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Prescribing Characteristics Associated With Opioid Overdose Following Buprenorphine Taper

2022· article· en· W4297997280 on OpenAlexaffabout
Nikki Bozinoff, Siyu Men, Paul Kurdyak, Peter Selby, Tara Gomes

Bibliographic record

VenueJAMA Network Open · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsSt. Michael's HospitalPublic Health OntarioUniversity of TorontoInstitute for Clinical Evaluative SciencesCentre for Addiction and Mental Health
FundersNational Institute on Drug Abuse
KeywordsBuprenorphineMedicineDiscontinuationRetrospective cohort studyHazard ratioOpioid overdoseOpioidPopulationCohort studyEmergency medicineAnesthesia(+)-NaloxoneInternal medicineConfidence intervalEnvironmental health

Abstract

fetched live from OpenAlex

Importance: Retention in buprenorphine therapy is associated with a lower risk of opioid overdose. Nevertheless, many patients discontinue treatment, and there is limited evidence to guide buprenorphine tapering. Objective: To understand what prescribing characteristics are associated with opioid overdose following buprenorphine taper. Design, Setting, and Participants: This is a population-based, retrospective, cohort study of adults who were maintained on buprenorphine for at least 60 days and underwent a buprenorphine taper. The study was conducted in the Canadian province of Ontario, using linked administrative health data. New buprenorphine treatment episodes were accrued between January 1, 2013, and January 1, 2019, and the maximum follow-up was April 30, 2020. Data analysis was performed from December 2020 to August 2022. Exposures: The primary exposure of interest was time to taper initiation (≤1 year vs >1 year). Secondary exposures included mean rate of taper, percentage days during which the dose was decreasing, and taper duration. Main Outcomes and Measures: The primary outcome measure was time to fatal or nonfatal opioid overdose within 18 months following treatment discontinuation. Results: Among 5774 individuals, the median (IQR) age at index date was 34 (28-44) years, and 3462 individuals (60.0%) were male. Time to taper initiation longer than 1 year vs 1 year or less (6.73 vs 10.35 overdoses per 100 person-years; adjusted hazard ratio [aHR], 0.69; 95% CI, 0.48-0.997), a lower mean rate of taper (≤2 mg per month, 6.95 overdoses per 100 person-years; >2 to ≤4 mg per month, 11.48 overdoses per 100 person-years; >4 mg per month, 17.27 overdoses per 100 person-years; ≤2 mg per month vs >4 mg per month, aHR, 0.65; 95% CI, 0.46-0.91; >2 to ≤4 mg per month vs >4 mg per month, aHR, 0.69; 95% CI, 0.51-0.93), and dose decreases in 1.75% or less of days vs more than 3.50% of days during the taper period (5.87 vs 13.87 overdoses per 100 person-years; aHR, 0.64; 95% CI, 0.43-0.93) were associated with reduced risk of opioid overdose; however, taper duration was not. Conclusions and Relevance: In this retrospective cohort study, buprenorphine tapers undertaken after at least 1 year of therapy, a slower rate of taper, and a lower percentage of days during which the dose was decreasing were associated with a significantly lower risk of opioid overdose, regardless of taper duration. These findings underscore the importance of a carefully planned taper and could contribute to reduction in opioid-related overdose death.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.573

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.259
Teacher spread0.241 · 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 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".

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Citations13
Published2022
Admission routes2
Has abstractyes

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