| 1. |
- Westhall, Erik, et al.
(författare)
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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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Ingår i: BMC Neurology. - : Springer Science and Business Media LLC. - 1471-2377. ; 14
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Westhall, Erik, et al.
(författare)
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Interrater agreement of EEG interpretation in comatose post cardiac arrest patients
- 2015
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Ingår i: Clinical Neurophysiology. - : Elsevier BV. - 1388-2457. ; 126:8, s. 171-171
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Konferensbidrag (refereegranskat)abstract
- Question: What is the interrater agreement of EEG interpretation in adult comatose post cardiac arrest patients using the American Clinical Neurophysiology Society (ACNS) standardized critical care EEG terminology? Methods: The EEG-data were obtained from patients included in the Target Temperature Management trial (TTM), an international, multicenter, clinical trial of temperature management in comatose cardiac arrest patients [N Engl J Med 2013]. In the TTM trial a routine EEG was performed in patients still comatose 12-36. h after rewarming.For this study, one EEG-specialist (IR) chose 20 EEGs, covering important aspects of the ACNS EEG terminology. Four EEG-specialists with different nationalities (Sweden: EW, Denmark: TWK, The Netherlands: AFvR and Switzerland: AOR) acquired the ACNS EEG terminology [J Clin Neurophys 2013;30:1-27] and studied a web-based training-module. The four EEG-specialists subsequently interpreted (blinded to patients' identity) the 20 EEGs, reporting the findings according to the ACNS EEG terminology. Percent agreement and Fleiss kappa values for every category in the terminology were calculated. Percent agreement was defined as the proportion of the 20 EEGs in which all interpreters reported identical findings. Results: There was 65% agreement on whether a rhythmic or periodic pattern was present or not (Kappa 0.44). If a rhythmic or periodic pattern was present there was 93% agreement on which type of pattern (periodic discharges, rhythmic delta activity, rhythmic spike-and-wave/polyspike-and-wave/sharp-and-slow-wave) (Kappa 0.65). Conclusions: Using the ACNS EEG terminology in adult comatose post cardiac arrest patients there was moderate agreement on the presence and type of periodic and rhythmic patterns.
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| 3. |
- Westhall, Erik, et al.
(författare)
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Interrater variability of EEG interpretation in comatose cardiac arrest patients.
- 2015
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Ingår i: Clinical Neurophysiology. - : Elsevier BV. - 1872-8952 .- 1388-2457. ; 126:12, s. 2397-2404
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Tidskriftsartikel (refereegranskat)abstract
- EEG is widely used to predict outcome in comatose cardiac arrest patients, but its value has been limited by lack of a uniform classification. We used the EEG terminology proposed by the American Clinical Neurophysiology Society (ACNS) to assess interrater variability in a cohort of cardiac arrest patients included in the Target Temperature Management trial. The main objective was to evaluate if malignant EEG-patterns could reliably be identified.
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| 4. |
- Westhall, Erik, et al.
(författare)
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Standardized EEG interpretation accurately predicts prognosis after cardiac arrest
- 2016
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Ingår i: Neurology. - 0028-3878. ; 86:16, s. 1482-1490
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3-5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p <0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome.
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