Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index
Frontiers in bioengineering and biotechnology(2023)
Abstract
Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. Methods: Nine parameters (peak amplitudes) commonly used to quantify three-dimensional knee moments during walking were analyzed for 98 individuals (58.7 +/- 9.2 years old, 1.69 +/- 0.09 m, 76.9 +/- 14.5 kg, 56% female), corresponding to three medial knee osteoarthritis severity groups: non-osteoarthritis (n = 22), mild osteoarthritis (n = 38) and severe osteoarthritis (n = 38). Multinomial logistic regression was used to create a severity index. Comparison and regression analyses were performed with respect to disease severity. Results: Six of the nine moment parameters differed statistically significantly among severity groups (p <= 0.039) and five reported statistically significant correlation with disease severity (0.23 <= vertical bar r vertical bar <= 0.59). The proposed severity index was highly reliable (ICC = 0.96) and statistically significantly different between the three groups (p < 0.001) as well as correlated with disease severity (r = 0.70). Conclusion: While medial knee osteoarthritis research has mostly focused on a few knee moment parameters, this study showed that other parameters differ with disease severity. In particular, it shed light on three parameters frequently disregarded in prior works. Another important finding is the possibility of combining the parameters into a severity index, which opens promising perspectives based on a single figure assessing the knee moments in their entirety. Although the proposed index was shown to be reliable and associated with disease severity, further research will be necessary particularly to assess its validity.
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Key words
gait analysis,kinetics,knee adduction moment,knee flexion moment,biomechanics,machine learning
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