Everyday Stepping Quantity and Quality Among Older Adult Fallers With and Without Mild Cognitive Impairment: Initial Evidence for New Motor Markers of Cognitive Deficits?
Bibliographic record
Abstract
Background: Recent work demonstrated that the gait of people with mild cognitive impairment (MCI) differs from that of age-matched controls and, in general, that walking ability, as measured in the clinic, does not necessarily reflect actual, daily performance. We evaluated if the quantity and quality of everyday walking (ie, community ambulation) differs in older adults with MCI, compared to age-matched controls. Methods: Inclusion criteria included: age 65-90 years, able to walk at least 5 minutes unassisted, and ≥2 falls in the past 6 months. Subjects with MCI were included if they scored 0.5 on the Clinical Dementia Rating Scale. To assess stepping quantity and quality, subjects wore a tri-axial accelerometer on the lower-back for 7 days. Results: Age and gender were similar (p > .10) in MCI (n = 36, 77.8 ± 6.4 years; 27.8% men) and controls (n = 100, 76.0 ± 6.2 years; 22.0% men). As expected, Montreal Cognitive Assessment scores were lower (p < .001) in MCI (21.31 ± 4.05), compared to controls (25.81 ± 2.64). Walking time was lower (p = .016) in MCI (0.74 ± 0.48 hours/d), compared to controls (1.05 ± 0.66 hours/d). Within-bout walking (eg, stride regularity) was less consistent (p = .024) in MCI (0.51 ± 0.14), compared to controls (0.58 ± 0.14). Changes in stride regularity across bouts were lower (p < .001) in MCI (0.13 ± 0.04), compared to controls (0.17 ± 0.01). Conclusions: Older adults with MCI walk less and with a more variable within-bout and less variable across-bout walking pattern, as compared to cognitively-intact subjects matched with respect to age and gender. These findings extend previous clinical work and suggest that MCI affects both the quantity and quality of community ambulation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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 | 0.000 |
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".