Browsing by Author "Kaymakoglu, Mehmet"

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Citation - WoS: 9
Citation - Scopus: 11
Can Popular AI Large Language Models Provide Reliable Answers to Frequently Asked Questions About Rotator Cuff Tears
(Elsevier, 2025) Kolac, Ulas Can; Karademir, Orhan Mete; Ayik, Gokhan; Kaymakoglu, Mehmet; Familiari, Filippo; Huri, Gazi
Background: Rotator cuff tears are common upper-extremity injuries that significantly impair shoulder function, leading to pain, reduced range of motion, and a decrease in quality of life. With the increasing reliance on artificial intelligence large language models (AI LLMs) for health information, it is crucial to evaluate the quality and readability of the information provided by these models. Methods: A pool of 50 questions was generated related to rotator cuff tear by querying popular AI LLMs (ChatGPT 3.5, ChatGPT 4, Gemini, and Microsoft CoPilot) and using Google search. After that, responses from the AI LLMs were saved and evaluated. For information quality the DISCERN tool and a Likert Scale was used, for readability the Patient Education Materials Assessment Tool for Printable Materials (PEMAT) Understandability Score and the Flesch-Kincaid Reading Ease Score was used. Two orthopedic surgeons assessed the responses, and discrepancies were resolved by a senior author. Results: Out of 198 answers, the median DISCERN score was 40, with 56.6% considered sufficient. The Likert Scale showed 96% sufficiency. The median PEMAT Understandability score was 83.33, with 77.3% sufficiency, while the Flesch-Kincaid Reading Ease score had a median of 42.05 with 88.9% sufficiency. Overall, 39.8% of the answers were sufficient in both information quality and readability. Differences were found among AI models in DISCERN, Likert, PEMAT Understandability, and Flesch-Kincaid scores. Conclusion: AI LLMs generally cannot offer sufficient information quality and readability. While they are not ready for use in medical field, they show a promising future. There is a necessity for continuous reevaluation of these models due to their rapid evolution. Developing new, comprehensive tools for evaluating medical information quality and readability is crucial for ensuring these models can effectively support patient education. Future research should focus on enhancing readability and consistent information quality to better serve patients. (c) 2024 The Author(s). Published by Elsevier Inc. on behalf of American Shoulder and Elbow Surgeons. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Comparing the Effects of Surgical and Conservative Treatment on Scapular Dyskinesis in Minimally Displaced Midshaft Clavicle Fractures
(Springer, 2026) Aksoy, Taha; Kaymakoglu, Mehmet; Ayik, Gokhan; Ibik, Serkan; Kolac, Ulas Can; Kara, Dilara; Huri, Gazi
Purpose Midshaft clavicle fractures are common and often associated with scapular dyskinesis (ScD), particularly in cases of shortening. While fractures with less than 2 cm shortening are often treated conservatively, emerging evidence suggests that even minor shortening can increase the risk of ScD and impair functional outcomes. This study investigates the impact of surgical versus conservative treatment on ScD and functional recovery. Methods A retrospective analysis of 60 patients with isolated midshaft clavicle fractures was conducted. Patients were categorized into surgical and conservative groups. Fracture shortening was assessed using radiographs, outcomes were assessed using the SICK Scapula Rating Scale, Simple Shoulder Test (SST), American Shoulder and Elbow Surgeons Scale and Visual Analog Scale (VAS). Logistic regression and ROC analysis was applied to identify ScD predictors, and critical shortening threshold. Results ScD was observed in 43.3% of all patients, with 53.6% of the conservative group, and 34.4% of the surgical group; however, the difference was not statistically significant (p = 0.216). Surgical treatment was associated with significantly better SST and VAS scores at the final follow-up (p < 0.05). Logistic regression identified clavicular shortening (p < 0.001) and lower BMI (p = 0.033 - univariate) as significant predictors of ScD. ROC analysis revealed that a shortening threshold of 0.4 cm had a sensitivity of 73.08% and a specificity of 91.18% for predicting ScD (AUC = 0.874, p < 0.001). Conclusion Surgical treatment may reduce residual shortening and lower the prevalence of ScD, indicating a possible benefit in limiting dyskinesis even in minimally displaced fractures. Level of evidence Level III, retrospective comperative study.
Response To the Letter To the Editor Regarding "Can Popular Artificial Intelligence Large Language Models Provide Reliable Answers To Frequently Asked Questions About Rotator Cuff Tears?" -Reply
(Elsevier, 2025) Kolac, Ulas Can; Karademir, Orhan Mete; Ayik, Gokhan; Kaymakoglu, Mehmet; Familiari, Filippo; Huri, Gazi