A validated multivariable machine learning model to predict cardio-kidney risk in diabetic kidney disease
CREDENCE (Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation; NCT02065791) and CANVAS (Canagliflozin Cardiovascular Assessment Study; NCT01032629/NCT01989754).
Authors
- Michael K. Hansen (ORCID: https://orcid.org/0000-0002-0062-0520)
- Craig A. Magaret (ORCID: https://orcid.org/0000-0002-5056-2664)
- Rhonda F Rhyne (ORCID: https://orcid.org/0000-0001-9891-9629)
- Muthiah Vaduganathan (ORCID: https://orcid.org/0000-0003-0885-1953)
- Javed Butler (ORCID: https://orcid.org/0000-0003-4267-6933)
- Serge Masson (ORCID: https://orcid.org/0000-0002-1446-0281)
- Yuxi Liu (ORCID: https://orcid.org/0009-0002-2876-8567)
- James L. Januzzi (ORCID: https://orcid.org/0000-0002-8338-1798)
- Naveed Sattar
Institutions
- Roche (Switzerland) (CH)
- Brigham and Women's Hospital (US)
- Harvard University (US)
- University of Mississippi (US)
- Massachusetts General Hospital (US)
- Janssen (United States) (US)
- Baylor Scott & White Health (US)
- University of Glasgow (GB)
Publication Details
- Journal
- Cardiovascular Diabetology
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1186/s12933-025-02779-5
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 8.81