Neurosurgery
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Meta Analysis
A Quantitative Systematic Review of Clinical Outcome Measure Use in Peripheral Nerve Injury of the Upper Limb.
Peripheral nerve injury (PNI) is common, leading to reduced function, pain, and psychological impact. Treatment has not progressed partly due to inability to compare outcomes between centers managing PNI. Numerous outcome measures exist but there is no consensus on which outcome measures to use nor when. ⋯ Lack of consensus on outcome measure use hinders comparison of outcomes between nerve injury centers and the development of novel treatments. Development of a core outcome set will help standardize outcome reporting, improve translation of novel treatments from lab to clinical practice, and ensure future research in PNI is more amenable to systematic review and meta-analysis.
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Randomized Controlled Trial
Thalamic Deep Brain Stimulation for Spasmodic Dysphonia: A Phase I Prospective Randomized Double-Blind Crossover Trial.
Adductor spasmodic dysphonia (SD) is a dystonia of the vocal folds causing difficulty with speech. The current standard of care is repeated botulinum toxin injections to weaken the adductor muscles. We sought to ameliorate the underlying neurological cause of SD with a novel therapy-deep brain stimulation (DBS). ⋯ This phase I randomized controlled trial confirmed that DBS can be performed safely in patients with SD. Blinded DBS produced a strong trend toward improved quality of life and objective quality of voice despite the small sample size. The cerebellar circuit, not the pallidal circuit, appears to be crucial for motor control of the vocal folds.
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Molecular characterization of glioma has implications for prognosis, treatment planning, and prediction of treatment response. Current histopathology is limited by intratumoral heterogeneity and variability in detection methods. Advances in computational techniques have led to interest in mining quantitative imaging features to noninvasively detect genetic mutations. ⋯ ML application to preoperative MRI demonstrated promising results for predicting IDH mutation, MGMT methylation, and 1p/19q codeletion in glioma. Optimized ML models could lead to a noninvasive, objective tool that captures molecular information important for clinical decision making. Future studies should use multicenter data, external validation and investigate clinical feasibility of ML models.