ChatGPT versus NASS clinical guidelines for degenerative spondylolisthesis: a comparative analysis

Wasil Ahmed, Michael Saturno,Rami Rajjoub,Akiro H. Duey,Bashar Zaidat,Timothy Hoang, Mateo Restrepo Mejia, Zachary S. Gallate, Nancy Shrestha,Justin Tang,Ivan Zapolsky,Jun S. Kim,Samuel K. Cho

European Spine Journal(2024)

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摘要
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. The study aimed to compare ChatGPT’s concordance with the recommendations set forth by The North American Spine Society (NASS) Clinical Guideline for the Diagnosis and Treatment of Degenerative Spondylolisthesis and assess ChatGPT’s accuracy within the context of the most recent literature. ChatGPT-3.5 and 4.0 was prompted with questions from the NASS Clinical Guideline for the Diagnosis and Treatment of Degenerative Spondylolisthesis and graded its recommendations as “concordant” or “nonconcordant” relative to those put forth by NASS. A response was considered “concordant” when ChatGPT generated a recommendation that accurately reproduced all major points made in the NASS recommendation. Any responses with a grading of “nonconcordant” were further stratified into two subcategories: “Insufficient” or “Over-conclusive,” to provide further insight into grading rationale. Responses between GPT-3.5 and 4.0 were compared using Chi-squared tests. ChatGPT-3.5 answered 13 of NASS’s 28 total clinical questions in concordance with NASS’s guidelines (46.4
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关键词
Degenerative spondylolisthesis,Clinical guidelines,Artificial intelligence,Large language models,Spine
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