Multicenter Study for the Validation of Willem AI: Aortic StenoSis Early Diagnosis With AI-electrocardiogram Study

NCT07479992 | Recruiting

• 1 other identifier: AoS-SEDAI_01
• Study Type: observational
• Target: 5,000
• Locations: 1 country
• Sites: 2

Brief Summary

AoS-SEDAI study is an observational, multicenter, retrospective and prospective clinical study. This study aims to assess Willem Artificial Intelligence (AI) ability to distinguish between aortic stenosis (AS) and non-AS patients from 12-lead electrocardiogram (ECG) data.

Conditions

Aortic Stenosis

Keywords

artificial intelligence; electrocardiogram; deep learning; cardiac disease; aortic stenosis

Outcome Measures

Primary Outcomes (1)

• Willem performance to detect severe Aortic Stenosis

  Performance of Willem AI platform to distinguish between severe Aortic Stenosis (AS) patients with confirmed diagnosis and non-AS patients, by means of the following performance metrics: Area Under the Receiver Operating Characteristic curve (AUROC), diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The Standard Of Care (SOC) investigator diagnosis will be used as the ground truth.

  ECG will be performed at baseline, and ECG analysis by Willem AI will be performed retrospectively throughout the trial, and finalized upon recruitment completion.

Secondary Outcomes (1)

• Willem performance to detect moderate Aortic Stenosis

  ECG will be performed at baseline, and ECG analysis by Willem AI will be performed retrospectively throughout the trial, and finalized upon recruitment completion.

Study Arms (2)

Aortic Stenosis patients

Subjects with an Aortic Stenosis diagnosis confirmed by the physician following their routine practice (e.g. ESC Guidelines), including complete clinical assessment with echocardiogram or other complementary techniques.

Device: Willem AI ECG assessment

Non-Aortic Stenosis patients (Controls)

Subjects without Aortic Stenosis confirmed by the physician after thorough evaluation following their routine practice.

Device: Willem AI ECG assessment

Interventions

Willem AI ECG assessment DEVICE

There is no study intervention. The Willem AI platform will assess all study electrocardiograms (ECGs) for the identification of aortic stenosis. Regardless of retrospective or prospective enrollment, Willem output will not be provided to the healthcare professional user for clinical evaluation, and therefore routine practice will not be impacted nor altered.

Aortic Stenosis patients; Non-Aortic Stenosis patients (Controls)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The target population consists of patients under assessment of Aortic Stenosis (AS). Screened patients need to have 12-lead ECG recordings within 90 days of a transthoracic echocardiogram (TTE). In the case of multiple ECGs and TTEs per patient, all of them will be selected and analysed accordingly considering the corresponding PI diagnosis at each time. In the event of a patient with a different diagnosis over time (e.g. non-AS confirmed diagnosis later on diagnosed with AS), multiple timepoint ECGs will be categorized so that the same patient is not included both in the control and in the AS populations. Controls will include non-AS patients with relevant TTE and clinical findings during AS differential diagnosis (such as hypertensive heart disease, structural heart diseases, hypertrophic cardiomyopathy among other cardiomyopathies, mild aortic stenosis, and no significant aortic leaflet calcification).

You may qualify if:

• 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

Sponsors & Collaborators

• Idoven 1903 S.L.: lead

Study Sites (2)

Universitätsklinikum Bonn

Bonn, Germany

RECRUITING

Technical University of Munich

Munich, Germany

NOT YET RECRUITING

MeSH Terms

Conditions

Aortic Valve Stenosis; Heart Diseases

Condition Hierarchy (Ancestors)

Aortic Valve Disease; Heart Valve Diseases; Cardiovascular Diseases; Ventricular Outflow Obstruction

Central Study Contacts

Manuel Marina-Breysse, MD, PhD

CONTACT

+34669752391; clinical@idoven.ai

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: OTHER
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 13, 2026
• First Posted: March 18, 2026
• Study Start: April 28, 2026
• Primary Completion (Estimated): July 1, 2026
• Study Completion (Estimated): July 1, 2026
• Last Updated: May 12, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

DE (2)