AI-Enhanced ECG Interpretation for Structural Heart Disease
(HEART-AI Trial)

Recruiting in Palo Alto (17 mi)

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Waitlist Available

Sponsor: Montreal Heart Institute

No Placebo Group

Trial Summary

What is the purpose of this trial?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) 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) 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 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 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

This trial is for healthcare professionals at the Montreal Heart Institute who read ECGs, and patients aged 18 or older with single ventricle or structural heart disease. Participants must have recorded a high-quality 12-lead ECG during the study period and given informed consent.

Inclusion Criteria

ECGs of adequate technical quality for interpretation, as determined by the recording software and visual inspection

I visited the outpatient, cardiology clinic, or emergency room for my ECG.

Users providing clinical care and reading ECGs as part of their practice

+6 more

Exclusion Criteria

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

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

Participant Groups

The HEART-AI trial tests an AI platform called DeepECG that analyzes ECGs to help diagnose structural heart disease faster. It compares time to diagnosis between those using the AI tool (ECHONeXT scores displayed) and standard care without AI assistance.

2Treatment groups

Experimental Treatment

Active Control

Group I: ECHONEXT interpretationExperimental Treatment1 Intervention

The ECHONeXT algorithm was trained to predict the presence of SHD on TTE using a single 12-lead ECG. It was developed at Columbia hospital, released as open-weights and validated at the MHI. It was trained on 800,000 ECG and TTE pairs.

Group II: No ECHONEXT interpretationActive Control1 Intervention

Not displaying the ECHONEXT algorithm interpretation.