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Do clinical assessments, steady-state or daily-life gait characteristics predict falls in ambulatory chronic stroke survivors?

Auteur(s) Michiel Punt; Sjoerd M. Bruijn; Harriët Wittink; Ingrid G. Port, van de; Jaap H. Dieën, van
Publicatiedatum 2017
Publicatietype Artikel
Kenniscentrum Hogeschool Utrecht, Kenniscentrum Gezond en Duurzaam Leven
Lectoraat Leefstijl en Gezondheid
Samenvatting Objective: This exploratory study investigated to what extent gait characteristics and clinical physical therapy assessments predict falls in chronic stroke survivors. Design: Prospective study. Subjects: Chronic fall-prone and non-fall-prone stroke survivors. Methods: Steady-state gait characteristics were collected from 40 participants while walking on a treadmill with motion capture of spatio-temporal, variability, and stability measures. An accelerometer was used to collect daily-life gait characteristics during 7 days. Six physical and psychological assessments were administered. Fall events were determined using a “fall calendar” and monthly phone calls over a 6-month period. After data reduction through principal component analysis, the predictive capacity of each method was determined by logistic regression. Results: Thirty-eight percent of the participants were classified as fallers. Laboratory-based and daily-life gait characteristics predicted falls acceptably well, with an area under the curve of, 0.73 and 0.72, respectively, while fall predictions from clinical assessments were limited (0.64). Conclusion: Independent of the type of gait assessment, qualitative gait characteristics are better fall predictors than clinical assessments. Clinicians should therefore consider gait analyses as an alternative for identifying fall-prone stroke survivors.
Trefwoorden vallen, beroerte, accelerometrie
Taal Engels
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Gepubliceerd in Journal of Rehabilitation Medicine
Jaargang/Volume 49 nr. 5
Paginabereik 402-409
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