Tests AI heart tracing tools for detecting structural heart disease
Tests AI analysis of ECG recordings to detect heart valve, failure or lung pressure problems.
Plain-language title generated from the registry record
Registry title: Prospective Evaluation of AI-ECG for SHD Detection
Key facts
- Where
- Bristol and London, United KingdomSee the 6 sites
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 18 and 90 years old?
Source: NCT07057466, who can take part
Where in United Kingdom
- Bristol Royal InfirmaryBristol, United KingdomTaking people
- Southmead HospitalBristol, United KingdomTaking people
- Chelsea And Westminster HospitalLondon, United KingdomTaking people
- Hammersmith HospitalLondon, United KingdomTaking people
- St Mary's HospitalLondon, United KingdomTaking people
- West Middlesex University HospitalLondon, United KingdomTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Imperial College London
- Trial code
- NCT07057466
- Record updated
- 8 October 2026
- Original description
AI-ECG-SHD is a multicentre prospective observational diagnostic accuracy study evaluating artificial intelligence-enhanced electrocardiography (AI-ECG) for the detection of structural heart disease in adults undergoing clinically indicated transthoracic echocardiography (TTE).Read full original descriptionShow less
Prospective Evaluation of Artificial Intelligence-enhanced Electrocardiography for Detection of Structural Heart Disease
AI-ECG-SHD is a multicentre prospective observational diagnostic accuracy study evaluating artificial intelligence-enhanced electrocardiography (AI-ECG) for the detection of structural heart disease in adults undergoing clinically indicated transthoracic echocardiography (TTE).
Participants undergo standard 12-lead ECG acquisition together with ECG recordings obtained using portable or wearable single-, 3-, and 6-lead devices. Established AI-ECG models will be evaluated for the detection of heart failure, pulmonary hypertension and valvular heart disease using TTE as the clinical reference standard, with performance compared across ECG acquisition modalities within the same prospective cohort.
AI-ECG predictions are generated offline and are not provided to treating clinicians or used to alter clinical care. The study will also compare AI-ECG performance with N-terminal pro-B-type natriuretic peptide (NT-proBNP) and evaluate the diagnostic performance of a combined AI-ECG and NT-proBNP approach.
The study aims to recruit 590 participants across six NHS hospital sites. A prespecified subgroup of 203 participants will undergo dedicated venous blood sampling for NT-proBNP; eligible same-day NT-proBNP measurements obtained as part of routine clinical care will also be included where available.
Inclusion: Patients awaiting a transthoracic echocardiogram (TTE) based on clinical grounds as part of their standard care; Age 18-90 years; Able to provide informed consent.
Exclusion: Severe arrhythmia or unstable cardiovascular disease; Cardiac implantable electronic device in situ, including a permanent pacemaker or implantable cardioverter defibrillator; Known severe structural heart disease, defined as any of the following: severe left ventricular systolic dysfunction (LVEF ≤35%); severe valvular heart disease according to current British Society of Echocardiography criteria; high echocardiographic probability of pulmonary hypertension according to current British Society of Echocardiography criteria; or previous structural cardiac intervention, including valve repair, valve replacement/implantation, or surgical repair of a cardiac chamber or congenital structural abnormality; Current or recent involvement in another research study.