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Record W2755304799 · doi:10.1097/adm.0000000000000359

A Case of Opioid Overdose and Subsequent Death After Medically Supervised Withdrawal: The Problematic Role of Rapid Tapers for Opioid Use Disorder

2017· article· en· W2755304799 on OpenAlexafffund
Derek C. Chang, Ján Klimas, Evan Wood, Nadia Fairbairn

Bibliographic record

VenueJournal of Addiction Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsSt. Paul's Hospital
FundersNational Institutes of HealthIrish Research CouncilNational Institute on Drug AbuseCanada Research ChairsEuropean Commission
KeywordsBuprenorphineMedicineOpioid use disorder(+)-NaloxoneMethadoneOpioidOpioid overdoseIntensive care medicineOpioid-Related DisordersDrug overdoseAnesthesiaAgonistNarcotic antagonistsOpiate Substitution TreatmentPartial agonistPsychiatryPoison controlEmergency medicineOpioid epidemicInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Relapse to opioid use is common after rapid opioid withdrawal. As a result, short-term tapers of opioid agonist/partial agonist medications, such as methadone and buprenorphine/naloxone, are no longer recommended by recent clinical care guidelines for the management of opioid use disorder. Nonetheless, rapid tapers are still commonplace in medically supervised withdrawal settings. CASE SUMMARY: We report a case of an individual with opioid use disorder who was prescribed a rapid buprenorphine/naloxone taper in a medically supervised withdrawal facility and who had a subsequent opioid overdose and death after discharge. DISCUSSION: The fatal outcome in this case study underscores the potential severe harms associated with use of rapid tapers. Given the increased overdose risk, tapers should be avoided and continuing care strategies, such as maintenance pharmacotherapy, should be initiated in medically supervised withdrawal settings.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.280
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations15
Published2017
Admission routes2
Has abstractyes

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