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Updated: Aug 4, 2025
Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
Published on: March 4, 2018
Relationships between Clinical Status and Gait Parameters in Ankylosing Spondylitis
Yong Geon Park1, Tae Sik Goh1, Dong Suk Kim1
1Biomedical Research Institute, Department of Orthopaedic Surgery, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
Background:
This study aimed to identify the relationship between gait parameters and health-related quality of life (HRQOL) in patients with ankylosing spondylitis (AS).
Methods:
The study group comprised 134 patients with AS and 124 patients were enrolled as controls. All study participants underwent instrumented gait analysis and completed clinical questionnaires. The kinematic parameters of gait were walking speed, step length, cadence, stance phase, single support, double support, phase coordination index (PCI), and gait asymmetry (GA). For each patient, a visual analog scale (VAS; 0-10) score was used to assess back pain, 36-item short form survey (SF-36) questionnaire was administered to evaluate the HRQOL, and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) was calculated. Using kinematic parameters and questionnaires, statistical analyses were done to investigate significant differences between the groups. Relationship of gait kinematic data and questionnaires of clinical outcome was also evaluated.
Results:
Among the 134 patients with AS, 34 were women and 100 were men. In the control group, 26 were women and 98 were men. The patients with AS and control group patients had significant differences in terms of walking speed, step length, single support, PCI, and GA. However, such differences were not observed in cadence, stance phase, and double support (p > 0.05). In correlation analyses, gait kinematic parameters and clinical outcomes were significantly related with each other. In multiple regression analysis performed to identify predictive factors for clinical outcome, walking speed was found to predict VAS, and walking speed and step length were found to predict the BASDAI and SF-36 scores.
Conclusions:
Patients with and without AS had significant differences in the gait parameters. Correlation analysis showed significant correlation between the gait kinematic data and clinical outcomes. In particular, walking speed and step length successfully predicted clinical outcomes in patients with AS.
