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
To identify the incidence and risk factors for five-year same-site recurrent disc herniation (sRDH) after primary single-level lumbar discectomy. Secondary outcome was the incidence and risk factors for five-year sRDH reoperation. A retrospective study was conducted using prospectively collected data and patient-reported outcome measures, including the Oswestry Disability Index (ODI), between 2008 and 2019. Postoperative sRDH was identified from clinical notes and the centre’s MRI database, with all imaging providers in the region checked for missing events. The Kaplan-Meier method was used to calculate five-year sRDH incidence. Cox proportional hazards model was used to identify independent variables predictive of sRDH, with any variable not significant at the p < 0.1 level removed. Hazard ratios (HRs) were calculated with 95% confidence intervals (CIs).Aims
Methods
We compared decompression alone to decompression with fusion surgery for lumbar spinal stenosis, with or without degenerative spondylolisthesis (DS). The aim was to evaluate if five-year outcomes differed between the groups. The two-year results from the same trial revealed no differences. The Swedish Spinal Stenosis Study was a multicentre randomized controlled trial with recruitment from September 2006 to February 2012. A total of 247 patients with one- or two-level central lumbar spinal stenosis, stratified by the presence of DS, were randomized to decompression alone or decompression with fusion. The five-year Oswestry Disability Index (ODI) was the primary outcome. Secondary outcomes were the EuroQol five-dimension questionnaire (EQ-5D), visual analogue scales for back and leg pain, and patient-reported satisfaction, decreased pain, and increased walking distance. The reoperation rate was recorded.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
The purpose of this study was to devise a simple
but reliable radiological method of identifying a lumbosacral transitional
vertebra (LSTV) with a solid bony bridge on sagittal MRI, which
could then be applied to a lateral radiograph. The vertical mid-vertebral angle (VMVA) and the vertical anterior
vertebral angle (VAVA) of the three most caudal segments of the
lumbar spine were measured on MRI and/or on a lateral radiograph
in 92 patients with a LSTV and 94 controls, and the differences
per segment (Diff-VMVA and Diff-VAVA) were calculated. The Diff-VMVA
of the two most caudal vertebrae was significantly higher in the
control group (25° ( Using this simple method (Diff-VMVA ≤ +10°), solid bony bridging
of the posterior elements of a LSTV, and therefore the first adjacent
mobile segment, can be easily identified without the need for additional
imaging. Cite this article:
