Artificial Intelligence for Early Detection of Peripheral Artery Disease

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

7800 participants

Study Classification

INTERVENTIONAL

Study Start Date

2026-07-01

Study Completion Date

2028-06-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

Digital Ankle Brachial Index (ABI) as a Screening Tool in Detecting Peripheral Arterial Disease

NCT03161327

Peripheral Artery Disease Amputation Smoking +3 more

COMPLETED NA

Simplified and Easy Detection of Arterial Disease in Nursing Homes

NCT03362710

Artery Disease, Peripheral

COMPLETED NA

Artificial Intelligence to Improve Detection and Risk Stratification of Acute Pulmonary Embolism (AID-PE)

NCT06093217

Pulmonary Embolism

COMPLETED

Detecting Peripheral Artery Disease With the Pulse

NCT07226193

Peripheral Artery Disease (PAD)

NOT_YET_RECRUITING NA

BRAVO: Biomarker Risk Assessment in Vulnerable Outpatients

NCT02276781

Peripheral Arterial Disease

COMPLETED

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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

See the medical conditions and disease areas that this research is targeting or investigating.

Peripheral Arterial Disease

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

A stepped wedge cluster randomization design was chosen as a pragmatic way to evaluate the "real world" impact of AI-based PAD screening. The stepped wedge design has been used to evaluate a variety of interventions, including digital health-based studies. This particular design allows for analysis within and between clusters and can reduce the total number of clusters needed to see an effect, helping increase statistical power compared to parallel cluster randomization. A stepped wedge design, like other cluster randomization designs, also helps reduce possible contamination effects. By using institutions as the basis for clustering, we minimize the possibility that physicians increase their PAD diagnosis rates based on knowledge of the screening tool from adjacent clinics rather than direct use.

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Clinical Site 1

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

Group Type EXPERIMENTAL

AI-based PAD screening intervention

Intervention Type DIAGNOSTIC_TEST

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.

Clinical Site 2

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

Group Type EXPERIMENTAL

AI-based PAD screening intervention

Intervention Type DIAGNOSTIC_TEST

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.

Clinical Site 3

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

Group Type EXPERIMENTAL

AI-based PAD screening intervention

Intervention Type DIAGNOSTIC_TEST

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.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

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.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

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