Risk prediction in people with acute myocardial infarction in England: a cohort study using data from 1521 general practices
These models can support clinicians in identifying patients at increased risk of short-term adverse outcomes following AMI, whether newly diagnosed or with a prior history. This can inform monitoring strategies and secondary prevention and guide patient counselling on modifiable risk factors.
Authors
- Darren Mark Ashcroft (ORCID: https://orcid.org/0000-0002-2958-915X)
- Matthew Carr (ORCID: https://orcid.org/0000-0001-7336-1606)
- Harindra C. Wijeysundera (ORCID: https://orcid.org/0000-0001-8464-1080)
- Corneliu Arsene (ORCID: https://orcid.org/0000-0001-5982-0503)
- Azfar Zaman (ORCID: https://orcid.org/0000-0003-4891-8892)
- Evangelos Kontopantelis (ORCID: https://orcid.org/0000-0001-6450-5815)
- Mamas A. Mamas (ORCID: https://orcid.org/0000-0001-9241-8890)
- Salwa S. Zghebi (ORCID: https://orcid.org/0000-0002-7978-1094)
- Nicholas Chew (ORCID: https://orcid.org/0000-0002-0640-0430)
- Kamlesh K. Khunti (ORCID: https://orcid.org/0000-0003-2343-7099)
- Rosa Parisi (ORCID: https://orcid.org/0000-0002-0968-9153)
Institutions
- University of Leicester (GB)
- University of Toronto (CA)
- Manchester Academic Health Science Centre (GB)
- Freeman Hospital (GB)
- University of Manchester (GB)
- National Institute for Health and Care Research (GB)
- National University Health System (SG)
- NIHR Manchester Biomedical Research Centre (GB)
- Keele University (GB)
- Newcastle University (GB)
Publication Details
- Journal
- BMJ Open
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1136/bmjopen-2024-094961
- Primary Topic
- Acute Myocardial Infarction Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute for Health and Care Research
- Department of Health and Social Care
- Heart Research UK