Gait Biomechanics and Patient-Reported Function as Predictors of Response to a Hip Strengthening Exercise Intervention in Patients with Knee Osteoarthritis

Abstract

ObjectiveMuscle strengthening exercises have been shown to improve pain and function in adults with mild-to-moderate knee osteoarthritis, but individual response rates can vary greatly. Predicting individuals who respond and those who do not is important in developing a more efficient and effective model of care for knee osteoarthritis (OA). Therefore, the purpose of this study was to use pre-intervention gait kinematics and patient-reported outcome measures to predict post-intervention response to a 6-week hip strengthening exercise intervention in patients with mild-to-moderate knee OA.MethodsThirty-nine patients with mild-to-moderate knee osteoarthritis completed a 6-week hip-strengthening program and were subgrouped as Non-Responders, Low-Responders, or High-Responders following the intervention based on their change in Knee injury Osteoarthritis Outcome Score (KOOS). Predictors of responder subgroups were retrospectively determined from baseline patient-reported outcome measures and kinematic gait parameters in a discriminant analysis of principal components. A 3–4 year follow-up on 16 of the patients with knee OA was also done to examine long-term changes in these parameters.ResultsA unique combination of patient-reported outcome measures and kinematic factors was able to successfully subgroup patients with knee osteoarthritis with a cross-validated classification accuracy of 85.4%. Lower patient-reported function in daily living (ADL) scores and hip frontal plane kinematics during the loading response were most important in classifying High-Responders from other sub-groups, while a combination of hip, knee, ankle kinematics were used to classify Non-Responders from Low-Responders.ConclusionPatient-reported outcome measures and objective biomechanical gait data can be an effective method of predicting individual treatment success to an exercise intervention. Measuring gait kinematics, along with patient-reported outcome measures in a clinical setting can be useful in helping make evidence-based decisions regarding optimal treatment for patients with knee OA.

New Considerations for Collecting Biomechanical Data Using Wearable Sensors: The Effect of Different Running Environments

“…Despite the use of 10fold cross-validation of the training dataset to attempt to improve generalizability of classification, the model slightly overfit to the training dataset as there was lower classification accuracy for the independent testing dataset compared to the 10-fold crossvalidation of the training dataset. Regarding real-world usability, previous studies that have classified IMU-generated running and walking patterns have consistently reported classification accuracy greater than 80% (Kobsar et al, 2014(Kobsar et al, , 2015Phinyomark et al, 2014;Ahamed et al, 2018Ahamed et al, , 2019Benson et al, 2018b;Clermont et al, 2018). Thus, the reported 93.17% accuracy for the training dataset and 83.81% accuracy for the independent testing dataset in the current study suggests that this classification mechanism has practical use.…”

The use of real-time feedback to improve kinematic marker placement consistency among novice examiners

“…Frontal plane kinematics of the knee and hip have been identified in research surrounding the aetiology of knee osteoarthritis (OA) and the difference in prevalence between males and females (Phinyomark, Osis, Hettinga, Kobsar, & Ferber, 2016). Again working with a sample of individuals with knee OA, research has shown difference in hip frontal plane kinematics between those that were classified as high-responders to treatment as compared to those that were grouped into the low-or non-responder category (Kobsar, Osis, Hettinga, & Ferber, 2015). The potential to predict with high accuracy whether a patient will respond well to a specific treatment has meaningful implications for clinical practice by saving time and resources.…”

Association between Pre‐intervention Physical Activity Level and Treatment Response to Exercise Therapy in Persons with Knee Osteoarthritis—An Exploratory Study

“…There is no cure for OA; current nonsurgical management guidelines recommend exercise, weight management, and biomechanical interventions to reduce symptoms and preserve function . Although it is well accepted that exercise therapy leads to improvements in pain, physical function, and quality of life, the reported treatment success varies, possibly because of variances in therapy intensity or dosage and substantial heterogeneity in disease severity, age, body mass index (BMI), and pre‐intervention movement mechanics and activity levels . Identifying characteristics that enhance or diminish treatment response would facilitate a more tailored approach to exercise intervention and optimize efficacy and minimize adverse events.…”