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Record W4200217608 · doi:10.1002/hep4.1875

Aiming for Functional Cure With Established and Novel Therapies for Chronic Hepatitis B

2021· review· en· W4200217608 on OpenAlexaff
Hannah Choi, Alexander Tonthat, Harry L.A. Janssen, Norah A. Terrault

Bibliographic record

VenueHepatology Communications · 2021
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineAdverse effectHepatitis B virusChronic hepatitisCure rateHepatitis BImmune systemImmunologyVirusIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Chronic hepatitis B virus (HBV) infection remains difficult to cure due to the persistent, self-replenishing nature of the viral genome and impaired host immune responses. Current treatment goals for chronic hepatitis B (CHB) are to prevent or significantly delay liver-related adverse outcomes and death, and two types of treatments are available: nucleos(t)ide analogues (NAs) and interferons (IFNs). NAs effectively suppress HBV replication, and IFNs improve serological response rates, thereby decreasing the risk of adverse outcomes. However, their efficacy in attaining serological responses, especially functional cure (i.e., loss of serum hepatitis B surface antigen), is very limited. Various strategies such as stopping antiviral therapy or combining therapies have been investigated to enhance response, but efficacy is only modestly improved. Importantly, the development of novel direct-acting antivirals and immunomodulators is underway to improve treatment efficacy and enhance rates of functional cure. The present review provides an overview of the treatment goals and indications, the possibility of expanding indications, and the safety and efficacy of different treatment strategies involving established and/or novel therapies as we continue our search for a cure.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.157
GPT teacher head0.387
Teacher spread0.230 · 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 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

Citations45
Published2021
Admission routes1
Has abstractyes

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