Quantitative gait parameters from MCI to moderate dementia: results from the GOOD initiative (P2.231)
Bibliographic record
Abstract
Background: Gait abnormalities in patients with dementia are common. The quantification of gait parameters from the earliest to the latter stages of dementia and in different type of dementia has been not examined yet. Objective: To compare quantitative gait parameters in cognitively healthy individuals, patients with amnestic (aMCI) and non-amnestic (naMCI) MCI, and patients with mild and moderate stages of Alzheimer’s disease (AD) and non-Alzheimer’s disease (non-AD). Design/Methods: A total of 1719 participants (77.4±7.3 years, 53.9[percnt] female) were included in this cross sectional study from seven countries participating in the “Gait, cOgnitiOn & Decline” initiative. Quantitative gait parameters were measured at self-selected speed with the GAITRite® system at all sites. Results: Mean gait speed declined from 104.7±22.2 cm/s in healthy older adults to 61.7±20.3 cm/s in patients with moderate non-AD dementia. Spatio-temporal gait parameters declined in parallel to the cognitive impairment from MCI status to moderate dementia. Patients with naMCI presented more disturbed gait parameters compared to patients with aMCI. Patients with non-AD dementia had worse gait performance than those with AD dementia. Degradation of the gait parameters was similar between mean values and coefficients of variation of spatio-temporal gait parameters in the earliest stages of cognitive decline, but different in the most advanced stages, especially in the non-AD subtypes. Conclusions/Relevance: Quantitative gait parameters were more disturbed in the advanced stages of dementia, and more affected in the non-AD dementias than in AD. These findings support that quantitative gait parameters could be considered 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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.
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".