CARLA: Adjusted common average referencing for cortico-cortical evoked potential data.

Human brain connectivity can be mapped by single pulse electrical stimulation during intracranial EEG measurements. The raw cortico-cortical evoked potentials (CCEP) are often contaminated by noise. Common average referencing (CAR) removes common noise and preserves response shapes but can introduce bias from responsive channels. We address this issue with an adjusted, adaptive CAR algorithm termed "CAR by Least Anticorrelation (CARLA)". CARLA was tested on simulated CCEP data and real CCEP data collected from four human participants. In CARLA, the channels are ordered by increasing mean cross-trial covariance, and iteratively added to the common average until anticorrelation between any single channel and all re-referenced channels reaches a minimum, as a measure of shared noise. We simulated CCEP data with true responses in 0-45 of 50 total channels. We quantified CARLA's error and found that it erroneously included 0 (median) truly responsive channels in the common average with ≤42 responsive channels, and erroneously excluded ≤2.5 (median) unresponsive channels at all responsiveness levels. On real CCEP data, signal quality was quantified with the mean R2 between all pairs of channels, which represents inter-channel dependency and is low for well-referenced data. CARLA re-referencing produced significantly lower mean R2 than standard CAR, CAR using a fixed bottom quartile of channels by covariance, and no re-referencing. CARLA minimizes bias in re-referenced CCEP data by adaptively selecting the optimal subset of non-responsive channels. It showed high specificity and sensitivity on simulated CCEP data and lowered inter-channel dependency compared to CAR on real CCEP data.

Clinical evaluation of a stereotactic system for single-stage deep brain stimulation surgery under general anesthesia: technical note.

OBJECTIVE: Conventional frame-based stereotactic systems have circumferential base frames, often necessitating deep brain stimulation (DBS) surgery in two stages: intracranial electrode insertion followed by surgical re-preparation and pulse generator implantation. Some patients do not tolerate awake surgery, underscoring the need for a safe alternative for asleep DBS surgery. A frame-based stereotactic system with a skull-mounted "key" in lieu of a circumferential base frame received US FDA clearance. The authors describe the system's application for single-stage, asleep DBS surgery in 8 patients at their institution and review its workflow and technical considerations. METHODS: Eight patients underwent DBS lead insertion and IPG implantation in a single surgical preparation under general anesthesia using the system. Postoperative CT imaging confirmed lead placement. RESULTS: Eight patients underwent implantation of 15 total leads targeting the ventral intermediate nucleus (4 patients), globus pallidus internus (GPi; 3 patients), and subthalamic nucleus (STN; 1 patient). Intraoperative microelectrode recording was conducted for GPi and STN targets. Postoperative CT imaging revealed a mean ± SD radial error of 1.24 ± 0.45 mm (n = 15 leads), without surgical complications. CONCLUSIONS: The stereotactic system facilitated safe and effective asleep, single-stage DBS surgery, maintaining traditional lead accuracy standards.

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.

Emerging approaches in neurostimulation for epilepsy.

PURPOSE OF REVIEW: Neurostimulation is a quickly growing treatment approach for epilepsy patients. We summarize recent approaches to provide a perspective on the future of neurostimulation. RECENT FINDINGS: Invasive stimulation for treatment of focal epilepsy includes vagus nerve stimulation, responsive neurostimulation of the cortex and deep brain stimulation of the anterior nucleus of the thalamus. A wide range of other targets have been considered, including centromedian, central lateral and pulvinar thalamic nuclei; medial septum, nucleus accumbens, subthalamic nucleus, cerebellum, fornicodorsocommissure and piriform cortex. Stimulation for generalized onset seizures and mixed epilepsies as well as increased efforts focusing on paediatric populations have emerged. Hardware with more permanently implanted lead options and sensing capabilities is emerging. A wider variety of programming approaches than typically used may improve patient outcomes. Finally, noninvasive brain stimulation with its favourable risk profile offers the potential to treat increasingly diverse epilepsy patients. SUMMARY: Neurostimulation for the treatment of epilepsy is surprisingly varied. Flexibility and reversibility of neurostimulation allows for rapid innovation. There remains a continued need for excitability biomarkers to guide treatment and innovation. Neurostimulation, a part of bioelectronic medicine, offers distinctive benefits as well as unique challenges.

Status Epilepticus in Older Adults: Diagnostic and Treatment Considerations.

Status epilepticus (SE) is one of the leading life-threatening neurological emergencies in the elderly population, with significant morbidity and mortality. SE presents unique diagnostic and therapeutic challenges in the older population given overlap with other causes of encephalopathy, complicating diagnosis, and the common occurrence of multiple comorbid diseases complicates treatment. First-line therapy involves the use of rescue benzodiazepine in the form of intravenous lorazepam or diazepam, intramuscular or intranasal midazolam and rectal diazepam. Second-line therapies include parenteral levetiracetam, fosphenytoin, valproate and lacosamide, and underlying comorbidities guide the choice of appropriate medication, while third-line therapies may be influenced by the patient's code status as well as the cause and type of SE. The standard of care for convulsive SE is treatment with an intravenous anesthetic, including midazolam, propofol, ketamine and pentobarbital. There is currently limited evidence guiding appropriate therapy in patients failing third-line therapies. Adjunctive strategies may include immunomodulatory treatments, non-pharmacological strategies such as ketogenic diet, neuromodulation therapies and surgery in select cases. Surrogate decision makers should be updated early and often in refractory episodes of SE and informed of the high morbidity and mortality associated with the disease as well as the high probability of subsequent epilepsy among survivors.

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.

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.

Outcomes of seizures, status epilepticus, and EEG findings in critically ill patient with COVID-19.

OBJECTIVE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has a myriad of neurological manifestations and its effects on the nervous system are increasingly recognized. Seizures and status epilepticus (SE) are reported in the novel coronavirus disease (COVID-19), both new onset and worsening of existing epilepsy; however, the exact prevalence is still unknown. The primary aim of this study was to correlate the presence of seizures, status epilepticus, and specific critical care EEG patterns with patient functional outcomes in those with COVID-19. METHODS: This is a retrospective, multicenter cohort of COVID-19-positive patients in Southeast Michigan who underwent electroencephalography (EEG) from March 12th through May 15th, 2020. All patients had confirmed nasopharyngeal PCR for COVID-19. EEG patterns were characterized per 2012 ACNS critical care EEG terminology. Clinical and demographic variables were collected by medical chart review. Outcomes were divided into recovered, recovered with disability, or deceased. RESULTS: Out of the total of 4100 patients hospitalized with COVID-19, 110 patients (2.68%) had EEG during their hospitalization; 64% were male, 67% were African American with mean age of 63 years (range 20-87). The majority (70%) had severe COVID-19, were intubated, or had multi-organ failure. The median length of hospitalization was 26.5 days (IQR = 15 to 44 days). During hospitalization, of the patients who had EEG, 21.8% had new-onset seizure including 7% with status epilepticus, majority (87.5%) with no prior epilepsy. Forty-nine (45%) patients died in the hospital, 46 (42%) recovered but maintained a disability and 15 (14%) recovered without a disability. The EEG findings associated with outcomes were background slowing/attenuation (recovered 60% vs recovered/disabled 96% vs died 96%, p < 0.001) and normal (recovered 27% vs recovered/disabled 0% vs died 1%, p < 0.001). However, these findings were no longer significant after adjusting for severity of COVID-19. CONCLUSION: In this large multicenter study from Southeast Michigan, one of the early COVID-19 epicenters in the US, none of the EEG findings were significantly correlated with outcomes in critically ill COVID-19 patients. Although seizures and status epilepticus could be encountered in COVID-19, the occurrence did not correlate with the patients' functional outcome.

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.

Differentiation of psychogenic nonepileptic attacks from status epilepticus among patients intubated for convulsive activity.

BACKGROUND AND OBJECTIVE: Patients with psychogenic nonepileptic attacks (PNEA) sometimes receive aggressive treatment leading to intubation. This study aimed to identify patient characteristics that can help differentiate PNEA from status epilepticus (SE). METHODS: We retrospectively identified patients with a final diagnosis of PNEA or SE, who were intubated for emergent convulsive symptoms and underwent continuous electroencephalography (cEEG) between 2012 and 2017. Patients who had acute brain injury or progressive brain disease as the cause of SE were excluded. We compared clinical features and laboratory values between the two groups, and identified risk factors for PNEA-related convulsive activity. RESULTS: Over a six-year period, 24 of 148 consecutive patients (16%) intubated for convulsive activity had a final diagnosis of PNEA rather than SE. Compared to patients intubated for SE, intubated PNEA patients more likely were <50 years of age, female, white, had a history of a psychiatric disorder, had no history of an intracranial abnormality, and had a maximum systolic blood pressure <140 mm Hg (all P < 0.001). Patients with 0-2 of these six risk factors had a 0% (0/88) likelihood of having PNEA, those with 3-4 had a 15% (6/39) chance of having PNEA, and those with 5-6 had an 86% (18/21) chance of having PNEA. Sensitivity for PNEA among those with 5-6 risk factors was 75% (95% CI: 53-89%) and specificity was 98% (95% CI: 93-99%). CONCLUSIONS: In the absence of a clear precipitating brain injury, approximately one in six patients intubated for emergent convulsive symptoms had PNEA rather than SE. Although PNEA cannot be diagnosed only by the presence of these risk factors, these simple characteristics could raise clinical suspicion for PNEA in the appropriate setting. Urgent neurological consultation may prevent unnecessary intubation of this at-risk patient population.

Effect of seizure timing on long-term survival in patients with brain tumor.

OBJECTIVE: Seizures often occur in patients with primary brain tumor (BT). The aim of this study was to determine if there is an association between the time of occurrence of seizures during the course of BT and survival of these patients. METHODS: This retrospective cohort study at Henry Ford Hospital, an urban tertiary referral center, included all patients who were diagnosed with primary BTs at Henry Ford Health System between January 2006 and December 2014. Timing of seizure occurrence, if occurred at presentation or after the tumor diagnosis during follow-up period, in different grades of BTs, and survival of these patients were analyzed. RESULTS: Of the 901 identified patients, 662 (53% male; mean age: 56 years) were included in final analysis, and seizures occurred in 283 patients (43%). Patients with World Health Organization (WHO) grade III BT with seizures as a presenting symptom only had better survival (adjusted hazard ratio (HR): 0.27; 95% confidence interval (CI), 0.11-0.67; P = 0.004). Seizures that occurred after tumor diagnosis only (adjusted HR: 2.11; 95% CI, 1.59-2.81; P < 0.001) in patients with WHO grade II tumors (adjusted HR: 3.41; 95% CI, 1.05-11.1; P = 0.041) and WHO grade IV tumors (adjusted HR: 2.14; 95% CI, 1.58-2.90; P < 0.001) had higher mortality. Seizures that occurred at presentation and after diagnosis also had higher mortality (adjusted HR: 1.34; 95% CI, 1.00-1.80; P = 0.049), in patients with meningioma (adjusted HR: 6.19; 95% CI, 1.30-29.4; P = 0.021) and grade III tumors (adjusted HR: 6.19; 95% CI, 2.56-15.0; P < 0.001). CONCLUSION: Seizures occurred in almost half of the patients with BTs. The association between seizures in patients with BT and their survival depends on the time of occurrence of seizures, if occurring at presentation or after tumor diagnosis, and the type of tumor. Better survival was noted in patients with WHO grade III BTs who had seizures at presentation at the time of diagnosis, while higher mortality was noted in WHO grade II tumors who had seizure at presentation and after tumor diagnosis, and in grade IV tumors after tumor diagnosis.

Nitrous oxide-induced demyelination: Clinical presentation, diagnosis and treatment recommendations.

BACKGROUND: Recreational use of nitrous oxide (NO) in the general public has led to increasing reports of NO-induced demyelination (NOID). We describe the varying clinical presentations and pathophysiology, and offer a treatment paradigm. METHODS: A literature search of MEDLINE and EMBASE resulted in 42 publications with 37 studies meeting the inclusion criteria, for a total of 51 patients. Our case series included 5 patients seen from 2014 to 2018 followed over 3-60 months. RESULTS: Those with sensory symptoms and subjective weakness were categorized as having "mild" symptoms (25%). Symptoms indicating involvement outside the dorsal columns such as observer-graded weakness were categorized as "moderate" (61%). Patients with the aforementioned plus cognitive effects were categorized as "severe" (12%). There was no dose-dependent relationship between the amount of NO used and clinical impairment. There was a trend between the severity of neurologic impairment and serum levels of B12. Two patients were noncompliant. One initiated only oral therapy and did not improve. One received injections a month apart and worsened. CONCLUSIONS: Patients with NOID tend to have worse symptoms when presenting with lower serum vitamin B12 levels and have good recovery rates when treated with intramuscular B12 and oral supplementation.

Electrographic seizures and ictal-interictal continuum (IIC) patterns in critically ill patients.

Critical care long-term continuous electroencephalogram (cEEG) monitoring has expanded dramatically in the last several decades spurned by technological advances in EEG digitalization and several key clinical findings: 1-Seizures are relatively common in the critically ill-large recent observational studies suggest that around 20% of critically ill patients placed on cEEG have seizures. 2-The majority (~75%) of patients who have seizures have exclusively "electrographic seizures", that is, they have no overt ictal clinical signs. Along with the discovery of the unexpectedly high incidence of seizures was the high prevalence of EEG patterns that share some common features with archetypical electrographic seizures but are not uniformly considered to be "ictal". These EEG patterns include lateralized periodic discharges (LPDs) and generalized periodic discharges (GPDs)-patterns that at times exhibit ictal-like behavior and at other times behave more like an interictal finding. Dr. Hirsch and colleagues proposed a conceptual framework to describe this spectrum of patterns called the ictal-interictal continuum (IIC). In the following years, investigators began to answer some of the key pragmatic clinical concerns such as which patients are at risk of seizures and what is the optimal duration of cEEG use. At the same time, investigators have begun probing the core questions for critical care EEG-what is the underlying pathophysiology of these patterns, at what point do these patterns cause secondary brain injury, what are the optimal treatment strategies, and how do these patterns affect clinical outcomes such as neurological disability and the development of epilepsy. In this review, we cover recent advancements in both practical concerns regarding cEEG use, current treatment strategies, and review the evidence associating IIC/seizures with poor clinical outcomes.

Tales of a department: how the COVID-19 pandemic transformed Detroit's Henry Ford Hospital, Department of Neurology-part I: the surge.

The COVID-19 pandemic has reshaped the way healthcare systems operate around the world. The major hurdles faced have been availability of personal protective equipment, intensive care unit beds, ventilators, treatments and medical personnel. Detroit, Michigan has been an epidemic 'hotspot' in the USA with Wayne County among the hardest hit counties in the nation. The Department of Neurology at Henry Ford Hospital, in the heart of Detroit, has responded effectively to the pandemic by altering many aspects of its operations. The rapid engagement of the department and enhanced utilisation of teleneurology were two of the pivotal elements in the successful response to the pandemic. In this review, we describe the transformation our department has undergone, as it relates to its infrastructure redesigning, coverage restructuring, redeployment strategies, medical education adaptations and novel research initiatives.

Electrographic Seizures in Patients with Acute Encephalitis.

INTRODUCTION: Clinical seizures and status epilepticus are frequent complications of encephalitis, can lead to depressed level of consciousness, and are associated with poor outcome. We sought to determine the frequency, risk factors, and clinical impact of electrographic seizures detected with continuing electroencephalography (cEEG) in patients with encephalitis and altered level of consciousness. METHODS: We retrospectively identified all patients with presumed or definite viral or autoimmune encephalitis who underwent cEEG monitoring at Henry Ford Hospital from January 2012 to October 2017. Clinical data and cEEG monitoring reports were abstracted and recorded. The primary outcome was electrographic seizures detected by cEEG. RESULTS: Of 1,735 patients who underwent a minimum of 12 h of cEEG monitoring, we identified 54 with a verified discharge diagnosis of encephalitis. Twenty-two of these patients (41%) had electrographic seizures on cEEG. Compared with encephalitis patients without seizures, electrographic seizures were associated with lower serum sodium levels (137 ± 5 vs 141 ± 7, P = 0.027) and more often were on antiepileptic therapy (100% vs 78%, P = 0.033) on the first day of monitoring. Seizures were also associated with a higher frequency of cortical imaging abnormalities (68% vs 28%, P = 0.005), lateralized periodic discharges (LPDs; 50% vs 16%, P = 0.014), delta background frequency (81% vs 45%, P = 0.010), low or suppressed voltage (96% vs 62%, P = 0.005), and focal slowing (86% vs 47%, P = 0.004). There was no association between electrographic seizures and clinical outcome at discharge. CONCLUSION: Electrographic seizures occur in approximately 40% of patients with acute encephalitis. Low serum sodium, cortical imaging abnormalities, and on cEEG LPDs and background abnormalities are associated factors. The lack of association with short-term outcome suggests that with aggressive treatment, the clinical impact of electrographic seizures in encephalitis can be minimized.

Intubation for Psychogenic Non-Epileptic Attacks: Frequency, Risk Factors, and Impact on Outcome.

PURPOSE: Patients with psychogenic non-epileptic attacks (PNEA) sometimes receive aggressive treatment leading to endotracheal intubation. We sought to identify the frequency, risk factors, and impact on outcome of intubation for PNEA. METHODS: We retrospectively reviewed all PNEA patients admitted via the emergency department (ED) who had an episode of PNEA documented by continuous video electroencephalography (vEEG) at Henry Ford Hospital between January 2012 and October 2017. Patients with comorbid epilepsy were excluded. Clinical features, treatments, and vEEG reports were compared between intubated and non-intubated patients. RESULTS: Of 80 patients who were admitted via the ED and had PNEA documented by vEEG, 12 (15%) were intubated. Compared with non-intubated PNEA patients, intubated patients had longer duration of convulsive symptoms (25 [IQR 7-53] vs 2 [IQR 1-9] minutes, P = 0.01), were less likely to have a normal Glasgow Coma Scale score of 15 (33% vs 94%, P < 0.001), received higher doses of benzodiazepines (30 [IQR 16-45] vs 10 [IQR 5-20] mg of diazepam equivalents, P = 0.004), and were treated with more antiepileptic drugs (AEDs, 2 [IQR 1-3] vs 1 [IQR 1-2], P = 0.01). Hospital length of stay was longer (3 [IQR 3-5] vs 2 [IQR 2-3], P = 0.001), and the rate of complications (25% vs 4%, P = 0.04) and re-hospitalization from a recurrent episode of PNEA within 30 days was higher among intubated PNEA patients (17% vs 0%, P = 0.02). CONCLUSION: Fifteen percent of patients hospitalized for vEEG-documented PNEA were intubated. Intubated patients had longer length of stay, more in-hospital complications, and a high rate of re-hospitalization from recurrent PNEA symptoms. Prolonged duration of convulsive symptoms, depressed level of consciousness, and aggressive treatment with benzodiazepines were associated with intubation for PNEA.

Bilateral independent periodic discharges are associated with electrographic seizures and poor outcome: A case-control study.

OBJECTIVE: To determine the clinical correlates bilateral independent periodic discharges (BIPDs) and their association with electrographic seizures and outcome. METHODS: Retrospective case-control study of patients with BIPDs compared to patients without periodic discharges ("No PDs") and patients with lateralized periodic discharges ("LPDs"), matched for age, etiology and level of alertness. RESULTS: We included 85 cases and 85 controls in each group. The most frequent etiologies of BIPDs were stroke, CNS infections, and anoxic brain injury. Acute bilateral cerebral injury was more common in the BIPDs group than in the No PDs and LPDs groups (70% vs. 37% vs. 35%). Electrographic seizures were more common with BIPDs than in the absence of PDs (45% vs. 8%), but not than with LPDs (52%). Mortality was higher in the BIPDs group (36%) than in the No PDs group (18%), with fewer patients with BIPDs achieving good outcome (moderate disability or better; 18% vs. 36%), but not than in the LPDs group (24% mortality, 26% good outcome). In multivariate analyses, BIPDs remained associated with mortality (OR: 3.0 [1.4-6.4]) and poor outcome (OR: 2.9 [1.4-6.2]). CONCLUSION: BIPDs are caused by bilateral acute brain injury and are associated with a high risk of electrographic seizures and of poor outcome. SIGNIFICANCE: BIPDs are uncommon but their identification in critically ill patients has potential important implications, both in terms of clinical management and prognostication.

Ictal Interictal Continuum Patterns.

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

Time-dependent risk of seizures in critically ill patients on continuous electroencephalogram.

OBJECTIVE: Find the optimal continuous electroencephalographic (CEEG) monitoring duration for seizure detection in critically ill patients. METHODS: We analyzed prospective data from 665 consecutive CEEGs, including clinical factors and time-to-event emergence of electroencephalographic (EEG) findings over 72 hours. Clinical factors were selected using logistic regression. EEG risk factors were selected a priori. Clinical factors were used for baseline (pre-EEG) risk. EEG findings were used for the creation of a multistate survival model with 3 states (entry, EEG risk, and seizure). EEG risk state is defined by emergence of epileptiform patterns. RESULTS: The clinical variables of greatest predictive value were coma (31% had seizures; odds ratio [OR] = 1.8, p < 0.01) and history of seizures, either remotely or related to acute illness (34% had seizures; OR = 3.0, p < 0.001). If there were no epileptiform findings on EEG, the risk of seizures within 72 hours was between 9% (no clinical risk factors) and 36% (coma and history of seizures). If epileptiform findings developed, the seizure incidence was between 18% (no clinical risk factors) and 64% (coma and history of seizures). In the absence of epileptiform EEG abnormalities, the duration of monitoring needed for seizure risk of <5% was between 0.4 hours (for patients who are not comatose and had no prior seizure) and 16.4 hours (comatose and prior seizure). INTERPRETATION: The initial risk of seizures on CEEG is dependent on history of prior seizures and presence of coma. The risk of developing seizures on CEEG decays to <5% by 24 hours if no epileptiform EEG abnormalities emerge, independent of initial clinical risk factors. Ann Neurol 2017;82:177-185.