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Treatment of HBeAg‐positive patients with nucleos/tide analogues

2009· review· en· W2053868208 on OpenAlexaff
Carla S. Coffin, Samuel S. Lee

Bibliographic record

VenueLiver International · 2009
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEntecavirAdefovirTelbivudineLamivudineMedicinePegylated interferonHepatocellular carcinomaEmtricitabineHepatitis BInternal medicineHBeAgHepatitis B virusVirologyImmunologyChronic hepatitisVirusHBsAgRibavirin

Abstract

fetched live from OpenAlex

The two main goals of hepatitis B therapy are durable viral suppression and avoidance of antiviral resistance. Recent treatment guidelines now recognize the importance of these treatment endpoints in the prevention of end-stage liver disease and hepatocellular carcinoma rather then other surrogate markers such as HBeAg seroconversion and serum alanine aminotransferase normalization, especially in patients who acquired hepatitis B virus infection early in life. A variety of therapeutic options are now available for the treatment of chronic hepatitis B infection, including four nucleos/tide analogues (i.e lamivudine, adefovir, entecavir and telbivudine), along with standard and pegylated interferon. Newer oral nucleos/tide analogues that include tenofovir, emtricitabine and clevudine are soon likely to be approved worldwide. Given the wide array of choices and the complex nature of chronic hepatitis B infection, selection of the appropriate therapeutic agent can be challenging for clinicians. Effective treatment decisions require an understanding of the natural history of hepatitis B and knowledge of its life cycle and molecular biology. This review includes the range of treatment options and criteria for determining when and how to most effectively intervene with antiviral therapy for chronically infected patients positive for the HBeAg.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.327
Teacher spread0.287 · 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 designOther design
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

Citations8
Published2009
Admission routes1
Has abstractyes

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