Aims. The aim of this study was to determine whether fixation, as opposed to revision arthroplasty, can be safely used to treat reducible Vancouver B type fractures in association with a cemented collarless polished tapered femoral stem (the Exeter). Methods. This retrospective cohort study assessed 152 operatively managed consecutive unilateral Vancouver B fractures involving Exeter stems; 130 were managed with open reduction and internal fixation (ORIF) and 22 with revision arthroplasty. Mean follow-up was 6.5 years (SD 2.6; 3.2 to 12.1). The primary outcome measure was revision of at least one component. Kaplan–Meier survival analysis was performed. Regression analysis was used to identify risk factors for revision following ORIF. Secondary outcomes included any reoperation, complications, blood transfusion, length of
Aims. Dual mobility (DM) bearings are an attractive treatment option to obtain hip stability during challenging primary and revision total hip arthroplasty (THA) cases. The purpose of this study was to analyze data submitted to the American Joint Replacement Registry (AJRR) to characterize utilization trends of DM bearings in the USA. Methods. All primary and revision THA procedures reported to AJRR from 2012 to 2018 were analyzed. Patients of all ages were included and subdivided into DM and traditional bearing surface cohorts. Patient demographics, geographical region,
Aims. We aimed to evaluate the long-term outcome of highly cross-linked polyethylene (HXLPE) cemented acetabular components and assess whether any radiolucent lines (RLLs) which arose were progressive. Methods. We retrospectively reviewed 170 patients who underwent 187 total hip arthroplasties at two
Aims. The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs?. Methods. The PubMed and Embase databases were systematically searched from January 2010 to October 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The type of EV, characteristics of the external dataset, and diagnostic performance characteristics on the IV and EV datasets were collected and compared. Quality assessment was conducted using a seven-item checklist based on a modified Methodologic Index for NOn-Randomized Studies instrument (MINORS). Results. Out of 1,349 studies, 36 reported development of a CNN for fracture detection and/or classification. Of these, only four (11%) reported a form of EV. One study used temporal EV, one conducted both temporal and geographical EV, and two used geographical EV. When comparing the CNN’s performance on the IV set versus the EV set, the following were found: AUCs of 0.967 (IV) versus 0.975 (EV), 0.976 (IV) versus 0.985 to 0.992 (EV), 0.93 to 0.96 (IV) versus 0.80 to 0.89 (EV), and F1-scores of 0.856 to 0.863 (IV) versus 0.757 to 0.840 (EV). Conclusion. The number of externally validated CNNs in orthopaedic trauma for fracture recognition is still scarce. This greatly limits the potential for transfer of these CNNs from the developing institute to another
Aims. The COVID-19 pandemic drastically affected elective orthopaedic services globally as routine orthopaedic activity was largely halted to combat this global threat. Our institution (University College London
Aims. To compare rates of serious adverse events in patients undergoing revision knee arthroplasty with consideration of the indication for revision (urgent versus elective indications), and compare these with primary arthroplasty and re-revision arthroplasty. Methods. Patients undergoing primary knee arthroplasty were identified in the national
Aims. Knee arthroplasty surgery is a highly effective treatment for arthritis and disorders of the knee. There are a wide variety of implant brands and types of knee arthroplasty available to surgeons. As a result of a number of highly publicized failures, arthroplasty surgery is highly regulated in the UK and many other countries through national registries, introduced to monitor implant performance, surgeons, and
Aims. This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Methods. Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to
Aims. A multicentre, randomized, clinician-led, pragmatic, parallel-group orthopaedic trial of two surgical procedures was set up to obtain high-quality evidence of effectiveness. However, the trial faced recruitment challenges and struggled to maintain recruitment rates over 30%, although this is not unusual for surgical trials. We conducted a qualitative study with the aim of gathering information about recruitment practices to identify barriers to patient consent and participation to an orthopaedic trial. Methods. We collected 11 audio recordings of recruitment appointments and interviews of research team members (principal investigators and research nurses) from five