Ankle sprain history and clinical outcome have limited influence on walking and running biomechanics among runners: a cross-sectional study

作者
Jean-Louis Peters-Dickie,Christine Detrembleur,Michel Bertrand,Emma Detrembleur,Anh Phong Nguyen
出处
期刊:Frontiers in sports and active living [Frontiers Media]
卷期号:7: 1553995-1553995
标识
DOI:10.3389/fspor.2025.1553995
摘要

Background Lateral ankle sprain (LAS) is prevalent among runners, with many developing chronic ankle instability (CAI). While CAI is associated with many motor-behavioral, sensory-perceptual, and pathomechanical factors, its impact on gait biomechanics remains unclear. This cross-sectional study aimed to assess gait biomechanics and other factors contributing to CAI in runners. Methods Seventy participants (47 men and 23 women) were categorized as healthy ( n = 24), acute LAS ( n = 17), CAI ( n = 16) and copers ( n = 13). Walking and running spatiotemporal, kinetic and kinematic parameters were collected on an instrumented treadmill. Rehabilitation-oriented assessment outcomes were also assessed. One-way ANOVA or Kruskal–Wallis tests were used, along with their corresponding post-hoc tests. Effect sizes (g or r according to normality) were reported. Results Runners with CAI and acute LAS reported significantly greater perceived instability ( r = 0.68–0.86) and worse self-reported function ( r = 0.47–0.67) than healthy controls and copers. However, running biomechanics did not differ between groups, suggesting that traditional biomechanical assessments at comfortable speeds may not be sensitive to functional deficits in CAI. A notable finding was the lower mechanical work recovery during walking in copers compared to healthy controls (g = 0.98). Conclusion These results highlight the importance of considering self-reported function and perceived instability when assessing LAS and CAI. The absence of gross running gait alterations suggests that rehabilitation could safely integrate running early in recovery. However, more demanding tasks or advanced biomechanical modeling techniques may be needed to identify residual gait impairments.

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