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- Sandroni, Claudio, et al.
(author)
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Prognostication in comatose survivors of cardiac arrest: An advisory statement from the European Resuscitation Council and the European Society of Intensive Care Medicine
- 2014
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In: Intensive Care Medicine. - : Springer Science and Business Media LLC. - 0342-4642 .- 1432-1238. ; 40:12, s. 1816-1831
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Journal article (peer-reviewed)abstract
- To review and update the evidence on predictors of poor outcome (death, persistent vegetative state or severe neurological disability) in adult comatose survivors of cardiac arrest, either treated or not treated with controlled temperature, to identify knowledge gaps and to suggest a reliable prognostication strategy. GRADE-based systematic review followed by expert consensus achieved using Web-based Delphi methodology, conference calls and face-to-face meetings. Predictors based on clinical examination, electrophysiology, biomarkers and imaging were included. Evidence from a total of 73 studies was reviewed. The quality of evidence was low or very low for almost all studies. In patients who are comatose with absent or extensor motor response at a parts per thousand yen72 h from arrest, either treated or not treated with controlled temperature, bilateral absence of either pupillary and corneal reflexes or N20 wave of short-latency somatosensory evoked potentials were identified as the most robust predictors. Early status myoclonus, elevated values of neuron-specific enolase at 48-72 h from arrest, unreactive malignant EEG patterns after rewarming, and presence of diffuse signs of postanoxic injury on either computed tomography or magnetic resonance imaging were identified as useful but less robust predictors. Prolonged observation and repeated assessments should be considered when results of initial assessment are inconclusive. Although no specific combination of predictors is sufficiently supported by available evidence, a multimodal prognostication approach is recommended in all patients.
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- Westhall, Erik, et al.
(author)
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Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design
- 2014
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In: BMC Neurology. - : Springer Science and Business Media LLC. - 1471-2377. ; 14
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Journal article (peer-reviewed)abstract
- Background: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. In the Target Temperature Management (TTM) trial, a large international trial on temperature management after cardiac arrest, EEG-examinations were part of the prospective study design. The main objective of this study is to evaluate EEG-data from the TTM-trial and to identify malignant EEG-patterns reliably predicting a poor neurological outcome. Methods/Design: In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. After the end of the trial, the EEGs were retrieved to form a central EEG-database. The EEG-data will be analysed using the ACNS EEG terminology. We designed an electronic case record form (eCRF). Four EEG-specialists from different countries, blinded to patient outcome, will independently classify the EEGs and report through the eCRF. We will describe the prognostic values of pre-specified EEG patterns to predict poor as well as good outcome. We hypothesise three patterns to always be associated with a poor outcome (suppressed background without discharges, suppressed background with continuous periodic discharges and burst-suppression). Inter- and intra-rater variability and whether sedation or level of temperature affects the prognostic values will also be analyzed. Discussion: A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. The results of this study may help to validate the ACNS terminology for assessing post cardiac arrest EEGs and identify patterns that could reliably predict outcome.
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