Better prediction of outcome after total hip arthroplasty (THA) is warranted. Systemic inflammation and central neuroinflammation are possibly involved in progression of osteoarthritis and pain. We explored whether inflammatory biomarkers in blood and cerebrospinal fluid (CSF) were associated with clinical outcome, and baseline pain or disability, 12 months after THA. A total of 50 patients from the Danish Pain Research Biobank (DANPAIN-Biobank) between January and June 2018 were included. Postoperative outcome was assessed as change in Oxford Hip Score (OHS) from baseline to 12 months after THA, pain was assessed on a numerical rating scale, and disability using the Pain Disability Index. Multiple regression models for each clinical outcome were included for biomarkers in blood and CSF, respectively, including age, sex, BMI, and Kellgren-Lawrence score.Aims
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Extracellular matrix (ECM) is a critical determinant of tissue mechanobiology, yet remains poorly characterized in joint tissues beyond cartilage in osteoarthritis (OA). This review aimed to define the composition and architecture of non-cartilage soft joint tissue structural ECM in human OA, and to compare the changes observed in humans with those seen in animal models of the disease. A systematic search strategy, devised using relevant matrix, tissue, and disease nomenclature, was run through the MEDLINE, Embase, and Scopus databases. Demographic, clinical, and biological data were extracted from eligible studies. Bias analysis was performed.Aims
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Aims. Pain is the most frequent complaint associated with osteonecrosis of the femoral head (ONFH), but the factors contributing to such pain are poorly understood. This study explored diverse demographic, clinical, radiological, psychological, and neurophysiological factors for their potential contribution to pain in patients with ONFH. Methods. This cross-sectional study was carried out according to the “STrengthening the Reporting of OBservational studies in Epidemiology” statement. Data on 19 variables were collected at a single timepoint from 250 patients with ONFH who were treated at our medical centre between July and December 2023 using validated instruments or, in the case of hip pain, a numerical rating scale. Factors associated with pain severity were identified using hierarchical multifactor linear regression. Results. Regression identified the following characteristics as independently associated with higher pain score, after adjustment for potential confounders: Association Research Circulation Osseous
The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared.Aims
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This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
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Aims. This study aimed to assess the risk of acute kidney injury (AKI) associated with combined intravenous (IV) and topical antibiotic therapy in patients undergoing treatment for periprosthetic joint infections (PJIs) following total knee arthroplasty (TKA), utilizing the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for
This study aimed to analyze kinematics and kinetics of the tibiofemoral joint in healthy subjects with valgus, neutral, and varus limb alignment throughout multiple gait activities using dynamic videofluoroscopy. Five subjects with valgus, 12 with neutral, and ten with varus limb alignment were assessed during multiple complete cycles of level walking, downhill walking, and stair descent using a combination of dynamic videofluoroscopy, ground reaction force plates, and optical motion capture. Following 2D/3D registration, tibiofemoral kinematics and kinetics were compared between the three limb alignment groups.Aims
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Aims. The presence of facet tropism has been correlated with an elevated susceptibility to lumbar disc pathology. Our objective was to evaluate the impact of facet tropism on chronic lumbosacral discogenic pain through the analysis of clinical data and finite element modelling (FEM). Methods. Retrospective analysis was conducted on clinical data, with a specific focus on the spinal units displaying facet tropism, utilizing FEM analysis for motion simulation. We studied 318 intervertebral levels in 156 patients who had undergone provocation discography. Significant predictors of clinical findings were identified by univariate and multivariate analyses. Loading conditions were applied in FEM simulations to mimic biomechanical effects on intervertebral discs, focusing on maximal displacement and intradiscal pressures, gauged through alterations in disc morphology and physical stress. Results. A total of 144 discs were categorized as ‘positive’ and 174 discs as ‘negative’ by the results of provocation discography. The presence of defined facet tropism (OR 3.451, 95% CI 1.944 to 6.126) and higher Adams
This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms. We analyzed microarray data from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA), machine learning, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify common genetic factors between POMP and sarcopenia. Further validation was done via differential gene expression in a new cohort. Single-cell analysis identified high expression cell subsets, with mononuclear macrophages in osteoporosis and muscle stem cells in sarcopenia, among others. A competitive endogenous RNA network suggested regulatory elements for these genes.Aims
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The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA. Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database.Aims
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Aims. This study aimed to evaluate the BioFire Joint Infection (JI) Panel in cases of hip and knee periprosthetic joint infection (PJI) where conventional microbiology is unclear, and to assess its role as a complementary intraoperative diagnostic tool. Methods. Five groups representing common microbiological scenarios in hip and knee revision arthroplasty were selected from our arthroplasty registry, prospectively maintained PJI databases, and biobank: 1) unexpected-negative cultures (UNCs), 2) unexpected-positive cultures (UPCs), 3) single-positive intraoperative cultures (SPCs), and 4) clearly septic and 5) aseptic cases. In total, 268 archived synovial fluid samples from 195 patients who underwent acute/chronic revision total hip or knee arthroplasty were included. Cases were classified according to the International Consensus Meeting 2018 criteria. JI panel evaluation of synovial fluid was performed, and the results were compared with cultures. Results. The JI panel detected microorganisms in 7/48 (14.5%) and 15/67 (22.4%) cases related to UNCs and SPCs, respectively, but not in cases of UPCs. The correlation between JI panel detection and infection
Achilles tendon re-rupture (ATRR) poses a significant risk of postoperative complication, even after a successful initial surgical repair. This study aimed to identify risk factors associated with Achilles tendon re-rupture following operative fixation. This retrospective cohort study analyzed a total of 43,287 patients from national health claims data spanning 2008 to 2018, focusing on patients who underwent surgical treatment for primary Achilles tendon rupture. Short-term ATRR was defined as cases that required revision surgery occurring between six weeks and one year after the initial surgical repair, while omitting cases with simultaneous infection or skin necrosis. Variables such as age, sex, the presence of Achilles tendinopathy, and comorbidities were systematically collected for the analysis. We employed multivariate stepwise logistic regression to identify potential risk factors associated with short-term ATRR.Aims
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Aims. In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method. Methods. We retrospectively collected CT imaging data of 108 hips with non-traumatic osteonecrosis of the femoral head from 76 consecutive patients (mean age 34.3 years (SD 8.1), 56.58% male (n = 43)) in two clinical centres. The femoral head was divided into 288 standard units (based on the orientation of units within the femoral head, designated as N[Superior], S[Inferior], E[Anterior], and W[Posterior]) using a new measurement system called the longitude and latitude division system (LLDS). A computer-aided design (CAD) measurement tool was also developed to visualize the measurement of the spatial location of necrotic lesions in CT images. Two orthopaedic surgeons independently performed measurements, and the results were used to draw 2D and 3D heat maps of spatial distribution of necrotic lesions in the femoral head, and for statistical analysis. Results. The results showed that the LLDS has high inter-rater reliability. As illustrated by the heat map, the distribution of Japanese Investigation Committee (JIC)
The aims of this study were to identify and evaluate the current literature examining the prognostic factors which are associated with failure of total elbow arthroplasty (TEA). Electronic literature searches were conducted using MEDLINE, Embase, PubMed, and Cochrane. All studies reporting prognostic estimates for factors associated with the revision of a primary TEA were included. The risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool, and the quality of evidence was assessed using the modified Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework. Due to low quality of the evidence and the heterogeneous nature of the studies, a narrative synthesis was used.Aims
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This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate.Aims
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Fracture-related infection (FRI) is commonly classified based on the time of onset of symptoms. Early infections (< two weeks) are treated with debridement, antibiotics, and implant retention (DAIR). For late infections (> ten weeks), guidelines recommend implant removal due to tolerant biofilms. For delayed infections (two to ten weeks), recommendations are unclear. In this study we compared infection clearance and bone healing in early and delayed FRI treated with DAIR in a rabbit model.
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The present study investigated receptor activator of nuclear factor kappa-Β ligand (RANKL), osteoprotegerin (OPG), and Runt-related transcription factor 2 (RUNX2) gene expressions in giant cell tumour of bone (GCTB) patients in relationship with tumour recurrence. We also aimed to investigate the influence of CpG methylation on the transcriptional levels of RANKL and OPG. A total of 32 GCTB tissue samples were analyzed, and the expression of RANKL, OPG, and RUNX2 was evaluated by quantitative polymerase chain reaction (qPCR). The methylation status of RANKL and OPG was also evaluated by quantitative methylation-specific polymerase chain reaction (qMSP).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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Aims. This study aimed to evaluate the clinical application of the PJI-TNM
Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers.Aims
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