Neuropsychiatric complications of coronavirus disease 2019: Mount Sinai Health System cohort study

OBJECTIVE

To describe the frequency of neuropsychiatric complications among hospitalized patients with coronavirus disease 2019 (COVID-19) and their association with pre-existing comorbidities and clinical outcomes.

METHODS

We retrospectively identified all patients hospitalized with COVID-19 within a large multicenter New York City health system between March 15, 2020 and May 17, 2021 and randomly selected a representative cohort for detailed chart review. Clinical data, including the occurrence of neuropsychiatric complications (categorized as either altered mental status [AMS] or other neuropsychiatric complications) and in-hospital mortality, were extracted using an electronic medical record database and individual chart review. Associations between neuropsychiatric complications, comorbidities, laboratory findings, and in-hospital mortality were assessed using multivariate logistic regression.

RESULTS

Our study cohort consisted of 974 patients, the majority were admitted during the first wave of the pandemic. Patients were treated with anticoagulation (88.4%), glucocorticoids (24.8%), and remdesivir (10.5%); 18.6% experienced severe COVID-19 pneumonia (evidenced by ventilator requirement). Neuropsychiatric complications occurred in 58.8% of patients; 39.8% experienced AMS; and 19.0% experienced at least one other complication (seizures in 1.4%, ischemic stroke in 1.6%, hemorrhagic stroke in 1.0%) or symptom (headache in 11.4%, anxiety in 6.8%, ataxia in 6.3%). Higher odds of mortality, which occurred in 22.0%, were associated with AMS, ventilator support, increasing age, and higher serum inflammatory marker levels. Anticoagulant therapy was associated with lower odds of mortality and AMS.

CONCLUSION

Neuropsychiatric complications of COVID-19, especially AMS, were common, varied, and associated with in-hospital mortality in a diverse multicenter cohort at an epicenter of the COVID-19 pandemic.

Health care access, psychosocial outcomes and mental health in adults living with epilepsy during the COVID-19 pandemic

PURPOSE

People living with epilepsy (PLWE) have a higher prevalence of mental health comorbidities and poorer psychosocial outcomes compared to the general population. The aim of this study was to examine psychosocial outcomes, mental health, healthcare accessibility, and seizure burden in PLWE during the COVID-19 pandemic.

METHODS

We conducted a cross-sectional study of adults with epilepsy treated in an urban multicenter health system from 2021 to 2022. A standardized questionnaire assessed for COVID-19 history, comorbidities, access to antiseizure medications (ASMs) and neurological care, seizure burden, and psychosocial outcomes (e.g., employment, social and financial support). The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were administered to evaluate for depression and anxiety. Frequency and proportions for categorical variables and median and interquartile ranges for continuous variables were calculated.

RESULTS

Fifty-five PLWE participated (95 % response rate). Median age was 40 years (IQR 31.5-66.5), 61.8 % were women, 47.3 % had a bachelor's degree or higher and 29.1 % each had Medicaid and Medicare insurance. Race (from highest to lowest %) was: 32.7 % White, 20 % Black, 20 % Latinx, 14.5 % Asian, and 12.7 % selected "other" or "prefer not to say." COVID-19 had been diagnosed in 21.8 % of participants. Symptoms of anxiety and depression were self-reported by 43.6 % and 34.5 % of patients, respectively, with many describing this symptom as new post-pandemic (37.5 % and 31.6 %, respectively). Using validated scales, 52.7 % had depression (PHQ-9 score ≥ 5) with 30.9 % having moderate/severe depression (PHQ-9 score ≥ 10), while 29.1 % had probable generalized anxiety disorder (GAD-7 score ≥ 8). Seizure burden increased in 21.8 % of participants, while 20 % reported fewer seizures and 29.1 % were seizure free since the COVID-19 pandemic. Economic impacts of the pandemic included job loss (25 % amongst those employed at onset of pandemic), new or worsened financial difficulties (40 %), and new or worsened social support issues (30.9 %). Of all participants, 18.2 % reported difficulties accessing ASMs and 25.5 % cancelled visits, but of those with cancelled visits, 78.6 % had their appointments rescheduled as a telehealth visit.

CONCLUSION

Our cohort of PLWE experienced some challenges during the COVID-19 pandemic including poorer mental health and financial and employment-related stressors. Encouragingly, healthcare access was relatively spared during the COVID-19 crisis, with some patients even reporting a reduction in seizure burden. However, PLWE require ongoing psychosocial support with particular attention to decompensation of mental health and social stressors that may be exacerbated by the COVID-19 pandemic.

Older adults with epilepsy and COVID-19: Outcomes in a multi-hospital health system

BACKGROUND

Coronavirus disease 2019 (COVID-19) is associated with high rates of mortality and morbidity in older adults, especially those with pre-existing conditions. There is little work investigating how neurological conditions affect older adults with COVID-19. We aimed to compare in-hospital outcomes, including mortality, in older adults with and without epilepsy.

METHODS

This retrospective study in a large multicenter New York health system included consecutive older patients (age ≥65 years) either with or without epilepsy who were admitted with COVID-19 between 3/2020-5/2021. Epilepsy was identified using a validated International Classification of Disease (ICD) and antiseizure medicationbased case definition. Univariate comparisons were calculated using Chi-square, Fisher's exact, Mann-Whitney U, or Student's t-tests. Multivariable logistic regression models were generated to examine factors associated with mortality, discharge disposition and length of stay (LOS).

RESULTS

We identified 5384 older adults admitted with COVID-19 of whom 173 (3.21 %) had epilepsy. Mean age was significantly lower in those with (75.44, standard deviation (SD): 7.23) compared to those without epilepsy (77.98, SD: 8.68, p = 0.007). Older adults with epilepsy were more likely to be ventilated (35.84 % vs. 16.18 %, p < 0.001), less likely to be discharged home (21.39 % vs. 43.12 %, p < 0.001), had longer median LOS (13 days vs. 8 days, p < 0.001), and had higher in-hospital death (35.84 % vs. 28.29 %, p = 0.030) compared to those without epilepsy. Epilepsy in older adults was associated with increased odds of in-hospital death (adjusted odds ratio (aOR), 1.55; 95 % CI 1.12-2.14, p = 0.032), non-routine discharge disposition (aOR, 3.34; 95 % CI 2.21-5.03, p < 0.001), and longer LOS (46.46 % 95 % CI 34 %-59 %, p < 0.001).

CONCLUSIONS

In models that adjusted for multiple confounders including comorbidity and age, our study found that epilepsy was still associated with higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19 higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19. This work reinforces that epilepsy is a risk factor for worse outcomes in older adults admitted with COVID-19. Timely identification and treatment of COVID-19 in epilepsy may improve outcomes in older people with epilepsy.

Long-term outcomes after responsive neurostimulation for treatment of refractory epilepsy: a single-center experience of 100 cases

OBJECTIVE

Despite antiepileptic drugs, more than 30% of people with epilepsy continue to have seizures. Patients with such drug-resistant epilepsy (DRE) may undergo invasive treatment such as resection, laser ablation of the epileptogenic focus, or vagus nerve stimulation, but many are not candidates for epilepsy surgery or fail to respond to such interventions. Responsive neurostimulation (RNS) provides a neuromodulatory option. In this study, the authors present a single-center experience with the use of RNS over the last 5 years to provide long-term control of seizures in patients with DRE with at least 1 year of follow-up.

METHODS

The authors performed a retrospective analysis of a prospectively collected single-center database of consecutive DRE patients who underwent RNS system implantation from September 2015 to December 2020. Patients were followed-up postoperatively to evaluate seizure freedom and complications.

RESULTS

One hundred patients underwent RNS placement. Seven patients developed infections: 2 responded to intravenous antibiotic therapy, 3 required partial removal and salvaging of the system, and 2 required complete removal of the RNS device. No postoperative tract hemorrhages, strokes, device migrations, or malfunctions were documented in this cohort. The average follow-up period was 26.3 months (range 1-5.2 years). In terms of seizure reduction, 8 patients had 0%-24% improvement, 14 had 25%-49% improvement, 29 experienced 50%-74% improvement, 30 had 75%-99% improvement, and 19 achieved seizure freedom. RNS showed significantly better outcomes over time: patients with more than 3 years of RNS therapy had 1.8 higher odds of achieving 75% or more seizure reduction (95% CI 1.07-3.09, p = 0.02). Also, patients who had undergone resective or ablative surgery prior to RNS implantation had 8.25 higher odds of experiencing 50% or more seizure reduction (95% CI 1.05-65.1, p = 0.04).

CONCLUSIONS

Responsive neurostimulator implantation achieved 50% or more seizure reduction in approximately 80% of patients. Even in patients who did not achieve seizure freedom, significant improvement in seizure duration, severity, or postictal state was reported in more than 68% of cases. Infection (7%) was the most common complication. Patients with prior resective or ablative procedures and those who had been treated with RNS for more than 3 years achieved better outcomes.

In-hospital outcomes in patients with and without epilepsy diagnosed with COVID-19-A cohort study

OBJECTIVES

Coronavirus disease 2019 (COVID-19) is associated with mortality in persons with comorbidities. The aim of this study was to evaluate in-hospital outcomes in patients with COVID-19 with and without epilepsy.

METHODS

We conducted a retrospective study of patients with COVID-19 admitted to a multicenter health system between March 15, 2020, and May 17, 2021. Patients with epilepsy were identified using a validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/ICD-10-CM case definition. Logistic regression models and Kaplan-Meier analyses were conducted for mortality and non-routine discharges (i.e., not discharged home). An ordinary least-squares regression model was fitted for length of stay (LOS).

RESULTS

We identified 9833 people with COVID-19 including 334 with epilepsy. On univariate analysis, people with epilepsy had significantly higher ventilator use (37.70% vs 14.30%, p < .001), intensive care unit (ICU) admissions (39.20% vs 17.70%, p < .001) mortality rate (29.60% vs 19.90%, p < .001), and longer LOS (12 days vs 7 days, p < .001). and fewer were discharged home (29.64% vs 57.37%, p < .001). On multivariate analysis, only non-routine discharge (adjusted odds ratio [aOR] 2.70, 95% confidence interval [CI] 2.00-3.70; p < .001) and LOS (32.50% longer, 95% CI 22.20%-43.60%; p < .001) were significantly different. Factors associated with higher odds of mortality in epilepsy were older age (aOR 1.05, 95% CI 1.03-1.08; p < .001), ventilator support (aOR 7.18, 95% CI 3.12-16.48; p < .001), and higher Charlson comorbidity index (CCI) (aOR 1.18, 95% CI 1.04-1.34; p = .010). In epilepsy, admissions between August and December 2020 or January and May 2021 were associated with a lower odds of non-routine discharge and decreased LOS compared to admissions between March and July 2020, but this difference was not statistically significant.

SIGNIFICANCE

People with COVID-19 who had epilepsy had a higher odds of non-routine discharge and longer LOS but not higher mortality. Older age (≥65), ventilator use, and higher CCI were associated with COVID-19 mortality in epilepsy. This suggests that older adults with epilepsy and multimorbidity are more vulnerable than those without and should be monitored closely in the setting of COVID-19.

Mood and Anxiety Disorders and Suicidality in Patients With Newly Diagnosed Focal Epilepsy: An Analysis of a Complex Comorbidity

BACKGROUND AND OBJECTIVES

Mood, anxiety disorders, and suicidality are more frequent in people with epilepsy than in the general population. Yet, their prevalence and the types of mood and anxiety disorders associated with suicidality at the time of the epilepsy diagnosis are not established. We sought to answer these questions in patients with newly diagnosed focal epilepsy and to assess their association with suicidal ideation and attempts.

METHODS

The data were derived from the Human Epilepsy Project study. A total of 347 consecutive adults aged 18-60 years with newly diagnosed focal epilepsy were enrolled within 4 months of starting treatment. The types of mood and anxiety disorders were identified with the Mini International Neuropsychiatric Interview, whereas suicidal ideation (lifetime, current, active, and passive) and suicidal attempts (lifetime and current) were established with the Columbia Suicidality Severity Rating Scale (CSSRS). Statistical analyses included the t test, χ2 statistics, and logistic regression analyses.

RESULTS

A total of 151 (43.5%) patients had a psychiatric diagnosis; 134 (38.6%) met the criteria for a mood and/or anxiety disorder, and 75 (21.6%) reported suicidal ideation with or without attempts. Mood (23.6%) and anxiety (27.4%) disorders had comparable prevalence rates, whereas both disorders occurred together in 43 patients (12.4%). Major depressive disorders (MDDs) had a slightly higher prevalence than bipolar disorders (BPDs) (9.5% vs 6.9%, respectively). Explanatory variables of suicidality included MDD, BPD, panic disorders, and agoraphobia, with BPD and panic disorders being the strongest variables, particularly for active suicidal ideation and suicidal attempts.

DISCUSSION

In patients with newly diagnosed focal epilepsy, the prevalence of mood, anxiety disorders, and suicidality is higher than in the general population and comparable to those of patients with established epilepsy. Their recognition at the time of the initial epilepsy evaluation is of the essence.

High-resolution transcriptomics informs glial pathology in human temporal lobe epilepsy

The pathophysiology of epilepsy underlies a complex network dysfunction between neurons and glia, the molecular cell type-specific contributions of which remain poorly defined in the human disease. In this study, we validated a method that simultaneously isolates neuronal (NEUN +), astrocyte (PAX6 + NEUN–), and oligodendroglial progenitor (OPC) (OLIG2 + NEUN–) enriched nuclei populations from non-diseased, fresh-frozen human neocortex and then applied it to characterize the distinct transcriptomes of such populations isolated from electrode-mapped temporal lobe epilepsy (TLE) surgical samples. Nuclear RNA-seq confirmed cell type specificity and informed both common and distinct pathways associated with TLE in astrocytes, OPCs, and neurons. Compared to postmortem control, the transcriptome of epilepsy astrocytes showed downregulation of mature astrocyte functions and upregulation of development-related genes. To gain further insight into glial heterogeneity in TLE, we performed single cell transcriptomics (scRNA-seq) on four additional human TLE samples. Analysis of the integrated TLE dataset uncovered a prominent subpopulation of glia that express a hybrid signature of both reactive astrocyte and OPC markers, including many cells with a mixed GFAP + OLIG2 + phenotype. A further integrated analysis of this TLE scRNA-seq dataset and a previously published normal human temporal lobe scRNA-seq dataset confirmed the unique presence of hybrid glia only in TLE. Pseudotime analysis revealed cell transition trajectories stemming from this hybrid population towards both OPCs and reactive astrocytes. Immunofluorescence studies in human TLE samples confirmed the rare presence of GFAP + OLIG2 + glia, including some cells with proliferative activity, and functional analysis of cells isolated directly from these samples disclosed abnormal neurosphere formation in vitro. Overall, cell type-specific isolation of glia from surgical epilepsy samples combined with transcriptomic analyses uncovered abnormal glial subpopulations with de-differentiated phenotype, motivating further studies into the dysfunctional role of reactive glia in temporal lobe epilepsy.

Responsive Neurostimulation of the Thalamus for the Treatment of Refractory Epilepsy

Introduction

One-third of patients with epilepsy continue to have seizures despite antiepileptic medications. Some of these refractory patients may not be candidates for surgical resection primarily because the seizure onset zones (SOZs) involve both hemispheres or are located in eloquent areas. The NeuroPace Responsive Neurostimulation System (RNS) is a closed-loop device that uses programmable detection and stimulation to tailor therapy to a patient's individual neurophysiology. Here, we present our single-center experience with the use of RNS in thalamic nuclei to provide long-term seizure control in patients with refractory epilepsy.

Methods

We performed a prospective single-center study of consecutive refractory epilepsy patients who underwent RNS system implantation in the anterior (ANT) and centromedian (CM) thalamic nuclei from September 2015 to December 2020. Patients were followed postoperatively to evaluate seizure freedom and complications.

Results

Twenty-three patients underwent placement of 36 RNS thalamic leads (CM = 27 leads, ANT = 9 leads). Mean age at implant was 18.8 ± 11.2 years (range 7.8–62 years-old). Two patients (8.7%) developed infections: 1 improved with antibiotic treatments alone, and 1 required removal with eventual replacement of the system to recover the therapeutic benefit. Mean time from RNS implantation to last follow-up was 22.3 months. Based on overall reduction of seizure frequency, 2 patients (8.7%) had no- to <25% improvement, 6 patients (26.1%) had 25–49% improvement, 14 patients (60.9%) had 50–99% improvement, and 1 patient (4.3%) became seizure-free. All patients reported significant improvement in seizure duration and severity, and 17 patients (74%) reported improved post-ictal state. There was a trend for subjects with SOZs located in the temporal lobe to achieve better outcomes after thalamic RNS compared to those with extratemporal SOZs. Of note, seizure etiology was syndromic in 12 cases (52.2%), and 7 patients (30.4%) had undergone resection/disconnection surgery prior to thalamic RNS therapy.

Conclusion

Thalamic RNS achieved ≥50% seizure control in ~65% of patients. Infections were the most common complication. This therapeutic modality may be particularly useful for patients affected by aggressive epilepsy syndromes since a young age, those whose seizure foci are located in the mesial temporal lobe, and those who have failed prior surgical interventions.

Electroencephalography at the height of a pandemic: EEG findings in patients with COVID-19

OBJECTIVE

To characterize continuous video electroencephalogram (VEEG) findings of hospitalized COVID-19 patients.

METHODS

We performed a retrospective chart review of patients admitted at three New York City hospitals who underwent VEEG at the peak of the COVID-19 pandemic. Demographics, comorbidities, neuroimaging, VEEG indications and findings, treatment, and outcomes were collected.

RESULTS

Of 93 patients monitored, 77% had severe COVID-19 and 40% died. Acute ischemic or hemorrhagic stroke was present in 26% and 15%, respectively. Most common VEEG indications were encephalopathy/coma (60%) and seizure-like movements (38%). Most common VEEG findings were generalized slowing (97%), generalized attenuation (31%), generalized periodic discharges (17%) and generalized sharp waves (15%). Epileptiform abnormalities were present in 43% and seizures in 8% of patients, all of whom had seizure risk factors. Factors associated with an epileptiform VEEG included increasing age (OR 1.07, p = 0.001) and hepatic/renal failure (OR 2.99, p = 0.03).

CONCLUSIONS

Most COVID-19 patients who underwent VEEG monitoring had severe COVID-19 and over one-third had acute cerebral injury (e.g., stroke, anoxia). Seizures were uncommon. VEEG findings were nonspecific.

SIGNIFICANCE

VEEG findings in this cohort of hospitalized COVID-19 patients were those often seen in critical illness. Seizures were uncommon and occurred in the setting of common seizure risk factors.

Quantification of brain age using high-resolution 7 tesla MR imaging and implications for patients with epilepsy

Purpose

Epilepsy patients exhibit morphological differences on neuroimaging compared to age-matched healthy controls, including cortical and sub-cortical volume loss and altered gray-white matter ratios. The objective was to develop a model of normal aging using the 7T MRIs of healthy controls. This model can then be used to determine if the changes in epilepsy patients resemble the changes seen in aging, and potentially give a marker for the severity of those changes.

Methods

Sixty-nine healthy controls (24F/45M, mean age 36.5 ± 10.5 years) and forty-four epilepsy patients (24F/20M, 33.2 ± 9.9 years) non-lesional at 3T were scanned with volumetric T1-MPRAGE at 7T. These images were segmented and quantified using FreeSurfer. A linear regression-based model trained on healthy controls was developed to predict ages using derived imaging features among the epilepsy patient cohort. The model used 114 features with significant linear correlation with age.

Results

The regression-based model estimated brain age with mean absolute error (MAE) of 6.6 years among controls. Comparable prediction accuracy of 6.9 years MAE was seen epilepsy patients. T-test of mean absolute error showed no difference in the prediction accuracy with controls and epilepsy patients (p = 0.68). However, average signed error showed elevated (+5.0 years, p = 0.0007) predicted age differences (PAD; brain-PAD=, predicted minus biological age) among epilepsy patients. Morphological metrics in the medial temporal lobe were major contributors to PAD. Additionally, patients with seizure frequency greater than once a week showed significantly elevated brain-PAD (+8.2 ± 5.3 years, n = 13) compared to patients with lower seizure frequency (3.7 ± 6.5 years, n = 31, p = 0.033).

Major conclusions

Morphological patterns suggestive of premature aging were observed in non-lesional epilepsy patients vs. controls and in high seizure frequency patients vs. low frequency patients. Modeling brain age with 7T MRI may provide a sensitive imaging marker to assess the differential effects of the aging process in diseases such as epilepsy.

Deep Learning of Simultaneous Intracranial and Scalp EEG for Prediction, Detection, and Lateralization of Mesial Temporal Lobe Seizures

In people with drug resistant epilepsy (DRE), seizures are unpredictable, often occurring with little or no warning. The unpredictability causes anxiety and much of the morbidity and mortality of seizures. In this work, 102 seizures of mesial temporal lobe onset were analyzed from 19 patients with DRE who had simultaneous intracranial EEG (iEEG) and scalp EEG as part of their surgical evaluation. The first aim of this paper was to develop machine learning models for seizure prediction and detection (i) using iEEG only, (ii) scalp EEG only and (iii) jointly analyzing both iEEG and scalp EEG. The second goal was to test if machine learning could detect a seizure on scalp EEG when that seizure was not detectable by the human eye (surface negative) but was seen in iEEG. The final question was to determine if the deep learning algorithm could correctly lateralize the seizure onset. The seizure detection and prediction problems were addressed jointly by training Deep Neural Networks (DNN) on 4 classes: non-seizure, pre-seizure, left mesial temporal onset seizure and right mesial temporal onset seizure. To address these aims, the classification accuracy was tested using two deep neural networks (DNN) against 3 different types of similarity graphs which used different time series of EEG data. The convolutional neural network (CNN) with the Waxman similarity graph yielded the highest accuracy across all EEG data (iEEG, scalp EEG and combined). Specifically, 1 second epochs of EEG were correctly assigned to their seizure, pre-seizure, or non-seizure category over 98% of the time. Importantly, the pre-seizure state was classified correctly in the vast majority of epochs (>97%). Detection from scalp EEG data alone of surface negative seizures and the seizures with the delayed scalp onset (the surface negative portion) was over 97%. In addition, the model accurately lateralized all of the seizures from scalp data, including the surface negative seizures. This work suggests that highly accurate seizure prediction and detection is feasible using either intracranial or scalp EEG data. Furthermore, surface negative seizures can be accurately predicted, detected and lateralized with machine learning even when they are not visible to the human eye.

Safety of responsive neurostimulation in pediatric patients with medically refractory epilepsy

OBJECTIVE

Approximately 75% of pediatric patients who suffer from epilepsy are successfully treated with antiepileptic drugs, while the disease is drug resistant in the remaining patients, who continue to have seizures. Patients with drug-resistant epilepsy (DRE) may have options to undergo invasive treatment such as resection, laser ablation of the epileptogenic focus, or vagus nerve stimulation. To date, treatment with responsive neurostimulation (RNS) has not been sufficiently studied in the pediatric population because the FDA has not approved the RNS device for patients younger than 18 years of age. Here, the authors sought to investigate the safety of RNS in pediatric patients.

METHODS

The authors performed a retrospective single-center study of consecutive patients with DRE who had undergone RNS system implantation from September 2015 to December 2019. Patients were followed up postoperatively to evaluate seizure freedom and complications.

RESULTS

Of the 27 patients studied, 3 developed infections and were treated with antibiotics. Of these 3 patients, one required partial removal and salvaging of a functioning system, and one required complete removal of the RNS device. No other complications, such as intracranial hemorrhage, stroke, or device malfunction, were seen. The average follow-up period was 22 months. All patients showed improvement in seizure frequency.

CONCLUSIONS

The authors demonstrated the safety and efficacy of RNS in pediatric patients, with infections being the main complication.

ABBREVIATIONS

DBS = deep brain stimulation; DRE = drug-resistant epilepsy; MDC = multidisciplinary conference; MER = microelectrode recording; MSHS = Mount Sinai Health System; RNS = responsive neurostimulation; SEEG = stereo-EEG; VNS = vagus nerve stimulation.

Abstract TP426: Impact of Electrographic Seizure Activity on Outcomes Among Critically-ill Patients with Stroke

Introduction: Patients with severe acute stroke can suffer secondary neurological injury due to a variety of causes. The clinical impact of electrographic seizures among critically-ill stroke patients remains unclear.

Methods: We retrospectively analyzed a cohort of consecutive stroke patients admitted to the Neuroscience Intensive Care Unit (NSICU) at the Mount Sinai Hospital who underwent ≥24 hours of continuous video EEG (cEEG) monitoring for alteration in level of consciousness or suspected non-convulsive seizures between May 2013 and June 2015.

Results: Of 106 consecutive severe stroke patients admitted to the NSICU who underwent cEEG monitoring, 15 (14%) had clinical or electrographic seizures. The median duration of cEEG monitoring was 1.2 days. Observed seizures included purely electrographic seizures with no clinical correlate in 53%, subtle twitching or altered mental status in 33%, and generalized tonic-clonic seizures with an EEG correlate in 13%. Generalized or lateralized periodic discharges (PEDs) were present in 93% (14/15) of patients in the seizure group, compared to 20% (18/89) in the non-seizure group (P= 0.00). The survival rate at discharge was 53% in the seizure group compared to 73% in the non-seizure group (p = 0.12). Mean ICU length of stay was 16 days in both groups. Of the 11 survivors in the seizure group 100% were severely disabled at discharge (mRS 4 or 5) compared to 75% of the 65 survivors in the non-seizure group.(P=0.06).

Conclusion: Critically-ill stroke patients with clinical or electrographic seizures in the ICU tend to have higher mortality and worse functional outcome at the time of discharge. PEDS are an important marker of patients at high risk for ictal activity. Careful identification of acute stroke patients that might benefit from seizure prophylaxis is warranted.