Aims. 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. Methods. 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
Aims. To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Methods. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation. Results. For THA, there were 5,558 patient radiology reports included, of which 4,137 were used for model
Aims. Ankle fracture fixation is commonly performed by junior trainees. Simulation
Anterior cruciate ligament (ACL) injuries are among the most common and debilitating knee injuries in professional athletes with an incidence in females up to eight-times higher than their male counterparts. ACL injuries can be career-threatening and are associated with increased risk of developing knee osteoarthritis in future life. The increased risk of ACL injury in females has been attributed to various anatomical, developmental, neuromuscular, and hormonal factors. Anatomical and hormonal factors have been identified and investigated as significant contributors including osseous anatomy, ligament laxity, and hamstring muscular recruitment. Postural stability and impact absorption are associated with the stabilizing effort and stress on the ACL during sport activity, increasing the risk of noncontact pivot injury. Female patients have smaller diameter hamstring autografts than males, which may predispose to increased risk of re-rupture following ACL reconstruction and to an increased risk of chondral and meniscal injuries. The addition of an extra-articular tenodesis can reduce the risk of failure; therefore, it should routinely be considered in young elite athletes. Prevention programs target key aspects of
The anterior cruciate ligament (ACL) is frequently injured in elite athletes, with females up to eight times more likely to suffer an ACL tear than males. Biomechanical and hormonal factors have been thoroughly investigated; however, there remain unknown factors that need investigation. The mechanism of injury differs between males and females, and anatomical differences contribute significantly to the increased risk in females. Hormonal factors, both endogenous and exogenous, play a role in ACL laxity and may modify the risk of injury. However, data are still limited, and research involving oral contraceptives is potentially associated with methodological and ethical problems. Such characteristics can also influence the outcome after ACL reconstruction, with higher failure rates in females linked to a smaller diameter of the graft, especially in athletes aged < 21 years. The addition of a lateral extra-articular tenodesis can improve the outcomes after ACL reconstruction and reduce the risk of failure, and it should be routinely considered in young elite athletes. Sex-specific environmental differences can also contribute to the increased risk of injury, with more limited access to and availablility of advanced
Aims. Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. Methods. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy. Results. Of the 455 studies identified, only 12 were suitable for inclusion. Nine reported implant identification and three described predicting risk of implant failure. Of the 12, three studies compared AI performance with orthopaedic surgeons. AI-based implant identification achieved AUC 0.992 to 1, and most algorithms reported an accuracy > 90%, using 550 to 320,000
Aims. Trained immunity confers non-specific protection against various types of infectious diseases, including bone and joint infection. Platelets are active participants in the immune response to pathogens and foreign substances, but their role in trained immunity remains elusive. Methods. We first trained the innate immune system of C57BL/6 mice via intravenous injection of two toll-like receptor agonists (zymosan and lipopolysaccharide). Two, four, and eight weeks later, we isolated platelets from immunity-trained and control mice, and then assessed whether immunity
Aims. This study aims to assess the feasibility of conducting a pragmatic, multicentre randomized controlled trial (RCT) to test the clinical and cost-effectiveness of an informal caregiver
Aims. Periacetabular osteotomy (PAO) is widely recognized as a demanding surgical procedure for acetabular reorientation. Reports about the learning curve have primarily focused on complication rates during the initial learning phase. Therefore, our aim was to assess the PAO learning curve from an analytical perspective by determining the number of PAOs required for the duration of surgery to plateau and the accuracy to improve. Methods. The study included 118 consecutive PAOs in 106 patients. Of these, 28 were male (23.7%) and 90 were female (76.3%). The primary endpoint was surgical time. Secondary outcome measures included radiological parameters. Cumulative summation analysis was used to determine changes in surgical duration. A multivariate linear regression model was used to identify independent factors influencing surgical time. Results. The learning curve in this series was 26 PAOs in a period of six months. After 26 PAO procedures, a significant drop in surgical time was observed and a plateau was also achieved. The mean duration of surgery during the learning curve was 103.8 minutes (SD 33.2), and 69.7 minutes (SD 18.6) thereafter (p < 0.001). Radiological correction of acetabular retroversion showed a significant improvement after having performed a total of 93 PAOs, including anteverting PAOs on 35 hips with a retroverted acetabular morphology (p = 0.005). Several factors were identified as independent variables influencing duration of surgery, including patient weight (β = 0.5 (95% confidence interval (CI) 0.2 to 0.7); p < 0.001), learning curve procedure phase of 26 procedures (β = 34.0 (95% CI 24.3 to 43.8); p < 0.001), and the degree of lateral correction expressed as the change in the lateral centre-edge angle (β = 0.7 (95% CI 0.001 to 1.3); p = 0.048). Conclusion. The learning curve for PAO surgery requires extensive surgical
Aims. 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. Methods. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes. Results. The four intersecting themes identified were: 1) validity in traditional research, 2) confusion around the definition of AI, 3) an inability to validate AI research, and 4) cautious optimism about AI research. Underpinning these themes is the notion of a validity heuristic that is strongly rooted in traditional research teaching and embedded in medical and surgical
The December 2022 Research Roundup. 360. looks at: Halicin is effective against Staphylococcus aureus biofilms in vitro; Synovial fluid and serum neutrophil-to-lymphocyte ratio: useful in septic arthritis?; Transcutaneous oximetry and wound healing; Orthopaedic surgery causes gut microbiome dysbiosis and intestinal barrier dysfunction; Mortality in alcohol-related cirrhosis: a nationwide population-based cohort study; Self-reported resistance
The April 2023 Children’s orthopaedics Roundup. 360. looks at: Can you treat type IIA supracondylar humerus fractures conservatively?; Bone bruising and anterior cruciate ligament injury in paediatrics; Participation and motor abilities after treatment with the Ponseti method; Does fellowship
Aims. The purpose of this survey study was to examine the demographic and lifestyle factors of women currently in orthopaedic surgery. Methods. An electronic survey was conducted of practising female orthopaedic surgeons based in the USA through both the Ruth Jackson Society and the online Facebook group “Women of Orthopaedics”. Results. The majority of surveyed female orthopaedic surgeons reported being married (76.4%; 285/373) and having children (67.6%; 252/373). In all, 66.5% (247/373) were collegiate athletes; 82.0% (306/373) reported having no female orthopaedic surgeon mentors in undergraduate and medical school. Their mean height is 65.8 inches and average weight is 147.3 lbs. Conclusion. The majority of female orthopaedic surgeons did not have female mentorship during their
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