Prediction of regaining consciousness despite an early epileptiform EEG after cardiac arrest

Quantitative Characterization of Rhythmic and Periodic EEG Patterns in Patients in a Coma After Cardiac Arrest and Association With Outcome

OBJECTIVES

Rhythmic and periodic patterns (RPPs) on EEG in patients in a coma after cardiac arrest are associated with a poor neurologic outcome. We characterize RPPs using qEEG in relation to outcomes.

METHODS

Post hoc analysis was conducted on 172 patients in a coma after cardiac arrest from the TELSTAR trial, all with RPPs. Quantitative EEG included corrected background continuity index (BCI*), relative discharge power (RDP), discharge frequency, and shape similarity. Neurologic outcomes at 3 months after arrest were categorized as poor (CPC = 3-5) or good (CPC = 1-2).

RESULTS

A total of 16 patients (9.3%) had a good outcome. Patients with good outcomes showed later RPP onset (28.5 vs 20.1 hours after arrest, p < 0.05) and higher background continuity at RPP onset (BCI* = 0.83 vs BCI* = 0.59, p < 0.05). BCI* <0.45 at RPP onset, maximum BCI* <0.76, RDP >0.47, or shape similarity >0.75 were consistently associated with poor outcomes, identifying 36%, 22%, 40%, or 24% of patients with poor outcomes, respectively. In patients meeting both BCI* >0.44 at RPP onset and BCI* >0.75 within 72 hours, the probability of good outcomes doubled to 18%.

DISCUSSION

Sufficient EEG background continuity before and during RPPs is crucial for meaningful recovery. Background continuity, discharge power, and shape similarity can help select patients with relevant chances of recovery and may guide treatment.

TRIAL REGISTRATION INFORMATION

February 4, 2014, ClinicalTrial.gov, NCT02056236.

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 Role of Routine Electroencephalography in the Diagnosis of Seizures in Medical Intensive Care Units

Seizures should be diagnosed and treated to ensure optimal health outcomes in critically ill patients admitted in the medical intensive care unit (MICU). Continuous electroencephalography is still infrequently used in the MICU. We investigated the effectiveness of routine EEG (rEEG) in detecting seizures in the MICU. A total of 560 patients admitted to the MICU between October 2018 and March 2023 and who underwent rEEG were reviewed. Seizure-related rEEG constituted 47% of all rEEG studies. Totally, 39% of the patients experienced clinical seizures during hospitalization; among them, 48% experienced the seizure, and 13% experienced their first seizure after undergoing an rEEG study. Seventy-seven percent of the patients had unfavorable short-term outcomes. Patients with cardiovascular diseases were the most likely to have the suppression/burst suppression (SBS) EEG pattern and the highest mortality rate. The rhythmic and periodic patterns (RPPs) and electrographic seizure (ESz) EEG pattern were associated with seizures within 24 h after rEEG, which was also related to unfavorable outcomes. Significant predictors of death were age > 59 years, the male gender, the presence of cardiovascular disease, a Glasgow Coma Scale score ≤ 5, and the SBS EEG pattern, with a predictive performance of 0.737 for death. rEEG can help identify patients at higher risk of seizures. We recommend repeated rEEG in patients with ESz or RPP EEG patterns to enable a more effective monitoring of seizure activities.

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.

Combined depth and scalp electroencephalographic monitoring in acute brain injury: Yield and prognostic value

BACKGROUND AND PURPOSE

Depth electroencephalography (dEEG) is an emerging neuromonitoring technology in acute brain injury (ABI). We aimed to explore the concordances between electrophysiological activities on dEEG and on scalp EEG (scEEG) in ABI patients.

METHODS

Consecutive ABI patients who received dEEG monitoring between 2018 and 2022 were included. Background, sporadic epileptiform discharges, rhythmic and periodic patterns (RPPs), electrographic seizures, brief potentially ictal rhythmic discharges, ictal-interictal continuum (IIC) patterns, and hourly RPP burden on dEEG and scEEG were compared.

RESULTS

Sixty-one ABI patients with a median dEEG monitoring duration of 114 h were included. dEEG significantly showed less continuous background (75% vs. 90%, p = 0.03), higher background amplitude (p < 0.001), more frequent rhythmic spike-and-waves (16% vs. 3%, p = 0.03), more IIC patterns (39% vs. 21%, p = 0.03), and greater hourly RPP burden (2430 vs. 1090 s/h, p = 0.01), when compared to scEEG. Among five patients with seizures on scEEG, one patient had concomitant seizures on dEEG, one had periodic discharges (not concomitant) on dEEG, and three had no RPPs on dEEG. Features and temporal occurrence of electrophysiological activities observed on dEEG and scEEG are not strongly associated. Patients with seizures and IIC patterns on dEEG seemed to have a higher rate of poor outcomes at discharge than patients without these patterns on dEEG (42% vs. 25%, p = 0.37).

CONCLUSIONS

dEEG can detect abnormal electrophysiological activities that may not be seen on scEEG and can be used as a complement in the neuromonitoring of ABI patients.

2023 American Heart Association Focused Update on Adult Advanced Cardiovascular Life Support: An Update to the American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

Cardiac arrest is common and deadly, affecting up to 700 000 people in the United States annually. Advanced cardiac life support measures are commonly used to improve outcomes. This "2023 American Heart Association Focused Update on Adult Advanced Cardiovascular Life Support" summarizes the most recent published evidence for and recommendations on the use of medications, temperature management, percutaneous coronary angiography, extracorporeal cardiopulmonary resuscitation, and seizure management in this population. We discuss the lack of data in recent cardiac arrest literature that limits our ability to evaluate diversity, equity, and inclusion in this population. Last, we consider how the cardiac arrest population may make up an important pool of organ donors for those awaiting organ transplantation.

Status epilepticus in the ICU

Status epilepticus (SE) is a common medical emergency associated with significant morbidity and mortality. Management that follows published guidelines is best suited to improve outcomes, with the most severe cases frequently being managed in the intensive care unit (ICU). Diagnosis of convulsive SE can be made without electroencephalography (EEG), but EEG is required to reliably diagnose nonconvulsive SE. Rapidly narrowing down underlying causes for SE is crucial, as this may guide additional management steps. Causes may range from underlying epilepsy to acute brain injuries such as trauma, cardiac arrest, stroke, and infections. Initial management consists of rapid administration of benzodiazepines and one of the following non-sedating intravenous antiseizure medications (ASM): (fos-)phenytoin, levetiracetam, or valproate; other ASM are increasingly used, such as lacosamide or brivaracetam. SE that continues despite these medications is called refractory, and most commonly treated with continuous infusions of midazolam or propofol. Alternatives include further non-sedating ASM and non-pharmacologic approaches. SE that reemerges after weaning or continues despite management with propofol or midazolam is labeled super-refractory SE. At this step, management may include non-sedating or sedating compounds including ketamine and barbiturates. Continuous video EEG is necessary for the management of refractory and super-refractory SE, as these are almost always nonconvulsive. If possible, management of the underlying cause of seizures is crucial particularly for patients with autoimmune encephalitis. Short-term mortality ranges from 10 to 15% after SE and is primarily related to increasing age, underlying etiology, and medical comorbidities. Refractoriness of treatment is clearly related to outcome with mortality rising from 10% in responsive cases, to 25% in refractory, and nearly 40% in super-refractory SE.

Predictive Performance of Neuron-Specific Enolase (NSE) for Survival after Resuscitation from Cardiac Arrest: A Systematic Review and Meta-Analysis

The prediction of outcomes following cardiac arrest continues to provide significant difficulties. A preferred strategy involves adopting a multimodal approach, which encompasses the careful evaluation of the biomarker neuron-specific enolase (NSE). This systematic review and meta-analysis aimed to gather and summarize new and existing evidence on the prediction effect of neuron-specific enolase for survival to hospital discharge among adult patients with cardiac arrest. We searched PubMed Central, Scopus, EMBASE databases, and the Cochrane Library without language restrictions from their inceptions until 30 October 2023 and checked the reference lists of the included studies. Pooled results were reported as standardized mean differences (SMDs) and were presented with corresponding 95% confidence intervals (CIs). The primary outcome was survival to hospital discharge (SHD). Eighty-six articles with 10,845 participants were included. NSE showed a notable degree of specificity in its ability to predict mortality as well as neurological status among individuals who experienced cardiac arrest (p < 0.05). This study demonstrates the ability to predict fatality rates and neurological outcomes, both during the time of admission and at various time intervals after cardiac arrest. The use of NSE in a multimodal neuroprognostication algorithm has promise in improving the accuracy of prognoses for persons who have undergone cardiac arrest.

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

BACKGROUND AND OBJECTIVES

Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.

METHODS

Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.

RESULTS

One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.

DISCUSSION

Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

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.

What happens in the brain when we die? Deciphering the neurophysiology of the final moments in life

When do we die and what happens in the brain when we die? The mystery around these questions has engaged mankind for centuries. Despite the challenges to obtain recordings of the dying brain, recent studies have contributed to better understand the processes occurring during the last moments of life. In this review, we summarize the literature on neurophysiological changes around the time of death. Perhaps the only subjective description of death stems from survivors of near-death experiences (NDEs). Hallmarks of NDEs include memory recall, out-of-body experiences, dreaming, and meditative states. We survey the evidence investigating neurophysiological changes of these experiences in healthy subjects and attempt to incorporate this knowledge into the existing literature investigating the dying brain to provide valuations for the neurophysiological footprint and timeline of death. We aim to identify reasons explaining the variations of data between studies investigating this field and provide suggestions to standardize research and reduce data variability.

Preservation of thalamocortical circuitry is essential for good recovery after cardiac arrest

Continuous electroencephalographam (EEG) monitoring contributes to prediction of neurological outcome in comatose cardiac arrest survivors. While the phenomenology of EEG abnormalities in postanoxic encephalopathy is well known, the pathophysiology, especially the presumed role of selective synaptic failure, is less understood. To further this understanding, we estimate biophysical model parameters from the EEG power spectra from individual patients with a good or poor recovery from a postanoxic encephalopathy. This biophysical model includes intracortical, intrathalamic, and corticothalamic synaptic strengths, as well as synaptic time constants and axonal conduction delays. We used continuous EEG measurements from hundred comatose patients recorded during the first 48 h postcardiac arrest, 50 with a poor neurological outcome [cerebral performance category ( CPC = 5 ) ] and 50 with a good neurological outcome ( CPC = 1 ). We only included patients that developed (dis-)continuous EEG activity within 48 h postcardiac arrest. For patients with a good outcome, we observed an initial relative excitation in the corticothalamic loop and corticothalamic propagation that subsequently evolved towards values observed in healthy controls. For patients with a poor outcome, we observed an initial increase in the cortical excitation-inhibition ratio, increased relative inhibition in the corticothalamic loop, delayed corticothalamic propagation of neuronal activity, and severely prolonged synaptic time constants that did not return to physiological values. We conclude that the abnormal EEG evolution in patients with a poor neurological recovery after cardiac arrest may result from persistent and selective synaptic failure that includes corticothalamic circuitry and also delayed corticothalamic propagation.

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.

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.

Cardiac arrest: An interdisciplinary scoping review of clinical literature from 2020

Objectives

The Interdisciplinary Cardiac Arrest Research Review (ICARE) group was formed in 2018 to conduct an annual search of peer-reviewed literature relevant to cardiac arrest. Now in its third year, the goals of the review are to highlight annual updates in the interdisciplinary world of clinical cardiac arrest research with a focus on clinically relevant and impactful clinical and population-level studies from 2020.

Methods

A search of PubMed using keywords related to clinical research in cardiac arrest was conducted. Titles and abstracts were screened for relevance and sorted into 7 categories: Epidemiology & Public Health Initiatives; Prehospital Resuscitation, Technology & Care; In-Hospital Resuscitation & Post-Arrest Care; Prognostication & Outcomes; Pediatrics; Interdisciplinary Guidelines & Reviews; and a new section dedicated to the coronavirus disease 2019 (COVID-19) pandemic. Screened manuscripts underwent standardized scoring of methodological quality and impact on the respective fields by reviewer teams lead by a subject matter expert editor. Articles scoring higher than 99 percentiles by category were selected for full critique. Systematic differences between editors' and reviewers' scores were assessed using Wilcoxon signed-rank test.

Results

A total of 3594 articles were identified on initial search; of these, 1026 were scored after screening for relevance and deduplication, and 51 underwent full critique. The leading category was Prehospital Resuscitation, Technology & Care representing 35% (18/51) of fully reviewed articles. Four COVID-19 related articles were included for formal review that was attributed to a relative lack of high-quality data concerning cardiac arrest and COVID-19 specifically by the end of the 2020 calendar year. No significant differences between editor and reviewer scoring were found among review articles (P = 0.697). Among original research articles, section editors scored a median 1 point (interquartile range, 0-3; P < 0.01) less than reviewers.

Conclusions

Several clinically relevant studies have added to the evidence base for the management of cardiac arrest patients including methods for prognostication of neurologic outcome following arrest, airway management strategy, timing of coronary intervention, and methods to improve expeditious performance of key components of resuscitation such as chest compressions in adults and children.

Association Between EEG Patterns and Serum Neurofilament Light After Cardiac Arrest

Background and Objectives

EEG is widely used for prediction of neurologic outcome after cardiac arrest. To better understand the relationship between EEG and neuronal injury, we explored the association between EEG and neurofilament light (NfL) as a marker of neuroaxonal injury, evaluated whether highly malignant EEG patterns are reflected by high NfL levels, and explored the association of EEG backgrounds and EEG discharges with NfL.

Methods

We performed a post hoc analysis of the Target Temperature Management After Out-of-Hospital Cardiac Arrest trial. Routine EEGs were prospectively performed after the temperature intervention ≥36 hours postarrest. Patients who awoke or died prior to 36 hours postarrest were excluded. EEG experts blinded to clinical information classified EEG background, amount of discharges, and highly malignant EEG patterns according to the standardized American Clinical Neurophysiology Society terminology. Prospectively collected serum samples were analyzed for NfL after trial completion. The highest available concentration at 48 or 72 hours postarrest was used.

Results

A total of 262/939 patients with EEG and NfL data were included. Patients with highly malignant EEG patterns had 2.9 times higher NfL levels than patients with malignant patterns and NfL levels were 13 times higher in patients with malignant patterns than those with benign patterns (95% CI 1.4–6.1 and 6.5–26.2, respectively; effect size 0.47; p < 0.001). Both background and the amount of discharges were independently strongly associated with NfL levels (p < 0.001). The EEG background had a stronger association with NfL levels than EEG discharges (R² = 0.30 and R² = 0.10, respectively). NfL levels in patients with a continuous background were lower than for any other background (95% CI for discontinuous, burst-suppression, and suppression, respectively: 2.26–18.06, 3.91–41.71, and 5.74–41.74; effect size 0.30; p < 0.001 for all). NfL levels did not differ between suppression and burst suppression. Superimposed discharges were only associated with higher NfL levels if the EEG background was continuous.

Discussion

Benign, malignant, and highly malignant EEG patterns reflect the extent of brain injury as measured by NfL in serum. The extent of brain injury is more strongly related to the EEG background than superimposed discharges. Combining EEG and NfL may be useful to better identify patients misclassified by single methods.

Trial Registration Information

ClinicalTrials.gov NCT01020916.

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.

Neuroprognostication Under ECMO After Cardiac Arrest: Are Classical Tools Still Performant?

BACKGROUND

According to international guidelines, neuroprognostication in comatose patients after cardiac arrest (CA) is performed using a multimodal approach. However, patients undergoing extracorporeal membrane oxygenation (ECMO) may have longer pharmacological sedation and show alteration in biological markers, potentially challenging prognostication. Here, we aimed to assess whether routinely used predictors of poor neurological outcome also exert an acceptable performance in patients undergoing ECMO after CA.

METHODS

This observational retrospective study of our registry includes consecutive comatose adults after CA. Patients deceased within 36 h and not undergoing prognostic tests were excluded. Veno-arterial ECMO was initiated in patients < 80 years old presenting a refractory CA, with a no flow < 5 min and a low flow ≤ 60 min on admission. Neuroprognostication test performance (including pupillary reflex, electroencephalogram, somatosensory-evoked potentials, neuron-specific enolase) toward mortality and poor functional outcome (Cerebral Performance Categories [CPC] score 3-5) was compared between patients undergoing ECMO and those without ECMO.

RESULTS

We analyzed 397 patients without ECMO and 50 undergoing ECMO. The median age was 65 (interquartile range 54-74), and 69.8% of patients were men. Most had a cardiac etiology (67.6%); 52% of the patients had a shockable rhythm, and the median time to return of an effective circulation was 20 (interquartile range 10-28) minutes. Compared with those without ECMO, patients receiving ECMO had worse functional outcome (74% with CPC scores 3-5 vs. 59%, p = 0.040) and a nonsignificant higher mortality (60% vs. 47%, p = 0.080). Apart from the neuron-specific enolase level (higher in patients with ECMO, p < 0.001), the presence of prognostic items (pupillary reflex, electroencephalogram background and reactivity, somatosensory-evoked potentials, and myoclonus) related to unfavorable outcome (CPC score 3-5) in both groups was similar, as was the prevalence of at least any two such items concomitantly. The specificity of each these variables toward poor outcome was between 92 and 100% in both groups, and of the combination of at least two items, it was 99.3% in patients without ECMO and 100% in those with ECMO. The predictive performance (receiver operating characteristic curve) of their combination toward poor outcome was 0.822 (patients without ECMO) and 0.681 (patients with ECMO) (p = 0.134).

CONCLUSIONS

Pending a prospective assessment on a larger cohort, in comatose patients after CA, the performance of prognostic factors seems comparable in patients with ECMO and those without ECMO. In particular, the combination of at least two poor outcome criteria appears valid across these two groups.

Regional Distribution of Brain Injury After Cardiac Arrest: Clinical and Electrographic Correlates

BACKGROUND AND OBJECTIVES

Disorders of consciousness, EEG background suppression, and epileptic seizures are associated with poor outcome after cardiac arrest. Our objective was to identify the distribution of diffusion MRI-measured anoxic brain injury after cardiac arrest and to define the regional correlates of disorders of consciousness, EEG background suppression, and seizures.

METHODS

We analyzed patients from a single-center database of unresponsive patients who underwent diffusion MRI after cardiac arrest (n = 204). We classified each patient according to recovery of consciousness (command following) before discharge, the most continuous EEG background (burst suppression vs continuous), and the presence or absence of seizures. Anoxic brain injury was measured with the apparent diffusion coefficient (ADC) signal. We identified ADC abnormalities relative to controls without cardiac arrest (n = 48) and used voxel lesion symptom mapping to identify regional associations with disorders of consciousness, EEG background suppression, and seizures. We then used a bootstrapped lasso regression procedure to identify robust, multivariate regional associations with each outcome variable. Last, using area under receiver operating characteristic curves, we then compared the classification ability of the strongest regional associations to that of brain-wide summary measures.

RESULTS

Compared to controls, patients with cardiac arrest demonstrated ADC signal reduction that was most significant in the occipital lobes. Disorders of consciousness were associated with reduced ADC most prominently in the occipital lobes but also in deep structures. Regional injury more accurately classified patients with disorders of consciousness than whole-brain injury. Background suppression mapped to a similar set of brain regions, but regional injury could no better classify patients than whole-brain measures. Seizures were less common in patients with more severe anoxic injury, particularly in those with injury to the lateral temporal white matter.

DISCUSSION

Anoxic brain injury was most prevalent in posterior cerebral regions, and this regional pattern of injury was a better predictor of disorders of consciousness than whole-brain injury measures. EEG background suppression lacked a specific regional association, but patients with injury to the temporal lobe were less likely to have seizures. Regional patterns of anoxic brain injury are relevant to the clinical and electrographic sequelae of cardiac arrest and may hold importance for prognosis.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that disorders of consciousness after cardiac arrest are associated with widely lower ADC values on diffusion MRI and are most strongly associated with reductions in occipital ADC.

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.

Treating Rhythmic and Periodic EEG Patterns in Comatose Survivors of Cardiac Arrest

BACKGROUND

Whether the treatment of rhythmic and periodic electroencephalographic (EEG) patterns in comatose survivors of cardiac arrest improves outcomes is uncertain.

METHODS

We conducted an open-label trial of suppressing rhythmic and periodic EEG patterns detected on continuous EEG monitoring in comatose survivors of cardiac arrest. Patients were randomly assigned in a 1:1 ratio to a stepwise strategy of antiseizure medications to suppress this activity for at least 48 consecutive hours plus standard care (antiseizure-treatment group) or to standard care alone (control group); standard care included targeted temperature management in both groups. The primary outcome was neurologic outcome according to the score on the Cerebral Performance Category (CPC) scale at 3 months, dichotomized as a good outcome (CPC score indicating no, mild, or moderate disability) or a poor outcome (CPC score indicating severe disability, coma, or death). Secondary outcomes were mortality, length of stay in the intensive care unit (ICU), and duration of mechanical ventilation.

RESULTS

We enrolled 172 patients, with 88 assigned to the antiseizure-treatment group and 84 to the control group. Rhythmic or periodic EEG activity was detected a median of 35 hours after cardiac arrest; 98 of 157 patients (62%) with available data had myoclonus. Complete suppression of rhythmic and periodic EEG activity for 48 consecutive hours occurred in 49 of 88 patients (56%) in the antiseizure-treatment group and in 2 of 83 patients (2%) in the control group. At 3 months, 79 of 88 patients (90%) in the antiseizure-treatment group and 77 of 84 patients (92%) in the control group had a poor outcome (difference, 2 percentage points; 95% confidence interval, -7 to 11; P = 0.68). Mortality at 3 months was 80% in the antiseizure-treatment group and 82% in the control group. The mean length of stay in the ICU and mean duration of mechanical ventilation were slightly longer in the antiseizure-treatment group than in the control group.

CONCLUSIONS

In comatose survivors of cardiac arrest, the incidence of a poor neurologic outcome at 3 months did not differ significantly between a strategy of suppressing rhythmic and periodic EEG activity with the use of antiseizure medication for at least 48 hours plus standard care and standard care alone. (Funded by the Dutch Epilepsy Foundation; TELSTAR ClinicalTrials.gov number, NCT02056236.).

Critical care EEG standardized nomenclature in clinical practice: Strengths, limitations, and outlook on the example of prognostication after cardiac arrest

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Optimal use of the ACNS nomenclature implies integration of clinical information.

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Knowledge of pathophysiological mechanisms of EEG patterns may help interpretation.

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Standardized therapeutic procedures for critical care patients are needed.

We discuss the achievements of the ACNS critical care EEG nomenclature proposed in 2013 and, from a clinical angle, outline some limitations regarding translation into treatment implications. While the recently proposed updated 2021 version of the nomenclature will probable improve some uncertainty areas, a refined understanding of the mechanisms at the origin of the EEG patterns, and a multimodal integration of the nomenclature to the clinical context may help improving the rationale supporting therapeutic procedures. We illustrate these aspects on prognostication after cardiac arrest.

Status Myoclonus with Post-cardiac-arrest Syndrome: Implications for Prognostication

BACKGROUND

Status myoclonus (SM) after cardiac arrest (CA) may signify devastating brain injury. We hypothesized that SM correlates with severe neurologic and systemic post-cardiac-arrest syndrome (PCAS).

METHODS

Charts of patients admitted with CA to Mayo Clinic Saint Marys Hospital between 2005 and 2019 were retrospectively reviewed. Data included the neurologic examination, ancillary neurologic tests, and systemic markers of PCAS. Nonsustained myoclonus was clinically differentiated from SM. The cerebral performance category score at discharge was assessed; poor outcome was a cerebral performance category score > 2 prior to withdrawal of life-sustaining therapies or death.

RESULTS

Of 296 patients included, 276 (93.2%) had out-of-hospital arrest and 202 (68.5%) had a shockable rhythm; the mean time to return of spontaneous circulation was 32 ± 19 min. One hundred seventy-six (59.5%) patients had a poor outcome. One hundred one (34.1%) patients had myoclonus, and 74 (73.2%) had SM. Neurologic predictors of poor outcome were extensor or absent motor response to noxious stimulus (p = 0.02, odds ratio [OR] 3.8, confidence interval [CI] 1.2-12.4), SM (p = 0.01, OR 10.3, CI 1.5-205.4), and burst suppression on EEG (p = 0.01, OR 4.6, CI 1.4-17.4). Of 74 patients with SM, 73 (98.6%) had a poor outcome. A nonshockable rhythm (p < 0.001, OR 4.5, CI 2.6-7.9), respiratory arrest (p < 0.001, OR 3.5, CI 1.7-7.2), chronic kidney disease (p < 0.001, OR 3.1, CI 1.6-6.0), and a pressor requirement (p < 0.001, OR 4.4, CI 1.8-10.6) were associated with SM. No patients with SM, anoxic-ischemic magnetic resonance imaging findings, and absent electroencephalographic reactivity had a good outcome.

CONCLUSIONS

Sustained status myoclonus after CPR is observed in patients with other reliable indicators of severe acute brain injury and systemic PCAS. These clinical determinants should be incorporated as part of a comprehensive approach to prognostication after CA.

Stimulus-induced EEG-patterns and outcome after cardiac arrest

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Presence of SIRPIDs on a late routine-EEG adds no reliable prognostic information.

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SIRPIDs was rare among patients with a highly malignant EEG.

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Whether specific subtypes of SIRPIDs have prognostic implications needs further investigation.

Objective

EEG is commonly used to predict prognosis in post anoxic coma. We investigated if stimulus-induced rhythmic, periodic or ictal discharges (SIRPIDs) add prognostic information after cardiac arrest.

Methods

In the multicenter Targeted Temperature Management trial, routine-EEGs were prospectively recorded after rewarming (≥36 h). Presence and subtype of SIRPIDs and main EEG-pattern (benign, malignant, highly malignant) were retrospectively reported according to a standardised classification. Patients were followed up after 180 days. Poor outcome was defined as severe neurological disability or death (Cerebral Performance Category 3–5).

Results

Of 142 patients, 71% had poor outcome and 14% had SIRPIDs. There was no significant difference in outcome between patients with and without SIRPIDs, even when subgrouped according to underlying main EEG-pattern. Comparing subtypes of SIRPIDs, 82% of patients with stimulus-induced periodic discharges had poor outcome compared to 44% of patients with stimulus-induced rhythmic delta activity, but the difference was not significant.

Conclusions

In EEGs performed ≥36 h after cardiac arrest, SIRPIDs cannot be used to reliably predict poor outcome. Whether certain subtypes of SIRPIDs indicate worse prognosis needs further investigation.

Significance

Categorising the main EEG-pattern has important prognostic implications, but assessment of late appearing SIRPIDs does not seem to add prognostic information.

European Resuscitation Council and European Society of Intensive Care Medicine guidelines 2021: post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.

Neuromonitoring After Cardiac Arrest: Can Twenty-First Century Medicine Personalize Post Cardiac Arrest Care?

Cardiac arrest survivors comprise a heterogeneous population, in which the etiology of arrest, systemic and neurologic comorbidities, and sequelae of post-cardiac arrest syndrome influence the severity of secondary brain injury. The degree of secondary neurologic injury can be modifiable and is influenced by factors that alter cerebral physiology. Neuromonitoring techniques provide tools for evaluating the evolution of physiologic variables over time. This article reviews the pathophysiology of hypoxic-ischemic brain injury, provides an overview of the neuromonitoring tools available to identify risk profiles for secondary brain injury, and highlights the importance of an individualized approach to post cardiac arrest care.

European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: Post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation, and organ donation.

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.

Update on the management of status epilepticus

PURPOSE OF REVIEW

Randomized controlled trials investigating the initial pharmacological treatment of status epilepticus have been recently published. Furthermore, status epilepticus arising in comatose survivors after cardiac arrest has received increasing attention in the last years. This review offers an updated assessment of status epilepticus treatment in these different scenarios.

RECENT FINDINGS

Initial benzodiazepines underdosing is common and correlates with development of status epilepticus refractoriness. The recently published ESETT trial provides high-level evidence regarding the equivalence of fosphenytoin, valproate, and levetiracetam as a second-line option. Myoclonus or epileptiform transients on electroencephalography occur in up to 1/3 of patients surviving a cardiac arrest. Contrary to previous assumptions regarding an almost invariable association with death, at least 1/10 of them may awaken with reasonably good prognosis, if treated. Multimodal prognostication including clinical examination, EEG, somatosensory evoked potentials, biochemical markers, and neuroimaging help identifying patients with a chance to recover consciousness, in whom a trial with antimyoclonic compounds and at times general anesthetics is indicated.

SUMMARY

There is a continuous, albeit relatively slow progress in knowledge regarding different aspect of status epilepticus; recent findings refine some treatment strategies and help improving patients' outcomes. Further high-quality studies are clearly needed to further improve the management of these patients, especially those with severe, refractory status epilepticus forms.

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.