AI-powered ECG Analysis Using Willem™ Software in High-risk Cardiac Patients (WILLEM)

Condition(s) studied

Investigational drug(s) / intervention(s)

AI-powered ECG analysis to detect cardiac arrhythmic episodes: ECG recording and processing by AI platform

Study 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. 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

Primary outcome measure(s)

• Detection of cardiac arrhythmias and cardiac patterns in the electrocardiographic signals — real time to 7 minutes
  Willem™ heart rhythm and cardiac pattern performance compared to standard manually performed cardiologist diagnosis.

Trial sites (13)

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