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Record W3130322427 · doi:10.1002/alz.12298

Gait variability across neurodegenerative and cognitive disorders: Results from the Canadian Consortium of Neurodegeneration in Aging (CCNA) and the Gait and Brain Study

2021· article· en· W3130322427 on OpenAlexafffundabout
Frederico Pieruccini‐Faria, Sandra E. Black, Mario Masellis, Eric E. Smith, Quincy J. Almeida, Karen Li, Louis Bherer, Richard Camicioli, Manuel Montero‐Odasso

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of AlbertaUniversité de MontréalInstitut Universitaire de Gériatrie de MontréalMontreal Heart InstituteParkwood InstituteWilfrid Laurier UniversityUniversity of CalgaryWomen and Children’s Health Research InstituteHotchkiss Brain InstituteHealth Sciences CentreWestern UniversityUniversity of TorontoLawson Health Research InstituteSunnybrook Health Science CentreConcordia University
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health ResearchConsortium canadien en neurodégénérescence associée au vieillissement
KeywordsGaitDementiaCognitionPhysical medicine and rehabilitationParkinson's diseaseFrontotemporal dementiaPsychologySTRIDEGait DisturbanceCognitive declineNeurodegenerationDiseaseMedicineNeuroscienceInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Gait impairment is common in neurodegenerative disorders. Specifically, gait variability-the stride-to-stride fluctuations in distance and time-has been associated with neurodegeneration and cognitive impairment. However, quantitative comparisons of gait impairments across the cognitive spectrum of dementias have not been systematically investigated. METHODS: Older adults (N = 500) with subjective cognitive impairment, Parkinson disease (PD), mild cognitive impairment (MCI), PD-MCI, Alzheimer's disease (AD), PD-dementia, Lewy body dementia, and frontotemporal dementia, as well cognitive normal controls, who were assessed for their gait and cognitive performance. RESULTS: Factor analyses grouped 11 quantitative gait parameters and identified four independent gait domains: rhythm, pace, variability, and postural control, for group comparisons and classification analysis. Among these domains, only high gait variability was associated with lower cognitive performance and accurately discriminated AD from other neurodegenerative and cognitive conditions. DISCUSSION: Our findings indicate that high gait variability is a marker of cognitive-cortical dysfunction, which can help to identify Alzheimer's disease dementia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.711
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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 teacher head, 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

Citations196
Published2021
Admission routes3
Has abstractyes

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