This observational study aims to improve how doctors use handheld devices, like arterial 'stethoscopes' (continuous wave Doppler devices), to check for conditions like atherosclerosis (hardening of the arteries) and wounds. Many doctors haven't had much training in using these devices or understanding their results, which can lead to delays or mistakes in diagnosis. Researchers are creating a machine-learning algorithm (a computer program that learns from data) to help doctors interpret the sounds from these devices. They will collect sound files from routine vascular tests and compare the algorithm's results to existing, established tests. There are no invasive procedures involved, and the use of these devices is already part of standard care. If successful, this technology could be used in a smartphone app to help with testing in the future.

Study design

This is an observational study with a planned enrollment of 180 participants. It is not a randomized or blinded study.

What's involved

You would undergo clinically indicated non-invasive vascular testing, and the sound files from these tests would be collected for the study.

Compensation

Not stated in the trial record.

Follow-up

The primary endpoint, algorithm generated Doppler classification, will be measured at 1 year.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.