World Neurosurg
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Neurotechnology is set to expand rapidly in the coming years as technological innovations in hardware and software are translated to the clinical setting. Given our unique access to patients with neurologic disorders, expertise with which to guide appropriate treatments, and technical skills to implant brain-machine interfaces (BMIs), neurosurgeons have a key role to play in the progress of this field. ⋯ Our key message is to encourage the neurosurgical community to proactively engage in collaborating with other health care professionals, engineers, scientists, ethicists, and regulators in tackling these issues. By doing so, we will equip ourselves with the skills and expertise to drive the field forward and avoid being mere technicians in an industry driven by those around us.
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The treatment of neuropathic pain (NP) continues to be controversial as well as an economic health issue and a challenge to health care. Neurosurgery can offer different methods of neuromodulation that may improve patients' condition, including deep brain stimulation (DBS), motor cortex stimulation (MCS), spinal cord stimulation (SCS), and posterior insula stimulation (PIS). There is no consensus of opinion as to the final effects of these procedures, which stimulation parameters to select, the correct timing, or how to select the patients who will best benefit from these procedures. ⋯ This systematic review highlights the literature supporting SCS, DBS, MCS, and PIS methods for the treatment of NP. We found consistent evidence supporting MCS, DBS, and SCS as possible treatments for NP; however, we were not able to define which procedure should be indicated for each cause. Furthermore, we did not find enough evidence to justify the routine use of PIS. We conclude that unanswered points need to be discussed in this controversial field and emphasize that new research must be developed to treat patients with NP, to improve their quality of life.
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Machine learning has emerged as a viable asset in the setting of pituitary surgery. In the past decade, the number of machine learning models developed to aid in the diagnosis of pituitary lesions and predict intraoperative and postoperative complications following transsphenoidal surgery has increased exponentially. As computational processing power continues to increase, big data sets continue to expand, and learning algorithms continue to surpass gold standard predictive tools, machine learning will serve to become an important component in improving patient care and outcomes. ⋯ The field of machine learning is broad, with radiomics and artificial neural networks comprising 2 commonly used supervised learning methods in pituitary surgery. Given the large heterogeneity of pituitary and sellar lesions, the promise of machine learning lies in its ability to identify relationships and patterns that are otherwise hidden from standard statistical methods. While machine learning has great potential as a clinical adjunct during the surgical preplanning process and in predicting complications and outcomes, challenges moving forward include standardization and validation of these paradigms.
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Drug-resistant epilepsy accounts for approximately one third of all epilepsy cases; yet its exact etiopathogenesis still remains under intense exploration. Several factors have been advocated for predicting drug resistance in patients with epilepsy. ⋯ This study analyzes the relationship between drug-resistant epilepsy and OSA, and the findings indicate a strong role of rapid eye movement sleep (REMS) in the pathogenesis of this relationship. It also emerges from the study that REMS reduction is a prominent feature of OSA, and drug resistance in patients with epilepsy and treatment of OSA has been shown to restore REMS in several studies with concomitant improvement in seizure control.
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Comparative Study
Comparative Analysis of Survival Outcomes and Prognostic Factors of Supratentorial versus Cerebellar Glioblastoma in the Elderly: Does Location Really Matter?
Cerebellar glioblastomas (cGBMs) are rare tumors that are uncommon in the elderly. In this study, we compare survival outcomes and identify prognostic factors of cGBM compared with the supratentorial (stGBM) counterpart in the elderly. ⋯ In our study, elderly patients with cGBM and stGBM have similar outcomes in overall survival, and those undergoing maximal resection with adjuvant therapies, independent of tumor location, have improved outcomes. Thus, aggressive treatment should be encouraged for cGBM in geriatric patients to confer the same survival benefits seen in stGBM. Single-institutional and multi-institutional studies to identify patient-level prognostic factors are warranted to triage the best surgical candidates.