Implementation of time-limited parenteral hydromorphone in people with treatment-resistant injecting opioid use disorder: a protocol for a single-site, uncontrolled, open-label study to assess feasibility, safety and cost
Bibliographic record
Abstract
INTRODUCTION: Supervised injectable opioid treatment (SIOT) is an evidence-based intervention targeting opioid-dependent people for whom existing treatments have been ineffective. This project will primarily assess the feasibility and the acceptability of time-limited SIOT using injectable hydromorphone delivered in an existing Australian public opioid treatment programme, with secondary outcomes of safety, cost, changes in drug use and other health outcomes. If feasible, the goal is to scale up the intervention to be more widely available in Australia. METHODS AND ANALYSIS: Between 20 and 30 participants will be offered two times per day hydromorphone to inject under direct observation, in addition to their current opioid agonist treatment (OAT), for up to 2 years. At the end of 2 years of supervised hydromorphone treatment, participants will be continued on standard OAT only. Informed consent will be obtained from all participants included in the study. This is a single-site, uncontrolled, open-label study where quantitative and qualitative interview data will be collected at baseline, 12 months and lastly at 3 months following their final hydromorphone dose. The main outcome measures are feasibility, as assessed by recruitment, retention and participation in treatment, and acceptability to participants, clinic staff and other stakeholders assessed by qualitative interviews. Secondary outcome measures of safety, as assessed by adverse events, and cost will also be assessed, as well as a range of other drug and health outcomes. ETHICS AND DISSEMINATION: This study received ethical approval from the St Vincent's Hospital Human Research Ethics Committee (2019/ETH00418). This will be the first study of time-limited SIOT in the Australian setting. All results will be submitted to peer-reviewed journals, scientific conferences and local practice meetings. A preliminary report on outcomes will also be presented to local health policy makers. A consumer and community forum will also be held to feedback results to a broader audience. TRIAL REGISTRATION NUMBER: ACTRN12621001729819.
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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 | 0.049 | 0.029 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.036 | 0.010 |
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".