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Breastfeeding practices and childhood growth in a Canadian newborn screened cystic fibrosis population

2025· article· W4415767747 on OpenAlexaffabout
Daina Kalnins, Jordan Beaulieu, Kendra Tapscott, Michelle Shaw, Melinda Solomon

Bibliographic record

Venuenot available
Typearticle
Language
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsBreastfeedingCystic fibrosisPopulationNewborn screeningBreast feedingMalnutrition

Abstract

fetched live from OpenAlex

Introduction Newborn screening for cystic fibrosis (CF) has provided an opportunity to intervene earlier to improve growth outcomes in these children. However, the focus on nutrition and growth from birth in this population has led to increased use of formula fortification and consequently lower breastfeeding rates. This is at odds with the mounting evidence that breastfeeding not only offers the known immunological benefits that all babies benefit from, but also milder disease severity and preserved lung function. It is currently unclear whether encouraging breastfeeding in infants with CF can come at the cost of growth outcomes. The purpose of this study was to evaluate the breastfeeding practices in our clinic and to assess how this affects short- and long-term growth, specifically in the Canadian population. Methods This is a survey of newborn-screened children with CF followed from 2008 onwards. Mothers were surveyed about their breastfeeding practices. Clinical data, such as demographics and anthropometric measurements at each clinic visit for the first ten years of life were obtained through the Canadian CF Registry. Flexible non-linear regression was used to compare changes in height-for-age and weight-for-age z-scores with age accounting for repeated measures in the same person. Results The survey was completed by 48 mothers; the demographics of their babies were representative of our clinic (58% female, 98% pancreatic insufficient, 17% with meconium ileus at birth). While the intended plan was to exclusively breastfeed for 71% of mothers, only 50% exclusively breastfed for the first four months. Children who were breastfed for at least four months started at a higher height-for-age z-score (Δ 0.78, 95% CI 0.20, 1.37; p=0.01), but there was no overall difference in height-for-age between breastfed-predominant and formula-predominant children. There were also no differences in weight-for-age z-scores between groups. Conclusions Clinicians may safely encourage breastfeeding with close follow up for infants with CF, as this does promote good growth and weight gain. Breastfeeding is highly beneficial for both infant health and maternal well-being, and with normal growth expected, encouragement of this route with supportive guidance and intervention when required can supplement early CF 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 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)0.002
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 score0.015
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.010
GPT teacher head0.306
Teacher spread0.295 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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