Association of Low Physical Activity Levels With Gait Patterns Considered at Risk for Clinical Knee Osteoarthritis Progression

Lower extremity muscle patterns and frontal plane biomechanics are altered in the contralateral knee of adults with osteoarthritis compared to asymptomatic adults

PURPOSE

To compare knee joint muscle activity during gait between the contralateral limb of individuals with knee osteoarthritis (OA) and an asymptomatic older adult group. A secondary objective was to compare frontal and sagittal plane moment and sagittal plane motion features between groups.

SCOPE

84 individuals with moderate knee OA (61 ± 6 years, 43 % female, BMI 29.2 ± 5.7 kg/m2), and 45 asymptomatic older adults (61 ± 7 years, 49 % female, BMI 25.0 ± 3.4 kg/m2) participated. Participants walked at a self-selected pace on a dual belt treadmill. Surface electromyograms of the quadriceps, hamstrings, and gastrocnemius, segment motions and ground reaction forces were recorded. Principal component analyses identified amplitude and temporal electromyogram features. Sagittal plane motion and net external sagittal and frontal plane moments were calculated. Analysis of Variance models using Bonferroni corrections determined between and within group differences in these gait features.

CONCLUSIONS

The contralateral knee showed prolonged lateral hamstring activation and altered temporal features of the gastrocnemius and greater knee adduction moments compared to asymptomatic adults. Group, muscle, or interaction effects were not found for the quadriceps. These findings highlight the importance of exploring the implications of contralateral knee function of individuals with moderate knee OA, particularly considering the altered antagonist muscle activations, and heightened frontal plane moments.

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.

Influence of body mass index and anterior cruciate ligament reconstruction on gait biomechanics

Body mass index (BMI) and history of anterior cruciate ligament reconstruction (ACLR) independently influence gait biomechanics and knee osteoarthritis risk, but the interaction between these factors is unclear. The purpose of this study was to compare gait biomechanics between individuals with and without ACLR, and with and without overweight/obesity. We examined 104 individuals divided into four groups: with and without ACLR, and with low or high BMI (n = 26 per group). Three-dimensional gait biomechanics were evaluated at preferred speed. The peak vertical ground reaction force, knee flexion angle and excursion, external knee flexion moment, and external knee adduction moment were extracted for analysis. Gait features were compared between groups using 2 (with and without overweight/obesity) × 2 (with and without ACLR) analysis of variance. Primary findings indicated that those with ACLR and high BMI had a larger external knee adduction moment compared with those with low BMI and with (p = 0.004) and without ACLR (p = 0.005), and compared with those without ACLR and high BMI (p = 0.001). The main effects of ACLR and BMI group were found for the knee flexion moment, and those with ACLR and with high BMI had lower knee flexion moments compared with those without ACLR (p = 0.031) and with low BMI (p = 0.021), respectively. Data suggest that individuals with ACLR and high BMI may benefit from additional intervention targeting the knee adduction moment. Moreover, lower external knee flexion moments in those with high BMI and ACLR were consistent, but high BMI did not exacerbate deficits in the knee flexion moment in those with ACLR. [Correction added on 9 November 2022, after first online publication: In the preceding sentence, for clarity, the words "reductions in the lower" was removed from the initial sentence to read "Moreover, lower external knee flexion moments".].