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. 2024 Mar:109:9-14.
doi: 10.1016/j.gaitpost.2024.01.014. Epub 2024 Jan 16.

Relationships between mediolateral step modulation and clinical balance measures in people with chronic stroke

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Relationships between mediolateral step modulation and clinical balance measures in people with chronic stroke

Keith E Howard et al. Gait Posture. 2024 Mar.

Abstract

Background: Many people with chronic stroke (PwCS) exhibit walking balance deficits linked to increased fall risk and decreased balance confidence. One potential contributor to these balance deficits is a decreased ability to modulate mediolateral stepping behavior based on pelvis motion. This behavior, hereby termed mediolateral step modulation, is thought to be an important balance strategy but can be disrupted in PwCS.

Research question: Are biomechanical metrics of mediolateral step modulation related to common clinical balance measures among PwCS?

Methods: In this cross-sectional study, 93 PwCS walked on a treadmill at their self-selected speed for 3-minutes. We quantified mediolateral step modulation for both paretic and non-paretic steps by calculating partial correlations between mediolateral pelvis displacement at the start of each step and step width (ρSW), mediolateral foot placement relative to the pelvis (ρFP), and final mediolateral location of the pelvis (ρPD) at the end of the step. We also assessed several common clinical balance measures (Functional Gait Assessment [FGA], Activities-specific Balance Confidence scale [ABC], self-reported fear of falling and fall history). We performed Spearman correlations to relate each biomechanical metric of step modulation to FGA and ABC scores. We performed Wilcoxon rank sum tests to compare each biomechanical metric between individuals with and without a fear of falling and a history of falls.

Results: Only ρFP for paretic steps was significantly related to all four clinical balance measures; higher paretic ρFP values tended to be observed in participants with higher FGA scores, with higher ABC scores, without a fear of falling and without a history of falls. However, the strength of each of these relationships was only weak to moderate.

Significance: While the present results do not provide insight into causality, they justify future work investigating whether interventions designed to increase ρFP can improve clinical measures of post-stroke balance in parallel.

Keywords: Balance; Foot placement; Gait; Stroke.

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Conflict of interest statement

Declaration of Competing Interest No conflicts were present.

Figures

Figure 1.
Figure 1.
Schematic illustration of mediolateral step measurements, shown for a right step and adapted from [27]. At the start of each step (left illustration), we calculated mediolateral pelvis displacement between the sacrum and stance heel. At the end of the step (right illustration), we calculated final mediolateral pelvis displacement, mediolateral foot placement between the sacrum and swing heel, and step width. Step width was the sum of final pelvis displacement and foot placement.
Figure 2.
Figure 2.
Comparison between biomechanical gait metrics (rows) and clinical balance measures (columns). For all panels, dots indicate individual participant values. Biomechanical gait metrics for paretic steps are plotted in the top three rows, and metrics for non-paretic steps are in the bottom three rows. In the first column, all six biomechanical gait metrics are plotted relative to FGA score. The effect size (r = Spearman correlation) and p-value are indicated at the top of each panel; panels without a significant relationship are shaded gray. In the case of a significant correlation, the best linear fit is shown for illustrative purposes. The second column follows the same structure for comparisons with ABC score. The third column presents box plots comparing biomechanical gait metrics between participants without and with a fear of falling. The central horizontal line indicates the median, the top and bottom edges of the box indicate the upper and lower quartile, and the whiskers indicate values 1.5 interquartile ranges above or below the corresponding quartile value (often used to identify outliers). The effect size (c = Cliff’s delta) and p-value are indicated at the top of each panel, which is shaded gray if no significant relationship was detected. The fourth column follows the same structure for comparisons between participants with and without a self-reported fall in the prior year.

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