Evidence map›Paper›PMID 41830626›Full record

ArticleEpilepsia open2026

Prediction of treatment response in infantile epileptic spasms syndrome using EEG phase-amplitude coupling.

Soudeh Mostaghimi, Marco A Pinto-Orellana, Nathaniel Green, Daniel W Shrey, Makoto Miyakoshi, Shaun A Hussain, Beth A Lopour

Abstract read
In one paragraph

Article in Epilepsia open, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Soudeh MostaghimiDepartment of Biomedical Engineering, University of California, Irvine, California, USA.ORCID https://orcid.org/0000-0003-3532-0250
Marco A Pinto-OrellanaDepartment of Biomedical Engineering, University of California, Irvine, California, USA.ORCID https://orcid.org/0000-0001-6495-1305
Nathaniel GreenDepartment of Biomedical Engineering, University of California, Irvine, California, USA.ORCID https://orcid.org/0009-0006-9735-0382
Daniel W ShreyDivision of Neurology, Children's Hospital of Orange County, Orange, California, USA.ORCID https://orcid.org/0000-0002-3163-4773
Makoto MiyakoshiDivision of Child and Adolescent Psychiatry, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.ORCID https://orcid.org/0000-0002-4062-6679
Shaun A HussainDivision of Pediatric Neurology, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-6947-8852
Beth A LopourDepartment of Biomedical Engineering, University of California, Irvine, California, USA.ORCID https://orcid.org/0000-0003-4233-4802

Funding

John C. Hench FoundationUCB Biopharma
6 · The paper itself

Abstract

objectiveTreatment selection for infantile epileptic spasms syndrome (IESS) is complex and multifaceted, and currently no electroencephalogram (EEG) biomarkers can guide this decision by predicting treatment response. We tested the predictive value of phase-amplitude coupling (PAC) as IESS patients are known to have elevated PAC.

methodsWe analyzed retrospective EEG recordings from 40 IESS patients, before and after treatment, and 20 healthy controls. Patients were classified as responders (n = 25) or nonresponders (n = 15) based on short-term treatment outcomes. We measured PAC in each EEG using modulation index (MI) and mean vector length (MVL) and analyzed the relationship between pre- and posttreatment values and the ability of pretreatment values to predict response.

resultsMI and MVL values decreased with treatment in almost all subjects. However, nonresponders had significantly higher pretreatment MI than responders (p < 0.05), suggesting utility for predicting treatment response. Logistic regression modeling suggested that a 0.5-unit decrease in ln(MI), which is approximately one IQR of the pretreatment ln(MI) values, results in a 3.5-fold increase in odds of positive treatment response. MI reflects short-term treatment response and is a candidate predictive EEG biomarker for IESS. SIGNIFICANCE: MI may offer individualized insights for treatment selection and management strategies for IESS. PLAIN LANGUAGE SUMMARY: We examined brain activity in infants with infantile epileptic spasms syndrome (IESS) to predict which infants' seizures would stop with standard medication. Specifically, we measured coupling between slow and fast brain waves in both healthy infants and those with IESS. Infants for whom medication failed had stronger coupling, even before the treatment was started, while those with weaker coupling (more similar to healthy infants) were more likely to have their seizures stop after treatment. These findings suggest that brain wave coupling could help doctors predict which infants will need more aggressive treatment.

Indexed as

AnticonvulsantsBrainElectroencephalographySpasms, InfantileFemaleHumansInfantMalePredictive Value of TestsRetrospective StudiesTreatment OutcomeAnticonvulsantsbiomarkerdiagnosisepilepsyepileptic encephalopathymodulation indexpediatric

Identifiers

PMID41830626
PMCPMC13238781

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LicenceCC BY-NC-ND
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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.