In order to achieve a level of community involvement and physical independence, being able to walk is the primary aim of many stroke survivors. It is therefore one of the most important goals during rehabilitation. Falls are common in all stages after stroke. Reported fall rates in the chronic stage after stroke range from 43 to 70% during one year follow up. Moreover, stroke survivors are more likely to become repeated fallers as compared to healthy older adults. Considering the devastating effects of falls in stroke survivors, adequate fall risk assessment is of paramount importance, as it is a first step in targeted fall prevention. As the majority of all falls occur during dynamic activities such as walking, fall risk could be assessed using gait analysis. It is only recent that technology enables us to monitor gait over several consecutive days, thereby allowing us to assess quality of gait in daily life. This thesis studies a variety of gait assessments with respect to their ability to assess fall risk in ambulatory chronic stroke survivors, and explores whether stroke survivors can improve their gait stability through PBT.
DOCUMENT
The aim of this study was to test the inter- and intraobserver reliability of the Physician Rating Scale (PRS) and the Edinburgh Visual Gait Analysis Interval Testing (GAIT) scale for use in children with cerebral palsy (CP). Both assessment scales are quantitative observational scales, evaluating gait. The study involved 24 patients ages 3 to 10 years (mean age 6.7 years) with an abnormal gait caused by CP. They were all able to walk independently with or without walking aids. Of the children 15 had spastic diplegia and 9 had spastic hemiplegia. With a minimum time interval of 6 weeks, video recordings of the gait of these 24 patients were scored twice by three independent observers using the PRS and the GAIT scale. The study showed that both the GAIT scale and the PRS had excellent intraobserver reliability but poor interobserver reliability for children with CP. In the total scores of the GAIT scale and the PRS, the three observers showed systematic differences. Consequently, the authors recommend that longitudinal assessments of a patient should be done by one observer only.
LINK
Background: Falls in stroke survivors can lead to serious injuries and medical costs. Fall risk in older adults can be predicted based on gait characteristics measured in daily life. Given the different gait patterns that stroke survivors exhibit it is unclear whether a similar fall-prediction model could be used in this group. Therefore the main purpose of this study was to examine whether fall-prediction models that have been used in older adults can also be used in a population of stroke survivors, or if modifications are needed, either in the cut-off values of such models, or in the gait characteristics of interest. Methods: This study investigated gait characteristics by assessing accelerations of the lower back measured during seven consecutive days in 31 non fall-prone stroke survivors, 25 fall-prone stroke survivors, 20 neurologically intact fall-prone older adults and 30 non fall-prone older adults. We created a binary logistic regression model to assess the ability of predicting falls for each gait characteristic. We included health status and the interaction between health status (stroke survivors versus older adults) and gait characteristic in the model. Results: We found four significant interactions between gait characteristics and health status. Furthermore we found another four gait characteristics that had similar predictive capacity in both stroke survivors and older adults. Conclusion: The interactions between gait characteristics and health status indicate that gait characteristics are differently associated with fall history between stroke survivors and older adults. Thus specific models are needed to predict fall risk in stroke survivors.
DOCUMENT
