European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
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Review Meta Analysis
The predictive power of the Roussouly classification on mechanical complications after surgery for adult spinal deformity: systematic review and meta-analysis.
With the increasing prevalence of adult spinal deformity (ASD) in the aging population, the need for corrective surgery has surged, highlighting the importance of preventing mechanical complications (MC) such as junctional kyphosis/failure and rod breakage. The Roussouly classification, which categorizes natural variations in spinal posture, may hold predictive value in assessing the risk of these complications, as it guides the restoration of sagittal alignment based on a patient's preoperative spinal shape. ⋯ III.
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The purpose of this study was to investigate threshold values for classifying bone as normal or osteoporotic based on Computed Tomography (CT) Hounsfield Units (HU) and to determine if clinically applicable values could be derived to aid spine surgeons evaluating bone quality using CT. ⋯ There is variation in HU values used to differentiate normal from compromised bone quality, even after limiting studies. For patients with HU values between or near 170 or 115 HU, a DEXA scan may be warranted for further evaluation. With ongoing investigation in this area, threshold values for classifying bone quality using CT will be continually refined.
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An atypical presentation of cervical spondylopathy (CS), trigeminal neuralgia (TN) is attributable to the extension of trigeminal nuclei into the spinal cord and is frequently overlooked, leading to limited discussion with patients regarding potential anterior cervical surgery. Our systematic review assesses the effectiveness of cervical surgery for concurrent trigeminal neuralgia in cases of cervical spondylopathy. ⋯ Besides common manifestations, high cervical stenosis can cause trigeminal neuralgia. This case report and systematic review confirms spinal decompression and fusion surgery may be effective in select cases. Surgeons should raise the possibility of cervical spine involvement when counseling patients with this disease.
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An atypical presentation of cervical spondylopathy (CS), trigeminal neuralgia (TN) is attributable to the extension of trigeminal nuclei into the spinal cord and is frequently overlooked, leading to limited discussion with patients regarding potential anterior cervical surgery. Our systematic review assesses the effectiveness of cervical surgery for concurrent trigeminal neuralgia in cases of cervical spondylopathy. ⋯ Besides common manifestations, high cervical stenosis can cause trigeminal neuralgia. This case report and systematic review confirms spinal decompression and fusion surgery may be effective in select cases. Surgeons should raise the possibility of cervical spine involvement when counseling patients with this disease.
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Lumbar spinal stenosis (LSS) is a frequently occurring condition defined by narrowing of the spinal or nerve root canal due to degenerative changes. Physicians use MRI scans to determine the severity of stenosis, occasionally complementing it with X-ray or CT scans during the diagnostic work-up. However, manual grading of stenosis is time-consuming and induces inter-reader variability as a standardized grading system is lacking. Machine Learning (ML) has the potential to aid physicians in this process by automating segmentation and classification of LSS. However, it is unclear what models currently exist to perform these tasks. ⋯ DL models achieve excellent performance for segmentation and classification tasks for LSS, outperforming conventional ML algorithms. However, comparisons between studies are challenging due to the variety in outcome measures and test datasets. Future studies should focus on the segmentation task using DL models and utilize a standardized set of outcome measures and publicly available test dataset to express model performance. In addition, these models need to be externally validated to assess generalizability.