Harnessing ECG Artificial Intelligence for Rapid Treatment and Accurate Identification of Structural Heart Disease

The HEART-AI (Harnessing ECG Artificial Intelligence for Rapid Treatment and Accurate Interpretation) study primarily aims to assess the effect of displaying the ECHONeXT interpretation on the time interval from the initial ECG to the rate of Structural Heart Disease (SHD) diagnosis on transthoracic echocardiograms or magnetic resonance imaging.

We will achieve this by comparing the time between the first ECG and diagnosis of SHD on TTE or MRI between the intervention group, where the ECHONeXT interpretation is displayed to users, and the control group, where it is not displayed, thereby quantifying the influence of AI-supported diagnostics on clinical decision-making and patient management strategies.

For the purpose of the study, SHD will be defined as presence of any of the following on TTE or MRI:

• LVEF ≤ 45%
• Mild, moderate or severe RV Dysfunction
• The presence of one or multiple valvulopathies in this list:

• Moderate-to-severe pulmonary regurgitation
• Moderate-to-severe tricuspid regurgitation
• Moderate-to-severe mitral regurgitation
• Moderate-to-severe aortic regurgitation
• Moderate-to-severe aortic stenosis
• Moderate or severe pericardial effusion (Tamponade or any effusion > 1 cm)
• LV wall thickness ≥ 1.3 cm
• Apical cardiomyopathy
• Pulmonary hypertension as defined using the systolic pressure of the pulmonary artery greater or equal to 25 mm Hg on TTE.

Inclusion criteria

• Users

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

ECG

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

Patients

• Patients aged 18 years or older

Additional Inclusion criteria for the randomization part of the study

• 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"]

• New patients without a prior formal evaluation by a cardiologist or internal medicine specialist for suspected or provisionally identified cardiac conditions, including:

• Arrhythmia
• Heart Failure
• Coronary Artery Disease
• Valvular Heart Disease
• Cardiomyopathy
• Other cardiac conditions
• Patients with previous TTE or MRI:

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

Exclusion criteria

Users

• 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

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