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Analyzing correlation between epicardial fat area and metabolic syndrome risk factor by using low-dose Lung CT

Authors
Jang, Hyon-CholLee, Hae-KagLee, HeonCha, Jang-GyuKim, Yoon-ShinCho, Jae-Hwan
Issue Date
Sep-2015
Publisher
Professional Medical Publications
Keywords
Blood Count; Epicardial Area; Metabolic Syndrome; Metabolic Risk Factors
Citation
Pakistan Journal of Medical Sciences, v.31, no.5, pp 1207 - 1212
Pages
6
Journal Title
Pakistan Journal of Medical Sciences
Volume
31
Number
5
Start Page
1207
End Page
1212
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/10315
DOI
10.12669/pjms.315.7991
ISSN
1682-024X
1681-715X
Abstract
Objectives: To study about the blood count of a risk factor related to physical measurement and metabolic syndrome, and the area of epicardial fat for medical checkup patients. Methods: From April 1st to November 15th in 2014, we measured the area of epicardial fat in the adult out patients under 60 years of age, who are in good health; and the patients took the blood test and low-dose lung CT. In order to identify the relationship between the area of epicardial fat and the risk factor of metabolic syndrome, we conducted correlation analysis. Then, we performed multiple regression analysis to evaluate an independent correlation of epicardial area. In addition, we computed the cut-off value of epicardial fat area by using ROC (Receiver Operating Characteristic) curve to foresee a metabolic syndrome factor that has the most proper sensitivity and specificity. Results: Waist circumference, fasting blood sugar, triglyceride, high-density lipoprotein (HDL) cholesterol, systolic blood pressure, and diastolic blood pressure were shown to be the factors that affect the area of epicardial fat. Therefore, if waist circumference, fasting blood sugar, triglyceride, systolic blood pressure, and diastolic blood pressure were increased, the area of epicardial fat would be significantly increased (P<0.05); and if high-density lipoprotein cholesterol was increased, the area of epicardial fat would be significantly decreased (P<0.05). Out of metabolic syndrome factors, waist circumference's ROC curve area was 0.79 (Confidence Interval 0.73-0.84, P<0.05), which was the highest. The sensitivity was 83.7% when specificity was 70.1%, which proves that they are important factors for the diagnosis. In brief, metabolic syndrome is a disease that mostly appears in obesity patients, so we should try to monitor and cure the disease. Conclusion: The risk factors of metabolic syndrome can be managed through health care, and if we try to decrease the risk factors, we will be able to shrink epicardial fat area and decrease metabolic syndrome at the same time.
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