Uncommon EEG burst-suppression in severe postanoxic encephalopathy

Early Burst Suppression Similarity Association with Structural Brain Injury Severity on MRI After Cardiac Arrest

BACKGROUND

Identical bursts on electroencephalography (EEG) are considered a specific predictor of poor outcomes in cardiac arrest, but its relationship with structural brain injury severity on magnetic resonance imaging (MRI) is not known.

METHODS

This was a retrospective analysis of clinical, EEG, and MRI data from adult comatose patients after cardiac arrest. Burst similarity in first 72 h from the time of return of spontaneous circulation were calculated using dynamic time-warping (DTW) for bursts of equal (i.e., 500 ms) and varying (i.e., 100-500 ms) lengths and cross-correlation for bursts of equal lengths. Structural brain injury severity was measured using whole brain mean apparent diffusion coefficient (ADC) on MRI. Pearson's correlation coefficients were calculated between mean burst similarity across consecutive 12-24-h time blocks and mean whole brain ADC values. Good outcome was defined as Cerebral Performance Category of 1-2 (i.e., independence for activities of daily living) at the time of hospital discharge.

RESULTS

Of 113 patients with cardiac arrest, 45 patients had burst suppression (mean cardiac arrest to MRI time 4.3 days). Three study participants with burst suppression had a good outcome. Burst similarity calculated using DTW with bursts of varying lengths was correlated with mean ADC value in the first 36 h after cardiac arrest: Pearson's r: 0-12 h: - 0.69 (p = 0.039), 12-24 h: - 0.54 (p = 0.002), 24-36 h: - 0.41 (p = 0.049). Burst similarity measured with bursts of equal lengths was not associated with mean ADC value with cross-correlation or DTW, except for DTW at 60-72 h (- 0.96, p = 0.04).

CONCLUSIONS

Burst similarity on EEG after cardiac arrest may be associated with acute brain injury severity on MRI. This association was time dependent when measured using DTW.

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.

Electroencephalographic Burst-Suppression, Perioperative Neuroprotection, Postoperative Cognitive Function, and Mortality: A Focused Narrative Review of the Literature

Burst-suppression is an electroencephalographic pattern that results from a diverse array of pathophysiological causes and/or metabolic neuronal suppression secondary to the administration of anesthetic medications. The purpose of this review is to provide an overview of the physiological mechanisms that underlie the burst-suppression pattern and to present in a comprehensive way the available evidence both supporting and in opposition to the clinical use of this electroencephalographic pattern as a therapeutic measure in various perioperative settings.

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.

Awakening from post anoxic coma with burst suppression with identical bursts

Background

Electroencephalography (EEG) is commonly used after cardiac arrest. Burst suppression with identical bursts (BSIB) has been reported as a perfectly specific predictor of poor outcome but published case series are small. We describe two patients with BSIB who awakened from coma after cardiac arrest.

Methods

We identified two out-of-hospital cardiac arrest (OHCA) patients with coma and BSIB. We determined the etiology of arrest, presenting neurological examination, potential confounders to neurological assessment, neurodiagnostics and time to awakening. We reviewed and interpreted EEGs using 2021 American Clinical Neurophysiology Society guidelines. We quantified identicality of bursts by calculating pairwise correlation coefficients between the first 500 ms of each aligned burst.

Results

In case one we present a 62-year-old man with OHCA secondary to septic shock. EEG showed burst suppression pattern, with bursts consisted of high amplitude generalized spike waves in lock-step with myoclonus (inter-burst correlation = 0.86). He followed commands 3 days after arrest, when repeat EEG showed a continuous, variable and reactive background without epileptiform activity. Case two was a 49-year-old woman with OHCA secondary to polysubstance overdose. Initial EEG revealed burst suppression with high amplitude generalized polyspike-wave bursts with associated myoclonus. She followed commands on post-arrest day 4, when repeat EEG showed a continuous, variable and reactive background with frequent runs of bifrontal predominant sharply contoured rhythmic delta activity.

Conclusion

These cases highlight the perils of prognosticating with a single modality in comatose cardiac arrest patients.

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.

Stimulus induced bursts in severe postanoxic encephalopathy

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

Neonatal electroencephalography recordings

The growth processes involved early in gestation and further into the intricate signaling networks in the brain form the basis for rapid cortical electrical bursting patterns. This leads to the quantification of cortical activity from the electroencephalogram (EEG) in full-term hypoxic infants and preterm infants. The associated neurological sequelae in both populations are foregrounded by a summary into current epidemiology and common clinical practices. The present review article highlights recent advances in physics and neuroscience, which will help in development of reliable predictors of outcome for full-term and preterm neonates after birth.

EEG in postanoxic coma: Prognostic and diagnostic value

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

Infraslow EEG activity modulates cortical excitability in postanoxic encephalopathy

Infraslow activity represents an important component of physiological and pathological brain function. We study infraslow activity (<0.1 Hz) in 41 patients with postanoxic coma after cardiac arrest, including the relationship between infraslow activity and EEG power in the 3-30 Hz range, using continuous full-band scalp EEG. In all patients, infraslow activity (0.015-0.06 Hz) was present, irrespective of neurological outcome or EEG activity in the conventional frequency bands. In two patients, low-amplitude (10-30 μV) infraslow activity was present while the EEG showed no rhythmic activity above 0.5 Hz. In 13/15 patients with a good outcome and 20/26 patients with a poor one, EEG power in the 3-30 Hz frequency range was correlated with the phase of infraslow activity, quantified by the modulation index. In 9/14 patients with burst-suppression with identical bursts, bursts appeared in clusters, phase-locked to the infraslow oscillations. This is substantiated by a simulation of burst-suppression in a minimal computational model. Infraslow activity is preserved in postanoxic encephalopathy and modulates cortical excitability. The strongest modulation is observed in patients with severe postanoxic encephalopathy and burst-suppression with identical bursts.

Detection of burst suppression patterns in EEG using recurrence rate

Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and multiple comparison tests showed that the RR could detect BSP and that it was superior to other measures with the highest sensitivity of suppression detection (96.49%, P = 0.03). Tracking BSP patterns is essential for clinical monitoring in critically ill and anesthetized patients. The purposed RR may provide an effective burst suppression detector for developing new patient monitoring systems.

Effect of Inpatient Electroencephalography on Clinical Decision Making

Context: Routine inpatient electroencephalography (EEG) is commonly used as a diagnostic and therapeutic decision-making tool in the care of patients with a wide spectrum of conditions. Previous investigations on EEG use have focused on current guidelines or specific clinical presentations.

Objective: To assess the effect of EEGs on clinical diagnosis and management of disease in adult inpatients in a community hospital.

Methods: Medical records of adult patients who underwent EEG between October 2008 and June 2009 in a single general community hospital were retrospectively reviewed. Data were collected for comorbidities, diagnoses, and management. Findings from EEGs were classified as normal, abnormal, or uninterpretable and according to whether they resulted in a change in diagnosis or management, supported clinical decision making and resulted in no change in diagnosis or management, or did not contribute to diagnosis or management.

Results: A total of 200 medical records were reviewed; 110 (55%) were for male patients and 90 (45%) were for female patients, with a mean (range) age of 60 (18-96) years. The most common pre-EEG diagnoses were altered mental status (52 [26%]) and seizure (48 [24%]). Of all EEGs, 115 (57.5%) had findings that were normal, 83 (41.5%) had findings that were abnormal, and 2 (1%) had findings that were uninterpretable. No EEGs had findings that resulted in a change in diagnosis or management, 8 EEGs (4%) had findings that supported clinical decision making and resulted in no change in diagnosis or management, and 192 EEGs (96%) had findings that did not contribute to diagnosis or management.

Conclusion: In this study, inpatient EEGs rarely contributed to clinical decision making and in no case resulted in a change in diagnosis or management. These findings warrant future research on the effectiveness of inpatient EEGs for a wide breadth of clinical inpatient diagnoses.

Continuous electroencephalography monitoring for early prediction of neurological outcome in postanoxic patients after cardiac arrest: a prospective cohort study

OBJECTIVE

To evaluate the value of continuous electroencephalography in early prognostication in patients treated with hypothermia after cardiac arrest.

DESIGN

Prospective cohort study.

SETTING

Medical intensive care unit.

PATIENTS

Sixty patients admitted to the intensive care unit for therapeutic hypothermia after cardiac arrest.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

In all patients, continuous electroencephalogram and daily somatosensory evoked potentials were recorded during the first 5 days of admission or until intensive care unit discharge. Neurological outcomes were based on each patient's best achieved Cerebral Performance Category score within 6 months. Twenty-seven of 56 patients (48%) achieved good neurological outcome (Cerebral Performance Category score 1-2).At 12 hrs after resuscitation, 43% of the patients with good neurological outcome showed continuous, diffuse slow electroencephalogram rhythms, whereas this was never observed in patients with poor outcome.The sensitivity for predicting poor neurological outcome of low-voltage and isoelectric electroencephalogram patterns 24 hrs after resuscitation was 40% (95% confidence interval 19%-64%) with a 100% specificity (confidence interval 86%-100%), whereas the sensitivity and specificity of absent somatosensory evoked potential responses during the first 24 hrs were 24% (confidence interval 10%-44%) and 100% (confidence interval: 87%-100%), respectively. The negative predictive value for poor outcome of low-voltage and isoelectric electroencephalogram patterns was 68% (confidence interval 50%-81%) compared to 55% (confidence interval 40%-60%) for bilateral somatosensory evoked potential absence, both with a positive predictive value of 100% (confidence interval 63%-100% and 59%-100% respectively). Burst-suppression patterns after 24 hrs were also associated with poor neurological outcome, but not inevitably so.

CONCLUSIONS

In patients treated with hypothermia, electroencephalogram monitoring during the first 24 hrs after resuscitation can contribute to the prediction of both good and poor neurological outcome. Continuous patterns within 12 hrs predicted good outcome. Isoelectric or low-voltage electroencephalograms after 24 hrs predicted poor outcome with a sensitivity almost two times larger than bilateral absent somatosensory evoked potential responses.

Ischemic cerebral damage: an appraisal of synaptic failure

In the human brain, ≈30% of the energy is spent on synaptic transmission. Disappearance of synaptic activity is the earliest consequence of cerebral ischemia. The changes of synaptic function are generally assumed to be reversible and persistent damage is associated with membrane failure and neuronal death. However, there is overwhelming experimental evidence of isolated, but persistent, synaptic failure resulting from mild or moderate cerebral ischemia. Early failure results from presynaptic damage with impaired transmitter release. Proposed mechanisms include dysfunction of adenosine triphosphate-dependent calcium channels and a disturbed docking of glutamate-containing vesicles resulting from impaired phosphorylation. We review energy distribution among neuronal functions, focusing on energy usage of synaptic transmission. We summarize the effect of ischemia on neurotransmission and the evidence of long-lasting synaptic failure as a cause of persistent symptoms in patients with cerebral ischemia. Finally, we discuss the implications of synaptic failure in the diagnosis of cerebral ischemia, including the limited sensitivity of diffusion-weighted MRI in those cases in which damage is presumably limited to the synapses.

Neural dynamics during anoxia and the "wave of death"

Recent experiments in rats have shown the occurrence of a high amplitude slow brain wave in the EEG approximately 1 minute after decapitation, with a duration of 5-15 s (van Rijn et al, PLoS One 6, e16514, 2011) that was presumed to signify the death of brain neurons. We present a computational model of a single neuron and its intra- and extracellular ion concentrations, which shows the physiological mechanism for this observation. The wave is caused by membrane potential oscillations, that occur after the cessation of activity of the sodium-potassium pumps has lead to an excess of extracellular potassium. These oscillations can be described by the Hodgkin-Huxley equations for the sodium and potassium channels, and result in a sudden change in mean membrane voltage. In combination with a high-pass filter, this sudden depolarization leads to a wave in the EEG. We discuss that this process is not necessarily irreversible.