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Gabapentin Use Among Individuals Initiating Buprenorphine Treatment for Opioid Use Disorder

2023· article· en· W4386466943 on OpenAlexaff
Matthew S. Ellis, Kevin Y. Xu, Vítor S. Tardelli, Thiago Marques Fidalgo, Mance E. Buttram, Richard A. Grucza

Bibliographic record

VenueJAMA Psychiatry · 2023
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Center for Advancing Translational SciencesNational Institute on Drug Abuse
KeywordsGabapentinMedicineOpioid use disorderBuprenorphineMedicaidMedical prescriptionRetrospective cohort studyPsychiatryOpioidInternal medicineHealth carePharmacologyAlternative medicine

Abstract

fetched live from OpenAlex

Importance: Gabapentin prescriptions have drastically increased in the US due to off-label prescribing in settings such as opioid use disorder (OUD) treatment to manage a range of comorbid conditions and withdrawal symptoms, despite a lack of evidence. Objective: To assess the purpose and associated risks of off-label gabapentin use in OUD treatment. Design, Setting, and Participants: This retrospective recurrent-event case-control study with a crossover design used administrative claims data from MarketScan Commercial and Multi-State Medicaid databases from January 1, 2006, to December 31, 2016. Individuals aged 12 to 64 years with an OUD diagnosis and filling buprenorphine prescriptions were included in the primary analysis conducted from July 1, 2022, through June 1, 2023. Unit of observation was the person-day. Exposures: Days covered by filled gabapentin prescriptions. Main Outcomes and Measures: Primary outcomes were receipt of gabapentin in the 90 days after initiation of buprenorphine treatment and drug-related poisoning. Drug-related poisonings were defined using codes from International Classification of Diseases, Ninth Revision, and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Results: A total of 109 407 patients were included in the analysis (mean [SD] age, 34.0 [11.2] years; 60 112 [54.9%] male). Among the 29 967 patients with Medicaid coverage, 299 (1.0%) were Hispanic, 1330 (4.4%) were non-Hispanic Black, 23 112 (77.1%) were non-Hispanic White, and 3399 (11.3%) were other. Gabapentin was significantly less likely to be prescribed to Black or Hispanic patients, and more likely to be prescribed to female patients, those with co-occurring substance use or mood disorders, and those with comorbid physical conditions such as neuropathic pain. Nearly one-third of persons who received gabapentin (4336 [31.1%]) had at least 1 drug-related poisoning after initiating buprenorphine treatment, compared with 13 856 (14.5%) among persons who did not receive gabapentin. Adjusted analyses showed that days of gabapentin use were not associated with hospitalization for drug-related poisoning (odds ratio, 0.98 [95% CI, 0.85-1.13]). Drug-related poisoning risks did not vary based on dosage. Conclusions and Relevance: Gabapentin is prescribed in the context of a myriad of comorbid conditions. Even though persons receiving gabapentin are more likely to have admissions for drug-related poisoning, these data suggest that gabapentin is not associated with an increased risk of drug-related poisoning alongside buprenorphine in adjusted analyses. More data on the safety profile of gabapentin in OUD settings are needed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.035
GPT teacher head0.306
Teacher spread0.272 · 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.

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

Citations13
Published2023
Admission routes1
Has abstractyes

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