While extragonadal seminomas resulting in spinal cord compression are rarely reported in the literature, most have been treated with surgical decompression followed by radiation therapy. In this report, we present the unique and interesting case of a 38-year-old man who initially presented as an outpatient with a chief complaint of axial neck pain and lateral thoracic wall pain. After an extensive malignancy workup, he was diagnosed with a primary cervical spine seminoma and was treated with a C6-T1 laminectomy with posterior spinal instrumentation from C5 to T2. He has since undergone chemotherapy with cisplatin, vinblastine, and bleomycin, and at 24-month follow-up, he remains asymptomatic with no signs of recurrent disease.
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http://dx.doi.org/10.5435/JAAOSGlobal-D-19-00177 | DOI Listing |
Sci Rep
January 2025
Department of Orthopedic Surgery, Beijing Chao-Yang Hospital, Capital Medical University, GongTiNanLu 8#, Chaoyang District, Beijing, 100020, China.
We aimed to analyze the cervical sagittal alignment change following the growing rod treatment in early-onset scoliosis (EOS) and identify the risk factors of sagittal cervical imbalance after growing-rod surgery of machine learning. EOS patients from our centre between 2007 and 2019 were retrospectively reviewed. Radiographic parameters include the cervical lordosis (CL), T1 slope, C2-C7 sagittal vertical axis (C2-7 SVA), primary curve Cobb angle, thoracic kyphosis (TK), C7-S1 sagittal vertical axis (C7-S1 SVA) and proximal junctional angle (PJA) were evaluated preoperatively, postoperatively and at the final follow-up.
View Article and Find Full Text PDFSci Rep
January 2025
College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Health, Dubai, UAE.
The first cervical vertebra (C1) is atypical in shape and bears a complex relationship with important neurovascular structures such as the vertebral artery and cervical spinal cord which are at risk of injury during misplaced screw fixation of C1. Placement of screws into the lateral mass of C1 vertebra is performed for stabilization of the craniovertebral junction. The objective of this study was to describe ideal screw dimensions, precise entry points, safe bony corridors, and ideal trajectories for placement of lateral mass screws in the Emirati population.
View Article and Find Full Text PDFSpine J
January 2025
Medical University of South Carolina, Charleston, SC, USA. Electronic address:
Background Context: Clinical outcomes are directly related to patient selection and treatment indications for improved quality of life. With emphasis on quality and value, it is essential that treatment recommendations are optimized.
Purpose: The purpose of the North American Spine Society (NASS) Appropriate Use Criteria (AUC) is to determine the appropriate (ie, reasonable) multidisciplinary treatment recommendations for patients with metastatic neoplastic vertebral fractures across a spectrum of more common clinical scenarios.
World Neurosurg
January 2025
Department of Endocrinology, Yinzhou No.2 Hospital, Ningbo, Zhejiang 315040, China. Electronic address:
Objective: This study aims to evaluate the clinical outcomes of utilizing C1 posterior arch screws (PAS) combined with C2 translaminar screws as an adjunct for reinforcing upper cervical spine fixation.
Methods: A retrospective analysis was conducted on four male patients who underwent surgery involving C1 PASs and C2 translaminar screws between January 2022 and February 2024. Surgical technique involved the insertion of standard C1 lateral mass screws (LMS) and C2 pedicle screws, followed by the placement of C1 PASs and C2 translaminar screws for additional fixation.
J Bone Joint Surg Am
November 2024
Department of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Background: An accurate knowledge of a patient's risk of cord-level intraoperative neuromonitoring (IONM) data loss is important for an informed decision-making process prior to deformity correction, but no prediction tool currently exists.
Methods: A total of 1,106 patients with spinal deformity and 205 perioperative variables were included. A stepwise machine-learning (ML) approach using random forest (RF) analysis and multivariable logistic regression was performed.
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