Intravenous Fentanyl for Symptom Management in Hospitalized Patients With Refractory Opioid Withdrawal: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVES: Potent synthetic opioids in the drug supply have resulted in patients with increasingly refractory opioid withdrawal syndromes. This study describes patient characteristics and short-term treatment outcomes for a cohort of hospitalized individuals with opioid use disorder (OUD) treated with intravenous fentanyl for opioid withdrawal. METHODS: A retrospective cohort study of inpatients with fentanyl use disorder and refractory opioid withdrawal, treated with intravenous fentanyl at St. Paul's Hospital (Vancouver, Canada) between November 2019 and December 2021. Descriptive variables included sociodemographic factors, substance use history, and fentanyl dosing. Treatment outcomes included retention in the hospital and initiation of medication for opioid use disorder (MOUD). Safety outcomes included opioid toxicity (excessive drowsiness, myoclonus, administration of naloxone, etc) and transfer to a higher level of care. RESULTS: Fifty-nine encounters were identified, consisting of 43 individuals (56% men), with 56% (n = 24) hospitalized with infection. Intravenous fentanyl bolus doses ranged from 250-5000 mcg. In 71% of encounters (n = 42), patients were prescribed 1000 mcg intravenously every 1-2 hours as needed. The average maximum dose received within 24 hours was a median of 6000 mcg (IQR: 3500-10150 mcg). Patients received a median of 9 days of treatment (IQR: 5-16 d). At discharge, 80% of encounters (n = 47) received an MOUD prescription. Opioid toxicity occurred in 19% of encounters (n = 11), including 8% (n = 5) overdoses. All overdose events involved the use of unregulated fentanyl. CONCLUSIONS: Prescribed intravenous fentanyl may support the management of refractory opioid withdrawal for hospitalized patients with severe OUD. Further evaluation of approaches to manage patients with tolerance to fentanyl and other high-potency opioids is a research priority.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".