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Record W2037298403 · doi:10.1517/14656566.2013.786701

Entecavir for the treatment of patients with hepatitis B virus-related decompensated cirrhosis

2013· review· en· W2037298403 on OpenAlexaff
Matthew D Sadler, Carla S. Coffin, Samuel S. Lee

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2013
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEntecavirMedicineCirrhosisLamivudineHepatocellular carcinomaDecompensationHepatitis BInternal medicineGastroenterologyHepatitis B virusVirologyVirus

Abstract

fetched live from OpenAlex

INTRODUCTION: Chronic hepatitis B (CHB) infection is common and carries a significant risk for the development of cirrhosis, hepatic decompensation, and hepatocellular carcinoma. The goal of treatment in patients with CHB-related decompensated cirrhosis is to improve hepatic dysfunction and reduce mortality through the inhibition of viral replication. Several studies have now shown nucleot(s)ide analogs to be safe and effective in decompensated cirrhosis due to CHB. AREAS COVERED: A review of the evidence for the use of entecavir in the treatment of decompensated hepatitis B cirrhosis is discussed. EXPERT OPINION: Entecavir is an effective treatment option for most patients with CHB. In treatment naïve patients, it is a potent antiviral agent with a very low resistance rate, making it an excellent option for the treatment of decompensated hepatitis B cirrhosis. The use of entecavir monotherapy in patients with a known rtM204V lamivudine-resistant mutation should be avoided due to increased risk of developing entecavir resistance and failing treatment.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.075
GPT teacher head0.402
Teacher spread0.328 · 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 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

Citations4
Published2013
Admission routes1
Has abstractyes

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