Increased septum wall thickness in patients undergoing aortic valve replacement predicts worse late survival

Ann Thorac Surg. 2012 Jul;94(1):66-71. doi: 10.1016/j.athoracsur.2012.03.027. Epub 2012 May 16.


Background: Following guidelines, aortic valve replacement (AVR) in asymptomatic patients with severe aortic valve stenosis is often postponed until symptoms do occur. Delaying AVR will inevitably lead to progression of left ventricular hypertrophy. We studied the relationship between septum wall thickness indexed for body surface area (SWTI) as a measure for LV hypertrophy and 30-day and late all-cause mortality after AVR.

Methods: This study included the data of adult patients who underwent isolated AVR between January 2006 and December 2010 and in whom a reliable measurement of the septum wall thickness could be made. The patients were stratified into three groups according to their SWTI. The SWTI was less than 6 mm/m(2) in 136 patients, between 6 and 8 mm/m(2) in 307 patients, and more than 8 mm/m(2) in 126 patients.

Results: Death occurred in 10 patients within 30 days (1.8%), and 41 patients died during follow-up (7.2%). Univariate logistic regression analysis revealed only endocarditis as predictor of early mortality. Multivariate Cox regression analyses revealed SWTI as a continuous variable as well as a categorical (group) variable to be a predictor of late mortality. Compared with the group SWTI less than 6 mm/m(2), odds ratio for the group with SWTI 6 to 8 mm/m(2) was 3.4 (p = 0.046), and for the group with SWTI more than 8 mm/m(2), it was 6.0 (p = 0.005).

Conclusions: In patients undergoing AVR, the SWTI was a strong predictor of late mortality. Whether avoidance of progression of left ventricular hypertrophy by early AVR leads to better outcome remains to be investigated.

MeSH terms

  • Adult
  • Aged
  • Aortic Valve / surgery*
  • Body Surface Area
  • Female
  • Heart Septum / pathology*
  • Heart Valve Prosthesis Implantation* / mortality
  • Humans
  • Hypertrophy, Left Ventricular / prevention & control
  • Logistic Models
  • Male
  • Middle Aged
  • Proportional Hazards Models