Routine EEG Research Articles

Focal, generalised epilepsy or both?

A 29-year-old woman presented with a witnessed convulsion, with semiology consistent with a focal-to-bilateral tonic-clonic seizure. Routine EEG supported a syndromic diagnosis of idiopathic generalised epilepsy with photosensitivity. We discuss the clinical utility of seizure semiology, highlighting the caveat that over-reliance or sole reliance on the ictal semiology may result in an erroneous diagnosis of focal epilepsy in someone with a generalised epilepsy.

EEG-Derived Markers to Improve Prognostic Evaluation of Disorders of Consciousness.

Disorders of consciousness (DoC) are characterized by alteration in arousal and/or awareness commonly caused by severe brain injury. There exists a consensus on adopting advanced neuroimaging and electrophysiological procedures to improve diagnosis/prognosis of DoC patients. Currently, these procedures are prevalently applied in a research-oriented context and their translation into clinical practice is yet to come. The aim of the study consisted in the identification of measures derived from routinary electroencephalography (EEG) able to support clinicians in the prediction of DoC patients' outcome. In the present study, a routine EEG was recorded during rest from a sample of 58 DoC patients clinically diagnosed as Unresponsive Wakefulness State (UWS) and Minimally Conscious State (MCS) and followed-up for 3 months. EEG-based features characterizing brain activity in terms of spectral content and resting state networks organization were used in a predictive machine learning model to i) identify which were the most promising features in predicting patients' exit from the DoC, regardless of the clinical diagnosis and ii) verify whether such features would have been the same best discriminating UWS from MCS or specific of the outcome prediction. A predictive machine learning model was built on EEG features related to spectral content and resting state networks which returned up to 85% of performance accuracy in outcome prediction and 76% in DoC state recognition (UWS vs MCS). We provided preliminary evidence for the exploitation of a routine EEG to improve the clinical management of non-communicative patients to be confirmed in a larger DoC population.

Clinical and Radiological Parameters Affecting the Yield of Routine Electroencephalography in Various Indications.

To highlight the significance of various clinical and radiological parameters in association with specific electroencephalographic (EEG) patterns in order to prioritize EEG referrals. This retrospective, cross-sectional study was conducted in the neurology department of King Fahad University Hospital, Alkhobar, and involved a review and analysis of EEG and medical records pertaining to 604 patients referred for routine EEG. The data were analyzed using SPSS version 22. An association between various parameters and EEG yield was established. Factors associated with the yield of abnormal EEG patterns were diverse, like generalized tonic-clonic seizures (GTCs) (P =.05), status epilepticus (SE) (P =.05), altered level of consciousness (ALC) (P =.00), abnormal movement (P =.00), cardiac arrest (P =.00), prior history of epilepsy (P =.04), chronic renal disease (CRD) (P =.03), abnormal neurological exam (P =.00), and cortical lesions on brain imaging (P =.00). Among the abnormal EEG patterns, epileptiform activity (EA) in EEG was associated with focal seizures (P =.03), GTCs (P =.00), falls (P =.05), cardiac arrest (P =.00), a history of epilepsy (P =.00), and hypoxic ischemic injury (P =.03). Encephalopathy in EEG was also associated with focal sz (P =.02), GTCs (P =.00), SE (P =.01), ALC (P =.00), cardiac arrest (P =.00), history of stroke (P =.01), and epilepsy (P =.00). Among the studied parameters, patient level of consciousness, neurological exam findings, and neuroimaging findings, with some discrepancies, were found to be the most consistent in predicting the EEG yield. The study demonstrated the value of a proper neurological exam and careful selection of patients to gain the optimum benefit from the routine EEG.

2023 IFCN & ILAE minimum recording standards for routine and sleep EEG. Applicability assessment in Russia

In 2023, the International Federation of Clinical Neurophysiology (IFCN) and the International League Against Epilepsy (ILAE) published the most up-to-date recommendations for conducting EEG examinations. The document sets out minimum standards necessary to improve the accuracy, efficiency, and reliability of routine and sleep EEG recordings. At the same time, it is indicated that based on availability specific rules and methods for conducting examinations should be proposed by medical organizations or departments independently. We present a selective translation of such recommendations and an assessment of their compliance with contemporary real-world opportunities in the Russian Federation. The possible “growth points” for the EEG technique in Russia are highlighted as well.

Role of EEG spindle-like activity in post cardiac arrest prognostication

AimEEG is considered in guidelines for poor outcome prognostication in comatose patients after cardiac arrest (CA), but elements related to favorable prognosis have also been increasingly described. While spindle EEG activity is known to herald good outcome in critically ill patients, its occurrence in CA has received limited attention, essentially in pediatric cohorts. We postulated that this feature is related to favorable outcome in adults. MethodsRetrospective assessment of comatose adults following CA in a prospective institutional registry (09.2021–09.2023). Spindle-like activity, noted prospectively on early (12–36 h) and late (36–72 h) routine EEGs, was tested using 2x2 tables and comparisons of proportions for the likelihood of favorable outcome (CPC 1–2 at 3 months), including combinations with existing benign EEG descriptions (Westhall: no malignant or highly malignant features; modified: also allowing background discontinuity, low voltage, inverse development). Spindles were correlated with peak serum neuron-specific enolase (NSE) at 24–48 h as a marker of neuronal damage. ResultsAmong 276 patients, spindle-like activity was observed in 66 (23.9 %) of them, more often in early EEGs. While, in isolation, this feature detected within 72 h showed high specificity for CPC 1–2 (82.2 %) and low sensitivity (36.8 %), its addition significantly enhanced sensitivity of modified benign EEG (from 90.5 % to 95.8 %; p < 0.001; specificity at 54.4 %). Patients with spindle-like activity had significantly lower NSE (median 25.7µg/l, interquartile range 16.1–24.4, vs. 39.4 µg/l, interquartile range 21.1–95.1; p < 0.001). ConclusionSpindle-like EEG activity may orient on prognostication of favorable outcome in adult post CA patients, and correlates with lower neuronal damage.

Characteristics of overnight video-EEG monitoring in infantile epileptic spasms syndrome at 2-week follow-up.

To determine the optimal duration of electroencephalography (EEG) recording to detect epileptic spasms (ES) based on inpatient overnight video-EEG monitoring in patients with infantile epileptic spasms syndrome (IESS) at the 2-week follow-up. Patients with IESS and overnight EEG monitoring between January 2020 and June 2022 were retrospectively reviewed. Time-to-ES, time-to-sleep and time-to-epileptic encephalopathy (EE) per the Burden of Amplitudes and Epileptiform Discharges (BASED 2021) score. BASED 2021 score were reported. ES and sleep detection sensitivity were calculated with respect to monitoring time. Etiology, treatment, and EEG features were assessed for strength of association with continued ES. Time-to-event analysis was performed with the first ES as the event of interest. Of 90 patients, 39 (43%) continued to have ES; 78.6% with EE continued to have ES, whereas only 27.4% without EE had ES (odds ratio [OR] 12.05). Structural etiologies were also associated with continued ES (OR 5.24). ES detection was 35.9%, 76.9%, and 84.6% at 1, 4, and 6 h, respectively, with corresponding negative likelihood ratios (NLRs) of .64, .23, and .15. ES detection reached >90% and >95% at 14 and 19 h, respectively. Sleep detection was 52.2%, 84.4%, and 95.6% at 1, 4, and 6 h, respectively, and captured in all patients by 11 h. EE was observed by 6 h for all associated patients. Typical routine EEG durations (<1 h) were not sufficient to detect ES, EE, or sleep in patients with IESS at the 2-week follow-up. Four hour outpatient EEG will capture ES in 77% and sleep in 84% of the patients. EE, if present, was shortly after sleep onset. Additional monitoring of up to 19 h was needed to capture >95% of patients with ES. Although EE was strongly associated with continued ES, 27.4% of patients without EE demonstrated ES. This study will help guide adequate duration of EEG monitoring at the 2-week follow-up for patients with IESS.

Neuronal current imaging of epileptic activity: An MRI study in patients with a first unprovoked epileptic seizure.

This study evaluates the performance of the novel MRI sequence stimulus-induced rotary saturation (SIRS) to map responses to interictal epileptic activity in the human cortex. Spin-lock pulses have been applied to indirectly detect neuronal activity through magnetic field perturbations. Following initial reports about the feasibility of the method in humans and animals with epilepsy, we aimed to investigate the diagnostic yield of spin-lock MR pulses in comparison with scalp-EEG in first seizure patients. We employed a novel method for measurements of neuronal activity through the detection of a resonant oscillating field, stimulus-induced rotary saturation contrast (SIRS) at spin-lock frequencies of 120 and 240 Hz acquired at a single 3T MRI system. Within a prospective observational study, we conducted SIRS experiments in 55 patients within 7 days after a suspected first unprovoked epileptic seizure and 61 healthy control subjects. In this study, we report on the analysis of data from a single 3T MRI system, encompassing 35 first seizure patients and 31 controls. The SIRS method was applicable in all patients and healthy controls at frequencies of 120 and 240 Hz. We did not observe any significant age- or sex-related differences. Specificity of SIRS at 120 Hz was 90.3% and 93.5% at 240 Hz. Sensitivity was 17.1% at 120 Hz and 40.0% at 240 Hz. SIRS targets neuronal oscillating magnetic fields in patients with epilepsy. The coupling of presaturated spins to epilepsy-related magnetic field perturbations may serve as a-at this stage experimental-diagnostic test in first seizure patients to complement EEG findings as a standard screening test. Routine diagnostic tests carry several limitations when applied after a suspected first seizure. SIRS is a noninvasive MRI method to enable time-sensitive diagnosis of image correlates of epileptic activity with increased sensitivity compared to routine EEG.

Epileptiform Discharges Recorded as Monopoles and Dipoles in the EEG: A Practical Approach to Differentiate Tangential and Radial Generators Using Electrode Position Versus Voltage Graphs.

Differentiating dipoles (tangential generators) from monopoles (radial generators) in routine EEG reading can be difficult. The polarity of sharp waves seen on surface EEG will change depending on the generator being located at the wall of the sulcus versus the crown of a gyrus. In this article, the authors introduce visual rules that may be used to determine polarity and estimate the localization of potentials during analysis of the EEG. They also review a practical approach to differentiate monopoles (radial generators) from dipoles (tangential dipoles) in the surface EEG using "electrode position versus voltage graphs." Finally, the authors illustrate examples of dipoles and monopoles with focal spikes located in the following locations: (1) bipolar spikes located in the anterior bank of the central sulcus, (2) bipolar spikes located in the posterior bank of the central sulcus, (3) monopolar spikes located in the crown of the precentral gyrus, (4) bipolar spikes with a vertically oriented dipole originated within the temporal (inferior) bank of the Sylvian fissure, and (5) monopolar spikes located in the convexity of a temporal gyrus. In summary, this article discusses electrographic features of spikes localized in various fissures and gyri and provides practical rules that permit the identification and location of dipoles and monopoles in standard scalp EEG recordings.

Continuous Electroencephalographic Monitoring in Adult ICU Challenges and Potential Solutions: A Scoping Review

Background: Continuous electroencephalographic (cEEG) monitoring is continuous monitoring of brain activity that is often used in the intensive care unit (ICU). Recently, the usage of cEEG has grown in many institutions as it detects non-convulsive seizures better than routine EEG (rEEG). However, due to the aggressive environment of ICU, the application and the prolonged recording is challenging. The objectives of this scoping review are to evaluate the common challenges faced during cEEG in adult ICU and proper solutions for optimal implementation. Methods: A scoping review was conducted using Arksey and O’Malley framework. The included articles contain “continuous EEG in ICU settings” in their titles, written in English, and published between 2010 and 2022. That was by searching the databases: PubMed, Google Scholar, and Summon. Results: 14 articles were included as they meet the criteria of this review. (28.57 %) of the included studies mentioned the challenges regarding staff, (42.85 %) addressed the challenges of electrode application and the alternative techniques in ICU, and (42.85%) discussed the difficulties in interpretation and duration of the recording. Conclusion: Continuous EEG is increasingly recognized as valuable mean of monitoring cerebral function, but it is faced with numerous challenges: the difficult environment of ICU and the type of critical patient admitted requiring the optimal electrode application and maintenance, minimizing artifacts and adequate duration of recording to detect abnormalities, and sufficiently trained personnel including ICU staff, technologist and neurophysiologist to provide the optimal patient care as it is the main goal.

Generalizability of electroencephalographic interpretation using artificial intelligence: An external validation study.

The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE-AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings. We assessed the diagnostic accuracy of a "fixed-and-frozen" AI model, using an independent dataset and external gold standard, and benchmarked it against three experts blinded to all other data. The dataset comprised 50% normal and 50% abnormal routine EEGs, equally distributed among the four major classes of EEG abnormalities (focal epileptiform, generalized epileptiform, focal nonepileptiform, and diffuse nonepileptiform). To assess diagnostic accuracy, we computed sensitivity, specificity, and accuracy of the AI model and the experts against the external gold standard. We analyzed EEGs from 104 patients (64 females, median age = 38.6 [range = 16-91] years). SCORE-AI performed equally well compared to the experts, with an overall accuracy of 92% (95% confidence interval [CI] = 90%-94%) versus 94% (95% CI = 92%-96%). There was no significant difference between SCORE-AI and the experts for any metric or category. SCORE-AI performed well independently of the vigilance state (false classification during awake: 5/41 [12.2%], false classification during sleep: 2/11 [18.2%]; p = .63) and normal variants (false classification in presence of normal variants: 4/14 [28.6%], false classification in absence of normal variants: 3/38 [7.9%]; p = .07). SCORE-AI achieved diagnostic performance equal to human experts in an EEG dataset independent of the development dataset, in a geographically distinct patient population, recorded with different equipment and technical settings than the development dataset.

Low-cost portable EEG device for bridging the diagnostic gap in resource-limited areas.

To develop a low-cost portable EEG system, with real-time automated guidance, for application in resource-limited areas, to bridge the diagnostic and treatment gap. We designed, developed, and produced a low-cost system, which records 27-channel EEG plus ECG and streams the signals to an application on a smartphone, which assesses the quality of the signal and gives feedback to the inexperienced user to correct the poor quality signals and reduce artifacts. The application guides the inexperienced user through the steps of recording routine clinical EEG. The recordings are uploaded to a secure cloud, for telemedicine applications. We recruited 10 participants without prior experience with recording EEG. After a brief training session, the participants recorded EEGs following the guidance from the app, without help from human experts. We assessed the usability of the system, with the System Usability Scale (SUS), and we evaluated the impedances and signal quality of the test EEGs recorded by the inexperienced users. All users completed the test EEG recordings, and none of the recordings were of insufficient quality for clinical use. The SUS score was 90.3 ± 6.8, and the average quality rating was 8.04. The low-cost, portable EEG system, which uses automated, real-time guidance for conducting EEG recordings, enables inexperienced users to record EEGs of a quality sufficient for clinical applications. This system has the potential to provide EEG services in resource-limited areas, and thereby help bridge the diagnostic and therapeutic gap.

Assessing the Yield of Reduced Duration-EEG Recordings in Children: A Cross-Sectional Study.

Introduction An EEG is an important tool in the diagnosis of neurological diseases. Performing an EEG on children can be challenging due to their tendency to not cooperate for the recommended duration. We aim to optimize the duration of EEG recording in children by finding the optimal duration of recording. Materials and methods A single-center prospective observational study was done after appropriate ethical clearance. Children aged 0-14 were recruited and examined, and the recommended EEG was done. Data were collected and analyzed. Results Of the 112 EEGs analyzed, 29 EEGs were normal, i.e., no diagnostic anomaly was noticed. In the remaining 83 EEGs, if the duration of the EEG was reduced to 20 minutes, it resulted in missing the diagnostic anomaly in 20 cases (24.1%; 95% CI: 11.2%-26.2%). Reducing the duration of the EEG recording to 10 minutes resulted in missing 63 of the diagnostic anomalies (75.9%; 95% CI: 46.6%-65.6%). Of the 86 drug-inducedEEGs, 22 were normal (25.6%; 95% CI: 16.8%-36.1%). Of the 24 routine EEGs, seven were normal (29.2%; 95% CI: 12.6%-51.1%). Of the two sleep-deprived EEGs, neither was normal (0.0%; 95% CI: 0.0%-84.1%). Conclusion In our study, we observed that optimization of the duration ofEEG recording can be done to 20 minutes in all populations. We also observed that if we find a diagnostic abnormality early during EEG recording, then continuation of the EEG may not be necessary to make a valid report. Having said so, having a negative EEG may not necessarily rule out a diagnosis. We did not find the superiority of any of the EEG protocols over others, as their yield was comparable.

Data-driven retrieval of population-level EEG features and their role in neurodegenerative diseases.

Electrophysiologic disturbances due to neurodegenerative disorders such as Alzheimer's disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional measure of disease severity. Traditional quantitative methods of EEG analysis often require an a-priori selection of clinically meaningful EEG features and are susceptible to bias, limiting the clinical utility of routine EEGs in the diagnosis and management of neurodegenerative disorders. We present a data-driven tensor decomposition approach to extract the top 6 spectral and spatial features representing commonly known sources of EEG activity during eyes-closed wakefulness. As part of their neurologic evaluation at Mayo Clinic, 11 001 patients underwent 12 176 routine, standard 10-20 scalp EEG studies. From these raw EEGs, we developed an algorithm based on posterior alpha activity and eye movement to automatically select awake-eyes-closed epochs and estimated average spectral power density (SPD) between 1 and 45 Hz for each channel. We then created a three-dimensional (3D) tensor (record × channel × frequency) and applied a canonical polyadic decomposition to extract the top six factors. We further identified an independent cohort of patients meeting consensus criteria for mild cognitive impairment (30) or dementia (39) due to Alzheimer's disease and dementia with Lewy Bodies (31) and similarly aged cognitively normal controls (36). We evaluated the ability of the six factors in differentiating these subgroups using a Naïve Bayes classification approach and assessed for linear associations between factor loadings and Kokmen short test of mental status scores, fluorodeoxyglucose (FDG) PET uptake ratios and CSF Alzheimer's Disease biomarker measures. Factors represented biologically meaningful brain activities including posterior alpha rhythm, anterior delta/theta rhythms and centroparietal beta, which correlated with patient age and EEG dysrhythmia grade. These factors were also able to distinguish patients from controls with a moderate to high degree of accuracy (Area Under the Curve (AUC) 0.59-0.91) and Alzheimer's disease dementia from dementia with Lewy Bodies (AUC 0.61). Furthermore, relevant EEG features correlated with cognitive test performance, PET metabolism and CSF AB42 measures in the Alzheimer's subgroup. This study demonstrates that data-driven approaches can extract biologically meaningful features from population-level clinical EEGs without artefact rejection or a-priori selection of channels or frequency bands. With continued development, such data-driven methods may improve the clinical utility of EEG in memory care by assisting in early identification of mild cognitive impairment and differentiating between different neurodegenerative causes of cognitive impairment.

Does Hyperventilation Increase the Diagnostic Yield of the Routine Electroencephalogram: A Retrospective Analysis of Adult and Pediatric Cohorts.

While hyperventilation (HV) increases the diagnostic yield of EEG in children, there is conflicting evidence to support its application in adults. For the first time in history, a large cohort of patients has undergone EEGs without HV during the COVID-19 pandemic. Utilizing this opportunity, we sought to investigate whether HV increases the diagnostic yield of EEG in children compared with adults. Patients aged six years and above who had routine EEGs at Monash Health between January 2019 and December 2020 were studied. The cohort was divided into two, pediatric (younger than 18 years) and adult (18 years or older). Epileptiform abnormalities (ictal and interictal) were the outcomes investigated. The effect of HV was examined with logistic regression to determine odds ratios with 95% confidence intervals. In total, we studied 3,273 patients (pediatric = 830, adult = 2,443). In the pediatric cohort, HV significantly increased the diagnostic yield of absence seizures (p = 0.01, odds ratios 2.44, 95% confidence intervals 1.21-4.93). In adults, HV did not increase the yield of absence seizures (p = 0.34, odds ratios 0.36, 95% confidence intervals 0.05-2.88). Interictal epileptiform discharges during HV were significantly more frequent in children compared with adults (p < 0.001, odds ratios 3.81, 95% confidence intervals 2.51-5.77). Hyperventilation is useful to increase the yield of interictal epileptiform discharges and absence seizures in pediatric patients but not in adults. Hence, routine EEG may be recorded in adults without HV when it is unsafe to perform.

The First 100 Seconds of Sleep of rEEGs Can Be a Reliable Scoring Method for D/EE-SWAS.

Developmental/epileptic encephalopathy with spike wave activation with sleep, formerly known as electrical status epilepticus in sleep, is an electrographic pattern in which the interictal epileptiform activity is augmented by transition to sleep. Recent studies demonstrate the utility of the first 100 seconds of sleep of long-term monitoring (LTM) as a scoring method for electrical status epilepticus in sleep. Our aim was to measure the reliability of the spike-wave index (SWI) of the first 100 seconds of sleep of routine EEG (rEEG) as a tool for diagnosis of developmental/epileptic encephalopathy with spike wave activation with sleep. Approximately three hundred forty LTMs were reviewed, and 25 studies from 25 unique patients had comparable rEEGs. Two neurophysiologists calculated the SWI of the first 100 seconds of spontaneous stage II non-random eye movement sleep, the first 5-minute bin of sleep, and three separate 5-minute bins throughout sleep in LTM. This was compared to the SWI of the first 100 seconds of sleep in rEEG. Agreement was analyzed using Lin's concordance correlation coefficient (CCC). Using 50% as a diagnostic cut-off, we observed moderate agreement between the SWI of the first 100 seconds of sleep of rEEG and three bin LTM (CCC = 0.94, 95% CI: 0.88-0.97). Agreement was slightly higher for the comparison to first bin LTM SWI (CCC = 0.96, 95% CI: 0.92-0.98) and first 100 seconds LTM SWI (CCC = 0.96, 95% CI: 0.92-0.98). This study demonstrates the first 100 seconds of sleep of rEEG technique as a time efficient diagnostic tool for patients with concern for developmental/epileptic encephalopathy with spike wave activation with sleep.

Detection of short-lasting and ictal spike-and-wave discharges in around-the-ears EEG recordings in children with absence epilepsy

PurposeLong-term ambulatory EEG recordings can improve the monitoring of absence epilepsy in children, but signal quality and increased review workload are a concern. We evaluated the feasibility of around-the-ears EEG arrays (cEEGrids) to capture 3-Hz short-lasting and ictal spike-and-wave discharges and assessed the performance of automated detection software in cEEGrids data. We compared patterns of bilateral synchronisation between short-lasting and ictal spike-and-wave discharges. MethodsWe recruited children with suspected generalised epilepsy undergoing routine video-EEG monitoring and performed simultaneous cEEGrids recordings. We used ASSYST software to detect short-lasting 3-Hz spike-and-wave discharges (1–3 s) and ictal spike-and-wave discharges in the cEEGrids data. We assessed data quality and sensitivity of cEEGrids for spike-and-wave discharges in routine EEG. We determined the sensitivity and false detection rate for automated spike-and-wave discharge detection in cEEGrids data. We compared bihemispheric synchrony across the onset of short-lasting and ictal spike-and-wave discharges using the mean phase coherence in the 2–4 Hz frequency band. ResultsWe included nine children with absence epilepsy (median age = 11 y, range 8–15 y, nine females) and recorded 4 h and 27 min of cEEGrids data. The recordings from seven participants were suitable for quantitative analysis, containing 82 spike-and-wave discharges. The cEEGrids captured 58 % of all spike-and-wave discharges (median individual sensitivity: 100 %, range: 47–100 %). ASSYST detected 82 % of all spike-and-wave discharges (median: 100 %, range: 41–100 %) with a false detection rate of 48/h (median: 6/h, range: 0–154/h). The mean phase coherence significantly increased during short-lasting and ictal spike-and-wave discharges in the 500-ms pre-onset to 1-s post-onset interval. ConclusionscEEGrids are of variable quality for monitoring spike-and-wave discharges in children with absence epilepsy. ASSYST could facilitate the detection of short-lasting and ictal spike-and-wave discharges with clear periodic structures but with low specificity. A similar course of bihemispheric synchrony between short-lasting and ictal spike-and-wave discharges indicates that cortico-thalamic driving may be relevant for both types of spike-and-wave discharges.

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.

The influence of wakefulness fluctuations on brain networks involved in centrotemporal spike occurrence

ObjectiveDrowsiness has been implicated in the modulation of centro-temporal spikes (CTS) in Self-limited epilepsy with Centro-Temporal Spikes (SeLECTS). Here, we explore this relationship and whether fluctuations in wakefulness influence the brain networks involved in CTS generation. MethodsFunctional MRI (fMRI) and electroencephalography (EEG) was simultaneously acquired in 25 SeLECTS. A multispectral EEG index quantified drowsiness (‘EWI’: EEG Wakefulness Index). EEG (Pearson Correlation, Cross Correlation, Trend Estimation, Granger Causality) and fMRI (PPI: psychophysiological interactions) analytic approaches were adopted to explore respectively: (a) the relationship between EWI and changes in CTS frequency and (b) the functional connectivity of the networks involved in CTS generation and wakefulness oscillations. EEG analyses were repeated on a sample of routine EEG from the same patient’s cohort. ResultsNo correlation was found between EWI fluctuations and CTS density during the EEG-fMRI recordings, while they showed an anticorrelated trend when drowsiness was followed by proper sleep in routine EEG traces. According to PPI findings, EWI fluctuations modulate the connectivity between the brain networks engaged by CTS and the left frontal operculum. ConclusionsWhile CTS frequency per se seems unrelated to drowsiness, wakefulness oscillations modulate the connectivity between CTS generators and key regions of the language circuitry, a cognitive function often impaired in SeLECTS. SignificanceThis work advances our understanding of (a) interaction between CTS occurrence and vigilance fluctuations and (b) possible mechanisms responsible for language disruption in SeLECTS.

Ictal Cotard delusion as a manifestation of nonconvulsive status epilepticus: A case report and commentary.

Psychosis of epileptic origin can present a wide range of cognitive and affective symptoms and is often underrecognized. Usually occurring in the inter- and postictal phase, epileptic psychosis is mostly related to temporal lobe epilepsy. Here, we describe the clinical presentation and diagnostic workup including routine EEG recording and brain MRI of a 63-year-old woman expressing isolated nihilistic delusions comprising belief of being dead and denial of self-existence. EEG showed an ictal pattern fulfilling the Salzburg criteria of nonconvulsive status epilepticus and brain MRI revealed extensive peri-ictal hyperperfusion. Delusional symptoms and EEG abnormalities subsided after acute antiseizure treatment. Our case illustrates how nihilistic delusions can occur as a direct clinical correlate of seizure activity, thereby expanding the spectrum of ictal neuropsychiatric phenomena in temporal lobe epilepsy and highlighting the need to consider an epileptic origin in patients presenting with psychotic symptoms.

Evaluation of Patients Complaining of Staring Spells: Single Center Experience

Objective: This study aimed to analyze the demographic characteristics, spell semiology, and electroencephalographic characteristics of children with a complaint of staring spells and determine the factors that differentiate epileptic and non-epileptic etiology. Material and Methods: Fifty-six patients were included retrospectively between October 1, 2022, and December 1, 2023. The patients’ age, gender, co-morbidities, and other characteristics of the staring spells (duration, frequency, automatism, and presence of post-attack symptoms), access time to the pediatric neurologist, referring unit and access time to the final diagnosis were also recorded. Electroencephalography (EEG) was performed on all patients. Results: Fifty-six patients were divided into two according to epileptic and non-epileptic etiology. Thirty-three patients (59%) were diagnosed with non-epileptic staring spells, 15 (26.7%) were diagnosed with generalized epilepsy, and 8 (14.3%) were diagnosed with focal epilepsy. The non-epileptic group had a longer spell time and spell frequency, the presence of verbal stimulation response, and no post-attack symptoms (p&amp;lt;0.001). The access time to the pediatric neurologist was detected as 5.5 days, and the access time to the final diagnosis was 6.6 days. EEG was diagnostic in 100% of the epileptic group. Most of the patients were referred by pediatricians and family physicians (p&amp;lt;0.001). Conclusion: Identifying the cause of staring spells is crucial for further follow-up. In this study, we emphasized that history and routine EEG are important to determine the etiology. It has been observed that access time to pediatric neurologists and final diagnosis are shorter in our country compared to the literature. It can be concluded that pediatricians and family physicians have a high awareness of staring spells.