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

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04208971
Recruitment Status : Not yet recruiting
First Posted : December 23, 2019
Last Update Posted : December 23, 2019
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 Phase
Atrial Fibrillation Other: AI-enabled ECG-based Screening Tool for AF Not Applicable

Study Design
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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 1000 participants
Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Screening
Official Title: Batch Enrollment for an Artificial Intelligence-Guided Intervention to Lower Neurologic Events in Patients With Unrecognized Atrial Fibrillation (BEAGLE)
Estimated Study Start Date : October 2020
Estimated Primary Completion Date : October 2021
Estimated Study Completion Date : October 2022

Resource links provided by the National Library of Medicine


Arms and Interventions
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Arm Intervention/treatment
Experimental: Positive Screening
Patients who have artificial intelligence-detected atrial fibrillation and are eligible for anticoagulation.
 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.
Active Comparator: Negative Screening
Patients who do not have artificial intelligence-detected atrial fibrillation but are similar to the positive screening group in other aspects.
 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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Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • Adult patients who have AI-detected AF and are eligible for anticoagulation will be eligible for the first group of patients.
  • Adult patients who do not have AI-detected AF but are similar to the first group in other aspects will be eligible as part of the second group of patients.

Exclusion Criteria:

  • Patients who are 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


Contacts
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Contact: Emma Behnken 507-293-0177 Behnken.Emma@mayo.edu

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: December 23, 2019
Last Verified: December 2019

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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