The association between non-concordance with the Canadian guideline for safe and effective use of opioids in chronic non-cancer pain and opioid overdose death in Quebec
Bibliographic record
Abstract
Background: In Canada, the United States of America (U.S.A), and many other regions world-wide, more and more people are dying of prescription opioid analgesic (POA) overdose death. The death rate from POA overdose has quadrupled in the U.S.A. since 1999 and tripled in Ontario. These pharmaceuticals remain useful and important tools in the practice of medicine, although many have suggested changes to prescribing behavior should be among the intervention strategies to curb this epidemic. Canadian physicians wish to minimize overdose and other opioid related-harms while using these medications to optimal clinical effectiveness. To assist physicians in achieving this balance, a national collaboration examined evidence and published the Canadian Guideline for Safe and Effective use of Opioids in Non-Cancer Pain (CGCNCP) in 2010. We retrospectively assessed if non-concordance with prescription characteristic recommendations given in this guideline was predictive of overdose death. Methods: Using a nested-case control design within the public health insurance cohort of Quebec from 2001-2010, we examined the relationship between death from opioid overdose and dispensed opioid prescriptions non-concordant with recommendations in the CGCNCP. Cases meeting criteria for prescription opioid overdose death were identified through provincial coroner and death certificate data and were restricted to individuals with pharmaceutical insurance from the Régie d'Assurance Maladie du Québec (RAMQ) in the 210 days prior to overdose death. Individuals with an active cancer diagnosis were excluded because of substantial differences in prescribing recommendations in cancer-related pain management. Controls were sampled randomly from time, age, and sex matched individuals in the same cohort and subject to the same inclusion criteria. Non-concordance was assessed through longitudinal analysis of data on prescriptions dispensed in the 180 days prior to case death. We used conditional logistic regression to estimate the magnitude of the relationship between number of non-concordance events and overdose death. Results: Five hundred people who died of POA overdose while covered by RAMQ pharmaceutical insurance were dispensed at least one POA in the 180 days prior to death, of which 73 had an age, sex, and time-matched control who had also been dispensed at least one POA in the same period. There were 1,326 dispensed opioid prescriptions among cases, with a total of 375 non-concordant events, and 469 dispensed opioid prescriptions among controls, with a total of 111 non-concordant events. In multivariate analysis, POA overdose death was associated with the number of dispensed benzodiazepine prescriptions (aOR 2.91; 95% CI 1.21-7.00), and opioid prescriptions (aOR 1.20; 95% CI 1.02-1.40), as well as initiating opioid therapy with an extended release formulation (aOR 6.38; 95% CI 1.07-37.94). Total number of non-concordance events was not significantly associated with POA overdose death (aOR 1.03; 95% CI 0.88-1.21). Interpretation: Increased numbers of dispensed opioid and benzodiazepine prescriptions are important risk factors for POA overdose death in Quebec. Prescription of extended release opioids to opioid naïve patients is significantly associated with increased odds of POA overdose death; prescribers should initiate therapy using immediate release formulations and transition patients to extended release when stable dosing is established. Further study with a larger number of cases is needed to determine whether non-concordance with additional CGCNCP recommendations is associated with POA overdose death.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".