Clinical Research Directory
Browse clinical research sites, groups, and studies.
Artificial Intelligence for Early Detection of Peripheral Artery Disease
Sponsor: University of California, San Diego
Summary
The goal of this clinical trial is to test an AI-based screening tool that will help to identify patients at high risk of having undiagnosed peripheral artery disease. The primary outcome measure is overall rate of new PAD diagnoses. Secondary outcomes include rate of new secondary prevention measures initiated for PAD, which will include new prescriptions for antiplatelets, PAD-dosed rivaroxaban, statins, smoking cessation counseling or referrals, and/or supervised exercise therapy referrals also aggregated at a clinic and site level.
Key Details
Gender
All
Age Range
50 Years - 85 Years
Study Type
INTERVENTIONAL
Enrollment
7800
Start Date
2026-07-01
Completion Date
2028-06-30
Last Updated
2024-07-17
Healthy Volunteers
Yes
Conditions
Interventions
AI-based PAD screening intervention
Providers will receive alerts for a patient that is flagged by model as being "high risk" for PAD. This will allow the provider to review the alert, check the patient's previous history, develop additional questions to assess the risk of PAD, and initiate orders prior to seeing a patient. Depending on their assessment during the patient visit the provider may choose to order an ABI test (or perform one at bedside) and/or initiate other secondary prevention measures. All patients for which an alert is triggered will be included for secondary analysis.