD and other factors in patients with DKD, demonstrating its effectiveness in estimating potential adverse events within this demographic.