World Neurosurg
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Multicenter Study Controlled Clinical Trial
Targeted Temperature Management for Poor grade Aneurysmal Subarachnoid Hemorrhage, A pilot study.
We assessed the effectiveness and safety of target temperature management (TTM) in treating patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH). The primary objective was to evaluate the neurological outcome at 3 months. Secondary objectives were to assess mortality, delayed cerebral ischemia, cerebral edema, hydrocephalus, midline shift, and laboratory indicators related to TTM. ⋯ This study demonstrated the effectiveness and safety of TTM in patients with poor-grade aSAH, and its implementation improved neurological outcomes. Multicenter randomized controlled studies with a large number of patients are needed to confirm these observations.
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Review Case Reports
Microvascular decompression for trigeminal neuralgia caused by vascular compression on the trigeminal sensory nucleus and descending trigeminal tract.
Trigeminal neuralgia (TN) is characterized by paroxysmal episodes of severe shocklike orofacial pain typically resulting from arterial compression on the trigeminal root entry zone. However, neurovascular conflict in more proximal parts of the trigeminal pathway within the pons is extremely rare. ⋯ Neurovascular compression in the trigeminal tract and nucleus is a rare but potential cause of TN. A thorough investigation of the trigeminal pathway should be considered during preoperative evaluation and intraoperative inspection, particularly if no clear offending vessel is identified.
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Temporal lobe epilepsy is the most common reason behind drug-resistant seizures and temporal lobectomy (TL) is performed after all other efforts have been taken for a Temporal lobe epilepsy. Our study aims to develop multiple machine learning (ML) models capable of predicting postoperative outcomes following TL surgery. ⋯ Our study uses ML to forecast adverse postoperative outcomes following TL. We developed accessible predictive models that enhance prognosis prediction for TL surgery. Making ML models available for this purpose represents a significant advancement in shifting toward a more patient-centric, data-driven paradigm.
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Radiomics is a machine-learning method that extracts features from medical images. The objective of the present systematic review was to assess the quality of existing studies that use radiomics methods to predict functional outcomes in patients after acute ischemic stroke. ⋯ The quality of the included studies was low to moderate. With increasing use of radiomics, future studies should attempt to adhere to and report established radiomics quality guidelines.