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Record W2584266435 · doi:10.1542/neo.18-2-e105

Gavage Feeding Practices in VLBW Infants: Physiological Aspects and Clinical Implications

2017· article· en· W2584266435 on OpenAlexaff
Ipsita Goswami, Belal Alshaikh

Bibliographic record

VenueNeoReviews · 2017
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineEnteral administrationAnabolismBolus (digestion)Parenteral nutritionEnergy expenditureBioavailabilityPhysiologyPopulationIntestinal motilityIntensive care medicinePediatricsInternal medicineMotilityPharmacologyEnvironmental healthBiology

Abstract

fetched live from OpenAlex

The goal of enteral nutrition in preterm infants is to adequately support growth without compromising the integrity of the immature gut. Gavage feeds given both by intermittent bolus and continuous infusion have been used in NICUs for years. There is no clear evidence that one method improves clinical outcome over the other, leading to practice variations that are often empirical and subject to clinician preference. This article reviews the physiological effects of the feeding method on gut perfusion, motility, energy expenditure, and interoceptive stress with special regard to anabolism and bioavailability of nutrients. Bolus feeding is followed by insulin surges, enhanced protein synthesis, and improved intestinal growth. Infusion feeding leads to a mature pattern of duodenal contractions and less energy expenditure but is associated with significant loss of key nutrients. An individualized approach based on physiological needs of preterm infants may improve feeding tolerance in this 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)0.003
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.263
GPT teacher head0.511
Teacher spread0.248 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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