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Objective <p>This study investigated the association between epilepsy and findings from neurological evaluations, including electroencephalography (EEG), neuroimaging, genetic testing, and developmental assessments, in children with Autism Spectrum Disorder (ASD).</p> Methods <p>Ninety-nine children with ASD (DSM-5-TR) were retrospectively evaluated at a tertiary center between 2012 and 2021. Data included demographics, EEG, neuroimaging, genetic testing, and developmental assessments.</p> Results <p>The cohort was predominantly male (76.8%), with a mean age of 10.2 ± 4.7 years. EEG was performed in 51 patients, with abnormalities detected in 43.1%. Epilepsy was diagnosed in 22.2% (<i>n</i> = 22). Among 42 patients who underwent chromosomal microarray analysis, pathogenic variants were identified in 52.4%. Chi-square analysis showed significant associations between epilepsy and abnormal EEG findings (χ²=45.45, <i>p</i> &lt; 0.001) and pathogenic variants (χ²=7.68, <i>p</i> = 0.006), but not gender (<i>p</i> = 0.823) or intellectual disability (<i>p</i> = 0.691). Logistic regression identified abnormal EEG findings as the strongest independent predictor of epilepsy (OR = 48.96, 95% CI: 12.90–190.97), followed by pathogenic variants (OR = 4.38, 95% CI: 1.64–12.10). EEG abnormalities were present in 77.3% of patients with seizures and 6.4% of those without seizures.</p> Conclusion <p>EEG abnormalities and epilepsy are highly prevalent in children with ASD. Abnormal EEG findings and pathogenic genetic variants were strong independent predictors of epilepsy in our cohort. EEG should be strongly considered in children with ASD, particularly those with seizures, developmental regression, unexplained paroxysmal events or pathogenic genetic variants. Prospective studies are needed to determine whether broader, potentially routine EEG at diagnosis is warranted in terms of diagnostic yield, cost-effectiveness and long-term outcomes.</p>

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Neurodevelopmental Assessment, EEG Findings and Epilepsy in Children With Autism Spectrum Disorder: A Retrospective Study

  • 期刊论文

  • 发表日期：

    2026年5月28日

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  • Elif Didinmez Taşkırdı,
  • Müge Baykan,
  • Gonca Özyurt,
  • Pınar Gençpınar,
  • Nihal Olgaç Dündar

摘要

Objective

This study investigated the association between epilepsy and findings from neurological evaluations, including electroencephalography (EEG), neuroimaging, genetic testing, and developmental assessments, in children with Autism Spectrum Disorder (ASD).

Methods

Ninety-nine children with ASD (DSM-5-TR) were retrospectively evaluated at a tertiary center between 2012 and 2021. Data included demographics, EEG, neuroimaging, genetic testing, and developmental assessments.

Results

The cohort was predominantly male (76.8%), with a mean age of 10.2 ± 4.7 years. EEG was performed in 51 patients, with abnormalities detected in 43.1%. Epilepsy was diagnosed in 22.2% (n = 22). Among 42 patients who underwent chromosomal microarray analysis, pathogenic variants were identified in 52.4%. Chi-square analysis showed significant associations between epilepsy and abnormal EEG findings (χ²=45.45, p < 0.001) and pathogenic variants (χ²=7.68, p = 0.006), but not gender (p = 0.823) or intellectual disability (p = 0.691). Logistic regression identified abnormal EEG findings as the strongest independent predictor of epilepsy (OR = 48.96, 95% CI: 12.90–190.97), followed by pathogenic variants (OR = 4.38, 95% CI: 1.64–12.10). EEG abnormalities were present in 77.3% of patients with seizures and 6.4% of those without seizures.

Conclusion

EEG abnormalities and epilepsy are highly prevalent in children with ASD. Abnormal EEG findings and pathogenic genetic variants were strong independent predictors of epilepsy in our cohort. EEG should be strongly considered in children with ASD, particularly those with seizures, developmental regression, unexplained paroxysmal events or pathogenic genetic variants. Prospective studies are needed to determine whether broader, potentially routine EEG at diagnosis is warranted in terms of diagnostic yield, cost-effectiveness and long-term outcomes.