Abstract
OBJECTIVE: This study aimed to examine the relationship between the triglyceride-glucose index (TyG) and sarcopenia in patients with chronic kidney disease (CKD). The aim was to gain new insights into preventing and treating sarcopenia in CKD patients. METHODS: The study utilized data from two cohorts, including the NHANES 2011-2018 cohort in the United States and the 2018-2023 cohort in China. After applying uniform inclusion and exclusion criteria, 827 patients with CKD in the US cohort and 1,038 patients with CKD in the Chinese cohort were ultimately included in the study. The relationship between the TyG index and sarcopenia was analyzed using logistic regression modeling and multivariate adjustment. The dose-response relationship was also explored using restricted cubic spline (RCS) modeling. Subgroup analyses were also conducted to investigate the potential heterogeneity among different characteristic subgroups. RESULTS: The TyG index was found to be significantly and positively associated with sarcopenia in patients with CKD in both the United States and Chinese cohorts. In the US cohort, the risk of sarcopenia was increased 4.01-fold in the highest TyG quartile group compared with the lowest quartile group (P=0.002). In the Chinese cohort, the corresponding risk was increased 3.25-fold (P<0.001). Furthermore, the RCS analysis corroborated the nonlinear positive association. Subgroup analyses revealed that the correlation between TyG and sarcopenia was more pronounced in patients without diabetes and without metabolic syndrome. CONCLUSION: The TyG index may serve as a potential biomarker for assessing sarcopenia in CKD patients, thereby supporting the critical role of insulin resistance in developing sarcopenia. Further research is required to elucidate the precise mechanisms by which TyG is associated with sarcopenia and to develop tailored intervention strategies for different patient groups.