Outcomes in Patients With Poststroke Seizures: A Systematic Review and Meta-Analysis.

Importance: Published data about the impact of poststroke seizures (PSSs) on the outcomes of patients with stroke are inconsistent and have not been systematically evaluated, to the authors' knowledge. Objective: To investigate outcomes in people with PSS compared with people without PSS. Data Sources: MEDLINE, Embase, PsycInfo, Cochrane, LILACS, LIPECS, and Web of Science, with years searched from 1951 to January 30, 2023. Study Selection: Observational studies that reported PSS outcomes. Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was used for abstracting data, and the Joanna Briggs Institute tool was used for risk-of-bias assessment. Data were reported as odds ratio (OR) and standardized mean difference (SMD) with a 95% CI using a random-effects meta-analysis. Publication bias was assessed using funnel plots and the Egger test. Outlier and meta-regression analyses were performed to explore the source of heterogeneity. Data were analyzed from November 2022 to January 2023. Main Outcomes and Measures: Measured outcomes were mortality, poor functional outcome (modified Rankin scale [mRS] score 3-6), disability (mean mRS score), recurrent stroke, and dementia at patient follow-up. Results: The search yielded 71 eligible articles, including 20 110 patients with PSS and 1 166 085 patients without PSS. Of the participants with PSS, 1967 (9.8%) had early seizures, and 10 605 (52.7%) had late seizures. The risk of bias was high in 5 studies (7.0%), moderate in 35 (49.3%), and low in 31 (43.7%). PSSs were associated with mortality risk (OR, 2.1; 95% CI, 1.8-2.4), poor functional outcome (OR, 2.2; 95% CI, 1.8-2.8), greater disability (SMD, 0.6; 95% CI, 0.4-0.7), and increased dementia risk (OR, 3.1; 95% CI, 1.3-7.7) compared with patients without PSS. In subgroup analyses, early seizures but not late seizures were associated with mortality (OR, 2.4; 95% CI, 1.9-2.9 vs OR, 1.2; 95% CI, 0.8-2.0) and both ischemic and hemorrhagic stroke subtypes were associated with mortality (OR, 2.2; 95% CI, 1.8-2.7 vs OR, 1.4; 95% CI, 1.0-1.8). In addition, early and late seizures (OR, 2.4; 95% CI, 1.6-3.4 vs OR, 2.7; 95% CI, 1.8-4.1) and stroke subtypes were associated with poor outcomes (OR, 2.6; 95% CI, 1.9-3.7 vs OR, 1.9; 95% CI, 1.0-3.6). Conclusions and Relevance: Results of this systematic review and meta-analysis suggest that PSSs were associated with significantly increased mortality and severe disability in patients with history of stroke. Unraveling these associations is a high clinical and research priority. Trials of interventions to prevent seizures may be warranted.

Quantitative assessment of burst suppression as a predictor of seizure recurrence in refractory status epilepticus.

OBJECTIVE: To determine whether quantitative EEG analysis of burst suppression can predict seizure recurrence in patients with refractory status epilepticus (RSE) being treated with anesthetic doses of continuous IV antiseizure medications (cIVASM). METHODS: Quantitative assessment of burst suppression (including epileptiform discharges [EDs] and evolution) in 31 occasions (from 27 patients), and correlation with seizure recurrence up to 48 hours post sedative wean. RESULTS: Occasions resulting in seizure recurrence (vs. no seizure recurrence) had lower burst (8.4 vs. 10.6 µV) and interburst interval (IBI) (4.2 vs. 4.8 µV) average amplitude, duration (bursts 2.8 vs. 3.6 s: IBIs 3.6 vs. 4.4 s); and burst total power (0.4 vs. 0.7 µV2). Bursts (0.86 vs. 0.60) and IBIs (0.28 vs. 0.07) with EDs, higher number of EDs within bursts (mean 2.1 vs. 1.4) and IBIs (0.6 vs. 0.2), and positive evolution measures all predicted seizure recurrence, although EDs had the greatest adjusted odds ratio on multivariate analysis. CONCLUSIONS: For patients in burst suppression, successful wean of cIVASM was not determined by classical burst suppression measures, but instead how "epileptiform" bursts and IBIs were, as determined by EDs in both bursts and IBIs and surrogates for evolution within bursts. SIGNIFICANCE: If confirmed, these objective measures could be used during clinical care to help determine when to wean cIVASM in patients with RSE.

Seizure forecasting: Where do we stand?

A lot of mileage has been made recently on the long and winding road toward seizure forecasting. Here we briefly review some selected milestones passed along the way, which were discussed at the International Conference for Technology and Analysis of Seizures-ICTALS 2022-convened at the University of Bern, Switzerland. Major impetus was gained recently from wearable and implantable devices that record not only electroencephalography, but also data on motor behavior, acoustic signals, and various signals of the autonomic nervous system. This multimodal monitoring can be performed for ultralong timescales covering months or years. Accordingly, features and metrics extracted from these data now assess seizure dynamics with a greater degree of completeness. Most prominently, this has allowed the confirmation of the long-suspected cyclical nature of interictal epileptiform activity, seizure risk, and seizures. The timescales cover daily, multi-day, and yearly cycles. Progress has also been fueled by approaches originating from the interdisciplinary field of network science. Considering epilepsy as a large-scale network disorder yielded novel perspectives on the pre-ictal dynamics of the evolving epileptic brain. In addition to discrete predictions that a seizure will take place in a specified prediction horizon, the community broadened the scope to probabilistic forecasts of a seizure risk evolving continuously in time. This shift of gears triggered the incorporation of additional metrics to quantify the performance of forecasting algorithms, which should be compared to the chance performance of constrained stochastic null models. An imminent task of utmost importance is to find optimal ways to communicate the output of seizure-forecasting algorithms to patients, caretakers, and clinicians, so that they can have socioeconomic impact and improve patients' well-being.

High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter.

Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial electroencephalography, a technique which has historically provided pioneering advances in our understanding of brain structure-function relationships. We used a consensus boundary mapping approach combining anatomical designations in Duvernoy's Atlas of the Human Brain, a widely recognized textbook of human brain anatomy, with the anatomy of the MNI152 template and the magnetic resonance imaging scans of an epilepsy surgery cohort. The Yale Brain Atlas consists of 690 one-square centimeter parcels based around conserved anatomical features and each with a unique identifier to communicate anatomically unambiguous localization. We report on the methodology we used to create the Atlas along with the findings of a neuroimaging study assessing the accuracy and clinical usefulness of cortical localization using the Atlas. We also share our vision for the Atlas as a tool in the clinical and research neurosciences, where it may facilitate precise localization of data on the cortex, accurate description of anatomical locations, and modern data science approaches using standardized brain regions.

Cellular recovery after prolonged warm ischaemia of the whole body.

After cessation of blood flow or similar ischaemic exposures, deleterious molecular cascades commence in mammalian cells, eventually leading to their death1,2. Yet with targeted interventions, these processes can be mitigated or reversed, even minutes or hours post mortem, as also reported in the isolated porcine brain using BrainEx technology3. To date, translating single-organ interventions to intact, whole-body applications remains hampered by circulatory and multisystem physiological challenges. Here we describe OrganEx, an adaptation of the BrainEx extracorporeal pulsatile-perfusion system and cytoprotective perfusate for porcine whole-body settings. After 1 h of warm ischaemia, OrganEx application preserved tissue integrity, decreased cell death and restored selected molecular and cellular processes across multiple vital organs. Commensurately, single-nucleus transcriptomic analysis revealed organ- and cell-type-specific gene expression patterns that are reflective of specific molecular and cellular repair processes. Our analysis comprises a comprehensive resource of cell-type-specific changes during defined ischaemic intervals and perfusion interventions spanning multiple organs, and it reveals an underappreciated potential for cellular recovery after prolonged whole-body warm ischaemia in a large mammal.

Prognostication of responsive neurostimulation system responsiveness using presurgical magnetoencephalography.

This scientific commentary refers to 'Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy', by Fan et al. (https://doi.org/10.1093/braincomms/fcac104).

Perspectives on Understanding Aberrant Brain Networks in Epilepsy.

Epilepsy is a neurological disorder affecting approximately 70 million people worldwide. It is characterized by seizures that are complex aberrant dynamical events typically treated with drugs and surgery. Unfortunately, not all patients become seizure-free, and there is an opportunity for novel approaches to treat epilepsy using a network view of the brain. The traditional seizure focus theory presumed that seizures originated within a discrete cortical area with subsequent recruitment of adjacent cortices with seizure progression. However, a more recent view challenges this concept, suggesting that epilepsy is a network disease, and both focal and generalized seizures arise from aberrant activity in a distributed network. Changes in the anatomical configuration or widespread neural activities spanning lobes and hemispheres could make the brain more susceptible to seizures. In this perspective paper, we summarize the current state of knowledge, address several important challenges that could further improve our understanding of the human brain in epilepsy, and invite novel studies addressing these challenges.

Oral glutamine supplementation increases seizure severity in a rodent model of mesial temporal lobe epilepsy.

Background: Glutamine synthetase (GS) is the only enzyme known to synthesize significant amounts of glutamine in mammals, and loss of GS in the hippocampus has been implicated in the pathophysiology of medication refractory mesial temporal lobe epilepsy (MTLE). Moreover, loss-of-function mutations of the GS gene causes severe epileptic encephalopathy, and supplementation with glutamine has been shown to normalize EEG and possibly improve the outcome in these patients. Here we examined whether oral glutamine supplementation is an effective treatment for MTLE by assessing the frequency and severity of seizures after supplementation in a translationally relevant model of the disease.Methods: Male Sprague Dawley rats (380-400 g) were allowed to drink unlimited amounts of glutamine in water (3.6% w/v; n = 8) or pure water (n = 8) for several weeks. Ten days after the start of glutamine supplementation, GS was chronically inhibited in the hippocampus to induce MTLE. Continuous video-intracranial EEG was collected for 21 days to determine the frequency and severity of seizures.Results: While there was no change in seizure frequency between the groups, the proportion of convulsive seizures was significantly higher in glutamine treated animals during the first three days of GS inhibition.Conclusion: The results suggest that oral glutamine supplementation transiently increases seizure severity in the initial stages of an epilepsy model, indicating a potential role of the amino acid in seizure propagation and epileptogenesis.

Combining Transcranial Doppler and EEG Data to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage.

BACKGROUND AND OBJECTIVES: Delayed cerebral ischemia (DCI) is the leading complication of subarachnoid hemorrhage (SAH). Because DCI was traditionally thought to be caused by large vessel vasospasm, transcranial Doppler ultrasounds (TCDs) have been the standard of care. Continuous EEG has emerged as a promising complementary monitoring modality and predicts increased DCI risk. Our objective was to determine whether combining EEG and TCD data improves prediction of DCI after SAH. We hypothesize that integrating these diagnostic modalities improves DCI prediction. METHODS: We retrospectively assessed patients with moderate to severe SAH (2011-2015; Fisher 3-4 or Hunt-Hess 4-5) who had both prospective TCD and EEG acquisition during hospitalization. Middle cerebral artery (MCA) peak systolic velocities (PSVs) and the presence or absence of epileptiform abnormalities (EAs), defined as seizures, epileptiform discharges, and rhythmic/periodic activity, were recorded daily. Logistic regressions were used to identify significant covariates of EAs and TCD to predict DCI. Group-based trajectory modeling (GBTM) was used to account for changes over time by identifying distinct group trajectories of MCA PSV and EAs associated with DCI risk. RESULTS: We assessed 107 patients; DCI developed in 56 (51.9%). Univariate predictors of DCI are presence of high-MCA velocity (PSV ≥200 cm/s, sensitivity 27%, specificity 89%) and EAs (sensitivity 66%, specificity 62%) on or before day 3. Two univariate GBTM trajectories of EAs predicted DCI (sensitivity 64%, specificity 62.75%). Logistic regression and GBTM models using both TCD and EEG monitoring performed better. The best logistic regression and GBTM models used both TCD and EEG data, Hunt-Hess score at admission, and aneurysm treatment as predictors of DCI (logistic regression: sensitivity 90%, specificity 70%; GBTM: sensitivity 89%, specificity 67%). DISCUSSION: EEG and TCD biomarkers combined provide the best prediction of DCI. The conjunction of clinical variables with the timing of EAs and high MCA velocities improved model performance. These results suggest that TCD and cEEG are promising complementary monitoring modalities for DCI prediction. Our model has potential to serve as a decision support tool in SAH management. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that combined TCD and EEG monitoring can identify delayed cerebral ischemia after SAH.

Passive localization of the central sulcus during sleep based on intracranial EEG.

We test the performance of a novel operator-independent EEG-based method for passive identification of the central sulcus (CS) and sensorimotor (SM) cortex. We studied seven patients with intractable epilepsy undergoing intracranial EEG (icEEG) monitoring, in whom CS localization was accomplished by standard methods. Our innovative approach takes advantage of intrinsic properties of the primary motor cortex (MC), which exhibits enhanced icEEG band-power and coherence across the CS. For each contact, we computed a composite power, coherence, and entropy values for activity in the high gamma band (80-115) Hz of 6-10 min of NREM sleep. Statistically transformed EEG data values that did not reach a threshold (th) were set to 0. We computed a metric M based on the transformed values and the mean Euclidian distance of each contact from contacts with Z-scores higher than 0. The last step was implemented to accentuate local network activity. The SM cortex exhibited higher EEG-band-power than non-SM cortex (P < 0.0002). There was no significant difference between the motor/premotor and sensory cortices (P < 0.47). CS was localized in all patients with 0.4 < th < 0.6. The primary hand and leg motor areas showed the highest metric values followed by the tongue motor area. Higher threshold values were specific (94%) for the anterior bank of the CS but not sensitive (42%). Intermediate threshold values achieved an acceptable trade-off (0.4: 89% specific and 70% sensitive).

Small loci of astroglial glutamine synthetase deficiency in the postnatal brain cause epileptic seizures and impaired functional connectivity.

OBJECTIVE: The astroglial enzyme glutamine synthetase (GS) is deficient in small loci in the brain in adult patients with different types of focal epilepsy; however, the role of this deficiency in the pathogenesis of epilepsy has been difficult to assess due to a lack of sufficiently sensitive and specific animal models. The aim of this study was to develop an in vivo approach for precise and specific deletions of the GS gene in the postnatal brain. METHODS: We stereotaxically injected various adeno-associated virus (AAV)-Cre recombinase constructs into the hippocampal formation and neocortex in 22-70-week-old GSflox/flox mice to knock out the GS gene in a specific and focal manner. The mice were subjected to seizure threshold determination, continuous video-electroencephalographic recordings, advanced in vivo neuroimaging, and immunocytochemistry for GS. RESULTS: The construct AAV8-glial fibrillary acidic protein-green fluorescent protein-Cre eliminated GS in >99% of astrocytes in the injection center with a gradual return to full GS expression toward the periphery. Such focal GS deletion reduced seizure threshold, caused spontaneous recurrent seizures, and diminished functional connectivity. SIGNIFICANCE: These results suggest that small loci of GS deficiency in the postnatal brain are sufficient to cause epilepsy and impaired functional connectivity. Additionally, given the high specificity and precise spatial resolution of our GS knockdown approach, we anticipate that this model will be extremely useful for rigorous in vivo and ex vivo studies of astroglial GS function at the brain-region and single-cell levels.

Artificial neural network trained on smartphone behavior can trace epileptiform activity in epilepsy.

A range of abnormal electrical activity patterns termed epileptiform discharges can occur in the brains of persons with epilepsy. These epileptiform discharges can be monitored and recorded with implanted devices that deliver therapeutic neurostimulation. These continuous recordings provide an opportunity to study the behavioral correlates of epileptiform discharges as the patients go about their daily lives. Here, we captured the smartphone touchscreen interactions in eight patients in conjunction with electrographic recordings (accumulating 35,714 h) and by using an artificial neural network model addressed if the behavior reflected the epileptiform discharges. The personalized model outputs based on smartphone behavioral inputs corresponded well with the observed electrographic data (R: 0.2-0.6, median 0.4). The realistic reconstructions of epileptiform activity based on smartphone use demonstrate how day-to-day digital behavior may be converted to personalized markers of disease activity in epilepsy.

Increased branched-chain amino acids at baseline and hours before a spontaneous seizure in the human epileptic brain.

The objective of this study was to monitor the extracellular brain chemistry dynamics at baseline and in relation to spontaneous seizures in human patients with refractory epilepsy. Thirty patients with drug-resistant focal epilepsy underwent intracranial electroencephalography and concurrent brain microdialysis for up to 8 continuous days. Extracellular brain glutamate, glutamine, and the branched-chain amino acids (BCAAs) valine, leucine, and isoleucine were quantified in the dialysis samples by liquid chromatography-tandem mass spectrometry. Extracellular BCAAs and glutamate were chronically elevated at baseline by approximately 1.5-3-fold in brain regions of seizure onset and propagation versus regions not involved by seizures. Moreover, isoleucine increased significantly above baseline as early as 3 h before a spontaneous seizure. BCAAs play important roles in glutamatergic neurotransmission, mitochondrial function, neurodegeneration, and mammalian target of rapamycin signaling. Because all of these processes have been implicated in epilepsy, the results suggest a novel role of BCAAs in the pathogenesis of spontaneous seizures.

Astroglial Glutamine Synthetase and the Pathogenesis of Mesial Temporal Lobe Epilepsy.

The enzyme glutamine synthetase (GS), also referred to as glutamate ammonia ligase, is abundant in astrocytes and catalyzes the conversion of ammonia and glutamate to glutamine. Deficiency or dysfunction of astrocytic GS in discrete brain regions have been associated with several types of epilepsy, including medically-intractable mesial temporal lobe epilepsy (MTLE), neocortical epilepsies, and glioblastoma-associated epilepsy. Moreover, experimental inhibition or deletion of GS in the entorhinal-hippocampal territory of laboratory animals causes an MTLE-like syndrome characterized by spontaneous, recurrent hippocampal-onset seizures, loss of hippocampal neurons, and in some cases comorbid depressive-like features. The goal of this review is to summarize and discuss the possible roles of astroglial GS in the pathogenesis of epilepsy.

Network-Related Changes in Neurotransmitters and Seizure Propagation During Rodent Epileptogenesis.

OBJECTIVE: To test the hypothesis that glutamate and GABA are linked to the formation of epilepsy networks and the triggering of spontaneous seizures, we examined seizure initiation/propagation characteristics and neurotransmitter levels during epileptogenesis in a translationally relevant rodent model of mesial temporal lobe epilepsy. METHODS: The glutamine synthetase (GS) inhibitor methionine sulfoximine was infused into one of the hippocampi in laboratory rats to create a seizure focus. Long-term video-intracranial EEG recordings and brain microdialysis combined with mass spectrometry were used to examine seizure initiation, seizure propagation, and extracellular brain levels of glutamate and GABA. RESULTS: All seizures (n = 78 seizures, n = 3 rats) appeared first in the GS-inhibited hippocampus of all animals, followed by propagation to the contralateral hippocampus. Propagation time decreased significantly from 11.65 seconds early in epileptogenesis (weeks 1-2) to 6.82 seconds late in epileptogenesis (weeks 3-4, paired t test, p = 0.025). Baseline extracellular glutamate levels were 11.6-fold higher in the hippocampus of seizure propagation (7.3 µM) vs the hippocampus of seizure onset (0.63 µM, analysis of variance/Fisher least significant difference, p = 0.01), even though the concentrations of the major glutamate transporter proteins excitatory amino acid transporter subtypes 1 and 2 and xCT were unchanged between the brain regions. Finally, extracellular GABA in the seizure focus decreased significantly from baseline several hours before a spontaneous seizure (paired t test/false discovery rate). CONCLUSION: The changes in glutamate and GABA suggest novel and potentially important roles of the amino acids in epilepsy network formation and in the initiation and propagation of spontaneous seizures.

Graph-based risk assessment and error detection in radiation therapy.

PURPOSE: The objective of this study was to formalize and automate quality assurance (QA) in radiation oncology. Quality assurance in radiation oncology entails a multistep verification of complex, personalized radiation plans to treat cancer involving an interdisciplinary team and high technology, multivendor software and hardware systems. We addressed the pretreatment physics chart review (TPCR) using methods from graph theory and constraint programming to study the effect of dependencies between variables and automatically identify logical inconsistencies and how they propagate. MATERIALS AND METHODS: We used a modular approach to decompose the TPCR process into tractable units comprising subprocesses, modules and variables. Modules represented the main software entities comprised in the radiation treatment planning workflow and subprocesses grouped the checks to be performed by functionality. Module-associated variables served as inputs to the subprocesses. Relationships between variables were modeled by means of a directed graph. The detection of errors, in the form of inconsistencies, was formalized as a constraint satisfaction problem whereby checks were encoded as logical formulae. The sequence in which subprocesses were visited was described in an activity diagram. RESULTS: The comprehensive model for the TPCR process comprised 5 modules, 19 subprocesses and 346 variables, 225 of which were distinct. Modules included "Treatment Planning System" and "Record and Verify System." Subprocesses included "Dose Prescription," "Documents," "CT Integrity," "Anatomical Contours," "Beam Configuration," "Dose Calculation," "3D Dose Distribution Quality," and "Treatment Approval." Variable inconsistencies, and their source and propagation were determined by checking for constraint violation and through graph traversal. Impact scores, obtained through graph traversal, combined with severity scores associated with an inconsistency, allowed risk assessment. CONCLUSIONS: Directed graphs combined with constraint programming hold promise for formalizing complex QA processes in radiation oncology, performing risk assessment and automating the TPCR process. Though complex, the process is tractable.

Circadian-Like Rhythmicity of Extracellular Brain Glutamate in Epilepsy.

Seizures often exhibit striking circadian-like (~24-h) rhythms. While chronotherapy has shown promise in treating epilepsy, it is not widely used, in part because the patterns of seizure rhythmicity vary considerably among patients and types of epilepsy. A better understanding of the mechanisms underlying rhythmicity in epilepsy could be expected to result in more effective approaches which can be tailored to each individual patient. The excitatory neurotransmitter glutamate is an essential modulator of circadian rhythms, and changes in the extracellular levels of glutamate likely affect the threshold to seizures. We used a reverse translational rodent model of mesial temporal lobe epilepsy (MTLE) combined with long-term intracerebral microdialysis to monitor the hourly concentrations of glutamate in the seizure onset area (epileptogenic hippocampus) over several days. We observed significant 24-h oscillations of extracellular glutamate in the epileptogenic hippocampus (n = 4, JTK_CYCLE test, p < 0.05), but not in the hippocampus of control animals (n = 4). To our knowledge, circadian glutamate oscillations have not been observed in a seizure onset region, and we speculate that the oscillations contribute to the rhythmicity of seizures in MTLE.

Controversies on the network theory of epilepsy: Debates held during the ICTALS 2019 conference.

Debates on six controversial topics on the network theory of epilepsy were held during two debate sessions, as part of the International Conference for Technology and Analysis of Seizures, 2019 (ICTALS 2019) convened at the University of Exeter, UK, September 2-5 2019. The debate topics were (1) From pathologic to physiologic: is the epileptic network part of an existing large-scale brain network? (2) Are micro scale recordings pertinent for defining the epileptic network? (3) From seconds to years: do we need all temporal scales to define an epileptic network? (4) Is it necessary to fully define the epileptic network to control it? (5) Is controlling seizures sufficient to control the epileptic network? (6) Does the epileptic network want to be controlled? This article, written by the organizing committee for the debate sessions and the debaters, summarizes the arguments presented during the debates on these six topics.