The Bone & Joint Journal has published several consensus statements in recent years, many of which have positively influenced clinical practice and policy. 1-13. However, even the most valued consensus statements have limitations, and all ultimately represent Level V evidence. Consensus studies add greatest value where higher-order evidence to aid decision making is ambiguous or lacking. In all settings, care must be taken to critically appraise standards of methodology, with particular attention to potential biases that may influence the conclusions which are drawn. Cite this article: Bone Joint J 2023;105-B(4):343–346

Chondrosarcoma is the second most common surgically treated primary bone sarcoma. Despite a large number of scientific papers in the literature, there is still significant controversy about diagnostics, treatment of the primary tumour, subtypes, and complications. Therefore, consensus on its day-to-day treatment decisions is needed. In January 2024, the Birmingham Orthopaedic Oncology Meeting (BOOM) attempted to gain global consensus from 300 delegates from over 50 countries. The meeting focused on these critical areas and aimed to generate consensus statements based on evidence amalgamation and expert opinion from diverse geographical regions. In parallel, periprosthetic joint infection (PJI) in oncological reconstructions poses unique challenges due to factors such as adjuvant treatments, large exposures, and the complexity of surgery. The meeting debated two-stage revisions, antibiotic prophylaxis, managing acute PJI in patients undergoing chemotherapy, and defining the best strategies for wound management and allograft reconstruction. The objectives of the meeting extended beyond resolving immediate controversies. It sought to foster global collaboration among specialists attending the meeting, and to encourage future research projects to address unsolved dilemmas. By highlighting areas of disagreement and promoting collaborative research endeavours, this initiative aims to enhance treatment standards and potentially improve outcomes for patients globally. This paper sets out some of the controversies and questions that were debated in the meeting. Cite this article: Bone Joint J 2024;106-B(5):425–429

Salter-Harris II fractures of the distal tibia affect children frequently, and when they are displaced present a treatment dilemma. Treatment primarily aims to restore alignment and prevent premature physeal closure, as this can lead to angular deformity, limb length difference, or both. Current literature is of poor methodological quality and is contradictory as to whether conservative or surgical management is superior in avoiding complications and adverse outcomes. A state of clinical equipoise exists regarding whether displaced distal tibial Salter-Harris II fractures in children should be treated with surgery to achieve anatomical reduction, or whether cast treatment alone will lead to a satisfactory outcome. Systematic review and meta-analysis has concluded that high-quality prospective multicentre research is needed to answer this question. The Outcomes of Displaced Distal tibial fractures: Surgery Or Casts in KidS (ODD SOCKS) trial, funded by the National Institute for Health and Care Research, aims to provide this high-quality research in order to answer this question, which has been identified as a top-five research priority by the British Society for Children’s Orthopaedic Surgery.

Cite this article: Bone Joint J 2023;105-B(5):471–473.

Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.