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The following is a summary of “Association between triglyceride glucose-body mass index and the trajectory of cardio-renal-metabolic multimorbidity: insights from multi-state modelling,” published in the March 2025 issue of the Cardiovascular Diabetology by Tang et al.

Despite prior research exploring the association between the triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes within the cardio-renal-metabolic (CRM) spectrum, its role in the progression of CRM multimorbidity remains largely unexplored. Furthermore, existing studies are constrained by limited sample sizes and inadequate consideration of competing risks from other CRM diseases. This study aimed to comprehensively assess the relationship between TyG-BMI and the development of CRM multimorbidity, utilizing data from the large-scale, prospective UK Biobank cohort. CRM multimorbidity was defined as the new onset of ischemic heart disease, type 2 diabetes mellitus, or chronic kidney disease during follow-up. To determine the independent association between TyG-BMI and CRM multimorbidity progression, multivariable Cox regression models were employed, evaluating first, double, and triple CRM disease occurrences. 

The predictive performance of these models was assessed using C-statistics, while restricted cubic spline analyses were conducted to examine dose-response relationships. Additionally, a multi-state model was implemented to evaluate the transition from baseline (CRM disease-free) to the first CRM disease, from a single CRM disease to double disease, and from double disease to triple disease, with disease-specific analyses incorporated. A total of 349,974 participants were included, with a mean age of 56.05 years (standard deviation [SD], 8.08), and 55.93% were female. Over a median follow-up period of approximately 14 years, 56,659 participants (16.19%) who were initially free of CRM disease developed at least one CRM condition. Among them, 8,451 (14.92%) progressed to double CRM disease, and 789 (9.34%) further advanced to triple CRM disease. In the unadjusted model, each SD increase in TyG-BMI was associated with a 47% higher risk of developing the first CRM disease, a 72% higher risk of progressing to double CRM disease, and a 95% higher risk of triple CRM disease, with corresponding C-statistics of 0.625, 0.694, and 0.764, respectively. 

Multi-state model analysis revealed that an elevated TyG-BMI was linked to a 32% increased risk of developing an initial CRM disease, a 24% increased risk of advancing to double CRM disease, and a 23% increased risk of further progression. Moreover, TyG-BMI exhibited significant associations with the onset of all individual first CRM diseases, except stroke, and played a critical role in transitions to double CRM disease. Subgroup analyses confirmed these associations despite observed interactions, and sensitivity analyses—including variations in time intervals for disease progression and an expanded CRM definition encompassing atrial fibrillation, heart failure, peripheral vascular disease, obesity, and dyslipidemia—further validated these findings. The results underscore the significant impact of TyG-BMI on both the onset and progression of CRM multimorbidity, highlighting its potential utility in predictive risk stratification and disease management strategies. These findings suggest that integrating TyG-BMI into CRM prevention and intervention frameworks could have substantial public health implications, reinforcing its role as a critical biomarker for identifying high-risk individuals and mitigating disease progression.

Source: cardiab.biomedcentral.com/articles/10.1186/s12933-025-02693-w