Evidence map›Paper›PMID 32272955›Full record

Observational studyItalian journal of pediatrics2020

Altered structural brain networks at term-equivalent age in preterm infants with grade 1 intraventricular hemorrhage.

Jong Ho Cha, Yong-Ho Choi, Jong-Min Lee, Joo Young Lee, Hyun-Kyung Park, Jinsup Kim, Il-Kewon Kim, Hyun Ju Lee

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Italian journal of pediatrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
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

8 authors at 2 institutions in 1 country.

Jong Ho ChaDepartment of Pediatrics, Hanyang University College of Medicine, Seoul, Hospital, 222-1 Wangsimni-ro Seongdong-gu, Seoul, 04763, South Korea.
Yong-Ho ChoiDepartment of Biomedical Engineering, Hanyang University, Seoul, South Korea.
Jong-Min LeeDepartment of Biomedical Engineering, Hanyang University, Seoul, South Korea.
Joo Young LeeDepartment of Pediatrics, Hanyang University College of Medicine, Seoul, Hospital, 222-1 Wangsimni-ro Seongdong-gu, Seoul, 04763, South Korea.
Hyun-Kyung ParkDepartment of Pediatrics, Hanyang University College of Medicine, Seoul, Hospital, 222-1 Wangsimni-ro Seongdong-gu, Seoul, 04763, South Korea.
Jinsup KimDepartment of Pediatrics, Hanyang University College of Medicine, Seoul, Hospital, 222-1 Wangsimni-ro Seongdong-gu, Seoul, 04763, South Korea.
Il-Kewon KimDivision of Neonatology and Developmental Medicine, Seoul Hanyang University Hospital, Seoul, South Korea.
Hyun Ju LeeDepartment of Pediatrics, Hanyang University College of Medicine, Seoul, Hospital, 222-1 Wangsimni-ro Seongdong-gu, Seoul, 04763, South Korea. blesslee77@hanmail.net.
Hanyang University · KRHanyang University Seoul Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreterm infants are at risk for structural disruption of brain connectivity due to perinatal complications encountered during the fetal and neonatal periods. This study aimed to investigate the development of connectivity using diffusion tensor imaging at near-term age and the effect of grade 1 intraventricular hemorrhage on it.

methodsA total of 86 infants (55 preterm infants, 24 full-term infants) without apparent brain injury underwent diffusion magnetic resonance imaging (MRI) between 36 and 41 weeks post-menstrual age. The diffusion-MRI based connectomics were constructed from 64-segmented regions by using the Johns Hopkins University neonate atlas and were weighted with fractional anisotropy. The connectomes were quantified in the structural networks and investigated using network metrics, such as the clustering coefficient, local efficiency, characteristic path length, global efficiency, and small-worldness. We compared the differences in the brain networks of preterm infants with or without grade 1 intraventricular hemorrhage in binary and fractional anisotropy-weighted (wFA) connectomes.

resultsThe 55 preterm infants had a mean gestational age at birth of 29.3 ± 4.1 weeks and the 24 term-born infants, 38.1 ± 1.1 weeks. A total of 13 of the 55 preterm infants (23.6%) were diagnosed with grade 1 intraventricular hemorrhage. The development of connectivity of the brain network in preterm infants without intraventricular hemorrhage was comparable at near-term age to that in term infants. The preterm infants with germinal matrix hemorrhage exhibited higher clustering (0.093 ± 0.015 vs. 0.088 ± 0.007, p = 0.027) and local efficiency (0.151 ± 0.022 vs. 0.141 ± 0.010, p = 0.025), implying the potential for segregation. However, the preterm infants with intraventricular hemorrhage revealed a longer path length (0.291 ± 0.035 vs. 0.275 ± 0.019, p = 0.020) and lower global efficiency (3.998 ± 0.473 vs. 4.212 ± 0.281, p = 0.048), indicating a decreased integration in the wFA connectivity matrix than those without germinal matrix hemorrhage, after correcting for gestational age, sex, bronchopulmonary dysplasia, and age at scan.

conclusionGrade 1 intraventricular hemorrhage in preterm infants may enhance the capacity for local information transfer and the relative reinforcement of the segregation of networks at the expense of global integration capacity.

Indexed as

Age FactorsBrainCerebral HemorrhageChild DevelopmentCohort StudiesDiffusion Magnetic Resonance ImagingFemaleHumansInfantInfant, NewbornInfant, PrematureInfant, Premature, DiseasesMaleBrain networkDiffusion tensor imagingIntraventricular hemorrhage (IVH)Preterm

Identifiers

PMID32272955
PMCPMC7146964
OpenAlexW3015785334

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.