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Gait characteristics related to fall risk in patients with cerebral small vessel disease
Yajing Wang1,2, Yanna Li1,2, Shoufeng Liu1,2
1Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China.
Insights
Cerebral small vessel disease (CSVD) patients face a high fall risk, even with normal-appearing gait. Gait analysis, focusing on toe-off angle and stride variability, can identify those at increased risk.
Area of Science:
- Neurology
- Geriatrics
- Biomedical Engineering
Background:
- Falls and gait disturbances are common in cerebral small vessel disease (CSVD).
- Limited research currently addresses gait characteristics and fall risk in CSVD patients.
- This study investigates gait parameters and fall risk in individuals with CSVD.
Purpose of the Study:
- To analyze gait characteristics in patients diagnosed with CSVD.
- To identify gait parameters associated with an increased risk of falling in CSVD patients.
Main Methods:
- 119 CSVD patients underwent cerebral MRI and a 2-minute walking test using wearable sensors (OPAL) and Mobility Lab software.
- Gait analyzer test system collected spatiotemporal and kinematic gait parameters.
- Logistic regression analysis identified independent risk factors for high fall risk.
Main Results:
- Multivariate logistic regression revealed significant independent risk factors for high fall risk.
- These factors include toe-off angle (OR=0.742), toe-off angle coefficient of variation (CV) (OR=0.717), stride length CV (OR=1.256), and terminal double support CV (OR=1.735).
- A decreased toe-off angle and increased gait variability (CV) were associated with higher fall risk.
Conclusions:
- CSVD patients, even those with seemingly normal gait, are at high risk of falling.
- Gait spatiotemporal-kinematic parameters, symmetry, and variability are crucial for assessing fall risk.
- Reduced toe-off angle and increased gait variability (CV) significantly elevate fall risk in CSVD patients.
Background:
Falls and gait disturbance are significant clinical manifestations of cerebral small vessel disease (CSVD). However, few relevant studies are reported at present. We aimed to investigate gait characteristics and fall risk in patients with CSVD.
Methods:
A total of 119 patients with CSVD admitted to the Department of Neurology at Tianjin Huanhu Hospital between 17 August 2018 and 7 November 2018 were enrolled in this study. All patients underwent cerebral magnetic resonance imaging scanning and a 2-min walking test using an OPAL wearable sensor and Mobility Lab software. Relevant data were collected using the gait analyzer test system to further analyze the time-space and kinematic parameters of gait. All patients were followed up, and univariate and multivariate logistic regression analyses were conducted to analyze the gait characteristics and relevant risk factors in patients with CSVD at an increased risk of falling.
Results:
All patients were grouped according to the presence or absence of falling and fear of falling and were divided into a high-fall risk group (n = 35) and a low-fall risk group (n = 72). Logistic multivariate regression analysis showed that the toe-off angle [odds ratio (OR) = 0.742, 95% confidence interval (CI) 0.584-0.942, p < 0.05], toe-off angle coefficient of variation (CV) (OR = 0.717, 95% CI: 0.535-0.962, p < 0.05), stride length CV (OR = 1.256, 95% CI: 1.017-1.552, p < 0.05), and terminal double support CV (OR = 1.735, 95% CI: 1.271-2.369, p < 0.05) were statistically significant (p < 0.05) and were independent risk factors for high-fall risk in patients with CSVD.
Conclusion:
CSVD patients with seemingly normal gait and ambulation independently still have a high risk of falling, and gait spatiotemporal-kinematic parameters, gait symmetry, and gait variability are important indicators to assess the high-fall risk. The decrease in toe-off angle, in particular, and an increase in related parameters of CV, can increase the fall risk of CSVD patients.
