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PURPOSE - Autonomic dysfunction has been reported in autism spectrum disorders (ASD). Less is known about autonomic function during sleep in ASD. The objective of this study is to provide insight into the autonomic cardiovascular control during different sleep stages in ASD. We hypothesized that patients with ASD have lower vagal and higher sympathetic modulation with elevated heart rate, as compared to typical developing children (TD).
METHODS - We studied 21 children with ASD and 23 TD children during overnight polysomnography. Heart rate and spectral parameters were calculated for each vigilance stage during sleep. Data from the first four sleep cycles were used to avoid possible effects of different individual sleep lengths and sleep cycle structures. Linear regression models were applied to study the effects of age and diagnosis (ASD and TD).
RESULTS - In both groups, HR decreased during non-REM sleep and increased during REM sleep. However, HR was significantly higher in stages N2, N3 and REM sleep in the ASD group. Children with ASD showed less high frequency (HF) modulation during N3 and REM sleep. LF/HF ratio was higher during REM. Heart rate decreases with age at the same level in ASD and in TD. We found an age effect in LF in REM different in ASD and TD.
CONCLUSION - Our findings suggest possible deficits in vagal influence to the heart during sleep, especially during REM sleep. Children with ASD may have higher sympathetic dominance during sleep but rather due to decreased vagal influence.
Sleep is a key requirement for an individual's health, though currently the options to study sleep rely largely on manual visual classification methods. In this paper we propose a new scheme for automated offline classification based upon cross-frequency-coupling (CFC) and compare it to the traditional band power estimation and the more recent preferential frequency band information estimation. All three approaches allowed sleep stage classification and provided whole-night visualization of sleep stages. Surprisingly, the simple average power in band classification achieved better overall performance than either the preferential frequency band information estimation or the CFC approach. However, combined classification with both average power and CFC features showed improved classification over either approach used singly.
OBJECTIVES - Standard sleep scoring criteria may be unreliable when applied to critically ill patients. We sought to quantify typical and atypical polysomnographic findings in critically ill patients and to begin development and reliability testing of methodology to characterize the atypical polysomnographic tracings that confound standard sleep scoring criteria.
DESIGN - Prospective convenience sample.
SETTING - Two academic, tertiary care medical centers.
PATIENTS - Thirty-seven critically ill, mechanically ventilated, medical ICU patients.
INTERVENTIONS - None.
MEASUREMENTS AND MAIN RESULTS - Mechanically ventilated subjects were monitored by continuous polysomnography. After noting frequent atypical polysomnographic findings (i.e., lack of stage N2 markers, the presence of polymorphic delta, burst suppression, or isoelectric electroencephalography), attempts to use standard sleep scoring criteria alone were abandoned. Atypical polysomnographic findings were characterized and used to develop a modified scoring system. Polysomnographic data were scored manually via this revised scoring scheme. Of 37 medical ICU patients enrolled, 36 experienced atypical sleep, which accounted for 85% of all recorded data, with 5.1% normal sleep and 9.4% wake. Coupling observed patient arousal levels with polysomnographic characteristics revealed that standard polysomnographic staging criteria did not reliably determine the presence or absence of sleep. Rapid eye movement occurred in only five patients (14%). The revised scoring system incorporating frequently seen atypical characteristics yielded very high interrater reliability (weighted κ = 0.80; bootstrapped 95% CI, [0.48, 0.89]).
CONCLUSIONS - Analysis of polysomnographic data revealed profound deficiencies in standard scoring criteria due to a predominance of atypical polysomnographic findings in ventilated patients. The revised scoring scheme proved reliable in sleep staging and may serve as a building block in future work.
The purpose of this review article is to describe the clinical data linking autism with sleep and epilepsy and to discuss the impact of treating sleep disorders in children with autism either with or without coexisting epileptic seizures. Studies are presented to support the view that sleep is abnormal in individuals with autistic spectrum disorders. Epilepsy and sleep have reciprocal relationships, with sleep facilitating seizures and seizures adversely affecting sleep architecture. The hypothesis put forth is that identifying and treating sleep disorders, which are potentially caused by or contributed to by autism, may impact favorably on seizure control and on daytime behavior. The article concludes with some practical suggestions for the evaluation and treatment of sleep disorders in this population of children with autism.
We report a case of new-onset seizures and narcolepsy in a previously healthy 40-year-old man. He developed severe daytime somnolence and cataplexy over the course of a few months. Brain MRI was normal, and polysomnography with multiple sleep latency testing confirmed a diagnosis of narcolepsy. His HLA haplotype is DQB1*0602 and cerebrospinal fluid analysis showed no detectable hypocretin. Approximately 18 months later, he developed complex partial seizures. Further MRI showed a progressively enlarging lesion involving the left frontotemporal and insular areas. Pathology from a partial resection was consistent with Rasmussen's syndrome. Evaluation for tumor, infectious, and paraneoplastic etiologies was negative. There was no further progression of the residual lesion on serial MRI. Although the pathophysiologic bases of narcolepsy and Rasmussen's syndrome are unknown, they may have an autoimmune basis. This unique case of both disorders in a single patient suggests the possibility of a common underlying disease process.