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Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment

BACKGROUND: A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect ga...

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Autores principales: Kikkert, Lisette H. J. C., Vuillerme, Nicolas, van Campen, Jos P., Appels, Bregje A., Hortobágyi, Tibor, Lamoth, Claudine J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557524/
https://www.ncbi.nlm.nih.gov/pubmed/28810928
http://dx.doi.org/10.1186/s12984-017-0297-z
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author Kikkert, Lisette H. J. C.
Vuillerme, Nicolas
van Campen, Jos P.
Appels, Bregje A.
Hortobágyi, Tibor
Lamoth, Claudine J.
author_facet Kikkert, Lisette H. J. C.
Vuillerme, Nicolas
van Campen, Jos P.
Appels, Bregje A.
Hortobágyi, Tibor
Lamoth, Claudine J.
author_sort Kikkert, Lisette H. J. C.
collection PubMed
description BACKGROUND: A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect gait, results from healthy old adults cannot easily be extrapolated to geriatric patients. Hence, we (1) quantified gait outcomes based on dynamical systems theory, and (2) determined their discriminative power in three groups: healthy old adults, geriatric patients with- and geriatric patients without cognitive impairment. METHODS: For the present cross-sectional study, 25 healthy old adults recruited from community (65 ± 5.5 years), and 70 geriatric patients with (n = 39) and without (n = 31) cognitive impairment from the geriatric dayclinic of the MC Slotervaart hospital in Amsterdam (80 ± 6.6 years) were included. Participants walked for 3 min during single- and dual-tasking at self-selected speed while 3D trunk accelerations were registered with an IPod touch G4. We quantified 23 gait outcomes that reflect multiple gait aspects. A multivariate model was built using Partial Least Square- Discriminant Analysis (PLS-DA) that best modelled participant group from gait outcomes. RESULTS: For single-task walking, the PLS-DA model consisted of 4 Latent Variables that explained 63 and 41% of the variance in gait outcomes and group, respectively. Outcomes related to speed, regularity, predictability, and stability of trunk accelerations revealed with the highest discriminative power (VIP > 1). A high proportion of healthy old adults (96 and 93% for single- and dual-task, respectively) was correctly classified based on the gait outcomes. The discrimination of geriatric patients with and without cognitive impairment was poor, with 57% (single-task) and 64% (dual-task) of the patients misclassified. CONCLUSIONS: While geriatric patients vs. healthy old adults walked slower, and less regular, predictable, and stable, we found no differences in gait between geriatric patients with and without cognitive impairment. The effects of multiple comorbidities on geriatric patients’ gait possibly causes a ‘floor-effect’, with no room for further deterioration when patients develop cognitive impairment. An accurate identification of cognitive status thus necessitates a multifactorial approach.
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spelling pubmed-55575242017-08-16 Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment Kikkert, Lisette H. J. C. Vuillerme, Nicolas van Campen, Jos P. Appels, Bregje A. Hortobágyi, Tibor Lamoth, Claudine J. J Neuroeng Rehabil Research BACKGROUND: A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect gait, results from healthy old adults cannot easily be extrapolated to geriatric patients. Hence, we (1) quantified gait outcomes based on dynamical systems theory, and (2) determined their discriminative power in three groups: healthy old adults, geriatric patients with- and geriatric patients without cognitive impairment. METHODS: For the present cross-sectional study, 25 healthy old adults recruited from community (65 ± 5.5 years), and 70 geriatric patients with (n = 39) and without (n = 31) cognitive impairment from the geriatric dayclinic of the MC Slotervaart hospital in Amsterdam (80 ± 6.6 years) were included. Participants walked for 3 min during single- and dual-tasking at self-selected speed while 3D trunk accelerations were registered with an IPod touch G4. We quantified 23 gait outcomes that reflect multiple gait aspects. A multivariate model was built using Partial Least Square- Discriminant Analysis (PLS-DA) that best modelled participant group from gait outcomes. RESULTS: For single-task walking, the PLS-DA model consisted of 4 Latent Variables that explained 63 and 41% of the variance in gait outcomes and group, respectively. Outcomes related to speed, regularity, predictability, and stability of trunk accelerations revealed with the highest discriminative power (VIP > 1). A high proportion of healthy old adults (96 and 93% for single- and dual-task, respectively) was correctly classified based on the gait outcomes. The discrimination of geriatric patients with and without cognitive impairment was poor, with 57% (single-task) and 64% (dual-task) of the patients misclassified. CONCLUSIONS: While geriatric patients vs. healthy old adults walked slower, and less regular, predictable, and stable, we found no differences in gait between geriatric patients with and without cognitive impairment. The effects of multiple comorbidities on geriatric patients’ gait possibly causes a ‘floor-effect’, with no room for further deterioration when patients develop cognitive impairment. An accurate identification of cognitive status thus necessitates a multifactorial approach. BioMed Central 2017-08-15 /pmc/articles/PMC5557524/ /pubmed/28810928 http://dx.doi.org/10.1186/s12984-017-0297-z Text en © The Author(s). 2017 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
Kikkert, Lisette H. J. C.
Vuillerme, Nicolas
van Campen, Jos P.
Appels, Bregje A.
Hortobágyi, Tibor
Lamoth, Claudine J.
Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
title Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
title_full Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
title_fullStr Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
title_full_unstemmed Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
title_short Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
title_sort gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557524/
https://www.ncbi.nlm.nih.gov/pubmed/28810928
http://dx.doi.org/10.1186/s12984-017-0297-z
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