Neurosurgery
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The perioperative multidisciplinary team approach has probably been best exemplified by the care of awake craniotomy patients. Advancement in anesthesia and meticulous perioperative care has supported the safety and complexity of the surgical and mapping efforts in glioma resection. The discussions in this review will emphasize on anesthetic and perioperative management strategies to prevent complications and minimize their effects if they occur, including current practice guidelines in anesthesia, updates on the applications of anesthetic medications, and emerging devices. Planning the anesthetic and perioperative management is based on understanding the pharmacology of the medications, the goals of different stages of the surgery and mapping, and anticipating potential problems.
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Long-term efficacy and mechanisms of action of deep brain stimulation (DBS) for treatment-resistant depression (TRD) are under investigation. ⋯ SCG-DBS for TRD is clearly effective in some patients. Active contacts' coordinates were highly variable within the region and, like electrical parameters, did not seem to correlate with clinical outcomes. In the current series, Brodmann area 10 medial and the forceps minor were the most frequently targeted area and modulated pathway, respectively.
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Meta Analysis
Optimal Donor Nerve to Restore Elbow Flexion After Traumatic Brachial Plexus Injury: A Systematic Review and Meta-Analysis.
Traumatic brachial plexus injuries (BPIs) often lead to devastating upper extremity deficits. Treatment frequently prioritizes restoring elbow flexion through transfer of various donor nerves; however, no consensus identifies optimal donor nerve sources. ⋯ Neurotization of partial BPI or TBPI through the intercostal nerve or phrenic nerve may result in functional advantage over cC7. In patients with upper trunk injuries, neurotization using ulnar, median, or double fascicle nerve transfers has similarly excellent functional recovery.
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Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predict surgical outcomes. However, the large quantity of data required and lack of model interpretability represent substantial barriers to the validity and reproducibility of DL models. The objective of this study was to systematically review the characteristics of DL studies involving neurosurgical outcome prediction and to assess their bias and reporting quality. ⋯ The use of DL for neurosurgical outcome prediction remains nascent. Lack of appropriate data sets poses a major concern for bias. Although studies have demonstrated promising results, greater transparency in model development and reporting is needed to facilitate reproducibility and validation.