Surveillance for Opioid-Associated Amnestic Syndrome in Canada, 2010-2022
Bibliographic record
Abstract
Abstract Objectives A single diagnostic code could be used to perform surveillance for opioid-associated amnestic syndrome (OAS) in healthcare datasets on a national scale. Methods A request was submitted to search the Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) in Canada for the ICD-10-CA code, F11.6 (mental and behavioural disorders due to use of opioids, amnesic syndrome) during fiscal years (FY) 2010-2011 through 2022-2023. The annual total of encounters using this code was determined and crude rates per million were calculated for the Canadian population represented. Results National counts from DAD and NACRS combined ranged from <5 to 14 annually. Rates per million for available years fell between 0.17 and 0.48. For available data through FY 2015-2016, the mean number of annual combined encounters nationally was 6.3; for those years after, the mean was 10. The mean rate per million was 0.23 and 0.35 for these two periods, respectively. Discussion This study represents the first effort to conduct surveillance for OAS on a national scale and suggests that the condition is relatively rare. Future efforts to validate the coded diagnosis of OAS with confirmed cases will help determine its value as a surveillance tool.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".