Early EEG contributes to multimodal outcome prediction of postanoxic coma

Epidermal Electrode Technology for Detecting Ultrasonic Perturbation of Sensory Brain Activity

OBJECTIVE

We aim to demonstrate the in vivo capability of a wearable sensor technology to detect localized perturbations of sensory-evoked brain activity.

METHODS

Cortical somatosensory evoked potentials (SSEPs) were recorded in mice via wearable, flexible epidermal electrode arrays. We then utilized the sensors to explore the effects of transcranial focused ultrasound, which noninvasively induced neural perturbation. SSEPs recorded with flexible epidermal sensors were quantified and benchmarked against those recorded with invasive epidural electrodes.

RESULTS

We found that cortical SSEPs recorded by flexible epidermal sensors were stimulus frequency dependent. Immediately following controlled, focal ultrasound perturbation, the sensors detected significant SSEP modulation, which consisted of dynamic amplitude decreases and altered stimulus-frequency dependence. These modifications were also dependent on the ultrasound perturbation dosage. The effects were consistent with those recorded with invasive electrodes, albeit with roughly one order of magnitude lower signal-to-noise ratio.

CONCLUSION

We found that flexible epidermal sensors reported multiple SSEP parameters that were sensitive to focused ultrasound. This work therefore 1) establishes that epidermal electrodes are appropriate for monitoring the integrity of major CNS functionalities through SSEP; and 2) leveraged this technology to explore ultrasound-induced neuromodulation. The sensor technology is well suited for this application because the sensor electrical properties are uninfluenced by direct exposure to ultrasound irradiation.

SIGNIFICANCE

The sensors and experimental paradigm we present involve standard, safe clinical neurological assessment methods and are thus applicable to a wide range of future translational studies in humans with any manner of health condition.

Low cerebral blood flow after cardiac arrest is not associated with anaerobic cerebral metabolism

AIM OF THE STUDY

Estimation of cerebral anaerobic metabolism in survivors and non-survivors after cardiac arrest.

METHODS

We performed an observational study in twenty comatose patients after cardiac arrest and 19 healthy control subjects. We measured mean flow velocity in the middle cerebral artery (MFV_MCA) by transcranial Doppler. Arterial and jugular blood samples were used for calculation of the jugular venous-to-arterial CO₂/arterial to-jugular venous O₂ content difference ratio.

RESULTS

After cardiac arrest, MFV_MCA increased from 26.0[18.6-40.4]cm/sec on admission to 63.9[48.3-73.1]cm/sec after 72h (p<0.0001), with no significant differences between survivors and non-survivors (p=0.4853). The MFV_MCA in controls was 59.1[52.8-69.0]cm/sec. The oxygen extraction fraction (O₂EF) was 38.9[24.4-47.7]% on admission and decreased significantly to 17.3[12.1-26.2]% at 72h (p<0.0001). The decrease in O₂EF was more pronounced in non-survivors (p=0.0173). O₂EF in the control group was 35.4[32.4-38.7]%. The jugular bulb-arterial CO₂ to arterial-jugular bulb O₂ content difference ratio was >1 at all time points after cardiac arrest and did not change during admission, with no differences between survivors and non-survivors. Values in cardiac arrest patients were similar to those in normal subjects.

CONCLUSIONS

In this study, low CBF after cardiac arrest is not associated with anaerobic metabolism. Hypoperfusion appears to be the consequence of a decrease of neuronal functioning and metabolic needs. Alternatively, hypoperfusion may decrease cerebral metabolism. Subsequently, metabolism increases in survivors, consistent with resumption of neuronal activity, whereas in non-survivors lasting low metabolism reflects irreversible neuronal damage.

Recorded time periods of bispectral index values equal to zero predict neurological outcome after out-of-hospital cardiac arrest

Background

Prognostication in out-of-hospital cardiac arrest (OHCA) survivors is often difficult. Recent studies have shown the predictive ability of bispectral index (BIS) monitoring to assist with early neuroprognostication. The aim of this study was to investigate whether characteristics of BIS values equal to zero (BIS 0) (i.e. duration and/or uni- versus bilateral presence) instead of simply their occurrence are better indicators for poor neurological outcome after OHCA by aiming at a specificity of 100%.

Methods

Between 2011 and 2015, all successfully resuscitated OHCA patients were treated with targeted temperature management (TTM) at 33 °C for 24 hours followed by rewarming over 12 hours (0.3 °C/h). In total, BIS values were registered in 77 OHCA patients. The occurrence of unilateral (BIS 0 at one hemisphere) and bilateral (BIS 0 at both hemispheres) BIS 0 values as well as their total duration were calculated. Receiver operating characteristic (ROC) curves were constructed using the total duration with BIS 0 values calculated from the initiation of TTM onwards to determine poor neurological outcome.

Results

In 30 of 77 OHCA patients (39%), at least one BIS 0 value occurred during the first 48 hours after admission. Of these 30 patients, six (20%) had a good (cerebral performance category (CPC) 1–2) and 24 (80%) a poor neurological outcome (CPC3–5) at 180 days post-CA. Within these 30 patients, the incidence of bilateral BIS 0 values was higher in patients with poor neurological outcome (CPC1–2: 2 (33%) vs. CPC3–5: 19 (79%); p = 0.028). The presence of a BIS 0 value predicted poor neurological outcome with a sensitivity of 62% and specificity of 84% (AUC: 0.729; p = 0.001). With a ROC analysis, a total duration of 30,3 minutes with BIS 0 values calculated over the first 48 hours predicted poor neurological outcome with a sensitivity of 63% and specificity of 100% (AUC: 0.861; p = 0.007).

Conclusions

This study shows that a prolonged duration with (bilateral) BIS 0 values serves as a better outcome predictor after OHCA as compared to a single observation.

Clinical evoked potentials in neurology: a review of techniques and indications

Evoked potentials (EPs) are a powerful and cost-effective tool for evaluating the integrity and function of the central nervous system. Although imaging techniques, such as MRI, have recently become increasingly important in the diagnosis of neurological diseases, over the past 30 years, many neurologists have continued to employ EPs in specific clinical applications. This review presents an overview of the recent evolution of 'classical' clinical applications of EPs in terms of early diagnosis and disease monitoring and is an extension of a previous review published in this journal in 2005 by Walsh and collaborators. We also provide an update on emerging EPs based on gustatory, olfactory and pain stimulation that may be used as clinically relevant markers of neurodegenerative disorders such as Parkinson's disease, Alzheimer's disease and cortical or peripheral impaired pain perception. EPs based on multichannel electroencephalography recordings, known as high-density EPs, help to better differentiate between healthy subjects and patients and, moreover, they provide valuable spatial information regarding the site of the lesion. EPs are reliable disease-progression biomarkers of several neurological diseases, such as multiple sclerosis and other demyelinating disorders. Overall, EPs are excellent neurophysiological tools that will expand standard clinical practice in modern neurology.

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach

INTRODUCTION

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability.

METHODS

We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns.

RESULTS

Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate).

CONCLUSION

Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy.

Early EEG for outcome prediction of postanoxic coma: prospective cohort study with cost-minimization analysis

Background

We recently showed that electroencephalography (EEG) patterns within the first 24 hours robustly contribute to multimodal prediction of poor or good neurological outcome of comatose patients after cardiac arrest. Here, we confirm these results and present a cost-minimization analysis. Early prognosis contributes to communication between doctors and family, and may prevent inappropriate treatment.

Methods

A prospective cohort study including 430 subsequent comatose patients after cardiac arrest was conducted at intensive care units of two teaching hospitals. Continuous EEG was started within 12 hours after cardiac arrest and continued up to 3 days. EEG patterns were visually classified as unfavorable (isoelectric, low-voltage, or burst suppression with identical bursts) or favorable (continuous patterns) at 12 and 24 hours after cardiac arrest. Outcome at 6 months was classified as good (cerebral performance category (CPC) 1 or 2) or poor (CPC 3, 4, or 5). Predictive values of EEG measures and cost-consequences from a hospital perspective were investigated, assuming EEG-based decision- making about withdrawal of life-sustaining treatment in the case of a poor predicted outcome.

Results

Poor outcome occurred in 197 patients (51% of those included in the analyses). Unfavorable EEG patterns at 24 hours predicted a poor outcome with specificity of 100% (95% CI 98–100%) and sensitivity of 29% (95% CI 22–36%). Favorable patterns at 12 hours predicted good outcome with specificity of 88% (95% CI 81–93%) and sensitivity of 51% (95% CI 42–60%). Treatment withdrawal based on an unfavorable EEG pattern at 24 hours resulted in a reduced mean ICU length of stay without increased mortality in the long term. This gave small cost reductions, depending on the timing of withdrawal.

Conclusions

Early EEG contributes to reliable prediction of good or poor outcome of postanoxic coma and may lead to reduced length of ICU stay. In turn, this may bring small cost reductions.

Early Presence of Sleep Spindles on Electroencephalography Is Associated With Good Outcome After Pediatric Cardiac Arrest

OBJECTIVES

The role of sleep architecture as a biomarker for prognostication after resuscitation from cardiac arrest in children hospitalized in an ICU remains poorly defined. We sought to investigate the association between features of normal sleep architecture in children after cardiac arrest and a favorable neurologic outcome at 6 months.

DESIGN

Retrospective review of medical records and continuous electroencephalography monitoring.

SETTING

Cardiac and PICU of a tertiary children's hospital.

PATIENTS

All patients from 6 months to 18 years old resuscitated from cardiac arrest who underwent continuous electroencephalography monitoring in the first 24 hours after in- or out-of-hospital cardiac arrest from January 2010 to June 2015.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Thirty-four patients underwent continuous electroencephalography monitoring after cardiac arrest. The median age was 6.1 years (interquartile range, 1.5-12.5 yr), 20 patients were male (59%). Most cases (n = 23, 68%) suffered from in-hospital cardiac arrest. Electroencephalography monitoring was initiated a median of 9.3 hours (5.8-14.9 hr) after return of spontaneous circulation, for a median duration of 14.3 hours (6.0-16.0 hr) within the first 24-hour period after the cardiac arrest. Five patients had normal spindles, five had abnormal spindles, and 24 patients did not have any sleep architecture. The presence of spindles was associated with a favorable neurologic outcome at 6-month postcardiac arrest (p = 0.001).

CONCLUSIONS

Continuous electroencephalography monitoring can be used in children to assess spindles in the ICU. The presence of spindles on continuous electroencephalography monitoring in the first 24 hours after resuscitation from cardiac arrest is associated with a favorable neurologic outcome. Assessment of sleep architecture on continuous electroencephalography after cardiac arrest could improve outcome prediction.

Prognosis of neurologic complications in critical illness

Neurologic complications of critical illness require extensive clinical and neurophysiologic evaluation to establish a reliable prognosis. Many sequelae of intensive care unit (ICU) treatment, such as delirium and ICU-acquired weakness, although highly associated with adverse outcomes, are less suitable for prognostication, but should rather prompt clinicians to seek previously unnoticed persisting underlying illnesses. Prognostication can be confounded by drug administration particularly because its clearance is abnormal in critical illness. Some neurological complications are severe, and can last for months or years after discharge from ICU. The most important ethical aspects regarding neurologic complications in critically ill patients are prevention, recognition, and identification, and prevention of self-fulfilling prophecies. This chapter summarizes the tool of prognostication of major neurological complications of critical illness.

Clinical neurophysiology for neurological prognostication of comatose patients after cardiac arrest

•

A multimodal prognostic approach is recommended after cardiac arrest.

•

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

•

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.

Minimal EEG montage with high yield for the detection of status epilepticus in the setting of postanoxic brain damage

For the diagnosis of electrographic seizures or status epilepticus, we reduced the number of EEG-electrodes to make urgent EEG monitoring more feasible. Unlike the current existing research, with mixed results, we studied a specific population with postanoxic brain damage, expecting a higher yield of detection of ictal EEG patterns. In a population treated with therapeutic hypothermia post-cardiac arrest, the initial EEGs were reformatted in a longitudinal, a hairline and an 8-lead montage, and independently reviewed by two investigators. The EEGs were categorized into three categories: one without ictal EEG activity, one with interictal activity and one with probable electrographic seizure(s). Generalized ictal EEG activity was the most frequently observed EEG pattern. The average sensitivity for the detection of probable electrographic seizure(s) was 100 % for the 8-lead montage and 92 % in the hairline montage. In comparison to the routine longitudinal montage, the 8-lead montage proved to be reliable for the detection of electrographic seizure activity in a postanoxic population even with limited training in EEG interpretation. The hairline montage did not suffice with regard to the differential diagnosis of triphasic waves associated with metabolic encephalopathy and generalized nonconvulsive status epilepticus, but nonetheless detected the vast majority of probable electrographic seizure(s). Our results support the use of EEG monitoring with fewer electrodes for the detection of ictal EEG activity in the postanoxic population.

EEG synchronization measures are early outcome predictors in comatose patients after cardiac arrest

OBJECTIVE

Outcome prognostication in comatose patients after cardiac arrest (CA) remains a major challenge. Here we investigated the prognostic value of combinations of linear and non-linear bivariate EEG synchronization measures.

METHODS

94 comatose patients with EEG within 24h after CA were included. Clinical outcome was assessed at 3months using the Cerebral Performance Categories (CPC). EEG synchronization between the left and right parasagittal, and between the frontal and parietal brain regions was assessed with 4 different quantitative measures (delta power asymmetry, cross-correlation, mutual information, and transfer entropy). 2/3 of patients were used to assess the predictive power of all possible combinations of these eight features (4 measures×2 directions) using cross-validation. The predictive power of the best combination was tested on the remaining 1/3 of patients.

RESULTS

The best combination for prognostication consisted of 4 of the 8 features, and contained linear and non-linear measures. Predictive power for poor outcome (CPC 3-5), measured with the area under the ROC curve, was 0.84 during cross-validation, and 0.81 on the test set. At specificity of 1.0 the sensitivity was 0.54, and the accuracy 0.81.

CONCLUSION

Combinations of EEG synchronization measures can contribute to early prognostication after CA. In particular, combining linear and non-linear measures is important for good predictive power.

SIGNIFICANCE

Quantitative methods might increase the prognostic yield of currently used multi-modal approaches.

Easily applicable SEP-monitoring of the N20 wave in the intensive care unit

In this technical note, a conveniently sized, single-channel somatosensory evoked potentials (SEP)-stimulation-recording unit for bedside use in the intensive care unit is presented. The validation of the SEP N20 wave in intensive care guidelines as initial parameter for the prognostic evaluation of cardiac arrest has increased the demand for a more widespread availability of SEP, outside the electrophysiological domain. A device with a simplified interface that safely guides the user through a complete examination and that includes artifact removal is a prerequisite for such more widespread use, in which expert interpretation can be reduced to a necessary minimum.

Brain Monitoring in Critically Neurologically Impaired Patients

Assessment of neurologic injury and the evolution of severe neurologic injury is limited in comatose or critically ill patients that lack a reliable neurologic examination. For common yet severe pathologies such as the comatose state after cardiac arrest, aneurysmal subarachnoid hemorrhage (aSAH), and severe traumatic brain injury (TBI), critical medical decisions are made on the basis of the neurologic injury. Decisions regarding active intensive care management, need for neurosurgical intervention, and withdrawal of care, depend on a reliable, high-quality assessment of the true state of neurologic injury, and have traditionally relied on limited assessments such as intracranial pressure monitoring and electroencephalogram. However, even within TBI there exists a spectrum of disease that is likely not captured by such limited monitoring and thus a more directed effort towards obtaining a more robust biophysical signature of the individual patient must be undertaken. In this review, multimodal monitoring including the most promising serum markers of neuronal injury, cerebral microdialysis, brain tissue oxygenation, and pressure reactivity index to access brain microenvironment will be discussed with their utility among specific pathologies that may help determine a more complete picture of the neurologic injury state for active intensive care management and long-term outcomes. Goal-directed therapy guided by a multi-modality approach appears to be superior to standard intracranial pressure (ICP) guided therapy and should be explored further across multiple pathologies. Future directions including the application of optogenetics to evaluate brain injury and recovery and even as an adjunct monitoring modality will also be discussed.

Continuous EEG monitoring enhances multimodal outcome prediction in hypoxic-ischemic brain injury

OBJECTIVE

Hypoxic brain injury is the largest contributor to disability and mortality after cardiac arrest. We aim to identify electroencephalogram (EEG) characteristics that can predict outcome on cardiac arrest patients treated with targeted temperature management (TTM).

METHODS

We retrospectively examined clinical, EEG, functional outcome at discharge, and in-hospital mortality for 373 adult subjects with return of spontaneous circulation after cardiac arrest. Poor outcome was defined as a Cerebral Performance Category score of 3-5. Pure suppression-burst (SB) was defined as SB not associated with status epilepticus (SE), seizures, or generalized periodic discharges.

RESULTS

In-hospital mortality was 68.6% (N=256). Presence of both unreactive EEG background and SE was associated with a positive predictive value (PPV) of 100% (95% confidence interval: 0.96-1) and a false-positive rate (FPR) of 0% (95% CI: 0-0.11) for poor functional outcome. A prediction model including demographics data, admission exam, presence of status epilepticus, pure SB, and lack of EEG reactivity had an area under the curve of 0.92 (95% CI: 0.87-0.95) for poor functional outcome prediction, and 0.96 (95% CI: 0.94-0.98) for in-hospital mortality. Presence of pure SB (N=87) was confounded by anesthetics use in 83.9% of the cases, and was not an independent predictor of poor functional outcome, having a FPR of 23% (95% CI: 0.19-0.28).

CONCLUSIONS

An unreactive EEG background and SE predicted poor functional outcome and in-hospital mortality in cardiac arrest patients undergoing TTM. Prognostic value of pure SB is confounded by use of sedative agents, and its use on prognostication decisions should be made with caution.

Utilization of electroencephalogram post cardiac arrest in the United States: A nationwide retrospective cohort analysis

OBJECTIVE

The use of electroencephalogram (EEG) has been demonstrated to have diagnostic and prognostic value in cardiac arrest patients. The use of this modality across the United States in this population is unknown.

METHODS

The Nationwide Inpatient Sample (NIS) is a federal database capturing 20% of all US hospital admissions. A cohort of patients who suffered both in and out of hospital cardiac arrests from the 2006 to 2012 NIS datasets was created.

RESULTS

The records of 55,208,382 hospitalizations were analyzed, of which 207,703 patients suffered a cardiac arrest. There were 2952 (1.42%) patients who also had an EEG. Patients who had an EEG compared to those who did not were: younger (62.2 years SD 16.6 vs 66.9 years SD 16.2, p<0.01), were less likely to have insurance coverage (89.9% vs 91.6%, p=0.03) and had significantly longer length of stay (8.6days IQR 3.7-17.1 vs 4.1days IQR 1.0-10.5, p<0.01). Patients treated at urban teaching hospitals were more likely to receive an EEG than patients treated at urban non-teaching and rural hospitals (p<0.01). The rate of EEG in survivors of cardiac arrest increased from 1.03% in 2006 to 2.16% in 2012, a relative increase of 110% (p<0.02). The median time to performance of an EEG was 1.6days IQR 0.33-4.53 days.

CONCLUSION

EEG is performed on approximately 2% of patients who suffer cardiac arrest in the United States. The treatment hospital and patient characteristics of those who received an EEG different from those who did not.

Combination of initial neurologic examination, quantitative brain imaging and electroencephalography to predict outcome after cardiac arrest

BACKGROUND

Prognosticating outcome following cardiac arrest is challenging and requires a multimodal approach. We tested the hypothesis that the combination of initial neurologic examination, quantitative analysis of head computed tomography (CT) and continuous EEG (cEEG) improve outcome prediction after cardiac arrest.

METHODS

Review of consecutive patients receiving head CT within 24h and cEEG monitoring between April 2010 and May 2013. Initial neurologic examination (Full Outline of UnResponsiveness_Brainstem reflexes (FOUR_B) score and initial Pittsburgh Post-Cardiac Arrest Category (PCAC)), gray matter to white matter attenuation ratio (GWR) on head CT and cEEG patterns were evaluated. The primary outcome was in-hospital mortality.

RESULTS

Of 240 subjects, 70 (29%) survived and 22 (9%) had a good neurologic outcome at hospital discharge. Combined determination of GW ratio and malignant cEEG had an incremental predictive value (AUC: 0.776 for mortality and 0.792 for poor neurologic outcome), with 0% false positive rate when compared with either test alone (AUC of GW ratio: 0.683 for mortality and 0.726 for poor outcome, AUC of malignant cEEG: 0.650 for mortality and 0.647 for poor outcome). Addition of FOUR_B or PCAC to this model improved prediction of mortality (p=0.014 for FOUR_B and 0.001 for PCAC) but not of poor outcome (p=0.786 for FOUR_B and 0.099 for PCAC).

CONCLUSIONS

Combining GWR with cEEG was superior to any individual test for predicting mortality and neurologic outcome. Addition of clinical variables further improved prognostication for mortality but not neurologic outcome. These preliminary data support a multi-modal prognostic workup in this population.

Persistent generalized periodic discharges: A specific marker of fatal outcome in cerebral hypoxia

OBJECTIVES

Electroencephalography (EEG) is one of the methods used in predicting the outcome after cerebral hypoxia. In this study we aim to evaluate the significance of generalized periodic discharges (GPD) as a prognostic marker.

METHODS

We retrospectively analyzed the medical histories of patients, who underwent an EEG after cardiac arrest during the time period from 2005 to 2013 at the University Hospital Zurich. All EEGs were re-interpreted using the 2012 American Clinical Neurophysiology Society (ACNS) classification for intensive care unit (ICU) EEGs.

RESULTS

Out of 131 patients, in which an EEG was recorded after cardiopulmonary resuscitation, 119 were included in our study. The average interval between cardiac arrest and EEG-recording was 3.8±3.0days (range: 0-14days). Persistent GPDs (i.e. GPDs more than 24h after the event) were found in thirty-two (26.9%) of the patients initial EEGs. The appearance of persistent GPDs preceded fatal outcome in 100% of all cases (vs. 69.0% in the non-GPD-group, p<0.0001).

CONCLUSION

Among other encephalopathic markers in EEG persistent GPDs are a highly specific prognostic marker of fatal outcome in patients with hypoxic encephalopathy.

SIGNIFICANCE

Using standardized EEG interpretation, this study identified persistent GPDs as a specific prognostic marker in post cardiac arrest syndrome.

ACNS Critical Care EEG Terminology: Value, Limitations, and Perspectives

The interpretation of the EEG in the critically ill remains a clinical challenge. Because continuous EEG monitoring plays an increasing role in patients' care, it is important that research efforts investigate the clinical significance of periodic and rhythmic discharges and of background abnormalities. The 2012 American Clinical Neurophysiology Society critical care EEG terminology was designed to provide a comprehensive and objective vocabulary for that purpose. The interrater reliability of most of the proposed terms has been established, confirming that they represent a solid basis for research. Studies using the terminology have already started to define the clinical and prognostic values of several known or newly described EEG patterns. Yet, as the field of critical care EEG evolves, improvements will be required to further enhance the clarity of the terminology and incorporate new findings from ongoing research.

Stimulus induced bursts in severe postanoxic encephalopathy

OBJECTIVE

To report on a distinct effect of auditory and sensory stimuli on the EEG in comatose patients with severe postanoxic encephalopathy.

METHODS

In two comatose patients admitted to the Intensive Care Unit (ICU) with severe postanoxic encephalopathy and burst-suppression EEG, we studied the effect of external stimuli (sound and touch) on the occurrence of bursts.

RESULTS

In patient A bursts could be induced by either auditory or sensory stimuli. In patient B bursts could only be induced by touching different facial regions (forehead, nose and chin). When stimuli were presented with relatively long intervals, bursts persistently followed the stimuli, while stimuli with short intervals (<1s) did not induce bursts. In both patients bursts were not accompanied by myoclonia. Both patients deceased.

CONCLUSIONS

Bursts in patients with a severe postanoxic encephalopathy can be induced by external stimuli, resulting in stimulus-dependent burst-suppression.

SIGNIFICANCE

Stimulus induced bursts should not be interpreted as prognostic favourable EEG reactivity.

Cardiac Arrest and Postanoxic Encephalopathy

PURPOSE OF REVIEW

Neuroprognostication following cardiac arrest is a common and challenging dilemma for neurologists and intensivists, complicated by the use of therapeutic hypothermia and targeted temperature management. Great advances have been made in understanding the mechanisms of disorders of consciousness in hypoxic-ischemic brain injury, and new diagnostic and therapeutic avenues are arising.

RECENT FINDINGS

In the era of therapeutic hypothermia and targeted temperature management, traditional clinical signs, electrophysiologic findings, and chemical biomarkers have now become questionable or variable, and the proper time for diagnostic and prognostic testing has become murky. Although the value of absent pupillary and corneal reflexes remains fairly robust, the presence of myoclonic status epilepticus and a motor response of extensor posturing or worse no longer appear to have acceptable false-positive rates. Somatosensory evoked potentials (SSEPs), thought to be the most reliable ancillary test for predicting prognosis, have recently been the subject of several reports showing unexpectedly good outcome in the face of absent cortical responses. The presence or absence of reactivity on EEG appears to be a promising prognostic sign, and aggressive treatment of seizures (and even status epilepticus) may lead to better than expected outcomes. Serum biomarkers that were previously felt to be valid, such as elevated neuron-specific enolase, have been drawn into question owing to multiple reports of patient survival with good outcome despite highly elevated levels. Advanced EEG and neuroimaging techniques, particularly looking at functional connectivity and underlying neuronal pathways, are giving great insights to the underlying mechanisms of disease and potential therapeutic targets.

SUMMARY

Predicting neurologic prognosis following cardiac arrest is an evolving field, with new prognostic methods and reevaluation of older techniques holding great promise for advancing our ability to predict outcome and improve patient care.

Early Electroencephalographic Findings Correlate With Neurologic Outcome in Children Following Cardiac Arrest

OBJECTIVES

To determine the clinical and electroencephalographic findings associated with prognosis in nonneonate children following cardiac arrest.

DESIGN

Retrospective observational study.

SETTING

PICU and cardiac ICU.

PATIENTS

Nonneonate children with a history of cardiac arrest more than 2 minutes.

INTERVENTIONS

Electroencephalographic monitoring within 72 hours of return of spontaneous circulation.

MEASUREMENTS AND MAIN RESULTS

Clinical and features, neurophysiologic data, and Pediatric Cerebral Performance Category scores were collected. Electroencephalographic traces were reviewed in a blinded manner, all seizures and electroencephalographic findings noted, and the electroencephalography was scored at 1 hour, 24 hours, and continuous electroencephalographic end. Discrete data regarding specific characteristics of the electroencephalographic background and seizures were studied. Univariate and multivariate analyses were performed to identify associations between clinical variables, electroencephalographic findings, and Pediatric Cerebral Performance Category score at hospital discharge. Multivariate analysis of 73 children revealed duration of cardiac arrest less than 20 minutes or continuous electroencephalographic background activity within 12 hours postreturn of spontaneous circulation were associated with good short term neurologic outcome. Change in electroencephalographic background score over time and electroencephalographic data collected after the initial hour were not associated with outcome.

CONCLUSIONS

Following pediatric cardiac arrest, an initially normal electroencephalography or generalized slowing of the electroencephalographic background was associated with good neurologic outcome at hospital discharge.

Clinically distinct electroencephalographic phenotypes of early myoclonus after cardiac arrest

OBJECTIVE

We tested the hypothesis that there are readily classifiable electroencephalographic (EEG) phenotypes of early postanoxic multifocal myoclonus (PAMM) that develop after cardiac arrest.

METHODS

We studied a cohort of consecutive comatose patients treated after cardiac arrest from January 2012 to February 2015. For patients with clinically evident myoclonus before awakening, 2 expert physicians reviewed and classified all EEG recordings. Major categories included: Pattern 1, suppression-burst background with high-amplitude polyspikes in lockstep with myoclonic jerks; and Pattern 2, continuous background with narrow, vertex spike-wave discharges in lockstep with myoclonic jerks. Other patterns were subcortical myoclonus and unclassifiable. We compared population characteristics and outcomes across these EEG subtypes.

RESULTS

Overall, 401 patients were included, of whom 69 (16%) had early myoclonus. Among these patients, Pattern 1 was the most common, occurring in 48 patients (74%), whereas Pattern 2 occurred in 8 patients (12%). The remaining patients had subcortical myoclonus (n = 2, 3%) or other patterns (n = 7, 11%). No patients with Pattern 1, subcortical myoclonus, or other patterns survived with favorable outcome. By contrast, 4 of 8 patients (50%) with Pattern 2 on EEG survived, and 4 of 4 (100%) survivors had favorable outcomes despite remaining comatose for 1 to 2 weeks postarrest.

INTERPRETATION

Early PAMM is common after cardiac arrest. We describe 2 distinct patterns with distinct prognostic significances. For patients with Pattern 1 EEGs, it may be appropriate to abandon our current clinical standard of aggressive therapy with conventional antiepileptic therapy in favor of early limitation of care or novel neuroprotective strategies. Ann Neurol 2016;80:175-184.

Standard EEG in diagnostic process of prolonged disorders of consciousness

OBJECTIVE

This cross-sectional study assessed the ability of standard EEG in distinguishing vegetative state (VS) from minimally conscious state plus (MCS+) or MCS minus (MCS-), and to correlate EEG features with aetiology and level of responsiveness assessed by Coma Recovery Scale-Revised (CRS-R).

METHODS

We analyzed background EEG activity and EEG reactivity to eye opening and closing and to tactile, acoustic, nociceptive stimuli and Intermittent Photic Stimulation (IPS) in 73 inpatients (VS=37, MCS-=11, MCS+=25), with traumatic (n=21), vascular (n=25) or anoxic (n=27) aetiology.

RESULTS

All patients, but one, showed abnormal background activity. EEG abnormalities were more severe in VS than in MCS+ or MCS-, and in anoxic than other aetiologies. MCS+ patients with normal or Mildly Abnormal background activity showed higher scores on CRS-R than patients with moderate to severe EEG abnormalities. Reactivity to IPS, and acoustic stimuli was significantly more frequent in MCS+ and MCS- than in VS patients.

CONCLUSIONS

EEG features differ between VS and MCS- or MCS+ patients and can provide evidence of relative sparing of thalamocortical connections in MCS+ patients. In anoxic patients EEG organization is more severely impaired and provides less discriminative diagnostic information.

SIGNIFICANCE

Conventional EEG can help clinicians to disentangle VS from MCS patients.

Neurological prognostication of outcome in patients in coma after cardiac arrest

Management of coma after cardiac arrest has improved during the past decade, allowing an increasing proportion of patients to survive, thus prognostication has become an integral part of post-resuscitation care. Neurologists are increasingly confronted with raised expectations of next of kin and the necessity to provide early predictions of long-term prognosis. During the past decade, as technology and clinical evidence have evolved, post-cardiac arrest prognostication has moved towards a multimodal paradigm combining clinical examination with additional methods, consisting of electrophysiology, blood biomarkers, and brain imaging, to optimise prognostic accuracy. Prognostication should never be based on a single indicator; although some variables have very low false positive rates for poor outcome, multimodal assessment provides resassurance about the reliability of a prognostic estimate by offering concordant evidence.

EEG in postanoxic coma: Prognostic and diagnostic value

Evolution of the EEG background pattern is a robust contributor to prediction of poor or good outcome of comatose patients after cardiac arrest. At 24h, persistent isoelectricity, low voltage activity, or burst-suppression with identical bursts predicts a poor outcome without false positives. Rapid recovery toward continuous patterns within 12h is strongly associated with a good neurological outcome. Predictive values are highest in the first 24h, despite the use of mild therapeutic hypothermia and sedative medication. Studies on reactivity or mismatch negativity have not included the EEG background pattern. Therefore, the additional predictive value of reactivity parameters remains unclear. Whether or not treatment of electrographic status epilepticus improves outcome is studied in the randomized multicenter Treatment of Electroencephalographic STatus epilepticus After cardiopulmonary Resuscitation (TELSTAR) trial (NCT02056236).

Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

Objective:

To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society.

Methods:

In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days.

Results:

Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome.

Conclusions:

Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome.

Predictive value of EEG-awakening for behavioral awakening from coma

BACKGROUND

A reliable predictor for early recovery of consciousness in comatose patients is of great clinical significance. Here we aimed to investigate the potentially prognostic value of electroencephalogram-reactivity (EEG-R) in combination with sleep spindles, termed EEG-awakening, for behavioral awakening in etiologically diverse comatose patients.

METHODS

We performed a prospectively observational study on a sample of patients, all of whom were in coma lasting longer than 3 days. Continuous EEG monitoring was performed for at least 24 h to detect the presence of EEG-R and sleep spindles. We then followed patients for 1 month to determine their subsequent level of consciousness, classifying them as either awakened or non-awakened. Finally, Univariate and multivariate analyses were employed to assess the association of predictors with consciousness recovery.

RESULTS

One hundred and six patients with different etiologies leading to coma were included in the study. Of these, 48 patients (45.3 %) awoke and 58 patients (54.7 %) did not awake in the month after the onset of the study. Of note, 26 patients (24.5 %) had a good neurological outcome, and 31 patients (29.3 %) died. Univariate analysis revealed that the Glasgow Coma Scale (GCS) score, EEG-R, sleep spindles, and EEG-awakening were all associated with one-month awakening. Comparisons of the area under the receiving operator characteristic curve (AUC) showed that EEG-awakening (0.839; 0.757-0.921) was superior to all of the following: EEG-R (0.798; 0.710-0.886), sleep spindles (0.772; 0.680-0.864), and GCS scores (0.720; 0.623-0.818). However, age, gender, etiology, and pupillary light reflex did not correlate significantly with one-month awakening. Further logistic regression analysis showed that only EEG-awakening and GCS scores at study entry were significant independent predictors of awakening and that the prognostic model containing these two variables yielded an outstanding predictive performance with an AUC of 0.903.

CONCLUSIONS

EEG-awakening incorporates both EEG-R and sleep spindles and is an excellent predictor for early behavioral awakening in comatose patients. The prognostic model combining EEG-awakening and GCS scores shows an outstanding discriminative power for awakening.

Acyl Ghrelin Improves Synapse Recovery in an In Vitro Model of Postanoxic Encephalopathy

Comatose patients after cardiac arrest have a poor prognosis. Approximately half never awakes as a result of severe diffuse postanoxic encephalopathy. Several neuroprotective agents have been tested, however without significant effect. In the present study, we used cultured neuronal networks as a model system to study the general synaptic damage caused by temporary severe hypoxia and the possibility to restrict it by ghrelin treatment. Briefly, we applied hypoxia (pO₂ lowered from 150 to 20 mmHg) during 6 h in 55 cultures. Three hours after restoration of normoxia, half of the cultures were treated with ghrelin for 24 h, while the other, non-supplemented, were used as a control. All cultures were processed immunocytochemically for detection of the synaptic marker synaptophysin. We observed that hypoxia led to drastic decline of the number of synapses, followed by some recovery after return to normoxia, but still below the prehypoxic level. Additionally, synaptic vulnerability was selective: large- and small-sized neurons were more susceptible to synaptic damage than the medium-sized ones. Ghrelin treatment significantly increased the synapse density, as compared with the non-treated controls or with the prehypoxic period. The effect was detected in all neuronal subtypes. In conclusion, exogenous ghrelin has a robust impact on the recovery of cortical synapses after hypoxia. It raises the possibility that ghrelin or its analogs may have a therapeutic potential for treatment of postanoxic encephalopathy.