High correlations between levels of consumption and mortality related to strong prescription opioid analgesics in British Columbia and Ontario, 2005 – 2009
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
PURPOSE: Prescription opioid analgesic (POA)-related burden of disease - including mortality - is high and constitutes a major public health problem in the US and Canada. Associations between the overall levels of POA consumption and key related morbidity indicators in the population have been demonstrated. We examined potential correlations between levels of consumption of four commonly used POAs and related mortality in British Columbia (BC) and Ontario. METHODS: We investigated the correlation between annual population standardized rates of fentanyl, hydromorphone, morphine and oxycodone-related mortality (based on provincial coroners' data) and the annual Defined Daily Doses per 1000 population/day for each of the drugs dispensed (based on representative retail pharmacy sales data) in the two provinces, 2005-2009. RESULTS: Death rates increased for three (Ontario) and two (BC) of the four POA drugs; the rate of deaths for each POA drug was consistently higher in the jurisdiction with higher use levels. For each drug, strong correlations (range 0.83 to 0.97; p < 0.003) were found between POA use and mortality levels; consistent within-province correlations were found for two drugs (hydromorphone and oxycodone). CONCLUSIONS: Our findings of strong correlations between select POA use and mortality levels reflect similar evidence from elsewhere on correlations between POA consumption and morbidity or mortality indicators. In the context of high and increasing levels of POA consumption in Canada, efforts to reduce POA-related mortality may require a comprehensively revised approach towards more appropriate and safer prescribing to reduce POA use volumes together with more effective monitoring of POA medications.
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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 | 0.001 | 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) | 0.001 | 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 it