Individual Gait Features Are Associated with Clinical Improvement After Total Knee Arthroplasty

Stepping beyond Counts in Recovery of Total Knee Arthroplasty: A Prospective Study on Passively Collected Gait Metrics

Advances in algorithms developed from sensor-based technology data allow for the passive collection of qualitative gait metrics beyond step counts. The purpose of this study was to evaluate pre- and post-operative gait quality data to assess recovery following primary total knee arthroplasty. This was a multicenter, prospective cohort study. From 6 weeks pre-operative through to 24 weeks post-operative, 686 patients used a digital care management application to collect gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-samples t-test. Recovery was operationally defined as when the respective weekly average gait metric was no longer statistically different than pre-operative. Walking speed and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-operative (p < 0.0001). Walking speed recovered at 21 weeks (1.00 m/s, p = 0.063) and double support percentage recovered at week 24 (32%, p = 0.089). Asymmetry percentage was recovered at 13 weeks (14.0%, p = 0.23) and was consistently superior to pre-operative values at week 19 (11.1% vs. 12.5%, p < 0.001). Step length did not recover during the 24-week period (0.60 m vs. 0.59 m, p = 0.004); however, this difference is not likely clinically relevant. The data suggests that gait quality metrics are most negatively affected two weeks post-operatively, recover within the first 24-weeks following TKA, and follow a slower trajectory compared to previously reported step count recoveries. The ability to capture new objective measures of recovery is evident. As more gait quality data is accrued, physicians may be able to use passively collected gait quality data to help direct post-operative recovery using sensor-based care pathways.

Identifying patient subgroups with different trends of patient-reported outcomes (PROMs) after elective knee arthroplasty

BACKGROUND

Patient-reported outcome measures (PROMs) are increasingly being used to assess the effectiveness of elective total knee arthroplasty (TKA). However, little is known about how PROMs scores change over time in these patients. The aim of this study was to identify the trajectories of quality of life and joint functioning, and their associated demographic and clinical features in patients undergoing elective TKA.

METHODS

A prospective, cohort study was conducted, in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, and Knee injury and Osteoarthritis Outcome Score Patient Satisfaction, KOOS-PS) were administered to patients at a single center undergoing elective TKA before surgery, and at 6 and 12 months after surgery. Latent class growth mixture models were used to analyze the patterns of change in PROMs scores over time. Multinomial logistic regression was used to investigate the association between patient characteristics and PROMs trajectories.

RESULTS

A total of 564 patients were included in the study. The analysis highlighted differential patterns of improvement after TKA. Three distinct PROMs trajectories were identified for each PROMs questionnaire, with one trajectory indicating the most favorable outcome. Female gender appears to be associated with a presentation to surgery with worse perceived quality of life and joint function than males, but also more rapid improvement after surgery. Having an ASA score greater than 3 is instead associated with a worse functional recovery after TKA.

CONCLUSION

The results suggest three main PROMs trajectories in patients undergoing elective TKA. Most patients reported improved quality of life and joint functioning at 6 months, which then stabilized. However, other subgroups showed more varied trajectories. Further research is needed to confirm these findings and to explore the potential clinical implications of these results.

Gait biomechanics phenotypes among total knee arthroplasty candidates by machine learning cluster analysis

Knee osteoarthritis patient phenotyping is relevant to developing targeted treatments and assessing the treatment efficacy of total knee arthroplasty (TKA). This study aimed to identify clusters among TKA candidates based on demographic and knee mechanic features during gait, and compare gait changes between clusters postoperatively. TKA patients underwent 3D gait analysis 1-week pre (n = 134) and 1-year post-TKA (n = 105). Principal component analysis was applied to frontal and sagittal knee angle and moment waveforms, extracting major patterns of variability. Age, sex, body mass index, gait speed, and frontal and sagittal pre-TKA angle and moment PC scores previously identified as relevant to TKA outcomes were standardized (mean = 0, SD = 1, [134 × 15]). Multidimensional scaling and machine learning-based hierarchical clustering were applied. Final clusters were validated by examining intercluster differences pre-TKA and gait feature changes (Post_PCscore  - Pre_PCscore ) by k-way Χ² and ANOVA tests. Four TKA candidate phenotypes yielded optimum clustering metrics, interpreted as higher and lower functioning clusters that were predominantly male and female. Higher functioning clusters pre-TKA (clusters 1 and 4) had more dynamic sagittal flexion moment (p < 0.001) and frontal plane adduction moment (p < 0.001) loading/un-loading patterns during stance. Post-TKA, higher functioning clusters demonstrated less knee mechanic improvements during gait (flexion angle p < 0.001; flexion moment p < 0.001). TKA candidates can be characterized by four clusters, predominately separated by sex and knee joint biomechanics. Post-TKA knee kinematics and kinetics improvements were cluster-specific; lower functioning clusters experienced more improvement. Cluster-based patient profiling may aid in triaging and developing OA management and surgical strategies meeting group-level function needs.

Early Identification of Patient Satisfaction Two Years After Total Knee Arthroplasty

BACKGROUND

There are numerous reports of poor satisfaction after total knee arthroplasty (TKA), yet there is little known about when to use evidence-based models of care to improve patient outcomes.

OBJECTIVE

This study aimed to characterize longitudinal changes in patient-reported satisfaction after TKA and to identify factors for early identification of poor satisfaction.

METHODS

For a cohort of primary TKA surgeries (n = 86), patient-reported outcomes were captured one week before TKA and 6 weeks, 12 weeks, 6 months, and 1 and 2 years after TKA. "Satisfied" versus "not fully satisfied" patients were defined using a binary response (≥90 vs <90) from a 100-point scale. Wilcoxon signed-rank tests identified changes in satisfaction between follow-up times, and longitudinal analyses examined demographic and questionnaire factors associated with satisfaction.

RESULTS

Improvements in satisfaction occurred within the first 6 months after TKA (P ≤ 0.01). Preoperative patient-reported outcome measures alone were not predictive of satisfaction. Key factors that improved longitudinal satisfaction included higher Oxford Knee Scores (odds ratio (OR) = 2.1, P < .001), general health (EQ-VAS, OR = 1.3, P = .03), and less visual analog scale pain (VAS; OR = 1.7, P < .001). Differences in these factors between satisfied and not fully satisfied patients were identified as early as 6 weeks after surgery.

CONCLUSION

Visibly different satisfaction profiles were captured among satisfied and not fully satisfied patient responses, with differences in patient-perceived joint function, general health, and pain severity occurring as early as 6 weeks after surgery. This study provides metrics to support early identification of patients at risk of poor TKA satisfaction, enabling clinicians to apply timely targeted treatment and support interventions, with the aim of improving patient outcomes.

Performance-based physical function correlates with walking speed and distance at 3 months post unilateral total knee arthroplasty

BACKGROUND

After total knee arthroplasty (TKA), walking speed and distance are main concerns of patients.

RESEARCH QUESTION

Which physical functions affect walking speed and distance after TKA?

METHODS

Cross-sectional data from 149 patients who underwent unilateral primary TKA and completed performance-based physical function tests. Instrumental gait evaluation for spatiotemporal parameters, isometric knee extensor and flexor strength of both knees, 6-minute walk test (6MWT), timed up-and-go (TUG) test, timed stair climbing test (SCT), and knee flexion and extension range of motion (ROM) of surgical knee were examined. Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) and EuroQol five dimensions (EQ-5D) questionnaires were also performed.

RESULTS

Univariate analyses revealed that post-operative walking speed showed significant positive correlations with cadence, stride length, propulsion index of surgical and non-surgical knee, peak torque (PT) of the extensor of surgical and non-surgical knee and flexor of surgical and non-surgical knee, 6MWT, EQ-5D, and significant negative correlations with gait cycle duration, TUG, SCT-ascent and descent, and WOMAC-pain scores. Post-operative walking distance had significant positive correlations with walking speed, cadence, stride length, swing phase duration, propulsion index of surgical and non-surgical knee, PT of the extensor of surgical and non-surgical knee, EQ-5D, and significant negative correlation with gait cycle duration, double support duration, TUG, SCT-ascent and descent. In the multivariate linear regression analyses, TUG, cadence, stride length and propulsion index of non-surgical knee were factor correlated with post-operative walking speed. The SCT-ascent and descent, TUG and propulsion index of surgical knee were factor correlated with post-operative walking distance.

SIGNIFICANCE

Physical performance factors correlated with walking speed and distance at 3 months after surgery. Based on these observations, rehabilitation of bilateral muscle strength and functional mobility would be important for functional recovery after unilateral TKA.

Osteoarthritis year in review 2020: mechanics

The mechanical environment of the joint during dynamic activity plays a significant role in osteoarthritis processes. Understanding how the magnitude, pattern and duration of joint-specific loading features contribute to osteoarthritis progression and response to treatment is a topic of on-going relevance. This narrative review synthesizes evidence from recent papers that have contributed to knowledge related to three identified emerging subthemes: 1) the role of the joint mechanical environment in osteoarthritis pathogenesis, 2) joint biomechanics as an outcome to arthroplasty treatment of osteoarthritis, and 3) methodological trends for advancing our knowledge of the role of biomechanics in osteoarthritis. Rather than provide an exhaustive review of a broad area of research, we have focused on evidence this year related to these subthemes. New research this year has indicated significant interest in using biomechanics investigations to understand structural vs clinical progression of osteoarthritis, the role and interaction in the three-dimensional loading environment of the joint, and the contribution of muscle activation and forces to osteoarthritis progression. There is ongoing interest in understanding how patient variability with respect to gait biomechanics influences arthroplasty surgery outcomes, and subgroup analyses have provided evidence for the potential utility in tailored treatment approaches. Finally, we are seeing a growing trend in the application of translational biomechanics tools such as wearable inertial measurement units for improved integration of biomechanics into clinical decision-making and outcomes assessment for osteoarthritis.