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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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:
Weightbearing instructions after musculoskeletal injury or orthopaedic surgery are a key aspect of the rehabilitation pathway and prescription. The terminology used to describe the weightbearing status of the patient is variable; many different terms are used, and there is recognition and evidence that the lack of standardized terminology contributes to confusion in practice. A consensus exercise was conducted involving all the major stakeholders in the patient journey for those with musculoskeletal injury. The consensus exercise primary aim was to seek agreement on a standardized set of terminology for weightbearing instructions.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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Safety concerns surrounding osseointegration are a significant barrier to replacing socket prosthesis as the standard of care following limb amputation. While implanted osseointegrated prostheses traditionally occur in two stages, a one-stage approach has emerged. Currently, there is no existing comparison of the outcomes of these different approaches. To address safety concerns, this study sought to determine whether a one-stage osseointegration procedure is associated with fewer adverse events than the two-staged approach. A comprehensive electronic search and quantitative data analysis from eligible studies were performed. Inclusion criteria were adults with a limb amputation managed with a one- or two-stage osseointegration procedure with follow-up reporting of complications.Aims
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Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp).Aims
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Chronic osteomyelitis (COM) of the lower limb in adults can be surgically managed by either limb reconstruction or amputation. This scoping review aims to map the outcomes used in studies surgically managing COM in order to aid future development of a core outcome set. A total of 11 databases were searched. A subset of studies published between 1 October 2020 and 1 January 2011 from a larger review mapping research on limb reconstruction and limb amputation for the management of lower limb COM were eligible. All outcomes were extracted and recorded verbatim. Outcomes were grouped and categorized as per the revised Williamson and Clarke taxonomy.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 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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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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The timing of when to remove a circular frame is crucial; early removal results in refracture or deformity, while late removal increases the patient morbidity and delay in return to work. This study was designed to assess the effectiveness of a staged reloading protocol. We report the incidence of mechanical failure following both single-stage and two stage reloading protocols and analyze the associated risk factors. We identified consecutive patients from our departmental database. Both trauma and elective cases were included, of all ages, frame types, and pathologies who underwent circular frame treatment. Our protocol is either a single-stage or two-stage process implemented by defunctioning the frame, in order to progressively increase the weightbearing load through the bone, and promote full loading prior to frame removal. Before progression, through the process we monitor patients for any increase in pain and assess radiographs for deformity or refracture.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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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 Hospital, UK) previously showed that during the first peak, a large proportion of patients were hesitant to be listed for their elective lower limb procedure. The aim of this study is to assess if there is a patient perception change towards having elective surgery now that we have passed the peak of the second wave of the pandemic. This is a prospective study of 100 patients who were on the waiting list of a single surgeon for an elective hip or knee procedure. Baseline characteristics including age, American Society of Anesthesiologists (ASA) grade, COVID-19 risk, procedure type, and admission type were recorded. The primary outcome was patient consent to continue with their scheduled surgical procedure. Subgroup analysis was also conducted to define if any specific patient factors influenced decision to continue with surgeryAims
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Patients undergoing limb reconstruction surgery often face a challenging and lengthy process to complete their treatment journey. The majority of existing outcome measures do not adequately capture the patient-reported outcomes relevant to this patient group in a single measure. Following a previous systematic review, the Stanmore Limb Reconstruction Score (SLRS) was designed with the intent to address this need for an effective instrument to measure patient-reported outcomes in limb reconstruction patients. We aim to assess the face validity of this score in a pilot study. The SLRS was designed following structured interviews with several groups including patients who have undergone limb reconstruction surgery, limb reconstruction surgeons, specialist nurses, and physiotherapists. This has subsequently undergone further adjustment for language and clarity. The score was then trialled on ten patients who had undergone limb reconstruction surgery, with subsequent structured questioning to understand the perceived suitability of the score.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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The response to the COVID-19 pandemic has raised the profile and level of interest in the use, acceptability, safety, and effectiveness of virtual outpatient consultations and telemedicine. These models of care are not new but a number of challenges have so far hindered widespread take-up and endorsement of these ways of working. With the response to the COVID-19 pandemic, remote and virtual working and consultation have become the default. This paper explores our experience of and learning from virtual and remote consultation and questions how this experience can be retained and developed for the future. Cite this article:
The primary aim is to estimate the current and potential number of patients on NHS England orthopaedic elective waiting lists by November 2020. The secondary aims are to model recovery strategies; review the deficit of hip and knee arthroplasty from National Joint Registry (NJR) data; and assess the cost of returning to pre-COVID-19 waiting list numbers. A model of referral, waiting list, and eventual surgery was created and calibrated using historical data from NHS England (April 2017 to March 2020) and was used to investigate the possible consequences of unmet demand resulting from fewer patients entering the treatment pathway and recovery strategies. NJR data were used to estimate the deficit of hip and knee arthroplasty by August 2020 and NHS tariff costs were used to calculate the financial burden.Aims
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Aims. This study presents patient-reported quality of life (QoL) over the first year following surgical debridement of long bone osteomyelitis. It assesses the bone involvement, antimicrobial options, coverage of soft tissues, and host status (BACH) classification as a prognostic tool and its ability to stratify cases into ‘uncomplicated’ or ‘complex’. Methods. Patients with long-bone osteomyelitis were identified prospectively between June 2010 and October 2015. All patients underwent surgical debridement in a single-staged procedure at a specialist bone infection unit. Self-reported QoL was assessed prospectively using the three-level EuroQol five-dimension questionnaire (EQ-5D-3L) index score and visual analogue scale (EQ-VAS) at five postoperative time-points (baseline, 14 days, 42 days, 120 days, and 365 days). BACH classification was applied retrospectively by two
Bone demonstrates good healing capacity, with a variety of strategies being utilized to enhance this healing. One potential strategy that has been suggested is the use of stem cells to accelerate healing. The following databases were searched: MEDLINE, CENTRAL, EMBASE, Cochrane Database of Systematic Reviews, WHO-ICTRP, ClinicalTrials.gov, as well as reference checking of included studies. The inclusion criteria for the study were: population (any adults who have sustained a fracture, not including those with pre-existing bone defects); intervention (use of stem cells from any source in the fracture site by any mechanism); and control (fracture healing without the use of stem cells). Studies without a comparator were also included. The outcome was any reported outcomes. The study design was randomized controlled trials, non-randomized or observational studies, and case series.Aims
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To describe the incidence of adverse clinical outcomes related to COVID-19 infection following corticosteroid injections (CSI) during the COVID-19 pandemic. To describe the incidence of positive SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) testing, positive SARS-COV2 IgG antibody testing or positive imaging findings following CSI at our institution during the COVID-19 pandemic. A retrospective observational study was undertaken of consecutive patients who had CSI in our local hospitals between 1 February and 30June 2020. Electronic patient medical records (EPR) and radiology information system (RIS) database were reviewed. SARS-CoV-2 RT-PCR testing, SARS-COV2 IgG antibody testing, radiological investigations, patient management, and clinical outcomes were recorded. Lung findings were categorized according to the British Society of Thoracic Imaging (BSTI) guidelines. Reference was made to the incidence of lab-confirmed COVID-19 cases in our region.Aims
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