Gait characteristics related to fall risk in patients with cerebral small vessel disease

Abstract

BackgroundFalls 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.MethodsA 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.ResultsAll 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.ConclusionCSVD 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.