BACKGROUND: Falls in people with stroke are extremely common and present a significant health risk to this population. Development of fall screening tools is an essential component of a comprehensive fall reduction plan. OBJECTIVE: The purpose of this study was to examine the accuracy of clinical measures representing various domains of the International Classification of Functioning, Disability and Health (ICF) relative to their ability to identify individuals with a history of multiple falls. DESIGN: A case series study design was used. SETTING: The study was conducted in a community setting. PARTICIPANTS: Twenty-seven people with stroke participated in the study. MEASUREMENTS: Clinical assessment tools included the lower-extremity subscale of the Fugl-Meyer Assessment of Sensorimotor Impairment (FMLE) and Five-Times-Sit-to-Stand Test (STS) representing the body function domain, the Berg Balance Scale (BBS) representing the activity domain, the Activities-specific Balance Confidence (ABC) Scale as a measure of personal factors, and the physical function subscale of the Stroke Impact Scale (SIS-16) as a broad measure of physical function. We used receiver operating characteristic (ROC) curves to generate cutoff scores, sensitivities, specificities, and likelihood ratios (LRs) relative to a history of multiple falls. RESULTS: The FMLE and the STS showed a weak association with fall history. The BBS demonstrated fair accuracy in identifying people with multiple falls, with a cutoff score of 49 and a positive LR of 2.80. The ABC Scale and the SIS-16 were most effective, with cutoff scores of 81.1 and 61.7, respectively, positive LRs of 3.60 and 7.00, respectively, and negative LRs of 0.00 and 0.25, respectively. LIMITATIONS: A limitation of the study was the small sample size. CONCLUSION: The findings suggest that the ICF is a useful framework for selecting clinical measures relative to fall history and support the need for prospective study of tools in more-complex domains of the ICF for their accuracy for fall prediction in people with stroke.
BACKGROUND: Falls in people with stroke are extremely common and present a significant health risk to this population. Development of fall screening tools is an essential component of a comprehensive fall reduction plan. OBJECTIVE: The purpose of this study was to examine the accuracy of clinical measures representing various domains of the International Classification of Functioning, Disability and Health (ICF) relative to their ability to identify individuals with a history of multiple falls. DESIGN: A case series study design was used. SETTING: The study was conducted in a community setting. PARTICIPANTS: Twenty-seven people with stroke participated in the study. MEASUREMENTS: Clinical assessment tools included the lower-extremity subscale of the Fugl-Meyer Assessment of Sensorimotor Impairment (FMLE) and Five-Times-Sit-to-Stand Test (STS) representing the body function domain, the Berg Balance Scale (BBS) representing the activity domain, the Activities-specific Balance Confidence (ABC) Scale as a measure of personal factors, and the physical function subscale of the Stroke Impact Scale (SIS-16) as a broad measure of physical function. We used receiver operating characteristic (ROC) curves to generate cutoff scores, sensitivities, specificities, and likelihood ratios (LRs) relative to a history of multiple falls. RESULTS: The FMLE and the STS showed a weak association with fall history. The BBS demonstrated fair accuracy in identifying people with multiple falls, with a cutoff score of 49 and a positive LR of 2.80. The ABC Scale and the SIS-16 were most effective, with cutoff scores of 81.1 and 61.7, respectively, positive LRs of 3.60 and 7.00, respectively, and negative LRs of 0.00 and 0.25, respectively. LIMITATIONS: A limitation of the study was the small sample size. CONCLUSION: The findings suggest that the ICF is a useful framework for selecting clinical measures relative to fall history and support the need for prospective study of tools in more-complex domains of the ICF for their accuracy for fall prediction in people with stroke.
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Authors: Sangeetha Madhavan; Anjali Sivaramakrishnan; Mark G Bowden; Neale R Chumbler; Edelle C Field-Fote; Trisha M Kesar Journal: Top Stroke Rehabil Date: 2021-02-18 Impact factor: 2.119
Authors: Elizabeth Regan; Addie Middleton; Jill C Stewart; Sara Wilcox; Joseph Lee Pearson; Stacy Fritz Journal: Top Stroke Rehabil Date: 2019-10-17 Impact factor: 2.119