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Record W2108127670 · doi:10.1177/1756283x10382816

Exploring the role of monitoring anti-TNFα drug and antibody levels in the management of inflammatory bowel disease

2010· article· en· W2108127670 on OpenAlexaff
Allen Lim, Remo Panaccione, Cynthia H. Seow

Bibliographic record

VenueTherapeutic Advances in Gastroenterology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseUlcerative colitisCrohn's diseaseAdverse effectTumor necrosis factor alphaDiseaseDrugImmunologyImmunogenicityInfliximabInternal medicineAntibodyIntensive care medicineGastroenterologyPharmacology

Abstract

fetched live from OpenAlex

Crohn's disease and ulcerative colitis are chronic inflammatory gastrointestinal disorders which often result in significant morbidity or surgery. Current treatment options are not curative and may cause significant adverse effects. The introduction of anti-tumour necrosis factor alpha (anti-TNFα) therapy over a decade ago was a welcome addition to the therapeutic armamentarium and revolutionized the treatment of inflammatory bowel disease (IBD). Despite their relative success, a significant proportion of patients with IBD fail to respond or subsequently lose response anti-TNFα therapy. This review identifies and explores the role of drug levels and immunogenicity (antibody formation) on the efficacy of anti-TNFα therapy and details how monitoring these parameters may help to optimize the management of patients with IBD.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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 designObservational
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

Citations5
Published2010
Admission routes1
Has abstractyes

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