Temporal Trends in Orthopaedic Scientific Publishing Before and After the Release of ChatGPT: A Bibliometric Analysis

Abstract

PURPOSE: This study aimed to assess bibliometric trends in orthopaedic research before and after the public release of ChatGPT. METHODS: A bibliometric analysis was conducted using PubMed data from January 2021 to December 2025, encompassing articles from ten high-impact orthopaedic journals. A seven-month washout period (December 2022 – June 2023) was applied to account for the typical lag between manuscript preparation and publication. Trends in daily publication frequency, number of co-authors per article, sentence length, lexical diversity, and sentiment were compared between the pre-ChatGPT period (January 2021 – June 2023) and the post-adoption period (July 2023 – December 2025). RESULTS: A total of 21,524 articles were analysed (10,403 before; 11,121 after). The mean number of publications per day increased from 11.42 ± 7.32 to 12.15 ± 8.26 (p = 0.044). After adjusting for monthly seasonality, the difference remained significant (adjusted increase: +1.15 publications/day; p = 0.002). The mean number of authors per article rose from 5.94 ± 3.95 to 6.28 ± 4.39 (p < 0.001). The average sentence length decreased from 14.81 ± 5.08 to 14.52 ± 5.06 words per sentence (p < 0.001), while lexical diversity increased (Type-Token Ratio: 0.51 ± 0.07 to 0.52 ± 0.07; p < 0.001). Mean sentiment scores rose from 3.28 ± 3.27 to 3.64 ± 3.47 (p < 0.001). CONCLUSION: Following the public release of ChatGPT, orthopaedic publications have exhibited a measurable rise in daily output, modest increases in co-authorship, and subtle changes in linguistic style. These temporal associations, while not evidence of causality, correspond with the widespread adoption of AI-assisted writing tools and warrant ongoing evaluation.

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