Wearable inertial sensors can detect abnormal gait associated with knee or hip osteoarthritis (OA). However, few studies have compared sensor-derived gait parameters between patients with hip and knee OA or evaluated the efficacy of sensors suitable for remote monitoring in distinguishing between the two. Hence, our study seeks to examine the differences in accelerations captured by low-frequency wearable sensors in patients with knee and hip OA and classify their gait patterns. We included patients with unilateral hip and knee OA. Gait analysis was conducted using an accelerometer ipsilateral with the affected joint on the lateral distal thighs. Statistical parametric mapping (SPM) was used to compare acceleration signals. The k-Nearest Neighbor (k-NN) algorithm was trained on 80% of the signals' Fourier coefficients and validated on the remaining 20% using 10-fold cross-validation to classify the gait patterns into hip and knee OA. We included 42 hip OA patients (19 females, age 70 [63–78], BMI of 28.3 [24.8–30.9]) and 59 knee OA patients (31 females, age 68 [62–74], BMI of 29.7 [26.3–32.6]). The SPM results indicated that one cluster (12–20%) along the vertical axis had accelerations exceeding the critical threshold of 2.956 (p=0.024). For the anteroposterior axis, three clusters were observed exceeding the threshold of 3.031 at 5–19% (p = 0.0001), 39–54% (p=0.00005), and 88–96% (p = 0.01). Regarding the mediolateral axis, four clusters were identified exceeding the threshold of 2.875 at 0–9% (p = 0.02), 14–20% (p=0.04), 28–68% (p < 0.00001), and 84–100% (p = 0.004). The k-NN model achieved an AUC of 0.79, an accuracy of 80%, and a precision of 85%. In conclusion, the Fourier coefficients of the signals recorded by wearable sensors can effectively discriminate the gait patterns of knee and hip OA. In addition, the most remarkable differences in the time domain were observed along the mediolateral axis

Introduction and Objective. An important subset of patients is dissatisfied after total joint arthroplasty (TJA) due to residual functional impairment. This study investigated the assessment of objectively measured step-up performance following TJA, to identify patients with poor functional improvement after surgery, and to predict residual functional impairment during early postoperative rehabilitation. Secondary, longitudinal changes of block step-up (BS) transfers were compared with functional changes of subjective patient reported outcome measures (PROMs) following TJA. Materials and Methods. Patients with end stage hip or knee osteoarthritis (n = 76, m/f = 44/32; mean age = 64.4 standard deviation 9.4 years) were measured preoperatively and 3 and 12 months postoperatively. PROMs were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function subscore. BS transfers were assessed by wearable-derived measures of time. In our cohort, subgroups were formed based on either 1) WOMAC function score or 2) BS performance, isolating the worst performing quartile (impaired) of each measure from the better performing others (non-impaired). Subgroup comparisons were performed with the Man-Whitney-U test and Wilcoxon Signed rank test resp. Responsiveness was calculated by the effect size, correlations with Pearson's correlation coefficient. A regression analysis was conducted to investigate predictors of poor functional outcome. Results. WOMAC function scores were strongly correlated to WOMAC pain scores (Pearson's r=0.67–0.84) and moderately correlated to BS performance (Pearson's r = 0.31–0.54). Prior to surgery, no significant differences for WOMAC function scores and BS performance were found between the impaired and non-impaired subgroups. One year after TJA, our cohort performed significantly better at WOMAC and BS with largest effect size for the non-impaired subgroups (0.62 and 0.43 resp.) At 12 months postop, 56% of patients allocated to the impaired subgroup defined by WOMAC, represented the impaired subgroup defined by BS. Allocation to the impaired subgroup at 3 months postop, raised the odds for belonging to the impaired subgroup at 12 months for WOMAC with an odds ratio=19.14 (67%) and for BS with an odds ratio=4.41 (42%). Conclusions. Assessment of BS performance following TJA reveals residual functional impairment that is not captured by pain-dominated PROMs. Its additional use may help to early identify those patients at risk for a poor outcome

There is an evolving body of evidence that demonstrates the role of epigenetic mechanisms, such as DNA-methylation in the pathogenesis of OA. This systematic review aims to summarize the current evidence of DNA methylation and its influence on the pathogenesis of OA. A pre-defined protocol in alignment with the PRISMA guidelines was employed to systematically review eight bibliographic databases, to identify associations between DNA-methylation of articular chondrocytes and osteoarthritis. A search of Medline (Ovid), Embase, Web-of-Science, Scopus, PubMed, Cinahl (EBSCOhost), Cochrane Central and Google Scholar was performed between 1st January 2015 to 31st January 2021. Data extraction was performed by two independent reviewers. During the observation period, we identified 15 gene specific studies and 24 genome wide methylation analyses. The gene specific studies mostly focused on the expression of pro-inflammatory markers, such as IL8 and MMP13 which are overexpressed in OA chondrocytes. DNA hypomethylation in the promoter region resulted in overexpression, whereas hypermethylation was seen in non-OA chondrocytes. Others reported on the association between OA risk genes and the DNA methylation pattern close to RUNX2, which is an important OA signal. The genome wide methylation studies reported mostly on differentially methylated regions comparing OA chondrocytes and non-OA chondrocytes. Clustering of the regions identified genes that are involved in skeletal morphogenesis and development. Differentially methylated regions were seen in hip OA and knee OA chondrocytes, and even within different regions of an OA affected knee joint, differentially methylated regions were identified depending on the disease stage. This systematic review demonstrates the growing evidence of epigenetic mechanisms, such as DNA methylation, in the pathogenesis of OA. In recent years, there has been a focus on the interplay between OA risk genes and DNA methylation changes which revealed a reactivation of genes responsible for endochondral ossification during development. These are important findings and may help to identify eventual future therapeutic targets. However, the current body of literature is mostly showing the differences in DNA methylation of OA chondrocytes and non-OA chondrocytes, but a true longitudinal analysis demonstrating the DNA methylation changes actually happening is still not available

Introduction. Limited physical activity (PA) is one indication for orthopaedic intervention and restoration of PA a treatment goal. However, the objective assessment of PA is not routinely performed and in particular the effect of spinal pathology on PA is hardly known. It is the purpose of this study using wearable accelerometers to measure if, by how much and in what manner spinal stenosis affects PA compared to age-matched healthy controls. Patients & Methods. Nine patients (m/f= 5/4, avg. age: 67.4 ±7.7 years, avg. BMI: 29.2 ±3.5) diagnosed with spinal stenosis but without decompressive surgery or other musculoskeletal complaints were measured. These patients were compared to 28 age-matched healthy controls (m/f= 17/11, avg. age: 67.4 ±7.6 years, avg. BMI: 25.3±2.9). PA was measured using a wearable accelerometer (GCDC X8M-3) worn during waking hours on the lateral side of the right leg for 4 consecutive days. Data was analyzed using previously validated activity classification algorithms in MATLAB to identify the type, duration and event counts of postures or PA like standing, sitting, walking or cycling. In addition, VAS pain and OSWESTRY scores were taken. Groups were compared using the t-test or Mann-Whitney U-test where applicable. Correlations between PA and clinical scores were tested using Pearson”s r. Results. Spinal stenosis patients showed much lower PA than healthy controls regarding all parameters like e.g. daily step count (2946 vs 8039, −63%, p<0.01) or the relative daily time-on-feet (%) (8.6% vs 28.3%, −70%, p<0.01) which is matched with increased sitting durations (80.3% vs 58.8%, p<0.01). Also qualitative parameters such as walking cadence was reduced in stenosis patients (83.7 vs 97.8 steps/min). With stenosis no patient ever walked >1000 steps without interruption. Also the number of walking bouts between 250–1000 steps was 4.5 times lower than in healthy controls (p<0.01). When the relative distribution of walking bout length was calculated, it became visible that stenosis patients showed more short walking bouts of 10–50 steps (p<0.05). There were no strong and significant correlations between the clinical scores and PA parameters. Discussion & Conclusions. Spinal stenosis greatly reduced physical activity to levels below WHO guidelines (e.g. <5000 steps= sedentary lifestyle) where the risk for general health (overall mortality), cardiovascular or endocrinological health is significantly increased. Activity levels are lower than reported for end-stage hip or knee osteoarthritis. Therefore, spinal stenosis patients should not only receive pain medication, but be made aware of their limited PA and its detrimental health effects, participate in activation programs, or be considered for surgical intervention. The absence of long walking bouts and the relatively more frequent short walking bouts seem indicative of intermittent claudication as typical in spinal stenosis

Osteoarthritis (OA) is an important cause of pain, disability and economic loss in humans, and is similarly important in the horse. Recent knowledge on post-traumatic OA has suggested opportunities for early intervention, but it is difficult to identify the appropriate time of these interventions. The horse provides two useful mechanisms to answer these questions: 1) extensive experience with clinical OA in horses; and 2) use of a consistently predictable model of OA that can help study early pathobiological events, define targets for therapeutic intervention and then test these putative therapies. This paper summarises the syndromes of clinical OA in horses including pathogenesis, diagnosis and treatment, and details controlled studies of various treatment options using an equine model of clinical OA.