Objectives. Despite the fact that research fraud and misconduct are under scrutiny in the field of orthopaedic research, little systematic work has been done to uncover and characterise the underlying reasons for academic retractions in this field. The purpose of this study was to determine the rate of retractions and identify the reasons for retracted publications in the orthopaedic literature. Methods. Two reviewers independently searched MEDLINE, EMBASE, and the Cochrane Library (1995 to current) using MeSH keyword headings and the ‘retracted’ filter. We also searched an independent website that reports and archives retracted scientific publications (. www.retractionwatch.com. ). Two reviewers independently extracted data including reason for retraction, study type, journal impact factor, and country of origin. Results. One hundred and ten retracted studies were included for data extraction. The retracted studies were published in journals with impact factors ranging from 0.000 (discontinued journals) to 13.262. In the 20-year search window, only 25 papers were retracted in the first ten years, with the remaining 85 papers retracted in the most recent decade. The most common reasons for retraction were fraudulent data (29), plagiarism (25) and duplicate publication (20). Retracted articles have been cited up to 165 times (median 6; interquartile range 2 to 19). Conclusion. The rate of retractions in the orthopaedic literature is increasing, with the majority of retractions attributed to academic misconduct and fraud. Orthopaedic retractions originate from numerous journals and countries, indicating that misconduct issues are widespread. The results of this study highlight the need to address academic integrity when training the next generation of orthopaedic investigators. Cite this article: J. Yan, A. MacDonald, L-P. Baisi, N. Evaniew, M. Bhandari, M. Ghert. Retractions in orthopaedic research: A systematic review. Bone Joint Res 2016;5:263–268. DOI: 10.1302/2046-3758.56.BJR-2016-0047

Aims

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.

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 orthopaedic research. Combining qualitative and quantitative methods may effectively address the complex and personal aspects of patients’ care, ensuring that outcomes align with patient values and enhance overall care 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 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 training. Conclusion. Research involving AI sometimes challenges the accepted traditional evidence-based framework. This can give rise to confusion among orthopaedic surgeons, who may be unable to confidently validate findings. In our study, the impact of this was mediated by cautious optimism based on an ingrained validity heuristic that orthopaedic surgeons develop through their medical training. Adding to this, the integration of AI into everyday life works to reduce suspicion and aid acceptance. Cite this article: Bone Jt Open 2023;4(9):696–703

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: Bone Joint Res 2014;4:89–94.

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 orthopaedic research consortium at a multi-hospital tertiary care academic medical system developed a three-part survey examining provider perspectives on strategies to expand orthopaedic patient care and financial recovery. Section 1 asked for preferences regarding extending clinic hours, section 2 assessed surgeon opinions on expanding surgical opportunities, and section 3 questioned preferred strategies for departmental financial recovery. The survey was sent to the institution’s surgical and nonoperative orthopaedic providers. Results. In all, 73 of 75 operative (n = 55) and nonoperative (n = 18) providers responded to the survey. A total of 92% of orthopaedic providers (n = 67) were willing to extend clinic hours. Most providers preferred extending clinic schedule until 6pm on weekdays. When asked about extending surgical block hours, 96% of the surgeons (n = 53) were willing to extend operating room (OR) block times. Most surgeons preferred block times to be extended until 7pm (63.6%, n = 35). A majority of surgeons (53%, n = 29) believe that over 50% of their surgical cases could be performed at an ambulatory surgery centre (ASC). Of the strategies to address departmental financial deficits, 85% of providers (n = 72) were willing to work extra hours without a pay cut. Conclusion. Most orthopaedic providers are willing to help with patient care backlogs and revenue recovery by working extended hours instead of having their pay reduced. These findings provide insights that can be incorporated into COVID-19 recovery strategies. Level of Evidence: III. Cite this article: Bone Jt Open 2021;2(7):562–568

Aims. The purpose of our study was to determine which groups of orthopaedic providers favour virtual care, and analyze overall orthopaedic provider perceptions of virtual care. We hypothesize that providers with less clinical experience will favour virtual care, and that orthopaedic providers overall will show increased preference for virtual care during the COVID-19 pandemic and decreased preference during non-pandemic circumstances. Methods. An orthopaedic research consortium at an academic medical system developed a survey examining provider perspectives regarding orthopaedic virtual care. Survey items were scored on a 1 to 5 Likert scale (1 = “strongly disagree”, 5 = “strongly agree”) and compared using nonparametric Mann-Whitney U test. Results. Providers with less experience were more likely to recommend virtual care for follow-up visits (3.61 on the Likert scale (SD 0.95) vs 2.90 (SD 1.23); p = 0.006) and feel that virtual care was essential to patient wellbeing (3.98 (SD 0.95) vs 3.00 (SD 1.16); p < 0.001) during the pandemic. Less experienced providers also viewed virtual visits as providing a similar level of care as in-person visits (2.41 (SD 1.02) vs 1.76 (SD 0.87); p = 0.006) and more time-efficient than in-person visits (3.07 (SD 1.19) vs 2.34 (SD 1.14); p = 0.012) in non-pandemic circumstances. During the pandemic, most providers viewed virtual care as effective in providing essential care (83.6%, n = 51) and wanted to schedule patients for virtual care follow-up (82.2%, n = 50); only 10.9% (n = 8) of providers preferred virtual visits in non-pandemic circumstances. Conclusion. Orthopaedic providers with less clinical experience seem to favourably view virtual care both during the pandemic and under non-pandemic circumstances. Providers in general appear to view virtual care positively during the pandemic but are less accommodating towards it in non-pandemic circumstances. Cite this article: Bone Jt Open 2021;2(6):405–410

Objectives. This investigation sought to advance the work published in our prior biomechanical study (Journal of Orthopaedic Research, 2016). We specifically sought to determine whether there are additional easy-to-measure parameters on plain radiographs of the proximal humerus that correlate more strongly with ultimate fracture load, and whether a parameter resembling the Dorr strength/quality characterisation of proximal femurs can be applied to humeri. Materials and Methods. A total of 33 adult humeri were used from a previous study where we quantified bone mineral density of the proximal humerus using radiographs and dual-energy x-ray absorptiometry (DEXA), and regional mean cortical thickness and cortical index using radiographs. The bones were fractured in a simulated backwards fall with the humeral head loaded at 2 mm/second via a frustum angled at 30° from the long axis of the bone. Correlations were assessed with ultimate fracture load and these new parameters: cortical index expressed in areas (“areal cortical index”) of larger regions of the diaphysis; the canal-to-calcar ratio used analogous to its application in proximal femurs; and the recently described medial cortical ratio. Results. The three new parameters showed the following correlations with ultimate fracture load: areal cortical index (r = 0.56, p < 0.001); canal-to-calcar ratio (r = 0.38, p = 0.03); and medial cortical ratio (r = 0.49, p < 0.005). These correlations were weaker when compared with those that we previously reported: mean cortical thickness of the proximal diaphysis versus ultimate fracture load (r = 0.71; p < 0.001); and mean density in the central humeral head versus ultimate fracture load (r = 0.70; p < 0.001). Conclusion. Simple-to-measure radiographic parameters of the proximal humerus reported previously are more useful in predicting ultimate fracture load than are areal cortical index, canal-to-calcar ratio, and medial cortical ratio. Cite this article: J. G. Skedros, C. S. Mears, W. Z. Burkhead. Ultimate fracture load of cadaver proximal humeri correlates more strongly with mean combined cortical thickness than with areal cortical index, DEXA density, or canal-to-calcar ratio. Bone Joint Res 2017;6:1–7. DOI: 10.1302/2046-3758.61.BJR-2016-0145.R1

Aims

To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design.

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Orthopaedic surgery requires grafts with sufficient mechanical strength. For this purpose, decellularized tissue is an available option that lacks the complications of autologous tissue. However, it is not widely used in orthopaedic surgeries. This study investigated clinical trials of the use of decellularized tissue grafts in orthopaedic surgery.

In 2017, the British Society for Children’s Orthopaedic Surgery engaged the profession and all relevant stakeholders in two formal research prioritization processes. In this editorial, we describe the impact of this prioritization on funding, and how research in children’s orthopaedics, which was until very recently a largely unfunded and under-investigated area, is now flourishing. Establishing research priorities was a crucial step in this process.

Cite this article: Bone Joint J 2024;106-B(5):422–424.

Aims

The aim of this study was to evaluate medium- to long-term outcomes and complications of the Stanmore Modular Individualised Lower Extremity System (SMILES) rotating hinge implant in revision total knee arthroplasty (rTKA) at a tertiary unit. It is hypothesized that this fully cemented construct leads to satisfactory clinical outcomes.

Aims

A novel enhanced cement fixation (EF) tibial implant with deeper cement pockets and a more roughened bonding surface was released to market for an existing total knee arthroplasty (TKA) system.This randomized controlled trial assessed fixation of the both the EF (ATTUNE S+) and standard (Std; ATTUNE S) using radiostereometric analysis.

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: Bone Joint Res 2023;12(7):447–454.

Aims

The aim of this study was to identify the information topics that should be addressed according to the parents of children with developmental dysplasia of the hip (DDH) in the diagnostic and treatment phase during the first year of life. Second, we explored parental recommendations to further optimize the information provision in DDH care.

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This study describes the variation in the annual volumes of revision hip arthroplasty (RHA) undertaken by consultant surgeons nationally, and the rate of accrual of RHA and corresponding primary hip arthroplasty (PHA) volume for new consultants entering practice.