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Published on: July 31, 2017
Electroencephalographic abnormalities and clinical phenotypes in children with autism spectrum disorder: a single
Natalia Wizner1, Michał Wizner1, Julia Rokosz1
1Department of Pediatric Neurology, Faculty of Medical Sciences, Students' Scientific Society, Medical University of Silesia, Katowice, Poland.
Insights
Electroencephalographic (EEG) abnormalities in children with autism spectrum disorder (ASD) are linked to sleep disturbances, particularly non-paroxysmal changes. Comorbid epilepsy in ASD is associated with increased intellectual disability, underscoring the need for thorough neurological assessments.
Area of Science:
- Neuroscience
- Pediatric Neurology
- Developmental Psychology
Background:
- Electroencephalographic (EEG) abnormalities are common in children with autism spectrum disorder (ASD), even without clinical seizures.
- The clinical relevance of various EEG patterns in ASD requires further investigation.
Purpose of the Study:
- To explore the relationship between EEG abnormalities and specific clinical features in children diagnosed with ASD.
Main Methods:
- Medical records of 180 children with ASD were analyzed.
- Patients were categorized by epilepsy diagnosis and EEG findings (normal, non-paroxysmal, paroxysmal).
- Clinical variables included developmental milestones, intellectual disability, sleep issues, hyperactivity, sensory integration, aggression, and motor deficits.
Main Results:
- Sleep disorders were significantly associated with EEG pattern type (p=0.041), most common in non-paroxysmal changes (20%).
- Children with epilepsy had higher rates and severity of intellectual disability (p=0.004, p=0.007) and more paroxysmal abnormalities (62% vs 38%, p=0.01).
- No significant associations were found between epilepsy/EEG and speech delay, aggression, sensory integration, or motor deficits after age adjustment.
Conclusions:
- Non-paroxysmal EEG changes may correlate with sleep disorders in children with ASD.
- Comorbid epilepsy in ASD is linked to intellectual disability, necessitating comprehensive neurological evaluation.
- Broader EEG categories showed limited associations, suggesting detailed EEG analysis might reveal subtle correlations.
Background:
Electroencephalographic (EEG) abnormalities are frequently observed in children with autism spectrum disorder (ASD), even in the absence of clinical seizures. However, the clinical significance of different EEG patterns in ASD remains incompletely understood.
Objective:
To investigate associations between EEG abnormalities and selected clinical characteristics in children with ASD.
Methods:
This study analyzed medical records of 180 children with ASD hospitalized at the Pediatric Neurology Department at the Upper Silesian Child Health Center in Katowice. Patients were stratified by epilepsy diagnosis and EEG characteristics (normal, non-paroxysmal changes, paroxysmal changes). Clinical variables analyzed included developmental milestones, intellectual disability severity, sleep disturbances, hyperactivity, sensory integration disorders, aggressive behaviors, and motor deficits. Statistical analysis employed Mann-Whitney U test, Kruskal-Wallis test, and Fisher's exact test as appropriate.
Results:
Sleep disorders showed significant association with EEG pattern type (p = 0.041), occurring most frequently in patients with non-paroxysmal changes (20%) compared to those with paroxysmal changes (5.9%) and normal recordings (7%). Children with comorbid epilepsy demonstrated significantly higher rates and severity of intellectual disability compared to those without epilepsy (p = 0.004 and p = 0.007, respectively). Paroxysmal abnormalities were more prevalent in the epilepsy group (62% versus 38%, p = 0.01). After adjusting for age, no significant associations were found between epilepsy diagnosis or EEG abnormalities and speech delay, aggression, sensory integration disorders, or motor deficits.
Conclusion:
Non-paroxysmal EEG abnormalities may represent a distinct neurophysiological correlate of sleep disorders in children with ASD. Comorbid epilepsy is strongly associated with intellectual disability severity, supporting the need for comprehensive neurological evaluation in this population. While broad categorical EEG patterns did not reveal significant associations with most clinical manifestations in our sample, more granular EEG analysis may detect subtle correlations not apparent with our simplified classification approach.
