NCT04000087

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
358

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Jun 2019

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

June 24, 2019

Completed
2 days until next milestone

Study Start

First participant enrolled

June 26, 2019

Completed
1 day until next milestone

First Posted

Study publicly available on registry

June 27, 2019

Completed
9 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

March 31, 2020

Completed
7 months until next milestone

Study Completion

Last participant's last visit for all outcomes

November 1, 2020

Completed
Last Updated

May 31, 2023

Status Verified

May 1, 2023

Enrollment Period

9 months

First QC Date

June 24, 2019

Last Update Submit

May 30, 2023

Conditions

Asymptomatic Left Ventricular Systolic Dysfunction (Disorder)Heart Failure

Outcome Measures

Primary Outcomes (1)

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

    Ejection fraction obtained by echocardiography.

    Within 90 days

Study Arms (2)

Intervention

EXPERIMENTAL

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

Other: AI-enabled ECG-based Screening Tool

Control

NO INTERVENTION

Care teams randomized to control will continue routine practice.

Interventions

AI-enabled ECG-based Screening ToolOTHER

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

Intervention

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • 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).

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Mayo Clinic in Rochester

Rochester, Minnesota, 55905, United States

Location

Related Publications (5)

  • 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.

    PMID: 31710842BACKGROUND

  • 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.

    PMID: 38875550DERIVED

  • 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.

    PMID: 37923529DERIVED

  • 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.

    PMID: 36333015DERIVED

  • 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.

    PMID: 33958795DERIVED

Related Links

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart DiseasesCardiovascular Diseases

Study Officials

  • Xiaoxi Yao, PhD, MPH

    Mayo Clinic

    PRINCIPAL INVESTIGATOR

  • Peter Noseworthy, MD

    Mayo Clinic

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
SCREENING
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator

Study Record Dates

First Submitted

June 24, 2019

First Posted

June 27, 2019

Study Start

June 26, 2019

Primary Completion

March 31, 2020

Study Completion

November 1, 2020

Last Updated

May 31, 2023

Record last verified: 2023-05

Locations

US(1)