Aims. Open lower limb fracture is life-changing, resulting in substantial morbidity and resource demand, while inconsistent outcome-reporting hampers systematic review and meta-analysis. A core outcome set establishes consensus among key
Aims. To explore key
Aims. A core outcome set for adult, open lower limb fracture has been established consisting of ‘Walking, gait and mobility’, ‘Being able to return to life roles’, ‘Pain or discomfort’, and ‘Quality of life’. This study aims to identify which outcome measurement instruments (OMIs) should be recommended to measure each core outcome. Methods. A systematic review and quality assessment were conducted to identify existing instruments with evidence of good measurement properties in the open lower limb fracture population for each core outcome. Additionally, shortlisting criteria were developed to identify suitable instruments not validated in the target population. Candidate instruments were presented, discussed, and voted on at a consensus meeting of key
Objectives. The annual incidence of hip fracture is 620 000 in the European Union. The cost of this clinical problem has been estimated at 1.75 million disability-adjusted life years lost, equating to 1.4% of the total healthcare burden in established market economies. Recent guidance from The National Institute for Health and Clinical Excellence (NICE) states that research into the clinical and cost effectiveness of total hip arthroplasty (THA) as a treatment for hip fracture is a priority. We asked the question: can a trial investigating THA for hip fracture currently be delivered in the NHS?. Methods. We performed a contemporaneous process evaluation that provides a context for the interpretation of the findings of WHiTE Two – a randomised study of THA for hip fracture. We developed a mixed methods approach to situate the trial centre within the context of wider United Kingdom clinical practice. We focused on fidelity, implementation, acceptability and feasibility of both the trial processes and interventions to
Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles ( Cite this article:
Open lower limb fracture is a life-changing injury affecting 11.5 per 100,000 adults each year, and causes significant morbidity and resource demand on trauma infrastructures. This study aims to identify what, and how, outcomes have been reported for people following open lower limb fracture over ten years. Systematic literature searches identified all clinical studies reporting outcomes for adults following open lower limb fracture between January 2009 and July 2019. All outcomes and outcome measurement instruments were extracted verbatim. An iterative process was used to group outcome terms under standardized outcome headings categorized using an outcome taxonomy.Aims
Methods
The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
Bone is one of the most highly adaptive tissues in the body, possessing the capability to alter its morphology and function in response to stimuli in its surrounding environment. The ability of bone to sense and convert external mechanical stimuli into a biochemical response, which ultimately alters the phenotype and function of the cell, is described as mechanotransduction. This review aims to describe the fundamental physiology and biomechanisms that occur to induce osteogenic adaptation of a cell following application of a physical stimulus. Considerable developments have been made in recent years in our understanding of how cells orchestrate this complex interplay of processes, and have become the focus of research in osteogenesis. We will discuss current areas of preclinical and clinical research exploring the harnessing of mechanotransductive properties of cells and applying them therapeutically, both in the context of fracture healing and de novo bone formation in situations such as nonunion. Cite this article:
