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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Deep learning (DL) algorithms can be used for automated analysis of medical imaging. The aim of this study was to assess the accuracy of an innovative, fully automated DL algorithm for analysis of sagittal balance in adult spinal deformity (ASD). ⋯ This is the first study evaluating a complete automated DL algorithm for analysis of sagittal balance with high accuracy for all evaluated parameters. The excellent accuracy in the challenging pathology of ASD with long construct instrumentation demonstrates the eligibility and possibility for implementation in clinical routine.
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Comparative Study
ChatGPT versus NASS clinical guidelines for degenerative spondylolisthesis: a comparative analysis.
Clinical guidelines, developed in concordance with the literature, are often used to guide surgeons' clinical decision making. Recent advancements of large language models and artificial intelligence (AI) in the medical field come with exciting potential. OpenAI's generative AI model, known as ChatGPT, can quickly synthesize information and generate responses grounded in medical literature, which may prove to be a useful tool in clinical decision-making for spine care. The current literature has yet to investigate the ability of ChatGPT to assist clinical decision making with regard to degenerative spondylolisthesis. ⋯ This study sheds light on the duality of LLM applications within clinical settings: one of accuracy and utility in some contexts versus inaccuracy and risk in others. ChatGPT was concordant for most clinical questions NASS offered recommendations for. However, for questions NASS did not offer best practices, ChatGPT generated answers that were either too general or inconsistent with the literature, and even fabricated data/citations. Thus, clinicians should exercise extreme caution when attempting to consult ChatGPT for clinical recommendations, taking care to ensure its reliability within the context of recent literature.
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Comparative Study Observational Study
Fusion versus decompression alone for lumbar degenerative spondylolisthesis and spinal stenosis: a target trial emulation with index trial benchmarking.
The value of adding fusion to decompression surgery for lumbar degenerative spondylolisthesis and spinal canal stenosis remains debated. Therefore, the comparative effectiveness and selected healthcare resource utilization of patients undergoing decompression with or without fusion surgery at 3 years follow-up was assessed. ⋯ Decompression alone should be considered the primary option for patients with lumbar degenerative spondylolisthesis and spinal stenosis.
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The spinopelvic reconstruction poses significant challenges following total sacrectomy in patients with malignant or aggressive benign bone tumours encompassing the entire sacrum. In this study, we aim to assess the functional outcomes and complications of an integrated 3D-printed sacral endoprostheses featuring a self-stabilizing design, eliminating the requirement for supplemental fixation. ⋯ The utilization of 3D-printed self-stabilizing endoprosthesis proved to be a viable approach, yielding satisfactory short-term outcomes in patients undergoing total sacral reconstruction without supplemental fixation.
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To develop a deep learning-based cascaded HRNet model, in order to automatically measure X-ray imaging parameters of lumbar sagittal curvature and to evaluate its prediction performance. ⋯ The cascaded HRNet model based on deep learning algorithm could accurately identify the sagittal curvature-related landmarks on lateral lumbar DR images and automatically measure the relevant parameters, which is of great significance in clinical application.