Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study
Updating models, by adjusting model coefficients to better reflect the characteristics and risk factors of older adults, improves CVD risk prediction in a large cohort of relatively healthy Caucasian population aged 70+. Further external validation in diverse older populations including those with frailty and multimorbidity is recommended before clinical implementation.
Authors
- Shiva Ganjali (ORCID: https://orcid.org/0000-0002-7446-3927)
- Andrew Tonkin (ORCID: https://orcid.org/0000-0001-5291-0610)
- Mohammadreza Mohebbi (ORCID: https://orcid.org/0000-0001-9713-7211)
- E. Chowdhury (ORCID: https://orcid.org/0000-0002-9709-794X)
- Mark Raymond Nelson (ORCID: https://orcid.org/0000-0001-9941-7161)
- Robyn L. Woods (ORCID: https://orcid.org/0000-0003-1249-6149)
- John J. McNeil (ORCID: https://orcid.org/0000-0002-1049-5129)
- Mojtaba Lotfaliany (ORCID: https://orcid.org/0000-0001-6594-9004)
- Christopher M. Reid (ORCID: https://orcid.org/0000-0001-9173-3944)
- Rory Wolfe (ORCID: https://orcid.org/0000-0002-2126-1045)
- Michael Berk (ORCID: https://orcid.org/0000-0002-5554-6946)
Institutions
- University of Tasmania (AU)
- Barwon Health (AU)
- Deakin University (AU)
- Curtin University (AU)
- Australian Centre for Heart Health (AU)
- Monash University (AU)
Publication Details
- Journal
- Heart
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1136/heartjnl-2025-325665
- Citations
- 2
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 2.71