Neurosurgery
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Cell therapy has been widely recognized as a promising strategy to enhance recovery in stroke survivors. However, despite an abundance of encouraging preclinical data, successful clinical translation remains elusive. ⋯ In the present work, we review the major clinical trials of cell therapy for stroke and highlight a mechanistic shift between the earliest studies, which aimed to replace dead and damaged neurons, and later ones that focused on exploiting the various neuromodulatory effects afforded by stem cells. We discuss why both mechanisms are worth pursuing and emphasize the means through which cell replacement can still be achieved.
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Randomized Controlled Trial
Encephaloduroarteriosynangiosis Averts Stroke in Atherosclerotic Patients With Border-Zone Infarct: Post Hoc Analysis From a Performance Criterion Phase II Trial.
Intracranial atherosclerotic disease (ICAD) is one of the leading causes of stroke worldwide. Patients with ICAD who initially present with ischemia in border-zone areas and undergo intensive medical management (IMM) have the highest recurrence rates (37% at 1 yr) because of association with hemodynamic failure and poor collaterals. ⋯ ICAD patients with BDZS at presentation have lower rates of recurrent stroke after EDAS surgery than those reported with medical management in the SAMMPRIS trial. These results support further investigation of EDAS in a randomized clinical trial.
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Multicenter Study
Stereotactic Radiosurgery for Perioptic Meningiomas: An International, Multicenter Study.
Stereotactic radiosurgery (SRS) is increasingly used for management of perioptic meningiomas. ⋯ SRS provides durable tumor control and quite acceptable rates of vision preservation in perioptic meningiomas. Margin dose of ≥12 Gy is associated with improved tumor control, while a dose to the optic apparatus of ≥10 Gy and tumor progression are associated with post-SRS visual decline.
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Multicenter Study
Predicting Discharge Disposition Following Meningioma Resection Using a Multi-Institutional Natural Language Processing Model.
Machine learning (ML)-based predictive models are increasingly common in neurosurgery, but typically require large databases of discrete variables for training. Natural language processing (NLP) can extract meaningful data from unstructured text. ⋯ ML and NLP are underutilized in neurosurgery. Here, we construct a multi-institutional NLP model that predicts nonhome discharge.