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Research Article
Muscular Function: An alternative way to identify cognitive impairment, Secondary Analysis From SABE-Colombia
Elkin Garcia-Cifuentes
Pontificia Universidad Javeriana
Corresponding Author
License:
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Background
Traditionally, the identification of cognitive impairment is based on neuropsychological tests and supported with not widely available biomarkers. This study aimed to establish the association between motor function (Gait Speed and Handgrip Strength) and the performance in a global cognitive performance and various cognitive domains. Our secondary objective was to determine a cut-off point for Gait Speed and Handgrip Strength to classify older adults as cognitively impaired.
Methods
This is a secondary analysis from the SABE Colombia study (Health, Well-Being, and Aging) conducted in 2015. We performed linear regression models, to establish association with motor function, clinical, and sociodemographic variables, and predict the scores of the Mini-mental State Examination and its domains (i.e. orientation, recall, counting, and language). The evaluation of the motor function variables as an instrument to separate cognitively impaired older adults was evaluated by developing a receiving operating characteristic curve (ROC).
Results
Gait speed was associated with orientation (r2 = 0.16), language (r2 = 0.15), recall memory (r2 = 0.14) and counting (r2 = 0.08). Similarly, handgrip strength was associated with orientation (r2 = 0.175), language (r2 = 0.164), recall memory (r2 = 0.137), and counting (r2 = 0.08). Slow gait had a cut-off point of 0,59 m/s, with an area under the curve (AUC) of 0.629 (0.613–0.646), whereas a weak handgrip strength had an AUC of 0.653 (0.645–0.661), with a cut-off point of 17.50 Kg for separating those older adults with cognitive impairment.
Conclusions
Gait Speed or Handgrip Strength are similarly associated with cognitive performance, exhibiting the larger associations with orientation and language domains. Gait Speed and Handgrip Strength can be easily performed by any clinician and seems to be useful screening tools to detect cognitive impairment.
Keywords
gait speed, handgrip strength, cognitive impairment, biomarker, preclinical dementia, motor dysfunction
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Figure 2
Due to technical limitations, table 3 is only available as a download in the Supplemental Files section.
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CURRENT STATUS: Under Review
Version 1
Posted 23 Dec, 2020
No community comments so far
Review #1 received
Received 20 Jan, 2021
Reviewer #1 agreed
On 10 Jan, 2021
Reviewer #3 agreed
On 10 Jan, 2021
Reviewer #4 agreed
On 10 Jan, 2021
Reviewer #2 agreed
On 10 Jan, 2021
Reviewers invited
Invitations sent on 21 Dec, 2020
Editor assigned
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
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On 21 Dec, 2020
First submitted
On 18 Dec, 2020
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Subject Areas
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This preprint is under consideration at BMC Geriatrics. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Muscular Function: An alternative way to identify cognitive impairment, Secondary Analysis From SABE-Colombia
Elkin Garcia-Cifuentes
Pontificia Universidad Javeriana
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 23 Dec, 2020
No community comments so far
Review #1 received
Received 20 Jan, 2021
Reviewer #1 agreed
On 10 Jan, 2021
Reviewer #3 agreed
On 10 Jan, 2021
Reviewer #4 agreed
On 10 Jan, 2021
Reviewer #2 agreed
On 10 Jan, 2021
Reviewers invited
Invitations sent on 21 Dec, 2020
Editor assigned
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
First submitted
On 18 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Geriatrics & Gerontology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Traditionally, the identification of cognitive impairment is based on neuropsychological tests and supported with not widely available biomarkers. This study aimed to establish the association between motor function (Gait Speed and Handgrip Strength) and the performance in a global cognitive performance and various cognitive domains. Our secondary objective was to determine a cut-off point for Gait Speed and Handgrip Strength to classify older adults as cognitively impaired.
Methods
This is a secondary analysis from the SABE Colombia study (Health, Well-Being, and Aging) conducted in 2015. We performed linear regression models, to establish association with motor function, clinical, and sociodemographic variables, and predict the scores of the Mini-mental State Examination and its domains (i.e. orientation, recall, counting, and language). The evaluation of the motor function variables as an instrument to separate cognitively impaired older adults was evaluated by developing a receiving operating characteristic curve (ROC).
Results
Gait speed was associated with orientation (r2 = 0.16), language (r2 = 0.15), recall memory (r2 = 0.14) and counting (r2 = 0.08). Similarly, handgrip strength was associated with orientation (r2 = 0.175), language (r2 = 0.164), recall memory (r2 = 0.137), and counting (r2 = 0.08). Slow gait had a cut-off point of 0,59 m/s, with an area under the curve (AUC) of 0.629 (0.613–0.646), whereas a weak handgrip strength had an AUC of 0.653 (0.645–0.661), with a cut-off point of 17.50 Kg for separating those older adults with cognitive impairment.
Conclusions
Gait Speed or Handgrip Strength are similarly associated with cognitive performance, exhibiting the larger associations with orientation and language domains. Gait Speed and Handgrip Strength can be easily performed by any clinician and seems to be useful screening tools to detect cognitive impairment.
Figure 1
Figure 2
Due to technical limitations, table 3 is only available as a download in the Supplemental Files section.