Relationship Between Pain, Opioid Treatment, and Delirium in Older Emergency Department Patients
Bibliographic record
Abstract
OBJECTIVES: Emergency department (ED) stay and its associated conditions (immobility, inadequate hydration and nutrition, lack of stimulation) increase the risk of delirium in older patients. Poorly controlled pain and paradoxically opioid pain treatment have also been identified as triggers for delirium. The aim of this study was to assess the relationship between pain, opioid treatment, and delirium in older ED patients. METHODS: A multicenter prospective cohort study was conducted in four hospitals across the province of Québec (Canada). Patients aged ≥ 65 years old, waiting for hospital admission between March and July 2015, who were nondelirious upon ED arrival, who were independent or semi-independent in their daily living activities, and who had an ED stay of at least 8 hours were included. Delirium assessments were conducted twice a day during the patient's entire ED stay and their first 24 hours on the hospital ward using the Confusion Assessment Method. Pain intensity was evaluated using a visual analog scale (VAS = 0-100) during the initial interview, and all opioid treatments were documented. RESULTS: A total of 338 patients were included; 51% were female, and mean (±SD) age was 77 (±8) years. Forty-one patients (12%) experienced delirium during their hospital stay occurring within a mean (±SD) delay of 47 (±19) hours after ED admission. Among patients with pain intensity ≥ 65 from VAS (0-100), 26% experienced delirium compared to 11% for patients with pain < 65 (p < 0.01), and no significant association was found between opioid consumption and delirium (p = 0.31). Logistic regression controlling for confounding factors showed that patients with pain intensity ≥ 65 are 3.3 (95% confidence interval = 1.4 to 7.9) times more likely to develop delirium than patients who had pain intensity of <65. CONCLUSIONS: Severe pain, not opioids, is associated with the development of delirium during ED stay. Adequate pain control during the hospital stay may contribute to a decrease in delirium episodes.
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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 | 0.003 |
| 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".