This study aimed to define the histopathology of degenerated humeral head cartilage and synovial inflammation of the glenohumeral joint in patients with omarthrosis (OmA) and cuff tear arthropathy (CTA). Additionally, the potential of immunohistochemical tissue biomarkers in reflecting the degeneration status of humeral head cartilage was evaluated. Specimens of the humeral head and synovial tissue from 12 patients with OmA, seven patients with CTA, and four body donors were processed histologically for examination using different histopathological scores. Osteochondral sections were immunohistochemically stained for collagen type I, collagen type II, collagen neoepitope C1,2C, collagen type X, and osteocalcin, prior to semiquantitative analysis. Matrix metalloproteinase (MMP)-1, MMP-3, and MMP-13 levels were analyzed in synovial fluid using enzyme-linked immunosorbent assay (ELISA).Aims
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Achieving accurate implant positioning and restoring native hip biomechanics are key surgeon-controlled technical objectives in total hip arthroplasty (THA). The primary objective of this study was to compare the reproducibility of the planned preoperative centre of hip rotation (COR) in patients undergoing robotic arm-assisted THA versus conventional THA. This prospective randomized controlled trial (RCT) included 60 patients with symptomatic hip osteoarthritis undergoing conventional THA (CO THA) versus robotic arm-assisted THA (RO THA). Patients in both arms underwent pre- and postoperative CT scans, and a patient-specific plan was created using the robotic software. The COR, combined offset, acetabular orientation, and leg length discrepancy were measured on the pre- and postoperative CT scanogram at six weeks following surgery.Aims
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This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA. Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization.Aims
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To explore the synovial expression of mucin 1 (MUC1) and its role in rheumatoid arthritis (RA), as well as the possible downstream mechanisms. Patients with qualified synovium samples were recruited from a RA cohort. Synovium from patients diagnosed as non-inflammatory orthopaedic arthropathies was obtained as control. The expression and localization of MUC1 in synovium and fibroblast-like synoviocytes were assessed by immunohistochemistry and immunofluorescence. Small interfering RNA and MUC1 inhibitor GO-203 were adopted for inhibition of MUC1. Lysophosphatidic acid (LPA) was used as an activator of Rho-associated pathway. Expression of inflammatory cytokines, cell migration, and invasion were evaluated using quantitative real-time polymerase chain reaction (PCR) and Transwell chamber assay.Aims
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Osteoarthritis (OA) is the most prevalent systemic musculoskeletal disorder, characterized by articular cartilage degeneration and subchondral bone (SCB) sclerosis. Here, we sought to examine the contribution of accelerated growth to OA development using a murine model of excessive longitudinal growth. Suppressor of cytokine signalling 2 (SOCS2) is a negative regulator of growth hormone (GH) signalling, thus mice deficient in SOCS2 ( We examined vulnerability of Aims
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The December 2023 Knee Roundup360 looks at: Obesity is associated with greater improvement in patient-reported outcomes following primary total knee arthroplasty; Does mild flexion of the femoral prosthesis in total knee arthroplasty result in better early postoperative outcomes?; Robotic or manual total knee arthroplasty: a randomized controlled trial; Patient-relevant outcomes following first revision total knee arthroplasty, by diagnosis: an analysis of implant survivorship, mortality, serious medical complications, and patient-reported outcome measures using the National Joint Registry data set; Sagittal alignment in total knee arthroplasty: are there any discrepancies between robotic-assisted and manual axis orientation?; Tourniquet use does not impact recovery trajectory in total knee arthroplasty; Impact of proximal tibial varus anatomy on survivorship after medial unicondylar knee arthroplasty; Bone cement directly to the implant in primary total knee arthroplasty?; Maintaining joint line obliquity optimizes outcomes in patients with constitutionally varus knees.
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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The purpose of this study is to determine an individual’s age-specific prevalence of total knee arthroplasty (TKA) after cruciate ligament surgery, and to identify clinical and genetic risk factors associated with undergoing TKA. This study was a retrospective case-control study using the UK Biobank to identify individuals reporting a history of cruciate ligament surgery. Data from verbal history and procedural codes recorded through the NHS were used to identify instances of TKA. Patient clinical and genetic data were used to identify risk factors for progression from cruciate ligament surgery to TKA. Individuals without a history of cruciate ligament reconstruction were used for comparison.Aims
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Postoperative length of stay (LOS) and discharge dispositions following arthroplasty can be used as surrogate measurements for improvements in patients’ pathways and costs. With the increasing use of robotic technology in arthroplasty, it is important to assess its impact on LOS. The aim of this study was to identify factors associated with decreased LOS following robotic arm-assisted total hip arthroplasty (RO THA) compared with the conventional technique (CO THA). This large-scale, single-institution study included 1,607 patients of any age who underwent 1,732 primary THAs for any indication between May 2019 and January 2023. The data which were collected included the demographics of the patients, LOS, type of anaesthetic, the need for treatment in a post-anaesthesia care unit (PACU), readmission within 30 days, and discharge disposition. Univariate and multivariate logistic regression models were used to identify factors and the characteristics of patients which were associated with delayed discharge.Aims
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Frailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data. We analyzed prospectively collected registry data from 2,108 patients aged ≥ 65 years who were admitted to a single major trauma centre over five years (1 October 2015 to 31 July 2020). We divided the sample equally into two, creating derivation and validation samples. In the derivation sample, we performed univariate analyses followed by multivariate regression, starting with 27 clinical variables in the registry to predict Clinical Frailty Scale (CFS; range 1 to 9) scores. Bland-Altman analyses were performed in the validation cohort to evaluate any biases between the Nottingham Trauma Frailty Index (NTFI) and the CFS.Aims
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Impaired fracture repair in patients with type 2 diabetes mellitus (T2DM) is not fully understood. In this study, we aimed to characterize the local changes in gene expression (GE) associated with diabetic fracture. We used an unbiased approach to compare GE in the fracture callus of Zucker diabetic fatty (ZDF) rats relative to wild-type (WT) littermates at three weeks following femoral osteotomy. Zucker rats, WT and homozygous for leptin receptor mutation (ZDF), were fed a moderately high-fat diet to induce T2DM only in the ZDF animals. At ten weeks of age, open femoral fractures were simulated using a unilateral osteotomy stabilized with an external fixator. At three weeks post-surgery, the fractured femur from each animal was retrieved for analysis. Callus formation and the extent of healing were assessed by radiograph and histology. Bone tissue was processed for total RNA extraction and messenger RNA (mRNA) sequencing (mRNA-Seq).Aims
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The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
Osteoarthritis (OA) is a highly prevalent degenerative joint disorder characterized by joint pain and physical disability. Aberrant subchondral bone induces pathological changes and is a major source of pain in OA. In the subchondral bone, which is highly innervated, nerves have dual roles in pain sensation and bone homeostasis regulation. The interaction between peripheral nerves and target cells in the subchondral bone, and the interplay between the sensory and sympathetic nervous systems, allow peripheral nerves to regulate subchondral bone homeostasis. Alterations in peripheral innervation and local transmitters are closely related to changes in nociception and subchondral bone homeostasis, and affect the progression of OA. Recent literature has substantially expanded our understanding of the physiological and pathological distribution and function of specific subtypes of neurones in bone. This review summarizes the types and distribution of nerves detected in the tibial subchondral bone, their cellular and molecular interactions with bone cells that regulate subchondral bone homeostasis, and their role in OA pain. A comprehensive understanding and further investigation of the functions of peripheral innervation in the subchondral bone will help to develop novel therapeutic approaches to effectively prevent OA, and alleviate OA pain. Cite this article:
Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects.Aims
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Pellino1 (Peli1) has been reported to regulate various inflammatory diseases. This study aims to explore the role of Peli1 in the occurrence and development of osteoarthritis (OA), so as to find new targets for the treatment of OA. After inhibiting Peli1 expression in chondrocytes with small interfering RNA (siRNA), interleukin (IL)-1β was used to simulate inflammation, and OA-related indicators such as synthesis, decomposition, inflammation, and apoptosis were detected. Toll-like receptor (TLR) and nuclear factor-kappa B (NF-κB) signalling pathway were detected. After inhibiting the expression of Peli1 in macrophages Raw 264.7 with siRNA and intervening with lipopolysaccharide (LPS), the polarization index of macrophages was detected, and the supernatant of macrophage medium was extracted as conditioned medium to act on chondrocytes and detect the apoptosis index. The OA model of mice was established by destabilized medial meniscus (DMM) surgery, and adenovirus was injected into the knee cavity to reduce the expression of Peli1. The degree of cartilage destruction and synovitis were evaluated by haematoxylin and eosin (H&E) staining, Safranin O/Fast Green staining, and immunohistochemistry.Aims
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Understanding spinopelvic mechanics is important for the success of total hip arthroplasty (THA). Despite significant advancements in appreciating spinopelvic balance, numerous challenges remain. It is crucial to recognize the individual variability and postoperative changes in spinopelvic parameters and their consequential impact on prosthetic component positioning to mitigate the risk of dislocation and enhance postoperative outcomes. This review describes the integration of advanced diagnostic approaches, enhanced technology, implant considerations, and surgical planning, all tailored to the unique anatomy and biomechanics of each patient. It underscores the importance of accurately predicting postoperative spinopelvic mechanics, selecting suitable imaging techniques, establishing a consistent nomenclature for spinopelvic stiffness, and considering implant-specific strategies. Furthermore, it highlights the potential of artificial intelligence to personalize care. Cite this article:
