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Dynamic balance and instrumented gait variables are independent predictors of falls following stroke

BACKGROUND: Falls are common following stroke and are frequently related to deficits in balance and mobility. This study aimed to investigate the predictive strength of gait and balance variables for evaluating post-stroke falls risk over 12 months following rehabilitation discharge. METHODS: A pros...

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Autores principales: Bower, Kelly, Thilarajah, Shamala, Pua, Yong-Hao, Williams, Gavin, Tan, Dawn, Mentiplay, Benjamin, Denehy, Linda, Clark, Ross
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322221/
https://www.ncbi.nlm.nih.gov/pubmed/30612584
http://dx.doi.org/10.1186/s12984-018-0478-4
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author Bower, Kelly
Thilarajah, Shamala
Pua, Yong-Hao
Williams, Gavin
Tan, Dawn
Mentiplay, Benjamin
Denehy, Linda
Clark, Ross
author_facet Bower, Kelly
Thilarajah, Shamala
Pua, Yong-Hao
Williams, Gavin
Tan, Dawn
Mentiplay, Benjamin
Denehy, Linda
Clark, Ross
author_sort Bower, Kelly
collection PubMed
description BACKGROUND: Falls are common following stroke and are frequently related to deficits in balance and mobility. This study aimed to investigate the predictive strength of gait and balance variables for evaluating post-stroke falls risk over 12 months following rehabilitation discharge. METHODS: A prospective cohort study was undertaken in inpatient rehabilitation centres based in Australia and Singapore. A consecutive sample of 81 individuals (mean age 63 years; median 24 days post stroke) were assessed within one week prior to discharge. In addition to comfortable gait speed over six metres (6mWT), a depth-sensing camera (Kinect) was used to obtain fast-paced gait speed, stride length, cadence, step width, step length asymmetry, gait speed variability, and mediolateral and vertical pelvic displacement. Balance variables were the step test, timed up and go (TUG), dual-task TUG, and Wii Balance Board-derived centre of pressure velocity during static standing. Falls data were collected using monthly calendars. RESULTS: Over 12 months, 28% of individuals fell at least once. The faller group had increased TUG time and reduced stride length, gait speed variability, mediolateral and vertical pelvic displacement, and step test scores (P < 0.001–0.048). Significant predictors, when adjusted for country, prior falls and assistance (i.e., physical assistance and/or gait aid use) were stride length, step length asymmetry, mediolateral pelvic displacement, step test and TUG scores (P < 0.040; IQR-odds ratio(OR) = 1.37–7.85). With comfortable gait speed as an additional covariate, to determine the additive benefit over standard clinical assessment, only mediolateral pelvic displacement, TUG and step test scores remained significant (P = 0.001–0.018; IQR-OR = 5.28–10.29). CONCLUSIONS: Reduced displacement of the pelvis in the mediolateral direction during walking was the strongest predictor of post-stroke falls compared with other gait variables. Dynamic balance measures, such as the TUG and step test, may better predict falls than gait speed or static balance measures. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-018-0478-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-63222212019-01-09 Dynamic balance and instrumented gait variables are independent predictors of falls following stroke Bower, Kelly Thilarajah, Shamala Pua, Yong-Hao Williams, Gavin Tan, Dawn Mentiplay, Benjamin Denehy, Linda Clark, Ross J Neuroeng Rehabil Research BACKGROUND: Falls are common following stroke and are frequently related to deficits in balance and mobility. This study aimed to investigate the predictive strength of gait and balance variables for evaluating post-stroke falls risk over 12 months following rehabilitation discharge. METHODS: A prospective cohort study was undertaken in inpatient rehabilitation centres based in Australia and Singapore. A consecutive sample of 81 individuals (mean age 63 years; median 24 days post stroke) were assessed within one week prior to discharge. In addition to comfortable gait speed over six metres (6mWT), a depth-sensing camera (Kinect) was used to obtain fast-paced gait speed, stride length, cadence, step width, step length asymmetry, gait speed variability, and mediolateral and vertical pelvic displacement. Balance variables were the step test, timed up and go (TUG), dual-task TUG, and Wii Balance Board-derived centre of pressure velocity during static standing. Falls data were collected using monthly calendars. RESULTS: Over 12 months, 28% of individuals fell at least once. The faller group had increased TUG time and reduced stride length, gait speed variability, mediolateral and vertical pelvic displacement, and step test scores (P < 0.001–0.048). Significant predictors, when adjusted for country, prior falls and assistance (i.e., physical assistance and/or gait aid use) were stride length, step length asymmetry, mediolateral pelvic displacement, step test and TUG scores (P < 0.040; IQR-odds ratio(OR) = 1.37–7.85). With comfortable gait speed as an additional covariate, to determine the additive benefit over standard clinical assessment, only mediolateral pelvic displacement, TUG and step test scores remained significant (P = 0.001–0.018; IQR-OR = 5.28–10.29). CONCLUSIONS: Reduced displacement of the pelvis in the mediolateral direction during walking was the strongest predictor of post-stroke falls compared with other gait variables. Dynamic balance measures, such as the TUG and step test, may better predict falls than gait speed or static balance measures. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-018-0478-4) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-07 /pmc/articles/PMC6322221/ /pubmed/30612584 http://dx.doi.org/10.1186/s12984-018-0478-4 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Bower, Kelly
Thilarajah, Shamala
Pua, Yong-Hao
Williams, Gavin
Tan, Dawn
Mentiplay, Benjamin
Denehy, Linda
Clark, Ross
Dynamic balance and instrumented gait variables are independent predictors of falls following stroke
title Dynamic balance and instrumented gait variables are independent predictors of falls following stroke
title_full Dynamic balance and instrumented gait variables are independent predictors of falls following stroke
title_fullStr Dynamic balance and instrumented gait variables are independent predictors of falls following stroke
title_full_unstemmed Dynamic balance and instrumented gait variables are independent predictors of falls following stroke
title_short Dynamic balance and instrumented gait variables are independent predictors of falls following stroke
title_sort dynamic balance and instrumented gait variables are independent predictors of falls following stroke
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322221/
https://www.ncbi.nlm.nih.gov/pubmed/30612584
http://dx.doi.org/10.1186/s12984-018-0478-4
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