An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data.Aims
Methods
The evidence base to inform the management of Achilles tendon
rupture is sparse. The objectives of this research were to establish
what current practice is in the United Kingdom and explore clinicians’
views on proposed further research in this area. This study was
registered with the ISRCTN (ISRCTN68273773) as part of a larger
programme of research. We report an online survey of current practice in the United
Kingdom, approved by the British Orthopaedic Foot and Ankle Society
and completed by 181 of its members. A total of ten of these respondents
were invited for a subsequent one-to-one interview to explore clinician
views on proposed further research in this area.Objectives
Methods
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The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
The incidence of limb fractures in patients living with HIV (PLWH) is increasing. However, due to their immunodeficiency status, the operation and rehabilitation of these patients present unique challenges. Currently, it is urgent to establish a standardized perioperative rehabilitation plan based on the concept of enhanced recovery after surgery (ERAS). This study aimed to validate the effectiveness of ERAS in the perioperative period of PLWH with limb fractures. A total of 120 PLWH with limb fractures, between January 2015 and December 2023, were included in this study. We established a multidisciplinary team to design and implement a standardized ERAS protocol. The demographic, surgical, clinical, and follow-up information of the patients were collected and analyzed retrospectively.Aims
Methods
Patient-reported outcome measures (PROMs) are being used increasingly in total knee arthroplasty (TKA). We conducted a systematic review aimed at identifying psychometrically sound PROMs by appraising their measurement properties. Studies concerning the development and/or evaluation of the measurement properties of PROMs used in a TKA population were systematically retrieved via PubMed, Web of Science, Embase, and Scopus. Ratings for methodological quality and measurement properties were conducted according to updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. Of the 155 articles on 34 instruments included, nine PROMs met the minimum requirements for psychometric validation and can be recommended to use as measures of TKA outcome: Oxford Knee Score (OKS); OKS–Activity and Participation Questionnaire (OKS-APQ); 12-item short form Knee Injury and Osteoarthritis Outcome (KOOS-12); KOOS Physical function Short form (KOOS-PS); Western Ontario and McMaster Universities Arthritis Index-Total Knee Replacement function short form (WOMAC-TKR); Lower Extremity Functional Scale (LEFS); Forgotten Joint Score (FJS); Patient’s Knee Implant Performance (PKIP); and University of California Los Angeles (UCLA) activity score. The pain and function subscales in WOMAC, as well as the pain, function, and quality of life subscales in KOOS, were validated psychometrically as standalone subscales instead of as whole instruments. However, none of the included PROMs have been validated for all measurement properties. Thus, further studies are still warranted to evaluate those PROMs. Use of the other 25 scales and subscales should be tempered until further studies validate their measurement properties. Cite this article:
Subtotal or total meniscectomy in the medial or lateral compartment
of the knee results in a high risk of future osteoarthritis. Meniscal
allograft transplantation has been performed for over thirty years
with the scientifically plausible hypothesis that it functions in
a similar way to a native meniscus. It is thought that a meniscal
allograft transplant has a chondroprotective effect, reducing symptoms
and the long-term risk of osteoarthritis. However, this hypothesis has
never been tested in a high-quality study on human participants.
This study aims to address this shortfall by performing a pilot
randomised controlled trial within the context of a comprehensive
cohort study design. Patients will be randomised to receive either meniscal transplant
or a non-operative, personalised knee therapy program. MRIs will
be performed every four months for one year. The primary endpoint
is the mean change in cartilage volume in the weight-bearing area
of the knee at one year post intervention. Secondary outcome measures
include the mean change in cartilage thickness, T2 maps, patient-reported
outcome measures, health economics assessment and complications.Objectives
Methods
To determine the morbidity and mortality outcomes of patients
presenting with a fractured neck of femur in an Australian context.
Peri-operative variables related to unfavourable outcomes were identified
to allow planning of intervention strategies for improving peri-operative
care. We performed a retrospective observational study of 185 consecutive
adult patients admitted to an Australian metropolitan teaching hospital
with fractured neck of femur between 2009 and 2010. The main outcome
measures were 30-day and one-year mortality rates, major complications
and factors influencing mortality. Objectives
Methods
