Rapid Overlap Initiation Protocol Using Low Dose Buprenorphine for Opioid Use Disorder Treatment in an Outpatient Setting: A Case Series
Bibliographic record
Abstract
OBJECTIVES: Fear and risk of precipitated withdrawal are barriers for initiating buprenorphine in individuals with opioid use disorder, particularly among those using fentanyl. A buprenorphine rapid overlap initiation (ROI) protocol (also knownas "rapidmicro-dosing") utilizing small, escalating doses of buprenorphine can overcome this barrier, reaching therapeutic doses in 3 to 4 days. We sought to demonstrate the feasibility of implementing a buprenorphine ROI protocol for buprenorphine initiation in the outpatient setting. METHODS: We conducted a retrospective chart review of patients prescribed an outpatient ROI protocol at the Office-based Buprenorphine Induction Clinic from October to December 2020. The ROI protocol utilizes divided doses of sublingual buprenorphine tablets and blister packaging for easier dosing. Patients were not required to stop other opioid use and were advised to follow up on day 4 of initiation. RESULTS: Twelve patients were included, of whom eleven (92%) were using fentanyl at intake. Eleven patients picked up their prescription. Seven patients returned for follow-up (58%), and all 7 completed the ROI protocol. One patient reported any withdrawal symptoms, which were mild. At 30 days, 7 patients (58%) were retained in care, and 5 (42%) were still receiving buprenorphine treatment, 4 (33%) of whom had been abstinent from nonprescribed opioid use for ≥2 weeks. CONCLUSIONS: The ROI protocol was successful in initiating buprenorphine treatment for patients in our outpatient clinic, many of whom were using fentanyl. The ROI protocol may offer a safe alternative to traditional buprenorphine initiation and warrants further study.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".