Predicting the risk of motor vehicle crash in the first year after cardioverter-defibrillator implantation
Crash prediction models based on health and driving data had a limited ability to distinguish individuals who subsequently crashed from individuals who did not. Observed crash risks are likely to be strongly influenced by unobserved changes in road exposure (the hours or miles of driving per week), limiting the application of these risk scores by clinicians and policy-makers.
Authors
- Daniel Daly‐Grafstein (ORCID: https://orcid.org/0000-0002-2331-5991)
- Andrew D. Krahn (ORCID: https://orcid.org/0000-0002-7982-1586)
- John A. Staples (ORCID: https://orcid.org/0000-0003-1397-1503)
- Nathaniel M. Hawkins (ORCID: https://orcid.org/0000-0003-1286-2014)
- Mayesha Khan (ORCID: https://orcid.org/0000-0002-3937-8874)
- Christian Steinberg (ORCID: https://orcid.org/0000-0003-4112-0028)
- Jeffrey R. Brubacher (ORCID: https://orcid.org/0000-0002-4866-4231)
- Shannon Erdelyi (ORCID: https://orcid.org/0000-0001-8364-364X)
- Herbert Chan (ORCID: https://orcid.org/0000-0003-0051-2076)
Institutions
- University of British Columbia (CA)
- Institut universitaire de cardiologie et de pneumologie de Québec (CA)
- Centre for Advancing Health Outcomes (CA)
Publication Details
- Journal
- Heart
- Published
- 2025-06-24
- DOI
- https://doi.org/10.1136/heartjnl-2025-326041
- Primary Topic
- Cardiac pacing and defibrillation studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Heart and Stroke Foundation of Canada
- Michael Smith Health Research BC
- Vancouver Coastal Health Research Institute