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.
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.
Authors: Leonid Emerel; James Thunes; Trevor Kickliter; Marie Billaud; Julie A Phillippi; David A Vorp; Spandan Maiti; Thomas G Gleason Journal: J Thorac Cardiovasc Surg Date: 2018-11-03 Impact factor: 5.209
Authors: Elif Seda Selamet Tierney; Jami C Levine; Shan Chen; Timothy J Bradley; Gail D Pearson; Steven D Colan; Lynn A Sleeper; M Jay Campbell; Meryl S Cohen; Julie De Backer; Lin T Guey; Haleh Heydarian; Wyman W Lai; Mark B Lewin; Edward Marcus; Christopher R Mart; Ricardo H Pignatelli; Beth F Printz; Angela M Sharkey; Girish S Shirali; Shubhika Srivastava; Ronald V Lacro Journal: J Am Soc Echocardiogr Date: 2013-04-10 Impact factor: 5.251
Authors: Andreas Kühn; Daniela Baumgartner; Christian Baumgartner; Jürgen Hörer; Christian Schreiber; John Hess; Manfred Vogt Journal: Pediatr Cardiol Date: 2008-08-07 Impact factor: 1.655
Authors: Elif Seda Selamet Tierney; Jami C Levine; Lynn A Sleeper; Mary J Roman; Timothy J Bradley; Steven D Colan; Shan Chen; M Jay Campbell; Meryl S Cohen; Julie De Backer; Haleh Heydarian; Arvind Hoskoppal; Wyman W Lai; Aimee Liou; Edward Marcus; Arni Nutting; Aaron K Olson; David A Parra; Gail D Pearson; Mary Ella Pierpont; Beth F Printz; Reed E Pyeritz; William Ravekes; Angela M Sharkey; Shubhika Srivastava; Luciana Young; Ronald V Lacro Journal: Am J Cardiol Date: 2018-02-13 Impact factor: 2.778
Authors: Philip J Kilner; Tal Geva; Harald Kaemmerer; Pedro T Trindade; Juerg Schwitter; Gary D Webb Journal: Eur Heart J Date: 2010-01-11 Impact factor: 29.983