Objectives. Despite the fact that research fraud and misconduct are under scrutiny in the field of
This paper outlines the recent development of an exchange Travelling Fellowship scheme between the British and American
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 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
Cartilage repair in terms of replacement, or
regeneration of damaged or diseased articular cartilage with functional tissue,
is the ‘holy grail’ of joint surgery. A wide spectrum of strategies
for cartilage repair currently exists and several of these techniques
have been reported to be associated with successful clinical outcomes
for appropriately selected indications. However, based on respective
advantages, disadvantages, and limitations, no single strategy, or
even combination of strategies, provides surgeons with viable options
for attaining successful long-term outcomes in the majority of patients.
As such, development of novel techniques and optimisation of current techniques
need to be, and are, the focus of a great deal of research from
the basic science level to clinical trials. Translational research
that bridges scientific discoveries to clinical application involves
the use of animal models in order to assess safety and efficacy
for regulatory approval for human use. This review article provides
an overview of animal models for cartilage repair. 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
Aims. Tibial cones are often utilized in revision total knee arthroplasty (TKA) with metaphyseal defects. Because there are few studies evaluating mid-term outcomes with a sufficient cohort, the purpose of this study was to evaluate tibial cone survival and complications in revision TKAs with tibial cones at minimum follow-up of five years. Methods. A retrospective review was completed from September 2006 to March 2015, evaluating 67 revision TKAs (64 patients) that received one specific porous tibial cone during revision TKA. The final cohort was composed of 62 knees (59 patients) with five years of clinical follow-up or reoperation. The mean clinical follow-up of the TKAs with minimum five-year clinical follow-up was 7.6 years (5.0 to 13.3). Survivorship analysis was performed with the endpoints of tibial cone revision for aseptic loosening, tibial cone revision for any reason, and reoperation. We also evaluated periprosthetic joint infection (PJI), risk factors for failure, and performed a radiological review. Results. The rate of cone revision for aseptic loosening was 6.5%, with an eight-year survival of 95%. Significant bone loss (Anderson
Aims. COVID-19-related patient care delays have resulted in an unprecedented patient care backlog in the field of orthopaedics. The objective of this study is to examine orthopaedic provider preferences regarding the patient care backlog and financial recovery initiatives in response to the COVID-19 pandemic. Methods. An