Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management

Duez, Christophe Henri Valdemar; Johnsen, Birger; Ebbesen, Mads Qvist; Kvaløy, Marie Bu; Grejs, Anders Morten; Jeppesen, Anni Nørgaard; Søreide, Eldar; Nielsen, Jørgen Feldbæk; Kirkegaard, Hans

doi:10.1016/j.resuscitation.2018.10.035

Cited by 35 publications

(35 citation statements)

References 23 publications

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“…For those 28 patients, 16 (57%) patients underwent EEG examination after 24 h following ROSC. These results are supported by a recent study from Duez et al [25]. They found no differences between prognostication at 24 h compared to 48 h, measured via the specificity and sensitivity of EEG categories, but when using EEG reactivity, prognostication was the best at 24 h compared to 48 h [25].…”

Section: The Prognostic Value Of Background Eeg Frequencysupporting

confidence: 65%

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

Kim

Koo

et al. 2020

JCM

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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.

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Section: The Prognostic Value Of Background Eeg Frequencysupporting

confidence: 65%

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

Kim

Koo

et al. 2020

JCM

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“…The accuracy of these patterns is reported in Table 45. The FPR of malignant patterns was generally higher and less consistent than that of highly malignant patterns, ranging from 0% [54,72] to 51.8% [57].…”

Section: Combinations Of Unfavourable Eeg Features (Tables 44 45)mentioning

confidence: 89%

“…The corresponding features included a discontinuous or unreactive background, a reversed antero-posterior gradient, alpha coma, periodic or rhythmic patterns, or discharges not associated with suppressed background, and seizures. However, some studies included features described as highly malignant in other studies, such as suppression [61,101], low voltage [52,57,72,90], and burst suppression [57,61,101]. The accuracy of these patterns is reported in Table 45.…”

Section: Combinations Of Unfavourable Eeg Features (Tables 44 45)mentioning

confidence: 99%

“…"Highly epileptiform bursts" is a standard ACNS term (ESM Table E4), while "identical bursts" and "heterogeneous" or "synchronous" characteristics of burst suppression are not. Burst suppression with identical bursts has been assessed as part of combined, "highly malignant" EEG patterns after cardiac arrest (see below) both by the same group of investigators who initially defined it [90,98] and by others [57], always showing 0% FPR from 24 to 72 h after ROSC. A consistent decrease in the prevalence of burst suppression with time after ROSC was observed for both synchronous and heterogeneous burst suppression [68] in patients with poor neurological outcome (Tables 27, 28, 29; see also ESM Fig.…”

Section: Eeg Background Continuity and Voltagementioning

confidence: 99%

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

et al. 2020

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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

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“…A patient not fulfilling the Step-2-criteria should be re-examined after ≥ 24 h. If GCS-M is still ≤ 2, Step 3 of the algorithm states that outcome will be “likely poor” if there are ≥ 2 pathological findings of the following: “high” serum neuron-specific enolase (NSE) according to locally established cut-off values, unreactive burst-suppression or unreactive status epilepticus on electroencephalography (EEG), generalized oedema on head computed tomography (CT) ≤ 24 h post-arrest or on magnetic resonance imaging (MRI) or early (≤ 48 h) status myoclonus. Since the publication of the ERC/ESICM guidelines, a standardized classification of post-arrest EEG patterns has been suggested [ 3 – 6 ] and two large studies on serum NSE levels have been published [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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 cutoff 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.

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Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management

Cited by 35 publications

References 23 publications

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

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

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

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

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Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management

Cited by 35 publications

References 23 publications

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

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

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

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

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Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management