Willem AI for early detection of aortic stenosis from a 12‑lead ECG
Official title: Multicenter Study for the Validation of Willem AI: Aortic StenoSis Early Diagnosis With AI-electrocardiogram (Willem AoS-SEDAI) Study
Run by Idoven 1903 S.L. · NCT07479992 · Data updated 2026-11-12
This project will test whether the Willem AI can detect aortic stenosis from routine 12‑lead ECGs in adults.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 5000 (estimated) |
| Sponsor | Idoven 1903 S.L. Industry-sponsored |
| Locations | 2 sites (Bonn and 1 other locations) |
| Status | Recruiting |
| Started | April 28, 2026 |
| Main results expected | January 2027 |
| Study ends | February 2027 |
| Registry record updated | November 4, 2026 |
| Trial ID | NCT07479992 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (≥18 years) with available digital 12‑lead ECGs (≥10 seconds) and a transthoracic echocardiogram performed within ±90 days of the ECG are the intended participants.
✕Probably not a fit
People under 18, those without digital 12‑lead ECGs or without a TTE within the specified ±90‑day window, and patients lacking the required clinical data would not be eligible or benefit from this validation.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a multicenter observational study using both retrospective and prospective ECG data to validate the Willem AI algorithm's ability to distinguish aortic stenosis from non‑AS patients. De‑identified digital 12‑lead ECG recordings of at least 10 seconds will be paired with clinical data and a transthoracic echocardiogram performed within ±90 days to establish ground truth. The algorithm's ECG-based classifications will be compared to echocardiographic diagnoses across participating centers in Germany. No exclusion criteria are defined beyond the required ECG and echocardiogram availability.
Why it matters
Potential benefit: If successful, the AI could enable earlier, more scalable detection of aortic stenosis from routine ECGs and prompt timely referral for echocardiography and treatment.
How similar studies have gone: Prior AI‑ECG research has shown promise in detecting structural heart disease and reduced ejection fraction, and initial reports suggest similar approaches may identify aortic stenosis, but large multicenter validation remains limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥ 18 years; * All available 12-lead ECG with a 10 seconds minimum length on raw data digital format will be included * Available clinical data corresponding to each ECG to confirm patient demographics and Aortic Stenosis diagnosis * Available transthoracic echocardiogram (TTE) within +/- 90 days of each ECG recording No exclusion criteria are defined for this study.
Where it's running
-
Universitätsklinikum Bonn
Bonn, Germany Recruiting -
Technical University of Munich
Munich, Germany Recruiting
Study contacts
- Study coordinator: Manuel Marina-Breysse, MD, PhD
- Email: clinical@idoven.ai
- Phone: +34669752391
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.