Overdose Risk and Acquiring Opioids for Nonmedical Use Exclusively from Physicians in Vancouver, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background A primary response to the alarming rise in overdose and mortality due to nonmedical prescription opioid (PO) use has been to restrict opioid prescribing; however, little is known about the relationship between obtaining opioids from a physician and overdose risk among people who use POs nonmedically and illicit street drugs. Objectives: Investigate the relationship between non-fatal overdose and acquiring POs exclusively from physicians for the purposes of engaging in nonmedical PO use. Methods: Data were collected between 2013 and 2016 among participants in two harmonized prospective cohort studies of people who use drugs in Vancouver: the At-Risk Youth Study (ARYS) and the Vancouver Injection Drug Users Study (VIDUS). Analyses were restricted to participants who engaged in nonmedical PO use and used generalized estimating equations. Results: Among 599 participants who used POs nonmedically, 82 (14%) individuals reported acquiring POs exclusively from a physician and 197 (33%) experienced a non-fatal overdose at some point over the study period. Acquiring POs exclusively from physicians was significantly and negatively associated with non-fatal overdose in the bivariate analysis (Odds Ratio = 0.60, 95% Confidence Interval (CI): 0.39–0.94) but not the final multivariate analysis (Adjusted Odds Ratio =0.87, 95% CI: 0.53–1.44). Conclusions: Compared to individuals who acquired POs from friends or the streets, participants who acquired POs exclusively from a physician were not at an increased risk of non-fatal overdose. Although responsible opioid prescribing is an important priority, additional strategies to address nonmedical PO use are urgently needed to reduce overdose and related morbidity and mortality.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it