Evidence map›Paper›PMID 36639960›Full record

ArticleBrain and behavior2023

Behavioral outcome of very preterm children at 5 years of age: Prognostic utility of brain tissue volumes at term-equivalent-age, perinatal, and environmental factors.

Maria Chiara Liverani, Serafeim Loukas, Laura Gui, Marie-Pascale Pittet, Maricé Pereira, Anita C Truttmann, Pauline Brunner, Myriam Bickle-Graz, Petra S Hüppi, Djalel-Eddine Meskaldji and 1 more

Open access · goldAbstract read
In one paragraph

Article in Brain and behavior, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 3% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

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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

11 authors at 2 institutions in 2 countries.

Maria Chiara LiveraniDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.ORCID 0000-0002-8021-9760
Serafeim LoukasDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
Laura GuiDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
Marie-Pascale PittetDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
Maricé PereiraDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
Anita C TruttmannClinic of Neonatology, Department of Women Mother Child, University Center Hospital and University of Lausanne, Lausanne, Switzerland.
Pauline BrunnerClinic of Neonatology, Department of Women Mother Child, University Center Hospital and University of Lausanne, Lausanne, Switzerland.
Myriam Bickle-GrazFollow Up Unit, Department of Women Mother Child, University Center Hospital and University of Lausanne, Lausanne, Switzerland.
Petra S HüppiDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
Djalel-Eddine MeskaldjiDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
Cristina Borradori-TolsaDivision of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland.
University of Geneva · CHMother Hospital · IN

Funding

Leenards Foundation 2667The Swiss National Science Foundation 32473B_135817The Swiss National Science Foundation 33CM30_140334
6 · The paper itself

Abstract

objectivePrematurity is associated with a high risk of long-term behavioral problems. This study aimed to assess the prognostic utility of volumetric brain data at term-equivalent-age (TEA), clinical perinatal factors, and parental social economic risk in the prediction of the behavioral outcome at 5 years in a cohort of very preterm infants (VPT, <32 gestational weeks).

methodsT2-weighted magnetic resonance brain images of 80 VPT children were acquired at TEA and automatically segmented into cortical gray matter, deep subcortical gray matter, white matter (WM), cerebellum (CB), and cerebrospinal fluid. The gray matter structure of the amygdala was manually segmented. Children were examined at 5 years of age with a behavioral assessment, using the strengths and difficulties questionnaire (SDQ). The utility of brain volumes at TEA, perinatal factors, and social economic risk for the prediction of behavioral outcome was investigated using support vector machine classifiers and permutation feature importance.

resultsThe predictive modeling of the volumetric data showed that WM, amygdala, and CB volumes were the best predictors of the SDQ emotional symptoms score. Among the perinatal factors, sex, sepsis, and bronchopulmonary dysplasia were the best predictors of the hyperactivity/inattention score. When combining the social economic risk with volumetric and perinatal factors, we were able to accurately predict the emotional symptoms score. Finally, social economic risk was positively correlated with the scores of conduct problems and peer problems.

conclusionsThis study provides information on the relation between brain structure at TEA and clinical perinatal factors with behavioral outcome at age 5 years in VPT children. Nevertheless, the overall predictive power of our models is relatively modest, and further research is needed to identify factors associated with subsequent behavioral problems in this population.

Indexed as

BrainInfant, Extremely PrematureChildChild, PreschoolFemaleGestational AgeGray MatterHumansInfantInfant, NewbornMagnetic Resonance ImagingPrognosisbehavioral outcomeclassificationmachine learningMRIpreterm infantsvolumetric brain data

Identifiers

PMID36639960
PMCPMC9927834
OpenAlexW4316095889

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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.