World Neurosurg
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Surgical Strategy and Decision Making in Recurrent Atlanto-Axial Dislocations: The Role of Traction.
To analyse patients with recurrent atlanto-axial dislocation and give a criterion of an ideal patient who can benefit from redo surgery. ⋯ The best candidates who can benefit after redo surgery are the ones who exhibit either clinical and/or radiological improvement on the trial of traction, as the pathological C1-C2 joints are either not fused or have undergone pseudoarthrosis. Those patients who do not exhibit significant clinical or radiological improvement post-trial of traction should not be offered subsequent surgical intervention.
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Anterior column realignment (ACR) is a powerful minimally invasive surgery technique to restore sagittal alignment in adult spinal deformity (ASD). This can accomplish similar segmental lordosis restoration as 3-column osteotomy with less blood loss and comparable complication rates. ACR can be performed at adjacent disease segments in the proximal lumbar spine in revision cases. However, two thirds of physiologic lordosis occurs between L4-S1, and concerns remain about altered lumbar morphology. We evaluated patients who underwent proximal lumbar ACR for iatrogenic flatback deformity. ⋯ Proximal lumbar ACR plus Smith-Peterson osteotomy can achieve sagittal correction with low major complication rates in patients with ASD and prior distal fusion. Differentially increasing proximal lumbar lordosis and lowering lumbar distribution index did not have deleterious effects on radiographic or clinical outcomes. Further work is needed to understand the effect of proximal ACR in the surgical management of ASD.
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Traumatic brain injury (TBI) is a severe neurosurgical emergency and a significant public health concern. Fishing-speargun TBIs are included in nonmissile injuries and have been implicated in only few cases of TBI in the past 68 years, mainly of accidental etiology. ⋯ In summary, the diverse presentation, management, outcomes, and identified influencing factors highlight the complexity of managing speargun-related injuries, and the need for personalized approaches and further research to enhance care protocols.
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Decentralized federated learning (DFL) may serve as a useful framework for machine learning (ML) tasks in multicentered studies, maximizing the use of clinical data without data sharing. We aim to propose the first workflow of DFL for ML tasks in multicentered studies, which can be as powerful as those using centralized data. ⋯ We demonstrate that the DFL workflow without data sharing should be a more appropriate method in ML tasks in multicentered studies. And the DFL workflow should be further exploited in clinical researches in other departments and it can encourage and facilitate multicentered studies.