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Record W2325744197 · doi:10.1097/anc.0000000000000141

Managing Gastroesophageal Reflux Symptoms in the Very Low-Birth-Weight Infant Postdischarge

2014· article· en· W2325744197 on OpenAlexaff
Tammy Sherrow, Donna Dressler-Mund, Kelly Kowal, Susan Dai, Melissa D. Wilson, Karen Lasby

Bibliographic record

VenueAdvances in Neonatal Care · 2014
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsAlberta Children's HospitalAlberta Health Services
Fundersnot available
KeywordsMedicineRefluxLow birth weightPsychological interventionConfusionDiseaseNeonatal intensive care unitPediatricsIntensive care medicineGERDInternal medicinePsychiatryPregnancy

Abstract

fetched live from OpenAlex

Gastroesophageal reflux and gastroesophageal reflux disease symptoms are common challenges for very low-birth-weight infants (<1500 g). These symptoms frequently result in feeding difficulties and family stress. Management of symptoms across healthcare disciplines may not be based on current evidence, and inconsistency can result in confusion for families and delayed interventions. The feeding relationship between infant and caregivers may be impaired when symptoms are persistent and poorly managed. An algorithm for managing gastroesophageal reflux-like symptoms in very low-birth-weight infants (from hospital discharge to 12 months corrected age) was developed through the formation of a multidisciplinary community of practice and critical appraisal of the literature. A case study demonstrates how the algorithm results in a consistent approach for identifying symptoms, applying appropriate management strategies, and facilitating appropriate timing of medical consultation. Application to managing gastroesophageal reflux symptoms in the neonatal intensive care unit will be briefly addressed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.175
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.004
GPT teacher head0.256
Teacher spread0.252 · 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 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

Citations9
Published2014
Admission routes1
Has abstractyes

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