Sleep scoring based on video-electroencephalography monitoring in an Epileptology Unit: Comparison with polysomnography

Longitudinal, EEG-based assessment of sleep in people with epilepsy: An automated sleep staging algorithm non-inferior to human raters

Objective

There is an unmet need in epilepsy management for tools that measure sleep objectively over long timespans. Subcutaneous EEG is well-suited for the task, but it requires a reliable automatic algorithm. Here, we present and evaluate such an algorithm, and we show clinical examples of how it produces important information.

Methods

A mix of scalp EEG and subcutaneous EEG was used to develop an algorithm to output sleep stages and common sleep parameters. The algorithm was tested on unseen data from 11 healthy subject and 12 people with epilepsy (PwE). Lastly, data (>3months) from three exemplary PwE were analyzed for sleep.

Results

The algorithm proved non-inferior at sleep stage segmentation on data from PwE compared to human raters using scalp EEG. It reached a Cohen's kappa score of 0.8 [CI 0.78 - 0.83] on healthy subjects and on data from PwE it got to 0.705 [CI 0.663---0.744] against rater D and 0.686 [CI 0.632---0.739] against rater E. The three examples showed that useful information can be gained from longitudinal sleep analysis.

Conclusion

Subcutaneous EEG and a sleep algorithm can be employed to effectively review sleep in PwE at a level that is non-inferior compared to human raters.

Significance

This has the potential to make objective sleep parameters available in the clinic as a valuable addition to subjective sleep assessments.

Dreams interrupted: characteristics of REM sleep-associated seizures and status epilepticus

STUDY OBJECTIVES

Seizures are rare in rapid eye movement (REM) sleep. However, seizures sometimes occur in REM sleep, and a small number of focal epilepsy patients display their maximum rate of interictal epileptiform discharges in REM sleep. We sought to systematically identify and characterize seizures in REM sleep.

METHODS

We reviewed all admissions to the epilepsy monitoring unit at the Winnipeg Health Sciences Center over 12 months in 2014-2015. American Academy of Sleep Medicine sleep-stage scoring was initially applied in the standard 30-second epochs. Then, to capture sudden changes in sleep-wake state on shorter timescales that are associated with seizure formation and propagation, we rescored ictal and peri-ictal electroencephalography epochs every 1 second. Patients found to have seizures in REM sleep were subject to chart review spanning 3 years pre- and postadmission.

RESULTS

REM sleep seizures occurred in 3 of 63 patients admitted to the epilepsy monitoring unit. Notably, 1 patient exhibited continuous epileptiform activity, consistent with focal nonconvulsive electrographic status epilepticus, throughout REM sleep cycles for each night of her admission. Otherwise, discrete REM sleep seizures constituted a small fraction of the other patients' total seizures (range 5.0-8.3%), occurred shortly after REM sleep onset from stage N2 sleep, and were manifest as minor epileptic arousals.

CONCLUSIONS

Our results confirm that REM sleep seizures are rare, while highlighting outliers who widen the known spectrum of heterogeneous sleep effects on seizures/epilepsy. We also report, to our knowledge, the first case of paradoxical status epilepticus in REM sleep.

CITATION

McLeod GA, Szelemej PA, Toutant D, McKenzie MB, Ng MC. Dreams interrupted: characteristics of REM sleep-associated seizures and status epilepticus. J Clin Sleep Med. 2025;21(1):23-32.

Clinical Utility of Sleep Recordings During Presurgical Epilepsy Evaluation With Stereo-Electroencephalography: A Systematic Review

SUMMARY

Although the role of sleep in modulating epileptic activity is well established, many epileptologists overlook the significance of considering sleep during presurgical epilepsy evaluations in cases of drug-resistant epilepsy. Here, we conducted a comprehensive literature review from January 2000 to May 2023 using the PubMed electronic database and compiled evidence to highlight the need to revise the current clinical approach. All articles were assessed for eligibility by two independent reviewers. Our aim was to shed light on the clinical value of incorporating sleep monitoring into presurgical evaluations with stereo-electroencephalography. We present the latest developments on the important bidirectional interactions between sleep and various forms of epileptic activity observed in stereo-electroencephalography recordings. Specifically, epileptic activity is modulated by different sleep stages, peaking in non-rapid eye movement sleep, while being suppressed in rapid eye movement sleep. However, this modulation can vary across different brain regions, underlining the need to account for sleep to accurately pinpoint the epileptogenic zone during presurgical assessments. Finally, we offer practical solutions, such as automated sleep scoring algorithms using stereo-electroencephalography data alone, to seamlessly integrate sleep monitoring into routine clinical practice. It is hoped that this review will provide clinicians with a readily accessible roadmap to the latest evidence concerning the clinical utility of sleep monitoring in the context of stereo-electroencephalography and aid the development of therapeutic and diagnostic strategies to improve patient surgical outcomes.

Movement Termination of Slow-Wave Sleep-A Potential Biomarker?

The duration of slow-wave sleep (SWS) is related to the reported sleep quality and to the important variables of mental and physical health. The internal cues to end an episode of SWS are poorly understood. One such internal cue is the initiation of a body movement, which is detectable as electromyographic (EMG) activity in sleep-electroencephalography (EEG). In the present study, we characterized the termination of SWS episodes by movement to explore its potential as a biomarker. To this end, we characterized the relation between the occurrence of SWS termination by movement and individual characteristics (age, sex), SWS duration and spectral content, chronotype, depression, medication, overnight memory performance, and, as a potential neurological application, epilepsy. We analyzed 94 full-night EEG-EMG recordings (75/94 had confirmed epilepsy) in the video-EEG monitoring unit of the EpiCARE Centre Salzburg, Austria. Segments of SWS were counted and rated for their termination by movement or not through the visual inspection of continuous EEG and EMG recordings. Multiple linear regression was used to predict the number of SWS episodes that ended with movement by depression, chronotype, type of epilepsy (focal, generalized, no epilepsy, unclear), medication, gender, total duration of SWS, occurrence of seizures during the night, occurrence of tonic-clonic seizures during the night, and SWS frequency spectra. Furthermore, we assessed whether SWS movement termination was related to overnight memory retention. According to multiple linear regression, patients with overall longer SWS experienced more SWS episodes that ended with movement (t = 5.64; p = 0.001). No other variable was related to the proportion of SWS that ended with movement, including no epilepsy-related variable. A small sample (n = 4) of patients taking Sertraline experienced no SWS that ended with movement, which was significant compared to all other patients (t = 8.00; p < 0.001) and to n = 35 patients who did not take any medication (t = 4.22; p < 0.001). While this result was based on a small subsample and must be interpreted with caution, it warrants replication in a larger sample with and without seizures to further elucidate the role of the movement termination of SWS and its potential to serve as a biomarker for sleep continuity and for medication effects on sleep.

Spotlight on Sleep Stage Classification Based on EEG

The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG], and electromyography [EMG]), derived from the Rechtschaffen and Kales manual, were published in 2007 at the initiative of the American Academy of Sleep Medicine, and regularly updated over years. They offer an important tool to assess objective markers in different types of sleep/wake subjective complaints. With the aims and advantages of simplicity, reproducibility and standardization of practices in research and, most of all, in sleep medicine, they have overall changed little in the way they describe sleep. However, our knowledge on sleep/wake physiology and sleep disorders has evolved since then. High-density electroencephalography and intracranial electroencephalography studies have highlighted local regulation of sleep mechanisms, with spatio-temporal heterogeneity in vigilance states. Progress in the understanding of sleep disorders has allowed the identification of electrophysiological biomarkers better correlated with clinical symptoms and outcomes than standard sleep parameters. Finally, the huge development of sleep medicine, with a demand for explorations far exceeding the supply, has led to the development of alternative studies, which can be carried out at home, based on a smaller number of electrophysiological signals and on their automatic analysis. In this perspective article, we aim to examine how our description of sleep has been constructed, has evolved, and may still be reshaped in the light of advances in knowledge of sleep physiology and the development of technical recording and analysis tools. After presenting the strengths and limitations of the classification of sleep stages, we propose to challenge the "EEG-EOG-EMG" paradigm by discussing the physiological signals required for sleep stages identification, provide an overview of new tools and automatic analysis methods and propose avenues for the development of new approaches to describe and understand sleep/wake states.

Evaluation of Sleep Disturbances in Patients with Nocturnal Epileptic Seizures in a Romanian Cross-Sectional Study

(1) Background: Based on the premise that epilepsy is frequently associated with hypnopathies, in this study we aim to analyze the prevalence of sleep disturbances among patients with epilepsy, with exclusively or predominantly nocturnal seizures, in relation to demographic factors as well as clinical and electroencephalography (EEG) aspects. (2) Methods: 69 patients with nocturnal epilepsy were included in our study. Sleep disturbances were measured with the Pittsburgh Sleep Quality Index (PSQI) questionnaire, followed by a long-term video-EEG monitoring during sleep. We analyzed the PSQI results in relation to patients' gender and age and determined the correlations between the PSQI scores and the modifications on video-EEG recordings, in comparison to a control group of 25 patients with epilepsy but without nocturnal seizures. (3) Results: We found a statistically significant difference between the PSQI of patients with nocturnal seizures compared to those without nocturnal epileptic manifestations. In the experimental group, the mean PSQI score was 7.36 ± 3.91 versus 5.04 ± 2.56 in controls. In women, the average PSQI score was 8.26, whilst in men it only reached 6.41, highlighting a statistically significant difference between genders (p ˂ 0.01). By examining the relationships between the PSQI scores and certain sleep-related factors, evidenced on the nocturnal video-EEG, we found a statistically significant difference between PSQI values of patients who reached the N2 stage, and those who reached the N3 stage of nonrapid eye movement (NREM) sleep, highlighting that those with a more superficial nocturnal sleep also had higher PSQI scores. There were no statistically significant differences regarding the PSQI scores between patients with or without interictal epileptiform discharges, and also in the few patients with nocturnal seizures where we captured ictal activity. (4) Conclusions: we evidenced in this study a poor quality of sleep in patients with nocturnal epilepsy, mostly in women, independent of age. We observed that sleep disturbances were due to superficial and fragmented sleep with frequent microarousals, not necessarily caused by the electrical epileptiform activity.

Semiology, EEG, and neuroimaging findings in temporal lobe epilepsies

Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. First descriptions of TLE date back in time and detailed portraits of epileptic seizures of temporal origin can be found in early medical reports as well as in the works of various artists and dramatists. Depending on the seizure onset zone, several subtypes of TLE have been identified, each one associated with peculiar ictal semiology. TLE can result from multiple etiological causes, ranging from genetic to lesional ones. While the diagnosis of TLE relies on detailed analysis of clinical as well as electroencephalographic (EEG) features, the lesions responsible for seizure generation can be highlighted by multiple brain imaging modalities or, in selected cases, by genetic investigations. TLE is the most common cause of refractory epilepsy and despite the great advances in diagnostic tools, no lesion is found in around one-third of patients. Surgical treatment is a safe and effective option, requiring presurgical investigations to accurately identify the seizure onset zone (SOZ). In selected cases, presurgical investigations need intracerebral investigations (such as stereoelectroencephalography) or dedicated metabolic imaging techniques (interictal PET and ictal SPECT) to correctly identify the brain structures to be removed.