Gait risk factors for disease progression differ between non-traumatic and post-traumatic knee osteoarthritis

Mechanical loading and orthobiologic therapies in the treatment of post-traumatic osteoarthritis (PTOA): a comprehensive review

The importance of mechanical loading and its relationship to orthobiologic therapies in the treatment of post-traumatic osteoarthritis (PTOA) is beginning to receive attention. This review explores the current efficacy of orthobiologic interventions, notably platelet-rich plasma (PRP), bone marrow aspirate (BMA), and mesenchymal stem/stromal cells (MSCs), in combating PTOA drawing from a comprehensive review of both preclinical animal models and human clinical studies. This review suggests why mechanical joint loading, such as running, might improve outcomes in PTOA management in conjunction with orthiobiologic administration. Accumulating evidence underscores the influence of mechanical loading on chondrocyte behavior and its pivotal role in PTOA pathogenesis. Dynamic loading has been identified as a key factor for optimal articular cartilage (AC) health and function, offering the potential to slow down or even reverse PTOA progression. We hypothesize that integrating the activation of mechanotransduction pathways with orthobiologic treatment strategies may hold a key to mitigating or even preventing PTOA development. Specific loading patterns incorporating exercise and physical activity for optimal joint health remain to be defined, particularly in the clinical setting following joint trauma.

A marker-less human motion analysis system for motion-based biomarker identification and quantification in knee disorders

In recent years the healthcare industry has had increased difficulty seeing all low-risk patients, including but not limited to suspected osteoarthritis (OA) patients. To help address the increased waiting lists and shortages of staff, we propose a novel method of automated biomarker identification and quantification for the monitoring of treatment or disease progression through the analysis of clinical motion data captured from a standard RGB video camera. The proposed method allows for the measurement of biomechanics information and analysis of their clinical significance, in both a cheap and sensitive alternative to the traditional motion capture techniques. These methods and results validate the capabilities of standard RGB cameras in clinical environments to capture clinically relevant motion data. Our method focuses on generating 3D human shape and pose from 2D video data via adversarial training in a deep neural network with a self-attention mechanism to encode both spatial and temporal information. Biomarker identification using Principal Component Analysis (PCA) allows the production of representative features from motion data and uses these to generate a clinical report automatically. These new biomarkers can then be used to assess the success of treatment and track the progress of rehabilitation or to monitor the progression of the disease. These methods have been validated with a small clinical study, by administering a local anaesthetic to a small population with knee pain, this allows these new representative biomarkers to be validated as statistically significant (p -value < 0.05 ). These significant biomarkers include the cumulative acceleration of elbow flexion/extension in a sit-to-stand, as well as the smoothness of the knee and elbow flexion/extension in both a squat and sit-to-stand.

Gait, physical activity and tibiofemoral cartilage damage: a longitudinal machine learning analysis in the Multicenter Osteoarthritis Study

OBJECTIVE

To (1) develop and evaluate a machine learning model incorporating gait and physical activity to predict medial tibiofemoral cartilage worsening over 2 years in individuals without advanced knee osteoarthritis and (2) identify influential predictors in the model and quantify their effect on cartilage worsening.

DESIGN

An ensemble machine learning model was developed to predict worsened cartilage MRI Osteoarthritis Knee Score at follow-up from gait, physical activity, clinical and demographic data from the Multicenter Osteoarthritis Study. Model performance was evaluated in repeated cross-validations. The top 10 predictors of the outcome across 100 held-out test sets were identified by a variable importance measure. Their effect on the outcome was quantified by g-computation.

RESULTS

Of 947 legs in the analysis, 14% experienced medial cartilage worsening at follow-up. The median (2.5-97.5th percentile) area under the receiver operating characteristic curve across the 100 held-out test sets was 0.73 (0.65-0.79). Baseline cartilage damage, higher Kellgren-Lawrence grade, greater pain during walking, higher lateral ground reaction force impulse, greater time spent lying and lower vertical ground reaction force unloading rate were associated with greater risk of cartilage worsening. Similar results were found for the subset of knees with baseline cartilage damage.

CONCLUSIONS

A machine learning approach incorporating gait, physical activity and clinical/demographic features showed good performance for predicting cartilage worsening over 2 years. While identifying potential intervention targets from the model is challenging, lateral ground reaction force impulse, time spent lying and vertical ground reaction force unloading rate should be investigated further as potential early intervention targets to reduce medial tibiofemoral cartilage worsening.

Patellofemoral joint loading and early osteoarthritis after ACL reconstruction

Patellofemoral joint (PFJ) osteoarthritis is common following anterior cruciate ligament reconstruction (ACLR) and may be linked with altered joint loading. However, little is known about the cross-sectional and longitudinal relationship between PFJ loading and osteoarthritis post-ACLR. This study tested if altered PFJ loading is associated with prevalent and worsening early PFJ osteoarthritis post-ACLR. Forty-six participants (mean ± 1 SD age 26 ± 5 years) approximately 1-year post-ACLR underwent magnetic resonance imaging (MRI) and biomechanical assessment of their reconstructed knee. Trunk and lower-limb kinematics plus ground reaction forces were recorded during the landing phase of a standardized forward hop. These data were input into a musculoskeletal model to calculate the PFJ contact force. Follow-up MRI was completed on 32 participants at 5-years post-ACLR. Generalized linear models (Poisson regression) assessed the relationship between PFJ loading and prevalent early PFJ osteoarthritis (i.e., presence of a PFJ cartilage lesion at 1-year post-ACLR) and worsening PFJ osteoarthritis (i.e., incident/progressive PFJ cartilage lesion between 1- and 5-years post-ACLR). A lower peak PFJ contact force was associated with prevalent early PFJ osteoarthritis at 1-year post-ACLR (n = 14 [30.4%]; prevalence ratio: 1.37; 95% confidence interval [CI]: 1.02-1.85) and a higher risk of worsening PFJ osteoarthritis between 1- and 5-years post-ACLR (n = 9 [28.1%]; risk ratio: 1.55, 95% CI: 1.13-2.11). Young adults post-ACLR who exhibited lower PFJ loading during hopping were more likely to have early PFJ osteoarthritis at 1-year and worsening PFJ osteoarthritis between 1- and 5-years. Clinical interventions aimed at mitigating osteoarthritis progression may be beneficial for those with signs of lower PFJ loading post-ACLR.

Osteoarthritis as an Umbrella Term for Different Subsets of Humans Undergoing Joint Degeneration: The Need to Address the Differences to Develop Effective Conservative Treatments and Prevention Strategies

Osteoarthritis (OA) of joints such as the knee and hip are very prevalent, and the number of individuals affected is expected to continue to rise. Currently, conservative treatments after OA diagnosis consist of a series of increasingly invasive interventions as the degeneration and pain increase, leading very often to joint replacement surgery. Most interventions are focused on alleviating pain, and there are no interventions currently available that stop and reverse OA-associated joint damage. For many decades OA was considered a disease of cartilage, but it is now considered a disease of the whole multi-tissue joint. As pain is the usual presenting symptom, for most patients, it is not known when the disease process was initiated and what the basis was for the initiation. The exception is post-traumatic OA which results from an overt injury to the joint that elevates the risk for OA development. This scenario leads to very long wait lists for joint replacement surgery in many jurisdictions. One aspect of why progress has been so slow in addressing the needs of patients is that OA has been used as an umbrella term that does not recognize that joint degeneration may arise from a variety of mechanistic causes that likely need separate analysis to identify interventions unique to each subtype (post-traumatic, metabolic, post-menopausal, growth and maturation associated). A second aspect of the slow pace of progress is that the bulk of research in the area is focused on post-traumatic OA (PTOA) in preclinical models that likely are not clearly relevant to human OA. That is, only ~12% of human OA is due to PTOA, but the bulk of studies investigate PTOA in rodents. Thus, much of the research community is failing the patient population affected by OA. A third aspect is that conservative treatment platforms are not specific to each OA subset, nor are they integrated into a coherent fashion for most patients. This review will discuss the literature relevant to the issues mentioned above and propose some of the directions that will be required going forward to enhance the impact of the research enterprise to affect patient outcomes.

Environmental Risk Factors for Osteoarthritis: The Impact on Individuals with Knee Joint Injury

Osteoarthritis is a debilitating chronic condition involving joint degeneration, impacting over 300 million people worldwide. This places a high social and economic burden on society. The knee is the most common joint impacted by osteoarthritis. A common cause of osteoarthritis is traumatic joint injury, specifically injury to the anterior cruciate ligament. The purpose of this review is to detail the non-modifiable and modifiable risk factors for osteoarthritis with particular focus on individuals after anterior cruciate ligament injury. After reading this, health care providers will better comprehend the wide variety of factors linked to osteoarthritis.

HURWA robotic-assisted total knee arthroplasty improves component positioning and alignment – A prospective randomized and multicenter study

Background

The objective of this study was to compare the radiologic and clinical outcomes of HURWA robotic-assisted total knee arthroplasty (TKA) to those of conventional TKA.

Methods

A total of 150 patients were randomized into two groups – 73 and 77 patients underwent robotic-assisted TKA and conventional TKA, respectively. Preoperative and postoperative Western Ontario McMaster University Osteoarthritis Index (WOMAC) score, Hospital for Special Surgery (HSS) score, 36-item Short Form Health Survey (SF-36) score, Knee Society Score (KSS) and range of motion (ROM) were obtained and compared between these two groups. The preoperative and postoperative hip-knee-ankle (HKA) angle and the rate of HKA≤3° in the two groups were also compared.

Results

The postoperative mean HKA angle was 1.801° ​± ​1.608° of varus for the robotic-assisted TKA group and 3.017° ​± ​2.735° of varus for the conventional TKA group; these values were significantly different. The alignment rate for mechanical axis lower than 3° in the robotic-assisted TKA group and the conventional TKA group were 81.2% and 63.5%, respectively. Patients undergone robotic-assisted TKA or conventional TKA had similarly improved knee flexion and functional recovery reflected by WOMAC score, HSS score, SF-36 score and KSS.

Conclusion

HURWA robotic-assisted TKA is a safe and effective, resulting in better alignment for mechanical axis than conventional TKA. The improvement in knee flexion and functional recovery after HURWA robotic-assisted TKA were similar to those after conventional TKA. However, longer follow-up is needed to determine whether the improved alignment of mechanical axis will produce better long-term clinical outcomes.

The translational potential of this article

Recently, the robotic-assisted TKA system has been introduced to clinical practice for TKA. Several robotic-assisted TKA systems, including CASPAR, Tsolution, ROSA, ROBODOC and Mako, have been implemented into clinical application.However, the clinical application of these robotic systems was limited due to their technical complexity, insufficient versatility and increased operative time. Until now, there are still no robotic-assisted TKA systems approved by the National Medical Products Administration of China. Therefore, more robotic-assisted TKA systems need to be designed and improved, particularly in China. Through our randomized, multicenter, single blind and parallel controlled trial, we showed that HURWA robot-assisted TKA system is a safe and effective system for TKA, which had improved knee flexion.