Evidence map›Paper›PMID 39523932›Full record

ArticleEpilepsia2025

Long-term characterization of behavior phenotypes in children with seizures: Analytic approach matters.

Karina Morales, Danielle Harvey, David Dunn, Jana Jones, Anna Byars, Joan Austin, Bruce Hermann, Temitayo Oyegbile-Chidi

Abstract read
In one paragraph

Article in Epilepsia, 2025. 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
–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

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.

  1. Review
  2. Article
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.

Karina MoralesDepartment of Neurology, University of California, Davis, Sacramento, California, USA.
Danielle HarveyDepartment of Public Health Sciences, University of California, Davis, Sacramento, California, USA.
David DunnDepartment of Psychiatry and Neurology, Indiana University, Indianapolis, Indiana, USA.
Jana JonesDepartment of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Anna ByarsDepartment of Pediatrics, Cincinnati Children's Hospital at the University of Cincinnati, Cincinnati, Ohio, USA.
Joan AustinDistinguished Professor Emerita, School of Nursing, Indiana University, Indianapolis, Indiana, USA.
Bruce HermannDepartment of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.ORCID 0000-0003-0133-4427
Temitayo Oyegbile-ChidiDepartment of Neurology, University of California, Davis, Sacramento, California, USA.ORCID 0000-0003-3844-315X

Funding

CHILDHOOD EPILEPSY-- FACTORS AFFECTING ADAPTATIONR37NS022416 · NINDS · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI AUSTIN, JOAN K · 2000 to 2006
$4.5M
Characterizing Sleep Signatures and its effects on Cognition in New-Onset Temporal Lobe EpilepsyK23NS131574 · NINDS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Temitayo Oyegbile-Chidi · 2023 to 2026
$769k
CHILDHOOD EPILEPSY: FACTORS AFFECTING ADAPTATIONR01NS022416 · NINDS · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI AUSTIN, JOAN K · 1986 to 1999
–
NINDS NIH HHS K23 NS131574NINDS NIH HHS NS131574NINDS NIH HHS NS22416NINDS NIH HHS R01 NS022416NINDS NIH HHS R37 NS022416
6 · The paper itself

Abstract

objectiveBehavioral problems in children with new onset epilepsies have been well established in the literature. More recently, the literature indicates the presence of unique behavioral patterns or phenotypes in youth with epilepsy that vary significantly in vulnerability and resilience to behavioral problems. This study contrasts the interpretation of behavioral risk as inferred from cross-sectional versus latent group analytic perspectives, as well as the presence, consistency, stability, and progression of behavioral phenotypes in youth with new onset epilepsy and sibling controls over 3 years.

methodsThree hundred twelve participants (6-16 years old) were recruited within 6 weeks of their first recognized seizure along with 223 unaffected siblings. Each child's behavior was recorded by parents and teachers frequently over 36 months using the Child Behavior Checklist (CBCL), and each child completed self-report measures of depression symptoms over 36 months. Measures were evaluated cross-sectionally and longitudinally to identify clusters with prototypical behavioral trajectories.

resultsCross-sectional analyses exhibited a pattern of generalized and undifferentiated behavioral problems compared to sibling controls at baseline and prospectively. In contrast, latent trajectory modeling identified three distinct behavior phenotype clusters across all raters (parents, teachers, and youth) over baseline and longitudinal assessments. CBCL Cluster 1 (~30% of youth with epilepsy) exhibited behavior similar to/better than controls, Cluster 2 (~50%) exhibited moderate behavior issues, and Cluster 3 (~20%) exhibited the most pronounced/problematic behavior, falling into Achenbach's clinically relevant behavior range. Behavior within clusters remained stable and consistent. Teachers' and children's behavior assessments corresponded to these cluster groupings consistently over 36 months. Predictors of cluster membership include seizure syndrome type and social determinants of health. SIGNIFICANCE: This study demonstrates the varying public health perspectives of behavioral risk in youth with epilepsy that result as a function of analytic approach as well as the presence of distinct latent behavioral trajectory phenotypes over time in youth with new onset epilepsy.

Indexed as

Child Behavior DisordersProblem BehaviorSeizuresAdolescentChildCross-Sectional StudiesFemaleHumansLongitudinal StudiesMalePhenotypeSiblingsbehaviorepilepsylatent trajectory phenotypespediatricpredictors

Identifiers

PMID39523932
PMCPMC11742550

What OpenQuestion holds

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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.