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Record W2095058829 · doi:10.1080/10428190500062932

Fatal reactivation of hepatitis B post-chemotherapy for lymphoma in a hepatitis B surface antigen-negative, hepatitis B core antibody-positive patient: Potential implications for future prophylaxis recommendations

2005· article· en· W2095058829 on OpenAlexaffabout
Joanna K. Law, Jin Kee Ho, Paul Hoskins, Siegfried R. Erb, Urs P. Steinbrecher, Eric M. Yoshida

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2005
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsMedicineHepatitis BHBsAgLamivudineHepatitis B virusRituximabChemotherapyVincristineImmunologyHepatitisInternal medicineLymphomaGastroenterologyCyclophosphamideVirus

Abstract

fetched live from OpenAlex

In the absence of prophylaxis, the reactivation of hepatitis B in oncology patients who are hepatitis B carriers is a well-known and often fatal complication of chemotherapy. The current recommendations in Canada and the USA are that patients who are positive for hepatitis B surface antigen (HBsAg) receive antiviral prophylaxis prior to chemotherapy. We report a 67-year-old man with B-cell lymphoma who developed hepatitis B reactivation following chemotherapy with cyclophosphamide, adriamycin, vincristine, prednisone and rituximab. Pre-chemotherapy, the patient was negative for HBsAg, positive for hepatitis B core antibody (anti-HBc) and weakly positive for hepatitis B surface antibody. Despite treatment with lamivudine, the patient died of fulminant hepatic failure. Our experience indicates that patients who are negative for HBsAg but positive for anti-HBc are still at risk for reactivation of latent hepatitis B during and after chemotherapy and may be considered for prophylaxis.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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

Citations125
Published2005
Admission routes2
Has abstractyes

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