Continuous amplitude-integrated electroencephalogram predicts outcome in hypothermia-treated cardiac arrest patients

Rundgren, Malin; Westhall, Erik; Cronberg, Tobias; Rosén, Ingmar; Friberg, Hans

doi:10.1097/ccm.0b013e3181eaa1e7

Cited by 250 publications

(237 citation statements)

References 35 publications

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“…Conversely, normal voltage ([20 lV) at any time is related to a good outcome in 71 % of patients, confirming earlier data along the same lines [6]. Considering the delicacy in reliably deciding upon a voltage amplitude around 20 lV in some patients [7], other groups concentrated rather on background reactivity to stimuli, which if present during TH has been reported to herald good prognosis in as much as 86 % [8], while lack of reactivity portended a poor prognosis in a much higher rate (99 % in [9]).…”

supporting

confidence: 80%

“…They reviewed all EEG recordings in the form of 5-min extracts taken at predefined intervals from the acute event (6,12,24,48, and 72 h). Blinded to patients' identity and outcome, they applied the recently published standardized American Clinical Neurophysiology Society (ACNS) critical care EEG terminology [4], correlating their data with those of other clinical investigations.…”

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confidence: 99%

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EEG for outcome prediction after cardiac arrest: when the quest for optimization needs standardization

Rossetti

2015

Intensive Care Med

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Early outcome prognostication of comatose patients following cardiac arrest represents a daunting task; several clinical, biochemical, radiological, and neurophysiological parameters have been intensively evaluated recently, in the context of growing popularity of targeted temperature management or therapeutic hypothermia (TH) in the last decade [1,2]. Among these potential predictors, EEG represents a relatively cheap, noninvasive tool available at the bedside, but the assessment of its exact role has to deal with the influence of timing, lingering pharmacological sedation, temperature, and not least the expertise of interpreters and the sometimes confusing taxonomy of the findings.In this issue, Dr. Sivaraju and colleagues report their effort to assess the prognostic significance of continuous EEG (cEEG) data in 100 patients treated with TH at 32-34°C [3]. They reviewed all EEG recordings in the form of 5-min extracts taken at predefined intervals from the acute event (6, 12, 24, 48, and 72 h). Blinded to patients' identity and outcome, they applied the recently published standardized American Clinical Neurophysiology Society (ACNS) critical care EEG terminology [4], correlating their data with those of other clinical investigations.The principal findings are that suppression-burst at any time (but not a discontinuous recording), and a low voltage (\20 lV) background after 24 h, have a false positive rate of 0 % for poor prognosis, defined as a Glasgow outcome scale (GOS) of 1-3 at hospital discharge, suggesting that in this cohort assessment at 24 h heralds the best prognostic value, despite the probable concomitant use of sedation (mostly midazolam, further details not given) and TH. As the authors acknowledge, other groups have reported different results regarding the temporal dynamics of evolution of the cEEG [5]; furthermore, the ACNS terminology puts a threshold between suppression-burst and discontinuous background at 50 % of relative suppression, which could prove tricky to label with certainty in specific borderline situations (in other words: EEG signals represent a continuous, not a discrete variable).Conversely, normal voltage ([20 lV) at any time is related to a good outcome in 71 % of patients, confirming earlier data along the same lines [6]. Considering the delicacy in reliably deciding upon a voltage amplitude around 20 lV in some patients [7], other groups concentrated rather on background reactivity to stimuli, which if present during TH has been reported to herald good prognosis in as much as 86 % [8], while lack of reactivity portended a poor prognosis in a much higher rate (99 % in [9]). This last figure contrasts with a predictive value of 86 % in this study (it was, however, not indicated when reactivity was assessed), pinpointing the lack of standardization of its testing (in this series with auditory and peripheral painful stimuli; in the aforementioned papers applying also vigorous pressure to the nipples) and its scoring [7,10]. In the same context, identical bursts, recently report...

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confidence: 99%

EEG for outcome prediction after cardiac arrest: when the quest for optimization needs standardization

Rossetti

2015

Intensive Care Med

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“…Rewarming is a common time for seizures to occur, either because a clinical motoric component (e.g., myoclonic status epilepticus) is revealed after discontinuation of paralytics [34,35], or because sedation or hypothermia suppressed or treated the electrographic activity [35]. In addition to detecting seizures, EEG demonstration of a reactive background rhythm or a continuous pattern on amplitude-integrated EEG had a high likelihood of good neurological prognosis, despite the presence of seizures [36][37][38]. Although myoclonic status may have a worse prognosis than nonconvulsive status epileptic in the setting of cardiac arrest treated with hypothermia, myoclonic status is not homogeneous and may have a worse prognosis when "reticular" rather than when associated with an EEG correlate [39].…”

Section: Patient Selectionmentioning

confidence: 99%

The Utility of EEG, SSEP, and Other Neurophysiologic Tools to Guide Neurocritical Care

Rosenthal

2012

Neurotherapeutics

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Neuromonitoring is an emerging field that aims to characterize real-time neurophysiology to tailor therapy for acute injuries of the central nervous system. While cardiac telemetry has been used for decades among patients requiring critical care of all kinds, neurophysiology and neurotelemetry has only recently emerged as a routine screening tool in comatose patients. The increasing utilization of electroencephalography in comatose patients is primarily due to the recognition of the common occurrence of nonconvulsive seizures among comatose patients, the development of quantitative measures to detect regional ischemia, and the appreciation of electroencephalography phenotypes that indicate prognosis after cardiac arrest. Other neuromonitoring tools, such as somatosensory evoked potentials have a complementary role, surveying the integrity of the neuroaxis as an indicator of prognosis or illness progression in both acute brain and spinal injuries.

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“…However, another recent study on EEG reactivity between 1 and 3 days after the anoxic event had a specificity of only 94% for predicting poor outcome (5). Furthermore, in the literature burst suppression on EEG is reported to have a specificity between 85 and 100% (4, 6, 7) and post-anoxic status epilepticus on EEG had a specificity of 98% for poor outcome (6). In a recent study, low-voltage and isoelectric EEG patterns were shown to be invariably associated with poor neurological outcome 24 h after the event in patients treated with MTH and sedation with a sensitivity of 40% and a specificity of 100%, while bilaterally absent cortical SSEP had a sensitivity of only 24% after 24 h in this study (7).…”

Section: Introductionmentioning

confidence: 99%

Small-world characteristics of EEG patterns in post-anoxic encephalopathy

Beudel

Cloostermans

Boersma

et al. 2013

Journal of the Neurological Sciences

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Post-anoxic encephalopathy (PAE) has a heterogenous outcome which is difficult to predict. At present, it is possible to predict poor outcome using somatosensory evoked potentials in only a minority of the patients at an early stage. In addition, it remains difficult to predict good outcome at an early stage. Network architecture, as can be quantified with continuous electroencephalography (cEEG), may serve as a candidate measure for predicting neurological outcome. Here, we explore whether cEEG monitoring can be used to detect the integrity of neural network architecture in patients with PAE after cardiac arrest. From 56 patients with PAE treated with mild therapeutic hypothermia, 19-channel cEEG data were recorded starting as soon as possible after cardiac arrest. Adjacency matrices of shared frequencies between 1 and 25 Hz of the EEG channels were obtained using Fourier transformations. Number of network nodes and connections, clustering coefficient (C), average path length (L), and small-world index (SWI) were derived. Outcome was quantified by the best cerebral performance category (CPC)-score within 6 months. Compared to nonsurvivors, survivors showed significantly more nodes and connections. L was significantly higher and C and SWI were significantly lower in the survivor group than in the non-survivor group. The number of nodes, connections, and the L were negatively correlated with the CPC-score. C and SWI correlated positively with the CPC-score. The combination of number of nodes, connections, C, and L showed the most significant difference and correlation between survivors and non-survivors and CPC-score. Our data might implicate that nonsurvivors have insufficient distribution and differentiation of neural activity for regaining normal brain function. These network differences, already present during hypothermia, might be further developed as early prognostic markers. The predictive values are however still inferior to current practice parameters.

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Continuous amplitude-integrated electroencephalogram predicts outcome in hypothermia-treated cardiac arrest patients

Cited by 250 publications

References 35 publications

EEG for outcome prediction after cardiac arrest: when the quest for optimization needs standardization

EEG for outcome prediction after cardiac arrest: when the quest for optimization needs standardization

The Utility of EEG, SSEP, and Other Neurophysiologic Tools to Guide Neurocritical Care

Small-world characteristics of EEG patterns in post-anoxic encephalopathy

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