These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: [Cut-off point of epicardial adipose tissue thickness for predicting metabolic syndrome in Venezuelan population].
    Author: Lima-Martínez MM, Paoli M, Donis JH, Odreman R, Torres C, Iacobellis G.
    Journal: Endocrinol Nutr; 2013 Dec; 60(10):570-6. PubMed ID: 23791773.
    Abstract:
    OBJECTIVE: To define an echocardiographically-assessed cut-off point for epicardial adipose tissue (EAT) thickness associated to metabolic syndrome (MS) components in Venezuelan subjects. METHODS: Fifty-two subjects aged 20-65 years diagnosed with MS according to International Diabetes Federation criteria and 45 sex- and age-matched controls were selected. Blood glucose and plasma lipids were tested; EAT thickness and left ventricular mass were measured by echocardiography. RESULTS: No significant age and sex differences were found between the two groups. Body weight, body mass index, waist circumference, and systolic and diastolic blood pressure were significantly higher (P=.0001) in the MS group. This group showed significantly higher levels of fasting blood glucose (P=.0001), total cholesterol (P=.002), LDL-C (P=.007), non-HDL-C (P=.0001), triglycerides (P=.0001), Tg-HDL-C ratio (P=.0001), and lower HDL-C levels (P=.0001) as compared to the control group. EAT thickness (P=.0001) and left ventricular mass (P=.017) were significantly higher in the MS group. The ROC curve showed an AUC of 0.852 (P=.0001) with a power of the test of 0.99. A 5-mm EAT thickness showed a sensitivity of 84.62% (95%CI: 71.9-93.1) and a specificity of 71.11% (95%CI: 55.7-83.6) for predicting MS. The odds ratio of this population for experiencing MS due to an EAT ≥ 5 mm was 8.25 (95%CI: 3.15-21.56; P=.0001). CONCLUSION: An EAT value ≥ 5 mm has good sensitivity and specificity for predicting MS in the Venezuelan population.
    [Abstract] [Full Text] [Related] [New Search]