Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): Pilot Study (FIND-AF)

Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): Pilot Study of a Risk Score for Early Detection of Atrial Fibrillation

The purpose of this study is to trial a new intervention - risk-guided AF screening using an EHR-based risk score and remote ECG monitoring process - and to characterise individuals at elevated predicted AF risk.

Study Overview

• Status: Active, not recruiting
• Conditions: Heart Diseases; Cardiovascular Diseases; Atrial Fibrillation
• Intervention / Treatment: Other: Development of an algorithm

Detailed Description

This pilot study will use a post-market device within its intended purpose and involve a change in standard care - that is the offer of ECG monitoring for individuals at risk of AF to understand whether this leads to an increase in detection rates of AF, and follow-through prescription of oral anticoagulation.

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.

• Study Type: Observational
• Enrollment (Estimated): 1955

Contacts and Locations

Study Locations

• United Kingdom
  • West Yorkshire
    • Leeds, West Yorkshire, United Kingdom, LS2 9JT
      • University of Leeds

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients aged >30 will be invited to screening in primary care from information present in their electronic health record (EHR) and their FIND-AF score. They will be given Zenicor ECG devices for up to period of 3 week during which they will be asked to record 4 daily ECG recordings.

Those patients who are higher risk for AF based on their FIND-AF score, will be reviewed further for multi-modal phenotyping.

Patient with new AF detected will be managed by their primary care clinicians.

Description

Inclusion Criteria:

• Age at enrolment ≥30 years
• Men with CHA2DS2VASC ≥ 2 and women with a CHA2DS2VASC ≥ 3

Exclusion Criteria:

• Known diagnosis of AF
• 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

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
To determine whether detection rates of AF during ECG monitoring are higher amongst participants identified as higher risk of AF, compared with those identified as lower risk	Rate ratio of AF detection rates during ECG monitoring in participants identified as higher risk by FIND-AF compared with participants identified as lower risk	6 months
To determine whether detection rates of AF during ECG monitoring are higher amongst participants identified as higher risk of AF, compared with those identified as lower risk	Rate ratio of AF detection rates during ECG monitoring in participants identified as higher risk by FIND-AF compared with participants identified as lower risk	5 years
To determine whether detection rates of AF during ECG monitoring are higher amongst participants identified as higher risk of AF, compared with those identified as lower risk	Rate ratio of AF detection rates during ECG monitoring in participants identified as higher risk by FIND-AF compared with participants identified as lower risk	10 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
To determine, of participants who are detected as having AF during ECG monitoring, the proportion who subsequently receive oral anticoagulation prescription	Number (%) of participants who receive an oral anticoagulant prescription after diagnoses of AF during ECG monitoring diagnosed	6 months
To determine, of participants who are detected as having AF during ECG monitoring, the proportion who subsequently receive oral anticoagulation prescription	Number (%) of participants who receive an oral anticoagulant prescription after diagnoses of AF during ECG monitoring diagnosed	5 years
To determine, of participants who are detected as having AF during ECG monitoring, the proportion who subsequently receive oral anticoagulation prescription	Number (%) of participants who receive an oral anticoagulant prescription after diagnoses of AF during ECG monitoring diagnosed	10 years

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
To determine the AF detection rates amongst participants who are identified as higher risk and lower risk, including in the periods outside of ECG monitoring to determine the incremental yield that is achieved by ECG monitoring over routine care	Risk of recorded AF diagnosis in EHR between individuals identified at higher and lower risk at six months after enrolment	6 months
To determine how diagnostic yield, C statistic/AUROC, NPV, PPV, sensitivity and specificity, varies at different cut off points of the FIND-AF risk score	Diagnostic yield, PPV, NPV, sensitivity and specificity amongst participants who receive ECG monitoring, to understand whether the numeric score at which a clinician implements ECG monitoring can be optimised	6 months
To determine the C statistic/AUROC, NPV, PPV, sensitivity and specificity for alternative approaches to guide systematic AF screening in participants who receive ECG monitoring:	Diagnostic yield, C statistic/AUROC, PPV, NPV, sensitivity and specificity in patients who are : CHA2DS2VASC≥3 in men and CHA2DS2VASC≥4 in women, age ≥70 years and age 75 and 76 years	6 months
To determine if yield from ECG monitoring varies across age groups (≥75 years and ≤75 years) and sex (men and women)	AF detection rates and risks comparing higher and lower risk participants stratified by subgroup	6 months
To determine recruitment rates, overall study.	Number (%) of people who consent to participate compared to number of people who are invited	Up to 24 months
To determine withdrawal rates	Number (%) of people who consent to participate but subsequently withdraw consent / decline ECG monitoring	Up to 24 months
To determine if there are differences between those who participate and those that do not participate	Characteristics of those who consent to participate and do not consent to participate	Up to 24 months
To determine if there are differences between those who participate and those that withdraw	Characteristics of those who participate and those that withdraw	Up to 24 months
To determine the adherence of ECG recordings amongst participants	Mean number of recordings compared to the maximum stipulated Number (%) of participants who record less than 50% of stipulated amount of ECG recordings	Up to 24 months
To determine the number of ECG recordings that need to be reviewed for possible AF detection	Number (%) of ECG recordings flagged as abnormal by the algorithm within ECG recorder software that require manual review to assess for potential AF diagnosis	Up to 24 months
To determine the burden of other arrhythmias that are diagnosed through ECG monitoring in participants identified as higher risk and lower risk	Number (%) of participants who are diagnosed with other arrhythmias ( (atrial tachycardia, supraventricular tachycardia, 2nd degree AV block, high grade AV block or 3rd degree heart block, pause/asystole, ventricular tachycardia, ventricular fibrillation) during ECG monitoring in participants	Up to 24 months
To determine the burden of non-diagnostic rhythm reports from ECG monitoring	Number (%) of participants who have an ECG monitoring period with consistent poor quality which precludes a diagnostic result	Up to 24 months
To determine recruitment rates - research clinic appointment	Number (%) of people who consent to attend a research clinic appointment compared to number of people who are invited	Up to 24 months
To determine what other conditions and cardiovascular risk factors are identified amongst participants classified as higher risk for AF at research clinic	Descriptive statistics of demographics, morbidities, medications, and cardiac ultrasound findings	End of recruitment
To observe the clinical outcomes of participants that participate in the study, and whether there is a difference between participants identified as higher and lower risk?	Number (%) of participants who experience at 5 years: AF; Ischaemic stroke; Haemorrhagic stroke; Systemic embolism; Gastrointestinal or intracranial bleeding; Death; Chronic obstructive pulmonary disease; Chronic kidney disease; Heart failure; Diabetes mellitus; Myocardial infarction; Peripheral vascular disease; Valvular heart disease	5 years from completion of recruitment
To observe the clinical outcomes of participants that participate in the study, and whether there is a difference between participants identified as higher and lower risk?	Number (%) of participants who experience at 10 years: AF; Ischaemic stroke; Haemorrhagic stroke; Systemic embolism; Gastrointestinal or intracranial bleeding; Death; Chronic obstructive pulmonary disease; Chronic kidney disease; Heart failure; Diabetes mellitus; Myocardial infarction; Peripheral vascular disease; Valvular heart disease	10 years from completion of recruitment

Collaborators and Investigators

• Sponsor: University of Leeds
• Collaborators: The Leeds Teaching Hospitals NHS Trust; British Heart Foundation; Daiichi Sankyo
• Investigators: Principal Investigator: Chris Gale, Yes, University of Leeds

Publications and helpful links

General Publications

• 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.

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2023
• Primary Completion (Actual): June 16, 2025
• Study Completion (Estimated): February 28, 2026

Study Registration Dates

• First Submitted: May 18, 2023
• First Submitted That Met QC Criteria: May 31, 2023
• First Posted (Actual): June 12, 2023

Study Record Updates

• Last Update Posted (Estimated): September 17, 2025
• Last Update Submitted That Met QC Criteria: September 10, 2025
• Last Verified: September 1, 2025

More Information

Terms related to this study

• Keywords: Stroke; Atrial fibrillation; Data Science; Computation
• Additional Relevant MeSH Terms: Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Pathologic Processes; Arrhythmias, Cardiac; Pathological Conditions, Signs and Symptoms; Stroke; Cardiovascular Diseases; Heart Diseases; Atrial Fibrillation
• Other Study ID Numbers: 318197_V1.0_230509

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: No individual participant data will be shared.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No