Identifying knee osteoarthritis patient phenotypes is relevant to assessing treatment efficacy. Biomechanics have not been applied to phenotyping, yet features may be related to total knee arthroplasty (TKA) outcomes, an inherently mechanical surgery. This study aimed to identify biomechanical phenotypes among TKA candidates based on demographic and gait mechanic similarities, and compare objective gait improvements between phenotypes post-TKA. Patients scheduled for TKA 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 the major patterns of gait variability. Demographics (age, gender, BMI), gait speed, and frontal and sagittal pre-TKA gait angle and moment PC scores previously found to differentiate gender, osteoarthritis severity, and symptoms of TKA recipients were standardized (mean=0, SD=1). Multidimensional scaling (2D) and hierarchical clustering were applied to the feature set [134×15]. Number of clusters was assessed by silhouette coefficients, Purpose
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