Work

Longitudinal TyG–BMI trajectories predict carotid atherosclerosis progression in a Chinese retrospective cohort

Year: 2025

Type: article

Abstract: Background: Carotid atherosclerosis (CAS) is a major precursor of ischemic stroke, underscoring the importance of early identification of reliable metabolic risk markers. Insulin resistance and metabolic dysfunction are recognized as key contributors to CAS development, and the triglyceride-glucose body mass index (TyG-BMI) has emerged as a promising surrogate biomarker. Methods: In this retrospective cohort study, we analyzed 2,329 Chinese adults who underwent serial health examinations, with a median follow-up of 1,826 days. Using latent class trajectory modeling, two distinct TyG-BMI trajectories were identified: stable (Class 1) and rising (Class 2). Results: CAS progression was observed in 46% of participants, with a higher incidence in the rising trajectory group (52.9% vs. 39.9%). Multivariable Cox regression showed that a rising TyG-BMI trajectory was independently associated with an increased risk of CAS progression (adjusted HR = 1.19, 95% CI: 1.04-1.36), particularly among younger adults (≤50 years, HR = 2.04) and women (HR = 1.88). Sensitivity analyses confirmed robustness. Extended prediction models incorporating trajectories demonstrated good calibration, higher discrimination, and greater clinical net benefit in decision curve analysis. Conclusion: These findings underscore the value of dynamic TyG-BMI monitoring in vascular risk stratification and targeted prevention. To our knowledge, this is the first large-scale study to establish the predictive value of longitudinal TyG-BMI trajectories for CAS progression in a Chinese population.

Source: Frontiers in Cardiovascular Medicine

DOI: 10.3389/fcvm.2025.1672514

Authors: Congling Wang, Ying Xu, Yongpeng Zhang, Ping Peng, Jing Li, Honghua Ye

Institution: Ningbo Medical Center Lihuili Hospital

Language: English

Topic: Diabetes, Cardiovascular Risks, and Lipoproteins

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801