Evidence map›Paper›PMID 40224385›Full record

ArticleFrontiers in pediatrics2025

Sex-differences in Mothers' own milk and neurodevelopmental outcomes in preterm infants.

Tingting Zhao, Aolan Li, Xiaolin Chang, Wanli Xu, Tyler Quinn, Jie Chen, Adam P Matson, Ming-Hui Chen, Sarah N Taylor, Xiaomei Cong

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In one paragraph

Article in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Tingting ZhaoSchool of Nursing, Yale University, Orange, CT, United States.
Aolan LiDepartment of Statistics, University of Connecticut, Storrs, CT, United States.
Xiaolin ChangDepartment of Statistics, University of Connecticut, Storrs, CT, United States.
Wanli XuSchool of Nursing, University of Connecticut, Storrs, CT, United States.
Tyler QuinnSchool of Nursing, Yale University, Orange, CT, United States.
Jie ChenCollege of Nursing, Florida State University, Tallahassee, FL, United States.
Adam P MatsonDivision of Neonatology, Connecticut Children's Medical Center, Hartford, CT, United States.
Ming-Hui ChenDepartment of Statistics, University of Connecticut, Storrs, CT, United States.
Sarah N TaylorDepartment of Pediatrics, Yale University, New Haven, CT, United States.
Xiaomei CongSchool of Nursing, Yale University, Orange, CT, United States.

Funding

Integrative omics analysis of pain/stress impact on mitochondrial function and neurodevelopment in preterm infantsF31NR019940 · NINR · UNIVERSITY OF CONNECTICUT STORRS · PI ZHAO, TINGTING · 2022 to 2022
$45k
NINR NIH HHS F31 NR019940
6 · The paper itself

Abstract

Objective: To identify sex-specific feeding patterns and associations with growth and neurodevelopment in preterm infants during NICU through 2 years of corrected age (CA). Methods: A cohort study was conducted with 216 preterm infants (gestational age 28 0/7 to 32 0/7 weeks). Daily feeding regimens, including mother's own milk (MOM), human donor milk, and formula; daily growth; acute and chronic pain/stress were documented during NICU. NICU Network Neurobehavioral Scale (NNNS) (36 to 38 postmenstrual age), and Bayley Scales of Infant and Toddler Development (Bayley) Edition III (1 and 2 years of CA) were measured. Results: Between week 9 to 16 after birth, only females showed a positive association between growth z-score and proportion of MOM intake before week 8 ( Conclusions: We discovered a sex-specific "window of opportunity" for feeding, growth and risk predictors for neurodevelopment up to 2 years of CA. These insights may inform development of tailored feeding regimens, potentially mitigating growth and development differences observed between males and females.

Indexed as

breastmilkfeedingneurodevelopmentpretermsex

Identifiers

PMID40224385
PMCPMC11985779

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.