Gait variability across neurodegenerative and cognitive disorders: Results from the Canadian Consortium of Neurodegeneration in Aging (CCNA) and the Gait and Brain Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".