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    Artificial intelligence as author: Can scientific reviewers recognize GPT-4o-generated manuscripts?
    (W B SAUNDERS CO-ELSEVIER INC, 2025) Öztürk, A; Karahan, AT; Günay, S; Erdal, AS; Komut, S; Komut, E; Yiğit, Y
    Introduction: Chat Generative Pre-Trained Transformer (ChatGPT) is a natural language processing model. It can be argued that ChatGPT has recently begun to assume the role of a technological assistant capable of supporting academics in the process of scientific writing. ChatGPT may contribute to the spread of incorrect or incomplete information within academic literature, leading to conceptual confusion and potential academic misconduct. The aim of this study is to determine whether a scientific article entirely generated by an AI application such as ChatGPT can be detected by an academic journal editor or peer reviewer. Methods: This study was conducted between November 1, 2024, and December 1, 2024. GPT-4o, was utilized in this study. ChatGPT was instructed to write a scientific article focused on predicting mortality and return of spontaneous circulation (ROSC) in OHCA cases. The manuscript written by ChatGPT-4o was sent to 14 different reviewers who had previously served as reviewers or editors. The reviewers were asked to evaluate the manuscript as if they were an SCI-E journal editor or peer reviewer. The reviewers were informed that the article had been written by ChatGPT and were asked whether they had identified this during their review. Results: Among the reviewers, 42.9 % (n = 6) decided to reject the manuscript at the editorial stage, whereas another 42.9% (n = 6) opted to forward it to a peer reviewer. During the peer review stage, 42.9 % (n = 6) of the reviewers recommended rejection, while 28.6 % (n = 4) suggested major revisions. 78.6 % (n = 11) of the reviewers did not realize that the manuscript had been generated by an artificial intelligence model. Conclusion: The findings of our study highlight the necessity for journal editors and peer reviewers to be wellinformed about ChatGPT and to develop systems capable of identifying whether a manuscript has been written by a human or generated by artificial intelligence. (c) 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
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    Diagnostic accuracy and potential triage utility of the Shetty test in foot and ankle trauma: a cross-sectional study
    (Tubitak Scientific & Technological Research Council Turkey, 2025) Doğan, B; Komut, S; Komut, E; Kavak, N; Güneş, O; Karahan, AT
    Background/aim: Foot and ankle trauma represents a common reason for emergency department visits. While the majority of cases involve soft tissue injuries, radiographic imaging is frequently overutilized due to concerns about missed fractures, leading to increased costs and emergency department crowding. The Shetty test, a recently introduced clinical decision rule, may serve as a simpler alternative to established tools such as the Ottawa ankle rules. This study aimed to assess the diagnostic accuracy of the Shetty test and its potential role as a supportive tool within existing triage systems for patients presenting with foot and ankle trauma. Materials and methods: In this cross-sectional study, 229 adult patients with isolated foot or ankle trauma were evaluated in the emergency department. All participants underwent the Shetty test and standard radiographic imaging. The Shetty test was performed by trained emergency physicians prior to imaging; a positive result was defined as an inability to apply downward pressure due to pain. Diagnostic accuracy metrics-including sensitivity, specificity, positive predictive value, and negative predictive value-were calculated using radiographic findings as the reference standard. Results: Fractures were identified in 25.3% of cases. The Shetty test demonstrated a sensitivity of 77.6%, specificity of 60.8%, positive predictive value of 40.2%, and a high negative predictive value of 88.9%. Among patients with confirmed fractures, 77.6% had a positive test result. The test performed best in ruling out displaced and incomplete fractures, and results showed significant correlation with both physical findings and imaging outcomes. Conclusion: The Shetty test exhibited moderate sensitivity and specificity, alongside a high negative predictive value, supporting its use as a reliable rule-out tool for foot and ankle fractures. Its simplicity, ease of application, and diagnostic potential make it a promising triage adjunct to optimize emergency department resource use. Prospective multicenter validation is warranted before broad clinical adoption.