Aims

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.

Aims

Radiological residual acetabular dysplasia (RAD) has been reported in up to 30% of children who had successful brace treatment of infant developmental dysplasia of the hip (DDH). Predicting those who will resolve and those who may need corrective surgery is important to optimize follow-up protocols. In this study we have aimed to identify the prevalence and predictors of RAD at two years and five years post-bracing.

Background

The Manchester-Oxford Foot Questionnaire (MOxFQ) is a condition specific patient reported outcome measure (PROM) for foot and ankle surgery. It consists of 16 items across three subscales measuring distinct, but related traits: walking/standing ability, pain, and social interaction. Although it is the most used foot and ankle PROM in the UK, initial MOxFQ validation involved analysis of only 100 individuals undergoing hallux valgus surgery. This project aimed to establish whether an individual's response to the MOxFQ varies with anatomical region of disease (measurement invariance), and to explore structural validity of the factor structure (subscale items) of the MOxFQ.

Aims

Isolated fractures of the ulnar diaphysis are uncommon, occurring at a rate of 0.02 to 0.04 per 1,000 cases. Despite their infrequency, these fractures commonly give rise to complications, such as nonunion, limited forearm pronation and supination, restricted elbow range of motion, radioulnar synostosis, and prolonged pain. Treatment options for this injury remain a topic of debate, with limited research available and no consensus on the optimal approach. Therefore, this trial aims to compare clinical, radiological, and functional outcomes of two treatment methods: open reduction and internal fixation (ORIF) versus nonoperative treatment in patients with isolated ulnar diaphyseal fractures.

Introduction

Debridement, antibiotics irrigation and implant retention (DAIR) is a common management strategy for hip and knee prosthetic joint infections (PJI). However, failure rates remain high, which has led to the development of predictive tools to help determine success. These tools include KLIC and CRIME80 for acute-postoperative (AP) and acute haematogenous (AH) PJI respectively. We investigated whether these tools were applicable to a Waikato cohort.

OpenPredictor, a machine learning-enabled clinical decision aid, has been developed to manage backlogs in elective surgeries. It aims to optimise the use of high volume, low complexity surgical pathways by accurately stratifying patient risk, thereby facilitating the allocation of patients to the most suitable surgical sites. The tool augments elective surgical pathways by providing automated secondary opinions for perioperative risk assessments, enhancing decision-making. Its primary application is in elective sites utilising lighter pre-assessment methods, identifying patients with minimal complication risks and those high-risk individuals who may benefit from early pre-assessment.

The Phase 1 clinical evaluation of OpenPredictor entailed a prospective analysis of 156 patient records from elective hip and knee joint replacement surgeries. Using a polynomial logistic regression model, patients were categorised into high, moderate, and low-risk groups. This categorisation incorporated data from various sources, including patient demographics, co-morbidities, blood tests, and overall health status.

In identifying patients at risk of postoperative complications, OpenPredictor demonstrated parity with consultant-led preoperative assessments. It accurately flagged 70% of patients who later experienced complications as moderate or high risk. The tool's efficiency in risk prediction was evidenced by its balanced accuracy (75.6%), sensitivity (70% with a 95% confidence interval of 62.05% to 76.91%), and a high negative predictive value (96.7%).

OpenPredictor presents a scalable and consistent solution for managing elective surgery pathways, comparable in performance to secondary consultant opinions. Its integration into pre-assessment workflows assists in efficient patient categorisation, reduces late surgery cancellations, and optimises resource allocation. The Phase 1 evaluation of OpenPredictor underscores its potential for broader clinical application and highlights the need for ongoing data refinement and system integration to enhance its performance.

Aims

Surgical site infection (SSI) after soft-tissue sarcoma (STS) resection is a serious complication. The purpose of this retrospective study was to investigate the risk factors for SSI after STS resection, and to develop a nomogram that allows patient-specific risk assessment.

Aims

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.

Aims

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.

Aims

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.

Prosthetic joint infections represent complications connected to the implantation of biomedical devices, they have high incidence, interfere with osseointegration, and lead to a high societal burden. The microbial biofilm, which is a complex structure of microbial cells firmly attached to a surface, is one of the main issues causing infections. Biofilm- forming bacteria are acquiring more and more resistances to common clinical treatments due to the abuse of antibiotics administration. Therefore, there is increasing need to develop alternative methods exerting antibacterial activities against multidrug-resistant biofilm-forming bacteria. In this context, metal-based coatings with antimicrobial activities have been investigated and are currently used in the clinical practice. However, traditional coatings exhibit some drawbacks related to the insufficient adhesion to the substrate, scarce uniformity and scarce control over the toxic metal release reducing their efficacy. Here, we propose the use of antimicrobial silver-based nanostructured thin films to discourage bacterial infections. Coatings are obtained by Ionized Jet Deposition, a plasma-assisted technique that permits to manufacture films of submicrometric thickness having a nanostructured surface texture, allow tuning silver release, and avoid delamination. To mitigate interference with osseointegration, here silver composites with bone apatite and hydroxyapatite were explored. The antibacterial efficacy of silver films was tested in vitro against gram- positive and gram-negative species to determine the optimal coatings characteristics by assessing reduction of bacterial viability, adhesion to substrate, and biofilm formation. Efficacy was tested in an in vivo rabbit model, using a multidrug-resistant strain of Staphylococcus aureus showing significant reduction of the bacterial load on the silver prosthesis both when coated with the metal only (>99% reduction) and when in combination with bone apatite (>86% reduction). These studies indicate that IJD films are highly tunable and can be a promising route to overcome the main challenges in orthopedic prostheses.

Artificial Intelligence (AI) is becoming more powerful but is barely used to counter the growth in health care burden. AI applications to increase efficiency in orthopedics are rare. We questioned if (1) we could train machine learning (ML) algorithms, based on answers from digitalized history taking questionnaires, to predict treatment of hip osteoartritis (either conservative or surgical); (2) such an algorithm could streamline clinical consultation.

Multiple ML models were trained on 600 annotated (80% training, 20% test) digital history taking questionnaires, acquired before consultation. Best performing models, based on balanced accuracy and optimized automated hyperparameter tuning, were build into our daily clinical orthopedic practice. Fifty patients with hip complaints (>45 years) were prospectively predicted and planned (partly blinded, partly unblinded) for consultation with the physician assistant (conservative) or orthopedic surgeon (operative). Tailored patient information based on the prediction was automatically sent to a smartphone app. Level of evidence: IV.

Random Forest and BernoulliNB were the most accurate ML models (0.75 balanced accuracy). Treatment prediction was correct in 45 out of 50 consultations (90%), p<0.0001 (sign and binomial test). Specialized consultations where conservatively predicted patients were seen by the physician assistant and surgical patients by the orthopedic surgeon were highly appreciated and effective.

Treatment strategy of hip osteoartritis based on answers from digital history taking questionnaires was accurately predicted before patients entered the hospital. This can make outpatient consultation scheduling more efficient and tailor pre-consultation patient education.

Decellularization techniques have advanced to reduce the risk of immune rejection in transplantation. Validation of these protocols typically relies on Crapo's criteria. 1. , which include the absence of visible nuclei and low DNA content. In our study, five decellularization protocols were compared to determine the optimal approach for human fascia lata (HFL) samples. However, our findings raised questions as to why recipients can still develop immunity despite meeting validation criteria. HFL samples were decellularized using four protocols with SDS-Triton X100-DNase (D1 to D4-HFL) and one protocol using solvent-detergent-based baths (D5-HFL). The decellularized samples (D-HFL) were compared to native samples (N-HFL) using histology, and DNA content was measured. The human leukocyte antigen (HLA) content within the matrix was assessed using western blot analysis. Both D-HFL and N-HFL samples, along with negative control patches, were implanted in the backs of 28 Wistar rats. Anti-human IgG serum levels were evaluated after one month. H&E and Hoechst staining revealed the absence of residual cells in all decellularization protocols. DNA content was consistently below the critical threshold (p<0.05). All implanted D-HFL samples resulted in significantly lower anti-human IgG levels compared to N-HFL (p<0.01). However, 2.5 out of 4 rats developed immunity after being implanted with D1 to D4-HFL, with varying levels of anti-human IgG. Only rats implanted with D5-HFL showed undetectable levels of IgG and were considered non-immunized. Western blot analysis indicated that only D5-HFL had a residual HLA content below 1%. The literature on decellularization has primarily relied on Crapo's criteria, which do not consider the role of HLA mismatch in acute immune rejection. Our results suggest that a residual HLA content below 1% should also be considered to prevent immunization, even if other validation criteria are met. Further research is needed to evaluate the impact of residual HLA levels on human allotransplantation outcomes

Aims

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.

Aim

There is growing evidence that bacteria encountered in periprosthetic joint infections (PJI) form surface-attached biofilms on prostheses, as well as biofilm aggregates embedded in synovial fluid and tissues. However, models allowing the investigation of these biofilms and the assessment of their antimicrobial susceptibility in physiologically relevant conditions are currently lacking. To address this, we developed a synthetic synovial fluid (SSF) model and we validated this model in terms of growth, aggregate formation and antimicrobial susceptibility testing, using multiple PJI isolates.

The purpose of this study was to develop a quality appraisal tool for the assessment of laboratory basic science biomechanical studies.

Materials andScore development comprised of the following phases: item identification/development, item reduction, content/face/criterion validity, weighting, test-retest reliability and internal consistency. For item identification/development, the panel was asked to independently list criteria and factors they considered important for cadaver study and generate items that should be used to appraise cadaver study quality. For content validity, the content validity ratio (CVR) was calculated. The minimum accepted content validity index (CVI) was set to 0.85. For weighting, equal weight for each item was 6.7% [15 items]. Based on these figures the panel was asked to either upscale or downscale the weight for each item ensuring that the final sum for all items was 100%. Face validity was assessed by each panel member using a Likert scale from 1–7. Strong face validity was defined as a mean score of >5. Test-retest reliability was assessed using 10 randomly selected studies. Criterion validity was assessed using the QUACS scale as standard. Internal consistency was assessed using Cronbach's alpha.

Five items reached a CVI of 1 and 10 items a CVI of 0.875. For weighting five items reached a final weight of 10% and ten items 5%. The mean score for face validity was 5.6. Test-retest reliability ranged from 0.78–1.00 with 9 items reaching a perfect score. Criterion validity was 0.76 and considered to be strong. Cronbach's alpha was calculated to be 0.71 indicating acceptable internal consistency.

The new proposed quality score for basic science studies consists of 15 items and has been shown to be reliable, valid and of acceptable internal consistency. It is suggested that this score should be utilised when assessing basic science studies.

Aims

Accurate skeletal age and final adult height prediction methods in paediatric orthopaedics are crucial for determining optimal timing of growth-guiding interventions and minimizing complications in treatments of various conditions. This study aimed to evaluate the accuracy of final adult height predictions using the central peak height (CPH) method with long leg X-rays and four different multiplier tables.

Aims

This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images.

Aims

The purpose of this study was to assess the reliability and responsiveness to hip surgery of a four-point modified Care and Comfort Hypertonicity Questionnaire (mCCHQ) scoring tool in children with cerebral palsy (CP) in Gross Motor Function Classification System (GMFCS) levels IV and V.