Incidence of mortality due to rebound toxicity after ‘treat and release’ practices in prehospital opioid overdose care: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Death due to opioid overdose was declared a public health crisis in Canada in 2015. Traditionally, patients who have overdosed on opioids that are managed by emergency medical services (EMS) are treated with the opioid antagonist naloxone, provided ventilatory support and subsequently transported to hospital. However, certain EMS agencies have permitted patients who have been reversed from opioid overdose to refuse transport, if the patient exhibits capacity to do so. Evidence on the safety of this practice is limited. Therefore, our intent was to examine the available literature to determine mortality and serious adverse events within 48 hours of EMS treat and release due to suspected rebound opioid toxicity after naloxone administration. METHODS: A systematic search was performed on 11 May 2017 in PubMed, Cochrane Central, Embase and CINHAL. Studies that reported on the outcome of patients treated with prehospital naloxone and released at the scene were included. Analyses for incidence of mortality and adverse events at the scene were conducted. Risk of bias and assessment of publication bias was also done. RESULTS: 1401 records were screened after duplicate removal. Eighteen full-text studies were reviewed with seven selected for inclusion. None were found to be high risk of bias. In most studies, heroin was the source of the overdose. Mortality within 48 hours was infrequent with only four deaths among 4912 patients ﴾0.081%﴿ in the seven studies. Only one study reported on adverse events and found no incidence of adverse events from their sample of 71 released patients. CONCLUSION: Mortality or serious adverse events due to suspected rebound toxicity in patients released on scene post-EMS treatment with naloxone were rare. However, studies involving longer-acting opioids were rare and no study involved fentanyl.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".