Fracture-related infections (FRIs) are a devastating complication of fracture management. However, the impact of FRIs on mental health remains understudied. The aim of this study was a longitudinal evaluation of patients’ psychological state, and expectations for recovery comparing patients with recurrent FRI to those with primary FRI. A prospective longitudinal study was conducted at a level 1 trauma centre from January 2020 to December 2022. In total, 56 patients treated for FRI were enrolled. The ICD-10 symptom rating (ISR) and an expectation questionnaire were assessed at five timepoints: preoperatively, one month postoperatively, and at three, six, and 12 months.Aims
Methods
Shoulder arthroplasty is effective in the management of end-stage glenohumeral joint arthritis. However, it is major surgery and patients must balance multiple factors when considering the procedure. An understanding of patients’ decision-making processes may facilitate greater support of those considering shoulder arthroplasty and inform the outcomes of future research. Participants were recruited from waiting lists of three consultant upper limb surgeons across two NHS hospitals. Semi-structured interviews were conducted with 12 participants who were awaiting elective shoulder arthroplasty. Transcribed interviews were analyzed using a grounded theory approach. Systematic coding was performed; initial codes were categorized and further developed into summary narratives through a process of discussion and refinement. Data collection and analyses continued until thematic saturation was reached.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
Brachial plexus injury (BPI) is an often devastating injury that affects patients physically and emotionally. The vast majority of the published literature is based on surgeon-graded assessment of motor outcomes, but the patient experience after BPI is not well understood. Our aim was to better understand overall life satisfaction after BPI, with the goal of identifying areas that can be addressed in future delivery of care. We conducted semi-structured interviews with 15 BPI patients after initial nerve reconstruction. The interview guide was focused on the patient’s experience after BPI, beginning with the injury itself and extending beyond surgical reconstruction. Inductive and deductive thematic analysis was used according to standard qualitative methodology to better understand overall life satisfaction after BPI, contributors to life satisfaction, and opportunities for improvement.Aims
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The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments. Based on a clinical series of 479 primary total knees and 1,305 associated surgical decisions, various ML models were developed. These models identified the indicated surgical decision based on available, intra-operative alignment, and tibiofemoral load data.Aims
Methods
The adequate provision of personal protective equipment (PPE) for healthcare workers has come under considerable scrutiny during the COVID-19 pandemic. This study aimed to evaluate staff awareness of PPE guidance, perceptions of PPE measures, and concerns regarding PPE use while caring for COVID-19 patients. In addition, responses of doctors, nurses, and other healthcare professionals (OHCPs) were compared. The inclusion criteria were all staff working in clinical areas of the hospital. Staff were invited to take part using a link to an online questionnaire advertised by email, posters displayed in clinical areas, and social media. Questions grouped into the three key themes - staff awareness, perceptions, and concerns - were answered using a five-point Likert scale. The Kruskal-Wallis test was used to compare results across all three groups of staff.Aims
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