Sex differences in plaque burden and outcomes in symptomatic patients with suspected coronary artery disease

Abstract

<div><h3>Background</h3><div>Sex-related differences in coronary artery disease (CAD) burden and outcomes are increasingly recognized but not fully understood, particularly when assessed using advanced imaging techniques.</div></div><div><h3>Objectives</h3><div>To investigate sex differences in coronary plaque characteristics and their association with long-term cardiovascular outcomes in symptomatic patients undergoing coronary computed tomography angiography (CTA).</div></div><div><h3>Methods</h3><div>A total of 2271 symptomatic patients without prior obstructive CAD underwent CTA, followed by artificial intelligence-based quantitative plaque analysis (AI-QCT) extracting plaque features including total plaque volume (TPV), non-calcified plaque (NCP), low-density plaque (LDP), and calcified plaque (CP). CAD severity was classified in accordance with CAD-RADS. Long-term outcomes, including myocardial infarction (MI), acute coronary syndrome (ACS) and death, were tracked over a median follow-up of 7.3 years. Analyses were stratified by sex and CAD-RADS category.</div></div><div><h3>Results</h3><div>Women (<em>n</em> = 1316) were older but had significantly lower plaque burden across all CAD-RADS categories compared to men (<em>n</em> = 955). Despite this, women had non-negligible number of MI (<em>n</em> = 31) and ACS (<em>n</em> = 46), with the highest rate in CAD-RADS 3 (1.1 % MI and 1.6 % ACS), whereas in men (totally 37 MI, 54 ACS), event rates were highest in CAD-RADS 4 (1.9 % MI and 2.5 % ACS). No cardiovascular events were recorded in CAD-RADS 0 for either sex. In multivariable Cox regression, stenosis severity was the strongest predictor of events in men, while TPV was more predictive in women. In gradient boosting machine (GBM) analysis, TPV and stenosis severity had the highest overall relative importance in explaining events.</div></div><div><h3>Conclusions</h3><div>This study demonstrates important sex-based differences in CAD phenotype and prognosis. Women had lower plaque burden, yet experienced adverse events with lower CAD-RADS, suggesting that current risk stratification may underestimate their risk. AI-QCT provides enhanced plaque characterization, which may in the future improve individualized assessment, especially in women.<br></div></div>