Cited by 117Artificial Intelligence in Healthcare and EducationArtificial Intelligence in HealthcareArtificial Intelligence Applications

Exploring the Potential of ChatGPT as a Supplementary Tool for Providing Orthopaedic Information

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Kaarre, Janina, Feldt, Robert, Keeling, Laura E., Dadoo, Sahil, Zsidai, Bálint, Hughes, Jonathan D., Samuelsson, Kristian, Musahl, Volker·2023·Knee Surgery Sports Traumatology Arthroscopy

Abstract

PURPOSE: To investigate the potential use of large language models (LLMs) in orthopaedics by presenting queries pertinent to anterior cruciate ligament (ACL) surgery to generative pre-trained transformer (ChatGPT, specifically using its GPT-4 model of March 14th 2023). Additionally, this study aimed to evaluate the depth of the LLM's knowledge and investigate its adaptability to different user groups. It was hypothesized that the ChatGPT would be able to adapt to different target groups due to its strong language understanding and processing capabilities. METHODS: ChatGPT was presented with 20 questions and response was requested for two distinct target audiences: patients and non-orthopaedic medical doctors. Two board-certified orthopaedic sports medicine surgeons and two expert orthopaedic sports medicine surgeons independently evaluated the responses generated by ChatGPT. Mean correctness, completeness, and adaptability to the target audiences (patients and non-orthopaedic medical doctors) were determined. A three-point response scale facilitated nuanced assessment. RESULTS: ChatGPT exhibited fair accuracy, with average correctness scores of 1.69 and 1.66 (on a scale from 0, incorrect, 1, partially correct, to 2, correct) for patients and medical doctors, respectively. Three of the 20 questions (15.0%) were deemed incorrect by any of the four orthopaedic sports medicine surgeon assessors. Moreover, overall completeness was calculated to be 1.51 and 1.64 for patients and medical doctors, respectively, while overall adaptiveness was determined to be 1.75 and 1.73 for patients and doctors, respectively. CONCLUSION: Overall, ChatGPT was successful in generating correct responses in approximately 65% of the cases related to ACL surgery. The findings of this study imply that LLMs offer potential as a supplementary tool for acquiring orthopaedic knowledge. However, although ChatGPT can provide guidance and effectively adapt to diverse target audiences, it cannot supplant the expertise of orthopaedic sports medicine surgeons in diagnostic and treatment planning endeavours due to its limited understanding of orthopaedic domains and its potential for erroneous responses. LEVEL OF EVIDENCE: V.

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References 21 · Cited by 117

Authors
Kaarre, J., Feldt, R., Keeling, L. E., Dadoo, S., Zsidai, B., Hughes, J. D., Samuelsson, K., & Musahl, V.
Affiliations
  • University of Pittsburgh (US)
  • Chalmers University of Technology (SE)
  • University of Gothenburg (SE)
  • Sahlgrenska University Hospital (SE)
Corresponding author
Kaarre, Janina
Venue
Knee Surgery Sports Traumatology Arthroscopy
Publisher
Wiley
Published
2023-08-08
Volume
31
Issue
11
Pages
5190-5198
ISSN
  • 0942-2056 (ISSN-L)
  • 1433-7347
OpenAlex
W4385667643
Cited by
117
References
21
Citations by year
2026: 23 · 2025: 43 · 2024: 46 · 2023: 5
FWCI
4.67
Type
journal article
Language
en
Open access
Locations
  • Knee Surgery Sports Traumatology Arthroscopy (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Chalmers Research (Chalmers University of Technology) (submittedVersion, other-oa)
Funders
  • University of Gothenburg
  • Göteborgs Universitet
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
ChatGPT, large language models, anterior cruciate ligament surgery, patient education, medical education, response accuracy, orthopaedic sports medicine, AI-generated medical information
MeSH terms
Orthopedic Surgeons, Humans, Language, Orthopedics, Anterior Cruciate Ligament, Orthopedic Procedures

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