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Can Metric Parameter Combining Metabolic Syndrome Components Usefully Predict Coronary Artery Disease? | OMICS International | Abstract
ISSN: 2167-0943

Journal of Metabolic Syndrome
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Research Article

Can Metric Parameter Combining Metabolic Syndrome Components Usefully Predict Coronary Artery Disease?

Sarraj Mohamed Youssef1*, Najah Mohamed1, Slimani Afef1, Ben Hamda Khaldoun3, Neffati Fadoua2, Najjar Mohamed Fadhel2 and Slimane Mohamed Naceur1
1Research Unit genetic and biological factors of atherosclerosis, Medicine Faculty, University of Monastir, Tunisia
2Laboratory of Biochemistry and Toxicology of the University Hospital of Monastir, Tunisia
3Department of Cardiology of the University Hospital of Monastir, Tunisia
Corresponding Author : Mohamed Youssef Sarraj
Research Unit 05/UR/09-12: Genetic
and Biological Factors of Atherosclerosis
Medicine Faculty, University of Monastir, Tunisia
Tel: 216-73-462-200
Fax: 216-73-460-737
E-mail: [email protected]
Received April 01, 2013; Accepted April 22, 2013; Published April 27, 2013
Citation: Youssef SM, Mohamed N, Afef S, Khaldoun BH, Fadoua N, et al. (2013) Can Metric Parameter Combining Metabolic Syndrome Components Usefully Predict Coronary Artery Disease? J Metabolic Synd 2:119. doi:10.4172/2167- 0943.1000119
Copyright: © 2013 Youssef SM, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Aims: We have investigated to what extent Metabolic Syndrome (MS) is related to Coronary Artery Disease (CAD) incidence and we tried to determine a metric parameter combining MS quantitative components to be used as a screening tool to diagnose CAD.

Materials and methods: 239 patients and 244 control subjects were investigated for clinical, biochemical, anthropometric and angiographic information. CAD is defined as 50% stenosis on the left main coronary artery or multiple significant (≥ 70% stenosis) in more than one coronary artery. The diagnosis of MS was based on the IDF and AHA/NHLBI definition. The computer model HOMA 2 was used to determine HOMA-β, HOMA-S and HOMA-IR. Triglycerides (TG), High Density Lipoprotein cholesterol (cHDL), Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP), HOMA-IR and Waist Circumference (WC) were used to calculate the different MS markers. The area under curve of ROC curves were used to compare the powers of these MS markers.

Results: MS was significantly related to the CAD. Each MS quantitative component was a significant discriminating factor for CAD. FPG followed by SBP were the principal predictive factors of CAD. A metric parameter combing MS qualitative components [(TG/cHDL) × (HOMA-IR × WC)] + SBP was more accurate to estimate CAD risk. Its cut-off point was 247.1

Conclusion: MS was associated with CAD. This marker, with sensitivity and specificity of 86.2 and 73.0 per cent can be used either to diagnose or to predict CAD incidence.

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