Aims. Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. Methods. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with
Paediatric bone sarcomas are a dual challenge for
Aims. To review the evidence and reach consensus on recommendations for follow-up after total hip and knee arthroplasty. Methods. A programme of work was conducted, including: a systematic review of the clinical and cost-effectiveness literature; analysis of routine national datasets to identify pre-, peri-, and postoperative predictors of mid-to-late term revision; prospective data analyses from 560 patients to understand how patients present for revision surgery; qualitative interviews with NHS managers and
Aims. Understanding of open fracture management is skewed due to reliance on small-number lower limb, specialist unit reports and large, unfocused registry data collections. To address this, we carried out the Open Fracture Patient Evaluation Nationwide (OPEN) study, and report the demographic details and the initial steps of care for patients admitted with open fractures in the UK. Methods. Any patient admitted to hospital with an open fracture between 1 June 2021 and 30 September 2021 was included, excluding phalanges and isolated hand injuries. Institutional information governance approval was obtained at the lead site and all data entered using Research Electronic Data Capture. Demographic details, injury, fracture classification, and patient dispersal were detailed. Results. In total, 1,175 patients (median age 47 years (interquartile range (IQR) 29 to 65), 61.0% male (n = 717)) were admitted across 51 sites. A total of 546 patients (47.1%) were employed, 5.4% (n = 63) were diabetic, and 28.8% (n = 335) were smokers. In total, 29.0% of patients (n = 341) had more than one injury and 4.8% (n = 56) had two or more open fractures, while 51.3% of fractures (n = 637) occurred in the lower leg. Fractures sustained in vehicle incidents and collisions are common (38.8%; n = 455) and typically seen in younger patients. A simple fall (35.0%; n = 410) is common in older people. Overall, 69.8% (n = 786) of patients were admitted directly to an orthoplastic centre, 23.0% (n = 259) were transferred to an orthoplastic centre after initial management elsewhere, and 7.2% were managed outwith specialist units (n = 81). Conclusion. This study describes the epidemiology of open fractures in the UK. For a decade,