World Neurosurg
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The purpose of this study was to explore the diagnostic value of convolutional neural networks (CNNs) in middle cerebral artery (MCA) stenosis by analyzing transcranial Doppler (TCD) images. ⋯ The diagnostic value of CNNs for MCA stenosis based on TCD images paralleled that of manual measurements. CNNs could be used as an auxiliary diagnostic tool to improve the diagnosis of MCA stenosis.
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It is well accepted that randomized controlled trials provide the greatest quality of evidence about effectiveness and safety of new interventions. In neurosurgery, randomized controlled trials face challenges, with their use remaining relatively low compared with other clinical areas. Adaptive designs have emerged as a method for improving the efficiency and patient benefit of trials. They allow modifications to the trial design to be made as patient outcome data are collected. The benefit they provide is highly variable, predominantly governed by the time taken to observe the primary endpoint compared with the planned recruitment rate. They also face challenges in design, conduct, and reporting. ⋯ Adaptive designs may provide benefits to neurosurgery trials and should be considered for use more widely. Use of some types of adaptive design, such as multiarm multistage, may further increase the number of interventions that can be tested with limited patient and financial resources.
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From a pathophysiological point of view, early neurosurgical treatment seems essential to prevent secondary brain injury and has been stated as the "time-is-brain" concept. However, the question immediately rises: "Is there an optimal time window for acute intracranial neurosurgical interventions?" In neurosurgery, treatment modality has been studied far more extensively than timing to surgery ("time-to-surgery"). The majority of acute intracranial neurosurgical interventions are carried out for traumatic brain injury and hemorrhagic or ischemic stroke. ⋯ In acute intracranial neurosurgical interventions, "delayed consent" procedures could play an important role for this field of research. Whether there is an optimal time window for acute intracranial neurosurgical interventions seems difficult to be answered with randomized controlled trials referred to in the current guidelines. Observational designs, such as comparative effectiveness research, and special statistical techniques, may provide a better understanding in the optimal "time-to-surgery."
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Observational Study
Application of Causal Inference Methods in the Analysis of Observational Neurosurgical Data: G-Formula and Marginal Structural Model.
When using observational data to estimate the causal effects of a treatment on clinical outcomes, we need to adjust for confounding. In the presence of time-dependent confounders that are affected by previous treatment, adjustments cannot be made via the conventional regression approach or propensity score-based methods, but requires sophisticated methods called g-methods. We aimed to introduce g-methods to estimate the causal effects of treatment strategies defined by treatment at multiple time points, such as treat 2 days versus treat only day 1 versus never-treat. ⋯ Both g-formula and inverse probability-weighted marginal structural models can correctly estimate the effect of the treatment strategy under 3 identifiability assumptions, which conventional regression analysis cannot. G-methods may assist in estimating the effect of treatment strategy defined by treatment at multiple time points.
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The expansion in treatments for medically refractory epilepsy heightens the importance of identifying patients who are likely to benefit from vagus nerve stimulation (VNS). Here, we identify predictors with a positive VNS response. ⋯ Patients with age at epilepsy onset ≥15 years, left-hand dominance, or baseline seizure frequency <5/month are ideal candidates for VNS.