Using Artificial Intelligence on Electrocardiograms to Detect Aortic Stenosis and Diastolic Dysfunction in Outpatient Care

What this Trial Is About

Researchers are evaluating two newly developed artificial intelligence-enabled electrocardiogram AI-ECG models designed to detect aortic stenosis and diastolic dysfunction in outpatients aged 60 and older. These AI-ECG models show promising sensitivity and specificity but have not yet been tested prospectively to assess their real-world diagnostic and prognostic value, especially in settings with limited access to advanced medical care. Participants undergo their standard outpatient electrocardiogram ECG, which is then processed through the AI-ECG Dashboard. If the AI-ECG indicates possible aortic stenosis or diastolic dysfunction, patients will receive a point-of-care ultrasound to confirm the diagnosis. The study is observational and involves no additional experimental treatments. During the study, researchers will track the number of patients with positive AI-ECG results and the quality of their ultrasound images. They will also compare AI-ECG findings with traditional transthoracic echocardiogram results. The study aims to understand the usefulness of AI-ECG in routine outpatient practice, with participation ongoing until March 2027.

AI in Outpatient Practice for Diagnosing Aortic Stenosis and Diastolic Dysfunction