Association of epicardial fat thickness assessed by echocardiography with the severity of coronary artery disease

Rostamzadeh, Alireza and Khademvatani, Kamal and Seyed Mohammadzadeh, Mir Hossein and Ashori, Shahrzad and Hajahmadi Poorrafsanjani, Mojgan and Rahimi, Behzad and Ghadrdoost, Behshid (2020) Association of epicardial fat thickness assessed by echocardiography with the severity of coronary artery disease. Journal of Cardiovascular and Thoracic Research, 12 (2). pp. 114-119. ISSN 2008-5117

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Abstract

Introduction: Epicardial fat thickness (EFT) can reflect risk of cardiovascular disease particularly coronary artery disease (CAD). The aim of this study was to investigate the association of EFT assessed by echocardiography and presence as well as severity of CAD.

Methods: Two hundred and twenty consecutive patients who candidate for coronary angiography because of possible CAD were studied. EFT was evaluated in standard parasternal long axis (PlAX) and parasternal short axis (PSAX) view from 3 cardiac cycles at the end of systole and diastole. The severity of CAD was defined in two ways: (1) SYNTAX score, (2) number of vessels with significant lesion.

Results: PLAX (EFTS ) (EFT in systole) and PLAX (EFTd ) (EFT in diastole) were significantly higher in patients with CAD in comparison with patients without CAD (P = 0.046, P = 0.041 respectively). There was a significant correlation between PLAX (EFTS ) (P = 0.05), PLAX (EFTd ) (P = 0.04) and SYNTAX score. There was no statistically significant relationship between EFT and number of diseased vessel (P > 0.05). Multivariate analysis was done for adjusting the effects of confounding factors and it showed that EFT (OR: 10.53, P = 0.004) was significantly correlated severe CAD as assessed by the SYNTAX score.

Conclusion: EFT assessed by transthoracic echocardiography was higher significantly in patients with CAD than in normal patients. EFT as an easily available and cost-effective echocardiographic feature might be useful to predict complexity of CAD.

Item Type: Article
Subjects: GO for STM > Medical Science
Depositing User: Unnamed user with email support@goforstm.com
Date Deposited: 04 May 2023 06:30
Last Modified: 21 Nov 2023 05:04
URI: http://archive.article4submit.com/id/eprint/734

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