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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The Cobb angle is a standard measurement to qualify and track the progression of scoliosis. However, the Cobb angle has high inter- and intra-observer variability. Consequently, its measurement varies with vertebrae and may even differ when the same vertebra is measured. Therefore, it is not constant and differs with measurements. This study aimed to develop a deep learning model that automatically measures the Cobb angle. The deep learning model for identifying vertebrae on spine radiographs was developed. ⋯ The authors believe the model will be useful in clinical practice by relieving clinicians of the burden of having to manually compute the Cobb angle. Further studies are needed to enhance the accuracy and versatility of this deep learning model.
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Integrating machine learning models into electronic medical record systems can greatly enhance decision-making, patient outcomes, and value-based care in healthcare systems. Challenges related to data accessibility, privacy, and sharing can impede the development and deployment of effective predictive models in spine surgery. Federated learning (FL) offers a decentralized approach to machine learning that allows local model training while preserving data privacy, making it well-suited for healthcare settings. Our objective was to describe federated learning solutions for enhanced predictive modeling in spine surgery. ⋯ Federated learning shows great promise in revolutionizing predictive modeling in spine surgery by addressing the challenges of data privacy, accessibility, and sharing. The applications of FL in telesurgery, AI-based predictive models, and medical image segmentation have demonstrated their potential to enhance patient outcomes and value-based care.
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This retropective multicentric study aims to investigate the clinical applicability of the NSE score in the elderly, to verify the role of this tool as an easy help for decision making also for this class of patients. ⋯ Far from the need or the aim to build dogmatic algorithms, the goal of preserving a proper performance status plays a key role in a modern oncological management: functional outcomes of the multicentric study group showed that the NSE score represents a reliable tool to establish the need for surgery also for elderly patients.