Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desirable, with frequent complications and limited improvement in quality of life. The accurate prediction of surgical outcome is crucial to the process of clinical decision-making. Consequently, the aim of this study was to develop and validate a model for predicting an ideal surgical outcome (ISO) two years after ASD surgery. We conducted a retrospective analysis of 458 consecutive patients who had undergone spinal fusion surgery for ASD between January 2016 and June 2022. The outcome of interest was achievement of the ISO, defined as an improvement in patient-reported outcomes exceeding the minimal clinically important difference, with no postoperative complications. Three machine-learning (ML) algorithms – LASSO, RFE, and Boruta – were used to identify key variables from the collected data. The dataset was randomly split into training (60%) and test (40%) sets. Five different ML models were trained, including logistic regression, random forest, XGBoost, LightGBM, and multilayer perceptron. The primary model evaluation metric was area under the receiver operating characteristic curve (AUROC).Aims
Methods
Cement augmentation of pedicle screws could be used to improve screw stability, especially in osteoporotic vertebrae. However, little is known concerning the influence of different screw types and amount of cement applied. Therefore, the aim of this biomechanical A total of 54 osteoporotic human cadaver thoracic and lumbar vertebrae were instrumented with pedicle screws (uncemented, solid cemented or fenestrated cemented) and augmented with high-viscosity PMMA cement (0 mL, 1 mL or 3 mL). The insertion torque and bone mineral density were determined. Radiographs and CT scans were undertaken to evaluate cement distribution and cement leakage. Pull-out testing was performed with a material testing machine to measure failure load and stiffness. The paired Objectives
Materials and Methods
Although vertebroplasty is very effective for relieving acute pain from an osteoporotic vertebral compression fracture, not all patients who undergo vertebroplasty receive the same degree of benefit from the procedure. In order to identify the ideal candidate for vertebroplasty, pre-operative prognostic demographic or clinico-radiological factors need to be identified. The objective of this study was to identify the pre-operative prognostic factors related to the effect of vertebroplasty on acute pain control using a cohort of surgically and non-surgically managed patients. Patients with single-level acute osteoporotic vertebral compression fracture at thoracolumbar junction (T10 to L2) were followed. If the patients were not satisfied with acute pain reduction after a three-week conservative treatment, vertebroplasty was recommended. Pain assessment was carried out at the time of diagnosis, as well as three, four, six, and 12 weeks after the diagnosis. The effect of vertebroplasty, compared with conservative treatment, on back pain (visual analogue score, VAS) was analysed with the use of analysis-of-covariance models that adjusted for pre-operative VAS scores.Objectives
Patients and Methods
