Aims. The Bankart and Latarjet procedures are two of the most common surgical techniques to treat anterior shoulder instability with satisfactory clinical and functional outcomes. However, the outcomes in the adolescent population remain unclear, and there is no information regarding the arthroscopic Latarjet in this population. The purpose of this study was to evaluate the outcomes of the arthroscopic Bankart and arthroscopic Latarjet procedures in the management of anterior shoulder instability in adolescents. Methods. We present a retrospective, matched-pair study of teenagers with anterior glenohumeral instability treated with an arthroscopic Bankart repair (ABR) or an arthroscopic Latarjet (AL) procedure with a minimum two-year follow-up. Preoperative demographic and
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
Methods
Serum inflammatory parameters are widely used to aid in diagnosing a periprosthetic joint infection (PJI). Due to their limited performances in the literature, novel and more accurate biomarkers are needed. Serum albumin-to-globulin ratio (AGR) and serum CRP-to-albumin ratio (CAR) have previously been proposed as potential new parameters, but results were mixed. The aim of this study was to assess the diagnostic accuracy of AGR and CAR in diagnosing PJI and to compare them to the established and widely used marker CRP. From 2015 to 2022, a consecutive series of 275 cases of revision total hip (n = 129) and knee arthroplasty (n = 146) were included in this retrospective cohort study. Based on the 2021 European Bone and Joint Infection Society (EBJIS) definition, 144 arthroplasties were classified as septic. Using receiver operating characteristic curve (ROC) analysis, the ideal thresholds and diagnostic performances were calculated. The areas under the curve (AUCs) were compared using the z-test.Aims
Methods
During total knee replacement (TKR), surgeons can choose whether or not to resurface the patella, with advantages and disadvantages of each approach. Recently, the National Institute for Health and Care Excellence (NICE) recommended always resurfacing the patella, rather than never doing so. NICE found insufficient evidence on selective resurfacing (surgeon’s decision based on intraoperative findings and symptoms) to make recommendations. If effective, selective resurfacing could result in optimal individualized patient care. This protocol describes a randomized controlled trial to evaluate the clinical and cost-effectiveness of primary TKR with always patellar resurfacing compared to selective patellar resurfacing. The PAtellar Resurfacing Trial (PART) is a patient- and assessor-blinded multicentre, pragmatic parallel two-arm randomized superiority trial of adults undergoing elective primary TKR for primary osteoarthritis at NHS hospitals in England, with an embedded internal pilot phase (ISRCTN 33276681). Participants will be randomly allocated intraoperatively on a 1:1 basis (stratified by centre and implant type (cruciate-retaining vs cruciate-sacrificing)) to always resurface or selectively resurface the patella, once the surgeon has confirmed sufficient patellar thickness for resurfacing and that constrained implants are not required. The primary analysis will compare the Oxford Knee Score (OKS) one year after surgery. Secondary outcomes include patient-reported outcome measures at three months, six months, and one year (Knee injury and Osteoarthritis Outcome Score, OKS, EuroQol five-dimension five-level questionnaire, patient satisfaction, postoperative complications, need for further surgery, resource use, and costs). Cost-effectiveness will be measured for the lifetime of the patient. Overall, 530 patients will be recruited to obtain 90% power to detect a four-point difference in OKS between the groups one year after surgery, assuming up to 40% resurfacing in the selective group.Aims
Methods
The aim of this study was to describe the prevalence and patterns of neuropathic pain over one year in a cohort of patients with chronic post-surgical pain at three months following total knee arthroplasty (TKA). Between 2016 and 2019, 363 patients with troublesome pain, defined as a score of ≤ 14 on the Oxford Knee Score pain subscale, three months after TKA from eight UK NHS hospitals, were recruited into the Support and Treatment After Replacement (STAR) clinical trial. Self-reported neuropathic pain and postoperative pain was assessed at three, nine, and 15 months after surgery using the painDETECT and Douleur Neuropathique 4 (DN4) questionnaires collected by postal survey.Aims
Methods
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
Methods
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
Methods
Therapeutic agents that prevent chondrocyte loss, extracellular matrix (ECM) degradation, and osteoarthritis (OA) progression are required. The expression level of epidermal growth factor (EGF)-like repeats and discoidin I-like domains-containing protein 3 (EDIL3) in damaged human cartilage is significantly higher than in undamaged cartilage. However, the effect of EDIL3 on cartilage is still unknown. We used human cartilage plugs (ex vivo) and mice with spontaneous OA (in vivo) to explore whether EDIL3 has a chondroprotective effect by altering OA-related indicators.Aims
Methods
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
Methods
Osteoarthritis (OA) is mainly caused by ageing, strain, trauma, and congenital joint abnormalities, resulting in articular cartilage degeneration. During the pathogenesis of OA, the changes in subchondral bone (SB) are not only secondary manifestations of OA, but also an active part of the disease, and are closely associated with the severity of OA. In different stages of OA, there were microstructural changes in SB. Osteocytes, osteoblasts, and osteoclasts in SB are important in the pathogenesis of OA. The signal transduction mechanism in SB is necessary to maintain the balance of a stable phenotype, extracellular matrix (ECM) synthesis, and bone remodelling between articular cartilage and SB. An imbalance in signal transduction can lead to reduced cartilage quality and SB thickening, which leads to the progression of OA. By understanding changes in SB in OA, researchers are exploring drugs that can regulate these changes, which will help to provide new ideas for the treatment of OA. Cite this article:
Chronic osteomyelitis (COM) of the lower limb in adults can be surgically managed by either limb reconstruction or amputation. This scoping review aims to map the outcomes used in studies surgically managing COM in order to aid future development of a core outcome set. A total of 11 databases were searched. A subset of studies published between 1 October 2020 and 1 January 2011 from a larger review mapping research on limb reconstruction and limb amputation for the management of lower limb COM were eligible. All outcomes were extracted and recorded verbatim. Outcomes were grouped and categorized as per the revised Williamson and Clarke taxonomy.Aims
Methods
The aims of this study were to determine the incidence and factors for developing periprosthetic joint infection (PJI) following hemiarthroplasty (HA) for hip fracture, and to evaluate treatment outcome and identify factors associated with treatment outcome. A retrospective review was performed of consecutive patients treated for HA PJI at a tertiary referral centre with a mean 4.5 years’ follow-up (1.6 weeks to 12.9 years). Surgeries performed included debridement, antibiotics, and implant retention (DAIR) and single-stage revision. The effect of different factors on developing infection and treatment outcome was determined.Aims
Methods
There remains a lack of consensus regarding the management of chronic anterior sternoclavicular joint (SCJ) instability. This study aimed to assess whether a standardized treatment algorithm (incorporating physiotherapy and surgery and based on the presence of trauma) could successfully guide management and reduce the number needing surgery. Patients with chronic anterior SCJ instability managed between April 2007 and April 2019 with a standardized treatment algorithm were divided into non-traumatic (offered physiotherapy) and traumatic (offered surgery) groups and evaluated at discharge. Subsequently, midterm outcomes were assessed via a postal questionnaire with a subjective SCJ stability score, Oxford Shoulder Instability Score (OSIS, adapted for the SCJ), and pain visual analogue scale (VAS), with analysis on an intention-to-treat basis.Aims
Methods
This study evaluated the definitions developed by the European Bone and Joint Infection Society (EBJIS) 2021, the International Consensus Meeting (ICM) 2018, and the Infectious Diseases Society of America (IDSA) 2013, for the diagnosis of periprosthetic joint infection (PJI). In this single-centre, retrospective analysis of prospectively collected data, patients with an indicated revision surgery after a total hip or knee arthroplasty were included between 2015 and 2020. A standardized diagnostic workup was performed, identifying the components of the EBJIS, ICM, and IDSA criteria in each patient.Aims
Methods
We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.Aims
Methods
We aimed to evaluate the utility of 68Ga-citrate positron emission tomography (PET)/CT in the differentiation of periprosthetic joint infection (PJI) and aseptic loosening (AL), and compare it with 99mTc-methylene bisphosphonates (99mTc-MDP) bone scan. We studied 39 patients with suspected PJI or AL. These patients underwent 68Ga-citrate PET/CT, 99mTc-MDP three-phase bone scan and single-photon emission CT (SPECT)/CT. PET/CT was performed at ten minutes and 60 minutes after injection, respectively. Images were evaluated by three nuclear medicine doctors based on: 1) visual analysis of the three methods based on tracer uptake model, and PET images attenuation-corrected with CT and those not attenuation-corrected with CT were analyzed, respectively; and 2) semi-quantitative analysis of PET/CT: maximum standardized uptake value (SUVmax) of lesions, SUVmax of the lesion/SUVmean of the normal bone, and SUVmax of the lesion/SUVmean of the normal muscle. The final diagnosis was based on the clinical and intraoperative findings, and histopathological and microbiological examinations.Aims
Methods
Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA. Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.Aims
Methods
Tuberculosis (TB) is one of the biggest communicable causes of mortality worldwide. While incidence in the UK has continued to fall since 2011, Bradford retains one of the highest TB rates in the UK. This study aims to examine the local disease burden of musculoskeletal (MSK) TB, by analyzing common presenting factors within the famously diverse population of Bradford. An observational study was conducted, using data from the Bradford Teaching Hospitals TB database of patients with a formal diagnosis of MSK TB between January 2005 and July 2017. Patient data included demographic data (including nationality/date of entry to the UK), disease focus, microbiology, and management strategies. Disease incidence was calculated using population data from the Office for National Statistics. Poisson confidence intervals were calculated to demonstrate the extent of statistical error. Disease incidence and nationality were also analyzed, and correlation sought, using the chi-squared test.Aims
Methods
The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation.Aims
Methods
Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
