Immediate and long-term management practices of acute symptomatic seizures and epileptiform abnormalities: A cross-sectional international survey

OBJECTIVES

Acute symptomatic seizures (ASyS) and epileptiform abnormalities (EAs) on electroencephalography (EEG) are commonly encountered following acute brain injury. Their immediate and long-term management remains poorly investigated. We conducted an international survey to understand their current management.

METHODS

The cross-sectional web-based survey of 21 fixed-response questions was based on a common clinical encounter: convulsive or suspected ASyS following an acute brain injury. Respondents selected the option that best matched their real-world practice. Respondents completing the survey were compared with those who accessed but did not complete it.

RESULTS

A total of 783 individuals (44 countries) accessed the survey; 502 completed it. Almost everyone used anti-seizure medications (ASMs) for secondary prophylaxis after convulsive or electrographic ASyS (95.4% and 97.2%, respectively). ASM dose escalation after convulsive ASyS depends on continuous EEG (cEEG) findings: most often increased after electrographic seizures (78% of respondents), followed by lateralized periodic discharges (LPDs; 41%) and sporadic epileptiform discharges (sEDs; 17.5%). If cEEG is unrevealing, one in five respondents discontinue ASMs after a week. In the absence of convulsive and electrographic ASyS, a large proportion of respondents start ASMs due to LPD (66.7%) and sED (44%) on cEEG. At hospital discharge, most respondents (85%) continue ASM without dose change. The recommended duration of outpatient ASM use is as follows: 1-3 months (36%), 3-6 months (30%), 6-12 months (13%), >12 months (11%). Nearly one-third of respondents utilized ancillary testing before outpatient ASM taper, most commonly (79%) a <2 h EEG. Approximately half of respondents had driving restrictions recommended for 6 months after discharge.

SIGNIFICANCE

ASM use for secondary prophylaxis after convulsive and electrographic ASyS is a universal practice and is continued upon discharge. Outpatient care, particularly the ASM duration, varies significantly. Wide practice heterogeneity in managing acute EAs reflects uncertainty about their significance and management. These results highlight the need for a structured outpatient follow-up and optimized care pathway for patients with ASyS.

Developing a Standardized Approach to Grading the Level of Brain Dysfunction on EEG

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs

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 ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: 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.

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.

Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy

BACKGROUND

Post-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).

METHODS

We performed a multicentre, retrospective case-control study of patients with TBI. 63 PTE1 patients were matched with 63 non-PTE1 patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1 using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.

RESULTS

In the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1 risk 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)).

CONCLUSIONS

Epileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1 prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

Management of epilepsy in older adults: A critical review by the ILAE Task Force on Epilepsy in the elderly

Older adults represent a highly heterogeneous population, with multiple diverse subgroups. Therefore, an individualized approach to treatment is essential to meet the needs of each unique subgroup. Most comparative studies focusing on treatment of epilepsy in older adults have found that levetiracetam has the best chance of long-term seizure freedom. However, there is a lack of studies investigating other newer generation antiseizure medications (ASMs). Although a number of randomized clinical trials have been performed on older adults with epilepsy, the number of participants studied was generally small, and they only investigated short-term efficacy and tolerability. Quality of life as an outcome is often missing but is necessary to understand the effectiveness and possible side effects of treatment. Prognosis needs to move beyond the focus on seizure control to long-term patient-centered outcomes. Dosing studies with newer generation ASMs are needed to understand which treatments are the best in the older adults with different comorbidities. In particular, more high-level evidence is required for older adults with Alzheimer's disease with epilepsy and status epilepticus. Future treatment studies should use greater homogeneity in the inclusion criteria to allow for clearer findings that can be comparable with other studies to build the existing treatment evidence base.

Electrographic Seizures in the Critically Ill

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.

Epileptiform Abnormalities in Acute Ischemic Stroke: Impact on Clinical Management and Outcomes

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.

Deep active learning for Interictal Ictal Injury Continuum EEG patterns

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.

Association of Epileptiform Abnormality on Electroencephalography with Development of Epilepsy After Acute Brain Injury

BACKGROUND/OBJECTIVES

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Proceedings from the Neurotherapeutics Symposium on Neurological Emergencies: Shaping the Future of Neurocritical Care

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.

Nonepileptic Electroencephalographic Correlates of Episodic Increases in Intracranial Pressure

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.

Assessment of the Validity of the 2HELPS2B Score for Inpatient Seizure Risk 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; <5% risk of seizures), medium- (2HELPS2B = 1; 12% risk of seizures), and high-risk (2HELPS2B, ≥2; risk of seizures, >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.

Sudden Onset Fluent Aphasia: Stroke or Seizure?

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.

Validation of the 2HELPS2B Seizure Risk Score in Acute Brain Injury Patients

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.

Neuroprognostication Practices in Postcardiac Arrest Patients: An International Survey of Critical Care Providers

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.

Corneal Reflex Testing in the Evaluation of a Comatose Patient: An Ode to Precise Semiology and Examination Skills

BACKGROUND/OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Comparison of intranasal midazolam versus intravenous lorazepam for seizure termination and prevention of seizure clusters in the adult epilepsy monitoring unit

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.

Comparison of machine learning models for seizure prediction in hospitalized patients

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 (<5% seizures risk in 48 h).

Methods

The Critical Care EEG Monitoring Research Consortium (CCEMRC) multicenter database contains 7716 continuous EEGs (cEEG). Neural networks (NN), elastic net logistic regression (EN), and sparse linear integer model (RiskSLIM) were trained to predict seizures. RiskSLIM was used previously to generate 2HELPS2B model of seizure predictions. Data were divided into training (60% for model fitting) and evaluation (40% for model evaluation) cohorts. Performance was measured using area under the receiver operating curve (AUC), mean risk calibration (CAL), and negative predictive value (NPV). A secondary analysis was performed using Monte Carlo simulation (MCS) to normalize all EEG recordings to 48 h and use only the first hour of EEG as a “screening EEG” to generate predictions.

Results

RiskSLIM recreated the 2HELPS2B model. All models had comparable AUC: evaluation cohort (NN: 0.85, EN: 0.84, 2HELPS2B: 0.83) and MCS (NN: 0.82, EN; 0.82, 2HELPS2B: 0.81) and NPV (absence of seizures in the group that the models predicted to be low risk): evaluation cohort (NN: 97%, EN: 97%, 2HELPS2B: 97%) and MCS (NN: 97%, EN: 99%, 2HELPS2B: 97%). 2HELPS2B model was able to identify the largest proportion of low‐risk patients.

Interpretation

For seizure risk stratification of hospitalized patients, the RiskSLIM generated 2HELPS2B model compares favorably to the complex NN and EN generated models. 2HELPS2B is able to accurately and quickly identify low‐risk patients with only a 1‐h screening EEG.

Electro-clinical characteristics and prognostic significance of post anoxic myoclonus

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.

Frontal Aslant Tract Abnormality on Diffusion Tensor Imaging in an Aphasic Patient With 49, XXXXY Syndrome

BACKGROUND

The karyotype 49, XXXXY is one of the most severe forms of chromosome aneuploidy and is characterized clinically by developmental delay and profound language impairment, particularly involving expressive language functions. We describe the neurocognitive profile and structural anatomy of language pathway in a 2-year-old boy with 49, XXXXY syndrome with expressive aphasia.

METHODS

Retrospective chart review of the patient was performed. We characterized the language deficits using neuropsychologic testing. We further studied the language pathways using diffusion tensor imaging analytical technique.

RESULTS

The neurocognitive profile of the patient showed relative weakness of expressive language skills compared with other domains. Diffusion tensor imaging analysis demonstrated a poorly developed frontal aslant tract, a weak indirect segment of arcuate fasciculus, and normally developed direct segment of arcuate fasciculus. The frontal aslant tract is a novel pathway that connects the Broca's area with the anterior cingulate and presupplementary motor area and plays a role in the "motor stream" of language.

CONCLUSION

A poorly developed frontal aslant tract may underlie the expressive language deficits and provide some insight into the role of X chromosome in modulating the development of language tracts.

Acute Onset Dystonia after Infarction of Premotor and Supplementary Motor Cortex

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.

Heightened aggressive behavior in mice with lifelong versus postweaning knockout of the oxytocin receptor

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.