Background: Coronary artery calcium (CAC) can be identified on non-gated chest CTs, but this finding is not consistently incorporated into care. A deep learning algorithm enables opportunistic CAC screening of non-gated chest CTs. Our objective was to evaluate the impact of notifying clinicians and patients of incidental CAC on statin initiation.
Methods: NOTIFY-1 was a randomized quality improvement project in the Stanford healthcare system. Patients without known atherosclerotic cardiovascular disease (ASCVD) or prior statin prescription were screened for CAC on a prior non-gated chest CT from 2014-2019 using a validated deep learning algorithm with radiologist confirmation. Patients with incidental CAC were randomized to notification of the primary care clinician and patient versus usual care. Notification included a patient-specific image of CAC and guideline recommendations regarding statin use. The primary outcome was statin prescription within 6 months.
Results: Among 2,113 patients who met initial clinical inclusion criteria, CAC was identified by the algorithm in 424 patients. After additional exclusions following chart review, a radiologist confirmed CAC among 173 of 194 patients (89.2%) who were randomized to notification or usual care. At 6 months, the statin prescription rate was 51.2% (44/86) in the notification arm versus 6.9% (6/87) with usual care (p<0.001). There was also more coronary artery disease testing in the notification arm (15.1% [13/86] vs. 2.3% [2/87], p=0.008).
Conclusions: Opportunistic CAC screening of prior non-gated chest CTs followed by clinician and patient notification led to a significant increase in statin prescriptions. Further research is needed to determine whether this approach can reduce ASCVD events.