Canadian Addiction Treatment Centre (CATC) opioid agonist treatment cohort in Ontario, Canada
Bibliographic record
Abstract
PURPOSE: The Canadian Addiction Treatment Centre (CATC) cohort was established during a period of increased provision of opioid agonist treatment (OAT), to study patient outcomes and trends related to the treatment of opioid use disorder (OUD) in Canada. The CATC cohort's strengths lie in its unique physician network, shared care model and event-level data, making it valuable for validation and integration studies. The CATC cohort is a valuable resource for examining OAT outcomes, providing insights into substance use trends and the impact of service-level factors. PARTICIPANTS: The CATC cohort comprises 32 246 people who received OAT prescriptions between April 2014 and February 2021, with ongoing tri-annual updates planned until 2027. The cohort includes data from all CATC clinics' electronic medical records and includes demographic information and OAT clinical indicators. FINDINGS TO DATE: This cohort profile describes the demographic and clinical characteristics of patients being treated in a large OAT physician network. As well, we report the longitudinal OAT retention by treatment type during a time of increasing exposure to a contaminated dangerous drug supply. Notable findings also include retention differences between methadone (32% of patients at 1 year) and buprenorphine (20% at 1 year). Previously published research from this cohort indicated that patient-level factors associated with retention include geographic location, concurrent substance use and prior treatment attempts. Service-level factors such as telemedicine delivery and frequency of urine drug screenings also influence retention. Additionally, the cohort identified rising OAT participation and a substantial increase in fentanyl use during the COVID-19 pandemic. FUTURE PLANS: Future research objectives are the longitudinal evaluation of retention and flexible modelling techniques that account for the changes as patients are treated with OAT. Furthermore, future research aims are the use of conditional models, and linkage with provincial-level administrative datasets.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".