Batch Enrollment for AI-Guided Intervention to Lower Neurologic Events in Unrecognized AF

Completed

• Conditions: Atrial Fibrillation
• Interventions: Other: AI-enabled ECG-based Screening Tool for AF

• Registration Number: NCT04208971
• Lead Sponsor: Mayo Clinic

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2019-12-19
• Study First Submitted QC: 2019-12-19
• Study First Posted: 2019-12-23
• Study Start: 2020-11-02
• Primary Completion: 2022-01-27
• Study Completion: 2022-01-27
• Status Verified: 2022-08
• Last Update Submitted: 2022-08-16
• Last Update Posted: 2022-08-18

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 1225

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.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
BEAGLE Participants	AI-enabled ECG-based Screening Tool for AF	Adult patients who have not been previously diagnosed with AF, are eligible for anticoagulation and have AI-predicted risks based on a normal sinus rhythm ECG.

Primary Outcome Measures

Name	Time	Method
Diagnosis of Atrial Fibrillation as Detected by Patch Application	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 \[AUC\]).

Trial Locations

Locations (1)

Mayo Clinic; 🇺🇸 Rochester, Minnesota, United States