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Case: We report a case of a lesser tuberosity avulsion fracture in a 14-year-old adolescent boy who presented to Orthopaedic Urgent Care where he was promptly diagnosed after magnetic resonance imaging. The patient was successfully treated with an open transosseous equivalent suture repair 3 weeks after initial injury., Conclusion: The purpose of this case report was to advance the understanding of these injuries, enable appropriate diagnosis and treatment, and optimize patient's shoulder outcomes and return to sport., Competing Interests: Disclosure: The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article (http://links.lww.com/JBJSCC/C477)., (Copyright © 2024 by The Journal of Bone and Joint Surgery, Incorporated.)

Background: The purpose of this study was to assess the effectiveness of an Artificial Intelligence-Large Language Model (AI-LLM) at improving the readability of hand and wrist radiology reports., Methods: The radiology reports of 100 hand and/or wrist radiographs, 100 hand and/or wrist computed tomography (CT) scans, and 100 hand and/or wrist magnetic resonance imaging (MRI) scans were extracted. The following prompt command was inserted into the AI-LLM: "Explain this radiology report to a patient in layman's terms in the second person: [Report Text]." The report length, Flesch reading ease score (FRES), and Flesch-Kincaid reading level (FKRL) were calculated for the original radiology report and the AI-LLM-generated report. The accuracy of the AI-LLM report was assessed via a 5-point Likert scale. Any "hallucination" produced by the AI-LLM-generated report was recorded., Results: There was a statistically significant improvement in mean FRES scores and FKRL scores in the AI-LLM-generated radiograph report, CT report, and MRI report. For all AI-LLM-generated reports, the mean reading level improved to below an eighth-grade reading level. The mean Likert score for the AI-LLM-generated radiograph report, CT report, and MRI report was 4.1 ± 0.6, 3.9 ± 0.6, and 3.9 ± 0.7, respectively. The hallucination rate in the AI-LLM-generated radiograph report, CT report, and MRI report was 3%, 6%, and 6%, respectively., Conclusions: This study demonstrates that AI-LLM effectively improves the readability of hand and wrist radiology reports, underscoring the potential application of AI-LLM as a promising and innovative patient-centric strategy to improve patient comprehension of their imaging reports. Level of Evidence: IV., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: John G. Kennedy is a consultant for Arteriocyte, In2Bones, and Arthrex. John G. Kennedy receives financial support from the Ohnell Family Foundation, Mr Winston Fisher, and Ms. Tatiana Rybak.

Background: Total shoulder arthroplasty (TSA) with a nonspherical humeral head component and inlay glenoid is a bone preserving treatment for glenohumeral arthritis. This study aims to describe minimum two year patient reported outcomes, patient acceptable symptomatic state (PASS) achievement, and complications following TSA with this prosthesis., Methods: A retrospective review of patients undergoing TSA with nonspherical humeral head and inlay glenoid was performed. Outcomes included Single Assessment Numeric Evaluation (SANE) scores, American Shoulder and Elbow Surgeons (ASES) scores, and complications. SANE and ASES scores were compared to established PASS threshold values to determine PASS achievement., Results: 56 TSA in 53 patients were identified. The mean age was 64.5 years, 64% were male, and mean follow-up was 29.2 ± 4.9 months (24.0-42.8). Two complications (3.6%) were observed: one subscapularis tear requiring revision to reverse TSA and one traumatic minimally displaced greater tuberosity fracture successfully treated nonoperatively. The mean SANE score was 84.3 ± 16.9 (40-100) and 77% of patients surpassed the PASS threshold of 75.5. The mean ASES score was 85.3 ± 15.7 (40-100) and 77% of patients surpassed the PASS threshold of 76., Discussion: Patients undergoing TSA with a nonspherical humeral head and inlay glenoid demonstrated high PASS achievement rates and few complications at short-term follow-up., Competing Interests: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JPZ reports a relationship with Arthrosurface that includes speaking and lecture fees, unrelated to this submitted work. All other authors, their immediate families, and any research foundation with which they are affiliated did not receive any financial payments or other benefits from any commercial entity related to the subject of this article. There was no funding source for this study., (© The Author(s) 2024.)

Total shoulder arthroplasty with a humeral head resurfacing (HHR) component and an inlay glenoid (OVOMotion; Arthrosurface) is a successful treatment option for patients with advanced glenohumeral arthritis, an intact rotator cuff, and adequate proximal humeral bone stock. In patients with poor proximal humeral bone, historically stemmed humeral components have been used instead of HHR. However, strategies can be used to successfully optimize HHR implant fixation in suboptimal bone without converting to stemmed implants or in surgical centers where stemmed prostheses are not available. This Technical Note describes 3 techniques-upsizing the humeral taper post, using humeral autograft, and cementation-to improve humeral implant fixation in patients with suboptimal bone stock when using the Arthrosurface OVOMotion implant., (© 2024 The Authors.)