Thresholds of acceptable early migration of the components in total knee arthroplasty (TKA) have traditionally ignored the effects of patient and implant factors that may influence migration. The aim of this study was to determine which of these factors are associated with overall longitudinal migration of well-fixed tibial components following TKA. Radiostereometric analysis (RSA) data over a two-year period were available for 419 successful primary TKAs (267 cemented and 152 uncemented in 257 female and 162 male patients). Longitudinal analysis of data using marginal models was performed to examine the associations of patient factors (age, sex, BMI, smoking status) and implant factors (cemented or uncemented, the size of the implant) with maximum total point motion (MTPM) migration. Analyses were also performed on subgroups based on sex and fixation.Aims
Methods
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. 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.Introduction
Methods
