Evidence map›Paper›PMID 36904276›Full record

ArticleNutrients2023

Early-Life Slow Enteral Feeding Progression Pattern Is Associated with Longitudinal Head-Size Growth Faltering and Neurodevelopmental Impairment Outcomes in Extremely Preterm Infants.

Yung-Chieh Lin, Chi-Hsiang Chu, Yen-Ju Chen, Ray-Bing Chen, Chao-Ching Huang

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Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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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

5 authors.

Yung-Chieh LinDepartment of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704302, Taiwan.ORCID 0000-0002-7698-8428
Chi-Hsiang ChuDepartment of Statistics, Tunghai University, Taichung 407224, Taiwan.ORCID 0000-0002-7883-377X
Yen-Ju ChenDepartment of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704302, Taiwan.
Ray-Bing ChenDepartment of Statistics, Institute of Data Science, National Cheng Kung University, Tainan 701401, Taiwan.
Chao-Ching HuangDepartment of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704302, Taiwan.

Funding

National Cheng Kung University Hospital NCKUH-11201003
6 · The paper itself

Abstract

objectiveTo determine whether feeding progression patterns in the first eight postnatal weeks, depicted by clustering analysis of daily enteral feeding volume, are associated with longitudinal head-circumference (HC) growth and neurodevelopmental outcomes in extremely preterm (EP) infants.

methods200 infants who were admitted at gestational ages 23-27 weeks between 2011 and 2018; survived to discharge; and underwent longitudinal HC growth measurements at birth, term-equivalent age (TEA), corrected age (CA) 6-month, 12-month, and 24-month; and neurodevelopmental assessment using the Bayley Scales of Infant Development at CA 24 months were included for analysis.

resultskmlShape analysis identified two distinct enteral feeding progression patterns: fast progression in 131 (66%) infants and slow progression in 69 (34%) infants. Compared to the fast progression group, the slow progression group showed significantly lower daily enteral volumes after day 13, was older in postnatal age reaching full feeding, had a higher rate of Delta z scores of HC (zHC) < -1 (

conclusionCharacterizing feeding progression pattern may help identify EP infants at high-risk of head-size growth faltering and NDI at early childhood.

Indexed as

Enteral NutritionInfant, Extremely PrematureChildChild, PreschoolGestational AgeHospitalizationHumansInfantInfant, NewbornPatient Dischargeclustering analysisenteral feeding progression patternsextremely preterm infantsgrowth falteringhead circumferenceneurodevelopmental impairment

Identifiers

PMID36904276
PMCPMC10005088

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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.