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Record W2626515875 · doi:10.1044/2017_ajslp-16-0052

Effect of Single-Use, Laser-Cut, Slow-Flow Nipples on Respiration and Milk Ingestion in Preterm Infants

2017· article· en· W2626515875 on OpenAlexaff
Katlyn McGrattan, David H. McFarland, Jesse C. Dean, Elizabeth G. Hill, David R. White, Bonnie Martin‐Harris

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2017
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsUniversité de MontréalMcGill University
FundersNational Institute on Deafness and Other Communication DisordersNational Center for Advancing Translational SciencesUniversity of South Carolina
KeywordsMedicineIngestionSlow FlowVentilation (architecture)RespirationAnesthesiaInternal medicineAnatomy

Abstract

fetched live from OpenAlex

PURPOSE: Single-use, laser-cut, slow-flow nipples were evaluated for their effect on respiration and milk ingestion in 13 healthy preterm infants (32.7-37.1 weeks postmenstrual age) under nonlaboratory, clinical conditions. METHOD: The primary outcomes of minute ventilation and overall milk transfer were measured by using integrated nasal airflow and volume-calibrated bottles during suck bursts and suck burst breaks during slow-flow and standard-flow nipple bottle feedings. Wilcoxon signed-ranks tests were used to test the effect of nipple type on both outcomes. RESULTS: Prefeeding minute ventilation decreased significantly during suck bursts and returned to baseline values during suck burst breaks across both slow-flow and standard-flow nipples. No differences were found in minute ventilation (p > .40) or overall milk transfer (p = .58) between slow-flow and standard-flow nipples. CONCLUSIONS: The lack of difference in primary outcomes between the single-use slow-flow and standard-flow nipples may reflect variability in nipple properties among nipples produced by the same manufacturer. Future investigations examining the effect of both single-use and reusable nipple products are warranted to better guide nipple selection during clinical care.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.315
Teacher spread0.298 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Speech-Language PathologySame topicBreastfeeding Practices and InfluencesFrench-language works237,207