Objectives. CT-based three-column classification (TCC) has been widely used in the treatment of tibial plateau fractures (TPFs). In its updated version (updated three-column concept, uTCC), a fracture morphology-based injury mechanism was proposed for effective treatment guidance. In this study, the injury mechanism of TPFs is further explained, and its inter- and intraobserver reliability is evaluated to perfect the uTCC. Methods. The radiological images of 90 consecutive TPF patients were collected. A total of 47 men (52.2%) and 43 women (47.8%) with a mean age of 49.8 years (. sd. 12.4; 17 to 77) were enrolled in our study. Among them, 57 fractures were on the left side (63.3%) and 33 were on the right side (36.7%); no bilateral fracture existed. Four observers were chosen to classify or estimate independently these randomized cases according to the Schatzker classification, TCC, and injury mechanism. With two rounds of evaluation, the kappa values were calculated to estimate the inter- and intrareliability. Results. The overall inter- and intraobserver agreements of the injury mechanism were substantial (κ. inter. = 0.699, κ. intra. = 0.749, respectively). The initial position and the force direction, which are two components of the injury mechanism, had substantial agreement for both inter-reliability or intrareliability. The inter- and intraobserver agreements were lower in high-energy fractures (Schatzker types IV to VI; κ. inter. = 0.605, κ. intra. = 0.721) compared with low-energy fractures (Schatzker types I to III; κ. inter. = 0.81, κ. intra. = 0.832). The inter- and intraobserver agreements were relatively higher in one-column fractures (κ. inter. = 0.759, κ. intra. = 0.801) compared with two-column and three-column fractures. Conclusion. The complete theory of injury mechanism of TPFs was first put forward to make the TCC consummate. It demonstrates substantial inter- and intraobserver agreement generally. Furthermore, the injury mechanism can be promoted clinically. Cite this article: B-B. Zhang, H. Sun, Y. Zhan, Q-F. He, Y. Zhu, Y-K. Wang, C-F. Luo. Reliability and repeatability of tibial plateau fracture assessment with an injury mechanism-based concept. Bone Joint Res 2019;8:357–366. DOI: 10.1302/2046-3758.88.BJR-2018-0331.R1

Aims. Plating displaced proximal humeral fractures is associated with a high rate of screw perforation. Dynamization of the proximal screws might prevent these complications. The aim of this study was to develop and evaluate a new gliding screw concept for plating proximal humeral fractures biomechanically. Methods. Eight pairs of three-part humeral fractures were randomly assigned for pairwise instrumentation using either a prototype gliding plate or a standard PHILOS plate, and four pairs were fixed using the gliding plate with bone cement augmentation of its proximal screws. The specimens were cyclically tested under progressively increasing loading until perforation of a screw. Telescoping of a screw, varus tilting and screw migration were recorded using optical motion tracking. Results. Mean initial stiffness (N/mm) was 581.3 (. sd. 239.7) for the gliding plate, 631.5 (. sd. 160.0) for the PHILOS and 440.2 (. sd. 97.6) for the gliding augmented plate without significant differences between the groups (p = 0.11). Mean varus tilting (°) after 7500 cycles was comparable between the gliding plate (2.6; . sd. 1.9), PHILOS (1.2; . sd. 0.6) and gliding augmented plate (1.7; . sd. 0.9) (p = 0.10). Similarly, mean screw migration(mm) after 7500 cycles was similar between the gliding plate (3.02; . sd. 2.85), PHILOS (1.30; . sd. 0.44) and gliding augmented plate (2.83; . sd. 1.18) (p = 0.13). Mean number of cycles until failure with 5° varus tilting were 12702 (. sd. 3687) for the gliding plate, 13948 (. sd. 1295) for PHILOS and 13189 (. sd. 2647) for the gliding augmented plate without significant differences between the groups (p = 0.66). Conclusion. Biomechanically, plate fixation using a new gliding screw technology did not show considerable advantages in comparison with fixation using a standard PHILOS plate. Based on the finding of telescoping of screws, however, it may represent a valid approach for further investigations into how to avoid the cut-out of screws. Cite this article: Y. P. Acklin, I. Zderic, J. A. Inzana, S. Grechenig, R. Schwyn, R. G. Richards, B. Gueorguiev. Biomechanical evaluation of a new gliding screw concept for the fixation of proximal humeral fractures. Bone Joint Res 2018;7:422–429. DOI: 10.1302/2046-3758.76.BJR-2017-0356.R1

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. Methods. 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. Results. C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients. Conclusion. This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the diagnosis and treatment of OA. Cite this article: Bone Joint Res 2023;12(12):702–711

Aims. The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Methods. Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA. Results. PLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model. Conclusion. SF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy trials and monitor the efficacy of such interventions. Cite this article: Bone Joint Res 2020;9(9):623–632

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.

Cite this article: Bone Joint Res 2023;12(6):372–374.

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Spinopelvic characteristics influence the hip’s biomechanical behaviour. However, to date there is little knowledge defining what ‘normal’ spinopelvic characteristics are. This study aims to determine how static spinopelvic characteristics change with age and ethnicity among asymptomatic, healthy individuals.

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Arthroplasty surgery of the knee and hip is performed in two to three million patients annually. Periprosthetic joint infections occur in 4% of these patients. Debridement, antibiotics, and implant retention (DAIR) surgery aimed at cleaning the infected prosthesis often fails, subsequently requiring invasive revision of the complete prosthetic reconstruction. Infection-specific imaging may help to guide DAIR. In this study, we evaluated a bacteria-specific hybrid tracer (^99mTc-UBI_29-41-Cy5) and its ability to visualize the bacterial load on femoral implants using clinical-grade image guidance methods.

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Cite this article: Bone Joint Res 2023;12(7):447–454.

Cite this article: Bone Joint Res 2022;11(8):514–517.

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The aim of this study was to identify the optimal lip position for total hip arthroplasties (THAs) using a lipped liner. There is a lack of consensus on the optimal position, with substantial variability in surgeon practice.

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In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method.

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The aim of this study was to determine the fracture haematoma (fxH) proteome after multiple trauma using label-free proteomics, comparing two different fracture treatment strategies.

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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).

Cite this article: Bone Joint Res 2023;12(1):5–8.

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Impaired fracture repair in patients with type 2 diabetes mellitus (T2DM) is not fully understood. In this study, we aimed to characterize the local changes in gene expression (GE) associated with diabetic fracture. We used an unbiased approach to compare GE in the fracture callus of Zucker diabetic fatty (ZDF) rats relative to wild-type (WT) littermates at three weeks following femoral osteotomy.

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To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory.

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The management of periprosthetic joint infection (PJI) remains a major challenge in orthopaedic surgery. In this study, we aimed to characterize the local bone microstructure and metabolism in a clinical cohort of patients with chronic PJI.

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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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Transcription factor nuclear factor kappa B (NF-κB) plays a major role in the pathogenesis of chronic inflammatory diseases in all organ systems. Despite its importance, NF-κB targeted drug therapy to mitigate chronic inflammation has had limited success in preclinical studies. We hypothesized that sex differences affect the response to NF-κB treatment during chronic inflammation in bone. This study investigated the therapeutic effects of NF-κB decoy oligodeoxynucleotides (ODN) during chronic inflammation in male and female mice.