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

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Peripheral Arterial Disease
• Intervention / Treatment: Diagnostic test: AI-based PAD screening intervention

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.

• Study Type: Interventional
• Enrollment (Estimated): 7800
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Kathleen Groh; Phone Number: 8585348103; Email: kagroh@health.ucsd.edu

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Clinical Site 1; Randomized to start AI-based PAD screening interventionat week 13.	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.
Experimental: Clinical Site 2; Randomized to start AI-based PAD screening intervention at Week 26.	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.
Experimental: Clinical Site 3; Randomized to start AI-based PAD screening intervention at Week 39.	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
PAD Diagnosis Rate	The primary outcome will be counted at a clinic and site level and will include number of new abnormal ABI tests (ABI< 0.9), and new diagnosis codes, procedures or affirmative text mentions for PAD for patients without a previous diagnosis	During 13-39 weeks prior to intervention compared to 13-39 weeks during intervention depending on timing of randomization to intervention period.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Initiation of secondary prevention measures	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 time period.	During 13-39 weeks prior to intervention compared to 13-39 weeks during intervention depending on timing of randomization to intervention period.

Collaborators and Investigators

• Sponsor: University of California, San Diego
• Collaborators: National Institute on Aging (NIA); Stanford University
• Investigators: Principal Investigator: Elsie Ross, MD, MSc, UC San Diego

Publications and helpful links

General Publications

• Ghanzouri I, Amal S, Ho V, Safarnejad L, Cabot J, Brown-Johnson CG, Leeper N, Asch S, Shah NH, Ross EG. Performance and usability testing of an automated tool for detection of peripheral artery disease using electronic health records. Sci Rep. 2022 Aug 3;12(1):13364. doi: 10.1038/s41598-022-17180-5.

Study record dates

Study Major Dates

• Study Start (Estimated): July 1, 2026
• Primary Completion (Estimated): July 1, 2027
• Study Completion (Estimated): June 30, 2028

Study Registration Dates

• First Submitted: July 10, 2024
• First Submitted That Met QC Criteria: July 10, 2024
• First Posted (Actual): July 17, 2024

Study Record Updates

• Last Update Posted (Actual): July 17, 2024
• Last Update Submitted That Met QC Criteria: July 10, 2024
• Last Verified: July 1, 2024

More Information

Terms related to this study

• Keywords: Peripheral Arterial Disease
• Additional Relevant MeSH Terms: Cardiovascular Diseases; Vascular Diseases; Arteriosclerosis; Arterial Occlusive Diseases; Atherosclerosis; Peripheral Arterial Disease; Peripheral Vascular Diseases
• Other Study ID Numbers: (AID-PAD); R01AG084343-01 (U.S. NIH Grant/Contract)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No