CONFIRM II: AI-QCT Assessment of Coronary Plaque Feature Confers Higher Relative Risk of MACE in Women
Coronary atherosclerotic phenotypes, including total plaque volume (TPV), noncalcified plaque (NCP), calcified plaque (CP) and percentage atheroma volume (PAV), assessed by artificial intelligence-based quantitative coronary computed tomography (AI-QCT) conferred a higher relative risk of major adverse cardiovascular events (MACE) in women, based on findings from the CONFIRM II trial presented at ACC.25 in Chicago and simultaneously published in Circulation: Cardiovascular Imaging.
The study enrolled 3,551 symptomatic patients with suspicion of coronary artery disease (CAD). AI-QCT was used to analyze 16 CAD features. The mean age of participants was approximately 59 years and half were women. The primary endpoint was MACE, defined as death, myocardial infarction, late revascularization, cerebrovascular events, unstable angina and congestive heart failure, over an average follow-up of 4.8 years.
All told, MACE occurred in 3.2% of women and 6.1% of men during the follow-up period. Researchers also noted that TPV, CP and PAV, assessed by AI-QCT, were significantly higher in men and that high-risk plaque was more prevalent in men compared with women (9.2% vs. 2.5%). Despite this higher burden in men, however, AI-QCT derived features of TPV, NCP, CP and PAV conferred a higher relative risk of MACE in women compared with men. For example, for every 50 mm3 increase in TPV, relative risk increased by 17.7% in women vs. 5.3% in men, researchers said. Additionally, NCP relative risk increased by 27.1% vs. 11.6%, and CP relative risk increased by 22.9% vs. 5.4%, respectively.
"The current study shows that symptomatic women with suspected CAD have approximately half the amount of coronary atherosclerosis compared with men, and experience approximately 50% lower MACE during follow-up. However, the relative risk associated with TPV, NCP, CP, and PAV was higher in women compared to men," said Gudrun M. Feuchtner, MD, and colleagues. They add that integrating quantitative AI-QCT parameters offers a more accurate risk estimate in women and "may prompt more aggressive anti-atherosclerotic therapy and reinforced preventive interventions."
Keywords: ACC Annual Scientific Session, ACC25
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