| 1. |
- Cronberg, Tobias, et al.
(author)
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Neurological prognostication after cardiac arrest : Recommendations from the Swedish Resuscitation Council
- 2013
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In: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 84:7, s. 867-872
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Journal article (peer-reviewed)abstract
- Cardiopulmonary resuscitation is started in 5000 victims of out-of-hospital cardiac arrest in Sweden each year and the survival rate is approximately 10%. The subsequent development of a global ischaemic brain injury is the major determinant of the neurological prognosis for those patients who reach the hospital alive. Induced hypothermia is a recommended treatment after cardiac arrest and has been implemented in most Swedish hospitals.Recent studies indicate that induced hypothermia may affect neurological prognostication and previous international recommendations are therefore no longer valid when hypothermia is applied. An expert group from the Swedish Resuscitation Council has reviewed the literature and made recommendations taking into account the effects of induced hypothermia and concomitant sedation.A delayed neurological evaluation at 72h after rewarming is recommended for hypothermia treated patients. This evaluation should be based on several independent methods and the possibility of lingering pharmacological effects should be considered.
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| 2. |
- Cronberg, Tobias, et al.
(author)
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Neuron-specific enolase correlates with other prognostic markers after cardiac arrest.
- 2011
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In: Neurology. - 1526-632X. ; 77:7, s. 623-630
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Journal article (peer-reviewed)abstract
- OBJECTIVE: Therapeutic hypothermia (TH) is a recommended treatment for survivors of cardiac arrest. Prognostication is complicated since sedation and muscle relaxation are used and established indicators of a poor prognosis are lacking. This prospective, observational study describes the pattern of commonly used prognostic markers in a hypothermia-treated cohort of cardiac arrest patients with prolonged coma. METHODS: Among 111 consecutive patients, 19 died, 58 recovered, and 34 were in coma 3 days after normothermia (4.5 days after cardiac arrest), defined as prolonged coma. All patients were monitored with continuous amplitude-integrated EEG and repeated samples of neuron-specific enolase (NSE) were collected. In patients with prolonged coma, somatosensory evoked potentials (SSEP) and brain MRI were performed. A postmortem brain investigation was undertaken in patients who died. RESULTS: Six of the 17 patients (35%) with NSE levels <33 μg/L at 48 hours regained the capacity to obey verbal commands. By contrast, all 17 patients with NSE levels >33 failed to recover consciousness. In the >33 NSE group, all 10 studied with MRI had extensive brain injury on diffusion-weighted images, 12/16 lacked cortical responses on SSEP, and all 6 who underwent autopsy had extensive severe histologic damage. NSE levels also correlated with EEG pattern, but less uniformly, since 11/17 with NSE <33 had an electrographic status epilepticus (ESE), only one of whom recovered. A continuous EEG pattern correlated to NSE <33 and awakening. CONCLUSIONS: NSE correlates well with other markers of ischemic brain injury. In patients with no other signs of brain injury, postanoxic ESE may explain a poor outcome.
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| 5. |
- Friberg, Hans, et al.
(author)
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Clinical review: Continuous and simplified electroencephalography to monitor brain recovery after cardiac arrest.
- 2013
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In: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535. ; 17:4
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Research review (peer-reviewed)abstract
- There has been a dramatic change in hospital care of cardiac arrest survivors in recent years, including the use of target temperature management (hypothermia). Clinical signs of recovery or deterioration, which previously could be observed, are now concealed by sedation, analgesia, and muscle paralysis. Seizures are common after cardiac arrest, but few centers can offer high-quality electroencephalography (EEG) monitoring around the clock. This is due primarily to its complexity and lack of resources but also to uncertainty regarding the clinical value of monitoring EEG and of treating post-ischemic electrographic seizures. Thanks to technical advances in recent years, EEG monitoring has become more available. Large amounts of EEG data can be linked within a hospital or between neighboring hospitals for expert opinion. Continuous EEG (cEEG) monitoring provides dynamic information and can be used to assess the evolution of EEG patterns and to detect seizures. cEEG can be made more simple by reducing the number of electrodes and by adding trend analysis to the original EEG curves. In our version of simplified cEEG, we combine a reduced montage, displaying two channels of the original EEG, with amplitude-integrated EEG trend curves (aEEG). This is a convenient method to monitor cerebral function in comatose patients after cardiac arrest but has yet to be validated against the gold standard, a multichannel cEEG. We recently proposed a simplified system for interpreting EEG rhythms after cardiac arrest, defining four major EEG patterns. In this topical review, we will discuss cEEG to monitor brain function after cardiac arrest in general and how a simplified cEEG, with a reduced number of electrodes and trend analysis, may facilitate and improve care.
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| 6. |
- Rundgren, Malin, et al.
(author)
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Amplitude-integrated EEG (aEEG) predicts outcome after cardiac arrest and induced hypothermia.
- 2006
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In: Intensive Care Medicine. - : Springer Science and Business Media LLC. - 0342-4642 .- 1432-1238. ; 32:6, s. 836-842
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Journal article (peer-reviewed)abstract
- Objective To evaluate the use of continuous amplitude-integrated EEG (aEEG) as a prognostic tool for survival and neurological outcome in cardiac arrest patients treated with hypothermia. Design Prospective, observational study. Setting Multidisciplinary intensive care unit in a university hospital. Intervention Comatose survivors of cardiac arrest were treated with induced hypothermia for 24 h. An aEEG recording was initiated upon arrival at the ICU and continued until the patient regained consciousness or, if the patient remained in coma, no longer than 120 h. The aEEG recording was not available to the ICU physician, and the aEEG tracings were interpreted by a neurophysiologist with no knowledge of the patient's clinical status. Only clinically visible seizures were treated. Measurements and results Thirty-four consecutive hypothermia-treated cardiac arrest survivors were included. At normothermia (mean 37 h after cardiac arrest), the aEEG pattern was discriminative for outcome. All 20 patients with a continuous aEEG at this time regained consciousness, whereas 14 patients with pathological aEEG patterns (flat, suppression-burst or status epilepticus) did not regain consciousness and died in hospital. Patients were evaluated neurologically upon discharge from the ICU and after 6 months, using the Cerebral Performance Category (CPC) scale. Eighteen patients were alive with a good cerebral outcome (CPC 1--2) at 6-month follow-up. Conclusion A continuous aEEG pattern at the time of normothermia was discriminative for regaining consciousness. aEEG is an easily applied method in the ICU setting.
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| 7. |
- Rundgren, Malin, et al.
(author)
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Continuous amplitude-integrated electroencephalogram predicts outcome in hypothermia-treated cardiac arrest patients.
- 2010
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In: Critical Care Medicine. - 1530-0293. ; Jul 1, s. 1838-1844
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Journal article (peer-reviewed)abstract
- OBJECTIVE:: To assess the prognostic value of continuous amplitude-integrated electroencephalogram in comatose survivors after cardiac arrest and treated with hypothermia. DESIGN:: Prospective observational study. SETTING:: General intensive care unit at a university hospital. PATIENTS:: Comatose patients after cardiac arrest and treated with hypothermia. INTERVENTIONS:: Patients were sedated and continuously monitored using an amplitude-integrated electroencephalogram. Monitoring was commenced on arrival in the intensive care unit and continued until recovery of consciousness, death, or 120 hrs after cardiac arrest. The amplitude-integrated electroencephalogram was interpreted together with the original electroencephalogram and analyzed without knowledge of the patient's clinical status. The amplitude-integrated electroencephalogram patterns at start of registration and at normothermia and the transitions of the amplitude-integrated electroencephalogram patterns over time were correlated to outcome. MEASUREMENTS AND MAIN RESULTS:: A total of 111 consecutive patients were assessed; 11 patients were not included because of technical reasons and five were excluded because of death before normothermia. Ninety-five patients remained; 57 (60%) eventually regained consciousness, of whom 49 (52%) lived an independent life at 6 months. Thirty-one patients (33%) at start of registration and 62 patients (65%) at normothermia had a continuous electroencephalogram pattern, and this was strongly associated with recovery of consciousness (29/31 [90%] and 54/62 [87%]). A suppression-burst pattern was always transient and patients with suppression-burst at any time remained in coma until death. An initial flat pattern was registered in 47 patients, but this had no prognostic value. Electrographic status epilepticus was a common finding (26/95 patients [27%]) and two types of electrographic status epilepticus were identified: one developed from suppression-burst and one developed from a continuous background. Two patients from the latter group regained consciousness. CONCLUSIONS:: Continuous amplitude-integrated electroencephalogram adds valuable early positive and negative prognostic information in comatose survivors after cardiac arrest. We identified two types of postanoxic electrographic status epilepticus, which is a novel finding with possible therapeutic implications.
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| 8. |
- 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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| 9. |
- Westhall, Erik, et al.
(author)
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Interrater variability of EEG interpretation in comatose cardiac arrest patients.
- 2015
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In: Clinical Neurophysiology. - : Elsevier BV. - 1872-8952 .- 1388-2457. ; 126:12, s. 2397-2404
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Journal article (peer-reviewed)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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| 10. |
- Westhall, Erik, et al.
(author)
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Standardized EEG interpretation accurately predicts prognosis after cardiac arrest
- 2016
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In: Neurology. - 0028-3878. ; 86:16, s. 1482-1490
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Journal article (peer-reviewed)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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