Microdosing and standard‐dosing take‐home buprenorphine from the emergency department: A feasibility study
Bibliographic record
Abstract
OBJECTIVE: Emergency department (ED)-initiated buprenorphine may prevent overdose. Microdosing is a novel approach that does not require withdrawal, which can be a barrier to standard inductions. We aimed to evaluate the feasibility of an ED-initiated buprenorphine/naloxone program providing standard-dosing and microdosing take-home packages and of randomizing patients to either intervention. METHODS: We broadly screened patients ≥18 years old for opioid use disorder at a large, urban ED. In a first phase, we provided consecutive patients with 3-day standard-dosing packages, and then we provided a subsequent group with 6-day microdosing packages. In a second phase, we randomized patients to standard dosing or microdosing. We attempted 7-day telephone follow-ups and 30-day in-person community follow-ups. The primary feasibility outcome was number of patients enrolled and accepting randomization. Secondary outcomes were numbers screened, follow-up rates, and 30-day opioid agonist therapy retention. RESULTS: We screened 3954 ED patients and identified 94 with opioid use disorders. Of the patients, 26 (27.7%) declined participation: 10 identified a negative prior experience with buprenorphine/naloxone as the reason, 5 specifically cited precipitated withdrawal, and none cited randomization. We enrolled 68 patients. A total of 14 left the ED against medical advice, 8 were excluded post-enrollment, 21 received standard dosing, and 25 received microdosing. The 7-day and 30-day follow-up rates were 9/46 (19.6%) and 15/46 (32.6%), respectively. At least 5/21 (23.8%) provided standard dosing and 8/25 (32.0%) provided microdosing remained on opioid agonist therapy at 30 days. CONCLUSIONS: ED-initiated take-home standard-dosing and microdosing buprenorphine/naloxone programs are feasible, and a randomized controlled trial would be acceptable to our target population.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".