Tibial Slope Is Not Associated With Implant Migration Following Cemented Total Knee Arthroplasty With a Single Implant Design.

BACKGROUND: The influence of tibial slope on tibial component migration following total knee arthroplasty has not been widely studied, although excessive posterior slope has been implicated in some failures. As implant micromotion measured with radiostereometric analysis can indicate successful fixation, the purpose of this study was to determine the associations between tibial slope, tibial component migration, and inducible displacement. METHODS: Radiostereometric analyses at 6 visits over 2 years quantified implant migration for 200 cemented total knee arthroplasties. Longitudinal data analysis examined the influence of postoperative tibial slope on implant migration (overall maximum total point motion (MTPM) migration and anterior-posterior tilt migration), accounting for age, sex, and body mass index. The correlations of tibial slope with 1-year migration, continuous migration, and inducible displacements were also examined. Additionally, the amount of change in slope was compared to migration. RESULTS: The mean posterior tibial slope was 8.0° (standard deviation [SD] 3.8°) preoperatively and 3.8° (SD 3.1°) postoperatively, with a mean reduction in slope of 4.2° (SD 4.7°). Postoperative tibial slope (range 14.0° posterior slope to 3.4° anterior slope) was not associated with longitudinal overall migration (P = .671) or anterior-posterior tilt migration (P = .704). There was no association between postoperative tibial slope and migration at 1 year postoperatively (P = .441 for MTPM migration, P = .570 for tilt migration), change in migration from 1 to 2 years (P = .951), or inducible displacement (P = .970 MTPM, P = .730 tilt). The amount of change in tibial slope was also not associated with migration or inducible displacement. CONCLUSIONS: Residual and change in postoperative tibial slope were not associated with implant migration into tilt or overall migration, or inducible displacement for a single implant design. These findings support positioning tibial implants in a range of slopes, which may support patient-specific approaches to implant alignment.

Unveiling distinct kinematic profiles among total knee arthroplasty candidates through clustering technique.

BACKGROUND: Characterizing the condition of patients suffering from knee osteoarthritis is complex due to multiple associations between clinical, functional, and structural parameters. While significant variability exists within this population, especially in candidates for total knee arthroplasty, there is increasing interest in knee kinematics among orthopedic surgeons aiming for more personalized approaches to achieve better outcomes and satisfaction. The primary objective of this study was to identify distinct kinematic phenotypes in total knee arthroplasty candidates and to compare different methods for the identification of these phenotypes. METHODS: Three-dimensional kinematic data obtained from a Knee Kinesiography exam during treadmill walking in the clinic were used. Various aspects of the clustering process were evaluated and compared to achieve optimal clustering, including data preparation, transformation, and representation methods. RESULTS: A K-Means clustering algorithm, performed using Euclidean distance, combined with principal component analysis applied on data transformed by standardization, was the optimal approach. Two unique kinematic phenotypes were identified among 80 total knee arthroplasty candidates. The two distinct phenotypes divided patients who significantly differed both in terms of knee kinematic representation and clinical outcomes, including a notable variation in 63.3% of frontal plane features and 81.8% of transverse plane features across 77.33% of the gait cycle, as well as differences in the Pain Catastrophizing Scale, highlighting the impact of these kinematic variations on patient pain and function. CONCLUSION: Results from this study provide valuable insights for clinicians to develop personalized treatment approaches based on patients' phenotype affiliation, ultimately helping to improve total knee arthroplasty outcomes.