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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 : July 21, 2020
Sponsor:
Information provided by (Responsible Party):
Xiaoxi Yao, Mayo Clinic

Tracking Information
First Submitted Date December 19, 2019
First Posted Date December 23, 2019
Last Update Posted Date July 21, 2020
Estimated Study Start Date October 2020
Estimated Primary Completion Date October 2021   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: December 19, 2019)
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]).
Original Primary Outcome Measures Same as current
Change History
Current Secondary Outcome Measures Not Provided
Original Secondary Outcome Measures Not Provided
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
 
Descriptive Information
Brief Title Batch Enrollment for AI-Guided Intervention to Lower Neurologic Events in Unrecognized AF
Official Title Batch Enrollment for an Artificial Intelligence-Guided Intervention to Lower Neurologic Events in Patients With Unrecognized Atrial Fibrillation (BEAGLE)
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 Provided
Study Type Observational
Study Design Observational Model: Cohort
Time Perspective: Prospective
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
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.
Condition Atrial Fibrillation
Intervention 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.
Study Groups/Cohorts 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.
Intervention: Other: AI-enabled ECG-based Screening Tool for AF
Publications * Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruitment Information
Recruitment Status Not yet recruiting
Estimated Enrollment
 (submitted: December 19, 2019)
1000
Original Estimated Enrollment Same as current
Estimated Study Completion Date October 2022
Estimated Primary Completion Date October 2021   (Final data collection date for primary outcome measure)
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.
Sex/Gender
Sexes Eligible for Study: All
Ages 18 Years and older   (Adult, Older Adult)
Accepts Healthy Volunteers No
Contacts
Contact: Emma Behnken 507-293-0177 Behnken.Emma@mayo.edu
Listed Location Countries Not Provided
Removed Location Countries  
 
Administrative Information
NCT Number NCT04208971
Other Study ID Numbers 19-012411
Has Data Monitoring Committee No
U.S. FDA-regulated Product
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
IPD Sharing Statement Not Provided
Responsible Party Xiaoxi Yao, Mayo Clinic
Study Sponsor Mayo Clinic
Collaborators Not Provided
Investigators
Principal Investigator: Xiaoxi Yao, PhD, MPH Mayo Clinic
Principal Investigator: Peter Noseworthy, MD Mayo Clinic
PRS Account Mayo Clinic
Verification Date July 2020