Gait phenotype from mild cognitive impairment to moderate dementia: results from the <scp>GOOD</scp> initiative
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The differences in gait abnormalities from the earliest to the later stages of dementia and in the different subtypes of dementia have not been fully examined. This study aims to compare spatiotemporal gait parameters in cognitively healthy individuals, patients with amnestic mild cognitive impairment (MCI) and non-amnestic MCI, and patients with mild and moderate stages of Alzheimer's disease (AD) and non-Alzheimer's disease (non-AD). METHODS: Based on a cross-sectional design, 1719 participants (77.4 ± 7.3 years, 53.9% female) were recruited from cohorts from seven countries participating in the Gait, Cognition and Decline (GOOD) initiative. Mean values and coefficients of variation of spatiotemporal gait parameters were measured during normal pace walking with the GAITRite system at all sites. RESULTS: Performance of spatiotemporal gait parameters declined in parallel with the stage of cognitive decline from MCI status to moderate dementia. Gait parameters of patients with non-amnestic MCI were more disturbed compared to patients with amnestic MCI, and MCI subgroups performed better than demented patients. Patients with non-AD dementia had worse gait performance than those with AD dementia. This degradation of gait parameters was similar between mean values and coefficients of variation of spatiotemporal gait parameters in the earliest stages of cognitive decline, but different in the most advanced stages, especially in the non-AD subtypes. CONCLUSIONS: Spatiotemporal gait parameters were more disturbed in the advanced stages of dementia, and more affected in the non-AD dementias than in AD. These findings suggest that quantitative gait parameters could be used as a surrogate marker for improving the diagnosis of 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".