Deployment and Evaluation of Artificial Intelligence Software for Electrocardiogram Analysis and Management in Primary Care (DAISEA-ECG)

The DAISEA-ECG project aims to improve the diagnosis of heart diseases in primary care through the DeepECG platform, which combines ECG-AI and ECHONeXT algorithms. This study uses a stepped wedge design, where each Family Medicine Group acts as its own control. The FMGs will gradually transition from the control period (without AI recommendations) to the intervention period (with AI recommendations activated) in a randomized sequence.

The primary objective is to compare the sensitivity of family physicians in detecting cardiac pathologies, with and without the assistance of the DeepECG platform. Sensitivity is defined as the proportion of patients correctly referred to cardiology or for transthoracic echocardiography (TTE) among those who indeed required cardiovascular evaluation, as confirmed by an independent adjudication committee.

Study Overview

• Status: Not yet recruiting
• Conditions: Structural Heart Disease; Primary Care Provider
• Intervention / Treatment: Device: DeepECG plateform diagnosis & recommendations

Detailed Description

Mathematically, sensitivity is calculated as True Positive / (True Positive + False Negative), where True Positive represents correctly referred patients and false negatives represents patients who should have been referred but were not.

The secondary objectives include determining the rate of cardiovascular evaluation referrals before and after the intervention (implementation of the DeepECG platform), the individual characteristics of the intervention (PPV, NPV, and specificity), as well as evaluating the feasibility of implementing AI-based automatic ECG interpretation in primary care through surveys of family physicians and cardiologists.

PPV: Positive predictive value NPV: Negative predictive value

• Study Type: Interventional
• Enrollment (Estimated): 2000
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Robert Avram, MD; Phone Number: 514 376 3330; Email: robert.avram.md@gmail.com
• Study Contact Backup: Name: Marie-Gabrielle Lessard, MSc; Phone Number: 2094 514 376 3330; Email: marie-gabrielle.lessard@icm-mhi.org

Study Locations

• Canada
  • Quebec
    • Montreal, Quebec, Canada, H1T1C8
      • Montreal Heart Institute
      • Contact: Marie-Gabrielle Lessard, MSc; Phone Number: 2094 5143763330; Email: marie-gabrielle.lessard@icm-mhi.org
      • Principal Investigator: Robert Avram, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

Family Physicians or Nurse Practitioners

Family physicians or nurse practitioners (NPs) practicing in one of the participating FMGs.

Family physicians who have given their free and informed consent. Patients

Adult patients (18 years or older). Patients without follow-up in cardiology or internal medicine for cardiovascular issues (arrhythmia, heart failure, myocardial infarction, atherosclerotic coronary artery disease, valvular heart disease) or those who had a negative investigation in the past with no additional follow-up.

ECG

Any 12-lead ECG performed with the MUSE GE 360 machine. ECG of adequate technical quality for interpretation (otherwise, it will be automatically rejected by the platform).

-

Exclusion Criteria:

• Family Physicians or Nurse Practitioners

Family physicians practicing exclusively in pediatrics (patients under 18 years old).

Family physicians unable to follow the project guidelines.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: No DeepECG plateform diagnosis & recommendations
Experimental: DeepECG plateform diagnosis & recommendations	Device: DeepECG plateform diagnosis & recommendations; EchoNeXT& ECG-AI algorithm

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
sensitivity of cardiology referrals	Compare the sensitivity of cardiology referrals made by family physicians and nurse practitioners before and after the activation of AI-assisted diagnostics and recommendations from the DeepECG platform.	18 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
specificity, negative predictive value, and positive predictive value of cardiology referrals	Compare the specificity, negative predictive value, and positive predictive value of cardiology referrals made by family physicians and nurse practitioners before and after the activation of AI-assisted diagnostics and recommendations.	18 months

Collaborators and Investigators

• Sponsor: Montreal Heart Institute

Publications and helpful links

Helpful Links

• Related Info

Study record dates

Study Major Dates

• Study Start (Estimated): October 6, 2025
• Primary Completion (Estimated): January 1, 2027
• Study Completion (Estimated): March 1, 2027

Study Registration Dates

• First Submitted: October 9, 2024
• First Submitted That Met QC Criteria: October 9, 2024
• First Posted (Actual): October 15, 2024

Study Record Updates

• Last Update Posted (Estimated): September 19, 2025
• Last Update Submitted That Met QC Criteria: September 18, 2025
• Last Verified: September 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Cardiovascular Diseases; Heart Diseases
• Other Study ID Numbers: DAISEA-ECG

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No