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      Multi-day rhythms modulate seizure risk in epilepsy

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          Abstract

          Epilepsy is defined by the seemingly random occurrence of spontaneous seizures. The ability to anticipate seizures would enable preventative treatment strategies. A central but unresolved question concerns the relationship of seizure timing to fluctuating rates of interictal epileptiform discharges (here termed interictal epileptiform activity, IEA), a marker of brain irritability observed between seizures by electroencephalography (EEG). Here, in 37 subjects with an implanted brain stimulation device that detects IEA and seizures over years, we find that IEA oscillates with circadian and subject-specific multidien (multi-day) periods. Multidien periodicities, most commonly 20–30 days in duration, are robust and relatively stable for up to 10 years in men and women. We show that seizures occur preferentially during the rising phase of multidien IEA rhythms. Combining phase information from circadian and multidien IEA rhythms provides a novel biomarker for determining relative seizure risk with a large effect size in most subjects.

          Abstract

          The ability to identify periods of heightened seizure risk could enable new treatments for patients with epilepsy. Here, the authors describe long term EEG recordings from 37 patients which allow them to identify multi-day fluctuations in interictal activity.

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          Most cited references40

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          Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study.

          Seizure prediction would be clinically useful in patients with epilepsy and could improve safety, increase independence, and allow acute treatment. We did a multicentre clinical feasibility study to assess the safety and efficacy of a long-term implanted seizure advisory system designed to predict seizure likelihood and quantify seizures in adults with drug-resistant focal seizures. We enrolled patients at three centres in Melbourne, Australia, between March 24, 2010, and June 21, 2011. Eligible patients had between two and 12 disabling partial-onset seizures per month, a lateralised epileptogenic zone, and no history of psychogenic seizures. After devices were surgically implanted, patients entered a data collection phase, during which an algorithm for identification of periods of high, moderate, and low seizure likelihood was established. If the algorithm met performance criteria (ie, sensitivity of high-likelihood warnings greater than 65% and performance better than expected through chance prediction of randomly occurring events), patients then entered an advisory phase and received information about seizure likelihood. The primary endpoint was the number of device-related adverse events at 4 months after implantation. Our secondary endpoints were algorithm performance at the end of the data collection phase, clinical effectiveness (measures of anxiety, depression, seizure severity, and quality of life) 4 months after initiation of the advisory phase, and longer-term adverse events. This trial is registered with ClinicalTrials.gov, number NCT01043406. We implanted 15 patients with the advisory system. 11 device-related adverse events were noted within four months of implantation, two of which were serious (device migration, seroma); an additional two serious adverse events occurred during the first year after implantation (device-related infection, device site reaction), but were resolved without further complication. The device met enabling criteria in 11 patients upon completion of the data collection phase, with high likelihood performance estimate sensitivities ranging from 65% to 100%. Three patients' algorithms did not meet performance criteria and one patient required device removal because of an adverse event before sufficient training data were acquired. We detected no significant changes in clinical effectiveness measures between baseline and 4 months after implantation. This study showed that intracranial electroencephalographic monitoring is feasible in ambulatory patients with drug-resistant epilepsy. If these findings are replicated in larger, longer studies, accurate definition of preictal electrical activity might improve understanding of seizure generation and eventually lead to new management strategies. NeuroVista. Copyright © 2013 Elsevier Ltd. All rights reserved.
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            Seizure prediction: the long and winding road.

            The sudden and apparently unpredictable nature of seizures is one of the most disabling aspects of the disease epilepsy. A method capable of predicting the occurrence of seizures from the electroencephalogram (EEG) of epilepsy patients would open new therapeutic possibilities. Since the 1970s investigations on the predictability of seizures have advanced from preliminary descriptions of seizure precursors to controlled studies applying prediction algorithms to continuous multi-day EEG recordings. While most of the studies published in the 1990s and around the turn of the millennium yielded rather promising results, more recent evaluations could not reproduce these optimistic findings, thus raising a debate about the validity and reliability of previous investigations. In this review, we will critically discuss the literature on seizure prediction and address some of the problems and pitfalls involved in the designing and testing of seizure-prediction algorithms. We will give an account of the current state of this research field, point towards possible future developments and propose methodological guidelines for future studies on seizure prediction.
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              Epilepsy: accuracy of patient seizure counts.

              To evaluate the effects of a daily patient reminder on seizure documentation accuracy. Randomized controlled trial. Monitoring unit of an academic department of epileptology. Patients Consecutive sample of 91 adult inpatients with focal epilepsies undergoing video-electroencephalographic monitoring. Intervention While all patients were asked to document seizures at the beginning of the monitoring period, patients from the experimental group were reminded each day to document seizures. Main Outcome Measure Documentation accuracy (percentage of documented seizures). A total of 582 partial seizures were recorded. Patients failed to document 55.5% of all recorded seizures, 73.2% of complex partial seizures, 26.2% of simple partial seizures, 41.7% of secondarily generalized tonic-clonic seizures, 85.8% of all seizures during sleeping, and 32.0% of all seizures during the awake state. The group medians of individual documentation accuracies for overall seizures, simple partial seizures, complex partial seizures, and secondarily generalized tonic-clonic seizures were 33.3%, 66.7%, 0%, and 83.3%, respectively. Neither the patient reminder nor cognitive performance affected documentation accuracy. A left-sided electroencephalographic focus or lesion, but not the site (frontal or temporal), contributed to documentation failure. Patient seizure counts do not provide valid information. Documentation failures result from postictal seizure unawareness, which cannot be avoided by reminders. Unchanged documentation accuracy is a prerequisite for the use of patient seizure counts in clinical trials and has to be demonstrated in a subsample of patients undergoing electroencephalographic monitoring.
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                Author and article information

                Contributors
                maxime.baud.neuro@gmail.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                8 January 2018
                8 January 2018
                2018
                : 9
                : 88
                Affiliations
                [1 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Neurology and Weill Institute for Neurosciences, , University of California, ; San Francisco, CA 94143 USA
                [2 ]ISNI 0000 0001 0721 9812, GRID grid.150338.c, Department of Neurology, , University Hospital Geneva, ; Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
                [3 ]Wyss Center for Bio and Neuroengineering, 1202 Geneva, Switzerland
                [4 ]ISNI 0000 0001 0726 5157, GRID grid.5734.5, Sleep-Wake-Epilepsy-Center, Department of Neurology, Inselspital, , University of Bern, ; 3010 Bern, Switzerland
                [5 ]NeuroPace, Inc., 455N. Bernardo Ave, Mountain View, CA 94043 USA
                [6 ]ISNI 0000 0001 0454 4791, GRID grid.33489.35, Department of Chemical and Biomolecular Engineering, , University of Delaware, ; Newark, DE 19716 USA
                [7 ]ISNI 0000000098234542, GRID grid.17866.3e, Department of Neurology, , California Pacific Medical Center, ; San Francisco, CA 94115 USA
                [8 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Neurological Surgery and Weill Institute for Neurosciences, , University of California, ; San Francisco, CA 94143 USA
                Author information
                http://orcid.org/0000-0002-6659-9488
                Article
                2577
                10.1038/s41467-017-02577-y
                5758806
                29311566
                44c02208-eef8-4928-8560-89dbc09decfa
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 February 2017
                : 12 December 2017
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