Phenotypic Clustering of Patients With Newly Diagnosed Coronary Artery Disease Using Cardiovascular Magnetic Resonance and Coronary Computed Tomography Angiography
Background: Epidemiological characteristics and prognostic profiles of patients with newly diagnosed coronary artery disease (CAD) are heterogeneous. Therefore, providing individualized cardiovascular (CV) risk stratification and tailored prevention is crucial.Objective: Phenotypic unsupervised clus...
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/a1bba726d9e0464ca6fab0b443f31d09 |
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| Sumario: | Background: Epidemiological characteristics and prognostic profiles of patients with newly diagnosed coronary artery disease (CAD) are heterogeneous. Therefore, providing individualized cardiovascular (CV) risk stratification and tailored prevention is crucial.Objective: Phenotypic unsupervised clustering integrating clinical, coronary computed tomography angiography (CCTA), and cardiac magnetic resonance (CMR) data were used to unveil pathophysiological differences between subgroups of patients with newly diagnosed CAD.Materials and Methods: Between 2008 and 2020, consecutive patients with newly diagnosed obstructive CAD on CCTA and further referred for vasodilator stress CMR were followed for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular death or non-fatal myocardial infarction. For this exploratory work, a cluster analysis was performed on clinical, CCTA, and CMR variables, and associations between phenogroups and outcomes were assessed.Results: Among 2,210 patients who underwent both CCTA and CMR, 2,015 (46% men, mean 70 ± 12 years) completed follow-up [median 6.8 (IQR 5.9–9.2) years], in which 277 experienced a MACE (13.7%). Three mutually exclusive and clinically distinct phenogroups (PG) were identified based upon unsupervised hierarchical clustering of principal components: (PG1) CAD in elderly patients with few traditional risk factors; (PG2) women with metabolic syndrome, calcified plaques on CCTA, and preserved left ventricular ejection fraction (LVEF); (PG3) younger men smokers with proximal non-calcified plaques on CCTA, myocardial scar, and reduced LVEF. Using survival analysis, the occurrence of MACE, cardiovascular mortality, and all-cause mortality (all p < 0.001) differed among the three PG, in which PG3 had the worse prognosis. In each PG, inducible ischemia was associated with MACE [PG1, Hazards Ratio (HR) = 3.09, 95% CI, 1.70–5.62; PG2, HR = 3.62, 95% CI, 2.31–5.7; PG3, HR = 3.55, 95% CI, 2.3–5.49; all p < 0.001]. The study presented some key limitations that may impact generalizability.Conclusions: Cluster analysis of clinical, CCTA, and CMR variables identified three phenogroups of patients with newly diagnosed CAD that were associated with distinct clinical and prognostic profiles. Inducible ischemia assessed by stress CMR remained associated with the occurrence of MACE within each phenogroup. Whether automated unsupervised phenogrouping of CAD patients may improve clinical decision-making should be further explored in prospective studies. |
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