Prolonged diacetylmorphine take‐home during the COVID‐19 pandemic—Results of a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Legal regulations for dispensing in Swiss heroin-assisted treatment were relaxed during the COVID-19 pandemic, allowing prolonged take-home of up to 7 days instead of two to reduce patient contact and the risk of infection. Our study aimed to measure the consequences of this new practice. DESIGN, SETTING AND PARTICIPANTS: This was a retrospective cohort study set in Switzerland's largest outpatient centre for opioid agonist therapy. One hundred and thirty-four (72.4%) of the 185 patients receiving oral diacetylmorphine (DAM) participated in the study. MEASUREMENTS: Through the utilization of electronic medication prescription and dispensing software, as well as the electronic medical record, the following data were extracted to explore the potential consequences: dose of DAM, the number of antibiotic therapies, emergency hospitalizations and incarcerations. Age, gender, prescriptions for psychotrophic drugs and additional prescription for injectable DAM were tested to assess an increased risk of losing prolonged take-home privileges. Data in the year since prolonged take-home (period 2) were compared with data from the equivalent prior year (period 1). FINDINGS: DAM take-home was not associated with a change in DAM dose (P = 0.548), the number of emergency hospitalizations (P = 0.186) or the number of incarcerations (P = 0.215); 79.1% of all patients were able to maintain their extended take-home privileges. However, patients who had injectable DAM experienced significant reductions in their prolonged take-home privileges. CONCLUSION: Allowing patients to take home oral diacetylmorphine for up to 7 days as treatment for opioid use disorder does not appear to pose any demonstrable health risk. It is generally manageable for the large majority of patients. However, careful consideration of prolonged take-home for patients with additional injectable diacetylmorphine is recommended, as these patients are more likely to lose take-home privileges.
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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) | 0.000 | 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".