World Neurosurg
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Degenerative cervical myelopathy is the most common cause of spinal cord injury in the elderly population in the developed world, and it significantly affects the quality of life of patients and their caregivers. Surgery remains the only treatment option able to halt disease progression and provide neurological recovery for most patients. Although it has remained challenging to predict exactly who will experience improvement after surgery, increasingly it has been shown that clinical, imaging, and electrophysiological factors can predict, with relatively good capacity, those more likely to benefit. ⋯ However, large studies are lacking. Although multivariate models have been conducted using clinical and magnetic resonance imaging data, no multimodal prediction models are available that encompass the predictive capacity of clinical, imaging, and electrophysiological data. In the present review, we examined the rationale for clinical, imaging, and electrophysiological usage in clinical practice and discussed a model of multimodal assessment for the management of degenerative cervical myelopathy.
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Facial paresis is one of the complications after treatment for vestibular schwannoma (VS). Acupuncture has been used for Bell palsy but not in iatrogenic facial paresis. The objective of this study is to measure the efficacy of using acupuncture for iatrogenic facial nerve palsy and patients' satisfaction. ⋯ Acupuncture for postresection VS facial paresis seemed to speed up its recovery. Both patients' recovery and satisfaction were good after acupuncture, and it seemed to be a safe procedure in trained hands.
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Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on "one-size-fits-all" guidelines. As epidemiological datasets continue to burgeon in size and complexity, powerful methods such as statistical machine learning and artificial intelligence (AI) become necessary to interpret and develop prognostic models from underlying data. Through such analysis, machine learning can be used to facilitate personalized medicine via its precise predictions. ⋯ In the present report, we discuss the current strides made in incorporating AI into research on spine disease, especially traumatic spinal cord injury and degenerative spine disease. We describe studies using AI to build accurate prognostic models, extract important information from medical reports via natural language processing, and evaluate functional status in a granular manner using computer vision. Through a case illustration, we have demonstrated how these breakthroughs can facilitate an increased role for more personalized medicine and, thus, change the landscape of spine care.
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Intracranial hypotension (IH) has a widely variable clinical and radiologic presentation. Secondary IH may be caused by degenerative spine disorders and in particular by thoracic disk herniations (TDHs). ⋯ This paper adds to the evidence that some cases of IH and even superficial siderosis are caused by transdural erosion of a TDH that may be otherwise asymptomatic. The dura may degenerate due to chronic compression, and a longitudinal slitlike dural defect with smooth lining may develop, causing continuous (Case 1) or intermittent (Case 2) intraspinal CSF leakage. To the best of our knowledge, such dural defects closely resembling the ones observed in idiopathic spinal cord herniation have never been demonstrated on intraoperative endoscopic video in IH patients.
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Traumatic atlantoaxial dislocation without associated odontoid fracture or neurologic deficit is rare. We present the case of a 39-year-old male pedestrian who was struck by a vehicle and sustained a traumatic grade 4 C1-2 retrolisthesis. Closed reduction was successful, and the patient underwent posterior occipitocervical fusion. His neurologic status was good throughout the hospital stay, and he was discharged to a rehabilitation facility with full strength.