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.
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 Type
OBSERVATIONAL
Enrollment
5,342
ECG recording and processing by AI platform
University Medical Center Groningen
Groningen, Provincie Groningen, Netherlands
COMPLETEDHospital Sant Joan de Déu
Barcelona, Barcelona, Spain
COMPLETEDHospital General Universitario de Ciudad Real
Ciudad Real, Ciudad Real, Spain
COMPLETEDComplejo Hospitalario Universitario A Coruña
A Coruña, La Coruña, Spain
COMPLETEDIdoven 1903 S.L.
Madrid, Madrid, Spain
RECRUITINGHospital Clínico San Carlos
Madrid, Madrid, Spain
COMPLETEDHospital Universitario Puerta de Hierro
Madrid, Madrid, Spain
RECRUITINGHospital Universitario General de Villalba
Madrid, Madrid, Spain
COMPLETEDHospital Universitario del Henares
Madrid, Madrid, Spain
COMPLETEDHospital Virgen de Arrixaca
Murcia, Murcia, Spain
COMPLETED...and 4 more locations
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 minutes
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)
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)
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)
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)
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