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
Anchorage of pedicle screw rod instrumentation in the elderly spine with poor bone quality remains challenging. Our study aims to evaluate how the screw bone anchorage is affected by screw design, bone quality, loading conditions, and cementing techniques. Micro-finite element (µFE) models were created from micro-CT (μCT) scans of vertebrae implanted with two types of pedicle screws (L: Ennovate and R: S4). Simulations were conducted for a 10 mm radius region of interest (ROI) around each screw and for a full vertebra (FV) where different cementing scenarios were simulated around the screw tips. Stiffness was calculated in pull-out and anterior bending loads.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
