Current neurology and neuroscience reports
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Curr Neurol Neurosci Rep · Nov 2019
Review Case ReportsSherpas, Coca Leaves, and Planes: High Altitude and Airplane Headache Review with a Case of Post-LASIK Myopic Shift.
High altitude headache is a common neurological symptom that is associated with ascent to high altitude. It is classified by the International Classification of Headache Disorders, 3rd Edition (ICHD-3) as a disorder of homeostasis. In this article, we review recent clinical and insights into the pathophysiological mechanisms of high altitude and airplane headache. We also report a second case of post-LASIK myopic shift at high altitude exposure secondary hypoxia. Headache attributed to airplane travel is a severe typically unilateral orbital headache that usually improves after landing. This was a relative recent introduction to the ICHD-3 diagnostic criteria. Headache pain with flight travel has long been known and may have been previously considered as a part of barotrauma. Recent studies have helped identify this as a distinct headache disorder. ⋯ Physiologic, hematological, and biochemical biomarkers have been identified in recent high altitude studies. There have been recent advance in identification of molecular mechanisms underlying neurophysiologic changes secondary to hypoxia. Calcitonin gene-related peptide, a potent vasodilator, has been implicated in migraine pathophysiology. Recent epidemiological studies indicate that the prevalence of airplane headache may be more common than we think in the adult as well at the pediatric population. Simulated flight studies have identified potential biomarkers. Although research is limited, there have been advances in both clinical and pathophysiological mechanisms associated with high altitude and airplane headache.
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Curr Neurol Neurosci Rep · Nov 2019
ReviewClinical Characteristics and Treatment of MOG-IgG-Associated Optic Neuritis.
Antibodies against myelin oligodendrocyte glycoprotein (MOG) are associated with a unique acquired central nervous system demyelinating disease-termed MOG-IgG-associated disorder (MOGAD)-which has a variety of clinical manifestations, including optic neuritis, transverse myelitis, acute disseminating encephalomyelitis, and brainstem encephalitis. In this review, we summarize the current knowledge of the clinical characteristics, neuroimaging, treatments, and outcomes of MOGAD, with a focus on optic neuritis. ⋯ The recent development of a reproducible, live cell-based assay for MOG-IgG, has improved our ability to identify and study this disease. Based on contemporary studies, it has become increasingly evident that MOGAD is distinct from multiple sclerosis and aquaporin-4-positive neuromyelitis optica spectrum disorder with different clinical features and treatment outcomes. There is now sufficient evidence to separate MOGAD from other inflammatory central nervous system demyelinating disorders, which will allow focused research on understanding the pathophysiology of the disease. Prospective treatment trials are needed to determine the best course of treatment, and until then, treatment plans must be individualized to the clinical manifestations and severity of disease.
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Curr Neurol Neurosci Rep · Nov 2019
ReviewMachine Learning and Artificial Intelligence in Neurocritical Care: a Specialty-Wide Disruptive Transformation or a Strategy for Success.
Neurocritical care combines the complexity of both medical and surgical disease states with the inherent limitations of assessing patients with neurologic injury. Artificial intelligence (AI) has garnered interest in the basic management of these complicated patients as data collection becomes increasingly automated. ⋯ In this opinion article, we highlight the potential AI has in aiding the clinician in several aspects of neurocritical care, particularly in monitoring and managing intracranial pressure, seizures, hemodynamics, and ventilation. The model-based method and data-driven method are currently the two major AI methods for analyzing critical care data. Both are able to analyze the vast quantities of patient data that are accumulated in the neurocritical care unit. AI has the potential to reduce healthcare costs, minimize delays in patient management, and reduce medical errors. However, these systems are an aid to, not a replacement for, the clinician's judgment.