Aims. The aims of this systematic review were to assess the learning curve of semi-active robotic arm-assisted total hip arthroplasty (rTHA), and to compare the accuracy, patient-reported functional outcomes, complications, and survivorship between rTHA and manual total hip arthroplasty (mTHA). Methods. Searches of PubMed, Medline, and Google Scholar were performed in April 2020 in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “robotic”, “hip”, and “arthroplasty”. The criteria for inclusion were published clinical research articles reporting the learning curve for rTHA (robotic arm-assisted only) and those comparing the implantation accuracy, functional outcomes, survivorship, or complications with mTHA. Results. There were 501 articles initially identified from databases and references. Following full text screening, 17 articles that satisfied the inclusion criteria were included. Four studies reported the learning curve of rTHA, 13 studies reported on implant positioning, five on functional outcomes, ten on complications, and four on survivorship. The meta-analysis showed a significantly greater number of cases of acetabular component placement in the safe zone compared with the mTHA group (95% confidence interval (CI) 4.10 to 7.94; p < 0.001) and that rTHA resulted in a significantly better Harris Hip Score compared to mTHA in the short- to mid-term follow-up (95% CI 0.46 to 5.64; p = 0.020). However, there was no difference in infection rates, dislocation rates, overall complication rates, and survival rates at short-term follow-up. Conclusion. The learning curve of rTHA was between 12 and 35 cases, which was dependent on the assessment goal, such as operating time, accuracy, and team working. Robotic arm-assisted total hip arthroplasty was associated with improved accuracy of component positioning and functional outcome, however no difference in complication rates or survival were observed at short- to mid-term follow-up. Overall, there remains an absence of high-quality level I evidence and cost analysis comparing rTHA and mTHA. Cite this article: Bone Joint J 2021;103-B(6):1009–1020

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.

Aims

Computer-based applications are increasingly being used by orthopaedic surgeons in their clinical practice. With the integration of technology in surgery, augmented reality (AR) may become an important tool for surgeons in the future. By superimposing a digital image on a user’s view of the physical world, this technology shows great promise in orthopaedics. The aim of this review is to investigate the current and potential uses of AR in orthopaedics.

Aims

Dislocation is the most common indication for further surgery following total hip arthroplasty (THA) when undertaken in patients with a femoral neck fracture. This study aimed to assess the complication rates of THA with dual mobility components (THA-DMC) following a femoral neck fracture and to compare outcomes between THA-DMC, conventional THA, and hemiarthroplasty (HA).