World Neurosurg
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Thoracolumbar corpectomy and percutaneous pedicle screw (PPS) fixation is becoming the standard method for correcting and stabilizing malalignment of spine, as is often seen in osteoporotic vertebral fracture. Nowadays, this procedure can be performed in a single lateral position with navigation. For an osteoporotic spine, accurate rod bending is necessary to prevent screw back-out. We describe a new technique using the spinal rod-bending system in a single lateral position. ⋯ Minimally invasive surgery thoracolumbar corpectomy using a computer-assisted spinal rod-bending system is a valuable technique to reduce screw back-out for osteoporotic vertebrae. With this new technique, the rod bending becomes easy, even for long PPS fusion with the severe osteoporotic or deformity patient in a single lateral position.
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The magnetic resonance imaging (MRI)-directed implantable guide tube technique allows for direct targeting of deep brain structures without microelectrode recording or intraoperative clinical assessment. This study describes a 10-year institutional experience of this technique including nuances that enable performance of surgery using readily available equipment. ⋯ The MRI-directed implantable guide tube technique is a highly accurate, low-cost, reliable method for introducing deep brain electrodes. This technique reduces brain shift secondary to pneumocephalus and allows for whole trajectory planning of multiple electrode contacts.
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Readmission after spine surgery is costly and a relatively common occurrence. Previous research identified several risk factors for readmission; however, the conclusions remain equivocal. Machine learning algorithms offer a unique perspective in analysis of risk factors for readmission and can help predict the likelihood of this occurrence. This study evaluated a neural network (NN), a supervised machine learning technique, to determine whether it could predict readmission after 3 lumbar fusion procedures. ⋯ The accurate metrics presented indicate the capability for NN algorithms to predict readmission after lumbar arthrodesis. Moreover, the results of this study serve as a catalyst for further research into the utility of machine learning in spine surgery.