Aims. This study aimed to evaluate the BioFire Joint Infection (JI) Panel in cases of hip and knee periprosthetic joint infection (PJI) where
Objectives. This study reports on a secondary exploratory analysis of the early clinical outcomes of a randomised clinical trial comparing robotic arm-assisted unicompartmental knee arthroplasty (UKA) for medial compartment osteoarthritis of the knee with manual UKA performed using traditional surgical jigs. This follows reporting of the primary outcomes of implant accuracy and gait analysis that showed significant advantages in the robotic arm-assisted group. Methods. A total of 139 patients were recruited from a single centre. Patients were randomised to receive either a manual UKA implanted with the aid of traditional surgical jigs, or a UKA implanted with the aid of a tactile guided robotic arm-assisted system. Outcome measures included the American Knee Society Score (AKSS), Oxford Knee Score (OKS), Forgotten Joint Score, Hospital Anxiety Depression Scale, University of California at Los Angeles (UCLA) activity scale, Short Form-12, Pain Catastrophising Scale, somatic disease (Primary Care Evaluation of Mental Disorders Score), Pain visual analogue scale, analgesic use, patient satisfaction, complications relating to surgery, 90-day pain diaries and the requirement for revision surgery. Results. From the first post-operative day through to week 8 post-operatively, the median pain scores for the robotic arm-assisted group were 55.4% lower than those observed in the manual surgery group (p = 0.040). At three months post-operatively, the robotic arm-assisted group had better AKSS (robotic median 164, interquartile range (IQR) 131 to 178, manual median 143, IQR 132 to 166), although no difference was noted with the OKS. At one year post-operatively, the observed differences with the AKSS had narrowed from a median of 21 points to a median of seven points (p = 0.106) (robotic median 171, IQR 153 to 179; manual median 164, IQR 144 to 182). No difference was observed with the OKS, and almost half of each group reached the ceiling limit of the score (OKS > 43). A greater proportion of patients receiving robotic arm-assisted surgery improved their UCLA activity score. Binary logistic regression modelling for dichotomised outcome scores predicted the key factors associated with achieving excellent outcome on the AKSS: a pre-operative activity level > 5 on the UCLA activity score and use of robotic-arm surgery. For the same regression modelling, factors associated with a poor outcome were manual surgery and pre-operative depression. Conclusion. Robotic arm-assisted surgery results in improved early pain scores and early function scores in some patient-reported outcomes measures, but no difference was observed at one year post-operatively. Although improved results favoured the robotic arm-assisted group in active patients (i.e. UCLA ⩾ 5), these do not withstand adjustment for multiple comparisons. Cite this article: M. J. G. Blyth, I. Anthony, P. Rowe, M. S. Banger, A. MacLean, B. Jones. Robotic arm-assisted versus
Aims. Unicompartmental and total knee arthroplasty (UKA and TKA) are successful treatments for osteoarthritis, but the solid metal implants disrupt the natural distribution of stress and strain which can lead to bone loss over time. This generates problems if the implant needs to be revised. This study investigates whether titanium lattice UKA and TKA implants can maintain natural load transfer in the proximal tibia. Methods. In a cadaveric model, UKA and TKA procedures were performed on eight fresh-frozen knee specimens, using
Aims. Highly cross-linked polyethylene (HXLPE) greatly reduces wear in total hip arthroplasty, compared to
Aims. This study investigates the use of the metabolic equivalent of task (MET) score in a young hip arthroplasty population, and its ability to capture additional benefit beyond the ceiling effect of
Aims. The aim of this study was to systematically compare the safety and accuracy of robot-assisted (RA) technique with
Aims. The main advantage of 3D-printed, off-the-shelf acetabular implants is the potential to promote enhanced bony fixation due to their controllable porous structure. In this study we investigated the extent of osseointegration in retrieved 3D-printed acetabular implants. Methods. We compared two groups, one made via 3D-printing (n = 7) and the other using
Objectives. We evaluated the accuracy of augmented reality (AR)-based navigation assistance through simulation of bone tumours in a pig femur model. Methods. We developed an AR-based navigation system for bone tumour resection, which could be used on a tablet PC. To simulate a bone tumour in the pig femur, a cortical window was made in the diaphysis and bone cement was inserted. A total of 133 pig femurs were used and tumour resection was simulated with AR-assisted resection (164 resection in 82 femurs, half by an orthropaedic oncology expert and half by an orthopaedic resident) and resection with the
Aims. The material and design of knee components can have a considerable effect on the contact characteristics of the tibial post. This study aimed to analyze the stress distribution on the tibial post when using different grades of polyethylene for the tibial inserts. In addition, the contact properties of fixed-bearing and mobile-bearing inserts were evaluated. Methods. Three different grades of polyethylene were compared in this study;
Aims. Tocilizumab, an interleukin-6 (IL-6) receptor (IL-6R) targeting antibody, enhances the anti-tumour effect of
Aims. Many biomechanical studies have shown that the weakest biomechanical point of a rotator cuff repair is the suture-tendon interface at the medial row. We developed a novel double rip-stop (DRS) technique to enhance the strength at the medial row for rotator cuff repair. The objective of this study was to evaluate the biomechanical properties of the DRS technique with the
This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated. A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification accuracy was calculated separately for each subcategory (reinfection, tissue and implant condition, non-human cells, and morbidity of the patient). Fleiss’ kappa and Cohen’s kappa were calculated for interobserver and intraobserver reliability, respectively.Aims
Methods
The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test accuracy. A total of 16,238 preoperative OSS were available in the National Joint Registry (NJR) for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey dataset (April 2012 to April 2022). Prior to CAT, the foundational item response theory (IRT) assumptions of unidimensionality, monotonicity, and local independence were established. CAT compared sequential item selection with stopping criteria set at standard error (SE) < 0.32 and SE < 0.45 (equivalent to reliability coefficients of 0.90 and 0.80) to full-length patient-reported outcome measure (PROM) precision.Aims
Methods
Extracellular vesicles (EVs) are nanoparticles secreted by all cells, enriched in proteins, lipids, and nucleic acids related to cell-to-cell communication and vital components of cell-based therapies. Mesenchymal stromal cell (MSC)-derived EVs have been studied as an alternative for osteoarthritis (OA) treatment. However, their clinical translation is hindered by industrial and regulatory challenges. In contrast, platelet-derived EVs might reach clinics faster since platelet concentrates, such as platelet lysates (PL), are already used in therapeutics. Hence, we aimed to test the therapeutic potential of PL-derived extracellular vesicles (pEVs) as a new treatment for OA, which is a degenerative joint disease of articular cartilage and does not have any curative or regenerative treatment, by comparing its effects to those of human umbilical cord MSC-derived EVs (cEVs) on an ex vivo OA-induced model using human cartilage explants. pEVs and cEVs were isolated by size exclusion chromatography (SEC) and physically characterized by nanoparticle tracking analysis (NTA), protein content, and purity. OA conditions were induced in human cartilage explants (10 ng/ml oncostatin M and 2 ng/ml tumour necrosis factor alpha (TNFα)) and treated with 1 × 109 particles of pEVs or cEVs for 14 days. Then, DNA, glycosaminoglycans (GAG), and collagen content were quantified, and a histological study was performed. EV uptake was monitored using PKH26 labelled EVs.Aims
Methods
Objectives. An important measure for the diagnosis and monitoring of knee osteoarthritis is the minimum joint space width (mJSW). This requires accurate alignment of the x-ray beam with the tibial plateau, which may not be accomplished in practice. We investigate the feasibility of a new mJSW measurement method from stereo radiographs using 3D statistical shape models (SSM) and evaluate its sensitivity to changes in the mJSW and its robustness to variations in patient positioning and bone geometry. 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. Results. The SSM-based measurement method was more robust (consistent output for a wide range of input data/consistent output under varying measurement circumstances) than the
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
Methods
This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic next-generation sequencing (mNGS), and the impact of mNGS on clinical diagnosis and treatment. A retrospective analysis was conducted on 235 patients with BJIs who were treated at our hospital between January 2015 and December 2021. Patients were divided into the no-mNGS group (microbial culture only) and the mNGS group (mNGS testing and microbial culture) based on whether mNGS testing was used or not.Aims
Methods
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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Methods
Objectives. Prosthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by
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
Methods