Reduced adaptability to balance perturbations in older adults with probable cognitive impairment after a severe fall
Bibliographic record
Abstract
Falls in older individuals often result from unexpected balance disturbances during walking, necessitating the analysis of recovery strategies for effective falls prevention. This becomes particularly crucial for individuals with cognitive impairment, who face a higher fall risk compared to cognitively healthy adults. Hence, our study aimed to compare the recovery response to standardized walking perturbations on a treadmill between older adults with cognitive impairment and cognitively healthy older adults. 36 individuals with a recent history of a severe fall, leading to an emergency department visit without subsequent admission, were stratified into two groups (with and without probable cognitive impairment) based on scores of the Montreal Cognitive Assessment. Recovery performance was quantified using force plate data from a perturbation treadmill (M-Gait, Motek Medical B.V., Amsterdam, the Netherlands), specifically evaluating the number of steps needed to restore step length and width to pre perturbation baseline across two trials of nine different perturbations. Individuals with cognitive impairment (n = 18, mean age: 74.7) required significantly (p = 0.045, Cohen's d = 0.69) more steps to recover total steps after perturbations compared to cognitively healthy individuals (n = 18, mean age: 69.7). While step width recovery was similar between the groups, those with probable cognitive impairment required significantly more steps to recover their step length (p = 0.039, Cohen's d = 0.72). Thus, our findings indicate that older adults with probable cognitive impairment manifest inferior gait adaptability, especially in adapting step length, potentially underscoring a critical aspect for effective falls prevention in this population.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".