Methods

The study population consisted of 391 patients from two international sarcoma centres (development cohort) who had undergone definitive surgery for a localized high-grade (histological grade II or III) conventional primary central chondrosarcoma or dedifferentiated chondrosarcoma. Disease progression captured the first event of either metastasis or local recurrence. An independent cohort of 221 patients from three additional hospitals was used for external validation. Two nomograms were internally and externally validated for discrimination (c-index) and calibration plot.

Methods

In total, 10,219 anteroposterior pelvic radiographs were retrospectively collected from April 2014 to December 2018. Clinicians labelled each radiograph using a uniform standard method. Radiographs were grouped according to age and into ‘dislocation’ (dislocation and subluxation) and ‘non-dislocation’ (normal cases and those with dysplasia of the acetabulum) groups based on clinical diagnosis. The deep learning system was trained and optimized using 9,081 radiographs; 1,138 test radiographs were then used to compare the diagnoses made by deep learning system and clinicians. The accuracy of the deep learning system was determined using a receiver operating characteristic curve, and the consistency of acetabular index measurements was evaluated using Bland-Altman plots.

Methods

Computational simulations of five subject-specific models were performed for intact and PCL-deficient UKA with tibial slopes. Anteroposterior (AP) kinematics and contact stresses of the patellofemoral (PF) joint and the articular cartilage were evaluated under the deep-knee-bend condition.

Methods

A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset.

Methods

Paediatric patients attending a speciality outpatient clinic were recruited through consecutive sampling. Two groups of patients were included: idiopathic scoliosis, and paediatric orthopaedic upper and lower limb condition without scoliosis. Patients were asked to complete PedsQL 4.0 generic core scales, Youth version of 5-level EuroQol-5-dimension questionnaire, and Refined Scoliosis Research Society 22-item (SRS-22r) questionnaire. Statistical analyses included scores comparison between scoliosis and limb pathology patients using independent-samples t-test, and correlation tests of PedsQL and SRS-22r.

Methods

The BOSS Study is a series of nationwide observational cohort studies of pre-specified orthopaedic disease. All relevant hospitals treating the disease are invited to contribute anonymised case details. Data will be collected digitally through REDCap, with an additional bespoke software solution used to regularly confirm case ascertainment, prompt follow-up reminders and identify potential missing cases from external sources of information (i.e. national administrative data). With their consent, patients will be invited to enrich the data collected by supplementing anonymised case data with patient reported outcomes.

The study will primarily seek to calculate the incidence of the rare diseases under investigation, with 95% confidence intervals. Descriptive statistics will be used to describe the case mix, treatment variations and outcomes. Inferential statistical analysis may be used to analyze associations between presentation factors and outcomes. Types of analyses will be contingent on the disease under investigation.

Methods

The expression profiles of mRNAs, lncRNAs, and circRNAs in OA cartilage were assessed using whole-transcriptome sequencing. Bioinformatics analyses included prediction and reannotation of novel lncRNAs and circRNAs, their classification, and their placement into subgroups. Gene ontology and pathway analysis were performed to identify differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed circRNAs (DECs). We focused on the overlap of DEGs and targets of DELs previously identified in seven high-throughput studies. The top ten DELs were verified by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in articular chondrocytes, both in vitro and in vivo.

Methods

This was a retrospective cohort study of consecutive patients referred to the orthopaedic department at a UK trauma centre with a proximal femoral metastasis (PFM) over a seven-year period (2010 to 2016). The study group were compared to a matched control group of non-metastatic hip fractures. Minimum follow-up was one year.

Patients and Methods

The study utilized data from the Swedish Hip Arthroplasty Register (SHAR) and information from patient records. We included all primary total hip arthroplasties (THAs) performed in Sweden since 1979, and undergoing further surgery due to Vancouver type B periprosthetic femoral fracture between 2001 and 2011. The primary outcome measure was any further reoperation between 2001 and 2013. Cross-referencing with the National Patient Register was performed in two stages, in order to identify all surgical procedures not recorded on the SHAR.

Patients and Methods

A descriptive observational study was performed by linking primary and secondary care information from two independent national databases of routinely collected data: the United Kingdom Clinical Practice Research Datalink and Hospital Episode Statistics. The study examined all children from 1 January 1990 to 1 January 2016 who had a new first diagnostic code for DDH aged between one and eight years old.

Methods

Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset.

Methods

The 16s rDNA test combines a polymerase chain reaction (PCR) for amplification of 16s rDNA with a lateral flow immunoassay in one fully automated system. The synovial fluid of 77 patients undergoing joint aspiration or primary or revision total hip or knee surgery was prospectively collected. The cohort was divided into a proof-of-principle cohort (n = 17) and a validation cohort (n = 60). Using the proof-of-principle cohort, an optimal cut-off for the discrimination between PJI and non-PJI samples was determined. PJI was defined as detection of the same bacterial species in a minimum of two microbiological samples, positive histology, and presence of a sinus tract or intra-articular pus.

Materials and Methods

A 10° opening wedge HTO was created in a composite tibia. Imaging and strain gauge data were used to create and validate FE models. Models of an intact tibia and a tibia implanted with a custom HTO plate using two different bridging spans were validated against experimental data. Physiological muscle forces and different stages of osteotomy gap healing simulating up to six weeks postoperatively were then incorporated. Predictions of plate stress and IFM for the custom plate were compared against predictions for an industry standard plate (TomoFix).

Methods

Seven human cadaveric hemipelves were CT scanned and bone models were segmented. Tantalum beads were placed in the pelvis and proximal femoral bone. RSA recordings of the hips were performed during flexion, adduction and internal rotation. Stereoradiographic recordings were all analyzed with DRR, MBM and MM. Migration results for the MBM and DRR with respect to MM were compared. Precision was assessed as systematic bias (mean difference) and random variation (Pitman’s test for equal variance).

Methods

We searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis.

Methods

We generated a subject-specific computational model followed by the development of ± 1 mm, ± 2 mm and ± 3 mm PCO models in the posterior direction, and -3°, 0°, 3° and 6° PTS models with each of the PCO models. Using a validated finite element (FE) model, we investigated the influence of the changes in PCO and PTS on the contact stress in the patellar button and the forces on the posterior cruciate ligament (PCL), patellar tendon and quadriceps muscles under the deep knee-bend loading conditions.

Methods

Microarray data sets GSE56815 and GSE56814, comprising 67 osteoporosis blood samples and 62 control blood samples, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in osteoporosis using Limma package (3.2.1) and Meta-MA packages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify biological functions. Furthermore, the transcriptional regulatory network was established between the top 20 DEGs and transcriptional factors using the UCSC ENCODE Genome Browser. Receiver operating characteristic (ROC) analysis was applied to investigate the diagnostic value of several DEGs.

Materials and Methods

A validation study was performed using five cadaver specimens. The actual mJSW was varied and images were acquired with variation in the cadaver positioning. For comparison purposes, the mJSW was also assessed from plain radiographs. To study the influence of SSM model accuracy, the 3D mJSW measurement was repeated with models from the actual bones, obtained from CT scans.

Methods

The intraclass correlation coefficient (ICC) was used for test-retest reliability, between PROMs completed twice with a two-week interval at six to eight months after DRF. Internal consistency was determined using Cronbach’s α for the dimensions found in the factor analysis. The measurement error was expressed by the smallest detectable change (SDC). A semi-structured interview was conducted between eight and 12 weeks after DRF to assess the content validity.

Methods

A total of 26 men and 25 women (18 to 35 years old) participated in this study. Participants walked on a treadmill with the KneeKG system at a slow imposed speed (2 km/hr) for three trials, then at a self-selected comfortable walking speed for another three trials. Paired t-tests, Wilcoxon signed-rank tests, Mann-Whitney U tests and Spearman’s rank correlation coefficients were conducted using Stata/IC 14 to compare kinematics of slow versus self-selected walking speed.