NCT04208971CompletedNot Applicable
Batch Enrollment for an Artificial Intelligence-Guided Intervention to Lower Neurologic Events in Patients With Unrecognized Atrial Fibrillation (BEAGLE)
Conditions
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Mayo Clinic
- Enrollment
- 1,225
- Locations
- 1
- Primary Endpoint
- Diagnosis of Atrial Fibrillation as Detected by Patch Application
Study Overview
Brief Summary
This is a prospective study to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis of unrecognized atrial fibrillation (AF) and stroke prevention.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Age ≥18 years
- •Had a 10-second 12-lead ECG done at Mayo Clinic
- •Men with CHA2DS2-VASc ≥2 or women with CHA2DS2-VASc ≥3
Exclusion Criteria
- •Diagnosed atrial fibrillation or atrial flutter
- •Missing date of birth or sex in the electronic health record (EHR)
- •A history of intracranial bleeding
- •A history of end-stage kidney disease
- •Have an implantable cardiac monitoring device, including a pacemaker, a defibrillator, or implanted loop recorder
- •Deemed by research personnel to have limitations that would prevent them from being able to provide informed consent, use the patch, or complete interviews will not be included.
Outcomes
Primary Outcomes
Diagnosis of Atrial Fibrillation as Detected by Patch Application
Time Frame: Three Months
The data will be used to examine the performance of the algorithm in detecting unrecognized atrial fibrillation (e.g. positive predictive value, negative predictive value, sensitivity, specificity, and area under the curve \[AUC\]).
Secondary Outcomes
No secondary outcomes reported
Investigators
Xiaoxi Yao
Principal Investigator
Mayo Clinic
Study Sites (1)
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