The Journal of Arthroplasty, Volume 35, Issue 3, 877 - 885

Current Preclinical Testing of New Hip Arthroplasty Technologies Does Not Reflect Real-World Loadings: Capturing Patient-Specific and Activity-Related Variation in Hip Contact Forces

Lunn, David E. et al.
Hip

Background

Total hip arthroplasty (THA) implants are routinely tested for their tribological performance through regulatory preclinical wear testing (eg, ISO-14242). The standardized loading conditions defined in these tests consist of simplified waveforms, which do not specifically represent in vivo loads in different groups of patients. The aim of this study is to investigate, through musculoskeletal modeling, patient-specific and activity-related variation in hip contact forces (HCFs) in a large cohort of THA patients during common activities of daily living (ADLs).

Methods

A total of 132 THA patients participated in a motion-capture analysis while performing different ADLs, including walk, fast walk, stair ascent, and descent (locomotor); sit to stand, stand to sit, squat, and lunge (nonlocomotor). HCFs were then calculated using the AnyBody Modeling System and qualitatively compared across all activities. The influence of gender on HCFs was analyzed through statistical parametric mapping analysis.

Results

Systematic differences were found in HCF magnitudes and individual components in both locomotor and nonlocomotor ADLs. The qualitative analysis of the ADLs revealed a large range and a large variability in forces experienced at the hip during different activities. Significant differences in the 3-dimensional loading patterns were observed between males and females across most activities.

Conclusion

THA patients present a large variability in the forces experienced at the hip joint during their daily life. The interpatient variation might partially explain the heterogeneity observed in implant survival rates. A more extensive preclinical implant testing standard under clinically relevant loading conditions has been advocated to better predict and avoid clinical wear problems.

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