Epicardial Fat Thickness and its Association with Cardiovascular Risk in Patients with Type 2 Diabetes Mellitus

被引:0
|
作者
Akyurek, Omer [1 ]
Efe, Duran [2 ]
Kaya, Zeynettin [3 ]
机构
[1] Mevlana Univ, Fac Med, Dept Internal Med, Konya, Turkey
[2] Mevlana Univ, Fac Med, Dept Radiol, Konya, Turkey
[3] Mevlana Univ, Fac Med, Dept Cardiol, Konya, Turkey
来源
EUROPEAN JOURNAL OF GENERAL MEDICINE | 2015年 / 12卷 / 02期
关键词
Type 2 diabetes mellitus; epicardial adipose tissue; cardiovascular risk;
D O I
暂无
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Previous studies have clearly shown that epicardial adipose tissue (EAT) mass is associated with increased incidence of coronary artery disease. In the present study, the relationship between the EAT volume measured by cardiac multislice computerized tomography (MSCT) and cardiovascular risk was investigated in patients with type 2 diabetes mellitus. Ninety type 2 diabetic patients and 62 healthy controls were included in the study. We examined metabolic and anthropometric parameters including body mass index (BMI), fasting glucose and serum lipids and EAT volume of patients in comparison to those of control subjects. EAT volume was higher in Type 2 diabetic patients compared to control group (172.75 +/- 64.85 cm3 and 68.94 +/- 37.74 cm3, respectively) (p<0.001). Type 2 diabetic patients had significantly higher levels of fasting glucose (p=0.014), total cholesterol (p<0.001), triglycerides (p=0,017) and LDL-cholesterol (p=0,022) versus control group. EAT volume was correlated with BMI, glucose, HbA1c, LDL-cholesterol, total cholesterol. In a stepwise regression analysis, Hba1c emerged as a significant predictor of EAT volume (beta=0.610, p square 0.001), accounting for 18% of its variability. These results provide additional evidence for the presence of subclinical cardiovascular disease (CVD) in type 2 diabetic patients. It is also important to note that our findings reveal significant relationships between HBA1c and cardiovascular changes and underline the importance of glucose control in predicting CVD.
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页码:131 / 135
页数:5
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