Registry Study for the Evaluation of High-risk Cardiac Patients by WILLEM AI-based ECG Platform (WILLEMRegistry)

The WILLEM Registry is a large-scale, single-group, observational, registry study to collect continuous clinical evidence of Willem in real-world settings. Cardiovascular diseases are a major problem for public health and healthcare systems. Electrocardiograms (ECGs) are simple tests which increase diagnostic performance and early detection of cardiovascular diseases. However, its interpretation is complex, time consuming for cardiology experts, and entails high costs for healthcare systems. Willem allows AI-based automatic interpretation and its performance has been examined in previous clinical trials, but additional clinical evidence is needed for its integration in real-world clinical settings. This study will collect clinical evidence of Willem performance to detect cardiac abnormalities in ECGs from high-risk cardiac patients admitted to cardiovascular units.

Study Overview

• Status: Recruiting
• Conditions: High-risk Cardiac Patients
• Intervention / Treatment: Device: Willem AI ECG assessment

Detailed Description

Patient enrollment will be both retrospective and prospective.

• Study Type: Observational
• Enrollment (Estimated): 200000

Contacts and Locations

• Study Contact: Name: Manuel Marina-Breysse, MD, PhD; Phone Number: +34669752391; Email: clinical@idoven.ai

Study Locations

• Spain
  • Madrid, Spain, 28046
    • Not yet recruiting
    • La Paz University Hospital
    • Contact: Teresa López, MD, PhD
  • Madrid, Spain, 28222
    • Not yet recruiting
    • Puerta de Hierro University Hospital
    • Contact: Pablo García Pavía, MD, PhD
  • Murcia, Spain, 30100
    • Not yet recruiting
    • Murcia University
    • Contact: Sergio Manzano Fernández, MD, PhD
• United States
  • Tennessee
    • Nashville, Tennessee, United States, 37232
      • Recruiting
      • Vanderbilt University Medical Center
      • Contact: Evan Brittain, MD, MSCI

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Subjects with high-risk and/or high-cost cardiac disease undergoing standard of care ECG assessment during the screening or diagnostic process, complementary tests, interventions, and/or clinical follow-up visits in any setup of care. Additionally, for the assessment of cardiac disease detection, subjects with no cardiac risk may be recruited as well for comparison between confirmed diagnosed patients and confirmed negative diagnosed subjects.

Description

Inclusion Criteria:

• EC/IRB approval of ICF waiver prior to recruitment; otherwise, signed informed consent form by subject and investigator
• Age > 18 years-old, with no upper limit
• Subjects undergoing standard of care electrocardiogram (ECG) of any duration from any hardware device
• All available, but at least one, legible ECG tracings in raw data format (e.g. DICOM, XML, EDF, JSON, HL7, SCP, WFDB, CSV, etc.)
• Available subject clinical data associated with the ECG
• For 12-lead ECGs, a minimum length of 10 seconds at a minimum sample frequency of 250 Hz
• For ECGs from Holters, wearables, patches, insertable cardiac monitors, telemetries, etc., a minimum length of 30 seconds at a minimum sample frequency of 200 Hz with a lead I / II or its MCL-DII lead approximation
• For prospective eligibility only:
• Signed informed consent form, unless previously waived by the EC/IRB
• Site technical viability for ECG and subject clinical data transfer (e.g. end-to-end integration following interoperability standards such as FHIR, HL7 or DICOM)

Exclusion Criteria:

• Unavailable or suboptimal quality of the raw data from the ECG signal
• Age < 18 years-old

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
High-risk cardiac patients; High-risk cardiac patients undergoing routine care electrocardiogram (ECG) for assessment of arrhythmias or cardiac diseases	Device: Willem AI ECG assessment; There is no study intervention. The Willem AI platform will assess all study ECGs for the identification of cardiac patterns, arrhythmias, and/or cardiac diseases. 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.
Controls; In case of any cardiac disease diagnosed to the high-risk cardiac patient cohort, controls will be any enrolled patient with no confirmed diagnosis of such cardiac disease	Device: Willem AI ECG assessment; There is no study intervention. The Willem AI platform will assess all study ECGs for the identification of cardiac patterns, arrhythmias, and/or cardiac diseases. 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Primary endpoint analysis: Willem performance	ECG data will be categorized according to SOC-defined cardiopathies, arrhythmic events, and cardiac diseases. If SOC diagnosis is unavailable or inconsistent, an independent committee of expert cardiologists will review and provide their diagnosis according to a cardiac defined ontology which extends values defined in HL7-aECG data store. Then, the performance of Willem to detect cardiac patterns, arrhythmias, and cardiac disease from ECGs will be assessed. In order to define True Positive, True Negative, False Positive, and False Negative classifications, the ground truth for comparison will be Standard Of Care (SOC) manually performed cardiologist diagnosis. Performance metrics such as diagnostic accuracy, sensitivity, specificity, predictive positive value (PPV), negative predictive value (NPV), F1-Score and Area Under the Receiver Operating Characteristic Curve (AUROC) will be obtained.	From enrollment to any standard of care timepoint when the patient underwent (retrospective) or will undergo within the next 10 years (prospective) an eligible electrocardiogram

Collaborators and Investigators

• Sponsor: Idoven 1903 S.L.

Study record dates

Study Major Dates

• Study Start (Actual): February 3, 2026
• Primary Completion (Estimated): January 1, 2036
• Study Completion (Estimated): January 1, 2036

Study Registration Dates

• First Submitted: December 30, 2025
• First Submitted That Met QC Criteria: December 30, 2025
• First Posted (Actual): January 12, 2026

Study Record Updates

• Last Update Posted (Actual): April 13, 2026
• Last Update Submitted That Met QC Criteria: April 8, 2026
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: artificial intelligence; registry; electrocardiogram; deep learning; cardiac disease
• Additional Relevant MeSH Terms: Cardiovascular Diseases; Heart Diseases
• Other Study ID Numbers: WR_01

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: No