The aim of this study was to investigate the effects of game-based electromyography (EMG)-biofeedback therapy on swallowing functions and quality of life in patients with post-stroke dysphagia. This prospective, assessor-blind, randomized controlled trial included 33 patients with post-stroke dysphagia. The study group performed the Mendelsohn maneuver and effortful swallow using game-based EMG-biofeedback, while the control group performed the same tasks with only verbal feedback for 30 min across a total of 15 sessions. In addition, both groups received oral motor exercises and thermal-tactile stimulation for equal durations. Patients were evaluated immediately before and after the treatment using clinical swallowing assessments, including the Functional Oral Intake Scale (FOIS), Penetration-Aspiration Scale (PAS), Dysphagia Outcome and Severity Scale (DOSS), and Dysphagia Handicap Index (DHI). Statistically significant improvements were observed in FOIS scores (p = 0.038), PAS-Liquid scores (p = 0.026), and DOSS scores (p = 0.003) in the study group, while no significant changes were noted in the control group. PAS-Semisolid scores improved in both groups (study group, p = 0.002; control group, p = 0.023); however, post-treatment scores were significantly higher in the study group compared to the control group (p = 0.031). Although significant improvements in DHI total, physical, emotional, and functional scores were observed in both groups at the end of treatment (all p < 0.05), post-treatment DHI scores were significantly higher in the study group compared to the control group (all p < 0.05). The addition of game-based EMG-biofeedback to conventional therapy improved clinical and radiological outcomes, as evidenced by improvements in FOIS, PAS-Liquid, and DOSS scores, and led to statistically significant improvements in PAS-Semisolid and DHI scores. In conclusion, the inclusion of game-based EMG-biofeedback therapy in swallowing rehabilitation programs may have a positive impact on treatment outcomes.

Betul Kula, Ahmet Kula, Fatih Bagcier, Bulent Alyanak. Korean J Orthod 2025;55:131-41. https://doi.org/10.4041/kjod24.106

Background: The proliferation of artificial intelligence has led to widespread patient use of large language models (LLMs). Purpose : We sought to characterize LLM responses to questions about piriformis syndrome (PS). Methods : On August 15, 2024, we asked 3 LLMs—ChatGPT-4, Copilot, and Gemini—to respond to the 25 most frequently asked questions about PS, as tracked by Google Trends. We evaluated the accuracy and completeness of the responses according to the Likert scale. We used the Ensuring Quality Information for Patients (EQIP) tool to assess the quality of the responses and assessed readability using Flesch–Kincaid Reading Ease (FKRE) and Flesch–Kincaid Grade Level (FKGL) scores. Results : The mean completeness scores of the responses obtained from ChatGPT, Copilot, and Gemini were 2.8 ± 0.3, 2.2 ± 0.6, and 2.6 ± 0.4, respectively. There was a significant difference in the mean completeness score among LLMs. In pairwise comparisons, ChatGPT and Gemini were superior to Copilot. There was no significant difference between the LLMs in terms of mean accuracy scores. In readability analyses, no significant difference was found in terms of FKRE scores. However, a significant difference was found in FKGL scores. A significant difference between LLMs was identified in the quality analysis performed according to EQIP scores. Conclusion : Although the use of LLMs in healthcare is promising, our findings suggest that these technologies need to be improved to perform better in terms of accuracy, completeness, quality, and readability on PS for a general audience.

Restriction of shoulder movements in frozen shoulder may negatively affect individual's daily living activities. The effect of the virtual reality (VR)-based exercise program, which is an innovative application and has been used in the field of physiotherapy in recent years, is unknown on patients diagnosed with frozen shoulder. This study was conducted to determine the effects of a VR-based exercise program provided to patients with frozen shoulder on their pain, joint motion, and quality of life. In the randomized controlled study, patients were divided into two groups to receive treatment five times a week for four weeks:VR-based exercise (VR group, n = 18) and conventional treatment(control group, n = 18). The data were collected using the VisualAnalog Scale, the Shoulder Pain and Disability Index, and the ShortForm - 36 health Scale. In comparison to the pre-treatment measurements, improvements were observed in pain, joint range of motion, and quality of life in both groups after the treatment (p < .001). The improvement in pain observed in the VR group after the treatment was greater than that observed in the control group (U=-2.064, p= .030). After the treatment, the quality of life in the mental health dimension was better for patients in the VR group (U= -1.979, p= .048). VR-based exercise was an effective method for reducing the pain levels and improving the mental health of patients diagnosed with frozen shoulder.