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Record W4391886458 · doi:10.1093/jcag/gwad061.228

A228 RISANKIZUMAB - DRUG INDUCED LIVER INJURY; A CASE REPORT

2024· article· en· W4391886458 on OpenAlexaff
F Borahmah, B Salh, Daljeet Chahal

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDrugLiver injuryMedicinePharmacology

Abstract

fetched live from OpenAlex

Abstract Background Risankizumab is a humanized monoclonal antibody to IL-23. It was initially used in the treatment of plaque psoriasis with recent approval to extend use to treat moderate to severe Crohn’s disease with evidence of endoscopic healing and clinical remission of disease. In the drugs safety manual, it has been reported to have transient liver enzyme elevation that is asymptomatic and not to a degree requiring drug discontinuation. No reported data on steatohepatitis. In this article we describe a 28 year old female, who had no evidence of liver disease in the past who underwent treatment with Risankizumab and within several months developed evidence of steatohepatitis with radiological evidence of significant hepatomegaly. Aims Case report details Drug induced liver injury to Risankizumab. Methods Case Report Results Drug induced liver injury with elevated liver enzyme levels and liver biopsy showing drug related liver changes likely in the setting of Risankizumab use. Conclusions Risankizumab is a newly approved drug in the setting of Crohn's disease, although described in the drug assessment report that it may cause transient hepatitis or eleveted liver enzymes in the setting of lower drug dose for Psoriasis use, the higher drug level used in the setting of Crohn's disease has not been formally evaluated and no previous known case reports of Drug induced Liver Injury to Risankizumab causing severe steatohepatitis Funding Agencies None

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.053
GPT teacher head0.360
Teacher spread0.307 · 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 designNot applicable
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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of GastroenterologySame topicDrug-Induced Hepatotoxicity and ProtectionFrench-language works237,207