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Record W3048934386

Balance Function: A Potential Early Indicator of Mild Cognitive Impairment

2020· article· en· W3048934386 on OpenAlexaboutno aff
Karen L. Bell

Bibliographic record

VenueDigital Commons - University of South Florida (University of South Florida) · 2020
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsBalance (ability)Cognitive impairmentCognitionFunction (biology)PsychologyMedicinePhysical medicine and rehabilitationPsychiatryBiology
DOInot available

Abstract

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This study examined oculomotor and vestibular function in young adults, cognitively normal older adults (CNOA), and older adults with MCI. Oculomotor and vestibular function were assessed using videonystagmography (VNG), vestibular evoked myogenic potentials (VEMPs), the modified Clinical Test of Sensory Integration and Balance (mCTSIB), and the Fukuda Stepping test. Forty-two participants comprised three groups (young adults, n = 15; CNOA, n = 13; MCI, n = 14). The Montreal Cognitive Assessment ([MoCA]; Nasreddine et al., 2005) was used to assess cognitive status, and a MCI diagnosis was confirmed using standardized neuropsychological testing and a physician’s exam. MANOVA was calculated to compare young and older adults with and without MCI on oculomotor and vestibular function. Chi-square analysis was calculated to examine the proportion of clinically significant unilateral weakness among groups. Results indicated the young adult group showed shorter saccade latencies than either CNOA or MCI groups. The MCI group also showed both a higher mean unilateral caloric weakness and a higher occurrence of unilateral caloric weakness than either young adult or CNOA groups. The young adult group showed larger P1-N1 amplitudes than either CNOA or MCI groups for cervical VEMPs. There were no additional group differences on remaining oculomotor or vestibular measures. These results indicate older adults with MCI may show vestibular asymmetry assessed using bithermal caloric irrigation, however, these findings are not conclusive. Functional balance and spatial ability are known to be impaired in older adults with cognitive decline. The purpose of this study was to examine the relationships between oculomotor and vestibular function, functional balance, and spatial ability in young adults and older adults with and without MCI. Oculomotor and vestibular function, and cognitive status were assessed using screening and diagnostic measures. This data was collected and described in the previous study. Functional balance was assessed using the Timed Up and Go (Podsiadlo & Richardson, 1991) and Functional Reach tests (Duncan et al., 1990). Spatial ability was assessed using the Hidden Goal Task (Kalová et al., 2005), a computerized test of spatial navigation. Forty-two participants comprised three groups (young adult, n = 15; CNOA, n = 13; MCI, n = 14). MANOVA was calculated to examine group differences on functional balance and spatial ability. Two multiple linear regressions were also calculated to examine the contribution of oculomotor or vestibular function to functional balance and spatial ability. The young adult group showed better performance on the Functional Reach and Timed Up and Go tests compared to MCI group, ps < .005, however, there were no differences between young adult and CNOA groups, ps > .114. The young adult group also showed better performance on the Hidden Goal Task compared to either CNOA or MCI groups, ps < .042. Results showed VOR and VSR were significantly associated with functional balance and spatial ability, respectively. These results suggest VOR and VSR assessment may be considered as part of routine non-invasive battery for detecting signs and symptoms linked to cognitive decline, such as reduced functional balance and spatial ability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.188
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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