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Record W2345669831 · doi:10.1016/j.jalz.2015.06.612

P2‐075: Gait performance as a biomarker of mild cognitive impairment: Clinical and imaging correlates

2015· article· en· W2345669831 on OpenAlexaff
Manuel Montero‐Odasso

Bibliographic record

VenueAlzheimer s & Dementia · 2015
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsGaitSTRIDECreatineBiomarkerPhysical medicine and rehabilitationMedicineCognitive declineInternal medicineCognitionPsychologyCardiologyPhysical therapyDiseaseNeuroscienceDementia

Abstract

fetched live from OpenAlex

Early motor changes associated with aging predict cognitive decline, which suggests that a “motor signature” can be detected in predementia states. We postulated that dual-task gait, walking while doing a cogntitive demanding task, is a reliable tool to detect MCI individuals with impeding cognitive decline and can be used as a clinical biomarker. Fifty-six older adults with MCI and 42 cognitively normal controls from the “Gait & Brain Study” were included. Gait velocity and stride time variability were measured while single (i.e., walking alone) and dual-tasking (walking while counting backwards by seven) using an electronic walkway (GAITRite). Ratios of N-acetyl-aspartate to creatine (NAA/Cr) and choline to creatine (Cho/Cr) and cortical volume were calculated, only in MCI participants, in the primary motor cortex using a 3TMRI Siemens equipment. From the 56 MCI (mean age 76.3±7.2; 50.9% female), 38 were amnestic-MCI (aMCI) and 18 were non amnestic-MCI (naMCI). Groups were similar in age, comorbidities, and history of falls. Forty-two cognitively normal controls (mean age 71.2±4.50;73% female) were also included. Amnestic-MCI participants walked slower than na-MCI (98.5 vs 112.2 cm/sec, p<0.03) in all test conditions. Adjusted multivariable linear regression showed aMCI was associated with slower gait and higher variability (p<.001) under dual-task tests. MCI participants were further categorized according to median NAA/Cr and Cho/Cr ratios. Participants with low NAA/Cr (n=35) had higher (worse) stride time variability while dual-tasking than those with high NAA/Cr (p= .006). Those with high Cho/Cr had slower (worse) gait velocity while single (p=.015) and dual-tasking (p=.001). Low NAA/Cr was associated with increased stride time variability while dual-tasking (p= 0.03). High Cho/Cr was associated with slower gait velocity while single- ( p=.009) and dual-tasking (p=.02). Cortical volume correlated significantly with better gait performance in both conditons, and with decreased stride time. Participants with aMCI, specifically with episodic memory impairment, had poor gait performance under dual-task conditions, suggesting that slowness and higher stride time variability while dual-tasking is a distinct motor feature in aMCI. Those aMCI participants with lower gait performance presented abnormal metabolite ratios in the primary motor cortex suggesting a potential neurodegenration mechanism.

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)0.002
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.047
GPT teacher head0.327
Teacher spread0.279 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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