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Record W2021861409 · doi:10.1586/egh.09.25

How to manage difficult Crohn’s disease: optimum delivery of anti-TNFs

2009· review· en· W2021861409 on OpenAlexaff
Darin Krygier, Hin Hin Ko, Brian Bressler

Bibliographic record

VenueExpert Review of Gastroenterology & Hepatology · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineNatalizumabCrohn's diseaseAdverse effectDiseaseInflammatory bowel diseaseDrugIntensive care medicineInternal medicineImmunologyPharmacology

Abstract

fetched live from OpenAlex

Crohn's disease is a chronic inflammatory condition that can involve any portion of the GI tract, leading to disabling symptoms and complications. Standard treatment with 5-aminosalicylic acid, antibiotics, corticosteroids and immunosuppressives has limited efficacy and is associated with serious potential adverse events. The anti-TNF-alpha agents are effective in the induction and maintenance of remission in luminal and fistulizing Crohn's disease. Recent evidence suggests that early treatment with anti-TNF agents and immunosuppressives may alter the natural history of the disease and prevent late complications. In those patients who have lost response to, or are intolerant of, a single anti-TNF agent, increasing the dose of the medication or switching to alternate biologic agents, such as another anti-TNF drug or natalizumab, have been shown to be effective treatments.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.819
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.012
GPT teacher head0.289
Teacher spread0.276 · 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 designNot applicable
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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

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