Case series: Symptom‐inhibited fentanyl induction (SIFI) onto treatment‐dose opioid agonist therapy in a community setting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Existing opioid agonist therapy (OAT) guidelines are far from sufficient to address rising opioid tolerances and potency of the unregulated opioid market in North America. Inadequate starting doses of OAT are a universally recognized barrier for people who use fentanyl. Our objectives are to present a novel induction protocol called symptom-inhibiting fentanyl induction (SIFI) that uses rapid intravenous fentanyl administration to inhibit symptoms of opioid withdrawal. METHODS: We describe two cases highlighting the potential clinical utility of SIFI. RESULTS: This case series demonstrates two safe and successful transitions onto higher-than-standard doses of methadone and slow-release oral morphine harnessing an emerging approach of SIFI in a community clinic setting. DISCUSSION AND CONCLUSIONS: These results support emerging evidence that SIFI is safe and feasible to meet patients' opioid requirements and facilitate rotation onto OAT. Further studies are needed to increase the generalizability of these findings. SCIENTIFIC SIGNIFICANCE: Safe transitions onto treatment-dose OAT are of heightened clinical importance at a time when fentanyl and high-potency synthetic opioids are now the norm. SIFI is a novel induction method that could address significant gaps in the currently available OAT options in the fentanyl era.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it