Dosage Regimes in the Prescription of Heroin and Other Narcotics to Chronic Opioid Addicts in Switzerland – Swiss National Cohort Study
Bibliographic record
Abstract
AIMS: Within the guidelines of the research programme on medical prescription of narcotics for opioid addicts (PROVE), heroin, morphine, and methadone were prescribed to heavily opioid addicted individuals in Switzerland since 1994. This contribution analyses the course of dose levels during the treatment period. DESIGN: Naturalistic description of consumed dosages per day and month. SETTING AND PARTICIPANTS: The study describes the dosages prescribed to all individuals who began outpatient treatment in the PROVE programme in Switzerland between 1994 and 1996. MEASUREMENTS: Consumed amount of narcotics per day and the course of dosage of injectable heroin in different treatment regimes. FINDINGS: Heroin was the most frequently prescribed narcotic. Of all consumption days, heroin had been applied in 77% as injection and in 9% in a smokeable form. The mean daily dosage was 474 mg for intravenous application and 993 mg for the smokeable form. Second most frequent was the prescription of oral methadone, in most cases in combination with heroin. The mean amount of daily consumption of oral methadone was 53 mg. There were dosage differences between treatment regimes. During the course of treatment the mean dosage for injectable heroin per day decreased significantly and, depending on the treatment regime, almost linearly. CONCLUSIONS: The significance of heroin dosages in heroin-assisted therapy for treatment outcome should be further explored, especially in the light of the markedly higher dosages in Switzerland compared to the UK. During the treatment period, dosages did not increase but generally decreased, indicating no further increase in tolerance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".