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Record W3115090584 · doi:10.1097/anc.0000000000000823

40% Glucose Gel for the Treatment of Asymptomatic Neonatal Hypoglycemia

2020· article· en· W3115090584 on OpenAlexaff
Brandi L. Gibson, Brigit Carter, Lawrence D. LeDuff, Angela Wallace

Bibliographic record

VenueAdvances in Neonatal Care · 2020
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsLeduc Community Hospital
Fundersnot available
KeywordsMedicineHypoglycemiaNeonatal hypoglycemiaAsymptomaticPediatricsParenteral nutritionEmergency medicineIntensive care medicineInternal medicineInsulinPregnancyGestation

Abstract

fetched live from OpenAlex

BACKGROUND: The Mother Infant Care Center at Fort Belvoir Community Hospital (FBCH) recently revised its asymptotic neonatal hypoglycemia (ANH) protocol and adopted 40% glucose gel into its treatment pathway. The previous protocol used infant formula as the primary intervention. PURPOSE: To evaluate the effectiveness of 40% glucose gel on exclusive human milk diet rates, time on protocol, level II Special Care Nursery (SCN) admission rates, length of stay (LOS), and total hospital costs for newborns with ANH at FBCH. METHODS: Infants with ANH were treated with 40% glucose gel (n = 35) and compared with a historical group of infants with ANH (n = 29) who were treated with formula. RESULTS: Exclusive human milk diet rates increased by 33.6%. The mean time on protocol dropped by 1.13 hours. The SCN admission rates dropped by 2.4% in the postimplementation group. The mean LOS was more than 12 hours less in the postimplementation group. The mean total cost per patient was $1190.60 lower after implementation of 40% glucose gel. IMPLICATIONS FOR PRACTICE: The use of 40% glucose gel is a patient-focused, less-invasive, and cost-effective treatment of ANH. IMPLICATIONS FOR RESEARCH: More studies are needed to better define neonatal hypoglycemia. The use of 40% glucose gel is safe for use in infants with ANH; however, more studies are needed to examine its comprehensive benefits.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.575

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 head0.015
GPT teacher head0.294
Teacher spread0.280 · 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 designOther design
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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

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