Aims. 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. Methods. We included 76 patients with distal radius GCTB in three sarcoma centres (1990 to 2019). Median follow-up was 8.8 years (2 to 23). Seven patients underwent curettage, 38 curettage with adjuvants, and 31 resection; 20 had denosumab. Results. Recurrence rate was 71% (5/7) after curettage, 32% (12/38) after curettage with adjuvants, and 6% (2/31) after resection. Median time to recurrence was 17 months (4 to 77). Recurrences were treated with curettage with adjuvants (11), resection (six), or curettage (two). Overall, 84% (38/45) was cured after one to thee intralesional procedures. Seven patients had 12 months neoadjuvant denosumab (5 to 15) and sixmonths adjuvant denosumab; two recurred (29%). Twelve patients had six months neoadjuvant denosumab (4 to 10); five recurred (42%). Two had pulmonary metastases (2.6%), both stable after denosumab. Complication rate was 18% (14/76, with 11 requiring surgery). At follow-up, median MusculoSkeletal Tumour Society score was 28 (18 to 30), median Short Form-36 Health Survey was 86 (41 to 95), and median Disability of Arm, Shoulder, and Hand was 7.8 (0 to 58). Conclusion. Distal radius GCTB treatment might deviate from general GCTB treatment because of
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. A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias.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
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
Methods
To systematically review the predominant complication rates and changes to patient-reported outcome measures (PROMs) following osteochondral allograft (OCA) transplantation for shoulder instability. This systematic review, following PRISMA guidelines and registered in PROSPERO, involved a comprehensive literature search using PubMed, Embase, Web of Science, and Scopus. Key search terms included “allograft”, “shoulder”, “humerus”, and “glenoid”. The review encompassed 37 studies with 456 patients, focusing on primary outcomes like failure rates and secondary outcomes such as PROMs and functional test results.Aims
Methods
Evidence exists of a consistent decline in the value and time that medical schools place upon their undergraduate orthopaedic placements. This limited exposure to trauma and orthopaedics (T&O) during medical school will be the only experience in the speciality for the majority of doctors. This review aims to provide an overview of undergraduate orthopaedic training in the UK. This review summarizes the relevant literature from the last 20 years in the UK. Articles were selected from database searches using MEDLINE, EMBASE, ERIC, Cochrane, and Web of Science. A total of 16 papers met the inclusion criteria.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 ability to edit DNA at the nucleotide level using clustered regularly interspaced short palindromic repeats (CRISPR) systems is a relatively new investigative tool that is revolutionizing the analysis of many aspects of human health and disease, including orthopaedic disease. CRISPR, adapted for mammalian cell genome editing from a bacterial defence system, has been shown to be a flexible, programmable, scalable, and easy-to-use gene editing tool. Recent improvements increase the functionality of CRISPR through the engineering of specific elements of CRISPR systems, the discovery of new, naturally occurring CRISPR molecules, and modifications that take CRISPR beyond gene editing to the regulation of gene transcription and the manipulation of RNA. Here, the basics of CRISPR genome editing will be reviewed, including a description of how it has transformed some aspects of molecular musculoskeletal research, and will conclude by speculating what the future holds for the use of CRISPR-related treatments and therapies in clinical orthopaedic practice. Cite this article:
This systematic review examines the current literature regarding surgical techniques for restoring articular cartilage in the hip, from the older microfracture techniques involving perforation to the subchondral bone, to adaptations of this technique using nanofractures and scaffolds. This review discusses the autologous and allograft transfer systems and the autologous matrix-induced chondrogenesis (AMIC) technique, as well as a summary of the previously discussed techniques, which could become common practice for restoring articular cartilage, thus reducing the need for total hip arthroplasty. Using the
Despite its intrinsic ability to regenerate form and function after injury, bone tissue can be challenged by a multitude of pathological conditions. While innovative approaches have helped to unravel the cascades of bone healing, this knowledge has so far not improved the clinical outcomes of bone defect treatment. Recent findings have allowed us to gain in-depth knowledge about the physiological conditions and biological principles of bone regeneration. Now it is time to transfer the lessons learned from bone healing to the challenging scenarios in defects and employ innovative technologies to enable biomaterial-based strategies for bone defect healing. This review aims to provide an overview on endogenous cascades of bone material formation and how these are transferred to new perspectives in biomaterial-driven approaches in bone regeneration. Cite this article: T. Winkler, F. A. Sass, G. N. Duda, K. Schmidt-Bleek. A review of biomaterials in bone defect healing, remaining shortcomings and future opportunities for bone tissue engineering: The unsolved challenge.
