Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection

Elger, Christian E.; Hoppe, Christian

doi:10.1016/s1474-4422(18)30038-3

Cited by 278 publications

(265 citation statements)

References 104 publications

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“…The treatment of epilepsy is still challenging, since only 70%-75% of the patients achieve a satisfactory seizure control under antiepileptic drugs [29]. A quest for more effective therapies can rely on the simplicity of the zebrafish model provided that recordings are analyzed with a sufficient sensitivity to attain a robust assessment and classification of all epileptic manifestation.…”

Section: Discussionmentioning

confidence: 99%

Evolution of Epileptiform Activity in Zebrafish by Statistical-Based Integration of Electrophysiology and 2-Photon Ca2+ Imaging

Cozzolino

Sicca

Paoli

et al. 2020

Cells

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The study of sources and spatiotemporal evolution of ictal bursts is critical for the mechanistic understanding of epilepsy and for the validation of anti-epileptic drugs. Zebrafish is a powerful vertebrate model representing an excellent compromise between system complexity and experimental accessibility. We performed the quantitative evaluation of the spatial recruitment of neuronal populations during physiological and pathological activity by combining local field potential (LFP) recordings with simultaneous 2-photon Ca 2+ imaging. We developed a method to extract and quantify electrophysiological transients coupled with Ca 2+ events and we applied this tool to analyze two different epilepsy models and to assess the efficacy of the anti-epileptic drug valproate. Finally, by cross correlating the imaging data with the LFP, we demonstrated that the cerebellum is the main source of epileptiform transients. We have also shown that each transient was preceded by the activation of a sparse subset of neurons mostly located in the optic tectum. of human pathologies, including behavioral aspects of the seizure phenotype, such as locomotor patterns and loss of posture [11,13]. Up to now, locomotion represents the main readout of the epileptic phenotype and the pattern and speed of swimming behavior of larvae can indeed be measured using automated locomotion-tracking [14] to provide information on seizure severity and on the outcome of administered drugs. Electrophysiological recordings [9,[15][16][17][18] permit activity monitoring in intact larvae, but the analysis of the electrophysiology data relies mostly on their visual inspection. Moreover, it is often difficult to tell true epileptiform activity apart from physiological events, such as eye and tail movements [18] on account of the high sensibility of the electric signal to muscle activity due to the small dimension of the entire organism. Therefore, electrophysiology requires additional information for the unequivocal identification of the mutant phenotypes and for the evaluation of anti-epileptic compounds.Recently, deep learning classifiers have been employed to identify electrophysiological events [19] and, although these methods are very fast and effective, they are unavoidably affected by the need of an a priori classification of epilepsy features and by the degree of completeness of the training dataset. A high-throughput local field potential (LFP) recording platform has also recently been used to analyze high-order statistical moments for an unsupervised detection of seizures [20]. However, these electrophysiological methods for seizure identification and classification are still prone to be affected by motion artefacts. Moreover, a complete physio-pathological interpretation of LFP recordings is hindered by the impossibility of identifying the sources of the electrophysiological signals and the spatial dynamics of epileptic activity of the underlying neuronal populations.A complementary window on brain function is provided by imaging the fluorescence of ...

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Section: Discussionmentioning

confidence: 99%

Evolution of Epileptiform Activity in Zebrafish by Statistical-Based Integration of Electrophysiology and 2-Photon Ca2+ Imaging

Cozzolino

Sicca

Paoli

et al. 2020

Cells

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“…19,20 To avoid misclassification, we labeled only those seizures with specific semiology as convulsions and we excluded the individual with newly diagnosed dissociative seizures from our analysis. We relied on seizure diaries and did not have video-EEG data.…”

Section: Discussionmentioning

confidence: 99%

“…As a consequence, seizures may have been underreported or misclassified. 19,20 To avoid misclassification, we labeled only those seizures with specific semiology as convulsions and we excluded the individual with newly diagnosed dissociative seizures from our analysis. The total number of convulsions may thus have been underestimated.…”

Section: Discussionmentioning

confidence: 99%

The yield of long‐term electrocardiographic recordings in refractory focal epilepsy

et al. 2019

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Objective:To determine the incidence of clinically relevant arrhythmias in refractory focal epilepsy and to assess the potential of postictal arrhythmias as risk markers for sudden unexpected death in epilepsy (SUDEP). Methods: We recruited people with refractory focal epilepsy without signs of ictal asystole and who had at least one focal seizure per month and implanted a loop recorder with 2-year follow-up. The devices automatically record arrhythmias. Subjects and caregivers were instructed to make additional peri-ictal recordings. Clinically relevant arrhythmias were defined as asystole ≥ 6 seconds; atrial fibrillation < 55 beats per minute (bpm), or > 200 bpm and duration > 30 seconds; persistent sinus bradycardia < 40 bpm while awake; and second-or third-degree atrioventricular block and ventricular tachycardia/fibrillation. We performed 12-lead electrocardiography (ECG) and tilt table testing to identify non-seizure-related causes of asystole. Results: We included 49 people and accumulated 1060 months of monitoring. A total of 16 474 seizures were reported, of which 4679 were captured on ECG. No clinically relevant arrhythmias were identified. Three people had a total of 18 shortlasting (<6 seconds) periods of asystole, resulting in an incidence of 2.91 events per 1000 patient-months. None of these coincided with a reported seizure; one was explained by micturition syncope. Other non-clinically relevant arrhythmias included paroxysmal atrial fibrillation (n = 2), supraventricular tachycardia (n = 1), and sinus tachycardia with a right bundle branch block configuration (n = 1). Significance: We found no clinically relevant arrhythmias in people with refractory focal epilepsy during long-term follow-up. The absence of postictal arrhythmias does not support the use of loop recorders in people at high SUDEP risk. K E Y W O R D Scardiac arrhythmias, ECG, epilepsy, implantable loop recorders, sudden unexpected death in epilepsy

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“…Some seizure types are particularly prone to underreporting, particularly focal impaired awareness events and those which occur in sleep. A variety of novel solutions have been developed to improve on this with the increasing sophistication and sensitivity of wearable devices . Strategies to accommodate this information in clinical practice and drug trials would be of great utility.…”

mentioning

confidence: 99%

Does my posterior look big in this?—Bayesian solutions to seizure counting problems

Cook

2019

Epilepsia Open

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Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection

Cited by 278 publications

References 104 publications

Evolution of Epileptiform Activity in Zebrafish by Statistical-Based Integration of Electrophysiology and 2-Photon Ca2+ Imaging

Evolution of Epileptiform Activity in Zebrafish by Statistical-Based Integration of Electrophysiology and 2-Photon Ca2+ Imaging

The yield of long‐term electrocardiographic recordings in refractory focal epilepsy

Does my posterior look big in this?—Bayesian solutions to seizure counting problems

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