Epicardial adipose tissue thickness by echocardiography is a marker for the presence and severity of coronary artery disease
Abstract Background and aim Epicardial adipose tissue (EAT), which is thought to be a component of visceral adiposity, is associated with the metabolic syndrome. We aimed to test the hypothesis that echocardiographic EAT thickness can be a marker for the presence and severity of coronary artery dise...
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Published in: | Nutrition, metabolism, and cardiovascular diseases Vol. 19; no. 3; pp. 211 - 217 |
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Main Authors: | , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Netherlands
Elsevier B.V
01-03-2009
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Subjects: | |
Online Access: | Get full text |
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Summary: | Abstract Background and aim Epicardial adipose tissue (EAT), which is thought to be a component of visceral adiposity, is associated with the metabolic syndrome. We aimed to test the hypothesis that echocardiographic EAT thickness can be a marker for the presence and severity of coronary artery disease (CAD). Method and results In all, 150 patients (100 patients with CAD and 50 patients with normal coronary arteries by diagnostic coronary angiography; 65 women, 85 men; mean age 55.7 ± 7.4 years) were enrolled. EAT thickness was measured using 2-D echocardiographic parasternal long- and short-axis views. EAT thickness measurements were compared with angiographic findings. EAT thickness was significantly higher in patients with CAD in comparison to those with normal coronary arteries (6.9 ± 1.5 mm vs. 4.4 ± 0.8 mm; P < 0.001). Furthermore, EAT thickness increased with the severity of CAD (multivessel disease 7.4 ± 1.2 mm vs. single vessel disease 5.7 ± 1.7 mm; P < 0.001). Gensini's score significantly correlated with EAT thickness ( r = 0.600, P < 0.001). EAT thickness of ≥5.2 mm had 85% sensitivity and 81% specificity (ROC area 0.914, P < 0.001, 95% CI [0.86–0.96]) for predicting CAD. Conclusion EAT thickness, which is easily and non-invasively evaluated by transthoracic echocardiography, can be an adjunctive marker to classical risk factors for the prediction of CAD. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0939-4753 1590-3729 |
DOI: | 10.1016/j.numecd.2008.05.002 |