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
Methods
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
Methods
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
Methods
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 knee periprosthetic joint infection (PJI). We conducted a systematic search on PubMed, Embase, Web of Science, and Cochrane library from inception until May 2021. Random effects meta-analyses and meta-regression was used to estimate, on a study level, the success rate of DAIR related to component exchange. Risk of bias was appraised using the (AQUILA) checklist.Aims
Methods
The diagnosis of periprosthetic joint infection (PJI) has always been challenging. Recently, D-dimer has become a promising biomarker in diagnosing PJI. However, there is controversy regarding its diagnostic value. We aim to investigate the diagnostic value of D-dimer in comparison to ESR and CRP. PubMed, Embase, and the Cochrane Library were searched in February 2020 to identify articles reporting on the diagnostic value of D-dimer on PJI. Pooled analysis was conducted to investigate the diagnostic value of D-dimer, CRP, and ESR.Aims
Methods
The aim of this meta-analysis was to compare the outcome of total elbow arthroplasty (TEA) undertaken for rheumatoid arthritis (RA) with TEA performed for post-traumatic conditions with regard to implant failure, functional outcome, and perioperative complications. We completed a comprehensive literature search on PubMed, Web of Science, Embase, and the Cochrane Library and conducted a systematic review and meta-analysis. Nine cohort studies investigated the outcome of TEA between RA and post-traumatic conditions. The preferred reporting items for systematic reviews and meta-analysis (Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)) guidelines and Newcastle-Ottawa scale were applied to assess the quality of the included studies. We assessed three major outcome domains: implant failures (including aseptic loosening, septic loosening, bushing wear, axle failure, component disassembly, or component fracture); functional outcomes (including arc of range of movement, Mayo Elbow Performance Score (MEPS), and the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire), and perioperative complications (including deep infection, intraoperative fracture, postoperative fracture, and ulnar neuropathy).Aims
Materials and Methods
