Quantity of opioids consumed following an emergency department visit for acute pain: a Canadian prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Prescription opioid diversion is a significant contributor to the opioid misuse epidemic. We examined the quantity of opioids consumed by emergency department (ED) discharged patients after treatment for an acute pain condition (musculoskeletal, fracture, renal colic, abdominal pain and other), and the percentage of unused opioids available for potential misuse. DESIGN: Prospective cohort study. SETTING: Tertiary care trauma centre academic hospital. PARTICIPANTS: A convenience sample of patients ≥18 years who visited the ED for an acute pain condition (≤2 weeks) and were discharged with an opioid prescription. Patients completed a 14-day paper diary of daily pain medication use. To reduce lost to follow-up, participants also responded to standardised phone interview questions about their previous 14-day pain medication use. OUTCOMES: Quantity of morphine 5 mg tablets (or equivalent) prescribed, consumed and unused during a 14-day follow-up. Quantity of opioids to adequately supply 80% of patients for 2 weeks and 95% of patients for the first 3 days was also calculated. RESULTS: Results for 627 patients were analysed (mean age ±SD: 51±16 years, 48% women). Patients consumed a median of seven tablets of morphine 5 mg (32% of the total prescribed opioids). The quantity of opioids to adequately supply 80% of patients for 2 weeks was 20 tablets of morphine 5 mg for musculoskeletal pain, 30 for fracture, 15 for renal colic or abdominal pain and 20 for other pain conditions. The quantity to adequately supply 95% of patients for the first 3 days was 15 tablets of morphine 5 mg. CONCLUSIONS: Patients discharged from the ED with an acute pain condition consumed a median of fewer than 10 tablets of morphine 5 mg (or equivalent). ED physicians should consider prescribing a smaller quantity of opioids and asking the pharmacist to dispense them in portions to minimise unused opioids. TRIAL REGISTRATION NUMBER: NCT02799004; Results.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".