Effects of antiepileptic treatment on sleep and seizures in nocturnal frontal lobe epilepsy

A-phase index: an alternative view for sleep stability analysis based on automatic detection of the A-phases from the cyclic alternating pattern

STUDY OBJECTIVES

Sleep stability can be studied by evaluating the cyclic alternating pattern (CAP) in electroencephalogram (EEG) signals. The present study presents a novel approach for assessing sleep stability, developing an index based on the CAP A-phase characteristics to display a sleep stability profile for a whole night's sleep.

METHODS

Two ensemble classifiers were developed to automatically score the signals, one for "A-phase" and the other for "non-rapid eye movement" estimation. Both were based on three one-dimension convolutional neural networks. Six different inputs were produced from the EEG signal to feed the ensembles' classifiers. A proposed heuristic-oriented search algorithm individually tuned the classifiers' structures. The outputs of the two ensembles were combined to estimate the A-phase index (API). The models can also assess the A-phase subtypes, their API, and the CAP cycles and rate.

RESULTS

Four dataset variations were considered, examining healthy and sleep-disordered subjects. The A-phase average estimation's accuracy, sensitivity, and specificity range was 82%-87%, 72%-80%, and 82%-88%, respectively. A similar performance was attained for the A-phase subtype's assessments, with an accuracy range of 82%-88%. Furthermore, in the examined dataset's variations, the API metric's average error varied from 0.15 to 0.25 (with a median range of 0.11-0.24). These results were attained without manually removing wake or rapid eye movement periods, leading to a methodology suitable to produce a fully automatic CAP scoring algorithm.

CONCLUSIONS

Metrics based on API can be understood as a new view for CAP analysis, where the goal is to produce and examine a sleep stability profile.

The interaction between circadian rhythm and epilepsy

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.

Autosomal dominant sleep-related hypermotor epilepsy associated with a novel mutation of KCNT1

Autosomal dominant sleep-related hypermotor epilepsy (ADSHE) is characterized by severe sleep-related rigid hypermotor seizures. The pathogenic genes of ADSHE include genes encoding subunits of the neuronal nicotinic acetylcholine receptor, KCNT1, DEPDC5, NPRL2/3, CABP4, and CRH. Individuals with KCNT1-related ADSHE are more likely to develop seizures at a younger age, have cognitive comorbidity, and display psychiatric and behavioral problems. In this study, a 12-year-old Chinese girl was referred for genetic evaluation of grand mal seizures. She had paroxysmal convulsions of the limbs and loss of consciousness just after falling asleep without obvious triggers. A novel heterozygous missense mutation c.2797C > T (p.Arg933Cys) in exon 24 of the KCNT1 was identified in the proband by whole-exome sequencing and Sanger sequencing, and the clinical symptoms were compatible with ADSHE. The proband’s father has been showing similar symptoms for more than 20 years and had the same site mutation. Her mother and sister were physically and genetically normal. The study revealed a novel variant in the KCNT1 and expanded the mutation spectrum for this clinical condition. Our results provide further evidence supporting a causative role in KCNT1 variants in ADSHE.

Non-rapid eye movement sleep instability in adults with epilepsy: a systematic review and meta-analysis of cyclic alternating pattern

STUDY OBJECTIVES

Epilepsy is characterized by disrupted sleep architecture. Studies on sleep macro- and microstructure revealed that patients with epilepsy experience disturbed rapid eye movement (REM) sleep; however, no consensus has been reached on non-REM (NREM) sleep changes. Cyclic alternating pattern (CAP) is a marker of sleep instability that occurs only during NREM sleep. This meta-analysis investigated CAP differences between patients with epilepsy and healthy controls.

METHODS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines in searching PubMed, Embase, and Cochrane Central database for studies comparing polysomnographic sleep microstructures between patients with epilepsy and healthy controls. A meta-analysis using a random-effects model was performed. We compared CAP rates, percentages of phase A1, A2, A3 subtypes, and phase B durations between patients with epilepsy and healthy controls.

RESULTS

A total of 11 studies, including 209 patients with epilepsy and 197 healthy controls, fulfilled the eligibility criteria. Compared with healthy controls, patients with epilepsy had significantly increased CAP rates and decreased A1 subtype percentages, and patients with sleep-related epilepsy had increased A3 subtype percentages. Subgroup analyses revealed that antiseizure medications (ASMs) decreased CAP rates and increased phase B durations but did not affect the microstates of phase A in patients with sleep-related epilepsy.

CONCLUSIONS

This meta-analysis detected statistically significant differences in CAP parameters between patients with epilepsy and healthy controls. Our findings suggest patients with epilepsy experience NREM sleep instability. ASMs treatment may decrease NREM instability but did not alter the microstates of phase A.

Factors determining the long-term compliance with PAP therapy in patients with sleep-related epilepsy

INTRODUCTION

In adult patients with epilepsy, treatment of comorbid obstructive sleep apnea syndrome (OSAS) by positive airway pressure (PAP) therapy results in improvements in the control of seizures. This is the first study investigating the long-term compliance with PAP therapy in patients with sleep-related epilepsy and OSAS.

METHODS

In this longitudinal study, patients with sleep-related epilepsy and OSAS were followed-up for five years. The compliance with PAP therapy was defined as the use of PAP therapy for at least four hours per night for more than 70 % of nights.

RESULTS

A total of 58 patients with sleep-related epilepsy and OSAS completed study protocol. Eleven patients (19.0 %) refused PAP treatment for OSAS, and 13 patients (22.3 %) showed irregular use. Remaining 34 patients (58.7 %) were compliant with PAP therapy. Females were found to be more compliant than males (p = 0.027), while the age was not found to correlate with the compliance (p = 0.721). Epilepsy-related factors including the types of seizures, whether pure sleep-related or mixed (p = 0.403), localization (p = 0.920) or lateralization (p = 0.697) of discharges, showed no effect on the compliance with PAP therapy. On the other hand, patients with a lower number of seizures (p = 0.042) or with a lower seizure frequency (p = 0.048) showed better compliance with PAP therapy. Polysomnographic parameters including severity of OSAS failed to show a significant correlation.

CONCLUSION

Our findings showed that about two thirds of the study population was compliant with PAP therapy after a mean follow-up duration of almost three years. Newly-diagnosed patients, mostly females, with a lower number of total seizures and lower seizure frequency seem to be more compliant with PAP therapy, which implies the significance of investigation and treatment of OSAS as early as possible in the patients with sleep-related seizures.

Commonalities and Differences in NREM Parasomnias and Sleep-Related Epilepsy: Is There a Continuum Between the Two Conditions?

Introduction: Differential diagnosis between disorders of arousal (DoA) and sleep-related hypermotor epilepsy (SHE) often represents a clinical challenge. The two conditions may be indistinguishable from a semiological point of view and the scalp video-polysomnography is often uninformative. Both disorders are associated with variable hypermotor manifestations ranging from major events to fragments of a hierarchical continuum of increasing intensity, complexity, and duration. Given their semiological overlap we decided to explore the sleep texture of DoA and SHE seeking for similarities and differences.

Methods: We analyzed sleep macrostructure and CAP (cyclic alternating pattern) parameters in a cohort of 35 adult DoA patients, 40 SHE patients and 24 healthy sleepers, all recorded and scored in the same sleep laboratory. Nocturnal behavioral manifestations included minor motor events, paroxysmal arousals and major attacks in SHE, and simple, rising, or complex arousal movements in DoA.

Results: Compared to healthy controls, DoA and SHE showed similar amounts of sleep efficiency, light sleep, deep sleep, REM sleep, CAP subtypes. Both groups also showed slow wave sleep fragmentation and an increased representation of stage N3 in the second part of the night. The only discriminating elements between the two conditions regarded sleep length (more reduced in DoA) and sleep instability (more elevated in SHE). In DoA recordings, all motor episodes arose from NREM sleep: 37% during light NREM stages and 63% during stage N3 (simple arousal movements: 94%). In SHE recordings, 57% of major attacks occurred during stage N3.

Conclusions: So far, emphasis has been placed on the differentiation of sleep-related epilepsy and NREM arousal disorders. However, the impressive analogies between DoA and SHE suggest the existence of an underestimated continuum across the conditions, linked by increased levels of sleep instability, higher amounts of slow wave sleep and NREM/REM sleep imbalance. Sleep texture is extremely similar in the two conditions, although CAP metrics disclose quantitative differences. In particular, SHE patients show a higher arousal instability compared to DoA subjects. Given their clinical and epidemiological overlap, a common genetic background is also hypothesized. In such a perspective, we suggest that the consolidated dichotomy DoA vs. SHE should be reappraised.

Objectively measured sleep-wake patterns in patients with drug-resistant epilepsy - Interaction with quality of life and antiepileptic treatment

RATIONALE

Patients with epilepsy experience frequent episodes of fragmented sleep which may contribute to chronic sleep loss. Enhancing sleep patterns might lead to improved quality of life in these patients. Currently, unlike some other antiepileptic drugs (AEDs), there are no data on the effects of clobazam, a novel AED on sleep. Therefore, we tested the hypothesis that patients with epilepsy will have longer, more consolidated sleep after treatment with clobazam.

METHODS

In this prospective study, we included adults with drug-resistant epilepsy who were being considered for treatment with clobazam. Patients with known untreated moderate/severe sleep apnea or with major circadian rhythm disorders were excluded. We tested a set of the following subjective sleep measures: Pittsburgh Sleep Quality Inventory (PSQI), Epworth Sleepiness Scale (ESS), Karolinska Sleepiness Scale (KSS), Insomnia Severity Index (ISI), and Quality of Life in Epilepsy (QOLIE) prior to starting the treatment, as well as after achieving a stable clobazam dose. We also measured sleep pattern using wrist actigraphy - before starting therapy and after achieving stable dose.

RESULTS

A total of 12 participants completed all parts of the study. After treatment, a lower number of awakenings and less wake after sleep onset (WASO) were seen, as well as a lower number of seizures. Average pretreatment bedtime was 23:45, and average wake time was 8:24. A higher seizure frequency significantly correlated with all subjective sleep measures, as well as with a higher amount actigraphy measured WASO and less total sleep time (TST) measured both by sleep log and by actigraphy. Those with higher baseline WASO by actigraphy also had more depressive symptoms, worse quality of life, longer duration of epilepsy, and a higher seizure frequency.

CONCLUSION

Both objective and subjective sleep metrics correlate with depressive symptoms and quality of life. After treatment, there were fewer awakenings as well as fewer seizures.

Sleep-related hypermotor epilepsy: prevalence, impact and management strategies

Sleep-related hypermotor epilepsy (SHE), previously called nocturnal frontal lobe epilepsy (NFLE), is a focal epilepsy characterized by asymmetric tonic/dystonic posturing and/or complex hyperkinetic seizures occurring mostly during sleep. SHE fulfills the definition of rare disease with an estimated minimum prevalence of 1.8/100,000 individuals, and it represents about 10% of drug-resistant surgical cases. Although SHE and autosomal-dominant SHE (ADSHE) have been considered benign epileptic conditions for a long time, emerging data have shed light on the severity of this disorder and some peculiar features can impact negatively on the quality of life of SHE patients. In fact, seizure frequency can be very high, resulting in nocturnal sleep fragmentation with possible diurnal consequences such as excessive sleepiness and fatigue. Moreover, recent studies, adopting a systematic neuropsychological assessment, have shown deficits in memory, executive functions and visuo-spatial abilities in almost half of SHE patients. Intellectual disabilities and psychiatric disorders have also been reported in some genetic forms. SHE may also exert a negative effect on health-related quality of life, especially in domains pertaining to a patient's role in the family, social context and patient's illness experience. Despite a good response to pharmacological treatment, especially with carbamazepine, 30% of SHE patients suffer from drug-resistant seizures. Finally, recent studies suggest a poor prognosis in a high percentage of SHE patients with a 20.4% cumulative probability of achieving terminal remission at 10 years from onset. For selected drug-resistant SHE patients, epilepsy surgery is the only treatment offering high probability of recovery, both for seizures and for epilepsy-related sleep alterations.

Cyclic alternating pattern and interictal epileptiform discharges during morning sleep after sleep deprivation in temporal lobe epilepsy

PURPOSE

Sleep deprivation (SD) increases the occurrence of interictal epileptiform discharges (IED) compared to basal EEG in temporal lobe epilepsy (TLE). In adults, EEG after SD is usually performed in the morning after SD. We aimed to evaluate whether morning sleep after SD bears additional IED-inducing effects compared with nocturnal physiological sleep, and whether changes in sleep stability (described by the cyclic alternating pattern-CAP) play a significant role.

METHODS

Adult patients with TLE underwent in-lab night polysomnography (n-PSG) and, within 7days from n-PSG, they underwent also a morning EEG after night SD (SD-EEG). We included only TLE patients in which both recordings showed IED. SD-EEG consisted of waking up patients at 2:00 AM and performing video EEG at 8:00 AM. For both recordings, we obtained the following markers for the first sleep cycle: IED/h (Spike Index, SI), sleep macrostructure, microstructure (NREM CAP rate; A1, A2 and A3 Indices), and SI association with CAP variables.

RESULTS

The macrostructure of the first sleep cycle was similar in n-PSG and morning SD-EEG, whereas CAP rate and SI were significantly higher in SD-EEG. SI increase was selectively associated with CAP phases.

CONCLUSIONS

SD increases the instability of morning recovery sleep compared with n-PSG, and particularly enhances CAP A1 phases, which are associated with the majority of IED. Thus, higher instability of morning recovery sleep may account at least in part for the increased IED yield in SD-EEG in TLE patients.