Periods of altered risk for non-fatal drug overdose: a self-controlled case series
Bibliographic record
Abstract
BACKGROUND: Being recently released from prison or discharged from hospital, or being dispensed opioids, benzodiazepines, or antipsychotics have been associated with an increased risk of fatal drug overdose. This study aimed to examine the association between these periods and non-fatal drug overdose using a within-person design. METHODS: In this self-controlled case series, we used data from the provincial health insurance client roster to identify a 20% random sample of residents (aged ≥10 years) in British Columbia, Canada between Jan 1, 2015, and Dec 31, 2017 (n=921 346). Individuals aged younger than 10 years as of Jan 1, 2015, or who did not have their sex recorded in the client roster were excluded. We used linked provincial health and correctional records to identify a cohort of individuals who had a non-fatal overdose resulting in medical care during this time period, and key exposures, including periods of incarceration, admission to hospital, emergency department care, and supply of medications for opioid use disorder (MOUD), opioids for pain (unrelated to MOUD), benzodiazepines, and antipsychotics. Using a self-controlled case series, we examined the association between the time periods during and after each of these exposures and the incidence of non-fatal overdose with case-only, conditional Poisson regression analysis. Sensitivity analyses included recurrent overdoses and pre-exposure risk periods. FINDINGS: We identified 4149 individuals who had a non-fatal overdose in 2015-17. Compared with unexposed periods (ie, all follow-up time that was not part of a designated risk period for each exposure), the incidence of non-fatal overdose was higher on the day of admission to prison (adjusted incidence rate ratio [aIRR] 2·76 [95% CI 1·51-5·04]), at 1-2 weeks (2·92 [2·37-3·61]), and 3-4 weeks (1·34 [1·01-1·78]) after release from prison, 1-2 weeks after discharge from hospital (1·35 [1·11-1·63]), when being dispensed opioids for pain (after ≥4 weeks) or benzodiazepines (entire use period), and from 3 weeks after discontinuing antipsychotics. The incidence of non-fatal overdose was reduced during use of MOUD (aIRRs ranging from 0·33 [0·26-0·42] to 0·41 [0·25-0·67]) and when in prison (0·12 [0·08-0·19]). INTERPRETATION: Expanding access to and increasing support for stable and long-term medication for the management of opioid use disorder, improving continuity of care when transitioning between service systems, and ensuring safe prescribing and medication monitoring processes for medications that reduce respiratory function (eg, benzodiazepines) could decrease the incidence of non-fatal overdose. FUNDING: Murdoch Children's Research Institute and National Health and Medical Research Council.
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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 | 0.001 | 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 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".