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Record W2999991521 · doi:10.2147/jmdh.s236130

<p>Multidisciplinary Management in Pediatric Ultrashort Bowel Syndrome</p>

2020· review· en· W2999991521 on OpenAlexaff
Christina Belza, Paul W. Wales

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2020
Typereview
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsHospital for Sick ChildrenSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsShort bowel syndromeMedicineIntestinal failureMultidisciplinary approachIntensive care medicinePopulationParenteral nutritionEnteral administrationGastrointestinal tractPediatricsInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Pediatric intestinal failure (IF) remains a complex and devastating condition resulting in the inability of the gastrointestinal tract to absorb adequate fluids and nutrients to sustain life. The goal in the management of IF is to achieve enteral autonomy and when not possible to avoid and minimize the development of long-term complications. Survival rates for children with IF have continued to improve resulting in an increased population of children with more altered anatomy. While IF remains a rare disease, children with IF secondary to ultrashort bowel syndrome comprise an even smaller patient population. The goal of this article is to review the recent literature related to the impact of multidisciplinary intestinal rehabilitation programs (IRPs) on the management and outcomes of intestinal failure in children with ultrashort bowel syndrome and potential avenues to further improve the long-term outcomes of this patient population.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.053
GPT teacher head0.384
Teacher spread0.331 · 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 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

Citations20
Published2020
Admission routes1
Has abstractyes

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