Registry Study for the Evaluation of High-risk Cardiac Patients by WILLEM AI-based ECG Platform
ConditionHigh-risk Cardiac Patients
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorIdoven 1903 S.L.
About this trial
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 criteria
This trial accepts healthy volunteersQualifiers
EC/IRB approval of ICF waiver prior to recruitment; otherwise, signed informed consent form by subject and investigator
Age > 18 years-old, with no upper limit
Subjects undergoing standard of care electrocardiogram (ECG) of any duration from any hardware device
All available, but at least one, legible ECG tracings in raw data format (e.g. DICOM, XML, EDF, JSON, HL7, SCP, WFDB, CSV, etc.)
Disqualifiers
Unavailable or suboptimal quality of the raw data from the ECG signal
Age < 18 years-old
Trial population
Subjects with high-risk and/or high-cost cardiac disease undergoing standard of care ECG assessment during the screening or diagnostic process, complementary tests, interventions, and/or clinical follow-up visits in any setup of care. Additionally, for the assessment of cardiac disease detection, subjects with no cardiac risk may be recruited as well for comparison between confirmed diagnosed patients and confirmed negative diagnosed subjects.
Trial design
Design model
Case-control
Time perspective
Other
Treatments tested in this trial
Willem AI ECG assessment
DeviceThere 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.
Treatment groups
200,000 Participants
are divided into 2 treatment groupsGroup A: High-risk cardiac patients1 intervention
Group B: Controls1 intervention
Trial outcomes
Primary outcomes
1
Primary endpoint analysis: Willem performance
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.
Time frame
From enrollment to any standard of care timepoint when the patient underwent (retrospective) or will undergo within the next 10 years (prospective) an eligible electrocardiogramSponsors and contacts
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Source ClinicalTrials.gov