An 18-month prospective cohort study of functional outcome of delirium in the elderly /
Bibliographic record
Abstract
4 groups of subjects were followed for 18 months after an emergency department visit: subjects with delirium, dementia, neither, and both. Outcome variables were activities of daily living (ADL), change in ADL, and the status of living at home. Covariates were initial age, sex, marital status, living situation, ADL, cognitive status, type and number of chronic medical conditions, and number of medications. All subjects were living at home prior to their emergency department visit. Unadjusted analyses suggested a trend toward poorer ADL at 6 and 12 months and a significant difference at 18 months in the delirium group versus the non-delirium group of the non-dementia stratum only. Unadjusted analyses showed significantly fewer individuals living at home at 6, 12 and 18 months in the delirium versus the non-delirium group of the non-dementia stratum only. Multivariable linear and logistic regression confirmed the interaction between delirium and dementia for both ADL and living at home. Linear regression adjusting for covariates in the non-dementia stratum suggested that initial ADL and several chronic medical conditions, but not delirium, were independent predictors of ADL outcome. Logistic regression in the non-dementia stratum suggested that several chronic medical conditions and other variables, including delirium, were independent predictors of loss of living at home.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".