To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology.Aims
Methods
Pedicle-lengthening osteotomy is a novel surgery for lumbar spinal stenosis (LSS), which achieves substantial enlargement of the spinal canal by expansion of the bilateral pedicle osteotomy sites. Few studies have evaluated the impact of this new surgery on spinal canal volume (SCV) and neural foramen dimension (NFD) in three different types of LSS patients. CT scans were performed on 36 LSS patients (12 central canal stenosis (CCS), 12 lateral recess stenosis (LRS), and 12 foraminal stenosis (FS)) at L4-L5, and on 12 normal (control) subjects. Mimics 14.01 workstation was used to reconstruct 3D models of the L4-L5 vertebrae and discs. SCV and NFD were measured after 1 mm, 2 mm, 3 mm, 4 mm, or 5 mm pedicle-lengthening osteotomies at L4 and/or L5. One-way analysis of variance was used to examine between-group differences.Objectives
Methods
