Aims. Deprivation underpins many societal and health inequalities. COVID-19 has exacerbated these disparities, with access to planned care falling greatest in the most deprived areas of the UK during 2020. This study aimed to identify the
Aims. The COVID-19 pandemic has had a significant
Aims. We aim to objectively assess the
The coronavirus 2019 (COVID-19) global pandemic has had a significant
Aims. The aim of this paper is to describe the
Aims. COVID-19 represents one of the greatest global healthcare challenges in a generation. Orthopaedic departments within the UK have shifted care to manage trauma in ways that minimize exposure to COVID-19. As the incidence of COVID-19 decreases, we explore the
Elective orthopaedic services have had to adapt to significant system-wide pressures since the emergence of COVID-19 in December 2019. Length of stay is often recognized as a key marker of quality of care in patients undergoing arthroplasty. Expeditious discharge is key in establishing early rehabilitation and in reducing infection risk, both procedure-related and from COVID-19. The primary aim was to determine the effects of the COVID-19 pandemic length of stay following hip and knee arthroplasty at a high-volume, elective orthopaedic centre. A retrospective cohort study was performed. Patients undergoing primary or revision hip or knee arthroplasty over a six-month period, from 1 July to 31 December 2020, were compared to the same period in 2019 before the COVID-19 pandemic. Demographic data, American Society of Anesthesiologists (ASA) grade, wait to surgery, COVID-19 status, and length of hospital stay were recorded.Aims
Methods
COVID-19 remains the major focus of healthcare provision. Managing orthopaedic emergencies effectively, while at the same time protecting patients and staff, remains a challenge. We explore how the UK lockdown affected the rate, distribution, and type of orthopaedic emergency department (ED) presentations, using the same period in 2019 as reference. This article discusses considerations for the ED and trauma wards to help to maintain the safety of patients and healthcare providers with an emphasis on more remote geography. The study was conducted from 23 March 2020 to 5 May 2020 during the full lockdown period (2020 group) and compared to the same time frame in 2019 (2019 group). Included are all patients who attended the ED at Raigmore Hospital during this period from both the local area and tertiary referral from throughout the UK Highlands. Data was collected and analyzed through the ED Information System (EDIS) as well as ward and theatre records.Aims
Methods
Aims. In the UK, the NHS generates an estimated 25 megatonnes of carbon dioxide equivalents (4% to 5% of the nation’s total carbon emissions) and produces over 500,000 tonnes of waste annually. There is limited evidence demonstrating the principles of sustainability and its benefits within orthopaedic surgery. The primary aim of this study was to analyze the environmental
Aims. As the world continues to fight successive waves of COVID-19 variants, we have seen worldwide infections surpass 100 million. London, UK, has been severely affected throughout the pandemic, and the resulting
Aims. The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons. Methods. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes. Results. The four intersecting themes identified were: 1) validity in traditional research, 2) confusion around the definition of AI, 3) an inability to validate AI research, and 4) cautious optimism about AI research. Underpinning these themes is the notion of a validity heuristic that is strongly rooted in traditional research teaching and embedded in medical and surgical training. Conclusion. Research involving AI sometimes challenges the accepted traditional evidence-based framework. This can give rise to confusion among orthopaedic surgeons, who may be unable to confidently validate findings. In our study, the
Aims. Early large treatment effects can arise in small studies, which lessen as more data accumulate. This study aimed to retrospectively examine whether early treatment effects occurred for two multicentre orthopaedic randomized controlled trials (RCTs) and explore biases related to this. Methods. Included RCTs were ProFHER (PROximal Fracture of the Humerus: Evaluation by Randomisation), a two-arm study of surgery versus non-surgical treatment for proximal humerus fractures, and UK FROST (United Kingdom Frozen Shoulder Trial), a three-arm study of two surgical and one non-surgical treatment for frozen shoulder. To determine whether early treatment effects were present, the primary outcome of Oxford Shoulder Score (OSS) was compared on forest plots for: the chief investigator’s (CI) site to the remaining sites, the first five sites opened to the other sites, and patients grouped in quintiles by randomization date. Potential for bias was assessed by comparing mean age and proportion of patients with indicators of poor outcome between included and excluded/non-consenting participants. Results. No bias in treatment effect was observed overall for the CI site, or the first five sites, compared with the remaining sites in either trial. An early treatment effect on the OSS was observed for the first quintile of participants recruited to ProFHER only (clinically relevant difference of seven points). Selection bias for age was observed in the ProFHER trial only, with slightly younger patients being recruited into the study. Both trials showed some selection bias for markers of poor prognosis, although these did not appear to change over time. Conclusion. No bias in treatment effects overall were found at the CI or early sites set-up. An early treatment effect was found in one of the two trials, which was likely a chance effect as this did not continue during the study. Selection bias was observed in both RCTs, however this was minimal and did not
Aims. Healthcare systems have been rapidly restructured to meet COVID-19 demand. Clinicians are working to novel clinical guidelines, treating new patient cohorts and working in unfamiliar environments. Trauma and orthopaedics (T&O) has experienced cancellation of routine clinics and operating, with redistribution of the workload and human resources. To date, no studies have evaluated the mental health
The COVID-19 pandemic has disrupted all segments of daily life, with the healthcare sector being at the forefront of this upheaval. Unprecedented efforts have been taken worldwide to curb this ongoing global catastrophe that has already resulted in many fatalities. One of the areas that has received little attention amid this turmoil is the disruption to trainee education, particularly in specialties that involve acquisition of procedural skills. Hand surgery in Singapore is a standalone combined programme that relies heavily on dedicated cross-hospital rotations, an extensive didactic curriculum and supervised hands-on training of increasing complexity. All aspects of this training programme have been affected because of the cancellation of elective surgical procedures, suspension of cross-hospital rotations, redeployment of residents, and an unsustainable duty roster. There is a real concern that trainees will not be able to meet their training requirements and suffer serious issues like burnout and depression. The long-term
Aims. To assess the
Aims. Europe has found itself at the epicentre of the COVID-19 pandemic. Naturally, this has placed added strain onto healthcare systems internationally. It was feared that the
Aims. To determine the
Aims. The worldwide COVID-19 pandemic is directly
Aims. The current global pandemic due to COVID-19 is generating significant burden on the health service in the UK. On 23 March 2020, the UK government issued requirements for a national lockdown. The aim of this multicentre study is to gain a greater understanding of the
The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales. We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID).Aims
Methods