Sentinel surveillance of suspected opioid-related poisonings and injuries: trends and context derived from the electronicCanadian Hospitals Injury Reporting and Prevention Program, March 2011 to June 2017
Bibliographic record
Abstract
INTRODUCTION: The opioid epidemic is currently a major public health problem in Canada. As such, knowledge of upstream risk factors associated with opioid use is needed to inform injury prevention, health promotion and harm reduction efforts. METHODS: We analyzed data extracted from 11 pediatric and 6 general hospital emergency departments (EDs) as part of the electronic Canadian Hospitals Injury Reporting and Prevention Program (eCHIRPP) from March 2011 to June 2017. We identified suspected opioid-related injuries using search strings and manually verified them. We computed age-adjusted and sex-stratified proportionate injury ratios (PIRs) and 95% confidence intervals (CIs) to compare opioid-related injuries to all injuries in eCHIRPP. Negative binomial regression was used to determine trends over time. We conducted qualitative analyses of narratives to identify common themes across life stages. RESULTS: Between March 2011 and June 2017, 583 suspected opioid-related poisoning/ injury cases were identified from eCHIRPP. Most of the cases were females (55%). Many of the injuries occurred in patients' own homes (51%). Forty-five percent of the injuries were intentional self-harm. Among children (aged 1-9 years), most injuries were caused by inadvertent consumption of opioids left unattended. Among youth (aged 10-19 years) and adults (aged 20-49 years), opioid use was associated with underlying mental illness. Overall, the average annual percent change (AAPC) in the rate of injuries (per 100 000 eCHIRPP cases) has been increasing since 2012 (AAPC = 11.9%, p < .05). The increase is particularly evident for males (AAPC = 16.3%, p < .05). Compared to other injuries, people with suspected opioid-related injuries were more likely to be admitted to hospital (PIR = 5.3, 95% CI: 4.6-6.2). CONCLUSION: The upstream determinants of opioid-related injuries are complex and likely vary by subpopulations. Therefore, continued monitoring of risk factors is important in providing the evidence necessary to prevent future overdoses and deaths.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".