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Orthopaedic Proceedings
Vol. 101-B, Issue SUPP_11 | Pages 46 - 46
1 Oct 2019
Young-Shand KL Roy PC Dunbar MJ Abidi SSR Astephen-Wilson JL
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Introduction

Identifying knee osteoarthritis patient phenotypes is relevant to assessing treatment efficacy. Biomechanical variability has not been applied to phenotyping, yet features may be related to outcomes of total knee arthroplasty (TKA), an inherently mechanical surgery. This study aimed to i) identify biomechanical phenotypes among TKA candidates based on demographic and gait mechanic similarities, and ii) compare objective gait improvements between phenotypes post-TKA.

Methods

TKA patients underwent 3D gait analysis one-week pre (n=134) and one-year post-TKA (n=105). Principal component analysis was applied to frontal and sagittal knee angle and moment gait waveforms, extracting major patterns of variability. Demographics (age, sex, BMI), gait speed, and frontal and sagittal pre-TKA angle and moment principal component (PC) scores previously found to differentiate sex, osteoarthritis (OA) severity, and symptoms of TKA recipients were standardized (mean=0, SD=1, [134×15]) to perform multidimensional scaling and machine learning based hierarchical clustering. Final clusters were validated by examining inter-cluster differences at baseline and gait changes (PostPCscore–PrePCscore) by k-way Chi-Squared, and ANOVA tests.


Orthopaedic Proceedings
Vol. 92-B, Issue SUPP_I | Pages 13 - 13
1 Mar 2010
Astephen JL Dunbar MJ Wilson D Deluzio KJ
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Purpose: To investigate the association between pre-operative gait patterns and the RSA defined migration migration pattern of cemented and uncemented tibial components post total knee arthroplasty (TKA).

Method: 43 patients with primary osteoarthritis of the knee underwent Optotrack gait analysis in the week before TKA surgery. Three-dimensional net external knee joint moments and angles were calculated with inverse dynamics. The variability in subject gait patterns was captured with a set of discrete scores that represented weightings on objectively-extracted features of the gait waveform data using principal component analysis. The subjects were randomized to receive the uncemented Nexgen Trabecular metal Monoblock tibial component (n=22; mean age=66 years; mean BMI=32) or the modular cemented cobalt chrome tibial component (n=21; mean age=65 years; mean BMI=33). Both groups were posterior-stabilized and used the same design femoral component. Four experienced surgeons followed a standardized surgical technique and postoperative protocol. Within 4 days of surgery and at 6 months post-operatively, patients had bi-planar knee x-rays taken. RSA analysis was performed with MB-RSA (MEDIS, Leiden). RSA results were reported as maximum total point motion, translations and rotations at 6 months. Spearman’s rank correlations were used to examine the relationship between the first three principle component (PC) scores for each gait variable and the RSA metrics (P< 0.05).

Results: There was a highly significant correlation between MTPM and the first principal component (PC) of the knee adduction moment, which represented the overall magnitude of moment during the stance phase of the gait cycle (r=0.459, P=0.005). Higher preoperative knee adduction moment magnitudes were associated with greater MTPM postoperatively. Internal rotation of the components was correlated with the second PC of internal/external rotation moment at the knee, which represented the magnitude of the moment at load acceptance (r=0.341, P=0.042). Greater knee internal rotation moments at load acceptance preoperatively were associated with higher internal rotation postoperatively.

Conclusion: The amount of postoperative migration of the tibial component in TKA was found to be correlated with preoperative gait patterns, particularly to the magnitude of the knee adduction moment.. These results suggest that surgical success and prosthesis survivorship may be dependent on the preoperative mechanical environment of the knee joint (i.e., gait).