AI-powered ECG Analysis Using Willem™ Software in High-risk Cardiac Patients (WILLEM)
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age4+
SponsorIdoven 1903 S.L.
About this 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:
1. A new AI-powered ECG analysis platform can automatice the classification and prediction of cardiac arrhythmic episodes at a cardiologist level. 2. 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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
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.
Disqualifiers
Unwillingness or inability to sign study written informed consent.
Unavailable or suboptimal quality of the electrocardiographic signal in raw data.
Trial 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.
Trial design
Design model
Cohort
Time perspective
Retrospective
Treatments tested in this trial
AI-powered ECG analysis to detect cardiac arrhythmic episodes
Diagnostic testECG recording and processing by AI platform
Treatment groups
5,342 Participants
are divided into 2 treatment groupsGroup A: Train group1 intervention
Group B: Test group1 intervention
Trial outcomes
Primary outcomes
1
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.
Time frame
real time to 7 minutesSecondary outcomes
1
Survival at follow-up
Patients alive at the time of follow-up
Time frame
1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)2
Major Adverse Cardiovascular and Cerebrovascular Events (MACCE)
MACCE rates defined as cardiovascular and cerebrovascular events during the follow up
Time frame
1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)3
Re-hospitalization
Number of Re-hospitalizations during the follow up.
Time frame
1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)4
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.
Time frame
1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Idoven 1903 S.L.
Lead sponsor
Fundación de Investigación en Red en Enfermedades Cardiovasculares
Collaborator
Spanish Society of Cardiology
Collaborator
Source ClinicalTrials.gov