Prevalence, management and outcomes of unrecognized delirium in a National Sample of 1,493 older emergency department patients: how many were sent home and what happened to them?
Bibliographic record
Abstract
BACKGROUND: Retrospective studies estimate Emergency Department (ED) delirium recognition at <20%; few prospective studies have assessed delirium recognition and outcomes for patients with unrecognized delirium. OBJECTIVES: To prospectively measure delirium recognition by ED nurses and physicians, document their confidence in diagnosis and disposition, actual dispositions, and patient outcomes. METHODS: Prospective observational study of people ≥65 years. We assessed delirium using the Confusion Assessment Method, then asked ED staff if the patient had delirium, confidence in their assessment, if the patient could be discharged, and contacted patients 1 week postdischarge. We report proportions and 95% confidence intervals (Cls). RESULTS: We enrolled 1,493 participants; mean age was 77.9 years; 49.2% were female, 79 (5.3%, 95% CI 4.2-6.5%) had delirium. ED nurses missed delirium in 43/78 cases (55.1%, 95% CI 43.4-66.4%). Nurses considered 12/43 (27.9%) patients with unrecognized delirium safe to discharge. Median confidence in their delirium diagnosis for patients with unrecognized delirium was 7.0/10. Physicians missed delirium in 10/20 (50.0%, 95% CI 27.2-72.8) cases and considered 2/10 (20.0%) safe to discharge. Median confidence in their delirium diagnosis for patients with unrecognized delirium was 8.0/10. Fifteen patients with unrecognized delirium were sent home: 6.7% died at 1 week follow-up vs. none in those with recognized delirium and 1.1% in the rest of the cohort. CONCLUSION: Delirium recognition by nurses and physicians was sub-optimal at ~50% and may be associated with increased mortality. Research should explore root causes of unrecognized delirium, and novel strategies to systematically improve delirium recognition and patient outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".