Diagnostic power of aortic elastic properties in young patients with Marfan syndrome.

Baumgartner, D; Baumgartner, C; Mátyás, G; Steinmann, B; Löffler-Ragg, J; Schermer, E; Schweigmann, U; Baldissera, I; Frischhut, B; Hess, J; Hammerer, I

doi:10.1016/j.jtcvs.2004.07.019

journal article

Dokumenttyp:: Journal Article
Autor(en):: Baumgartner, D; Baumgartner, C; Mátyás, G; Steinmann, B; Löffler-Ragg, J; Schermer, E; Schweigmann, U; Baldissera, I; Frischhut, B; Hess, J; Hammerer, I
Titel:: Diagnostic power of aortic elastic properties in young patients with Marfan syndrome.
Abstract:: BACKGROUND: 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. METHODS: 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. RESULTS: 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%. CONCLUSIONS: 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.
Zeitschriftentitel:: J Thorac Cardiovasc Surg
Jahr:: 2005
Band / Volume:: 129
Heft / Issue:: 4
Seitenangaben Beitrag:: 730-9
Sprache:: eng
Volltext / DOI:: doi:10.1016/j.jtcvs.2004.07.019
PubMed:: http://view.ncbi.nlm.nih.gov/pubmed/15821637
Print-ISSN:: 0022-5223
TUM Einrichtung:: Klinik für Kinderkardiologie und angeborene Herzfehler (Prof. Hess)
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mediaTUM Gesamtbestand Einrichtungen Schools TUM School of Medicine and Health Departments Clinical Medicine Lehr- und Forschungskooperationen mit den Kliniken und Instituten am Deutschen Herzzentrum Klinik für Kinderkardiologie und angeborene Herzfehler (DHM) (Prof. Ewert)2005