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Record W2912953799 · doi:10.21037/tp.2018.12.04

Growth failure in pediatric onset inflammatory bowel disease: mechanisms, epidemiology, and management

2019· review· en· W2912953799 on OpenAlexfundno aff
Takashi Ishige

Bibliographic record

VenueTranslational Pediatrics · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
FundersHospital for Sick ChildrenMinistry of Health, Labour and Welfare
KeywordsMedicineInflammatory bowel diseaseUlcerative colitisInternal medicineDiseaseDelayed pubertyGastroenterologyIncidence (geometry)Parenteral nutritionCrohn's diseaseMalabsorptionPediatricsHormone

Abstract

fetched live from OpenAlex

Impairment of growth is recognized as one of the most significant complications of inflammatory bowel disease (IBD) in pediatric patients. The reported incidence of growth failure at diagnosis is 15-40% in pediatric onset Crohn's disease (CD) and 3-10% in ulcerative colitis (UC). Growth failure is associated with decreased appetite, abdominal symptoms, malabsorption due to mucosal inflammation, growth hormone (GH) resistance due to inflammation, and even genetic factors. Several population-based studies and cohort studies suggest that patients with pre-pubertal onset CD have a higher risk of growth failure at disease onset. Final adult height is still lower than that of healthy controls; however, its prevalence is generally lower than that at the disease onset. Several IBD treatments were reported to improve patients' growth. In addition to enteral nutrition therapy, treatment with anti-tumor necrosis factor (TNF) agents was reported to have favorable effects on growth of patients with pre-pubertal onset CD. Avoiding corticosteroids (CS) and achieving deep remission seems to be important to maintain optimal growth in patients with pediatric onset 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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.022
GPT teacher head0.285
Teacher spread0.263 · 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 designSystematic review
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

Citations63
Published2019
Admission routes1
Has abstractyes

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