Guidelines for the use of EEG methodology in the diagnosis of epilepsy. International League Against Epilepsy: commission report. Commission on European Affairs: Subcommission on European Guidelines

Epilepsy in Duchenne and Becker muscular dystrophies

OBJECTIVE

Duchenne and Becker muscular dystrophies (DMD and BMD) are dystrophinopathies caused by variants in DMD gene, resulting in reduced or absent dystrophin. These conditions, characterized by muscle weakness, also manifest central nervous system (CNS) comorbidities due to dystrophin expression in the CNS. Prior studies have indicated a higher prevalence of epilepsy in individuals with dystrophinopathy compared to the general population. Our research aimed to investigate epilepsy prevalence in dystrophinopathies and characterize associated electroencephalograms (EEGs) and seizures.

METHODS

We reviewed 416 individuals with dystrophinopathy, followed up at three centers between 2010 and 2023, to investigate the lifetime epilepsy prevalence and characterize EEGs and seizures in those individuals diagnosed with epilepsy. Associations between epilepsy and type of dystrophinopathy, genotype, and cognitive involvement were studied.

RESULTS

Our study revealed a higher epilepsy prevalence than the general population (1.4%; 95% confidence interval: 0.7-3.2%), but notably lower than previously reported in smaller dystrophinopathy cohorts. No significant differences were found in epilepsy prevalence between DMD and BMD or based on underlying genotypes. Cognitive impairment was not found to be linked to higher epilepsy rates. The most prevalent epilepsy types in dystrophinopathies resembled those observed in the broader pediatric population, with most individuals effectively controlled through monotherapy.

INTERPRETATION

The actual epilepsy prevalence in dystrophinopathies may be markedly lower than previously estimated, possibly half or even less. Our study provides valuable insights into the epilepsy landscape in individuals with dystrophinopathy, impacting medical care, especially for those with concurrent epilepsy.

Semi-automated seizure detection using interpretable machine learning models

Despite the vast number of seizure detection publications there are no validated open-source tools for automating seizure detection based on electrographic recordings. Researchers instead rely on manual curation of seizure detection that is highly laborious, inefficient, error prone, and heavily biased. Here we developed an open-source software called SeizyML that uses sensitive machine learning models coupled with manual validation of detected events reducing bias and promoting efficient and accurate detection of electrographic seizures. We compared the validity of four interpretable machine learning models (decision tree, gaussian naïve bayes, passive aggressive classifier, and stochastic gradient descent classifier) on an extensive electrographic seizure dataset that we collected from chronically epileptic mice. We find that the gaussian naïve bayes and stochastic gradient descent models achieved the highest precision and f1 scores, while also detecting all seizures in our mouse dataset and only require a small amount of data to train the model and achieve good performance. Further, we demonstrate the utility of this approach to detect electrographic seizures in a human EEG dataset. This approach has the potential to be a transformative research tool overcoming the analysis bottleneck that slows research progress.

Melatonin vs. dexmedetomidine for sleep induction in children before electroencephalography

Background and objectives

In children requiring electroencephalography (EEG), sleep recording can provide crucial information. As EEG recordings during spontaneous sleep are not always possible, pharmacological sleep-inducing agents are sometimes required. The aim of the study was to evaluate safety and efficacy of melatonin (Mel) and dexmedetomidine (Dex; intranasal and sublingual application) for sleep induction prior to EEG.

Methods

In this prospective randomized study, 156 consecutive patients aged 1-19 years were enrolled and randomized by draw into melatonin group (Mel; n = 54; dose: 0.1 mg/kg), dexmedetomidine (Dex) sublingual group (DexL; n = 51; dose: 3 mcg/kg) or dexmedetomidine intranasal group (DexN; n = 51; dose: 3 mcg/kg). We compared the groups in several parameters regarding efficacy and safety and also carried out a separate analysis for a subgroup of patients with complex behavioral problems.

Results

Sleep was achieved in 93.6% of participants after the first application of the drug and in 99.4% after the application of another if needed. Mel was effective as the first drug in 83.3% and Dex in 99.0% (p < 0.001); in the subgroup of patients with complex developmental problems Mel was effective in 73.4% and Dex in 100% (p < 0.001). The patients fell asleep faster after intranasal application of Dex than after sublingual application (p = 0.006). None of the patients had respiratory depression, bradycardia, desaturation, or hypotension.

Conclusions

Mel and Dex are both safe for sleep induction prior to EEG recording in children. Dex is more effective compared to Mel in inducing sleep, also in the subgroup of children with complex behavioral problems.

Clinical Trial Registration

Dexmedetomidine and Melatonin for Sleep Induction for EEG in Children, NCT04665453.

Hyperventilation and Seizures: Not a New Sense: A Literature Review

Hyperventilation and seizures have a long association in the clinical literature and were known to have a relationship long before the electroencephalogram (EEG) was used to record changes in brain activity. As the use of EEG recording progressed, hyperventilation was the first activation method used to assist with diagnosis of epilepsy. Along with slowing of brain activity, hyperventilation can activate epileptiform spiking activity in patients with epilepsy. Currently, hyperventilation is used in standard practice to assist with the diagnosis of epilepsy during EEG recording. Hyperventilation activates epileptiform spiking activity more often than seizures but can trigger clinical seizures in up to 50% of patients with generalized epilepsy. It is more likely to trigger events in children with absence seizures than adults, and it acts as a trigger in patients with focal epilepsy far less often. However, while some clinicians suggest that its diagnostic value is limited, especially in adults with focal epilepsies, others suggest that it is simple, safe, and an important diagnostic tool, even in these patients. This review presents the history of hyperventilation and seizures, its use in the clinical practice, and possible mechanisms involved.

Network coupling and surgical treatment response in temporal lobe epilepsy: A proof-of-concept study

OBJECTIVE

This proof-of-concept study aimed to examine the overlap between structural and functional activity (coupling) related to surgical response.

METHODS

We studied intracranial rest and ictal stereoelectroencephalography (sEEG) recordings from 77 seizures in thirteen participants with temporal lobe epilepsy (TLE) who subsequently underwent resective/laser ablation surgery. We used the stereotactic coordinates of electrodes to construct functional (sEEG electrodes) and structural connectomes (diffusion tensor imaging). A Jaccard index was used to assess the similarity (coupling) between structural and functional connectivity at rest and at various intraictal timepoints.

RESULTS

We observed that patients who did not become seizure free after surgery had higher connectome coupling recruitment than responders at rest and during early and mid seizure (and visa versa).

SIGNIFICANCE

Structural networks provide a backbone for functional activity in TLE. The association between lack of seizure control after surgery and the strength of synchrony between these networks suggests that surgical intervention aimed to disrupt these networks may be ineffective in those that display strong synchrony. Our results, combined with findings of other groups, suggest a potential mechanism that explains why certain patients benefit from epilepsy surgery and why others do not. This insight has the potential to guide surgical planning (e.g., removal of high coupling nodes) following future research.

Diagnostic Yield of Five Minutes Compared to Three Minutes Hyperventilation During Electroencephalography in Children

Purpose: To investigate whether hyperventilation (HV) for 5 minutes increases the diagnostic yield of electroencephalography (EEG) compared to 3 minutes HV and to determine whether performing HV for 5 minutes is feasible and safe in children. Methods: Data were evaluated from 579 children aged less than 18 years, referred to EEG for epilepsy evaluation. Occurrence of seizures, HV induced interictal epileptiform discharges precipitation and potentiation and adverse events if any were noted during the first 3 minutes and last 2 minutes of HV separately. Results: 398 children (68.7%) completed 5 minutes HV. Seizures were precipitated during the first 3 minutes of HV in 2 children, and during the last 2 minutes in one more child. Inter-ictal EEG abnormalities were precipitated in the first 3 minutes of HV in 31 children, and during the last 2 min in 4 more children. All 398 children completed HV during the last 2 minutes successfully and no adverse events occurred during the last 2 minutes of HV. Conclusion: 33.33% of seizures and 11.5% of inter-ictal EEG abnormalities triggered by HV occurred during the last 2 min of HV. This finding supports the utility of prolonged hyperventilation for 5 minutes. Prolonged HV for 5 minutes increases the diagnostic yield of EEG in paediatric population and it is safe and feasible.

Melatonin versus Sleep Deprivation for Sleep Induction in Nap Electroencephalography: Protocol for a Prospective Randomized Crossover Trial in Children and Young Adults with Epilepsy

Electroencephalography (EEG) continues to be a pivotal investigation in children with epilepsy, providing diagnostic evidence and supporting syndromic classification. In the pediatric population, electroencephalographic recordings are frequently performed during sleep, since this procedure reduces the number of artifacts and activates epileptiform abnormalities. To date, no shared guidelines are available for sleep induction in EEG. Among the interventions used in the clinical setting, melatonin and sleep deprivation represent the most used methods. The main purpose of this study is to test the non-inferiority of 3–5 mg melatonin versus sleep deprivation in achieving sleep in nap electroencephalography in children and young adult patients with epilepsy. To test non-inferiority, a randomized crossover trial is proposed where 30 patients will be randomized to receive 3–5 mg melatonin or sleep deprivation. Each enrolled subject will perform EEG recordings during sleep in the early afternoon for a total of 60 EEGs. In the melatonin group, the study drug will be administered a single oral dose 30 min prior to the EEG recording. In the sleep deprivation group, parents will be required to subject the child to sleep deprivation the night before registration. Urinary and salivary concentrations of melatonin and of its main metabolite 6-hydroxymelatonin will be determined by using a validated LC-MS method. The present protocol aims to offer a standardized protocol for sleep induction to be applied to EEG recordings in those of pediatric age. In addition, melatonin metabolism and elimination will be characterized and its potential interference in interictal abnormalities will be assessed.

Routine and sleep EEG: Minimum recording standards of the International Federation of Clinical Neurophysiology and the International League Against Epilepsy

This article provides recommendations on the minimum standards for recording routine ("standard") and sleep electroencephalography (EEG). The joint working group of the International Federation of Clinical Neurophysiology (IFCN) and the International League Against Epilepsy (ILAE) developed the standards according to the methodology suggested for epilepsy-related clinical practice guidelines by the Epilepsy Guidelines Working Group. We reviewed the published evidence using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. The quality of evidence for sleep induction methods was assessed by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) method. A tool for Quality Assessment of Diagnostic Studies (QUADAS-2) was used to assess the risk of bias in technical and methodological studies. Where high-quality published evidence was lacking, we used modified Delphi technique to reach expert consensus. The GRADE system was used to formulate the recommendations. The quality of evidence was low or moderate. We formulated 16 consensus-based recommendations for minimum standards for recording routine and sleep EEG. The recommendations comprise the following aspects: indications, technical standards, recording duration, sleep induction, and provocative methods.

Routine and sleep EEG: Minimum recording standards of the International Federation of Clinical Neurophysiology and the International League Against Epilepsy

This article provides recommendations on the minimum standards for recording routine ("standard") and sleep electroencephalography (EEG). The joint working group of the International Federation of Clinical Neurophysiology (IFCN) and the International League Against Epilepsy (ILAE) developed the standards according to the methodology suggested for epilepsy-related clinical practice guidelines by the Epilepsy Guidelines Working Group. We reviewed the published evidence using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. The quality of evidence for sleep induction methods was assessed by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) method. A tool for Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess the risk of bias in technical and methodological studies. Where high-quality published evidence was lacking, we used modified Delphi technique to reach expert consensus. The GRADE system was used to formulate the recommendations. The quality of evidence was low or moderate. We formulated 16 consensus-based recommendations for minimum standards for recording routine and sleep EEG. The recommendations comprise the following aspects: indications, technical standards, recording duration, sleep induction, and provocative methods.

Electroencephalogram utilization and psychiatric comorbidities among children and adolescents with epilepsy in rural Southwestern Uganda

OBJECTIVE

This study aimed at describing routine electroencephalogram (EEG) findings among children and adolescents with a clinical diagnosis of epilepsy and determines how interictal EEG abnormalities vary with the psychiatric comorbidities.

METHODS

We conducted a cross-sectional study among children and adolescents with epilepsy aged 5-18 years receiving care from a regional referral hospital in Southwestern Uganda. Psychiatric comorbidities were assessed using an adapted parent version of Child and Adolescent Symptom Inventory-5. Thirty-minute EEG samples were taken from routine EEG recordings that were locally performed and remotely interpreted for all participants.

RESULTS

Of the 140 participants, 71 (50.7%) had normal EEG findings and 51 (36.4%) had epileptiform abnormalities while 18 (12.9%) had non-epileptiform. Of those who had epileptiform abnormalities on EEG, 23 (45.1%) were focal, 26 (51.0%) were generalized, and 2 (3.9%) were focal with bilateral spread. There was no significant association between the different psychiatric comorbidities and the interictal EEG abnormalities.

CONCLUSIONS

Among children and adolescents with a clinical diagnosis of epilepsy in Southwestern Uganda, only 36% showed epileptiform abnormalities on their EEG recordings. There was no association between the interictal EEG abnormalities and psychiatric comorbidities.

Brain magnetic resonance imaging findings among children with epilepsy in two urban hospital settings, Kampala-Uganda: a descriptive study

Background

Epilepsy is one of the most common neurological conditions in children worldwide. Its presentation is heterogeneous, with diverse underlying aetiology, clinical presentation, and prognosis. Structural brain abnormalities are among the recognized causes of epilepsy. Brain Magnetic Resonance Imaging (MRI) is the imaging modality of choice for epilepsy workup.

We aimed to determine the prevalence and describe the structural abnormalities identified in the brain MRI studies performed on children with epilepsy from two urban hospitals in Kampala, Uganda.

Methods

This was a cross-sectional descriptive study performed at two urban hospital MRI centres. The study population was 147 children aged 1 day to 17 years with confirmed epilepsy. Brain MRI was performed for each child and a questionnaire was used to collect clinical data.

Results

The prevalence of structural abnormalities among children with epilepsy was 74.15% (109 out of 147). Of these, 68.81% were male, and the rest were female. Among these, the majority, 40.14% (59 of 144) were aged 1 month to 4 years. Acquired structural brain abnormalities were the commonest at 69.22% with hippocampal sclerosis (HS) leading while disorders of cortical development were the most common congenital causes.

An abnormal electroencephalogram (EEG) was significant for brain MRI abnormalities among children with epilepsy with 95% of participants with an abnormal EEG study having epileptogenic structural abnormalities detected in their brain MRI studies.

Conclusion and recommendation

Two-thirds of children with epilepsy had structural brain abnormalities. Abnormal activity in the EEG study was found to positively correlate with abnormal brain MRI findings. As such, EEG study should be considered where possible before MRI studies as a determinant for children with epilepsy who will be having imaging studies done in the Ugandan setting.

Provoked seizures at the onset of progressive disease contribute to diagnosis delay - A tertiary center experience in a cohort of 22 children with CLN2

PURPOSE

The evaluation of epilepsy features and factors with impact to diagnosis delay in children with CLN2.

METHOD

The study included children with CLN2 treated from 2000 to 2020. Diagnosis was confirmed by: TPP1 deficiency and/or TPP1 gene mutation or pathognomonic electron microscopy findings. The seizure features were evaluated: the age of onset, provocation, semiology and EEG. The disease severity was assessed by CLN2 Clinical Rating Scale (CLN2-CRS). Statistical analysis included T test, chi-square test, Wilcoxon-Mann-Whitney test, using SPSS statistics 25.

RESULT

The study included 22 children with CLN2. Seizures were experienced by all cases at the early stage of disease, preceded by language delay in 18, and behavior problems in 14 pts. The first seizure was provoked in 9 children at mean age of 33.8 ± 4.6 months, and unprovoked in 13 at mean age of 34.6 ± 2.7 months. In patients with provoked first seizure, the average period from the first seizure to diagnosis was longer (35.1 months), with lower CLN2-CRS, then in those with unprovoked (23.8 months) first seizures (p < 0.008). Initial seizures were generalized tonic-clonic (Pampiglione and Harden, 1973 Feb) [8], atonic (Pampiglione and Harden, 1973 Feb) [8], and focal (Beltrán et al., 2018 Aug) [4], with recurrence within two months. With progression, the patients experienced multiple seizure types, and 1/3 suffered status epilepticus.

CONCLUSIONS

Provoked seizures at the onset of CLN2 have impact to diagnosis delay. The red flags are: preceding language delay and behavior problems, later FS onset comparing to the typical age, atonic, focal and long-lasting seizure, and recurrence of seizures within two months.

Minimum standards for inpatient long-term video-EEG monitoring: A clinical practice guideline of the international league against epilepsy and international federation of clinical neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events (see Table S1). For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and establish its clinical utility.

Minimum standards for inpatient long-term video-electroencephalographic monitoring: A clinical practice guideline of the International League Against Epilepsy and International Federation of Clinical Neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events. For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and to establish its clinical utility.

Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity

BACKGROUND AND PURPOSE

The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain.

METHODS

We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations.

RESULTS

We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters.

CONCLUSION

The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.

When should we obtain a routine EEG while managing people with epilepsy?

More than eight decades after its discovery, routine electroencephalogram (EEG) remains a safe, noninvasive, inexpensive, bedside test of neurological function. Knowing when a routine EEG should be obtained while managing people with epilepsy is a critical aspect of optimal care. Despite advances in neuroimaging techniques that aid diagnosis of structural lesions in the central nervous system, EEG continues to provide critical diagnostic evidence with implications on treatment. A routine EEG performed after a first unprovoked seizure can support a clinical diagnosis of epilepsy and differentiate those without epilepsy, classify an epilepsy syndrome to impart prognosis, and characterize seizures for antiseizure management. Despite a current viral pandemic, EEG services continue, and the value of routine EEG is unchanged.

Special Report on the Impact of the COVID-19 Pandemic on Clinical EEG and Research and Consensus Recommendations for the Safe Use of EEG

INTRODUCTION

The global COVID-19 pandemic has affected the economy, daily life, and mental/physical health. The latter includes the use of electroencephalography (EEG) in clinical practice and research. We report a survey of the impact of COVID-19 on the use of clinical EEG in practice and research in several countries, and the recommendations of an international panel of experts for the safe application of EEG during and after this pandemic.

METHODS

Fifteen clinicians from 8 different countries and 25 researchers from 13 different countries reported the impact of COVID-19 on their EEG activities, the procedures implemented in response to the COVID-19 pandemic, and precautions planned or already implemented during the reopening of EEG activities.

RESULTS

Of the 15 clinical centers responding, 11 reported a total stoppage of all EEG activities, while 4 reduced the number of tests per day. In research settings, all 25 laboratories reported a complete stoppage of activity, with 7 laboratories reopening to some extent since initial closure. In both settings, recommended precautions for restarting or continuing EEG recording included strict hygienic rules, social distance, and assessment for infection symptoms among staff and patients/participants.

CONCLUSIONS

The COVID-19 pandemic interfered with the use of EEG recordings in clinical practice and even more in clinical research. We suggest updated best practices to allow safe EEG recordings in both research and clinical settings. The continued use of EEG is important in those with psychiatric diseases, particularly in times of social alarm such as the COVID-19 pandemic.

Arterial spin-labelling and magnetic resonance spectroscopy as imaging biomarkers for detection of epileptogenic zone in non-lesional focal impaired awareness epilepsy

Background

The proper identification of an epileptic focus is a pivotal diagnostic issue; particularly in non-lesional focal impaired awareness epilepsy (FIAE). Seizures are usually accompanied by alterations of regional cerebral blood flow (rCBF) and metabolism. Arterial spin labeling-MRI (ASL-MRI) and proton magnetic resonance spectroscopy (1H-MRS) are MRI techniques that can, non-invasively, define the regions of cerebral perfusion and metabolic changes, respectively. The aim of the current study was to recognize the epileptogenic zone in patients with non-lesional FIAE by evaluating the interictal changes in rCBF and cerebral metabolic alterations, using PASL-MRI and 1H-MRS.

Results

For identification of the epileptogenic zone, increased ASLAI% assessed by PASL-MRI (at a cut-off value ≥ 5.96%) showed 95.78% accuracy, and increased %AF (at a cut-off value ≥ 9.98%) showed 98.14% accuracy, while decreased NAA/(Cho + Cr) ratio estimated by multi-voxels (MV) 1H-MRS (at a cut-off value ≥ 0.59) showed 97.74% accuracy. Moreover, the combined use of PASL-MRI and MV 1H-MRS yielded 100% sensitivity, 98.45% specificity and 98.86% accuracy.

Conclusion

The combined use of PASL-MRI and MV 1H-MRS can be considered as in-vivo proficient bio-marker for proper identification of epileptogenic zone in patients with non-lesional FIAE.

EEG Patterns Orienting to Lafora Disease Diagnosis-A Case Report in Two Beagles

Lafora Disease (LD) is a rare, fatal, late-onset, progressive form of myoclonic epilepsy, occurring in humans and dogs. Clinical manifestations of LD usually include seizures, spontaneous and reflex myoclonus with contractions of the neck and limb muscles. We studied the electroencephalogram (EEG) patterns of two beagles in whom LD was subsequently confirmed by genetic testing. In both cases, the EEG recordings, accompanied by electromyography (EMG), have shown similar uncommon patterns. The hypovoltaged background rhythm was interrupted by waxing “crescendo” polyspikes-slow wave complexes appearing 80–250 ms after the start of intermittent photic stimulation, followed by myoclonic jerks after 80–150 ms. This study highlights the value of EEG in establishing a presumptive diagnosis of LD in dogs.

Evaluation of state and trait anxiety levels of parents and children before electroencephalography procedures: A prospective study from a tertiary epilepsy center

BACKGROUND

Inadequate or misinformation about electroencephalography (EEG) and epilepsy may lead to anxiety in children and their parents. The purpose of this study was to make a simultaneous evaluation of the anxiety levels of children and parents before EEG procedures and to make a brief assessment of their knowledge about EEG.

METHODS AND MATERIALS

Children aged between 8 and 18 years who were referred for EEG tests at Department of Pediatric Neurology, Gazi University Faculty of Medicine, Ankara, Turkey and their parents were included in the study, prospectively. Data were collected through Personal Information Forms; an EEG questionnaire form, which questioned the knowledge of the participants about EEG; the Spielberger's State-Trait Anxiety Inventory (STAI) to determine anxiety levels of the parents; and the State-Trait Anxiety Inventory for Children-State form (STAIC) to determine the anxiety levels of the children. The following parameters were collected in a database: demographic data about children and parents (sex, age), indication of suspected diagnosis on EEG request (i.e., the referral diagnosis), history of epilepsy, number of EEG recordings, and results of previous EEG recordings. The state and trait anxiety test results of the children were compared between the girls and boys, between age groups, and their parents' results in terms of both trait and state anxiety in terms of EEG, sex, ages, educational levels, and working.

RESULTS

Eighty-five children (mean age: 13.25 ± 3.02 years) and 85 parents (mean age: 41.16 ± 7.65 years) were included in the study. The children's mean trait anxiety score was 32.51 ± 8.09, and the mean state anxiety score was 34.97 ± 7.62. Half of the children who had a trait anxiety score of ≤30 points had increased state anxiety levels because they received more than 30 points in the state anxiety evaluation score. No significant differences were found between the boys and girls in terms of the state and trait anxiety scores (p > 0.05). The parents' mean trait anxiety score was 39.16 ± 7.74, and the mean state anxiety score was 42.74 ± 6.22. Forty (47%) parents were found to have trait anxiety, and 52 (61.2%) parents had state anxiety before the EEG. The trait anxiety score of the mothers was statistically significantly higher than that of the fathers (p < 0.01). The investigation of the knowledge level of both parents and children about EEG demonstrated some misunderstandings or points of insufficiency.

CONCLUSION

The present study revealed that both parents and children had insufficient knowledge about EEG, and the procedure caused anxiety for both the parents and children. When EEG procedures are requested, parents and children should be given brief information about EEG and epilepsy. We think that in this way, the knowledge of both parents and children about this issue may be increased and their anxiety may be decreased.

How Deep Learning Solved My Seizure Detection Problems

Comparison of Different Input Modalities and Network Structures for Deep Learning-Based Seizure Detection

Cho KO, Jang HJ. Sci Rep. 2020;10(1):1-11. doi: 10.1038/s41598-019-56958-y

The manual review of an electroencephalogram (EEG) for seizure detection is a laborious and error-prone process. Thus, automated seizure detection based on machine learning has been studied for decades. Recently, deep learning has been adopted in order to avoid manual feature extraction and selection. In the present study, we systematically compared the performance of different combinations of input modalities and network structures on a fixed window size and data set to ascertain an optimal combination of input modalities and network structures. The raw time series EEG, periodogram of the EEG, 2-dimensional [2D] images of short-time Fourier transform results, and 2D images of raw EEG waveforms were obtained from 5-second segments of intracranial EEGs recorded from a mouse model of epilepsy. A fully connected neural network (FCNN), recurrent neural network (RNN), and convolutional neural network (CNN) were implemented to classify the various inputs. The classification results for the test data set showed that CNN performed better than FCNN and RNN, with the area under the curve (AUC) for the receiver operating characteristics curves ranging from 0.983 to 0.984, from 0.985 to 0.989, and from 0.989 to 0.993 for FCNN, RNN, and CNN, respectively. As for input modalities, 2D images of raw EEG waveforms yielded the best result with an AUC of 0.993. Thus, CNN can be the most suitable network structure for automated seizure detection when applied to the images of raw EEG waveforms, since CNN can effectively learn a general spatially invariant representation of seizure patterns in 2D representations of raw EEG.

EEG autoregressive modeling analysis: A diagnostic tool for patients with epilepsy without epileptiform discharges

OBJECTIVE

Numerous types of nonepileptic paroxysmal events, such as syncopes and psychogenic nonepileptic seizures, may imitate epileptic seizures and lead to diagnostic difficulty. Such misdiagnoses may lead to inappropriate treatment in patients that can considerably affect their lives. Electroencephalogram (EEG) is a commonly used tool in assisting diagnosis of epilepsy. Although the appearance of epileptiform discharges (EDs) in EEG recordings is specific for epilepsy diagnosis, only 25%-56% of patients with epilepsy show EDs in their first EEG examination.

METHODS

In this study, we developed an autoregressive (AR) model prediction error-based EEG classification method to distinguish EEG signals between controls and patients with epilepsy without EDs. Twenty-three patients with generalized epilepsy without EDs in their EEG recordings and 23 age-matched controls were enrolled. Their EEG recordings were classified using AR model prediction error-based EEG features.

RESULTS

Among different classification methods, XGBoost achieved the highest performance in terms of accuracy and true positive rate. The results showed that the accuracy, area under the curve, true positive rate, and true negative rate were 85.17%, 87.54%, 89.98%, and 81.81%, respectively.

CONCLUSIONS

Our proposed method can help neurologists in the early diagnosis of epilepsy in patients without EDs and might help in differentiating between nonepileptic paroxysmal events and epilepsy.

SIGNIFICANCE

EEG AR model prediction errors could be used as an alternative diagnostic marker of epilepsy.

Rapid eye movement (REM) sleep and seizure control in idiopathic generalized epilepsy

BACKGROUND

Sleep and epilepsy are bedfellows, and they affect each other reciprocally. Despite the well-known relationship between sleep and epilepsy, data about the impact of sleep on seizure control and responsiveness to therapy are scarce.

OBJECTIVE

The aim of this work was to study the impact of sleep architecture in drug-naïve patients with idiopathic generalized epilepsy (IGE) on seizure control and responsiveness to treatment.

METHODS

This is a prospective cohort study conducted on thirty newly diagnosed patients with IGE attending the epilepsy clinic in Alexandria University Hospital in Egypt and thirty healthy controls. All recruited subjects had a baseline overnight polysomnographic study, then patients were given sodium valproate in therapeutic doses and followed up for six months for assessment of seizure control. After follow-up, they were classified into fully controlled and inadequately controlled patients, and a comparison between them was made.

RESULTS

Of the recruited patients, 13 were fully controlled. Rapid eye movement (REM) sleep % was significantly lower among inadequately controlled patients (9.01 ± 6.23) than fully controlled group (19.6 ± 9.01) and controls (18.17 ± 4.85) (p = 0.002), and the REM sleep latency was significantly longer among the inadequately controlled patients (115.7 ± 72.8 min) than fully controlled patients (54.6 ± 77.3 min) and controls (68.75 ± 37.95 min) (p = 011). On univariate regression analysis, the Odd's ratio (OR) for REM sleep percentage was 3.04 (p = 0.001).

CONCLUSION

Rapid eye movement sleep percentage and latency can contribute to seizure control in IGE.

Epilepsy in LAMA2-related muscular dystrophy: An electro-clinico-radiological characterization

OBJECTIVE

To delineate the epileptic phenotype of LAMA2-related muscular dystrophy (MD) and correlate it with the neuroradiological and muscle biopsy findings, as well as the functional motor phenotype.

METHODS

Clinical, electrophysiological, neuroradiological, and histopathological data of 25 patients with diagnosis of LAMA2-related MD were analyzed.

RESULTS

Epilepsy occurred in 36% of patients with LAMA2-related MD. Mean age at first seizure was 8 years. The most common presenting seizure type was focal-onset seizures with or without impaired awareness. Visual aura and autonomic signs, including vomiting, were frequently reported. Despite a certain degree of variability, bilateral occipital or temporo-occipital epileptiform abnormalities were by far the most commonly observed. Refractory epilepsy was found in 75% of these patients. Epilepsy in LAMA2-related MD was significantly more prevalent in those patients in whom the cortical malformations were more extensive. In contrast, the occurrence of epilepsy was not found to be associated with the patients' motor ability, the size of their white matter abnormalities, or the amount of residual merosin expressed on muscle.

SIGNIFICANCE

The epileptic phenotype of LAMA2-related MD is characterized by focal seizures with prominent visual and autonomic features associated with EEG abnormalities that predominate in the posterior quadrants. A consistent correlation between epileptic phenotype and neuroimaging was identified, suggesting that the extension of the polymicrogyria may serve as a predictor of epilepsy occurrence.

Can commercially available wearable EEG devices be used for diagnostic purposes? An explorative pilot study

Electroencephalography (EEG) is a core element in the diagnosis of epilepsy syndromes and can help to monitor antiseizure treatment. Mobile EEG (mEEG) devices are increasingly available on the consumer market and may offer easier access to EEG recordings especially in rural or resource-poor areas. The usefulness of consumer-grade devices for clinical purposes is still underinvestigated. Here, we compared EEG traces of a commercially available mEEG device (Emotiv EPOC) to a simultaneously recorded clinical video EEG (vEEG). Twenty-two adult patients (11 female, mean age 40.2 years) undergoing noninvasive vEEG monitoring for clinical purposes were prospectively enrolled. The EEG recordings were evaluated by 10 independent raters with unmodifiable view settings. The individual evaluations were compared with respect to the presence of abnormal EEG findings (regional slowing, epileptiform potentials, seizure pattern). Video EEG yielded a sensitivity of 56% and specificity of 88% for abnormal EEG findings, whereas mEEG reached 39% and 85%, respectively. Interrater reliability coefficients were better in vEEG as compared to mEEG (ϰ = 0.50 vs. 0.30), corresponding to a moderate and fair agreement. Intrarater reliability between mEEG and vEEG evaluations of simultaneous recordings of a given participant was moderate (ϰ = 0.48). Given the limitations of our exploratory pilot study, our results suggest that vEEG is superior to mEEG, but that mEEG can be helpful for diagnostic purposes. We present the first quantitative comparison of simultaneously acquired clinical and mobile consumer-grade EEG for a clinical use-case.

Lafora Disease: Report of a Rare Entity

Lafora disease is a rare, genetic, glycogen metabolism disorder inherited as autosomal recessive characterized by the presence of inclusion bodies, known as Lafora bodies, within the cytoplasm of the cells in the heart, liver, muscle, and skin. Lafora disease presents as a neurodegenerative disorder that causes impairment in the development of cerebral cortical neurons. We present here a case of Lafora disease that presented with progressive myoclonus epilepsy (PME) and investigated at our center. She was diagnosed to have Lafora disease with typical histological findings on skin biopsy and was found to be positive for the pathogenic mutation on genetic testing.

Low Complexity Automatic Stationary Wavelet Transform for Elimination of Eye Blinks from EEG

The electroencephalogram signal (EEG) often suffers from various artifacts and noises that have physiological and non-physiological origins. Among these artifacts, eye blink, due to its amplitude is considered to have the most influence on EEG analysis. In this paper, a low complexity approach based on Stationary Wavelet Transform (SWT) and skewness is proposed to remove eye blink artifacts from EEG signals. The proposed method is compared against Automatic Wavelet Independent Components Analysis (AWICA) and Enhanced AWICA. Normalized Root Mean Square Error (NRMSE), Peak Signal-to-Noise Ratio (PSNR), and correlation coefficient ( ρ ) between filtered and pure EEG signals are utilized to quantify artifact removal performance. The proposed approach shows smaller NRMSE, larger PSNR, and larger correlation coefficient values compared to the other methods. Furthermore, the speed of execution of the proposed method is considerably faster than other methods, which makes it more suitable for real-time processing.

A Framework Proposal to Follow-Up on Preclinical Convulsive Signals of a New Molecular Entity in First-in-Human Studies Using Electroencephalographic Monitoring

Traditionally, in dose-escalating first-in-human (FiH) studies, a dose cap with a 10-fold safety margin to the no observed effect level in animals is implemented if convulsive events are observed in animals. However, the convulsive risk seen in animals does not generally translate to humans. Several lines of evidence are summarized indicating that in a dose-escalating setting, electroencephalographic epileptiform abnormalities occur at lower doses than clinical convulsive events. Therefore, we propose to consider the occurrence of epileptiform abnormalities in toxicology studies as premonitory signals for convulsions in dose-escalating FiH studies. Compared with the traditional dose-cap approach, this may allow the exploration of higher doses in FiH and, subsequently, phase II studies without compromising human safety. Similarly, the presence or absence of electroencephalographic epileptiform abnormalities may also aid the assessment of proconvulsive risk in situations of increased perpetrator burden as potentially present in pharmacokinetic and/or pharmacodynamic drug-drug interactions.

Assessment of the technical usability and efficacy of a new portable dry-electrode EEG recorder: First results of the HOMEONE study

OBJECTIVES

The HOME project is intended to provide evidence of diagnostic and therapeutic yield of a patient-controlled EEG home-monitoring for neurological outpatients.

METHODS

This study evaluated the technical and practical usability and efficacy of a new portable dry-electrode EEG recorder in comparison to conventional EEG devices based on technical assessments and inter-rater comparisons of EEG record examinations of office-based practitioners and two experienced neurologists.

RESULTS

The technical assessment was based on channel-wise comparisons of band power values derived from power spectra as observed in two recording modalities. Slight yet significant differences were observed only in the Delta-frequency band (1.5-4 Hz). The fraction of automatically detected artifact segments was larger in the new portable recordings than in conventional recordings (20% vs. 11%, median). Overall, 93% of raters' stated diagnostic findings gathered from conventional devices were concordant with stated diagnostic findings gathered from the new portable device.

CONCLUSION

The new EEG device was shown to have technical comparability to and a high concordance rate of diagnostic findings with conventional EEG devices.

SIGNIFICANCE

The new portable dry-electrode EEG device is suitable to meet the HOME projects' goal of establishing a patient-controlled EEG home-monitoring in the routine care of neurological outpatients.

TRIAL REGISTRATION

DRKS DRKS00012685. Registered 09 August 2017, retrospectively registered.

Update on Minimal Standards for Electroencephalography in Canada: A Review by the Canadian Society of Clinical Neurophysiologists

Surface electroencephalogram (EEG) recording remains the gold standard for noninvasive assessment of electrical brain activity. It is the most efficient way to diagnose and classify epilepsy syndromes as well as define the localization of the epileptogenic zone. The EEG is useful for management decisions and for establishing prognosis in some types of epilepsy. Electroencephalography is an evolving field in which new methods are being introduced. The Canadian Society of Clinical Neurophysiologists convened an expert panel to develop new national minimal guidelines. A comprehensive evidence review was conducted. This document is organized into 10 sections, including indications, recommendations for trained personnel, EEG yield, paediatric and neonatal EEGs, laboratory minimal standards, requisitions, reports, storage, safety measures, and quality assurance.

Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks

Numerous nonepileptic paroxysmal events, such as syncope and psychogenic nonepileptic seizures, may imitate seizures and impede diagnosis. Misdiagnosis can lead to mistreatment, affecting patients’ lives considerably. Electroencephalography is commonly used for diagnosing epilepsy. Although on electroencephalograms (EEGs), epileptiform discharges (ED) specifically indicate epilepsy, only approximately 50% of patients with epilepsy have ED in their first EEG. In this study, we developed a deep convolutional neural network (ConvNet)-based classifier to distinguish EEG between patients with epilepsy without ED and controls. Overall, 25 patients with epilepsy without ED in their EEGs and 25 age-matched patients with Tourette syndrome or syncope were enrolled. Their EEGs were classified using the deep ConvNet. When the EEG data without overlapping were used, the accuracy, sensitivity, and specificity were 65.00%, 48.00%, and 82.00%, respectively. The performance measures improved when the input EEG data were augmented through overlapping. With 95% EEG data overlapping, the accuracy, sensitivity, and specificity increased to 80.00%, 70.00%, and 90.00%, respectively. The proposed method could be regarded as a pilot study to demonstrate a proof of concept of a potential diagnostic value of deep ConvNet in patients with epilepsy without ED. Further studies are needed to assist neurologists in distinguishing nonepileptic paroxysmal events from epilepsy.

Sleep deprivation and melatonin for inducing sleep in paediatric electroencephalography: a prospective multicentre service evaluation

AIM

To compare the efficacy of the main methodologies in attaining sleep and electroencephalography (EEG) abnormalities in children with a view to producing recommendations on best practice.

METHOD

Fifty-one UK centres participated. Methods for sleep induction (sleep deprivation, melatonin, and combined sleep deprivation/melatonin) were compared. Data pertaining to demographics, achievement of stage II sleep, and recording characteristics (duration of study, presence of epileptiform activity in awake/sleep states) were prospectively collected for consecutive patients in November and December 2013.

RESULTS

Five hundred and sixty-five patients were included. Age range was 1 years to 17 years (mean 7y 10mo), 27.7 per cent had an underlying neurobehavioural condition. Stage II sleep was achieved in 69 per cent of sleep deprived studies, 77 per cent of melatonin studies, and 90 per cent of combined intervention studies (p<0.001, χ² ). In children who slept, there was no difference between the three interventions in eliciting epileptiform discharges. In children who did not sleep, epileptiform abnormalities were seen more often than after sleep deprivation alone (p=0.02, χ² ). Seizures were rare.

INTERPRETATION

Combined sleep deprivation/melatonin is more effective than either method alone in achieving sleep. The occurrence of epileptiform activity during sleep is broadly similar across the three groups. We recommend the combined intervention to induce sleep for paediatric EEG.

WHAT THIS PAPER ADDS

Combined sleep deprivation/melatonin is more effective in achieving sleep than either sleep deprivation or melatonin alone. Sleep latency is shorter with combined sleep deprivation/melatonin. When children do sleep, there is no difference in the occurrence of epileptiform abnormalities between different induction methods. Seizures are rare in sleep electroencephalography recordings.

How Long Should Routine EEG Be Recorded to Get Relevant Information?

OBJECTIVE

The optimal duration of routine EEG (rEEG) has not been determined on a clinical basis. This study aims to determine the time required to obtain relevant information during rEEG with respect to the clinical request.

METHOD

All rEEGs performed over 3 months in unselected patients older than 14 years in an academic hospital were analyzed retrospectively. The latency required to obtain relevant information was determined for each rEEG by 2 independent readers blinded to the clinical data. EEG final diagnoses and latencies were analyzed with respect to the main clinical requests: subacute cognitive impairment, spells, transient focal neurologic manifestation or patients referred by epileptologists.

RESULTS

From 430 rEEGs performed in the targeted period, 364 were analyzed: 92% of the pathological rEEGs were provided within the first 10 minutes of recording. Slowing background activity was diagnosed from the beginning, whereas interictal epileptiform discharges were recorded over time. Moreover, the time elapsed to demonstrate a pattern differed significantly in the clinical groups: in patients with subacute cognitive impairment, EEG abnormalities appeared within the first 10 minutes, whereas in the other groups, data could be provided over time.

CONCLUSION

Patients with subacute cognitive impairment differed from those in the other groups significantly in the elapsed time required to obtain relevant information during rEEG, suggesting that 10-minute EEG recordings could be sufficient, arguing in favor of individualized rEEG. However, this conclusion does not apply to intensive care unit patients.

Electroencephalography-based monitors

An electroencephalogram (EEG), detects changes and abnormalities in the electrical activity of the brain and thus provides a way to dynamically assess brain function. EEG may be used to diagnose and manage a number of clinical conditions such as epilepsy, convulsive and non-convulsive status epilepticus, encephalitis, barbiturate coma, brain death, etc., EEG provides a large amount of information to the anaesthesiologist for routine clinical practice as depth of anaesthesia monitors and detection of sub-clinical seizures; and also for understanding the complex mechanisms of anaesthesia-induced alteration of consciousness. In the initial years, the routine clinical applicability of EEG was hindered by the complexity of the raw EEG signal. However, with technological advancement, several EEG-derived dimensionless indices have been developed that correlate with the depth of the hypnotic component of anaesthesia and are easy to interpret. Similarly, with the development of quantitative EEG tools, the routine use of continuous EEG is ever expanding in the Intensive Care Units. This review, describe various commonly used EEG-based monitors and their clinical applicability in the field of anaesthesia and critical care.

Integration of 24 Feature Types to Accurately Detect and Predict Seizures Using Scalp EEG Signals

The neurological disorder epilepsy causes substantial problems to the patients with uncontrolled seizures or even sudden deaths. Accurate detection and prediction of epileptic seizures will significantly improve the life quality of epileptic patients. Various feature extraction algorithms were proposed to describe the EEG signals in frequency or time domains. Both invasive intracranial and non-invasive scalp EEG signals have been screened for the epileptic seizure patterns. This study extracted a comprehensive list of 24 feature types from the scalp EEG signals and found 170 out of the 2794 features for an accurate classification of epileptic seizures. An accuracy (Acc) of 99.40% was optimized for detecting epileptic seizures from the scalp EEG signals. A balanced accuracy (bAcc) was calculated as the average of sensitivity and specificity and our seizure detection model achieved 99.61% in bAcc. The same experimental procedure was applied to predict epileptic seizures in advance, and the model achieved Acc = 99.17% for predicting epileptic seizures 10 s before happening.

Genetic (idiopathic) epilepsy with photosensitive seizures includes features of both focal and generalized seizures

Clinically, some patients having genetic (idiopathic) epilepsy with photosensitive seizures were difficult to be diagnosed. We aimed to discuss whether the genetic (idiopathic) epilepsy with photosensitive seizures is a focal entity, a generalized entity or a continuum. Twenty-two patients with idiopathic epilepsies and photoconvulsive response (PCR) were retrospectively recruited. In the medical records, the seizure types included “generalized tonic-clonic seizures (GTCS)” in 15, “partial secondarily GTCS (PGTCS)” in 3, partial seizures (PS) in 3, myoclonic seizures in 2, eyelid myoclonus in one, and only febrile seizures in one. Seizure types of PCR included GTCS (1/22), PGTCS (6/22), PS (9/22), electrical seizures (ES) (3/22) and GTCS/PGTCS (3/22). Combined the medical history with PCR results, they were diagnosed as: idiopathic (photosensitive) occipital lobe epilepsy (I(P)OE) in 12, genetic (idiopathic) generalized epilepsy (GGE) in one, GGE/I(P)OE in 5, pure photosensitive seizure in one, and epilepsy with undetermined generalized or focal seizure in 3. So, the dichotomy between generalized and focal seizures might have been out of date regarding to pathophysiological advances in epileptology. To some extent, it would be better to recognize the idiopathic epilepsy with photosensitive seizures as a continuum between focal and generalized seizures.

Usefulness of EEG for the differential diagnosis of possible transient ischemic attack

OBJECTIVE

EEG value in possible transient ischemic attacks (TIA) is unknown. We aim to quantify focal slow wave activity (FSWA) and epileptiform activity (EA) frequency in possible TIA, and to analyse its contribution to the final diagnosis of seizures and/or definitive TIA.

METHODS

Prospective longitudinal study of possible TIA patients evaluated at a tertiary centre during 36 months and with 1-3 months follow-up. EEG was performed as soon as possible (early EEG) and one month later (late EEG). A stroke neurologist established final diagnosis after reassessing all clinical and diagnostic tests.

RESULTS

80 patients underwent an early EEG (45.8 h after possible TIA): 52 had FSWA and 6 of them also EA. Early FSWA was associated with epileptic seizure or definitive TIA final diagnosis (p = .041). Patients with these diagnoses had more frequently early FSWA (19/23; 82.6%) than EA (6/23; 26.1%). 6/13 (46.2%) patients with epileptic seizure final diagnosis had EA.In the late EEG, 43 (58.1%) patients demonstrated persistent FSWA and 3 of them also EA. Persistent FSWA in the late EEG was more frequent in seizures than in TIA patients (91.7% vs. 45.5%). FSWA disappearance was associated with acute vascular lesion on neuroimage.

CONCLUSIONS

FSWA was the commonest EEG abnormality found in the early EEG of patients with possible TIA, but did not distinguish between TIA and seizure patients. In patients with seizures, FSWA was more common than EA and its presence in the late EEG was more likely in patients with epileptic seizures than with TIA.

SIGNIFICANCE

The majority of possible TIA patients with the final diagnosis of epileptic seizures do not have EA in the early or late EEG.

Paroxysmal events during prolonged video-video electroencephalography monitoring in refractory epilepsy

INTRODUCTION

Given that epileptic seizures and non-epileptic paroxysmal events have similar clinical manifestations, using specific diagnostic methods is crucial, especially in patients with drug-resistant epilepsy. Prolonged video electroencephalography monitoring during epileptic seizures reveals epileptiform discharges and has become an essential procedure for epilepsy diagnosis. The main purpose of this study is to characterise paroxysmal events and compare patterns in patients with refractory epilepsy.

METHODS

We conducted a retrospective analysis of medical records from 91 patients diagnosed with refractory epilepsy who underwent prolonged video electroencephalography monitoring during hospitalisation.

RESULTS

During prolonged video electroencephalography monitoring, 76.9% of the patients (n=70) had paroxysmal events. The mean number of events was 3.4±2.7; the duration of these events was highly variable. Most patients (80%) experienced seizures during wakefulness. The most common events were focal seizures with altered levels of consciousness, progressive bilateral generalized seizures and psychogenic non-epileptic seizures. Regarding all paroxysmal events, no differences were observed in the number or type of events by sex, in duration by sex or age at onset, or in the number of events by type of event. Psychogenic nonepileptic seizures were predominantly registered during wakefulness, lasted longer, started at older ages, and were more frequent in women.

CONCLUSIONS

Paroxysmal events recorded during prolonged video electroencephalography monitoring in patients with refractory epilepsy show similar patterns and characteristics to those reported in other latitudes.

The relationship between epileptiform discharges and background activity in the visual analysis of electroencephalographic examinations in dogs with seizures of different etiologies

Electroencephalographic (EEG) recordings in 125 outpatient dogs with various epileptiform encephalopathies were acquired under medetomidine sedation using subdermal wire electrodes. The features of canine EEG (background activity [BGA] and epileptiform discharges [EDs]) were assessed, described and compared. The dogs included neurologically healthy controls (N, n = 19), dogs with portosystemic shunt (PSS, n = 9), dogs with intracranial pathologies (IP, n = 27) and dogs with idiopathic epilepsy (IE, n = 70). A visual EEG analysis revealed significantly more pronounced high voltage, low-frequency BGA in the PSS and IP groups in comparison to the N and IE groups (PSS vs. N, PSS vs. IE P <0.0001; IP vs. N, IP vs. IE P = 0.043). At least one ED in the recording was found in 47.37% (n = 9/19) of the individuals in the N group, 88.9% (n = 8/9) of the dogs in the PSS group, 77.78% (n = 21/27) of the dogs in the IP group and 61.43% (n = 43/70) of the dogs in the IE group. The presence of bilateral symmetric triphasic (BST) waves was significantly higher in the PSS group than in the remaining groups. There was a strong prevalence of spike-waves in dogs with idiopathic epilepsy and of BST waves in dogs with portosystemic shunt. None of the dogs in group N had spike-waves or BST activity. EDs were observed more frequently in high and very high voltage, low frequency BGA than in low voltage, high frequency BGA.