Original Research

Continuous Electroencephalogram in Comatose Postcardiac Arrest Syndrome Patients Treated With Therapeutic Hypothermia: Outcome Prediction Study

Journal of Intensive Care Medicine 2015, Vol. 30(5) 292-296 ª The Author(s) 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0885066613517214 jic.sagepub.com

Farid Sadaka, MD1, Danielle Doerr, MD1, Jiggar Hindia, DO1, K. Philip Lee, MD1, and William Logan, MD1

Abstract Purpose: Therapeutic Hypothermia (TH) is the only therapeutic intervention proven to significantly improve survival and neurologic outcome in comatose postcardiac arrest patients and is now considered standard of care. When we discuss prognostication with regard to comatose survivors postcardiac arrest, we should look for tools that are both reliable and accurate and that achieve a false-positive rate (FPR) equal to or very closely approaching zero. Methods: We retrospectively reviewed data that were prospectively collected on all cardiac arrest patients admitted to our ICU. Continuous electroencephalogram (cEEG) monitoring was performed as part of our protocol for therapeutic hypothermia in comatose postcardiac arrest patients. The primary outcome measure was the best score on hospital discharge on the 5-point Glasgow-Pittsburgh cerebral performance category (CPC) scores. Results: A total of 58 patients were included in this study. Twenty five (43%) patients had a good neurologic outcome (CPC score of 1-2). Three (5.2%) patients had nonconvulsive status epilepticus, all of whom had poor outcome (CPC ¼ 5). Seventeen (29%) patients had burst suppression (BS); all had poor outcome. Both nonconvuslsive seizures (NCS) and BS had a specificity of 100% (95% confidence interval [CI], 84%-100%), positive predictive values of 100% (95% CI, 31%-100%), and 100% (95% CI, 77%-100%), respectively. Both NCS and BS had FPRs of zero (95% CI, 0.0-0.69, and 0.0-0.23, respectively). Conclusions: In comatose postcardiac arrest patients treated with hypothermia, EEG during the maintenance and rewarming phase of hypothermia can contribute to prediction of neurologic outcome. Pending large multicenter prospective studies evaluating the role of cEEG in prognostication, our study adds to the existing evidence that cEEG can play a potential role in prediction of outcome in postcardiac arrest patients treated with hypothermia. Keywords coma, cardiac arrest, prognostication, EEG, electroencephalogram, continuous EEG, therapeutic hypothermia

Introduction In the era before therapeutic hypothermia (TH) was recommended and used as a therapeutic modality for out-ofhospital cardiac arrest (OHCA) patients, reported data suggest in-hospital mortality exceeded 58%.1-6 Mortality after a sudden and unexpected cardiac arrest (CA) is high, and the chance of survival to hospital discharge has, until recently, remained unchanged.7-8 In 1 report, OHCA in the United States has a mortality rate greater than 90% that results in more than 300 000 deaths per year.9 Those who survive the devastating event often retain a hypoxic brain injury and a permanently incapacitating neurologic deficit.9 In studies of patients who survived to ICU admission but subsequently died in the hospital, brain injury was the cause of death in 68% after out-of-hospital cardiac arrest and in 23% after in-hospital cardiac arrest.10,11 Therapeutic hypothermia is the only therapeutic intervention proven to significantly improve survival and neurologic outcome in

comatose ventricular fibrillation (VF) postcardiac arrest patients and is now considered standard of care. The new guidelines by European Resuscitation Council and the American Heart Association in 2010 recommend that comatose (ie, lack of meaningful response to verbal commands) adult patients with return of spontaneous circulation (ROSC) after out-of-hospital VF cardiac arrest should be cooled to 32 C to 34 C (89.6 F to 93.2 F) for 12 to 24 hours (Class I).12 Induced

1

Mercy Hospital St Louis; St Louis University, St. Louis, MO, USA

Received July 12, 2013, and in revised form October 8, 2013. Accepted for publication November 7, 2013. Corresponding Author: Farid Sadaka, Mercy Hospital St Louis; St Louis University, 621S. New Ballas Rd, suite 4006B, St. Louis, MO, 63141, USA. Email: [email protected]

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Table 1. Definitions of EEG Readings. NCS

Burst suppression severe background attenuation Epileptiform discharges Myoclonus

A range of conditions in which electrographic seizure activity is prolonged and results in nonconvulsive clinical symptoms. An EEG pattern in which high-voltage activity alternates with isoelectric quiescence. A reduction in background rhythm with no activity >2 mV in amplitude. Distinctive waves or complexes, distinguished from background activity, recorded in a proportion of patients with epilepsy. A brief, involuntary twitching of a muscle or a group of muscles.

Abbreviations: EEG, electroencephalogram; NCS, nonconvulsive status.

hypothermia may also be considered for comatose adult patients with ROSC after in-hospital cardiac arrest of any initial rhythm or after out-of-hospital cardiac arrest with an initial rhythm of pulseless electrical activity or asystole (Class IIb).12 When we discuss prognostication with regard to comatose survivors postcardiac arrest, we should look for tools that are both reliable and accurate. In order to help families determine how best to take care of their loved ones, it has been proven difficult to determine which patients will have fully functional outcomes, as this may takes weeks, months, or even years. What is more helpful is to provide families with information regarding situations where there is no chance of functional recovery with data that are fairly robust. With this type of situation, we are looking for studies and modalities that achieve a false-positive rate (FPR) equal to or very closely approaching zero.12 The frequency of seizures in postcardiac arrest patients is reported between 3% and 44%13-15 and they are associated with poor outcome.16 The 2006 American Academy of Neurology (AAN) guidelines stated that epileptiform complexes on a flat background, burst suppression (BS) pattern with generalized epileptiform activity/periodic, or generalized background suppression less than 20 uV, seen within 3 days of cardiac arrest, predicted poor outcome with an FPR of 3%.17 However, these guidelines were with respect to patients that had not undergone TH. We performed a retrospective cohort study to explore whether continuous electroencephalogram (cEEG) monitoring during therapeutic hypothermia for comatose cardiac arrest patients may serve as a predictor for neurological outcome.

Materials and Methods We retrospectively reviewed data that were prospectively collected on all cardiac arrest patients admitted to our ICU between January 2011 and July 2012. Our 16-bed Neuro-ICU is staffed by intensivists (board certified by the American Board of Internal Medicine in Internal Medicine and Critical Care Medicine and certified by the United Council of Neurologic Subspecialties in Neurocritical care) 24 hours/day. Electroencephalogram monitoring was performed as part of our protocol for TH in comatose postcardiac arrest patients. Since this is a retrospective review of data, our institutional review board waived need for written

informed consent. Consecutive adult patients (aged >18 yrs), who were resuscitated after a cardiac arrest, remained comatose, were admitted to the ICU and received TH were included. Exclusion criteria were history of seizures or epilepsy or other neurological injuries such as traumatic brain injury or any known history of severe neurological disorders. According to our protocol, comatose survivors are treated with TH regardless of the initial cardiac rhythm or the location of arrest (in-hospital or out-ofhospital). Hypothermia of 33 C was induced and maintained for 24 hours by intravenously administering 30 mL/kg of cold saline and using cooling pads. Afterward, patients were actively rewarmed at a rate of 0.25 to 0.33 C/hr to normothermia. According to our protocol, fentanyl and propofol or midazolam were used for sedation and against shivering until the body temperature had reached 36.5 C. Sedation was aimed at a level equivalent to a score of 4 (deep sedation) or 5 (unarousable) at the Richmond Agitation-Sedation Scale.18 On indication, a nondepolarizing muscle relaxant (rocuronium) was used intermittently to treat compensatory shivering.

Electroencephalogram Electroencephalogram recordings were started at some point during the maintenance phase of hypothermia and before rewarming phase was initiated and continued until patient attained normothermia, unless it was deemed necessary to continue monitoring such as in cases of seizures (epileptic or nonepileptic). Twenty-one silver–silverchloride cup electrodes were placed on the scalp according to the international 10–20 system. For practical reasons, EEG recordings were not started late at night. Instead, for patients admitted to the ICU after 11 PM, the recordings were started the next morning at 7 AM. All EEG analyses were performed by 2 board-certified neurologists (K.P.L, W.L.) at least twice per day and more frequently if asked by the treating neurointensivist. The neurologists were not consulted to partake of patient management or involved in neuroprognostication. However, the neurologists knew that this EEG was performed on postcardiac arrest patients on therapeutic hypothermia. The EEG data played minimal role in actual prognostication of outcome. However, the treating physicians were not completely blinded to the EEG to allow treatment of epileptiform discharges. Treatment of epileptiform discharges was left at the discretion of the treating physician. No doubt, a treating physician reading a report characterizing a poor EEG finding after cardiac arrest will be biased toward poor prognostication that may lead to self-fulfilling prophecies. However, in our institution, we do not factor EEG findings in neuroprognostication if possible. We rely on neurologic examination performed by the treating neurointensivist, and that is why prognostication is delayed till 96 hours after rewarming is achieved and patients are sedation free, in order to maximize the accuracy of the neurologic examination and minimize selffulfilling prophecy. Readings were presented to the team as follows: nonconvuslsive seizures (NCS), BS, severe background attenuation, and epileptiform discharges (including seizures and generalized periodic discharges; Table 1).

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Table 2. Comparison of Patient Characteristics Between Patients With Good Neurological Outcomes and Patients With Poor Neurological Outcomes. Good Poor Outcome Outcome (CPC 3-5) (CPC 1-2) Number of patients 33 25 Male gender, % 16 (48.5) 19 (76) Age, years, SD 62.9 (16.4) 60.1 (13.7) Number of out-of-hospital cardiac 18 (54.5) 15 (60) arrest,% Initial rhythm Ventricular fibrillation, n,% 11 (33.3) 14 (56) Asystole/pulseless electrical activity 22 (66.7) 11 (44) Presumed cardiac cause of arrest, n, % 17 (51.5) 16 (64) Time from arrest to target temperature, 559 (268) 523 (312) minutes, SD

P .03 .9 .7

.1 .1 .3 .9

Abbreviations: CPC, cerebral performance category; SD, standard deviation.

Outcome Assessment The primary outcome measure was the best score on hospital discharge on the 5-point Glasgow-Pittsburgh cerebral performance category (CPC) scores.19 Outcome was dichotomized between ‘‘good’’ and ‘‘poor.’’ A good outcome was defined as a CPC score of 1 or 2 (no or moderate neurological disability) and a poor outcome as a CPC score of 3, 4, or 5 (severe disability, comatose, or death).

Statistical Analysis Collected baseline characteristics include age, gender, location of cardiac arrest (in-hospital vs. out-of-hospital), cause of cardiac arrest, and initial cardiac rhythm. The following variables were compared between the groups of patients with a good neurological (CPC score 1–2) outcome and a poor neurological (CPC score 3–5) outcome: age, gender, percentage of out-ofhospital cardiac arrest, cause of cardiac arrest, initial rhythm, and time to target temperature (TTT) during the first 24 hours after cardiac arrest. Statistical analysis was performed using a Fisher exact test for the variables that were categorical. An independent t test or a Mann-Whitney U test was applied when the variables were continuous. A Mann-Whitney U test was performed in cases where the variable was not normally distributed. To evaluate the value of EEG in early prognostication, sensitivities, specificities, positive and negative predictive values, FPRs, and their 95% confidence intervals were calculated for the different EEG patterns.

Results A total of 58 patients were included in this study. Twenty five (43%) patients had a good neurologic outcome (CPC score of 1-2). An overview of patients’ characteristics is presented in Table 2. There were no statistically significant differences between patients with good and patients with poor neurologic

outcomes concerning age, percentage with OHCA, initial rhythm, cause of cardiac arrest, and TTT. More male patients were present in the good outcome group (76%) than in the poor outcome group (48.5%). Three (5.2%) patients had nonconvulsive status epilepticus, all of whom had poor outcome (CPC ¼ 5). Seventeen patients had BS; all had poor outcome (15 died secondary to very poor neurologic function and 2 were discharged with a CPC of 4). Severe background attenuation was recorded in 11 patients, 9 (82%) of whom developed poor outcome versus 2 (18%) patients who developed good outcome. Four patients developed tonic-clonic seizures for which they all received antiepileptic agents and they all had poor outcome. In addition, 6 patients had periodic epileptiform discharges, 5 (83%) of whom developed poor outcome (4 of those were treated with antiepileptic agents) and 1 (17%) had a good outcome (CPC ¼ 1). Myoclonus developed in 10 patients; 9 (90%) patients developed poor outcome (8 died and 1 with CPC ¼ 4), whereas 1 (10%) patient was discharged with CPC of 2. Table 3 summarizes the relevant sensitivity, specificity, predictive value rates and false positive ratesFPRs of the different EEG patterns for predicting good (CPC score 1-2) and poor (CPC score 3-5) outcome within 24 hours after resuscitation.

Discussion We explored the ability of cEEG monitoring for possibly predicting neurologic outcome in postcardiac arrest comatose patients treated with hypothermia. In our study population, 25 (43%) patients had a good neurologic outcome (CPC score of 1-2), which is within the 35% to 55% range shown in other studies.20-23 Three (5.2%) patients had nonconvulsive status epilepticus in our study, which is less than 10% to 12% found in other studies.24,15 This could be explained by the fact that more neuromuscular blockade was used in the other studies (continuous drips versus as needed in our study) and thus masked convulsive status epilepticus. Similar to other studies, all patients with NCS in our study had poor outcome. Although status myoclonus has been regarded as a reliable predictor of poor outcome,25 in our study 1 patient with status myoclonus progressed to good outcome with CPC ¼ 2 at hospital discharge. In our study, status myoclonus had a specificity of 96% and positive predictive values of 90% for predicting poor outcome and not 100%. There are other reports of good neurologic recovery after status myoclonus.26 Nonconvulsive status, severe background attenuation, and BSwere all associated with poor outcome with specificity of 100%, 92%, and 100%, and sensitivity of 9%, 27%, and 52%, respectively. Combining these together improved sensitivity to 67%. Compared to a similar study by Cloostermans et al,23 we have similar specificities but less sensitivities. For instance, in Cloostermans et al’s study, BS had sensitivity of 95% and sensitivity of 96%, and in our study

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Table 3. Sensitivity, Specificity, and Predictive Values for Early Prediction of Poor Neurologic Outcomes From EEG Patterns During Maintenance Phase and Rewarming From TH. Sensitivity (95% CI) NCS Burst suppression Severe background attenuation Epileptiform discharges NCS, or burst suppression NCS, burst suppression, or severe background attenuation NCS, burst suppression, severe background attenuation, or epileptiform discharges Myoclonus

9 52 27 21 58 67

(225) (3469) (1445) (1039) (40–74) (4881)

Specificity (95% CI) 100 100 92 96 100 92

(84100) (84100) (7298) (78100) (83100) (7398)

Positive Predictive Value (95% CI) 100 100 82 88 100 92

(31100) (77100) (4897) (4799) (79100) (7298)

Negative Predictive Value (95% CI) 46 61 49 48 64 68

False-Positive Rate (95% CI)

(3259) (4575) (3463) (3462) (4778) (4982)

0 (0.00.69) 0 (0.00.23) 0.18 (0.030.52) 0.12 (0.00.53) 0 (0.00.21) 0.08 (0.010.28)

76 (5788)

92 (7398)

93 (7499)

74 (5587)

0.07 (0.010.25)

27 (1446)

96 (78100)

90 (54100)

50 (3565)

0.1 (0.00.46)

Abbreviations: CI, confidence interval; EEG, electroencephalogram; NCS, nonconvulsive status.

it had a sensitivity of 52% and a specificity of 100%. In our study, FPR of zero was present for NCS and BS. None of the patients with BS in our series improved to good outcome. Rossetti et al, in a similar study, reported as well that BS was associated with poor outcome in cardiac arrest patients treated with hypothermia.26 In addition, all patients in our study that were treated with antiepileptic drugs (either tonic-clonic seizures or epileptiform discharges) had poor outcome. Treating seizures or epileptiform discharges did not improve outcome in our study. This is a finding similar to a recently published study by Crepeau et al.27 This could be an epiphenomenon of severe brain injury as well as contributing to brain injury itself. Our study has several limitations. A single-center study and the retrospective nature of the study are obvious limitations. Although all patients in our study were treated with the same sedative drugs according to same protocol, differences in sedation levels may have influenced the EEG patterns. However, it is unlikely that the most severe EEG patterns, such as NCS and BS patterns, are influenced by the sedatives we used. In our study, unlike Cloostermans et al’s, multiple readers did not score each EEG and therefore no kor other test of agreement is submitted to demonstrate the reading was reliable; however, all EEG analyses were performed by 2 board-certified neurologists. A limitation that is worth mentioning is that the 2 neurologists/neurophysiologists who read the EEGs knew that the EEGs were performed on postcardiac arrest patients on therapeutic hypothermia and thus were not totally blinded to the clinical conditions of the patients. However, they were not consulted to partake of patient management or involved in neuroprognostication. Another limitation is that the outcome was assessed at hospital discharge rather than later, like 3 or 6 months. However, it has been recently shown that CPC at hospital discharge is a useful surrogate measure of long-term prognosis and outcomes and can be an informative tool for programmatic evaluation and research of resuscitation.28 Another limitation was that the treating physician was not blinded to the EEG results; however, in our institution, EEG is not used for prognostication.

Conclusion Electroencephalogram monitoring started during maintenance phase of hypothermia and maintained during rewarming to normothermia used for comatose postcardiac arrest patients can add to the prediction of outcome. However, EEG should not be used as the sole predictor of outcome in cardiac arrest patients pending confirmation of our and other study results in large multicenter prospective studies and preferably studying EEG concomitantly with other possible prognostic factors such as neurologic examination, somatosensory-evoked potentials, and neurologic markers, such as neuron-specific enolase. Pending large mulicenter prospective studies evaluating the role of cEEG in prognostication, our study adds to the existing evidence that cEEG during the first 24 hours of resuscitation can contribute to the prediction of neurologic outcome. Authors’ Note This study was not sponsored. None of the authors have anything to disclose.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.

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