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Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
Published on: March 4, 2018
Preoperative gait patterns and BMI are associated with tibial component migration
Janie L Astephen Wilson1, David A J Wilson, Michael J Dunbar
1School of Biomedical Engineering, Dalhousie University, Halifax, Nova Scotia, Canada. janie.astephen@dal.ca
Acta Orthopaedica
|September 3, 2010
Summary
Preoperative knee joint loading patterns during gait predict total knee arthroplasty tibial component migration at six months. This finding may improve patient triage and treatment strategies for total knee arthroplasty outcomes.
Area of Science:
- Orthopedic surgery
- Biomechanics
- Biomedical engineering
Background:
- Standardized patient triage for total knee arthroplasty (TKA) is lacking.
- Objective measures for TKA success (function, longevity) are underdeveloped.
- Preoperative metrics influencing TKA outcomes require further investigation.
Purpose of the Study:
- To investigate the association between the preoperative mechanical joint environment during gait and post-TKA tibial component stability.
- To assess the utility of radiostereometric analysis (RSA) in measuring TKA outcomes.
- To identify preoperative functional characteristics that predict TKA success.
Main Methods:
- 37 subjects from a randomized RSA trial underwent 3D gait analysis preoperatively.
- Radiostereometric analysis (RSA) was used for longitudinal measurement of tibial component migration.
- Data were collected at 6 months and 1 year postoperatively.
Main Results:
- A significant association was found between preoperative knee adduction moment during gait and implant migration at 6 months.
- Implant type, preoperative joint loading, and BMI explained 45% of tibial component migration variability at 6 months.
- These associations were not statistically significant at the 1-year follow-up.
Conclusions:
- Preoperative patient functional characteristics, especially joint loading patterns, are crucial for TKA outcomes.
- This study is a foundational step towards predictive models for objective TKA outcomes.
- Findings may inform improved patient selection and treatment strategies for total knee arthroplasty.