Evidence map›Paper›PMID 42918827›Full record

ArticlePediatric research2026

Neonatal brain network integration trajectories predict neurodevelopment in congenital heart disease.

Lauren Harasymiw, Amy Kuang, Duan Xu, Aaron Scheffler, Elizabeth George, Shabnam Peyvandi, Patrick McQuillen

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Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

7 authors.

Lauren HarasymiwDepartment of Pediatrics; University of California San Francisco, San Francisco, CA, USA. Lauren.Harasymiw@ucsf.edu.ORCID http://orcid.org/0000-0003-0660-4131
Amy KuangDepartment of Radiology, University of California San Francisco, San Francisco, CA, USA.
Duan XuDepartment of Radiology, University of California San Francisco, San Francisco, CA, USA.
Aaron SchefflerDepartment of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA.
Elizabeth GeorgeDepartment of Radiology, University of California San Francisco, San Francisco, CA, USA.
Shabnam PeyvandiDepartment of Pediatrics; University of California San Francisco, San Francisco, CA, USA.
Patrick McQuillenDepartment of Pediatrics; University of California San Francisco, San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInfants with critical congenital heart disease (CHD) are at high risk for abnormal brain development and later neurodevelopmental impairment. We hypothesized that the trajectory of perioperative whole-brain network development would predict neurodevelopmental outcomes in early childhood.

methodsThis prospective longitudinal cohort of neonates with critical CHD (n = 97) underwent preoperative and/or postoperative brain MRI with diffusion imaging. Whole-brain network measures were derived from structural connectomes from 80 infants, and 50 had neurodevelopment assessed at 1-4 years using the Bayley Scales of Infant and Toddler Development.

resultsWhite matter injury was associated with a slower perioperative increase in global efficiency (p = 0.013), a measure of network integration, whereas cardiac physiology was not associated with network development. Infants with greater perioperative increases in global efficiency had higher cognitive (p = 0.001), language (p < 0.001), and motor (p = 0.008) scores. For each 1-standard deviation increase in the trajectory of global efficiency, cognitive scores increased by 8.2 points (95% CI: 3.64-12.78), independent of brain injury and socioeconomic factors.

conclusionIn infants with critical CHD, longitudinal whole-brain network development was associated with neurodevelopment across multiple domains. Early network development may serve as a biomarker of neurodevelopmental risk and resilience in this population. IMPACT: In infants with critical congenital heart disease, perioperative increase in whole-brain network integration was associated with cognitive, language, and motor outcomes in early childhood. White matter injury was associated with a slower increase in network integration, whereas cardiac physiology subtype was not associated with network development. This study extends prior work by showing that a longitudinal measure of neonatal whole-brain network development, rather than a single imaging timepoint, predicts neurodevelopment across multiple domains. These findings identify early network development as a potential biomarker of neurodevelopmental risk and resilience, and support future risk-stratification and intervention studies in this population.

Identifiers

PMID42918827

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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.