Aims. The evidence base within trauma and orthopaedics has traditionally favoured quantitative research methodologies. Qualitative research can provide unique insights which illuminate
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 impact of deprivation on patients on growing waiting lists for planned care. Methods. 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’. Results. The least deprived cohort were older (mean 65.95 years (SD 13.33)) than the most deprived (mean 59.48 years (SD 13.85)). Mean symptom duration was lower in the least deprived areas (68.59 months (SD 112.26)) compared to the most deprived (85.85 months (SD 122.50)). Mean pain visual analogue scores (VAS) were poorer in the most compared to the least deprived cohort (7.11 (SD 2.01) vs 5.99 (SD 2.57)), with mean mood scores also poorer (6.06 (SD 2.65) vs 4.71 (SD 2.78)). The most deprived areas exhibited lower mean quality of life (QoL) scores than the least (0.37 (SD 0.30) vs 0.53 (SD 0.31)). QoL findings correlated with health VAS and Generalized Anxiety Disorder 2-item (GAD2) scores, with the most deprived areas experiencing poorer health (health VAS 50.82 (SD 26.42) vs 57.29 (SD 24.19); GAD2: 2.94 (SD 2.35) vs 1.88 (SD 2.07)). Least-deprived patients had the highest self-reported activity levels and lowest sedentary cohort, with the converse true for patients from the most deprived areas. Conclusion. The most deprived
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
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
Methods
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
This study assesses patient barriers to successful telemedicine care in orthopaedic practices in a large academic practice in the COVID-19 era. In all, 381 patients scheduled for telemedicine visits with three orthopaedic surgeons in a large academic practice from 1 April 2020 to 12 June 2020 were asked to participate in a telephone survey using a standardized Institutional Review Board-approved script. An unsuccessful telemedicine visit was defined as patient-reported difficulty of use or reported dissatisfaction with teleconferencing. Patient barriers were defined as explicitly reported barriers of unsatisfactory visit using a process-based satisfaction metric. Statistical analyses were conducted using analysis of variances (ANOVAs), ranked ANOVAs, post-hoc pairwise testing, and chi-squared independent analysis with 95% confidence interval.Aims
Methods
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
Methods
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 increase in prescription opioid misuse and dependence is now a public health crisis in the UK. It is recognized as a whole-person problem that involves both the medical and the psychosocial needs of patients. Analyzing aspects of pathophysiology, emotional health, and social wellbeing associated with persistent opioid use after injury may inform safe and effective alleviation of pain while minimizing risk of misuse or dependence. Our objectives were to investigate patient factors associated with opioid use two to four weeks and six to nine months after an upper limb fracture. A total of 734 patients recovering from an isolated upper limb fracture were recruited in this study. Opioid prescription was documented retrospectively for the period preceding the injury, and prospectively at the two- to four-week post-injury visit and six- to nine-month post-injury visit. Bivariate and multivariate analysis sought factors associated with opioid prescription from demographics, injury-specific data, Patient Reported Outcome Measurement Instrumentation System (PROMIS), Depression computer adaptive test (CAT), PROMIS Anxiety CAT, PROMIS Instrumental Support CAT, the Pain Catastrophizing Scale (PCS), the Pain Self-efficacy Questionnaire (PSEQ-2), Tampa Scale for Kinesiophobia (TSK-11), and measures that investigate levels of social support.Aims
Methods
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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