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CompletedNCT04000087EAGLEUpdated May 31, 2023

ECG AI-Guided Screening for Low Ejection Fraction

An interventional study of AI-enabled ECG-based Screening Tool in Asymptomatic Left Ventricular Systolic Dysfunction (Disorder) and Heart Failure, sponsored by Mayo Clinic. Completed at 1 site in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2023-05-31.

Sponsored by Mayo Clinic · Not applicable, Interventional, and Screening

Phase
Not applicable
Study type
Interventional
Enrollment
358
Allocation
Randomized
Ages
18 Years and older
Sex
All
01

Study 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.

02

Conditions studied

  • Asymptomatic Left Ventricular Systolic Dysfunction (Disorder)
  • Heart Failure

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03

In context

Heart Failure

5,803 studies on the registry are indexed under Heart Failure; 1,222 are open to participants now.

This study's enrollment of 358 is above the median of 72 across 3,790 interventional studies indexed under Heart Failure.

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Lead sponsor

Mayo Clinic is the lead sponsor of 3,263 studies on the registry; 670 are open to participants now.

Of its 450 completed or terminated interventional studies of FDA-regulated products, 318 (71%) have results posted.

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Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

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

Exclusion Criteria:

  • Primary care clinicians working in pediatrics, acute care, nursing homes, and resident care teams.
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Study design

Phase
Not applicable
Primary purpose
Screening
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
358 participants (actual)

Study arms

  • Experimental
    Intervention

    Care teams randomized to intervention will have access to the screening tool.

    Other: AI-enabled ECG-based Screening Tool

  • No intervention
    Control

    Care teams randomized to control will continue routine practice.

Interventions

  • OtherAI-enabled ECG-based Screening Tool

    A novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of left ventricular systolic dysfunction.

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What researchers measure

Primary outcomes

  1. New Diagnosis of Low Ejection Fraction (defined as ejection fraction ≤50%)

    Ejection fraction obtained by echocardiography.

    Time frame: Within 90 days

07

Study locations

1 site
  • Mayo Clinic in Rochester
    Rochester, Minnesota 55905, United States
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References and documents

Publications

  • 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. PubMed 31710842 ↗
  • Barry B, Zhu X, Behnken E, Inselman J, Schaepe K, McCoy R, Rushlow D, Noseworthy P, Richardson J, Curtis S, Sharp R, Misra A, Akfaly A, Molling P, Bernard M, Yao X. Provider Perspectives on Artificial Intelligence-Guided Screening for Low Ejection Fraction in Primary Care: Qualitative Study. JMIR AI. 2022 Oct 14;1(1):e41940. doi: 10.2196/41940. PubMed 38875550 ↗
  • Zahrieh D, Croghan IT, Inselman JW, Mandrekar SJ. Guidelines for Data and Safety Monitoring in Pragmatic Randomized Clinical Trials Using Case Studies. Mayo Clin Proc. 2023 Nov;98(11):1712-1726. doi: 10.1016/j.mayocp.2023.02.019. PubMed 37923529 ↗
  • 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. PubMed 36333015 ↗
  • 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. PubMed 33958795 ↗
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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 31, 2023, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT04000087
Lead sponsor
Mayo Clinic
Responsible party
Xiaoxi Yao (Principal Investigator, Mayo Clinic) — Principal investigator
First posted
Jun 27, 2019
Start date
Jun 26, 2019
Primary completion
Mar 31, 2020
Completion
Nov 1, 2020
Last update
May 31, 2023

Study contacts

Xiaoxi Yao, PhD, MPH
principal investigator · Mayo Clinic
Peter Noseworthy, MD
principal investigator · Mayo Clinic

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in May 2023. You cannot join it, but the record below documents what was studied.

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