Objectives: To determine the prevalence of epilepsy and the clinical characteristics of children with ASD and epilepsy in a large patient population.
Methods: Cross-sectional study using four large cohorts of children with ASD for a total of 5,815 participants with ASD and 289 participants with co-occurring ASD and epilepsy. Children with and without epilepsy were compared on demographic and clinical characteristics. Multivariate logistic regression was used to examine the association between clinical characteristics and epilepsy.
Results: The prevalence of epilepsy in children with ASD age 2-17 years was 12.5%. In unadjusted analyses, epilepsy was associated with older age, female gender, lower cognitive ability, poorer adaptive and language functioning, and a history of developmental regression. After adjusting for IQ, age was the only characteristic that remained a significant predictor of epilepsy. In a multivariate model adjusting for all variables, age and cognitive ability were strongly and independently associated with epilepsy. Children age 10 or older had 1.61 times the odds of having epilepsy (p <.001), and for a one standard deviation increase in full scale IQ score, the odds of having epilepsy decreased by 48% (p <.001).
Conclusions: This is the largest study to date of clinical correlates in patients with ASD and co-occurring epilepsy. Based on a representative sample of children with ASD, the prevalence of epilepsy was approximately 12%, which is lower than previously reported. The proportion of epilepsy in ASD may be decreasing as the definition of ASD has expanded and the ability to detect cases has improved. Specifically, increases in the diagnosis of ASD in individuals of average or above-average IQ in recent years may have resulted in lower rates of epilepsy in the ASD population. Several clinical correlates of epilepsy were identified including female gender, low cognitive ability, poor adaptive and language functioning, and a history of developmental regression. Through statistical modeling we demonstrated that several of the most-widely reported factors are not predictive after adjusting for IQ. These findings can help guide prognosis and alert clinicians to patients who are at increased risk for epilepsy.
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