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Equal and differential antiepileptic drug (AED) dosing in nocturnal epilepsy. Equal (ED) and differential (DD) dosing of the AED carbamazepine used to treat nocturnal tonic-clonic epilepsy. The daytime peaks of serum drug levels associated with DD are lower than in ED. Nighttime levels are higher with DD when seizures are known to peak. Referenced from Guilhoto et al. 4
Source publication
Antiepileptic drug (AED) chronotherapy involves the delivery of a greater AED dose at the time of greatest seizure susceptibility usually associated with predictable seizure peaks. Although research has proven AED chronotherapy, commonly known as differential dosing, to be safe, well tolerated, and highly effective in managing cyclic seizure patter...
Citations
... Chronotherapy emphasizes that time-of-day-specific treatment is critical for maximizing therapeutic efficacies and minimizing side effects [21]. In epilepsy, differential dosing of AEDs at the circadian-modulated seizure peak is an effective means of chronotherapy [22]. Evidence has demonstrated that differentially dosing AEDs improves seizure control and prevents drug resistance [23,24]. ...
Epilepsy is a neurological disorder characterized by hypersynchronous recurrent neuronal activities and seizures, as well as loss of muscular control and sometimes awareness. Clinically, seizures have been reported to display daily variations. Conversely, circadian misalignment and circadian clock gene variants contribute to epileptic pathogenesis. Elucidation of the genetic bases of epilepsy is of great importance because the genetic variability of the patients affects the efficacies of antiepileptic drugs (AEDs). For this narrative review, we compiled 661 epilepsy-related genes from the PHGKB and OMIM databases and classified them into 3 groups: driver genes, passenger genes, and undetermined genes. We discuss the potential roles of some epilepsy driver genes based on GO and KEGG analyses, the circadian rhythmicity of human and animal epilepsies, and the mutual effects between epilepsy and sleep. We review the advantages and challenges of rodents and zebrafish as animal models for epileptic studies. Finally, we posit chronomodulated strategy-based chronotherapy for rhythmic epilepsies, integrating several lines of investigation for unraveling circadian mechanisms underpinning epileptogenesis, chronopharmacokinetic and chronopharmacodynamic examinations of AEDs, as well as mathematical/computational modeling to help develop time-of-day-specific AED dosing schedules for rhythmic epilepsy patients.
... Apart from optimizing the administration timing of ASMs according to the circadian rhythms, the pharmacokinetic characteristics should also be taken into account, including the absorption, metabolism, distribution and elimination of the drugs [14]. This chronotherapy has been applied in several chronic diseases with a circadian pattern, including epilepsy [126]. One study investigated whether clobazam treatment tailored to the timing of seizures could improve seizure control in 27 epileptic patients. ...
Evidence about the interaction between circadian rhythms (CR) and epilepsy has been expanded with the application of advanced detection technology. An adequate understanding of how circadian system and epilepsy interact with each other could contribute to more accurate seizure prediction as well as rapid development of potential treatment timed to specific phases of CR. In this review, we present the reciprocal relationship between CR and epileptic activities from aspects of sleep effect, genetic modulation and brain biochemistry. It has been found that sleep-wake patterns, circadian timing systems and multidien rhythms have essential roles in seizure activities and interictal epileptiform discharge (IED). For instance, specific distribution patterns of seizures and IED have been reported, i.e., lighter non-rapid eye movement (NREM) sleep stage (stage 2) induces seizures while deeper NREM sleep stage (stage 3) activates IEDs. Furthermore, the epilepsy type, seizure type and seizure onset zone can significantly affect the rhythms of seizure occurrence. Apart from the common seizure types, several specific epilepsy syndromes also have a close correlation with sleep-wakefulness patterns. Sleep influences the epilepsy rhythm, and conversely, epilepsy alters the sleep rhythm through multiple pathways. Clock genes accompanied by two feedback loops of regulation have an important role in cortical excitability and seizure occurrence, which may be involved in the mTORopathy. The suprachiasmatic nuclei (SCN) has a rhythm of melatonin and cortisol secretion under the circadian pattern, and then these hormones can feed back into a central oscillator to affect the SCN-dependent rhythms, leading to variable but prominent influence on epilepsy. Furthermore, we discuss the precise predictive algorithms and chronotherapy strategies based on different temporal patterns of seizure occurrence for patients with epilepsy, which may offer a valuable indication for non-invasive closed-loop treatment system. Optimization of the time and dose of antiseizure medications, and resynchronization of disturbed CR (by hormone therapy, light exposure, ketogenic diet, novel small molecules) would be beneficial for epileptic patients in the future. Before formal clinical practice, future large-scale studies are urgently needed to assist prediction and treatment of circadian seizure activities and address unsolved restrictions.
... One approach includes tailoring medication schedules with differential dosing times, without increasing the total daily dose of medication, to enable drug availability during periods of higher seizure susceptibility over the course of a day. Chronotherapy using anti-seizure medication is safe, effective, and well tolerated in children with epilepsy [132]. In a study of refractory epilepsy patients with nighttime and/or early morning seizures treated with clobazam, patients given differential clobazam dosing at night had a median seizure reduction of 75%, compared to 50% in controls (p < 0.005) [133]. ...
... Seizure diaries can be helpful in tracking seizure frequency but can be unreliable and subject to inaccuracies [135]. Wearable devices (e.g., Brain Sentinel [136], Empatica [132]) use automatic seizure detection algorithms to sense physiological parameters (e.g., heart rate, Fig. 1 Cyclical patterns in epilepsy. A Ultradian cycles occur during sleep. ...
Purpose of Review
To review the mutual interactions between sleep and epilepsy, including mechanisms of epileptogenesis, the relationship between sleep apnea and epilepsy, and potential strategies to treat seizures.
Recent Findings
Recent studies have highlighted the role of functional network systems underlying epileptiform activation in sleep in several epilepsy syndromes, including absence epilepsy, benign focal childhood epilepsy, and epileptic encephalopathy with spike-wave activation in sleep. Sleep disorders are common in epilepsy, and early recognition and treatment can improve seizure frequency and potentially reduce SUDEP risk. Additionally, epilepsy is associated with cyclical patterns, which has led to new treatment approaches including chronotherapy, seizure monitoring devices, and seizure forecasting. Adenosine kinase and orexin receptor antagonists are also promising new potential drug targets that could be used to treat seizures.
Summary
Sleep and epilepsy have a bidirectional relationship that intersects with many aspects of clinical management. In this article, we identify new areas of research involving future therapeutic opportunities in the field of epilepsy.
... If, for example, particular interictal EEG signatures predict more severe seizures, and these signatures are also influenced by AED dose, then one can hypothesise that responsively adapting AED dose according to these interictal signatures might decrease seizure severity. If this hypothesis can be verified, then ondemand drug-delivery systems programmed to respond to patient-specific interictal signatures could become the next generation of epilepsy treatments (Carney, Stanley, & Talathi, 2014;Manganaro, Loddenkemper, & Rotenberg, 2017;Ramgopal, Thome-Souza, & Loddenkemper, 2013). ...
Epilepsy is recognised as a dynamic disease, where both seizure susceptibility and seizure characteristics themselves change over time. Specifically, we recently quantified the variable electrographic spatio-temporal seizure evolutions that exist within individual patients. This variability appears to follow subject-specific circadian, or longer, timescale modulations. It is therefore important to know whether continuously recorded interictaliEEG features can capture signatures of these modulations over different timescales. In this study, we analyse continuous intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over timescales ranging from minutes up to 12 days. As expected and in agreement with previous studies, we find that all subjects show a circadian fluctuation in their iEEG band power. We additionally detect other fluctuations of similar magnitude on subject-specific timescales. Importantly, we find that a combination of these fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level. These results suggest that subject-specific fluctuations in iEEG band power over timescales of minutes to days may serve as markers of seizure modulating processes. We hope that future study can link these detected fluctuations to their biological driver(s). There is a critical need to better understand seizure modulating processes, as this will enable the development of novel treatment strategies that could minimise the seizure spread, duration or severity and therefore the clinical impact of seizures.
... ASD chronotherapy, termed differential dosing, is well tolerated, safe, and effective in managing recurring seizure patterns in certain epilepsies in children [161]. Using a clobazam dosing regimen, which is tailored to the timing of patients' seizures, improves its efficacy in controlling seizures. ...
Despite progress in the development of anti-seizure drugs, drug-resistant epilepsy (DRE) occurs in a third of patients. DRE is associated with poor quality of life and increased risk of sudden, unexplained death. The autonomic nervous system and chronobiology play a role in DRE. In the present paper, we provide a narrative review the mechanisms that underlie DRE and characterize some of the autonomic- and chronotherapy-associated parameters that contribute to the degree of response to therapy. Variability describes the functions of many biological systems, which are dynamic and continuously change over time. These systems are required for responses to continuing internal and external triggers, in order to maintain homeostasis and normal function. Both intra- and inter-subject variability in biological systems have been described. We present a platform, which comprises a personalized-based machine learning closed loop algorithm built on epilepsy-related signatures, autonomic signals, and chronotherapy, as a means for overcoming DRE, improving the response, and reducing the toxicity of current therapies.
... Currently, regimens to treat a number of chronic medical conditions are beginning to apply concepts related to chronotherapy, including asthma (178,179), hypertension (180), and type 2 diabetes (181,182). The premise of chronotherapy is to administer drugs (or other interventions) at strategic points of patients' circadian rhythms, particularly time periods when the chronic condition is most severe or when the drug would exhibit optimal bioavailability or effectiveness (183). ...
Seizure patterns observed in patients with epilepsy suggest that circadian rhythms and sleep/wake mechanisms play some role in the disease. This review addresses key topics in the relationship between circadian rhythms and seizures in epilepsy. We present basic information on circadian biology, but focus on research studying the influence of both the time of day and the sleep/wake cycle as independent but related factors on the expression of seizures in epilepsy. We review studies investigating how seizures and epilepsy disrupt expression of core clock genes, and how disruption of clock mechanisms impacts seizures and the development of epilepsy. We focus on the overlap between mechanisms of circadian-associated changes in SCN neuronal excitability and mechanisms of epileptogenesis as a means of identifying key pathways and molecules that could represent new targets or strategies for epilepsy therapy. Finally, we review the concept of chronotherapy and provide a perspective regarding its application to patients with epilepsy based on their individual characteristics (i.e., being a “morning person” or a “night owl”). We conclude that better understanding of the relationship between circadian rhythms, neuronal excitability, and seizures will allow both the identification of new therapeutic targets for treating epilepsy as well as more effective treatment regimens using currently available pharmacological and non-pharmacological strategies.
... Seizures may occur preferentially from different sleep stages [50], and REM-related interictal discharges may have a particular importance in epilepsy localization [51]. Automated sleep scoring paired with seizure or spike detection could be particularly useful for chronotherapy in epilepsy, where medications are specifically given at times when a particular patient is at greatest risk for having seizures, or when the greatest amount of epileptiform activity is noted to occur [52]. Automated sleep scoring of EEG recordings may also be of major help to clinicians and researchers in the epilepsy and neurophysiology community. ...
Study Objectives
Develop a high-performing, automated sleep scoring algorithm that can be applied to long-term scalp electroencephalography (EEG) recordings.
Methods
Using a clinical dataset of polysomnograms from 6,431 patients (MGH-PSG dataset), we trained a deep neural network to classify sleep stages based on scalp EEG data. The algorithm consists of a convolutional neural network (CNN) for feature extraction, followed by a recurrent neural network (RNN) that extracts temporal dependencies of sleep stages. The algorithm’s inputs are 4 scalp EEG bipolar channels (F3-C3, C3-O1, F4-C4, C4-O2), which can be derived from any standard PSG or scalp EEG recording. We initially trained the algorithm on the MGH-PSG dataset and used transfer learning to fine-tune it on a dataset of long-term (24-72 hour) scalp EEG recordings from 112 patients (scalpEEG dataset).
Results
The algorithm achieved a Cohen’s kappa of 0.74 on the MGH-PSG holdout testing set and cross-validated Cohen’s kappa of 0.78 after optimization on the scalpEEG dataset. The algorithm also performed well on two publicly available PSG datasets, demonstrating high generalizability. Performance on all datasets was comparable to the inter-rater agreement of human sleep staging experts (Cohen’s kappa ~ 0.75±0.11). The algorithm’s performance on long-term scalp EEGs was robust over a wide age range and across common EEG background abnormalities.
Conclusion
We developed a deep learning algorithm that achieves human expert level sleep staging performance on long-term scalp EEG recordings. This algorithm, which we have made publicly available, greatly facilitates the use of large long-term EEG clinical datasets for sleep-related research.
... Further, they often have poor prognoses in terms of seizure control, along with higher morbidity and mortality [115]. Drug resistance is a risk factor in status epilepticus and sudden death in epilepsy [116]. As the duration of the disease increases, there is a risk of drug resistance and polypharmacy. ...
Abstract Randomness is far from a disturbing disorder in nature. Rather, it underlies many processes and functions. Randomness can be used to improve the efficacy of development and of systems under certain conditions. Moreover, valid unpredictable random-number generators are needed for secure communication, rendering predictable pseudorandom strings unsuitable. This paper reviews methods of generating randomness in various fields. The potential use of these methods is also discussed. It is suggested that by disordering a “false order,” an effective disorder can be generated to improve the function of systems.
Objective: The objective of this study was to determine frequency of abnormal EEG findings in children from 1 month to 16 years of age presenting with epilepsy to Shifa International Hospital Islamabad. Study Design: It was a cross-sectional study. Setting: Research was conducted at Department of Pediatric Medicine, Shifa International Hospital Islamabad Duration: Duration of study was 6 months from 31st May 2018 to 30th November 2018. Material and Methods: This study involved 217 children of both genders aged between 1 month to 16 years diagnosed of epilepsy who were evaluated by EEG which was labeled abnormal if the wave frequency was 7 MHz or less. A written informed consent was obtained from parents of each patient. Results: The mean age of the children was 7.3±4.4 years. Majority (n=106, 48.8%) of the children were aged 5 years and under followed by 57 (26.3%) children aged between 6-10 years and 54 (24.9%) children aged between 11-16 years. There were 131 (60.4%) male and 86 (39.6%) female children in the study group with a male to female ratio of 1.5:1. Generalized seizures were most frequent type of seizures and were observed in 173 (79.7%) children followed by partial (10.6%), absence (7.4%) and unprovoked (2.3%) seizures. The duration of epilepsy ranged from 1 to 24 months with a mean of 10.8±6.5 months. Abnormal EEG was noted in 170 (78.3%) children with epilepsy. There was no statistically significant difference in the frequency of abnormal EEG across various subgroups based on child’s age (p-value=0.989), gender (p-value=0.900) and duration (p-value=0.958) and type of epilepsy (p-value=0.992). Conclusion: Abnormal EEG was observed in a substantial proportion of children with epilepsy which advocates preferred use of EEG in the diagnostic evaluation of such children owing to its non-invasive nature, low cost and widespread availability. Keywords: Epilepsy, Seizures, Electroencephalography
