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Record W4410760540 · doi:10.1002/jpr3.70025

Global insights on the diagnosis, management, and prevention of pediatric ingestions: A report from the FISPGHAN expert panel

2025· review· en· W4410760540 on OpenAlexaff
Michael A. Manfredi, Katsuhiro Arai, Huma Arshad Cheema, Andy Darma, Claudio Iglesias, Matjaž Homan, Omar I. Saadah, Catharine M. Walsh, Lissy de Ridder

Bibliographic record

VenueJPGN Reports · 2025
Typereview
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsMedicinePediatrics

Abstract

fetched live from OpenAlex

This is a comprehensive review of pediatric foreign body (FB) ingestions, emphasizing the global burden, epidemiology, and management strategies. Predominantly occurring in children under 6, with a peak between 6 months and 3 years, these incidents pose significant health risks with substantial regional variations in ingested objects-ranging from household items to caustic substances. The pathophysiological effects of ingestions are outlined, highlighting specific dangers associated with button batteries, sharp objects, and caustic agents, which can lead to severe tissue damage and long-term complications. A survey of (70) pediatric gastroenterologists from FISPGHAN societies revealed varied regional practices in the frequency of different FB ingestions with food impaction highest in North America and Ocenaia and caustic ingestion more common is Asia. Button batterers were serious concerns across all regions. Management approaches, specifically intubation practice varied across regions. A review of management protocols for different types of ingestions are provided, emphasizing the urgency of endoscopic removal and follow-up care. Prevention strategies are critical, with a focus on public health interventions, legislation, and education to mitigate the risks associated with FB and caustic ingestions. This report underscores the need for enhanced preventive measures and uniform management guidelines to reduce the incidence and improve outcomes of pediatric ingestions worldwide.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.738
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.093
GPT teacher head0.371
Teacher spread0.278 · 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.

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

Citations4
Published2025
Admission routes1
Has abstractyes

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