Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

Prognostic value of 'late' electroencephalography recordings in patients with cardiopulmonal resuscitation after cardiac arrest

Background

Electroencephalography (EEG) significantly contributes to the neuroprognostication after resuscitation from cardiac arrest. Recent studies suggest that the prognostic value of EEG is highest for continuous recording within the first days after cardiac arrest. Early continuous EEG, however, is not available in all hospitals. In this observational study, we sought to evaluate the predictive value of a ‘late’ EEG recording 5–14 days after cardiac arrest without sedatives.

Methods

We retrospectively analyzed EEG data in consecutive adult patients treated at the medical intensive care units (ICU) of the Charité—Universitätsmedizin Berlin. Outcome was assessed as cerebral performance category (CPC) at discharge from ICU, with an unfavorable outcome being defined as CPC 4 and 5.

Results

In 187 patients, a ‘late’ EEG recording was performed. Of these patients, 127 were without continuous administration of sedative agents for at least 24 h before the EEG recording. In this patient group, a continuously suppressed background activity < 10 µV predicted an unfavorable outcome with a sensitivity of 31% (95% confidence interval (CI) 20–45) and a specificity of 99% (95% CI 91–100). In patients with suppressed background activity and generalized periodic discharges, sensitivity was 15% (95% CI 7–27) and specificity was 100% (95% CI 94–100). GPDs on unsuppressed background activity were associated with a sensitivity of 42% (95% CI 29–46) and a specificity of 92% (95% CI 82–97).

Conclusions

A ‘late’ EEG performed 5 to 14 days after resuscitation from cardiac arrest can aide in prognosticating functional outcome. A suppressed EEG background activity in this time period indicates poor outcome.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10549-y.

Brain Injury in Extracorporeal Membrane Oxygenation: A Multidisciplinary Approach

Extracorporeal membrane oxygenation (ECMO) represents an established technique to provide temporary cardiac and/or pulmonary support. ECMO, in veno-venous, veno-arterial or in extracorporeal carbon dioxide removal modality, is associated with a high rate of brain injuries. These complications have been reported in 7 to 15% of adults and 20% of neonates, and are associated with poor survival. Thromboembolic events, loss of cerebral autoregulation, alteration of the blood-brain barrier, and hemorrhage related to anticoagulation represent the main causes of severe brain injury during ECMO. The most frequent forms of acute neurological injuries in ECMO patients are intracranial hemorrhage (2-21%), ischemic stroke (2-10%), seizures (2-6%), and hypoxic-ischemic brain injury; brain death may also occur in this population. Other frequent complications are infarction (1-8%) and cerebral edema (2-10%), as well as neuropsychological and psychiatric sequelae, including posttraumatic stress disorder.

SSEP amplitude accurately predicts both good and poor neurological outcome early after cardiac arrest; a post-hoc analysis of the ProNeCA multicentre study

AIM

To assess if, in comatose resuscitated patients, the amplitude of the N20 wave (N20amp) of somatosensory evoked potentials (SSEP) can predict 6-months neurological outcome.

SETTING

Multicentre study in 13 Italian intensive care units.

METHODS

The N20amp in microvolts (μV) was measured at 12 h, 24 h, and 72 h from cardiac arrest, along with pupillary reflex (PLR) and a 30-min EEG classified according to the ACNS terminology. Sensitivity and false positive rate (FPR) of N20amp alone or in combination were calculated.

RESULTS

403 patients (age 69[58-68] years) were included. At 12 h, an N20amp >3 μV predicted good neurological outcome (Cerebral Performance Categories [CPC] 1-2) with 61[50-72]% sensitivity and 11[6-18]% FPR. Combining it with a benign (continuous or nearly continuous) EEG increased sensitivity to 91[82-96]%. For poor outcome (CPC 3-5), an N20Amp ≤0.38 μV, ≤0.73 μV and ≤1.01 μV at 12 h, 24 h, and 72 h, respectively, had 0% FPR with sensitivity ranging from 61[51-69]% and 82[76-88]%. Sensitivity was higher than that of a bilaterally absent N20 at all time points. At 12 h and 24 h, a highly malignant (suppression or burst-suppression) EEG and bilaterally absent PLR achieved 0% FPR only when combined with SSEP. A combination of all three predictors yielded a 0[0-4]% FPR, with maximum sensitivity of 44[36-53]%.

CONCLUSION

At 12 h from arrest, a high N20Amp predicts good outcome with high sensitivity, especially when combined with benign EEG. At 12 h and 24 h from arrest a low-voltage N20amp has a high sensitivity and is more specific than EEG or PLR for predicting poor outcome.

The first national survey on practices of neurological prognostication after cardiac arrest in China, still a lot to do

AIMS

To investigate current awareness and practices of neurological prognostication in comatose cardiac arrest (CA) patients.

METHODS

An anonymous questionnaire was distributed to 1600 emergency physicians in 75 hospitals which were selected randomly from China between January and July 2018.

RESULTS

92.1% respondents fulfilled the survey. The predictive value of brain stem reflex, motor response and myoclonus was confirmed by 63.5%, 44.6% and 31.7% respondents, respectively. Only 30.7% knew that GWR value < 1.1 indicated poor prognosis and only 8.1% know the most commonly used SSEP N20. Status epilepticus, burst suppression and suppression were considered to predict poor outcome by only 35.0%, 27.4% and 20.9% respondents, respectively. Only 46.7% knew NSE and only 24.7% knew S-100. Only a few respondents knew that neurological prognostication should be performed later than 72 hours from CA either in TTM or non-TTM patients. In practice, the most commonly used method was clinical examination (85.4%). Only 67.9% had used brain CT for prognosis and 18.4% for MRI. NSE (39.6%) was a little more widely used than S-100β (18.0%). However, SSEP (4.4%) and EEG (11.4%) were occasionally performed.

CONCLUSIONS

Neurological prognostication in CA survivors had not been well understood and performed by emergency physicians in China. They were more likely to use clinical examination rather than objective tools, especially SSEP and EEG, which also illustrated that multimodal approach was not well performed in practice.

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

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

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

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

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

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

Early Thalamic Injury After Resuscitation From Severe Asphyxial Cardiac Arrest in Developing Rats

Children who survive cardiac arrest often develop debilitating sensorimotor and cognitive deficits. In animal models of cardiac arrest, delayed neuronal death in the hippocampal CA1 region has served as a fruitful paradigm for investigating mechanisms of injury and neuroprotection. Cardiac arrest in humans, however, is more prolonged than in most experimental models. Consequently, neurologic deficits in cardiac arrest survivors arise from injury not solely to CA1 but to multiple vulnerable brain structures. Here, we develop a rat model of prolonged pediatric asphyxial cardiac arrest and resuscitation, which better approximates arrest characteristics and injury severity in children. Using this model, we characterize features of microglial activation and neuronal degeneration in the thalamus 24 h after resuscitation from 11 and 12 min long cardiac arrest. In addition, we test the effect of mild hypothermia to 34°C for 8 h after 12.5 min of arrest. Microglial activation and neuronal degeneration are most prominent in the thalamic Reticular Nucleus (nRT). The severity of injury increases with increasing arrest duration, leading to frank loss of nRT neurons at longer arrest times. Hypothermia does not prevent nRT injury. Interestingly, injury occurs selectively in intermediate and posterior nRT segments while sparing the anterior segment. Since all nRT segments consist exclusively of GABA-ergic neurons, we asked if GABA-ergic neurons in general are more susceptible to hypoxic-ischemic injury. Surprisingly, cortical GABA-ergic neurons, like their counterparts in the anterior nRT segment, do not degenerate in this model. Hence, we propose that GABA-ergic identity alone is not sufficient to explain selective vulnerability of intermediate and posterior nRT neurons to hypoxic-ischemic injury after cardiac arrest and resuscitation. Our current findings align the animal model of pediatric cardiac arrest with human data and suggest novel mechanisms of selective vulnerability to hypoxic-ischemic injury among thalamic GABA-ergic neurons.

Assessing neurological prognosis in post-cardiac arrest patients from short vs plain text EEG reports: A survey among intensive care clinicians

BACKGROUND

Electroencephalography (EEG) patterns are predictive of neurological prognosis in comatose survivors from cardiac arrest but intensive care clinicians are dependent of neurophysiologist reports to identify specific patterns. We hypothesized that the proportion of correct assessment of neurological prognosis would be higher from short statements confirming specific EEG patterns compared with descriptive plain text reports.

METHODS

Volunteering intensive care clinicians at two university hospitals were asked to assess the neurological prognosis of a fictional patient with high neuron specific enolase. They were presented with 17 authentic plain text reports and three short statements, confirming whether a "highly malignant", "malignant" or "benign" EEG pattern was present. Primary outcome was the proportion of clinicians who correctly identified poor neurological prognosis from reports consistent with highly malignant EEG patterns. Secondary outcomes were how the prognosis was assessed from reports consistent with malignant and benign patterns.

RESULTS

Out of 57 participants, poor prognosis was correctly identified by 61% from plain text reports and by 93% from the short statement "highly malignant" EEG patterns. Unaffected prognosis was correctly identified by 28% from plain text reports and by 40% from the short statement "malignant" patterns. Good prognosis was correctly identified by 64% from plain text reports and by 93% from the short statement "benign" pattern.

CONCLUSION

Standardized short statement, "highly malignant EEG pattern present", as compared to plain text EEG descriptions in neurophysiologist reports, is associated with more accurate identification of poor neurological prognosis in comatose survivors of cardiac arrest.

Standardized visual EEG features predict outcome in patients with acute consciousness impairment of various etiologies

BACKGROUND

Early prognostication in patients with acute consciousness impairment is a challenging but essential task. Current prognostic guidelines vary with the underlying etiology. In particular, electroencephalography (EEG) is the most important paraclinical examination tool in patients with hypoxic ischemic encephalopathy (HIE), whereas it is not routinely used for outcome prediction in patients with traumatic brain injury (TBI).

METHOD

Data from 364 critically ill patients with acute consciousness impairment (GCS ≤ 11 or FOUR ≤ 12) of various etiologies and without recent signs of seizures from a prospective randomized trial were retrospectively analyzed. Random forest classifiers were trained using 8 visual EEG features-first alone, then in combination with clinical features-to predict survival at 6 months or favorable functional outcome (defined as cerebral performance category 1-2).

RESULTS

The area under the ROC curve was 0.812 for predicting survival and 0.790 for predicting favorable outcome using EEG features. Adding clinical features did not improve the overall performance of the classifier (for survival: AUC = 0.806, p = 0.926; for favorable outcome: AUC = 0.777, p = 0.844). Survival could be predicted in all etiology groups: the AUC was 0.958 for patients with HIE, 0.955 for patients with TBI and other neurosurgical diagnoses, 0.697 for patients with metabolic, inflammatory or infectious causes for consciousness impairment and 0.695 for patients with stroke. Training the classifier separately on subgroups of patients with a given etiology (and thus using less training data) leads to poorer classification performance.

CONCLUSIONS

While prognostication was best for patients with HIE and TBI, our study demonstrates that similar EEG criteria can be used in patients with various causes of consciousness impairment, and that the size of the training set is more important than homogeneity of ACI etiology.

Electroencephalographic Grading of Neuronal Dysfunction in Various Etiologies of Encephalopathy

OBJECTIVE

The objective of this work was to study the electroencephalographic (EEG) grading of neuronal dysfunction in encephalopathy of various etiologies and assess their association with clinical outcomes.

SUBJECTS AND METHODS

This retrospective cross-sectional study was performed between June and November 2018 at the Neurology Department of King Fahd Hospital of University, Kingdom of Saudi Arabia (KSA) and involved a review and analysis of EEG and medical records pertaining to 222 patients in whom encephalopathy was diagnosed.

RESULTS

In patients suffering from encephalopathy, advanced age (P = .01), low Glasgow Coma Scale (GCS) scores (P = .00), and certain etiologies, namely hypoxic-ischemic encephalopathy (HIE) (P = .00), septic encephalopathy (P = .01), and other illnesses (P = .00), were significantly associated with unfavorable clinical outcomes, whereas traumatic brain injury (TBI) (P = .01) and GCS >7 (P = .00) were associated with favorable outcomes. Among different etiologies, EEG grade I (P = .02) and grade IV (P = .04) neuronal dysfunction was significantly associated with TBI while grade III (P = .05) and grade V (P = .02) neuronal dysfunction was significantly associated with HIE. Grade I (P = .03) neuronal dysfunction was mostly observed in septic encephalopathy cases, while patients suffering from other illnesses were also found to have grade I (P = .04) and grade IV (P = .05) neuronal dysfunction based on their EEG.

CONCLUSION

EEG is being conducted routinely to determine the course and severity of various forms of encephalopathy. However, the clinical implications of EEG grading for neuronal dysfunction are largely dependent on underlying etiology and other clinical parameters, such as age and GCS score. Further larger prospective cohort studies involving other important prognostic parameters and continuous EEG monitoring are thus needed.

Adult Advanced Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science with Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations for advanced life support includes updates on multiple advanced life support topics addressed with 3 different types of reviews. Topics were prioritized on the basis of both recent interest within the resuscitation community and the amount of new evidence available since any previous review. Systematic reviews addressed higher-priority topics, and included double-sequential defibrillation, intravenous versus intraosseous route for drug administration during cardiac arrest, point-of-care echocardiography for intra-arrest prognostication, cardiac arrest caused by pulmonary embolism, postresuscitation oxygenation and ventilation, prophylactic antibiotics after resuscitation, postresuscitation seizure prophylaxis and treatment, and neuroprognostication. New or updated treatment recommendations on these topics are presented. Scoping reviews were conducted for anticipatory charging and monitoring of physiological parameters during cardiopulmonary resuscitation. Topics for which systematic reviews and new Consensuses on Science With Treatment Recommendations were completed since 2015 are also summarized here. All remaining topics reviewed were addressed with evidence updates to identify any new evidence and to help determine which topics should be the highest priority for systematic reviews in the next 1 to 2 years.

Adult Advanced Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations for advanced life support includes updates on multiple advanced life support topics addressed with 3 different types of reviews. Topics were prioritized on the basis of both recent interest within the resuscitation community and the amount of new evidence available since any previous review. Systematic reviews addressed higher-priority topics, and included double-sequential defibrillation, intravenous versus intraosseous route for drug administration during cardiac arrest, point-of-care echocardiography for intra-arrest prognostication, cardiac arrest caused by pulmonary embolism, postresuscitation oxygenation and ventilation, prophylactic antibiotics after resuscitation, postresuscitation seizure prophylaxis and treatment, and neuroprognostication. New or updated treatment recommendations on these topics are presented. Scoping reviews were conducted for anticipatory charging and monitoring of physiological parameters during cardiopulmonary resuscitation. Topics for which systematic reviews and new Consensuses on Science With Treatment Recommendations were completed since 2015 are also summarized here. All remaining topics reviewed were addressed with evidence updates to identify any new evidence and to help determine which topics should be the highest priority for systematic reviews in the next 1 to 2 years.

Neurologic prognostication after resuscitation from cardiac arrest

Out-of-hospital cardiac arrest remains a leading cause of mortality in the United States, and the majority of patients who die after achieving return of spontaneous circulation die from withdrawal of care due to a perceived poor neurologic prognosis. Unfortunately, withdrawal of care often occurs during the first day of admission and research suggests this early withdrawal of care may be premature and result in unnecessary deaths for patients who would have made a full neurologic recovery. In this review, we explore the evidence for neurologic prognostication in the emergency department for patients who achieve return of spontaneous circulation after an out-of-hospital cardiac arrest.

Brain injury after cardiac arrest: from prognostication of comatose patients to rehabilitation

More patients are surviving cardiac arrest than ever before; however, the burden now lies with estimating neurological prognoses in a large number of patients who were initially comatose, in whom the ultimate outcome is unclear. Neurologists, neurointensivists, and clinical neurophysiologists must accurately balance the concern that overly conservative prognostication could leave patients in a severely disabled state, with the possibility that inaccurately pessimistic prognostication could lead to the withdrawal of life-sustaining treatment in patients who might otherwise have a good functional outcome. Prognostic tools have improved greatly, including electrophysiological tests, neuroimaging, and chemical biomarkers. Conclusions about the prognosis should be delayed at least 72 h after arrest to allow for the clearance of sedative drugs. Cognitive impairments, emotional problems, and fatigue are common among patients who have survived cardiac arrest, and often go unrecognised despite being related to caregiver burden and a decreased participation in society. Through simple screening, these problems can be identified, and patients can be provided with adequate information and rehabilitation.

Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review

Purpose

To assess the ability of clinical examination, blood biomarkers, electrophysiology, or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict poor neurological outcome, defined as death, vegetative state, or severe disability (CPC 3–5) at hospital discharge/1 month or later, in comatose adult survivors from cardiac arrest (CA).

Methods

PubMed, EMBASE, Web of Science, and the Cochrane Database of Systematic Reviews (January 2013–April 2020) were searched. Sensitivity and false-positive rate (FPR) for each predictor were calculated. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed.

Results

Ninety-four studies (30,200 patients) were included. Bilaterally absent pupillary or corneal reflexes after day 4 from ROSC, high blood values of neuron-specific enolase from 24 h after ROSC, absent N20 waves of short-latency somatosensory-evoked potentials (SSEPs) or unequivocal seizures on electroencephalogram (EEG) from the day of ROSC, EEG background suppression or burst-suppression from 24 h after ROSC, diffuse cerebral oedema on brain CT from 2 h after ROSC, or reduced diffusion on brain MRI at 2–5 days after ROSC had 0% FPR for poor outcome in most studies. Risk of bias assessed using the QUIPS tool was high for all predictors.

Conclusion

In comatose resuscitated patients, clinical, biochemical, neurophysiological, and radiological tests have a potential to predict poor neurological outcome with no false-positive predictions within the first week after CA. Guidelines should consider the methodological concerns and limited sensitivity for individual modalities. (PROSPERO CRD42019141169)

Electronic supplementary material

The online version of this article (10.1007/s00134-020-06198-w) contains supplementary material, which is available to authorized users.

Proteomics-Enriched Prediction Model for Poor Neurologic Outcome in Cardiac Arrest Survivors

OBJECTIVES

Neurologic outcome prediction in out-of-hospital cardiac arrest survivors is highly limited due to the lack of consistent predictors of clinically relevant brain damage. The present study aimed to identify novel biomarkers of neurologic recovery to improve early prediction of neurologic outcome.

DESIGN

Prospective, single-center study, SETTING:: University-affiliated tertiary care center.

PATIENTS

We prospectively enrolled 96 out-of-hospital cardiac arrest survivors into our study.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Neurologic outcome was assessed by the Cerebral Performance Categories score. To identify plasma biomarkers for poor neurologic outcome (Cerebral Performance Categories score ≥ 3), we performed a three-step proteomics strategy of preselection by shotgun analyses, crosschecking in brain tissue samples, and verification by targeted proteomic analyses using a multistep statistical modeling approach. Sixty-three patients (66%) had a poor neurologic outcome. Out of a total of 299 proteins, we identified α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein as novel biomarkers for poor neurologic outcome. The implementation of these biomarkers into a clinical multimarker model, consisting of previously identified covariates associated to outcome, resulted in a significant improvement of neurologic outcome prediction (C-index, 0.70; explained variation, 11.9%; p for added value, 0.019).

CONCLUSIONS

This study identified four novel biomarkers for the prediction of poor neurologic outcome in out-of-hospital cardiac arrest survivors. The implementation of α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein into a multimarker predictive model along with previously identified risk factors significantly improved neurologic outcome prediction. Each of the proteomically identified biomarkers did not only outperform current risk stratification models but may also reflect important pathophysiologic pathways undergoing during cerebral ischemia.

Brain networks involved in generalized periodic discharges (GPD) in post-anoxic-ischemic encephalopathy

AIM

Generalized periodic discharge (GPD) is an EEG pattern of poor neurological outcome, frequently observed in comatose patients after cardiac arrest. The aim of our study was to identify the neuronal network generating ≤2.5 Hz GPD using EEG source localization and connectivity analysis.

METHODS

We analyzed 40 comatose adult patients with anoxic-ischemic encephalopathy, who had 19 channel-EEG recording. We computed electric source analysis based on distributed inverse solution (LAURA) and we estimated cortical activity in 82 atlas-based cortical brain regions. We applied directed connectivity analysis (Partial Directed Coherence) on these sources to estimate the main drivers.

RESULTS

Source analysis suggested that the GPD are generated in the cortex of the limbic system in the majority of patients (87.5%). Connectivity analysis revealed main drivers located in thalamus and hippocampus for the large majority of patients (80%), together with important activation also in amygdala (70%).

CONCLUSIONS

We hypothesize that the anoxic-ischemic dysfunction, leading to hyperactivity of the thalamo-cortical (limbic presumably) circuit, can result in an oscillatory thalamic activity capable of inducing periodic cortical (limbic, mostly medial-temporal and orbitofrontal) discharges, similarly to the case of generalized rhythmic spike-wave discharge in convulsive or non-convulsive status epilepticus.

Cost-effectiveness analysis of multimodal prognostication in cardiac arrest with EEG monitoring

OBJECTIVE

To determine cost-effectiveness parameters for EEG monitoring in cardiac arrest prognostication.

METHODS

We conducted a cost-effectiveness analysis to estimate the cost per quality-adjusted life-year (QALY) gained by adding continuous EEG monitoring to standard cardiac arrest prognostication using the American Academy of Neurology Practice Parameter (AANPP) decision algorithm: neurologic examination, somatosensory evoked potentials, and neuron-specific enolase. We explored lifetime cost-effectiveness in a closed system that incorporates revenue back into the medical system (return) from payers who survive a cardiac arrest with good outcome and contribute to the health system during the remaining years of life. Good outcome was defined as a Cerebral Performance Category (CPC) score of 1-2 and poor outcome as CPC of 3-5.

RESULTS

An improvement in specificity for poor outcome prediction of 4.2% would be sufficient to make continuous EEG monitoring cost-effective (baseline AANPP specificity = 83.9%). In sensitivity analysis, the effect of increased sensitivity on the cost-effectiveness of EEG depends on the utility (u) assigned to a poor outcome. For patients who regard surviving with a poor outcome (CPC 3-4) worse than death (u = -0.34), an increased sensitivity for poor outcome prediction of 13.8% would make AANPP + EEG monitoring cost-effective (baseline AANPP sensitivity = 76.3%). In the closed system, an improvement in sensitivity of 1.8% together with an improvement in specificity of 3% was sufficient to make AANPP + EEG monitoring cost-effective, assuming lifetime return of 50% (USD $70,687).

CONCLUSION

Incorporating continuous EEG monitoring into cardiac arrest prognostication is cost-effective if relatively small improvements in sensitivity and specificity are achieved.

EEG patterns associated with present cortical SSEP after cardiac arrest

BACKGROUND

After cardiac arrest (CA), present cortical somatosensory evoked potentials (N20 response of SSEPs) have low predictive value for good outcome and might be redundant with EEG.

AIMS

To determine whether specific features, or rather global, standardized EEG assessments, are reliably associated with cortical SSEP occurrence after cardiac arrest (CA).

METHODS

In a prospective CA registry, EEGs recorded within 72 hours were scored according to the ACNS nomenclature, and also categorized into "benign," "malignant," and "highly malignant." Correlations between EEGs and SSEPs (bilaterally absent vs present), and between EEGs/SSEPs and outcome (good: CPC 1-2) were assessed.

RESULTS

Among 709 CA episodes, 532 had present N20 and 366 "benign EEGs." While EEG categories as well as background, epileptiform features, and reactivity differed significantly between patients with and without N20 (each P < .001), only "benign EEG" was almost universally associated with present N20: 99.5% (95%CI: 97.9%-99.9%) PPV. The combination of "benign EEG" and present N20 showed similar PPV for good outcome as "benign" EEG alone: 69.0% (95% CI: 65.2-72.4) vs 68.6% (95% CI: 64.9-72.0).

CONCLUSION

Global EEG ("benign") assessment, rather than single EEG features, can reliably predict cortical SSEP occurrence. SSEP adjunction does not increase EEG prognostic performance toward good outcome. SSEP could therefore be omitted in patients with "benign EEG."

Prognostic significance of specific EEG patterns after cardiac arrest in a Lisbon Cohort

Objective

To evaluate if EEG patterns considered highly malignant are reliable predictors not only of poor neurological outcome but also reliable predictors of death.

Methods

Retrospectively, EEGs from Cardiac Arrest (CA) patients of two teaching hospitals in Lisbon were classified into 3 groups: highly malignant, malignant, and benign groups. Outcome was assessed at 6 months after CA by CPC (Cerebral Performance Categories) scale. We evaluated the accuracy of these patterns to predict poor neurological outcome and death.

Results

We included 106 patients for analysis. All patients with a highly malignant EEG (n = 37) presented a poor neurological outcome. Those patterns were also associated with death. Malignant EEG patterns were not associated with poor neurological outcome. Benign EEG patterns were associated with good neurological recovery (p < 0.0001).

Conclusion

Highly malignant EEG patterns were strongly associated with poor neurological outcome and can be considered to be predictors of death.

Significance

This study increased the knowledge about the value of EEG as a tool in outcome prediction of patients after cardiac arrest.

Postarrest Interventions that Save Lives

Patients resuscitated from cardiac arrest require complex management. An organized approach to early postarrest care can improve patient outcomes. Priorities include completing a focused diagnostic work-up to identify and reverse the inciting cause of arrest, stabilizing cardiorespiratory instability to prevent rearrest, minimizing secondary brain injury, evaluating the risk and benefits of transfer to a specialty care center, and avoiding early neurologic prognostication.

Prediction of the level of consciousness using pupillometer measurements in patients with impaired consciousness brought to the emergency and critical care center

Aim

We investigated whether the level of consciousness can be predicted using pupillometer measurements in patients with severe disturbance of consciousness.

Methods

Patients with a Glasgow Coma Scale (GCS) of 3–8, except for those after cardiac arrest, were included. Pupillary contraction rate and contraction velocity were each measured using a pupillometer.

Results

Thirty‐five patients were analyzed. At the time of discharge or changing hospitals, 16 patients had a GCS score of 3–13 and 19 patients had a GCS score of 14–15. In the non‐sedative group at about the time of arrival at our hospital, average pupillary contraction rates were 18.36% in the GCS 3–13 group and 19.67% in the GCS 14–15 group (P = 0.739), and average pupillary contraction velocities were 1.02 and 1.48, respectively (P = 0.182). Approximately 48 h after arrival, average pupillary contraction rates were 21.18% and 29.27%, respectively (P = 0.058), and average pupillary contraction velocities were 1.37 and 1.91, respectively (P = 0.172). Among the sedative group, at about the time of arrival, average pupillary contraction rates were 8.75% in the GCS 3–13 group and 19.75% in the GCS 14–15 group (P = 0.032). Average pupillary contraction velocities were 0.34 and 1.48, respectively (P = 0.001). Approximately 48 h after arrival, average pupillary contraction rates were 13.50% and 13.50%, respectively (P = 1.00), and average pupillary contraction velocities were 0.80 and 0.82, respectively (P = 0.93).

Conclusions

Pupillometer measurements could predict level of consciousness of patients with severe consciousness disorder.

EEG reactivity testing for prediction of good outcome in patients after cardiac arrest

Objective

To determine the additional value of EEG reactivity (EEG-R) testing to EEG background pattern for prediction of good outcome in adult patients after cardiac arrest (CA).

Methods

In this post hoc analysis of a prospective cohort study, EEG-R was tested twice a day, using a strict protocol. Good outcome was defined as a Cerebral Performance Category score of 1–2 within 6 months. The additional value of EEG-R per EEG background pattern was evaluated using the diagnostic odds ratio (DOR). Prognostic value (sensitivity and specificity) of EEG-R was investigated in relation to time after CA, sedative medication, different stimuli, and repeated testing.

Results

Between 12 and 24 hours after CA, data of 108 patients were available. Patients with a continuous (n = 64) or discontinuous (n = 19) normal voltage background pattern with reactivity were 3 and 8 times more likely to have a good outcome than without reactivity (continuous: DOR, 3.4; 95% confidence interval [CI], 0.97–12.0; p = 0.06; discontinuous: DOR, 8.0; 95% CI, 1.0–63.97; p = 0.0499). EEG-R was not observed in other background patterns within 24 hours after CA. In 119 patients with a normal voltage EEG background pattern, continuous or discontinuous, any time after CA, prognostic value was highest in sedated patients (sensitivity 81.3%, specificity 59.5%), irrespective of time after CA. EEG-R induced by handclapping and sternal rubbing, especially when combined, had highest prognostic value. Repeated EEG-R testing increased prognostic value.

Conclusion

EEG-R has additional value for prediction of good outcome in patients with discontinuous normal voltage EEG background pattern and possibly with continuous normal voltage. The best stimuli were clapping and sternal rubbing.

Racial and Ethnic Disparities in Postcardiac Arrest Targeted Temperature Management Outcomes

OBJECTIVES

To evaluate racial and ethnic disparities in postcardiac arrest outcomes in patients undergoing targeted temperature management.

DESIGN

Retrospective study.

SETTING

ICUs in a single tertiary care hospital.

PATIENTS

Three-hundred sixty-seven patients undergoing postcardiac arrest targeted temperature management, including continuous electroencephalogram monitoring.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Clinical variables examined in our clinical cohort included race/ethnicity, age, time to return of spontaneous circulation, cardiac rhythm at time of arrest, insurance status, Charlson Comorbidity Index, and time to withdrawal of life-sustaining therapy. CT at admission and continuous electroencephalogram monitoring during the first 24 hours were used as markers of early injury. Outcome was assessed as good (Cerebral Performance Category 1-2) versus poor (Cerebral Performance Category 3-5) at hospital discharge. White non-Hispanic ("White") patients were more likely to have good outcomes than white Hispanic/nonwhite ("Non-white") patients (34.4 vs 21.7%; p = 0.015). In a multivariate model that included age, time to return of spontaneous circulation, initial rhythm, combined electroencephalogram/CT findings, Charlson Comorbidity Index, and insurance status, race/ethnicity was still independently associated with poor outcome (odds ratio, 3.32; p = 0.003). Comorbidities were lower in white patients but did not fully explain outcomes differences. Nonwhite patients were more likely to exhibit signs of early severe anoxic changes on CT or electroencephalogram, higher creatinine levels and receive dialysis, but had longer duration to withdrawal of lifesustaining therapy. There was no significant difference in catheterizations or MRI scans. Subgroup analysis performed with patients without early electroencephalogram or CT changes still revealed better outcome in white patients.

CONCLUSIONS

Racial/ethnic disparity in outcome persists despite a strictly protocoled targeted temperature management. Nonwhite patients are more likely to arrive with more severe anoxic brain injury, but this does not account for all the disparity.

Mechanistic Wager on Outcome in Coma After Cardiac Arrest: The EEG Signature in Burst Suppression Provides Some Clues

Independent Functional Outcomes After Prolonged Coma Following Cardiac Arrest: A Mechanistic Hypothesis

Forgacs PB, Devinsky O, Schiff ND. Ann Neurol. 2020;87:618-632. doi:10.1002/ana.25690.

Objective:

Survivors of prolonged (>2 weeks) post-cardiac arrest (CA) coma are expected to remain permanently disabled. We aimed to investigate 3 outlier patients who ultimately achieved independent functional outcomes after prolonged post-CA coma to identify electroencephalographic (EEG) markers of their recovery potential. For validation purposes, we also aimed to evaluate these markers in an independent cohort of post-CA patients.

Methods:

We identified 3 patients with late recovery from coma (17-37 days) following CA who recovered to functionally independent behavioral levels. We performed spectral power analyses of available EEGs during prominent burst suppression patterns (BSP) present in all 3 patients. Using identical methods, we also assessed the relationship of intraburst spectral power and outcomes in a prospectively enrolled cohort of post-CA patients. We performed chart reviews of common clinical, imaging, and EEG prognostic variables and clinical outcomes for all patients.

Results:

All 3 patients with late recovery from coma lacked evidence of overwhelming cortical injury but demonstrated prominent BSP on EEG. Spectral analyses revealed a prominent theta (∼4-7 Hz) feature dominating the bursts during BSP in these patients. In the prospective cohort, similar intraburst theta spectral features were evident in patients with favorable outcomes; patients with BSP and unfavorable outcomes showed either no features, transient burst features, or decreasing intraburst frequencies with time.

Interpretation:

Burst suppression patterns with theta (∼4-7 Hz) peak intraburst spectral power after CA may index a recovery potential. We discuss our results in the context of optimizing metabolic substrate availability and stimulating the corticothalamic system during recovery from prolonged post-CA coma.

EEG signal varies with different outcomes in comatose patients: A quantitative method of electroencephalography reactivity

BACKGROUND

Electroencephalographic reactivity (EEG-R) is a major predictor of outcome in comatose patients; however, the inter-rater reliability is limited due to the lack of homogeneous stimuli and quantitative interpretation.

NEW METHODS

EEG-R testing was employed in comatose patients by quantifiable electrical stimulation. Reactivity at different frequency bands was computed as the difference between pre- and post-stimulations in power spectra and connectivity function (including magnitude squared coherence and transfer entropy). The clinical outcomes were dichotomized as good and poor according to the recovery of consciousness. Signal discrimination of EEG-R was compared between the two groups.

RESULTS

A total of 18 patients (43%) regained consciousness at a 3-month follow-up. In the patients who regained consciousness, the EEG power increased significantly (P < 0.05) at the Alpha and Beta frequency bands after stimulation as compared to those with no behavioral awakening. Also, connectivity enhancement (including linear and nonlinear analysis) in the Beta and Gamma bands and connectivity decrease (nonlinear transfer entropy analysis) in the Delta band after stimulus were observed in the good outcome group.

COMPARISON WITH EXISTING METHOD(S)

In this study, the combined use of quantifiable stimulation and quantitative analysis shed new light on differentiating brain responses in comatose patients with good and poor outcomes as well as exploring the nature of EEG changes concerning the recovery of consciousness.

CONCLUSIONS

The combination of quantifiable electrical stimulation and quantitative analysis with spectral power and connectivity for the EEG-R may be a promising method to predict the outcome of comatose patients.

Are providers overconfident in predicting outcome after cardiac arrest?

AIM

To quantify the accuracy of health care providers' predictions of survival and function at hospital discharge in a prospective cohort of patients resuscitated from cardiac arrest. To test whether self-reported confidence in their predictions was associated with increased accuracy and whether this relationship varied across providers.

METHODOLOGY

We presented critical care and neurology providers with clinical vignettes using real data from post-arrest patients. We asked providers to predict survival, function at discharge, and report their confidence in these predictions. We used mixed effects models to explore predictors of confidence, accuracy, and the relationship between the two.

RESULTS

We completed 470 assessments of 62 patients with 65 providers. Of patients, 49 (78%) died and 9 (15%) had functionally favourable survival. Providers accurately predicted survival in 308/470 (66%) assessments. In most errors (146/162, 90%), providers incorrectly predicted survival. Providers accurately predicted function in 349/470 (74%) assessments. In most errors (114/121, 94%), providers incorrectly predicted favourable functional recovery. Providers were confident (median confidence predicting survival 80 [IQR 60-90]; median confidence predicting function 80 [IQR 60-95]). Confidence explained 9% and 18% of variation in accuracy predicting survival and function, respectively. We observed significant between-provider variability in accuracy (median odds ratio (MOR) for predicting survival 2.93, 95%CI 1.94-5.52; MOR for predicting function 5.42, 95%CI 3.01-13.2).

CONCLUSIONS

Providers varied in accuracy predicting post-arrest outcomes and most errors were optimistic. Self-reported confidence explained little variation in accuracy.

Prognostic Value of Early Intermittent Electroencephalography in Patients after Extracorporeal Cardiopulmonary Resuscitation

The aim of this study was to investigate whether early intermittent electroencephalography (EEG) could be used to predict neurological prognosis of patients who underwent extracorporeal cardiopulmonary resuscitation (ECPR). This was a retrospective and observational study of adult patients who were evaluated by EEG scan within 96 h after ECPR. The primary endpoint was neurological status upon discharge from the hospital assessed with a Cerebral Performance Categories (CPC) scale. Among 69 adult cardiac arrest patients who underwent ECPR, 17 (24.6%) patients had favorable neurological outcomes (CPC score of 1 or 2). Malignant EEG patterns were more common in patients with poor neurological outcomes (CPC score of 3, 4 or 5) than in patients with favorable neurological outcomes (73.1% vs. 5.9%, p < 0.001). All patients with highly malignant EEG patterns (43.5%) had poor neurological outcomes. In multivariable analysis, malignant EEG patterns and duration of cardiopulmonary resuscitation were significantly associated with poor neurological outcomes. In this study, malignant EEG patterns within 96 h after cardiac arrest were significantly associated with poor neurological outcomes. Therefore, an early intermittent EEG scan could be helpful for predicting neurological prognosis of post-cardiac arrest patients after ECPR.

Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest

Purpose

To assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM).

Methods

Retrospective descriptive analysis with data from the Target Temperature Management (TTM) Trial. Associations between predicted and actual neurological outcome were investigated for each step of the algorithm with results from clinical neurological examinations, neuroradiology (CT or MRI), neurophysiology (EEG and SSEP) and serum neuron-specific enolase. Patients examined with Glasgow Coma Scale Motor Score (GCS-M) on day 4 (72–96 h) post-arrest and available 6-month outcome were included. Poor outcome was defined as Cerebral Performance Category 3–5. Variations of the ERC/ESICM algorithm were explored within the same cohort.

Results

The ERC/ESICM algorithm identified poor outcome patients with 38.7% sensitivity (95% CI 33.1–44.7) and 100% specificity (95% CI 98.8–100) in a cohort of 585 patients. An alternative cut-off for serum neuron-specific enolase, an alternative EEG-classification and variations of the GCS-M had minor effects on the sensitivity without causing false positive predictions. The highest overall sensitivity, 42.5% (95% CI 36.7–48.5), was achieved when prognosticating patients irrespective of GCS-M score, with 100% specificity (95% CI 98.8–100) remaining.

Conclusion

The ERC/ESICM algorithm and all exploratory multimodal variations thereof investigated in this study predicted poor outcome without false positive predictions and with sensitivities 34.6–42.5%. Our results should be validated prospectively, preferably in patients where withdrawal of life-sustaining therapy is uncommon to exclude any confounding from self-fulfilling prophecies.

Electronic supplementary material

The online version of this article (10.1007/s00134-020-06080-9) contains supplementary material, which is available to authorized users.

How can neurological outcomes be predicted in comatose pediatric patients after out-of-hospital cardiac arrest?

The prognosis of patients who are comatose after resuscitation remains uncertain. The accurate prediction of neurological outcome is important for management decisions and counseling. A neurological examination is an important factor for prognostication, but widely used sedatives alter the neurological examination and delay the response recovery. Additional studies including electroencephalography, somatosensory-evoked potentials, brain imaging, and blood biomarkers are useful for evaluating the extent of brain injury. This review aimed to assess the usefulness of and provide practical prognostic strategy for pediatric postresuscitation patients. The principles of prognostication are that the assessment should be delayed until at least 72 hours after cardiac arrest and the assessment should be multimodal. Furthermore, multiple factors including unmeasured confounders in individual patients should be considered when applying the prognostication strategy.

Relevance of Somatosensory Evoked Potential Amplitude After Cardiac Arrest

Objective: We present relations of SSEP amplitude with neurological outcome and of SSEP amplitude with EEG amplitude in comatose patients after cardiac arrest. Methods: This is a post hoc analysis of a prospective cohort study in comatose patients after cardiac arrest. Amplitude of SSEP recordings obtained within 48-72 h, and EEG patterns obtained at 12 and 24h after cardiac arrest were related to good (CPC 1-2) or poor (CPC 3-5) outcome at 6 months. In 39% of the study population multiple SSEP measurements were performed. Additionally, SSEP amplitude was related to mean EEG amplitude. Results: We included 138 patients (77% poor outcome). Absent SSEP responses, a N20 amplitude <0.4 μV within 48-72 h, and suppressed or synchronous EEG with suppressed background at 12 or 24 h after cardiac arrest were invariably associated with a poor outcome. Combined, these tests reached a sensitivity for prediction of poor outcome up to 58 at 100% specificity. N20 amplitude increased with a mean of 0.55 μV per day in patients with a poor outcome, and remained stable with a good outcome. There was no statistically significant correlation between SSEP and EEG amplitudes in 182 combined SSEP and EEG measurements (R ² < 0.01). Conclusions: N20 amplitude <0.4 μV is invariably associated with poor outcome. There is no correlation between SSEP and EEG amplitude. Significance: SSEP amplitude analysis may contribute to outcome prediction after cardiac arrest.

Background Frequency Patterns in Standard Electroencephalography as an Early Prognostic Tool in Out-of-Hospital Cardiac Arrest Survivors Treated with Targeted Temperature Management

We investigated the prognostic value of standard electroencephalography, a 30-min recording using 21 electrodes on the scalp, during the early post-cardiac arrest period, and evaluated the performance of electroencephalography findings combined with other clinical features for predicting favourable outcomes in comatose out-of-hospital cardiac arrest (OHCA) survivors treated with targeted temperature management (TTM). This observational registry-based study was conducted at a tertiary care hospital in Korea using the data of all consecutive adult non-traumatic comatose OHCA survivors who underwent standard electroencephalography during TTM between 2010 and 2018. The primary outcome was a 6-month favourable neurological outcome (Cerebral Performance Category score of 1 or 2). Among 170 comatose OHCA survivors with median electroencephalography time of 22 h, a 6-month favourable neurologic outcome was observed in 34.1% (58/170). After adjusting other clinical characteristics, an electroencephalography background with dominant alpha and theta waves had the highest odds ratio of 13.03 (95% confidence interval, 4.69–36.22) in multivariable logistic analysis. A combination of other clinical features (age < 65 years, initial shockable rhythm, resuscitation duration < 20 min) with an electroencephalography background with dominant alpha and theta waves increased predictive performance for favourable neurologic outcomes with a high specificity of up to 100%. A background with dominant alpha and theta waves in standard electroencephalography during TTM could be a simple and early favourable prognostic finding in comatose OHCA survivors.

Sensitivity of Continuous Electroencephalography to Detect Ictal Activity After Cardiac Arrest

IMPORTANCE

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

OBJECTIVE

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

DESIGN, SETTING, AND PARTICIPANTS

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

MAIN OUTCOMES AND MEASURES

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

RESULTS

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

CONCLUSIONS AND RELEVANCE

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

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

Objective

After cardiac arrest (CA), epileptiform EEG, occurring in about 1/3 of patients, often but not invariably heralds poor prognosis. We tested the hypothesis that a combination of specific EEG features identifies patients who may regain consciousness despite early epileptiform patterns.

Methods

We retrospectively analyzed a registry of comatose patients post-CA (2 Swiss centers), including those with epileptiform EEG. Background and epileptiform features in EEGs 12–36 hours or 36–72 hours from CA were scored according to the American Clinical Neurophysiology Society nomenclature. Best Cerebral Performance Category (CPC) score within 3 months (CPC 1–3 vs 4–5) was the primary outcome. Significant EEG variables were combined in a score assessed with receiver operating characteristic curves, and independently validated in a US cohort; its correlation with serum neuron-specific enolase (NSE) was also tested.

Results

Of 488 patients, 107 (21.9%) had epileptiform EEG <72 hours; 18 (17%) reached CPC 1–3. EEG 12–36 hours background continuity ≥50%, absence of epileptiform abnormalities (p< 0.00001 each), 12–36 and 36–72 hours reactivity (p< 0.0001 each), 36–72 hours normal background amplitude (p= 0.0004), and stimulus-induced discharges (p= 0.0001) correlated with favorable outcome. The combined 6-point score cutoff ≥2 was 100% sensitive (95% confidence interval [CI], 78%–100%) and 70% specific (95% CI, 59%–80%) for CPC 1–3 (area under the curve [AUC], 0.98; 95% CI, 0.94–1.00). Increasing score correlated with NSE (ρ = −0.46,p= 0.0001). In the validation cohort (41 patients), the score was 100% sensitive (95% CI, 60%–100%) and 88% specific (95% CI, 73%–97%) for CPC 1–3 (AUC, 0.96; 95% CI, 0.91–1.00).

Conclusion

Prognostic value of early epileptiform EEG after CA can be estimated combining timing, continuity, reactivity, and amplitude features in a score that correlates with neuronal damage.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Standardized EEG analysis to reduce the uncertainty of outcome prognostication after cardiac arrest

PURPOSE

Post-resuscitation guidelines recommend a multimodal algorithm for outcome prediction after cardiac arrest (CA). We aimed at evaluating the prevalence of indeterminate prognosis after application of this algorithm and providing a strategy for improving prognostication in this population.

METHODS

We examined a prospective cohort of comatose CA patients (n = 485) in whom the ERC/ESICM algorithm was applied. In patients with an indeterminate outcome, prognostication was investigated using standardized EEG classification (benign, malignant, highly malignant) and serum neuron-specific enolase (NSE). Neurological recovery at 3 months was dichotomized as good (Cerebral Performance Categories [CPC] 1-2) vs. poor (CPC 3-5).

RESULTS

Using the ERC/ESICM algorithm, 155 (32%) patients were prognosticated with poor outcome; all died at 3 months. Among the remaining 330 (68%) patients with an indeterminate outcome, the majority (212/330; 64%) showed good recovery. In this patient subgroup, absence of a highly malignant EEG by day 3 had 99.5 [97.4-99.9] % sensitivity for good recovery, which was superior to NSE < 33 μg/L (84.9 [79.3-89.4] % when used alone; 84.4 [78.8-89] % when combined with EEG, both p < 0.001). Highly malignant EEG had equal specificity (99.5 [97.4-99.9] %) but higher sensitivity than NSE for poor recovery. Further analysis of the discriminative power of outcome predictors revealed limited value of NSE over EEG.

CONCLUSIONS

In the majority of comatose CA patients, the outcome remains indeterminate after application of ERC/ESICM prognostication algorithm. Standardized EEG background analysis enables accurate prediction of both good and poor recovery, thereby greatly reducing uncertainty about coma prognostication in this patient population.

Prognostic role of EEG identical bursts in patients after cardiac arrest: Multimodal correlation

AIMS

EEG burst-suppression (BS) heralds poor outcome after cardiac arrest (CA). Within this pattern, identical bursts (IB) have been suggested to be absolutely specific, in isolation. We assessed IB prevalence and their added predictive value for poor outcome in a multimodal prognostic approach.

METHODS

We retrospectively analyzed a registry of comatose adults with CA (April 2011-February 2019), undergoing EEG at 5-36 h and 36-72 h. SB and IB were visually assessed. Cerebral Performance Categories (CPC) at 3 months were dichotomized as "good" (CPC 1-2), or "poor" (CPC 3-5). Sensitivity, specificity, positive, negative predictive values of BS and IB for poor outcome were calculated. A multimodal prognostic score was created assigning one point each to unreactive and epileptiform EEG, pupillary light reflex and SSEPs absence, NSE > 75 μg/l. In a second score, IB were added; predictive performances were compared using Receiver Operating Characteristic (ROC) curves.

RESULTS

Of 522 patients, 147 (28%) had BS in any EEG (10 [7%] had good outcome and 129 [88%] died). Of them, 53/147 (36%, 10% of total) showed IB, 47/53 (89%) of which within 36 h. IB were 100% specific for poor outcome, and associated with higher serum NSE than BS. However, there was no significant difference between the scores with and without IB for CPC 3-5 (p = 0.116).

CONCLUSION

IB occur in 10% of patients after CA. In our multimodal context, IB, albeit being very specific for poor outcome, seem redundant with other predictors.

Topography of MR lesions correlates with standardized EEG pattern in early comatose survivors after cardiac arrest

AIM

Multimodal prognostication in comatose patients after cardiac arrest (CA) is complicated by the fact that different modalities are usually not independent. Here we set out to systematically correlate early EEG and MRI findings.

METHODS

89 adult patients from a prospective register who underwent at least one EEG and one MRI in the acute phase after CA were included. The EEGs were characterized using pre-existent standardized categories (highly malignant, malignant, benign). For MRIs, the apparent diffusion coefficient (ADC) was computed in pre-defined regions. We then introduced a novel classification based on the topography of ADC reduction (MR-lesion pattern (MLP) 1: no lesion; MLP 2: purely cortical lesions; MLP 3: involvement of the basal ganglia; MLP 4 involvement of other deep grey matter regions).

RESULTS

EEG background reactivity and EEG background continuity were strongly associated with a lower MLP value (p < 0.001 and p = 0.003 respectively). The EEG categories highly malignant, malignant and benign were strongly correlated with the MLP values (rho = 0.46, p < 0.001).

CONCLUSION

The MRI lesions are highly correlated with the EEG pattern. Our results suggest that performing MRI in comatose patients after CA with either highly malignant or with a benign EEG pattern is unlikely to yield additional useful information for prognostication, and should therefore be performed in priority in patients with intermediate EEG patterns ("malignant pattern").

A Fate Worse Than Death: Prognostication of Devastating Brain Injury

OBJECTIVES

To describe the sources of uncertainty in prognosticating devastating brain injury, the role of the intensivist in prognostication, and ethical considerations in prognosticating devastating brain injury in the ICU.

DATA SOURCES

A PubMed literature review was performed.

STUDY SELECTION

Articles relevant to prognosis in intracerebral hemorrhage, acute ischemic stroke, traumatic brain injury, subarachnoid hemorrhage, and postcardiac arrest anoxic encephalopathy were selected.

DATA EXTRACTION

Data regarding definition and prognosis of devastating brain injury were extracted. Themes related to how clinicians perform prognostication and their accuracy were reviewed and extracted.

DATA SYNTHESIS

Although there are differences in pathophysiology and therefore prognosis in the various etiologies of devastating brain injury, some common themes emerge. Physicians tend to have fairly good prognostic accuracy, especially in severe cases with poor prognosis. Full supportive care is recommended for at least 72 hours from initial presentation to maximize the potential for recovery and minimize secondary injury. However, physician approaches to the timing of and recommendations for withdrawal of life-sustaining therapy have a significant impact on mortality from devastating brain injury.

CONCLUSIONS

Intensivists should consider the modern literature describing prognosis for devastating brain injury and provide appropriate time for patient recovery and for discussions with the patient's surrogates. Surrogates wish to have a prognosis enumerated even when uncertainty exists. These discussions must be handled with care and include admission of uncertainty when it exists. Respect for patient autonomy remains paramount, although physicians are not required to provide inappropriate medical therapies.

Postresuscitation Care after Out-of-hospital Cardiac Arrest: Clinical Update and Focus on Targeted Temperature Management

Out-of-hospital cardiac arrest is a major cause of mortality and morbidity worldwide. With the introduction of targeted temperature management more than a decade ago, postresuscitation care has attracted increased attention. In the present review, we discuss best practice hospital management of unconscious out-of-hospital cardiac arrest patients with a special focus on targeted temperature management. What is termed post-cardiac arrest syndrome strikes all organs and mandates access to specialized intensive care. All patients need a secured airway, and most patients need hemodynamic support with fluids and/or vasopressors. Furthermore, immediate coronary angiography and percutaneous coronary intervention, when indicated, has become an essential part of the postresuscitation treatment. Targeted temperature management with controlled sedation and mechanical ventilation is the most important neuroprotective strategy to take. Targeted temperature management should be initiated as quickly as possible, and according to international guidelines, it should be maintained at 32° to 36°C for at least 24 h, whereas rewarming should not increase more than 0.5°C per hour. However, uncertainty remains regarding targeted temperature management components, warranting further research into the optimal cooling rate, target temperature, duration of cooling, and the rewarming rate. Moreover, targeted temperature management is linked to some adverse effects. The risk of infection and bleeding is moderately increased, as is the risk of hypokalemia and magnesemia. Circulation needs to be monitored invasively and any deviances corrected in a timely fashion. Outcome prediction in the individual patient is challenging, and a self-fulfilling prophecy poses a real threat to early prognostication based on clinical assessment alone. Therefore, delayed and multimodal prognostication is now considered a key element of postresuscitation care. Finally, modern postresuscitation care can produce good outcomes in the majority of patients but requires major diagnostic and therapeutic resources and specific training. Hence, recent international guidelines strongly recommend the implementation of regional prehospital resuscitation systems with integrated and specialized cardiac arrest centers.