Neurosurgery
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Survival prediction of patients affected by brain tumors provides essential information to guide surgical planning, adjuvant treatment selection, and patient counseling. Current reliance on clinical factors, such as Karnofsky Performance Status Scale, and simplistic radiological characteristics are, however, inadequate for survival prediction in tumors such as glioma that demonstrate molecular and clinical heterogeneity with variable survival outcomes. ⋯ Here, we provide an overview of current literature that apply computational analysis tools such as radiomics and machine learning methods to the pipeline of image preprocessing, tumor segmentation, feature extraction, and construction of classifiers to establish survival prediction models based on neuroimaging. We also discuss challenges relating to the development and evaluation of such models and explore ethical issues surrounding the future use of machine learning predictions.
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Asleep vs awake surgery for right insula-centered low-grade glioma (LGG) is still debated. ⋯ This is the first study comparing asleep vs awake surgery for right insula-centered LGG. Despite similar extent of resection, functional outcomes were significantly better in awake patients by avoiding permanent neurological impairment and by increasing RTW. These results support the mapping of higher-order functions during awake procedure.
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Observational Study
Initial Clinical Outcome With Bilateral, Dual-Target Deep Brain Stimulation Trial in Parkinson Disease Using Summit RC + S.
Deep brain stimulation (DBS) is an effective therapy in advanced Parkinson disease (PD). Although both subthalamic nucleus (STN) and globus pallidus (GP) DBS show equivalent efficacy in PD, combined stimulation may demonstrate synergism. ⋯ Patients with PD preferred combined DBS stimulation in this preliminary cohort. Future studies will address efficacy of adaptive DBS as we further define biomarkers and control policy.
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The Centers for Medicare and Medicaid Services (CMS) hierarchical condition category (HCC) coding is a risk adjustment model that allows for the estimation of risk-and cost-associated with health care provision. Current models may not include key factors that fully delineate the risk associated with spine surgery. ⋯ The addition of key demographic and socioeconomic characteristics substantially improves the CMS HCC risk-adjustment models when modeling spinal fusion outcomes. This finding may have important implications for payers, hospitals, and policymakers.
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The early phase of the COVID-19 pandemic led to significant healthcare avoidance, perhaps explaining some of the excess reported deaths that exceeded known infections. The impact of the early COVID-19 era on aneurysmal subarachnoid hemorrhage (aSAH) care remains unclear. ⋯ aSAH in the early COVID-19 era was associated with delayed presentation, neurological complications, and worse outcomes at our center. These data highlight how healthcare avoidance may have increased morbidity and mortality in non-COVID-19-related neurosurgical disease.