Prof. Dr. Matthias Schmid
Institute of medical Biometry, Computer Science and Epidemiology
sekretariat@imbie.uni-bonn.de View member: Prof. Dr. Matthias Schmid
Clinical kidney journal
BACKGROUND: Epicardial adipose tissue (EAT) exerts cardiopathogenic effects, but the independent association between EAT and cardiovascular (CV) calcification in patients with chronic kidney disease (CKD) remains controversial. We therefore assessed the association between EAT, CV risk factors and CV calcifications.
METHODS: 257 patients with CKD Stage 3 and/or overt proteinuria underwent quantification of EAT, coronary artery calcification and aortic valve calcification by computed tomography. Framingham and American College of Cardiology and American Heart Association (ACC-AHA) 10-year CV event risk scores were calculated for each patient.
RESULTS: Using multivariable regression analysis, higher EAT was significantly associated with the majority of investigated risk factors {higher age: odds ratio [OR] 1.05/year [95% confidence interval (CI) 1.02-1.08]; male sex: OR 4.03 [95% CI 2.22-7.31]; higher BMI: OR 1.28/kg/m [95% CI 1.20-1.37]; former smoking: OR 1.84 [95% CI 1.07-3.17]; lower high-density lipoprotein cholesterol: OR 0.98/mg/dL [95% CI 0.96-1.00] and lower estimated glomerular filtration rate: OR 0.98/mL/min/1.73 m [95% CI 0.97-0.99]; all P < 0.05} and was not associated with diabetes mellitus, hypertensive nephropathy, total cholesterol and albuminuria. EAT was positively associated with higher ACC-AHA and Framingham risk scores. EAT correlated with coronary artery calcification and aortic valve calcification [Spearman ρ = 0.388 (95% CI 0.287-0.532) and = 0.409 (95% CI 0.310-0.556), respectively], but these correlations were dependent on CV risk factors.
CONCLUSIONS: The increase of EAT can be explained by individual CV risk factors and kidney function and correlates with 10-year risk for CV event scores, suggesting that EAT is a modifiable risk factor in patients with CKD. Although EAT correlates with CV calcifications, these relations depend on CV risk factors.
© The Author(s) 2019. Published by Oxford University Press on behalf of ERA-EDTA.
PMID: 32905245
Institute of medical Biometry, Computer Science and Epidemiology
sekretariat@imbie.uni-bonn.de View member: Prof. Dr. Matthias Schmid