Related Experiment Video
Updated: Jun 5, 2026
Evaluation of Patients' Posture and Gait Profile After Lumbar Fusion Surgery by Video Rasterstereography and Treadmill Gait Analysis
Published on: March 23, 2019
Spino-pelvic parameters after surgery can be predicted: a preliminary formula and validation of standing alignment
Virginie Lafage1, Frank Schwab, Shaleen Vira
1NYU Hospital for Joint Diseases, New York, NY 10010, USA. virginie.lafage@gmail.com
Study Design:
Prospective and retrospective radiographic study of adult patients with spinal deformities.
Objective:
Construct predictive models for pelvic tilt (PT) and global sagittal balance (sagittal vertical axis [SVA]) and evaluate the effectiveness of these predictive models against a group of patients after pedicle subtraction osteotomy.
Summary Of Background Data:
Spinal balance involves a complex interaction between the pelvis and vertebral column. In the setting of adult spinal deformity, prediction of postoperative alignment can be challenging.
Methods:
The study included 219 adult patients treated for spinal deformity. Full-length standing films were available for all subjects. Multilinear models with a stepwise condition were used on the first group of patients (n = 179) to predict PT and global sagittal balance (measured by the SVA). Prediction models were then applied on a second group of patients (n = 40) to estimate postoperative radiographic parameters after pedicle subtraction osteotomy surgery. Differences between estimated parameters and real values were evaluated.
Results:
Multilinear regression analysis applied on the first group of patients led to a predictive formula for PT (r = 0.93, standard error = 4.4°) using the following parameters: pelvic incidence, maximal lordosis, and maximal kyphosis. These parameters with the addition of the predicted PT were then used to predict the SVA (r = 0.89, standard error = 32 mm). Validation of predictive models (second group of patients) used pelvic incidence and postoperative sagittal curves. Postoperative PT was predicted with a mean error of 4.3° (SD 3.5°) and postoperative SVA was predicted with a mean error of 29 mm (SD = 23 mm).
Conclusion:
This is the first study to develop and validate pragmatic predictive models for key spino-pelvic parameters (PT and SVA) in the setting of adult spinal deformity. Using a morphologic pelvic parameter (pelvic incidence) and spinal parameters modifiable through surgery (lumbar lordosis and thoracic kyphosis), postoperative sagittal alignment can be predicted.
