To develop a multidisciplinary health research agenda (HRA) utilizing expertise from various disciplines to identify and prioritize evidence uncertainties in orthopaedics, thereby reducing research waste. We employed a novel, structured framework to develop a HRA. We started by systematically collecting all evidence uncertainties from stakeholders with an interest in orthopaedic care, categorizing them into 13 sub-themes defined by the Dutch Orthopaedic Association (NOV). Subsequently, a modified two-phased Delphi study (two rounds per phase), adhering to the Conducting and REporting DElphi Studies (CREDES) guideline, was conducted. In Phase 1, board members assessed the collected evidence uncertainties on a three-point Likert scale to confirm knowledge gaps. In Phase 2, diverse stakeholders, including orthopaedic surgeons, rated the confirmed knowledge gaps on a seven-point Likert scale. Panel members rated one self-selected sub-theme and two randomly assigned sub-themes. The results from Phase 2 were ranked based on the overall average score for each uncertainty. Finally, a focus group discussion with patient associations’ representatives identified their top-ranked uncertainty from a predefined consensus process, leading to the final HRA. An advisory board, the Federation of Medical Specialists, and the NOV research coordinator oversaw the process.Aims
Methods
Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.Aims
Methods
Multiligament knee injuries (MLKI) are devastating injuries that can result in significant morbidity and time away from sport. There remains considerable variation in strategies employed for investigation, indications for operative intervention, outcome reporting, and rehabilitation following these injuries. At present no study has yet provided a comprehensive overview evaluating the extent, range, and overall summary of the published literature pertaining to MLKI. Our aim is to perform a methodologically rigorous scoping review, mapping the literature evaluating the diagnosis and management of MLKI. This scoping review will address three aims: firstly, to map the current extent and nature of evidence for diagnosis and management of MLKI; secondly, to summarize and disseminate existing research findings to practitioners; and thirdly, to highlight gaps in current literature. A three-step search strategy as described by accepted methodology will be employed to identify peer-reviewed literature including reviews, technical notes, opinion pieces, and original research. An initial limited search will be performed to determine suitable search terms, followed by an expanded search of four electronic databases (MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, and Web of Science). Two reviewers will independently screen identified studies for final inclusion.Aims
Methods
Biofilm-related infection is a major complication that occurs in orthopaedic surgery. Various treatments are available but efficacy to eradicate infections varies significantly. A systematic review was performed to evaluate therapeutic interventions combating biofilm-related infections on in vivo animal models. Literature research was performed on PubMed and Embase databases. Keywords used for search criteria were “bone AND biofilm”. Information on the species of the animal model, bacterial strain, evaluation of biofilm and bone infection, complications, key findings on observations, prevention, and treatment of biofilm were extracted.Aims
Methods
Orthopaedic surgeries are complex, frequently performed procedures associated with significant haemorrhage and perioperative blood transfusion. Given refinements in surgical techniques and changes to transfusion practices, we aim to describe contemporary transfusion practices in orthopaedic surgery in order to inform perioperative planning and blood banking requirements. We performed a retrospective cohort study of adult patients who underwent orthopaedic surgery at four Canadian hospitals between 2014 and 2016. We studied all patients admitted to hospital for nonarthroscopic joint surgeries, amputations, and fracture surgeries. For each surgery and surgical subgroup, we characterized the proportion of patients who received red blood cell (RBC) transfusion, the mean/median number of RBC units transfused, and exposure to platelets and plasma.Aims
Methods
Trauma and orthopaedics is the largest of the
surgical specialties and yet attracts a disproportionately small
fraction of available national and international funding for health
research. With the burden of musculoskeletal disease increasing,
high-quality research is required to improve the evidence base for
orthopaedic practice. Using the current research landscape in the
United Kingdom as an example, but also addressing the international
perspective, we highlight the issues surrounding poor levels of
research funding in trauma and orthopaedics and indicate avenues
for improving the impact and success of surgical musculoskeletal
research. Cite this article:
