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Record W2129951806 · doi:10.1177/2333794x14568453

Retrospective Review of Current Nasojejunal Tube Insertion Practice

2015· article· en· W2129951806 on OpenAlexaff
Natasha Sheikh, Michelle Falkiner, Mary-Louise Greer

Bibliographic record

VenueGlobal Pediatric Health · 2015
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineCurrent (fluid)Retrospective cohort studyIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

Repeated fluoroscopically guided nasojejunal tube (NJT) insertions, particularly in children, can pose health risks through increased radiation exposure. We analyzed frequency of NJT reinsertions and associated radiation exposure through retrospective evaluation of children <18 years at our institution who underwent fluoroscopically guided NJT insertions from 2007 to 2012. Age and weight, reinsertion frequency per patient, radiation dose (dose actual percentage [DAP]), time interval between, and indication for reinsertion were recorded. A total of 252 children (3 days to17 years, 11 months) had 449 NJT insertions. Reinsertions occurred in 105 (41.7%) patients with 14 (5.6%) having ≥5 reinsertions, and 67.6% of reinsertions occurring in patients <1 year. Mean DAP increased with frequency of reinsertion, along with age and weight. Most common indication for reinsertion was a pulled NJT (34.0%). Fluoroscopic NJT reinsertion was most frequent in younger, smaller patients. Self-guided, bedside NJT insertion, and/or earlier instigation of definitive nutritional therapy delivery should be considered.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.413
Teacher spread0.357 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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