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Hepatic Dysfunction During and After Lymphoma Chemotherapy in Patients With Hepatitis C

2006· article· en· W1970116407 on OpenAlexaff
Justin A. Shah, Eric M. Yoshida, Joseph Connors, Sharlene Gill

Bibliographic record

VenueJournal of Clinical Gastroenterology · 2006
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsBC Cancer AgencyVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineChemotherapyInternal medicineHepatic dysfunctionGastroenterologyHepatitisHepatitis C virusLymphomaIncidence (geometry)Liver diseaseCancerViral hepatitisRetrospective cohort studyImmunologyVirus

Abstract

fetched live from OpenAlex

BACKGROUND: Hepatitis C is one of the most common causes of chronic liver disease. The literature regarding hepatic dysfunction in Hepatitis C patients during and after chemotherapy is limited. PURPOSE: The goal of this study was to determine the incidence of hepatic dysfunction in Hepatitis C positive patients during and/or after chemotherapy for lymphoma. METHODS: A retrospective chart review was performed. Patients included in the study were anti-hepatitis C virus positive patients treated with chemotherapy for lymphoma at the BC Cancer Agency since 1999. Serum transaminases and bilirubin were the primary criteria used to define and evaluate severity of hepatic dysfunction. Information regarding clinical outcomes was also collected. RESULTS: Forty-one eligible patients were identified. Twenty-four patient charts had sufficient information for review. Four patients met criteria for acute chemotherapy-associated hepatic dysfunction. No deaths secondary to acute hepatic dysfunction were identified. CONCLUSIONS: Hepatic dysfunction in patients with Hepatitis C being treated for lymphoma with chemotherapy occurs but is uncommon.

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 score0.008
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.300
Teacher spread0.290 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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