ArticleAmerican journal of preventive cardiology2026
Associations of 10-year predicted ASCVD risk by the PREVENT equations with AI-analyzed coronary atherosclerotic plaque characteristics.
Article in American journal of preventive cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The PREVENT equations estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk. If 10-year ASCVD risk is associated with coronary plaque burden, it can guide who should be screened. Methods: Asymptomatic patients without prior cardiovascular events underwent coronary CT angiography, with plaque features quantified using AI-based analysis. Ten-year predicted ASCVD risk was calculated by the PREVENT equations and categorized as low (<5%), borderline (5-<7.5%), and intermediate-high (≥7.5%). We used quantile regression to assess associations between 10-year predicted ASCVD risk and total plaque volume (TPV), percent atheroma volume (PAV), calcified plaque (CP), non-calcified plaque (NCP), and low-density non-calcified plaque (LDNCP). Results: Overall, 425 adults, median age 55 years; 31.5% female, were included. Higher 10-year ASCVD risk was associated with more TPV, PAV, NCP, LDNCP, CP, stenosis area and diameter, and remodeling index. For example, median TPV was 63.4, 109.0, and 212.7 mm Conclusion: Ten-year ASCVD risk estimated by the PREVENT equations was associated with coronary plaque burden.
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