Fundamentals of osteoarthritis. Rehabilitation: Exercise, diet, biomechanics, and physical therapist-delivered interventions

Evaluation of EMG-Assisted and EMG-Driven control modes in patients with medial compartment knee osteoarthritis

Knee osteoarthritis (OA) is associated with higher-than-normal knee joint contact forces (KJCFs) during walking which cannot be easily measured. KJCFs can be estimated using neuromusculoskeletal (NMSK) modelling in electromyogram (EMG)-driven and -assisted control modes. Previous research has not examined which control mode is most appropriate for estimating KJCFs in patients with knee OA. This study aimed to evaluate a NMSK modelling framework using both control modes in patients with medial-dominant knee OA. First, EMG-assisted mode was hypothesized to better track ID-computed joint moments. Second, KJCFs estimated using the two control modes were hypothesized to differ. Gait data were measured from 27 patients with medial-dominant tibiofemoral knee OA. An OpenSim model was scaled to patient-specific anthropometrics. Inverse kinematics, inverse dynamics, and muscle analysis were performed. Resulting joint angles, moments, musculotendon kinematics, and muscle activations were input into the Calibrated Electromyography Informed Neuromusculoskeletal Modelling Toolbox. Muscle forces and KJCFs were estimated using EMG-driven and -assisted control modes. EMG-assisted mode better tracked knee flexion moments (RMSE = 2.7 ± 2.1Nm, R2 = 0.9 ± 0.1) and estimated a higher, albeit non-significant, second peak medial compartment KJCF (2.3 ± 1.1BW) compared to EMG-driven mode (RMSE = 12.6 ± 3.9Nm, R2 = 0.6 ± 0.2, KJCF = 2.1 ± 0.9BW). EMG-assisted control mode may therefore be more appropriate for evaluating KJCFs in patients with knee OA.

Effect of gait retraining strategies on clinical and biomechanical outcomes in subjects with knee osteoarthritis: a systematic review with meta-analysis and GRADE recommendations

PURPOSE

To assess the effects of gait retraining strategies on clinical and/or biomechanical variables in knee osteoarthritis.

METHODS

This study was registered in PROSPERO-CRD42023402778. Studies were searched up to June/2024. PEDro scale and GRADE approach were used to assess methodological quality and certainty of evidence. A meta-analysis was conducted using R-software.

RESULTS

The included studies employed backward walking (5), toe-out (1), and freely strategies (2). The meta-analysis revealed a significant difference with low quality of evidence favoring gait retraining for pain (MD = -1.12; 95% CI: [-1.61; -0.62]; I2 = 78%; p < 0.01) and with high quality for function (SMD = -0.80; 95% CI: [-1.12; -0.48]; I2 = 0%; p = 0.42). A significant difference also favoring gait retraining was observed for first knee adduction moment (KAM) (MD = -0.20; 95% CI: [-0.38; -0.02]; I2 = 84%; p < 0.01). The comparisons indicated similarity between groups for second KAM (MD = -0.16; 95% CI: [-0.47; 0.16]; I2 = 79%; p = 0.03) and for knee flexion moment (MD = 0.07; 95% CI: [-0.07; 0.20]; I2 = 76%; p = 0.02).

CONCLUSION

Gait retraining improved pain, function and first KAM. Second KAM and knee flexion moment did not modify.

Ketogenic diet improves disease activity and cardiovascular risk in psoriatic arthritis: A proof of concept study

OBJECTIVES

Very low-calorie ketogenic diet (VLCKD) is a low-carbohydrate, low-calorie regimen that leads to rapid weight loss and may reduce inflammation. This study assessed the impact of VLCKD on anthropometric measurements, inflammatory biomarkers, metabolic health, and cardiovascular risk in psoriatic arthritis (PsA) patients moderately overweight or in class I obesity.

METHODS

A proof-of-concept single-arm monocentric study involved PsA patients undergoing a 9-week VLCKD treatment. Patients with Body Mass Index (BMI) ≥27 and <35, in stable (≥6 months) remission or low disease activity, as defined by Disease Activity in PSoriatic Arthritis (DAPSA) score, were included and underwent nutritional evaluations every 3 weeks. The study analyzed changes after the VLCKD intervention and the association between changes of anthropometric parameters and clinical and laboratory variables.

RESULTS

Twenty patients were enrolled since April 2022 and completed the study in May 2023. Median baseline BMI was 30.9 (interquartile range 29.1-33) kg/m². All participants exhibited low baseline disease activity, which correlated with BMI (Spearman's correlation coefficient (rs)=0.59,p=0.007). Following VLCKD, significant improvements were observed in all anthropometric measures (BMI -3.5[-4;-2.6]), PsA activity (DAPSA -6.1[-16.8;3.7]), cardiovascular parameters (SCORE2 index -0.2[-0.7;0.1]), insulin resistance (Homeostatic Model Assessment-Insuline Resistance -2.1[-1.1;-3.0]), and lipid profile. Most inflammatory biomarkers remained within normal limits. BMI reduction correlated with changes in DAPSA scores (rs=0.52,p=0.020). Patients with higher baseline weight or clinical activity experienced more pronounced improvements.

CONCLUSIONS

VLCKD significantly improved PsA activity and metabolic health. Patients with a higher BMI and less controlled disease are particularly motivated and could benefit more from VLCKD compared to those with lower BMI or better disease control.

Pyroptosis for osteoarthritis treatment: insights into cellular and molecular interactions inflammatory

Osteoarthritis (OA) is a widely prevalent chronic degenerative disease often associated with significant pain and disability. It is characterized by the deterioration of cartilage and the extracellular matrix (ECM), synovial inflammation, and subchondral bone remodeling. Recent studies have highlighted pyroptosis-a form of programmed cell death triggered by the inflammasome-as a key factor in sustaining chronic inflammation. Central to this process are the inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18), which play crucial roles mediating intra-articular pyroptosis through the NOD-like receptor protein 3 (NLRP3) inflammasome. This paper investigates the role of the pyroptosis pathway in perpetuating chronic inflammatory diseases and its linkage with OA. Furthermore, it explores the mechanisms of pyroptosis, mediated by nuclear factor κB (NF-κB), the purinergic receptor P2X ligand-gated ion channel 7 (P2X7R), adenosine monophosphate (AMP)-activated protein kinase (AMPK), and hypoxia-inducible factor-1α (HIF-1α). Additionally, it examines the interactions among various cellular components in the context of OA. These insights indicate that targeting the regulation of pyroptosis presents a promising therapeutic approach for the prevention and treatment of OA, offering valuable theoretical perspectives for its effective management.

Efficacy of high intensity laser therapy versus sham laser in symptomatic knee osteoarthritis: a double-blind randomized controlled trial

The purpose of this study is to evaluate the efficacy of six sessions of High-Intensity Laser Therapy (HILT), administered twice a week over three weeks, in reducing pain and improving function in patients with mild to moderate symptomatic osteoarthritis (OA) of the knee. Forty patients were randomly assigned to either the HILT group (n = 20) or a sham control group (n = 20). The HILT group received two initial sessions of analgesic mode HILT with a total energy of 600 J at the medial and lateral joint lines, followed by four sessions of biostimulation mode with 3000 J at the medial joint line. Both groups also participated in a supervised home exercise program. The visual analog scale (VAS) of pain, the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and timed up and go test (TUG) were evaluated before treatment and at 3 and 6 weeks after the initial treatment. The VAS and the WOMAC improved significantly in both groups. However, there were no significant differences in any of the measured outcomes between the two groups. Both groups showed no significant improvement in TUG. In treating mild to moderate OA knee, integrating twice a week, 6 sessions (2 sessions of analgesic and 4 sessions of biostimulation mode) HILT to exercise program is not superior to exercise alone.

Association between sedentary behavior, physical activity, and osteoarthritis: results from NHANES 2007-2020 and Mendelian randomization analysis

Introduction

Osteoarthritis (OA) is a prevalent and debilitating disorder that affects the joints and has a complex array of causes. While sedentary behavior (SB) and physical activity (PA) have been implicated in OA risk, the relationship between these factors and OA development remains unclear. This study investigates the correlation and potential causality between SB, PA, and OA using both cross-sectional and Mendelian randomization (MR) analysis.

Methods

We conducted a two-phase study that included a cross-sectional analysis using data from the National Health and Nutrition Examination Survey (NHANES) and a MR analysis. A weighted analysis was performed on data from the NHANES to explore the relationship between SB, PA, and the risk of OA. Logistic regression was used to assess the association between SB, PA, and OA, adjusting for potential confounders. Non-parametric curve fitting was applied to examine the dose-response relationship between PA levels and OA onset. Additionally, MR was utilized to infer the genetic causality between SB, PA, and OA risk, using genetic instruments as proxies for SB and PA.

Results

The final analysis, which included 24,738 participants, revealed that OA prevalence was 13.47%, with individuals diagnosed with OA exhibiting significantly higher levels of SB and lower levels of PA. A U-shaped relationship was observed between PA and OA risk, with a decrease in OA incidence as PA levels increased, although the protective effect of PA was less pronounced in individuals with severe SB. MR analysis indicated that genetically inferred SB was associated with a higher likelihood of OA (IVW OR 1.20, 95% CI 1.13-1.28), while increased PA was inversely associated with OA risk (IVW OR 0.85, 95% CI 0.73-0.98).

Conclusion

This research emphasizes the significance of SB and PA as modifiable factors influencing the risk of OA. It is recommended that individuals at risk of OA should aim to participate in regular physical activity and minimize sedentary behavior to lower their risk of developing the disease. The MR analysis results support the potential causal impact of SB and PA on OA, providing valuable information for the development of therapeutic and rehabilitative strategies.

XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study

OBJECTIVE

To use routine demographic and clinical data to develop an interpretable individual-level machine learning (ML) model to diagnose knee osteoarthritis (KOA) and to identify highly ranked features.

METHODS

In this retrospective, population-based cohort study, anonymized questionnaire data was retrieved from the Wu Chuan KOA Study, Inner Mongolia, China. After feature selections, participants were divided in a 7:3 ratio into training and test sets. Class balancing was applied to the training set for data augmentation. Four ML classifiers were compared by cross-validation within the training set and their performance was further analyzed with an unseen test set. Classifications were evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the curve(AUC), G-means, and F1 scores. The best model was explained using Shapley values to extract highly ranked features.

RESULTS

A total of 1188 participants were investigated in this study, among whom 26.3% were diagnosed with KOA. Comparatively, XGBoost with Boruta exhibited the highest classification performance among the four models, with an AUC of 0.758, G-means of 0.800, and F1 scores of 0.703. The SHAP method reveals the top 17 features of KOA according to the importance ranking, and the average of the experience of joint pain was recognized as the most important features.

CONCLUSIONS

Our study highlights the usefulness of machine learning in unveiling important factors that influence the diagnosis of KOA to guide new prevention strategies. Further work is needed to validate this approach.

The dynamic and diverse experience of adults with brachial plexus birth injury: a collective case study

PURPOSE

To explore brachial plexus birth injury (BPBI)-affected adults' health-related quality of life (HRQoL) experiences informed by the theoretical framework of the International Classification of Functioning, Disability, and Health.

METHODS

This study applied a qualitative collective case study design. Twelve participants who participated in a prior survey study were recruited using maximum variation sampling. One-on-one semi-structured interviews focused on gaining in-depth understanding of participants' experiences with HRQoL. Interviews were recorded verbatim and thematically analysed.

RESULTS

We identified two themes. First, the theme biopsychosocial dimensions of the experience comprised the ways BPBI affects physical and emotional health and how BPBI is intertwined with affected individuals' identities, activities/participation, and social environments. Second, the theme lifelong and variable experience encompassed how BPBI is a chronic condition that changes over time and varies among affected individuals. The cross-case analysis derived a conceptual model of BPBI HRQoL to describe the BPBI experience through the lifespan. In this model, multiple dimensions of BPBI HRQoL expand through the lifespan while BPBI-specific health resources' availability contract.

CONCLUSIONS

By providing insight into the many ways that BPBI affects and is affected by an individual's functioning and personal, social, and healthcare environmental factors, these findings underscore lifelong individualized care for BPBI-affected persons is needed.

Dropout From Exercise Interventions in Adults With Knee or Hip Osteoarthritis: A Systematic Review and Meta-analysis

OBJECTIVE

To investigate the prevalence and moderators of dropout rates among adults with knee or hip osteoarthritis participating in exercise randomized controlled trials (RCTs).

DATA SOURCES

Two authors searched Embase, CINAHL, PsycARTICLES, and PubMed up to 01/09/2023.

STUDY SELECTION

We included RCTs of exercise interventions in people with knee or hip osteoarthritis that reported dropout rates.

DATA EXTRACTION

Dropout rates from exercise and control conditions and exerciser/participant, provider, and design/implementation related moderators.

DATA SYNTHESIS

In total, 209 RCTs involving 277 exercise arms in 13,102 participants were included (mean age at study level=64 years; median prevalence of men participants=26.8%). The trim-and-fill-adjusted prevalence of dropout across all RCTs was 17.5% (95% CI=16.7%-18.2%), which is comparable with dropout observed in control conditions (trim-and-fill-adjusted odds ratio=0.89; 95% CI=0.71-1.12, P=.37). Higher prevalence of antidepressant use at study-level predicted higher dropout (R2=0.75, P=.002, N RCTs=6, n exercisers=412). Supervision by an exercise professional was associated with lower dropout rates, with a trim-and-fill-adjusted rate of 13.2% (95% CI=11.7%-14.9%) compared with 20.8% without supervision (95% CI=18.3%-23.5%) (P<.001).

CONCLUSIONS

Dropout rates for exercise in RCTs are comparable with control conditions, suggesting that exercise is a generally well-accepted intervention. However, interventions should be supervised by an exercise professional, such as a physiotherapist or exercise physiologist, to further minimize the risk of dropout. Health professionals should consider participants' use of antidepressants as a risk factor for dropout from exercise.

Osteoarthritis year in review 2023: Biomechanics

Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.