Delirium in Older Emergency Department Patients Discharged Home: Effect on Survival
Bibliographic record
Abstract
OBJECTIVES: To determine whether prevalent delirium is an independent predictor of mortality in older patients seen in emergency departments (EDs) and discharged home without admission. DESIGN: Prospective study with 18 months of follow-up. SETTING: EDs in two Montreal hospitals. PARTICIPANTS: From a cohort study of prognosis for delirium (107 delirious and 161 nondelirious subjects), 30 delirious and 77 nondelirious subjects aged 66 and older who were discharged home without admission were identified. MEASUREMENTS: Detailed interviews with patients and their proxies and review of medical charts were performed at enrollment. Trained lay interviewers determined delirium status using the Confusion Assessment Method. Subjects were followed up at 6-month intervals for a total of 18 months. Dates of death were obtained from the Ministère de la Santé et des Service Sociaux (Ministry of Health and Social Services). Survival analysis was performed using the Cox proportional hazards modeling adjusting for potential confounding variables. RESULTS: The analysis revealed a statistically significant association between delirium and mortality after adjustments for age, sex, functional level, cognitive status, comorbidity, and number of medications for the first 6 months of follow-up (hazard ratio = 7.24; 95% confidence interval = 1.62-32.35). The subjects whose delirium was not detected by the ED physician or nurse had the highest mortality over 6 months (30.8%). The mortality of delirious subjects detected in the ED was similar to that of the nondelirious subjects (11.8 vs 14.3%). CONCLUSION: The results of this study suggests that nondetection of delirium in the ED may be associated with increased mortality within 6 months after discharge. Further research is necessary to examine the effectiveness of improving detection on subsequent prognosis of older patients with delirium.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".