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

Abstract

Sarraj Mohamed Youssef, Najah Mohamed, Slimani Afef, Ben Hamda Khaldoun, Neffati Fadoua, Najjar Mohamed Fadhel and Slimane Mohamed Naceur

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.

மறுப்பு: இந்த சுருக்கமானது செயற்கை நுண்ணறிவு கருவிகளைப் பயன்படுத்தி மொழிபெயர்க்கப்பட்டது மற்றும் இன்னும் மதிப்பாய்வு செய்யப்படவில்லை அல்லது சரிபார்க்கப்படவில்லை

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