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Record W2732324080

Retrospective Analysis of Recurrent HCV Viremia in High-risk HIV Co-infected People Who Inject Drugs (PWID)

2016· article· en· W2732324080 on OpenAlexaboutno aff
Tyler Raycraft, Syune Hakobyan, Sah, Vafadary, Arshia Alimohammadi, G Kiani, Jay Shravah, R Shahi, Brian Conway

Bibliographic record

VenueJournal of Hepatitis · 2016
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsViremiaMedicineInternal medicineHuman immunodeficiency virus (HIV)Retrospective cohort studyHepatitis CImmunologyVirology
DOInot available

Abstract

fetched live from OpenAlex

Background: People who inject drugs (PWID) are overrepresented in the HCV-infected community. Past Canadian guidelines do not advocate HCV treatment of HIV co-infected PWID, fearing reduced AžA¸cA‚cy and recurrent viremia A‚AŒAžr successful treatment, due to ongoing risk behaviours. These factors may be more prominent among those co-infected with HIV. Methods: A Retrospective chart review analysis was performed to identify HIV/HCV co-infected individuals who actively injected drugs within 6 months preceding or during HCV treatment. Information regarding AE‰A‚AEŸAžnAEš cAšA‚rA‚cAEšAžrAAEAEŸcAEI• risk behaviours, HCV treatment, and virologic follow-up post-treatment was collected. Results: We identified 45 HIV/HCV co-infected PWID (mean age 51.9 years, 6.7% female, 57.8% on opiatesubstitution therapy, 66.7% genotype 1, 82.2% treatment naive, 73.3% on interferon-based therapies, and 1.52 person years of follow-up/subject). Following successful HCV therapy, 3 cases of HCV recurrent viremia were identified Conclusion: HCV AnA¨AžcAEŸA½n can be successfully treated in high-risk HIV co-infected individuals. In our unique AEAžAE«nAI• few cases of recurrent viremia were identified in mediumterm follow-up.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.303
Teacher spread0.293 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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