High-dose intravenous hydromorphone for patients who use opioids in the hospital setting: time to reduce the barriers
Bibliographic record
Abstract
Individuals who use opioids have higher rates of hospitalization compared to the general population. Insufficiently treated withdrawal and pain are major factors contributing to high rates of self-initiated hospital discharges (also referred to as leaving against medical advice) in this population. While injectable opioid agonist therapy is limited or unavailable in the majority of Canadian communities, intravenous hydromorphone (IV HM) is widely available in the hospital setting and high-dose IV HM may be a useful treatment adjunct to improve comfort and engagement in inpatient care for some individuals who use opioids. However, major barriers to its use exist including lack of comfort amongst healthcare providers and hospital policies restricting administration. In this commentary, we highlight the potential usefulness of high-dose IV HM as a treatment adjunct for individuals who use opioids in the hospital setting and advocate for expanded hospital policies to facilitate its use.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.023 | 0.020 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".