Persistent nonconvulsive status epilepticus after the control of convulsive status epilepticus

Nonconvulsive status epilepticus after convulsive status epilepticus: Clinical features, outcomes, and prognostic factors

OBJECTIVES

To investigate clinical characteristics and outcomes of nonconvulsive status epilepticus (NCSE) after convulsive status epilepticus (CSE) and determine risk factors for unfavorable outcomes.

METHODS

We reviewed consecutive patients with NCSE after CSE over eight years in the neurological intensive care unit. Clinical presentations and the Salzburg EEG criteria for NCSE were used to identify patients with NCSE after CSE. Demographics, clinical features, and anti-epileptic treatment responses were collected and analyzed. Modified Rankin Scale (mRS) was used to evaluate three-month outcomes. A multivariate logistic regression model was used to determine independent prognostic factors.

RESULTS

Among 145 consecutive patients with convulsive SE, 48 (33.1%) patents eventually evolved into NCSE. Two patients with cerebral anoxia were exclude. At three-month follow-up, 23 patients (50.0%) had mRS ≥ 3, and 16 (34.8%) died. Thirty-two patients (69.6%) were given continuous intravenous anesthetic drugs (CIVADs). Fourteen patients (30.4%) had CIVAD at the rate >50% proposed maximal dose (PMD). There was a single predictor factor found significant after multivariate logistic regression analysis: the recurrence of EEG seizures within two hours of initiation of CIVAD at a dose of greater than half the proposed maximal dose (OR, 9.63; 95%CI, 1.08-86.18; p = 0.043). The use of CIVAD, even with a high dose (>50% PMD), was not independently associated with unfavorable outcomes.

CONCLUSIONS

The recurrence of EEG seizures within two hours of initiation of CIVAD at a dose of greater than half the proposed maximal dose predicts unfavorable outcomes in NCSE after CSE. The refractoriness of the seizures might be a significantly greater risk for poor outcome in NCSE after CSE than treatment with CIVADs.

Successful Use of Therapeutic Hypothermia for Refractory Nonconvulsive Status Epilepticus

Therapeutic hypothermia (TH) has rarely been utilized as an adjunct to anticonvulsants in treating patients with refractory convulsive status epilepticus (CSE). However, determining the effectiveness of TH in CSE is difficult due to the unavoidable use of sedative drugs to manage hypothermia. Additionally, the effectiveness of TH has not been studied in patients with refractory non-convulsive status epilepticus (NCSE). Here, we report the successful use of TH without additional sedative drugs in a patient with temporal lobe epilepsy and refractory NCSE. A 46-year-old man was referred to the neurology department because of recurrent seizure attacks. Electroencephalography (EEG) after first-line status treatment showed continuous periodic discharges consistent with NCSE. He was started simultaneously on continuous EEG monitoring and TH, but was not administered any benzodiazepines to control shivering or maintain TH. During TH, EEG abnormalities gradually improved, and the patient regained consciousness in accordance with the improvement in EEG. The patient was alert and his EEG had normalized a few days after starting TH. To the best of our knowledge, this is the first report describing the successful treatment of refractory NCSE with TH. As no sedative drugs were used during the maintenance of hypothermia, NCSE control may have been achieved by TH alone.

Association of an Electroencephalography-Based Risk Score With Seizure Probability in Hospitalized Patients

Importance

Continuous electroencephalography (EEG) use in critically ill patients is expanding. There is no validated method to combine risk factors and guide clinicians in assessing seizure risk.

Objective

To use seizure risk factors from EEG and clinical history to create a simple scoring system associated with the probability of seizures in patients with acute illness.

Design, Setting, and Participants

We used a prospective multicenter (Emory University Hospital, Brigham and Women's Hospital, and Yale University Hospital) database containing clinical and electrographic variables on 5427 continuous EEG sessions from eligible patients if they had continuous EEG for clinical indications, excluding epilepsy monitoring unit admissions. We created a scoring system model to estimate seizure risk in acutely ill patients undergoing continuous EEG. The model was built using a new machine learning method (RiskSLIM) that is designed to produce accurate, risk-calibrated scoring systems with a limited number of variables and small integer weights. We validated the accuracy and risk calibration of our model using cross-validation and compared its performance with models built with state-of-the-art logistic regression methods. The database was developed by the Critical Care EEG Research Consortium and used data collected over 3 years. The EEG variables were interpreted using standardized terminology by certified reviewers.

Exposures

All patients had more than 6 hours of uninterrupted EEG recordings.

Main Outcomes and Measures

The main outcome was the average risk calibration error.

Results

There were 5427 continuous EEGs performed on 4772 participants (2868 men, 49.9%; median age, 61 years) performed at 3 institutions, without further demographic stratification. Our final model, 2HELPS2B, had an area under the curve of 0.819 and average calibration error of 2.7% (95% CI, 2.0%-3.6%). It included 6 variables with the following point assignments: (1) brief (ictal) rhythmic discharges (B[I]RDs) (2 points); (2) presence of lateralized periodic discharges, lateralized rhythmic delta activity, or bilateral independent periodic discharges (1 point); (3) prior seizure (1 point); (4) sporadic epileptiform discharges (1 point); (5) frequency greater than 2.0 Hz for any periodic or rhythmic pattern (1 point); and (6) presence of "plus" features (superimposed, rhythmic, sharp, or fast activity) (1 point). The probable seizure risk of each score was 5% for a score of 0, 12% for a score of 1, 27% for a score of 2, 50% for a score of 3, 73% for a score of 4, 88% for a score of 5, and greater than 95% for a score of 6 or 7.

Conclusions and Relevance

The 2HELPS2B model is a quick accurate tool to aid clinical judgment of the risk of seizures in critically ill patients.

Management of Status Epilepticus

Status epilepticus is due to a range of insults to the central nervous system and results in significant mortality rates, especially in the elderly. We review the current management of this disorder in light of the latest developments from recent trials and guidelines. Important principles in management includes early recognition of status epilepticus, identification of the underlying cause and prompt treatment to terminate seizures and reduce complications. The differentiation diagnosis, role of electroencephalographic monitoring and different treatment regimes are examined.

Early withdrawal of non-anesthetic antiepileptic drugs after successful termination of nonconvulsive seizures and nonconvulsive status epilepticus

PURPOSE

Multiple antiepileptic drugs (AEDs) are often necessary to treat nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE). AED polypharmacy places patients at risk for adverse side effects and drug-drug interactions. Identifying the likelihood of seizure relapse when weaning non-anesthetic AEDs may provide guidance in the critical care unit.

METHOD

Ninety-nine adult patients with successful treatment of electrographic-proven NCS or NCSE on continuous critical care EEG (CCEEG) monitoring were identified retrospectively. Patients were determined to undergo an AED wean if the number of non-anesthetic AEDs was reduced at the time of discharge compared to the number of non-anesthetic AEDs at primary seizure cessation. Primary outcome was recurrent seizures either clinically or by CCEEG during hospitalization. Secondary outcome measures included hospital length of stay and discharge disposition.

RESULTS

The rate of recurrent seizures in the wean group was not statistically different when compared to the group that did not undergo an AED wean (17% vs. 13%, respectively; p = 0.77). The wean group had a median value of 4 (IQR: 3-4) non-anesthetic AEDs at the time of primary seizure cessation compared with 3 (IQR: 2-3) in the non-wean group (p < 0.0001). However, both groups had similar values of AEDs at discharge (median of 2 (IQR: 2-3) vs. 3 (IQR: 2-3) for wean and non-wean groups respectively; p = 0.40). Discharge disposition (favorable, acceptable, or unfavorable) was similar between groups (p = 0.32).

CONCLUSIONS

Early weaning of non-anesthetic AEDs does not increase the risk of recurrent seizures in patients treated for NCS or NCSE during their hospitalization.

Clinical presentation, epidemiology, neurophysiological findings, treatment and outcome of nonconvulsive status epilepticus: a 3-year prospective, hospital-based study

Objective: This study reports the prevalence of Nonconvulsive Status Epilepticus (NCSE) in patients with altered mental status (AMS), and describes the clinical presentation, etiology, neurophysiological findings, neuroimaging, treatment, and outcome of NCSE in Qatar. Recording duration of continuous EEG monitoring was also discussed.

Methods: This was a 3-year, prospective, hospital-based study involving patients with AMS and continuous EEG monitoring admitted to the Emergency and ICUs of Hamad Hospital, Qatar. Patients with confirmed diagnosis of NCSE were compared to the patients who did not show EEG and clinical features compatible with NCSE. Descriptive statistics in terms of mean with standard deviation, as well as frequency and percentages for categorical variables, were calculated; Student’s t test as well as Chi-square tests or Fisher’s exact tests were applied. Logistic regressions NSCE was performed using significance level 0.05 for independent variables at univariate analysis.

Results: Number of patients with AMS and continuous EEG monitoring was 250. Number of patients with EEG compatible with NCSE: 65 (age range, 12–79 ys; m, 37; f, 28). Number of controls (defined as patients with EEG not compatible with NCSE): 185 (age range, 12–80 ys; m, 101; f, 84). Rate of occurrence of NCSE in patients with AMS: 26%. NCSE group was younger than controls (p < .001). Twenty patients with NCSE (31%) and 35 patients in the control group (19%) died. Death was more frequent in comatose NCSE compared to controls (p < .0007). NCSE proper and comatose NCSE had longer hospital stays than controls (p < .02 and p < .03, respectively). Complete recovery occurred in 26 NCSE patients (40%) and in 98 controls (53%) (p < .08). Twenty-one patients (31%) presented with refractory NCSE: 12 patients survived, 9 died.

Conclusion: This was the first prospective study reporting a high number of NCSE in Qatar, a small country in the MENA region. This prevalence (26%) was in the middle range. NCSE patients did not perform better than controls, outcome being worse with comatose NCSE. NCSE is an emergent condition warranting expedited diagnosis and management. Three days of continuous EEG monitoring were able to diagnose most cases of NCSE.

Hidden in plain sight: Non-convulsive status epilepticus-Recognition and management

Non-convulsive status epilepticus (NCSE) is an electroclinical state associated with an altered level of consciousness but lacking convulsive motor activity. It can present in a multitude of ways, but classification based on the clinical presentation and electroencephalographic appearances assists in determining prognosis and planning treatment. The aggressiveness of treatment should be based on the likely prognosis and the underlying cause of the NCSE.

A Systematic Appraisal of Neurosurgical Seizure Prophylaxis: Guidance for Critical Care Management

Clinical decisions are often made in the presence of some uncertainty. Health care should be based on a combination of scientific evidence, clinical experience, economics, patient value judgments, and preferences. Seizures are not uncommon following brain injury, surgical trauma, hemorrhage, altered brain metabolism, hypoxia, or ischemic events. The impact of seizures in the immediate aftermath of injury may be a prolonged intensive care stay or compounding of the primary injury. The aim of brain injury management is to limit the consequences of the secondary damage. The original intention of seizure prophylaxis was to limit the incidence of early-onset seizures. However, clinical trials have been equivocal on this point, and there is concern about the adverse effects of antiepileptic drug therapy. This review of the literature raises concerns regarding the arbitrary division of seizures into early onset (7 d) and late onset (8 d and beyond). In many cases it would appear that seizures present within 24 hours of the injury or after 7 days, which would be outside of the scope of current seizure prophylaxis guidance. There also does not appear to be a pathophysiological reason to divide brain injury-related seizures into these timeframes. Therefore, a solution to the conundrum is to reevaluate current practice. Prophylaxis could be offered to those receiving intensive care for the primary brain injury, where the impact of seizure would be detrimental to the management of the brain injury, or other clinical judgments where prophylaxis is prudent. Neurosurgical seizure management can then focus attention on which agent has the best adverse effect profile and the duration of therapy. The evidence seems to support levetiracetam as the most appropriate agent. Although previous reviews have identified an increase cost associated with the use of levetiracetam, current cost comparisons with phenytoin demonstrate a marginal price differential. The aim of this review is to assimilate the applicable literature regarding seizure prophylaxis. The final guidance is a forum upon which further clinical research could evaluate a new seizure prophylaxis paradigm.

An update on the recognition and treatment of non-convulsive status epilepticus in the intensive care unit

INTRODUCTION

Non-convulsive status epilepticus (NCSE) is a complex and diverse condition which is often an under-recognised entity in the intensive care unit. When NCSE is identified the optimal treatment strategy is not always clear. Areas covered: This review is based on a literature review of the key literature in the field over the last 5-10 years. The articles were selected based on their importance to the field by the authors. Expert commentary: This review discusses the complex situations when a neurological consultation may occur in a critical care setting and provides an update on the latest evidence regarding the recognition of NCSE and the decision making around determining the aggressiveness of treatment. It also considers the ictal-interictal continuum of conditions which may be met with, particularly in the era of continuous EEG, and provides an approach for dealing with these. Suggestions for how the field will develop are discussed.

Time-dependent risk of seizures in critically ill patients on continuous electroencephalogram

OBJECTIVE

Find the optimal continuous electroencephalographic (CEEG) monitoring duration for seizure detection in critically ill patients.

METHODS

We analyzed prospective data from 665 consecutive CEEGs, including clinical factors and time-to-event emergence of electroencephalographic (EEG) findings over 72 hours. Clinical factors were selected using logistic regression. EEG risk factors were selected a priori. Clinical factors were used for baseline (pre-EEG) risk. EEG findings were used for the creation of a multistate survival model with 3 states (entry, EEG risk, and seizure). EEG risk state is defined by emergence of epileptiform patterns.

RESULTS

The clinical variables of greatest predictive value were coma (31% had seizures; odds ratio [OR] = 1.8, p < 0.01) and history of seizures, either remotely or related to acute illness (34% had seizures; OR = 3.0, p < 0.001). If there were no epileptiform findings on EEG, the risk of seizures within 72 hours was between 9% (no clinical risk factors) and 36% (coma and history of seizures). If epileptiform findings developed, the seizure incidence was between 18% (no clinical risk factors) and 64% (coma and history of seizures). In the absence of epileptiform EEG abnormalities, the duration of monitoring needed for seizure risk of <5% was between 0.4 hours (for patients who are not comatose and had no prior seizure) and 16.4 hours (comatose and prior seizure).

INTERPRETATION

The initial risk of seizures on CEEG is dependent on history of prior seizures and presence of coma. The risk of developing seizures on CEEG decays to <5% by 24 hours if no epileptiform EEG abnormalities emerge, independent of initial clinical risk factors. Ann Neurol 2017;82:177-185.

Electroencephalographic Patterns Recorded by Continuous EEG Monitoring in Patients with Change of Consciousness in the Neurological Intensive Care Unit

INTRODUCTION

Our aim was to examine the frequency of various electrographic patterns including periodic discharges (PD), repetitive spike waves (RSW), rhythmic delta activities (RDA), nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE) in continuous EEG monitoring (cEEG) of the critically ill patients with change of consciousness and the presence of specific clinical and laboratory findings associated with these important patterns in this study.

METHODS

Patients with changes of consciousness in the neurological intensive care unit (NICU) were consecutively monitored with cEEG during 2 years. Their clinical, electrophysiological, radiological and laboratory findings were evaluated retrospectively.

RESULTS

This sample consisted of 57 (25 men) patients with a mean age of 68.2 years. Mean duration of cEEG monitoring was 2532.6 minutes. The most common electrographic patterns were PD (33%) and NCS-NCSE (26.3%). The presence of NCS-NCSE was significantly associated with PD (57.9%, p<0.001). PD and NCS-NCSE were the mostly seen in patients with acute stroke and hypoxic encephalopathy. Duration of monitoring was significantly longer in the group with PD and NCS-NCSE (p:0.004, p:0.014). Detection of any electrographic pattern in EEG before monitoring was associated with the presence of any pattern in cEEG (59.3%, p<0.0001). Convulsive or nonconvulsive seizure during monitoring was common in patients with electrographic patterns (p<0.0001). 66.7% of NCS-NCSE was seen within the first 12 hours and 26.7% was seen within the 12-24 hours of the monitoring.

CONCLUSION

Detection of any electrographic pattern in EEG before monitoring was associated with the presence of any important pattern in cEEG monitoring. This association suggest that at least 24 hours-monitoring of these patients could be useful for the diagnosis of clinical and/or electrographic seizures.

Brain Multimodality Monitoring: A New Tool in Neurocritical Care of Comatose Patients

Neurocritical care patients are at risk of developing secondary brain injury from inflammation, ischemia, and edema that follows the primary insult. Recognizing clinical deterioration due to secondary injury is frequently challenging in comatose patients. Multimodality monitoring (MMM) encompasses various tools to monitor cerebral metabolism, perfusion, and oxygenation aimed at detecting these changes to help modify therapies before irreversible injury sets in. These tools include intracranial pressure (ICP) monitors, transcranial Doppler (TCD), Hemedex™ (thermal diffusion probe used to measure regional cerebral blood flow), microdialysis catheter (used to measure cerebral metabolism), Licox™ (probe used to measure regional brain tissue oxygen tension), and continuous electroencephalography. Although further research is needed to demonstrate their impact on improving clinical outcomes, their contribution to illuminate the black box of the brain in comatose patients is indisputable. In this review, we further elaborate on commonly used MMM parameters, tools used to measure them, and the indications for monitoring per current consensus guidelines.

Spectrum and Predictors of Refractory Status Epilepticus in a Developing Country

OBJECTIVE

Refractory status epilepticus (RSE) can influence the outcome of status epilepticus (SE). In the present study, we report the aetiology and predictors of outcomes of RSE in a developing country.

METHODS

This is a prospective hospital-based study of SE patients (continuous seizures for five minutes or more). Those who had SE persisting after two antiepileptic drugs were defined as having RSE. We present the demographic information, duration, and type of SE, and we note its severity using the status epilepticus severity score (STESS), its aetiology, comorbidities and imaging findings. The outcome of RSE was defined as cessation of seizures and the condition upon discharge, as assessed by the modified Rankin Scale.

RESULTS

A total of 35 (42.5%) of our 81 patients had RSE. The median duration of SE before starting treatment was 2 hours (range=0.008-160 h). The most common causes of RSE were stroke in 5 (14.3%), central nervous system (CNS) infections in 12 (34.3%) and metabolic encephalopathies in 13 (37.1%) patients. Some 21 (60%) patients had comorbidities, and the STESS was favourable in 7 (20%) patients. A total of 14 (20%) patients died, but death was directly related to SE in only one of these. Some 10 patients had super-refractory status epilepticus, which was due to CNS infection in 5 (50%) and metabolic encephalopathy in 3 (30%). On multivariate analysis, an unfavourable STESS (p=0.05) and duration of SE before treatment (p=0.01) predicted RSE. Metabolic aetiology (p=0.05), mechanical ventilation (p60 years (p=0.003) were predictors of poor outcomes.

CONCLUSIONS

RSE was common (42.5%) among patients with SE in a tertiary care center in India. It was associated with high mortality and poor outcomes. Age above 60 years and metabolic aetiology were found to be predictors of poor outcomes.

Management of status epilepticus

Status epilepticus is a neurologic and medical emergency manifested by prolonged seizure activity or multiple seizures without return to baseline. It is associated with substantial medical cost, morbidity, and mortality. There is a spectrum of severity dependent on the type of seizure, underlying pathology, comorbidities, and appropriate and timely medical management. This chapter discusses the evolving definitions of status epilepticus and multiple patient and clinical factors which influence outcome. The pathophysiology of status epilepticus is reviewed to provide a better understanding of the mechanisms which contribute to status epilepticus, as well as the potential long-term effects. The clinical presentations of different types of status epilepticus in adults are discussed, with emphasis on the hospital course and management of the most dangerous type, generalized convulsive status epilepticus. Strategies for the evaluation and management of status epilepticus are provided based on available evidence from clinical trials and recommendations from the Neurocritical Care Society and the European Federation of Neurological Societies.

Seizures in the critically ill

Critically ill patients with seizures are either admitted to the intensive care unit because of uncontrolled seizures requiring aggressive treatment or are admitted for other reasons and develop seizures secondarily. These patients may have multiorgan failure and severe metabolic and electrolyte disarrangements, and may require complex medication regimens and interventions. Seizures can be seen as a result of an acute systemic illness, a primary neurologic pathology, or a medication side-effect and can present in a wide array of symptoms from convulsive activity, subtle twitching, to lethargy. In this population, untreated isolated seizures can quickly escalate to generalized convulsive status epilepticus or, more frequently, nonconvulsive status epileptics, which is associated with a high morbidity and mortality. Status epilepticus (SE) arises from a failure of inhibitory mechanisms and an enhancement of excitatory pathways causing permanent neuronal injury and other systemic sequelae. Carrying a high 30-day mortality rate, SE can be very difficult to treat in this complex setting, and a portion of these patients will become refractory, requiring narcotics and anesthetic medications. The most significant factor in successfully treating status epilepticus is initiating antiepileptic drugs as soon as possible, thus attentiveness and recognition of this disease are critical.

Continuous EEG monitoring in the intensive care unit

The purpose and indications for continuous electroencephalography monitoring (CEEG) in intensive care unit (ICU) patients include seizure detection, monitoring the effects of treatment (including depth of sedation), grading and classification of EEG abnormalities, ischemia detection and prognostication. Practical considerations of ICU CEEG include: choice of montages (patterns of electrode placement and connections), EEG electrodes, recognition of artifacts, and the use of automated or computerized analysis. These aspects are reviewed, along with an identifcation of current advances and challenges for the future of CEEG in the ICU.

The initial use of arterial spin labeling perfusion and diffusion-weighted magnetic resonance images in the diagnosis of nonconvulsive partial status epileptics

BACKGROUND

In the diagnosis of nonconvulsive status epilepticus (NCSE), capture of ongoing ictal electroencephalographic (EEG) findings is the gold standard; however, this is practically difficult without continuous EEG monitoring facilities. Magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI) and perfusion MRI with arterial spin labeling (ASL), have been applied mainly in emergency situations. Recent reports have described that ictal MRI findings, including ictal hyperperfusion on ASL and cortical hyperintensity of cytotoxic edema on DWI, can be obtained from epileptically activated cortex. We demonstrate the characteristics and clinical value of ictal MRI findings.

METHODS

Fifteen patients diagnosed as having NCSE (eight had complex partial status epilepticus (SE) and seven subtle SE) who underwent an initial MRI and subsequent EEG confrmation, participated in this study. Follow-up MRI and repeated routine EEG were performed.

RESULTS

In 11 patients (73%), ictal MRI findings were obtained on both DWI and ASL, while in four (27%) patients, ictal hyperperfusion was found on ASL without any DWI findings being obtained. In all 10 patients with an epileptogenic lesion, there was a tight topographical relationship between the lesion and the localization of ictal MRI findings. In the other five patients, ictal MRI findings were useful to demonstrate the pathophysiological mechanism of NCSE of non-lesional elderly epilepsy, or 'de novo' NCSE of frontal origin as situation-related NCSE. Ictal MRI findings are generally transient; however, in three cases they still persisted, even though ictal EEG findings had completely improved.

CONCLUSION

The present study clearly demonstrates that the initial use of ASL and DWI could help to diagnose partial NCSE and also combined use of the MRI and EEG allows documentation of the pathophysiological mechanism in each patient.

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection

Continuous electroencephalographic monitoring of critically ill patients is an established procedure in intensive care units. Seizure detection algorithms, such as support vector machines (SVM), play a prominent role in this procedure. To correct for inter-human differences in EEG characteristics, as well as for intra-human EEG variability over time, dynamic EEG feature normalization is essential. Recently, the median decaying memory (MDM) approach was determined to be the best method of normalization. MDM uses a sliding baseline buffer of EEG epochs to calculate feature normalization constants. However, while this method does include non-seizure EEG epochs, it also includes EEG activity that can have a detrimental effect on the normalization and subsequent seizure detection performance. In this study, EEG data that is to be incorporated into the baseline buffer are automatically selected based on a novelty detection algorithm (Novelty-MDM). Performance of an SVM-based seizure detection framework is evaluated in 17 long-term ICU registrations using the area under the sensitivity-specificity ROC curve. This evaluation compares three different EEG normalization methods, namely a fixed baseline buffer (FB), the median decaying memory (MDM) approach, and our novelty median decaying memory (Novelty-MDM) method. It is demonstrated that MDM did not improve overall performance compared to FB (p < 0.27), partly because seizure like episodes were included in the baseline. More importantly, Novelty-MDM significantly outperforms both FB (p = 0.015) and MDM (p = 0.0065).

Yield of repeated intermittent EEG for seizure detection in critically ill adults

INTRODUCTION

Seizures are common in critically ill patients and prevalence can exceed 30% in the neuro-intensive care unit (ICU). Continuous EEG monitoring (cEEG) is the gold standard for seizure detection in critically ill patients.

OBJECTIVES

To determine the yield of intermittent EEG (iEEG) to detect critically ill adult patients with seizures and to identify the factors that affect this yield.

METHODS

We retrospectively analyzed cEEG data and medical records from 977 consecutive critically ill patients undergoing cEEG. We included those presenting at least one electrographic seizure during the first 24hours of cEEG. Patients with hypoxic-ischemic encephalopathy were excluded. For seizure detection, we reviewed six 30-minute epochs on cEEG selected at H0, H3, H6, H12, H18 and H24.

RESULTS

Seizures occurred in 10.75% (105/977) of patients. Level of consciousness was impaired in 79 (75%) of patients, with 42 (40%) in coma. Review of the H0 epoch on cEEG permitted to detect seizures in 61 (58%) patients. These figures increased to 70 (67%), 75 (71%), 91 (87%) and 97 (92%) patients for a sampling every 24, 12, 6 and 3hours, respectively (P=0.02). Frequency of seizures on cEEG was the only factor significantly affecting the probability of seizure detection. Sampling every 6hours revealed seizures in all patients with more than six seizures per 24hours.

CONCLUSIONS

iEEG repeated every 6hours can accurately detect patients presenting seizures, especially when seizure frequency is greater than six per 24hours. These findings have practical implications for electrographic seizure detection in critically ill patients in settings lacking cEEG.

Emergency Neurological Life Support: Status Epilepticus

Patients with prolonged or rapidly recurring convulsions lasting more than 5 min are in status epilepticus (SE) and require immediate resuscitation. Although there are relatively few randomized clinical trials, available evidence and experience suggest that early and aggressive treatment of SE improves patient outcomes, for which reason this was chosen as an Emergency Neurological Life Support protocol. The current approach to the emergency treatment of SE emphasizes rapid initiation of adequate doses of first-line therapy, as well as accelerated second-line anticonvulsant drugs and induced coma when these fail, coupled with admission to a unit capable of neurological critical care and electroencephalography monitoring. This protocol will focus on the initial treatment of SE but also review subsequent steps in the protocol once the patient is hospitalized.

Emergency electroencephalogram: Usefulness in the diagnosis of nonconvulsive status epilepticus by the on-call neurologist

INTRODUCTION

We aim to describe the use of emergency electroencephalogram (EmEEG) by the on-call neurologist when nonconvulsive status epilepticus (NCSE) is suspected, and in other indications, in a tertiary hospital.

SUBJECTS AND METHODS

Observational retrospective cohort study of emergency EEG (EmEEG) recordings with 8-channel systems performed and analysed by the on-call neurologist in the emergency department and in-hospital wards between July 2013 and May 2015. Variables recorded were sex, age, symptoms, first diagnosis, previous seizure and cause, previous stroke, cancer, brain computed tomography, diagnosis after EEG, treatment, patient progress, routine control EEG (rEEG), and final diagnosis. We analysed frequency data, sensitivity, and specificity in the diagnosis of NCSE.

RESULTS

The study included 135 EEG recordings performed in 129 patients; 51.4% were men and their median age was 69 years. In 112 cases (83%), doctors ruled out suspected NCSE because of altered level of consciousness in 42 (37.5%), behavioural abnormalities in 38 (33.9%), and aphasia in 32 (28.5%). The EmEEG diagnosis was NCSE in 37 patients (33%), and this was confirmed in 35 (94.6%) as the final diagnosis. In 3 other cases, NCSE was the diagnosis on discharge as confirmed by rEEG although the EmEEG missed this condition at first. EmEEG performed to rule out NCSE showed 92.1% sensitivity, 97.2% specificity, a positive predictive value of 94.6%, and a negative predictive value of 96%.

CONCLUSIONS

Our experience finds that, in an appropriate clinical context, EmEEG performed by the on-call neurologist is a sensitive and specific tool for diagnosing NCSE.

Brain Multimodality Monitoring: Updated Perspectives

The challenges posed by acute brain injury (ABI) involve the management of the initial insult in addition to downstream inflammation, edema, and ischemia that can result in secondary brain injury (SBI). SBI is often subclinical, but can be detected through physiologic changes. These changes serve as a surrogate for tissue injury/cell death and are captured by parameters measured by various monitors that measure intracranial pressure (ICP), cerebral blood flow (CBF), brain tissue oxygenation (PbtO2), cerebral metabolism, and electrocortical activity. In the ideal setting, multimodality monitoring (MMM) integrates these neurological monitoring parameters with traditional hemodynamic monitoring and the physical exam, presenting the information needed to clinicians who can intervene before irreversible damage occurs. There are now consensus guidelines on the utilization of MMM, and there continue to be new advances and questions regarding its use. In this review, we examine these recommendations, recent evidence for MMM, and future directions for MMM.

Clinical characteristics of non-convulsive status epilepticus diagnosed by simplified continuous electroencephalogram monitoring at an emergency intensive care unit

Aim

The present study aimed to elucidate the clinical characteristics of non‐convulsive status epilepticus (NCSE) in patients with altered mental status (AMS).

Methods

This single‐center retrospective study comprised 149 patients who were hospitalized between March 1, 2015 and September 30, 2015 at the emergency intensive care unit (ICU) of the Kagawa University Hospital (Kagawa, Japan). The primary outcome was NCSE incidence. The secondary outcome was the comparison of duration of ICU stay, hospital stay, and a favorable neurological outcome, as assessed using the modified Rankin Scale score, at discharge from our hospital between patients with and without NCSE. Favorable neurological outcome and poor neurological outcome were defined as modified Rankin Scale scores of 0–2 and 3–6, respectively.

Results

Simplified continuous electroencephalogram was used to monitor 36 patients (median age, 68 years; 69.4% males) with acute AMS; among them, NCSE was observed in 11 (30.1%) patients. Rates of favorable neurological outcome, duration of ICU stay, and hospital stay were not significantly different between the NCSE and non‐NCSE groups (P = 0.45, P = 0.30, and P = 0.26, respectively).

Conclusion

Approximately 30% of the patients with AMS admitted to emergency ICUs developed NCSE. The outcomes of AMS patients with and without NCSE did not differ significantly when appropriate medical attention and antiepileptic drugs were initiated. Simplified continuous electroencephalogram monitoring may be recommended in patients with AMS in emergency ICU to obtain early detection of NCSE followed by appropriate intervention.

Should We Treat Electroencephalographic Discharges in the Clinic or in the Intensive Care Unit, and if so When and How?

The important question that often emerges in the clinic is how aggressive the therapy for nonconvulsive status epilepticus and electrical status epilepticus in sleep ought to be and how continuous the discharges in each of these 2 entities should be before therapy is aimed at them. Additionally, as the use of electroencephalographic monitoring continues to expand to include the clinic and intensive care unit populations, it is important to identify epileptiform patterns that warrant identification and treatment. This review will present the state-of-the-art data and suggest algorithms to manage these conditions.

Optimal training dataset composition for SVM-based, age-independent, automated epileptic seizure detection

Automated seizure detection is a valuable asset to health professionals, which makes adequate treatment possible in order to minimize brain damage. Most research focuses on two separate aspects of automated seizure detection: EEG feature computation and classification methods. Little research has been published regarding optimal training dataset composition for patient-independent seizure detection. This paper evaluates the performance of classifiers trained on different datasets in order to determine the optimal dataset for use in classifier training for automated, age-independent, seizure detection. Three datasets are used to train a support vector machine (SVM) classifier: (1) EEG from neonatal patients, (2) EEG from adult patients and (3) EEG from both neonates and adults. To correct for baseline EEG feature differences among patients feature, normalization is essential. Usually dedicated detection systems are developed for either neonatal or adult patients. Normalization might allow for the development of a single seizure detection system for patients irrespective of their age. Two classifier versions are trained on all three datasets: one with feature normalization and one without. This gives us six different classifiers to evaluate using both the neonatal and adults test sets. As a performance measure, the area under the receiver operating characteristics curve (AUC) is used. With application of FBC, it resulted in performance values of 0.90 and 0.93 for neonatal and adult seizure detection, respectively. For neonatal seizure detection, the classifier trained on EEG from adult patients performed significantly worse compared to both the classifier trained on EEG data from neonatal patients and the classier trained on both neonatal and adult EEG data. For adult seizure detection, optimal performance was achieved by either the classifier trained on adult EEG data or the classifier trained on both neonatal and adult EEG data. Our results show that age-independent seizure detection is possible by training one classifier on EEG data from both neonatal and adult patients. Furthermore, our results indicate that for accurate age-independent seizure detection, it is important that EEG data from each age category are used for classifier training. This is particularly important for neonatal seizure detection. Our results underline the under-appreciated importance of training dataset composition with respect to accurate age-independent seizure detection.

Baseline EEG pattern on continuous ICU EEG monitoring and incidence of seizures

PURPOSE

To identify the probability of detecting nonconvulsive seizures based on the initial pattern seen in the first 30 minutes of continuous EEG (cEEG) monitoring.

METHODS

Continuous EEG monitoring reports from 243 adult patients were reviewed, assessing the baseline cEEG monitoring pattern and the presence of seizures during the entire monitoring period. The baseline EEG patterns were classified into nine categories: seizures, lateralized periodic discharges, generalized periodic discharges, focal epileptiform discharges, burst suppression, asymmetric background, generalized slowing, generalized periodic discharges with triphasic morphology, and normal.

RESULTS

Overall, 51 patients (21%) had nonconvulsive seizures at any time during cEEG monitoring. Notably, 112 patients had generalized slowing as the initial EEG pattern, and none of these patients were noted to have seizures. Seizure rates among the types of baseline EEG findings were as follows: lateralized periodic discharges (56%, n = 9), burst suppression (50%, n = 10), generalized periodic discharges (50%, n = 2), normal (33%, n = 3), focal epileptiform discharges (31%, n = 35), and asymmetric background (11%, n = 46).

CONCLUSIONS

Patients with only generalized slowing seen on the baseline EEG recording are unlikely to develop seizures on subsequent cEEG monitoring. Depending on the clinical circumstance, the standard duration of cEEG recording (24-48 hours) may be unnecessary in patients with generalized slowing as their only cEEG abnormality.

Consensus statement on continuous EEG in critically ill adults and children, part I: indications

INTRODUCTION

Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance.

METHODS

The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children.

RECOMMENDATIONS

The consensus panel recommends CCEEG for diagnosis of nonconvulsive seizures, nonconvulsive status epilepticus, and other paroxysmal events, and for assessment of the efficacy of therapy for seizures and status epilepticus. The consensus panel suggests CCEEG for identification of ischemia in patients at high risk for cerebral ischemia; for assessment of level of consciousness in patients receiving intravenous sedation or pharmacologically induced coma; and for prognostication in patients after cardiac arrest. For each indication, the consensus panel describes the patient populations for which CCEEG is indicated, evidence supporting use of CCEEG, utility of video and quantitative EEG trends, suggested timing and duration of CCEEG, and suggested frequency of review and interpretation.

CONCLUSION

CCEEG has an important role in detection of secondary injuries such as seizures and ischemia in critically ill adults and children with altered mental status.

EEG and Coma

Coma is defined as a state of extreme unresponsiveness, in which a person exhibits no voluntary movement or behavior even to painful stimuli. The utilization of EEG for patients in coma has increased dramatically over the last few years. In fact, many institutions have set protocols for continuous EEG (cEEG) monitoring for patients in coma due to potential causes such as subarachnoid hemorrhage or cardiac arrest. Consequently, EEG plays an important role in diagnosis, managenent, and in some cases even prognosis of coma patients.

Status Epilepticus

Although the majority of seizures are brief and cause no long-term consequences, a subset is sufficiently prolonged that long-term consequences can result. These very prolonged seizures are termed "status epilepticus" (SE) and are considered a neurological emergency. The clinical presentation of SE can be diverse. SE can occur at any age but most commonly occurs in the very young and the very old. There are numerous studies on SE in animals in which the pathophysiology, medication responses, and pathology can be rigorously studied in a controlled fashion. Human data are consistent with the animal data. In particular, febrile status epilepticus (FSE), a form of SE common in young children, is associated with injury to the hippocampus and subsequent temporal lobe epilepsy (TLE) in both animals and humans.

Treatment of Convulsive Status Epilepticus

OPINION STATEMENT

Convulsive status epilepticus (CSE) is a medical emergency with an associated high mortality and morbidity. It is defined as a convulsive seizure lasting more than 5 min or consecutive seizures without recovery of consciousness. Successful management of CSE depends on rapid administration of adequate doses of anti-epileptic drugs (AEDs). The exact choice of AED is less important than rapid treatment and early consideration of reversible etiologies. Current guidelines recommend the use of benzodiazepines (BNZ) as first-line treatment in CSE. Midazolam is effective and safe in the pre-hospital or home setting when administered intramuscularly (best evidence), buccally, or nasally (the latter two possibly faster acting than intramuscular (IM) but with lower levels of evidence). Regular use of home rescue medications such as nasal/buccal midazolam by patients and caregivers for prolonged seizures and seizure clusters may prevent SE, prevent emergency room visits, improve quality of life, and lower health care costs. Traditionally, phenytoin is the preferred second-line agent in treating CSE, but it is limited by hypotension, potential arrhythmias, allergies, drug interactions, and problems from extravasation. Intravenous valproate is an effective and safe alternative to phenytoin. Valproate is loaded intravenously rapidly and more safely than phenytoin, has broad-spectrum efficacy, and fewer acute side effects. Levetiracetam and lacosamide are well tolerated intravenous (IV) AEDs with fewer interactions, allergies, and contraindications, making them potentially attractive as second- or third-line agents in treating CSE. However, data are limited on their efficacy in CSE. Ketamine is probably effective in treating refractory CSE (RCSE), and may warrant earlier use; this requires further study. CSE should be treated aggressively and quickly, with confirmation of treatment success with epileptiform electroencephalographic (EEG), as a transition to non-convulsive status epilepticus is common. If the patient is not fully awake, EEG should be continued for at least 24 h. How aggressively to treat refractory non-convulsive SE (NCSE) or intermittent non-convulsive seizures is less clear and requires additional study. Refractory SE (RSE) usually requires anesthetic doses of anti-seizure medications. If an auto-immune or paraneoplastic etiology is suspected or no etiology can be identified (as with cryptogenic new onset refractory status epilepticus, known as NORSE), early treatment with immuno-modulatory agents is now recommended by many experts.

Prediction of functional outcome in patients with convulsive status epilepticus: the END-IT score

BACKGROUND

Prediction of the functional outcome for patients with convulsive status epilepticus (CSE) has been a challenge. The aim of this study was to characterize the prognostic factors and functional outcomes of patients after CSE in order to develop a practicable scoring system for outcome prediction.

METHODS

We performed a retrospective explorative analysis on consecutive patients diagnosed with CSE between March, 2008 and November, 2014 in a tertiary academic medical center in northwest China. The modified Rankin Scale (mRS) was used to measure the functional outcome at three months post discharge.

RESULTS

A total of 132 CSE patients was included, with a median age of 25.5 years and 60.6% were male. Three months post discharge, an unfavorable outcome with mRS of 3-6 was seen in 62 (47.0%) patients, 25 (18.9%) of whom died. Logistic regression analysis revealed that encephalitis (p = 0.029), nonconvulsive SE (p = 0.018), diazepam resistance (p = 0.005), image abnormalities (unilateral lesions, p = 0.027; bilateral lesions or diffuse cerebral edema, p < 0.001) and tracheal intubation (p = 0.032) were significant independent predictors for unfavorable outcomes. Based on the coefficients in the model, these predictors were assigned a value of 1 point each, with the exception of the image, creating a 6-point scoring system, which we refer to as END-IT, for the outcome prediction of CSE. The area under the receiver operating characteristic curve for the END-IT score was 0.833 and using a cut-off point of 3 produced the highest sum sensitivity (83.9%) and specificity (68.6%). Compared with status epilepticus severity score (STESS) and Epidemiology-based Mortality score in SE (EMSE), END-IT score showed better discriminative power and predictive accuracy for the outcome prediction.

CONCLUSIONS

We developed an END-IT score with a strong discriminative power for predicting the functional outcome of CSE patients. External prospective validation in different cohorts is needed for END-IT score.

StatNet Electroencephalogram: A Fast and Reliable Option to Diagnose Nonconvulsive Status Epilepticus in Emergency Setting

BACKGROUND

The StatNet electrode set is a system that can be applied by a non-electroencephalogram (EEG) technologist after minimal training. The primary objectives of this study are to assess the quality and reliability of the StatNet recordings in comparison to the conventional EEG.

METHODS

Over 10 months, 19 patients with suspected nonconvulsive status epilepticus were included from university hospital emergency settings. Each patient received a StatNet EEG by a trained epilepsy fellow and a conventional EEG by registered technologists. We compared the studies in a blinded fashion, for the timeframe from EEG order to the setup time, start of acquisition, amount of artifact, and detection of abnormalities. The nonparametric Mann-Whitney two-sample t test was used for comparisons. The kappa score was used to assess reliability.

RESULTS

Mean age of patients was 61±16.3 (25-93) years. The inter-observer agreement for detection of abnormal findings was 0.83 for StatNet and 0.75 for conventional EEG. Nonconvulsive status epilepticus was detected in 10% (2/19) in both studies. The delay from the time of EEG requisition to acquisition was shorter in the StatNet (22.4±2.5 minutes) than the conventional EEG (217.7±44.6 minutes; p<0.0001). The setup time was also shorter in the StatNet (9.9±0.8 minutes) compared with the conventional EEG (17.8±0.8 minutes; p<0.0001). There was no difference in the percentage of artifact duration between the two studies (p=0.89).

CONCLUSION

This study demonstrates that StatNet EEG is a practical and reliable tool in the emergency setting, which reduces the delay of testing compared with conventional EEG, without significant compromise of study quality.

Rhythmic and periodic EEG patterns of 'ictal-interictal uncertainty' in critically ill neurological patients

OBJECTIVES

To study periodic and rhythmic EEG patterns classified according to Standardized Critical Care EEG Terminology (SCCET) of the American Clinical Neurophysiology Society and their relationship to electrographic seizures.

METHODS

We classified 655 routine EEGs in 371 consecutive critically ill neurological patients into (1) normal EEGs or EEGs with non-specific abnormalities or interictal epileptiform discharges, (2) EEGs containing unequivocal ictal EEG patterns, and (3) EEGs showing rhythmic and periodic EEG patterns of 'ictal-interictal uncertainty' (RPPIIIU) according to SCCET.

RESULTS

313 patients (84.4%) showed normal EEGs, non-specific or interictal abnormalities, 14 patients (3.8%) had EEGs with at least one electrographic seizure, and 44 patients (11.8%) at least one EEG containing RPPIIIU, but no EEG with electrographic seizures. Electrographic seizures occurred in 11 of 55 patients (20%) with RPPIIIU, but only in 3 of 316 patients (0.9%) without RPPIIIU (p⩽0.001). Conversely, we observed RPPIIIU in 11 of 14 patients (78.6%) with electrographic seizures, but only in 44 of 357 patients (12.3%) without electrographic seizures (p⩽0.001).

CONCLUSIONS

On routine-EEG in critically ill neurological patients RPPIIIU occur 3 times more frequently than electrographic seizures and are highly predictive for electrographic seizures.

SIGNIFICANCE

RPPIIIU can serve as an indication for continuous EEG recordings.

Electrophysiologic monitoring in acute brain injury

To determine the optimal use and indications of electroencephalography (EEG) in critical care management of acute brain injury (ABI). An electronic literature search was conducted for articles in English describing electrophysiological monitoring in ABI from January 1990 to August 2013. A total of 165 studies were included. EEG is a useful monitor for seizure and ischemia detection. There is a well-described role for EEG in convulsive status epilepticus and cardiac arrest (CA). Data suggest EEG should be considered in all patients with ABI and unexplained and persistent altered consciousness and in comatose intensive care unit (ICU) patients without an acute primary brain condition who have an unexplained impairment of mental status. There remain uncertainties about certain technical details, e.g., the minimum duration of EEG studies, the montage, and electrodes. Data obtained from both EEG and EP studies may help estimate prognosis in ABI patients, particularly following CA and traumatic brain injury. Data supporting these recommendations is sparse, and high quality studies are needed. EEG is used to monitor and detect seizures and ischemia in ICU patients and indications for EEG are clear for certain disease states, however, uncertainty remains on other applications.

Delays and Factors Related to Cessation of Generalized Convulsive Status Epilepticus

Introduction. This study was designed to identify the delays and factors related to and predicting the cessation of generalized convulsive SE (GCSE). Methods. This retrospective study includes 70 consecutive patients (>16 years) diagnosed with GCSE and treated in the emergency department of a tertiary hospital over 2 years. We defined cessation of SE stepwise using clinical seizure freedom, achievement of burst-suppression, and return of consciousness as endpoints and calculated delays for these cessation markers. In addition 10 treatment delay parameters and 7 prognostic and GCSE episode related factors were defined. Multiple statistical analyses were performed on their relation to cessation markers. Results. Onset-to-second-stage-medication (p = 0.027), onset-to-burst-suppression (p = 0.005), and onset-to-clinical-seizure-freedom (p = 0.035) delays correlated with the onset-to-consciousness delay. We detected no correlation between age, epilepsy, STESS, prestatus period, type of SE onset, effect of the first medication, and cessation of SE. Conclusion. Our study demonstrates that rapid administration of second-stage medication and early obtainment of clinical seizure freedom and burst-suppression predict early return of consciousness, an unambiguous marker for the end of SE. We propose that delays in treatment chain may be more significant determinants of SE cessation than the previously established outcome predictors. Thus, streamlining the treatment chain is advocated.

Which EEG patterns in coma are nonconvulsive status epilepticus?

Nonconvulsive status epilepticus (NCSE) is common in patients with coma with a prevalence between 5% and 48%. Patients in deep coma may exhibit epileptiform EEG patterns, such as generalized periodic spikes, and there is an ongoing debate about the relationship of these patterns and NCSE. The purposes of this review are (i) to discuss the various EEG patterns found in coma, its fluctuations, and transitions and (ii) to propose modified criteria for NCSE in coma. Classical coma patterns such as diffuse polymorphic delta activity, spindle coma, alpha/theta coma, low output voltage, or burst suppression do not reflect NCSE. Any ictal patterns with a typical spatiotemporal evolution or epileptiform discharges faster than 2.5 Hz in a comatose patient reflect nonconvulsive seizures or NCSE and should be treated. Generalized periodic diacharges or lateralized periodic discharges (GPDs/LPDs) with a frequency of less than 2.5 Hz or rhythmic discharges (RDs) faster than 0.5 Hz are the borderland of NCSE in coma. In these cases, at least one of the additional criteria is needed to diagnose NCSE (a) subtle clinical ictal phenomena, (b) typical spatiotemporal evolution, or (c) response to antiepileptic drug treatment. There is currently no consensus about how long these patterns must be present to qualify for NCSE, and the distinction from nonconvulsive seizures in patients with critical illness or in comatose patients seems arbitrary. The Salzburg Consensus Criteria for NCSE [1] have been modified according to the Standardized Terminology of the American Clinical Neurophysiology Society [2] and validated in three different cohorts, with a sensitivity of 97.2%, a specificity of 95.9%, and a diagnostic accuracy of 96.3% in patients with clinical signs of NCSE. Their diagnostic utility in different cohorts with patients in deep coma has to be studied in the future. This article is part of a Special Issue entitled "Status Epilepticus".

Prospective assessment and validation of rhythmic and periodic pattern detection in NeuroTrend: A new approach for screening continuous EEG in the intensive care unit

BACKGROUND

NeuroTrend is a computational method that analyzes long-term scalp EEGs in the ICU according to ACNS standardized critical care EEG terminology (CCET) including electrographic seizures. At present, it attempts to become a screening aid for continuous EEG (cEEG) recordings in the ICU to facilitate the review process and optimize resources.

METHODS

A prospective multicenter study was performed in two neurological ICUs including 68 patients who were subjected to video-cEEG. Two reviewers independently annotated the first minute of each hour in the cEEG according to CCET. These segments were also screened for faster patterns with frequencies higher than 4 Hz. The matching annotations (2911 segments) were then used as gold standard condition to test sensitivity and specificity of the rhythmic and periodic pattern detection of NeuroTrend.

RESULTS

Interrater agreement showed substantial agreement for localization (main term 1) and pattern type (main term 2) of the CCET. The overall detection sensitivity of NeuroTrend was 94% with high detection rates for periodic discharges (PD = 80%) and rhythmic delta activity (RDA = 82%). Overall specificity was moderate (67%) mainly because of false positive detections of RDA in cases of general slowing. In contrast, a detection specificity of 88% for PDs was reached. Localization revealed only a slight agreement between reviewers and NeuroTrend.

CONCLUSIONS

NeuroTrend might be a suitable screening tool for cEEG in the ICU and has the potential to raise efficiency of long-term EEG monitoring in the ICU. At this stage, pattern localization and differentiation between RDA and general slowing need improvement. This article is part of a Special Issue entitled "Status Epilepticus".