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AI versus the spinal surgeons in the management of controversial spinal surgery scenarios

Lookup NU author(s): Andrew Bowey

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Abstract

© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. Aims: The use of artificial intelligence (AI) in spinal surgery is expanding, yet its ability to match the diagnostic and treatment planning accuracy of human surgeons remains unclear. This study aims to compare the performance of AI models—ChatGPT-3.5, ChatGPT-4, and Google Bard—with that of experienced spinal surgeons in controversial spinal scenarios. Methods: A questionnaire comprising 54 questions was presented to ten spinal surgeons on two occasions, four weeks apart, to assess consistency. The same questionnaire was also presented to ChatGPT-3.5, ChatGPT-4, and Google Bard, each generating five responses per question. Responses were analyzed for consistency and agreement with human surgeons using Kappa values. Thematic analysis of AI responses identified common themes and evaluated the depth and accuracy of AI recommendations. Results: Test-retest reliability among surgeons showed Kappa values from 0.535 to 1.00, indicating moderate to perfect reliability. Inter-rater agreement between surgeons and AI models was generally low, with nonsignificant p-values. Fair agreements were observed between surgeons’ second occasion responses and ChatGPT-3.5 (Kappa = 0.24) and ChatGPT-4 (Kappa = 0.27). AI responses were detailed and structured, while surgeons provided more concise answers. Conclusions: AI large language models are not yet suitable for complex spinal surgery decisions but hold potential for preliminary information gathering and emergency triage. Legal, ethical, and accuracy issues must be addressed before AI can be reliably integrated into clinical practice.

Publication metadata

Author(s): Mehmet S, Elmarawany M, Harding I, Bowey A, Andrews J, Chan D, Jayasuriya R, Srinivas S, Tomlinson J, Bayley E, Grevitt M, James S, Jones A, McCarthy MJH

Publication type: Article

Publication status: Published

Journal: European Spine Journal

Year: 2025

Pages: Epub ahead of print

Online publication date: 03/04/2025

Acceptance date: 25/03/2025

ISSN (print): 0940-6719

ISSN (electronic): 1432-0932

Publisher: Springer Nature

URL: https://doi.org/10.1007/s00586-025-08825-w

DOI: 10.1007/s00586-025-08825-w

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