Literature DB >> 24954286

Can aortic atherosclerosis or epicardial adipose tissue volume be used as a marker for predicting coronary artery disease?

Gökhan Yüce1, Aysel Türkvatan2, Özlem Yener1.   

Abstract

PURPOSE: To investigate whether aortic atherosclerosis or epicardial adipose tissue (EAT) volume on multidetector computed tomography (CT) can predict the presence of significant coronary artery disease (CAD).
MATERIALS AND METHODS: Coronary CT angiography was performed in 202 cases of CAD that were known or based on suspicion. Based on coronary CT angiography results, the patients with significant stenosis (≥50%) and without significant stenosis (<50%) were compared in terms of demographic characteristics, traditional cardiovascular risk factors, aortic atherosclerosis, and EAT volume.
RESULTS: Significant coronary artery stenosis was detected in 92 cases (45.5%). Although EAT volume was higher in the patients with significant stenosis, the difference between the two groups was not statistically significant. The presence of calcification in the descending aorta was significantly higher in the patients with significant stenosis than the patients without significant stenosis (50.4% and 15.4%, respectively, p=0.0001). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy rates of the presence of calcification in the descending aorta in predicting the presence of significant coronary artery stenosis were respectively found as 53.8%, 84.4%, 74.6%, 68.1%, and 70.3%. The sensitivity, specificity, PPV, NPV, and accuracy rates of the ≥2.45mm wall thickness of the descending aorta in predicting the presence of significant coronary artery stenosis were respectively found as 75.3%, 74.3%, 71.4%, 77.9%, and 74.8%.
CONCLUSION: There is a strong relationship between thoracic aortic atherosclerosis and CAD. However, the relationship between EAT volume and CAD is not significant. The presence of aortic atherosclerosis can be used as an additional marker together with traditional cardiovascular risk factors for predicting CAD.
Copyright © 2014 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Aorta; Atherosclerosis; Coronary artery disease; Epicardial adipose tissue; Multidetector computed tomography

Mesh:

Year:  2014        PMID: 24954286     DOI: 10.1016/j.jjcc.2014.03.017

Source DB:  PubMed          Journal:  J Cardiol        ISSN: 0914-5087            Impact factor:   3.159


  5 in total

1.  Diet-induced early-stage atherosclerosis in baboons: Lipoproteins, atherogenesis, and arterial compliance.

Authors:  Michael C Mahaney; Genesio M Karere; David L Rainwater; Venkata S Voruganti; Edward J Dick; Michael A Owston; Karen S Rice; Laura A Cox; Anthony G Comuzzie; John L VandeBerg
Journal:  J Med Primatol       Date:  2017-06-16       Impact factor: 0.667

2.  High levels of thyroid-stimulating hormone are associated with aortic wall thickness in the general population.

Authors:  Till Ittermann; Roberto Lorbeer; Marcus Dörr; Tobias Schneider; Alexander Quadrat; Lydia Heßelbarth; Michael Wenzel; Ina Lehmphul; Josef Köhrle; Birger Mensel; Henry Völzke
Journal:  Eur Radiol       Date:  2016-03-14       Impact factor: 5.315

3.  Epicardial Adipose Tissue Thickness Is an Independent Predictor of Critical and Complex Coronary Artery Disease by Gensini and Syntax Scores.

Authors:  Aycan Fahri Erkan; Asli Tanindi; Sinan Altan Kocaman; Murat Ugurlu; Hasan Fehmi Tore
Journal:  Tex Heart Inst J       Date:  2016-02-01

4.  RPS3A positively regulates the mitochondrial function of human periaortic adipose tissue and is associated with coronary artery diseases.

Authors:  Yan Tang; Yi He; Chen Li; Wenjuan Mu; Ying Zou; Conghui Liu; Shuwen Qian; Fuchuang Zhang; Jiabao Pan; Yina Wang; Haiyan Huang; Dongning Pan; Pengyuan Yang; Ju Mei; Rong Zeng; Qi-Qun Tang
Journal:  Cell Discov       Date:  2018-08-21       Impact factor: 10.849

5.  Is echocardiographic epicardial fat thickness increased in patients with coronary artery disease? A systematic review and meta-analysis.

Authors:  Mohammad Ali Ansari; Mohsen Mohebati; Farid Poursadegh; Mahdi Foroughian; Alireza Sepehri Shamloo
Journal:  Electron Physician       Date:  2018-09-09
  5 in total

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