World Neurosurg
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Patients with World Federation of Neurosurgical Societies (WFNS) grade V subarachnoid hemorrhage (SAH) frequently have poor outcomes. The current understanding of the predictors of functional outcome only in WFNS grade V SAH is limited. ⋯ The final outcome of patients with WFNS grade V SAH was still poor and highly predicted by Glasgow Coma Scale score of 3, high-grade Early Brain Edema Score, absence of bilaterally light reflex and neurologic improvement, and a history of hypertension. The efficacy of aggressive surgical treatment for these patients remains controversial, and the indications should be clearly defined in patients with desolate clinical status on admission.
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We aimed to predict hematoma expansion in intracerebral hemorrhage (ICH) patients by using the deep learning technique. ⋯ More than 90% of hematomas with or without expansion can be precisely classified by deep learning technology within this study, which is better than other methods based on clinical variables only. Deep learning technology could favorably predict hematoma expansion from non-contrast CT scan images.
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Parkinson disease (PD) is a risk factor for worse surgical outcomes. The degree to which PD affects outcomes in cervical spine surgery is not well understood. Therefore, we characterize rates of postoperative complications among patients with PD who undergo cervical spine surgery. ⋯ Patients with PD who receive ACDF have higher rates of pulmonary (6.05%), neurologic (5.24%), and psychiatric (3.23%) complications at 90 days. The differences did not reach statistical significance. This finding suggests that patients with PD do not experience higher rates of acute postoperative complications when undergoing 1-level cervical spine surgery.
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Our aim of this study was to identify risk factors and develop a prediction model for unplanned neurological intensive care unit (NICU) events after elective infratentorial brain tumor resection in order to propose an individualized admission to the NICU tailored to patient needs. ⋯ Several patient and operative characteristics are associated with a greater likelihood of the occurrence of unplanned NICU events. In the future, we may be able to provide better help for the resource allocation of NICUs according to these risk factors and prediction models.