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Record W4296301832 · doi:10.1097/mpg.0000000000003615

Routine Elective Gastrojejunostomy Tube Changes Are Associated With Reduced Tube Complications and Radiation Exposure

2022· article· en· W4296301832 on OpenAlexaff
Thomas Hoang, Sanjay Maroo, Esther J. Lee, Tammie Dewan, Manraj Heran, Vishal Avinashi

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2022
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsCalgary General HospitalUniversity of CalgaryVancouver Native Health SocietyBC Children's HospitalVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineAspiration pneumoniaSedationTube (container)Feeding tubeSurgeryRetrospective cohort studyPneumoniaRadiation exposureAnesthesiaNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

Gastrojejunostomy tubes (GJTs) can be a long-term solution for patients with intragastric feeding intolerance. Our retrospective study of 101 patients correlates the frequency of routine and urgent GJT changes, as well as complications and radiation exposure. Over a 2.75-year median duration, 60%, 33%, and 28% of patients had >1 episodes of a tube dislodgement/malpositioning, blockage, or leakage, respectively. Aspiration pneumonia hospital admission was required for 23% of patients. Patients with <1 routine tube change/year had more urgent changes/year (3.0) compared to patients with 1-2 (1.2) or >2 (0.8) routine yearly change. These patients required more frequent sedation for tube placement (21% vs 4.7%, P = 0.03) and experienced greater annual radiation exposure (9599 vs 304.5 and 69.1 μGym 2 , P = 0.01 and 0.008, respectively). Overall, aiming for a routine tube change at least every 6-12 months is associated with fewer urgent changes and complications as well as reduced radiation exposure and sedation requirements.

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)0.006
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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