Multi-day rhythms modulate seizure risk in epilepsy.
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ABSTRACT:
SUBMITTER: Baud MO
PROVIDER: S-EPMC5758806 | biostudies-other | 2018 Jan
REPOSITORIES: biostudies-other
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Project description:BackgroundWhile the effects of prolonged sleep deprivation (≥24 h) on seizure occurrence has been thoroughly explored, little is known about the effects of day-to-day variations in the duration and quality of sleep on seizure probability. A better understanding of the interaction between sleep and seizures may help to improve seizure management.MethodsTo explore how sleep and epileptic seizures are associated, we analysed continuous intracranial electroencephalography (EEG) recordings collected from 10 patients with refractory focal epilepsy undergoing ordinary life activities between 2010 and 2012 from three clinical centres (Austin Health, The Royal Melbourne Hospital, and St Vincent's Hospital of the Melbourne University Epilepsy Group). A total of 4340 days of sleep-wake data were analysed (average 434 days per patient). EEG data were sleep scored using a semi-automated machine learning approach into wake, stages one, two, and three non-rapid eye movement sleep, and rapid eye movement sleep categories.FindingsSeizure probability changes with day-to-day variations in sleep duration. Logistic regression models revealed that an increase in sleep duration, by 1·66 ± 0·52 h, lowered the odds of seizure by 27% in the following 48 h. Following a seizure, patients slept for longer durations and if a seizure occurred during sleep, then sleep quality was also reduced with increased time spent aroused from sleep and reduced rapid eye movement sleep.InterpretationOur results suggest that day-to-day deviations from regular sleep duration correlates with changes in seizure probability. Sleeping longer, by 1·66 ± 0·52 h, may offer protective effects for patients with refractory focal epilepsy, reducing seizure risk. Furthermore, the occurrence of a seizure may disrupt sleep patterns by elongating sleep and, if the seizure occurs during sleep, reducing its quality.
| S-EPMC8343264 | biostudies-literature
Project description:Chronic brain recordings suggest that seizure risk is not uniform, but rather varies systematically relative to daily (circadian) and multiday (multidien) cycles. Here, one human and seven dogs with naturally occurring epilepsy had continuous intracranial EEG (median 298 days) using novel implantable sensing and stimulation devices. Two pet dogs and the human subject received concurrent thalamic deep brain stimulation (DBS) over multiple months. All subjects had circadian and multiday cycles in the rate of interictal epileptiform spikes (IES). There was seizure phase locking to circadian and multiday IES cycles in five and seven out of eight subjects, respectively. Thalamic DBS modified circadian (all 3 subjects) and multiday (analysis limited to the human participant) IES cycles. DBS modified seizure clustering and circadian phase locking in the human subject. Multiscale cycles in brain excitability and seizure risk are features of human and canine epilepsy and are modifiable by thalamic DBS.
| S-EPMC8688461 | biostudies-literature
Project description:ObjectiveWe conducted clinical testing of an automated Bayesian machine learning algorithm (Epilepsy Seizure Assessment Tool [EpiSAT]) for outpatient seizure risk assessment using seizure counting data, and validated performance against specialized epilepsy clinician experts.MethodsWe conducted a prospective longitudinal study of EpiSAT performance against 24 specialized clinician experts at three tertiary referral epilepsy centers in the United States. Accuracy, interrater reliability, and intra-rater reliability of EpiSAT for correctly identifying changes in seizure risk (improvements, worsening, or no change) were evaluated using 120 seizures from four synthetic seizure diaries (seizure risk known) and 120 seizures from four real seizure diaries (seizure risk unknown). The proportion of observed agreement between EpiSAT and clinicians was evaluated to assess compatibility of EpiSAT with clinical decision patterns by epilepsy experts.ResultsEpiSAT exhibited substantial observed agreement (75.4%) with clinicians for assessing seizure risk. The mean accuracy of epilepsy providers for correctly assessing seizure risk was 74.7%. EpiSAT accurately identified seizure risk in 87.5% of seizure diary entries, corresponding to a significant improvement of 17.4% (P = .002). Clinicians exhibited low-to-moderate interrater reliability for seizure risk assessment (Krippendorff's ? = 0.46) with good intrarater reliability across a 4- to 12-week evaluation period (Scott's ? = 0.89).SignificanceThese results validate the ability of EpiSAT to yield objective clinical recommendations on seizure risk which follow decision patterns similar to those from specialized epilepsy providers, but with improved accuracy and reproducibility. This algorithm may serve as a useful clinical decision support system for quantitative analysis of clinical seizure frequency in clinical epilepsy practice.
| S-EPMC6980278 | biostudies-literature
Project description:BackgroundPeople with epilepsy are burdened with the apparent unpredictability of seizures. In the past decade, converging evidence from studies using chronic EEG (cEEG) revealed that epileptic brain activity shows robust cycles, operating over hours (circadian) and days (multidien). We hypothesised that these cycles can be leveraged to estimate future seizure probability, and we tested the feasibility of forecasting seizures days in advance.MethodsWe did a feasibility study in distinct development and validation cohorts, involving retrospective analysis of cEEG data recorded with an implanted device in adults (age ?18 years) with drug-resistant focal epilepsy followed at 35 centres across the USA between Jan 19, 2004, and May 18, 2018. Patients were required to have had 20 or more electrographic seizures (development cohort) or self-reported seizures (validation cohort). In all patients, the device recorded interictal epileptiform activity (IEA; ?6 months of continuous hourly data), the fluctuations in which helped estimate varying seizure risk. Point process statistical models trained on initial portions of each patient's cEEG data (both cohorts) generated forecasts of seizure probability that were tested on subsequent unseen seizure data and evaluated against surrogate time-series. The primary outcome was the percentage of patients with forecasts showing improvement over chance (IoC).FindingsWe screened 72 and 256 patients, and included 18 and 157 patients in the development and validation cohorts, respectively. Models incorporating information about multidien IEA cycles alone generated daily seizure forecasts for the next calendar day with IoC in 15 (83%) patients in the development cohort and 103 (66%) patients in the validation cohort. The forecasting horizon could be extended up to 3 days while maintaining IoC in two (11%) of 18 patients and 61 (39%) of 157 patients. Forecasts with a shorter horizon of 1 h, possible only for electrographic seizures in the development cohort, showed IoC in all 18 (100%) patients.InterpretationThis study shows that seizure probability can be forecasted days in advance by leveraging multidien IEA cycles recorded with an implanted device. This study will serve as a basis for prospective clinical trials to establish how people with epilepsy might benefit from seizure forecasting over long horizons.FundingNone. VIDEO ABSTRACT.
| S-EPMC7968722 | biostudies-literature
Project description:Advances in ambulatory intracranial EEG devices have enabled objective analyses of circadian and multiday seizure periodicities, and seizure clusters in humans. This study characterizes circadian and multiday seizure periodicities, and seizure clusters in dogs with naturally occurring focal epilepsy, and considers the implications of an animal model for the study of seizure risk patterns, seizure forecasting and personalized treatment protocols. In this retrospective cohort study, 16 dogs were continuously monitored with ambulatory intracranial EEG devices designed for humans. Detailed medication records were kept for all dogs. Seizure periodicity was evaluated with circular statistics methods. Circular non-uniformity was assessed for circadian, 7-day and approximately monthly periods. The Rayleigh test was used to assess statistical significance, with correction for multiple comparisons. Seizure clusters were evaluated with Fano factor (index of dispersion) measurements, and compared to a Poisson distribution. Relationships between interseizure interval (ISI) and seizure duration were evaluated. Six dogs met the inclusion criteria of having at least 30 seizures and were monitored for an average of 65 weeks. Three dogs had seizures with circadian seizure periodicity, one dog had a 7-day periodicity, and two dogs had approximately monthly periodicity. Four dogs had seizure clusters and significantly elevated Fano factor values. There were subject-specific differences in the dynamics of ISI and seizure durations, both within and between lead and clustered seizure categories. Our findings show that seizure timing in dogs with naturally occurring epilepsy is not random, and that circadian and multiday seizure periodicities, and seizure clusters are common. Circadian, 7-day, and monthly seizure periodicities occur independent of antiseizure medication dosing, and these patterns likely reflect endogenous rhythms of seizure risk.
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Project description:This SuperSeries is composed of the SubSeries listed below.
2023-02-08 | GSE190453 | GEO
Project description:OBJECTIVE:To evaluate the safety of stimulants in children with epilepsy. METHODS:In a retrospective cohort study based on Medicaid Analytic eXtract billing records from 26 U.S. states from 1999 to 2010, we identified incident stimulant use among children with epilepsy through outpatient encounter claims and pharmacy claims. We established a control group of nonusers and used frequency matching to generate index dates. We followed both cohorts for 12 months and calculated hazard ratios [HRs] of current and former use of stimulants versus no use on the outcome of seizure-related hospitalization using multivariate Cox proportional hazard models. RESULTS:We identified 18,166 stimulant users and 54,197 nonusers in children with epilepsy. The incidence of seizure-related hospitalization in current stimulant users, former users, and nonusers was 3.6, 3.5, and 4.3 per 100 patient-years. After adjustment for confounders, we found current and former use of stimulants did not increase seizure-related hospitalizations (HR 0.95, 95% confidence interval [CI]: 0.83, 1.09 and HR 0.99, 95% CI: 0.85, 1.15). Children with cerebral palsy, congenital nervous system anomalies, or intellectual disability did not have significantly higher HRs than those without the already mentioned comorbidities. CONCLUSION:This study has not identified any overall increase in the rate of seizure-related hospitalizations with the use of stimulants in children with epilepsy.
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Project description:Clinicians often encounter patients whose neurologic attacks appear to cluster. In a daily diary study, the authors explored whether clustering is a true phenomenon in epilepsy and can be identified in the clinical setting. Nearly half the subjects experienced at least one episode of three or more seizures in 24 hours; 20% also met a statistical clustering criterion. Utilizing the clinical definition of clustering should identify all seizure clusterers, and false positives can be determined with diary data.
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Project description:To determine seizure semiology in children with newly diagnosed childhood absence epilepsy and to evaluate associations with short-term treatment outcomes.For participants enrolled in a multicenter, randomized, double-blind, comparative-effectiveness trial, semiologic features of pretreatment seizures were analyzed as predictors of treatment outcome at the week 16 to 20 visit.Video of 1,932 electrographic absence seizures from 416 participants was evaluated. Median seizure duration was 10.2 seconds; median time between electrographic seizure onset and clinical manifestation onset was 1.5 seconds. For individual seizures and by participant, the most common semiology features were pause/stare (seizure 95.5%, participant 99.3%), motor automatisms (60.6%, 86.1%), and eye involvement (54.9%, 76.5%). The interrater agreement for motor automatisms and eye involvement was good (72%-84%). Variability of semiology features between seizures even within participants was high. Clustering analyses revealed 4 patterns (involving the presence/absence of eye involvement and motor automatisms superimposed on the nearly ubiquitous pause/stare). Most participants experienced more than one seizure cluster pattern. No individual semiologic feature was individually predictive of short-term outcome. Seizure freedom was half as likely in participants with one or more seizure having the pattern of eye involvement without motor automatisms than in participants without this pattern.Almost all absence seizures are characterized by a pause in activity or staring, but rarely is this the only feature. Semiologic features tend to cluster, resulting in identifiable absence seizure subtypes with significant intraparticipant seizure phenomenologic heterogeneity. One seizure subtype, pause/stare and eye involvement but no motor automatisms, is specifically associated with a worse treatment outcome.
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Project description:Epilepsy is one of the most prevalent and drug-refractory neurological disorders. Zinc finger DHHC-type containing 8 (ZDHHC8) is a putative palmitoyltransferase that is highly expressed in the brain. However, the impact of ZDHHC8 on seizures remains unclear. We aimed to explore the association of ZDHHC8 with epilepsy and investigate its in epileptogenesis in in vivo and in vitro models through behavioral, electrophysiological, and pathological studies. We used kainic acid- and pilocarpine-induced C57BL/6 mice and magnesium-free-induced pyramidal neurons as experimental epileptic models in this study. We first found increased ZDHHC8 expression in the brains of temporal lobe epilepsy (TLE) patients, similar to that observed in chronic epileptic mice, strongly suggesting that ZDHHC8 is correlated with human epilepsy. In the in vitro seizure models, knocking down ZDHHC8 using recombinant adeno-associated virus (rAAV) delayed seizure precipitation and decreased chronic spontaneous recurrent seizures (SRSs) and epileptiform-like discharges, while ZDHHC8 overexpression had the opposite effect. ZDHHC8 levels were consistent with seizure susceptibility in induced mice with SRSs. In an in vitro magnesium-free model, neuronal hyperexcitability and hypersynchrony were reduced in ZDHHC8-knockdown neurons but were increased in ZDHHC8-overexpressing neurons. To further explore the potential mechanisms, we observed that ZDHHC8 had a significant modulatory effect on 2-amino-3-(5-methyl-3-oxo-1,2-oxazol-4-yl) propanoic acid (AMPA) receptor-related excitatory, but not inhibitory, glutamatergic synaptic neurotransmission, further affecting the inward rectification of AMPA currents in acute hippocampal slices in whole-cell recordings. ZDHHC8 facilitated GluA1 trafficking to the neuronal surface in the hippocampus, as shown by immunoprecipitation and Western blotting. These results suggest that ZDHHC8 may promote the generation and propagation of seizures in humans and that knocking down ZDHHC8 might produce anti-epileptogenic effects in drug-resistant epilepsy. Our study provides evidence that may facilitate the development of an alternative approach for the treatment of epilepsy by modulating AMPA/GluA1-mediated neurotransmission.
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