Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study
Our findings establish CMI as a significant predictor of cardiovascular events in the aging population, with the relationship partially mediated through hypertension and insulin resistance pathways. The validated nomogram, developed using longitudinal data from a substantial elderly cohort, incorporates CMI to enable preclinical risk stratification, supporting timely preventive strategies.
Authors
- Lin Xin (ORCID: https://orcid.org/0000-0002-4589-8593)
- Chong Sheng
- Zhiyang Yin (ORCID: https://orcid.org/0009-0005-7606-2309)
- Ping Zhang (ORCID: https://orcid.org/0000-0001-9163-6191)
- Yuan-Xi Luo
- Dongjin Wang (ORCID: https://orcid.org/0000-0002-2792-1067)
- Yunxing Xue
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Nanjing Drum Tower Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2025-04-01
- DOI
- https://doi.org/10.3389/fendo.2025.1551779
- Citations
- 3
- Primary Topic
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Type
- article
- Field-Weighted Citation Impact
- 3.88