Prolonged opioid use among opioid-naive individuals after prescription for nonspecific low back pain in the emergency department
Bibliographic record
Abstract
ABSTRACT: Low back pain is a leading cause of disability globally. It is a common reason for presentation to the emergency department where opioids are commonly prescribed. This is a retrospective cohort study of opioid-naive adults with low back pain presenting to 1 of 4 emergency departments in Nova Scotia. We use routinely collected administrative clinical and drug-use data (July 2010-November 2017) to investigate the prevalence of prolonged opioid use and associated individual and prescription characteristics. In total, 23,559 eligible individuals presented with nonspecific low back pain, with 84.4% being opioid-naive. Our study population included 4023 opioid-naive individuals who filled a new opioid prescription within 7 days after their index emergency department visit (24.4%). The prevalence of prolonged opioid use after a new opioid prescription for low back pain (filling an opioid prescription 8-90 days after the emergency department visit and filling a subsequent prescription ±30 days of 6 months) was 4.6% (185 individuals). Older age and female sex were associated with clinically important increased odds of prolonged opioid use. First prescription average >90 morphine milligram equivalents/day (odds ratio 1.6, 95% confidence interval 1.0-2.6) and greater than 7-day supply (1.9, 1.1-3.1) were associated with prolonged opioid use in adjusted models. We found evidence of declining opioid prescriptions over the study period, but that 24.3% of first opioid prescriptions in 2016 would not have aligned with current guideline recommendations. Our study provides evidence to support a cautious approach to prescribing in opioid-naive populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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".