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Record W3112964431 · doi:10.14218/jcth.2020.00090

Occult Hepatitis B Reactivation after Liver Transplant: The Role of a Novel Mutation in the Surface Antigen

2020· article· en· W3112964431 on OpenAlexaff
Harjot Bedi, Daljeet Chahal, Christopher F. Lowe, Gordon Ritchie, Trana Hussaini, Vladimir Marquez, Eric M. Yoshida

Bibliographic record

VenueJournal of Clinical and Translational Hepatology · 2020
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineHBsAgHepatitis B virusViral loadVirologyHepatocellular carcinomaImmunologyHepatitis BAntigenVirusInternal medicine

Abstract

fetched live from OpenAlex

Occult hepatitis B infection is characterized by loss of hepatitis B surface antigen (HBsAg) and persistence of low levels of hepatitis B virus (HBV) replication that may or may not be detectable in plasma/serum. We present a case of HBV reactivation in a male patient who underwent orthotopic liver transplant for hepatocellular carcinoma secondary to active hepatitis C (HCV) infection. Pre-transplant, he was HBsAg-negative and hepatitis B core antibody-positive, with an undetectable HBV viral load that was incidentally found to be positive at a very low HBV viral load on the day of transplant. Post-transplant, his HBsAg remained undetectable, with an undetectable HBV viral load, until eradication of his HCV infection with direct acting antiviral agents. After eradication of HCV, there was reactivation of HBV, with a high viral load and emergence of serum HBsAg. A deep sequencing genetic analysis of his HBV both pre- and post-transplant revealed the presence of a mutation in the "a" determinant of the HBV surface antigen. The role of HBV genotype 'a' determinant mutation in HBV reactivation post-transplant is unknown and needs further examination. Our experience suggests a possible role for antiviral prophylaxis in these patients or monitoring of HBV viral loads post-transplant.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.068
GPT teacher head0.346
Teacher spread0.278 · 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 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

Citations3
Published2020
Admission routes1
Has abstractyes

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