We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Predominance of Abdominal Visceral Adipose Tissue Reflects the Presence of Aortic Valve Calcification.
- Authors
Oikawa, Masayoshi; Owada, Takashi; Yamauchi, Hiroyuki; Misaka, Tomofumi; Machii, Hirofumi; Yamaki, Takayoshi; Sugimoto, Koichi; Kunii, Hiroyuki; Nakazato, Kazuhiko; Suzuki, Hitoshi; Saitoh, Shu-ichi; Takeishi, Yasuchika
- Abstract
Background. Aortic valve calcification (AVC) is a common feature of aging and is related to coronary artery disease. Although abdominal visceral adipose tissue (VAT) plays fundamental roles in coronary artery disease, the relationship between abdominal VAT and AVC is not fully understood. Methods. We investigated 259 patients who underwent cardiac and abdominal computed tomography (CT). AVC was defined as calcified lesion on the aortic valve by CT. %abdominal VAT was calculated as abdominal VAT area/total adipose tissue area. Results. AVC was detected in 75 patients, and these patients showed higher %abdominal VAT (44% versus 38%, p<0.05) compared to those without AVC. When the cutoff value of %abdominal VAT was set at 40.9%, the area under the curve to diagnose AVC was 0.626. Multivariable logistic regression analysis showed that age (OR 1.120, 95% CI 1.078–1.168, p<0.01), diabetes (OR 2.587, 95% CI 1.323–5.130, p<0.01), and %abdominal VAT (OR 1.032, 95% CI 1.003–1.065, p<0.05) were independent risk factors for AVC. The net reclassification improvement value for detecting AVC was increased when %abdominal VAT was added to the model: 0.5093 (95% CI 0.2489–0.7697, p<0.01). Conclusion. We determined that predominance of VAT is associated with AVC.
- Subjects
ABDOMINAL adipose tissue; CALCIFICATION; AORTIC valve diseases; CORONARY disease; ABDOMINAL radiography; COMPUTED tomography; LOGISTIC regression analysis; CORONARY heart disease risk factors; ADIPOSE tissues; AGING; HUMAN body composition; CHOLESTEROL; HIGH density lipoproteins; HYPERLIPIDEMIA; LOW density lipoproteins; MULTIVARIATE analysis; SMOKING; BODY mass index; PATIENT selection; DATA analysis software; CALCINOSIS; DIAGNOSIS
- Publication
BioMed Research International, 2016, Vol 2016, p1
- ISSN
2314-6133
- Publication type
Article
- DOI
10.1155/2016/2174657