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Record W2021552786 · doi:10.1097/mog.0b013e3283457ce0

Management of autoimmune hepatitis

2011· review· en· W2021552786 on OpenAlexfundno aff
Marlyn J. Mayo

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2011
Typereview
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsnot available
FundersAlberta Innovates - Health Solutions
KeywordsAutoimmune hepatitisMedicineImmunosuppressionPrednisoneBudesonideTacrolimusClinical trialHepatitisDiseaseAzathioprineAutoimmune diseaseIntensive care medicineImmunologyInternal medicineCorticosteroidTransplantation

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Autoimmune hepatitis (AIH) is a chronic, progressive hepatitis of uncertain cause which has fluctuating activity characterized by periods of flares and remissions. Initial placebo-controlled trials carried out in the 1970s demonstrated that immunosuppression with steroids was extremely effective in reducing flares and progression of disease. The late 1980s-1990s could be described as the 'Dark Ages' of AIH treatment research. Very few clinical studies were performed during this time, although it became increasingly apparent that not all patients tolerated or responded to traditional immunosuppression, and that not all patients were easy to diagnose because of overlapping features with other autoimmune conditions. Fortunately, clinical research in the treatment of AIH has experienced a renaissance in the 21st century. RECENT FINDINGS: This review highlights some of the more important recent discoveries, including the creation of the clinically useful short form of the autoimmune hepatitis diagnostic scoring system; accumulation of data supporting the use of mycophenolate and tacrolimus as second-line treatment; and the recent completion of the largest, double-blind, placebo-controlled trial of AIH treatment to date, comparing budesonide to prednisone. SUMMARY: These new findings are pertinent to the everyday clinical management of patients with AIH.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.100
GPT teacher head0.379
Teacher spread0.279 · 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.

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

Citations20
Published2011
Admission routes1
Has abstractyes

Explore more

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