Standardized EEG interpretation in patients after cardiac arrest: Correlation with other prognostic predictors

Electroencephalography in encephalopathy and encephalitis

Electroencephalography (EEG) is a useful adjunct to clinical neurological examination, particularly as it may detect subtle or subclinical disturbance of cerebral function and it allows monitoring of cerebral activity over time. Continuous EEG combined with quantitative analysis and machine learning may help identify changes in real time, before the emergence of clinical signs and response to interventions. EEG is rarely pathognomonic in encephalopathy/encephalitis but when interpreted correctly and within the clinical context, certain phenotypes may indicate a specific pathophysiology (eg, lateralised periodic discharges in HSV-1, generalised periodic discharges in sporadic Creutzfeldt-Jakob disease, and extreme delta brushes in anti-n-methyl-D-aspartate receptor autoimmune encephalitis). EEG is included in some specialist guidelines for disease assessment, monitoring and prognostication (ie, hepatic, cancer immunotherapy, viral, prion, autoimmune encephalitis and hypoxic ischaemic encephalopathy). EEG is invaluable for confirming or excluding non-convulsive seizures or status epilepticus, particularly in critically ill patients, and in understanding new concepts such as epileptic encephalopathy and the ictal-interictal continuum.

Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis

Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

Benign EEG for prognostication of favorable outcome after cardiac arrest: A reappraisal

AIM

The current EEG role for prognostication after cardiac arrest (CA) essentially aims at reliably identifying patients with poor prognosis ("highly malignant" patterns, defined by Westhall et al. in 2014). Conversely, "benign EEGs", defined by the absence of elements of "highly malignant" and "malignant" categories, has limited sensitivity in detecting good prognosis. We postulate that a less stringent "benign EEG" definition would improve sensitivity to detect patients with favorable outcomes.

METHODS

Retrospectively assessing our registry of unconscious adults after CA (1.2018-8.2021), we scored EEGs within 72 h after CA using a modified "benign EEG" classification (allowing discontinuity, low-voltage, or reversed anterio-posterior amplitude development), versus Westhall's "benign EEG" classification (not allowing the former items). We compared predictive performances towards good outcome (Cerebral Performance Category 1-2 at 3 months), using 2x2 tables (and binomial 95% confidence intervals) and proportions comparisons.

RESULTS

Among 381 patients (mean age 61.9 ± 15.4 years, 104 (27.2%) females, 240 (62.9%) having cardiac origin), the modified "benign EEG" definition identified a higher number of patients with potential good outcome (252, 66%, vs 163, 43%). Sensitivity of the modified EEG definition was 0.97 (95% CI: 0.92-0.97) vs 0.71 (95% CI: 0.62-0.78) (p < 0.001). Positive predictive values (PPV) were 0.53 (95% CI: 0.46-0.59) versus 0.59 (95% CI: 0.51-0.67; p = 0.17). Similar statistics were observed at definite recording times, and for survivors.

DISCUSSION

The modified "benign EEG" classification demonstrated a markedly higher sensitivity towards favorable outcome, with minor impact on PPV. Adaptation of "benign EEG" criteria may improve efficient identification of patients who may reach a good outcome.

Prognostication after cardiac arrest: how EEG and evoked potentials may improve the challenge

About 80% of patients resuscitated from CA are comatose at ICU admission and nearly 50% of survivors are still unawake at 72 h. Predicting neurological outcome of these patients is important to provide correct information to patient's relatives, avoid disproportionate care in patients with irreversible hypoxic-ischemic brain injury (HIBI) and inappropriate withdrawal of care in patients with a possible favorable neurological recovery. ERC/ESICM 2021 algorithm allows a classification as "poor outcome likely" in 32%, the outcome remaining "indeterminate" in 68%. The crucial question is to know how we could improve the assessment of both unfavorable but also favorable outcome prediction. Neurophysiological tests, i.e., electroencephalography (EEG) and evoked-potentials (EPs) are a non-invasive bedside investigations. The EEG is the record of brain electrical fields, characterized by a high temporal resolution but a low spatial resolution. EEG is largely available, and represented the most widely tool use in recent survey examining current neuro-prognostication practices. The severity of HIBI is correlated with the predominant frequency and background continuity of EEG leading to "highly malignant" patterns as suppression or burst suppression in the most severe HIBI. EPs differ from EEG signals as they are stimulus induced and represent the summated activities of large populations of neurons firing in synchrony, requiring the average of numerous stimulations. Different EPs (i.e., somato sensory EPs (SSEPs), brainstem auditory EPs (BAEPs), middle latency auditory EPs (MLAEPs) and long latency event-related potentials (ERPs) with mismatch negativity (MMN) and P300 responses) can be assessed in ICU, with different brain generators and prognostic values. In the present review, we summarize EEG and EPs signal generators, recording modalities, interpretation and prognostic values of these different neurophysiological tools. Finally, we assess the perspective for futures neurophysiological investigations, aiming to reduce prognostic uncertainty in comatose and disorders of consciousness (DoC) patients after CA.

Repetitive Electroencephalography as Biomarker for the Prediction of Survival in Patients with Post-Hypoxic Encephalopathy

Predicting survival in patients with post-hypoxic encephalopathy (HE) after cardiopulmonary resuscitation is a challenging aspect of modern neurocritical care. Here, continuous electroencephalography (cEEG) has been established as the gold standard for neurophysiological outcome prediction. Unfortunately, cEEG is not comprehensively available, especially in rural regions and developing countries. The objective of this monocentric study was to investigate the predictive properties of repetitive EEGs (rEEGs) with respect to 12-month survival based on data for 199 adult patients with HE, using log-rank and multivariate Cox regression analysis (MCRA). A total number of 59 patients (29.6%) received more than one EEG during the first 14 days of acute neurocritical care. These patients were analyzed for the presence of and changes in specific EEG patterns that have been shown to be associated with favorable or poor outcomes in HE. Based on MCRA, an initially normal amplitude with secondary low-voltage EEG remained as the only significant predictor for an unfavorable outcome, whereas all other relevant parameters identified by univariate analysis remained non-significant in the model. In conclusion, rEEG during early neurocritical care may help to assess the prognosis of HE patients if cEEG is not available.

Alpha-power in electroencephalography as good outcome predictor for out-of-hospital cardiac arrest survivors

This study aimed to investigate the utility of quantitative EEG biomarkers for predicting good neurologic outcomes in OHCA survivors treated with targeted temperature management (TTM) using power spectral density (PSD), event-related spectral perturbation (ERSP), and spectral entropy (SE). This observational registry-based study was conducted at a tertiary care hospital in Korea using data of adult nontraumatic comatose OHCA survivors who underwent standard EEG and treated with TTM between 2010 and 2018. Good neurological outcome at 1 month (Cerebral Performance Category scores 1 and 2) was the primary outcome. The linear mixed model analysis was performed for PSD, ESRP, and SE values of all and each frequency band. Thirteen of the 54 comatose OHCA survivors with TTM and EEG were excluded due to poor EEG quality or periodic/rhythmic pattern, and EEG data of 41 patients were used for analysis. The median time to EEG was 21 h, and the rate of the good neurologic outcome at 1 month was 52.5%. The good neurologic outcome group was significantly younger and showed higher PSD and ERSP and lower SE features for each frequency than the poor outcome group. After age adjustment, only the alpha-PSD was significantly higher in the good neurologic outcome group (1.13 ± 1.11 vs. 0.09 ± 0.09, p = 0.031) and had best performance with 0.903 of the area under the curve for predicting good neurologic outcome. Alpha-PSD best predicts good neurologic outcome in OHCA survivors and is an early biomarker for prognostication. Larger studies are needed to conclusively confirm these findings.

Quantitative pupillometry in comatose out-of-hospital cardiac arrest patients: A post-hoc analysis of the TTH48 trial

Background

Quantitative pupillometry is an objective method to examine pupil reaction and subsequently grade the response on a neurological pupil index (NPi) scale from 0 to 5. The aim of the present sub‐study was to explore the long‐term prognostic value of NPi in comatose out‐of‐hospital cardiac arrest patients undergoing targeted temperature management (TTM).

Methods

This planned sub‐study of the “Targeted temperature management for 48 versus 24 h and neurological outcome after out‐of‐hospital cardiac arrest: A randomized clinical trial.” NPi was assessed from admission and throughout day 3 and linked to the Cerebral Performance Categories score at 6 months. We compared the prognostic performance of NPi in 65 patients randomized to a target temperature of 33 ± 1°C for 24 or 48 h.

Results

The NPi values were not different between TTM groups (p > .05). When data were pooled, NPi was strongly associated with neurological outcome at day 1 with a mean NPi of 3.6 (95% CI 3.4–3.8) versus NPi 3.9 (3.6–4.1) in the poor versus good outcome group, respectively (p < .01). At day 2, NPi values were 3.6 (3.1–4.0) and 4.1 (3.9–4.2) (p = .01) and at day 3, the values were 3.3 (2.6–4.0) and 4.3 (4.1–4.6), respectively (p < .01). The prognostic ability of NPi, defined by area under the receiver operating characteristic curve was best at day three.

Conclusion

Quantitative pupillometry measured by NPi was not different in the two TTM groups, but overall, significantly associated with good and poor neurological outcomes at 6 months. NPI has a promising diagnostic accuracy, but larger studies are warranted.

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

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

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Knowledge of pathophysiological mechanisms of EEG patterns may help interpretation.

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Standardized therapeutic procedures for critical care patients are needed.

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

EEG patterns and their correlations with short- and long-term mortality in patients with hypoxic encephalopathy

OBJECTIVE

To analyze the association between electroencephalographic (EEG) patterns and overall, short- and long-term mortality in patients with hypoxic encephalopathy (HE).

METHODS

Retrospective, mono-center analysis of 199 patients using univariate log-rank tests (LR) and multivariate cox regression (MCR).

RESULTS

Short-term mortality, defined as death within 30-days post-discharge was 54.8%. Long-term mortality rates were 69.8%, 71.9%, and 72.9%, at 12-, 24-, and 36-months post-HE, respectively. LR revealed a significant association between EEG suppression (SUP) and short-term mortality, and identified low voltage EEG (LV), burst suppression (BSP), periodic discharges (PD) and post-hypoxic status epilepticus (PSE) as well as missing (aBA) or non-reactive background activity (nrBA) as predictors for overall, short- and long-term mortality. MCR indicated SUP, LV, BSP, PD, aBA and nrBA as significantly associated with overall and short-term mortality to varying extents. LV and BSP were significant predictors for long-term mortality in short-term survivors. Rhythmic delta activity, stimulus induced rhythmic, periodic or ictal discharges and sharp waves were not significantly associated with a higher mortality.

CONCLUSION

The presence of several specific EEG patterns can help to predict overall, short- and long-term mortality in HE patients.

SIGNIFICANCE

The present findings may help to improve the challenging prognosis estimation in HE patients.

Application of a standardized EEG pattern classification in the assessment of neurological prognosis after cardiac arrest: A retrospective analysis

INTRODUCTION

Electroencephalogram (EEG) is used in the neurological prognostication after cardiac arrest. "Highly malignant" EEG patterns classified according to Westhall have a high specificity for poor neurological outcome when applied within protocols of recent studies. However, their predictive performance when applied in everyday clinical practice has not been investigated. We studied the prognostic accuracy and the interrater agreement when standardized EEG patterns were analysed and compared to neurological outcome in a patient cohort at a tertiary centre not involved in the original study of the standardized EEG pattern classification.

METHODS

Comatose patients treated for out-of-hospital cardiac arrest were included. Poor outcome was defined as Cerebral Performance Category 3-5. Two senior consultants and one resident in clinical neurophysiology, blinded to clinical data and outcome, independently reviewed their EEG registrations and categorised the pattern as "highly malignant", "malignant" or "benign". These categories were compared to neurological outcome at hospital discharge. Interrater agreement was assessed using Cohen's Kappa.

RESULTS

In total, 62 patients were included. The median (IQR) time to EEG was 59 (42-91) h after return of spontaneous circulation. Poor outcome was found in 52 (84%) patients. In 21 patients at least one of the raters considered the EEG to contain a "highly malignant" pattern, all with poor outcome (42% sensitivity, 100% specificity). The interrater agreement varied from kappa 0.62 to 0.29.

CONCLUSION

"Highly malignant" patterns predict poor neurological outcome with a high specificity in everyday practice. However, interrater agreement may vary substantially even between experienced EEG interpreters.

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.

Update on the management of status epilepticus

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

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.

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.

A Systematic Review Assessing the Current State of Automated Pupillometry in the NeuroICU

The aim of this study was to assess the current state of automated pupillometry technology and its application in the neurointensive care unit (neuroICU). We performed a literature search using the PubMed, MEDLINE, and EMBASE databases from database inception through a search end date of October 18, 2018, to identify studies reporting on the use of automated pupillometry in the care of critically ill patients with neurological impairment. Two independent reviewers reviewed all titles and abstracts in two filtering phases. Data were extracted independently. One hundred and forty-one articles/abstracts have been published on the use of automated pupillometry in critical care since inception of the PubMed, MEDLINE, and EMBASE databases. We selected and reviewed 22 full-text articles and 8 abstracts, of which 26 were prospective, 2 were retrospective, and 2 were larger case series. Automated pupillometry increased precision, reliability, and reproducibility compared with the manual pupillary examination; detected subtle and early pupillary changes; detected pupillary changes that indicate a rise, or impending rise, in intracranial pressure detected level of analgesia and depth of sedation; served as a prognostic indicator; estimated the clinical severity of aneurysmal subarachnoid hemorrhage; and served as a noninvasive monitor of response to osmotic therapy. At present, no consensus guidelines exist endorsing routine use of automated pupillometry in the neuroICU. However, an increasing quantity of research supports the usefulness of automated pupillometry in this setting. Further large-scale prospective studies are needed before updated consensus guidelines recommending widespread adoption of automated pupillometry are produced.

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.

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.

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.

Neurocritical Care Outcomes, Research, and Technology: A Review

Importance

Neurocritical care has grown into an organized specialty that may have consequences for patient care, outcomes, research, and neurointensive care (neuroICU) technology.

Observations

Neurocritical care improves care and outcomes of the patients who are neurocritically ill, and neuroICUs positively affect the financial state of health care systems. The development of neurocritical care as a recognized subspecialty has fostered multidisciplinary research, neuromonitoring, and neurocritical care information technology, with advances and innovations in practice and progress.

Conclusions and Relevance

Neurocritical care has become an important part of health systems and an established subspecialty of neurology. Understanding its structure, scope of practice, consequences for care, and research are important.

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").

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.

Otoacoustic Emissions for Outcome Prediction in Postanoxic Brain Injury

Background: Non-invasive, easy-to-use bedside tools to estimate prognosis in unresponsive patients with postanoxic brain injury are needed. We assessed the usefulness of otoacoustic emissions as outcome markers after cardiac arrest. Methods: Distortion product otoacoustic emissions (DPOAE) and transient evoked otoacoustic emissions (TEOAE) were measured in cardiac arrest patients whose prognosis was deemed to be poor following standard neurological assessment (n = 10). Ten patients with myocardial infarction without prior loss of consciousness served as controls. Results: Compared to controls with myocardial infarction, cardiac arrest patients with poor neurological prognosis had significantly less often preserved DPOAE (9.2 vs. 40.8% positive measurements; OR 0.15 (CI 0.07-0.30); p < 0.0001). Partially preserved DPOAE were noted in 4 cardiac arrest patients. TEOAE were not statistically different between the two groups. Conclusions: Despite their convenience, otoacoustic emissions cannot be used as reliable prognostic markers in cardiac arrest survivors. This is because we identified 4 cases with partially preserved otoacoustic emissions in a sample of 10 unresponsive post-cardiac arrest patients whose neurological condition was so poor that active treatment was withdrawn. However, we suggest that future research should address if decaying outer hair cell function over time may serve as a proxy for evolving ischemic brain damage.

Somatosensory and auditory deviance detection for outcome prediction during postanoxic coma

Objective

Prominent research in patients with disorders of consciousness investigated the electrophysiological correlates of auditory deviance detection as a marker of consciousness recovery. Here, we extend previous studies by investigating whether somatosensory deviance detection provides an added value for outcome prediction in postanoxic comatose patients.

Methods

Electroencephalography responses to frequent and rare stimuli were obtained from 66 patients on the first and second day after coma onset.

Results

Multivariate decoding analysis revealed an above chance‐level auditory discrimination in 25 patients on the first day and in 31 patients on the second day. Tactile discrimination was significant in 16 patients on the first day and in 23 patients on the second day. Single‐day sensory discrimination was unrelated to patients’ outcome in both modalities. However, improvement of auditory discrimination from first to the second day was predictive of good outcome with a positive predictive power (PPV) of 0.73 (CI = 0.52–0.88). Analyses considering the improvement of tactile, auditory and tactile, or either auditory or tactile discrimination showed no significant prediction of good outcome (PPVs = 0.58–0.68).

Interpretation

Our results show that in the acute phase of coma deviance detection is largely preserved for both auditory and tactile modalities. However, we found no evidence for an added value of somatosensory to auditory deviance detection function for coma‐outcome prediction.