{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T01:12:54Z","timestamp":1790557974360,"version":"4.1.0"},"reference-count":37,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Orthop Surg (Hong Kong)"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>This study aims to compare the performance of two artificial intelligence (AI) models, ChatGPT-4.0 and DeepSeek-R1, in addressing clinical questions related to degenerative lumbar spinal stenosis (DLSS) using the North American Spine Society (NASS) guidelines as the benchmark.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>15 clinical questions spanning five domains (diagnostic criteria, non-surgical management, surgical indications, perioperative care, and emerging controversies) were designed based on the 2013 NASS evidence-based clinical guidelines for the diagnosis and management of DLSS. Responses from both models were independently evaluated by two board-certified spine surgeons across four metrics: accuracy, completeness, supplementality, and misinformation. Inter-rater reliability was assessed using Cohen\u2019s \u03ba coefficient, while Mann-Whitney U and Chi-square tests were employed to analyze statistical differences between models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      DeepSeek-R1 demonstrated superior performance over ChatGPT-4.0 in accuracy (median score: 3 vs 2,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.009), completeness (2 vs 1,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.010), and supplementality (2 vs 1,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.018). Both models exhibited comparable performance in avoiding misinformation (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.671). DeepSeek-R1 achieved higher inter-rater agreement in accuracy (\u03ba = 0.727 vs 0.615), whereas ChatGPT-4.0 showed stronger consistency in ssupplementality (\u03ba = 0.792 vs 0.762).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>While both AI models demonstrate potential for clinical decision support, DeepSeek-R1 aligns more closely with NASS guidelines. ChatGPT-4.0 excels in providing supplementary insights but exhibits variability in accuracy. These findings underscore the need for domain-specific optimization of AI models to enhance reliability in medical applications.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/10225536251407382","type":"journal-article","created":{"date-parts":[[2025,12,7]],"date-time":"2025-12-07T10:35:57Z","timestamp":1765103757000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Generative AI in degenerative lumbar spinal stenosis care: A NASS guideline-compliant comparative analysis of ChatGPT and DeepSeek"],"prefix":"10.1177","volume":"33","author":[{"given":"Meng","family":"Zhang","sequence":"first","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiameng","family":"Li","sequence":"additional","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaluo","family":"Zhou","sequence":"additional","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiwu","family":"Chen","sequence":"additional","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pan","family":"Wang","sequence":"additional","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Hu","sequence":"additional","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0510-3082","authenticated-orcid":false,"given":"Zhong","family":"Xiang","sequence":"additional","affiliation":[{"name":"The Fourth Hospital of Changsha (Integrated Traditional Chinese and Western Medicine Hospital of Changsha)"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,12,7]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00586-020-06339-1"},{"issue":"1","key":"e_1_3_5_3_2","first-page":"9","article-title":"Degenerative lumbar spinal stenosis","volume":"56","author":"Hennemann S","year":"2021","unstructured":"Hennemann S, de Abreu MR. 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