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Record W2753851907 · doi:10.21767/2471-9706.100017

Analysis of Adherence to AllOral HCV Therapy in a Cohort of People who Inject Drugs (PWID)

2017· article· en· W2753851907 on OpenAlexaffabout
R Shahi, Ghazaleh Kiani, Arshia Alimohammadi, Tyler Raycraft, Arpreet Singh, Brian Conway

Bibliographic record

VenueJournal of Hepatitis · 2017
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsVancouver Infectious Diseases Centre
Fundersnot available
KeywordsMedicinePillCohortClinical trialPopulationHepatitis CHuman immunodeficiency virus (HIV)Cohort studyFamily medicineIntensive care medicineInternal medicineEnvironmental healthNursing

Abstract

fetched live from OpenAlex

The majority of prevalent and incident cases of HCV infection in Canada occur among people who inject drugs (PWID). The benefits of more effective and better tolerated all-oral regimens will only be achieved with proper strategies to ensure adherence in this population. We hypothesize that the provision of treatment within a multidisciplinary centre attending to all health care needs will maximize the likelihood of achieving this goal. Within a cohort of 87 patients receiving all oral HCV therapy over a median of 12 weeks, 1135/1150 (98.7%) scheduled weekly appointments were attended, with pill counts reflecting over 90% adherence to therapy. In this model of care, adherence to HCV therapy among PWID met or exceeded the standard established in clinical trials. These data directly address one of the major concerns about increasing availability of HCV treatment among PWID and lend further support to the expansion of such programs in clinical practice.

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 score0.045
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.374
Teacher spread0.336 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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