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

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ClinicalTrials.gov Identifier: NCT04208971
Recruitment Status : Enrolling by invitation
First Posted : December 23, 2019
Last Update Posted : November 12, 2020
Sponsor:
Information provided by (Responsible Party):
Xiaoxi Yao, Mayo Clinic

Study Description
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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.

Condition or disease Intervention/treatment
Atrial Fibrillation Other: AI-enabled ECG-based Screening Tool for AF

Study Design
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Study Type : Observational
Estimated Enrollment : 1000 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Batch Enrollment for an Artificial Intelligence-Guided Intervention to Lower Neurologic Events in Patients With Unrecognized Atrial Fibrillation (BEAGLE)
Actual Study Start Date : November 2, 2020
Estimated Primary Completion Date : October 2021
Estimated Study Completion Date : October 2022

Resource links provided by the National Library of Medicine


Groups and Cohorts
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Group/Cohort Intervention/treatment
BEAGLE Participants
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.
 Other: AI-enabled ECG-based Screening Tool for AF
A novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool to improve atrial fibrillation diagnosis and stroke prevention.


Outcome Measures
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Primary Outcome Measures :
  1. 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]).


Eligibility Criteria
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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
This study aims to enroll 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.
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.
Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04208971


Locations
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United States, Minnesota
Mayo Clinic
Rochester, Minnesota, United States, 55905
Sponsors and Collaborators
Mayo Clinic
Investigators
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Principal Investigator: Xiaoxi Yao, PhD, MPH Mayo Clinic
Principal Investigator: Peter Noseworthy, MD Mayo Clinic
More Information
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Responsible Party: Xiaoxi Yao, Principal Investigator, Mayo Clinic
ClinicalTrials.gov Identifier: NCT04208971    
Other Study ID Numbers: 19-012411
First Posted: December 23, 2019    Key Record Dates
Last Update Posted: November 12, 2020
Last Verified: November 2020

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
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Atrial Fibrillation
Arrhythmias, Cardiac
Heart Diseases
Cardiovascular Diseases
Pathologic Processes