NOVEL MEASURES OF BENZODIAZEPINE & Z-DRUG UTILISATION TRENDS IN A CANADIAN PROVINCIAL ADULT POPULATION (2001-2016 )
Bibliographic record
Abstract
PURPOSE: 1) To evaluate trends for benzodiazepines (BZD) and Z-Drugs over 15-years in a general Canadian adult population measured by: a) consumption b) pharmacologic exposure c) dose intensity and d) prevalence of use. 2) To demonstrate the utility of Diazepam Milligram Equivalence (DME) based measurements when used in conjunction with traditional standard measurements of drug utilization such as the Defined Daily Dose (DDD) system. METHODS: Administrative data covering all prescriptions from April 2001-March 2016 for BZD and Z-Drugs for patients ≥18 years was used. Consumption was calculated as DDD/1000-person days. Dose intensity (DI) was determined by conversion of individual daily doses to Diazepam Milligram Equivalents (DME). Pharmacologic exposure (PE) was calculated as DME-DDD/1000-person days. Prevalence was determined as the proportion of the adult population with receipt of ≥1 prescription in a given year. Changes were assessed using either Poisson or simple linear regression at an alpha of 0.05. RESULTS: Z-Drug usage (~99% zopiclone) statistically increased on every measure over the course of the study period; consumption (8.2 to 28.6 DDD/1000-person days), PE (4.1 to 14.3 DME-DDD/1000-person days), DI (5.0 to 5.43 DME/day) and prevalence (2.0% to 4.8%). For BZD the only statistically significant changes were in DI (17.1 to 20.1 DME/day) and prevalence (9.3% to 8.1%). Consumption and PE gradually increased from 2001 to 2011 for BZD before declining thus producing a non-significant trend for BZD. CONCLUSION: 1) Z-Drug usage increased markedly from 2001 to 2016 whereas BZD use only increased in terms of DI. 2) DME-based measurements enable further interpretation of BZD utilization compared to sole reliance on DDD.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".