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:
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.
In this review, we discuss the evidence for patients returning to sport after hip arthroplasty. This includes the choices regarding level of sporting activity and revision or complications, the type of implant, fixation and techniques of implantation, and how these choices relate to health economics. It is apparent that despite its success over six decades, hip arthroplasty has now evolved to accommodate and support ever-increasing patient demands and may therefore face new challenges. Cite this article:
Many aspects of total knee arthroplasty have
changed since its inception. Modern prosthetic design, better fixation techniques,
improved polyethylene wear characteristics and rehabilitation, have
all contributed to a large change in revision rates. Arthroplasty
patients now expect longevity of their prostheses and demand functional
improvement to match. This has led to a re-examination of the long-held
belief that mechanical alignment is instrumental to a successful
outcome and a focus on restoring healthy joint kinematics. A combination
of kinematic restoration and uncemented, adaptable fixation may
hold the key to future advances. Cite this article:
