NCT06505317

Artificial Intelligence for Early Detection of Peripheral Artery Disease

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 7,800 (estimated)
• Sponsor: University of California, San Diego · Academic / Other
• Sex: All
• Age: 50 Years – 85 Years
• Healthy volunteers: Accepted

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.

Detailed description

After providers consent to participate in this study, a screening tool will be deployed for their weekly clinics to identify patients at high risk of having undiagnosed PAD. These high risk alerts will be provided after a patient has checked in for their outpatient appointment. The alert will be sent to their treating provider once the visit is initiated in the electronic health record system (EHR). 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. For secondary analysis we will specifically evaluate patients who generated an alert and assess how patient demographics and/or clinical factors are associated with likelihood of ABI testing, rate of abnormal ABIs (i.e. true positive rate), and subsequent initiation of secondary prevention measures. UC San Diego Health (UCSDH), VA San Diego Health Care (VASDHC), and Stanford Health Care (SHC) will be the sites for study enrollment. UCSDH - La Jolla campus, UCSDH - Hillcrest campus, and VASDHC will begin a pre-intervention observation period at the same time, and then each site will be randomized to begin screening tool intervention in a stepped wedge pattern at 13-week intervals for a total of 52 weeks. We will enroll 10 clinics per site based on power calculations for number of patients needed to screen each week and to minimize the number of alerts per clinic/ provider. After this 52 week period, the Stanford site will serve as a validation site and will undergo randomization of 10 clinical sites to three 13 week intervals for a total of 52 weeks.

Conditions

• Peripheral Arterial Disease

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	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.

Timeline

• Start date: 2026-07-01
• Primary completion: 2027-07-01
• Completion: 2028-06-30
• First posted: 2024-07-17
• Last updated: 2024-07-17