European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
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Review Meta Analysis
Are combined conservative interventions effective in reducing pain, disability and/or global rating of pain in people with sciatica with known neuropathic pain mechanisms?
National Clinical Guidelines recommend an integrated combination of conservative management strategies for sciatica. However, the efficacy of such combinations have not been established. The purpose of this systemic review with meta-analysis was to determine the efficacy of combined conservative (non-pharmacological) compared to single interventions for people with sciatica with a confirmed neuropathic mechanism. ⋯ There are few studies that have combined conservative (non-pharmacological) interventions for the management of sciatica with a neuropathic component pain mechanism, as recommended by National Clinical Guidelines. This review indicates that combining conservative (no-pharmacological) management strategies appeared more effective than single interventions for the outcomes of low back pain in the short and long term, and for disability in the short term, but not for leg pain at any time point. The overall low certainty of evidence, suggests that future studies with more robust methodologies are needed.
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Giant Tarlov cysts (GTCs) are perineural cysts and their presacral intrapelvic extension are extremely rare entities. We present a case of GTC with intrapelvic extension who has preoperative Magnetic Resonance Imaging (MRI) follow-ups of 12 years, and we demonstrate the annual growth rate and the time-size correlation of a GTC. ⋯ When the time-size correlation is observed, it becomes evident that the GTSs' growing speed increases over the years because of minimal resistance in the intrapelvic cavity. Early surgery may be considered to prevent rapid growth in the intrapelvic cavity and to reduce possible complications of the giant cyst.
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This study aimed to develop and validate a machine learning (ML) model to predict high-grade heterotopic ossification (HO) following Anterior cervical disc replacement (ACDR). ⋯ Through an ML approach, the model identified risk factors and predicted development of high grade HO following ACDR with good discrimination and overall performance. By addressing the shortcomings of traditional statistics and adopting a new logical approach, ML techniques can support discovery, clinical decision-making, and intraoperative techniques better.