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

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

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

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

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

An increased number of neutrophils (NEUs) has long been associated with infections in the knee joints; their contribution to knee osteoarthritis (KOA) pathophysiology remains largely unexplored. This study aimed to compare the phenotypic and functional characteristics of synovial fluid (SF)-derived NEUs in KOA and knee infection (INF). Flow cytometric analysis, protein level measurements (ELISA), NEU oxidative burst assays, detection of NEU phagocytosis (pHrodo. TM. Green Zymosan Biparticles. TM. Conjugate for Phagocytosis), morphological analysis of the SF-derived/synovial tissue NEUs, and cultivation of human umbilical vein endothelial cells (HUVECs) using SF supernatant were used to characterise NEUs functionally/morphologically. Results: Compared with INF NEUs, KOA NEUs were characterised by a lower expression of CD11b, CD54 and CD64, a higher expression of CD62L, TLR2 and TLR4, and lower production of inflammatory mediators and proteases, except CCL2. Functionally, KOA NEUs displayed an increased production of radical oxygen species and phagocytic activity compared with INF NEUs. Morphologically, KOA and INF cells displayed different cell sizes and morphology, histological characteristics of the surrounding synovial tissues and influence on endothelial cells. KOA NEUs were further subdivided into two groups: SF containing <10% and SF with 10%–60% of NEUs. Analyses of two KOA NEU subgroups revealed that NEUs with SF <10% were characterised by 1) higher CD54, CD64, TLR2 and TLR4 expression on their surface; 2) higher concentrations of TNF-α, sTREM-1, VILIP-1, IL-1RA and MMP-9 in SFs. Our findings reveal a key role for NEUs in the pathophysiology of KOA, indicating that these cells are morphologically and functionally different from INF NEUs. Further studies should explore the mechanisms that contribute to the increased number of NEUs and their crosstalk with other immune cells in KOA. This study was supported by the Ministry of Health of the Czech Republic (NU20-06-00269; NU21-06-00370)

With the rising rates, and associated costs, of total knee arthroplasty (TKA), enhanced clarity regarding patient appropriateness for TKA is warranted. Towards addressing this gap, we elucidated in qualitative research that surgeons and osteoarthritis (OA) patients considered TKA need, readiness/willingness, health status, and expectations of TKA most important in determining patient appropriateness for TKA. The current study evaluated the predictive validity of pre-TKA measures of these appropriateness domains for attainment of a good TKA outcome. This prospective cohort study recruited knee OA patients aged 30+ years referred for TKA at two hip/knee surgery centers in Alberta, Canada. Those receiving primary, unilateral TKA completed questionnaires pre-TKA assessing TKA need (WOMAC-pain, ICOAP-pain, NRS-pain, KOOS-physical function, Perceived Arthritis Coping Efficacy, prior OA treatment), TKA readiness/willingness (Patient Acceptable Symptom State (PASS), willingness to undergo TKA), health status (PHQ-8, BMI, MSK and non-MSK comorbidities), TKA expectations (HSS KR Expectations survey items) and contextual factors (e.g., age, gender, employment status). One-year post-TKA, we assessed for a ‘good outcome’ (yes/no), defined as improved knee symptoms (OARSI-OMERACT responder criteria) AND overall satisfaction with TKA results. Multiple logistic regression, stepwise variable selection, and best possible subsets regression was used to identify the model with the smallest number of independent variables and greatest discriminant validity for our outcome. Receiver Operating Characteristic (ROC) curves were generated to compare the discriminative ability of each appropriateness domain based on the ‘area under the ROC curve’ (AUC). Multivariable robust Poisson regression was used to assess the relationship of the variables to achievement of a good outcome. f 1,275 TKA recipients, 1,053 (82.6%) had complete data for analyses (mean age 66.9 years [SD 8.8]; 58.6% female). Mean WOMAC pain and KOOS-PS scores were 11.5/20 (SD 3.5) and 52.8/100 (SD 17.1), respectively. 78.1% (95% CI 75.4–80.5%) achieved a good outcome. Stepwise variable selection identified optimal discrimination was achieved with 13 variables. The three best 13-variable models included measures of TKA need (WOMAC pain, KOOS-PS), readiness/willingness (PASS, TKA willingness), health status (PHQ-8, troublesome hips, contralateral knee, low back), TKA expectations (the importance of improved psychological well-being, ability to go up stairs, kneel, and participate in recreational activities as TKA outcomes), and patient age. Model discrimination was fair for TKA need (AUC 0.68, 95% CI 0.63-0.72), TKA readiness/willingness (AUC 0.61, 95% CI 0.57-0.65), health status (AUC 0.59, 95% CI 0.54-0.63) and TKA expectations (AUC 0.58, 95% CI 0.54-0.62), but the model with all appropriateness variables had good discrimination (AUC 0.72, 95% CI 0.685-0.76). The likelihood of achieving a good outcome was significantly higher for those with greater knee pain, disability, unacceptable knee symptoms, definite willingness to undergo TKA, less depression who considered improved ability to perform recreational activities or climb stairs ‘very important’ TKA outcomes, and lower in those who considered it important that TKA improve psychological wellbeing or ability to kneel. Beyond surgical need (OA symptoms) and health status, assessment of patients’ readiness and willingness to undergo, and their expectations for, TKA, should be incorporated into assessment of patient appropriateness for surgery

Introduction. The use of stem cell and platelet-rich plasma (PRP) injections for knee osteoarthritis (OA) is extremely controversial and at best experimental. These treatments are being given to patients across the nation for “cash only payments”. Our objectives were (1) to determine the proportion of board certified orthopedic surgeons who offer stem cell or PRP treatment for knee OA, (2) how much the practices charge for those treatments and (3) if members of the knee society use these therapies. Methods. Board certified orthopedic surgeons’ offices in our county were identified by their AAOS active membership. Knee society membership roll was also utilized. Offices were contacted by telephone and presented with a hypothetical patient with end stage knee osteoarthritis searching for specific treatment (stem cells or PRP injections). T-test was used to compare the Dade county board certified orthopedists to knee society members. Results. A total of 186 board certified orthopedic surgeons’ offices were contacted. 17.6% of all contacted orthopedics offices offered PRP and 12.5% offered stem cell treatments. 61.2% of the offices were transparent on the pricing of PRP while 31.8% gave a price for stem cell therapy. The remaining practices stated that pricing would be “determined or discussed” during a scheduled visit. Mean cost for a PRP injection was $887 (SE 101; range: $350–$1700) and for a stem cell injection was $2800 (SE 852; range: $1000–$6000). Usage of these therapies amongst general AAOS members and Knee Society members was found to be significantly different for both PRP and stem cells (17% vs. 10%; p<0.001 and 26% vs. 13%; p<0.001, respectively). No practice had a “free” research protocol to study the treatments. Conclusions. Biological injectables as a treatment for knee OA has theoretical potential promise in the management of arthritis but continues to be at best investigational. Knee Society members demonstrated significantly more caution using these treatments

Abstract. Introduction. The effectiveness of single intra-articular injections of polyacrylamide hydrogel (iPAAG) and hyaluronic acid (HA) was compared in subgroups of participants from an RCT based on baseline age, BMI or Kellgren-Lawrence (KL) grade. Methodology. 239 participants were randomised to 6 mL iPAAG (Arthrosamid; n=119) or 6 mL HA (Synvisc-One; n=120). Participants continued analgesics (except 48 hours prior to visits) and non-pharmacological therapy. Topical therapies and intra-articular corticosteroids were not allowed. Pre-specified subgroup analyses (age: <70 years, ≥70 years; BMI: normal, overweight, obese; KL grade: 2, 3, 4, 2–3) of change from baseline in WOMAC pain subscale at 52 weeks were based on the least squares means for the treatment-by-week interaction effect using a mixed model for repeated measurement with a restricted maximum likelihood-based approach. Results. Across all patients, change from baseline in WOMAC pain subscale in the iPAAG group was non-inferior to HA at 26 weeks and approached superiority (p=0.0572) at 52 weeks. Treatment differences for change from baseline in WOMAC pain subscale in favour of iPAAG over HA were statistically significant for the age <70 years (p=0.019), BMI normal (p=0.011) and KL grade 2–3 (p=0.033) subgroups. Treatment differences for all other subgroups favoured iPAAG, except for KL grade 4 which favoured HA, without reaching statistical significance. Conclusion. iPAAG approached superiority to HA across all participants at 52weeks, but demonstrated statistical superiority in participants with normal BMI, participants <70 years old or participants with KL score 2–3. iPAAG represents a useful alternative to HA for the treatment of knee OA

Abstract. Objectives. Exploring the relationship of gait function pre and post total knee replacement (TKR) in two groups of patients. Methods. Three-dimensional gait analysis was performed at Cardiff University, UK, and Karolinska University Hospital, Sweden, on 29 and 25 non-pathological (NP) volunteers, and 39 and 28 patients with end-stage knee osteoarthritis (OA), respectively. Patients were assessed pre and one-year post-TKR. Data reduction was performed via Principal Component (PC) analysis on twenty-four kinematic and kinetic waveforms in both NP and pre/post-TKR. Cardiff's and Karolinska's cohorts were analysed separately. The Cardiff Classifier, a classification system based on the Dempster-Shafer theory, was trained with the first 3 PCs of each variable for each cohort. The Classifier classifies each participant by assigning them a belief in NP, belief in OA (BOA) and belief in uncertainty, based on their biomechanical features. The correlation between patient's BOA values (range: 0–1, 0 indicates null BOA and 1 high BOA) pre and post-TKR was tested through Spearman's correlation coefficient in each cohort. The related-samples Wilcoxon signed-rank test (α=0.05) determined the significant changes in BOA in each cohort of patients. The Mann-Whitney U test (α=0.05) was run to explore differences between the patients’ cohorts. Results. There were no significant differences between patients’ cohorts in median age (p=0.096), height (p=0.673), weight (p=0.064) or KOOS sub-scores pre or post-TKR (p-value ranged 0.069 to 0.955) but Cardiff's patients had a significantly higher BMI (p=0.047). There was a significant, median decrease of 0.12 and 0.19 in the BOA pre to post TKR (p<0.001) in Cardiff's and Karolinska's patients, respectively. There was a statistically significant, strong positive correlation between the BOA pre and post-TKR (Cardiff:r. s. =0.706, p<0.001; Karolinska:r. s. =0.669, p<0.001). Conclusions. In two distinct cohorts of patients, having a more compromised gait function in end-stage knee OA was correlated with poorer gait function post-TKR

Summary Statement. This study provides preliminary evidence that people with knee osteoarthritis have greater asymmetry in joint loading than healthy controls. Altered loading of the contralateral limb may signify increased risk of injury to other lower limb joints in knee osteoarthritis. Introduction. Compensatory overloading of other lower limb joints is a potential reason for the non-random evolution of osteoarthritis (OA). In individuals with knee OA altered joint loading exists of the contralateral cognate joints. However, previous studies have neglected the temporal features of asymmetry in joint loading. The study aimed to identify the amount and temporal features of asymmetry in lower limb joint loading in advanced knee OA. Patients and Methods. Participants (n=15) were awaiting primary unilateral total knee replacement for OA (age 67.0 SD 8.9 years, height 1.66 SD 0.13 m, mass 84.2 SD 15.8 kg, BMI 30.7 SD 6.2 kg/m. 2. , median KL grade 4). Data were compared to asymptomatic age and sex matched controls. Kinematic and kinetic data during walking was acquired with 12 cameras (VICON MX-F20) and two Kistler force platforms at 100 Hz and 400 Hz respectively. Data were analysed in Visual3D (C-Motion Inc., USA). Asymmetry was computed in MatLab using a recently published symmetry index (SI) and symmetry function (SF). Variables (computed using inverse dynamics) were the peak external moments (%BW∗Height) of the hip, knee and ankle. Differences between means of the SI variables in the OA and control groups were compared using Student's t-tests. Discrete variables were also compared between limbs (paired t-test) or between the affected limb and matched control limb. Effect sizes (Cohen's d) for the differences were also computed. Results. A significant between group difference (OA and control) for SI was observed for the transverse plane ankle joint moment (16.1 SD 8.0 vs. 10.4 SD 4.8 d = 0.8 p = 0.049). A large effect size for the sagittal plane knee joint moment (22.9 SD 12.1 vs. 12.7 SD 5.1 d = 1.1 p = 0.178) and a medium effect size for the transverse plane hip joint moment (26.4 SD 15.9 vs. 16.6 SD 9.0 d = 0.7 p = 0.098) were observed. The unaffected limb (OA group) had higher peak hip flexion (5.76 SD 1.49 vs.5.32 SD 1.51 p = 0.041) and internal rotation moments (−0.67 SD 0.34 vs. −0.41 SD 0.18 d = 0.004) and a lower ankle inversion moment (0.16 SD 0.14 vs. 0.34 SD 0.24 d = 0.9 p = 0.030) compared to the affected limb. Only the difference in the first peak knee adduction moment for the affected and matched control limb was statistically significant (−2.65 SD 1.38 vs. −2.16 SD 1.16 d = 0.7 p = 0.031). Discussion and Conclusion. This study provides preliminary evidence of more asymmetry in joint moments of the lower limb in people with knee OA compared to controls. Further investigation with a larger sample is required to verify these findings. Altered loading of the contralateral cognate joints may signify increased risk of injury at the hip and ankle and highlights the need for monitoring of other lower limb joints in knee OA

Modern gait analysis offers a unique means to measure the biomechanical response to diseases of the musculoskeletal system during activities of daily living. The objective of this on-going study is to quantify the biomechanical environment of the knee joint in subjects with moderate knee osteoarthritis (OA). We collected 3-D motion, ground reaction force, and electromyographic data from seven normal subjects and five subjects with moderate knee OA. There were no differences in stride characteristics or joint motion patterns between the two groups. In contrast, we found differences in knee joint kinetics between the moderate OA subjects and the normal control subjects. The objective of this on-going study is to quantify the biomechanical environment of the knee joint in subjects with moderate knee osteoarthritis (OA). Our goal is to identify biomechanical characteristics related to treatment interventions. The moderate knee OA patients walked with a visibly normal gait as measured by stride characteristics and joint angles. Differences were detected in the joint loading (ie adduction and flexion moments). The biomechanical differences between normal and osteoarthritic knees will provide the basis upon which to design and evaluate non-invasive treatments for knee OA. Subjects performed, in random order, five trials of their normal selected speed, and a fast walk (150% of the normal speed). Three-dimensional motion and force data were used to calculate three dimensional joint angles, moments and forces. There were no differences in stride characteristics (walking speeds, stride lengths, or stride times) between the two groups. The moderate OA patients walked with normal knee joint motion patterns. In contrast, we found differences in knee joint kinetics between the moderate OA subjects and the normal control subjects. The magnitude of the adduction moment during stance was larger for the moderate OA patients at both walking speeds (p< 0.05). We also identified differences in the pattern of the flexion moment, but only at the higher walking speed (p< 0.05). Gait analysis can provide insight into the mechanical factors of knee osteoarthritis by quantifying the dynamic loading and alignment of the knee during activities of daily living

Knee osteoarthritis (OA) affects an estimated 250 million people worldwide, with a cure yet to be found. Consequently, there is an urgent need to improve our understanding of OA physiopathology. While knee OA has long been mostly described as a loss of cartilage thickness (CTh) and research has focused on this characteristic, the role of bone alterations is rapidly gaining in interest. Analyzing subchondral bone mineral density (sBMD) is particularly interesting because this could inform on the mechanical environment at the knee. However, there is a paucity of data on sBMD in literature mainly because of the lack of prior methods to measure this parameter. A method for 3D sBMD assessment based on computed tomography (CT) scans was recently proposed, thus allowing testing for sBMD differences in knee OA. This study aimed at comparing non-OA and medial OA knees in terms of tibial sBMD and CTh. Specifically, it was hypothesized that sBMD and CTh differ with OA. Ten knees with severe medial OA and 10 matched non-OA knees were analyzed after ethical approval (50% male; 60 ± 3 years old). The arthro-CT scans of the 20 knees were segmented using custom software to build 3D mesh models of the tibial bone and cartilage. CTh maps were obtained by calculating the distance between cartilage and bone meshes, while sBMD maps were calculated based on the intensity of the CT in the first 3mm of bone. For each knee, the average CTh and sBMD values over the entire medial and lateral compartments were calculated and used to determine the medial-to-lateral (M/L) CTh and sBMD ratios. Unpaired t-tests and receiver operating characteristic (ROC) were used for statistical analysis. The M/L sBMD ratio was significantly higher in OA compared to non-OA knees (1.14 ± 0.04 vs. 1.08 ± 0.03; p<0.01), whereas the CTh ratio was not significantly different between groups (0.70 ± 0.21 vs. 0.85 ± 0.10; p=0.06). No significant differences were found between OA and non-OA knees for the average medial CTh and sBMD (p>0.4). High classification performance was obtained for the sBMD ratio and low performance for the average sBMD in the medial compartment (areas under the ROC curve of 0.9 and 0.6, respectively). CTh ratio and medial compartment average provided medium classification performances (areas under the curve of 0.7). This study showed that sBMD differed between non-OA and severe medial OA knees and that sBMD M/L ratio was more sensitive to OA severity than CTh variables. These results brought new insights into the pathogenesis of knee OA, by supporting the idea that sBMD is altered with OA and suggesting that sBMD could play a role in disease development. Indeed, the mechanical stresses on the cartilages are related to the mechanical characteristics of the bones. Indirectly, this study also demonstrated the value of arthro-CT scans to simultaneously assess sBMD and CTh. Additional studies with larger cohorts of patients at different stages of the disease are necessary to better understand when changes in sBMD occur

Abstract. Objectives. Current tools to measure pain are broadly subjective impressions of the impact of the nociceptive impulse felt by the patient. A direct measure of nociception may offer a more objective indicator. Specifically, movement-induced physiological responses to nociception may offer a useful way to monitor knee OA. In this proof-of-concept study, we evaluated whether integrated biomechanical and physiological sensor datasets could display linked and quantifiable information to a nociceptive stimulus. Method. Following ethical approval, we applied a quantified thermal pain stimulus to a volunteer during stationary standing in a gait lab setting. An inertial measurement unit (IMU) and an electromyography (EMG) lower body marker set were tested and integrated with ground reaction force (GRF) data collection. Galvanic skin response electrodes and skin thermal sensors were manually timestamp linked to the integrated system. Results. The integrated EMG, GRF and IMU data show fluctuations within 0.5 seconds of each other when a thermal pain trigger is applied at several time points during a stationary standing test. Manually timestamped physiology measures displayed increased values during testing for skin conductivity (up to 5 µSiemens, 37% compared to baseline) and skin temperature (up to 0.3˚C, 1% compared to baseline). Conclusions. This proof-of-concept study suggests that physiological data mimics biomechanical data in response to a known pain stimuli. While this protocol requires further evaluation as to the measurement parameters, the association of the physiological output to the known pain stimulus suggests the potential development of wearable nociceptive sensors that can measure disease progression and treatment effectiveness

Introduction. Pain related to knee osteoarthritis (OA) is a complex phenomenon that cannot be fully explained by radiographic disease severity. We hypothesized that pain phenotypes are likely to be derived from a confluence of factors across multiple domains: knee OA pathology, psychology, and neurophysiological pain processing. The purpose of this study was to identify distinct phenotypes of knee OA, using measures from the proposed domains. Methods. Data from 3494 subjects participating in the Osteoarthritis Initiative (OAI) study was analyzed. Variables analyzed included: radiographic OA severity (Kellgren-Lawrence grade), isometric quadriceps strength, Body Mass Index (BMI), comorbidities, CES-D Depression subscale score, Coping Strategies Questionnaire Catastrophizing subscale score, number of pain sites, and knee tenderness on physical examination. Variables used for comparison across classes included pain severity, WOMAC disability score, sex and age. Latent Class Analysis was performed. Model solutions were evaluated using the Bayesian Information Criterion. One-way ANOVAs and post hoc least significance difference tests were used for comparison of classes. Results. A four-class model was identified. Class 1 (57% of study population) had lesser radiographic OA, little psychological involvement, greater strength, and less pain sensitivity. Class 2 (28%) had higher rates of knee joint tenderness. Class 3 (10%) had greater psychological distress and more bodily pain sites. Class 4 (4%) had more comorbidities. Additionally, Class 1 was the youngest, had the lowest disability, and least pain. Class 4 was the oldest. Class 2 had a higher proportion of females. Class 3 had the worst disability and most pain. Conclusions. Four distinct pain phenotypes for knee OA were identified. Psychological factors, knee tenderness, and comorbidities appear to be important in defining phenotypes of OA-related pain. Therapies in knee OA should take a multicomponent approach, recognizing the factors most relevant to an individual's experience of pain

Osteoarthritis (OA) is the most common form of arthritis worldwide. It is a major cause of disability in the adult population with its prevalence expected to increase dramatically over the next 20 years. Although current therapies can alleviate symptoms and improve function in early course of the disease, OA inevitably progresses to end-stage disease requiring total joint arthroplasty. Mesenchymal stromal cells (MSCs) have emerged as a candidate cell type with great potential for intra-articular (IA) repair therapy. However, there is still a considerable lack of knowledge concerning their behaviour, biology and therapeutic effects. To start addressing this, we explored the secretory profile of bone marrow derived MSCs in early and end-stage knee OA synovial fluid (SF). Subjects were recruited and categorised into early [Kellgren-Lawrence (KL) grade I and II, n=12] and end-stage (KL grade III and IV, n=11) knee OA groups. The SF proteome of early and end-stage OA was tested before and three days after the addition of bone marrow MSCs (16.5×10^3, single donor) using multiplex ELISA (64 cytokines) and mass spectrometry (302 proteins detected). Non parametric Wilcoxon-signed rank test for paired samples was used to compare the levels of proteins before and after addition of MSCs in early and end-stage knee OA SF. Significant differences were determined after multiple comparisons correction (FDR) with a p<0.05. Gender distribution and BMI were not statistically different between the two cohorts (p>0.05). However, patients in early knee OA cohort were significantly younger (44.7 years, SD=7.1) than patients in the end-stage cohort (58.6 years, SD=4.4; p<0.05). In both early and end-stage knee OA, MSCs increased the levels of VEGF-A (by 320.24 pg/mL), IL-6 (by 826.78 pg/mL) and IL-8 (by 128.85 pg/mL), factors involved in angiogenesis; CXCL1/2/3 (by 103.35 pg/mL), CCL2 (by 1187.27 pg/mL), CCL3 (by 15.82 pg/mL) and CCL7 (by 10.43 pg/mL), growth factors and chemokines. However, CXCL5 (by 48.61 pg/mL) levels increased only in early knee OA, whereas PDGF-AA (by 15.36 pg/mL) and CXCL12 (by 497.19 pg/mL) levels increased only in end-stage knee OA. This study demonstrates that bone marrow derived MSCs secrete angiogenic and chemotactic factors both in early and end-stage knee OA. More importantly, MSCs show a differential reaction between early and end-stage OA. Functional assays are required to further understand on how the therapeutic effect of MSCs is modulated when exposed to OA SF