Correlates of cognitive functioning in independent elderly patients discharged home from the emergency department after a minor injury
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to explore correlates of cognitive functioning of older adults visiting the emergency department (ED) after a minor injury. METHODS: These results are derived from a large prospective study in three Canadian EDs. Participants were aged ≥ 65 years and independent in basic activities of daily living, visiting the ED for minor injuries and discharged home within 48 hours (those with known dementia, confusion, and delirium were excluded). They completed the Montreal Cognitive Assessment (MoCA). Potential correlates included sociodemographic and injury variables, and measures of psychological and physical health, social support, mobility, falls, and functional status. RESULTS: Multivariate analyses revealed that male sex, age ≥ 85 years, higher depression scores, slower walking speed, and self-reported memory problems were significantly associated with lower baseline MoCA scores. CONCLUSIONS: These characteristics could help ED professionals identify patients who might need additional cognitive evaluations or follow-ups after their passage through the ED. Obtaining information on these characteristics is potentially feasible in the ED context and could help professionals alter favorably elderly's trajectory of care. Since a significant proportion of elderly patients consulting at an ED have cognitive impairment, the ED is an opportunity to prevent functional and cognitive decline.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".