AI-powered ECG analysis to detect cardiac arrhythmic episodes
Diagnostic TestECG recording and processing by AI platform
NCT Number: NCT05890716
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.
Interested in participating?
Request Info4 year and older
All sexes
Observational
University Medical Center Groningen, Groningen, Provincie Groningen, Netherlands
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).
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
ECG recording and processing by AI platform
Time frame: real time to 7 minutes
Willem™ heart rhythm and cardiac pattern performance compared to standard manually performed cardiologist diagnosis.
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
Patients alive at the time of follow-up
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
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)
Number of Re-hospitalizations during the follow up.
Time frame: 1 year after the first ECG (prospective patients) or after patient enrollment (retrospective patients)
European Quality of Life-5 Dimensions (EQ-5D) index an utility scores anchored at 0 for death and 1 for perfect health.
Contact information is provided by the study sponsor or research team.
José María Lillo, PhD
CONTACT
Manuel Marina-Breysse, MSc, MD
CONTACT
Idoven 1903 S.L.
Industry
Evaluation of Electrocardiographic Data From High-risk Cardiac Patients Using Willem™ Cardiologist-level Artificial Intelligence Software. WILLEM Trial.
Acronym: WILLEM
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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