Accuracy of a self-report prescription opioid use diary for patients discharge from the emergency department with acute pain: a multicentre prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Self-reported approaches that assess opioid usage can be subject to social desirability and recall biases that may underestimate actual pill consumption. Our objective was to determine the accuracy of patient self-reported opioid consumption using a 14-day daily paper or electronic diary. DESIGN: Prospective cohort study. SETTING: Multicentre study conducted in four Québec (Canada) emergency departments (ED): three university-affiliated centres, two of them Level I trauma centres and one urban community hospital. PARTICIPANTS: ED patients aged ≥18 years with acute pain (≤2 weeks) who were discharged with an opioid prescription. Patients completed a 14-day daily diary (paper or electronic) assessing the quantity of opioids consumed. On diary completion, a random sample from the main cohort was selected for a follow-up visit to the hospital or a virtual video visit where they had to show and count the remaining pills. Patients were blinded to the main objective of the follow-up visit. OUTCOMES: Quantity of opioid pills consumed during the 2-week follow-up period self-reported in the 14-day diary (paper or electronic) and calculated from remaining pills counted during the follow-up visit. Intraclass correlation coefficient (ICC) and Bland-Altman plots were used to assess accuracy. RESULTS: A total of 166 participants completed the 14-day diary as well as the in-person or virtual visit; 49.4% were women and median age was 47 years (IQR=21). The self-reported consumed quantity of opioid in the 14-day diary and the one calculated from counting remaining opioid pills during the follow-up visit were very similar (ICC=0.992; 95% CI: 0.989 to 0.994). The mean difference between both measures from Bland-Altman analysis was almost zero (0.048 pills; 95% CI: -3.77 to 3.87). CONCLUSION: Self-reported prescription opioid use in a 14-day diary is an accurate assessment of the quantity of opioids consumed in ED discharged patients. TRIAL REGISTRATION NUMBER: NCT03953534.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".