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Bone & Joint Open
Vol. 2, Issue 8 | Pages 583 - 593
2 Aug 2021
Kulkarni K Shah R Armaou M Leighton P Mangwani J Dias J

Aims

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.

Methods

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.


Bone & Joint Open
Vol. 1, Issue 6 | Pages 236 - 244
11 Jun 2020
Verstraete MA Moore RE Roche M Conditt MA

Aims

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.

Methods

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.


Bone & Joint Open
Vol. 1, Issue 5 | Pages 131 - 136
15 May 2020
Key T Mathai NJ Venkatesan AS Farnell D Mohanty K

Aims

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.

Methods

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.