Identifying knee osteoarthritis (OA) patient phenotypes is relevant to assessing treatment efficacy, yet biomechanical variability has not been applied to phenotyping. This study aimed to identify demographic and gait related groups (clusters) among total knee arthroplasty (TKA) candidates, and examine inter-cluster differences in gait feature improvement post-TKA. Knee OA patients scheduled for TKA underwent three-dimensional gait analysis one-week pre and one-year post-TKA, capturing lower-limb external ground reaction forces and kinematics using a force platform and optoelectronic motion capture. Principal component analysis was applied to frontal and sagittal knee angle and moment waveforms (n=135 pre-TKA, n=106 post-TKA), resulting in a new uncorrelated dataset of subject PCscores and PC vectors, describing major modes of variability throughout one gait cycle (0–100%). Demographics (age, gender, body mass index (BMI), gait speed), and gait angle and moment PCscores were standardized and assessed for outliers. One patient exceeding Tukey's outer (3IQR) fence was removed. Two-dimensional multidimensional scaling followed by k-medoids clustering was applied to scaled demographics and pre-TKA PCscores [134×15]. Number of clusters (k=2:10) were assessed by silhouette coefficients, s, and stability by Adjusted Rand Indices (ARI) of 100 data subsets. Clusters were validated by examining inter-cluster differences at baseline, and inter-cluster gait changes (PostPCscore–PrePCscore, n=105) by k-way ANOVA and Tukey's honestly significant difference (HSD) criterion. Four (k=4) TKA candidate groups yielded optimum clustering metrics (s = 0.4, ARI=0.75). Cluster 1 was all-males (male:female=19:0) who walked with faster gait speeds (1>2,3), larger flexion angle magnitudes and stance-phase angle range (PC1 & PC4 1>2,3,4), and more flexion (PC2 1>2,3,4) and adduction moment (PC2 & PC3 1>2,3) range patterns. Cluster 1 had the most dynamic kinematics and kinetic loading/unloading range amongst the clusters, representing a higher-functioning (less “stiff”) male subset. Cluster 2 captured older (2>1,3) males (31:1) with slower gait speeds (2 4), and lower flexion angle magnitude (PC1 3 2,3) and less stiff kinematic and kinetic patterns relative to Clusters 2 and 3, representing a higher-functioning female subset. Radiographic severity did not differ between clusters (Kellgren-Lawrence Grade, p=0.9, n=102), and after removing demographics and re-clustering, gender differences remained (p < 0 .04). Pre-TKA, higher-functioning clusters (1&4) had more dynamic loading/un-loading kinetic patterns. Post-TKA, high-functioning clusters experienced less gait improvement (flexion angle PC2, 1,4 < 3, p≥0.004, flexion moment PC2, 4 < 2,3), with some sagittal range patterns decreasing postoperatively. TKA candidates can be characterized by four clusters, differing by demographics and biomechanical severity features. Post-TKA, functional gains were cluster-specific, stiff-gait clusters experienced more improvement, while higher-functioning clusters experienced less gain and showed some decline. Results suggest the presence of cohorts who may not benefit functionally from TKA. Cluster profiling may support triaging and developing targeted OA treatment strategies, meeting individual function needs.
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
Methods
To characterize the knee kinematic profiles of total knee arthroplasty patient knees intraoperatively, before implant insertion, using principal component analysis. Ninety-two patientsreceived Stryker Triathlon total knee arthroplasty (TKA) implants. The Stryker surgical navigation system was used for all surgeries. The system was used to define rigid bodies representing the femur and tibia, and to track the three-dimensional movement of the knee joint during surgery. Each knee was moved through a passive range of knee flexion/extension before and after implantation of the arthroplasty components. The frontal plane (medial-lateral) movement of the knee joint through a range of 10 to 120 degrees of flexion before implantation was calculated for each knee using the joint coordinate system (referred to as the pre-implant knee kinematic curve). Visual inspection of these patterns indicated three predominant curve types: a backward S shape, a backward C shape and a valgus to varus shape. Each curve was subjectively categorized into one of these three categories. Principal component analysis (PCA), a multivariate statistical analysis technique, was applied to the pre-implant knee kinematic pattern data to objectively extract the major patterns of curve types within the 92 knees. Analysis of variance was used to compare the mean differences in PC scores between the curve shape groups to confirm visual categorization.Purpose
Method
Aseptic loosening of the tibial component of total knee prosthesis is a common cause of revision surgery. While micromotion at the bone-implant interface can now be accurately measured with Radiostereometric Analysis (RSA), mechanisms responsible for loosening remain poorly understood. The purpose of this study was to investigate the association between bone density in the proximal tibia and post-operative knee implant migration. Fifty-one subjects who received total knee arthroplasty surgery with the Wright Medical Advance Biofoam (uncemented) implant were recruited. Bone density of seven regions of the proximal tibia (medial, lateral, anterior, posterior, and three regions below implant tip) was measured with DEXA post operatively at two, six, 12 and 24 weeks. RSA exams were also taken immediately post-operatively, and at six, 12 and 24 weeks. Correlations between bone mineral density and RSA migration were examined at 24 weeks post-operatively.Purpose
Method
