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
The principle strategies of fracture-related infection (FRI) treatment are debridement, antimicrobial therapy, and implant retention (DAIR) or debridement, antimicrobial therapy, and implant removal/exchange. Increasing the period between fracture fixation and FRI revision surgery is believed to be associated with higher failure rates after DAIR. However, a clear time-related cut-off has never been scientifically defined. This systematic review analyzed the influence of the interval between fracture fixation and FRI revision surgery on success rates after DAIR. A systematic literature search was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, in PubMed (including MEDLINE), Embase, and Web of Science Core Collection, investigating the outcome after DAIR procedures of long bone FRIs in clinical studies published until January 2020.Aims
Methods
Gender bias and sexual discrimination (GBSD) have been widely recognized across a range of fields and are now part of the wider social consciousness. Such conduct can occur in the medical workplace, with detrimental effects on recipients. The aim of this review was to identify the prevalence and impact of GBSD in orthopaedic surgery, and to investigate interventions countering such behaviours. A systematic review was conducted by searching Medline, EMCARE, CINAHL, PsycINFO, and the Cochrane Library Database in April 2020, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to which we adhered. Original research papers pertaining to the prevalence and impact of GBSD, or mitigating strategies, within orthopaedics were included for review.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
The aim of this study was to assess the quality and scope of the current cost-effectiveness analysis (CEA) literature in the field of hand and upper limb orthopaedic surgery. We conducted a systematic review of MEDLINE and the CEA Registry to identify CEAs that were conducted on or after 1 January 1997, that studied a procedure pertaining to the field of hand and upper extremity surgery, that were clinical studies, and that reported outcomes in terms of quality-adjusted life-years. We identified a total of 33 studies that met our inclusion criteria. The quality of these studies was assessed using the Quality of Health Economic Analysis (QHES) scale.Aims
Materials and Methods
