Registry Study for the Evaluation of High-risk Cardiac Patients by WILLEM AI-based ECG Platform

Condition(s) studied

Investigational drug(s) / intervention(s)

Willem AI ECG assessment: There is no study intervention. The Willem AI platform will assess all study ECGs for the identification of cardiac patterns, arrhythmias, and/or cardiac diseases. Regardless of retrospective or prospective enrollment, Willem output will not be provided to the healthcare professional user for clinical evaluation, and therefore routine practice will not be impacted nor altered.

Study summary

The WILLEM Registry is a large-scale, single-group, observational, registry study to collect continuous clinical evidence of Willem in real-world settings. Cardiovascular diseases are a major problem for public health and healthcare systems. Electrocardiograms (ECGs) are simple tests which increase diagnostic performance and early detection of cardiovascular diseases. However, its interpretation is complex, time consuming for cardiology experts, and entails high costs for healthcare systems. Willem allows AI-based automatic interpretation and its performance has been examined in previous clinical trials, but additional clinical evidence is needed for its integration in real-world clinical settings. This study will collect clinical evidence of Willem performance to detect cardiac abnormalities in ECGs from high-risk cardiac patients admitted to cardiovascular units.

Eligibility

Primary outcome measure(s)

• Primary endpoint analysis: Willem performance — From enrollment to any standard of care timepoint when the patient underwent (retrospective) or will undergo within the next 10 years (prospective) an eligible electrocardiogram
  ECG data will be categorized according to SOC-defined cardiopathies, arrhythmic events, and cardiac diseases. If SOC diagnosis is unavailable or inconsistent, an independent committee of expert cardiologists will review and provide their diagnosis according to a cardiac defined ontology which extends values defined in HL7-aECG data store. Then, the performance of Willem to detect cardiac patterns, arrhythmias, and cardiac disease from ECGs will be assessed. In order to define True Positive, True Negative, False Positive, and False Negative classifications, the ground truth for comparison will be Standard Of Care (SOC) manually performed cardiologist diagnosis. Performance metrics such as diagnostic accuracy, sensitivity, specificity, predictive positive value (PPV), negative predictive value (NPV), F1-Score and Area Under the Receiver Operating Characteristic Curve (AUROC) will be obtained.

Trial sites (5)

More Idoven 1903 S.L. trials in Spain