Batch Enrollment for an Artificial Intelligence-Guided Intervention to Lower Neurologic Events in Patients With Unrecognized Atrial Fibrillation (BEAGLE)

Mayo Clinic1 site in 1 country1,225 target enrollmentNovember 2, 2020

ConditionsAtrial Fibrillation

Overview

Phase: Not Applicable
Intervention: Not specified
Conditions: Atrial Fibrillation
Sponsor: Mayo Clinic
Enrollment: 1225
Locations: 1
Primary Endpoint: Diagnosis of Atrial Fibrillation as Detected by Patch Application
Status: Completed
Last Updated: 3 years ago

Overview Investigators Eligibility Criteria Outcomes Sites Similar Trials

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.

Registry

clinicaltrials.gov

Start Date

November 2, 2020

End Date

January 27, 2022

Last Updated

3 years ago

Study Type

Observational

Sex

All

Investigators

Sponsor

Mayo Clinic

Responsible Party

Principal Investigator

Xiaoxi Yao

Principal Investigator

Mayo Clinic

Eligibility Criteria

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 \[AUC\]).