Back to resultsECG AI-Guided Screening for Low Ejection Fraction (EAGLE)
Primary Purpose
Asymptomatic Left Ventricular Systolic Dysfunction (Disorder), Heart Failure
Status
Completed
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
AI-enabled ECG-based Screening Tool
Sponsored by
About this trial
This is an interventional screening trial for Asymptomatic Left Ventricular Systolic Dysfunction (Disorder)
Eligibility Criteria
Inclusion Criteria:
- Primary care clinicians who are part of a participating care team that care for adult patients and have the ability to order ECG and TTE (this includes physicians, nurse practitioners, and physician assistants).
Exclusion Criteria:
- Primary care clinicians working in pediatrics, acute care, nursing homes, and resident care teams.
Sites / Locations
- Mayo Clinic in Rochester
Arms of the Study
Arm 1
Arm 2
Arm Type
Experimental
No Intervention
Arm Label
Intervention
Control
Arm Description
Care teams randomized to intervention will have access to the screening tool.
Care teams randomized to control will continue routine practice.
Outcomes
Primary Outcome Measures
New Diagnosis of Low Ejection Fraction (defined as ejection fraction ≤50%)
Ejection fraction obtained by echocardiography.
Secondary Outcome Measures
Full Information
1. Study Identification
Unique Protocol Identification Number
NCT04000087
Brief Title
ECG AI-Guided Screening for Low Ejection Fraction
Acronym
EAGLE
Official Title
Electrocardiogram Artificial Intelligence-Guided Screening for Low Ejection Fraction (EAGLE)
Study Type
Interventional
2. Study Status
Record Verification Date
May 2023
Overall Recruitment Status
Completed
Study Start Date
June 26, 2019 (Actual)
Primary Completion Date
March 31, 2020 (Actual)
Study Completion Date
November 1, 2020 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Mayo Clinic
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No
5. Study Description
Brief Summary
This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of left ventricular systolic dysfunction.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Asymptomatic Left Ventricular Systolic Dysfunction (Disorder), Heart Failure
7. Study Design
Primary Purpose
Screening
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
None (Open Label)
Allocation
Randomized
Enrollment
358 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Intervention
Arm Type
Experimental
Arm Description
Care teams randomized to intervention will have access to the screening tool.
Arm Title
Control
Arm Type
No Intervention
Arm Description
Care teams randomized to control will continue routine practice.
Intervention Type
Other
Intervention Name(s)
AI-enabled ECG-based Screening Tool
Intervention Description
A novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of left ventricular systolic dysfunction.
Primary Outcome Measure Information:
Title
New Diagnosis of Low Ejection Fraction (defined as ejection fraction ≤50%)
Description
Ejection fraction obtained by echocardiography.
Time Frame
Within 90 days
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Primary care clinicians who are part of a participating care team that care for adult patients and have the ability to order ECG and TTE (this includes physicians, nurse practitioners, and physician assistants).
Exclusion Criteria:
Primary care clinicians working in pediatrics, acute care, nursing homes, and resident care teams.
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Xiaoxi Yao, PhD, MPH
Organizational Affiliation
Mayo Clinic
Official's Role
Principal Investigator
First Name & Middle Initial & Last Name & Degree
Peter Noseworthy, MD
Organizational Affiliation
Mayo Clinic
Official's Role
Principal Investigator
Facility Information:
Facility Name
Mayo Clinic in Rochester
City
Rochester
State/Province
Minnesota
ZIP/Postal Code
55905
Country
United States
12. IPD Sharing Statement
Citations:
PubMed Identifier
31710842
Citation
Yao X, McCoy RG, Friedman PA, Shah ND, Barry BA, Behnken EM, Inselman JW, Attia ZI, Noseworthy PA. ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial. Am Heart J. 2020 Jan;219:31-36. doi: 10.1016/j.ahj.2019.10.007. Epub 2019 Oct 25.
Results Reference
background
PubMed Identifier
36333015
Citation
Rushlow DR, Croghan IT, Inselman JW, Thacher TD, Friedman PA, Yao X, Pellikka PA, Lopez-Jimenez F, Bernard ME, Barry BA, Attia IZ, Misra A, Foss RM, Molling PE, Rosas SL, Noseworthy PA. Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care. Mayo Clin Proc. 2022 Nov;97(11):2076-2085. doi: 10.1016/j.mayocp.2022.04.008.
Results Reference
derived
PubMed Identifier
33958795
Citation
Yao X, Rushlow DR, Inselman JW, McCoy RG, Thacher TD, Behnken EM, Bernard ME, Rosas SL, Akfaly A, Misra A, Molling PE, Krien JS, Foss RM, Barry BA, Siontis KC, Kapa S, Pellikka PA, Lopez-Jimenez F, Attia ZI, Shah ND, Friedman PA, Noseworthy PA. Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial. Nat Med. 2021 May;27(5):815-819. doi: 10.1038/s41591-021-01335-4. Epub 2021 May 6.
Results Reference
derived
Links:
URL
https://www.mayo.edu/research/clinical-trials
Description
Mayo Clinic Clinical Trials
Learn more about this trial
ECG AI-Guided Screening for Low Ejection Fraction
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