Electroencephalogram Predicts Outcome in Patients With Postanoxic Coma During Mild Therapeutic Hypothermia*

Tjepkema-Cloostermans, Marleen C.; Hofmeijer, Jeannette; Trof, Ronald J.; Blans, Michiel J.; Beishuizen, Albertus; Putten, Michel Johannes Antonius Maria van

doi:10.1097/ccm.0000000000000626

Cited by 82 publications

(104 citation statements)

References 39 publications

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“…This is explained by an evolution of the EEG toward less specific patterns beyond 24 hours. The results of this study are partly in accordance with our own 3,4,19 and other 9,15-17,23,24 previous reports. However, current predictive values are higher, without false positives for unfavorable EEG patterns at 24 hours for poor outcome prediction.…”

supporting

confidence: 83%

“…1,2 Early identification of patients without potential for recovery of brain function may prevent inappropriate continuation of medical treatment. [3][4][5][6][7][8][9][10][11][12][13] A bilaterally absent somatosensory evoked potential (SSEP) is currently the most reliable predictor of poor outcome, but its sensitivity to detect poor outcome is low. 10,14 Pathologic EEG patterns, such as burst-suppression and epileptiform patterns, have been associated with poor outcome, but not invariably so.…”

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confidence: 99%

“…Part of the EEG results from the first 148 patients was reported previously. 4 Standard protocol approvals, registrations, and patient consents. The Medical Ethical Committee Twente approved the protocol and waived the need for informed consent for EEG monitoring and clinical follow-up.…”

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confidence: 99%

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Early EEG contributes to multimodal outcome prediction of postanoxic coma

Sethi¹,

Lattanzi²,

Hofmeijer³

et al. 2016

Neurology

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Objectives: Early identification of potential recovery of postanoxic coma is a major challenge. We studied the additional predictive value of EEG.Methods: Two hundred seventy-seven consecutive comatose patients after cardiac arrest were included in a prospective cohort study on 2 intensive care units. Continuous EEG was measured during the first 3 days. EEGs were classified as unfavorable (isoelectric, low-voltage, burst-suppression with identical bursts), intermediate, or favorable (continuous patterns), at 12, 24, 48, and 72 hours. Outcome was dichotomized as good or poor. Resuscitation, demographic, clinical, somatosensory evoked potential, and EEG measures were related to outcome at 6 months using logistic regression analysis. Analyses of diagnostic accuracy included receiver operating characteristics and calculation of predictive values.Results: Poor outcome occurred in 149 patients (54%). Single measures unequivocally predicting poor outcome were an unfavorable EEG pattern at 24 hours, absent pupillary light responses at 48 hours, and absent somatosensory evoked potentials at 72 hours. Together, these had a specificity of 100% and a sensitivity of 50%. For the remaining 203 patients, who were still in the "gray zone" at 72 hours, a predictive model including unfavorable EEG patterns at 12 hours, absent or extensor motor response to pain at 72 hours, and higher age had an area under the curve of 0.90 (95% confidence interval 0.84-0.96). Favorable EEG patterns at 12 hours were strongly associated with good outcome. EEG beyond 24 hours had no additional predictive value.Conclusions: EEG within 24 hours is a robust contributor to prediction of poor or good outcome of comatose patients after cardiac arrest. Neurology ® 2015;85:137-143 GLOSSARY CI 5 confidence interval; CPC 5 Cerebral Performance Category; GPD 5 generalized periodic discharge; ICU 5 intensive care unit; OR 5 odds ratio; SSEP 5 somatosensory evoked potential.Of patients who remain comatose after cardiac arrest, 40% to 66% never regain consciousness.

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confidence: 99%

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Early EEG contributes to multimodal outcome prediction of postanoxic coma

Sethi¹,

Lattanzi²,

Hofmeijer³

et al. 2016

Neurology

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“…The primary goal was to explore if infraslow activity was present in patients with a postanoxic encephalopathy and to further our understanding of burst clusters in patients with burst-suppression with identical bursts. At present, EEG features as reactivity, amplitude, continuity, dominant frequency, and characteristics of the burstsuppression patterns have shown to be strongly predictive of outcome in patients with postanoxic encephalopathy (Cloostermans et al 2012;Hofmeijer et al 2014b;Rossetti et al 2010;Tjepkema-Cloostermans et al 2015). Although amplitudes of the infraslow activity larger than 35 V or a MI Ͼ 0.016 were always associated with poor outcome, we did not explore if these features have additional diagnostic value; this will be the topic of a future study.…”

Section: Discussionmentioning

confidence: 99%

“…Previously, we have shown that in these patients irreversible brain damage is associated with persistent isoelectric or severely depressed EEG activity (Cloostermans et al 2012;Tjepkema-Cloostermans et al 2015). In some patients, isoelectric recordings were interpuncted with stereotypical bursts, resulting in "burst-suppression with identical bursts" (Hofmeijer et al 2014b), that may appear in clusters.…”

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Infraslow EEG activity modulates cortical excitability in postanoxic encephalopathy

Putten

Tjepkema-Cloostermans

Hofmeijer

2015

Journal of Neurophysiology

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van Putten MJAM, Tjepkema-Cloostermans MC, Hofmeijer J. Infraslow EEG activity modulates cortical excitability in postanoxic encephalopathy. J Neurophysiol 113: 3256 -3267, 2015. First published February 18, 2015 doi:10.1152/jn.00714.2014.-Infraslow activity represents an important component of physiological and pathological brain function. We study infraslow activity (Ͻ0.1 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 V) 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. infraslow fluctuations; EEG; postanoxic coma; burst-suppression CLINICAL EEG TYPICALLY RECORDS signals in the 0.1-70 Hz frequency range. However, brain rhythms include activity below 0

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Sensitivity of Continuous Electroencephalography to Detect Ictal Activity After Cardiac Arrest

et al. 2020

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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 postcardiac arrest outcome prediction. DESIGN, SETTING, AND PARTICIPANTSThis 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 MEASURESEpileptiform EEG patterns associated with neurological outcome at hospital discharge, such as seizures likely to cause secondary injury. RESULTSOverall, 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 RELEVANCECompared 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.

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Electroencephalogram Predicts Outcome in Patients With Postanoxic Coma During Mild Therapeutic Hypothermia*

Abstract: Electroencephalogram allows reliable prediction of both good and poor neurologic outcome of patients with postanoxic encephalopathy treated with mild therapeutic hypothermia within 24 hours after cardiac arrest.

Cited by 82 publications

References 39 publications

Early EEG contributes to multimodal outcome prediction of postanoxic coma

Early EEG contributes to multimodal outcome prediction of postanoxic coma

Infraslow EEG activity modulates cortical excitability in postanoxic encephalopathy

Sensitivity of Continuous Electroencephalography to Detect Ictal Activity After Cardiac Arrest

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