Yield of intermittent versus continuous EEG in comatose survivors of cardiac arrest treated with hypothermia

Utility and rationale for continuous EEG monitoring: a primer for the general intensivist

This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.

The Evolving Role of Electroencephalography in Postarrest Care

Electroencephalography is an accessible, portable, noninvasive and safe means of evaluating a patient's brain activity. It can aid in diagnosis and management decisions for post-cardiac arrest patients with seizures, myoclonus and other non-epileptic movements. It also plays an important role in a multimodal approach to neuroprognostication predicting both poor and favorable outcomes. Individuals ordering, performing and interpreting these tests, regardless of the indication, should understand the supporting evidence, logistical considerations, limitations and impact the results may have on postarrest patients and their families as outlined herein.

Lance-Adams Syndrome in the Intensive Care Unit: A Case Report

Lance-Adams syndrome (LAS), or chronic post-hypoxic myoclonus, is a myoclonic disorder following acute cerebral hypoxia after successful cardiopulmonary resuscitation (CPR). LAS is distinct from acute post-hypoxic myoclonus (acute PHM), presenting with myoclonic jerks and cerebellar ataxia after regaining consciousness. However, the overlap at the onset complicates differentiation and may lead to the withdrawal of life-sustaining measures, especially in sedated ICU patients. The presented case involves a 77-year-old male diagnosed with LAS post-CPR. Despite the presence of early myoclonic jerks EEG, laboratory testing, and neuroimaging showed no definitive proof of irreversible neurological damage. Once diagnosed, treatment involved sequential antiseizure medications and physical therapy when the patient achieved full consciousness. However, the patient ultimately faced severe disabilities and was unable to recover. This case report emphasizes the importance of limiting sedation, comprehensive clinical examination, and the use of complementary tests when no definitive proof of irreversible neurological damage is present after acute cerebral hypoxia. While LAS has a better vital prognosis than acute PHM, it is associated with poor neurofunctional recovery and chronic disability in most cases. Further research is essential for evidence-based management.

Value of EEG in outcome prediction of hypoxic-ischemic brain injury in the ICU: A narrative review

Prognostication of comatose patients after cardiac arrest aims to identify patients with a large probability of favourable or unfavouble outcome, usually within the first week after the event. Electroencephalography (EEG) is a technique that is increasingly used for this purpose and has many advantages, such as its non-invasive nature and the possibility to monitor the evolution of brain function over time. At the same time, use of EEG in a critical care environment faces a number of challenges. This narrative review describes the current role and future applications of EEG for outcome prediction of comatose patients with postanoxic encephalopathy.

Relationship between serum neuron-specific enolase and EEG after cardiac arrest: A reappraisal

OBJECTIVE

Electroencephalogram (EEG) and serum neuron specific enolase (NSE) are frequently used prognosticators after cardiac arrest (CA). This study explored the association between NSE and EEG, considering the role of EEG timing, its background continuity, reactivity, occurrence of epileptiform discharges, and pre-defined malignancy degree.

METHODS

Retrospective analysis including 445 consecutive adults from a prospective registry, surviving the first 24 hours after CA and undergoing multimodal evaluation. EEG were interpreted blinded to NSE results.

RESULTS

Higher NSE was associated with poor EEG prognosticators, such as increasing malignancy, repetitive epileptiform discharges and lack of background reactivity, independently of EEG timing (including sedation and temperature). When stratified for background continuity, NSE was higher with repetitive epileptiform discharges, except in the case of suppressed EEGs. This relationship showed some variation according to the recording time.

CONCLUSIONS

Neuronal injury after CA, reflected by NSE, correlates with several EEG features: increasing EEG malignancy, lack of background reactivity, and presence of repetitive epileptiform discharges. The correlation between epileptiform discharges and NSE is influenced by underlying EEG background and timing.

SIGNIFICANCE

This study, describing the complex interplay between serum NSE and epileptiform features, suggests that epileptiform discharges reflect neuronal injury particularly in non-suppressed EEG.

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.

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.

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.

Management of Refractory Status Epilepticus: An International Cohort Study (MORSE CODe) Analysis of Patients Managed in the ICU

BACKGROUND AND OBJECTIVES

Status epilepticus that continues after the initial benzodiazepine and a second anticonvulsant medication is known as refractory status epilepticus (RSE). Management is highly variable because adequately powered clinical trials are missing. We aimed to determine whether propofol and midazolam were equally effective in controlling RSE in the intensive care unit, focusing on management in resource-limited settings.

METHODS

Patients with RSE treated with midazolam or propofol between January 2015 and December 2018 were retrospectively identified among 9 centers across 4 continents from upper-middle-income economies in Latin America and high-income economies in North America, Europe, and Asia. Demographics, Status Epilepticus Severity Score, etiology, treatment details, and discharge modified Rankin Scale (mRS) were collected. The primary outcome measure was good functional outcome defined as a mRS score of 0-2 at hospital discharge.

RESULTS

Three hundred eighty-seven episodes of RSE (386 patients) were included, with 162 (42%) from upper-middle-income and 225 (58%) from high-income economies. Three hundred six (79%) had acute and 79 (21%) remote etiologies. Initial RSE management included midazolam in 266 (69%) and propofol in 121 episodes (31%). Seventy episodes (26%) that were initially treated with midazolam and 42 (35%) with propofol required the addition of a second anesthetic to treat RSE. Baseline characteristics and outcomes of patients treated with midazolam or propofol were similar. Breakthrough (odds ratio [OR] 1.6, 95% CI 1.3-2.0) and withdrawal seizures (OR 2.0, 95% CI 1.7-2.5) were associated with an increased number of days requiring continuous intravenous anticonvulsant medications (cIV-ACMs). Prolonged EEG monitoring was associated with fewer days of cIV-ACMs (1-24 hours OR 0.5, 95% CI 0.2-0.9, and >24 hours OR 0.7, 95% CI 0.5-1.0; reference EEG <1 hour). This association was seen in both, high-income and upper-middle-income economies, but was particularly prominent in high-income countries. One hundred ten patients (28%) were dead, and 80 (21%) had good functional outcomes at hospital discharge.

DISCUSSION

Outcomes of patients with RSE managed in the intensive care unit with propofol or midazolam infusions are comparable. Prolonged EEG monitoring may allow physicians to decrease the duration of anesthetic infusions safely, but this will depend on the implementation of RSE management protocols. Goal-directed management approaches including EEG targets may hold promise for patients with RSE.

CLASSIFICATION OF EVIDENCE

This study provides Class III data that propofol and midazolam are equivalently efficacious for RSE.

Conventional and Investigational Approaches Leveraging Clinical EEG for Prognosis in Acute Disorders of Consciousness

Prediction of recovery of consciousness after severe brain injury is difficult and limited by a lack of reliable, standardized biomarkers. Multiple approaches for analysis of clinical electroencephalography (EEG) that shed light on prognosis in acute severe brain injury have emerged in recent years. These approaches fall into two major categories: conventional characterization of EEG background and quantitative measurement of resting state or stimulus-induced EEG activity. Additionally, a small number of studies have associated the presence of electrophysiologic sleep features with prognosis in the acute phase of severe brain injury. In this review, we focus on approaches for the analysis of clinical EEG that have prognostic significance and that could be readily implemented with minimal additional equipment in clinical settings, such as intensive care and intensive rehabilitation units, for patients with acute disorders of consciousness.

Continuous versus routine EEG in patients after cardiac arrest-Analysis of a randomized controlled trial (CERTA) - RESUS-D-22-00369

BACKGROUND

Electroencephalography (EEG) is essential to assess prognosis in patients after cardiac arrest (CA). Use of continuous EEG (cEEG) is increasing in critically-ill patients, but it is more resource-consuming than routine EEG (rEEG). Observational studies did not show a major impact of cEEG versus rEEG on outcome, but randomized studies are lacking.

METHODS

We analyzed data of the CERTA trial (NCT03129438), including comatose adults after CA undergoing cEEG (30-48 hours) or two rEEG (20-30 minutes each). We explored correlations between recording EEG type and mortality (primary outcome), or Cerebral Performance Categories (CPC, secondary outcome), assessed blindly at 6 months, using uni- and multivariable analyses (adjusting for other prognostic variables showing some imbalance across groups).

RESULTS

We analyzed 112 adults (52 underwent rEEG, 60 cEEG,); 31 (27.7%) were women; 68 (60.7%) patients died. In univariate analysis, mortality (rEEG 59%, cEEG 65%, p=0.318) and good outcome (CPC 1-2; rEEG 33%, cEEG 27%, p=0.247) were comparable across EEG groups. This did not change after multiple logistic regressions, adjusting for shockable rhythm, time to return of spontaneous circulation, serum neuron-specific enolase, EEG background reactivity, regarding mortality (rEEG vs cEEG: OR 1.60, 95% CI 0.43 - 5.83, p=0.477), and good outcome (OR 0.51, 95% CI 0.14 - 1.90, p=0.318).

CONCLUSION

This analysis suggests that cEEG or repeated rEEG are related to comparable outcomes of comatose patients after CA. Pending a prospective, large randomized trial, this finding does not support the routine use of cEEG for prognostication in this setting. Trial registration Continuous EEG Randomized Trial in Adults (CERTA); NCT03129438; July 25, 2019.

Revisiting EEG as part of the multidisciplinary approach to post-cardiac arrest care and prognostication: A review

Since the 1960s, EEG has been used to assess the neurologic function of patients in the hours and days after cardiac arrest. Accurate and reliable prognostication after cardiac arrest is vital for tailoring aggressive patient care for those with a high likelihood of recovery and setting appropriate goals of care for those who have a high likelihood of a poor outcome. Attempts to define EEG's role in this process has evolved over the years. In this review, we provide important historical context about EEG's use, it's perceived unreliability in the post-cardiac arrest patient in the past and provide a detailed analysis of how this role has changed recently. A review of the 71 most recent and highest quality studies demonstrates that the introduction of a uniform classification and a timed approach to EEG analysis have positioned EEG as a complementary tool in the multimodal approach for prognostication. The review was created and intended for medical staff in the intensive care units and emphasizes EEG patterns and timing which portend both favorable and poor prognoses. Also, the review addresses the overall quality of the existing studies and discusses future directions to address the knowledge gaps in this field.

A comparison of continuous and intermittent EEG recordings in geese: How much data are needed to reliably estimate sleep-wake patterns?

Recent technological advancements allow researchers to measure electrophysiological parameters of animals, such as sleep, in remote locations by using miniature dataloggers. Yet, continuous recording of sleep might be constrained by the memory and battery capacity of the recording devices. These limitations can be alleviated by recording intermittently instead of continuously, distributing the limited recording capacity over a longer period. We assessed how reduced sampling of sleep recordings affected measurement precision of NREM sleep, REM sleep, and Wake. We analysed a dataset on sleep in barnacle geese that we resampled following 12 different recording schemes, with data collected for 1 min per 5 min up to 1 min per 60 min in steps of 5 min. Recording 1 min in 5 min still yielded precise estimates of hourly sleep–wake values (correlations of 0.9) while potentially extending the total recording period by a factor of 5. The correlation strength gradually decreased to 0.5 when recording 1 min per 60 min. For hourly values of Wake and NREM sleep, the correlation strength in winter was higher compared with summer, reflecting more fragmented sleep in summer. Interestingly for hourly values of REM sleep, correlations were unaffected by season. Estimates of total 24 h sleep–wake values were similar for all intermittent recording schedules compared to the continuous recording. These data indicate that there is a large safe range in which researchers can periodically record sleep. Increasing the sample size while maintaining precision can substantially increase the statistical power, and is therefore recommended whenever the total recording time is limited.

Using electronic health data to explore effectiveness of ICU EEG and anti-seizure treatment

Objectives

The purpose of this study was to examine critical care continuous electroencephalography (cEEG) utilization and downstream anti‐seizure treatment patterns, their association with outcomes, and generate hypotheses for larger comparative effectiveness studies of cEEG‐guided interventions.

Methods

Single‐center retrospective study of critically ill patients (n = 14,523, age ≥18 years). Exposure defined as ≥24 h of cEEG and subsequent anti‐seizure medication (ASM) escalation, with or without concomitant anesthetic. Exposure window was the first 7 days of admission. Primary outcome was in‐hospital mortality. Multivariable analysis was performed using penalized logistic regression.

Results

One thousand and seventy‐three patients underwent ≥24 h of cEEG within 7 days of admission. After adjusting for disease severity, ≥24 h of cEEG followed by ASM escalation in patients not on anesthetics (n = 239) was associated with lower in‐hospital mortality (OR 0.76 [0.53–1.07]), though the finding did not reach significance. ASM escalation with concomitant anesthetic use (n = 484) showed higher odds for mortality (OR 1.41 [1.03–1.94]). In the seizures/status epilepticus subgroup, post cEEG ASM escalation without anesthetics showed lower odds for mortality (OR 0.43 [0.23–0.74]). Within the same subgroup, ASM escalation with concomitant anesthetic use showed higher odds for mortality (OR 1.34 [0.92–1.91]) though not significant.

Interpretation

Based on our findings we propose the following hypotheses for larger comparative effectiveness studies investigating the direct causal effect of cEEG‐guided treatment on outcomes: (1) cEEG‐guided ASM escalation may improve outcomes in critically ill patients with seizures; (2) cEEG‐guided treatment with combination of ASMs and anesthetics may not improve outcomes in all critically ill patients.

EEG Patterns and Outcomes After Hypoxic Brain Injury: A Systematic Review and Meta-analysis

Electroencephalography (EEG) is used to prognosticate recovery in comatose patients with hypoxic ischemic brain injury (HIBI) secondary to cardiac arrest. We sought to determine the prognostic use of specific EEG patterns for predicting disability and death following HIBI secondary to cardiac arrest. This systematic review searched Medline, Embase, and Cochrane Central up to January 2020. We included original research involving prospective and retrospective cohort studies relating specific EEG patterns to disability and death in comatose adult patients suffering HIBI post cardiac arrest requiring admission to an intensive care setting. We evaluated study quality using the Quality of Diagnostic Accuracy Studies 2 tool. Descriptive statistics were used to summarize study, patient, and EEG characteristics. We pooled study-level estimates of sensitivity and specificity for EEG patterns defined a priori using a random effect bivariate and univariate meta-analysis when appropriate. Funnel plots were used to assess publication bias. Of 5191 abstracts, 333 were reviewed in full text, of which 57 were included in the systematic review and 32 in meta-analyses. No reported EEG pattern was found to be invariably associated with death or disability across all studies. Pooled specificities of status epilepticus, burst suppression, and electrocerebral silence were high (92-99%), but sensitivities were low (6-39%) when predicting a composite outcome of disability and death. Study quality varied depending on domain; patient flow and timing performed was well conducted in all, whereas EEG interpretation was retrospective in 17 of 39 studies. Accounting for variable study quality, EEG demonstrates high specificity with a low risk of false negative outcome attribution for disability and death when status epilepticus, burst suppression, or electrocerebral silence is detected. Increased use of standardized cross-study protocols and definitions of EEG patterns are required to better evaluate the prognostic use of EEG for comatose patients with HIBI following cardiac arrest.

Quantitative analysis of EEG reactivity for neurological prognostication after cardiac arrest

OBJECTIVE

To test whether 1) quantitative analysis of EEG reactivity (EEG-R) using machine learning (ML) is superior to visual analysis, and 2) combining quantitative analyses of EEG-R and EEG background pattern increases prognostic value for prediction of poor outcome after cardiac arrest (CA).

METHODS

Several types of ML models were trained with twelve quantitative features derived from EEG-R and EEG background data of 134 adult CA patients. Poor outcome was a Cerebral Performance Category score of 3-5 within 6 months.

RESULTS

The Random Forest (RF) trained on EEG-R showed the highest AUC of 83% (95-CI 80-86) of tested ML classifiers, predicting poor outcome with 46% sensitivity (95%-CI 40-51) and 89% specificity (95%-CI 86-92). Visual analysis of EEG-R had 80% sensitivity and 65% specificity. The RF was also the best classifier for EEG background (AUC 85%, 95%-CI 83-88) at 24 h after CA, with 62% sensitivity (95%-CI 57-67) and 84% specificity (95%-CI 79-88). Combining EEG-R and EEG background RF classifiers reduced the number of false positives.

CONCLUSIONS

Quantitative EEG-R using ML predicts poor outcome with higher specificity, but lower sensitivity compared to visual analysis of EEG-R, and is of some additional value to ML on EEG background data.

SIGNIFICANCE

Quantitative EEG-R using ML is a promising alternative to visual analysis and of some added value to ML on EEG background data.

Continuous vs Routine Electroencephalogram in Critically Ill Adults With Altered Consciousness and No Recent Seizure: A Multicenter Randomized Clinical Trial

Question

In patients with acute consciousness impairment and no recent seizures, does continuous electroencephalogram (cEEG) correlate with reduced mortality compared with repeated routine EEG (rEEG)?

Findings

In this pragmatic, multicenter randomized clinical trial analyzing 364 adults, cEEG translated into a higher rate of seizures/status epilepticus detection and antiseizure treatment modifications but did not improve mortality compared with rEEG.

Meaning

Pending larger studies, rEEG may represent a valid alternative to cEEG in centers with limited resources.

Importance

In critically ill patients with altered consciousness, continuous electroencephalogram (cEEG) improves seizure detection, but is resource-consuming compared with routine EEG (rEEG). It is also uncertain whether cEEG has an effect on outcome.

Objective

To assess whether cEEG is associated with reduced mortality compared with rEEG.

Design, Setting, and Participants

The pragmatic multicenter Continuous EEG Randomized Trial in Adults (CERTA) was conducted between 2017 and 2018, with follow-up of 6 months. Outcomes were assessed by interviewers blinded to interventions.The study took place at 4 tertiary hospitals in Switzerland (intensive and intermediate care units). Depending on investigators’ availability, we pragmatically recruited critically ill adults having Glasgow Coma Scale scores of 11 or less or Full Outline of Responsiveness score of 12 or less, without recent seizures or status epilepticus. They had cerebral (eg, brain trauma, cardiac arrest, hemorrhage, or stroke) or noncerebral conditions (eg, toxic-metabolic or unknown etiology), and EEG was requested as part of standard care. An independent physician provided emergency informed consent.

Interventions

Participants were randomized 1:1 to cEEG for 30 to 48 hours vs 2 rEEGs (20 minutes each), interpreted according to standardized American Clinical Neurophysiology Society guidelines.

Main Outcomes and Measures

Mortality at 6 months represented the primary outcome. Secondary outcomes included interictal and ictal features detection and change in therapy.

Results

We analyzed 364 patients (33% women; mean [SD] age, 63 [15] years). At 6 months, mortality was 89 of 182 in those with cEEG and 88 of 182 in those with rEEG (adjusted relative risk [RR], 1.02; 95% CI, 0.83-1.26; P = .85). Exploratory comparisons within subgroups stratifying patients according to age, premorbid disability, comorbidities on admission, deeper consciousness reduction, and underlying diagnoses revealed no significant effect modification. Continuous EEG was associated with increased detection of interictal features and seizures (adjusted RR, 1.26; 95% CI, 1.08-1.15; P = .004 and 3.37; 95% CI, 1.63-7.00; P = .001, respectively) and more frequent adaptations in antiseizure therapy (RR, 1.84; 95% CI, 1.12-3.00; P = .01).

Conclusions and Relevance

This pragmatic trial shows that in critically ill adults with impaired consciousness and no recent seizure, cEEG leads to increased seizure detection and modification of antiseizure treatment but is not related to improved outcome compared with repeated rEEG. Pending larger studies, rEEG may represent a valid alternative to cEEG in centers with limited resources.

Trial Registration

ClinicalTrials.gov Identifier: NCT03129438

EEG in the Pediatric Intensive Care Unit: An Irish Experience

INTRODUCTION

Evidence for continuous EEG monitoring in the pediatric intensive care unit (PICU) is increasing. However, 24/7 access to EEG is not routinely available in most centers, and clinical management is often informed by more limited EEG resources. The experience of EEG was reviewed in a tertiary PICU where 24/7 EEG cover is unavailable.

METHODS

Retrospective EEG and clinical review of 108 PICU patients. Correlations were carried out between EEG and clinical variables including mortality. The role of EEG in clinical decision making was documented.

RESULTS

One hundred ninety-six EEGs were carried out in 108 PICU patients over 2.5 years (434 hours of recording). After exclusion of 1 outlying patient with epileptic encephalopathy, 136 EEGs (median duration, 65 minutes; range, 20 minutes to 4 hours 40 minutes) were included. Sixty-two patients (57%) were less than 12 months old. Seizures were detected in 18 of 107 patients (17%); 74% of seizures were subclinical; 72% occurred within the first 30 minutes of recording. Adverse EEG findings were associated with high mortality. Antiepileptic drug use was high in the studied population irrespective of EEG seizure detection. Prevalence of epileptiform discharges and EEG seizures diminished with increasing levels of sedation.

CONCLUSIONS

EEG provides important diagnostic information in a large proportion of PICU patients. In the absence of 24/7 EEG availability, empirical antiepileptic drug utilization is high.

What's new on EEG monitoring in the ICU

Continuous video-EEG (cEEG, lasting hours to several days) is increasingly used in ICU patients, as it is more sensitive than routine video-EEG (rEEG, lasting 20-30 min) to detect seizures or status epilepticus, and allows more frequent changes in therapeutic regimens. However, cEEG is more resource-consuming, and its relationship to outcome compared to repeated rEEG has only been formally assessed very recently in a randomized controlled trial, which did not show any significant difference in terms of long-term mortality or functional outcome. Awaiting more refined trials, it seems therefore that using repeated rEEG in ICU patients may represent a reasonable alternative in resource-limited settings. Prolonged EEG has been used recently in patients with severe COVID-19 infection, the proportion of seizures seems albeit relatively low, and similar to ICU patients with medical conditions. As in any case a timely EEG recording is recommended in the ICU, r ecent technical developments may ease its use in clinical practice.

A matter of timing: EEG monitoring for neurological prognostication after cardiac arrest in the era of targeted temperature management

Neuromonitoring with electroencephalography (EEG) is an essential tool in neurological prognostication post-cardiac arrest. EEG allows reliable and real-time assessment of early changes in background patterns, development of seizures and epileptiform activity, as well as testing for background reactivity to stimuli despite use of sedation or targeted temperature management. Delayed emergence of consciousness post-cardiac arrest is common, therefore longitudinal monitoring of EEG allows the detection of trends indicative of neurological improvement before coma recovery can be observed clinically. In this review, we summarize essential recent literature in EEG monitoring for neurological prognostication post-cardiac arrest in the context of targeted temperature management, with a particular focus on the importance of the evolution of EEG patterns in the first few days following resuscitation.

Are neurophysiologic tests reliable, ultra-early prognostic indices after cardiac arrest?

OBJECTIVES

Determining early and reliable prognosis in comatose subjects after cardiac arrest is a central component of post-cardiac arrest care both for developing realistic prognostic expectations for families, and for better determining which resources are mobilized or withheld for individual patients. The aim of the study was to evaluate the prognostic accuracy of EEG and SEP patterns during the very early period (within the first 6 h) after cardiac arrest.

METHODS

We retrospectively analysed comatose patients after CA, either inside or outside the hospital, in which prognostic evaluation was made during the first 6 h from CA. Prognostic evaluation comprised clinical evaluation (GCS and pupillary light reflex) and neurophysiological (electroencephalography (EEG) and somatosensory evoked potentials (SEP)) studies. Prognosis was evaluated with regards to likelihood of recovery of consciousness and also likelihood of failure to regain consciousness.

RESULTS

Forty-one comatose patients after cardiac arrest were included. All patients with continuous and nearly continuous EEG recovered consciousness. Isoelectric EEG was always associated with poor outcome. Burst-suppression, suppression and discontinuous patterns were usually associated with poor outcome although some consciousness recovery was observed. Bilaterally absent SEP responses were always associated with poor outcome. Continuous and nearly continuous EEG patterns were never associated with bilaterally absent SEP.

CONCLUSIONS

During the very early period following cardiac arrest (first 6 h), EEG and SEP maintain their high predictive value to predict respectively recovery and failure of recovery of consciousness. A very early EEG exam allows identification of patients with very high probability of a good outcome, allowing rapid use of the most appropriate therapeutic procedures.

Electroencephalogram Monitoring in Critical Care

Seizures are common in critically ill patients. Electroencephalogram (EEG) is a tool that enables clinicians to provide continuous brain monitoring and to guide treatment decisions-brain telemetry. EEG monitoring has particular utility in the intensive care unit as most seizures in this setting are nonconvulsive. Despite the increased use of EEG monitoring in the critical care unit, it remains underutilized. In this review, we summarize the utility of EEG and different EEG modalities to monitor patients in the critical care setting.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Sensitivity of Continuous Electroencephalography to Detect Ictal Activity After Cardiac Arrest

IMPORTANCE

Epileptiform electroencephalographic (EEG) patterns are common after resuscitation from cardiac arrest, are associated with patient outcome, and may require treatment. It is unknown whether continuous EEG monitoring is needed to detect these patterns or if brief intermittent monitoring is sufficient. If continuous monitoring is required, the necessary duration of observation is unknown.

OBJECTIVE

To quantify the time-dependent sensitivity of continuous EEG for epileptiform event detection, and to compare continuous EEG to several alternative EEG-monitoring strategies for post-cardiac arrest outcome prediction.

DESIGN, SETTING, AND PARTICIPANTS

This observational cohort study was conducted in 2 academic medical centers between September 2010 and January 2018. Participants included 759 adults who were comatose after being resuscitated from cardiac arrest and who underwent 24 hours or more of EEG monitoring.

MAIN OUTCOMES AND MEASURES

Epileptiform EEG patterns associated with neurological outcome at hospital discharge, such as seizures likely to cause secondary injury.

RESULTS

Overall, 759 patients were included in the analysis; 281 (37.0%) were female, and the mean (SD) age was 58 (17) years. Epileptiform EEG activity was observed in 414 participants (54.5%), of whom only 26 (3.4%) developed potentially treatable seizures. Brief intermittent EEG had an estimated 66% (95% CI, 62%-69%) to 68% (95% CI, 66%-70%) sensitivity for detection of prognostic epileptiform events. Depending on initial continuity of the EEG background, 0 to 51 hours of monitoring were needed to achieve 95% sensitivity for the detection of prognostic epileptiform events. Brief intermittent EEG had a sensitivity of 7% (95% CI, 4%-12%) to 8% (95% CI, 4%-12%) for the detection of potentially treatable seizures, and 0 to 53 hours of continuous monitoring were needed to achieve 95% sensitivity for the detection of potentially treatable seizures. Brief intermittent EEG results yielded similar information compared with continuous EEG results when added to multivariable models predicting neurological outcome.

CONCLUSIONS AND RELEVANCE

Compared with continuous EEG monitoring, brief intermittent monitoring was insensitive for detection of epileptiform events. Monitoring EEG results significantly improved multimodality prediction of neurological outcome, but continuous monitoring appeared to add little additional information compared with brief intermittent monitoring.

The characteristics of patients with bilateral absent evoked potentials after post-anoxic brain damage: A multicentric cohort study

OBJECTIVES

Patients with bilateral absence of cortical response (N20_ABS) to somatosensory evoked potentials (SSEPs) have poor neurological outcome after cardiac arrest (CA). However, SSEPs are not available in all centers. The aim of this study was to identify predictors of N20_ABS.

METHODS

Retrospective analysis of institutional databases (2008-2015) in three ICUs including all adult admitted comatose patients undergoing SSEPs between 48 and 72 h after CA. We collected clinical (i.e. absence of pupillary reflexes, PLR, myoclonus and absent or posturing motor response and myoclonus on day 2-3), electroencephalographic (EEG; i.e. unreactive to painful stimuli; presence of a highly malignant patterns, such as burst-suppression or flat tracings) findings during the first 48 h, and the highest NSE levels on the first 3 days after CA. Unfavorable neurological outcome (UO) was assessed at 3 months using the Cerebral Performance Categories of 3-5.

RESULTS

We studied 532 patients with SSEPs, including 143 (27%) without N20_ABS; UO was observed in 334 (63%) patients. Median time to SSEPs was 72 [48-72] h after CA. No patient with absent PLR and myoclonus during the ICU stay had N20 present; similar results were observed with the combination of absent PLR, myoclonus and any EEG pattern (i.e. unreactive or highly malignant). Similar results were observed in the subgroup of patients where NSE was available (n = 303). In a multivariate logistic regression, non-cardiac etiology of arrest, unreactive EEG to painful stimuli, absence of pupillary reflexes and posturing motor response, were independent predictors of N20_ABS. When available, the highest NSE was also an independent predictor of N20_ABS.

CONCLUSIONS

Clinical and EEG findings predicting patients with N20_ABS, confirm that N20_ABS reflects a severe and permanent cerebral damage after CA.

How and Whom to Monitor for Seizures in an ICU: A Systematic Review and Meta-Analysis

OBJECTIVES

To pool prevalence of nonconvulsive seizure, nonconvulsive status epilepticus, and epileptiform activity detected by different electroencephalography types in critically ills and to compare detection rates among them.

DATA SOURCES

MEDLINE (via PubMed) and SCOPUS (via Scopus) STUDY SELECTION:: Any type of study was eligible if studies were done in adult critically ill, applied any type of electroencephalography, and reported seizure rates. Case reports and case series were excluded.

DATA EXTRACTION

Data were extracted independently by two investigators. Separated pooling of prevalence of nonconvulsive seizure/nonconvulsive status epilepticus/epileptiform activity and odds ratio of detecting outcomes among different types of electroencephalography was performed using random-effect models. This meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and also adhered to the Meta-analyses Of Observational Studies in Epidemiology guidelines. Quality of evidence was assessed with the Newcastle-Ottawa Quality Assessment Scale for observational studies and Cochrane methods for randomized controlled trial studies.

DATA SYNTHESIS

A total of 78 (16,707 patients) and eight studies (4,894 patients) were eligible for pooling prevalence and odds ratios. For patients with mixed cause of admission, the pooled prevalence of nonconvulsive seizure, nonconvulsive status epilepticus, either nonconvulsive seizure or nonconvulsive status epilepticus detected by routine electroencephalography was 3.1%, 6.2%, and 6.3%, respectively. The corresponding prevalence detected by continuous electroencephalography monitoring was 17.9%, 9.1%, and 15.6%, respectively. In addition, the corresponding prevalence was high in post convulsive status epilepticus (33.5%, 20.2%, and 32.9%), CNS infection (23.9%, 18.1%, and 23.9%), and post cardiac arrest (20.0%, 17.3%, and 22.6%). The pooled conditional log odds ratios of nonconvulsive seizure/nonconvulsive status epilepticus detected by continuous electroencephalography versus routine electroencephalography from studies with paired data 2.57 (95% CI, 1.11-5.96) and pooled odds ratios from studies with independent data was 1.57 (95% CI, 1.00-2.47).

CONCLUSIONS

Prevalence of seizures detected by continuous electroencephalography was significantly higher than with routine electroencephalography. Prevalence was particularly high in post convulsive status epilepticus, CNS infection, and post cardiac arrest.

Early electroencephalography for outcome prediction of postanoxic coma: A prospective cohort study

Objective

To provide evidence that early electroencephalography (EEG) allows for reliable prediction of poor or good outcome after cardiac arrest.

Methods

In a 5‐center prospective cohort study, we included consecutive, comatose survivors of cardiac arrest. Continuous EEG recordings were started as soon as possible and continued up to 5 days. Five‐minute EEG epochs were assessed by 2 reviewers, independently, at 8 predefined time points from 6 hours to 5 days after cardiac arrest, blinded for patients’ actual condition, treatment, and outcome. EEG patterns were categorized as generalized suppression (<10 μV), synchronous patterns with ≥50% suppression, continuous, or other. Outcome at 6 months was categorized as good (Cerebral Performance Category [CPC] = 1–2) or poor (CPC = 3–5).

Results

We included 850 patients, of whom 46% had a good outcome. Generalized suppression and synchronous patterns with ≥50% suppression predicted poor outcome without false positives at ≥6 hours after cardiac arrest. Their summed sensitivity was 0.47 (95% confidence interval [CI] = 0.42–0.51) at 12 hours and 0.30 (95% CI = 0.26–0.33) at 24 hours after cardiac arrest, with specificity of 1.00 (95% CI = 0.99–1.00) at both time points. At 36 hours or later, sensitivity for poor outcome was ≤0.22. Continuous EEG patterns at 12 hours predicted good outcome, with sensitivity of 0.50 (95% CI = 0.46–0.55) and specificity of 0.91 (95% CI = 0.88–0.93); at 24 hours or later, specificity for the prediction of good outcome was <0.90.

Interpretation

EEG allows for reliable prediction of poor outcome after cardiac arrest, with maximum sensitivity in the first 24 hours. Continuous EEG patterns at 12 hours after cardiac arrest are associated with good recovery. ANN NEUROL 2019;86:203–214

Value of EEG reactivity for prediction of neurologic outcome after cardiac arrest: Insights from the Parisian registry

PURPOSE

To evaluate the predictive value of EEG reactivity assessment and confounders for neurological outcome after cardiac arrest.

METHODS

All consecutive patients admitted in a tertiary cardiac arrest center between 2007 and 2016 still alive 48 h after admission with at least one EEG recorded during coma. EEG reactivity was defined as a reproducible waveform change in amplitude or frequency following standardized stimulation. Each EEG was classified based on American Clinical Neurophysiology Society nomenclatures and classified in highly malignant (including status epilepticus), malignant, or benign EEG. We assessed the predictive values of EEG reactivity and sedation effect for neurologic outcome at ICU discharge using the Cerebral Performance Category scale (with CPC 1-2 assumed as favorable outcome and CPC 3-4-5 considered as poor outcome).

RESULTS

Among 428 patients, a poor outcome was observed in 80% patients. The median time to EEG recording was 3 (1-4) days and 51% patients had a non-reactive EEG. The positive predictive value (PPV) of a non-reactive EEG to predict an unfavorable outcome was 97.1% (IC95% 93.6-98.9), increasing to 98.3% (IC95 94.1-99.8) when the EEG had been performed without sedation. In multivariate analysis, a non-reactive EEG was associated with poor outcome (OR 12.6 IC95% 4.7-33.6; p < 0.001). In multivariate analysis, concomitant sedation was not statistically associated with EEG non-reactivity. The PPV of a benign EEG to predict favorable outcome was 49.7% (IC95% 41.5-57.9), increasing to 66.2% (IC95% 54.3-76.8) when EEG was recorded earlier, with ongoing sedation.

CONCLUSIONS

After cardiac arrest, absence of EEG reactivity was predictive of unfavorable outcome. By contrast, a benign EEG was slightly predictive of a favorable outcome. Reactivity assessment may have important implications in the neuroprognostication process after cardiac arrest and could be influenced by sedation.

Continuous Electroencephalography in the Critically Ill: Clinical and Continuous Electroencephalography Markers for Targeted Monitoring

PURPOSE

Electrographic seizures detected by continuous electroencephalography (CEEG) in critically ill patients with altered mental status is becoming increasingly recognized. Data guiding the appropriate selection of patients to be monitored on CEEG are lacking. The aims of this article were to study the incidence of seizures in the critical care setting and to evaluate for clinical predictors to improve the efficiency of CEEG monitoring.

METHODS

Retrospective review of the CEEG and clinical data on 1,123 consecutive patients who had continuous video EEG over a 24-month period.

RESULTS

Seizures were recorded in 215 patients on CEEG monitoring (19.1%). In total, 89.3% of these seizures occurred without clinical signs. Patients who were in a coma were more likely to have EEG seizures (odds ratio, 3.64; 95% confidence interval, 2.23-5.95) compared with those awake. The incidence of seizures was overrepresented in patients with extra-axial tumors (41.9%), multiple sclerosis (35.7%), and intra-axial tumors (33.0%). Lateralized periodic discharges were predictive (odds ratio, 8.27; 95% confidence interval, 5.52-12.46) of seizure occurrence compared with those with no epileptiform patterns. Only generalized periodic discharges with triphasic morphology had no increased odds of seizure (odds ratio, 1.02; 95% confidence interval, 0.24-3.03). When present, electroencephalography seizures were detected within 24 hours in 92% of monitored patients.

CONCLUSIONS

Continuous electroencephalography monitoring in the critical care setting demonstrates a linear increase in seizure incidence with declining mental status. Recognizing clinical conditions and electroencephalography markings may help in the appropriate selection of critically ill patients for CEEG monitoring.

Targeted Temperature Management and Multimodality Monitoring of Comatose Patients After Cardiac Arrest

Out-of-hospital cardiac arrest (CA) remains a leading cause of sudden morbidity and mortality; however, outcomes have continued to improve in the era of targeted temperature management (TTM). In this review, we highlight the clinical use of TTM, and provide an updated summary of multimodality monitoring possible in a modern ICU. TTM is neuroprotective for survivors of CA by inhibiting multiple pathophysiologic processes caused by anoxic brain injury, with a final common pathway of neuronal death. Current guidelines recommend the use of TTM for out-of-hospital CA survivors who present with a shockable rhythm. Further studies are being completed to determine the optimal timing, depth and duration of hypothermia to optimize patient outcomes. Although a multidisciplinary approach is necessary in the CA population, neurologists and neurointensivists are central in selecting TTM candidates and guiding patient care and prognostic evaluation. Established prognostic tools include clinal exam, SSEP, EEG and MR imaging, while functional MRI and invasive monitoring is not validated to improve outcomes in CA or aid in prognosis. We recommend that an evidence-based TTM and prognostication algorithm be locally implemented, based on each institution's resources and limitations. Given the high incidence of CA and difficulty in predicting outcomes, further study is urgently needed to determine the utility of more recent multimodality devices and studies.

Does continuous EEG influence prognosis in patients after cardiac arrest?

AIM

Electroencephalography (EEG) is a key modality for assessment of prognosis following cardiac arrest (CA); however, whether continuous EEG (cEEG) is superior to routine intermittent EEG (rEEG) remains debated. We examined the impact of cEEG (>18 h) vs. rEEG (<30 min) on outcome in comatose CA patients as part of multimodal prognostication.

METHODS

We analysed a large prospective registry of comatose post-CA adults (n = 497; 2009-2018), stratified based on whether they received cEEG (n = 62) or rEEG (n = 435), including standardized reactivity testing at two time-points. The primary endpoint was the impact of cEEG vs. rEEG on Glasgow-Pittsburgh Cerebral Performance Categories (CPC) at three months; we also assessed impact on time to death.

RESULTS

Main patients' baseline clinical characteristics and CPC scores were comparable between the EEG groups. By multivariable analysis age, non-shockable rhythm, presence of early myoclonus, absent EEG background reactivity, absent somato-sensory evoked potentials, and serum NSE were independently associated with poor neurological outcome (CPC 3-5), while the EEG approach had no impact on patient prognosis and time to death.

CONCLUSIONS

Our data suggest that cEEG does not confer any advantage over intermittent rEEG regarding outcome in patients with CA, and does not influence the time to death.

Anoxic-Ischemic Brain Injury

Improvements in cardiopulmonary resuscitation and intensive care medicine have led to declining mortality rates for patients with out-of-hospital cardiac arrest, but overall it is still a minority that achieves good outcomes. Estimating neurologic prognosis for patients that remain comatose after resuscitation remains a challenge and the need for accurate and early prognostic predictors is crucial. A thoughtful approach is required and should take into account information acquired from multiple tests in association with neurologic examination. No decision should be made based on a single predictor. In addition to clinical examination, somatosensory evoked potentials, electroencephalogram, serum biomarkers, and neuroimaging provide complimentary information to inform prognosis.

Continuous Electroencephalography Monitoring in Adults in the Intensive Care Unit

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2018. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2018. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Extended EEG and non-convulsive status epilepticus: Benefit over routine EEG?

OBJECTIVE

EEG monitoring is increasingly used in critically ill patients, but impact on clinical outcome remains unclear. We aimed to investigate the benefit of repeated extended EEG in the prognosis of patients with non-convulsive status epilepticus (SE).

MATERIALS & METHODS

We retrospectively collected 29 consecutive patients with non-convulsive SE without coma, who underwent repeated extended EEG between 2013 and 2015. We compared these patients with an historical age-matched group of 58 patients managed between 2011 and 2013 with routine EEG only. We excluded patients treated with therapeutic coma for SE treatment. Outcome at hospital discharge was categorized as return to baseline conditions, new disability, and death.

RESULTS

Severity of SE was similar in the two groups, with similar proportion of potential fatal etiologies (58% in the extended EEG group vs 60%, P=.529), similar STESS scores (median was three in both groups, P=.714), and comparable acute hospitalization duration (median of 15 vs 11 days, P=.131). The extended EEG group received slightly more anti-epileptic drugs (median was three in both groups, P=.026). Distribution of the outcome categories at hospital discharge was similar (P=.129).

CONCLUSIONS

Extended EEG used for the management of non-convulsive status epilepticus does not seem to improve clinical outcome, but is associated with a higher number of prescribed anti-epileptic drugs. The benefit of continuous EEG monitoring in non-convulsive SE without coma SE should be addressed through a randomized trial.

Clinical neurophysiology for neurological prognostication of comatose patients after cardiac arrest

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A multimodal prognostic approach is recommended after cardiac arrest.

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EEG (background and, reactivity, repetitive epileptiform features) and SSEP are core assessments.

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Some outlook into long-latency evoked potentials is offered.

Early prognostication of outcome in comatose patients after cardiac arrest represents a daunting task for clinicians, also considering the nowadays commonly used targeted temperature management with sedation in the first 24–48 h. A multimodal approach is currently recommended, in order to minimize the risks of false-positive prediction of poor outcome, including clinical examination off sedation, EEG (background characterization and reactivity, occurrence of repetitive epileptiform features), and early-latency SSEP responses represent the core assessments in this setting; they may be complemented by biochemical markers and neuroimaging.

This paper, which relies on a recent comprehensive review, focuses on an updated review of EEG and SSEP, and also offers some outlook into long-latency evoked potentials, which seem promising in clinical use.

Neuroprognostication after adult cardiac arrest treated with targeted temperature management: task force for Belgian recommendations

The prognosis of patients who are admitted to the hospital after cardiac arrest often relies on neurological examination, which could be significantly influenced by the use of sedative drugs or the implementation of targeted temperature management. The need for early and accurate prognostication is crucial as up to 15-20% of patients could be considered as having a poor outcome and may undergo withdrawal of life-sustaining therapies while a complete neurological recovery is still possible. As current practice in Belgium is still based on a very early assessment of neurological function in these patients, the Belgian Society of Intensive Care Medicine created a multidisciplinary Task Force to provide an optimal approach for monitoring and refine prognosis of CA survivors. This Task Force underlined the importance to use a multimodal approach using several additional tools (e.g., electrophysiological tests, neuroimaging, biomarkers) and to refer cases with uncertain prognosis to specialized centers to better evaluate the extent of brain injury in these patients.

The Benefit of Neuromuscular Blockade in Patients with Postanoxic Myoclonus Otherwise Obscuring Continuous Electroencephalography (CEEG)

Introduction. Myoclonus status epilepticus is independently associated with poor outcome in coma patients after cardiac arrest. Determining if myoclonus is of cortical origin on continuous electroencephalography (CEEG) can be difficult secondary to the muscle artifact obscuring the underlying CEEG. The use of a neuromuscular blocker can be useful in these cases. Methods. Retrospective review of CEEG in patients with postanoxic myoclonus who received cisatracurium while being monitored. Results. Twelve patients (mean age: 53.3 years; 58.3% male) met inclusion criteria of clinical postanoxic myoclonus. The initial CEEG patterns immediately prior to neuromuscular blockade showed myoclonic artifact with continuous slowing (50%), burst suppression with myoclonic artifact (41.7%), and continuous myogenic artifact obscuring CEEG (8.3%). After intravenous administration of cisatracurium (0.1 mg–2 mg), reduction in artifact improved quality of CEEG recordings in 9/12 (75%), revealing previously unrecognized patterns: continuous EEG seizures (33.3%), lateralizing slowing (16.7%), burst suppression (16.7%), generalized periodic discharges (8.3%), and, in the patient who had an initially uninterpretable CEEG from myogenic artifact, continuous slowing. Conclusion. Short-acting neuromuscular blockade is useful in determining background cerebral activity on CEEG otherwise partially or completely obscured by muscle artifact in patients with postanoxic myoclonus. Fully understanding background cerebral activity is important in prognostication and treatment, particularly when there are underlying EEG seizures.

Yield of repeated intermittent EEG for seizure detection in critically ill adults

INTRODUCTION

Seizures are common in critically ill patients and prevalence can exceed 30% in the neuro-intensive care unit (ICU). Continuous EEG monitoring (cEEG) is the gold standard for seizure detection in critically ill patients.

OBJECTIVES

To determine the yield of intermittent EEG (iEEG) to detect critically ill adult patients with seizures and to identify the factors that affect this yield.

METHODS

We retrospectively analyzed cEEG data and medical records from 977 consecutive critically ill patients undergoing cEEG. We included those presenting at least one electrographic seizure during the first 24hours of cEEG. Patients with hypoxic-ischemic encephalopathy were excluded. For seizure detection, we reviewed six 30-minute epochs on cEEG selected at H0, H3, H6, H12, H18 and H24.

RESULTS

Seizures occurred in 10.75% (105/977) of patients. Level of consciousness was impaired in 79 (75%) of patients, with 42 (40%) in coma. Review of the H0 epoch on cEEG permitted to detect seizures in 61 (58%) patients. These figures increased to 70 (67%), 75 (71%), 91 (87%) and 97 (92%) patients for a sampling every 24, 12, 6 and 3hours, respectively (P=0.02). Frequency of seizures on cEEG was the only factor significantly affecting the probability of seizure detection. Sampling every 6hours revealed seizures in all patients with more than six seizures per 24hours.

CONCLUSIONS

iEEG repeated every 6hours can accurately detect patients presenting seizures, especially when seizure frequency is greater than six per 24hours. These findings have practical implications for electrographic seizure detection in critically ill patients in settings lacking cEEG.

Should Postanoxic Status Epilepticus be Treated Aggressively?-No!

Electrographic status epilepticus and myoclonus represent frequent findings in patients surviving cardiac arrest; both features have been related to poor clinical outcome. Recent data have outlined that status epilepticus appearing during therapeutic hypothermia and sedation is practically and invariably related to a fatal issue, as opposed to some patients presenting status epilepticus and/or myoclonus after return to normothermic conditions. Although it seems reasonable to give a chance of awakening to the latter patients by administering consequent antiepileptic treatment, especially if other favorable prognostic markers are observed, an aggressive treatment of status epilepticus arising during hypothermia seems futile in view of the existing evidence.

EEG as an Indicator of Cerebral Functioning in Postanoxic Coma

Postanoxic coma after cardiac arrest is one of the most serious acute cerebral conditions and a frequent cause of admission to critical care units. Given substantial improvement of outcome over the recent years, a reliable and timely assessment of clinical evolution and prognosis is essential in this context, but may be challenging. In addition to the classic neurologic examination, EEG is increasingly emerging as an important tool to assess cerebral functions noninvasively. Although targeted temperature management and related sedation may delay clinical assessment, EEG provides accurate prognostic information in the early phase of coma. Here, the most frequently encountered EEG patterns in postanoxic coma are summarized and their relations with outcome prediction are discussed. This article also addresses the influence of targeted temperature management on brain signals and the implication of the evolution of EEG patterns over time. Finally, the article ends with a view of the future prospects for EEG in postanoxic management and prognostication.

Clinical Use of EEG in the ICU: Technical Setting

Neurophysiology is an essential tool for clinicians dealing with patients in the intensive care unit. Because of consciousness disorders, clinical examination is frequently limited. In this setting, neurophysiological examination provides valuable information about seizure detection, treatment guidance, and neurological outcome. However, to acquire reliable signals, some technical precautions need to be known. EEG is prone to artifacts, and the intensive care unit environment is rich in artifact sources (electrical devices including mechanical ventilation, dialysis, and sedative medications, and frequent noise, etc.). This review will discuss and summarize the current technical guidelines for EEG acquisition and also some practical pitfalls specific for the intensive care unit.