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Record W4391450554 · doi:10.3138/canlivj-2023-0019

Immunosuppression in two cases of indeterminate hepatitis

2024· article· en· W4391450554 on OpenAlexaffvenue
Alexandra Cohen, Fernando Álvarez

Bibliographic record

VenueCanadian Liver Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineImmunosuppressionIndeterminateAplastic anemiaAutoimmune hepatitisImmunologyHepatitisPopulationAnti-thymocyte globulinDiseaseGlobulinInternal medicine

Abstract

fetched live from OpenAlex

Background: Pediatric acute liver failure (PALF) is a potentially lethal and rapidly progressive clinical syndrome, with a large proportion of cases remaining indeterminate despite extensive investigations. Patients and Results: In this case report, we describe two male children with indeterminate PALF and a family history of autoimmune disease, both of whom were lymphopenic with necrosis, inflammation, and lymphocytic infiltrates on their liver biopsies. One of these patients subsequently developed hepatitis-associated aplastic anemia. Notably, in addition to receiving standard liver failure care, both patients were successfully treated off-label with anti-thymocyte globulin (ATG), as well as a more prolonged course of cyclosporine and corticosteroids. Conclusions: The fact that these medications all suppress T lymphocytes further supports the theory that T-cell activation plays a prominent role in the pathophysiology of indeterminate hepatitis. Further research should examine the short-term and long-term effects of ATG in this population, as well as the necessary duration of treatment with immune-suppressing agents.

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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0040.003
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 head0.016
GPT teacher head0.287
Teacher spread0.270 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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