Publication Name	World Journal of Orthopedics
Manuscript ID	118593
Country	United States

Category	Orthopedics
Manuscript Type	Observational Study
Article Title	Open evidence performs at similar levels compared to current and previous GPT models on orthopedic training and education questions
Manuscript Source	Unsolicited Manuscript
All Author List	Kashif Javid, Alexander Driessche, Colton Clymer, Muhammad J Abbas, Annamarie Pantuso, Lindsay M Maier, Joseph Hoegler, William M Hakeos and Stuart T Guthrie
Funding Agency and Grant Number
Corresponding Author	Kashif Javid, Department of Orthopaedic Surgery, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI 48202, Detroit, MI 48202, United States. kjavid1@hfhs.org
Key Words	Artificial intelligence; Medical education; Orthopedic training; Large language models; Chatbot
Core Tip	We evaluated the performance of contemporary large language models on orthopedic board-style questions, comparing ChatGPT-5 and Open Evidence (OE), with the established GPT-4. Using a standardized orthopedic training exam question set, we found that ChatGPT-5 achieved the highest overall accuracy and consistently outperformed prior models across subspecialties and question formats. OE performed comparably to GPT-4 across multiple fields. All models demonstrated reduced accuracy on image-based questions, highlighting persistent limitations in visual interpretation. We assert that OE is a reputable addition to the tools available to orthopedists. The added benefit of training drawn from peer-reviewed literature adds to its potential value.
Citation	Javid K, Driessche A, Clymer C, Abbas MJ, Pantuso A, Maier LM, Hoegler J, Hakeos WM, Guthrie ST. Open evidence performs at similar levels compared to current and previous GPT models on orthopedic training and education questions. World J Orthop 2026; In press

Received	2026-01-07 05:54
Peer-Review Started	2026-01-07 05:55
First Decision by Editorial Office Director	2026-01-23 08:00
Return for Revision	2026-01-23 08:00
Revised	2026-02-06 02:51
Publication Fee Transferred	2026-02-10 21:35
Second Decision by Editor	2026-03-30 02:34
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-03-30 08:35
Articles in Press	2026-03-30 08:35
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2218-5836 (online)
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Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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