Aims

Though most humeral shaft fractures heal nonoperatively, up to one-third may lead to nonunion with inferior outcomes. The Radiographic Union Score for HUmeral Fractures (RUSHU) was created to identify high-risk patients for nonunion. Our study evaluated the RUSHU’s prognostic performance at six and 12 weeks in discriminating nonunion within a significantly larger cohort than before.

Aims

The survival of humeral hemiarthroplasties in patients with relatively intact glenoid cartilage could theoretically be extended by minimizing the associated postoperative glenoid erosion. Ceramic has gained attention as an alternative to metal as a material for hemiarthroplasties because of its superior tribological properties. The aim of this study was to assess the in vitro wear performance of ceramic and metal humeral hemiarthroplasties on natural glenoids.

Aims

The objective of this study was to compare simulated range of motion (ROM) for reverse total shoulder arthroplasty (rTSA) with and without adjustment for scapulothoracic orientation in a global reference system. We hypothesized that values for simulated ROM in preoperative planning software with and without adjustment for scapulothoracic orientation would be significantly different.

Aims. Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. Methods. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures. Results. Out of 1,160 studies initially identified, 39 were included. Most studies (85%) were published between 2020 and 2024, with 82% using publicly available datasets, primarily the Osteoarthritis Initiative. ML methods were predominantly supervised, with significant variability in the definitions of OA progression: most studies focused on structural changes (59%), while fewer addressed pain progression or both. Deep learning was used in 44% of studies, while automated ML was used in 5%. There was a lack of standardization in evaluation metrics and limited external validation. Interpretability was explored in 54% of studies, primarily using SHapley Additive exPlanations. Conclusion. Our systematic review demonstrates the feasibility of ML models in predicting OA progression, but also uncovers critical limitations that currently restrict their clinical applicability. Future priorities should include diversifying data sources, standardizing outcome measures, enforcing rigorous validation, and integrating more sophisticated algorithms. This paradigm shift from predictive modelling to actionable clinical tools has the potential to transform patient care and disease management in orthopaedic practice. Cite this article: Bone Joint J 2024;106-B(11):1216–1222

Aims

The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population.

Aims

Treatment of high-grade limb bone sarcoma that invades a joint requires en bloc extra-articular excision. MRI can demonstrate joint invasion but is frequently inconclusive, and its predictive value is unknown. We evaluated the diagnostic accuracy of direct and indirect radiological signs of intra-articular tumour extension and the performance characteristics of MRI findings of intra-articular tumour extension.

Aims

This study aimed to investigate the optimal sagittal positioning of the uncemented femoral component in total knee arthroplasty to minimize the risk of aseptic loosening and periprosthetic fracture.

Aims

This study aims to describe a new method that may be used as a supplement to evaluate humeral rotational alignment during intramedullary nail (IMN) insertion using the profile of the perpendicular peak of the greater tuberosity and its relation to the transepicondylar axis. We called this angle the greater tuberosity version angle (GTVA).

Aims

This study aimed to define the histopathology of degenerated humeral head cartilage and synovial inflammation of the glenohumeral joint in patients with omarthrosis (OmA) and cuff tear arthropathy (CTA). Additionally, the potential of immunohistochemical tissue biomarkers in reflecting the degeneration status of humeral head cartilage was evaluated.

Aims

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.

Aims

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.

Aims

This study aimed to demonstrate the promoting effect of elastic fixation on fracture, and further explore its mechanism at the gene and protein expression levels.

Aims

The outcomes of patients with unexpected positive cultures (UPCs) during revision total hip arthroplasty (THA) and total knee arthroplasty (TKA) remain unknown. The objectives of this study were to establish the prevalence and infection-free implant survival in UPCs during presumed aseptic single-stage revision THA and TKA at mid-term follow-up.

Bone defects are frequently observed in anterior shoulder instability. Over the last decade, knowledge of the association of bone loss with increased failure rates of soft-tissue repair has shifted the surgical management of chronic shoulder instability. On the glenoid side, there is no controversy about the critical glenoid bone loss being 20%. However, poor outcomes have been described even with a subcritical glenoid bone defect as low as 13.5%. On the humeral side, the Hill-Sachs lesion should be evaluated concomitantly with the glenoid defect as the two sides of the same bipolar lesion which interact in the instability process, as described by the glenoid track concept. We advocate adding remplissage to every Bankart repair in patients with a Hill-Sachs lesion, regardless of the glenoid bone loss. When critical or subcritical glenoid bone loss occurs in active patients (> 15%) or bipolar off-track lesions, we should consider anterior glenoid bone reconstructions. The techniques have evolved significantly over the last two decades, moving from open procedures to arthroscopic, and from screw fixation to metal-free fixation. The new arthroscopic techniques of glenoid bone reconstruction procedures allow precise positioning of the graft, identification, and treatment of concomitant injuries with low morbidity and faster recovery. Given the problems associated with bone resorption and metal hardware protrusion, the new metal-free techniques for Latarjet or free bone block procedures seem a good solution to avoid these complications, although no long-term data are yet available.

Cite this article: Bone Joint J 2024;106-B(10):1100–1110.

Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles (. https://www.ideal-collaboration.net/. ). Adherence to the framework would provide a robust evidence-based mechanism for developing trust in AI applications, where the underlying algorithms are unlikely to be fully understood by clinical teams. Cite this article: Bone Joint Res 2024;13(9):507–512

Aims

Advances in treatment have extended the life expectancy of patients with metastatic bone disease (MBD). Patients could experience more skeletal-related events (SREs) as a result of this progress. Those who have already experienced a SRE could encounter another local management for a subsequent SRE, which is not part of the treatment for the initial SRE. However, there is a noted gap in research on the rate and characteristics of subsequent SREs requiring further localized treatment, obligating clinicians to extrapolate from experiences with initial SREs when confronting subsequent ones. This study aimed to investigate the proportion of MBD patients developing subsequent SREs requiring local treatment, examine if there are prognostic differences at the initial treatment between those with single versus subsequent SREs, and determine if clinical, oncological, and prognostic features differ between initial and subsequent SRE treatments.

Aims

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.

Aims. Custom-made partial pelvis replacements (PPRs) are increasingly used in the reconstruction of large acetabular defects and have mainly been designed using a triflange approach, requiring extensive soft-tissue dissection. The monoflange design, where primary intramedullary fixation within the ilium combined with a monoflange for rotational stability, was anticipated to overcome this obstacle. The aim of this study was to evaluate the design with regard to functional outcome, complications, and acetabular reconstruction. Methods. Between 2014 and 2023, 79 patients with a mean follow-up of 33 months (SD 22; 9 to 103) were included. Functional outcome was measured using the Harris Hip Score and EuroQol five-dimension questionnaire (EQ-5D). PPR revisions were defined as an endpoint, and subgroups were analyzed to determine risk factors. Results. Implantation was possible in all cases with a 2D centre of rotation deviation of 10 mm (SD 5.8; 1 to 29). PPR revision was necessary in eight (10%) patients. HHS increased significantly from 33 to 72 postoperatively, with a mean increase of 39 points (p < 0.001). Postoperative EQ-5D score was 0.7 (SD 0.3; -0.3 to 1). Risk factor analysis showed significant revision rates for septic indications (p ≤ 0.001) as well as femoral defect size (p = 0.001). Conclusion. Since large acetabular defects are being treated surgically more often, custom-made PPR should be integrated as an option in treatment algorithms. Monoflange PPR, with primary iliac fixation, offers a viable treatment option for Paprosky III defects with promising functional results, while requiring less soft-tissue exposure and allowing immediate full weightbearing. Cite this article: Bone Jt Open 2024;5(8):688–696

Aims. Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential. Cite this article: Bone Jt Open 2024;5(8):671–680

Aims

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.