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Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data
- Source :
- Scientific Reports, Scientific Reports, 11(1). NATURE PORTFOLIO, Scientific reports, vol 11, iss 1, Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Publishing Group UK, 2021.
-
Abstract
- Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (− 5.7 mm3 and − 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (− 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.
- Subjects :
- Male
medicine.medical_specialty
Aging
Science
Plaque progression
Coronary Artery Disease
Cardiovascular
Coronary Angiography
Gastroenterology
Article
Internal medicine
Medicine
2.1 Biological and endogenous factors
Cluster Analysis
Humans
Coronary artery disease and stable angina
Aetiology
Vascular Calcification
Computed tomography
Coronary atherosclerosis
Heart Disease - Coronary Heart Disease
Plaque
Atherosclerotic
Aged
Multidisciplinary
business.industry
Plaque composition
Volume percent
Coronary computed tomography angiography
Middle Aged
medicine.disease
Atherosclerosis
Plaque, Atherosclerotic
Heart Disease
Biomedical Imaging
Registry data
Female
Unsupervised clustering
business
Progressive disease
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....daa05dd14c0284e63b20503f12a5080b