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A longitudinal study of the prole and predictors of left ventricular mass regression after stentless aortic valve replacement.

Research output: Contribution to journalJournal articlepeer-review

Published
  • Eric Lim
  • Ayyaz Ali
  • Panagiotis Theodorou
  • Ines Pereira Silva Cunha Sousa
  • Hutan Ashrafian
  • Chamageorgakis Chamageorgakis
  • Alison Duncan
  • Michael Henein
  • Peter Diggle
  • John Pepper
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<mark>Journal publication date</mark>06/2008
<mark>Journal</mark>Annals of Thoracic Surgery
Issue number6
Volume85
Number of pages4
Pages (from-to)2026-2029
Publication StatusPublished
<mark>Original language</mark>English

Abstract

Background
The aim of this study was to evaluate the long-term profile and determine the factors that would influence the effect and rate of ventricular mass regression with time after aortic valve replacement with a stentless or a homograft valve.

Methods
We studied 300 patients during a 10-year period with at least a year of follow-up with a total of 1,273 serial echocardiographic measurements. Left ventricular mass was calculated from M-mode recordings and indexed to body surface area. Longitudinal data analysis was performed using a linear mixed effects model.

Results
The mean age (± standard deviation) was 65 (±14) years, consisting of 216 (72%) males. A stentless valve was implanted in 156 (52%), and a homograft in 144 (48%). The median time (interquartile range) to follow-up was 4.7 (2.8 to 6.6) years. The greatest rate of left ventricular mass regression occurred in the first year after surgery. On multivariable modeling, independent predictors of left ventricular mass were valve size (p = 0.011), left ventricular function (moderate impairment, p = 0.418; severe impairment, p = 0.011), and baseline left ventricular mass (middle tercile, p < 0.001; highest tercile, p < 0.001). Only baseline ventricular mass influenced the rate of subsequent left ventricular mass regression; the greatest rate of regression occurred in patients with the highest baseline values of ventricular mass (p < 0.001).

Conclusions
The greatest rate of left ventricular mass regression occurs in the first year with baseline left ventricular mass as the strongest predictor and the only identified variable that influenced the rate of left ventricular mass regression.