EEG Seizure Research Articles

Allopregnanolone and progesterone in relation to a single electroconvulsive therapy seizure and subsequent clinical outcome: an observational cohort study

BackgroundElectroconvulsive therapy (ECT) is an important treatment for several severe psychiatric conditions, yet its precise mechanism of action remains unknown. Increased inhibition in the brain after ECT seizures, mediated by γ-aminobutyric acid (GABA), has been linked to clinical effectiveness. Case series on epileptic patients report a postictal serum concentration increase of the GABAA receptor agonist allopregnanolone. Serum allopregnanolone remains unchanged after a full ECT series, but possible transient effects directly after a single ECT seizure remain unexplored. The primary aim was to measure serum concentrations of allopregnanolone and its substrate progesterone after one ECT seizure. Secondary aims were to examine whether concentrations at baseline, or postictal changes, either correlate with seizure generalization or predict clinical outcome ratings after ECT.MethodsA total of 130 participants (18–85 years) were included. Generalization parameters comprised peak ictal heart rate, electroencephalographic (EEG) seizure duration, and prolactin increase. Outcome measures were ratings of clinical global improvement, perceived health status and subjective memory impairment. Non-parametric tests were used for group comparisons and correlations. The prediction analyses were conducted with binary logistic and simple linear regression analyses.ResultsAllopregnanolone and progesterone remained unchanged and correlated neither with seizure generalization nor with clinical outcome. In men (n = 50), progesterone increased and allopregnanolone change correlated negatively with EEG seizure duration. In a subgroup analysis (n = 62), higher baseline allopregnanolone and progesterone correlated with postictal EEG suppression.ConclusionsECT seizures have different physiologic effects than generalized seizures in epilepsy. Progesterone might have implications for psychiatric illness in men.

Identifying the infraslow activity associated with faciobrachial dystonic seizures in EEG.

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Patterns of ictal surface EEG in occipital seizures: A simultaneous scalp and intracerebral recording study

ObjectiveTo describe the ictal scalp EEG patterns of occipital seizures (OS) and their spatiotemporal correlations with intracerebral occipital ictal discharges derived from simultaneous SEEG-EEG recordings. MethodsPatients with SEEG confirmed OS (14 OS from 8 patients) were selected from an epilepsy surgery center and were monitored 3–10 days using simultaneous scalp EEG and SEEG recordings. ResultsOn scalp EEG, the most common onset patterns were background activity suppression (28.6 %) and high amplitude slow wave corresponding to intracerebral DC-shift (28.6 %) and occurred with a median delay of 0 s after intra-cerebral onset. The initial discharge involved occipital electrodes in only 50 % of the seizures (7/14) with additional basal temporal (8/14) or parietal electrodes (5/14). The onset was ipsilateral to the intra-cerebral onset zone in 71.4 % of seizures and bilateral in the remaining (28.6 %). The most common propagation pattern was either unilateral (50 %) or bilateral (50 %) and a rhythmic slow activity (66.7 %). Different OS subtypes display distinct scalp EEG patterns. ConclusionScalp EEG accurately determines intra-cerebral seizure onset time in OS and has good lateralizing value. However, initial scalp modification does not always involves occipital electrodes and the second modification is well lateralizing in only 50 % of seizures. SignificanceThis study describes will help clinicians to better identify OS during video EEG and better plan intra-cerebral explorations for epilepsy surgery.

Adjuvant High Dose Erythropoietin with Delayed Therapeutic Hypothermia in Neonatal Hypoxic-Ischemic Encephalopathy

BackgroundTherapeutic hypothermia (TH) is the standard of treatment for moderate to severe HIE. However, half of asphyxiated babies have a disability despite undergoing hypothermia. Erythropoietin (EPO) is a potential neuroprotective agent. ObjectiveTo evaluate the benefits of high-dose EPO combined with TH on brain magnetic resonance imaging (MRI) scores and neurodevelopmental outcomes in neonates with moderate-to-severe HIE, especially in neonates who received TH between 6–12 h of birth. MethodsThis prospective, single-blinded, randomized, placebo-controlled trial enrolled term newborns with moderate to severe HIE admitted to neonatal ICU between April 2018 and April 2022. Hypothermia was started within 12 hours of age. Infants were randomized to receive EPO 1000 units/kg or an equal volume of normal saline (placebo) on days 1,2,3,5 and 7 of age in combination with hypothermia. ResultsFifty-seven neonates with moderate-to-severe HIE were recruited; ten were excluded. Forty-seven patients were included: 32 received TH within 6 hours (group I) and 15 TH was started within 6–12 h of birth (group II). The clinical characteristics of mothers, infants, maternal complications, and resuscitations performed during the perinatal period showed no statistical differences between EPO and placebo groups I and II. The MRI scores and brain injury patterns did not differ between the EPO and placebo groups. There is no statistical significance in either group's seizure and severe EEG background (initial and after rewarming) between EPO and placebo in each group. There were no differences in developmental outcomes (Abnormal Denver II >2 area, GMFCS >1), BSID-III score (cognitive, language, and motor), or disability (hearing impairment and impaired vision) between the EPO and placebo Groups I and II at 12 and 18 months. ConclusionsAmong term infants with moderate-to-severe HIE, TH with EPO administration, compared with TH alone, did not reduce brain injury on MRI or reduce the risk of neurological sequelae both in TH within 6 h and in patients who received TH late later (6–12 h). Further studies on the benefit of EPO injection alone or before TH in situations where TH cannot be performed are required.

Machine Learning Models for Probability Classification in Spectrographic EEG Seizures Dataset

The examination of brain signals, namely the Electroencephalogram (EEG) signals, is an approach to possibly detect seizures of the brain. Due to the nature of these signals, deep learning techniques have offered the opportunity to perform automatic or semi-automatic analysis which could support decision and therapeutical approaches. This paper focuses on the possibility of classifying EEG seizure using convolutional layers (namely EfficientNetV2 architectures, i.e., EfficientNetV2S and EfficientNetV2B2), Long Short-Term Memory (LSTM) units, and fine-tuned mechanisms of attention. We use these techniques to untangle the complexity of these signals and accurately predict seizures. The proposed system provided interesting results with an 86.45% accuracy under the Kullback-Leibler Divergence loss of 0.95. Moreover, these results showed that embedding LSTM layers deeply increases the quality of the results since these layers support the analysis of the spatial-temporal dynamics of the EEG signals. On the other hand, it is important to mention that hardware limitations could affect these results and therefore it is important, when setting this architectural system, to fine-tune the data set and balance the performance vs the computational cost of the process.

Effect of quantitative consciousness index on seizure parameters during electroconvulsive therapy in patients with major depressive disorder

BACKGROUND Electroconvulsive therapy (ECT) is both an effective treatment for patients with major depressive disorder (MDD) and a noxious stimulus. Although some studies have explored the effect of sedation depth on seizure parameters in ECT, there is little research on the noxious stimulation response to ECT. In this study, we used two electroencephalography (EEG)-derived indices, the quantitative consciousness (qCON) index and quantitative nociceptive (qNOX) index, to monitor sedation, hypnosis, and noxious stimulation response in patients with MDD undergoing acute ECT. AIM To evaluate the effect of anesthesia depth based on the qCON and qNOX indices on seizure parameters. METHODS Patients with MDD (n = 24) underwent acute bilateral temporal ECT under propofol anesthesia. Before ECT, the patients were randomly divided into three groups according to qCON scores (qCON60-70, qCON50-60, and qCON40-50). Continuous qCON monitoring was performed 3 minutes before and during ECT, and the qCON, qNOX, vital signs, EEG seizure parameters, and complications during the recovery period were recorded. The 24-item Hamilton Rating Scale for Depression, Zung’s Self-rating Depression Scale, and Montreal Cognitive Assessment scores were evaluated before the first ECT session, after the fourth ECT session, and after the full course of ECT. RESULTS A total of 193 ECT sessions were performed on 24 participants. The qCON index significantly affected the EEG seizure duration, peak mid-ictal amplitude, and maximum heart rate during ECT (P < 0.05). The qNOX index significantly affected the post-ictal suppression index (P < 0.05). Age, number of ECT sessions, and anesthetic-ECT time intervals also had a significant effect on EEG seizure parameters (P < 0.05). However, there were no significant differences in complications, 24-item Hamilton Rating Scale for Depression scores, Zung’s Self-rating Depression Scale scores, or Montreal Cognitive Assessment scores among the three groups (P > 0.05). CONCLUSION Electrical stimulation at a qCON index of 60-70 resulted in better EEG seizure parameters without increasing complications in patients with MDD undergoing bilateral temporal ECT under propofol anesthesia.

Total posterior quadrant disconnection for drug‐resistant epilepsy in children

AbstractObjectiveTo assess seizure outcomes, prognostic factors, and developmental changes in children undergoing total posterior quadrant disconnection (PQD) for drug‐resistant epilepsy (DRE).MethodsWe conducted a retrospective analysis of the clinical data of children with DRE who underwent total PQD surgery. The study focused on Engel's classification for seizure outcomes, exploring correlation of preoperative data and surgical effectiveness, and predictors of seizure prognosis. It involved a comparative analysis of developmental levels pre‐ and 3 months postoperatively using Griffiths Mental Development Scales‐China (GMDS‐C), and the correlation between clinical characteristics and GMDS‐C results.ResultsOut of 61 pediatric patients, 70.5% showed no seizure recurrence postoperatively. In the univariate analysis, interictal electroencephalogram (EEG), magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG‐PET), and acute postoperative seizure (APOS) were significantly related to surgical prognosis. In multivariate analysis, interictal EEG and APOS were identified as predictors of seizure prognosis. Survival analysis indicated significant associations between MRI, interictal EEG, FDG‐PET, APOS and postoperative seizure occurrence. Preoperative GMDS‐C levels were significantly correlated with epilepsy duration, seizure frequency, interictal EEG, and FDG‐PET. GMDS‐C scores improved postoperatively, while developmental quotients remained stable.SignificanceFor patients with structural abnormalities in the entire posterior quadrant, thorough preoperative assessment and timely total PQD surgery can effectively control seizures without causing neurological development deterioration. APOS and interictal EEG abnormalities beyond the posterior quadrant are predictors for seizure prognosis but should not be deemed contraindications for surgery.Plain Language SummaryDue to lack of analysis on pediatric total PQD cases, 61 pediatric patients who underwent total PQD surgery were retrospectively enrolled. Seizure and development results were collected and analyzed as dependent variables. The study found that 70.5% of patients were seizure‐free and showed development improvement, with no deaths or severe complications reported. Prognosis predictors included APOS and interictal EEG abnormalities beyond the posterior quadrant.

Does Electroencephalography Seizure Duration Account for an Adequate Treatment of Magnetic Seizure Therapy for Schizophrenia?

A seizure lasting >15 s has been considered to indicate treatment for magnetic seizure therapy (MST), a modification of electroconvulsive therapy (ECT), without much validation. This study aimed to investigate whether this seizure duration was suitable for the treatment of schizophrenia. Altogether, 34 and 33 in-patients with schizophrenia received 10 sessions of MST and ECT, respectively. Clinical symptoms were assessed using the Positive and Negative Symptom Scale at baseline and at the 4-week follow-up. Electroencephalogram (EEG) was monitored during each MST or ECT treatment using bifrontal electrodes. The proportion of participants who achieved the 15-second threshold was only 28.6% in the MST group, with a significant difference between responders and nonresponders. For patients receiving MST, the average EEG seizure duration correlated with the percentage of Positive and Negative Symptom Scale reduction (t(32) = 2.51, P = 0.017, uncorrected; t(32) = 2.00, P = 0.055, corrected with clinical characteristics). The average EEG seizure duration predicted the clinical response at a trend level (Z = 1.76, P = 0.078) with an optimal cutoff of 11.3 seconds. All patients in the ECT group achieved the 15-second threshold. However, their average EEG seizure duration was uncorrelated with clinical improvement. The duration of EEG seizures may be associated with the antipsychotic effects of MST. This association may have been influenced by various clinical and technical factors. More research is needed to define the specific criteria for adequate MST in schizophrenia in order to achieve personalized dosing.

Astrocytic connexin 43‐hemichannels aggravate seizures by modulating blood‐brain barrier permeability in temporal lobe epilepsy mice

AbstractThe involvement of astrocytic connexin 43 (Cx43) in epileptogenesis has been extensively studied through various approaches, yet the underlying mechanism remains enigmatic. In this study, we explored whether astrocytic Cx43 forms hemichannels (HCs) that contribute to seizure progression in temporal lobe epilepsy (TLE) in mice. We focused on how these HCs influence the permeability of the blood‐brain barrier (BBB), a crucial factor in the pathophysiology of epilepsy. Immunofluorescence staining and western blot analysis were employed to assess Cx43 expression in kainic acid‐induced TLE mice, while BBB permeability was evaluated in TLE mice and those treated with TAT‐Gap19 (an astrocytic Cx43 HC inhibitor) using Evans Blue permeation, serum S100β protein quantification, ZO‐1 expression, and albumin extravasation into brain parenchyma via western blotting. Furthermore, seizure burden was monitored continuously using telemetric electroencephalography (EEG) and video monitoring in epileptic and TAT‐Gap19‐treated mice. Results demonstrated a significant increase in Cx43 content in hippocampal tissue in the TLE group, with a pronounced expression around blood vessels. TAT‐GAP19 treatment alleviated EEG seizures and BBB permeability in TLE mice. These findings suggest that astrocytic Cx43 HCs in the hippocampus play a crucial role in epileptogenesis and seizure progression by regulating BBB permeability. Targeting Cx43‐formed HCs distributed around the neurovascular unit may offer a novel therapeutic approach for epilepsy.

Classifier Combination Supported by the Sleep-Wake Cycle Improves EEG Seizure Prediction Performance.

Seizure prediction is a promising solution to improve the quality of life for drug-resistant patients, which concerns nearly 30% of patients with epilepsy. The present study aimed to ascertain the impact of incorporating sleep-wake information in seizure prediction. We developed five patient-specific prediction approaches that use vigilance state information differently: i) using it as an input feature, ii) building a pool of two classifiers, each with different weights to sleep/wake training samples, iii) building a pool of two classifiers, each with only sleep/wake samples, iv) changing the alarm-threshold concerning each sleep/wake state, and v) adjusting the alarm-threshold after a sleep-wake transition. We compared these approaches with a control method that did not integrate sleep-wake information. Our models were tested with data (43 seizures and 482 hours) acquired during presurgical monitoring of 17 patients from the EPILEPSIAE database. As EPILEPSIAE does not contain vigilance state annotations, we developed a sleep-wake classifier using 33 patients diagnosed with nocturnal frontal lobe epilepsy from the CAP Sleep database. Although different patients may require different strategies, our best approach, the pool of weighted predictors, obtained 65% of patients performing above chance level with a surrogate analysis (against 41% in the control method). The inclusion of vigilance state information improves seizure prediction. Higher results and testing with long-term recordings from daily-life conditions are necessary to ensure clinical acceptance. As automated sleep-wake detection is possible, it would be feasible to incorporate these algorithms into future devices for seizure prediction.

Postoperative EEG abnormalities in relation to neurodevelopmental outcomes after pediatric cardiac surgery.

We had reported that postoperative EEG background including sleep-wake cycle (SWC) and discharge (seizures, spikes/sharp waves) abnormalities were significantly correlated with adverse early outcomes in children after cardiac surgery. We aimed to analyze the relations between these EEG abnormalities and neurodevelopmental outcomes at about2 years after cardiac surgery. We enrolled 121 patients undergoing cardiac surgery at 3.3 months (0.03 ~ 28 months). EEG abnormalities described above during the first postoperative 48 h were evaluated. Griffiths Mental Development Scales-Chinese was used to evaluate the quotients of overall development and 5 subscales of the child's locomotor, language, personal-social, eye-hand coordination and performance skills at 16 ~ 31 months of age. EEG background abnormalities occurred in 59/121 (48.8%) patients and 33 (55.9%) unrecovered to normal by 48 h. Abnormal SWC occurred in 15 (12.4%) patients and 7 (5.8%) unrecovered to normal by 48 h. EEG seizures occurred in 11 (9.1%) patients with frontal lobe seizures in 4. Spikes/sharp waves occurred in 100 (82.6%). EEG background abnormalities, number of spikes/sharp waves and frontal lobe seizures were significantly associated with neurodevelopmental impairment at about 1 ~ 2 year after surgery (Ps ≤ 0.05). Most parameters of EEG abnormalities were significantly associated with neurodevelopmental impairment after cardiac surgery. Neurodevelopmental impairment in children with congenital heart disease remain poorly understood. Previous studies had reported that either EEG seizures or background abnormalities were associated with worse neurodevelopmental outcomes. Our present study showed that all the EEG background and discharge abnormalities including EEG background, seizures and spikes/sharp waves in the early postoperative period were significantly associated with neurodevelopmental impairment at about 1 ~ 2 years after cardiac surgery. Comprehensive evaluation of early postoperative EEG may provide further insights about postoperative brain injury, its relation with neurodevelopmental impairment, and guide to improve clinical management.

The Surgical Method of Craniectomy Differentially Affects Acute Seizures, Brain Deformation and Behavior in a TBI Animal Model.

Traumatic brain injury (TBI) is the leading cause of morbidity and mortality worldwide. Multiple injury models have been developed to study this neurological disorder. One such model is the lateral fluid-percussion injury (LFPI) rodent model. The LFPI model can be generated with different surgical procedures that could affect the injury and be reflected in neurobehavioral dysfunction and acute EEG changes. A craniectomy was performed either with a trephine hand drill or with a trephine electric drill that was centered over the left hemisphere of adult, male Sprague Dawley rats. Sham craniectomy groups were assessed by hand-drilled (ShamHMRI) and electric-drilled (ShamEMRI) to evaluate by MRI. Then, TBI was induced in separate groups (TBIH) and (TBIE) using a fluid-percussion device. Sham-injured rats (ShamH/ShamE) underwent the same surgical procedures as the TBI rats. During the same surgery session, rats were implanted with screw and microwire electrodes positioned in the neocortex and hippocampus and the EEG activity was recorded 24 hours for the first 7 days after TBI for assessing the acute EEG seizure and Gamma Event Coupling (GEC). The electric drilling craniectomy induced greater tissue damage and sensorimotor deficits compared to the hand drill. Analysis of the EEG revealed acute seizures in at least one animal from each group after the procedure. Both TBI and Sham rats from the electric drill groups had a significant greater total number of seizures than the animals that were craniectomized manually (p<0.05). Similarly, EEG functional connectivity was lower in ShamE compared to ShamH rats. These results suggest that electrical versus hand drilling craniectomies produce cortical injury in addition to the LFPI which increases the likelihood for acute post-traumatic seizures. Differences in the surgical approach could be one reason for the variability in the injury that makes it difficult to replicate results between preclinical TBI studies.

New-Onset Seizures and Seizure Worsening in the Course of COVID-19 Infection.

The aim of our study is to assess the clinical manifestations, investigation results, and outcomes in Bulgarian patients with seizures in the course of COVID-19 infection. We performed an open, prospective study during a 12-month period from January 2021 with the participation of 290inpatients and outpatients with seizures whoattended the Clinic of Neurology at the University Hospital in Plovdiv, Bulgaria. After a detailed anamnesis, they underwent neurological examination, EEG, neuroimaging, and lumbar puncture when needed. There was a prospective one-year follow-up regarding seizure frequency, EEG, and treatment. In 18 (5.9%) patients, seizures were related to COVID-19 infection. Nine (3.1%) patients had new-onset seizures, and in nine (3.1%) participants with epilepsy, there was a worsening of seizure frequency. New-onset seizures were more likely to occur inpeople above 65 years of age, within one to two months from the infection diagnosis. In one participant, seizures were related to fever. The most common seizure types were generalized tonic-clonic and focal motor seizures with/without loss of awareness. Antiseizure medications were started in seven participants. Viral encephalopathy was confirmed in two patients, one of them died. EEG showed focal epileptiform activity in four participants. The one-year prospective observation showed a favorable outcome in five patients who were without seizures, had normal EEG, and three were without treatment. Seizure frequency increase or seizure recurrence was typically observed for a short period of time in the epilepsy group. EEG was worsened in one patient and treatment changes were needed in five participants. In conclusion, our study results provide evidence about the progress and possible relationshipbetweennew-onset seizures and seizure worsening with COVID-19 infection.

Seizure Duration and Electroconvulsive Therapy in Major Depressive Disorder

Electroconvulsive therapy (ECT), wherein a generalized epileptic seizure is induced, is a treatment for major depressive disorder (MDD). Currently, it is unclear whether there is an association between seizure length and treatment outcome. To explore the association between seizure duration, potential confounding variables, and ECT treatment outcome. This population-based cohort study obtained data from the Swedish National Quality Register for ECT. Patients treated for unipolar MDD with unilateral electrode placement between January 1, 2012, and December 31, 2019, were included. The electroencephalographic (EEG) seizure duration from the first ECT treatment session for each patient was used for analysis. Data analyses were performed between March 2021 and May 2024. The primary outcome was remission, defined as a cutoff score of less than 10 points on the self-assessment version of the Montgomery-Åsberg Depression Rating Scale within 1 week after ECT. Multivariate logistic regression analysis was performed to calculate odds ratios (ORs) between different seizure duration groups. Furthermore, the associations between concomitant use of pharmacological treatments, seizure duration, and remission rate were explored. Among the 6998 patients included, 4229 (60.4%) were female and the mean (SD) age was 55.2 (18.6) years. Overall, 2749 patients (39.3%) achieved remission after ECT. Patients with EEG seizure duration of 60 to 69 seconds had the highest remission rates compared with patients with seizure duration of less than 20 seconds (OR, 2.17; 95% CI, 1.63-2.88; P < .001). Anticonvulsant medications were associated with shorter seizure duration (eg, lamotrigine: β coefficient [SE], -6.02 [1.08]; P < .001) and lower remission rates (eg, lamotrigine: adjusted OR, 0.67; 95% CI, 0.53-0.84; P < .001). This study found an association between seizure length and remission from MDD. Use of anticonvulsant medication during ECT was associated with shorter seizure duration and lower remission rates after ECT.

Portability rules detection by Epilepsy Tracking META-Set Analysis

Epilepsy is a severe and common neurological disease that causes sudden and irregular seizures, necessitating patient-specific detection models for effective management. The proposed methodology, Epilepsy Tracking META-Set Analysis, establishes portability rules that identify similar patients, enabling the transfer of these detection models from one patient to another. Main issue is to identify clusters of patients analyzing a set of meta-features of each patient in terms of clinical descriptors, performance metrics of a machine learning model for seizure detection, and data complexity measures. The investigation of complexity measures represents a novelty in such a medical field, allowing to compare patients and to support automated seizure detection methods. The proposed methodology is validated using the well-known Epileptic Seizure EEG Database from the Epilepsy Center of the University Hospital of Freiburg and demonstrates promising results in transferring detection models to new cases.

The Effect of Remimazolam on Seizure Profile, Hemodynamics, and Recovery in Patients With Electroconvulsive Therapy Comparison With Propofol and Etomidate: A Retrospective Study.

To compare seizure-related, hemodynamic, and recovery outcomes when using remimazolam for ECT with those of other anesthetics, specifically propofol and etomidate. A total of 49 patients who underwent 405 ECT treatment sessions under general anesthesia were retrospectively analyzed. Remimazolam, propofol, and etomidate were used for 93, 138, and 174 ECT sessions, respectively. The primary outcome was durations of motor and electroencephalogram (EEG) seizure activity, whereas secondary outcomes included hemodynamics (ie, mean arterial pressure [MAP] and heart rate [HR] at various time points from induction to postanesthesia care unit [PACU] discharge), antihypertensive drugs administration after electrical stimulus, and recovery profiles (ie, length of PACU stay and incidence of postictal confusion). Durations of motor and EEG seizures were shorter for remimazolam than etomidate (motor, P < 0.001; EEG, P = 0.003) but similar compared with propofol (motor, P = 0.191; EEG, P = 0.850). During seizure, remimazolam showed a comparable MAP and HR to etomidate (MAP: P = 0.806; HR: P = 0.116). The antihypertensive drug use was lowest for remimazolam (6.8%), followed by propofol (35.6%) and etomidate (65.6%), and the mean length of PACU stay was comparable for remimazolam (19.7 min), propofol (22.8 min), and etomidate (24.5 min). The occurrence of postictal confusion did not differ among the 3 agents (P > 0.050). Remimazolam is a promising anesthetic option for ECT because of its comparable seizure profiles, stable hemodynamics, and comparable PACU stay when compared with propofol and etomidate without additional adverse events.

Clinical and genetic analysis of a child with West syndrome due to a de novo variant of NEXMIF gene

To investigate the clinical features and genetic variant of a child with West syndrome due to a variant of NEXMIF gene. A child who was admitted to the First Medical Center of Chinese PLA General Hospital in March 2021 was selected as the study subject. Clinical data of the patient was collected. The child and his parents were subjected to whole exome sequencing. Candidate variant was verified by Sanger sequencing and pathogenicity analysis. The child, a 4-month-old boy, had presented with spastic seizures with no obvious cause. Abnormal EEG, severe hypsarrhythmia, and multiple spastic seizures were discovered. Cranial MRI revealed widening of the extracerebral space at the top of the frontal lobe. Physical examination revealed that the child could not hold his head up, and could not respond to sounds or follow objects with his eyes. He also has microcephaly, with height < 1 s. The child was diagnosed with West syndrome at a local hospital, and was given prednisone orally for 3 months, with seizures under control. Topiramate tablets were taken orally for maintenance treatment, and he has been seizure-free for 7 months. DNA sequencing revealed that he has harbored a de novo nonsense variant of c.982_c.983delTT (p.L328Dfs*23) in the NEXMIF gene. For children with West syndrome with severe developmental delay or even regression as the first symptoms, uncontrollable seizures and abnormal facial appearance, mutations of the NEXMIF gene should be suspected, and genetic testing can facilitate early diagnosis and treatment.

Automatic detection of epilepsy from EEGs using a temporal convolutional network with a self-attention layer

BackgroundOver 60% of epilepsy patients globally are children, whose early diagnosis and treatment are critical for their development and can substantially reduce the disease’s burden on both families and society. Numerous algorithms for automated epilepsy detection from EEGs have been proposed. Yet, the occurrence of epileptic seizures during an EEG exam cannot always be guaranteed in clinical practice. Models that exclusively use seizure EEGs for detection risk artificially enhanced performance metrics. Therefore, there is a pressing need for a universally applicable model that can perform automatic epilepsy detection in a variety of complex real-world scenarios.MethodTo address this problem, we have devised a novel technique employing a temporal convolutional neural network with self-attention (TCN-SA). Our model comprises two primary components: a TCN for extracting time-variant features from EEG signals, followed by a self-attention (SA) layer that assigns importance to these features. By focusing on key features, our model achieves heightened classification accuracy for epilepsy detection.ResultsThe efficacy of our model was validated on a pediatric epilepsy dataset we collected and on the Bonn dataset, attaining accuracies of 95.50% on our dataset, and 97.37% (A v. E), and 93.50% (B vs E), respectively. When compared with other deep learning architectures (temporal convolutional neural network, self-attention network, and standardized convolutional neural network) using the same datasets, our TCN-SA model demonstrated superior performance in the automated detection of epilepsy.ConclusionThe proven effectiveness of the TCN-SA approach substantiates its potential as a valuable tool for the automated detection of epilepsy, offering significant benefits in diverse and complex real-world clinical settings.

Predictors of seizure detection and EEG clinical impact in an italian tertiary emergency department.

Epileptic seizures pose challenges in emergency departments(ED), affecting up to 10% of admitted patients. This study aimed to assess emergency electroencephalogram (EmEEG) utilization, identifying factors predicting seizure detection and its influence on clinical decisions. A retrospective review of 1135 EmEEGs on 1017 patients at a tertiary teaching hospital between June 2022 and June 2023 was conducted. Data included demographics, medical history, EmEEG indications, neuroimaging findings, and clinical outcomes. Statistical analyses utilized Fisher's exact tests and logistic regression models. EmEEG detected status epilepticus-related seizures in 5.40% of cases, seizures without status epilepticus in 3.05%, and status epilepticus without discrete seizures in 3.74%. Epileptiform abnormalities were noted in 22.12% of EmEEGs. EmEEG influenced initial diagnoses (21.24%), antiseizure medication changes (20.85%), and discharge decisions (39.04%). Predictors for seizures/status epilepticus included previous neurosurgery, seizures in the ED, and cognitive/behavioral impairment (p < 0.001). EmEEG significantly altered initial diagnoses based on witnessed seizures, involuntary movements, epileptiform abnormalities, and 1-2Hz generalized periodic discharges (p < 0.001). Changes in antiseizure medications correlated with seizure occurrence, neuroimaging results, epileptiform abnormalities, and EEG background slowing (p < 0.001). Factors influencing discharge decisions included previous neurosurgery, consciousness impairment, acute neuroimaging pathology, EEG focal slowing, and EEG background slowing (p < 0.001). The study clarifies EmEEG's role in modifying initial diagnoses, treatment approaches, and discharge decisions. The study provides insights into the nuanced impact of EmEEG in different clinical scenarios, offering valuable guidance for clinicians in selecting patients for EmEEG, particularly in conditions of limited EEG availability.

The Role of Routine Electroencephalography in the Diagnosis of Seizures in Medical Intensive Care Units.

Seizures should be diagnosed and treated to ensure optimal health outcomes in critically ill patients admitted in the medical intensive care unit (MICU). Continuous electroencephalography is still infrequently used in the MICU. We investigated the effectiveness of routine EEG (rEEG) in detecting seizures in the MICU. A total of 560 patients admitted to the MICU between October 2018 and March 2023 and who underwent rEEG were reviewed. Seizure-related rEEG constituted 47% of all rEEG studies. Totally, 39% of the patients experienced clinical seizures during hospitalization; among them, 48% experienced the seizure, and 13% experienced their first seizure after undergoing an rEEG study. Seventy-seven percent of the patients had unfavorable short-term outcomes. Patients with cardiovascular diseases were the most likely to have the suppression/burst suppression (SBS) EEG pattern and the highest mortality rate. The rhythmic and periodic patterns (RPPs) and electrographic seizure (ESz) EEG pattern were associated with seizures within 24 h after rEEG, which was also related to unfavorable outcomes. Significant predictors of death were age > 59 years, the male gender, the presence of cardiovascular disease, a Glasgow Coma Scale score ≤ 5, and the SBS EEG pattern, with a predictive performance of 0.737 for death. rEEG can help identify patients at higher risk of seizures. We recommend repeated rEEG in patients with ESz or RPP EEG patterns to enable a more effective monitoring of seizure activities.