The Bone & Joint Journal has published several consensus statements in recent years, many of which have positively influenced clinical practice and policy.^1-13 However, even the most valued consensus statements have limitations, and all ultimately represent Level V evidence. Consensus studies add greatest value where higher-order evidence to aid decision making is ambiguous or lacking. In all settings, care must be taken to critically appraise standards of methodology, with particular attention to potential biases that may influence the conclusions which are drawn.

Cite this article: Bone Joint J 2023;105-B(4):343–346.

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines.

Cite this article: Bone Joint J 2021;103-B(12):1754–1758.

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.

Cell therapies hold significant promise for the treatment of injured or diseased musculoskeletal tissues. However, despite advances in research, there is growing concern about the increasing number of clinical centres around the world that are making unwarranted claims or are performing risky biological procedures. Such providers have been known to recommend, prescribe, or deliver so called ‘stem cell’ preparations without sufficient data to support their true content and efficacy. In this annotation, we outline the current environment of stem cell-based treatments and the strategies of marketing directly to consumers. We also outline the difficulties in the regulation of these clinics and make recommendations for best practice and the identification and reporting of illegitimate providers.

Cite this article: Bone Joint J 2020;102-B(2):148–154

We recently published a paper comparing the incidence of adverse outcomes after unicompartmental and total knee arthroplasty (UKA and TKA). The conclusion of this study, which was in favour of UKA, was dismissed as “biased” in a review in Bone & Joint 360. Although this study is one of the least biased comparisons of UKA and TKA, this episode highlights the biases that exist both for and against UKA. In this review, we explore the different types of bias, particularly selection, reporting and measurement. We conclude that comparisons between UKA and TKA are open to bias. These biases can be so marked, particularly in comparisons based just on national registry data, that the conclusions can be misleading. For a fair comparison, data from randomised studies or well-matched, prospective observational cohort studies, which include registry data, are required, and multiple outcome measures should be used. The data of this type that already exist suggest that if UKA is used appropriately, compared with TKA, its advantages outweigh its disadvantages.

Cite this article: Bone Joint J 2017;99-B:12–15.

Procedures performed at the incorrect anatomical site are commonly perceived as being relatively rare. However, they can be a devastating event for patients and doctors. Evidence from the United Kingdom and North America suggests that wrong-site, wrong-procedure and wrong-patient events occur more commonly than we think. Furthermore, their incidence may be increasing as NHS Trusts increase the volume and complexity of procedures undertaken in order to cope with increasing demands on the system. In previous studies from North America orthopaedic surgery has been found to be the worst-offending specialty.

In this paper we review the existing literature on wrong-site surgery and analyse data from the National Patient Safety Agency and NHS Litigation Authority on 292 cases of wrong-site surgery in England and Wales. Orthopaedic surgery accounted for 87 (29.8%) of these cases. In the year 2006 to 2007, the rate of wrong-site surgery in England and Wales was highest in orthopaedic surgery, in which the estimated rate was 1:105 712 cases.

Randomised controlled trials represent the gold standard in the evaluation of outcome of treatment. They are needed because differences between treatment effects have been minimised and observational studies may give a biased estimation of the outcome. However, conducting this kind of trial is challenging. Several methodological issues, including patient or surgeon preference, blinding, surgical standardisation, as well as external validity, have to be addressed in order to lower the risk of bias. Specific tools have been developed in order to take into account the specificity of evaluation of the literature on non-pharmacological intervention. A better knowledge of methodological issues will allow the orthopaedic surgeon to conduct more appropriate studies and to better appraise the limits of his intervention.