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Record W4296799598 · doi:10.1097/adm.0000000000001072

48-hour Induction of Transdermal Buprenorphine to Sublingual Buprenorphine/Naloxone: The IPPAS Method

2022· article· en· W4296799598 on OpenAlexaff
Pouya Azar, James S.H. Wong, Nickie Mathew, Marc Vogel, Jeanmarie Perrone, Andrew A. Herring, Julio Montaner, Mark K. Greenwald, Anil R. Maharaj

Bibliographic record

VenueJournal of Addiction Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsBC Mental Health & Substance Use ServicesProvincial Health Services Authority
Fundersnot available
KeywordsBuprenorphineMedicine(+)-NaloxoneTransdermalOpioid use disorderFentanylAnesthesiaOpioidPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Buprenorphine is an effective medication for the treatment of opioid use disorder. However, the traditional method of buprenorphine induction requires a period of abstinence and the development of at least moderate withdrawal, which can be barriers in starting treatment. We present the case of a hospitalized patient with opioid use disorder using unregulated fentanyl, who underwent a transdermal buprenorphine induction over 48 hours to initiate sublingual buprenorphine/naloxone on the third day. The patient experienced minimal levels of withdrawal and did not experience precipitated withdrawal. The ease of use of this novel induction method over previously published induction protocols can greatly improve the accessibility of buprenorphine for patients and healthcare staff.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.021
GPT teacher head0.314
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations12
Published2022
Admission routes1
Has abstractyes

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