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Background and Aims: The management of complications of arteriovenous fistula (AVF) for hemodialysis, principally stenosis, remains a major challenge for clinicians with a substantial impact on health resources. Stenosis not infrequently preludes to thrombotic events with the loss of AVF functionality. A functioning AVF, when listened by a stethoscope, has a continuous systolic-diastolic low-frequency murmur, while with stenosis, the frequency of the murmur increases and the duration of diastolic component decreases, disappearing in severe stenosis. These evidences are strictly subjective and dependent from operator skill and experience. New generation digital stethoscopes are able to record sound and subsequently dedicated software allows to extract quantitative variables that characterize the sound in an absolutely objective and repeatable way. The aim of our study was to analyze with an appropriate software sounds from AVFs taken by a commercial digital stethoscope and to investigate the potentiality to develop an objective way to detect stenosis., Methods: Between September 2022 and January 2023, 64 chronic hemodialysis (HD) patients were screened by two blinded experienced examiners for recognized criteria for stenosis by Doppler ultrasound (DUS) and, consequently, the sound coming from the AVFs using a 3 M™ Littmann® CORE Digital Stethoscope 8570 in standardized sites was recorded. The sound waves were transformed into quantitative variables (amplitude and frequency) using a sound analysis software. The practical usefulness of the core digital stethoscope for a quick identification of an AVF stenosis was further evaluated through a pragmatic trial. Eight young nephrologist trainees underwent a simple auscultatory training consisting of two sessions of sound auscultation focusing two times on a "normal" AVF sound by placing the digital stethoscope on a convenience site of a functional AVF., Results: In 48 patients eligible, all sound components displayed, alone, a remarkable diagnostic capacity. More in detail, the AUC of the average power was 0.872 [95% CI 0.729-0.951], while that of the mean normalized frequency was 0.822 [95% 0.656-0.930]. From a total of 32 auscultations (eight different block sequences, each one comprising four auscultations), the young clinicians were able to identify the correct sound (stenosis/normal AVF) in 25 cases, corresponding to an overall accuracy of 78.12% (95% CI 60.03-90.72%)., Conclusions: The analysis of sound waves by a digital stethoscope permitted us to distinguish between stenotic and no stenotic AVFs. The standardization of this technique and the introducing of data in a deep learning algorithm could allow an objective and fast method for a frequent monitoring of AVF., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)