CardiomyopathiesWILLEMNCT05890716
AI-powered ECG Analysis Using Willem™ Software in High-risk Cardiac Patients (WILLEM)
An observational study of Cardiomyopathies and Cardiac Arrest, run by Idoven 1903 S.L. at 13 sites in 2 countries.
Trial summary
WILLEM is a multi-center, prospective and retrospective cohort study. The study will assess the performance of a cloud-based and AI-powered ECG analysis platform, named Willem™, developed to detect arrhythmias and other abnormal cardiac patterns. The main questions it aims to answer are: 1. Read more about this study
- Who is it for?
- Ages 4 years and olderHealthy volunteers can take part
- Conditions the study is for
- Cardiomyopathies, Cardiac Arrest, Cardiac Arrhythmias
- What is being tested?
- AI-powered ECG analysis to detect cardiac arrhythmic episodes
- How many people
- 5,342 participants
- Where
- 13 sitesin 2 countries
- Study dates
- 4 Apr 2023to Nov 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 4 years and older
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Patients recorded with a mid to long-term ECG device according to guidelines. ECG data (ECG must have been recorded according to the technical standards for the safety and essential performance of medical electrical equipment defined in EN 60601-2-47:2015.): 12-lead ECGs including rest electrocardiograms, stress ECG Test (exercise Electrocardiogram or treadmill test), Holter devices, long-duration Holter devices, event recorders, insertable cardiac monitors, 6,3,2,1-lead ECG wearables, textile electrodes and patches, smartwatches, cardiac monitors, cardiac telemetries, hemodynamic and electrophysiology recording system (i.e., polygraphs), automatic external defibrillator (AED), semi-automatic defibrillator (DESA), home telemonitoring systems and other similar devices.
Who may be able to join
- Patient presenting relevant cardiac arrhythmias and cardiac patterns (including supraventricular tachycardias, abnormal ECG patterns, ventricular tachycardias, ventricular fibrillation, pulseless electrical activity or asystole among others) that have been recorded with at least one short-term ECG medical device according to guidelines with ≥1 signal-channel.
- Patient with suspected or diagnosed acute/chronic cardiac diseases (including patients with heart failure, patients with history of cardiac arrhythmias, patients with probable coronary artery diseases, patients with cardiomyopathies, patients with pacemakers or implantable cardioverter-defibrillators (ICD), patients with indication of pacemaker or ICD in current or short-term phase, patients participating in other interventional clinical investigation, patients with hemodynamic instability or acute coronary syndromes, pregnant patients, patients with cancer and chemotherapy, patients with life-expectancy lower than 24 months, patients with in or out-of-hospital cardiac arrest with ventricular fibrillation as first documented rhythm).
- At least one ECG tracing that can be exported in raw data.
- Signed informed consent. Patients unable to consent, it will be requested to an authorized relative.
Who cannot join
- Unwillingness or inability to sign study written informed consent.
- Unavailable or suboptimal quality of the electrocardiographic signal in raw data.
Trial locations and contacts
13 sites in 2 countries. Contact the study team or a site near you to ask about taking part.
José María Lillo, PhD contact
13 sites in 2 countries
Spain12 sites, 2 recruiting
- Completed
Complejo Hospitalario Universitario A Coruña
A Coruña, La Coruña, 15006
- Completed
Hospital Sant Joan de Déu
Barcelona, Barcelona, 08950
- Recruiting
Hospital Universitario de Basurto
Bilbao, Vizcaya, 48013
Alain García Olea, MD
Alain García Olea
- Completed
Hospital General Universitario de Ciudad Real
Ciudad Real, Ciudad Real, 13005
- Completed
Hospital Clínico San Carlos
Madrid, Madrid, 28040
- Completed
Hospital Universitario Puerta de Hierro
Madrid, Madrid, 28222
- Completed
Hospital Universitario General de Villalba
Madrid, Madrid, 28400
- Completed
Hospital Universitario del Henares
Madrid, Madrid, 28822
- Completed
Hospital Virgen de Arrixaca
Murcia, Murcia, 30120
- Recruiting
Clínica Universitaria Navarra
Pamplona, Navarre, 31008
Manuel García de Yébenes Castro, MD
Manuel García de Yébenes Castro
- Completed
Hospital Universitario Nuestra Señora de Candelaria
Santa Cruz de Tenerife, Santa Cruz de Tenerife, 38010
- Completed
Hospital Universitario y Politécnico La Fe
Valencia, Valencia, 46026
Netherlands1 site
- Completed
University Medical Center Groningen
Groningen, Provincie Groningen, 9713 GZ
About this study
Official title: Evaluation of Electrocardiographic Data From High-risk Cardiac Patients Using Willem™ Cardiologist-level Artificial Intelligence Software. WILLEM Trial.
WILLEM is a multi-center, prospective and retrospective cohort study.
The study will assess the performance of a cloud-based and AI-powered ECG analysis platform, named Willem™, developed to detect arrhythmias and other abnormal cardiac patterns. The main questions it aims to answer are:
Read more
- A new AI-powered ECG analysis platform can automatice the classification and prediction of cardiac arrhythmic episodes at a cardiologist level.
- This AI-powered ECG analysis can delay or even avoid harmful therapies and severe cardiac adverse events such as sudden death.
The prerequisites for inclusion of patients will be the availability of at least one ECG record in raw data, along with patient clinical data and evolution data after more than 1-year follow-up.
Cardiac electrical signals from multiple medical devices will be collected by cardiology experts after obtaining the informed consent. Every cardiac electrical signal from every subject will be reviewed by a board-certified cardiologist to label the arrhythmias and patterns recorded in those tracings. In order to obtain tracings of relevant information, >95% of the subjects enrolled will have rhythm disorders or abnormal ECG's patterns at the time of enrollment.
Read the detailed description
The WILLEM study is an investigator-initiated, multicenter, observational trial aiming to validate a cloud-based AI-powered ECG analysis platform to early diagnose and predict the behavior of cardiac abnormalities and cardiac diseases from patients admitted to cardiovascular units. Model-derived diagnosis will be compared with cardiology expert's diagnosis in a test dataset. Clinical outcomes will be included to assess model prediction capabilities: sensitivity, specificity and accuracy. In this observational study, patients will be randomly divided into two groups: (1) a training group to design new methodologies and algorithms; and (2) a test group to evaluate performance of methodologies aiming to avoid overfitting.
Willem™ AI-powered ECG analysis platform supports the analysis of cardiac electrical signals ≥ 10 seconds onwards obtained from devices in-clinic (E.g., 12-lead ECG devices at hospitals or primary care, telemetries, monitors) and at-home or telemedicine interfaces (E.g., Holter devices, event recorders, 6, 3, 2, 1-lead ECG wearables, textile electrodes and patches for mobile cardiac telemetry).
- Being tested
- AI-powered ECG analysis to detect cardiac arrhythmic episodes
- Keywords
- Artificial intelligence, Cardiac arrhythmias, Heart disease, Cardiac electrical signals, Electrocardiogram, Electrogram
- Medical subject headings
- Cardiomyopathies, Heart Arrest, Arrhythmias, Cardiac, Death, Sudden, Cardiac, Heart Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-powered ECG analysis to detect cardiac arrhythmic episodesDiagnostic test
ECG recording and processing by AI platform
| Study group | Role | What they receive |
|---|---|---|
| Train group | Consecutive patients admitted to the hospital due to cardiac disorders (retrospective and prospective) with at least one relevant ECG record >10 sec in raw data will be used to design new methodologies and algorithms for cardiac patterns recognition. Receives: Diagnostic Test: AI-powered ECG analysis to detect cardiac arrhythmic episodes | |
| Test group | Consecutive patients admitted to the hospital due to cardiac disorders (retrospective and prospective) with at least one relevant ECG record >10 sec in raw data will be used to evaluate performance of methodologies aiming to avoid overfitting. Every 10 patients included in Train group; a new patient is included in the test group. Receives: Diagnostic Test: AI-powered ECG analysis to detect cardiac arrhythmic episodes |
What is being measured
The primary outcome is the main question the study is designed to answer.
Detection of cardiac arrhythmias and cardiac patterns in the electrocardiographic signals
Willem™ heart rhythm and cardiac pattern performance compared to standard manually performed cardiologist diagnosis.
Measured: real time to 7 minutes
Secondary outcomes (4)
Survival at follow-up
Patients alive at the time of follow-up
Measured: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Major Adverse Cardiovascular and Cerebrovascular Events (MACCE)
MACCE rates defined as cardiovascular and cerebrovascular events during the follow up
Measured: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Re-hospitalization
Number of Re-hospitalizations during the follow up.
Measured: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Change in quality of life
European Quality of Life-5 Dimensions (EQ-5D) index an utility scores anchored at 0 for death and 1 for perfect health.
Measured: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Jun 2023
- Study start4 Apr 2023
- Primary completionNov 2026 (estimated)
- Study completionNov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for CardiomyopathiesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 5,342 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Idoven 1903 S.L.
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Fundación de Investigación en Red en Enfermedades Cardiovasculares, Spanish Society of Cardiology
- Responsible party
- Sponsor
- Investigators
- María De La Parte, MD, Principal investigator, Idoven 1903 S.L.
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05890716
- Sponsor's protocol ID
- 1903/21
- Acronym
- WILLEM
- Status last verified
- Jul 2026
- First submitted
- 26 May 2023
- Last updated
- 20 Jul 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Lillo-Castellano JM, Marina-Breysse M, Gomez-Gallanti A, Martinez-Ferrer JB, Alzueta J, Perez-Alvarez L, Alberola A, Fernandez-Lozano I, Rodriguez A, Porro R, Anguera I, Fontenla A, Gonzalez-Ferrer JJ, Canadas-Godoy V, Perez-Castellano N, Garofalo D, Salvador-Montanes O, Calvo CJ, Quintanilla JG, Peinado R, Mora-Jimenez I, Perez-Villacastin J, Rojo-Alvarez JL, Filgueiras-Rama D. Safety threshold of R-wave amplitudes in patients with implantable cardioverter defibrillator. Heart. 2016 Oct 15;102(20):1662-70. doi: 10.1136/heartjnl-2016-309295. Epub 2016 Jun 13.
PubMed 27296239Lillo-Castellano JM, Gonzalez-Ferrer JJ, Marina-Breysse M, Martinez-Ferrer JB, Perez-Alvarez L, Alzueta J, Martinez JG, Rodriguez A, Rodriguez-Perez JC, Anguera I, Vinolas X, Garcia-Alberola A, Quintanilla JG, Alfonso-Almazan JM, Garcia J, Borrego L, Canadas-Godoy V, Perez-Castellano N, Perez-Villacastin J, Jimenez-Diaz J, Jalife J, Filgueiras-Rama D. Personalized monitoring of electrical remodelling during atrial fibrillation progression via remote transmissions from implantable devices. Europace. 2020 May 1;22(5):704-715. doi: 10.1093/europace/euz331.
PubMed 31840163Quartieri F, Marina-Breysse M, Pollastrelli A, Paini I, Lizcano C, Lillo-Castellano JM, Grammatico A. Artificial intelligence augments detection accuracy of cardiac insertable cardiac monitors: Results from a pilot prospective observational study. Cardiovasc Digit Health J. 2022 Aug 4;3(5):201-211. doi: 10.1016/j.cvdhj.2022.07.071. eCollection 2022 Oct.
PubMed 36310681Martinez-Selles M, Marina-Breysse M. Current and Future Use of Artificial Intelligence in Electrocardiography. J Cardiovasc Dev Dis. 2023 Apr 17;10(4):175. doi: 10.3390/jcdd10040175.
PubMed 37103054
Study at a glance
From the registry record, last updated by the sponsor on 20 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of Electrocardiographic Data From High-risk Cardiac Patients Using Willem™ Cardiologist-level Artificial Intelligence Software. WILLEM Trial.
- ClinicalTrials.gov ID
- NCT05890716
- Acronym / sponsor ID
- WILLEM / 1903/21
- Keywords
- Artificial intelligence, Cardiac arrhythmias, Heart disease, Cardiac electrical signals, Electrocardiogram, Electrogram
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 5,342 participants (estimated)
- Lead sponsor
- Idoven 1903 S.L.Industry (pharma, biotech, devices)
- Collaborators
- Fundación de Investigación en Red en Enfermedades Cardiovasculares, Spanish Society of Cardiology
- Study start
- 4 Apr 2023 (actual)
- Primary completion
- Nov 2026 (estimated)
- Study completion
- Nov 2026 (estimated)
- First posted
- 6 Jun 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
WILLEM is a multi-center, prospective and retrospective cohort study.
The study will assess the performance of a cloud-based and AI-powered ECG analysis platform, named Willem™, developed to detect arrhythmias and other abnormal cardiac patterns. The main questions it aims to answer are:
- A new AI-powered ECG analysis platform can automatice the classification and prediction of cardiac arrhythmic episodes at a cardiologist level.
- This AI-powered ECG analysis can delay or even avoid harmful therapies and severe cardiac adverse events such as sudden death.
The prerequisites for inclusion of patients will be the availability of at least one ECG record in raw data, along with patient clinical data and evolution data after more than 1-year follow-up.
Cardiac electrical signals from multiple medical devices will be collected by cardiology experts after obtaining the informed consent. Every cardiac electrical signal from every subject will be reviewed by a board-certified cardiologist to label the arrhythmias and patterns recorded in those tracings. In order to obtain tracings of relevant information, >95% of the subjects enrolled will have rhythm disorders or abnormal ECG's patterns at the time of enrollment.
Detailed description
The WILLEM study is an investigator-initiated, multicenter, observational trial aiming to validate a cloud-based AI-powered ECG analysis platform to early diagnose and predict the behavior of cardiac abnormalities and cardiac diseases from patients admitted to cardiovascular units. Model-derived diagnosis will be compared with cardiology expert's diagnosis in a test dataset. Clinical outcomes will be included to assess model prediction capabilities: sensitivity, specificity and accuracy. In this observational study, patients will be randomly divided into two groups: (1) a training group to design new methodologies and algorithms; and (2) a test group to evaluate performance of methodologies aiming to avoid overfitting.
Willem™ AI-powered ECG analysis platform supports the analysis of cardiac electrical signals ≥ 10 seconds onwards obtained from devices in-clinic (E.g., 12-lead ECG devices at hospitals or primary care, telemetries, monitors) and at-home or telemedicine interfaces (E.g., Holter devices, event recorders, 6, 3, 2, 1-lead ECG wearables, textile electrodes and patches for mobile cardiac telemetry).
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Train group | – | Diagnostic Test: AI-powered ECG analysis to detect cardiac arrhythmic episodesConsecutive patients admitted to the hospital due to cardiac disorders (retrospective and prospective) with at least one relevant ECG record >10 sec in raw data will be used to design new methodologies and algorithms for cardiac patterns recognition. |
| Test group | – | Diagnostic Test: AI-powered ECG analysis to detect cardiac arrhythmic episodesConsecutive patients admitted to the hospital due to cardiac disorders (retrospective and prospective) with at least one relevant ECG record >10 sec in raw data will be used to evaluate performance of methodologies aiming to avoid overfitting. Every 10 patients included in Train group; a new patient is included in the test group. |
Who may qualify
- Ages
- 4 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients recorded with a mid to long-term ECG device according to guidelines. ECG data (ECG must have been recorded according to the technical standards for the safety and essential performance of medical electrical equipment defined in EN 60601-2-47:2015.): 12-lead ECGs including rest electrocardiograms, stress ECG Test (exercise Electrocardiogram or treadmill test), Holter devices, long-duration Holter devices, event recorders, insertable cardiac monitors, 6,3,2,1-lead ECG wearables, textile electrodes and patches, smartwatches, cardiac monitors, cardiac telemetries, hemodynamic and electrophysiology recording system (i.e., polygraphs), automatic external defibrillator (AED), semi-automatic defibrillator (DESA), home telemonitoring systems and other similar devices.
Key inclusion criteria (4 listed)
- Patient presenting relevant cardiac arrhythmias and cardiac patterns (including supraventricular tachycardias, abnormal ECG patterns, ventricular tachycardias, ventricular fibrillation, pulseless electrical activity or asystole among others) that have been recorded with at least one short-term ECG medical device according to guidelines with ≥1 signal-channel.
- Patient with suspected or diagnosed acute/chronic cardiac diseases (including patients with heart failure, patients with history of cardiac arrhythmias, patients with probable coronary artery diseases, patients with cardiomyopathies, patients with pacemakers or implantable cardioverter-defibrillators (ICD), patients with indication of pacemaker or ICD in current or short-term phase, patients participating in other interventional clinical investigation, patients with hemodynamic instability or acute coronary syndromes, pregnant patients, patients with cancer and chemotherapy, patients with life-expectancy lower than 24 months, patients with in or out-of-hospital cardiac arrest with ventricular fibrillation as first documented rhythm).
- At least one ECG tracing that can be exported in raw data.
- Signed informed consent. Patients unable to consent, it will be requested to an authorized relative.
Key exclusion criteria (2 listed)
- Unwillingness or inability to sign study written informed consent.
- Unavailable or suboptimal quality of the electrocardiographic signal in raw data.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-powered ECG analysis to detect cardiac arrhythmic episodesECG recording and processing by AI platform | Diagnostic test | Test group, Train group |
Primary outcome
Detection of cardiac arrhythmias and cardiac patterns in the electrocardiographic signals
Time frame: real time to 7 minutes
Willem™ heart rhythm and cardiac pattern performance compared to standard manually performed cardiologist diagnosis.
4 secondary outcomes
Survival at follow-up
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Major Adverse Cardiovascular and Cerebrovascular Events (MACCE)
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Re-hospitalization
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Change in quality of life
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Jul 2026.
- Background: PubMed 27296239Lillo-Castellano JM, Marina-Breysse M, Gomez-Gallanti A, Martinez-Ferrer JB, Alzueta J, Perez-Alvarez L, Alberola A, Fernandez-Lozano I, Rodriguez A, Porro R, Anguera I, Fontenla A, Gonzalez-Ferrer JJ, Canadas-Godoy V, Perez-Castellano N, Garofalo D, Salvador-Montanes O, Calvo CJ, Quintanilla JG, Peinado R, Mora-Jimenez I, Perez-Villacastin J, Rojo-Alvarez JL, Filgueiras-Rama D. Safety threshold of R-wave amplitudes in patients with implantable cardioverter defibrillator. Heart. 2016 Oct 15;102(20):1662-70. doi: 10.1136/heartjnl-2016-309295. Epub 2016 Jun 13.
- Background: PubMed 31840163Lillo-Castellano JM, Gonzalez-Ferrer JJ, Marina-Breysse M, Martinez-Ferrer JB, Perez-Alvarez L, Alzueta J, Martinez JG, Rodriguez A, Rodriguez-Perez JC, Anguera I, Vinolas X, Garcia-Alberola A, Quintanilla JG, Alfonso-Almazan JM, Garcia J, Borrego L, Canadas-Godoy V, Perez-Castellano N, Perez-Villacastin J, Jimenez-Diaz J, Jalife J, Filgueiras-Rama D. Personalized monitoring of electrical remodelling during atrial fibrillation progression via remote transmissions from implantable devices. Europace. 2020 May 1;22(5):704-715. doi: 10.1093/europace/euz331.
- Background: PubMed 36310681Quartieri F, Marina-Breysse M, Pollastrelli A, Paini I, Lizcano C, Lillo-Castellano JM, Grammatico A. Artificial intelligence augments detection accuracy of cardiac insertable cardiac monitors: Results from a pilot prospective observational study. Cardiovasc Digit Health J. 2022 Aug 4;3(5):201-211. doi: 10.1016/j.cvdhj.2022.07.071. eCollection 2022 Oct.
- Background: PubMed 37103054Martinez-Selles M, Marina-Breysse M. Current and Future Use of Artificial Intelligence in Electrocardiography. J Cardiovasc Dev Dis. 2023 Apr 17;10(4):175. doi: 10.3390/jcdd10040175.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
José María Lillo, PhD contact
María De La Parte, MD principal investigator
Idoven 1903 S.L.
13 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cardiomyopathies and Cardiac Arrest, run by Idoven 1903 S.L. at 13 sites in 2 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 20 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 13 sites in Spain, Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Manuel Marina-Breysse, MSc, MD (+34618103160, manuel.marina@idoven.ai), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Detection of cardiac arrhythmias and cardiac patterns in the electrocardiographic signals (time frame: real time to 7 minutes). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05890716, which also lists 4 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Jul 2026.