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Record W2022876395 · doi:10.1002/ibd.21576

Transitioning the adolescent inflammatory bowel disease patient: Guidelines for the adult and pediatric gastroenterologist

2010· article· en· W2022876395 on OpenAlexaff
Yvette Leung, Melvin B. Heyman, Uma Mahadevan

Bibliographic record

VenueInflammatory Bowel Diseases · 2010
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicineInflammatory bowel diseaseAdult careIncidence (geometry)StaffingDiseaseIntensive care medicinePediatricsPediatric gastroenterologyMEDLINEFamily medicineYoung adultInternal medicineNursing

Abstract

fetched live from OpenAlex

Twenty percent of inflammatory bowel disease (IBD) patients present in the pediatric years, with recent reports suggesting a rising incidence in the pediatric age group. This highlights the need for both pediatric and adult gastroenterologists to better understand issues related to the process of transition from pediatric to adult care. Research from other disciplines outside of IBD provide evidence that the transition period can be associated with poorer health outcomes and that a structured transition program may improve patient compliance and disease control. Recent data from the IBD literature support a need for transition clinics. The ideal model of a transition program has not been established. Controlled trials are not available to measure the impact of a structured transition program on clinically relevant endpoints such as disease control and hospital admissions. As local resources and availability of staffing and funding are highly variable, we have summarized some practical guidelines for the adult and pediatric gastroenterologist that can be used as an aid to help adolescents through the transition process even without the support of an established transition clinic.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.354
Teacher spread0.313 · 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 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

Citations100
Published2010
Admission routes1
Has abstractyes

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