A call for compassionate opioid overdose response
Bibliographic record
Abstract
• Standard dose naloxone is 0.4 mg intramuscular (IM) or ≤4 mg intranasal (IN). • high dose and long-acting opioid antagonists have no use in overdose response. • people who use drugs should be involved in opioid antagonist development. • harm reduction programs can teach rescue breathing to mitigate withdrawal risk. • withdrawal should be carefully considered in opioid antagonist product selection. High dose and long-acting opioid overdose reversal drugs can precipitate withdrawal in people who are opioid dependent. Products recently brought to market for community use in the United States (US) have drawn international concern because of their increased risk of withdrawal. At the March 18–19, 2024, Compassionate Overdose Response Summit & Naloxone Dosing Meeting, a panel of harm reduction experts issued the following call to action: 1) people who use drugs should be directly involved in decisions regarding the research, development, selection, and distribution of opioid overdose reversal products; 2) regulatory agencies and pharmaceutical manufacturers should carefully consider and communicate the risk and duration of withdrawal associated with higher dose and longer-acting opioid antagonists; 3) take-home naloxone kits should include at least two doses of an intramuscular (IM) product containing 0.4 mg or an intranasal (IN) product containing ≤4 mg; 4) At this time, high dose and long-acting opioid antagonists have no use in acute opioid overdose response; and, 5) overdose response educational materials, instructions on overdose response, and training should emphasize the restoration of breathing, avoiding withdrawal, and compassionate post-overdose support and care. High dose and long-acting opioid overdose reversal drugs were approved without testing for withdrawal and are often aggressively marketed despite decades of evidence from naloxone distribution programs worldwide that the ideal dose of naloxone is one that restores breathing without inducing withdrawal. Government agencies should direct resources to harm reduction programs to make standard dose take-home naloxone products widely available among people who use drugs. Lay bystanders, people who use drugs, their families, and professional first responders can learn and apply a compassionate approach to opioid overdose response.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.040 | 0.029 |
| Insufficient payload (model declined to judge) | 0.201 | 0.078 |
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".