Surrogate markers of insulin resistance and coronary artery disease in type 2 diabetes: U-shaped TyG association and insights from machine learning integration
Surrogate IR indices could be used as valuable tools for evaluating cardiometabolic risk in patients with T2D, who are at high risk for CAD. Integrating machine learning models further improved CAD prediction, underscoring their potential for better risk stratification. The observed association between these indices and CAD in T2D may help clarify the complex pathophysiology of CAD and offer insights for future research.
Authors
- Amirhossein Yadegar (ORCID: https://orcid.org/0000-0002-7370-9307)
- Seyed Arsalan Seyedi (ORCID: https://orcid.org/0000-0002-1504-3893)
- Manouchehr Nakhjavani (ORCID: https://orcid.org/0000-0002-9744-2328)
- Soghra Rabizadeh (ORCID: https://orcid.org/0000-0002-3752-302X)
- Fatemeh Mohammadi (ORCID: https://orcid.org/0000-0003-0601-9872)
- Kiana Seifouri
- Alireza Esteghamati (ORCID: https://orcid.org/0000-0001-5114-3982)
- Sepideh Yadegar
- Kiavash Mokhtarpour (ORCID: https://orcid.org/0000-0001-5010-2062)
- Ehsan Bahrami Hazaveh
Institutions
- Tehran University of Medical Sciences (IR)
Publication Details
- Journal
- Lipids in Health and Disease
- Published
- 2025-03-15
- DOI
- https://doi.org/10.1186/s12944-025-02526-5
- Citations
- 16
- Primary Topic
- Cardiovascular Function and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 22.21