Association of executive function impairment, history of falls and physical performance in older adults: A cross-sectional population-based study in Eastern France
Bibliographic record
Abstract
OBJECTIVE: To estimate: (1) the association between executive function (EF) impairment and falls; and (2) the association of EF impairment on tests of physical function used in the evaluation of fall risk. DESIGN: Cross-sectional study. SETTING: Thirteen health examination centres in Eastern France. PARTICIPANTS: Four thousand four hundred and eighty one community-dwelling older adults without dementia aged 65 to 97 years (mean age 71.8±5.4, women 47.6%). MEASUREMENTS: Participants underwent a comprehensive medical assessment that included evaluations of EF using the Clock Drawing Test and of physical performance using the Timed Up and Go Test (TUG). Analysis used multivariable modified Poisson regression to evaluate the association between impaired EF and each of the fall outcomes (any fall, recurrent falls, fall-related injuries). Multivariable linear regression was used to evaluate the association between EF impairment and performance on the TUG and grip strength. RESULTS: EF impairment, assessed using the clock drawing test, was present in 24.9% of participants. EF impairment was independently associated with an increased risk of any fall (RR=1.13, 95% CI (1.03, 1.25)) and major soft tissue fall-related injury (RR= 2.42, 95% CI (1.47, 4.00)). Additionally, EF impairment was associated with worse performance on the TUG (p<0.0001). CONCLUSIONS: EF impairment among older adults without dementia was highly prevalent and was independently associated with an increased risk for falls, fall-related injuries and with decreased physical function. The use of the Clock Drawing Test is an easy to administer measure of EF that can be used routinely in comprehensive fall risk evaluations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".