Aims. This systematic review aims to compare the precision of component positioning, patient-reported outcome measures (PROMs), complications, survivorship, cost-effectiveness, and learning curves of MAKO robotic arm-assisted unicompartmental knee arthroplasty (RAUKA) with manual medial unicompartmental knee arthroplasty (mUKA). Methods. Searches of PubMed, MEDLINE, and Google Scholar were performed in November 2021 according to the Preferred Reporting Items for Systematic Review and Meta-­Analysis statement. Search terms included “robotic”, “unicompartmental”, “knee”, and “arthroplasty”. Published clinical research articles reporting the learning curves and cost-effectiveness of MAKO RAUKA, and those comparing the component precision, functional outcomes, survivorship, or complications with mUKA, were included for analysis. Results. A total of 179 articles were identified from initial screening, of which 14 articles satisfied the inclusion criteria and were included for analysis. The papers analyzed include one on learning curve, five on implant positioning, six on functional outcomes, five on complications, six on survivorship, and three on cost. The learning curve was six cases for operating time and zero for precision. There was consistent evidence of more precise implant positioning with MAKO RAUKA. Meta-analysis demonstrated lower overall complication rates associated with MAKO RAUKA (OR 2.18 (95% confidence interval (CI) 1.06 to 4.49); p = 0.040) but no difference in re-intervention, infection, Knee Society Score (KSS; mean difference 1.64 (95% CI -3.00 to 6.27); p = 0.490), or Western Ontario and McMaster Universities Arthritis Index (WOMAC) score (mean difference -0.58 (95% CI -3.55 to 2.38); p = 0.700). MAKO RAUKA was shown to be a cost-effective procedure, but this was directly related to volume. Conclusion. MAKO RAUKA was associated with improved precision of component positioning but was not associated with improved PROMs using the KSS and WOMAC scores. Future longer-term studies should report functional outcomes, potentially using scores with minimal ceiling effects and survival to assess whether the improved precision of MAKO RAUKA results in better outcomes. Cite this article: Bone Joint J 2022;104-B(5):541–548

Aims. The aim of this study was to report the pooled prevalence of post-traumatic osteoarthritis (PTOA) and examine whether the risk of developing PTOA after anterior cruciate ligament (ACL) injury has decreased in recent decades. Methods. The PubMed and Web of Science databases were searched from 1 January 1980 to 11 May 2022. Patient series, observational studies, and clinical trials having reported the prevalence of radiologically confirmed PTOA after ACL injury, with at least a ten-year follow-up, were included. All studies were analyzed simultaneously, and separate analyses of the operative and nonoperative knees were performed. The prevalence of PTOA was calculated separately for each study, and pooled prevalence was reported with 95% confidence intervals (CIs) using either a fixed or random effects model. To examine the effect of the year of injury on the prevalence, a logit transformed meta-regression analysis was used with a maximum-likelihood estimator. Results from meta-regression analyses were reported with the unstandardized coefficient (β). Results. The pooled prevalence of PTOA was 37.9% (95% CI 32.1 to 44) for operatively treated ACL injuries with a median follow-up of 14.6 years (interquartile range (IQR) 10.6 to 16.7). For nonoperatively treated ACL injuries, the prevalence was 40.5% (95% CI 28.9 to 53.3), with a median of follow-up of 15 years (IQR 11.7 to 20.0). The association between the year of operation and the prevalence of PTOA was weak and imprecise and not related to the choice of treatment (operative β -0.038 (95% CI -0.076 to 0.000) and nonoperative β -0.011 (95% CI -0.101 to 0.079)). Conclusion. The initial injury, irrespective of management, has, by the balance of probability, resulted in PTOA within 20 years. In addition, the prevalence of PTOA has only slightly decreased during past decades. Therefore, further research is warranted to develop strategies to prevent the development of PTOA after ACL injuries. Cite this article: Bone Joint J 2023;105-B(11):1140–1148

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.

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Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA.

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To determine whether obesity and malnutrition have a synergistic effect on outcomes from skeletal trauma or elective orthopaedic surgery.

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Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials.

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As an increasing number of female surgeons are choosing orthopaedics, it is important to recognize the impact of pregnancy within this cohort. The aim of this review was to examine common themes and data surrounding pregnancy, parenthood, and fertility within orthopaedics.

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In the UK, the agricultural, military, and construction sectors have stringent rules about the use of hearing protection due to the risk of noise-induced hearing loss. Orthopaedic staff may also be at risk due to the use of power tools. The UK Health and Safety Executive (HSE) have clear standards as to what are deemed acceptable occupational levels of noise on A-weighted and C-weighted scales. The aims of this review were to assess the current evidence on the testing of exposure to noise in orthopaedic operating theatres to see if it exceeds these regulations.

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The preoperative diagnosis of periprosthetic joint infection (PJI) remains a challenge due to a lack of biomarkers that are both sensitive and specific. We investigated the performance characteristics of polymerase chain reaction (PCR), interleukin-6 (IL6), and calprotectin of synovial fluid in the diagnosis of PJI.

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The goal of the current systematic review was to assess the impact of implant placement accuracy on outcomes following total knee arthroplasty (TKA).

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This study aimed to answer two questions: what are the best diagnostic methods for diagnosing bacterial arthritis of a native joint?; and what are the most commonly used definitions for bacterial arthritis of a native joint?

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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).

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This study evaluates the quality of patient-reported outcome measures (PROMs) reported in childhood fracture trials and recommends outcome measures to assess and report physical function, functional capacity, and quality of life using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) standards.

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The aim of this systematic review and meta-analysis is to evaluate differences in functional outcomes and complications between single- (SI) and double-incision (DI) techniques for the treatment of distal biceps tendon rupture.

Deep gluteal syndrome is an increasingly recognized disease entity, caused by compression of the sciatic or pudendal nerve due to non-discogenic pelvic lesions. It includes the piriformis syndrome, the gemelli-obturator internus syndrome, the ischiofemoral impingement syndrome, and the proximal hamstring syndrome. The concept of the deep gluteal syndrome extends our understanding of posterior hip pain due to nerve entrapment beyond the traditional model of the piriformis syndrome. Nevertheless, there has been terminological confusion and the deep gluteal syndrome has often been undiagnosed or mistaken for other conditions. Careful history-taking, a physical examination including provocation tests, an electrodiagnostic study, and imaging are necessary for an accurate diagnosis.

After excluding spinal lesions, MRI scans of the pelvis are helpful in diagnosing deep gluteal syndrome and identifying pathological conditions entrapping the nerves. It can be conservatively treated with multidisciplinary treatment including rest, the avoidance of provoking activities, medication, injections, and physiotherapy.

Endoscopic or open surgical decompression is recommended in patients with persistent or recurrent symptoms after conservative treatment or in those who may have masses compressing the sciatic nerve.

Many physicians remain unfamiliar with this syndrome and there is a lack of relevant literature. This comprehensive review aims to provide the latest information about the epidemiology, aetiology, pathology, clinical features, diagnosis, and treatment.

Cite this article: Bone Joint J 2020;102-B(5):556–567.

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The aims of this study were to validate the outcome of total elbow arthroplasty (TEA) in patients with rheumatoid arthritis (RA), and to identify factors that affect the outcome.

The application of robotics in the operating theatre for knee arthroplasty remains controversial. As with all new technology, the introduction of new systems might be associated with a learning curve. However, guidelines on how to assess the introduction of robotics in the operating theatre are lacking. This systematic review aims to evaluate the current evidence on the learning curve of robot-assisted knee arthroplasty. An extensive literature search of PubMed, Medline, Embase, Web of Science, and Cochrane Library was conducted. Randomized controlled trials, comparative studies, and cohort studies were included. Outcomes assessed included: time required for surgery, stress levels of the surgical team, complications in regard to surgical experience level or time needed for surgery, size prediction of preoperative templating, and alignment according to the number of knee arthroplasties performed. A total of 11 studies met the inclusion criteria. Most were of medium to low quality. The operating time of robot-assisted total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA) is associated with a learning curve of between six to 20 cases and six to 36 cases respectively. Surgical team stress levels show a learning curve of seven cases in TKA and six cases for UKA. Experience with the robotic systems did not influence implant positioning, preoperative planning, and postoperative complications. Robot-assisted TKA and UKA is associated with a learning curve regarding operating time and surgical team stress levels. Future evaluation of robotics in the operating theatre should include detailed measurement of the various aspects of the total operating time, including total robotic time and time needed for preoperative planning. The prior experience of the surgical team should also be evaluated and reported.

Cite this article: Bone Joint J 2020;102-B(4):407–413.

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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.

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We performed a meta-analysis investigating the association between preoperative psychological distress and postoperative pain and function after total knee arthroplasty (TKA).

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The aims of this systematic review were to describe the quantity and methodological quality of meta-analyses in orthopaedic surgery published during the last 17 years.