Uptake of Low-dose Buprenorphine Initiation and Associated Patient Characteristics in British Columbia, Canada: A Population-based Cohort Study
Bibliographic record
Abstract
OBJECTIVES: To characterize patterns of outpatient buprenorphine induction and examine factors associated with the use of low-dose initiation (LDI). METHODS: A retrospective cohort study of 4510 adults initiating buprenorphine between January 1, 2016 and December 31, 2019 in British Columbia (BC), Canada, was undertaken using linked administrative data in the Provincial Overdose Cohort, which contains a 20% random sample of BC residents. Using multivariable modelling, we examined the association between sociodemographic, co-morbidity, treatment, and health service utilization variables, and the outcome of LDI. Joinpoint analysis was also conducted to assess inflection points in the prevalence of this practice. RESULTS: Overall, 7.2% of included buprenorphine inductions during the study period were classified as LDI. Joinpoint analysis revealed that the percentage of buprenorphine inductions classified as LDI increased significantly beginning in the fourth quarter of 2017. In multivariable analyses, factors positively associated with LDI included: older age (adjusted odds ratio [aOR]: 1.01, 95% CI: 1.00-1.02), living in Vancouver Coastal (aOR: 1.53, 95% CI: 1.13-2.06) and Fraser Health Authority regions (aOR: 2.56, 95% CI: 1.89-3.48) (vs interior region); having been prescribed slow-release oral morphine for opioid use disorder in the last 3 years (aOR: 4.03, 95% CI: 2.51-6.49), and having 1 (aOR: 2.40, 95% CI: 1.80-3.20) or ≥2 (vs 0) opioid agonist treatment episodes in the last 5 years (aOR: 2.56, 95% CI: 1.89-3.48). Factors negatively associated with microinduction included: male sex (aOR: 0.50, 95% CI:0.41-0.61), alcohol use disorder (aOR: 0.62, 95% CI: 0.40-0.96), injection drug use (aOR: 0.75, 95% CI: 0.61-0.94) and past-year incarceration (aOR: 0.19, 95% CI: 0.10-0.33). CONCLUSIONS: The use of LDI has increased in BC in recent years. Markers of treatment experience were positively associated with receipt of LDI. A ssessment of outcomes associated with LDI is needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".