Aims. Intra-articular (IA) injection may be used when treating hip osteoarthritis (OA). Common injections include steroids, hyaluronic acid (HA), local anaesthetic, and platelet-rich plasma (PRP). Network meta-analysis allows for comparisons between two or more treatment groups and uses direct and indirect comparisons between interventions. This network meta-analysis aims to compare the efficacy of various IA injections used in the management of hip OA with a follow-up of up to six months. Methods. This systematic review and network meta-analysis used a Bayesian random-effects model to evaluate the direct and indirect comparisons among all treatment options. PubMed, Web of Science, Clinicaltrial.gov, EMBASE, MEDLINE, and the Cochrane Library were searched from inception to February 2023. Randomized controlled trials (RCTs) which evaluate the efficacy of HA, PRP, local anaesthetic, steroid, steroid+anaesthetic, HA+PRP, and physiological saline injection as a placebo, for patients with hip OA were included. Results. In this meta-analysis of 16 RCTs with a total of 1,735 participants, steroid injection was found to be significantly more effective than placebo injection on reported pain at three months, but no significant difference was observed at six months. Furthermore, steroid injection was considerably more effective than placebo injection for functional outcomes at three months, while the combination of HA+PRP injection was substantially more effective at six months. Conclusion. Evidence suggests that steroid injection is more effective than saline injection for the treatment of hip joint pain, and restoration of functional outcomes. Cite this article: Bone Joint J 2024;106-B(6):532–539

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.

Cite this article: Bone Joint J 2022;104-B(12):1292–1303.