Harnessing ECG Artificial Intelligence for Rapid Treatment and Accurate Interpretation, an Open Label Randomized Controlled Trial
Trial ID: NCT06462989
Status: ENROLLING_BY_INVITATION
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-04-16
Completion date: 2027-01-31
Sponsor: Montreal Heart Institute
Conditions: Structural Heart Abnormality; Structural Heart Disease
Interventions: ECHONEXT
Locations: Montreal Heart Institute
Countries: Canada
Enrollment: 16160
Age range: 18 Years - None
Sex: ALL

Summary:
The HEART-AI (Harnessing ECG Artificial Intelligence for Rapid Treatment and Accurate Interpretation) is an open-label, single-center, randomized controlled trial, that aims to deploy a platform called DeepECG at point-of-care for AI-analysis of 12-lead ECGs. The platform will be tested among healthcare professionals (medical students, residents, doctors, nurse practitioners) who read 12-lead ECGs. In the intervention group, the platform will display the ECHONeXT structural heart disease (SHD) scores in randomized patients to help doctors prioritize transthoracic echocardiography (TTEs) or magnetic resonance imaging (MRI) and reduce the time to diagnosis of structural heart disease. Also, this platform will display the DeepECG-AI interpretation which detects problems such as ischemic conditions, arrhythmias or chamber enlargements and acts an improved alternative to commercially available ECG interpretation systems such as MUSE.

Our primary objective is to assess the impact of displaying the ECHONeXT interpretation on 12-lead ECGs on the time to diagnosis of Structural Heart Disease (SHD) among newly referred patients at MHI. We will compare the time interval from the initial ECG to SHD diagnosis by transthoracic echocardiogram (TTE) or magnetic resonance imaging (MRI) between patients in the intervention arm (where ECHONeXT prediction of SHD and TTE priority recommendation are displayed) and patients in the control arm (where ECHONeXT prediction and recommendation are hidden).

The main secondary objective is to evaluate the rate of SHD detection on TTE or MRI among newly referred patients. We also aim to assess the delay between the time of the first ECG opened in the platform and the TTE or MRI evaluation among newly referred patients at high or intermediate risk of SHD.

By integrating an AI-analysis platform at the point of care and evaluating its impact on ECG interpretation accuracy and prioritization of incremental tests, the HEART-AI study aims to provide valuable insights into the potential of AI in improving cardiac care and patient outcomes.

Eligibility criteria:
Inclusion Criteria:

* Users

  1. Users who are providing clinical care and who read ECGs as part of their practice.
  2. Users who have provided informed consent to participate in the study.
  3. Users who have completed the required training on the use of the DeepECG platform.

ECG

1. 12-lead ECGs recorded during the study period at the Montreal Heart Institute.
2. ECGs of adequate technical quality for interpretation, as determined by the recording software and visual inspection.

Patients

1\. Patients aged 18 years or older

Additional Inclusion criteria for the randomization part of the study

1. Outpatients or patients who presented at the ambulatory emergency department. The location will be determined according to the ECG where it was recorded which is entered by the ECG technician. These locations will be included for the eligibility of the randomization:

   a. locations\_to\_keep = \['21\_URGENCE AMBULATOIRE', '1\_CARDIOLOGIE GENERALE', "17\_CLINIQUE D'ARYTHMIE"\]
2. New patients without a prior formal evaluation by a cardiologist or internal medicine specialist for suspected or provisionally identified cardiac conditions, including:

   1. Arrhythmia
   2. Heart Failure
   3. Coronary Artery Disease
   4. Valvular Heart Disease
   5. Cardiomyopathy
   6. Other cardiac conditions
3. Patients with previous TTE or MRI:

   1. Have no documented history of any cardiac condition
   2. No transthoracic echocardiogram or MRI in the last 24 months (from any center)

Exclusion Criteria:

Users

1\. Users who are unable to commit to the duration of the study (approximately 1 month minimum) or adhere to the study protocol.

Additional Exclusion criteria for the randomization part of the study ECG

1\. ECG with too many artefacts or without any QRS visible as interpretated by the MUSE GE algorithm.

Outcomes:
Assess the effect of displaying the ECHONeXT interpretation on the time to diagnosis of Structural Heart Disease (SHD)