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Identifying and treating critically ill patients with seizures can be challenging. In this article, the authors review the available data on patient populations at risk, seizure prognostication with tools such as 2HELPS2B, electrographic seizures and the various ictal-interictal continuum patterns with their latest definitions and associated risks, ancillary testing such as imaging studies, serum biomarkers, and invasive multimodal monitoring. They also illustrate 5 different patient scenarios, their treatment and outcomes, and propose recommendations for targeted treatment of electrographic seizures in critically ill patients.

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 abnormalities (EA) on continuous electroencephalography (cEEG) are associated with increased risk of acute seizures; however, data on their association with development of long-term epilepsy are limited. We aimed to investigate the association of EA in patients with acute brain injury (ABI): ischemic or hemorrhagic stroke, traumatic brain injury, encephalitis, or posterior reversible encephalopathy syndrome, and subsequent development of epilepsy. This was a retrospective, single-center study of patients with ABI who had at least 6 hours of cEEG during the index admission between 1/1/2017 and 12/31/2018 and at least 12 months of follow-up. We compared patients with EAs; defined as lateralized periodic discharges (LPDs), lateralized rhythmic delta activity (LRDA), generalized periodic discharges (GPDs), and sporadic interictal epileptiform discharges (sIEDs) to patients without EAs on cEEG. The primary outcome was the new development of epilepsy, defined as the occurrence of spontaneous clinical seizures following hospital discharge. Secondary outcomes included time to development of epilepsy and use of anti-seizure medications (ASMs) at the time of last follow-up visit. One hundred and one patients with ABI met study inclusion criteria. Thirty-one patients (30.7%) had EAs on cEEG. The median (IQR) time to cEEG was 2 (1–5) days. During a median (IQR) follow-up period of 19.1 (16.2–24.3) months, 25.7% of patients developed epilepsy; the percentage of patients who developed epilepsy was higher in those with EAs compared to those without EAs (41.9% vs. 18.6%, p = 0.025). Patients with EAs were more likely to be continued on ASMs during follow-up compared to patients without EAs (67.7% vs. 38.6%, p = 0.009). Using multivariable Cox regression analysis, after adjusting for age, mental status, electrographic seizures on cEEG, sex, ABI etiology, and ASM treatment on discharge, patients with EAs had a significantly increased risk of developing epilepsy compared to patients without EA (hazard ratio 3.39; 95% CI 1.39–8.26; p = 0.007). EAs on cEEG in patients with ABI are associated with a greater than three-fold increased risk of new-onset epilepsy. cEEG findings in ABI may therefore be a useful risk stratification tool for assessing long-term risk of seizures and serve as a biomarker for new-onset epilepsy.

BackgroundPost-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1).MethodsWe performed a multicentre, retrospective case–control study of patients with TBI. 63 PTE1patients were matched with 63 non-PTE1patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.ResultsIn the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)).ConclusionsEpileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

BACKGROUND AND OBJECTIVES: The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as “ictal-interictal-injury continuum” (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC. METHODS: This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as “seizure (SZ),” “lateralized periodic discharges (LPDs),” “generalized periodic discharges (GPDs),” “lateralized rhythmic delta activity (LRDA),” “generalized rhythmic delta activity (GRDA),” or “other.” EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability. RESULTS: Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Image: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Image: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds. DISCUSSION: Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

To assess variability in interpretation of electroencephalogram (EEG) background activity and qualitative grading of cerebral dysfunction based on EEG findings, including which EEG features are deemed most important in this determination.A web-based survey (Qualtrics) was disseminated to electroencephalographers practicing in institutions participating in the Critical Care EEG Monitoring Research Consortium between May 2017 and August 2018. Respondents answered 12 questions pertaining to their training and EEG interpretation practices and graded 40 EEG segments (15-second epochs depicting patients' most stimulated state) using a 6-grade scale. Fleiss' Kappa statistic evaluated interrater agreement.Of 110 respondents, 78.2% were attending electroencephalographers with a mean of 8.3 years of experience beyond training. Despite 83% supporting the need for a standardized approach to interpreting the degree of dysfunction on EEG, only 13.6% used a previously published or an institutional grading scale. The overall interrater agreement was fair (k = 0.35). Having Critical Care EEG Monitoring Research Consortium nomenclature certification (40.9%) or EEG board certification (70%) did not improve interrater agreement (k = 0.26). Predominant awake frequencies and posterior dominant rhythm were ranked as the most important variables in grading background dysfunction, followed by continuity and reactivity.Despite the preference for a standardized grading scale for background EEG interpretation, the lack of interrater agreement on levels of dysfunction even among experienced academic electroencephalographers unveils a barrier to the widespread use of EEG as a clinical and research neuromonitoring tool. There was reasonable agreement on the features that are most important in this determination. A standardized approach to grading cerebral dysfunction, currently used by the authors, and based on this work, is proposed.

Effective treatment options for patients with life-threatening neurological disorders are limited. To address this unmet need, high-impact translational research is essential for the advancement and development of novel therapeutic approaches in neurocritical care. “The Neurotherapeutics Symposium 2019—Neurological Emergencies” conference, held in Rochester, New York, in June 2019, was designed to accelerate translation of neurocritical care research via transdisciplinary team science and diversity enhancement. Diversity excellence in the neuroscience workforce brings innovative and creative perspectives, and team science broadens the scientific approach by incorporating views from multiple stakeholders. Both are essential components needed to address complex scientific questions. Under represented minorities and women were involved in the organization of the conference and accounted for 30–40% of speakers, moderators, and attendees. Participants represented a diverse group of stakeholders committed to translational research. Topics discussed at the conference included acute ischemic and hemorrhagic strokes, neurogenic respiratory dysregulation, seizures and status epilepticus, brain telemetry, neuroprognostication, disorders of consciousness, and multimodal monitoring. In these proceedings, we summarize the topics covered at the conference and suggest the groundwork for future high-yield research in neurologic emergencies.

Purpose Continuous EEG can potentially be used as real-time brain telemetry for the early detection of neurologic decline. Scant literature on EEG changes related to elevated intracranial pressure (ICP) limits its use in this context. Methods Retrospective, observational case series of patients in whom we noted EEG changes correlating with a clinical concern for elevated ICP, measured or unmeasured. Results We noted EEG changes of varying severity and duration correlating with either measured or unmeasured clinical concern for elevated ICP. In two patients with recurrent transient unresponsiveness (presumed from plateau waves), generalized rhythmic delta activity and attenuation of fast activity occurred 30 minutes before a clinical change. Elevated ICP in two patients, one related to progressive mass effect from infarctions, and the other to dialysis, correlated with generalized slowing and attenuation of fast activity up to 24 hours before clinical deterioration, leading to diffuse suppression. Two patients with intraventricular hemorrhage had cyclic patterns at ∼1 per minute and ∼6 per minute (similar frequency to described frequency of Lundberg B and C waves, respectively). Conclusions Cyclic patterns and varying degrees of slowing and attenuation often preceded clinical deterioration associated with intracranial hypertension. Future systematic studies of EEG changes in this setting will facilitate early and noninvasive detection of elevated ICP.

The corneal reflex assesses the integrity of the trigeminal and facial cranial nerves. This brainstem reflex is fundamental in neuroprognostication after cardiac arrest and in brain death determination. We sought to investigate corneal reflex testing methods among neurologists and general critical care providers in the context of neuroprognostication following cardiac arrest. This is an international cross-sectional study disseminated to members of the Neurocritical Care Society, Society of Critical Care Medicine, and American Academy of Neurology. We utilized an open Web-based survey (Qualtrics®, Provo, UT, USA) to disseminate 26 questions regarding neuroprognostication practices following cardiac arrest, in which 3 questions pertained to corneal reflex testing. Descriptive statistical measures were used, and subgroup analyses performed between neurologists and non-neurologists. Questions were not mandatory; therefore, the percentages were relative to the number of respondents for each question. There were 959 respondents in total. Physicians comprised 85.1% of practitioners (762 out of 895), of which 55% (419) identified themselves as non-neurologists and 45% (343) as neurologists. Among physicians, 85.9% (608 out of 708) deemed corneal reflex relevant for prognostication following cardiac arrest (neurologists 84.4% versus non-neurologists 87.0%). A variety of techniques were employed for corneal reflex testing, the most common being “light cotton touch” (59.2%), followed by “cotton-tipped applicator with pressure” (23.9%), “saline or water squirt” (15.9%), and “puff of air” (1.0%). There were no significant differences in the methods for testing between neurologists and non-neurologists (p = 0.52). The location of stimulus application was variable, and 26.1% of physicians (148/567) apply the stimulus on the temporal conjunctiva rather than on the cornea itself. Corneal reflex testing remains a cornerstone of the coma exam and is commonly used in neuroprognostication of unconscious cardiac arrest survivors and in brain death determination. A wide variability of techniques is noted among practitioners, including some that may provide suboptimal stimulation of corneal nerve endings. Imprecise testing in this setting may lead to inaccuracies in critical settings, which carries significant consequences such as guiding decisions of care limitations, misdiagnosis of brain death, and loss of public trust.

Objective The objective of the study was to compare the performance of intravenous (IV) lorazepam (IVL) and intranasal midazolam (INM) for seizure termination and prevention of seizure clusters in adults admitted to the epilepsy monitoring unit (EMU) in whom seizures were captured on continuous video-electroencephalogram. Methods Retrospective cohort of consecutive adults (≥ 18 years) with epilepsy admitted to the EMU at a single tertiary academic center, who experienced epileptic seizures (confirmed electroencephalographically) and required rescue therapy. The study spanned from January 2015 until December 2016, which included one year before and one year after transitioning from IVL to INM as the standard rescue therapy at our institution. Results A total of 50 subjects received rescue therapy and were included in the analysis. In the first year, out of 216 patients with epilepsy admitted to the EMU, 27 (13%) received IVL; in the second year, 23/217 (11%) received INM. There were no differences in baseline characteristics and markers of epilepsy severity, the median duration of index seizure (1.7 min [interquartile range (IQR): 1.1–2.7] in IVL vs. 2.0 min [IQR: 1.5–2.6] in INM group, p = 0.20), or in the number of subjects requiring repeat benzodiazepine administrations (IVL 8/27 [29.6%] vs. INM 7/23 [30.4%], p = 0.95). There were no differences in the median number of recurrent seizures in 24 h (1 [IQR: 1–3] in IVL vs. 2 [IQR: 1–4] in INM, p = 0.27), occurrence of status epilepticus (IVL 4/27 [14.8%] subjects vs. INM 1/23 [4.3%] subjects, p = 0.36), incidence of seizure clusters (IVL 8/27 [29.6%] subjects vs. INM 7/23 [30.4%] subjects, p = 0.95), need for transfer to an intensive care unit (ICU), or other adverse events. Significance In our retrospective study, INM was comparable with IVL for seizure termination and prevention of seizure clusters in the adult EMU. Intranasal midazolam circumvents the need for IV access to be maintained throughout hospitalization and is an attractive alternative to IVL as a rescue therapy in this setting. Ideally, future large, prospective, randomized, and double blind studies are needed to confirm these findings.

Conventional understanding of acute onset language deficits indicates that fluent aphasias are due to perisylvian lesions in the dominant hemisphere, most often in the setting of acute stroke. Case studies and retrospective analyses, however, suggest the need to keep ictal phenomena as an alternative diagnostic possibility. The following case illustrates an epileptic mechanism of sudden onset fluent aphasia mimicking an acute stroke presentation. We utilize the case to illustrate means by which to differentiate stroke versus ictal etiology by way of electroencephalography/response to antiseizure drugs as well as perfusion/diffusion imaging. We review the literature case reports to demonstrate that isolated fluent aphasia typically localizes to left-hemispheric, temporal foci. Finally, we provide a brief synthesis of potential neurologic mechanisms by which left temporal lesions may cause fluent aphasia.

Objectives: Seizures and seizure-like electroencephalography (EEG) patterns, collectively referred to as “ictal interictal injury continuum” (IIIC) patterns, are commonly encountered in critically ill patients. Automated detection is important for patient care and to enable research. However, training accurate detectors requires a large labeled dataset. Active Learning (AL) may help select informative examples to label, but the optimal AL approach remains unclear. Methods: We assembled >200,000 h of EEG from 1,454 hospitalized patients. From these, we collected 9,808 labeled and 120,000 unlabeled 10-second EEG segments. Labels included 6 IIIC patterns. In each AL iteration, a Dense-Net Convolutional Neural Network (CNN) learned vector representations for EEG segments using available labels, which were used to create a 2D embedding map. Nearest-neighbor label spreading within the embedding map was used to create additional pseudo-labeled data. A second Dense-Net was trained using real- and pseudo-labels. We evaluated several strategies for selecting candidate points for experts to label next. Finally, we compared two methods for class balancing within queries: standard balanced-based querying (SBBQ), and high confidence spread-based balanced querying (HCSBBQ). Results: Our results show: 1) Label spreading increased convergence speed for AL. 2) All query criteria produced similar results to random sampling. 3) HCSBBQ query balancing performed best. Using label spreading and HCSBBQ query balancing, we were able to train models approaching expert-level performance across all pattern categories after obtaining ∼7000 expert labels. Conclusion: Our results provide guidance regarding the use of AL to efficiently label large EEG datasets in critically ill patients., SCOPUS: ar.j, info:eu-repo/semantics/published

PURPOSE: Studies examining seizures (Szs) and epileptiform abnormalities (EAs) using continuous EEG in acute ischemic stroke (AIS) are limited. Therefore, we aimed to describe the prevalence of Sz and EA in AIS, its impact on anti-Sz drug management, and association with discharge outcomes. METHODS: The study included 132 patients with AIS who underwent continuous EEG monitoring >6 hours. Continuous EEG was reviewed for background, Sz and EA (lateralized periodic discharges [LPD], generalized periodic discharges, lateralized rhythmic delta activity, and sporadic epileptiform discharges). Relevant clinical, demographic, and imaging factors were abstracted to identify risk factors for Sz and EA. Outcomes included all-cause mortality, functional outcome at discharge (good outcome as modified Rankin scale of 0–2 and poor outcome as modified Rankin scale of 3–6) and changes to anti-Sz drugs (escalation or de-escalation). RESULTS: The frequency of Sz was 7.6%, and EA was 37.9%. Patients with Sz or EA were more likely to have cortical involvement (84.6% vs. 67.5% P = 0.028). Among the EAs, the presence of LPD was associated with an increased risk of Sz (25.9% in LPD vs. 2.9% without LPD, P = 0.001). Overall, 21.2% patients had anti-Sz drug changes because of continuous EEG findings, 16.7% escalation and 4.5% de-escalation. The presence of EA or Sz was not associated with in-hospital mortality or discharge functional outcomes. CONCLUSIONS: Despite the high incidence of EA, the rate of Sz in AIS is relatively lower and is associated with the presence of LPDs. These continuous EEG findings resulted in anti-Sz drug changes in one-fifth of the cohort. Epileptiform abnormality and Sz did not affect mortality or discharge functional outcomes.

Background and Objective: Seizures are common after traumatic brain injury (TBI), aneurysmal subarachnoid hemorrhage (aSAH), subdural hematoma (SDH), and non-traumatic intraparenchymal hemorrhage (IPH)—collectively defined herein as acute brain injury (ABI). Most seizures in ABI are subclinical, meaning that they are only detectable with EEG. A method is required to identify patients at greatest risk of seizures and thereby in need of prolonged continuous EEG monitoring. 2HELPS2B is a simple point system developed to address this need. 2HELPS2B estimates seizure risk for hospitalized patients using five EEG findings and one clinical finding (pre-EEG seizure). The initial 2HELPS2B study did not specifically assess the ABI subpopulation. In this study, we aim to validate the 2HELPS2B score in ABI and determine its relative predictive accuracy compared to a broader set of clinical and electrographic factors. Methods: We queried the Critical Care EEG Monitoring Research Consortium database for ABI patients age ≥ 18 with > 6 h of continuous EEG monitoring; data were collected between February 2013 and November 2018. The primary outcome was electrographic seizure. Clinical factors considered were age, coma, encephalopathy, ABI subtype, and acute suspected or confirmed pre-EEG clinical seizure. Electrographic factors included 18 EEG findings. Predictive accuracy was assessed using a machine-learning paradigm with area under the receiver operator characteristic (ROC) curve as the primary outcome metric. Three models (clinical factors alone, EEG factors alone, EEG and clinical factors combined) were generated using elastic-net logistic regression. Models were compared to each other and to the 2HELPS2B model. All models were evaluated by calculating the area under the curve (AUC) of a ROC analysis and then compared using permutation testing of AUC with bootstrapping to generate confidence intervals. Results: A total of 1528 ABI patients were included. Total seizure incidence was 13.9%. Seizure incidence among ABI subtype varied: IPH 17.2%, SDH 19.1%, aSAH 7.6%, TBI 9.2%. Age ≥ 65 (p = 0.015) and pre-cEEG acute clinical seizure (p < 0.001) positively affected seizure incidence. Clinical factors AUC = 0.65 [95% CI 0.60–0.71], EEG factors AUC = 0.82 [95% CI 0.77–0.87], and EEG and clinical factors combined AUC = 0.84 [95% CI 0.80–0.88]. 2HELPS2B AUC = 0.81 [95% CI 0.76–0.85]. The 2HELPS2B AUC did not differ from EEG factors (p = 0.51), or EEG and clinical factors combined (p = 0.23), but was superior to clinical factors alone (p < 0.001). Conclusions: Accurate seizure risk forecasting in ABI requires the assessment of EEG markers of pathologic electro-cerebral activity (e.g. sporadic epileptiform discharges and lateralized periodic discharges). The 2HELPS2B score is a reliable and simple method to quantify these EEG findings and their associated risk of seizure., SCOPUS: ar.j, info:eu-repo/semantics/published

Epileptiform abnormalities (EA) on continuous electroencephalography (cEEG) are associated with increased risk of acute seizures; however, data on their association with development of long-term epilepsy are limited. We aimed to investigate the association of EA in patients with acute brain injury (ABI): ischemic or hemorrhagic stroke, traumatic brain injury, encephalitis, or posterior reversible encephalopathy syndrome, and subsequent development of epilepsy.This was a retrospective, single-center study of patients with ABI who had at least 6 hours of cEEG during the index admission between 1/1/2017 and 12/31/2018 and at least 12 months of follow-up. We compared patients with EAs; defined as lateralized periodic discharges (LPDs), lateralized rhythmic delta activity (LRDA), generalized periodic discharges (GPDs), and sporadic interictal epileptiform discharges (sIEDs) to patients without EAs on cEEG. The primary outcome was the new development of epilepsy, defined as the occurrence of spontaneous clinical seizures following hospital discharge. Secondary outcomes included time to development of epilepsy and use of anti-seizure medications (ASMs) at the time of last follow-up visit.One hundred and one patients with ABI met study inclusion criteria. Thirty-one patients (30.7%) had EAs on cEEG. The median (IQR) time to cEEG was 2 (1-5) days. During a median (IQR) follow-up period of 19.1 (16.2-24.3) months, 25.7% of patients developed epilepsy; the percentage of patients who developed epilepsy was higher in those with EAs compared to those without EAs (41.9% vs. 18.6%, p = 0.025). Patients with EAs were more likely to be continued on ASMs during follow-up compared to patients without EAs (67.7% vs. 38.6%, p = 0.009). Using multivariable Cox regression analysis, after adjusting for age, mental status, electrographic seizures on cEEG, sex, ABI etiology, and ASM treatment on discharge, patients with EAs had a significantly increased risk of developing epilepsy compared to patients without EA (hazard ratio 3.39; 95% CI 1.39-8.26; p = 0.007).EAs on cEEG in patients with ABI are associated with a greater than three-fold increased risk of new-onset epilepsy. cEEG findings in ABI may therefore be a useful risk stratification tool for assessing long-term risk of seizures and serve as a biomarker for new-onset epilepsy.

Objectives To compare electrographic seizures, hyperexcitable patterns, and clinical outcomes in lobar and deep intraparenchymal hemorrhage. Additionally, to characterize electrographic seizure and hyperexcitable pattern predictors in each group and determine seizure risk with thalamic involvement. Design Retrospective cohort study. Setting Tertiary academic medical center. Patients Consecutive adult patients with nontraumatic intraparenchymal hemorrhage undergoing continuous electroencephalography at our center between January 2013 and December 2016. Interventions Not applicable. Measurements and main results Based on head CT closest to the initial continuous electroencephalography session, we classified intraparenchymal hemorrhage as isolated deep (no insular, subarachnoid, subdural extension) or lobar. Hyperexcitable patterns included the following: periodic discharges, spike-wave complexes, any rhythmic delta other than generalized. We used Fisher exact test for categorical and Mann-Whitney U test for continuous variables. Multivariable regression identified predictors of electrographic seizures, hyperexcitable patterns, and poor outcomes (score of 1-2 on Glasgow Outcome Scale) in lobar intraparenchymal hemorrhage. The cohort comprised of 128 patients, 88 lobar, and 40 deep intraparenchymal hemorrhage. Electrographic seizures occurred in 17% of lobar and 5% of deep intraparenchymal hemorrhage (p = 0.09). Hyperexcitable patterns were more frequent in the lobar group (44.3% vs 17.5%; p = 0.005). In multivariable analyses in the lobar group, lateralized rhythmic delta activity predicted electrographic seizures (odds ratio, 6.24; CI, 1.49-26.08; p = 0.012); insular involvement predicted hyperexcitable patterns (odds ratio, 4.88; CI, 1.36-17.57; p = 0.015); coma, temporal lobe involvement, intraparenchymal hemorrhage volume, and electrographic seizures predicted poor outcome. Thalamic involvement did not affect electrographic seizures or hyperexcitable patterns in either group. Conclusions Electrographic seizures are frequent in lobar intraparenchymal hemorrhage, occurring in one in six monitored patients, as opposed to only 5% in isolated deep intraparenchymal hemorrhage not extending to cortex/insula, subarachnoid, or subdural spaces. Patients with lobar intraparenchymal hemorrhage and lateralized rhythmic delta activity were six times as likely to have electrographic seizures, which were associated with 5.47 higher odds of a poor outcome. Coma, temporal lobe involvement, hematoma volume, and electrographic seizures predicted poor outcome in lobar intraparenchymal hemorrhage.

Seizures are common after traumatic brain injury (TBI), aneurysmal subarachnoid hemorrhage (aSAH), subdural hematoma (SDH), and non-traumatic intraparenchymal hemorrhage (IPH)-collectively defined herein as acute brain injury (ABI). Most seizures in ABI are subclinical, meaning that they are only detectable with EEG. A method is required to identify patients at greatest risk of seizures and thereby in need of prolonged continuous EEG monitoring. 2HELPS2B is a simple point system developed to address this need. 2HELPS2B estimates seizure risk for hospitalized patients using five EEG findings and one clinical finding (pre-EEG seizure). The initial 2HELPS2B study did not specifically assess the ABI subpopulation. In this study, we aim to validate the 2HELPS2B score in ABI and determine its relative predictive accuracy compared to a broader set of clinical and electrographic factors.We queried the Critical Care EEG Monitoring Research Consortium database for ABI patients age ≥ 18 with 6 h of continuous EEG monitoring; data were collected between February 2013 and November 2018. The primary outcome was electrographic seizure. Clinical factors considered were age, coma, encephalopathy, ABI subtype, and acute suspected or confirmed pre-EEG clinical seizure. Electrographic factors included 18 EEG findings. Predictive accuracy was assessed using a machine-learning paradigm with area under the receiver operator characteristic (ROC) curve as the primary outcome metric. Three models (clinical factors alone, EEG factors alone, EEG and clinical factors combined) were generated using elastic-net logistic regression. Models were compared to each other and to the 2HELPS2B model. All models were evaluated by calculating the area under the curve (AUC) of a ROC analysis and then compared using permutation testing of AUC with bootstrapping to generate confidence intervals.A total of 1528 ABI patients were included. Total seizure incidence was 13.9%. Seizure incidence among ABI subtype varied: IPH 17.2%, SDH 19.1%, aSAH 7.6%, TBI 9.2%. Age ≥ 65 (p = 0.015) and pre-cEEG acute clinical seizure (p 0.001) positively affected seizure incidence. Clinical factors AUC = 0.65 [95% CI 0.60-0.71], EEG factors AUC = 0.82 [95% CI 0.77-0.87], and EEG and clinical factors combined AUC = 0.84 [95% CI 0.80-0.88]. 2HELPS2B AUC = 0.81 [95% CI 0.76-0.85]. The 2HELPS2B AUC did not differ from EEG factors (p = 0.51), or EEG and clinical factors combined (p = 0.23), but was superior to clinical factors alone (p 0.001).Accurate seizure risk forecasting in ABI requires the assessment of EEG markers of pathologic electro-cerebral activity (e.g., sporadic epileptiform discharges and lateralized periodic discharges). The 2HELPS2B score is a reliable and simple method to quantify these EEG findings and their associated risk of seizure.

Objective To determine the incidence, causes, predictors, and costs of 30-day readmissions in patients admitted with status epilepticus (SE) from a large representative United States (US) population. Methods Adults (age ≥18 years) hospitalized with a primary diagnosis of SE (International Classification of Diseases-Ninth Revision-CM codes 345.2 or 345.3) between January 2013 and September 2015 were identified using the Nationwide Readmissions Database. A multivariable logistic regression model was used to identify predictors of 30-day readmissions. Results Of 42,232 patients with index SE, 6372 (15.0%) were readmitted within 30 days. In the multivariable analysis, intracranial hemorrhage (odds ratio, 1.56; 95% confidence interval, 1.12–2.18), psychosis (1.26 95%, 1.05–1.50), diabetes mellitus (1.12, 95%, 1.00–1.25), chronic kidney disease (1.50, 95%, 1.31–1.72), chronic liver disease (1.51; 95%, 1.24–1.84), >3 Elixhauser comorbidities (1.18; 95%, 1.06–1.31), length of stay >4 days during index hospitalization (1.41; 95%, 1.28–1.56) and discharge to skilled nursing facility (SNF) (1.14; 95%, 1.01–1.28) were independent predictors of 30-day readmission. The most common reason for readmission was seizures (45.1%). Median length of stay and costs of readmission were 4 days (interquartile range [IQR], 2–7 days) and $7882 (IQR, $4649–$15,012), respectively. Conclusion Thirty-day readmissions after SE occurs in 15% of patients, the majority of which were due to seizures. Readmitted patients are more likely to have multiple comorbidities, a longer length of stay, and discharge to SNF. Awareness of these predictors can help identify and target high-risk patients for interventions to reduce readmissions and costs.

Objectives To characterize approaches to neurologic outcome prediction by practitioners who assess prognosis in unconscious cardiac arrest individuals, and assess compliance to available guidelines. Design International cross-sectional study. Setting We administered a web-based survey to members of Neurocritical Care Society, Society of Critical Care Medicine, and American Academy of Neurology who manage unconscious cardiac arrest patients to characterize practitioner demographics and current neuroprognostic practice patterns. Subjects Physicians that are members of aforementioned societies who care for successfully resuscitated cardiac arrest individuals. Interventions Not applicable. Measurements and main results A total of 762 physicians from 22 countries responses were obtained. A significant proportion of respondents used absent corneal reflexes (33.5%) and absent pupillary reflexes (36.2%) at 24 hours, which is earlier than the recommended 72 hours in the standard guidelines. Certain components of the neurologic examination may be overvalued, such as absent motor response or extensor posturing, which 87% of respondents considered being very or critically important prognostic indicators. Respondents continue to rely on myoclonic status epilepticus and neuroimaging, which were favored over median nerve somatosensory evoked potentials for prognostication, although the latter has been demonstrated to have a higher predictive value. Regarding definitive recommendations based on poor neurologic prognosis, most physicians seem to wait until the postarrest timepoints proposed by current guidelines, but up to 25% use premature time windows. Conclusions Neuroprognostic approaches to hypoxic-ischemic encephalopathy vary among physicians and are often not consistent with current guidelines. The overall inconsistency in approaches and deviation from evidence-based recommendations are concerning in this disease state where mortality is so integrally related to outcome prediction.

Importance Seizure risk stratification is needed to boost inpatient seizure detection and to improve continuous electroencephalogram (cEEG) cost-effectiveness. 2HELPS2B can address this need but requires validation. Objective To use an independent cohort to validate the 2HELPS2B score and develop a practical guide for its use. Design, Setting, and Participants This multicenter retrospective medical record review analyzed clinical and EEG data from patients 18 years or older with a clinical indication for cEEG and an EEG duration of 12 hours or longer who were receiving consecutive cEEG at 6 centers from January 2012 to January 2019. 2HELPS2B was evaluated with the validation cohort using the mean calibration error (CAL), a measure of the difference between prediction and actual results. A Kaplan-Meier survival analysis was used to determine the duration of EEG monitoring to achieve a seizure risk of less than 5% based on the 2HELPS2B score calculated on first- hour (screening) EEG. Participants undergoing elective epilepsy monitoring and those who had experienced cardiac arrest were excluded. No participants who met the inclusion criteria were excluded. Main Outcomes and Measures The main outcome was a CAL error of less than 5% in the validation cohort. Results The study included 2111 participants (median age, 51 years; 1113 men [52.7%]; median EEG duration, 48 hours) and the primary outcome was met with a validation cohort CAL error of 4.0% compared with a CAL of 2.7% in the foundational cohort (P = .13). For the 2HELPS2B score calculated on only the first hour of EEG in those without seizures during that hour, the CAL error remained at less than 5.0% at 4.2% and allowed for stratifying patients into low- (2HELPS2B = 0; 25%) groups. Each of the categories had an associated minimum recommended duration of EEG monitoring to achieve at least a less than 5% risk of seizures, a 2HELPS2B score of 0 at 1-hour screening EEG, a 2HELPS2B score of 1 at 12 hours, and a 2HELPS2B score of 2 or greater at 24 hours. Conclusions and Relevance In this study, 2HELPS2B was validated as a clinical tool to aid in seizure detection, clinical communication, and cEEG use in hospitalized patients. In patients without prior clinical seizures, a screening 1-hour EEG that showed no epileptiform findings was an adequate screen. In patients with any highly epileptiform EEG patterns during the first hour of EEG (ie, a 2HELPS2B score of ≥2), at least 24 hours of recording is recommended.

The corneal reflex assesses the integrity of the trigeminal and facial cranial nerves. This brainstem reflex is fundamental in neuroprognostication after cardiac arrest and in brain death determination. We sought to investigate corneal reflex testing methods among neurologists and general critical care providers in the context of neuroprognostication following cardiac arrest.This is an international cross-sectional study disseminated to members of the Neurocritical Care Society, Society of Critical Care Medicine, and American Academy of Neurology. We utilized an open Web-based survey (QualtricsThere were 959 respondents in total. Physicians comprised 85.1% of practitioners (762 out of 895), of which 55% (419) identified themselves as non-neurologists and 45% (343) as neurologists. Among physicians, 85.9% (608 out of 708) deemed corneal reflex relevant for prognostication following cardiac arrest (neurologists 84.4% versus non-neurologists 87.0%). A variety of techniques were employed for corneal reflex testing, the most common being "light cotton touch" (59.2%), followed by "cotton-tipped applicator with pressure" (23.9%), "saline or water squirt" (15.9%), and "puff of air" (1.0%). There were no significant differences in the methods for testing between neurologists and non-neurologists (p = 0.52). The location of stimulus application was variable, and 26.1% of physicians (148/567) apply the stimulus on the temporal conjunctiva rather than on the cornea itself.Corneal reflex testing remains a cornerstone of the coma exam and is commonly used in neuroprognostication of unconscious cardiac arrest survivors and in brain death determination. A wide variability of techniques is noted among practitioners, including some that may provide suboptimal stimulation of corneal nerve endings. Imprecise testing in this setting may lead to inaccuracies in critical settings, which carries significant consequences such as guiding decisions of care limitations, misdiagnosis of brain death, and loss of public trust.

Objective: To systematically examine the electro-clinical characteristics of post anoxic myoclonus (PAM) and their prognostic implications in comatose cardiac arrest (CA) survivors. Methods: Fifty-nine CA survivors who developed myoclonus within 72 h of arrest and underwent continuous EEG monitoring were included in the study. Retrospective chart review was performed for all relevant clinical variables including time of PAM onset (“early onset” when within 24 h) and semiology (multi-focal, facial/ocular, whole body and limbs only). EEG findings including background, reactivity, epileptiform patterns and EEG correlate to myoclonus were reviewed at 6, 12, 24, 48 and 72 h after the return of spontaneous circulation (ROSC). Outcome was categorized as either with recovery of consciousness (Cerebral Performance Category (CPC) 1–3) or without recovery of consciousness (CPC 4–5) at the time of discharge. Results: Seven of the 59 patients (11.9%) regained consciousness, including 6/51 (11.8%) with early onset PAM. Patients with recovery of consciousness had shorter time to ROSC, and were more likely to have preserved brainstem reflexes and normal voltage background at all times. No patient with suppression burst or low voltage background (N = 52) at any point regained consciousness. In the subset where precise electro-clinical correlation was possible, all (5/5) those with recovery of consciousness had multi-focal myoclonus and most (4/5) had midline-maximal spikes over a continuous background. No patient with any other semiology (N = 21) regained consciousness. Conclusions: Early onset PAM is not always associated with lack of recovery of consciousness. EEG can help discriminate between patients who may or may not regain consciousness by the time of hospital discharge., SCOPUS: ar.j, info:eu-repo/semantics/published

To identify the role of acute surgical intervention in the treatment of refractory status epilepticus (RSE). Retrospective review of consecutive patients who underwent epilepsy surgery from 2006 to 2015 was done to identify cases where acute surgical intervention was employed for the treatment of RSE. In addition, the adult and pediatric RSE literature was reviewed for reports of surgical treatment of RSE. Nine patients, aged 20–68 years, with various etiologies were identified to have undergone acute surgical resection for the treatment of RSE, aided by electrocorticography. Patients required aggressive medical therapy with antiepileptic drugs and intravenous anesthetic drugs for 10–54 days and underwent extensive neurodiagnostic testing prior to resective surgery. Eight out of nine patients survived and five patients were seizure-free at the last follow-up. The literature revealed 13 adult and 48 pediatric cases where adequate historical detail was available for review and comparison. We present the largest cohort of consecutive adult patients who underwent resective surgery in the setting of RSE. We also reveal that surgery can be efficacious in aborting status and in some can lead to long-term seizure freedom. Acute surgical intervention is a viable option in prolonged RSE and proper evaluation for such intervention should be conducted, although the timing and type of surgical intervention remain poorly defined.

Objective: To compare machine learning methods for predicting inpatient seizures risk and determine the feasibility of 1-h screening EEG to identify low-risk patients (, SCOPUS: ar.j, info:eu-repo/semantics/published

PRESENTATION A rare infection raging within the brain of a 50-year-old African-American man was impossible to diagnose until after his death. He presented to the emergency department after the acute onset of garbled speech, confusion, right-arm weakness, and right facial droop. His medical history was significant for poorly controlled diabetes mellitus and polysubstance abuse, including intravenous drug abuse. He had never had a stroke, had no sick contacts, and had not traveled recently.

Objective Poststroke dystonia is the second most common movement disorder after chorea and often has a delayed manifestation. Lesions of the contralateral lenticular nucleus, particularly the putamen, have been implicated in the pathogenesis of dystonia. We present an unusual case of rapid onset of focal dystonia of the left upper extremity, which developed after infarction of the right premotor cortex (PMC) and the supplementary motor area (SMA). Method A retrospective chart review of the patient was performed. Results and Conclusion We propose that disruption of the afferents from PMC and SMA in the setting of chronic striatal abnormality can result in acute dystonia due to disinhibition of the thalamocortical circuit.

There has been a substantial increase in the use of continuous electroencephalography (C-EEG) in critically ill patients, most commonly for detection of nonconvulsive seizures. Studies have found that not only patients with primary brain insults but also those with systemic illness are at high risk of developing nonconvulsive status epilepticus (NCSE). The Neurocrit Care Society and The American Clinical Neurophysiology Society have published consensus statements or guidelines on the indications, duration, and technical aspects of EEG monitoring for status epilepticus (SE). Unified criteria for defining NCSE have also been proposed and published. Nevertheless, critically ill patients can have equivocal patterns, not clearly ictal (“ictal” is used to mean an electrographic seizure pattern in this chapter) or interictal, and have been considered to lie on an ictal-interictal continuum. Diagnostic treatment trials with IV benzodiazepines and non-sedating anti-seizure drugs (ASDs) can be helpful to determine if equivocal patterns are contributing to the patient’s impaired mental status or other neurologic deficits. The labor-intensive and time-consuming process of reviewing 24 h of EEG on many patients can be expedited by using tools such as quantitative EEG (Q-EEG) via commercial software packages. Thus far, there is some evidence to suggest that after strokes and head trauma, NCSE may worsen outcomes. Whether C-EEG monitoring and aggressive treatment of these seizures translates into improved patient outcomes is yet to be proven.

Introduction The incidence of electrographic seizures after non-traumatic intraparenchymal hemorrhage (IPH) ranges from 1.7% to 31%. It is unclear if the risk of seizures or hyperexcitable patterns (HEPs: any rhythmic delta activity except generalized, any periodic discharges, or any spike-wave pattern, using ACNS criteria) for deep IPH is similar to lobar, subarachnoid and subdural hemorrhages. We hypothesized that the incidence of seizures or hyperexcitable patterns (SZ or HEPs) in deep IPH is lower than reported, but thalamic involvement may confer higher risk due to its role in physiologic and pathologic rhythmic activity, such as sleep spindles and generalized spike wave discharges. Methods On retrospective review, 45 patients had deep IPH (defined as IPH not involving cortex/juxtacortical regions other than the insula (analyzed separately), with or without intraventricular hemorrhage IVH) and underwent continuous EEG (cEEG) between 1/2013 and 12/2016. Patients with involvement of cortex, subarachnoid or subdural areas were excluded. Age, sex, prior history of epilepsy, clinical seizure at ictus, anti-seizure drugs (ASDs), sedative infusions during EEG and surgical interventions such as ventriculostomy (EVD) or decompressive hemicraniectomy (DHC) were reviewed. The cEEG closest to admission was reviewed for seizures, HEPs, and generalized rhythmic delta activity (GRDA). The head CT in closest proximity to the index cEEG was reviewed for hematoma volume, thalamic involvement and insular involvement. Results Two of 45 patients had SZ, 7/45 had HEPs, 1/45 had both and a total of 8/45 had SZ or HEPs. Of the HEPs , LRDA was seen in 4/8, LPDs in 2/8, both LPDs and LRDA in 1/8. Of those with the lateralized HEPs, 4/7 were contralateral to IPH, 1/7 (14.2%) were bilateral and 2/7 were ipsilateral. Of the 5/7 with HEPs contralateral to the IPH, 2 had an EVD ipsilateral to the HEPs. Patients with SZ or HEPs had significantly higher hematoma volume compared to patients who did not have SZ or HEPs (32.7 ± 19.4 vs 15.4 ± 17.7, p = 0.02). Patients who underwent surgery (DHC/EVD or both) had higher incidence of HEPs or SZ compared to those who did not (7/23, 30.4% vs 1/22, 4.5%, p = 0.047). DHC was associated with significantly higher risk of SZ or HEPs (4/4, 100% vs 4/41, 9.8%, p Conclusion Risk of SZ or HEPs with deep IPH ± IVH was 17.7% and correlated with mean hematoma volume and DHC. The, risk in the absence of a surgical intervention was low (1/22, 4.5%, vs 7/23, 30.4% p = 0.047). Thalamic involvement did not correlate with SZ or HEPs in this small cohort of patients with deep IPH.

Previous work implicating the neuropeptide oxytocin (Oxt) in the neural regulation of aggression in males has been limited. However, there are reports of heightened aggression in Oxt knockout and Oxt receptor (Oxtr) knockout male mice when they are born to null mutant mothers; suggesting that intrauterine exposure to Oxt may be important to normal aggression in adulthood. To explore this, we examined aggression in two lines of Oxtr mice, a total knockout (Oxtr-/-), in which the Oxtr gene is absent from the time of conception, and a predominantly forebrain specific knockout (Oxtr FB/FB), in which the Oxtr gene is not excised until approximately 21-28days postnatally. Aggression was measured in males from both lines, as well as control littermates, using a resident-intruder behavioral test. Consistent with previous reports, male Oxtr-/- mice had elevated levels of aggression relative to controls. Oxtr FB/FB mice on the other hand displayed levels of aggression similar to control animals. In addition, following a resident-intruder test, Oxtr+/+ mice that displayed aggression had less c-fos immunoreactivity in the ventral portion of the lateral septum than those that did not. Further, Oxtr-/- mice had increased c-fos immunoreactivity in the medial amygdala relative to controls. These data suggest that Oxt may play an important role during development in the organization of the neural circuits that underlie aggressive behavior in adulthood, with its absence resulting in heightened aggression.

PurposeTo determine the incidence, predictors, and outcomes of generalized convulsive status epilepticus (GCSE) in traumatic brain injury (TBI) patients.MethodsWe conducted a retrospective cross-sectional study of adult patients with acute TBI using the 2002–2010 Nationwide Inpatient Sample (NIS) database of USA. We used multivariable logistic regression analyses to identify independent predictors of GCSE in patients with TBI and to determine the impact of GCSE on outcomes (in-hospital mortality, length of stay, total hospital charges, and discharge disposition).ResultsAmong 1,457,869 patients hospitalized with TBI, 2315 (0.16%) had GCSE. In-hospital mortality was significantly higher in patients with GCSE (32.5% vs. 9.6%; unadjusted OR 4.54, 95% CI 4.16–4.96; p35 years (OR 2.15; 95% CI 1.87–2.47), CNS infections (OR 4.86; 95% CI 3.70–6.38), anoxic brain injury (OR 9.54; 95% CI 8.10–11.22), and acute ischemic stroke (OR 4.09; 95% CI 3.41–4.87) were independent predictors of GCSE in TBI patients. Epilepsy was an independent negative predictor of GCSE (OR 0.74; 95% CI 0.55–0.99).ConclusionDespite its low incidence, GCSE in TBI patients was associated with worse outcomes with threefold higher in-hospital mortality, prolonged hospitalization, higher hospital charges, and worse discharge disposition. Surprisingly, epilepsy is a negative predictor of GCSE in this population.