Diacetylmorphine versus Methadone for the Treatment of Opioid Addiction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Studies in Europe have suggested that injectable diacetylmorphine, the active ingredient in heroin, can be an effective adjunctive treatment for chronic, relapsing opioid dependence. METHODS: In an open-label, phase 3, randomized, controlled trial in Canada, we compared injectable diacetylmorphine with oral methadone maintenance therapy in patients with opioid dependence that was refractory to treatment. Long-term users of injectable heroin who had not benefited from at least two previous attempts at treatment for addiction (including at least one methadone treatment) were randomly assigned to receive methadone (111 patients) or diacetylmorphine (115 patients). The primary outcomes, assessed at 12 months, were retention in addiction treatment or drug-free status and a reduction in illicit-drug use or other illegal activity according to the European Addiction Severity Index. RESULTS: The primary outcomes were determined in 95.2% of the participants. On the basis of an intention-to-treat analysis, the rate of retention in addiction treatment in the diacetylmorphine group was 87.8%, as compared with 54.1% in the methadone group (rate ratio for retention, 1.62; 95% confidence interval [CI], 1.35 to 1.95; P<0.001). The reduction in rates of illicit-drug use or other illegal activity was 67.0% in the diacetylmorphine group and 47.7% in the methadone group (rate ratio, 1.40; 95% CI, 1.11 to 1.77; P=0.004). The most common serious adverse events associated with diacetylmorphine injections were overdoses (in 10 patients) and seizures (in 6 patients). CONCLUSIONS: Injectable diacetylmorphine was more effective than oral methadone. Because of a risk of overdoses and seizures, diacetylmorphine maintenance therapy should be delivered in settings where prompt medical intervention is available. (ClinicalTrials.gov number, NCT00175357.)
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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 it