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Record W2957874784 · doi:10.1093/cid/ciz633

Patterns of Drug and Alcohol Use and Injection Equipment Sharing Among People With Recent Injecting Drug Use or Receiving Opioid Agonist Treatment During and Following Hepatitis C Virus Treatment With Direct-acting Antiviral Therapies: An International Study

2019· article· en· W2957874784 on OpenAlexafffund
Andreea Adelina Artenie, Evan B. Cunningham, Gregory J. Dore, Brian Conway, Olav Dalgård, Jeff Powis, Philip Bruggmann, Margaret Hellard, Curtis Cooper, Philip A. Read, Jordan J. Feld, Behzad Hajarizadeh, Janaki Amin, Karine Lacombe, Catherine Stedman, Alain H. Litwin, Pip Marks, Gail Matthews, Sophie Quiene, Amanda Erratt, Julie Bruneau, Jason Grebely

Bibliographic record

VenueClinical Infectious Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsToronto General HospitalOttawa HospitalVancouver Infectious Diseases CentreRegent Park Community Health CentreUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersNational Institute on Drug AbuseNational Health and Medical Research CouncilCanadian Institutes of Health ResearchNational Institutes of HealthDepartment of Health and Ageing, Australian Government
KeywordsMedicineOmbitasvirDasabuvirParitaprevirRitonavirInternal medicineHepatitis COdds ratioConfidence intervalDrugBuprenorphineHepatitis C virusOpioid use disorderOpioidPharmacologyRibavirinImmunologyVirusViral load

Abstract

fetched live from OpenAlex

BACKGROUND: In many settings, recent or prior injection drug use remains a barrier to accessing direct-acting antiviral treatment (DAA) for hepatitis C virus (HCV) infection. We examined patterns of drug and alcohol use and injection equipment sharing among people with recent injecting drug use or receiving opioid agonist treatment (OAT) during and following DAA-based treatment. METHODS: SIMPLIFY and D3FEAT are phase 4 trials evaluating the efficacy of DAA among people with past 6-month injecting drug use or receiving OAT through a network of 25 international sites. Enrolled in 2016-2017, participants received sofosbuvir/velpatasvir (SIMPLIFY) or paritaprevir/ritonavir/dasabuvir/ombitasvir ± ribavirin (D3FEAT) for 12 weeks and completed behavioral questionnaires before, during, and up to 2 years posttreatment. The impact of time in HCV treatment and follow-up on longitudinally measured longitudinally measured behaviors was estimated using generalized estimating equations. RESULTS: At screening, of 190 participants (mean age, 47 years; 74% male), 62% reported any past-month injecting 16% past-month injection equipment sharing, and 61% current OAT. Median alcohol use was 2 (Alcohol Use Disorders Identification Test-Consumption; range, 1-12). During follow-up, opioid injecting (odds ratio [OR], 0.95; 95% confidence interval [CI], 0.92-0.99) and sharing (OR, 0.87; 95% CI, 0.80-0.94) decreased, whereas no significant changes were observed for stimulant injecting (OR, 0.98; 95% CI, 0.94-1.02) or alcohol use (OR, 0.99; 95% CI, 0.95-1.04). CONCLUSIONS: Injecting drug use and risk behaviors remained stable or decreased following DAA-based HCV treatment. Findings further support expanding HCV treatment to all, irrespective of injection drug use. CLINICAL TRIALS REGISTRATION: SIMPLIFY, NCT02336139; D3FEAT, NCT02498015.

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)0.002
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.054
GPT teacher head0.368
Teacher spread0.314 · 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".

Quick stats

Citations34
Published2019
Admission routes2
Has abstractyes

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