The DECIDE study will evaluate the impact of AI-enabled quantitative atherosclerotic plaque measurement on changes in preventive and anti-ischemic care for 20,000 patients with suspected or known CAD.
Does AI-enabled quantitative coronary plaque assessment (QCPA) change preventive and anti-ischemic care in patients with suspected or known CAD?
The DECIDE study will evaluate whether AI-enabled quantitative plaque assessment on coronary CTA improves the implementation of preventive and anti-ischemic care in patients with CAD.
BACKGROUND: Approximately half of the patients with abnormal findings have no minimal changes in clinical management after stress testing. OBJECTIVES: The primary aim of this study is to assess changes in preventive and anti-ischemic care for stable patients with atherosclerotic plaque on coronary computed tomographic angiography (CTA). METHODS: Projected enrollment is 20,000 patients (∼40 sites) who underwent diagnostic testing for suspected or known coronary artery disease. Changes in medical therapy (dosing and type) and coronary revascularization will be collected through an automated electronic health record data extraction through 1 year of follow-up. In select subgroups, artificial intelligence-enabled quantitative measures of coronary atherosclerotic plaque (QCPA) will be provided promptly or delayed by 90 days, such that prompt decisions guided by coronary artery disease stenosis alone can be compared with QCPA-guided treatment. RESULTS: A total of 6 care pathways will be evaluated: 1) no QCPA is provided (usual testing); 2) QCPA is provided but delayed and subsequently incorporated into a revised final report to guide patient management; 3) immediate QCPA is provided in nonrevascularized patients; 4) immediate QCPA is provided to patients with prior stenting in 1 vessel; 5) immediate QCPA is provided to asymptomatic patients referred for coronary CTA; and 6) patients referred to stress testing with no coronary CTA (ie, the comparator). CONCLUSIONS: The DECIDE (DErived Plaque Quantification: CCTA and AI-QCPA for Determining Effective CAD management) study will enroll and characterize a broad spectrum of patients who require initiation and intensification of preventive care. The authors will use efficient and automated systems to evaluate the impact of quantitative atherosclerotic plaque measurement on preventive care that will help guide implementation strategies to improve outcomes for patients undergoing coronary CTA.
Rinehart et al. (Wed,) conducted a other in Suspected or known coronary artery disease (n=20,000). Artificial intelligence-enabled quantitative measures of coronary atherosclerotic plaque (QCPA) vs. Usual testing (no QCPA) or stress testing with no coronary CTA was evaluated on Changes in preventive and anti-ischemic care (medical therapy and coronary revascularization). The DECIDE study will evaluate the impact of AI-enabled quantitative atherosclerotic plaque measurement on changes in preventive and anti-ischemic care for 20,000 patients with suspected or known CAD.
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