Aims. This study aimed to evaluate
Symptomatic spinal stenosis is a very common problem, and decompression surgery has been shown to be superior to nonoperative treatment in selected patient groups. However, performing an instrumented fusion in addition to decompression may avoid revision and improve outcomes. The aim of the SpInOuT feasibility study was to establish whether a definitive randomized controlled trial (RCT) that accounted for the spectrum of pathology contributing to spinal stenosis, including pelvic incidence-lumbar lordosis (PI-LL) mismatch and mobile spondylolisthesis, could be conducted. As part of the SpInOuT-F study, a pilot randomized trial was carried out across five NHS hospitals. Patients were randomized to either spinal decompression alone or spinal decompression plus instrumented fusion. Patient-reported outcome measures were collected at baseline and three months. The intended sample size was 60 patients.Aims
Methods
Postoperative malalignment of the femur is one of the main complications in distal femur fractures. Few papers have investigated the impact of intraoperative malalignment on postoperative function and bone healing outcomes. The aim of this study was to investigate how intraoperative fracture malalignment affects postoperative bone healing and functional outcomes. In total, 140 patients were retrospectively identified from data obtained from a database of hospitals participating in a trauma research group. We divided them into two groups according to coronal plane malalignment of more than 5°: 108 had satisfactory fracture alignment (< 5°, group S), and 32 had unsatisfactory alignment (> 5°, group U). Patient characteristics and injury-related factors were recorded. We compared the rates of nonunion, implant failure, and reoperation as healing outcomes and Knee Society Score (KSS) at three, six, and 12 months as functional outcomes. We also performed a sub-analysis to assess the effect of fracture malalignment by plates and nails on postoperative outcomes.Aims
Methods
The purpose of this study was to compare the radiological outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Postoperative radiological outcomes from 86 consecutive robotic-assisted UKAs (RAUKA group) from a single academic centre were retrospectively reviewed and compared to 253 manual UKAs (MUKA group) drawn from a prior study at our institution. Femoral coronal and sagittal angles (FCA, FSA), tibial coronal and sagittal angles (TCA, TSA), and implant overhang were radiologically measured to identify outliers.Aims
Methods
High-grade dysplastic spondylolisthesis is a disabling disorder for which many different operative techniques have been described. The aim of this study is to evaluate Scoliosis Research Society 22-item (SRS-22r) scores, global balance, and regional spino-pelvic alignment from two to 25 years after surgery for high-grade dysplastic spondylolisthesis using an all-posterior partial reduction, transfixation technique. SRS-22r and full-spine lateral radiographs were collected for the 28 young patients (age 13.4 years (SD 2.6) who underwent surgery for high-grade dysplastic spondylolisthesis in our centre (Scottish National Spinal Deformity Service) between 1995 and 2018. The mean follow-up was nine years (2 to 25), and one patient was lost to follow-up. The standard surgical technique was an all-posterior, partial reduction, and S1 to L5 transfixation screw technique without direct decompression. Parameters for segmental (slip percentage, Dubousset’s lumbosacral angle) and regional alignment (pelvic tilt, sacral slope, L5 incidence, lumbar lordosis, and thoracic kyphosis) and global balance (T1 spino-pelvic inclination) were measured. SRS-22r scores were compared between patients with a balanced and unbalanced pelvis at final follow-up.Aims
Methods
The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments. Based on a clinical series of 479 primary total knees and 1,305 associated surgical decisions, various ML models were developed. These models identified the indicated surgical decision based on available, intra-operative alignment, and tibiofemoral load data.Aims
Methods
