Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

Electroencephalography in Epilepsy Evaluation

PURPOSE OF REVIEW

Epilepsy is a heterogeneous disorder that is often associated with abnormal electroencephalogram (EEG) findings. This article provides an overview of common EEG findings in epileptic disorders. The physiologic basis of EEG and intracranial EEG studies is also discussed.

RECENT FINDINGS

EEG is widely used in clinical practice. Because of the paroxysmal nature of seizure disorders, interictal epileptiform discharges, such as spikes and sharp waves, are often used to support the diagnosis of epilepsy when a habitual seizure is not captured by EEG. Interictal and ictal EEG findings also underlie the classification of seizures and epilepsy. Continuous critical care EEG monitoring has become an invaluable study in the diagnosis and treatment of subclinical seizures and nonconvulsive status epilepticus. Intracranial EEG with subdural or intraparenchymal electrodes is warranted when localization of the seizure focus and mapping of eloquent brain areas are required to plan epilepsy surgery.

SUMMARY

The EEG is a key tool in the diagnosis of epilepsy. Interictal and ictal EEG findings are crucial for the confirmation and classification of seizure disorders. Intracranial EEG monitoring is also indispensable for planning surgery for some patients.

Electroencephalographic Reporting for Refractory Status Epilepticus

PURPOSE

We aimed to determine whether clinical EEG reports obtained from children in the intensive care unit with refractory status epilepticus could provide data for comparative effectiveness research studies.

METHODS

We conducted a retrospective descriptive study to assess the documentation of key variables within clinical continuous EEG monitoring reports based on the American Clinical Neurophysiology Society's standardized EEG terminology for children with refractory status epilepticus from 10 academic centers. Two pediatric electroencephalographers reviewed the EEG reports. We compared reports generated using free text or templates.

RESULTS

We reviewed 191 EEG reports. Agreement between the electroencephalographers regarding whether a variable was described in the report ranged from fair to very good. The presence of electrographic seizures (ES) was documented in 46% (87/191) of reports, and these reports documented the time of first ES in 64% (56/87), ES duration in 72% (63/85), and ES frequency in 68% (59/87). Reactivity was documented in 16% (31/191) of reports, and it was more often documented in template than in free-text reports (40% vs. 14%, P = 0.006). Other variables were not differentially reported in template versus free-text reports.

CONCLUSIONS

Many key EEG features are not documented consistently in clinical continuous EEG monitoring reports, including ES characteristics and reactivity assessment. Standardization may be needed for clinical EEG reports to provide informative data for large multicenter observational studies.

Neurological outcome of postanoxic refractory status epilepticus after aggressive treatment

Refractory status epilepticus (RSE) occurs in up to 30% of patients following resuscitation after cardiac arrest. The impact of aggressive treatment of postanoxic RSE on long-term neurological outcome remains uncertain. We investigated neurological outcome of cardiac arrest patients with RSE treated with a standardized aggressive protocol with antiepileptic drugs and anesthetics, compared with patients with other electroencephalographic (EEG) patterns. A prospective cohort of 166 consecutive patients with cardiac arrest in coma was stratified according to four independent EEG patterns (benign; RSE; generalized periodic discharges (GPDs); malignant nonepileptiform) and multimodal prognostic indicators. Primary outcomes were survival and cerebral performance category (CPC) at 6 months. Refractory status epilepticus occurred in 36 patients (21.7%) and was treated with an aggressive standardized protocol as long as multimodal prognostic indicators were not unfavorable. Refractory status epilepticus started after 3 ± 2.3 days after cardiac arrest and lasted 4.7 ± 4.3 days. A benign electroencephalographic patterns was recorded in 76 patients (45.8%), a periodic pattern (GPDs) in 13 patients (7.8%), and a malignant nonepileptiform EEG pattern in 41 patients (24.7%). The four EEG patterns were highly associated with different prognostic indicators (low flow time, clinical motor seizures, N20 responses, neuron-specific enolase (NSE), neuroimaging). Survival and good neurological outcome (CPC 1 or 2) at 6 months were 72.4% and 71.1% for benign EEG pattern, 54.3% and 44.4% for RSE, 15.4% and 0% for GPDs, and 2.4% and 0% for malignant nonepileptiform EEG pattern, respectively. Aggressive and prolonged treatment of RSE may be justified in cardiac arrest patients with favorable multimodal prognostic indicators. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".

Neurophysiology for predicting good and poor neurological outcome at 12 and 72 h after cardiac arrest: The ProNeCA multicentre prospective study

AIMS

To assess the accuracy of electroencephalogram (EEG) and somatosensory evoked potentials (SEPs) recorded at 12 and 72 h from resuscitation for predicting six-months neurological outcome in patients who are comatose after cardiac arrest.

METHODS

Prospective multicentre prognostication study. EEG was classified according to the American Clinical Neurophysiology Society terminology. SEPs were graded according to the presence and amplitude of their cortical responses. Neurological outcome was defined as good (cerebral performance categories [CPC] 1-3) vs. poor (CPC 4-5). None of the patients underwent withdrawal of life-sustaining treatment.

RESULTS

A total of 351 patients were included, of whom 134 (38%) had good neurological outcome. At 12 h, a continuous, nearly continuous and low-voltage EEG pattern predicted good neurological outcome with 71[61-80]% sensitivity, while an isoelectric EEG and a bilaterally absent/absent-pathological amplitude (AA/AP) cortical SEP pattern predicted poor neurological outcome with 14[8-21]% and 59[50-68]% sensitivity, respectively. Specificity was 100[97-100]% for all predictors. At 72 h, both an isoelectric, suppression or burst-suppression pattern on EEG and an AA/AP SEP pattern predicted poor outcome with 100[97-100]% specificity. Their sensitivities were 63[55-70]% and 66[58-74]%, respectively. When EEG and SEPs were combined, sensitivity for poor outcome prediction increased to 79%.

CONCLUSIONS

In comatose resuscitated patients, EEG and SEPs predicted good and poor neurological outcome respectively, with 100% specificity as early as 12 h after cardiac arrest. At 72 h after arrest, unfavourable EEG and SEP patterns predicted poor neurological outcome with 100% specificity and high sensitivity, which further increased after their combination.

Serum Neurofilament Light Chain for Prognosis of Outcome After Cardiac Arrest

Importance

Prognostication of neurologic outcome after cardiac arrest is an important but challenging aspect of patient therapy management in critical care units.

Objective

To determine whether serum neurofilament light chain (NFL) levels can be used for prognostication of neurologic outcome after cardiac arrest.

Design, Setting and Participants

Prospective clinical biobank study of data from the randomized Target Temperature Management After Cardiac Arrest trial, an international, multicenter study with 29 participating sites. Patients were included between November 11, 2010, and January 10, 2013. Serum NFL levels were analyzed between August 1 and August 23, 2017, after trial completion. A total of 782 unconscious patients with out-of-hospital cardiac arrest of presumed cardiac origin were eligible.

Exposures

Serum NFL concentrations analyzed at 24, 48, and 72 hours after cardiac arrest with an ultrasensitive immunoassay.

Main Outcomes and Measures

Poor neurologic outcome at 6-month follow-up, defined according to the Cerebral Performance Category Scale as cerebral performance category 3 (severe cerebral disability), 4 (coma), or 5 (brain death).

Results

Of 782 eligible patients, 65 patients (8.3%) were excluded because of issues with aliquoting, missing sampling, missing outcome, or transport problems of samples. Of the 717 patients included (91.7%), 580 were men (80.9%) and median (interquartile range [IQR]) age was 65 (56-73) years. A total of 360 patients (50.2%) had poor neurologic outcome at 6 months. Median (IQR) serum NFL level was significantly increased in the patients with poor outcome vs good outcome at 24 hours (1426 [299-3577] vs 37 [20-70] pg/mL), 48 hours (3240 [623-8271] vs 46 [26-101] pg/mL), and 72 hours (3344 [845-7838] vs 54 [30-122] pg/mL) (P < .001 at all time points), with high overall performance (area under the curve, 0.94-0.95) and high sensitivities at high specificities (eg, 69% sensitivity with 98% specificity at 24 hours). Serum NFL levels had significantly greater performance than the other biochemical serum markers (ie, tau, neuron-specific enolase, and S100). At comparable specificities, serum NFL levels had greater sensitivity for poor outcome compared with routine electroencephalogram, somatosensory-evoked potentials, head computed tomography, and both pupillary and corneal reflexes (ranging from 29.2% to 49.0% greater for serum NFL level).

Conclusions and Relevance

Findings from this study suggest that the serum NFL level is a highly predictive marker of long-term poor neurologic outcome at 24 hours after cardiac arrest and may be a useful complement to currently available neurologic prognostication methods.

Targeted hypothermia versus targeted Normothermia after out-of-hospital cardiac arrest (TTM2): A randomized clinical trial-Rationale and design

BACKGROUND

Less than 500 participants have been included in randomized trials comparing hypothermia with regular care for out-of-hospital cardiac arrest patients, and many of these trials were small and at a high risk of bias. Consequently, the accrued data on this potentially beneficial intervention resembles that of a drug following small phase II trials. A large confirmatory trial is therefore warranted.

METHODS

The TTM2-trial is an international, multicenter, parallel group, investigator-initiated, randomized, superiority trial in which a target temperature of 33°C after cardiac arrest will be compared with a strategy to maintain normothermia and early treatment of fever (≥37.8°C). Participants will be randomized within 3 hours of return of spontaneous circulation with the intervention period lasting 40 hours in both groups. Sedation will be mandatory for all patients throughout the intervention period. The clinical team involved with direct patient care will not be blinded to allocation group due to the inherent difficulty in blinding the intervention. Prognosticators, outcome-assessors, the steering group, the trial coordinating team, and trial statistician will be blinded. The primary outcome will be all-cause mortality at 180 days after randomization. We estimate a 55% mortality in the control group. To detect an absolute risk reduction of 7.5% with an alpha of 0.05 and 90% power, 1900 participants will be enrolled. The main secondary neurological outcome will be poor functional outcome (modified Rankin Scale 4-6) at 180 days after arrest.

DISCUSSION

The TTM2-trial will compare hypothermia to 33°C with normothermia and early treatment of fever (≥37.8°C) after out-of-hospital cardiac arrest.

Timing of brain computed tomography and accuracy of outcome prediction after cardiac arrest

AIM

Gray-white-matter ratio (GWR) calculated from head CT is a radiologic index of tissue changes associated with hypoxic-ischemic encephalopathy after cardiac arrest (CA). Evidence from previous studies indicates high specificity for poor outcome prediction at GWR thresholds of 1.10-1.20. We aimed to determine the relationship between accuracy of neurologic prognostication by GWR and timing of CT.

METHODS

We included 195 patients admitted to the ICU following CA. GWR was calculated from CT radiologic densities in 16 regions of interest. Outcome was determined upon intensive care unit discharge using the cerebral performance category (CPC). Accuracy of outcome prediction of GWR was compared for 3 epochs (<6, 6-24, and >24 h after CA).

RESULTS

125 (64%) patients had poor (CPC4-5) and 70 (36%) good outcome (CPC1-3). Irrespective of timing, specificity for poor outcome prediction was 100% at a GWR threshold of 1.10. Among 50 patients with both early and late CT, GWR decreased significantly over time (p = 0.002) in patients with poor outcome, sensitivity for poor outcome prediction was 12% (7-20%) with early CTs (<6 h) and 48% (38-58%) for late CTs (>24 h). Across all patients, sensitivity of early and late CT was 17% (9-28%) and 39% (28-51%), respectively.

CONCLUSION

A GWR below 1.10 predicts poor outcome (CPC4-5) in patients after CA with high specificity irrespective of time of acquisition of CT. Because GWR decreases over time in patients with severe HIE, sensitivity for prediction of poor outcome is higher for late CTs (>24 h after CA) as compared to early CTs (<6 h after CA).

Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury

OBJECTIVE

Electroencephalogram (EEG) reactivity is a robust predictor of neurological recovery after cardiac arrest, however interrater-agreement among electroencephalographers is limited. We sought to evaluate the performance of machine learning methods using EEG reactivity data to predict good long-term outcomes in hypoxic-ischemic brain injury.

METHODS

We retrospectively reviewed clinical and EEG data of comatose cardiac arrest subjects. Electroencephalogram reactivity was tested within 72 h from cardiac arrest using sound and pain stimuli. A Quantitative EEG (QEEG) reactivity method evaluated changes in QEEG features (EEG spectra, entropy, and frequency features) during the 10 s before and after each stimulation. Good outcome was defined as Cerebral Performance Category of 1-2 at six months. Performance of a random forest classifier was compared against a penalized general linear model (GLM) and expert electroencephalographer review.

RESULTS

Fifty subjects were included and sixteen (32%) had good outcome. Both QEEG reactivity methods had comparable performance to expert EEG reactivity assessment for good outcome prediction (mean AUC 0.8 for random forest vs. 0.69 for GLM vs. 0.69 for expert review, respectively; p non-significant).

CONCLUSIONS

Machine-learning models utilizing quantitative EEG reactivity data can predict long-term outcome after cardiac arrest.

SIGNIFICANCE

A quantitative approach to EEG reactivity assessment may support prognostication in cardiac arrest.

Association of antiepileptic drugs with resolution of epileptiform activity after cardiac arrest

INTRODUCTION

We tested the impact of antiepileptic drug (AED) administration on post-cardiac arrest epileptiform electroencephalographic (EEG) activity.

METHODS

We studied an observational cohort of comatose subjects treated at a single academic medical center after cardiac arrest from September 2010 to January 2018. We aggregated the observed EEG patterns into 5 categories: suppressed; discontinuous background with superimposed epileptiform activity; discontinuous background without epileptiform features; continuous background with epileptiform activity; and continuous background without epileptiform activity. We calculated overall probabilities of transitions between EEG states in a multistate model, then used Aalen's additive regression to test if AEDs or hypothermia are associated with a change in these probabilities.

RESULTS

Overall, 828 subjects had EEG-monitoring for 42,840 h with a median of 40 [IQR 23-64] h per subject. Among patients with epileptiform findings on initial monitoring, 50% transitioned at least once to a non-epileptiform, non-suppressed state. By contrast, 19% with non-epileptiform initial activity transitioned to an epileptiform state at least once. Overall, 568 (78%) patients received at least one AED. Among patients with continuous EEG background activity, valproate, levetiracetam and lower body temperature were each associated with an increased probability of transition from epileptiform states to non-epileptiform states, where patients with discontinuous EEG background activity no agent linked to an increased probability of transitioning from epileptiform states.

CONCLUSION

After cardiac arrest, the impact of AEDs may depend on the presence of continuous cortical background activity. These data serve to inform experimental work to better define the opportunities to improve neurologic care post-cardiac arrest.

Prognostication via early computed tomography head in patients treated with targeted temperature management after cardiac arrest

BACKGROUND

We evaluated computed tomography head (CTH) imaging obtained prior to targeted temperature management (TTM) in patients after cardiac arrest, and its role in prognostication.

METHODS

In this retrospective cohort study in a tertiary-care hospital, 341 adults presenting with out-of-hospital cardiac arrest received a CTH prior to TTM. Associations between outcomes and neuroimaging variables were evaluated with Chi-square analysis for significant associations that yielded a composite neuroimaging score-Tennessee Early Neuroimaging Score (TENS). Univariable and multivariable logistic regression analysis including TENS as an independent variable and the four outcome dependent variables were analyzed.

RESULTS

Four of the neuroimaging variables-sulcal effacement, partial gray-white matter effacement, total gray-white matter effacement, deep nuclei effacement-had significant associations with each of the four outcome variables and yielded TENS. In multivariable logistic regression models adjusted for potential confounders, TENS was associated with poor discharge CPC (OR 2.15, 95%CI 1.16-3.98, p = .015), poor disposition (OR 2.62, 95%CI 1.37-5.02, p = .004), in-hospital mortality (OR 1.99, 95%CI 1.09-3.62, p = .024), and ICU mortality (OR 1.89, 95%CI 1.12-3.20, p = .018).

CONCLUSION

Imaging prior to TTM may help identify post-cardiac arrest patients with severe anoxic brain injury and poor outcomes.

EEG-based outcome prediction after cardiac arrest with convolutional neural networks: Performance and visualization of discriminative features

Prognostication for comatose patients after cardiac arrest is a difficult but essential task. Currently, visual interpretation of electroencephalogram (EEG) is one of the main modality used in outcome prediction. There is a growing interest in computer-assisted EEG interpretation, either to overcome the possible subjectivity of visual interpretation, or to identify complex features of the EEG signal. We used a one-dimensional convolutional neural network (CNN) to predict functional outcome based on 19-channel-EEG recorded from 267 adult comatose patients during targeted temperature management after CA. The area under the receiver operating characteristic curve (AUC) on the test set was 0.885. Interestingly, model architecture and fine-tuning only played a marginal role in classification performance. We then used gradient-weighted class activation mapping (Grad-CAM) as visualization technique to identify which EEG features were used by the network to classify an EEG epoch as favorable or unfavorable outcome, and also to understand failures of the network. Grad-CAM showed that the network relied on similar features than classical visual analysis for predicting unfavorable outcome (suppressed background, epileptiform transients). This study confirms that CNNs are promising models for EEG-based prognostication in comatose patients, and that Grad-CAM can provide explanation for the models' decision-making, which is of utmost importance for future use of deep learning models in a clinical setting.

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

Objective

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

Methods

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

Results

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

Interpretation

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

[Postcardiac arrest treatment guide]

BACKGROUND

Treatment after cardiac arrest has become more complex and interdisciplinary over the last few years. Thus, the clinically active intensive and emergency care physician not only has to carry out the immediate care and acute diagnostics, but also has to prognosticate the neurological outcome.

AIM

The different, most important steps are presented by leading experts in the area, taking into account the interdisciplinarity and the currently valid guidelines.

MATERIALS AND METHODS

Attention was paid to a concise, practice-oriented presentation.

RESULTS AND DISCUSSION

The practical guide contains all important steps from the acute care to the neurological prognosis generation that are relevant for the clinically active intensive care physician.

Spectral Content of Electroencephalographic Burst-Suppression Patterns May Reflect Neuronal Recovery in Comatose Post-Cardiac Arrest Patients

PURPOSE

To assess the potential biologic significance of variations in burst-suppression patterns (BSPs) after cardiac arrest in relation to recovery of consciousness. In the context of recent theoretical models of BSP, bursting frequency may be representative of underlying network dynamics; discontinuous activation of membrane potential during impaired cellular energetics may promote neuronal rescue.

METHODS

We reviewed a database of 73 comatose post-cardiac arrest patients who underwent therapeutic hypothermia to assess for the presence of BSP and clinical outcomes. In a subsample of patients with BSP (n = 14), spectral content of burst and suppression periods were quantified using multitaper method.

RESULTS

Burst-suppression pattern was seen in 45/73 (61%) patients. Comparable numbers of patients with (31.1%) and without (35.7%) BSP regained consciousness by the time of hospital discharge. In addition, in two unique cases, BSP initially resolved and then spontaneously reemerged after completion of therapeutic hypothermia and cessation of sedative medications. Both patients recovered consciousness. Spectral analysis of bursts in all patients regaining consciousness (n = 6) showed a prominent theta frequency (5-7 Hz) feature, but not in age-matched patients with induced BSP who did not recover consciousness (n = 8).

CONCLUSIONS

The prognostic implications of BSP after hypoxic brain injury may vary based on the intrinsic properties of the underlying brain state itself. The presence of theta activity within bursts may index potential viability of neuronal networks underlying recovery of consciousness; emergence of spontaneous BSP in some cases may indicate an innate neuroprotective mechanism. This study highlights the need for better characterization of various BSP patterns after cardiac arrest.

Electroencephalographic reactivity as predictor of neurological outcome in postanoxic coma: A multicenter prospective cohort study

Objective

Outcome prediction in patients after cardiac arrest (CA) is challenging. Electroencephalographic reactivity (EEG‐R) might be a reliable predictor. We aimed to determine the prognostic value of EEG‐R using a standardized assessment.

Methods

In a prospective cohort study, a strictly defined EEG‐R assessment protocol was executed twice per day in adult patients after CA. EEG‐R was classified as present or absent by 3 EEG readers, blinded to patient characteristics. Uncertain reactivity was classified as present. Primary outcome was best Cerebral Performance Category score (CPC) in 6 months after CA, dichotomized as good (CPC = 1–2) or poor (CPC = 3–5). EEG‐R was considered reliable for predicting poor outcome if specificity was ≥95%. For good outcome prediction, a specificity of ≥80% was used. Added value of EEG‐R was the increase in specificity when combined with EEG background, neurological examination, and somatosensory evoked potentials (SSEPs).

Results

Of 160 patients enrolled, 149 were available for analyses. Absence of EEG‐R for poor outcome prediction had a specificity of 82% and a sensitivity of 73%. For good outcome prediction, specificity was 73% and sensitivity 82%. Specificity for poor outcome prediction increased from 98% to 99% when EEG‐R was added to a multimodal model. For good outcome prediction, specificity increased from 70% to 89%.

Interpretation

EEG‐R testing in itself is not sufficiently reliable for outcome prediction in patients after CA. For poor outcome prediction, it has no substantial added value to EEG background, neurological examination, and SSEPs. For prediction of good outcome, EEG‐R seems to have added value. ANN NEUROL 2019

Electroencephalographic monitoring in the critically ill patient: What useful information can it contribute?

Monitoring is a crucial part of the care of the critically ill patient. It detects organ dysfunction and provides guidance on the therapeutic approach. Intensivists closely monitor the function of various organ systems, and the brain is no exception. Continuous EEG monitoring is a noninvasive and uninterrupted way of assessing cerebral cortical activity with good spatial and excellent temporal resolution. The diagnostic effectiveness of non-convulsive status epilepticus as a cause of unexplained consciousness disorder has increased the use of continuous EEG monitoring in the neurocritical care setting. However, non-convulsive status epilepticus is not the only indication for the assessment of cerebral cortical activity. This study summarizes the indications, usage and methodology of continuous EEG monitoring in the intensive care unit, with the aim of allowing practitioners to become familiarized the technique.

Update on Minimal Standards for Electroencephalography in Canada: A Review by the Canadian Society of Clinical Neurophysiologists

Surface electroencephalogram (EEG) recording remains the gold standard for noninvasive assessment of electrical brain activity. It is the most efficient way to diagnose and classify epilepsy syndromes as well as define the localization of the epileptogenic zone. The EEG is useful for management decisions and for establishing prognosis in some types of epilepsy. Electroencephalography is an evolving field in which new methods are being introduced. The Canadian Society of Clinical Neurophysiologists convened an expert panel to develop new national minimal guidelines. A comprehensive evidence review was conducted. This document is organized into 10 sections, including indications, recommendations for trained personnel, EEG yield, paediatric and neonatal EEGs, laboratory minimal standards, requisitions, reports, storage, safety measures, and quality assurance.

Electroencephalography-based power spectra allow coma outcome prediction within 24 h of cardiac arrest

BACKGROUND

Outcome prediction in comatose patients following cardiac arrest remains challenging. Here, we assess the predictive performance of electroencephalography-based power spectra within 24 h from coma onset.

METHODS

We acquired electroencephalography (EEG) from comatose patients (n = 138) on the first day of coma in four hospital sites in Switzerland. Outcome was categorised as favourable or unfavourable based on the best state within three months. Data were split in training and test sets. We evaluated the predictive performance of EEG power spectra for long term outcome and its added value to standard clinical tests.

RESULTS

Out of 138 patients, 80 had a favourable outcome. Power spectra comparison between favourable and unfavourable outcome in the training set yielded significant differences at 5.2-13.2 Hz and above 21 Hz. Outcome prediction based on power at 5.2-13.2 Hz was accurate in training and test sets. Overall, power spectra predicted patients' outcome with maximum specificity and positive predictive value: 1.00 (95% with CI: 0.94-1.00 and 0.89-1.00, respectively). The combination of power spectra and reactivity yielded better accuracy and sensitivity (0.81, 95% CI: 0.71-0.89) than prediction based on power spectra alone.

CONCLUSIONS

On the first day of coma following cardiac arrest, low power spectra values around 10 Hz, typically linked to impaired cortico-thalamic structural connections, are highly specific of unfavourable outcome. Peaks in this frequency range can predict long-term outcome.

Electroencephalogram and somatosensory evoked potential evaluation for good and poor neurological prognosis after cardiac arrest: a prospective multicenter cohort trial (ProNeCA)

Aim: Hypoxic-ischemic-encephalopathy is a severe and frequent neurological complication of successful cardiopulmonary-resuscitation after cardiac arrest. Prognosticating neurological outcomes in patients with hypoxic-ischemic-encephalopathy is challenging and recent guidelines suggest a multimodal approach. Only few studies have analyzed the prognostic power of the association between instrumental tests and, in addition, most of them were monocentric, retrospective and evaluating only poor outcome. Methods/design: We designed a multicenter prospective cohort study to assessing the prognostic power of the association of electroencephalogram and somatosensory evoked potentials for the prediction of both poor and good neurological outcomes at different times after cardiac arrest. Discussion: The results of our study will provide a high level of evidence for the use of neurophysiological evaluation in the current clinical practice.

Update in Neurocritical Care: a summary of the 2018 Paris international conference of the French Society of Intensive Care

The 2018 Paris Intensive Care symposium entitled "Update in Neurocritical Care" was organized in Paris, June 21-22, 2018, under the auspices of the French Intensive Care Society. This 2-day post-graduate educational symposium comprised several chapters, aiming first to provide all-board intensivists with current standards for the clinical assessment of altered consciousness states (including coma and delirium) and peripheral nervous system in critically ill patients, monitoring of brain function (specifically, electro-encephalography) and best practices for sedation-analgesia-delirium management. An update on the treatment of specific severe brain pathologies-including ischaemic/haemorrhagic stroke, cerebral venous thrombosis, hypoxic-ischaemic brain injury, immune-mediated and infectious encephalitis and refractory status epilepticus-was also provided. Finally, we discuss how to approach some difficult decisions, namely the role of decompressive craniectomy and prognostication models in patients with head injury. For each chapter, the scope of the present review was to provide important issues and key messages, provide most recent and relevant literature in the field, and briefly describe new developments in the field.

Death after awakening from post-anoxic coma: the "Best CPC" project

BACKGROUND

In patients who recover consciousness after cardiac arrest (CA), a subsequent death from non-neurological causes may confound the assessment of long-term neurological outcome. We investigated the prevalence and causes of death after awakening (DAA) in a multicenter cohort of CA patients.

METHODS

Observational multicenter cohort study on patients resuscitated from CA in eight European intensive care units (ICUs) from January 2007 to December 2014. DAA during the hospital stay was extracted retrospectively from patient medical records. Demographics, comorbidities, initial CA characteristics, concomitant therapies, prognostic tests (clinical examination, electroencephalography (EEG), somatosensory evoked potentials (SSEPs)), and cause of death were identified.

RESULTS

From a total 4646 CA patients, 2478 (53%) died in-hospital, of whom 196 (4.2%; ranges 0.6-13.0%) had DAA. DAA was less frequent among out-of-hospital than in-hospital CA (82/2997 [2.7%] vs. 114/1649 [6.9%]; p < 0.001). Median times from CA to awakening and from awakening to death were 2 [1-5] and 9 [3-18] days, respectively. The main causes of DAA were multiple organ failure (n = 61), cardiogenic shock (n = 61), and re-arrest (n = 26). At day 3 from admission, results from EEG (n = 56) and SSEPs (n = 60) did not indicate poor outcome.

CONCLUSIONS

In this large multicenter cohort, DAA was observed in 4.2% of non-survivors. Information on DAA is crucial since it may influence epidemiology and the design of future CA studies evaluating neuroprognostication and neuroprotection.

Differential association of subtypes of epileptiform activity with outcome after cardiac arrest

BACKGROUND

Epileptiform activity is common after cardiac arrest, although intensity of electroencephalographic (EEG) monitoring may affect detection rates. Prior work has grouped these patterns together as "malignant," without considering discrete subtypes. We describe the incidence of distinct patterns in the ictal-interictal spectrum at two centers and their association with outcomes.

METHODS

We analyzed a retrospective cohort of comatose post-arrest patients admitted at two academic centers from January 2011 to October 2014. One center uses routine continuous EEG, the other acquires "spot" EEG at the treating physicians' discretion. We reviewed all available EEG data and classified epileptiform patterns. We abstracted antiepileptic drugs (AEDs) administrations from the electronic medical record. We compared apparent incidence of each pattern between centers, and compared outcomes (awakening from coma, survival to discharge, discharge modified Rankin Scale (mRS) 0-2) across EEG patterns and number of AEDs administered.

RESULTS

We included 818 patients. Routine continuous EEG was associated with a higher apparent incidence of polyspike burst-suppression (25% vs 13% P < 0.001). Frequency of other epileptiform findings did not differ. Among patients with any epileptiform pattern, only 2/258 (1%, 95%CI 0-3%) were discharged with mRS 0-2, although 24/258 (9%, 95%CI 6-14%) awakened and 36/258 (14%, 95%CI 10-19%) survived. The proportions that awakened and survived decreased in a stepwise manner with progressively worse EEG patterns (range 38% to 2% and 32% to 7%, respectively). Among patients receiving ≥3 AEDs, only 5/80 (6%, 95%CI 2-14%) awakened and 1/80 (1%, 95%CI 0-7%) had a mRS 0-2.

CONCLUSION

We found high rates of epileptiform EEG findings, regardless of intensity of EEG monitoring. The association of distinct ictal-interictal EEG findings with outcome was variable.

The Prognostic Value of Simplified EEG in Out-of-Hospital Cardiac Arrest Patients

BACKGROUND

We previously validated simplified electroencephalogram (EEG) tracings obtained by a bispectral index (BIS) device against standard EEG. This retrospective study now investigated whether BIS EEG tracings can predict neurological outcome after cardiac arrest (CA).

METHODS

Bilateral BIS monitoring (BIS VISTA™, Aspect Medical Systems, Inc. Norwood, USA) was started following intensive care unit admission. Six, 12, 18, 24, 36 and 48 h after targeted temperature management (TTM) at 33 °C was started, BIS EEG tracings were extracted and reviewed by two neurophysiologists for the presence of slow diffuse rhythm, burst suppression, cerebral inactivity and epileptic activity (defined as continuous, monomorphic, > 2 Hz generalized sharp activity or continuous, monomorphic, < 2 Hz generalized blunt activity). At 180 days post-CA, neurological outcome was determined using cerebral performance category (CPC) classification (CPC1-2: good and CPC3-5: poor neurological outcome).

RESULTS

Sixty-three out-of-hospital cardiac arrest patients were enrolled for data analysis of whom 32 had a good and 31 a poor neurological outcome. Epileptic activity within 6-12 h predicted CPC3-5 with a positive predictive value (PPV) of 100%. Epileptic activity within time frames 18-24 and 36-48 h showed a PPV for CPC3-5 of 90 and 93%, respectively. Cerebral inactivity within 6-12 h predicted CPC3-5 with a PPV of 57%. In contrast, cerebral inactivity between 36 and 48 h predicted CPC3-5 with a PPV of 100%. The pattern with the worst predictive power at any time point was burst suppression with PPV of 44, 57 and 40% at 6-12 h, at 18-24 h and at 36-48 h, respectively. Slow diffuse rhythms at 6-12 h, at 18-24 h and at 36-48 h predicted CPC1-2 with PPV of 74, 76 and 80%, respectively.

CONCLUSION

Based on simplified BIS EEG, the presence of epileptic activity at any time and cerebral inactivity after the end of TTM may assist poor outcome prognostication in successfully resuscitated CA patients. A slow diffuse rhythm at any time after CA was indicative for a good neurological outcome.

Sources of interrater variability and prognostic value of standardized EEG features in post-anoxic coma after resuscitated cardiac arrest

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We identified a new approach to improve the prognostic value of EEG patterns.

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Interrater agreement was evaluated and reported for each different EEG pattern.

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Causes for discrepancy were elucidated to improve interrater concordance.

Objectives

To assess interrater variability and prognostic value of simple EEG features based on the recent American Clinical Neurophysiology Society (ACNS) classification in post cardiac arrest comatose patients.

Methods

All patients admitted for a resuscitated cardiac arrest in a university hospital were prospectively included in the study. EEG interpretation was made by 3 independent neurophysiologists (2 senior and 1 junior) blind to the outcome. Kappa score and prognostic performances were estimated for each EEG pattern and discrepancies were analyzed.

Results

122 cardiac arrest patients were admitted of whom 48 went through a full neurologic evaluation. Eighty-one percent had an unfavorable outcome. Burst suppression, paroxystic seizure activity, and non-reactive EEG were strongly associated with an unfavorable evolution. Kappa score between the senior neurophysiologists was excellent or substantial while it was only fair or slight between the junior and senior neurophysiologists. Reactivity, discontinuity and electrographic seizure were patterns particularly subject to discrepancy.

Conclusions

Bedside EEG is an excellent tool for predicting outcome of post-anoxic coma through simple EEG features. However, the interrater variability emphasizes the need to be well trained for the standardized methods of evaluating EEG parameters.

Significance

A second look at complex patterns seems mandatory. The development of automated tools could help to improve the reliability of EEG interpretation.

Monitorage cérébral après arrêt cardiaque : techniques et utilité clinique potentielle

L’arrêt cardiaque cause une hypoxie-ischémie globale, suivi de reperfusion, qui est susceptible d’engendrer des effets délétères sur la perfusion et l’oxygénation cérébrales, ainsi que le métabolisme cellulaire. Dans ce contexte, et en l’absence de thérapies spcéfiques de l’ischémie-reperfusion globale, le traitement est essentiellement de soutien, visant à optimiser la perfusion et l’oxygénation cérébrale, dans le but de prévenir ou atténuer les dégâts secondaires sur la fonction cérébrale. Dans ce contexte, le monitorage cérébral multimodal, notamment les techniques non-invasives, ont une utilité potentielle à la phase agiuë de l’arrêt cardiaque. Le but prinicpal de cette revue est de décrire les techniques actuellement dipsonibles, en nous focalisant surtout sur les outils noninvasifs (doppler transcranien, spectrospcope de proche infrarouge, électroencéphalographie, pupillométrie automatisée proche infrarouge), leur utilité clinique potentielle ainsi que leurs limitations, dans la prise en charge aiguë (optimisation de la perfusion et de l’oxygénation cérébrales) ainsi que pour la détermination du pronostic précoce après arrêt cardiaque.

Short "Infraslow" Activity (SISA) With Burst Suppression in Acute Anoxic Encephalopathy: A Rare, Specific Ominous Sign With Acute Posthypoxic Myoclonus or Acute Symptomatic Seizures

OBJECTIVE

Slow wave with frequency <0.5 Hz are recorded in various situations such as normal sleep, epileptic seizures. However, its clinical significance has not been fully clarified. Although infra-slow activity was recently defined as activity between 0.01 and 0.1 Hz, we focus on the activity recorded with time constant of 2 seconds for practical usage. We defined short "infraslow" activity (SISA) less than 0.5 Hz recorded with time constant of 2 seconds and investigated the occurrence and clinical significance of SISA in acute anoxic encephalopathy.

METHODS

This study evaluated the findings of electroencephalography in consecutive 98 comatose patients with acute anoxic encephalopathy after cardiac arrest. We first classified electroencephalography findings conventionally, then investigated SISA by time constant of 2 second and a high-cut filter of 120 Hz, to clarify the relationship between SISA and clinical profiles, especially of clinical outcomes and occurrence of acute posthypoxic myoclonus or acute symptomatic seizures.

RESULTS

Short infra-slow activity was found in six patients (6.2%), superimposed on the burst phase of the burst-suppression pattern. All six patients showed acute posthypoxic myoclonus or acute symptomatic seizures (generalized tonic-clonic seizures) and its prognosis was poor. This 100% occurrence of acute posthypoxic myoclonus or acute symptomatic seizures was significantly higher than that in patients without SISA (39.1%; P < 0.05).

CONCLUSIONS

Short infra-slow activity in acute anoxic encephalopathy could be associated with acute posthypoxic myoclonus and acute symptomatic seizures. Short infra-slow activity could be a practically feasible biomarker for myoclonus or seizures and poor prognosis in acute anoxic encephalopathy, if it occurs with burst suppression.

EEG Reactivity Evaluation Practices for Adult and Pediatric Hypoxic-Ischemic Coma Prognostication in North America

PURPOSE

The aim of this study was to assess the variability in EEG reactivity evaluation practices during cardiac arrest prognostication.

METHODS

A survey of institutional representatives from North American academic hospitals participating in the Critical Care EEG Monitoring Research Consortium was conducted to assess practice patterns involving EEG reactivity evaluation. This 10-question multiple-choice survey evaluated metrics related to technical, interpretation, personnel, and procedural aspects of bedside EEG reactivity testing and interpretation specific to cardiac arrest prognostication. One response per hospital was obtained.

RESULTS

Responses were received from 25 hospitals, including 7 pediatric hospitals. A standardized EEG reactivity protocol was available in 44% of centers. Sixty percent of respondents believed that reactivity interpretation was subjective. Reactivity bedside testing always (100%) started during hypothermia and was performed daily during monitoring in the majority (71%) of hospitals. Stimulation was performed primarily by neurodiagnostic technologists (76%). The mean number of activation procedures modalities tested was 4.5 (SD 2.1). The most commonly used activation procedures were auditory (83.3%), nail bed pressure (63%), and light tactile stimuli (63%). Changes in EEG amplitude alone were not considered consistent with EEG reactivity in 21% of centers.

CONCLUSIONS

There is substantial variability in EEG reactivity evaluation practices during cardiac arrest prognostication among North American academic hospitals. Efforts are needed to standardize protocols and nomenclature according with national guidelines and promote best practices in EEG reactivity evaluation.

Neurologic outcome of postanoxic refractory status epilepticus after aggressive treatment

OBJECTIVE

To investigate neurologic outcome of patients with cardiac arrest with refractory status epilepticus (RSE) treated with a standardized aggressive protocol with antiepileptic drugs and anesthetics compared to patients with other EEG patterns.

METHODS

In the prospective cohort study, 166 consecutive patients with cardiac arrest in coma were stratified according to 4 independent EEG patterns (benign, RSE, generalized periodic discharges [GPDs], malignant nonepileptiform) and multimodal prognostic indicators. Primary outcomes were survival and cerebral performance category (CPC) at 6 months.

RESULTS

RSE occurred in 36 patients (21.7%) and was treated with an aggressive standardized protocol as long as multimodal prognostic indicators were not unfavorable. RSE started after 3 ± 2.3 days after cardiac arrest and lasted 4.7 ± 4.3 days. A benign EEG pattern was recorded in 76 patients (45.8%); a periodic pattern (GPDs) was seen in 13 patients (7.8%); and a malignant nonepileptiform EEG pattern was recorded in 41 patients (24.7%). The 4 EEG patterns were highly associated with different prognostic indicators (low-flow time, clinical motor seizures, N20 responses, neuron-specific enolase, neuroimaging). Survival and good neurologic outcome (CPC 1 or 2) at 6 months were 72.4% and 71.1% for benign EEG pattern, 54.3% and 44.4% for RSE, 15.4% and 0% for GPDs, and 2.4% and 0% for malignant nonepileptiform EEG pattern, respectively.

CONCLUSIONS

Aggressive and prolonged treatment of RSE may be justified in patients with cardiac arrest with favorable multimodal prognostic indicators.

Categorization of post-cardiac arrest patients according to the pattern of amplitude-integrated electroencephalography after return of spontaneous circulation

Background

Continuous electroencephalography (cEEG), interpreted by an experienced neurologist, has been reported to be useful in predicting neurological outcome in adult patients post cardiac arrest. Amplitude-integrated electroencephalography (aEEG) is a type of quantitative EEG and is easily interpreted by a non-neurologist. A few studies have shown the effectiveness of aEEG in prognostication among adult patients post cardiac arrest. In this study, we hypothesized that the pattern of aEEG after return of spontaneous circulation (ROSC) could successfully categorize patients post cardiac arrest according to their expected neurological outcome.

Methods

We assessed the comatose survivors of out-of-hospital cardiac arrest who received targeted temperature management with midazolam-based sedation and were monitored with aEEG at our tertiary emergency care center from January 2013 to June 2017. We categorized the patients into categories 1 (C1) to 4 (C4). C1 included patients who regained continuous normal voltage (CNV) within 12 h post ROSC, C2 included those who recovered CNV 12–36 h post ROSC, C3 included those who did not recover CNV before 36 h post ROSC, and C4 included those who had burst suppression at any time post ROSC. We evaluated the outcomes of neurological function for each category at hospital discharge. A good outcome was defined as a cerebral performance category of 1 or 2.

Results

A total of 61 patients were assessed (median age, 60 years), among whom 42 (70%) had an initial shockable rhythm, and 52 (85%) had cardiac etiology. Of all 61 patients, 40 (66%) survived to hospital discharge and 27 (44%) had a good neurological outcome. Of 20 patients in C1, 19 (95%) had a good outcome, while the percentage dropped to 57% among C2 patients. No patients in C3 or C4 had a good outcome. Three patients could not be classified into any category.

Conclusions

The pattern of aEEG during the early post-cardiac-arrest period can successfully categorize patients according to their neurological prognoses and could be used as a potential guide to customize post-cardiac-arrest care for each patient.

Electronic supplementary material

The online version of this article (10.1186/s13054-018-2138-2) contains supplementary material, which is available to authorized users.

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

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

Does continuous EEG influence prognosis in patients after cardiac arrest?

AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Anoxic-Ischemic Brain Injury

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

Unresponsive wakefulness or coma after cardiac arrest-A long-term follow-up study

OBJECTIVE

To investigate the clinical course and early prognostic markers in cardiac arrest (CA) patients discharged from the intensive care unit (ICU) in an unresponsive wakefulness syndrome (UWS) or coma.

METHODS

89 patients were identified from a prospective CA database. Follow-up was conducted by telephone interviews with legal guardians, evaluation of re-admission and rehabilitation reports assessing core elements of the coma recovery scale-revised (CRS-R). Somatosensory evoked potential (SSEP) and electroencephalography (EEG) original recordings were re-analyzed, the gray-white-matter ratio (GWR) was determined from brain computed tomography (CT) and neuron-specific enolase (NSE) serum concentrations were retrieved.

RESULTS

Follow-up was successful for 32/50 (64%) patients admitted between 2001-2009 and 31/39 (79%) between 2009-2015. Median ICU stay was 27 days (IQR 20-36). Neurological improvement beyond UWS was found in 2 of 63 patients. Among 61 patients with successful follow-up and no improvement, NSE serum concentrations within the reference range, SSEP amplitudes above 2.5 μV or continuous reactive EEG were found in 5%, 3% and 2% of those tested. NSE > 90 μg/L, SSEP ≤ 0.3 μV, highly malignant EEG or GWR < 1.10 were found in 44%, 49%, 35% and 22% of those tested.

CONCLUSIONS

Neurological recovery was rare in CA patients discharged in UWS after prolonged ICU treatment. Status epilepticus requiring prolonged deep sedation is one potential reason for delayed awakening. Sensitivity for established poor outcome parameters to predict persistent UWS early after CA was moderate. SSEP, EEG and NSE may indicate absence of severe HIE early after CA.

Prognostication after cardiac arrest

Hypoxic-ischaemic brain injury (HIBI) is the main cause of death in patients who are comatose after resuscitation from cardiac arrest. A poor neurological outcome-defined as death from neurological cause, persistent vegetative state, or severe neurological disability-can be predicted in these patients by assessing the severity of HIBI. The most commonly used indicators of severe HIBI include bilateral absence of corneal and pupillary reflexes, bilateral absence of N₂O waves of short-latency somatosensory evoked potentials, high blood concentrations of neuron specific enolase, unfavourable patterns on electroencephalogram, and signs of diffuse HIBI on computed tomography or magnetic resonance imaging of the brain. Current guidelines recommend performing prognostication no earlier than 72 h after return of spontaneous circulation in all comatose patients with an absent or extensor motor response to pain, after having excluded confounders such as residual sedation that may interfere with clinical examination. A multimodal approach combining multiple prognostication tests is recommended so that the risk of a falsely pessimistic prediction is minimised.