The 6 and 12 month outcomes of older medical inpatients who recover from delirium
Bibliographic record
Abstract
OBJECTIVE: To compare the 6 and 12 month outcomes of patients who recovered from delirium by 8 weeks with those who did not have an index episode. METHODS: Older medical inpatients were assessed for delirium using the Confusion Assessment Method. All patients with delirium and a sample of patients without delirium were enrolled. Recovery from delirium at 8 weeks was determined using the Delirium Index and an algorithm based on DSM-III-R criteria. The primary composite outcome was cognitive or functional decline, institutional residence or death at 6 and 12 months. We fitted two logistic regression models to predict outcome odds ratio (OR) of delirium-recovered vs no delirium groups, adjusting for co-morbidity, severity of physical illness and demographic variables. In secondary analyses, we examined each component of the primary outcome separately. RESULTS: Of 361 patients enrolled, 59 died, 33 withdrew and one was lost to follow-up before 8 weeks. Of 268 patients assessed at 8 weeks, 115 and 95 were in delirium-recovered and no delirium groups, respectively. The 6 month OR for the primary composite outcome was 0.89 (95% CI 0.46, 1.70); the 12 month OR was 1.5 (95% CI 0.77, 2.90). Secondary analyses revealed a clinically important increase in mortality at 6 and 12 months. CONCLUSION: Among patients who survived, there were no significant differences in cognition, function or institutional status between delirium-recovered and no delirium groups at 6 and 12 months. If replicated, these findings have potentially important implications for clinical practice and research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".