World Neurosurg
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This study aimed to establish a precise preoperative high-risk factor scoring system and algorithm for antibiotic prophylaxis decision-making, provide guidance for the judicious use of AMP, refine interventions, and ensure the appropriate application of AMP for class I incisions in neurosurgery. ⋯ The established index for AMP utilization and SOPs in the preoperative period of class I neurosurgical incisions proves valuable, contributing to improved patient outcomes in neurosurgical procedures.
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Dumbbell-shaped schwannomas are slow-growing tumors that are typically benign lesions. They account for 6%-14% of spinal neoplasms, with 30% having intradural and extradural components.1 A schwannoma is considered "giant" if it extends beyond the spine by >2.5 cm and involves more than 2 vertebral levels.2 The Eden classification categorizes these tumors into 4 types on the basis of the primary component.3 Surgery is recommended for individuals experiencing prolonged nerve damage and persistent neurogenic pain that cannot be managed.2 There are 3 surgical options for managing thoracic dumbbell schwannomas4: the single-stage posterior-only approach,5 the single-stage anterior-only approach,6 and the single-stage combined posteroanterior neurosurgical and video-assisted thoracoscopic approach. The latter option allows for the most comprehensive lesion control including vascular and nerve structures and optimal hemostasis control. ⋯ A simultaneous thoracoscopic and neurosurgical approach was performed. The surgical team successfully removed the schwannoma, and the patient's recovery was smooth, with no neurologic issues or pain. This case highlights the benefits of using a single-stage combined approach for treating Eden II and Eden III giant dumbbell thoracic schwannomas.
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Modic changes are pathologies that are common in the population and cause low back pain. The aim of the study is to analyze the modic changes detected in magnetic resonance imaging (MRI) using deep learning modalities. ⋯ Evaluation of MRI findings of MC in the etiology of lower back pain with deep learning architectures can significantly reduce the workload of the radiologist by providing ease of diagnosis.
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Endoscopic skull base surgery is constantly evolving and its scope has expanded. The acquisition of surgical skills involves a long learning curve with significant risks for the patient. Therefore, training in the laboratory has become essential to achieve appropriate proficiency and reduce the morbidity and mortality associated with these procedures. The objective of our work is to develop and validate a cost-effective and easily replicable simulator for endonasal endoscopy training using a swine cadaveric model. ⋯ The endonasal endoscopy training simulator using a swine cadaveric model is a useful and accessible tool for enhancing surgical skills in this field. It provides an opportunity for training outside the operating room, reducing the potential risks associated with patient practice, and improving the training of residents.