Do sleep-deprived EEG recordings reflect spike index as found in full-night EEG recordings?

Larsson, Pål G.; Evsiukova, Tatiana; Brockmeier, Frans; Ramm-Pettersen, Anette; Eeg‐Olofsson, Orvar

doi:10.1016/j.yebeh.2010.07.021

Cited by 21 publications

(9 citation statements)

References 27 publications

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“…In addition, there is an even more urgent need for controlled trials to assess the effectiveness of treating epileptiform activity in patients with autism. For clinical trials to yield optimal information, a standardized method of assessing epileptiform discharges that will serve as a reliable measure of spike burden, such as the spike index [79], needs to be agreed upon. This will allow quantification of EEG improvement and proper correlation with cognitive and behavioral improvements.…”

Section: Resultsmentioning

confidence: 99%

Interictal epileptiform activity and autism

Ghacibeh

Fields

2015

Epilepsy & Behavior

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Section: Resultsmentioning

confidence: 99%

Interictal epileptiform activity and autism

Ghacibeh

Fields

2015

Epilepsy & Behavior

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“…EEG epileptiform activity during the first 5 min of NREM2 sleep is highly correlated with the EEG epileptiform activity measured overnight (Hadjiloizou et al., 2009 [Abstract]) and we provide further data on the validity of sampling the first 5 min of NREM sleep (Data S1). In the future, shorter EEG recordings including sleep may provide reliable spike counts (Larsson et al., 2010) without the need for overnight EEG recordings. Consequently, tracking the evolution of epileptiform activity over time may become easier and less costly.…”

Section: Discussionmentioning

confidence: 99%

Clinical staging and electroencephalographic evolution of continuous spikes and waves during sleep

et al. 2012

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SUMMARYPurpose: Currently, in continuous spikes and waves during sleep (CSWS) there is a lack of systematic assessments of the clinically relevant stages and the evolution of the electroencephalographic features. The aim of this study is to describe the evolution over time of clinical and electroencephalographic features in CSWS. Methods: We enrolled patients from our video-electroencephalography (EEG) monitoring unit with CSWS and with overnight EEG studies with at least one overnight assessment per year over a minimum period of 3 years. We studied clinical presentation and electroencephalographic features. We calculated the (1) spike-wave percentage (SWP) as the percentage of 1-s bins containing at least one spike-wave complex and (2) spike frequency (SF) as the number of spikes per 100 s. Key Findings: Nine children (six boys) met the inclusion criteria during a 15-year period. Seven (78%) had an abnormal development prior to the epilepsy onset, and in two (22%) seizures were the only presenting symptom. Median age at epilepsy onset was 2 years (range 2 days to 4 years), at neuropsychological regression 5.1 years (4-7.7 years), and at seizure freedom 8.6 years (6.5-11.4 years). Median duration and range of clinically relevant stages were as follows: dormant stage (birth-epilepsy onset median 2 years, range 2 days-4 years), prodromal stage (epilepsy onset-neuropsychological regression 3.9 years, range 0.9-7.7 years), acute stage (neuropsychological regression-seizure freedom 2.9 years, range 2.1-6.6 years), and residual stage (after seizure freedom). Seven patients (78%) had a structural lesion on neuroimaging. At last follow-up (median 11.4 years, range 7.2-20.3 years), eight patients (89%) were receiving antiepileptic treatment, and all patients had residual neurocognitive deficits. During the acute stage, SWP was <85% in 13 (42%) of 31 assessments, and after seizure freedom, 3 of 5 patients (60%) had SWP >85%. Evolution of electroencephalographic patterns included increasing-decreasing, continuously elevated, and fluctuating patterns (33.3% each). There was good correlation between SWP and SF (Spearman correlationcoefficient = 0.942; p < 0.0001). SF, which can exceed 100%, reflected changes in electroencephalography pattern in more detail than SWP, which cannot exceed 100% and therefore has a ceiling effect. Significance: Our series systematically studied the age of occurrence of the significant clinical events. These may assist in defining clinical stages, which can provide a useful framework for future clinical trials in patients with CSWS. The severity of the epileptiform discharges on EEG did not always correlate with seizure frequency and severity; epileptiform discharges could be prominent after seizure freedom and fluctuated along the course of the disease. The values of SWP and SF correlated well, but SWP based on 1-s bins has the potential disadvantage of a ceiling effect.

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“…Indeed, ESES can be diagnosed only when there is evidence of an appearance or worsening of a neuropsychological impairment, associated with a striking increase of the epileptic activity during sleep. Quantitative variation of the epileptiform activity during the night is sporadically mentioned (Tassinari et al, 2000;Galanopoulou et al, 2000;Larsson et al, 2010), most often reporting an increase of the epileptic activity during the first part of the night. An accentuation of the epileptic discharges can be observed in the period preceding the sleep onset (figure 9).…”

Section: Measures In Eses Eeg Recording Techniques In Esesmentioning

confidence: 99%

EEG features in Encephalopathy related to Status Epilepticus during slow Sleep

Gardella

Cantalupo

Larsson

et al. 2019

Epileptic Disorders

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Encephalopathy related to Status Epilepticus during slow Sleep (ESES) is a peculiar electro‐clinical condition, with variable etiologies, characterized by an age‐dependent phenomenon of extreme activation of epileptic activity during sleep, i.e. “status epilepticus during sleep”, that is strictly associated with the appearance of cognitive and behavioral disturbances. Even though the peculiar EEG picture is fundamental for the diagnosis of ESES, clear‐cut and shared diagnostic criteria for defining the EEG boundaries of this syndrome are still lacking. The diagnosis of ESES can be further complicated by the variability of the EEG findings, that during the course of the disease can change from diffuse to more or less focal and viceversa, depending both on the spontaneous clinical evolution of this condition and/or on the effects of medications. Given the complexity and the heterogeneity of EEG parameters during the ESES course, it is important to correlate the EEG findings with the concomitant cognitive and behavioral status, possibly taking into account not only the spike‐wave index, but also other parameters, such as for instance the topography of the epileptic abnormalities, their patterns of spread, and their fluctuations over time. Moreover, the epileptiform activity not only during sleep, but also during wakefulness, the presence of focal slowing, the organization of the EEG background and a derangement of the sleep architecture may play a role in determining the clinical picture.

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Do sleep-deprived EEG recordings reflect spike index as found in full-night EEG recordings?

Cited by 21 publications

References 27 publications

Interictal epileptiform activity and autism

Interictal epileptiform activity and autism

Clinical staging and electroencephalographic evolution of continuous spikes and waves during sleep

EEG features in Encephalopathy related to Status Epilepticus during slow Sleep

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