Identifying and ranking non-traditional risk factors for cardiovascular disease prediction in people with type 2 diabetes
This study identifies numerous replicated non-traditional CVD risk factors for people with T2DM, providing insight to improve guideline recommended risk prediction models which currently overlook these features.
Authors
- Amand F. Schmidt (ORCID: https://orcid.org/0000-0003-1327-0424)
- Folkert W. Asselbergs (ORCID: https://orcid.org/0000-0002-1692-8669)
- Katarzyna Dziopa (ORCID: https://orcid.org/0000-0001-9497-0208)
- Nish Chaturvedi (ORCID: https://orcid.org/0000-0002-6211-2775)
Institutions
- National Institute for Health and Care Research (GB)
- UCL Biomedical Research Centre (GB)
- Health Data Research UK (GB)
- Amsterdam University Medical Centers (NL)
- University College London (GB)
- University of Amsterdam (NL)
Publication Details
- Journal
- Communications Medicine
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1038/s43856-025-00785-y
- Citations
- 5
- Primary Topic
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Type
- article
- Field-Weighted Citation Impact
- 6.47
Funders
- Wellcome Trust
- European Federation of Pharmaceutical Industries and Associations
- Government of the United Kingdom
- UK Research and Innovation
- National Institute for Health and Care Research
- British Heart Foundation
- University College London
- Rosetrees Trust
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Northwest Regional Development Agency
- National Institutes of Health
- HORIZON EUROPE Framework Programme
- Medical Research Council