Sleep and Epilepsy, Clinical Spectrum and Updated Review

Wu, Ting; Avidan, Alon Y.; Engel, Jerome

doi:10.1016/j.jsmc.2021.02.011

Cited by 12 publications

(5 citation statements)

References 66 publications

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“…Sleep disturbances in particular may be difficult to load on individual factors contributing to TAND symptomology as it may also be driven by factors fully independent of TAND. For example, circadian rhythms are known to be perturbed directly via the mTOR pathway [ 24 ], as well as influenced by epilepsy and anti-seizure medications [ 25 ].…”

Section: Discussionmentioning

confidence: 99%

Symptom rates and profile clustering in tuberous sclerosis complex-associated neuropsychiatric disorders (TAND)

Alperin

Krueger

Franz

et al. 2021

J Neurodevelop Disord

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Background Tuberous Sclerosis Complex (TSC) is associated with a range of neuropsychiatric difficulties, appropriately termed TSC-Associated Neuropsychiatric Disorders (TAND). The objectives of the study were to analyze the rates of TAND symptoms in a cohort of patients seen at the TSC Center of Excellence at Cincinnati Children’s Hospital and to identify clinically meaningful profiles based on TAND symptoms. Methods Data from the TAND Checklist was obtained from participants seen at the TSC Center of Excellence at Cincinnati Children’s Hospital Medical Center from June 2015 to August 2018. Cluster and factor analyses for each TAND symptom were performed. Factor scores were then calculated for participants, and a K-means cluster analysis of these scores was used to empirically identify distinct overall TAND symptom profiles occurring in TSC. Results A total of 1545 checklists was completed for 668 participants (37% adults and 63% children). Approximately 90% of participants reported at least one TAND symptom with an average of 12 symptoms (out of 29). Symptom rates ranged between 5 and 60%. The most common symptoms were neuropsychologic symptoms. A seven-cluster and seven-factor solution were found to be optimal. K-means cluster analysis resulted in a seven-profile solution, ranging from low to high symptom burden. Conclusion This study is the first to identify natural phenotypic profiles of TAND symptoms. Study of specific TAND subpopulations with shared profiles may facilitate better understanding of the underlying biology of TAND and better assessment of more targeted treatments.

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Section: Discussionmentioning

confidence: 99%

Symptom rates and profile clustering in tuberous sclerosis complex-associated neuropsychiatric disorders (TAND)

Alperin

Krueger

Franz

et al. 2021

J Neurodevelop Disord

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“…Such a system allows for the continuous long-term monitoring of brain electrophysiological activity, which can provide useful insights into the long-term dynamics of the signal, and aid in characterizing neuronal changes that influence susceptibility to seizures over extended periods during both wakefulness and sleep [24][25][26]. Given the high comorbidity between epilepsy and sleep disorders [27,28], a practical wearable EEG system could therefore help quantify the relationship between seizures and sleep, leading to more accurate detection and better understanding of epilepsy classification in the short-term [29]. Over the long-term, measuring sleep quality and epileptiform activity during sleep may have a predictive value in determining the likelihood of seizures occurring in the following day [29].…”

Section: Introduction 1advancements and Limitations Of Wearable Syste...mentioning

confidence: 99%

“…Given the high comorbidity between epilepsy and sleep disorders [27,28], a practical wearable EEG system could therefore help quantify the relationship between seizures and sleep, leading to more accurate detection and better understanding of epilepsy classification in the short-term [29]. Over the long-term, measuring sleep quality and epileptiform activity during sleep may have a predictive value in determining the likelihood of seizures occurring in the following day [29].…”

Section: Introduction 1advancements and Limitations Of Wearable Syste...mentioning

confidence: 99%

Optimizing Electrode Configurations for Wearable EEG Seizure Detection Using Machine Learning

Gelbard-Sagiv,

Pardo,

Getter

et al. 2023

Sensors

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Epilepsy, a prevalent neurological disorder, profoundly affects patients’ quality of life due to the unpredictable nature of seizures. The development of a reliable and user-friendly wearable EEG system capable of detecting and predicting seizures has the potential to revolutionize epilepsy care. However, optimizing electrode configurations for such systems, which is crucial for balancing accuracy and practicality, remains to be explored. This study addresses this gap by developing a systematic approach to optimize electrode configurations for a seizure detection machine-learning algorithm. Our approach was applied to an extensive database of prolonged annotated EEG recordings from 158 epilepsy patients. Multiple electrode configurations ranging from one to eighteen were assessed to determine the optimal number of electrodes. Results indicated that the performance was initially maintained as the number of electrodes decreased, but a drop in performance was found to have occurred at around eight electrodes. Subsequently, a comprehensive analysis of all eight-electrode configurations was conducted using a computationally intensive workflow to identify the optimal configurations. This approach can inform the mechanical design process of an EEG system that balances seizure detection accuracy with the ease of use and portability. Additionally, this framework holds potential for optimizing hardware in other machine learning applications. The study presents a significant step towards the development of an efficient wearable EEG system for seizure detection.

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“…Recently, it calls for more attention that anti‐seizure therapies, either anti‐seizure medications or non‐pharmaceutical approaches, can take direct or indirect influence on sleep in patients with epilepsy 2 . With a rapid development in sleep medicine and a wide application of polysomnogram (PSG), the field of sleep disorder in epilepsy has achieved some progress in past decades 3 . In addition, the recent discovery in circuits of sleep–wake control help clinicians to understand and manage sleep disorders 4 .…”

Section: Introductionmentioning

confidence: 99%

“…2 With a rapid development in sleep medicine and a wide application of polysomnogram (PSG), the field of sleep disorder in epilepsy has achieved some progress in past decades. 3 In addition, the recent discovery in circuits of sleep-wake control help clinicians to understand and manage sleep disorders. 4 Here, we give a comprehensive review on recent advances in the effect of anti-seizure therapies on sleep with an aim to optimize these treatments in the future.…”

mentioning

confidence: 99%

Effects of anti‐seizure therapies on sleep in patients with epilepsy: A literature review

Chen

et al. 2022

Acta Neuro Scandinavica

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Sleep disorder is common in epilepsy. With a recent rapid development in sleep medicine, it has been increasingly recognized that anti‐seizure therapies, either anti‐seizure medications (ASMs) or non‐pharmaceutical approaches, can take direct or indirect influence on sleep in patients with epilepsy. Here, we systematically review the effect of anti‐seizure treatments on sleep. ASMs targeting at different sites exerted various effects on both sleep structure and sleep quality. Non‐pharmaceutical treatments including resective surgery, ketogenic diet, and transcranial magnetic stimulation appear to have a positive effect on sleep, while vagus nerve stimulation, deep brain stimulation, and brain‐responsive neurostimulation are likely to interrupt sleep and exacerbate sleep‐disordered breathing. The potential mechanisms underlying how non‐pharmacological approaches affect sleep are also discussed. The limitation of most studies is that they were largely based on small cohorts by short‐term observations. Further well‐designed and large‐scale investigations in this field are warranted. Understanding the effect of anti‐seizure therapies on sleep can guide clinicians to optimize epilepsy treatment in the future.

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Sleep and Epilepsy, Clinical Spectrum and Updated Review

Cited by 12 publications

References 66 publications

Symptom rates and profile clustering in tuberous sclerosis complex-associated neuropsychiatric disorders (TAND)

Symptom rates and profile clustering in tuberous sclerosis complex-associated neuropsychiatric disorders (TAND)

Optimizing Electrode Configurations for Wearable EEG Seizure Detection Using Machine Learning

Effects of anti‐seizure therapies on sleep in patients with epilepsy: A literature review

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