Aims. This study aimed to determine the expression and clinical significance of a cartilage protein, cartilage oligomeric matrix protein (COMP), in knee osteoarthritis (OA) patients. Methods. A total of 270 knee OA patients and 93 healthy controls were recruited. COMP messenger RNA (mRNA) and protein levels in serum, synovial fluid, synovial tissue, and fibroblast-like synoviocytes (FLSs) of knee OA patients were determined using enzyme-linked immunosorbent assay, real-time polymerase chain reaction, and immunohistochemistry. Results. COMP protein levels were significantly elevated in serum and synovial fluid of knee OA patients, especially those in the advanced stages of the disease. Serum COMP was significantly correlated with radiological severity as well as measures of body composition, physical performance, knee pain, and disability. Receiver operating characteristic curve analysis unveiled a diagnostic value of serum COMP as a biomarker of knee OA (41.64 ng/ml, area under the curve (AUC) = 1.00), with a sensitivity of 99.6% and a specificity of 100.0%. Further analysis uncovered that COMP mRNA expression was markedly upregulated in the inflamed synovium of knee OA, consistent with immunohistochemical staining revealing localization of COMP protein in the lining and sub-lining layers of knee OA inflamed synovium. Most notably, relative COMP mRNA expression in knee OA synovium was positively associated with its protein levels in serum and synovial fluid of knee OA patients. In human knee OA FLSs activated with tumour necrosis factor-alpha, COMP mRNA expression was considerably up-regulated in a time-dependent manner. Conclusion. All results indicate that COMP might serve as a supportive diagnostic marker for knee OA in conjunction with the standard diagnostic methods. Cite this article: Bone Joint Res 2024;13(6):261–271

Aims. Knee osteoarthritis (OA) is characterized by a chronic inflammatory process involving multiple cytokine pathways, leading to articular cartilage degeneration. Intra-articular therapies using pharmaceutical or autologous anti-inflammatory factors offer potential non-surgical treatment options. Autologous protein solution (APS) is one such product that uses the patient’s blood to produce a concentrate of cells and anti-inflammatory cytokines. This study evaluated the effect of a specific APS intra-articular injection (nSTRIDE) on patient-reported outcome measures compared to saline in moderate knee OA. Methods. A parallel, double-blinded, placebo-controlled randomized controlled trial was conducted, where patients with unilateral moderate knee OA (Kellgren-Lawrence grade 2 or 3) received either nSTRIDE or saline (placebo) injection to their symptomatic knee. The primary outcome was the difference in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score at 12 months post-intervention. Secondary outcomes included WOMAC component scores, Knee injury and Osteoarthritis Outcome Score (KOOS), and visual analogue scale (VAS) scores at all follow-up timepoints (three, six, and 12 months). Results. A total of 40 patients were analyzed (21 nSTRIDE; 19 saline) in the study. No significant difference was found between nSTRIDE and saline groups for WOMAC total score at 12 months (mean difference -10.4 (95% CI -24.4 to 3.6; p = 0.141). There were no significant differences in WOMAC or KOOS scores across all timepoints. VAS scores favoured the saline group for both rest and worst pain scales at 12 months post-injection (mean difference (worst) 12 months 21.5 (95% CI 6.2 to 36.8; p = 0.008); mean difference (rest) 12 months 17.8 (95% CI 2.2 to 33.4; p = 0.026)). There were no adverse events recorded in either study group. Conclusion. Our study demonstrates no significant differences between nSTRIDE and saline groups in KOOS and WOMAC scores over time. Notably, APS injection resulted in significantly worse pain symptoms at 12 months compared to saline injection. Cite this article: Bone Joint J 2024;106-B(9):907–915

Aims. The purpose of our study was to determine whether mesenchymal stem cells (MSCs) are an effective and safe therapeutic agent for the treatment of knee osteoarthritis (OA), owing to their cartilage regeneration potential. Methods. We searched PubMed, Embase, and the Cochrane Library, with keywords including “knee osteoarthritis” and “mesenchymal stem cells”, up to June 2019. We selected randomized controlled trials (RCTs) that explored the use of MSCs to treat knee OA. The visual analogue scale (VAS), Western Ontario and McMaster University Osteoarthritis Index (WOMAC), adverse events, and the whole-organ MRI score (WORMS) were used as the primary evaluation tools in the studies. Our meta-analysis included a subgroup analysis of cell dose and cell source. Results. Seven trials evaluating 256 patients were included in the meta-analysis. MSC treatment significantly improved the VAS (mean difference (MD), –13.24; 95% confidence intervals (CIs) –23.28 to –3.20, p = 0.010) and WOMAC (MD, –7.22; 95% CI –12.97 to –1.47, p = 0.010). The low-dose group with less than 30 million cells showed lower p-values for both the VAS and WOMAC. Adipose and umbilical cord–derived stem cells also had lower p-values for pain scores than those derived from bone marrow. Conclusion. Overall, MSC-based cell therapy is a relatively safe treatment that holds great potential for OA, evidenced by a positive effect on pain and knee function. Using low-dose (25 million) and adipose-derived stem cells is likely to achieve better results, but further research is needed. Cite this article: Bone Joint Res 2020;9(10):719–728

Objectives. Normal sagittal spine-pelvis-lower extremity alignment is crucial in humans for maintaining an ergonomic upright standing posture, and pathogenesis in any segment leads to poor balance. The present study aimed to investigate how this sagittal alignment can be affected by severe knee osteoarthritis (KOA), and whether associated changes corresponded with symptoms of lower back pain (LBP) in this patient population. Methods. Lateral radiograph films in an upright standing position were obtained from 59 patients with severe KOA and 58 asymptomatic controls free from KOA. Sagittal alignment of the spine, pelvis, hip and proximal femur was quantified by measuring several radiographic parameters. Global balance was accessed according to the relative position of the C7 plumb line to the sacrum and femoral heads. The presence of chronic LBP was documented. Comparisons between the two groups were carried by independent samples t-tests or chi-squared test. Results. Patients with severe KOA showed significant backward femoral inclination (FI), hip flexion, forward spinal inclination, and higher prevalence of global imbalance (27.1% versus 3.4%, p < 0.001) compared with controls. In addition, patients with FI of 10° (n = 23) showed reduced lumbar lordosis and significant forward spinal inclination compared with controls, whereas those with FI > 10° (n = 36) presented with significant pelvic anteversion and hip flexion. A total of 39 patients with KOA (66.1%) suffered from LBP. There was no significant difference in sagittal alignment between KOA patients with and without LBP. Conclusions. The sagittal alignment of spine-pelvis-lower extremity axis was significantly influenced by severe KOA. The lumbar spine served as the primary source of compensation, while hip flexion and pelvic anteversion increased for further compensation. Changes in sagittal alignment may not be involved in the pathogenesis of LBP in this patient population. Cite this article: W. J. Wang, F. Liu, Y.W. Zhu, M.H. Sun, Y. Qiu, W. J. Weng. Sagittal alignment of the spine-pelvis-lower extremity axis in patients with severe knee osteoarthritis: A radiographic study. Bone Joint Res 2016;5:198–205. DOI:10.1302/2046-3758.55.2000538

Aims. The aim of this study was to estimate time to arthroplasty among patients with hip and knee osteoarthritis (OA), and to identify factors at enrolment to first-line intervention that are prognostic for progression to surgery. Methods. In this longitudinal register-based observational study, we identified 72,069 patients with hip and knee OA in the Better Management of Patients with Osteoarthritis Register (BOA), who were referred for first-line OA intervention, between May 2008 and December 2016. Patients were followed until the first primary arthroplasty surgery before 31 December 2016, stratified into a hip and a knee OA cohort. Data were analyzed with Kaplan-Meier and multivariable-adjusted Cox regression. Results. At five years, Kaplan-Meier estimates showed that 46% (95% confidence interval (CI) 44.6 to 46.9) of those with hip OA, and 20% (95% CI 19.7 to 21.0) of those with knee OA, had progressed to arthroplasty. The strongest prognostic factors were desire for surgery (hazard ratio (HR) hip 3.12 (95% CI 2.95 to 3.31), HR knee 2.72 (95% CI 2.55 to 2.90)), walking difficulties (HR hip 2.20 (95% CI 1.97 to 2.46), HR knee 1.95 (95% CI 1.73 to 2.20)), and frequent pain (HR hip 1.56 (95% CI 1.40 to 1.73), HR knee 1.77 (95% CI 1.58 to 2.00)). In hip OA, the probability of progression to surgery was lower among those with comorbidities (e.g. ≥ four conditions; HR 0.64 (95% CI 0.59 to 0.69)), with no detectable effects in the knee OA cohort. Instead, being overweight or obese increased the probability of OA progress in the knee cohort (HR 1.25 (95% CI 1.15 to 1.37)), but not among those with hip OA. Conclusion. Patients with hip OA progressed faster and to a greater extent to arthroplasty than patients with knee OA. Progression was strongly influenced by patients’ desire for surgery and by factors related to severity of OA symptoms, but factors not directly related to OA symptoms are also of importance. However, a large proportion of patients with OA do not seem to require surgery within five years, especially among those with knee OA. Cite this article: Bone Joint J 2022;104-B(7):792–800

Abstract. Objectives. Biomechanics is an essential form of measurement in the understanding of the development and progression of osteoarthritis (OA). However, the number of participants in biomechanical studies are often small and there is limited ways to share or combine data from across institutions or studies. This is essential for applying modern machine learning methods, where large, complex datasets can be used to identify patterns in the data. Using these data-driven approaches, it could be possible to better predict the optimal interventions for patients at an early stage, potentially avoiding pain and inappropriate surgery or rehabilitation. In this project we developed a prototype database platform for combining and sharing biomechanics datasets. The database includes methods for importing and standardising data and associated variables, to create a seamless, searchable combined dataset of both healthy and knee OA biomechanics. Methods. Data was curated through calls to members of the OATech Network+ (. https://www.oatechnetwork.org/. ). The requirements were 3D motion capture data from previous studies that related to analysing the biomechanics of knee OA, including participants with OA at any stage of progression plus healthy controls. As a minimum we required kinematic data of the lower limbs, plus associated kinetic data (i.e. ground reaction forces). Any additional, complementary data such as EMG could also be provided. Relevant ethical approvals had to be in place that allowed re-use of the data for other research purposes. The datasets were uploaded to a University hosted cloud platform. The database platform was developed using Javascript and hosted on a Windows server, located and managed within the department. Results. Three independent datasets were curated following the call to OATech Network+ members. These originated from separate studies collected from biomechanics labs at Cardiff University, Keele University, and Imperial College London. Participants with knee OA were at various stages of progression and all datasets included healthy controls. The total sample size of the three datasets is n=244, split approximately equally between healthy and knee OA participants. Naming conventions and formatting of the exported data varied greatly across datasets. Datasets were therefore formatted into a common format prior to upload, with guidelines developed for future contributions. Uploading data at the marker set level was too complicated for combination at the prototype stage. Therefore, processed variables relating to joint angles and joint moments were used. The resulting prototype database included an import function to align and standardise variables. A a simple query tool was further developed to extract outputs from the database, along with a suitable user interface for basic data exploration. Conclusion. Combining biomechanics dataset presents a wide range of challenges from both a technical and data governance context. Here we have taken the first steps to demonstrate a proof-of-concept that can combine heterogenous data from independent OA-related biomechanics studies into a combined, searchable resource. Expanding this in the future to a fully open access database will create an essential resource that will facilitate the application of data-driven models and analyses for better understanding, stratification and prediction of OA progression. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aims. This study aims to determine the rate of and risk factors for total knee arthroplasty (TKA) after operative management of tibial plateau fractures (TPFs) in older adults. Methods. This is a retrospective cohort study of 182 displaced TPFs in 180 patients aged ≥ 60 years, over a 12-year period with a minimum follow-up of one year. The mean age was 70.7 years (SD 7.7; 60 to 89), and 139/180 patients (77.2%) were female. Radiological assessment consisted of fracture classification; pre-existing knee osteoarthritis (OA); reduction quality; loss of reduction; and post-traumatic OA. Fracture depression was measured on CT, and the volume of defect estimated as half an oblate spheroid. Operative management, complications, reoperations, and mortality were recorded. Results. Nearly half of the fractures were Schatzker II AO B3.1 fractures (n = 85; 47%). Radiological knee OA was present at fracture in 59/182 TPFs (32.6%). Primary management was fixation in 174 (95.6%) and acute TKA in eight (4.4%). A total of 13 patients underwent late TKA (7.5%), most often within two years. By five years, 21/182 12% (95% confidence interval (CI) 6.0 to 16.7) had required TKA. Larger volume defects of greater depth on CT (median 15.9 mm vs 9.4 mm; p < 0.001) were significantly associated with TKA requirement. CT-measured joint depression of > 12.8 mm was associated with TKA requirement (area under the curve (AUC) 0.766; p = 0.001). Severe joint depression of > 15.5 mm (hazard ratio (HR) 6.15 (95% CI 2.60 to 14.55); p < 0.001) and pre-existing knee OA (HR 2.70 (95% CI 1.14 to 6.37); p = 0.024) were independently associated with TKA requirement. Where patients with severe joint depression of > 15.5 mm were managed with fixation, 11/25 ultimately required TKA. Conclusion. Overall, 12% of patients aged ≥ 60 years underwent TKA within five years of TPF. Severe joint depression and pre-existing knee arthritis were independent risk factors for both post-traumatic OA and TKA. These features should be investigated as potential indications for acute TKA in older adults with TPFs. Cite this article: Bone Joint J 2024;106-B(1):28–37

The aim of this research was to determine biomechanical markers which differentiate medial knee osteoarthritis (OA) patients who do and do not show structural progression over a 2-year period. A cohort of 36 subjects was selected from a longitudinal study (Meireles et al 2017) using Kellgren-Lawrence (KL) scores at baseline and 2-year follow-up. The cohort consisted of 10 healthy controls (HC) (KL=0 at both time points), 15 medial knee OA non-progressors (NPKOA) (KL≥1 at baseline and no change over 2 years), and 11 medial knee OA progressors (PKOA) (KL≥1 at baseline and increase of ≥1 over 2 years). 3D integrated motion capture data from three walking trials were processed through a musculoskeletal modelling framework (Smith et al 2016) to estimate knee joint loading parameters (i.e., magnitude of mean contact pressure, and centre of pressure (COP)). Parameters at first and second peak were extracted and compared between groups using Kruskal-Wallis and Mann-Whitney tests. Higher magnitudes were observed in PKOA vs NPKOA, and PKOA vs HC groups at both time points. Additionally, a posterior (1st and 2nd peak), and lateral (2nd peak) shift in medial compartment COP was shown between PKOA and NPKOA, and PKOA and HC subjects. Interestingly, in the studied parameters, no differences were observed between NPKOA and HC groups. Significantly higher magnitude, and a more posterior and lateral COP was observed between PKOA and NPKOA patients. These differences, combined with an absence of difference between NPKOA and HC suggest structural OA progression is driven by a combination of altered loading magnitude and location. These results may serve as guidelines for targeted gait retraining rehabilitation to slow or stop knee OA progression whereby shifting COP anterior and medial and reducing magnitude by ~22% may shift patients from a PKOA to a NPKOA trajectory

Abstract. Osteoarthritis (OA) is a degenerative disorder associated with cartilage loss and is a leading cause of disability around the world. In old age, the capacity of cartilage to regenerate is diminished. With an aging population, the burden of OA is set to rise. Currently, there is no definitive treatment for OA. However, cell-based therapies derived from adipose tissue are promising. A PRISMA systematic review was conducted employing four databases (MEDLINE, EMBASE, Cochrane, Web of Science) to identify all clinical studies that utilized adipose tissue derived mesenchymal stem cells (AMSCs) or stromal vascular fraction (SVF) for the treatment of knee OA. Eighteen studies were included, which met the inclusion criteria. Meta-analyses were conducted on fourteen of these studies, which all documented WOMAC scores after the administration of AMSCs. Pooled analysis revealed that cell-based treatments definitively improve WOMAC scores, post treatment. These improvements increased with time. The studies in this meta-analysis have established the safety and efficacy of both AMSC therapy and SVF therapy for knee OA in old adults and show that they reduce pain and improve knee function in symptomatic knee OA suggesting that they may be effective therapies to improve mobility in an aging population

Abstract. Objectives. To compare the effectiveness of phonophoresis (PH) and conventional therapeutic ultrasound (US) on the functional and pain outcomes of patients with knee osteoarthritis. Methods. We conducted an electronic search through PubMed, Cochrane Central Register of Clinical Trials (CENTRAL), Web of Science (WOS), and Scopus databases. We screened the retrieved articles to include only English full-text randomized controlled trials that examined the effect of phonophoresis versus conventional therapeutic ultrasound on patients with knee osteoarthritis. Two reviewers screened, extracted the data, and independently assessed the quality of the included articles. Results. A total of five randomized controlled trials met our inclusion criteria out of 267 studies screened. Our results showed no statistically significant differences between the PH and US groups (1), (2), (3),(4), and (5). The PH group demonstrated more significant effects than the UT group in reducing VAS pain scores (P=0.009) and improving WOMAC scores, although this did not reach the level of significance (P=0.143) (5). In the long term, PH therapy was found to be superior to US in improving painless walking duration and distance VAS scores (p=0.034, 0.017) respectively, as well as walking and resting walking VAS scores (p=0.03, 0.007) respectively, which were found to be permanent (3). Conclusions. Both therapies improve pain and function. However, we suggest conducting more high-quality trials with larger sample sizes and do not recommend the use of these therapies in clinical practice due to limitations in gender selection and high risk of bias. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aberrant infrapatellar fat metabolism is a notable feature provoking inflammation and fibrosis in the progression of osteoarthritis (OA). Irisin, a secretory subunit of fibronectin type III domain containing 5 (FNDC5) regulate adipose morphogenesis, energy expenditure, skeletal muscle, and bone metabolism. This study aims to characterize the biological roles of Irisin signaling in an infrapatellar fat formation and OA development. Injured articular specimens were harvested from 19 patients with end-stage knee OA and 11 patients with the femoral neck fracture. Knee joints in mice that overexpressed Irisin were subjected to intra-articular injection of collagenase to provoke OA. Expressions of Irisin, adipokines, and MMPs probed with RT-quantitative PCR. Infrapatellar adiposity, articular cartilage damage, and synovial integrity verified with histomorphometry and immunohistochemistry. Infrapatellar adipose and synovial tissues instead of articular cartilage exhibited Irisin immunostaining. Human OA specimens showed 40% decline in Irisin expression than the non-OA group. In vitro, the gain of Irisin function enabled synovial fibroblasts but not chondrocytes to display minor responses to the IL-1β provocation of MMP3 and MMP9 expression. Of note, Irisin signaling reduced adipogenic gene expression and adipocyte formation of mesenchymal progenitor cells. In collagenase-mediated OA knee pathogenesis, forced FNDC5 expression in articular compromised the collagenase-induced infrapatellar adipose hypertrophy, synovial hypercellularity, and membrane hyperplasia. These adipose-regulatory actions warded off the affected knees from cartilage destruction and gait aberrance. Likewise, intra-articular injection of Irisin recombinant protein mitigated the development of infrapatellar adiposity and synovitis slowing down the progression of cartilage erosion and walking profile irregularity. Affected joints and adipocytes responded to the Irisin recombinant protein treatment by reducing the expressions of cartilage-deleterious adipokines IL-6, leptin, and adiponectin through regulating PPAR&gamma, function. Irisin dysfunction is relevant to the existence of end-stage knee OA. Irisin signaling protects from excessive adipogenesis of mesenchymal precursor cells and diminished inflammation and cartilage catabolism actions aggravated by adipocytes and synovial cells. This study sheds emerging new light on the Irisin signaling stabilization of infrapatellar adipose homeostasis and the perspective of the therapeutic potential of Irisin recombinant protein for deescalating knee OA development

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

Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA). Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. To create a reliable and interpretable precision health tool that predicts rapid knee OA progression over a 2-year period from baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising disease progression into pain and/or radiographic progression) and binary predictions. Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics. Interpretability analyses were carried out to identify important predictors of progression. Our final models yielded higher accuracy scores for multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856-0.860) compared to binary predictions (AUC-ROC: 0.717, 95% CI: 0.712-0.722). Important predictors of rapid disease progression included WOMAC scores and MRI features. Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression. Our models provide accurate predictions and, importantly, allow specific predictors of rapid disease progression to be identified. Furthermore, the transparency and explainability of our methods may facilitate their acceptance by clinicians and patients, enabling effective translation to clinical practice

Aims. Osteoarthritis (OA) is the most prevalent joint disease. However, the specific and definitive genetic mechanisms of OA are still unclear. Methods. Tissue-related transcriptome-wide association studies (TWAS) of hip OA and knee OA were performed utilizing the genome-wide association study (GWAS) data of hip OA and knee OA (including 2,396 hospital-diagnosed hip OA patients versus 9,593 controls, and 4,462 hospital-diagnosed knee OA patients versus 17,885 controls) and gene expression reference to skeletal muscle and blood. The OA-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the messenger RNA (mRNA) expression profiles of hip OA and knee OA. Functional enrichment and annotation analysis of identified genes was performed by the DAVID and FUMAGWAS tools. Results. We detected 33 common genes, eight common gene ontology (GO) terms, and one common pathway for hip OA, such as calcium and integrin-binding protein 1 (CIB1) (PTWAS = 0.025, FCmRNA = -1.575 for skeletal muscle), adrenomedullin (ADM) (PTWAS = 0.022, FCmRNA = -4.644 for blood), Golgi apparatus (PTWAS <0.001, PmRNA = 0.012 for blood), and phosphatidylinositol 3' -kinase-protein kinase B (PI3K-Akt) signalling pathway (PTWAS = 0.033, PmRNA = 0.005 for blood). For knee OA, we detected 24 common genes, eight common GO terms, and two common pathways, such as histocompatibility complex, class II, DR beta 1 (HLA-DRB1) (PTWAS = 0.040, FCmRNA = 4.062 for skeletal muscle), Follistatin-like 1 (FSTL1) (PTWAS = 0.048, FCmRNA = 3.000 for blood), cytoplasm (PTWAS < 0.001, PmRNA = 0.005 for blood), and complement and coagulation cascades (PTWAS = 0.017, PmRNA = 0.001 for skeletal muscle). Conclusion. We identified a group of OA-associated genes and pathways, providing novel clues for understanding the genetic mechanism of OA. Cite this article:Bone Joint Res. 2020;9(3):130–138

Abstract. Introduction. Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA), a degenerative joint disease affecting over 300 million people worldwide. Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. Objectives. This study aims to create a trustworthy and interpretable precision health tool that predicts rapid knee OA progression based on baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. Methods. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising patients into non-progressors, pain-only progressors, radiographic-only progressors, and both pain and radiographic progressors) and binary predictions (categorising patients into non-progressors and progressors). Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics, such as AUC-ROC, AUC-PRC, F1-score, precision, and recall. Additionally, interpretability analyses were carried out to identify important predictors of rapid disease progression. Results. Our final models yielded high accuracy scores for both multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856–0.860; AUC-PRC: 0.675, 95% CI: 0.671–0.679; F1-score: 0.560, 95% CI: 0.554–0.566) and binary predictions (AUC-ROC: 0.717, 95% CI: 0.712–0.722; AUC-PRC: 0.620, 95% CI: 0.616–0.624; F1-score: 0.676, 95% CI: 0.673–0679). Important predictors of rapid disease progression included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and MRI features. Our models were further successfully validated using a hold-out dataset, which was previously omitted from model development and training (AUC-ROC: 0.877 for multi-class predictions; AUC-ROC: 0.746 for binary predictions). Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger (AUC-ROC: 0.862, 95% CI: 0.861–0.863 for multi-class predictions; AUC-ROC: 0.736, 95% CI: 0.734–0.738 for binary predictions). Conclusions. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression using “Autoprognosis 2.0”. Our models provide accurate predictions and offer insights into important predictors of rapid disease progression. Furthermore, the transparency and interpretability of our methods may facilitate their acceptance by clinicians and patients, enabling effective utilisation in clinical practice. Future work should focus on refining these models by increasing the sample size, integrating additional features, and using independent datasets for external validation. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

To design osteoarthritis (OA) care based on prognosis, we need to identify individuals who are most likely of disease progression. We estimated survival time of the native hip and knee joint and evaluated what patient-related and OA disease-related factors associated with progression to joint replacement surgery. We included 72,069 patients referred to first-line OA intervention (patient education and exercise) during 2008 and 2016 and registered in the Swedish quality register Better Management of Patients with Osteoarthritis (BOA). Kaplan–Meier survival analyses were used to estimate joint survival time. Hazard ratios (HR) with 95% confidence interval [CI] were calculated using multiple Cox regression. The 5-year survival time of the native joint was 56% for hip OA and 80% for knee OA. Disease-related factors were more strongly associated with progression to joint replacement (e.g. willingness for surgery HR; hip 2.9 [95% CI, 2.7–3.1], knee 2.7 [2.6–2.9] and walking difficulties (HR; hip 2.2 [2.0–2.5], knee 1.9 [1.7–2.2]), than patient-related factors such socioeconomic factors (e.g. highest income quartile HR; hip 1.3 [1.2–1.3], knee 1.3 [1.2–1.4]) and comorbidities (e.g. ≥6 conditions HR; hip: 0.7 [0.6–0.7], knee; 1.1 [1.0–1.2]). Patients with hip OA were more likely to undergo surgery and at an earlier time compared with those with knee OA. Progression was strongly influenced by factors associated with the OA disease, but other patient-related factors are important. However, a large proportion of patients with OA do not seem to require surgery, especially among those with knee OA

Introduction. Polyacrylamide hydrogel (iPAAG. 1. ), is CE marked for treating symptomatic knee osteoarthritis (OA), meeting the need for an effective, long-lasting, and safe non-surgical option. This study evaluates the efficacy and safety of a single 6 ml intra-articular injection of iPAAG in participants with moderate to severe knee OA over a 5-year post-treatment period, presenting data from the 4-year follow up. Method. This prospective multicentre study (3 sites in Denmark) involved 49 participants (31 females) with an average age of 70 (range 44 – 86 years). They received a single 6 mL iPAAG injection. All participants provided informed consent and re-consented to continue after 1 year. The study followed GCP principles and was approved by Danish health authorities and local Health Research Ethics committees. Twenty-seven participants completed the 4-year follow-up. The study evaluated WOMAC pain, stiffness, function, and Patient Global Assessment (PGA) of disease impact. Changes from baseline were analysed using a mixed model for repeated measurement (MMRM). Sensitivity analyses were applied on the extension data, where the MMRM analysis was repeated only including patients in the extension phase and an ANCOVA model was used, replacing missing values at 4-years with baseline values (BOCF). Results. The planned MMRM analysis (n=49) revealed a statistically significant decrease in WOMAC pain subscale scores (-22.0; 95%CI: -29.5; -14.4) from baseline to 4-years. Analysis of the extension phase (n=27) showed similar results (-21.8; 95%CI: -29.0; -14.6) compared to the initial analysis. Furthermore, BOCF analysis indicated a statistically significant reduction in WOMAC pain subscale scores from baseline (-13.0 units). Four new adverse events were reported between the 3-year and 4-year visits; none were related to treatment. Conclusions. This study shows that single injections of 6 ml intra-articular iPAAG were well tolerated and continued to provide clinically important effectiveness at 4-years after treatment. Acknowledgements. The study was sponsored by Contura International A/S

Aims. Although knee osteoarthritis (OA) is diagnosed and monitored radiologically, actual full-thickness cartilage loss (FTCL) has rarely been correlated with radiological classification. This study aims to analyze which classification system correlates best with FTCL and to assess their reliability. Methods. A prospective study of 300 consecutive patients undergoing unilateral total knee arthroplasty (TKA) for OA (mean age 69 years (44 to 91; standard deviation (SD) 9.5), 178 (59%) female). Two blinded examiners independently graded preoperative radiographs using five common systems: Kellgren-Lawrence (KL); International Knee Documentation Committee (IKDC); Fairbank; Brandt; and Ahlbäck. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Intraoperatively, anterior cruciate ligament (ACL) status and the presence of FTCL in 16 regions of interest were recorded. Radiological classification and FTCL were correlated using the Spearman correlation coefficient. Results. Knees had a mean of 6.8 regions of FTCL (SD 3.1), most common medially. The commonest patterns of FTCL were medial ± patellofemoral (143/300, 48%) and tricompartmental (89/300, 30%). ACL status was associated with pattern of FTCL (p = 0.023). All radiological classification systems demonstrated moderate ICC, but this was highest for the IKDC: whole knee 0.68 (95% confidence interval (CI) 0.60 to 0.74); medial compartment 0.84 (95% CI 0.80 to 0.87); and lateral compartment 0.79 (95% CI 0.73 to 0.83). Correlation with actual FTCL was strongest for Ahlbäck (Spearman rho 0.27 to 0.39) and KL (0.30 to 0.33) systems, although all systems demonstrated medium correlation. The Ahlbäck score was the most discriminating in severe knee OA. Osteophyte presence in the medial compartment had high positive predictive value (PPV) for FTCL, but not in the lateral compartment. Conclusion. The Ahlbäck and KL systems had the highest correlation with confirmed cartilage loss at TKA. However, the IKDC system displayed the best interobserver reliability, with favourable correlation with FTCL in medial and lateral compartments, although it was less discriminating in more severe disease. Cite this article: Bone Joint J 2020;102-B(3):301–309

Aims. The aetiologies of common degenerative spine, hip, and knee pathologies are still not completely understood. Mechanical theories have suggested that those diseases are related to sagittal pelvic morphology and spinopelvic-femoral dynamics. The link between the most widely used parameter for sagittal pelvic morphology, pelvic incidence (PI), and the onset of degenerative lumbar, hip, and knee pathologies has not been studied in a large-scale setting. Methods. A total of 421 patients from the Cohort Hip and Cohort Knee (CHECK) database, a population-based observational cohort, with hip and knee complaints < 6 months, aged between 45 and 65 years old, and with lateral lumbar, hip, and knee radiographs available, were included. Sagittal spinopelvic parameters and pathologies (spondylolisthesis and degenerative disc disease (DDD)) were measured at eight-year follow-up and characteristics of hip and knee osteoarthritis (OA) at baseline and eight-year follow-up. Epidemiology of the degenerative disorders and clinical outcome scores (hip and knee pain and Western Ontario and McMaster Universities Osteoarthritis Index) were compared between low PI (< 50°), normal PI (50° to 60°), and high PI (> 60°) using generalized estimating equations. Results. Demographic details were not different between the different PI groups. L4 to L5 and L5 to S1 spondylolisthesis were more frequently present in subjects with high PI compared to low PI (L4 to L5, OR 3.717; p = 0.024 vs L5 to S1 OR 7.751; p = 0.001). L5 to S1 DDD occurred more in patients with low PI compared to high PI (OR 1.889; p = 0.010), whereas there were no differences in L4 to L5 DDD among individuals with a different PI. The incidence of hip OA was higher in participants with low PI compared to normal (OR 1.262; p = 0.414) or high PI (OR 1.337; p = 0.274), but not statistically different. The incidence of knee OA was higher in individuals with a high PI compared to low PI (OR 1.620; p = 0.034). Conclusion. High PI is a risk factor for development of spondylolisthesis and knee OA. Low pelvic incidence is related to DDD, and may be linked to OA of the hip. Level of Evidence: 1b. Cite this article: Bone Joint J 2020;102-B(9):1261–1267

The tendency towards using inertial sensors for remote monitoring of the patients at home is increasing. One of the most important characteristics of the sensors is sampling rate. Higher sampling rate results in higher resolution of the sampled signal and lower amount of noise. However, higher sampling frequency comes with a cost. The main aim of our study was to determine the validity of measurements performed by low sampling frequency (12.5 Hz) accelerometers (SENS) in patients with knee osteoarthritis compared to standard sensor-based motion capture system (Xsens). We also determined the test-retest reliability of SENS accelerometers. Participants were patients with unilateral knee osteoarthritis. Gait analysis was performed simultaneously by using Xsens and SENS sensors during two repetitions of over-ground walking at a self-selected speed. Gait data from Xsens were used as an input for AnyBody musculoskeletal modeling software to measure the accelerations at the exact location of two defined virtual sensors in the model (VirtualSENS). After preprocessing, the signals from SENS and VirtualSENS were compared in different coordinate axes in time and frequency domains. ICC for SENS data from first and second trials were calculated to assess the repeatability of the measurements. We included 32 patients (18 females) with median age 70.1[48.1 – 85.4]. Mean height and weight of the patients were 173.2 ± 9.6 cm and 84.2 ± 14.7 kg respectively. The correlation between accelerations in time domain measured by SENS and VirtualSENS in different axes was r = 0.94 in y-axis (anteroposterior), r = 0.91 in x-axis (vertical), r = 0.83 in z-axis (mediolateral), and r = 0.89 for the magnitude vector. In frequency domain, the value and the power of fundamental frequencies (F. 0. ) of SENS and VirtualSENS signals demonstrated strong correlation (r = 0.98 and r = 0.99 respectively). The result of test-retest evaluation showed excellent repeatability for acceleration measurement by SENS sensors. ICC was between 0.89 to 0.94 for different coordinate axes. Low sampling frequency accelerometers can provide valid and reliable measurements especially for home monitoring of the patients, in which handling big data and sensors cost and battery lifetime are among important issues