Autism and Epilepsy Co-Morbidity
Bibliographic record
Abstract
Source: Clarke DF, Roberts W, Daraksan M, et al. The prevalence of autistic spectrum disorder in children surveyed in a tertiary care epilepsy clinic. Epilepsia. 2005;46:1970–1977.The prevalence of autistic spectrum disorder (ASD) in children aged 2–18 years with epilepsy was evaluated at the Tertiary Care Epilepsy Clinic at the Hospital for Sick Children in Toronto, Ontario. Parents were asked to complete 2 questionnaires based on the DSM-IV diagnostic criteria: an autism screening questionnaire (ASQ) addressing age, social interaction, and language development of the child; and a pediatric sleep questionnaire (PSQ) relating to sleep disorders and behavior. Of 290 questionnaires distributed, 107 were returned, and 97 (33%) subjects were included in the study. The mean age was 12.7 years. A diagnosis of ASD had not been previously suspected in the majority. Patients with scores above the ASQ diagnostic cutoff of 15 (31 patients [32%]) were assigned to the ASD group and those with scores below the ASQ cutoff (66 patients [68%]) were included in the non-ASD group. A comparison of ASD and non-ASD groups showed similar mean age (11 years), body mass indices, male sex predominance (61% and 49%), average seizure frequency (10.5 and 5.38 per month), and number with generalized seizures (12/29 [41%] and 29/61 [47%]). Statistically significant differences included younger mean age at first seizure in the ASD group (21 months vs 55 months; P=.0001) and greater mean number of antiepileptic drugs (AEDs) used in the ASD group (1.77±0.80 vs 1.45±0.91; P=.04). An increase in sleep-related problems in the ASD group included an increased frequency of nocturnal arousals (38% vs 17%, P=.06), difficulty in falling back to sleep after arousal (42% vs 18%, P=.02), early morning awakening (55% vs 26%, P=.01), and more daytime sleepiness reported by teachers (73% vs 45%, P=.01). Behavior scores pertaining to attention, hyperactivity, and impulsiveness were worse in the ASD versus non-ASD groups (3.7 vs 2.2, P=.001). Sleep-disordered breathing was strongly associated with a worse mean behavioral score of 3.45 in the ASD group versus 2.17 for non-ASD subjects.Dr. Millichap has disclosed no financial relationship relevant to this commentary. This commentary does not contain a discussion of a commercial product/device. This commentary does not contain a discussion of an unapproved/investigative use of a commercial product/device.The Committee on Children with Disabilities of the American Academy of Pediatrics (AAP) recommends a prolonged sleep-deprived EEG in autistic children with regression.1 Sleep disorders are reported in children with epilepsy,2,3 and in those with autism.4 Sleep EEGs are abnormal in children with autism and subclinical seizures, and treatment with the anticonvulsant valproate results in improvement in language and social skills,5 an observation confirmed in children with autism and epilepsy.6The present report emphasizes the importance of clinical vigilance for symptoms of autism and regression in language and communication in children with an onset of epilepsy. The authors also demonstrate the frequency of sleep and behavioral disorders in children with co-morbid symptoms of epilepsy and ASD. Other co-morbidities associated with epilepsy include ADHD, developmental disabilities, migraines, depression/anxiety, and accidental injury.7 Children with autism and co-morbid cognitive impairment are at higher risk for epilepsy and abnormal EEGs (P<.05), according to a recent retrospective study of 56 patients with autism referred for routine EEG.8Before seizing these results, the limitations of this study are worth noting. The questionnaires used are intended for screening and not definitive diagnosis.9 In addition, the 33% response rate may reflect some selection bias in that parents of children with ASD may have been more likely to participate. On the other hand, even if we assume the non-respondents were 100% non-autistic, the rate of ASD was greater in this population than in the general population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".