The coronavirus 2019 (COVID-19) global pandemic has had a significant impact on trauma and orthopaedic (T&O) departments worldwide. To manage the peak of the epidemic, orthopaedic staff were redeployed to frontline medical care; these roles included managing minor injury units, forming a “proning” team, and assisting in the intensive care unit (ICU). In addition, outpatient clinics were restructured to facilitate virtual consultations, elective procedures were cancelled, and inpatient hospital admissions minimized to reduce nosocomial COVID-19 infections. Urgent operations for fractures, infection and tumours went ahead but required strict planning to ensure patient safety. Orthopaedic training has also been significantly impacted during this period. This article discusses the impact of COVID-19 on T&O in the UK and highlights key lessons learned that may help to proactively prepare for the next global pandemic. Cite this article:
Aims. The primary aim is to estimate the current and potential number of patients on
Aims. In the UK, the
Aims. The aim of this study was to surveil whether the standard operating procedure created for the
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 impact on the
Aims. To evaluate safety outcomes and patient satisfaction of the re-introduction of elective orthopaedic surgery on ‘green’ (non-COVID-19) sites during the COVID-19 pandemic. Methods. A strategy consisting of phased relaxation of clinical comorbidity criteria was developed. Patients from the orthopaedic waiting list were selected according to these criteria and observed recommended preoperative isolation protocols. Surgery was performed at green sites (two local private hospitals) under the COVID-19
Introduction. The aim of this study is to report the 30 day COVID-19 related morbidity and mortality of patients assessed as SARS-CoV-2 negative who underwent emergency or urgent orthopaedic surgery in the
Aims. The exact risk to patients undergoing surgery who develop COVID-19 is not yet fully known. This study aims to provide the current data to allow adequate consent regarding the risks of post-surgery COVID-19 infection and subsequent COVID-19-related mortality. Methods. All orthopaedic trauma cases at the Wrightington Wigan and Leigh
Our primary aim was to establish the proportion of female orthopaedic consultants who perform arthroplasty via cases submitted to the National Joint Registry (NJR), which covers England, Wales, Northern Ireland, the Isle of Man, and Guernsey. Secondary aims included comparing time since specialist registration, private practice participation, and number of hospitals worked in between male and female surgeons. Publicly available data from the NJR was extracted on the types of arthroplasty performed by each surgeon, and the number of procedures of each type undertaken. Each surgeon was cross-referenced with the General Medical Council (GMC) website, using GMC number to extract surgeon demographic data. These included sex, region of practice, and dates of full and specialist registration.Aims
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The aims of this study were to describe the demographic, socioeconomic, and educational factors associated with core surgical trainees (CSTs) who apply to and receive offers for higher surgical training (ST3) posts in Trauma & Orthopaedics (T&O). Data collected by the UK Medical Education Database (UKMED) between 1 January 2014 and 31 December 2019 were used in this retrospective longitudinal cohort study comprising 1,960 CSTs eligible for ST3. The primary outcome measures were whether CSTs applied for a T&O ST3 post and if they were subsequently offered a post. A directed acyclic graph was used for detecting confounders and adjusting logistic regression models to calculate odds ratios (ORs), which assessed the association between the primary outcomes and relevant exposures of interest, including: age, sex, ethnicity, parental socioeconomic status (SES), domiciliary status, category of medical school, Situational Judgement Test (SJT) scores at medical school, and success in postgraduate examinations. This study followed STROBE guidelines.Aims
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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. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes.Aims
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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. 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.Aims
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The evidence base within trauma and orthopaedics has traditionally favoured quantitative research methodologies. Qualitative research can provide unique insights which illuminate patient experiences and perceptions of care. Qualitative methods reveal the subjective narratives of patients that are not captured by quantitative data, providing a more comprehensive understanding of patient-centred care. The aim of this study is to quantify the level of qualitative research within the orthopaedic literature. A bibliometric search of journals’ online archives and multiple databases was undertaken in March 2024, to identify articles using qualitative research methods in the top 12 trauma and orthopaedic journals based on the 2023 impact factor and SCImago rating. The bibliometric search was conducted and reported in accordance with the preliminary guideline for reporting bibliometric reviews of the biomedical literature (BIBLIO).Aims
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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 impact of deprivation on patients on growing waiting lists for planned care. Questionnaires were sent to orthopaedic waiting list patients at the start of the UK’s first COVID-19 lockdown to capture key quantitative and qualitative aspects of patients’ health. A total of 888 respondents were divided into quintiles, with sampling stratified based on the Index of Multiple Deprivation (IMD); level 1 represented the ‘most deprived’ cohort and level 5 the ‘least deprived’.Aims
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Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles ( Cite this article:
The number of females within the speciality of trauma and orthopaedics (T&O) is increasing. The aim of this study was to identify: 1) current attitudes and behaviours of UK female T&O surgeons towards pregnancy; 2) any barriers faced towards pregnancy with a career in T&O surgery; and 3) areas for improvement. This is a cross-sectional study using an anonymous 13-section web-based survey distributed to female-identifying T&O trainees, speciality and associate specialist surgeons (SASs) and locally employed doctors (LEDs), fellows, and consultants in the UK. Demographic data was collected as well as closed and open questions with adaptive answering relating to attitudes towards childbearing and experiences of fertility and complications associated with pregnancy. A descriptive data analysis was carried out.Aims
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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
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Tuberculosis (TB) is one of the biggest communicable causes of mortality worldwide. While incidence in the UK has continued to fall since 2011, Bradford retains one of the highest TB rates in the UK. This study aims to examine the local disease burden of musculoskeletal (MSK) TB, by analyzing common presenting factors within the famously diverse population of Bradford. An observational study was conducted, using data from the Bradford Teaching Hospitals TB database of patients with a formal diagnosis of MSK TB between January 2005 and July 2017. Patient data included demographic data (including nationality/date of entry to the UK), disease focus, microbiology, and management strategies. Disease incidence was calculated using population data from the Office for National Statistics. Poisson confidence intervals were calculated to demonstrate the extent of statistical error. Disease incidence and nationality were also analyzed, and correlation sought, using the chi-squared test.Aims
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Due to widespread cancellations in elective orthopaedic procedures, the number of patients on waiting list for surgery is rising. We aim to determine and quantify if disparities exist between inpatient and day-case orthopaedic waiting list numbers; we also aim to determine if there is a ‘hidden burden’ that already exists due to reductions in elective secondary care referrals. Retrospective data were collected between 1 April 2020 and 31 December 2020 and compared with the same nine-month period the previous year. Data collected included surgeries performed (day-case vs inpatient), number of patients currently on the orthopaedic waiting list (day-case vs inpatient), and number of new patient referrals from primary care and therapy services.Aims
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COVID-19 has compounded a growing waiting list problem, with over 4.5 million patients now waiting for planned elective care in the UK. Views of patients on waiting lists are rarely considered in prioritization. Our primary aim was to understand how to support patients on waiting lists by hearing their experiences, concerns, and expectations. The secondary aim was to capture objective change in disability and coping mechanisms. A minimum representative sample of 824 patients was required for quantitative analysis to provide a 3% margin of error. Sampling was stratified by body region (upper/lower limb, spine) and duration on the waiting list. Questionnaires were sent to a random sample of elective orthopaedic waiting list patients with their planned intervention paused due to COVID-19. Analyzed parameters included baseline health, change in physical/mental health status, challenges and coping strategies, preferences/concerns regarding treatment, and objective quality of life (EuroQol five-dimension questionnaire (EQ-5D), Generalized Anxiety Disorder 2-item scale (GAD-2)). Qualitative analysis was performed via the Normalization Process Theory.Aims
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