Gait characteristics under different walking conditions: Association with the presence of cognitive impairment in community-dwelling older people
Bibliographic record
Abstract
BACKGROUND: Gait characteristics measured at usual pace may allow profiling in patients with cognitive problems. The influence of age, gender, leg length, modified speed or dual tasking is unclear. METHODS: Cross-sectional analysis was performed on a data registry containing demographic, physical and spatial-temporal gait parameters recorded in five walking conditions with a GAITRite® electronic carpet in community-dwelling older persons with memory complaints. Four cognitive stages were studied: cognitively healthy individuals, mild cognitive impaired patients, mild dementia patients and advanced dementia patients. RESULTS: The association between spatial-temporal gait characteristics and cognitive stages was the most prominent: in the entire study population using gait speed, steps per meter (translation for mean step length), swing time variability, normalised gait speed (corrected for leg length) and normalised steps per meter at all five walking conditions; in the 50-to-70 years old participants applying step width at fast pace and steps per meter at usual pace; in the 70-to-80 years old persons using gait speed and normalised gait speed at usual pace, fast pace, animal walk and counting walk or steps per meter and normalised steps per meter at all five walking conditions; in over-80 years old participants using gait speed, normalised gait speed, steps per meter and normalised steps per meter at fast pace and animal dual-task walking. Multivariable logistic regression analysis adjusted for gender predicted in two compiled models the presence of dementia or cognitive impairment with acceptable accuracy in persons with memory complaints. CONCLUSION: Gait parameters in multiple walking conditions adjusted for age, gender and leg length showed a significant association with cognitive impairment. This study suggested that multifactorial gait analysis could be more informative than using gait analysis with only one test or one variable. Using this type of gait analysis in clinical practice could facilitate screening for cognitive impairment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".