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Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
Baumgartner, D; Baumgartner, C; Mátyás, G; Steinmann, B; Löffler-Ragg, J; Schermer, E; Schweigmann, U; Baldissera, I; Frischhut, B; Hess, J; Hammerer, I.
Diagnostic power of aortic elastic properties in young patients with Marfan syndrome.
J Thorac Cardiovasc Surg. 2005; 129(4): 730-739.
Doi: 10.1016/j.jtcvs.2004.07.019
Web of Science
PubMed
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- Leading authors Med Uni Graz
- Baumgartner Daniela
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- Abstract:
- In patients with Marfan syndrome, progressive aortic dilation implicates a still-unpredictable risk of life-threatening aortic dissection and rupture. We sought to quantify aortic wall dysfunction noninvasively, determine the diagnostic power of various aortic parameters, and establish a diagnostic model for the early detection of aortic abnormalities associated with Marfan syndrome. In 19 patients with Marfan syndrome (age, 17.7 +/- 9.5 years) and 19 age- and sex-matched healthy control subjects, computerized ascending and abdominal aortic wall contour analysis with continuous determination of aortic diameters was performed out of transthoracic M-mode echocardiographic tracings. After simultaneous oscillometric blood pressure measurement, aortic elastic properties were determined automatically. The following ascending aortic elastic parameters showed statistically significant differences between the Marfan group and the control group: (1) decreased aortic distensibility ( P < .001), (2) increased wall stiffness index ( P < .01), (3) decreased systolic diameter increase ( P < .01), and (4) decreased maximum systolic area increase ( P < .001). The diagnostic power of all investigated parameters was tested by single logistic regression models. A multiple logistic regression model including solely aortic parameters yielded a sensitivity of 95% and a specificity of 100%. In young patients with Marfan syndrome, a computerized image-analyzing technique revealed decreased aortic elastic properties expressed by parameters showing high diagnostic power. A multiple logistic regression model including merely aortic parameters can serve as useful predictor for Marfan syndrome.
- Find related publications in this database (using NLM MeSH Indexing)
- Adolescent -
- Adult -
- Aorta - diagnostic imaging
- Aorta - physiopathology
- Aorta, Abdominal - diagnostic imaging
- Aorta, Abdominal - physiopathology
- Aortic Diseases - diagnosis
- Blood Pressure - physiology
- Case-Control Studies -
- Child -
- Child, Preschool -
- Diastole -
- Echocardiography -
- Elasticity -
- Female -
- Humans -
- Image Processing, Computer-Assisted -
- Male -
- Marfan Syndrome - diagnostic imaging
- Marfan Syndrome - genetics
- Marfan Syndrome - physiopathology
- Mutation - genetics
- Predictive Value of Tests -
- Systole -
- Vectorcardiography -