Methadone maintenance treatment and mortality in people with criminal convictions: A population-based retrospective cohort study from Canada
Bibliographic record
Abstract
BACKGROUND: Individuals with criminal histories have high rates of opioid dependence and mortality. Excess mortality is largely attributable to overdose deaths. Methadone maintenance treatment (MMT) is one of the best evidence-based opioid substitution treatments (OSTs), but there is uncertainty about whether methadone treatment reduces the risk of mortality among convicted offenders over extended follow-up periods. The objective of this study was to investigate the association between adherence to MMT and overdose fatality as well as other causes of mortality. METHODS AND FINDINGS: We conducted a retrospective cohort study involving linked population-level administrative data among individuals in British Columbia (BC), Canada with a history of conviction and who filled a methadone prescription between January 1, 1998 and March 31, 2015. Participants were followed from the date of first-dispensed methadone prescription until censoring (date of death or March 31, 2015). Methadone was divided into medicated (methadone was dispensed) and nonmedicated (methadone was not dispensed) periods and analysed as a time-varying exposure. Hazard ratios (HRs) with 95% CIs were estimated using multivariable Cox regression to examine mortality during the study period. All-cause and cause-specific mortality rates were compared during medicated and nonmedicated methadone periods. Participants (n = 14,530) had a mean age of 34.5 years, were 71.4% male, and had a median follow-up of 6.9 years. A total of 1,275 participants died during the observation period. The overall all-cause mortality rate was 11.2 per 1,000 person-years (PYs). Participants were significantly less likely to die from both nonexternal (adjusted HR [AHR] 0.27 [95% CI 0.23-0.33]) and external (AHR 0.41 [95% CI 0.33-0.51]) causes during medicated periods, independent of sociodemographic, criminological, and health-related factors. Death due to infectious diseases was 5 times lower (AHR 0.20 [95% CI 0.13-0.30]), and accidental poisoning (overdose) deaths were nearly 3 times lower (AHR 0.39 [95% CI 0.30-0.50]) during medicated periods. A competing risk regression demonstrated a similar pattern of results. The use of a Canadian offender population may limit generalizability of results. Furthermore, our observation period represents community-based methadone prescribing and may omit prescriptions administered during hospital separations. Therefore, the magnitude of the protective effects of methadone from nonexternal causes of death should be interpreted with caution. CONCLUSIONS: Adherence to methadone was associated with significantly lower rates of death in a population-level cohort of Canadian convicted offenders. Achieving higher rates of adherence may reduce overdose deaths and other causes of mortality among offenders and similarly marginalized populations. Our findings warrant examination in other study centres in response to the crisis of opiate-involved deaths.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".