Spatiotemporal gait characteristics post-total hip arthroplasty and its impact on locomotive syndrome: a before-after comparative study in hip osteoarthritis patients
Authors: Miyazaki Shigeaki , Fujii Yoshinori , Tsuruta Kurumi , Yoshinaga Saori , Hombu Amy , Funamoto Taro , Sakamoto Takero , Tajima Takuya , Arakawa Hideki , Kawaguchi Tsubasa , Nakatake Jun , Chosa Etsuo 
Published: October 2024

Background

Understanding the gait pattern of patients eligible for total hip arthroplasty (THA) due to hip osteoarthritis (OA) offers valuable information for improving locomotive syndrome (LS). This study aims to measure the gait patterns of THA-eligible patients using an optical motion capture system and to analyze these patterns using principal component analysis (PCA). Additionally, this study examines the relationship between THA-induced gait patterns and LS.

Methods

This before-after study included 237 patients who underwent unilateral primary THA due to hip OA. The primary outcome measures were spatiotemporal gait parameters. Secondary outcome measures included three LS risk tests: a stand-up test, a two-step test, a 25-question Geriatric Locomotive Function Scale (GLFS-25), and total clinical decision limits stages. PCA was performed using 16 spatiotemporal gait parameters collected before and three months after THA. Principal components (PC) were selected to achieve a cumulative contribution rate of 90% (0.9) or higher. Each summarized PC was compared using a paired t-test before and three months after THA. Furthermore, multiple regression analysis was conducted to determine how changes in each PC between before and three months after THA related to changes in the four LS evaluation items.

Results

PCA identified three principal components (PC1, PC2, PC3) that accounted for a cumulative contribution rate of 0.910 using 16 spatiotemporal gait parameters. When comparing before and three months after THA for all three PCs, significant differences were observed in each PC (p < 0.001), with overall walking ability and stance phase being higher three months after THA than before THA, while the asymmetry of support time was lower three months after THA. The results of multiple regression analysis revealed that PC1, PC2, and PC3 were the most influential factors in total clinical decision limits stage. For each LS risk test, the factors related to the stand-up test were identified as PC1, PC2, and PC3, while the factors related to the two-step test were identified as PC1 and PC2. The factors related to the GLFS-25 were also identified as PC1 and PC2.

Conclusions

The most important findings of this study indicate that the three PCs represent over 90% of the 16 spatiotemporal gait parameters, which are associated with total clinical decision limits stage and LS risk tests. The present results suggest that PC1 represents overall walking ability, PC2 represents the stance phase, and PC3 represents asymmetry of support time. Gait pattern characteristics, such as overall walking ability, stance phase, and asymmetry of support time, were clearly defined by these PCs. Regarding the relationship between PC and LS, all three PCs are related to total clinical decision limits stage. In addition, PC1 and PC2 related to all three LS risk tests, and PC3 related only to the stand-up test.