Machine Learning for Handheld Vascular Studies

NCT02932176 | Recruiting

• 1 other identifier: Pro00070090
• Study Type: observational
• Target: 180
• Locations: 1 country
• Sites: 1

Brief Summary

The use of handheld arterial 'stethoscopes' (continuous wave Doppler devices) are ubiquitous in clinical practice. However, most users have received no formal training in their use or the interpretation of the returned data. This leads to delays in diagnosis and errors in diagnosis. The investigators intend to create a novel machine-learning algorithm to assist clinicians in the use of this data. This study will allow the investigators to collect sound files from the use of the devices and compare the algorithms output to established, existing vascular testing. There will be no invasive procedures, and use of these stethoscopes is part of routine clinical care. If successful, this data and algorithm will be later deployed via smartphone app for point of case testing in a separate study

Conditions

Atherosclerosis; Wounds and Injuries

Keywords

Arteries

Outcome Measures

Primary Outcomes (1)

• Algorithm generated Doppler classification

  1 year

Secondary Outcomes (4)

• Presence or absence of pulse

  1 year

• Quality of pulse

  1 year

• Presence or absence of Doppler signal

  1 year

• Quality of Doppler signal

  1 year

Study Arms (1)

Non-invasive vascular testing

All patients undergoing non-invasive vascular testing will be eligible for this study. The official results will be used to develop the algorithm and to evaluate the accuracy of the algorithm

Device: Non-invasive vascular testing; Device: machine-learning algorithm

Interventions

Non-invasive vascular testing DEVICE

Results of clinically indicated non-invasive vascular testing will be used to develop a machine learning algorithm

Also known as: Continuous wave Doppler, plethysmography

Non-invasive vascular testing

machine-learning algorithm DEVICE

Non-invasive vascular testing

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with a clinical indication and order for non-invasive vascular testing

You may qualify if:

• A clinically driven request for non-invasive vascular testing must be present

You may not qualify if:

• None (other than patient declines to participate)

Sponsors & Collaborators

• Duke University: lead

Study Sites (1)

Duke University Medical Center

Durham, North Carolina, 27710, United States

RECRUITING

MeSH Terms

Conditions

Atherosclerosis; Wounds and Injuries

Interventions

Plethysmography

Condition Hierarchy (Ancestors)

Arteriosclerosis; Arterial Occlusive Diseases; Vascular Diseases; Cardiovascular Diseases

Intervention Hierarchy (Ancestors)

Diagnostic Techniques, Cardiovascular; Diagnostic Techniques and Procedures; Diagnosis

Central Study Contacts

Leila Mureebe, MD

CONTACT

leila.mureebe@duke.edu

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 19, 2016
• First Posted: October 13, 2016
• Study Start: September 7, 2016
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: March 5, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)