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Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
Published on: March 4, 2018
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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.
Clinics in Orthopedic Surgery
|April 3, 2023
Summary
Gait analysis in ankylosing spondylitis (AS) reveals significant differences compared to healthy individuals. Key parameters like walking speed and step length predict disease activity and quality of life.
Area of Science:
- Rheumatology
- Biomechanics
- Physical Therapy
Background:
- Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the spine.
- Gait disturbances are common in AS, impacting patient mobility and quality of life.
- Understanding the relationship between gait and health-related quality of life (HRQOL) is crucial for AS management.
Purpose of the Study:
- To investigate the relationship between gait parameters and HRQOL in patients with AS.
- To compare gait parameters between AS patients and healthy controls.
- To identify gait parameters that predict clinical outcomes in AS.
Main Methods:
- Instrumented gait analysis was performed on 134 AS patients and 124 controls.
- Gait parameters included walking speed, step length, cadence, stance phase, single support, double support, phase coordination index (PCI), and gait asymmetry (GA).
- Clinical outcomes were assessed using the visual analog scale (VAS) for back pain, SF-36 for HRQOL, and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI).
Main Results:
- Significant differences in walking speed, step length, single support, PCI, and GA were observed between AS patients and controls.
- Gait parameters showed significant correlations with clinical outcomes.
- Walking speed predicted VAS scores, while walking speed and step length predicted BASDAI and SF-36 scores.
Conclusions:
- Patients with AS exhibit distinct gait patterns compared to healthy individuals.
- Gait kinematic data are significantly correlated with clinical outcomes in AS.
- Walking speed and step length are important predictors of clinical outcomes, including pain, disease activity, and HRQOL, in AS patients.

