Utilization of AI to Diagnose Aortic Stenosis in Patients Undergoing Hemodialysis

Background: Patients undergoing maintenance hemodialysis (HD) have a high risk of developing cardiovascular diseases due to calcification of the heart valves and coronary arteries, which results in a high mortality rate. In particular, aortic stenosis (AS) is an independent risk factor for heart failure-related mortality in patients undergoing HD. Recently, the analysis of digitized heart sounds using artificial intelligence (AI) has promoted the automation of cardiac disease detection and technological advances in diagnostic algorithms. Methods: We retrospectively investigated the 203 consecutive patients receiving HD who had undergone visualized phonocardiography using a regulatory-approved medical device (Japan) between January and May 2025 to detect AS. The usefulness of this phonocardiogram device, which utilizes acoustic analysis and an AI-based automatic diagnostic algorithm named the “Super Stethoscope”, was evaluated for the screening of AS in patients undergoing HD based on comparisons with findings obtained from echocardiography. Results: The results showed a significant correlation between the severity of systolic murmurs determined by the AI-based approach and the peak aortic jet velocity measured in 19 patients diagnosed with AS using transthoracic echocardiography (r = 0.578, p < 0.05). Additionally, for the AI-based diagnosis of AS based on systolic murmurs, the sensitivity and specificity in detecting moderate or severe AS were 0.90 and 0.70, respectively, among the patients undergoing HD. Conclusions: The AI-based diagnostic approach using the ECG-gated phonocardiogram “Super Stethoscope” could be a promising tool for AS screening. Transthoracic echocardiography is recommended in cases classified as grade B or higher by AI-based assessment.