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Record W2916260541 · doi:10.1097/ftd.0000000000000610

Biomarkers of Drug-Induced Liver Toxicity

2019· review· en· W2916260541 on OpenAlexaff
Manuela G. Neuman

Bibliographic record

VenueTherapeutic Drug Monitoring · 2019
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLiver toxicityToxicityPharmacologyDrugMedicineDrug toxicityInternal medicine

Abstract

fetched live from OpenAlex

Drug-induced liver injury (DILI) is a comprehensive phenomenon. The injury to the liver may occur as an unexpected and undesired reaction to a therapeutic dose of a drug (idiosyncratic reaction) or as an expected therapeutic effect of the direct (intrinsic) toxicity of a drug taken in a large enough dose to cause liver injury. The direct toxicity (type A) reactions represent an extension of the drug's therapeutic effect; they occur relatively frequently and are typically dose-related and frequency-of-exposure-related. By contrast, idiosyncratic reactions, or type B reactions, are unpredictable, occurring only in susceptible individuals, and are unrelated to the dose or frequency of exposure. DILI encompasses both acute and/or chronic hepatic lesions. The liver injury may be the only clinical manifestation of the adverse drug effect. Otherwise, it may be accompanied by injury to other organs, or by systemic manifestations. The liver injury may be observed in 1-8 days from taking the drug. DILI cases may result in the disapproval of a new drug or in the removal of a useful drug from the market by regulatory agencies. The purpose of this review is to provide guidance to facilitate the detection and assessment of hepatotoxicity induced by therapeutics that received market authorization. This review supports the safe and effective use of drugs by patients and guides laboratory medicine professional in determining the possible drug-induced liver damage.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.337
GPT teacher head0.477
Teacher spread0.140 · 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 designOther design
Domainnot available
GenreReview

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

Citations22
Published2019
Admission routes1
Has abstractyes

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