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Record W2108173593 · doi:10.1186/1752-1947-4-227

Hepatic steatosis secondary to capecitabine: a case report

2010· article· en· W2108173593 on OpenAlexaff
Sheray N. Chin, Tae Kyoung Kim, Lillian L. Siu

Bibliographic record

VenueJournal of Medical Case Reports · 2010
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsToronto General HospitalPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsCapecitabineMedicineSteatosisColorectal cancerDiscontinuationInternal medicineGastroenterologyCancer

Abstract

fetched live from OpenAlex

INTRODUCTION: There are no known case reports of hepatic steatosis caused by oral fluoropyrimidines such as capecitabine. With increasing use of capecitabine since its approval for the treatment of metastatic colon cancer in 2001, and more recently for adjuvant treatment of colon cancer and treatment of metastatic breast cancer, we can anticipate increased recognition of potential toxicities associated with this 5-fluorouracil derivative. CASE PRESENTATION: We report the case of a 74-year-old Armenian woman who received capecitabine as adjuvant treatment for colon cancer and subsequently developed abnormal liver biochemical tests and radiographic findings in keeping with hepatic steatosis. There was complete reversal of liver enzyme abnormalities with discontinuation of the drug and this patient represents a case of reversible liver injury due to capecitabine. CONCLUSION: In this original case report, capecitabine use was associated with hepatic steatosis. It is important for clinicians to recognize and monitor for this potential toxicity, which may be a cause of abnormal liver enzymes in this patient population.

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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0050.002

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 head0.014
GPT teacher head0.318
Teacher spread0.304 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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