Abstract

Knee mechanical disorders, such as osteoarthritis, affect knee function and kinematics. Establishing phenotypes in healthy individuals is essential to understand "normal" knee movement to be able to adequately assess the impact of injuries and refine treatments. PURPOSE: To identify and characterize phenotypes in healthy 3D knee kinematics. METHODS: Three-dimensional (3D) knee kinematics, namely varus/valgus, flexion/extension, and tibial external/internal rotation movements, were measured via knee kinesiography. A global approach based on a hierarchical discriminant model (BIRCH) was used to separate 3D knee kinematics into homogeneous clusters. Between-phenotype comparisons were made using intracluster correlation coefficient (ICC) and 1D-Statistical parametric mapping (for kinematics), ANOVA and chi-square tests (for participants’ characteristics). RESULTS: Three phenotypes were identified from 150 healthy knees (34 men, 41 women, 33 ± 10 years, Figure 1). First phenotype (blue curve) is characterized by predominant dynamic varus alignment, neutral axial rotation during stance, and more internal tibia rotation during initial swing. This group was composed mostly of men (60.4%). Phenotype 2 (orange), comprised mainly of women (70%), show predominant dynamic valgus alignment, an externally rotated tibia throughout gait cycle. Phenotype 3 (green) shows the most neutral frontal and transverse plane alignment, but greater flexion contracture at heel strike and throughout stance. Phenotype 2 had a higher body mass index than phenotype 1 (p < 0.05). Mean ICC within each phenotype was higher in frontal (0.67) and transverse (0.53) planes compared to sagittal (0.38), suggesting a greater contribution of these planes to identify distinct phenotypes. CONCLUSION: Healthy knee 3D kinematics may be divided in three phenotypes. This finding will help better understand the impact of knee disorders and therefore help define more personalized care plan.

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