Aims. Robotic-assisted unicompartmental knee arthroplasty (R-UKA) has been proposed as an approach to improve the results of the conventional manual UKA (C-UKA). The aim of this meta-analysis was to analyze the studies comparing R-UKA and C-UKA in terms of clinical outcomes, radiological results, operating time, complications, and revisions. Methods. The literature search was conducted on three databases (PubMed, Cochrane, and Web of Science) on 20 February 2024 according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Inclusion criteria were comparative studies, written in the English language, with no time limitations, on the comparison of R-UKA and C-UKA. The quality of each article was assessed using the Downs and Black Checklist for Measuring Quality. Results. Among the 3,669 articles retrieved, 21 studies on 19 series of patients were included. A total of 3,074 patients (59.5% female and 40.5% male; mean age 65.2 years (SD 3.9); mean BMI 27.4 kg/m. 2. (SD 2.2)) were analyzed. R-UKA obtained a superior Knee Society Score improvement compared to C-UKA (mean difference (MD) 4.9; p < 0.001) and better Forgotten Joint Score postoperative values (MD 5.5; p = 0.032). The analysis of radiological outcomes did not find a statistically significant difference between the two approaches. R-UKA showed longer operating time (MD 15.6; p < 0.001), but reduced complication and revision rates compared to C-UKA (5.2% vs 10.1% and 4.1% vs 7.2%, respectively). Conclusion. This meta-analysis showed that the robotic approach for UKA provided a significant improvement in functional outcomes compared to the conventional manual technique. R-UKA showed similar radiological results and longer operating time, but reduced complication and revision rates compared to C-UKA. Overall, R-UKA seems to provide relevant benefits over C-UKA in the management of patients undergoing UKA. Cite this article: Bone Jt Open 2024;5(5):374–384

Aims. 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. Methods. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures. Results. Out of 1,160 studies initially identified, 39 were included. Most studies (85%) were published between 2020 and 2024, with 82% using publicly available datasets, primarily the Osteoarthritis Initiative. ML methods were predominantly supervised, with significant variability in the definitions of OA progression: most studies focused on structural changes (59%), while fewer addressed pain progression or both. Deep learning was used in 44% of studies, while automated ML was used in 5%. There was a lack of standardization in evaluation metrics and limited external validation. Interpretability was explored in 54% of studies, primarily using SHapley Additive exPlanations. Conclusion. Our systematic review demonstrates the feasibility of ML models in predicting OA progression, but also uncovers critical limitations that currently restrict their clinical applicability. Future priorities should include diversifying data sources, standardizing outcome measures, enforcing rigorous validation, and integrating more sophisticated algorithms. This paradigm shift from predictive modelling to actionable clinical tools has the potential to transform patient care and disease management in orthopaedic practice. Cite this article: Bone Joint J 2024;106-B(11):1216–1222

Aims. The value of core decompression (CD) in the treatment of osteonecrosis of the femoral head (ONFH) remains controversial. We conducted a systematic review and meta-analysis to evaluate whether CD combined with other treatments could improve the clinical and radiological outcomes of ONFH patients compared with CD alone. Methods. We searched the PubMed, Embase, Web of Science, and Cochrane Library databases until June 2020. All randomized controlled trials (RCTs) and clinical controlled trials (CCTs) comparing CD alone and CD combined with other measures (CD + cell therapy, CD + bone grafting, CD + porous tantalum rod, etc.) for the treatment of ONFH were considered eligible for inclusion. The primary outcomes of interest were Harris Hip Score (HHS), ONFH stage progression, structural failure (collapse) of the femoral head, and conversion to total hip arthroplasty (THA). The pooled data were analyzed using Review Manager 5.3 software. Results. A total of 20 studies with 2,123 hips were included (CD alone = 768, CD combined with other treatments = 1,355). The combination of CD with other therapeutic interventions resulted in a higher HHS (mean difference (MD) = 6.46, 95% confidence interval (CI) = 2.10 to 10.83, p = 0.004) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score (MD = −10.92, 95% CI = -21.41 to -4.03, p = 0.040) and a lower visual analogue scale (VAS) score (MD = −0.99, 95% CI = -1.56 to -0.42, p < 0.001) than CD alone. For the rates of disease stage progression, 91 (20%) progressed in the intervention group compared to 146 (36%) in the control group (odds ratio (OR) = 0.32, 95% CI = 0.16 to 0.64, p = 0.001). In addition, the intervention group had a more significant advantage in delaying femoral head progression to the collapsed stage (OR = 0.32, 95% CI = 0.17 to 0.61, p < 0.001) and reducing the odds of conversion to THA (OR = 0.35, 95% CI = 0.23 to 0.55, p < 0.001) compared to the control group. There were no serious adverse events in either group. Subgroup analysis showed that the addition of cell therapy significantly improved clinical and radiological outcomes compared to CD alone, and this approach appeared to be more effective than other therapies, particularly in precollapse (stage I to II) ONFH patients. Conclusion. There was marked heterogeneity in the studies. There is a trend towards improved clinical outcomes with the addition of stem cell therapy to CD. Cite this article: Bone Joint Res 2021;10(7):445–458

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To systematically review the efficacy of split tendon transfer surgery on gait-related outcomes for children and adolescents with cerebral palsy (CP) and spastic equinovarus foot deformity.

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To systematically review the predominant complication rates and changes to patient-reported outcome measures (PROMs) following osteochondral allograft (OCA) transplantation for shoulder instability.

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The aims of this study were to identify and evaluate the current literature examining the prognostic factors which are associated with failure of total elbow arthroplasty (TEA).

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Posterior malleolar (PM) fractures are commonly associated with ankle fractures, pilon fractures, and to a lesser extent tibial shaft fractures. The tibialis posterior (TP) tendon entrapment is a rare complication associated with PM fractures. If undiagnosed, TP entrapment is associated with complications, ranging from reduced range of ankle movement to instability and pes planus deformities, which require further surgeries including radical treatments such as arthrodesis.

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Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.

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Giant cell tumour of bone (GCTB) treatment changed since the introduction of denosumab from purely surgical towards a multidisciplinary approach, with recent concerns of higher recurrence rates after denosumab. We evaluated oncological, surgical, and functional outcomes for distal radius GCTB, with a critically appraised systematic literature review.

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The aim of this study was to review the current evidence surrounding curve type and morphology on curve progression risk in adolescent idiopathic scoliosis (AIS).

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Return to sport following undergoing total (TKA) and unicompartmental knee arthroplasty (UKA) has been researched with meta-analyses and systematic reviews of varying quality. The aim of this study is to create an umbrella review to consolidate the data into consensus guidelines for returning to sports following TKA and UKA.

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Recurrent dislocation is both a cause and consequence of glenoid bone loss, and the extent of the bony defect is an indicator guiding operative intervention. Literature suggests that loss greater than 25% requires glenoid reconstruction. Measuring bone loss is controversial; studies use different methods to determine this, with no clear evidence of reproducibility. A systematic review was performed to identify existing CT-based methods of quantifying glenoid bone loss and establish their reliability and reproducibility

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Metal allergy in knee arthroplasty patients is a controversial topic. We aimed to conduct a scoping review to clarify the management of metal allergy in primary and revision total knee arthroplasty (TKA).

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It is important to understand the rate of complications associated with the increasing burden of revision shoulder arthroplasty. Currently, this has not been well quantified. This review aims to address that deficiency with a focus on complication and reoperation rates, shoulder outcome scores, and comparison of anatomical and reverse prostheses when used in revision surgery.

Background

Due to the overwhelming demand for trauma services, resulting from increasing emergency department attendances over the past decade, virtual fracture clinics (VFCs) have become the fashion to keep up with the demand and help comply with the BOA Standards for Trauma and Orthopaedics (BOAST) guidelines. In this article, we perform a systematic review asking, “How useful are VFCs?”, and what injuries and conditions can be treated safely and effectively, to help decrease patient face to face consultations. Our primary outcomes were patient satisfaction, clinical efficiency and cost analysis, and clinical outcomes.

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Scapular notching is thought to have an adverse effect on the outcome of reverse total shoulder arthroplasty (RTSA). However, the matter is still controversial. The aim of this study was to determine the clinical impact of scapular notching on outcomes after RTSA.

Objectives

This review aims to summarize the outcomes used to describe effectiveness of treatments for paediatric wrist fractures within existing literature.

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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.

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Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes.

Bone is one of the most highly adaptive tissues in the body, possessing the capability to alter its morphology and function in response to stimuli in its surrounding environment. The ability of bone to sense and convert external mechanical stimuli into a biochemical response, which ultimately alters the phenotype and function of the cell, is described as mechanotransduction. This review aims to describe the fundamental physiology and biomechanisms that occur to induce osteogenic adaptation of a cell following application of a physical stimulus. Considerable developments have been made in recent years in our understanding of how cells orchestrate this complex interplay of processes, and have become the focus of research in osteogenesis. We will discuss current areas of preclinical and clinical research exploring the harnessing of mechanotransductive properties of cells and applying them therapeutically, both in the context of fracture healing and de novo bone formation in situations such as nonunion.

Cite this article: Bone Joint Res 2019;9(1):1–14.