Aims. The aim of this meta-analysis is to assess the association between exchange of modular parts in debridement, antibiotics, and implant retention (DAIR) procedure and outcomes for hip and
Osteoarthritis (OA) is mainly caused by ageing, strain, trauma, and congenital joint abnormalities, resulting in articular cartilage degeneration. During the pathogenesis of OA, the changes in subchondral bone (SB) are not only secondary manifestations of OA, but also an active part of the disease, and are closely associated with the severity of OA. In different stages of OA, there were microstructural changes in SB. Osteocytes, osteoblasts, and osteoclasts in SB are important in the pathogenesis of OA. The signal transduction mechanism in SB is necessary to maintain the balance of a stable phenotype, extracellular matrix (ECM) synthesis, and bone remodelling between articular cartilage and SB. An imbalance in signal transduction can lead to reduced cartilage quality and SB thickening, which leads to the progression of OA. By understanding changes in SB in OA, researchers are exploring drugs that can regulate these changes, which will help to provide new ideas for the treatment of OA. Cite this article:
The aim of this study was to perform a systematic review and bias evaluation of the current literature to create an overview of risk factors for re-revision following revision total knee arthroplasty (rTKA). A systematic search of MEDLINE and Embase was completed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The studies were required to include a population of index rTKAs. Primary or secondary outcomes had to be re-revision. The association between preoperative factors and the effect on the risk for re-revision was also required to be reported by the studies.Aims
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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. 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.Aims
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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. 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.Aims
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Biofilm-related infection is a major complication that occurs in orthopaedic surgery. Various treatments are available but efficacy to eradicate infections varies significantly. A systematic review was performed to evaluate therapeutic interventions combating biofilm-related infections on in vivo animal models. Literature research was performed on PubMed and Embase databases. Keywords used for search criteria were “bone AND biofilm”. Information on the species of the animal model, bacterial strain, evaluation of biofilm and bone infection, complications, key findings on observations, prevention, and treatment of biofilm were extracted.Aims
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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. Systematic reviews and meta-analyses written between 2010 and 2020 were systematically searched. Studies were independently screened by two reviewers and methodology quality was assessed. Variables for analysis included objective classification of which sports are safe to participate in postoperatively, time to return to sport, prognostic indicators of returning, and reasons patients do not.Aims
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Transforming growth factor-beta2 (TGF-β2) is recognized as a versatile cytokine that plays a vital role in regulation of joint development, homeostasis, and diseases, but its role as a biological mechanism is understood far less than that of its counterpart, TGF-β1. Cartilage as a load-resisting structure in vertebrates however displays a fragile performance when any tissue disturbance occurs, due to its lack of blood vessels, nerves, and lymphatics. Recent reports have indicated that TGF-β2 is involved in the physiological processes of chondrocytes such as proliferation, differentiation, migration, and apoptosis, and the pathological progress of cartilage such as osteoarthritis (OA) and rheumatoid arthritis (RA). TGF-β2 also shows its potent capacity in the repair of cartilage defects by recruiting autologous mesenchymal stem cells and promoting secretion of other growth factor clusters. In addition, some pioneering studies have already considered it as a potential target in the treatment of OA and RA. This article aims to summarize the current progress of TGF-β2 in cartilage development and diseases, which might provide new cues for remodelling of cartilage defect and intervention of cartilage diseases.
Osteoarthritis (OA), one of the most common motor system disorders, is a degenerative disease involving progressive joint destruction caused by a variety of factors. At present, OA has become the fourth most common cause of disability in the world. However, the pathogenesis of OA is complex and has not yet been clarified. Long non-coding RNA (lncRNA) refers to a group of RNAs more than 200 nucleotides in length with limited protein-coding potential, which have a wide range of biological functions including regulating transcriptional patterns and protein activity, as well as binding to form endogenous small interference RNAs (siRNAs) and natural microRNA (miRNA) molecular sponges. In recent years, a large number of lncRNAs have been found to be differentially expressed in a variety of pathological processes of OA, including extracellular matrix (ECM) degradation, synovial inflammation, chondrocyte apoptosis, and angiogenesis. Obviously, lncRNAs play important roles in regulating gene expression, maintaining the phenotype of cartilage and synovial cells, and the stability of the intra-articular environment. This article reviews the results of the latest research into the role of lncRNAs in a variety of pathological processes of OA, in order to provide a new direction for the study of OA pathogenesis and a new target for prevention and treatment. Cite this article:
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:
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:
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. A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines using the MEDLINE, Embase, PubMed, and Cochrane databases. Studies included were case series, case control series, and cohort studies looking specifically at HSF.Aims
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