John T Braun1, Ephraim Akyuz. 1. Department of Orthopedics, University of Utah School of Medicine, Salt Lake City, UT 84132, USA. john.braun@hsc.utah.edu
Abstract
OBJECTIVES: Currently, prediction of progression in scoliosis is accomplished by analysis of several factors, which provide only a broad percentage chance, rather than an accurate risk assessment, of deformity progression. A model for prediction of scoliosis progression was investigated using an experimental scoliosis: A goat model was used to predict curve progression based on the percentage of vertebral body wedging in the region of maximal deformity. METHODS: Structural, lordoscoliotic curves of significant magnitude (> or = 30 degrees) convex to the right in the thoracic spine were created in 15 immature goats using a rigid posterior asymmetric tether in combination with convex rib resection and concave rib tethering. At 12 weeks, all posterior tethers were removed, and the goats were observed for an additional 4-week period. Serial radiographs were used to document progression (defined as > or = 5 degrees) and vertebral body wedging within the maximal scoliotic deformity. RESULTS: During the additional 4-week observation period following removal of the tether, seven goats developed progressive curves (mean progression: +10.1 degrees, range: +6 degrees to +17 degrees) and eight goats developed nonprogressive curves (mean: -1.6 degrees, range: -8 degrees to +4 degrees). At the beginning of the observation period, the percentage of vertebral body wedging was 60.4% versus 50.2% in the progressive versus nonprogressive groups (P = 0.002). Thus, at 55.3% vertebral body wedging, prediction of curve progression was possible for 85% of progressors and 88% of nonprogressors. CONCLUSIONS: Prediction of curve progression is often difficult when based on skeletal maturity and curve magnitude alone. In an immature goat scoliosis model, however, in which these two factors are relatively well controlled, curve progression can be predicted based on the percentage of vertebral body wedging in the region of maximal deformity.
OBJECTIVES: Currently, prediction of progression in scoliosis is accomplished by analysis of several factors, which provide only a broad percentage chance, rather than an accurate risk assessment, of deformity progression. A model for prediction of scoliosis progression was investigated using an experimental scoliosis: A goat model was used to predict curve progression based on the percentage of vertebral body wedging in the region of maximal deformity. METHODS: Structural, lordoscoliotic curves of significant magnitude (> or = 30 degrees) convex to the right in the thoracic spine were created in 15 immature goats using a rigid posterior asymmetric tether in combination with convex rib resection and concave rib tethering. At 12 weeks, all posterior tethers were removed, and the goats were observed for an additional 4-week period. Serial radiographs were used to document progression (defined as > or = 5 degrees) and vertebral body wedging within the maximal scoliotic deformity. RESULTS: During the additional 4-week observation period following removal of the tether, seven goats developed progressive curves (mean progression: +10.1 degrees, range: +6 degrees to +17 degrees) and eight goats developed nonprogressive curves (mean: -1.6 degrees, range: -8 degrees to +4 degrees). At the beginning of the observation period, the percentage of vertebral body wedging was 60.4% versus 50.2% in the progressive versus nonprogressive groups (P = 0.002). Thus, at 55.3% vertebral body wedging, prediction of curve progression was possible for 85% of progressors and 88% of nonprogressors. CONCLUSIONS: Prediction of curve progression is often difficult when based on skeletal maturity and curve magnitude alone. In an immature goat scoliosis model, however, in which these two factors are relatively well controlled, curve progression can be predicted based on the percentage of vertebral body wedging in the region of maximal deformity.
Authors: Patricia M Kallemeier; Glenn R Buttermann; Brian P Beaubien; Xinqian Chen; David J Polga; William D Lew; Kirkham B Wood Journal: Eur Spine J Date: 2005-11-04 Impact factor: 3.134
Authors: Andriy Noshchenko; Lilian Hoffecker; Emily M Lindley; Evalina L Burger; Christopher Mj Cain; Vikas V Patel; Andrew P Bradford Journal: World J Orthop Date: 2015-08-18