W12-P-006 The impact of abnormalities of fatty acid metabolism in nonagenarians with coronary artery disease

2005 ◽  
Vol 6 (1) ◽  
pp. 62-63
Author(s):  
V. Bláha ◽  
D. Solichová ◽  
D. Cenohorský ◽  
R. Hyšpler ◽  
P. Vyroubal ◽  
...  
2015 ◽  
Vol 197 ◽  
pp. 192-199 ◽  
Author(s):  
Panagiotis A. Vorkas ◽  
Giorgis Isaac ◽  
Anders Holmgren ◽  
Elizabeth J. Want ◽  
John P. Shockcor ◽  
...  

1987 ◽  
Vol 26 (04) ◽  
pp. 172-176 ◽  
Author(s):  
H. Schicha ◽  
U. Tebbei ◽  
P. Neumann ◽  
D. Emrich ◽  
E. Voth

Using 123l-ω-heptadecanoic acid (HDA) and 201TI, respectively, myocardial fatty acid metabolism and perfusion were studied in 51 symptomatic patients with mitral valve prolapse (MVP) as diagnosed by ventriculography, and no evidence of coronary artery disease. Twelve subjects with normal coronary arteries and normal ventriculogram served as a control group for the evaluation of elimination kinetics of HDA. In the control group, the mean elimination halflife was 26.1 ± 3.6 min, whereas the patients with MVP had a mean value of ± 6.4 min. In patients with MVP, a high incidence concerning abnormalities of accumulation and/or elimination of HDA occurred, namely accumulation defects in 31 % and both prolonged and shortened elimination half-lives in 16% and 29%, respectively. Myocardial perfusion scintigraphy using 201TI showed abnormalities in 76%. Correlations were found between decreased uptake of HDA and prolonged elimination half-life as well as defects by 201TI, presumably due to ischemia based on small-vessel disease or abnormalities of cellular metabolism.


2013 ◽  
Vol 11 (5) ◽  
pp. 779-784 ◽  
Author(s):  
Vasilios G. Athyros ◽  
Konstantinos Tziomalos ◽  
Niki Katsiki ◽  
Thomas D. Gossios ◽  
Olga Giouleme ◽  
...  

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
F Andre ◽  
S Seitz ◽  
P Fortner ◽  
R Sokiranski ◽  
F Gueckel ◽  
...  

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Siemens Healthineers Introduction Coronary CT angiography (CCTA) plays an increasing role in the detection and risk stratification of patients with coronary artery disease (CAD). The Coronary Artery Disease – Reporting and Data System (CAD-RADS) allows for standardized classification of CCTA results and, thus, may improve patient management. Purpose Aim of this study was to assess the impact of CCTA in combination with CAD-RADS on patient management and to identify the impact of cardiovascular risk factors (CVRF) on CAD severity. Methods CCTA was performed on a third-generation dual-source CT scanner in patients, who were referred to a radiology centre by their attending physicians. In a total of 4801 patients, CVRF were derived from medical reports and anamnesis. Results The study population consisted of 4770 patients (62.0 (54.0-69.0) years, 2841 males) with CAD (CAD-RADS 1-5), while 31 patients showed no CAD and were excluded from further analyses. Age, male gender and the number of CVRF were associated with more severe CAD stages (all p < 0.001). 3040 patients (63.7 %) showed minimal or mild CAD requiring optimization of CVRF i.e. medical therapy but no further assessment at his time. A group of 266 patients (5.6 %) had a severe CAD defined as CAD-RADS 4B/5. In the multivariate regression analysis, age, male gender, history of smoking, diabetes mellitus and hyperlipidaemia were significant predictors for severe CAD, whereas arterial hypertension and family history of CAD did not reach significance. Of note, a subgroup of 28 patients (10.5 %) with a severe CAD (68.5 (65.5-70.0) years, 26 males, both p = n.s.) had no CVRF. Conclusions CCTA in combination with the CAD-RADS allowed for effective risk stratification of CAD patients. The majority of the patients showed non-obstructive CAD and, thus, could be treated conservatively without the need for further CAD assessment. CVRF out of arterial hypertension and family history had an impact on CAD severity reflected in higher CAD-RADs gradings. Of note, a relevant fraction of patients with CAD did not have any CVRF and, thus, may not be covered by risk stratification models. CAD-RADS n Age (years) Males (%) 1 1453 56.0 (50.0-62.0) 623 (42.9 %) 2 1587 62.0 (55.0-69.0) 918 (57.8 %) 3 1067 66.0 (59.0-71.0) 749 (70.2 %) 4A 397 66.0 (59.0-72.0) 317 (79.8 %) 4B 162 67.0 (61.0-74.0) 139 (85.8 %) 5 104 66.0 (58.5.0-77.0) 95 (91.3 %)


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