Artificial Intelligence for Early Detection of Peripheral Artery Disease ((AID-PAD))

University of California San Diego

Status: Begins enrollment in 4 months

Conditions: Peripheral Arterial Disease

Treatments: Diagnostic Test: AI-based PAD screening intervention

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT06505317

R01AG084343-01 (U.S. NIH Grant/Contract)

(AID-PAD)

Details and patient eligibility

About

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.

Full 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.

Enrollment: 7,800 estimated patients

Sex: All

Ages: 50 to 85 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Aged 50-85 years
• Presenting to an outpatient appointment at UCSDH, SDVA, or SHC
• No previous diagnosis of PAD
• No prior PAD alert triggered for a previous visit

Exclusion criteria

• <50 years of age or > 85 years of age
• Prior diagnosis of PAD

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: None (Open label)

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7,800 participants in 3 patient groups

Clinical Site 1

Experimental group

Description:

Randomized to start AI-based PAD screening interventionat week 13.

Treatment:

Diagnostic Test: AI-based PAD screening intervention

Clinical Site 2

Experimental group

Description:

Randomized to start AI-based PAD screening intervention at Week 26.

Treatment:

Diagnostic Test: AI-based PAD screening intervention

Clinical Site 3

Experimental group

Description:

Randomized to start AI-based PAD screening intervention at Week 39.

Treatment:

Diagnostic Test: AI-based PAD screening intervention