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.
Non-gated chest CT performed within the prior 2 years within the health system
Active enrollment in the site's integrated healthcare plan (e.g., Kaiser Permanente Northern California), OR
LDL-C measured within the health system within the prior 2 years, OR
Outpatient cardiovascular medication prescription within the prior year
Dementia
Heart transplant
Active hospice
Other life-limiting illness as determined by the site investigator (e.g., metastatic cancer)
Parallel
AI-Detected CAC Notification and Care Facilitation
Other interventionAfter 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.
Lipid-lowering therapy initiation or intensification (LLTI)
* Number of new statin prescriptions * Number of statin doses/intensity increase * Number of PSCK9 inhibitor initiation (monoclonal antibodies and siRNA) * Number of Ezetimibe initiations * Number of Bempedoic acid initiations
Aspirin prescription
Number of new Aspirin or other antiplatelet prescription
Lipid panel (total cholesterol, HDL-C, LDL-C, triglycerides) ordering
Number of Lipid panel ordering
Lipoprotein(a) test ordering
Number of Lipoprotein(a) test ordering
Changes of total cholesterol, HDL-C, LDL-C, triglycerides, Lipoprotein(a) levels
This outcome measure the changes of the test levels
Click on the lead sponsor to view all of their trials.
Stanford University
Lead sponsor
Amgen
Collaborator
Baylor Scott and White Health
Collaborator
Kaiser Permanente
Collaborator
Vanderbilt University Medical Center
Collaborator
Duke University
Collaborator
University of California, Los Angeles
Collaborator
This trial is not recruiting at the moment. You can still explore other options:
