Assessing the performance of GPT-4 in the filed of osteoarthritis and orthopaedic case consultation

Abstract

Abstract Background Large Language Models (LLMs) like GPT-4 demonstrate potential applications in diverse areas, including healthcare and patient education. This study evaluates GPT-4’s competency against osteoarthritis (OA) treatment guidelines from the United States and China and assesses its ability in diagnosing and treating orthopedic diseases. Methods Data sources included OA management guidelines and orthopedic examination case questions. Queries were directed to GPT-4 based on these resources, and its responses were compared with the established guidelines and cases. The accuracy and completeness of GPT-4’s responses were evaluated using Likert scales, while case inquiries were stratified into four tiers of correctness and completeness. Results GPT-4 exhibited strong performance in providing accurate and complete responses to OA management recommendations from both the American and Chinese guidelines, with high Likert scale scores for accuracy and completeness. It demonstrated proficiency in handling clinical cases, making accurate diagnoses, suggesting appropriate tests, and proposing treatment plans. Few errors were noted in specific complex cases. Conclusions GPT-4 exhibits potential as an auxiliary tool in orthopedic clinical practice and patient education, demonstrating high accuracy and completeness in interpreting OA treatment guidelines and analyzing clinical cases. Further validation of its capabilities in real-world clinical scenarios is needed.

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