There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines. Cite this article:
Periprosthetic femoral fractures are increasing in incidence, and typically occur in frail elderly patients. They are similar to pathological fractures in many ways. The aims of treatment are the same, including 'getting it right first time' with a single operation, which allows immediate unrestricted weightbearing, with a low risk of complications, and one that avoids the creation of stress risers locally that may predispose to further peri-implant fracture. The surgical approach to these fractures, the associated soft-tissue handling, and exposure of the fracture are key elements in minimizing the high rate of complications. This annotation describes the approaches to the femur that can be used to facilitate the surgical management of peri- and interprosthetic fractures of the femur at all levels using either modern methods of fixation or revision arthroplasty. Cite this article:
