Aims. The influence of metabolic syndrome (MetS) on the outcome after
Aims. To review the evidence and reach consensus on recommendations for follow-up after total
Aims. Our main aim was to describe the trend in the comorbidities of patients undergoing elective total hip arthroplasties (THAs) and knee arthroplasties (KAs) between 1 January 2005 and 31 December 2018 in England. Methods. We combined data from the National Joint Registry (NJR) on primary elective
Aims. We investigated the efficacy and safety profile of commonly used venous thromboembolism (VTE) prophylaxis agents following
Aims. Access to joint replacement is being restricted for patients with comorbidities in a number of high-income countries. However, there is little evidence on the impact of comorbidities on outcomes. The purpose of this study was to determine the safety and effectiveness of
Aims. The aim of this study was to report health-related quality of life (HRQoL) and joint-specific function in patients waiting for total
Aims. Histology is widely used for diagnosis of persistent infection during reimplantation in two-stage revision
Aims. The aim of this study was to give estimates of the incidence of component incompatibility in
Aims. The primary aim was to assess the rate of postoperative COVID-19 following
Aims. To investigate whether chronic kidney disease (CKD) is associated with the risk of all-cause revision or revision due to a periprosthetic joint infection (PJI) after primary
Aims. The aim of this meta-analysis was to determine the pooled incidence of postoperative urinary retention (POUR) following total
Aims. To develop and validate patient-centred algorithms that estimate individual risk of death over the first year after elective joint arthroplasty surgery for osteoarthritis. Methods. A total of 763,213 hip and knee joint arthroplasty episodes recorded in the National Joint Registry for England and Wales (NJR) and 105,407 episodes from the Norwegian Arthroplasty Register were used to model individual mortality risk over the first year after surgery using flexible parametric survival regression. Results. The one-year mortality rates in the NJR were 10.8 and 8.9 per 1,000 patient-years after
Aims. We studied the outcomes of
Aims. To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Methods. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in
Objectives. Wound complications are reported in up to 10%
Aims. To calculate how the likelihood of obtaining measurable benefit from
Aims. In 2020, the COVID-19 pandemic meant that proceeding with elective surgery was restricted to minimize exposure on wards. In order to maintain throughput of elective cases, our hospital (St Michaels Hospital, Toronto, Canada) was forced to convert as many cases as possible to same-day procedures rather than overnight admission. In this retrospective analysis, we review the cases performed as same-day arthroplasty surgeries compared to the same period in the previous 12 months. Methods. We conducted a retrospective analysis of patients undergoing total
Aims. This study aimed to investigate the estimated change in primary and revision arthroplasty rate in the Netherlands and Denmark for hips, knees, and shoulders during the COVID-19 pandemic in 2020 (COVID-period). Additional points of focus included the comparison of patient characteristics and hospital type (2019 vs COVID-period), and the estimated loss of quality-adjusted life years (QALYs) and impact on waiting lists. Methods. All hip, knee, and shoulder arthroplasties (2014 to 2020) from the Dutch Arthroplasty Register, and
Aims. Surgical costs are a major component of healthcare expenditures in the USA. Intraoperative communication is a key factor contributing to patient outcomes. However, the effectiveness of communication is only partially determined by the surgeon, and understanding how non-surgeon personnel affect intraoperative communication is critical for the development of safe and cost-effective staffing guidelines. Operative efficiency is also dependent on high-functioning teams and can offer a proxy for effective communication in highly standardized procedures like primary total
Aims. While internet search engines have been the primary information source for patients’ questions, artificial intelligence large language models like ChatGPT are trending towards becoming the new primary source. The purpose of this study was to determine if ChatGPT can answer patient questions about total