Fall-risk Factors in Community-dwelling Ambulatory Individuals with Chronic Stroke.

Falls are a common complication post-stroke. Falls in individuals with stroke are multifactorial and are associated with a wide range of stroke-related impairments. Such associated impairments in conjunction with the challenging ambulatory environments predisposes people with stroke to fall-risk and may result in physical, psychosocial, and socioeconomic consequences, thereby effecting their quality of life. While there are several fall-risk prediction models to identify individuals with stroke at high risk of falls, there is a lack of comprehensive analysis of fall-risk factors. Most fall-risk prediction models consider only physical factors such as balance, sensorimotor impairment, and muscle strength, but do not take into account psychosocial factors, such as fear of falling, as fall-risk factors. Furthermore, few models include only clinical measures and do not consider instrumented measures, which are objective in nature for fall-risk prediction. In addition to assessing intrinsic fall-risk factors that predispose an individual to fall on experiencing a perturbation, it is also essential to assess their responses to overcome the perturbation and prevent a fall. Considering the complex nature of falls and their consequences, there is a need to determine the most sensitive fall-risk factors that can help in identifying individuals with stroke at high fall-risk. The main purpose of this thesis was to perform a multifactorial analysis of fall-risk factors to determine the most sensitive factors and measures to predict fall-risk in community-dwelling ambulatory individuals with chronic stroke. This purpose was achieved by including clinical and instrumented measures assessing various fall-risk factors from each of the domains of the International Classification of Functioning, Disability and Health (ICF) framework. Such a framework enables us to identify fall-risk factors at different levels of the ICF and help us develop feasible fall-prevention paradigms focusing on those domains. In addition to assessing intrinsic fall-risk factors focusing on volitional balance control, we also aimed to assess reactive balance control by assessing stepping responses crucial for fall prevention. Thus, we utilized the Spring Scale Test (SST) described by DePasquale and Toscano which can induce waist-pull perturbations to assess and quantify reactive stepping response measures. The SST has been determined as a reliable, valid, and feasible reactive balance assessment tool. We conducted a pilot study focusing on assessing reactive balance using the SST to determine whether there is a correlation between these stepping measures and fall history in individuals with stroke. The first study aimed to perform a multifactorial analysis comprising of various clinical and instrumented measures in order to assess fall-risk factors from each of the domains of the ICF. We conducted statistical analyses on the data collected from fifty-six individuals with stroke to determine the sensitivity and accuracy of measures from each of the domains of the ICF in predicting laboratory-induced slip fall-risk. The results indicated a model comprising of measures from the body structure and function domain (dynamic gait stability and hip extensor strength) and activity limitation domain (Timed Up and Go) as sensitive predictors of laboratory-induced slip-related fall-risk. The data is presented in Chapter Ⅱ. While the first study focused on intrinsic fall-risk factors, primarily focusing on volitional balance control, the second study is a pilot study done on seven individuals with stroke to assess reactive balance in individuals with stroke by administering the Spring Scale Test to assess stepping responses crucial for fall prevention. The results indicated that stepping response measures correlated with fall history in individuals with stroke. The study also included a secondary analysis to determine the correlation between stepping response measures and various fall-risk factors such as balance, mobility, and sensorimotor impairment to determine whether fall-risk factors influence stepping response measures. The data is presented in Chapter Ⅲ.