Sleep Disruption Worsens Seizures: Neuroinflammation as a Potential Mechanistic Link

Differences in factors associated with insomnia symptoms between patients with epilepsy with and without depressive symptoms

OBJECTIVE

To determine if insomnia-related factors differ depending on the presence of depression in patients with epilepsy.

METHODS

This cross-sectional multicenter study collected data on depressive symptoms, insomnia symptoms, and excessive daytime sleepiness, which were defined as a Patient Health Questionnaire-9 (PHQ-9) score of ≥ 10, an Insomnia Severity Index (ISI) score of ≥ 15, and an Epworth Sleepiness Scale (ESS) of ≥ 11, respectively. Further, uncontrolled seizures were defined as one or more seizures per month during antiseizure medications treatment. A stepwise logistic regression analysis was conducted, with a logistic regression with interaction terms performed to identify differences in insomnia-related factors depending on depressive symptoms.

RESULTS

Of 282 adults with epilepsy (men, 58 %; mean age, 40.4 ± 13.9 years), a PHQ-9 score ≥ 10, an ISI score ≥ 15, an ESS score ≥ 11 were noted in 23.4 % (n = 66), 20.2 % (n = 57), and 12.8 % (n = 36), respectively. More patients with depressive symptoms had an ISI score ≥ 15 (56.1 % vs. 9.3 %; p < 0.001) than those without. In multiple logistic regression, uncontrolled seizures (odds ratio [OR], 4.896; p < 0.01), daytime sleepiness (OR, 5.369; p < 0.05), and a history of psychiatric disorders (OR, 3.971; p < 0.05) were identified as significant factors that were more likely to be associated with an ISI score ≥ 15; however, this was only true in patients without depressive symptoms. In contrast, use of perampanel (OR, 0.282; p < 0.05) was less likely associated, while female sex (OR, 3.178; p < 0.05) was more likely associated with an ISI score ≥ 15 only in patients with depressive symptoms.

CONCLUSIONS

Insomnia-related factors in patients with epilepsy may differ between patients with and without depression. Our findings of different insomnia-related factors based on the presence of depression may facilitate the management of patients with epilepsy.

Transforming Neurology Care Delivery Through a Population Health Data Strategy

Background

With more than 30% of global data originating from health care, deriving usable insights that improve health requires population health analytics. In neurology, data-driven approaches have grown in significance because of digital health records and advanced analytics. A vital aspect of this evolution is adopting a population health data strategy (PHDS).

Recent Findings

Crafting a tailored PHDS for neurology involves cataloging data points and measures spanning demographics, clinical history, genetics, and social determinants. Neurologic outcomes include mortality rates, functional and cognitive abilities, and imaging results. A robust strategy relies on interoperability, advanced analytics, and transparent AI algorithms.

Summary

Neurology is embracing data-driven health care. The PHDS synthesizes diverse patient data to provide personalized care. It includes a wide range of outcome measures to address neurologic complexities. Advanced analytics and collaboration among neurologists, data scientists, and business leaders uncover hidden patterns and promote outcome-driven medicine in the 21st century.

Effective Early Detection of Epileptic Seizures through EEG Signals Using Classification Algorithms Based on t-Distributed Stochastic Neighbor Embedding and K-Means

Epilepsy is a neurological disorder in the activity of brain cells that leads to seizures. An electroencephalogram (EEG) can detect seizures as it contains physiological information of the neural activity of the brain. However, visual examination of EEG by experts is time consuming, and their diagnoses may even contradict each other. Thus, an automated computer-aided diagnosis for EEG diagnostics is necessary. Therefore, this paper proposes an effective approach for the early detection of epilepsy. The proposed approach involves the extraction of important features and classification. First, signal components are decomposed to extract the features via the discrete wavelet transform (DWT) method. Principal component analysis (PCA) and the t-distributed stochastic neighbor embedding (t-SNE) algorithm were applied to reduce the dimensions and focus on the most important features. Subsequently, K-means clustering + PCA and K-means clustering + t-SNE were used to divide the dataset into subgroups to reduce the dimensions and focus on the most important representative features of epilepsy. The features extracted from these steps were fed to extreme gradient boosting, K-nearest neighbors (K-NN), decision tree (DT), random forest (RF) and multilayer perceptron (MLP) classifiers. The experimental results demonstrated that the proposed approach provides superior results to those of existing studies. During the testing phase, the RF classifier with DWT and PCA achieved an accuracy of 97.96%, precision of 99.1%, recall of 94.41% and F1 score of 97.41%. Moreover, the RF classifier with DWT and t-SNE attained an accuracy of 98.09%, precision of 99.1%, recall of 93.9% and F1 score of 96.21%. In comparison, the MLP classifier with PCA + K-means reached an accuracy of 98.98%, precision of 99.16%, recall of 95.69% and F1 score of 97.4%.

Orexin receptor antagonists in the pathophysiology and treatment of sleep disorders and epilepsy

The correlation between sleep and epilepsy has been argued over the past decades among scientists. Although the similarities and contrasts between sleep and epilepsy had been considered, their intertwined nature was not revealed until the nineteenth century. Sleep is recognized as a recurring state of mind and body through alternating brain electrical activities. It is documented that sleep disorders are associated with epilepsy. The origin, suppression, and spread of seizures are affected by sleep. As such, in patients with epilepsy, sleep disorders are a frequent comorbidity. Meanwhile, orexin, a wake-promoting neuropeptide, provides a bidirectional effect on both sleep and epilepsy. Orexin and its cognate receptors, orexin receptor type 1 (OX1R) and type 2 (OX2R), orchestrate their effects by activating various downstream signaling pathways. Although orexin was considered a therapeutic target in insomnia shortly after its discovery, its potential usefulness for psychiatric disorders and epileptic seizures has been suggested in the pre-clinical studies. This review aimed to discuss whether the relationship between sleep, epilepsy, and orexin is clearly reciprocal.

Intricate role of sleep deprivation in modulating depression: focusing on BDNF, VEGF, serotonin, cortisol, and TNF-α

In this review article, we aimed to discuss intricate roles of SD in modulating depression in preclinical and clinical studies. Decades of research have shown the inconsistent effects of SD on depression, focusing on SD duration. However, inconsistent role of SD seems to be more complicated, and SD duration cannot be the only one factor. Regarding this issue, we chose some important factors involved in the effects of SD on cognitive functions and mood including brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), serotonin, cortisol, and tumor necrosis factor-alpha (TNF-α). It was concluded that SD has a wide-range of inconsistent effects on BDNF, VEGF, serotonin, and cortisol levels. It was noted that BDNF diurnal rhythm is significantly involved in the modulatory role of SD in depression. Furthermore, the important role of VEGF in blood-brain barrier permeability which is involved in modulating depression was discussed. It was also noted that there is a negative correlation between cortisol and BDNF that modulates depression. Eventually, it was concluded that TNF-α regulates sleep/wake cycle and is involved in the vulnerability to cognitive and behavioral impairments following SD. TNF-α also increases the permeability of the blood-brain barrier which is accompanied by depressive behavior. In sum, it was suggested that future studies should focus on these mechanisms/factors to better investigate the reasons behind intricate roles of SD in modulating depression.

Clinical Spectrum and Trajectory of Innovative Therapeutic Interventions for Insomnia: A Perspective

Increasing incidences of insomnia in adults, as well as the aging population, have been reported for their negative impact on the quality of life. Insomnia episodes may be associated with neurocognitive, musculoskeletal, cardiovascular, gastrointestinal, renal, hepatic, and metabolic disorders. Epidemiological evidence also revealed the association of insomnia with oncologic and asthmatic complications, which has been indicated as bidirectional. Two therapeutic approaches including cognitive behavioral therapy (CBT) and drugs-based therapies are being practiced for a long time. However, the adverse events associated with drugs limit their wide and long-term application. Further, Traditional Chinese medicine, acupressure, and pulsed magnetic field therapy may also provide therapeutic relief. Notably, the recently introduced cryotherapy has been demonstrated as a potential candidate for insomnia which could reduce pain, by suppressing oxidative stress and inflammation. It seems that the synergistic therapeutic approach of cryotherapy and the above-mentioned approaches might offer promising prospects to further improve efficacy and safety. Considering these facts, this perspective presents a comprehensive summary of recent advances in pathological aetiologies of insomnia including COVID-19, and its therapeutic management with a greater emphasis on cryotherapy.

Psychobehavioural and Cognitive Adverse Events of Anti-Seizure Medications for the Treatment of Developmental and Epileptic Encephalopathies

The developmental and epileptic encephalopathies encompass a group of rare syndromes characterised by severe drug-resistant epilepsy with onset in childhood and significant neurodevelopmental comorbidities. The latter include intellectual disability, developmental delay, behavioural problems including attention-deficit hyperactivity disorder and autism spectrum disorder, psychiatric problems including anxiety and depression, speech impairment and sleep problems. Classical examples of developmental and epileptic encephalopathies include Dravet syndrome, Lennox-Gastaut syndrome and tuberous sclerosis complex. The mainstay of treatment is with multiple anti-seizure medications (ASMs); however, the ASMs themselves can be associated with psychobehavioural adverse events, and effects (negative or positive) on cognition and sleep. We have performed a targeted literature review of ASMs commonly used in the treatment of developmental and epileptic encephalopathies to discuss the latest evidence on their effects on behaviour, mood, cognition, sedation and sleep. The ASMs include valproate (VPA), clobazam, topiramate (TPM), cannabidiol (CBD), fenfluramine (FFA), levetiracetam (LEV), brivaracetam (BRV), zonisamide (ZNS), perampanel (PER), ethosuximide, stiripentol, lamotrigine (LTG), rufinamide, vigabatrin, lacosamide (LCM) and everolimus. Bromide, felbamate and other sodium channel ASMs are discussed briefly. Overall, the current evidence suggest that LEV, PER and to a lesser extent BRV are associated with psychobehavioural adverse events including aggressiveness and irritability; TPM and to a lesser extent ZNS are associated with language impairment and cognitive dulling/memory problems. Patients with a history of behavioural and psychiatric comorbidities may be more at risk of developing psychobehavioural adverse events. Topiramate and ZNS may be associated with negative effects in some aspects of cognition; CBD, FFA, LEV, BRV and LTG may have some positive effects, while the remaining ASMs do not appear to have a detrimental effect. All the ASMs are associated with sedation to a certain extent, which is pronounced during uptitration. Cannabidiol, PER and pregabalin may be associated with improvements in sleep, LTG is associated with insomnia, while VPA, TPM, LEV, ZNS and LCM do not appear to have detrimental effects. There was variability in the extent of evidence for each ASM: for many first-generation and some second-generation ASMs, there is scant documented evidence; however, their extensive use suggests favourable tolerability and safety (e.g. VPA); second-generation and some third-generation ASMs tend to have the most robust evidence documented over several years of use (TPM, LEV, PER, ZNS, BRV), while evidence is still being generated for newer ASMs such as CBD and FFA. Finally, we discuss how a variety of factors can affect mood, behaviour and cognition, and untangling the associations between the effects of the underlying syndrome and those of the ASMs can be challenging. In particular, there is enormous heterogeneity in cognitive, behavioural and developmental impairments that is complex and can change naturally over time; there is a lack of standardised instruments for evaluating these outcomes in developmental and epileptic encephalopathies, with a reliance on subjective evaluations by proxy (caregivers); and treatment regimes are complex involving multiple ASMs as well as other drugs.

Sleep Quality Among Adolescents and Its Relation to Inhalant, Khat, and Internet Use, and Physical Illness: A Community-Based Exploratory Cross-Sectional Study

Sleep-related health problems are under investigated among adolescents in low-income countries, including our country, Ethiopia. Therefore, this study aimed to assess the sleep quality and its associated factors among adolescents aged 10 to 19 years in Ethiopia. A community-based cross-sectional study was conducted among 799 adolescents from May 27 to July 27, 2021, using a systematic random sampling technique. Sleep quality was assessed by using the Petersburg sleep quality index. The data was entered into Epi-data version 3.1 and exported to the Statistical Package for Social Science (SPSS) Version 21. A logistic regression model was used, and variables with a P-value less than .05 in the final fitting model were stated as independent predictors of poor sleep quality (PSQ). About 1 in 3 adolescents (38%) had a poor sleep quality. The rates of inhalant, khat, and internet use disorders were 16%, 38%, and 18%, respectively. Also, 27.4% of adolescents used alcohol as a sleep medication, and 75% of adolescents with internet addiction had PSQ. Moreover, adolescents with physical illness had about 4 times higher odds of association with PSQ (AOR = 3.76 and 95% CI = 2.30-6.15%CI), and inhalant use disorder (AOR = 1.98 and 95% CI = 1.29-3.04%CI), internet addiction (AOR = 3.33 and 95% CI = 2.09-5.30%CI), and khat use disorder (AOR = 1.74 and 95% CI = 1.11-2.73%CI), were positively associated with PSQ. PSQ was higher among adolescents, and problematic inhalants, khat, and internet use and physical illness were risk factors for PSQ.