This paper outlines the recent development of an exchange Travelling Fellowship scheme between the British and American
Objectives. Despite the fact that research fraud and misconduct are under scrutiny in the field of
The follow-up interval of a study represents an important aspect that is frequently mentioned in the title of the manuscript. Authors arbitrarily define whether the follow-up of their study is short-, mid-, or long-term. There is no clear consensus in that regard and definitions show a large range of variation. It was therefore the aim of this study to systematically identify clinical research published in high-impact orthopaedic journals in the last five years and extract follow-up information to deduce corresponding evidence-based definitions of short-, mid-, and long-term follow-up. A systematic literature search was performed to identify papers published in the six highest ranked orthopaedic journals during the years 2015 to 2019. Follow-up intervals were analyzed. Each article was assigned to a corresponding subspecialty field: sports traumatology, knee arthroplasty and reconstruction, hip-preserving surgery, hip arthroplasty, shoulder and elbow arthroplasty, hand and wrist, foot and ankle, paediatric orthopaedics, orthopaedic trauma, spine, and tumour. Mean follow-up data were tabulated for the corresponding subspecialty fields. Comparison between means was conducted using analysis of variance.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:
Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
Aims. The evidence base within trauma and orthopaedics has traditionally favoured quantitative research methodologies. Qualitative research can provide unique insights which illuminate patient experiences and perceptions of care. Qualitative methods reveal the subjective narratives of patients that are not captured by quantitative data, providing a more comprehensive understanding of patient-centred care. The aim of this study is to quantify the level of qualitative research within the orthopaedic literature. Methods. A bibliometric search of journals’ online archives and multiple databases was undertaken in March 2024, to identify articles using qualitative research methods in the top 12 trauma and orthopaedic journals based on the 2023 impact factor and SCImago rating. The bibliometric search was conducted and reported in accordance with the preliminary guideline for reporting bibliometric reviews of the biomedical literature (BIBLIO). Results. Of the 7,201 papers reviewed, 136 included qualitative methods (0.1%). There was no significant difference between the journals, apart from Bone & Joint Open, which included 21 studies using qualitative methods, equalling 4% of its published articles. Conclusion. This study demonstrates that there is a very low number of qualitative research papers published within trauma and orthopaedic journals. Given the increasing focus on patient outcomes and improving the patient experience, it may be argued that there is a requirement to support both quantitative and qualitative approaches to
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
Economic evaluation provides a framework for assessing the costs and consequences of alternative programmes or interventions. One common vehicle for economic evaluations in the healthcare context is the decision-analytic model, which synthesizes information on parameter inputs (for example, probabilities or costs of clinical events or health states) from multiple sources and requires application of mathematical techniques, usually within a software program. A plethora of decision-analytic modelling-based economic evaluations of orthopaedic interventions have been published in recent years. This annotation outlines a number of issues that can help readers, reviewers, and decision-makers interpret evidence from decision-analytic modelling-based economic evaluations of orthopaedic interventions. Cite this article:
Aims. Management of displaced paediatric supracondylar elbow fractures remains widely debated and actual practice is unclear. This national trainee collaboration aimed to evaluate surgical and postoperative management of these injuries across the UK. Methods. This study was led by the South West
