Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): Pilot Study
NCT ID: NCT05898165
Last Updated: 2025-09-17
Study Results
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Basic Information
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ACTIVE_NOT_RECRUITING
1955 participants
OBSERVATIONAL
2023-10-01
2026-02-28
Brief Summary
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Detailed Description
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Starting with the population that are eligible for oral anticoagulation (men with a CHA2DS2VASC ≥ 2 and women with a CHA2DS2VASC ≥ 3), but without AF, this pilot study will use FIND-AF within its intended purpose to predict the absolute risk of AF diagnosis for individuals within the next 6 months. It will be observed whether systematic AF screening leads to higher detection rates of AF in individuals at higher risk for AF than individuals at lower risk for AF.
This will give pilot data for whether systematic screening for AF in individuals at higher AF risk results in an incrementally higher yield of AF detection compared with screening approaches that have been targeted by age and risk of AF-related stroke. If the pilot shows that detection rates for AF are higher in the group at higher AF risk, then it would be suitable to plan a randomised controlled trial to determine whether systematic AF screening guided by AF risk increases detection rates of AF compared with routine care, and whether this is associated with a lower rate of stroke. The detection rates during systematic AF screening in this pilot study for individuals at higher and lower risk can establish power calculations required for a full-scale study and whether the numeric score at which a clinician would implement the intervention can be optimised.
In addition, this pilot study will establish the technical, logistic and administrative feasibility of a full-scale remote AF screening study including issues of recruitment and protocol adherence. It will also inform as to whether individuals diagnosed with AF by systematic AF screening in the community will receive oral anticoagulation interventions in primary care, and thus whether treatment of screen-detected AF in a full-scale study should be implemented in primary care or in secondary care under cardiology.
Finally this study will offer participants at higher AF risk the opportunity to attend a research clinic to determine whether these individuals have risk factors and comorbidities that could be identified and treated to reduce their subsequent risk of AF and other adverse events. This will establish whether individuals at risk of AF will attend for review, and their burden of modifiable risk factors for AF. This will establish power calculations that would be required for a full-scale study to test the hypothesis that primary prevention of AF is possible through interventions aimed at individuals at risk of AF.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Development of an algorithm
Prospective verification of a developed algorithm to predict the risk of a new onset Atrial Fibrillation
Eligibility Criteria
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Inclusion Criteria
* Men with CHA2DS2VASC ≥ 2 and women with a CHA2DS2VASC ≥ 3
Exclusion Criteria
* On anticoagulation therapy
* On the palliative care register
* Unable to give written informed consent for participation in the study
* Unable to adhere to the study requirements
30 Years
ALL
No
Sponsors
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British Heart Foundation
OTHER
Daiichi Sankyo
INDUSTRY
The Leeds Teaching Hospitals NHS Trust
OTHER
University of Leeds
OTHER
Responsible Party
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Dr Christopher Gale
Professor of Cardiovascular Medicine
Principal Investigators
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Chris Gale, Yes
Role: PRINCIPAL_INVESTIGATOR
University of Leeds
Locations
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University of Leeds
Leeds, West Yorkshire, United Kingdom
Countries
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References
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Hamilton E, Shone L, Reynolds C, Wu J, Nadarajah R, Gale C. Perceptions of healthcare professionals on the use of a risk prediction model to inform atrial fibrillation screening: qualitative interview study in English primary care. BMJ Open. 2025 Feb 5;15(2):e091675. doi: 10.1136/bmjopen-2024-091675.
Nadarajah R, Wahab A, Reynolds C, Raveendra K, Askham D, Dawson R, Keene J, Shanghavi S, Lip GYH, Hogg D, Cowan C, Wu J, Gale CP. Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): pilot study of an electronic health record machine learning algorithm-guided intervention to identify undiagnosed atrial fibrillation. Open Heart. 2023 Sep;10(2):e002447. doi: 10.1136/openhrt-2023-002447.
Other Identifiers
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318197_V1.0_230509
Identifier Type: -
Identifier Source: org_study_id
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