Epileptiform abnormalities predict delayed cerebral ischemia in subarachnoid hemorrhage

Anti-Apoptotic Effects of AMPA Receptor Antagonist Perampanel in Early Brain Injury After Subarachnoid Hemorrhage in Mice

This study was aimed to investigate if acute neuronal apoptosis is induced by activation of AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionate) receptors (AMPARs) and inhibited by a clinically available selective AMPAR antagonist and antiepileptic drug perampanel (PER) in subarachnoid hemorrhage (SAH), and if the mechanisms include upregulation of an inflammation-related matricellular protein periostin. Sham-operated and endovascular perforation SAH mice randomly received an administration of 3 mg/kg PER or the vehicle intraperitoneally. Post-SAH neurological impairments and increased caspase-dependent neuronal apoptosis were associated with activation of AMPAR subunits GluA1 and GluA2, and upregulation of periostin and proinflammatory cytokines interleukins-1β and -6, all of which were suppressed by PER. PER also inhibited post-SAH convulsion-unrelated increases in the total spectral power on video electroencephalogram (EEG) monitoring. Intracerebroventricularly injected recombinant periostin blocked PER's anti-apoptotic effects on neurons. An intracerebroventricular injection of a selective agonist for GluA1 and GluA2 aggravated neurological impairment, neuronal apoptosis as well as periostin upregulation, but did not increase the EEG total spectral power after SAH. A higher dosage (10 mg/kg) of PER had even more anti-apoptotic effects compared with 3 mg/kg PER. Thus, this study first showed that AMPAR activation causes post-SAH neuronal apoptosis at least partly via periostin upregulation. A clinically available AMPAR antagonist PER appears to be neuroprotective against post-SAH early brain injury through the anti-inflammatory and anti-apoptotic effects, independent of the antiepileptic action, and deserves further study.

Perampanel attenuates oxidative stress and pyroptosis following subarachnoid hemorrhage via the SIRT3/FOXO3α pathway

Subarachnoid hemorrhage (SAH) occurs most commonly after rupture of an aneurysm, resulting in high disability and mortality due to the absence of effective therapy. Its subsequent stage, early brain injury (EBI), promotes the sustainable development of injury in the brain and ultimately leads to poor prognosis. As a new antiepileptic drug, the effect of perampanel on EBI after SAH is unknown. Pyroptosis, a process of inflammatory programmed cell death, has been confirmed in most studies to play a substantial role in aggravating SAH-post EBI. Similarly, oxidative stress is closely involved in neuronal pyroptosis and the pathophysiological mechanism of SAH-post EBI, leading to a devastating outcome for SAH patients. Nonetheless, no studies have been conducted to determine whether perampanel reduces pyroptosis and oxidative stress in the context of SAH-induced EBI. Rat SAH model via endovascular perforation was constructed in this study, to assess the neuroprotective effect of perampanel on SAH-post EBI, and to clarify the possible molecular mechanism. By means of the neurological score, brain edema detection, FJB staining, immunofluorescence, WB, ELISA, and ROS assay, we found that perampanel can improve neuroscores and reduce brain edema and neuronal degeneration at 24 h after SAH; we also found that perampanel reduced oxidative stress, neuronal pyroptosis, and inhibition of the SIRT3-FOXO3α pathway at 24 h after SAH. When 3-TYP, an inhibitor of SIRT3, was administered, the effects of perampanel on the SIRT3-FOXO3a pathway, antioxidant stress, and neuronal pyroptosis were reversed. Taken together, our data indicate that perampanel attenuates oxidative stress and pyroptosis following subarachnoid hemorrhage via the SIRT3/FOXO3α pathway. This study highlights the application value of perampanel in subarachnoid hemorrhage and lays a foundation for clinical research and later transformation of perampanel in SAH.

Effects of New-Generation Antiepileptic Drug Prophylaxis on Delayed Neurovascular Events After Aneurysmal Subarachnoid Hemorrhage

Neuroelectric disruptions such as seizures and cortical spreading depolarization may contribute to the development of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (SAH). However, effects of antiepileptic drug prophylaxis on outcomes remain controversial in SAH. The authors investigated if prophylactic administration of new-generation antiepileptic drugs levetiracetam and perampanel was beneficial against delayed neurovascular events after SAH. This was a retrospective single-center cohort study of 121 consecutive SAH patients including 56 patients of admission World Federation of Neurological Surgeons grades IV - V who underwent aneurysmal obliteration within 72 h post-SAH from 2013 to 2021. Prophylactic antiepileptic drugs differed depending on the study terms: none (2013 - 2015), levetiracetam for patients at high risks of seizures (2016 - 2019), and perampanel for all patients (2020 - 2021). The 3rd term had the lowest occurrence of delayed cerebral microinfarction on diffusion-weighted magnetic resonance imaging, which was related to less development of DCI. Other outcome measures were similar among the 3 terms including incidences of angiographic vasospasm, computed tomography-detectable delayed cerebral infarction, seizures, and 3-month good outcomes (modified Rankin Scale 0 - 2). The present study suggests that prophylactic administration of levetiracetam and perampanel was not associated with worse outcomes and that perampanel may have the potential to reduce DCI by preventing microcirculatory disturbances after SAH. Further studies are warranted to investigate anti-DCI effects of a selective α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor antagonist perampanel in SAH patients in a large-scale prospective study.

Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury

Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.

2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association

AIM

The "2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage" replaces the 2012 "Guidelines for the Management of Aneurysmal Subarachnoid Hemorrhage." The 2023 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with aneurysmal subarachnoid hemorrhage.

METHODS

A comprehensive search for literature published since the 2012 guideline, derived from research principally involving human subjects, published in English, and indexed in MEDLINE, PubMed, Cochrane Library, and other selected databases relevant to this guideline, was conducted between March 2022 and June 2022. In addition, the guideline writing group reviewed documents on related subject matter previously published by the American Heart Association. Newer studies published between July 2022 and November 2022 that affected recommendation content, Class of Recommendation, or Level of Evidence were included if appropriate. Structure: Aneurysmal subarachnoid hemorrhage is a significant global public health threat and a severely morbid and often deadly condition. The 2023 aneurysmal subarachnoid hemorrhage guideline provides recommendations based on current evidence for the treatment of these patients. The recommendations present an evidence-based approach to preventing, diagnosing, and managing patients with aneurysmal subarachnoid hemorrhage, with the intent to improve quality of care and align with patients' and their families' and caregivers' interests. Many recommendations from the previous aneurysmal subarachnoid hemorrhage guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

Association of Epileptiform Activity With Outcomes in Toxic-Metabolic Encephalopathy

The clinical significance of epileptiform abnormalities (EAs) specific to toxic-metabolic encephalopathy (TME) is unknown.

OBJECTIVES

To quantify EA burden in patients with TME and its association with neurologic outcomes.

DESIGN SETTING AND PARTICIPANT

This is a retrospective study. A cohort of patients with TME and EA (positive) were age, Sequential Organ Failure Assessment Score, Acute Physiology and Chronic Health Evaluation II (APACHE-II) score matched to a cohort of TME patients without EA (control). Univariate analysis compared EA-positive patients against controls. Multivariable logistical regression adjusting for underlying disease etiology was performed to examine the relationship between EA burden and probability of poor neurologic outcome (modified Rankin Score [mRS] 4-6) at discharge. Consecutive admissions to inpatient floors or ICUs that underwent continuous electroencephalography (cEEG) monitoring at a single center between 2012 and 2019. Inclusion criteria were 1) patients with TME diagnosis, 2) age greater than 18 years, and 3) greater than or equal to 16 hours of cEEG. Patients with acute brain injury and cardiac arrest were excluded.

MAIN OUTCOMES AND MEASURES

Poor neurologic outcome defined by mRS (mRS 4-6).

RESULTS

One hundred sixteen patients were included, 58 with EA and 58 controls without EA, where matching was performed on age and APACHE-II score. The median age was 66 (Q1-Q3, 57-75) and median APACHE II score was 18 (Q1-Q3, 13-22). Overall cohort discharge mortality was 22% and 70% had a poor neurologic outcome. Peak EA burden was defined as the 12-hour window of recording with the highest prevalence of EAs. In multivariable analysis adjusted for Charlson Comorbidity Index and primary diagnosis, presence of EAs was associated with poor outcome (odds ratio 3.89; CI [1.05-14.2], p = 0.041). Increase in peak EA burden from 0% to 100% increased probability of poor discharge neurologic outcome by 30%.

CONCLUSIONS AND RELEVANCE

Increasing burden of EA is associated with worse discharge outcomes in patients with TME. Future studies are needed to determine whether short-term treatment with anti-seizure medications while medically treating the underlying metabolic derangement improves outcomes.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation

BACKGROUND AND OBJECTIVES

Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns.

METHODS

We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes.

RESULTS

SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively.

DISCUSSION

SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

Epileptiform activity in the acute phase of stroke predicts the outcomes in patients without seizures

Background and purpose

The abnormalities in EEG of stroke-patients increase the risk of epilepsy but their significancy for poststroke outcome is unclear. This presented study was aimed at determining the prevalence and nature of changes in EEG recordings from the stroke hemisphere and from the contralateral hemisphere. Another objective was to determine the significance of abnormalities in EEG in the first days of stroke for the post-stroke functional status on the acute and chronic phase of disease.

Methods

In all qualified stroke-patients, EEG was performed during the first 3 days of hospitalization and at discharge. The correlation between EEG abnormalities both in the stroke hemisphere and in the collateral hemisphere with the neurological and functional state in various time points was performed.

Results

One hundred thirty-one patients were enrolled to this study. Fifty-eight patients (44.27%) had abnormal EEG. The sporadic discharges and generalized rhythmic delta activity were the most common abnormalities in the EEG. The neurological status on the first day and the absence of changes in the EEG in the hemisphere without stroke were the independent factors for good neurological state (0–2 mRS) at discharge. The age-based analysis model (OR 0.981 CI 95% 0.959–1.001, p = 0.047), neurological status on day 1 (OR 0.884 CI 95% 0.82–0.942, p < 0.0001) and EEG recording above the healthy hemisphere (OR 0.607 CI 95% 0.37–0.917, p = 0.028) had the highest prognostic value in terms of achieving good status 90 days after stroke.

Conclusions

Abnormalities in EEG without clinical manifestation are present in 40% of patients with acute stroke. Changes in EEG in acute stroke are associated with a poor neurological status in the first days and poor functional status in the chronic period of stroke.

Bispectral index monitoring to detect delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

PURPOSE

Evaluate the bispectral index (BIS) monitoring to detect delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH).

MATERIALS AND METHODS

A single-center prospective study in patients with aSAH. BIS monitoring was recorded during 25-120 min in two periods, within the initial 72 h (BIS1) and between days 4 and 6 (BIS2) from admission. The median for each exported BIS parameter was analyzed. Transcranial Doppler (TCD) sonography was simultaneously performed with BIS1 (TCD1) and BIS2 (TCD2) monitoring. A multivariate logistic regression model was built to identify the variables associated with DCI.

RESULTS

Sixty-four patients were included and 16 (25%) developed DCI. During BIS2 monitoring, significant differences were found in BIS value (left, p = 0.01; right, p = 0.009), 95% spectral edge frequency (left and right, p = 0.04), and total power (left and right, p = 0.04). In multivariable analysis, vasospasm on TCD2 (OR 42.8 [95% CI 3.1-573]; p = 0.005), a median BIS2 value <85 in one or both sides (OR 6.2 [95% CI 1.28-30]; p = 0.023), and age (OR 1.08 [95% CI 1.00-1.17]; p = 0.04) were associated with the development of DCI.

CONCLUSIONS

BIS value is the most useful BIS parameter for detecting DCI after aSAH. Pending further validation, BIS monitoring might be even more accurate than TCD.

Automated EEG-based prediction of delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

Delayed cerebral ischemia (DCI) is a leading complication of aneurysmal subarachnoid hemorrhage (SAH) and electroencephalography (EEG) is increasingly used to evaluate DCI risk. Our goal is to develop an automated DCI prediction algorithm integrating multiple EEG features over time.

METHODS

We assess 113 moderate to severe grade SAH patients to develop a machine learning model that predicts DCI risk using multiple EEG features.

RESULTS

Multiple EEG features discriminate between DCI and non-DCI patients when aligned either to SAH time or to DCI onset. DCI and non-DCI patients have significant differences in alpha-delta ratio (0.08 vs 0.05, p < 0.05) and percent alpha variability (0.06 vs 0.04, p < 0.05), Shannon entropy (p < 0.05) and epileptiform discharge burden (205 vs 91 discharges per hour, p < 0.05) based on whole brain and vascular territory averaging. Our model improves predictions by emphasizing the most informative features at a given time with an area under the receiver-operator curve of 0.73, by day 5 after SAH and good calibration between 48-72 hours (calibration error 0.13).

CONCLUSIONS

Our proposed model obtains good performance in DCI prediction.

SIGNIFICANCE

We leverage machine learning to enable rapid, automated, multi-featured EEG assessment and has the potential to increase the utility of EEG for DCI prediction.

High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

To investigate whether epileptiform discharge burden can identify those at risk for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH).

METHODS

Retrospective analysis of 113 moderate to severe grade SAH patients who had continuous EEG (cEEG) recordings during their hospitalization. We calculated the burden of epileptiform discharges (ED), measured as number of ED per hour.

RESULTS

We find that many SAH patients have an increase in ED burden during the first 3-10 days following rupture, the major risk period for DCI. However, those who develop DCI have a significantly higher hourly burden from days 3.5-6 after SAH vs. those who do not. ED burden is higher in DCI patients when assessed in relation to the onset of DCI (area under the receiver operator curve 0.72). Finally, specific trends of ED burden over time, assessed by group-based trajectory analysis, also help stratify DCI risk.

CONCLUSIONS

These results suggest that ED burden is a useful parameter for identifying those at higher risk of developing DCI after SAH. The higher burden rate associated with DCI supports the theory of metabolic supply-demand mismatch which contributes to this complication.

SIGNIFICANCE

ED burden is a novel biomarker for predicting those at high risk of DCI.

Antiseizure Medication Treatment and Outcomes in Patients with Subarachnoid Hemorrhage Undergoing Continuous EEG Monitoring

BACKGROUND

Patients with aneurysmal subarachnoid hemorrhage (aSAH) with electroencephalographic epileptiform activity (seizures, periodic and rhythmic patterns, and sporadic discharges) are frequently treated with antiseizure medications (ASMs). However, the safety and effectiveness of ASM treatment for epileptiform activity has not been established. We used observational data to investigate the effectiveness of ASM treatment in patients with aSAH undergoing continuous electroencephalography (cEEG) to develop a causal hypothesis for testing in prospective trials.

METHODS

This was a retrospective single-center cohort study of patients with aSAH admitted between 2011 and 2016. Patients underwent ≥ 24 h of cEEG within 4 days of admission. All patients received primary ASM prophylaxis until aneurysm treatment (typically within 24 h of admission). Treatment exposure was defined as reinitiation of ASMs after aneurysm treatment and cEEG initiation. We excluded patients with non-cEEG indications for ASMs (e.g., epilepsy, acute symptomatic seizures). Outcomes measures were 90-day mortality and good functional outcome (modified Rankin Scale scores 0-3). Propensity scores were used to adjust for baseline covariates and disease severity.

RESULTS

Ninety-four patients were eligible (40 continued ASM treatment; 54 received prophylaxis only). ASM continuation was not significantly associated with higher 90-day mortality (propensity-adjusted hazard ratio [HR] = 2.01 [95% confidence interval (CI) 0.57-7.02]). ASM continuation was associated with lower likelihood for 90-day good functional outcome (propensity-adjusted HR = 0.39 [95% CI 0.18-0.81]). In a secondary analysis, low-intensity treatment (low-dose single ASM) was not significantly associated with mortality (propensity-adjusted HR = 0.60 [95% CI 0.10-3.59]), although it was associated with a lower likelihood of good outcome (propensity-adjusted HR = 0.37 [95% CI 0.15-0.91]), compared with prophylaxis. High-intensity treatment (high-dose single ASM, multiple ASMs, or anesthetics) was associated with higher mortality (propensity-adjusted HR = 6.80 [95% CI 1.67-27.65]) and lower likelihood for good outcomes (propensity-adjusted HR = 0.30 [95% CI 0.10-0.94]) compared with prophylaxis only.

CONCLUSIONS

Our findings suggest the testable hypothesis that continuing ASMs in patients with aSAH with cEEG abnormalities does not improve functional outcomes. This hypothesis should be tested in prospective randomized studies.

Cortical Spreading Depolarizations and Clinically Measured Scalp EEG Activity After Aneurysmal Subarachnoid Hemorrhage and Traumatic Brain Injury

BACKGROUND

Spreading depolarizations (SDs) are associated with worse outcome following subarachnoid hemorrhage (SAH) and traumatic brain injury (TBI), but gold standard detection requires electrocorticography with a subdural strip electrode. Electroencephalography (EEG) ictal-interictal continuum abnormalities are associated with poor outcomes after TBI and with both delayed cerebral ischemia (DCI) and poor outcomes after SAH. We examined rates of SD detection in patients with SAH and TBI with intraparenchymal and subdural strip electrodes and assessed which continuous EEG (cEEG) measures were associated with intracranially quantified SDs.

METHODS

In this single-center cohort, we included patients with SAH and TBI undergoing ≥ 24 h of interpretable intracranial monitoring via eight-contact intraparenchymal or six-contact subdural strip platinum electrodes or both. SDs were rated according to established consensus criteria and compared with cEEG findings rated according to the American Clinical Neurophysiology Society critical care EEG monitoring consensus criteria: lateralized rhythmic delta activity, generalized rhythmic delta activity, lateralized periodic discharges, generalized periodic discharges, any ictal-interictal continuum, or a composite scalp EEG tool for seizure risk estimation: the 2HELPS2B score. Among patients with SAH, cEEG was assessed for validated DCI biomarkers: new or worsening epileptiform abnormalities and new background deterioration.

RESULTS

Over 6 years, SDs were recorded in 5 (18%) of 28 patients recorded with intraparenchymal electrodes and 4 (40%) of 10 patients recorded with subdural strip electrodes. There was no significant association between occurrence of SDs and day 1 cEEG findings (American Clinical Neurophysiology Society main terms lateralized periodic discharges, generalized periodic discharges, lateralized rhythmic delta activity, or seizures, individually or in combination). After SAH, established cEEG DCI predictors were not associated with SDs.

CONCLUSIONS

Intraparenchymal recordings yielded low rates of SD, and documented SDs were not associated with ictal-interictal continuum abnormalities or other cEEG DCI predictors. Identifying scalp EEG correlates of SD may require training computational EEG analytics and use of gold standard subdural strip electrocorticography recordings.

Neuroelectric Mechanisms of Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage

Delayed cerebral ischemia (DCI) remains a challenging but very important condition, because DCI is preventable and treatable for improving functional outcomes after aneurysmal subarachnoid hemorrhage (SAH). The pathologies underlying DCI are multifactorial. Classical approaches to DCI focus exclusively on preventing and treating the reduction of blood flow supply. However, recently, glutamate-mediated neuroelectric disruptions, such as excitotoxicity, cortical spreading depolarization and seizures, and epileptiform discharges, have been reported to occur in high frequencies in association with DCI development after SAH. Each of the neuroelectric disruptions can trigger the other, which augments metabolic demand. If increased metabolic demand exceeds the impaired blood supply, the mismatch leads to relative ischemia, resulting in DCI. The neuroelectric disruption also induces inverted vasoconstrictive neurovascular coupling in compromised brain tissues after SAH, causing DCI. Although glutamates and the receptors may play central roles in the development of excitotoxicity, cortical spreading ischemia and epileptic activity-related events, more studies are needed to clarify the pathophysiology and to develop novel therapeutic strategies for preventing or treating neuroelectric disruption-related DCI after SAH. This article reviews the recent advancement in research on neuroelectric disruption after SAH.

Higher cystatin C level increases the risk of delayed cerebral ischemia after endovascular treatment of aneurysmal subarachnoid hemorrhage: a case-control study

Cystatin C (CysC) has been found to be associated with hemorrhagic and ischemic stroke in many studies. However, the association between CysC level and the risk of delayed cerebral ischemia after endovascular treatment of aneurysmal subarachnoid hemorrhage has been reported rarely. Our study was proposed to explore this association. Consecutive patients from June 2015 to February 2021 in this single-center retrospective study were selected. Univariate and multivariate analyses were used to identify potential prognostic risk factors for delayed cerebral ischemia, and the stability of the association was demonstrated by several statistical methods, such as subgroup analysis, interaction testing, generalized linear models, and propensity score matching. A total of 424 patients were included in the analysis. Cystatin C was independently associated with delayed cerebral ischemia. The independent effects of CysC on delayed cerebral ischemia were shown in generalized linear models with a logit link, and the results were relatively stable in crude, partial, and full models with ORs (95% CIs) for delayed cerebral ischemia. Subgroup analysis showed no significant subgroup differences in the effect of CysC on delayed cerebral ischemia. There was also no interaction effect between CysC and other confounders. Patients in the high CysC group had a higher risk of delayed cerebral ischemia than those in the low CysC group before and after propensity score matching. CysC level could be an independent predictor for the risk of delayed cerebral ischemia after endovascular treatment of aneurysmal subarachnoid hemorrhage.

The Utility of Quantitative EEG in Detecting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

SUMMARY

In this review, we discuss the utility of quantitative EEG parameters for the detection of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage in the context of the complex pathophysiology of DCI and the limitations of current diagnostic methods. Because of the multifactorial pathophysiology of DCI, methodologies solely assessing blood vessel narrowing (vasospasm) are insufficient to detect all DCI. Quantitative EEG has facilitated the exploration of EEG as a diagnostic modality of DCI. Multiple quantitative EEG parameters such as alpha power, relative alpha variability, and alpha/delta ratio show reliable detection of DCI in multiple studies. Recent studies on epileptiform abnormalities suggest that their potential for the detection of DCI. Quantitative EEG is a promising, continuous, noninvasive, monitoring modality of DCI implementable in daily practice. Future work should validate these parameters in larger populations, facilitated by the development of automated detection algorithms and multimodal data integration.

Electroencephalography for detection of vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a retrospective analysis and systematic review

OBJECTIVE

Good functional outcomes after aneurysmal subarachnoid hemorrhage (aSAH) are often dependent on early detection and treatment of cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI). There is growing evidence that continuous monitoring with cranial electroencephalography (cEEG) can predict CVS and DCI. Therefore, the authors sought to assess the value of continuous cEEG monitoring for the detection of CVS and DCI in aSAH.

METHODS

The cerebrovascular database of a quaternary center was reviewed for patients with aSAH and cEEG monitoring between January 1, 2017, and July 31, 2019. Demographic data, cardiovascular risk factors, Glasgow Coma Scale score at admission, aneurysm characteristics, and outcomes were abstracted from the medical record. Patient data were retrospectively analyzed for DCI and angiographically assessed CVS. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and odds ratio for cEEG, transcranial Doppler ultrasonography (TCDS), CTA, and DSA in detecting DCI and angiographic CVS were calculated. A systematic literature review was conducted in accordance with PRISMA guidelines querying the PubMed, Cochrane Controlled Trials Register, Web of Science, and Embase databases.

RESULTS

A total of 77 patients (mean age 60 years [SD 15 years]; female sex, n = 54) were included in the study. Continuous cEEG monitoring detected DCI and angiographically assessed CVS with specificities of 82.9% (95% CI 66.4%–93.4%) and 94.4% (95% CI 72.7%–99.9%), respectively. The sensitivities were 11.1% (95% CI 3.1%–26.1%) for DCI (n = 71) and 18.8% (95% CI 7.2%–36.4%) for angiographically assessed CVS (n = 50). Furthermore, TCDS detected angiographically determined CVS with a sensitivity of 87.5% (95% CI 71.0%–96.5%) and specificity of 25.0% (95% CI 7.3%–52.4%). In patients with DCI, TCDS detected vasospasm with a sensitivity of 85.7% (95% CI 69.7%–95.2%) and a specificity of 18.8% (95% CI 7.2%–36.4%). DSA detected vasospasm with a sensitivity of 73.9% (95% CI 51.6%–89.8%) and a specificity of 47.8% (95% CI 26.8%–69.4%).

CONCLUSIONS

The study results suggest that continuous cEEG monitoring is highly specific in detecting DCI as well as angiographically assessed CVS. More prospective studies with predetermined thresholds and endpoints are needed to assess the predictive role of cEEG in aSAH.

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.

Neurocritical care management of poor-grade subarachnoid hemorrhage: Unjustified nihilism to reasonable optimism

BACKGROUND AND PURPOSE

Historically, overall outcomes for patients with high-grade subarachnoid hemorrhage (SAH) have been poor. Generally, between physicians, either reluctance to treat, or selectivity in treating such patients has been the paradigm. Recent studies have shown that early and aggressive care leads to significant improvement in survival rates and favorable outcomes of grade V SAH patients. With advancements in both neurocritical care and end-of-life care, non-treatment or selective treatment of grade V SAH patients is rarely justified. Current paradigm shifts towards early and aggressive care in such cases may lead to improved outcomes for many more patients.

MATERIALS AND METHODS

We performed a detailed review of the current literature regarding neurointensive management strategies in high-grade SAH, discussing multiple aspects. We discussed the neurointensive care management protocols for grade V SAH patients.

RESULTS

Acutely, intracranial pressure control is of utmost importance with external ventricular drain placement, sedation, optimization of cerebral perfusion pressure, osmotherapy and hyperventilation, as well as cardiopulmonary support through management of hypotension and hypertension.

CONCLUSIONS

Advancements of care in SAH patients make it unethical to deny treatment to poor Hunt and Hess grade patients. Early and aggressive treatment results in a significant improvement in survival rate and favorable outcome in such patients.

Seizures, Status Epilepticus, and Continuous EEG in the Intensive Care Unit

PURPOSE OF REVIEW

This article discusses the evolving definitions of seizures and status epilepticus in the critical care environment and the role of critical care EEG in both diagnosing seizure activity and serving as a predictive biomarker of clinical trajectory.

RECENT FINDINGS

Initial screening EEG has been validated as a tool to predict which patients are at risk of future seizures. However, accepted definitions of seizures and nonconvulsive status epilepticus encourage a treatment trial when the diagnosis on EEG is indeterminate because of periodic or rhythmic patterns or uncertain clinical correlation. Similarly, recent data have demonstrated the diagnostic utility of intracranial EEG in increasing the yield of seizure detection. EEG has additionally been validated as a diagnostic biomarker of covert consciousness, a predictive biomarker of cerebral ischemia and impending neurologic deterioration, and a prognostic biomarker of coma recovery and status epilepticus resolution. A recent randomized trial concluded that patients allocated to continuous EEG had no difference in mortality than those undergoing intermittent EEG but could not demonstrate whether this lack of difference was because of studying heterogeneous conditions, examining a monitoring tool rather than a therapeutic approach, or examining an outcome measure (mortality) perhaps more strongly associated with early withdrawal of life-sustaining therapy than to a sustained response to pharmacotherapy.

SUMMARY

Seizures and status epilepticus are events of synchronous hypermetabolic activity that are either discrete and intermittent or, alternatively, continuous. Seizures and status epilepticus represent the far end of a continuum of ictal-interictal patterns that include lateralized rhythmic delta activity and periodic discharges, which not only predict future seizures but may be further classified as status epilepticus on the basis of intracranial EEG monitoring or a diagnostic trial of antiseizure medication therapy. In particularly challenging cases, neuroimaging or multimodality neuromonitoring may be a useful adjunct documenting metabolic crisis. Specialized uses of EEG as a prognostic biomarker have emerged in traumatic brain injury for predicting language function and covert consciousness, cardiac arrest for predicting coma recovery, and subarachnoid hemorrhage for predicting neurologic deterioration due to delayed cerebral ischemia.

Inhibition of AMPA (α-Amino-3-Hydroxy-5-Methyl-4-Isoxazole Propionate) Receptor Reduces Acute Blood-Brain Barrier Disruption After Subarachnoid Hemorrhage in Mice

Activation of α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor (AMPAR) is thought to cause acute brain injury, but the role remains poorly understood in subarachnoid hemorrhage (SAH). This study was conducted to evaluate if AMPAR activation induces acute blood-brain barrier (BBB) disruption after SAH. C57BL/6 male adult mice (n = 117) underwent sham or filament perforation SAH modeling, followed by a random intraperitoneal injection of vehicle or two dosages (1 mg/kg or 3 mg/kg) of a selective noncompetitive AMPAR antagonist perampanel (PER) at 30 min post-modeling. The effects were evaluated by mortality, neurological scores, and brain water content at 24-48 h and video electroencephalogram monitoring, immunostaining, and Western blotting at 24 h post-SAH. PER significantly suppressed post-SAH neurological impairments, brain edema, and BBB disruption. SAH developed epileptiform spikes without obvious convulsion, which were also inhibited by PER. Western blotting showed that the expression of AMPAR subunits GluA1 and GluA2 was unchanged after SAH, but they were significantly activated after SAH. PER prevented post-SAH activation of GluA1/2, associated with the suppression of post-SAH induction of tenascin-C, a causative mediator of post-SAH BBB disruption. Meanwhile, an intracerebroventricular injection of a subtype-selective GluA1/2 agonist augmented the activation of GluA1/2 and the induction of tenascin-C in brain capillary endothelial cells and aggravated post-SAH BBB disruption without increases in epileptiform spikes. Neurological impairments and brain edema were not correlated with the occurrence of epileptiform spikes. This study first showed that AMPAR plays an important role in the development of post-SAH BBB disruption and can be a novel therapeutic target against it.

Automated Annotation of Epileptiform Burden and Its Association with Outcomes

OBJECTIVE

This study was undertaken to determine the dose-response relation between epileptiform activity burden and outcomes in acutely ill patients.

METHODS

A single center retrospective analysis was made of 1,967 neurologic, medical, and surgical patients who underwent >16 hours of continuous electroencephalography (EEG) between 2011 and 2017. We developed an artificial intelligence algorithm to annotate 11.02 terabytes of EEG and quantify epileptiform activity burden within 72 hours of recording. We evaluated burden (1) in the first 24 hours of recording, (2) in the 12-hours epoch with highest burden (peak burden), and (3) cumulatively through the first 72 hours of monitoring. Machine learning was applied to estimate the effect of epileptiform burden on outcome. Outcome measure was discharge modified Rankin Scale, dichotomized as good (0-4) versus poor (5-6).

RESULTS

Peak epileptiform burden was independently associated with poor outcomes (p < 0.0001). Other independent associations included age, Acute Physiology and Chronic Health Evaluation II score, seizure on presentation, and diagnosis of hypoxic-ischemic encephalopathy. Model calibration error was calculated across 3 strata based on the time interval between last EEG measurement (up to 72 hours of monitoring) and discharge: (1) <5 days between last measurement and discharge, 0.0941 (95% confidence interval [CI] = 0.0706-0.1191); 5 to 10 days between last measurement and discharge, 0.0946 (95% CI = 0.0631-0.1290); >10 days between last measurement and discharge, 0.0998 (95% CI = 0.0698-0.1335). After adjusting for covariates, increase in peak epileptiform activity burden from 0 to 100% increased the probability of poor outcome by 35%.

INTERPRETATION

Automated measurement of peak epileptiform activity burden affords a convenient, consistent, and quantifiable target for future multicenter randomized trials investigating whether suppressing epileptiform activity improves outcomes. ANN NEUROL 2021;90:300-311.

A model of metabolic supply-demand mismatch leading to secondary brain injury

Secondary brain injury (SBI) is defined as new or worsening injury to the brain after an initial neurologic insult, such as hemorrhage, trauma, ischemic stroke, or infection. It is a common and potentially preventable complication following many types of primary brain injury (PBI). However, mechanistic details about how PBI leads to additional brain injury and evolves into SBI are poorly characterized. In this work, we propose a mechanistic model for the metabolic supply demand mismatch hypothesis (MSDMH) of SBI. Our model, based on the Hodgkin-Huxley model, supplemented with additional dynamics for extracellular potassium, oxygen concentration, and excitotoxity, provides a high-level unified explanation for why patients with acute brain injury frequently develop SBI. We investigate how decreased oxygen, increased extracellular potassium, excitotoxicity, and seizures can induce SBI and suggest three underlying paths for how events following PBI may lead to SBI. The proposed model also helps explain several important empirical observations, including the common association of acute brain injury with seizures, the association of seizures with tissue hypoxia and so on. In contrast to current practices which assume that ischemia plays the predominant role in SBI, our model suggests that metabolic crisis involved in SBI can also be nonischemic. Our findings offer a more comprehensive understanding of the complex interrelationship among potassium, oxygen, excitotoxicity, seizures, and SBI.NEW & NOTEWORTHY We present a novel mechanistic model for the metabolic supply demand mismatch hypothesis (MSDMH), which attempts to explain why patients with acute brain injury frequently develop seizure activity and secondary brain injury (SBI). Specifically, we investigate how decreased oxygen, increased extracellular potassium, excitotoxicity, seizures, all common sequalae of primary brain injury (PBI), can induce SBI and suggest three underlying paths for how events following PBI may lead to SBI.

Aneurysmal Subarachnoid Hemorrhage

Aneurysmal subarachnoid hemorrhage is a neurologic emergency that requires immediate patient stabilization and prompt diagnosis and treatment. Early measures should focus on principles of advanced cardiovascular life support. The aneurysm should be evaluated and treated in a comprehensive stroke center by a multidisciplinary team capable of endovascular and, operative approaches. Once the aneurysm is secured, the patient is best managed by a dedicated neurocritical care service to prevent and manage complications, including a syndrome of delayed neurologic decline. The goal of such specialized care is to prevent secondary injury, reduce length of stay, and improve outcomes for survivors of the disease.

Electroencephalography, Hospital Complications, and Longitudinal Outcomes After Subarachnoid Hemorrhage

BACKGROUND

Following non-traumatic subarachnoid hemorrhage (SAH), in-hospital delayed cerebral ischemia is predicted by two chief events on continuous EEG (cEEG): new or worsening epileptiform abnormalities (EAs) and deterioration of cEEG background frequencies. We evaluated the association between longitudinal outcomes and these cEEG biomarkers. We additionally evaluated the association between longitudinal outcomes and other in-hospital complications.

METHODS

Patients with nontraumatic SAH undergoing ≥ 3 days of cEEG monitoring were enrolled in a prospective study evaluating longitudinal outcomes. Modified Rankin Scale (mRS) was assessed at discharge, and at 3- and 6-month follow-up time points. Adjusting for baseline severity in a cumulative proportional odds model, we modeled the mRS ordinally and measured the association between mRS and two forms of in-hospital cEEG deterioration: (1) cEEG evidence of new or worsening epileptiform abnormalities and (2) cEEG evidence of new background deterioration. We compared the magnitude of these associations at each time point with the association between mRS and other in-hospital complications: (1) delayed cerebral ischemia (DCI), (2) hospital-acquired infections (HAI), and (3) hydrocephalus. In a secondary analysis, we employed a linear mixed effects model to examine the association of mRS over time (dichotomized as 0-3 vs. 4-6) with both biomarkers of cEEG deterioration and with other in-hospital complications.

RESULTS

In total, 175 mRS assessments were performed in 59 patients. New or worsening EAs developed in 23 (39%) patients, and new background deterioration developed in 24 (41%). Among cEEG biomarkers, new or worsening EAs were independently associated with mRS at discharge, 3, and 6 months, respectively (adjusted cumulative proportional odds 4.99, 95% CI 1.60-15.6; 3.28, 95% CI 1.14-9.5; and 2.71, 95% CI 0.95-7.76), but cEEG background deterioration lacked an association. Among hospital complications, DCI was associated with discharge, 3-, and 6-month outcomes (adjusted cumulative proportional odds 4.75, 95% CI 1.64-13.8; 3.4; 95% CI 1.24-9.01; and 2.45, 95% CI 0.94-6.6), but HAI and hydrocephalus lacked an association. The mixed effects model demonstrated that these associations were sustained over longitudinal assessments without an interaction with time.

CONCLUSION

Although new or worsening EAs and cEEG background deterioration have both been shown to predict DCI, only new or worsening EAs are associated with a sustained impairment in functional outcome. This novel finding raises the potential for identifying therapeutic targets that may also influence outcomes.

Development of Expert-Level Automated Detection of Epileptiform Discharges During Electroencephalogram Interpretation

Importance

Interictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are a biomarker of epilepsy, seizure risk, and clinical decline. However, there is a scarcity of experts qualified to interpret EEG results. Prior attempts to automate IED detection have been limited by small samples and have not demonstrated expert-level performance. There is a need for a validated automated method to detect IEDs with expert-level reliability.

Objective

To develop and validate a computer algorithm with the ability to identify IEDs as reliably as experts and classify an EEG recording as containing IEDs vs no IEDs.

Design, Setting, and Participants

A total of 9571 scalp EEG records with and without IEDs were used to train a deep neural network (SpikeNet) to perform IED detection. Independent training and testing data sets were generated from 13 262 IED candidates, independently annotated by 8 fellowship-trained clinical neurophysiologists, and 8520 EEG records containing no IEDs based on clinical EEG reports. Using the estimated spike probability, a classifier designating the whole EEG recording as positive or negative was also built.

Main Outcomes and Measures

SpikeNet accuracy, sensitivity, and specificity compared with fellowship-trained neurophysiology experts for identifying IEDs and classifying EEGs as positive or negative or negative for IEDs. Statistical performance was assessed via calibration error and area under the receiver operating characteristic curve (AUC). All performance statistics were estimated using 10-fold cross-validation.

Results

SpikeNet surpassed both expert interpretation and an industry standard commercial IED detector, based on calibration error (SpikeNet, 0.041; 95% CI, 0.033-0.049; vs industry standard, 0.066; 95% CI, 0.060-0.078; vs experts, mean, 0.183; range, 0.081-0.364) and binary classification performance based on AUC (SpikeNet, 0.980; 95% CI, 0.977-0.984; vs industry standard, 0.882; 95% CI, 0.872-0.893). Whole EEG classification had a mean calibration error of 0.126 (range, 0.109-0.1444) vs experts (mean, 0.197; range, 0.099-0.372) and AUC of 0.847 (95% CI, 0.830-0.865).

Conclusions and Relevance

In this study, SpikeNet automatically detected IEDs and classified whole EEGs as IED-positive or IED-negative. This may be the first time an algorithm has been shown to exceed expert performance for IED detection in a representative sample of EEGs and may thus be a valuable tool for expedited review of EEGs.

Cerebrovascular pathophysiology of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

Aneurysmal subarachnoid hemorrhage (SAH) remains a serious cerebrovascular disease. Even if SAH patients survive the initial insults, delayed cerebral ischemia (DCI) may occur at 4 days or later post-SAH. DCI is characteristics of SAH, and is considered to develop by blood breakdown products and inflammatory reactions, or secondary to early brain injury, acute pathophysiological events that occur in the brain within the first 72 hours of aneurysmal SAH. The pathology underlying DCI may involve large artery vasospasm and/or microcirculatory disturbances by microvasospasm, microthrombosis, dysfunction of venous outflow and compression of microvasculature by vasogenic or cytotoxic tissue edema. Recent clinical evidence has shown that large artery vasospasm is not the only cause of DCI, and that both large artery vasospasm-dependent and -independent cerebral infarction causes poor outcome. Animal studies suggest that mechanisms of vasospasm may differ between large artery and arterioles or capillaries, and that many kinds of cells in the vascular wall and brain parenchyma may be involved in the pathogenesis of microcirculatory disturbances. The impairment of the paravascular and glymphatic systems also may play important roles in the development of DCI. As pathological mediators for DCI, glutamate and several matricellular proteins have been investigated in addition to inflammatory molecules. Glutamate is involved in excitotoxicity contributing to cortical spreading ischemia and epileptic activity-related events. Microvascular dysfunction is an attractive mechanism to explain the cause of poor outcomes independently of large cerebral artery vasospasm, but needs more studies to clarify the pathophysiologies or mechanisms and to develop a novel therapeutic strategy.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Validation of an algorithm of time-dependent electro-clinical risk stratification for electrographic seizures (TERSE) in critically ill patients

OBJECTIVE

The clinical implementation of continuous electroencephalography (CEEG) monitoring in critically ill patients is hampered by the substantial burden of work that it entails for clinical neurophysiologists. Solutions that might reduce this burden, including by shortening the duration of EEG to be recorded, would help its widespread adoption. Our aim was to validate a recently described algorithm of time-dependent electro-clinical risk stratification for electrographic seizure (ESz) (TERSE) based on simple clinical and EEG features.

METHODS

We retrospectively reviewed the medical records and EEG recordings of consecutive patients undergoing CEEG between October 1, 2015 and September, 30 2016 and assessed the sensitivity of TERSE for seizure detection, as well as the reduction in EEG time needed to be reviewed.

RESULTS

In a cohort of 407 patients and compared to full CEEG review, the model allowed the detection of 95% of patients with ESz and 97% of those with electrographic status epilepticus. The amount of CEEG to be recorded to detect ESz was reduced by two-thirds, compared to the duration of CEEG taht was actually recorded.

CONCLUSIONS

TERSE allowed accurate time-dependent ESz risk stratification with a high sensitivity for ESz detection, which could substantially reduce the amount of CEEG to be recorded and reviewed, if applied prospectively in clinical practice.

SIGNIFICANCE

Time-dependent electro-clinical risk stratification, such as TERSE, could allow more efficient practice of CEEG and its more widespread adoption. Future studies should aim to improve risk stratification in the subgroup of patients with acute brain injury and absence of clinical seizures.

Hyperemia in subarachnoid hemorrhage patients is associated with an increased risk of seizures

The association between impaired brain perfusion, cerebrovascular reactivity status and the risk of ictal events in patients with subarachnoid hemorrhage is unknown. We identified 13 subarachnoid hemorrhage (SAH) patients with seizures and 22 with ictal-interictal continuum (IIC), and compared multimodality physiological recordings to 38 similarly poor-grade SAH patients without ictal activity. We analyzed 10,179 cumulative minutes of seizure and 12,762 cumulative minutes of IIC. Cerebrovascular reactivity (PRx) was not different between subjects with seizures, IIC, or controls. Cerebral perfusion pressure (CPP) was higher in patients with seizures [99 ± 6.5, p = .005] and IIC [97 ± 8.5, p = .007] when compared to controls [89 ± 12.3]. DeltaCPP, defined as actual CPP minus optimal CPP (CPPopt), was also higher in the seizure group [8.3 ± 7.9, p = .0003] and IIC [8.1 ± 10.3, p = .0006] when compared to controls [-0.1 ± 5]. Time spent with supra-optimal CPP was higher in the seizure group [342 ± 213 min/day, p = .002] when compared to controls [154 ± 120 min/day]. In a temporal examination, a supra-optimal CPP preceded increased seizures and IIC in SAH patients, an hour before and continued to increase during the events [p < .0001].

Burden of Epileptiform Activity Predicts Discharge Neurologic Outcomes in Severe Acute Ischemic Stroke

BACKGROUND/OBJECTIVES

Clinical seizures following acute ischemic stroke (AIS) appear to contribute to worse neurologic outcomes. However, the effect of electrographic epileptiform abnormalities (EAs) more broadly is less clear. Here, we evaluate the impact of EAs, including electrographic seizures and periodic and rhythmic patterns, on outcomes in patients with AIS.

METHODS

This is a retrospective study of all patients with AIS aged ≥ 18 years who underwent at least 18 h of continuous electroencephalogram (EEG) monitoring at a single center between 2012 and 2017. EAs were classified according to American Clinical Neurophysiology Society (ACNS) nomenclature and included seizures and periodic and rhythmic patterns. EA burden for each 24-h epoch was defined using the following cutoffs: EA presence, maximum daily burden < 10% versus > 10%, maximum daily burden < 50% versus > 50%, and maximum daily burden using categories from ACNS nomenclature ("rare" < 1%; "occasional" 1-9%; "frequent" 10-49%; "abundant" 50-89%; "continuous" > 90%). Maximum EA frequency for each epoch was dichotomized into ≥ 1.5 Hz versus < 1.5 Hz. Poor neurologic outcome was defined as a modified Rankin Scale score of 4-6 (vs. 0-3 as good outcome) at hospital discharge.

RESULTS

One hundred and forty-three patients met study inclusion criteria. Sixty-seven patients (46.9%) had EAs. One hundred and twenty-four patients (86.7%) had poor outcome. On univariate analysis, the presence of EAs (OR 3.87 [1.27-11.71], p = 0.024) and maximum daily burden > 10% (OR 12.34 [2.34-210], p = 0.001) and > 50% (OR 8.26 [1.34-122], p = 0.035) were associated with worse outcomes. On multivariate analysis, after adjusting for clinical covariates (age, gender, NIHSS, APACHE II, stroke location, stroke treatment, hemorrhagic transformation, Charlson comorbidity index, history of epilepsy), EA presence (OR 5.78 [1.36-24.56], p = 0.017), maximum daily burden > 10% (OR 23.69 [2.43-230.7], p = 0.006), and maximum daily burden > 50% (OR 9.34 [1.01-86.72], p = 0.049) were associated with worse outcomes. After adjusting for covariates, we also found a dose-dependent association between increasing EA burden and increasing probability of poor outcomes (OR 1.89 [1.18-3.03] p = 0.009). We did not find an independent association between EA frequency and outcomes (OR: 4.43 [.98-20.03] p = 0.053). However, the combined effect of increasing EA burden and frequency ≥ 1.5 Hz (EA burden * frequency) was significantly associated with worse outcomes (OR 1.64 [1.03-2.63] p = 0.039).

CONCLUSIONS

Electrographic seizures and periodic and rhythmic patterns in patients with AIS are associated with worse outcomes in a dose-dependent manner. Future studies are needed to assess whether treatment of this EEG activity can improve outcomes.

The PET Sandwich: Using Serial FDG-PET Scans with Interval Burst Suppression to Assess Ictal Components of Disease

BACKGROUND

Determining the cause of refractory seizures and/or interictal continuum (IIC) findings in the critically ill patient remains a challenge. These electrographic abnormalities may represent primary ictal pathology or may instead be driven by an underlying infectious, inflammatory, or neoplastic pathology that requires targeted therapy. In these cases, it is unclear whether escalating antiepileptic therapy will be helpful or harmful. Herein, we report the use of serial [F-18] fluorodeoxyglucose positron emission tomography (FDG-PET) coupled with induced electrographic burst suppression to distinguish between primary and secondary ictal pathologies. We propose that anesthetic suppression of hypermetabolic foci suggests clinical responsiveness to escalating antiepileptic therapy, whereas non-suppressible hypermetabolic foci are suggestive of non-ictal pathologies that likely require multimodal therapy.

METHODS

We describe 6 patients who presented with electrographic findings of seizure or IIC abnormalities, severe neurologic injury, and clinical concern for confounding pathologies. All patients were continuously monitored on video electroencephalography (cvEEG). Five patients underwent at least two sequential FDG-PET scans of the brain: one in a baseline state and the second while under electrographic burst suppression. FDG-avid loci and EEG tracings were compared pre- and post-burst suppression. One patient underwent a single FDG-PET scan while burst-suppressed.

RESULTS

Four patients had initially FDG-avid foci that subsequently resolved with burst suppression. Escalation of antiepileptic therapy in these patients resulted in clinical improvement, suggesting that the foci were related to primary ictal pathology. These included clinical diagnoses of electroclinical status epilepticus, new-onset refractory status epilepticus, stroke-like migraine attacks after radiotherapy, and epilepsy secondary to inflammatory cerebral amyloid angiopathy. Conversely, two patients with high-grade EEG abnormalities had FDG-avid foci that persisted despite burst suppression. The first presented with a poor examination, fever, and concern for encephalitis. Postmortem pathology confirmed suspicion of herpes simplex virus encephalitis. The second patient presented with concern for checkpoint inhibitor-induced autoimmune encephalitis. The persistence of the FDG-avid focus, despite electrographic burst suppression, guided successful treatment through escalation of immunosuppressive therapy.

CONCLUSIONS

In appropriately selected patients, FDG-PET scans while in burst suppression may help dissect the underlying pathophysiologic cause of IIC findings observed on EEG and guide tailored therapy.

Soluble ST2 Is Associated With New Epileptiform Abnormalities Following Nontraumatic Subarachnoid Hemorrhage

Background and Purpose- We evaluated the association between 2 types of predictors of delayed cerebral ischemia after nontraumatic subarachnoid hemorrhage, including biomarkers of the innate immune response and neurophysiologic changes on continuous electroencephalography. Methods- We studied subarachnoid hemorrhage patients that had at least 72 hours of continuous electroencephalography and blood samples collected within the first 5 days of symptom onset. We measured inflammatory biomarkers previously associated with delayed cerebral ischemia and functional outcome, including soluble ST2 (sST2), IL-6 (interleukin-6), and CRP (C-reactive protein). Serial plasma samples and cerebrospinal fluid sST2 levels were available in a subgroup of patients. Neurophysiologic changes were categorized into new or worsening epileptiform abnormalities (EAs) or new background deterioration. The association of biomarkers with neurophysiologic changes were evaluated using the Wilcoxon rank-sum test. Plasma and cerebrospinal fluid sST2 were further examined longitudinally using repeated measures mixed-effects models. Results- Forty-six patients met inclusion criteria. Seventeen (37%) patients developed new or worsening EAs, 21 (46%) developed new background deterioration, and 8 (17%) developed neither. Early (day, 0-5) plasma sST2 levels were higher among patients with new or worsening EAs (median 115 ng/mL [interquartile range, 73.8-197]) versus those without (74.7 ng/mL [interquartile range, 44.8-102]; P=0.024). Plasma sST2 levels were similar between patients with or without new background deterioration. Repeated measures mixed-effects modeling that adjusted for admission risk factors showed that the association with new or worsening EAs remained independent for both plasma sST2 (β=0.41 [95% CI, 0.09-0.73]; P=0.01) and cerebrospinal fluid sST2 (β=0.97 [95% CI, 0.14-1.8]; P=0.021). IL-6 and CRP were not associated with new background deterioration or with new or worsening EAs. Conclusions- In patients admitted with subarachnoid hemorrhage, sST2 level was associated with new or worsening EAs but not new background deterioration. This association may identify a link between a specific innate immune response pathway and continuous electroencephalography abnormalities in the pathogenesis of secondary brain injury after subarachnoid hemorrhage.

Predictive Accuracy of Alpha-Delta Ratio on Quantitative Electroencephalography for Delayed Cerebral Ischemia in Patients with Aneurysmal Subarachnoid Hemorrhage: Meta-Analysis

OBJECTIVE

Delayed cerebral ischemia (DCI) is significantly related to death and unfavorable functional outcome in patients with aneurysmal subarachnoid hemorrhage (SAH). The association between alpha-delta ratio (ADR) on quantitative electroencephalography (EEG) and DCI has been reported in several previous studies, but their results are conflicting. This meta-analysis was conducted to assess the accuracy of ADR for DCI prediction in patients with aneurysmal SAH.

METHODS

PubMed and Embase were systematically searched for related records. Study selection and data collection were completed by 2 investigators. Sensitivity, specificity, and their 95% confidence intervals (CIs) were pooled. A summary receiver operating characteristic curve was plotted to show the pooled accuracy. Deeks funnel plot was used to evaluate publication bias.

RESULTS

Five studies were included in this meta-analysis. The pooled sensitivity and specificity of worsening ADR for DCI prediction in patients with aneurysmal SAH were 0.83 (95% CI 0.44-0.97) and 0.74 (95% CI 0.50-0.89), respectively. In addition, the area under the summary receiver operating characteristic curve was 0.84 (95% CI 0.81-0.87). No obvious publication bias was found using Deeks funnel plot (P = 0.29).

CONCLUSIONS

Worsening ADR on quantitative EEG is a reliable predictor of DCI in patients with aneurysmal SAH. Further studies are still needed to confirm the role of quantitative EEG in DCI prediction.

Ictal-Interictal Continuum

The term "ictal-interictal" continuum has seen wide adoption in the critical care EEG domain, referring to the presence of abnormal periodic activity on the scalp EEG variably associated with seizures. The historical origin of the ictal-interictal continuum concept is discussed with a review of known and surmised physiological mechanisms for their origin and relationship to seizures. Therapeutic approaches to patients exhibiting ictal-interictal continuum EEG patterns are reviewed, and some open scientific questions highlighted. Further understanding of the ictal-interictal continuum is likely to significantly improve the care of the critically ill neurological patient.

Effect of epileptiform abnormality burden on neurologic outcome and antiepileptic drug management after subarachnoid hemorrhage

OBJECTIVE

To quantify the burden of epileptiform abnormalities (EAs) including seizures, periodic and rhythmic activity, and sporadic discharges in patients with aneurysmal subarachnoid hemorrhage (aSAH), and assess the effect of EA burden and treatment on outcomes.

METHODS

Retrospective analysis of 136 high-grade aSAH patients. EAs were defined using the American Clinical Neurophysiology Society nomenclature. Burden was defined as prevalence of <1%, 1-9%, 10-49%, 50-89%, and >90% for each 18-24 hour epoch. Our outcome measure was 3-month Glasgow Outcome Score.

RESULTS

47.8% patients had EAs. After adjusting for clinical covariates EA burden on first day of recording and maximum daily burden were associated with worse outcomes. Patients with higher EA burden were more likely to be treated with anti-epileptic drugs (AEDs) beyond the standard prophylactic protocol. There was no difference in outcomes between patients continued on AEDs beyond standard prophylaxis compared to those who were not.

CONCLUSIONS

Higher burden of EAs in aSAH independently predicts worse outcome. Although nearly half of these patients received treatment, our data suggest current AED management practices may not influence outcome.

SIGNIFICANCE

EA burden predicts worse outcomes and may serve as a target for prospective interventional controlled studies to directly assess the impact of AEDs, and create evidence-based treatment protocols.

Diagnostic accuracy of quantitative EEG to detect delayed cerebral ischemia after subarachnoid hemorrhage: A preliminary study

OBJECTIVE

Delayed cerebral ischemia (DCI) is the most important and preventable morbidity cause after subarachnoid hemorrhage (SAH). Therefore, DCI early detection is a major challenge. Yet, neurological examination can be unreliable in poor grade SAH patients. EEG provides information from most superficial cortical area, with ischemia-related changes. This study aims at defining an alpha-theta/delta (AT/D) ratio decrease thresholds to detect DCI.

METHODS

We used EEG with a montage matching vascular territories (right and left anterior central and posterior) and compared them to follow-up brain imaging.

RESULTS

15 SAH patients (Fischer ≥ 3, World Federation of Neurological Surgeons scale ≥4, 9 DCI) were monitored during 6.4 [4-8] days (min = 2d, max = 13d). AT/D changes could follow three different patterns: (1) prolonged or (2) transient decrease and (3) no decrease or progressive increase. A regional 30% decrease outlasting 3.7 h reached 100% sensitivity and 88.9% specificity to detect DCI. Only 22.6% were in a zone of uncertain diagnosis (3.7-8.04 h). These prolonged decreases, with a loss of transient changes, started in cortical areas evolving toward DCI, and preceded intracranial changes when available.

CONCLUSION

Although this study has a small sample size, prolonged AT/D decrease seems to be a reliable biomarker of DCI.

SIGNIFICANCE

cEEG changes are likely to precede cerebral infarction and could be useful at the bedside to detect DCI before irreversible damage.

Ictal Interictal Continuum Patterns

PURPOSE OF REVIEW

To present data available on the epidemiology and significance of rhythmic and periodic patterns that lie on the ictal interictal continuum and propose an algorithm for the clinical approach to patients exhibiting these patterns.

RECENT FINDINGS

There is accumulating evidence on the prognostic implications of various rhythmic and periodic patterns in the critically ill population. These patterns are not only associated with increased seizure risk but have also been associated with worse outcome and increased long-term risk of epilepsy in recent studies. There is emerging evidence suggesting that certain EEG features as well as ancillary studies including serum, neuroimaging, and invasive multimodality monitory can assist in the risk stratification of neuronal injury associated with these patterns, allowing for a targeted approach to these patterns. We present a case illustrating the clinical nuances of these patterns. We propose an algorithm for a personalized and targeted approach to ictal interictal patterns based on risk stratification according to clinical, EEG, imaging, and invasive monitoring markers.