American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology: 2021 Version

Imaging of status epilepticus: Making the invisible visible. A prospective study on 206 patients

BACKGROUND

Peri-ictal MRI abnormalities (PMA) frequently affect the cerebral cortex, hippocampus, pulvinar of the thalamus, corpus callosum, and cerebellum. In this prospective study, we aimed to characterize the spectrum of PMA in a large cohort of patients with status epilepticus.

METHODS

We prospectively recruited 206 patients with SE and an acute MRI. The MRI protocol included diffusion weighted imaging (DWI), fluid-attenuated inversion recovery (FLAIR), arterial spin labeling (ASL), and T1-weighted imaging pre-and post-contrast application. Peri-ictal MRI abnormalities were stratified as either neocortical or non-neocortical. Amygdala, hippocampus, cerebellum, and corpus callosum were regarded as non-neocortical structures.

RESULTS

Peri-ictal MRI abnormalities were observed in 93/206 (45%) of patients in at least one MRI sequence. Diffusion restriction was observed in 56/206 (27%) of patients, which was mainly unilateral in 42/56 (75%) affecting neocortical structures in 25/56 (45%), non-neocortical structures in 20/56 (36%) and both areas in 11/56 (19%) of patients. Cortical DWI lesions were located mostly in frontal lobes 15/25 (60%); non-neocortical diffusion restriction affected either the pulvinar of the thalamus or hippocampus 29/31 (95%). Alterations in FLAIR were observed in 37/203 (18%) of patients. They were mainly unilateral 24/37 (65%); neocortical 18/37 (49%), non-neocortical 16/37 (43%), or affecting both neocortical and non-neocortical structures 3/37 (8%). In ASL, 51/140 (37%) of patients had ictal hyperperfusion. Hyperperfused areas were located mainly in the neocortex 45/51 (88%) and were unilateral 43/51 (84%). In 39/66 (59%) of patients, PMA were reversible in one week. In 27/66 (41%), the PMA persisted and a second follow-up MRI was performed three weeks later in 24/27 (89%) patients. In 19/24 (79%) PMA were resolved.

CONCLUSIONS

Almost half of the patients with SE had peri-ictal MRI abnormalities. The most prevalent PMA was ictal hyperperfusion followed by diffusion restriction and FLAIR abnormalities. Neocortex was most frequently affected especially the frontal lobes. The majority of PMAs were unilateral. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.

[Status epilepticus-Detection and treatment in the intensive care unit]

Status epilepticus is characterized by persistent or repetitive seizures which, without successful treatment, can lead to neuronal damage, neurological deficits and death of the patient.While status epilepticus with motor symptoms can usually be clinically diagnosed, nonconvulsive status epilepticus is often clinically overlooked due to its ambiguous semiology, so that electroencephalography (EEG) recording is necessary. The treatment of status epilepticus is performed in four treatment steps, whereby a difficult to treat status epilepticus is present from the third step at the latest and intensive medical care of the patient is necessary. Timely initiation of treatment and sufficient dosage of anticonvulsive medication are decisive for the success of treatment. There is little evidence for the "late" stages of treatment. Intensive medical measures pose the risk of complications that worsen the prognosis. Especially in nonconvulsive status epilepticus, the use of anesthetics must be weighed against possible complications of mechanical ventilation.

Epilepsy in cerebral amyloid angiopathy: an observational retrospective study of a large population

OBJECTIVE

Cerebral amyloid angiopathy (CAA) is a major cause of spontaneous intracranial hemorrhage in older adults. Epilepsy represents a possible sequela of the disease. To date, studies on epilepsy in CAA are lacking, and the few data available mainly focus on CAA-related inflammation (CAA-ri), the inflammatory form of the disease.

METHODS

In this retrospective observational study, we consecutively recruited CAA patients observed over a time span of 10 years, collecting demographic, clinical, and instrumental data. Significant baseline characteristics were evaluated as potential risk factors for the development of epilepsy in the CAA population, and in the subgroups of CAA-ri and CAA without inflammatory reaction (CAA-nri). The effect of potential risk factors for epilepsy was measured as odds ratio with 95% confidence interval.

RESULTS

Within 96 recruited CAA cases, 33 (34.4%) developed epilepsy during follow-up (median = 13.5 months). The prevalent type of seizure was focal (81.3%); 12.1% of the epileptic patients presented status epilepticus, and 6.1% developed drug-resistant epilepsy. Electroencephalographic traces revealed slow and epileptic discharge activity in the majority of epileptic patients, but also in those without epilepsy. The presence of focal or disseminated cortical superficial siderosis (cSS) was associated with an increased risk of epilepsy in the CAA-nri group, and the association with CAA-ri and epilepsy was present in the overall population.

SIGNIFICANCE

Epilepsy is a common manifestation during the course of CAA, where CAA-ri and cSS represent predisposing factors for the development of seizures. These data suggest the importance of a deep characterization of CAA patients, to better select those more prone to develop epilepsy.

Usefulness and yield of routine electroencephalogram: a retrospective study

BACKGROUND

The electroencephalogram (EEG) is a common diagnostic tool used to investigate patients for various indications including seizure disorders.

AIMS

To investigate factors that predict the presence of epileptiform abnormalities on EEG and review the common indications for ordering an EEG.

METHODS

We retrospectively reviewed all routine adult EEG performed in a hospital over a 6-month period. Data collated included patient demographics, clinical indication for EEG, setting in which EEG was performed, activation procedures utilised, history of epilepsy, and whether the patient was on antiepileptic medication. Our primary objective was to evaluate the factors that were predictive of an EEG with epileptiform abnormalities.

RESULTS

Two hundred and thirty-nine routine EEG were included with indications, including first seizure (25.9%), known epilepsy (25.1%), cognitive change (15.9%), syncope (15.0%), movement disorder (6.7%), psychogenic non-epileptic events (5.4%), unresponsiveness/intensive care unit (4.6%) and psychiatric presentation (1.3%). Most (48.1%) EEG were normal; 8.9% of the EEG demonstrated epileptiform abnormalities. Using multivariate logistic regression, three variables proved significant in predicting an EEG with epileptiform abnormalities. Any seizure as an indication (first seizure or seizure in known epileptic), increasing patient age, and EEG conducted in an inpatient setting and within 48 h of seizure event were all statistically more likely to yield epileptiform abnormalities on EEG.

CONCLUSIONS

Our findings suggest that careful selection of patients based on appropriate indications for EEG referral would likely improve the yield of an EEG. Depending on the indication, a normal EEG result can be of similar usefulness to an abnormal EEG demonstrating epileptiform abnormalities.

Reducing seizure to needle times in nonconvulsive status epilepticus with multifaceted quality improvement initiatives

OBJECTIVES

Delayed management of nonconvulsive status epilepticus (NCSE) can lead to an increased morbidity and mortality. We previously established that inefficient treatment of NCSE at our institution stemmed from delayed initiation of emergent anti-seizure medications (ASM). In the present study, we assessed the trajectories of these time parameters and determined patient outcomes following the specific quality improvement (QI) interventions.

METHODS

The QI interventions, including the revision of the educational content for trainees and pharmacy workflow optimization were implemented between January 2019 and September 2021 by a dedicated multidisciplinary task force. The times needed to initiate and administer the ASMs for patients with NCSE as well as patient mortality were assessed in comatose and noncomatose patients and compared with the corresponding values prior to the interventions.

RESULTS

There were 79 occurrences of NCSE in 74 patients. The median time from seizure detection on EEG to the order of the first and second ASM for NCSE was reduced by 4 (p = 0.83) and 8 min (p = 0.52), respectively compared to the times prior to the initiation of interventions. The median times from the order to administration of the first and third ASM for all NCSE occurrences were reduced by 8 and 10 min, respectively (p = 0.28 and p = 0.10). In the present cohort of comatose patients, the median time spent to order the first ASM was reduced by 16.5 min and the time to administer it reduced by 35 min compared to that in our previous study. The overall patient mortality was decreased by 11.1%.

SIGNIFICANCE

More efficient delivery of rescue ASMs in patients with NCSE and improvement in their mortality can be achieved with multidisciplinary team efforts aimed at streamlining the functioning of pharmacy and strengthening the education of trainees and nurses.

Always Assess the Raw Electroencephalogram: Why Automated Burst Suppression Detection May Not Detect All Episodes

BACKGROUND

Electroencephalogram (EEG)-based monitors of anesthesia are used to assess patients' level of sedation and hypnosis as well as to detect burst suppression during surgery. One of these monitors, the Entropy module, uses an algorithm to calculate the burst suppression ratio (BSR) that reflects the percentage of suppressed EEG. Automated burst suppression detection monitors may not reliably detect this EEG pattern. Hence, we evaluated the detection accuracy of BSR and investigated the EEG features leading to errors in the identification of burst suppression.

METHODS

With our study, we were able to compare the performance of the BSR to the visual burst suppression detection in the raw EEG and obtain insights on the architecture of the unrecognized burst suppression phases.

RESULTS

We showed that the BSR did not detect burst suppression in 13 of 90 (14%) patients. Furthermore, the time comparison between the visually identified burst suppression duration and elevated BSR values strongly depended on the BSR value being used as a cutoff. A possible factor for unrecognized burst suppression by the BSR may be a significantly higher suppression amplitude ( P = .002). Six of the 13 patients with undetected burst suppression by BSR showed intraoperative state entropy values >80, indicating a risk of awareness while being in burst suppression.

CONCLUSIONS

Our results complement previous results regarding the underestimation of burst suppression by other automated detection modules and highlight the importance of not relying solely on the processed index, but to assess the native EEG during anesthesia.

Epileptiform patterns predicting unfavorable outcome in postanoxic patients: A matter of time?

OBJECTIVE

Historically, epileptiform malignant EEG patterns (EMPs) have been considered to anticipate an unfavorable outcome, but an increasing amount of evidence suggests that they are not always or invariably associated with poor prognosis. We evaluated the prognostic significance of an EMP onset in two different timeframes in comatose patients after cardiac arrest (CA): early-EMPs and late-EMPs, respectively.

METHODS

We included all comatose post-CA survivors admitted to our intensive care unit (ICU) between 2016 and 2018 who underwent at least two 30-minute EEGs, collected at T0 (12-36 h after CA) and T1 (36-72 h after CA). All EEGs recordings were re-analyzed following the 2021 ACNS terminology by two senior EEG specialists, blinded to outcome. Malignant EEGs with abundant sporadic spikes/sharp waves, rhythmic and periodic patterns, or electrographic seizure/status epilepticus, were included in the EMP definition. The primary outcome was the cerebral performance category (CPC) score at 6 months, dichotomized as good (CPC 1-2) or poor (CPC 3-5) outcome.

RESULTS

A total of 58 patients and 116 EEG recording were included in the study. Poor outcome was seen in 28 (48%) patients. In contrast to late-EMPs, early-EMPs were associated with a poor outcome (p = 0.037), persisting after multiple regression analysis. Moreover, a multivariate binomial model coupling the timing of EMP onset with other EEG predictors such as T1 reactivity and T1 normal voltage background can predict outcome in the presence of an otherwise non-specific malignant EEG pattern with quite high specificity (82%) and moderate sensitivity (77%).

CONCLUSIONS

The prognostic significance of EMPs seems strongly time-dependent and only their early-onset may be associated with an unfavorable outcome. The time of onset of EMP combined with other EEG features could aid in defining prognosis in patients with intermediate EEG patterns.

Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation?

BACKGROUND

Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical care.

OBJECTIVE

The aim of this work was to derive a proxy of autonomic functions via the RR variability and compare its diagnostic capability with known neurophysiological biomarkers of consciousness.

METHODS

In a cohort of sub-acute patients with brain injury during post-acute rehabilitation, polygraphy (ECG, EEG) recordings were collected. The EEG was labeled via descriptors based on American Clinical Neurophysiology Society terminology and the respiration variability was extracted by computing the Approximate Entropy (ApEN) of the ECG-derived respiration signal. Competing logistic regressions were applied to evaluate the improvement in model performances introduced by the RR ApEN.

RESULTS

Higher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models' performances in contrast to the ones built with only electroencephalographic descriptors.

CONCLUSIONS

Adding a quantitative, instrumentally based complexity measure of RR variability to multimodal consciousness assessment protocols may improve diagnostic accuracy based only on electroencephalographic descriptors. Overall, this study promotes the integration of biomarkers derived from the central and the autonomous nervous system for the most comprehensive diagnosis of consciousness in a rehabilitation setting.

Rhythmic mid-Temporal Theta of Drowsiness Activated by Hyperventilation- Uncommon Trigger of a Rare Benign EEG Variant in Pediatrics. An Educational Review

Distinguishing abnormal electroencephalogram (EEG) waveforms from benign variants is critical for accurate interpretation of EEG. Hyperventilation (HV) is one of the basic procedures during EEG to enable activation of epileptiform activity. Rarely, HV can activate benign EEG rhythms. Herein, we illustrate two pediatric cases with bursts of rhythmic mid-temporal theta of drowsiness (RMTD), activated by hyperventilation. Continued awareness of this EEG phenomenology and its variations in pediatrics is important in avoiding misdiagnosis of epilepsy.

Periodic discharges in veterinary electroencephalography-A visual review

First described in human EEG over 60 years ago, there are very few examples of periodic discharges in the veterinary literature. They are associated with a wide variety of etiologies, both intracranial and systemic, making interpretation challenging. Whether these patterns are indicative of ictal, interictal, or postictal activity is a matter of debate and may vary depending on the clinical features in an individual patient. Periodic discharges have a repeated waveform occurring at nearly regular intervals, with varying morphology of individual discharges from simple sharp waves or slow waves to more complex events. Amplitudes, frequencies, and morphologies of the discharges can fluctuate, occasionally evolving, or resolving over time. This study presents a visual review of several veterinary cases with periodic discharges on EEG similar to those described in human EEG, and discusses the current known pathophysiology of these discharges.

Implications of stimulus-induced, rhythmic, periodic, or ictal discharges (SIRPIDs) in hospitalized patients

Background

Stimulus-induced electroencephalographic (EEG) patterns are commonly seen in acutely ill patients undergoing continuous EEG monitoring. Despite ongoing investigations, the pathophysiology, therapeutic and prognostic significance of stimulus-induced rhythmic, periodic or ictal discharges (SIRPIDs) and how it applies to specific pathologies remain unclear. We aimed to investigate the clinical implications of SIRPIDs in hospitalized patients.

Methods

This is a retrospective single-center study of hospitalized patients from May 2016 to August 2017. We included patients above the age of 18 years who underwent >16 h of EEG monitoring during a single admission. We excluded patients with cardiac arrest and anoxic brain injury. Demographic data were obtained as well as admission GCS, and discharge modified Rankin Score (mRS). EEGs were reviewed for background activity in addition to epileptiform, periodic, and rhythmic patterns. The presence or absence of SIRPIDs was recorded. Our outcome was discharge mRS defined as good outcome, mRS 0-4, and poor outcome mRS, 5-6.

Results

A total of 351 patients were included in the final analysis. The median age was 63 years and 175 (50%) were women. SIRPIDs were identified in 82 patients (23.4%). Patients with SIRPIDs had a median initial GCS of 12 (IQR, 6-15) and a length of stay of 12 days (IQR, 6-15). They were more likely to have absent posterior dominant rhythm, decreased reactivity, and more likely to have spontaneous periodic and rhythmic patterns and higher frequency of burst suppression. After adjusting for baseline clinical variables, underlying disease type and severity, and EEG background features, the presence of SIRPIDs was also associated with poor outcomes classified as MRS 5 or 6 (OR 4.75 [2.74-8.24] p ≤ 0.0001).

Conclusion

In our cohort of hospitalized patients excluding anoxic brain injury, SIRPIDs were identified in 23.4% and were seen most commonly in patients with primary systemic illness. We found SIRPIDs were independently associated with poor neurologic outcomes. Several studies are indicated to validate these findings and determine the risks vs. benefits of anti-seizure treatment.

Normative Structure of Resting-State EEG in Bipolar Derivations for Daily Clinical Practice: A Pilot Study

We used numerical methods to define the normative structure of resting-state EEG (rsEEG) in a pilot study of 37 healthy subjects (10-74 years old), using a double-banana bipolar montage. Artifact-free 120-200 s epoch lengths were visually identified and divided into 1 s windows with a 10% overlap. Differential channels were grouped by frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum was calculated and used to compute the area for delta (0-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) bands and was log-transformed. Furthermore, Shannon's spectral entropy (SSE) and coherence by bands were computed. Finally, we also calculated the main frequency and amplitude of the posterior dominant rhythm. According to the age-dependent distribution of the bands, we divided the patients in the following three groups: younger than 20; between 21 and 50; and older than 51 years old. The distribution of bands and coherence was different for the three groups depending on the brain lobes. We described the normative equations for the three age groups and for every brain lobe. We showed the feasibility of a normative structure of rsEEG picked up with a double-banana montage.

Auditory stimulation and deep learning predict awakening from coma after cardiac arrest

Assessing the integrity of neural functions in coma after cardiac arrest remains an open challenge. Prognostication of coma outcome relies mainly on visual expert scoring of physiological signals, which is prone to subjectivity and leaves a considerable number of patients in a 'grey zone', with uncertain prognosis. Quantitative analysis of EEG responses to auditory stimuli can provide a window into neural functions in coma and information about patients' chances of awakening. However, responses to standardized auditory stimulation are far from being used in a clinical routine due to heterogeneous and cumbersome protocols. Here, we hypothesize that convolutional neural networks can assist in extracting interpretable patterns of EEG responses to auditory stimuli during the first day of coma that are predictive of patients' chances of awakening and survival at 3 months. We used convolutional neural networks (CNNs) to model single-trial EEG responses to auditory stimuli in the first day of coma, under standardized sedation and targeted temperature management, in a multicentre and multiprotocol patient cohort and predict outcome at 3 months. The use of CNNs resulted in a positive predictive power for predicting awakening of 0.83 ± 0.04 and 0.81 ± 0.06 and an area under the curve in predicting outcome of 0.69 ± 0.05 and 0.70 ± 0.05, for patients undergoing therapeutic hypothermia and normothermia, respectively. These results also persisted in a subset of patients that were in a clinical 'grey zone'. The network's confidence in predicting outcome was based on interpretable features: it strongly correlated to the neural synchrony and complexity of EEG responses and was modulated by independent clinical evaluations, such as the EEG reactivity, background burst-suppression or motor responses. Our results highlight the strong potential of interpretable deep learning algorithms in combination with auditory stimulation to improve prognostication of coma outcome.

Balancing the risks and benefits of anesthetics in status epilepticus

PURPOSE

According to international guidelines, status epilepticus refractory to first- and second-line antiseizure medication should be treated with anesthetics. Therefore, continuously delivered intravenous midazolam, propofol, or barbiturates are recommended as third-line therapy. While electroencephalographically (EEG)-controlled titration of anesthetics to seizure termination or to the emergence of an EEG burst-suppression pattern makes sense, evidence of the efficacy and tolerability of such third-line treatment is limited and concerns regarding the risks of anesthesia remain. The lack of treatment alternatives and persistent international discord reflecting contradictory results from some studies leave clinicians on their own when deciding to escalate treatment. In this conference-accompanying narrative review, we highlight the challenges of EEG-monitored third-line treatment and discuss recent studies that examined earlier administration of anesthetics.

RESULTS

Based on the literature, maintaining continuous burst suppression is difficult despite the constant administration of anesthetics, and the evidence for burst suppression as an adequate surrogate target is limited by methodological shortcomings as acknowledged by international guidelines. In our Swiss cohort including 102 patients with refractory status epilepticus, burst suppression as defined by the American Clinical Neurophysiology Society's Critical Care EEG Terminology 2021 was established in only 21%. Besides case reports suggesting that rapid but short-termed anesthesia can be sufficient to permanently stop seizures, a study including 205 patients revealed that anesthesia as second-line treatment was associated with a shorter median duration of status epilepticus (0.5 versus 12.5 days, p < 0.001), median ICU (2 versus 5.5 days, p < 0.001) and hospital stay (8 versus 17 days, p < 0.001) with equal rates of complications when compared to anesthesia as third-line treatment.

CONCLUSIONS

Recent investigations have led to important findings and new insights regarding the use of anesthetics in refractory status epilepticus. However, numerous methodological limitations and remaining questions need to be considered when it comes to the translation into clinical practice, and, in consequence, call for prospective randomized studies. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.

Benign EEG for prognostication of favorable outcome after cardiac arrest: A reappraisal

AIM

The current EEG role for prognostication after cardiac arrest (CA) essentially aims at reliably identifying patients with poor prognosis ("highly malignant" patterns, defined by Westhall et al. in 2014). Conversely, "benign EEGs", defined by the absence of elements of "highly malignant" and "malignant" categories, has limited sensitivity in detecting good prognosis. We postulate that a less stringent "benign EEG" definition would improve sensitivity to detect patients with favorable outcomes.

METHODS

Retrospectively assessing our registry of unconscious adults after CA (1.2018-8.2021), we scored EEGs within 72 h after CA using a modified "benign EEG" classification (allowing discontinuity, low-voltage, or reversed anterio-posterior amplitude development), versus Westhall's "benign EEG" classification (not allowing the former items). We compared predictive performances towards good outcome (Cerebral Performance Category 1-2 at 3 months), using 2x2 tables (and binomial 95% confidence intervals) and proportions comparisons.

RESULTS

Among 381 patients (mean age 61.9 ± 15.4 years, 104 (27.2%) females, 240 (62.9%) having cardiac origin), the modified "benign EEG" definition identified a higher number of patients with potential good outcome (252, 66%, vs 163, 43%). Sensitivity of the modified EEG definition was 0.97 (95% CI: 0.92-0.97) vs 0.71 (95% CI: 0.62-0.78) (p < 0.001). Positive predictive values (PPV) were 0.53 (95% CI: 0.46-0.59) versus 0.59 (95% CI: 0.51-0.67; p = 0.17). Similar statistics were observed at definite recording times, and for survivors.

DISCUSSION

The modified "benign EEG" classification demonstrated a markedly higher sensitivity towards favorable outcome, with minor impact on PPV. Adaptation of "benign EEG" criteria may improve efficient identification of patients who may reach a good outcome.

Detection of ictal and periictal hyperperfusion with subtraction of ictal-interictal 1.5-Tesla pulsed arterial spin labeling images co-registered to conventional magnetic resonance images (SIACOM)

Background

Our recent report showed that 1.5-T pulsed arterial spin labeling (ASL) magnetic resonance (MR) perfusion imaging (1.5-T Pulsed ASL [PASL]), which is widely available in the field of neuroemergency, is useful for detecting ictal hyperperfusion. However, the visualization of intravascular ASL signals, namely, arterial transit artifact (ATA), is more remarkable than that of 3-T pseudocontinuous ASL and is easily confused with focal hyperperfusion. To eliminate ATA and enhance the detectability of (peri) ictal hyperperfusion, we developed the subtraction of ictal-interictal 1.5-T PASL images co-registered to conventional MR images (SIACOM).

Methods

We retrospectively analyzed the SIACOM findings in four patients who underwent ASL during both (peri) ictal and interictal states and examined the detectability for (peri) ictal hyperperfusion.

Results

In all patients, the ATA of the major arteries was almost eliminated from the subtraction image of the ictal-interictal ASL. In patients 1 and 2 with focal epilepsy, SIACOM revealed a tight anatomical relationship between the epileptogenic lesion and the hyperperfusion area compared with the original ASL image. In patient 3 with situation-related seizures, SIACOM detected minute hyperperfusion at the site coinciding with the abnormal electroencephalogram area. SIACOM of patient 4 with generalized epilepsy diagnosed ATA of the right middle cerebral artery, which was initially thought to be focal hyperperfusion on the original ASL image.

Conclusion

Although it is necessary to examine several patients, SIACOM can eliminate most of the depiction of ATA and clearly demonstrate the pathophysiology of each epileptic seizure.

Large-scale transient peri-ictal perfusion magnetic resonance imaging abnormalities detected by quantitative image analysis

Epileptic seizures require a rapid and safe diagnosis to minimize the time from onset to adequate treatment. Some epileptic seizures can be diagnosed clinically with the respective expertise. For more subtle seizures, imaging is mandatory to rule out treatable structural lesions and potentially life-threatening conditions. MRI perfusion abnormalities associated with epileptic seizures have been reported in CT and MRI studies. However, the interpretation of transient peri-ictal MRI abnormalities is routinely based on qualitative visual analysis and therefore reader dependent. In this retrospective study, we investigated the diagnostic yield of visual analysis of perfusion MRI during ictal and postictal states based on comparative expert ratings in 51 patients. We further propose an automated semi-quantitative method for perfusion analysis to determine perfusion abnormalities observed during ictal and postictal MRI using dynamic susceptibility contrast MRI, which we validated on a subcohort of 27 patients. The semi-quantitative method provides a parcellation of 3D T₁-weighted images into 32 standardized cortical regions of interests and subcortical grey matter structures based on a recently proposed method, direct cortical thickness estimation using deep learning-based anatomy segmentation and cortex parcellation for brain anatomy segmentation. Standard perfusion maps from a Food and Drug Administration-approved image analysis tool (Olea Sphere 3.0) were co-registered and investigated for region-wise differences between ictal and postictal states. These results were compared against the visual analysis of two readers experienced in functional image analysis in epilepsy. In the ictal group, cortical hyperperfusion was present in 17/18 patients (94% sensitivity), whereas in the postictal cohort, cortical hypoperfusion was present only in 9/33 (27%) patients while 24/33 (73%) showed normal perfusion. The (semi-)quantitative dynamic susceptibility contrast MRI perfusion analysis indicated increased thalamic perfusion in the ictal cohort and hypoperfusion in the postictal cohort. Visual ratings between expert readers performed well on the patient level, but visual rating agreement was low for analysis of subregions of the brain. The asymmetry of the automated image analysis correlated significantly with the visual consensus ratings of both readers. We conclude that expert analysis of dynamic susceptibility contrast MRI effectively discriminates ictal versus postictal perfusion patterns. Automated perfusion evaluation revealed favourable interpretability and correlated well with the classification of the visual ratings. It may therefore be employed for high-throughput, large-scale perfusion analysis in extended cohorts, especially for research questions with limited expert rater capacity.

Altered EEG, disrupted hippocampal long-term potentiation and neurobehavioral deficits implicate a delirium-like state in a mouse model of sepsis

Sepsis and systemic inflammation are often accompanied by severe encephalopathy, sleep disruption and delirium that strongly correlate with poor clinical outcomes including long-term cognitive deficits. The cardinal manifestations of delirium are fluctuating altered mental status and inattention, identified in critically ill patients by interactive bedside assessment. The lack of analogous assessments in mouse models or clear biomarkers is a challenge to preclinical studies of delirium. In this study, we utilized concurrent measures of telemetric EEG recordings and neurobehavioral tasks in mice to characterize inattention and persistent cognitive deficits following polymicrobial sepsis. During the 24-hour critical illness period for the mice, slow-wave EEG dominance, sleep disruption, and hypersensitivity to auditory stimuli in neurobehavioral tasks resembled clinical observations in delirious patients in which alterations in similar outcome measurements, although measured differently in mice and humans, are reported. Mice were tested for nest building ability 7 days after sepsis induction, when sickness behaviors and spontaneous activity had returned to baseline. Animals that showed persistent deficits determined by poor nest building at 7 days also exhibited molecular changes in hippocampal long-term potentiation compared to mice that returned to baseline cognitive performance. Together, these behavioral and electrophysiological biomarkers offer a robust mouse model with which to further probe molecular pathways underlying brain and behavioral changes during and after acute illness such as sepsis.

Power spectrum analysis and outcomes of non-convulsive status epilepticus: a single-center study

OBJECTIVES

Diagnosis of non-convulsive status epilepticus (NCSE) is challenging and outcomes during follow-up are not clear. This study aimed to conduct power spectrum analysis in NCSE and measure outcomes of patients.

METHODS

We searched continuous EEG monitoring (cEEG) recordings to identify patients of NCSE. An artifact-free cEEG epoch of continuous 60 s was chosen for spectral power analysis. We also collected electronic medical records of the patients for extracting clinical information. Patients recruited were followed up at least every half a year.

RESULTS

There were 48 patients with 64 independent NCSE episodes during different course of disease recruited in the study, with a mean age of 40.3 ± 19.1 years (range, 12-72 years), including 24 males (50%) and 24 females (50%). When the spectral power of 60 s equaled to 11.30 μV² for predicting impairment of consciousness, (sensitivity, specificity) = (0.979, 0.625). When the spectral power of 60 s equaled to 52.70 μV² for predicting myoclonic jerks, (sensitivity, specificity) = (0.783, 0.756). There were 27 patients (56.3%) followed up with a duration over 12 months. Nineteen patients (70.4%) continued to have seizures. Eleven (40.7%) resisted to at least two kinds of appropriate anti-seizure medication at maximum tolerated levels. Five patients with prolonged NCSE suffered from loss of brain parenchymal volume on follow-up MRI scans.

CONCLUSION

Spectral power analysis can be used to detect mental status and limb jerks. Early diagnosis and treatment of NCSE are important, which can influence outcomes of the patients during follow-up.

Nonconvulsive status epilepticus following cardiac arrest: overlooked, untreated and misjudged

AIMS

Seizures and status epilepticus (SE) are detected in almost a third of the comatose cardiac arrest survivors. As the literature is quite exhaustive regarding SE with motor symptoms in those patients, little is known about nonconvulsive SE (NCSE). Our aim was to compile the evidence from the literature of the frequency and outcome of NCSE in adult patients remaining in coma after resuscitation.

METHODS

The medical search PubMed was screened for most relevant articles reporting the emergence and outcome of NCSE in comatose post-resuscitated adult patients.

RESULTS

We identified 11 cohort studies (four prospective observational, seven retrospective) including 1092 patients with SE in 29-96% and NCSE reported in 1-20%. EEG evaluation started at a median of 9.5 h (range 7.5-14.8) after cardiac arrest, during sedation and targeted temperature management (TTM). Favorable outcome after NCSE occurred in 24.5%. We found no study reporting EEG to detect or exclude NCSE in patients remaining in coma prior to the initiation of TTM and without sedation withing the first hours after ROSC.

DISCUSSION

Studies on NCSE after ROSC are scarce and unsystematic, reporting favorable outcome in every fourth patient experiencing NCSE after ROSC. This suggests that NCSE is often overlooked and outcome after NCSE is not always poor. The low data quality does not allow firm conclusions regarding the effects of NCSE on outcome calling for further investigation. In the meantime, clinicians should avoid equating NCSE after ROSC with poor prognosis.

From Alpha to Zeta: A Systematic Review of Zeta Waves

PURPOSE

Electroencephalogram is used for prognostication and diagnosis in critically ill patients and is vital in developing clinical management algorithms. Unique waveforms on EEG may distinguish neurological disorders and define a potential for seizures. To better characterize zeta waves, we sought to define their electroclinical spectrum.

METHODS

We performed a systematic review using MEDLINE, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Review [through Ovid], Scopus, Science Citation Index Expanded and Emerging Sources Citation Index [through the Web of Science], and Epistemonikos. Grey literature resources were searched.

RESULTS

Five hundred thirty-seven articles were identified. After excluding duplicates and reviewing titles, abstracts, and bodies and bibliographies of articles, four studies reported 64 cases describing data from patients with zeta waves, with a prevalence of 3 to 4%. Various and often incomplete clinical, neuroimaging, and EEG data were available. 57 patients (89.1%) had a focal cerebral lesion concordant with the location of zeta waves on EEG. 26 patients (40.6%) had clinical seizures, all but one being focal onset. Thirteen patients (20%) had epileptiform activity on EEG. Typically, zeta waves were located in the frontal head regions, often with generalized, frontal, predominant, rhythmic delta activity and associated with focal EEG suppression.

CONCLUSIONS

Zeta waves frequently represent an underlying focal structural lesion. Their presence suggests a heightened risk for seizures. The small number of retrospective cases series in the literature reporting zeta waves might be an underrepresentation. We suggest a need for prospective studies of cEEG in critically ill patients to determine their clinical significance.

Quantitative artifact reduction and pharmacologic paralysis improve detection of EEG epileptiform activity in critically ill patients

OBJECTIVE

Epileptiform activity is common in critically ill patients, but movement-related artifacts-including electromyography (EMG) and myoclonus-can obscure EEG, limiting detection of epileptiform activity. We sought to determine the ability of pharmacologic paralysis and quantitative artifact reduction (AR) to improve epileptiform discharge detection.

METHODS

Retrospective analysis of patients who underwent continuous EEG monitoring with pharmacologic paralysis. Four reviewers read each patient's EEG pre- and post- both paralysis and AR, and indicated the presence of epileptiform discharges. We compared the interrater reliability (IRR) of identifying discharges at baseline, post-AR, and post-paralysis, and compared the performance of AR and paralysis according to artifact type.

RESULTS

IRR of identifying epileptiform discharges at baseline was slight (N = 30; κ = 0.10) with a trend toward increase post-AR (κ = 0.26, p = 0.053) and a significant increase post-paralysis (κ = 0.51, p = 0.001). AR was as effective as paralysis at improving IRR of identifying discharges in those with high EMG artifact (N = 15; post-AR κ = 0.63, p = 0.009; post-paralysis κ = 0.62, p = 0.006) but not with primarily myoclonus artifact (N = 15).

CONCLUSIONS

Paralysis improves detection of epileptiform activity in critically ill patients when movement-related artifact obscures EEG features. AR improves detection as much as paralysis when EMG artifact is high, but is ineffective when the primary source of artifact is myoclonus.

SIGNIFICANCE

In the appropriate setting, both AR and paralysis facilitate identification of epileptiform activity in critically ill patients.

Rapid response EEG with needle electrodes in an intensive care unit with limited resources

Objective

Continuous EEG (cEEG) is the gold standard for detecting seizures and rhythmic and periodic patterns (RPPs) in critically ill patients but is often not available in health systems with limited resources. The current study aims to determine the feasibility and utility of low-cost, practical, limited montage, sub-dermal needle electrode EEG in a setting where otherwise no EEG would be available.

Methods

The study included all adult patients admitted to the intensive care unit of a single center over a 24-month period. Members of the existing ICU care team, mostly nurses, were trained to place 8 sub-dermal needle EEG electrodes to achieve rapid, limited montage-EEG recording. Clinical outcomes were recorded, including any reported major complications; and the EEG findings documented, including background characterization, RPPs, and seizures.

Results

One hundred twenty-three patients, mean age 68 years, underwent an average of 15.6 min of EEG recording. There were no complications of electrode placement. Overall, 13.0% had seizures (8.1% qualifying as status epilepticus [SE]), 18.7 % had generalized periodic discharges (GPDs), 4.9% had lateralized periodic discharges (LPDs), and 11.4 % sporadic epileptiform discharges (sEDs). Greater mortality was observed in patients with worse background EEGs, seizures, LPDs, or sEDs.

Conclusions

Rapid, limited montage EEG could be achieved safely and inexpensively in a broad population of critically ill patients following minimal training of existing care teams.

Significance

For resource poor centers or centers outside of major metropolitan areas who otherwise have no access to EEG, this may prove a useful method for screening for non-convulsive seizures and status epilepticus.

Early Neurological ASsessment with pupillometrY during Cardiac Arrest REsuscitation (EASY-CARE): protocol for an observational multicentre prospective study

INTRODUCTION

Out-of-hospital cardiac arrest is burdened with a high rate of ineffective resuscitation and poor neurological outcome among survivors. To date, there are few perfusion assessment tools during cardiopulmonary resuscitation and none of them provide reliable data. Despite the lack of information, physicians must decide whether to extend or terminate resuscitation efforts.

METHOD AND ANALYSIS

This is a multicentre prospective, observational cohort study, involving adult patients, victims of unexpected out-of-hospital cardiac arrest. Early Neurological ASsessment with pupillometrY during Cardiac Arrest Resuscitation aims to primarily describe the reliability of quantitative pupillometry through use of the Neurological Pupillary Index (NPi) during the manoeuvre of cardiopulmonary resuscitation, as a predictor of the return of spontaneous circulation. The second objective is to seek and describe the association between the NPi and neurological outcome in the surviving cohort. Patients will be excluded if they are less than 18 years of age, have sustained traumatic brain injury, cerebrovascular emergencies, direct injury to the eyes or have pupil anomalies. Neurological outcome will be collected at intensive care unit discharge, at 30 days, 6 months and at 1 year. The Glasgow Coma Scale (GCS) will be used in the emergency department; modified Rankin Score will be adopted for neurological assessment; biomarkers and neurophysiology exams will be collected as well.

ETHICS AND DISSEMINATION

The study has been approved by Ethics Committee of Milano. Local committee acceptance is required for each of the centres involved in the clinical and follow-up data collection. Data will be disseminated to the scientific community through original articles submitted to peer-reviewed journals and abstracts to conferences.

TRIAL REGISTRATION NUMBER

NCT05192772.

Prognostication after cardiac arrest: how EEG and evoked potentials may improve the challenge

About 80% of patients resuscitated from CA are comatose at ICU admission and nearly 50% of survivors are still unawake at 72 h. Predicting neurological outcome of these patients is important to provide correct information to patient's relatives, avoid disproportionate care in patients with irreversible hypoxic-ischemic brain injury (HIBI) and inappropriate withdrawal of care in patients with a possible favorable neurological recovery. ERC/ESICM 2021 algorithm allows a classification as "poor outcome likely" in 32%, the outcome remaining "indeterminate" in 68%. The crucial question is to know how we could improve the assessment of both unfavorable but also favorable outcome prediction. Neurophysiological tests, i.e., electroencephalography (EEG) and evoked-potentials (EPs) are a non-invasive bedside investigations. The EEG is the record of brain electrical fields, characterized by a high temporal resolution but a low spatial resolution. EEG is largely available, and represented the most widely tool use in recent survey examining current neuro-prognostication practices. The severity of HIBI is correlated with the predominant frequency and background continuity of EEG leading to "highly malignant" patterns as suppression or burst suppression in the most severe HIBI. EPs differ from EEG signals as they are stimulus induced and represent the summated activities of large populations of neurons firing in synchrony, requiring the average of numerous stimulations. Different EPs (i.e., somato sensory EPs (SSEPs), brainstem auditory EPs (BAEPs), middle latency auditory EPs (MLAEPs) and long latency event-related potentials (ERPs) with mismatch negativity (MMN) and P300 responses) can be assessed in ICU, with different brain generators and prognostic values. In the present review, we summarize EEG and EPs signal generators, recording modalities, interpretation and prognostic values of these different neurophysiological tools. Finally, we assess the perspective for futures neurophysiological investigations, aiming to reduce prognostic uncertainty in comatose and disorders of consciousness (DoC) patients after CA.

EEG-Delta brushes in DPPX encephalitis - Welcome to the club

Background

Extreme Delta Brushes are a rare interictal EEG pattern that was first described in NMDA-R encephalitis and has been considered a pathognomonic pattern for this subtype of autoimmune encephalitis. Recently, extreme delta brushes have been described as a rare EEG phenomenon in other forms of encephalitis.

Case report

We describe to our knowledge the first occurrence of EEG Delta brushes in DPPX encephalitis. In this article, we present a comprehensive case report and discuss clinical differential diagnosis with special emphasis on the diagnostic value of the EEG, leading the way to the correct diagnosis. We also present current diagnostic criteria and clinical screening scales for initial evaluation for patients with suspected autoimmune encephalitis.

EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review

OBJECTIVE

Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in patients with DoC in a rehabilitation setting.

METHODS

We conducted a systematic literature search of EEG-based strategies for consciousness recovery prognosis in five electronic databases.

RESULTS

The search resulted in 2964 papers. After screening, 15 studies were included in the review. Our analyses revealed that simpler experimental settings and similar filtering cut-off frequencies are preferred. The results of studies were categorised by extracting qualitative and quantitative features. The quantitative features were further classified into evoked/event-related potentials, spectral measures, entropy measures, and graph-theory measures. Despite the variety of methods, features from all categories, including qualitative ones, exhibited significant correlations with DoC prognosis. Moreover, no agreement was found on the optimal set of EEG-based features for the multivariate prognosis of patients with DoC, which limits the computational methods applied for outcome prediction and correlation analysis to classical ones. Nevertheless, alpha power, reactivity, and higher complexity metrics were often found to be predictive of consciousness recovery.

CONCLUSIONS

This study's findings confirm the essential role of qualitative EEG and suggest an important role for quantitative EEG. Their joint use could compensate for their reciprocal limitations.

SIGNIFICANCE

This study emphasises the need for further efforts toward guidelines on standardised EEG analysis pipeline, given the already proven role of EEG markers in the recovery prognosis of patients with DoC.

Paroxysmal fast activity is a biomarker of treatment response in deep brain stimulation for Lennox-Gastaut syndrome

OBJECTIVE

Epilepsy treatment trials typically rely on seizure diaries to determine seizure frequency, but these are time-consuming and difficult to maintain accurately. Fast, reliable, and objective biomarkers of treatment response are needed, particularly in Lennox-Gastaut syndrome (LGS), where high seizure frequency and comorbid cognitive and behavioral issues are additional obstacles to accurate diary-keeping. Here, we measured generalized paroxysmal fast activity (GPFA), a key interictal electrographic feature of LGS, and correlated GPFA burden with seizure diaries during a thalamic deep brain stimulation (DBS) treatment trial (Electrical Stimulation of the Thalamus in Epilepsy of Lennox-Gastaut Phenotype [ESTEL]).

METHODS

GPFA and electrographic seizure counts from intermittent, 24-h electroencephalograms (EEGs) were compared to 3-month diary-recorded seizure counts in 17 young adults with LGS (mean age ± SD = 24.9 ± 6.6) in the ESTEL study, a randomized clinical trial of DBS lasting 12 months (comprising a 3-month baseline and 9 months of postimplantation follow-up).

RESULTS

Baseline median seizures measured by diaries numbered 2.6 (interquartile range [IQR] = 1.4-5) per day, compared to 284 (IQR = 120.5-360) electrographic seizures per day, confirming that diaries capture only a small fraction of seizure burden. Across all patient EEGs, the average number of GPFA discharges per hour of sleep was 138 (IQR =72-258). GPFA duration and frequency, quantified over 2-h windows of sleep EEG, were significantly associated with diary-recorded seizure counts over 3-month intervals (p < .001, η2 p  = .30-.48). For every GPFA discharge, there were 20-25 diary seizures witnessed over 3 months. There was high between-patient variability in the ratio between diary seizure burden and GPFA burden; however, within individual patients, the ratio was similar over time, such that the percentage change from pre-DBS baseline in seizure diaries strongly correlated with the percentage change in GPFA.

SIGNIFICANCE

When seeking to optimize treatment in patients with LGS, monitoring changes in GPFA may allow rapid titration of treatment parameters, rather than waiting for feedback from seizure diaries.

Interictal epileptiform discharges as a predictive biomarker for recurrence of poststroke epilepsy

Poststroke epilepsy is a major ischaemic/haemorrhagic stroke complication. Seizure recurrence risk estimation and early therapeutic intervention are critical, given the association of poststroke epilepsy with worse functional outcomes, quality of life and greater mortality. Several studies have reported risk factors for seizure recurrence; however, in poststroke epilepsy, the role of EEG in predicting the risk of seizures remains unclear. This multicentre observational study aimed to clarify whether EEG findings constitute a risk factor for seizure recurrence in patients with poststroke epilepsy. Patients with poststroke epilepsy were recruited from the PROgnosis of POst-Stroke Epilepsy study, an observational multicentre cohort study. The enrolled patients with poststroke epilepsy were those admitted at selected hospitals between November 2014 and June 2017. All patients underwent EEG during the interictal period during admission to each hospital and were monitored for seizure recurrence over 1 year. Board-certified neurologists or epileptologists evaluated all EEG findings. We investigated the relationship between EEG findings and seizure recurrence. Among 187 patients with poststroke epilepsy (65 were women with a median age of 75 years) admitted to the lead hospital, 48 (25.7%) had interictal epileptiform discharges on EEG. During the follow-up period (median, 397 days; interquartile range, 337-450 days), interictal epileptiform discharges were positively correlated with seizure recurrence (hazard ratio, 3.82; 95% confidence interval, 2.09-6.97; P < 0.01). The correlation remained significant even after adjusting for age, sex, severity of stroke, type of stroke and generation of antiseizure medications. We detected periodic discharges in 39 patients (20.9%), and spiky/sharp periodic discharges were marginally associated with seizure recurrence (hazard ratio, 1.85; 95% confidence interval, 0.93-3.69; P = 0.08). Analysis of a validation cohort comprising 187 patients with poststroke epilepsy from seven other hospitals corroborated the association between interictal epileptiform discharges and seizure recurrence. We verified that interictal epileptiform discharges are a risk factor for seizure recurrence in patients with poststroke epilepsy. Routine EEG may facilitate the estimation of seizure recurrence risk and the development of therapeutic regimens for poststroke epilepsy.

Human periventricular nodular heterotopia shows several interictal epileptic patterns and hyperexcitability of neuronal firing

Periventricular nodular heterotopia (PNH) is a malformation of cortical development that frequently causes drug-resistant epilepsy. The epileptogenicity of ectopic neurons in PNH as well as their role in generating interictal and ictal activity is still a matter of debate. We report the first in vivo microelectrode recording of heterotopic neurons in humans. Highly consistent interictal patterns (IPs) were identified within the nodules: (1) Periodic Discharges PLUS Fast activity (PD+F), (2) Sporadic discharges PLUS Fast activity (SD+F), and (3) epileptic spikes (ES). Neuronal firing rates were significantly modulated during all IPs, suggesting that multiple IPs were generated by the same local neuronal populations. Furthermore, firing rates closely followed IP morphologies. Among the different IPs, the SD+F pattern was found only in the three nodules that were actively involved in seizure generation but was never observed in the nodule that did not take part in ictal discharges. On the contrary, PD+F and ES were identified in all nodules. Units that were modulated during the IPs were also found to participate in seizures, increasing their firing rate at seizure onset and maintaining an elevated rate during the seizures. Together, nodules in PNH are highly epileptogenic and show several IPs that provide promising pathognomonic signatures of PNH. Furthermore, our results show that PNH nodules may well initiate seizures.

Therapeutically induced EEG burst-suppression pattern to treat refractory status epilepticus—what is the evidence?

Current guidelines advocate to treat refractory status epilepticus (RSE) with continuously administered anesthetics to induce an artificial coma if first- and second-line antiseizure drugs have failed to stop seizure activity. A common surrogate for monitoring the depth of the artificial coma is the appearance of a burst-suppression pattern (BS) in the EEG. This review summarizes the current knowledge on the origin and neurophysiology of the BS phenomenon as well as the evidence from the literature for the presumed benefit of BS as therapy in adult patients with RSE.

Severe encephalopathy associated with SARS-CoV-2 Omicron BA.1 variant infection in a neonate

INTRODUCTION

The coronavirus disease 2019 (COVID-19), including the Omicron variant, is less severe in children than in adults. To date, there has been no detailed description of COVID-19-associated severe encephalopathy due to the Omicron variant during the neonatal and early infantile periods.

CASE PRESENTATION

During the outbreak of the Omicron variant, a 29-day-old male presented with a pale and ill appearance. The patient was intubated for mechanical ventilation owing to recurrent apnea, which subsequently turned out to be a breath-holding that may have been caused by seizure. In addition, nonconvulsive status epilepticus was observed. Total duration of repetitive seizure activities was approximately 30 min per hour when seizures were most severe. Brain magnetic resonance imaging (MRI) on day 14 revealed extensive hyperintensity in the T2 sequence, hypointensity in the fluid-attenuated inversion recovery (FLAIR) sequence in the deep and subcortical white matter, and diffusion restriction in the corpus callosum. The Omicron BA.1 variant of the severe acute respiratory syndrome coronavirus 2 was detected in his respiratory sample. Follow-up MRI on day 45 revealed multiple cystic cavitations.

CONCLUSION

Although COVID-19 is not severe in most children, life-threatening conditions such as COVID-19-associated severe encephalopathy can occur during the neonatal and early infantile periods.

Repetitive Electroencephalography as Biomarker for the Prediction of Survival in Patients with Post-Hypoxic Encephalopathy

Predicting survival in patients with post-hypoxic encephalopathy (HE) after cardiopulmonary resuscitation is a challenging aspect of modern neurocritical care. Here, continuous electroencephalography (cEEG) has been established as the gold standard for neurophysiological outcome prediction. Unfortunately, cEEG is not comprehensively available, especially in rural regions and developing countries. The objective of this monocentric study was to investigate the predictive properties of repetitive EEGs (rEEGs) with respect to 12-month survival based on data for 199 adult patients with HE, using log-rank and multivariate Cox regression analysis (MCRA). A total number of 59 patients (29.6%) received more than one EEG during the first 14 days of acute neurocritical care. These patients were analyzed for the presence of and changes in specific EEG patterns that have been shown to be associated with favorable or poor outcomes in HE. Based on MCRA, an initially normal amplitude with secondary low-voltage EEG remained as the only significant predictor for an unfavorable outcome, whereas all other relevant parameters identified by univariate analysis remained non-significant in the model. In conclusion, rEEG during early neurocritical care may help to assess the prognosis of HE patients if cEEG is not available.

How to evaluate and assess the epileptogenic/seizure potential of periodic discharges along the ictal-interictal continuum?

The ictal–interictal continuum (IIC) is a concept used for those particular EEG patterns that do not meet the strict criteria for status epilepticus but may be associated with neuronal injury. The aim of this article is to review equivocal periodic patterns and to discuss their clinical significance along the IIC. The risk of seizures increases when the frequency of periodic discharges exceeds 2 Hz and when the pattern has features of superimposed rhythmic, sharp, or fast activity (plus modifier). Lateralized periodic discharges (LPDs) are one of the best examples of the IIC. Criteria have been proposed for identifying patterns along the IIC that we called “peri-ictal” LPDs. There is ongoing debate about when to treat patients with these EEG patterns along this spectrum. The term IIC is only an EEG description, and does not in itself reflect a clinical diagnosis, hence management is based on EEG alone. The decision to intensify treatment is based on the combination of EEG, the underlying etiology, the level of consciousness, comorbidities, imaging, and other surrogates of “damage.”

Critical care management of meningitis and encephalitis: an update

PURPOSE OF REVIEW

Meningitis and encephalitis represent severe neurological syndromes associated with encephalopathy, seizures, focal deficits, and neurological sequelae in survivors. We update on the critical care management of adult patients with severe meningitis and encephalitis.

RECENT FINDINGS

Large multicenter studies conducted in the adult population improved current knowledge on the epidemiology and outcomes of patients with severe meningitis and encephalitis. An early multimodal diagnostic workup (including CSF analysis, brain MRI, EEG, and serum studies) is mandatory for diagnosis and prognostication in those patients.New diagnostic methods, including multiplex PCR and next-generation sequencing techniques, allow for a faster differential diagnosis of infectious causes that may require specific antimicrobial therapy. Autoimmune causes of encephalitis, which may require urgent immunotherapy, are also increasingly recognized in the ICU setting. Although observational data suggest that early combined immunotherapy is associated with better neurological outcomes in patients with autoimmune encephalitis, randomized clinical trials have yet to be performed.

SUMMARY

Our review highlights the importance of an early multimodal approach for diagnosing severe meningitis and encephalitis. Randomized clinical trials are needed to identify pharmacological interventions that may improve patients' outcomes.

Electroencephalogram in the intensive care unit: a focused look at acute brain injury

Over the past decades, electroencephalography (EEG) has become a widely applied and highly sophisticated brain monitoring tool in a variety of intensive care unit (ICU) settings. The most common indication for EEG monitoring currently is the management of refractory status epilepticus. In addition, a number of studies have associated frequent seizures, including nonconvulsive status epilepticus (NCSE), with worsening secondary brain injury and with worse outcomes. With the widespread utilization of EEG (spot and continuous EEG), rhythmic and periodic patterns that do not fulfill strict seizure criteria have been identified, epidemiologically quantified, and linked to pathophysiological events across a wide spectrum of critical and acute illnesses, including acute brain injury. Increasingly, EEG is not just qualitatively described, but also quantitatively analyzed together with other modalities to generate innovative measurements with possible clinical relevance. In this review, we discuss the current knowledge and emerging applications of EEG in the ICU, including seizure detection, ischemia monitoring, detection of cortical spreading depolarizations, assessment of consciousness and prognostication. We also review some technical aspects and challenges of using EEG in the ICU including the logistics of setting up ICU EEG monitoring in resource-limited settings.

Electric Source Imaging in Presurgical Evaluation of Epilepsy: An Inter-Analyser Agreement Study

Electric source imaging (ESI) estimates the cortical generator of the electroencephalography (EEG) signals recorded with scalp electrodes. ESI has gained increasing interest for the presurgical evaluation of patients with drug-resistant focal epilepsy. In spite of a standardised analysis pipeline, several aspects tailored to the individual patient involve subjective decisions of the expert performing the analysis, such as the selection of the analysed signals (interictal epileptiform discharges and seizures, identification of the onset epoch and time-point of the analysis). Our goal was to investigate the inter-analyser agreement of ESI in presurgical evaluations of epilepsy, using the same software and analysis pipeline. Six experts, of whom five had no previous experience in ESI, independently performed interictal and ictal ESI of 25 consecutive patients (17 temporal, 8 extratemporal) who underwent presurgical evaluation. The overall agreement among experts for the ESI methods was substantial (AC1 = 0.65; 95% CI: 0.59–0.71), and there was no significant difference between the methods. Our results suggest that using a standardised analysis pipeline, newly trained experts reach similar ESI solutions, calling for more standardisation in this emerging clinical application in neuroimaging.

Ketamine for Management of Neonatal and Pediatric Refractory Status Epilepticus

BACKGROUND AND OBJECTIVES

Few data are available regarding the use of anesthetic infusions for refractory status epilepticus (RSE) in children and neonates, and ketamine use is increasing despite limited data. We aimed to describe the impact of ketamine for RSE in children and neonates.

METHODS

Retrospective single-center cohort study of consecutive patients admitted to the intensive care units of a quaternary care children's hospital treated with ketamine infusion for RSE.

RESULTS

Sixty-nine patients were treated with a ketamine infusion for RSE. The median age at onset of RSE was 0.7 years (interquartile range 0.15-7.2), and the cohort included 13 (19%) neonates. Three patients (4%) had adverse events requiring intervention during or within 12 hours of ketamine administration, including hypertension in 2 patients and delirium in 1 patient. Ketamine infusion was followed by seizure termination in 32 patients (46%), seizure reduction in 19 patients (28%), and no change in 18 patients (26%).

DISCUSSION

Ketamine administration was associated with few adverse events, and seizures often terminated or improved after ketamine administration. Further data are needed comparing first-line and subsequent anesthetic medications for treatment of pediatric and neonatal RSE.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence on the therapeutic utility of ketamine for treatment of RSE in children and neonates.

Timing matters: there are significant differences in short-term outcomes between two time points of status epilepticus

Background

In 2015, the International League Against Epilepsy proposed a new conceptual definition of status epilepticus (SE) with two operational dimensions (t1 and t2) to guide emergency treatment. The purpose of this study was to compare clinical characteristics and prognoses of patients at these two different time points.

Methods

We conducted a prospective observational cohort study of consecutive adults diagnosed with SE. In case of convulsive SE, t1 is 5 min and t2 is 30 min, whereas in case of focal SE with impaired consciousness, t1 is 10 min, t2 is 60 min. Data on clinical characteristics, including age, gender, history of prior seizures, neuroimaging, semiology, duration, and etiology of SE, were collected. The primary outcome was mortality, with seizure recurrence as a secondary measure, and functional status as tertiary outcome of enrolled patients at 3 months after SE onset.

Results

We screened one hundred patients with SE, with a median age of 66 years and 61% were male. Fifty-six (56.0%) patients reached t1 of SE, while 44 (44.0%) reached t2 of SE. Convulsive SE (52.0%, n = 52) was more common than focal SE with impaired consciousness (48.0%, n = 48). Status epilepticus secondary to an acute symptomatic process was the most common (50%, n = 50). Patients meeting t2 of SE demonstrated a remarkably increased risk of mortality (unadjusted analysis-RR 3.606, 95%CI 1.552–8.376, p = 0.003; adjusted analysis-RR 2.924, 95%CI 1.221–7.003, p = 0.016) and unfavorable functional status (unadjusted analysis-RR 1.803, 95%CI 1.280–2.539, p = 0.001; adjusted analysis-RR 1.664, 95%CI 1.184–2.340, p = 0.003) at 3 months compared to those who only reached t1 of SE. Patients reaching t2 of SE were more likely to experience seizure recurrence, however, there was no significant difference between the two cohorts.

Conclusions

Our study provides strong support for the new definition of SE. Patients meeting t2 of SE tend to have a remarkably increased risk of mortality and unfavorable functional outcomes compared to those who only reached t1 of SE. Furthermore, patients were likely to experience seizure recurrence after undergoing an episode of SE. Physicians must be educated about prompt recognition and appropriate management of SE.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02868-y.

Bayesian Outcome Prediction After Resuscitation From Cardiac Arrest

BACKGROUND AND OBJECTIVES

Postarrest prognostication research does not typically account for the sequential nature of real-life data acquisition and interpretation and reports nonintuitive estimates of uncertainty. Bayesian approaches offer advantages well suited to prognostication. We used Bayesian regression to explore the usefulness of sequential prognostic indicators in the context of prior knowledge and compared this with a guideline-concordant algorithm.

METHODS

We included patients hospitalized at a single center after cardiac arrest. We extracted prospective data and assumed these data accrued over time as in routine practice. We considered predictors demographic and arrest characteristics, initial and daily neurologic examination, laboratory results, therapeutic interventions, brain imaging, and EEG. We fit Bayesian hierarchical generalized linear multivariate models predicting discharge Cerebral Performance Category (CPC) 4 or 5 (poor outcomes) vs 1-3 including sequential clinical and prognostic data. We explored outcome posterior probability distributions (PPDs) for individual patients and overall. As a comparator, we applied the 2021 European Resuscitation Council and European Society of Intensive Care Medicine (ERC/ESICM) guidelines.

RESULTS

We included 2,692 patients of whom 864 (35%) were discharged with a CPC 1-3. Patients' outcome PPDs became narrow and shifted toward 0 or 1 as sequentially acquired information was added to models. These changes were largest after arrest characteristics and initial neurologic examination were included. Using information typically available at or before intensive care unit admission, sensitivity predicting poor outcome was 51% with a 0.6% false-positive rate. In our most comprehensive model, sensitivity for poor outcome prediction was 76% with 0.6% false-positive rate (FPR). The ERC/ESICM algorithm applied to 547 of 2,692 patients and yielded 36% sensitivity with 0% FPR.

DISCUSSION

Bayesian models offer advantages well suited to prognostication research. On balance, our findings support the view that in expert hands, accurate neurologic prognostication is possible in many cases before 72 hours postarrest. Although we caution against early withdrawal of life-sustaining therapies, rapid outcome prediction can inform clinical decision making and future clinical trials.

Perioperative electroencephalography in cardiac surgery with hypothermic circulatory arrest: a narrative review

OBJECTIVES

Cardiac surgery with hypothermic circulatory arrest (HCA) is associated with neurological morbidity of variable severity and electroencephalography (EEG) is a sensitive proxy measure of brain injury. We conducted a narrative review of the literature to evaluate the role of perioperative EEG monitoring in cardiac surgery involving HCA.

METHODS

Medline, Embase, Central and LILACS databases were searched to identify studies utilizing perioperative EEG during surgery with HCA in all age groups, published since 1985 in any language. We aimed to compare EEG use with no use but due to the lack of comparative studies, we performed a narrative review of its utility. Two or more reviewers independently screened studies for eligibility and extracted data.

RESULTS

Fourty single-centre studies with a total of 3287 patients undergoing surgery were identified. Most were observational cohort studies (34, 85%) with only 1 directly comparing EEG use with no use. EEG continuity (18, 45%), seizures (15, 38%) and electrocerebral inactivity prior to circulatory arrest (15, 38%) were used to detect, monitor, prevent and prognose neurological injury. Neurological dysfunction was reported in almost all studies and occurred in 0-21% of patients. However, the heterogeneity of reported clinical and EEG outcome measures prevented meta-analysis.

CONCLUSIONS

EEG is used to detect cortical ischaemia and seizures and predict neurological abnormalities and may guide intraoperative cerebral protection. However, there is a lack of comparative data demonstrating the benefit of perioperative EEG monitoring. Use of a standardized methodology for performing EEG and reporting outcome metrics would facilitate the conduct of high-quality clinical trials.