Aims. Machine learning (ML) holds significant promise in optimizing various aspects of total shoulder arthroplasty (TSA), potentially improving patient outcomes and enhancing surgical decision-making. The aim of this systematic review was to identify ML algorithms and evaluate their effectiveness, including those for predicting clinical outcomes and those used in image analysis. Methods. We searched the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases for studies applying ML algorithms in TSA. The analysis focused on dataset characteristics, relevant subspecialties, specific ML algorithms used, and their performance outcomes. Results. Following the final screening process, 25 articles satisfied the eligibility criteria for our review. Of these, 60% focused on tabular data while the remaining 40% analyzed image data. Among them, 16 studies were dedicated to developing new models and nine used transfer learning to leverage existing pretrained models. Additionally, three of these models underwent external validation to confirm their reliability and effectiveness. Conclusion. ML algorithms used in TSA demonstrated fair to good performance, as evidenced by the reported metrics. Integrating these models into daily clinical practice could revolutionize TSA, enhancing both surgical precision and patient outcome predictions. Despite their potential, the lack of transparency and generalizability in many current models poses a significant challenge, limiting their clinical utility. Future research should prioritize addressing these limitations to truly propel the field forward and maximize the benefits of ML in enhancing patient care. Cite this article: Bone Jt Open 2025;6(2):126–134

Aims. Posterior malleolar (PM) fractures are commonly associated with ankle fractures, pilon fractures, and to a lesser extent tibial shaft fractures. The tibialis posterior (TP) tendon entrapment is a rare complication associated with PM fractures. If undiagnosed, TP entrapment is associated with complications, ranging from reduced range of ankle movement to instability and pes planus deformities, which require further surgeries including radical treatments such as arthrodesis. Methods. The inclusion criteria applied in PubMed, Scopus, and Medline database searches were: all adult studies published between 2012 and 2022; and studies written in English. Outcome of TP entrapment in patients with ankle injuries was assessed by two reviewers independently. Results. Four retrospective studies and eight case reports were accepted in this systematic review. Collectively there were 489 Pilon fractures, 77 of which presented with TP entrapment (15.75%). There were 28 trimalleolar fractures, 12 of which presented with TP entrapment (42.86%). All the case report studies reported inability to reduce the fractures at initial presentation. The diagnosis of TP entrapment was made in the early period in two (25%) cases, and delayed diagnosis in six (75%) cases reported. Using modified Clavien-Dindo complication classification, 60 (67%) of the injuries reported grade IIIa complications and 29 (33%) grade IIIb complications. Conclusion. TP tendon was the commonest tendon injury associated with pilon fracture and, to a lesser extent, trimalleolar ankle fracture. Early identification using a clinical suspicion and CT imaging could lead to early management of TP entrapment in these injuries, which could lead to better patient outcomes and reduced morbidity. Cite this article: Bone Jt Open 2024;5(3):252–259

Aims. Recurrent dislocation is both a cause and consequence of glenoid bone loss, and the extent of the bony defect is an indicator guiding operative intervention. Literature suggests that loss greater than 25% requires glenoid reconstruction. Measuring bone loss is controversial; studies use different methods to determine this, with no clear evidence of reproducibility. A systematic review was performed to identify existing CT-based methods of quantifying glenoid bone loss and establish their reliability and reproducibility. Methods. A Preferred Reporting Items for Systematic reviews and Meta-Analyses-compliant systematic review of conventional and grey literature was performed. Results. A total of 25 studies were initially eligible. Following screening, nine papers were included for review. Main themes identified compared 2D and 3D imaging, as well as linear- compared with area-based techniques. Heterogenous data were acquired, and therefore no meta-analysis was performed. Conclusion. No ideal CT-based method is demonstrated in the current literature, however evidence suggests that surface area methods are more reproducible and lead to fewer over-estimations of bone loss, provided the views used are standardized. A prospective imaging trial is required to provide a more definitive answer to this research question. Cite this article: Bone Jt Open 2022;3(2):114–122

Aims

Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.

Aims

Robotic-assisted unicompartmental knee arthroplasty (R-UKA) has been proposed as an approach to improve the results of the conventional manual UKA (C-UKA). The aim of this meta-analysis was to analyze the studies comparing R-UKA and C-UKA in terms of clinical outcomes, radiological results, operating time, complications, and revisions.

Aims

To systematically review the predominant complication rates and changes to patient-reported outcome measures (PROMs) following osteochondral allograft (OCA) transplantation for shoulder instability.

Background

Due to the overwhelming demand for trauma services, resulting from increasing emergency department attendances over the past decade, virtual fracture clinics (VFCs) have become the fashion to keep up with the demand and help comply with the BOA Standards for Trauma and Orthopaedics (BOAST) guidelines. In this article, we perform a systematic review asking, “How useful are VFCs?”, and what injuries and conditions can be treated safely and effectively, to help decrease patient face to face consultations. Our primary outcomes were patient satisfaction, clinical efficiency and cost analysis, and clinical outcomes.