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Record W3005191572 · doi:10.14740/gr1188

Mifepristone: An Uncommon Cause of Drug-Induced Liver Injury

2019· article· en· W3005191572 on OpenAlexvenueno aff
Ishani Shah, Tyler Putnam, Evan Daugherty, Neil Vyas, Keng–Yu Chuang

Bibliographic record

VenueGastroenterology Research · 2019
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsMifepristoneMedicineLiver injuryJaundiceDrugAbdominal painLiver biopsyGastroenterologyInternal medicineSurgeryBiopsyPharmacologyPregnancy

Abstract

fetched live from OpenAlex

Mifepristone is frequently used in large doses for management of Cushing's syndrome. This is a case of a 35-year-old woman with Cushing's syndrome, who presented with abdominal pain and jaundice. A month prior to admission, she had been started on a daily dose of 1,200 mg mifepristone. After evaluating for various other causes of liver injury, biopsy revealed cholestatic pattern of liver disease, likely associated with drug-induced hepatotoxicity. Mifepristone was discontinued and her symptoms resolved. We believe this is one of the first few reported cases of drug-induced liver injury (DILI) associated with mifepristone use.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.261
GPT teacher head0.505
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2019
Admission routes1
Has abstractyes

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