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J Thorac Cardiovasc Surg 2005;129:730-739
© 2005 The American Association for Thoracic Surgery
Surgery for Congenital Heart Disease |
a Department of Pediatric Cardiology, Innsbruck Medical University, Innsbruck, Austria
b Research Group for Biomedical Data Mining, Institute for Information Systems, University for Health Sciences, Medical Informatics and Technology, Innsbruck, Austria
c Division of Metabolism and Molecular Pediatrics, University Childrens Hospital, Zurich, Switzerland
d Institute of Medical Genetics, University of Zurich, Schwerzenbach, Switzerland
e Institute of Medical Biology and Human Genetics, Innsbruck Medical University, Innsbruck, Austria
f Department of Ophthalmology, Innsbruck Medical University, Innsbruck, Austria
g Department of Orthopedics, Innsbruck Medical University, Innsbruck, Austria
h Department of Pediatric Cardiology and Congenital Heart Disease, German Heart Center, Munich, Germany
Received for publication March 4, 2004; revisions received June 21, 2004; accepted for publication July 8, 2004. * Address for reprints: Daniela Baumgartner, MD, Department of Pediatric Cardiology, Innsbruck Medical University, Anichstr 35, A-6020 Innsbruck, Austria (E-mail: Daniela.Baumgartner{at}aon.at).
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.
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