Arnold J. Sansevere

Development and Feasibility Testing of a Critical Care EEG Monitoring Database for Standardized Clinical Reporting and Multicenter Collaborative Research.

Purpose: The rapid expansion of the use of continuous critical care electroencephalogram (cEEG) monitoring and resulting multicenter research studies through the Critical Care EEG Monitoring Research Consortium has created the need for a collaborative data sharing mechanism and repository. The authors describe the development of a research database incorporating the American Clinical Neurophysiology Society standardized terminology for critical care EEG monitoring. The database includes flexible report generation tools that allow for daily clinical use. Methods: Key clinical and research variables were incorporated into a Microsoft Access database. To assess its utility for multicenter research data collection, the authors performed a 21-center feasibility study in which each center entered data from 12 consecutive intensive care unit monitoring patients. To assess its utility as a clinical report generating tool, three large volume centers used it to generate daily clinical critical care EEG reports. Results: A total of 280 subjects were enrolled in the multicenter feasibility study. The duration of recording (median, 25.5 hours) varied significantly between the centers. The incidence of seizure (17.6%), periodic/rhythmic discharges (35.7%), and interictal epileptiform discharges (11.8%) was similar to previous studies. The database was used as a clinical reporting tool by 3 centers that entered a total of 3,144 unique patients covering 6,665 recording days. Conclusions: The Critical Care EEG Monitoring Research Consortium database has been successfully developed and implemented with a dual role as a collaborative research platform and a clinical reporting tool. It is now available for public download to be used as a clinical data repository and report generating tool.

Time to electroencephalography is independently associated with outcome in critically ill neonates and children

To identify factors associated with in‐hospital mortality in neonates and children undergoing continuous electroencephalography (cEEG) monitoring in the intensive care unit (ICU).

Conventional and Quantitative EEG in Status Epilepticus

PURPOSE To summarize the use of continuous electroencephalographic monitoring (cEEG) in the diagnosis and management of pediatric convulsive status epilepticus (CSE) and subsequent non-convulsive seizures (NCS) with a focus on available guidelines and infrastructure. In addition, we provide an overview of quantitative EEG (QEEG) for the identification of NCS in critically ill children. METHODS We performed a review of the medical literature on the use of cEEG and QEEG in pediatric CSE. This included published guideline, consensus statements, and literature focused on the use of cEEG and QEEG to detect NCS. RESULTS cEEG monitoring is recommended for prompt recognition of ongoing seizures that may be subtle, masked by pharmacologic paralysis, and or converted from convulsive seizures to NCS after administration of anti-seizure medications. Evidence indicating that high seizure burden is associated with worse outcome has motivated prompt recognition and management of NCS. The American Clinical Neurophysiology Societys consensus statement recommends a minimum of 24 h to exclude electrographic seizures, while the Neurocritical Care Societys guideline suggests 48 h in patients that are comatose. The use of QEEG amongst electroencephalographers and critical care medicine providers is increasing for NCS detection in critically ill children. The sensitivity and specificity of QEEG to detect NCS ranges from 65 to 83% and 65-92%, respectively. CONCLUSION The use of cEEG is important to the diagnosis and treatment of NCS or subtle clinical seizures after pediatric CSE. QEEG allows cEEG data to be reviewed and interpreted quickly and is a useful tool for detection of NCS after CSE.

Time to continuous electroencephalogram in repeated admissions to the pediatric intensive care unit

PURPOSE Describe timing from intensive care unit (ICU) admission to initiation of continuous electroencephalogram (cEEG) in repeated ICU admissions. METHOD We performed a retrospective observational study in pediatric patients who underwent repeated ICU admissions with cEEG from 2011 to 2013. The main outcome measure was time from ICU admission to cEEG. RESULTS There were 41 patients (54% males) with at least 2 ICU admissions with cEEG (median (p25-p75) age at first admission: 3.3 (0.3-8.4) years, at second admission: 3.9 (1.1-9.4) years), 7 patients (57% males, 9.9 (2.9-11.5) years) with at least 3 ICU admissions, and 5 patients (60% males, 10.1 (4-10.5) years) with at least 4 ICU admissions. One patient had 21 ICU admissions. The median (p25-p75) time from ICU admission to cEEG was not different during the first and second ICU admissions [10.7 (1.9-22.9) hours versus 13 (0.2-36.7) hours; p=0.908]. Among patients with electrographic seizures on first admission, time to cEEG was not different during the first and second admissions [7.9 (0.5-23.4) hours versus 14.5 (-2 to 44.5) hours; p=0.636]. Among patients with status epilepticus during the first admission, time to cEEG was not different between the first and second admissions [15.3 (9-79) hours versus 40.7 (19.3-42.6) hours; p=0.75]. CONCLUSIONS The time from ICU admission to the initiation of cEEG did not decrease in second or subsequent ICU admissions, even in patients with seizures or status epilepticus on the first admission.

Post-arrest therapeutic hypothermia in pediatric patients with congenital heart disease

BACKGROUND While therapeutic hypothermia (TH) is an effective neuroprotective therapy for neonatal hypoxic-ischemic encephalopathy, TH has not been demonstrated to improve outcome in other pediatric populations. Patients with acquired or congenital heart disease (CHD) are at high risk of both cardiac arrest and neurodevelopmental impairments, and therapies are needed to improve neurologic outcome. The primary goal of our study was to compare safety/efficacy outcomes in post-arrest CHD patients treated with TH versus controls not treated with TH. METHODS Patients with CHD treated during the first 18 months after initiation of a post-arrest TH protocol (temperature goal: 33.5 °C) were compared to historical and contemporary post-arrest controls not treated with TH. Post-arrest data, including temperature, safety measures (e.g. arrhythmia, bleeding), neurodiagnostic data (EEG, neuroimaging), and survival were compared. RESULTS Thirty arrest episodes treated with TH and 51 control arrest episodes were included. The groups did not differ in age, duration of arrest, post-arrest lactate, or use of ECMO-CPR. The TH groups post-arrest temperature was significantly lower than controls (33.6 ± 0.2 °C vs 34.7 ± 0.5 °C, p < 0.001). There was no difference between the groups in safety/efficacy measures, including arrhythmia, infections, chest-tube output, or neuroimaging abnormalities, nor in hospital survival (TH 61.5% vs control 59.1%, p = NS). Significantly more controls had seizures than TH patients (26.1% vs. 4.0%, p = 0.04). Almost all seizures were subclinical and occurred more than 24 h post-arrest. CONCLUSION Our data show that pediatric CHD patients who suffer cardiac arrest can be treated effectively and safely with TH, which may decrease the incidence of seizures.

Machine Learning for Outcome Prediction in Electroencephalograph (EEG)-Monitored Children in the Intensive Care Unit

The aim of this study was to evaluate the performance of models predicting in-hospital mortality in critically ill children undergoing continuous electroencephalography (cEEG) in the intensive care unit (ICU). We evaluated the performance of machine learning algorithms for predicting mortality in a database of 414 critically ill children undergoing cEEG in the ICU. The area under the receiver operating characteristic curve (AUC) in the test subset was highest for stepwise selection/elimination models (AUC = 0.82) followed by least absolute shrinkage and selection operator (LASSO) and support vector machine with linear kernel (AUC = 0.79), and random forest (AUC = 0.71). The explanatory models had the poorest discriminative performance (AUC = 0.63 for the model without considering etiology and AUC = 0.45 for the model considering etiology). Using few variables and a relatively small number of patients, machine learning techniques added information to explanatory models for prediction of in-hospital mortality.

Treatment of Status Epilepticus in Pediatrics

Nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE) are commonly seen in neonates and children undergoing continuous electroencephalography (cEEG) in the pediatric, neonatal, cardiac, and surgical intensive care units. Nonconvulsive seizures and nonconvulsive status epilepticus have been estimated to occur in 7–46 % of children who undergo a clinically indicated EEG in the intensive care unit (ICU) [1–4]. The neonatal population is also at high risk as 14–43 % of neonates monitored meet the criteria for status epilepticus (SE), while as many as 80–90 % of neonatal seizures are electrographic only [5, 17].

Electrographic Seizures in Preterm Neonates in the Neonatal Intensive Care Unit

Objective: Characterize clinical and electroencephalography (EEG) characteristics of preterm neonates undergoing continuous EEG in the neonatal intensive care unit. Methods: Retrospective study of preterm neonates born less than 37 weeks’ gestational age undergoing continuous EEG in the neonatal intensive care unit at Boston Children’s Hospital over a 2-year period. Results: Fifty-two preterms (46% male) had a mean gestational age of 32.8 weeks (standard deviation = 4.17). Seizures were detected in 12/52 (23%), with EEG seizures detected in 4/12 (33%). The median time from EEG to the first seizure was 0.5 hours (interquartile range 0.24-4). Factors associated with seizures were male gender (odds ratio = 4.65 [95% confidence interval = 1.02-21.24], P = .047) and lack of EEG state change (odds ratio = 0.043 [95% confidence interval = 0.005-0.377], P = .04). Conclusion: Twenty-three percent of preterms undergoing continuous EEG had EEG seizures or electrographic seizures with no clear clinical correlate. This confirms recent American Clinical Neurophysiology Society guidelines suggesting that preterm neonates are at high risk for seizures.

Diagnostic and Therapeutic Management of a First Unprovoked Seizure in Children and Adolescents With a Focus on the Revised Diagnostic Criteria for Epilepsy

By definition, unprovoked seizures are not precipitated by an identifiable factor, such as fever or trauma. A thorough history and physical examination are essential to caring for pediatric patients with a potential first unprovoked seizure. Differential diagnosis, EEG, neuroimaging, laboratory tests, and initiation of treatment will be reviewed. Treatment is typically initiated after 2 unprovoked seizures, or after 1 seizure in select patients with distinct epilepsy syndromes. Recent expansion of the definition of epilepsy by the ILAE allows for the diagnosis of epilepsy to be made after the first seizure if the clinical presentation and supporting diagnostic studies suggest a greater than 60% chance of a second seizure. This review summarizes the current literature on the diagnostic and therapeutic management of first unprovoked seizure in children and adolescents while taking into consideration the revised diagnostic criteria of epilepsy.

Neurophysiological evidence of preserved connectivity in tuber tissue

We present a case of preserved corticospinal connectivity in a cortical tuber, in a 10 year-old boy with intractable epilepsy and tuberous sclerosis complex (TSC). The patient had multiple subcortical tubers, one of which was located in the right central sulcus. In preparation for epilepsy surgery, motor mapping, by neuronavigated transcranial magnetic stimulation (nTMS) coupled with surface electromyography (EMG) was performed to locate the primary motor cortical areas. The resulting functional motor map revealed expected corticospinal connectivity in the left precentral gyrus. Surprisingly, robust contralateral deltoid and tibialis anterior motor evoked potentials (MEPs) were also elicited with direct stimulation of the cortical tuber in the right central sulcus. MRI with diffusion tensor imaging (DTI) tractography confirmed corticospinal fibers originating in the tuber. As there are no current reports of preserved connectivity between a cortical tuber and the corticospinal tract, this case serves to highlight the functional interdigitation of tuber and eloquent cortex. Our case also illustrates the widening spectrum of neuropathological abnormality in TSC that is becoming apparent with modern MRI methodology. Finally, our finding underscores the need for further study of preserved function in tuber tissue during presurgical workup in patients with TSC.