Using population-wide electronic health records for timely contemporary assessment of cardiovascular disease risk prediction model performance: COVID-19 impact on the SCORE2 models
The SCORE2-FOMs demonstrated good calibration and discrimination, suggesting that no adaptation is needed in response to the COVID-19 pandemic. Short-term EHRs provide a valuable resource for timely contemporary risk model validation and, if necessary, for adaptation according to shifts in CVD trends.
Authors
- Elena Raffetti (ORCID: https://orcid.org/0000-0001-8742-3986)
- Alexia Sampri (ORCID: https://orcid.org/0000-0002-4889-7983)
- Anna J. Stevenson (ORCID: https://orcid.org/0000-0002-0435-3562)
- A. Jamie Wood (ORCID: https://orcid.org/0000-0002-6119-852X)
- S. R. Wild
- Stelios Boulitsakis Logothetis (ORCID: https://orcid.org/0009-0004-7622-9423)
- Spencer Keene (ORCID: https://orcid.org/0000-0003-0622-6476)
- Lisa Pennells (ORCID: https://orcid.org/0000-0002-8594-3061)
- Carmen Petitjean
- Fionna Chalmers
- Lois G. Kim (ORCID: https://orcid.org/0000-0002-4552-3820)
- Kamlesh K. Khunti (ORCID: https://orcid.org/0000-0003-2343-7099)
- Geneviève Cézard (ORCID: https://orcid.org/0000-0002-3011-7416)
- S H Y Ip
- Thomas Bolton
- Emanuele Di Angelantonio
- Spiros Denaxas
- Naveed Sattar
- Stephen Kaptoge
Institutions
- University College Hospital (GB)
- University of Leicester (GB)
- University of Cambridge (GB)
- Karolinska Institutet (SE)
- Victor (Japan) (JP)
- British Heart Foundation (GB)
- National Institute for Health and Care Research (GB)
- Human Technopole (IT)
- UCL Biomedical Research Centre (GB)
- Health Data Research UK (GB)
- NIHR Leicester Biomedical Research Centre (GB)
- University College London (GB)
- University of Glasgow (GB)
- University of Edinburgh (GB)
Publication Details
- Journal
- European Journal of Preventive Cardiology
- Published
- 2026-03-27
- DOI
- https://doi.org/10.1093/eurjpc/zwag179
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00