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. To identify the minimum set of outcomes that should be collected in clinical practice and reported in research related to the care of children with idiopathic congenital talipes equinovarus (CTEV). Methods. A list of outcome measurement tools (OMTs) was obtained from the literature through a systematic review. Further outcomes were collected from patients and families through a questionnaire and interview process. The combined list, as well as the appropriate follow-up timepoint, was rated for importance in a two-round Delphi process that included an international group of
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,
Aims. The aim of this study was to assess the current trends in the estimation of survival and the preferred forms of treatment of pathological fractures among national and international general and oncological
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
Aim. The coronavirus disease 2019 (COVID-19) pandemic presents significant challenges to healthcare systems globally.
Aims. This study assesses patient barriers to successful telemedicine care in orthopaedic practices in a large academic practice in the COVID-19 era. Methods. In all, 381 patients scheduled for telemedicine visits with three