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Record W2981134481 · doi:10.1111/ajad.12964

Case Series: Limited Opioid Withdrawal With Use of Transdermal Buprenorphine to Bridge to Sublingual Buprenorphine in Hospitalized Patients

2019· article· en· W2981134481 on OpenAlexaff
Victor M. Tang, Jessica Lam‐Shang‐Leen, Thomas D. Brothers, Keith Hansen, Alexander Caudarella, Wiplove Lamba, Tim Guimond

Bibliographic record

VenueAmerican Journal on Addictions · 2019
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsDalhousie UniversityUniversity of TorontoCentre for Addiction and Mental HealthSt. Michael's Hospital
FundersNational Institute on Drug Abuse
KeywordsBuprenorphineMedicineTransdermalOpioidAnesthesiaOpioid use disorderRetrospective cohort studySurgeryInternal medicinePharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: Prerequisite opioid withdrawal symptoms prior to buprenorphine induction are unacceptable to many patients. We assessed whether transdermal buprenorphine minimized withdrawal while bridging to sublingual therapy among hospital inpatients. METHODS: Retrospective chart review of (n = 23) inpatients with opioid use disorder or opioid dependence due to chronic pain. RESULTS: Of 23 inpatients, 65% transitioned without symptoms, while 35% experienced mild withdrawal. Ninety-six percent completed planned hospitalizations, with 83% engaged in treatment 4 weeks post-discharge. DISCUSSION AND CONCLUSIONS: Bridging to sublingual therapy with transdermal buprenorphine patches was feasible without withdrawal symptoms. SCIENTIFIC SIGNIFICANCE: This strategy may facilitate buprenorphine therapy in hospital inpatients. (Am J Addict 2019;00:1-4).

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations29
Published2019
Admission routes1
Has abstractyes

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Same venueAmerican Journal on AddictionsSame topicOpioid Use Disorder TreatmentFrench-language works237,207