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Record W2883801271 · doi:10.3138/canlivj.1.2.006

Remaining clinical issues in hepatitis C treatment

2018· review· en· W2883801271 on OpenAlexaffvenue
Alexander Wong, Cynthia Tsien, Sarah Mansour, Curtis Cooper

Bibliographic record

VenueCanadian Liver Journal · 2018
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of SaskatchewanOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsRibavirinMedicineHepatocellular carcinomaHepatitis C virusCirrhosisIntensive care medicineHepatitis CLiver diseaseViral hepatitisImmunologyInternal medicineVirus

Abstract

fetched live from OpenAlex

Key advances in the evaluation and treatment of hepatitis C virus (HCV) infection have positively transformed the management and outcomes of those living with this chronic viral infection. Previously difficult-to-cure populations, including those coinfected with HIV infection, now enjoy similarly high success rates with interferon-free, orally administered direct-acting antiviral (DAA) therapies. Nonetheless, relevant unresolved clinical questions remain. The role and impact of viral resistance testing on treatment selection and outcome remain to be fully determined. The consequences of developing resistance while on DAA treatments that ultimately prove unsuccessful requires further evaluation. Optimal HCV management strategies in decompensated liver disease are unclear, and the role for ribavirin in DAA treatment-naïve and treatment-experienced patients is uncertain. A chief concern for those with cirrhosis relates to the risk for de novo and recurrent hepatocellular carcinoma among DAA recipients. In this article, we present and interpret current data and consider pragmatic, clinically useful options.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.278
GPT teacher head0.499
Teacher spread0.221 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2018
Admission routes2
Has abstractyes

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