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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