Objective: Automated detection of spikes and seizures has been a subject of research for several decades now. There have been important advances, yet automated detection in EMU (Epilepsy Monitoring... Show moreObjective: Automated detection of spikes and seizures has been a subject of research for several decades now. There have been important advances, yet automated detection in EMU (Epilepsy Monitoring Unit) settings has not been accepted as standard practice. We intend to implement this software at our EMU and so carried out a qualitative study to identify factors that hinder ('barriers') and facilitate ('enablers') implementation.Method: Twenty-two semi-structured interviews were conducted with 14 technicians and neurologists involved in recording and reporting EEGs and eight neurologists who receive EEG reports in the outpatient department. The study was reported according to the Consolidated Criteria for Reporting Qualitative Studies (COREQ).Results: We identified 14 barriers and 14 enablers for future implementation. Most barriers were reported by technicians. The most prominent barrier was lack of trust in the software, especially regarding seizure detection and false positive results. Additionally, technicians feared losing their EEG review skills or their jobs. Most commonly reported enablers included potential efficiency in the EEG workflow, the opportunity for quantification of EEG findings and the willingness to try the software. Conclusions: This study provides insight into the perspectives of users and offers recommendations for implementing automated spike and seizure detection in EMUs. Show less
Migraine is associated with altered sensory processing, that may be evident as changes in cortical responsivity due to altered excitability, especially in migraine with aura. Cortical excitability... Show moreMigraine is associated with altered sensory processing, that may be evident as changes in cortical responsivity due to altered excitability, especially in migraine with aura. Cortical excitability can be directly assessed by combining transcranial magnetic stimulation with electroencephalography (TMS-EEG). We measured TMS evoked potential (TEP) amplitude and response consistency as these measures have been linked to cortical excitability but were not yet reported in migraine.We recorded 64-channel EEG during single-pulse TMS on the vertex interictally in 10 people with migraine with aura and 10 healthy controls matched for age, sex and resting motor threshold. On average 160 pulses around resting motor threshold were delivered through a circular coil in clockwise and counterclockwise direction. Trial-averaged TEP responses, frequency spectra and phase clustering (over the entire scalp as well as in frontal, central and occipital midline electrode clusters) were compared between groups, including comparison to sham-stimulation evoked responses.Migraine and control groups had a similar distribution of TEP waveforms over the scalp. In migraine with aura, TEP responses showed reduced amplitude around the frontal and occipital N100 peaks. For the migraine and control groups, responses over the scalp were affected by current direction for the primary motor cortex, somatosensory cortex and sensory association areas, but not for frontal, central or occipital midline clusters.This study provides evidence of altered TEP responses in-between attacks in migraine with aura. Decreased TEP responses around the N100 peak may be indicative of reduced cortical GABA-mediated inhibition and expand observations on enhanced cortical excitability from earlier migraine studies using more indirect measurements. Show less
Introduction: The lack of reliable biomarkers constrain epilepsy management. We assessed the potential of repeated transcranial magnetic stimulation with electromyography (TMS-EMG) to track... Show moreIntroduction: The lack of reliable biomarkers constrain epilepsy management. We assessed the potential of repeated transcranial magnetic stimulation with electromyography (TMS-EMG) to track dynamical changes in cortical excitability on a within-subject basis. Methods: We recruited people with refractory focal epilepsy who underwent video-EEG monitoring and drug tapering as part of the presurgical evaluation. We performed daily TMS-EMG measurements with additional postictal assessments 1- 6 h following seizures to assess resting motor threshold (rMT), and motor evoked potentials (MEPs) with single- and paired-pulse protocols. Anti-seizure medication (ASM) regimens were recorded for the day before each measurement and expressed in proportion to the dosage before tapering. Additional measurements were performed in healthy controls to evaluate day-to-day rMT variability. Results: We performed 77 (58 baseline, 19 postictal) measurements in 16 people with focal epilepsy and 35 in seven healthy controls. Controls showed minimal day-to-day rMT variation. Withdrawal of ASMs was associated with a lower rMT without affecting MEPs of single- and paired-pulse TMS-EMG paradigms. Postictal measurements following focal to bilateral tonic- clonic seizures demonstrated unaltered rMT and increased short interval intracortical inhibition, while measurements following focal seizures with impaired awareness showed decreased rMT's and reduced short and long interval intracortical inhibition. Conclusion: Serial withinsubject rMT measurements yielded reproducible, stable results in healthy controls. ASM tapering and seizures had distinct effects on TMS-EMG excitability indices in people with epilepsy. Drug tapering decreased rMT, indicating increased overall corticospinal excitability, whereas seizures affected intracortical inhibition with contrasting effects between seizure types. Show less
Purpose: We assessed whether automated detection software, combined with live observation, enabled reliable seizure detection using three commercial software packages: Persyst, Encevis and BESA.... Show morePurpose: We assessed whether automated detection software, combined with live observation, enabled reliable seizure detection using three commercial software packages: Persyst, Encevis and BESA. Methods: Two hundred and eighty-six prolonged EEG records of individuals aged 16-86 years, collected between August 2019 and January 2020, were retrospectively processed using all three packages. The reference standard included all seizures mentioned in the clinical report supplemented with true detections made by the software and not previously detected by clinical physiologists. Sensitivity was measured for offline review by clinical physiologists and software seizure detection, both in combination with live monitoring in an EMU setting, for all three software packages at record and seizure level. Results: The database contained 249 seizures in 64 records. The sensitivity of seizure detection was 98% for Encevis and Persyst, and 95% for BESA, when a positive results was defined as detection at least one of the seizures occurring within an individual record. When positivity was defined as recognition of all seizures, sensitivity was 93% for Persyst, 88% for Encevis and 84% for BESA. Clinical physiologists' review had a sensitivity of 100% at record level and 98% at seizure level. The median false positive rate per record was 1.7 for Persyst, 2.4 for BESA and 5.5 for Encevis per 24 h. Conclusion: Automated seizure detection software does not perform as well as technicians do. However, it can be used in an EMU setting when the user is aware of its weaknesses. This assessment gives future users helpful insight into these strengths and weaknesses. The Persyst software performs best. Show less
Purpose: We assessed three commercial automated spike detection software packages (Persyst, Encevis and BESA) to see which had the best performance. Methods: Thirty prolonged EEG records from... Show morePurpose: We assessed three commercial automated spike detection software packages (Persyst, Encevis and BESA) to see which had the best performance. Methods: Thirty prolonged EEG records from people aged at least 16 years were collected and 30-minute representative epochs were selected. Interictal epileptiform discharges (IEDs) were marked by three human experts and by all three software packages. For each 30-minutes selection and for each 10-second epoch we measured whether or not IEDs had occurred. We defined the gold standard as the combined detections of the experts. Kappa scores, sensitivity and specificity were estimated for each software package. Results: Sensitivity for Persyst in the default setting was 95% for 30-minute selections and 82% for 10-second epochs. Sensitivity for Encevis was 86% (30-minute selections) and 61% (10-second epochs). The specificity for both packages was 88% for 30-minute selections and 96%-99% for the 10-second epochs. Interrater agreement between Persyst and Encevis and the experts was similar than between experts (0.67-0.83 versus 0.63-0.67). Sensitivity for BESA was 40% and specificity 100%. Interrater agreement (0.25) was low. Conclusions: IED detection by the Persyst automated software is better than the Encevis and BESA packages, and similar to human review, when reviewing 30-minute selections and 10-second epochs. This findings may help prospective users choose a software package. Show less
Purpose: The spike–wave index (SWI) is a key feature in thediagnosis of electrical status epilepticus during slow-wave sleep.Estimating the SWI manually is time-consuming and is subject... Show morePurpose: The spike–wave index (SWI) is a key feature in thediagnosis of electrical status epilepticus during slow-wave sleep.Estimating the SWI manually is time-consuming and is subject tointerrater and intrarater variability. Use of automated detectionsoftware would save time. Thereby, this software willconsistently detect a certain EEG phenomenon as epileptiformand is not influenced by human factors. To determinenoninferiority in calculating the SWI, we compared theperformance of a commercially available spike detectionalgorithm (P13 software, Persyst Development Corporation,San Diego, CA) with human expert consensus.Methods: The authors identified all prolonged EEG recordingsfor the diagnosis or follow-up of electrical status epilepticusduring slow-wave sleep carried out from January to December2018 at an epilepsy tertiary referral center. The SWI during thefirst 10 minutes of sleep was estimated by consensus of twohuman experts. This was compared with the SWI calculated bythe automated spike detection algorithm using the threeavailable sensitivity settings: “low,” “medium,” and “high.” In thesoftware, these sensitivity settings are denoted as perceptionvalues.Results: Forty-eight EEG recordings from 44 individuals wereanalyzed. The SWIs estimated by human experts did not differfrom the SWIs calculated by the automated spike detectionalgorithm in the “low” perception mode (P ¼ 0.67). The SWIscalculated in the “medium” and “high” perception settings were,however, significantly higher than the human expert estimatedSWIs (both P , 0.001).Conclusions: Automated spike detection (P13) is a useful tool indetermining SWI, especially when using the “low” sensitivitysetting. Using such automated detection tools may save time,especially when reviewing larger epochs. Show less
Purpose: Complete visual review of prolonged video-EEG recordings at an EMU (Epilepsy Monitoring Unit) is time consuming and can cause problems in times of paucity of educated personnel. In this... Show morePurpose: Complete visual review of prolonged video-EEG recordings at an EMU (Epilepsy Monitoring Unit) is time consuming and can cause problems in times of paucity of educated personnel. In this study we aimed to show non inferiority for electroclinical diagnosis using sampled review in combination with EEG analysissoftware (P13 software, Persyst Corporation), in comparison to complete visual review.Method: Fifty prolonged video-EEG recordings in adults were prospectively evaluated using sampled visual EEG review in combination with automated detection software of the complete EEG record. Visually assessed samples consisted of one hour during wakefulness, one hour during sleep, half an hour of wakefulness after wake-up and all clinical events marked by the individual and/or nurses. The final electro-clinical diagnosis of this new review approach was compared with the electro-clinical diagnosis after complete visual review as presently used.Results: The electro-clinical diagnosis based on sampled visual review combined with automated detectionsoftware did not differ from the diagnosis based on complete visual review. Furthermore, the detection software was able to detect all records containing epileptiform abnormalities and epileptic seizures.Conclusion: Sampled visual review in combination with automated detection using Persyst 13 is non-inferior to complete visual review for electroclinical diagnosis of prolonged video-EEG at an EMU setting, which makes this approach promising. Show less
Purpose Caffeine is the most commonly used central nervous system (CNS) stimulant. The relationship between caffeine, seizures, epilepsy, and antiepileptic drugs (AEDs) is complex and not fully... Show morePurpose Caffeine is the most commonly used central nervous system (CNS) stimulant. The relationship between caffeine, seizures, epilepsy, and antiepileptic drugs (AEDs) is complex and not fully understood. Case reports suggest that caffeine triggers seizures in susceptible people. Our systematic review reports on the relationship between caffeine, seizures, and drugs in animal and human studies. Quantitative analyses were also done on animal studies regarding the effects of caffeine on AEDs. Methods PubMed was searched for studies assessing the effects of caffeine on seizure susceptibility, epilepsy, and drug interactions in people and in animal models. To quantify the interaction between AEDs and caffeine, the data of six animal studies were pooled and analyzed using a general linear model univariate analysis or One-way Analysis of Variance (ANOVA). Results In total, 442 items were identified from which we included 105 studies. Caffeine can increase seizure susceptibility and protect from seizures, depending on the dose, administration type (chronic or acute), and the developmental stage at which caffeine exposure started. In animal studies, caffeine decreased the antiepileptic potency of some drugs; this effect was strongest in topiramate. Conclusion Preclinical studies suggest that caffeine increases seizure susceptibility. In some cases, chronic use of caffeine may protect against seizures. Caffeine lowers the efficacy of several drugs, especially topiramate. It is unclear how these findings in models can be translated to the clinical condition. Until clinical studies suggest otherwise, caffeine intake should be considered as a factor in achieving and maintaining seizure control in epilepsy. Show less
