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Health Enhanced Artery Risk Tracking With Widespread Implementation and Screening Effort in ASCVD (HEARTWISE-ASCVD)
Sponsor: Stanford University
Summary
This multi-site study will test whether an opportunistic AI-based CAC screening and notification intervention can improve cholesterol treatment and lower cholesterol levels in adults. The study uses artificial intelligence to detect calcium buildup in heart arteries (coronary artery calcium or CAC) on chest CT scans that patients have already had for other reasons. The study will focus on adults who either have known atherosclerotic cardiovascular disease (ASCVD) or have significant calcium buildup (a CAC score of 100 or higher), and whose cholesterol is not well controlled. It will also evaluate how well this approach can be implemented at scale across multiple health systems. The main questions it aims to answer are: Does notifying patients and their clinicians about incidental CAC increase lipid-lowering therapy(LLT) initiation or intensification? Does the intervention improve Low-Density Lipoprotein(LDL)-cholesterol control and related lipid testing? How does the intervention affect downstream care (e.g., clinic visits, cardiology referrals, and cardiac testing)? Researchers will use an FDA-cleared AI algorithm to quantify CAC on previously performed non-gated chest CT scans and identify eligible participants through the electronic health record. Participants will be randomized to receive CAC notification either right away or after a 6-month delay.
Official title: Health Enhanced Artery Risk Tracking With Widespread Implementation and Screening Effort in AtheroSclerotic CardioVascular Disease (HEARTWISE-ASCVD) Study
Key Details
Gender
All
Age Range
18 Years - 74 Years
Study Type
INTERVENTIONAL
Enrollment
120000
Start Date
2026-03
Completion Date
2028-03
Last Updated
2026-01-21
Healthy Volunteers
No
Interventions
AI-Detected CAC Notification and Care Facilitation
After randomization to the early notification arm, the study team will send a standardized notification message to the participant's affiliated clinician. The study team will send a message to the participant after a brief delay. Each site will determine the timing between the initial message to the clinician and the participant based on stakeholder feedback. The notification is about the AI-CAC identified on the participant's previous chest CT. It will provide an overview of AI-CAC, a personalized image of AI-CAC, and a recommended risk discussion with their clinician. These clinicians will also be notified of the findings. For participants randomized to early notification who do not undergo LLT initiation, intensification, or LDL testing within 2 months, the clinician and participant will receive a second message at that time. The participants in the delayed notification arm will receive a similar notification 6 months later.
Locations (6)
University of California, Los Angeles
Los Angeles, California, United States
Kaiser Permanente Northern California
Pleasanton, California, United States
Stanford University
Stanford, California, United States
Duke University Medical Center
Durham, North Carolina, United States
Vanderbilt University Medical Center
Nashville, Tennessee, United States
Baylor Scott & White
Dallas, Texas, United States