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Aims: Optimal glenoid positioning in reverse shoulder arthroplasty (RSA) is crucial to provide impingement-free range of motion (ROM). Lateralization and inclination correction are not yet systematically used. Using planning software, we simulated the most used glenoid implant positions. The primary goal was to determine the configuration that delivers the best theoretical impingement-free ROM. Methods: With the use of a 3D planning software (Blueprint) for RSA, 41 shoulders in 41 consecutive patients (17 males and 24 females; means age 73 years (SD 7)) undergoing RSA were planned. For the same anteroposterior positioning and retroversion of the glenoid implant, four different glenoid baseplate configurations were used on each shoulder to compare ROM: 1) no correction of the RSA angle and no lateralization (C-L-); 2) correction of the RSA angle with medialization by inferior reaming (C+M+); 3) correction of the RSA angle without lateralization by superior compensation (C+L-); and 4) correction of the RSA angle and additional lateralization (C+L+). The same humeral inlay implant and positioning were used on the humeral side for the four different glenoid configurations with a 3 mm symmetric 135° inclined polyethylene liner. Results: The configuration with lateralization and correction of the RSA angle (C+L+) led to better ROM in flexion, extension, adduction, and external rotation (p ≤ 0.001). Only internal rotation was not significantly different between groups (p = 0.388). The configuration where correction of the inclination was done by medialization (C+M+) led to the worst ROM in adduction, extension, abduction, flexion, and external rotation of the shoulder. Conclusion: Our software study shows that, when using a 135° inlay reversed humeral implant, correcting glenoid inclination (RSA angle 0°) and lateralizing the glenoid component by using an angled bony or metallic augment of 8 to 10 mm provides optimal impingement-free ROM. Cite this article: Bone Jt Open 2024;5(10):851–857.

BackgroundLarge language models (LLMs) have raised both interest and concern in the academic community. They offer the potential for automating literature search and synthesis for systematic reviews but raise concerns regarding their reliability, as the tendency to generate unsupported (hallucinated) content persist. ObjectiveThe aim of the study is to assess the performance of LLMs such as ChatGPT and Bard (subsequently rebranded Gemini) to produce references in the context of scientific writing. MethodsThe performance of ChatGPT and Bard in replicating the results of human-conducted systematic reviews was assessed. Using systematic reviews pertaining to shoulder rotator cuff pathology, these LLMs were tested by providing the same inclusion criteria and comparing the results with original systematic review references, serving as gold standards. The study used 3 key performance metrics: recall, precision, and F1-score, alongside the hallucination rate. Papers were considered “hallucinated” if any 2 of the following information were wrong: title, first author, or year of publication. ResultsIn total, 11 systematic reviews across 4 fields yielded 33 prompts to LLMs (3 LLMs×11 reviews), with 471 references analyzed. Precision rates for GPT-3.5, GPT-4, and Bard were 9.4% (13/139), 13.4% (16/119), and 0% (0/104) respectively (P

Background: The Neer classification is among the most widely used systems to describe proximal humerus fractures (PHF) despite the poor interobserver agreement. The purpose of this study was to verify whether or not blinded shoulder surgeons and trainees agree with the authors of articles published in the highest impact-factor orthopedic journals. Methods: All articles regarding PHF published between 2017 and 2019 in the top 10 orthopedic journals as rated by impact factor were searched. Articles were included if the authors used the Neer classification to describe at least 1 PHF in the figures. Figures were extracted without the legend, and X-rays ± computed tomography scan images were included when available. An international survey was conducted among 138 shoulder surgeons who were asked to record the Neer classification for each de-identified radiograph in the publications. The type of fracture mentioned in the legend of the published figure was considered as the gold standard. Results: Survey participants agreed with the published article authors in 55% of cases overall (range 6%-96%, n = 35). The most common response disagreed with the article authors in 13 cases (37%), underestimating the number of parts in 11 of 13 cases. The interobserver agreement between the 138 responders was fair (k = 0.296). There was an association between the percentage of concordant answers and greater experience (number of years of shoulder surgery practice) of the responders (P = .0023). The number of parts, the number or type of available imaging modalities, and the geographic origin of participants did not influence the agreement between responders and authors. Discussion: In more than one-third of cases, specialized shoulder surgeons disagree with article authors when interpreting the Neer classification of de-identified images of PHF in published manuscripts. Morphologic classification of PHF as the sole basis for treatment algorithms and surgical success should be scrutinized.