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Artificial Intelligence for Early Detection of Peripheral Artery Disease

NCT06505317 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 7800

Last updated 2024-07-17

No results posted yet for this study

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.

Conditions

  • Peripheral Arterial Disease

Interventions

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.

Sponsors & Collaborators

Principal Investigators

  • Elsie Ross, MD, MSc · UC San Diego

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
CROSSOVER

Eligibility

Min Age
50 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-07-01
Primary Completion
2027-07-01
Completion
2028-06-30

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06505317 on ClinicalTrials.gov