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Record W3046586005 · doi:10.3138/canlivj-2020-0009

Rituximab-induced autoimmune hepatitis: A case study and literature review

2020· article· en· W3046586005 on OpenAlexaffvenue
Polymnia Galiatsatos, Sarit Assouline, Adrian Gologan, Nir Hilzenrat

Bibliographic record

VenueCanadian Liver Journal · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsRituximabMedicineCD20Autoimmune hepatitisLymphomaImmunologyMonoclonal antibodyMonoclonalHepatitisLiver injuryHepatitis BAntibodyInternal medicine

Abstract

fetched live from OpenAlex

Rituximab is a monoclonal antibody to CD20, often used to treat B-cell lymphomas and various autoimmune diseases. While there is extensive literature on rituximab-induced liver injury related to hepatitis B reactivation, there have been no reports to date of autoimmune-type idiopathic drug-induced liver injury from this drug. We present a case of necro-inflammatory hepatitis with autoimmune features in a 40-year-old female after receiving a second dose of rituximab for mucosa-associated lymphoid tissue (MALT) lymphoma, with a review of the literature.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.137
GPT teacher head0.391
Teacher spread0.254 · 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 designCase report
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

Citations14
Published2020
Admission routes2
Has abstractyes

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