Aims. To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design. Methods. Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics. Results. Survey responses (n = 19 HCP/Rs, 39 PJDs) supported studies testing pharmacological agents preventing PTOA. All HCP/Rs and 30/31 (97%) PJDs supported the development of new treatments that improved or delayed knee symptoms and damage to knee structure. PJDs thought that improving structural knee damage was more important than knee symptoms. Both groups found studies more acceptable as expected future benefit and risk of PTOA increased. All drug delivery routes were acceptable. Workshop participants (around n = 60) reflected survey views. Discussions suggested that stratifying using molecular testing for likely drug response appeared to be more acceptable than using characteristics such as sex, age, and BMI. Conclusion. Our findings supported PTOA drug intervention studies, including situations where there is low risk of disease, no expected benefit of treatment, and frequent treatment administration. PJDs appeared less risk-averse than HCP/Rs. This work reinforces the benefits of consensus and involvement work in the co-creation of PTOA drug trial design. Involvement of key stakeholders, such as PJDs with different risks of OA and regulatory representatives, are critical for trial design success. Cite this article: Bone Joint Res 2024;13(9):513–524

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

Aims. A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. Methods. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Aims. Tibial plateau fractures (TPFs) are complex injuries around the knee caused by high- or low-energy trauma. In the present study, we aimed to define the distribution and frequency of TPF lines using a 3D mapping technique and analyze the rationalization of divisions employed by frequently used classifications. Methods. In total, 759 adult patients with 766 affected knees were retrospectively reviewed. The TPF fragments on CT were multiplanar reconstructed, and virtually reduced to match a 3D model of the proximal tibia. 3D heat mapping was subsequently created by graphically superimposing all fracture lines onto a tibia template. Results. The cohort included 405 (53.4%) cases with left knee injuries, 347 (45.7%) cases with right knee injuries, and seven (0.9%) cases with bilateral injuries. On mapping, the hot zones of the fracture lines were mainly concentrated around the anterior cruciate ligament insertion, posterior cruciate ligament insertion, and the inner part of the lateral condyle that extended to the junctional zone between Gerdy’s tubercle and the tibial tubercle. Moreover, the cold zones were scattered in the posteromedial fragment, superior tibiofibular syndesmosis, Gerdy’s tubercle, and tibial tubercle. TPFs with different Orthopaedic Trauma Association/AO Foundation (OTA/AO) subtypes showed peculiar characteristics. Conclusion. TPFs occurred more frequently in the lateral and intermedial column than in the medial column. Fracture lines of tibial plateau occur frequently in the transition zone with marked changes in cortical thickness. According to 3D mapping, the four-column and nine-segment classification had a high degree of matching as compared to the frequently used classifications. Cite this article: Bone Joint Res 2020;9(6):258–267

Patient-reported outcome measures (PROMs) are being used increasingly in total knee arthroplasty (TKA). We conducted a systematic review aimed at identifying psychometrically sound PROMs by appraising their measurement properties. Studies concerning the development and/or evaluation of the measurement properties of PROMs used in a TKA population were systematically retrieved via PubMed, Web of Science, Embase, and Scopus. Ratings for methodological quality and measurement properties were conducted according to updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. Of the 155 articles on 34 instruments included, nine PROMs met the minimum requirements for psychometric validation and can be recommended to use as measures of TKA outcome: Oxford Knee Score (OKS); OKS–Activity and Participation Questionnaire (OKS-APQ); 12-item short form Knee Injury and Osteoarthritis Outcome (KOOS-12); KOOS Physical function Short form (KOOS-PS); Western Ontario and McMaster Universities Arthritis Index-Total Knee Replacement function short form (WOMAC-TKR); Lower Extremity Functional Scale (LEFS); Forgotten Joint Score (FJS); Patient’s Knee Implant Performance (PKIP); and University of California Los Angeles (UCLA) activity score. The pain and function subscales in WOMAC, as well as the pain, function, and quality of life subscales in KOOS, were validated psychometrically as standalone subscales instead of as whole instruments. However, none of the included PROMs have been validated for all measurement properties. Thus, further studies are still warranted to evaluate those PROMs. Use of the other 25 scales and subscales should be tempered until further studies validate their measurement properties. Cite this article: Bone Joint Res 2021;10(3):203–217

Aims

Focal knee arthroplasty is an attractive alternative to knee arthroplasty for young patients because it allows preservation of a large amount of bone for potential revisions. However, the mechanical behaviour of cartilage has not yet been investigated because it is challenging to evaluate in vivo contact areas, pressure, and deformations from metal implants. Therefore, this study aimed to determine the contact pressure in the tibiofemoral joint with a focal knee arthroplasty using a finite element model.

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.

Aims

This study aimed to investigate the role and mechanism of meniscal cell lysate (MCL) in fibroblast-like synoviocytes (FLSs) and osteoarthritis (OA).

Aims

Orthopaedic surgery requires grafts with sufficient mechanical strength. For this purpose, decellularized tissue is an available option that lacks the complications of autologous tissue. However, it is not widely used in orthopaedic surgeries. This study investigated clinical trials of the use of decellularized tissue grafts in orthopaedic surgery.

Aims

To explore the efficacy of extracorporeal shockwave therapy (ESWT) in the treatment of osteochondral defect (OCD), and its effects on the levels of transforming growth factor (TGF)-β, bone morphogenetic protein (BMP)-2, -3, -4, -5, and -7 in terms of cartilage and bone regeneration.

Aims

The effects of remnant preservation on the anterior cruciate ligament (ACL) and its relationship with the tendon graft remain unclear. We hypothesized that the co-culture of remnant cells and bone marrow stromal cells (BMSCs) decreases apoptosis and enhances the activity of the hamstring tendons and tenocytes, thus aiding ACL reconstruction.

Aims

Adenosine, lidocaine, and Mg²⁺ (ALM) therapy exerts differential immuno-inflammatory responses in males and females early after anterior cruciate ligament (ACL) reconstruction (ACLR). Our aim was to investigate sex-specific effects of ALM therapy on joint tissue repair and recovery 28 days after surgery.

Aims

Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes.

Aims

The anterior cruciate ligament (ACL) is known to have a poor wound healing capacity, whereas other ligaments outside of the knee joint capsule such as the medial collateral ligament (MCL) apparently heal more easily. Plasmin has been identified as a major component in the synovial fluid that varies among patients. The aim of this study was to test whether plasmin, a component of synovial fluid, could be a main factor responsible for the poor wound healing capacity of the ACL.

Aims

Proliferation, migration, and differentiation of anterior cruciate ligament (ACL) remnant and surrounding cells are fundamental processes for ACL reconstruction; however, the interaction between ACL remnant and surrounding cells is unclear. We hypothesized that ACL remnant cells preserve the capability to regulate the surrounding cells’ activity, collagen gene expression, and tenogenic differentiation. Moreover, extracorporeal shock wave (ESW) would not only promote activity of ACL remnant cells, but also enhance their paracrine regulation of surrounding cells.

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.

Objectives

In this study, we compared the pain behaviour and osteoarthritis (OA) progression between anterior cruciate ligament transection (ACLT) and osteochondral injury in surgically-induced OA rat models.

Objectives

Given the function of adiponectin (ADIPOQ) on the inflammatory condition of obesity and osteoarthritis (OA), we hypothesized that the ADIPOQ gene might be a candidate gene for a marker of susceptibility to OA.

Objectives

The aims of this study were to determine whether the administration of anti-inflammatory and antifibrotic agents affect the proliferation, viability, and expression of markers involved in the fibrotic development of the fibroblasts obtained from arthrofibrotic tissue in vitro, and to evaluate the effect of the agents on arthrofibrosis prevention in vivo.

Objectives

The injured anterior cruciate ligament (ACL) is thought to exhibit an impaired healing response, and attempts at surgical repair have not been successful. Connective tissue growth factor (CTGF) is reported to be associated with wound healing, probably through transforming growth factor beta 1 (TGF-β1).