EEG background as predictor of electrographic seizures in high-risk neonates

Leveraging electronic medical record-embedded standardised electroencephalogram reporting to develop neonatal seizure prediction models: a retrospective cohort study

BACKGROUND

Accurate prediction of seizures can help to direct resource-intense continuous electroencephalogram (CEEG) monitoring to neonates at high risk of seizures. We aimed to use data from standardised EEG reports to generate seizure prediction models for vulnerable neonates.

METHODS

In this retrospective cohort study, we included neonates who underwent CEEG during the first 30 days of life at the Children's Hospital of Philadelphia (Philadelphia, PA, USA). The hypoxic ischaemic encephalopathy subgroup included only patients with CEEG data during the first 5 days of life, International Classification of Diseases, revision 10, codes for hypoxic ischaemic encephalopathy, and documented therapeutic hypothermia. In January, 2018, we implemented a novel CEEG reporting system within the electronic medical record (EMR) using common data elements that incorporated standardised terminology. All neonatal CEEG data from Jan 10, 2018, to Feb 15, 2022, were extracted from the EMR using age at the time of CEEG. We developed logistic regression, decision tree, and random forest models of neonatal seizure prediction using EEG features on day 1 to predict seizures on future days.

FINDINGS

We evaluated 1117 neonates, including 150 neonates with hypoxic ischaemic encephalopathy, with CEEG data reported using standardised templates between Jan 10, 2018, and Feb 15, 2022. Implementation of a consistent EEG reporting system that documents discrete and standardised EEG variables resulted in more than 95% reporting of key EEG features. Several EEG features were highly correlated, and patients could be clustered on the basis of specific features. However, no simple combination of features adequately predicted seizure risk. We therefore applied computational models to complement clinical identification of neonates at high risk of seizures. Random forest models incorporating background features performed with classification accuracies of up to 90% (95% CI 83-94) for all neonates and 97% (88-99) for neonates with hypoxic ischaemic encephalopathy; recall (sensitivity) of up to 97% (91-100) for all neonates and 100% (100-100) for neonates with hypoxic ischaemic encephalopathy; and precision (positive predictive value) of up to 92% (84-96) in the overall cohort and 97% (80-99) in neonates with hypoxic ischaemic encephalopathy.

INTERPRETATION

Using data extracted from the standardised EEG report on the first day of CEEG, we predict the presence or absence of neonatal seizures on subsequent days with classification performances of more than 90%. This information, incorporated into routine care, could guide decisions about the necessity of continuing EEG monitoring beyond the first day, thereby improving the allocation of limited CEEG resources. Additionally, this analysis shows the benefits of standardised clinical data collection, which can drive learning health system approaches to personalised CEEG use.

FUNDING

Children's Hospital of Philadelphia, the Hartwell Foundation, the National Institute of Neurological Disorders and Stroke, and the Wolfson Foundation.

Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischemic encephalopathy

OBJECTIVE

To assess if early clinical and electroencephalography (EEG) features predict later seizure development in infants with hypoxic-ischemic encephalopathy (HIE).

METHODS

Clinical and EEG parameters <12 h of birth from infants with HIE across eight European Neonatal Units were used to develop seizure-prediction models. Clinical parameters included intrapartum complications, fetal distress, gestational age, delivery mode, gender, birth weight, Apgar scores, assisted ventilation, cord pH, and blood gases. The earliest EEG hour provided a qualitative analysis (discontinuity, amplitude, asymmetry/asynchrony, sleep-wake cycle [SWC]) and a quantitative analysis (power, discontinuity, spectral distribution, inter-hemispheric connectivity) from full montage and two-channel amplitude-integrated EEG (aEEG). Subgroup analysis, only including infants without anti-seizure medication (ASM) prior to EEG was also performed. Machine-learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver-operating characteristic curve (AUC).

RESULTS

The study included 162 infants with HIE (53 had seizures). Low Apgar, need for ventilation, high lactate, low base excess, absent SWC, low EEG power, and increased EEG discontinuity were associated with seizures. The following predictive models were developed: clinical (MCC 0.368, AUC 0.681), qualitative EEG (MCC 0.467, AUC 0.729), quantitative EEG (MCC 0.473, AUC 0.730), clinical and qualitative EEG (MCC 0.470, AUC 0.721), and clinical and quantitative EEG (MCC 0.513, AUC 0.746). The clinical and qualitative-EEG model significantly outperformed the clinical model alone (MCC 0.470 vs 0.368, p-value .037). The clinical and quantitative-EEG model significantly outperformed the clinical model (MCC 0.513 vs 0.368, p-value .012). The clinical and quantitative-EEG model for infants without ASM (n = 131) had MCC 0.588, AUC 0.832. Performance for quantitative aEEG (n = 159) was MCC 0.381, AUC 0.696 and clinical and quantitative aEEG was MCC 0.384, AUC 0.720.

SIGNIFICANCE

Early EEG background analysis combined with readily available clinical data helped predict infants who were at highest risk of seizures, hours before they occur. Automated quantitative-EEG analysis was as good as expert analysis for predicting seizures, supporting the use of automated assessment tools for early evaluation of HIE.

Neuromonitoring in neonatal critical care part I: neonatal encephalopathy and neonates with possible seizures

The blooming of neonatal neurocritical care over the last decade reflects substantial advances in neuromonitoring and neuroprotection. The most commonly used brain monitoring tools in the neonatal intensive care unit (NICU) are amplitude integrated EEG (aEEG), full multichannel continuous EEG (cEEG), and near-infrared spectroscopy (NIRS). While some published guidelines address individual tools, there is no consensus on consistent, efficient, and beneficial use of these modalities in common NICU scenarios. This work reviews current evidence to assist decision making for best utilization of neuromonitoring modalities in neonates with encephalopathy or with possible seizures. Neuromonitoring approaches in extremely premature and critically ill neonates are discussed separately in the companion paper. IMPACT: Neuromonitoring techniques hold promise for improving neonatal care. For neonatal encephalopathy, aEEG can assist in screening for eligibility for therapeutic hypothermia, though should not be used to exclude otherwise eligible neonates. Continuous cEEG, aEEG and NIRS through rewarming can assist in prognostication. For neonates with possible seizures, cEEG is the gold standard for detection and diagnosis. If not available, aEEG as a screening tool is superior to clinical assessment alone. The use of seizure detection algorithms can help with timely seizures detection at the bedside.

Clinical manifestations of neonatal seizures

Neonatal seizures present a unique diagnostic challenge with clinical manifestations often subtle or absent to the bedside observer. Seizures can be overdiagnosed in newborns with unusual paroxysmal movements and underdiagnosed in newborns without clinical signs of seizures. Electroclinical "uncoupling" also adds to the diagnostic challenge. Reliable diagnosis requires additional tools; continuous electroencephalogram (EEG) monitoring is the gold standard for diagnosis of neonatal seizures. Certain high-risk neonatal populations with known brain injury, such as stroke or hypoxic-ischemic encephalopathy, are most likely to benefit from continuous EEG. Studies have shown that risk stratification for continuous EEG has positive impact on care, including rapid and accurate diagnosis and treatment of neonatal seizures, which leads to reduced use of antiseizure medicines and length of hospital stay. This review describes common clinical manifestations of neonatal seizures, and clinical situations in which EEG monitoring to screen for seizures should be considered.

Does the first hour of continuous electroencephalography predict neonatal seizures?

OBJECTIVE

Prolonged continuous video-electroencephalography (cEEG) is recommended for neonates at risk of seizures. The cost and expertise required to provide a real-time response to detected seizures often limits its utility. We hypothesised that the first hour of cEEG could predict subsequent seizures.

DESIGN AND SETTING

Retrospective multicentre diagnostic accuracy study.

PATIENTS

266 term neonates at risk of seizure or with suspected seizures.

INTERVENTION

The first hour of cEEG was graded by expert and novice interpreters as normal, mildly, moderately or severely abnormal; seizures were identified.

MAIN OUTCOME MEASURES

Association between abnormalities in the first hour of cEEG and the presence of seizures during total cEEG monitoring.

RESULTS

50/98 (51%) of neonates who developed seizures had their first seizure in the first hour of cEEG monitoring. The 'time-to-event' risk of seizure from 0 to 96 hours was 0.38 (95% CI 0.32 to 0.44) while the risk in the first hour was 0.19 (95% CI 0.15 to 0.24). cEEG background was normal in 48% of neonates, mildly abnormal in 30%, moderately abnormal in 13% and severely abnormal in 9%. Inter-rater agreement for determination of background was very good (weighted kappa=0.81, 95% CI 0.72 to 0.91). When neonates with seizures during the first hour were excluded, an abnormal background resulted in 2.4 times increased risk of seizures during the subsequent monitoring period (95% CI 1.3 to 4.4, p<0.003) while a severely abnormal background resulted in a sevenfold increased risk (95% CI 3.4 to 14.3, p<0.0001).

CONCLUSIONS

The first hour of cEEG in at-risk neonates is useful in identifying and predicting whether seizures occur during cEEG monitoring up to 96 hours. This finding enables identification of high-risk neonates who require closer observation.

Early Electroencephalogram Background Could Guide Tailored Duration of Monitoring for Neonatal Encephalopathy Treated with Therapeutic Hypothermia

OBJECTIVE

To evaluate whether features of the early electroencephalographic (EEG) background could guide the optimal duration of continuous video EEG monitoring for seizure detection in newborn infants treated with therapeutic hypothermia for hypoxic ischemic encephalopathy (HIE).

STUDY DESIGN

Retrospective cohort study of 114 consecutive infants treated with therapeutic hypothermia for moderate to severe HIE at a level IV neonatal intensive care unit (NICU) between 2012 and 2018. All infants were monitored with continuous video EEG through cooling and rewarming. Archived samples from the first 24 hours of these EEG traces were reviewed systematically and classified by background characteristics.

RESULTS

Electrographic seizures occurred in 56 of the 114 infants (49%). Seizure onset was within the first 24 hours after initiation of continuous video EEG in 49 if these 56 infants (88%), between 24 and 48 hours in 4 infants (7%), and >72 hours in 3 infants (5%). Infants with a normal or mildly abnormal EEG background either had seizure onset within the first 24 hours or never developed seizures. Four patients with seizure onset between 24 and 48 hours had markedly abnormal EEG backgrounds. The 3 patients with seizure onset beyond 72 hours had moderate or severely abnormal early continuous video EEG backgrounds.

CONCLUSIONS

The use of early continuous video EEG background categorization may be appropriate to guide the duration of continuous video EEG for infants with HIE treated with therapeutic hypothermia. Some infants may reasonably be monitored for 24 hours rather than throughout cooling and rewarming without a significant risk of missed seizures. This could have significant implications for continuous video EEG resource utilization.

EEG Monitoring of the Epileptic Newborn

PURPOSE OF REVIEW

Although differentiating neonatal-onset epilepsies from acute symptomatic neonatal seizures has been increasingly recognized as crucial, existing guidelines, and recommendations on EEG monitoring are mainly based on acute symptomatic seizures, especially secondary to hypoxic-ischemic encephalopathy. We aimed to narratively review current knowledge on neonatal-onset epilepsies of genetic, metabolic, and structural non-acquired origin, with special emphasis on EEG features and monitoring.

RECENT FINDINGS

A wide range of rare conditions are increasingly described, reducing undiagnosed cases. Although distinguishing features are identifiable in some, how to best monitor and detect less described etiologies is still an issue. A comprehensive approach considering onset, seizure evolution, ictal semiology, clinical, laboratory, EEG, and neuroimaging data is key to diagnosis. Phenotypic variability prevents precise recommendations, but a solid, consistent method moving from existing published guidelines helps in correctly assessing these newborns in order to provide better care, especially in view of expanding precision therapies.

Acute Symptomatic Seizures in Neonates

Seizures are an important sign of neurologic dysfunction in neonates, and they most often represent acute brain injury such as hypoxic-ischemic encephalopathy, stroke, or intracranial hemorrhage (acute symptomatic seizures). Clinical identification of seizures is not reliable since seizures in neonates often do not have an apparent clinical correlate; therefore, electroencephalography should be used to accurately diagnose and manage neonatal seizures. Seizures are refractory to initial loading doses of standard medications in >50% of cases. Since seizures are commonly associated with adverse acute and long-term outcomes, and the seizures themselves may result in additional brain injury, it is important to quickly recognize, diagnose, and treat seizures in neonates. Local practice pathways may optimize efficiency in assessment and treatment for affected newborns. Herein, we review the etiology, methods of diagnosis, treatment, and current knowledge gaps for neonatal seizures.

Seizure Prediction Models in the Neonatal Intensive Care Unit

PURPOSE

Conventional video-EEG monitoring is required to diagnose seizures accurately in neonates. This tool is resource-intense and has limited availability in many centers. Seizure prediction models could help allocate resources by improving efficiency in which conventional video-EEG monitoring is used to detect subclinical seizures. The aim of this retrospective study was to create a neonate-specific seizure prediction model using clinical characteristics and EEG background findings.

METHODS

We conducted a 3-year retrospective study of all consecutive neonates who underwent conventional video-EEG monitoring at a tertiary care pediatric hospital. Variables including age, EEG indication, high-risk clinical characteristics, and EEG background informed seizure prediction models based on a multivariable logistic regression model. A Cox proportional hazard regression model was used to construct time to first EEG seizure.

RESULTS

Prediction models with clinical variables or background EEG features alone versus combined clinical and background EEG features were created from 210 neonates who met inclusion criteria. The combined clinical and EEG model had a higher area under the curve for combined sensitivity and specificity to 83.0% when compared to the clinical model (76.4%) or EEG model (66.2%). The same trend of higher sensitivity of the combined model was found for time to seizure outcome.

CONCLUSIONS

While both clinical and EEG background features were predictive of neonatal seizures, the combination improved overall prediction of seizure occurrence and prediction of time to first seizure as compared with prediction models based solely on clinical or EEG features alone. With prospective validation, this model may improve efficiency of patient-oriented EEG monitoring.

The probability of seizures during continuous EEG monitoring in high-risk neonates

OBJECTIVE

We evaluated the impact of monitoring indication, early electroencephalography (EEG), and clinical features on seizure risk in all neonates undergoing continuous EEG (cEEG) monitoring following a standardized monitoring protocol.

METHODS

All cEEGs from unique neonates 34-48 weeks postmenstrual age monitored from 1/2011-10/2017 (n = 291) were included. We evaluated the impact of cEEG monitoring indication (acute neonatal encephalopathy [ANE], suspicious clinical events [SCEs], or other high-risk conditions [OHRs]), age, medication status, and early EEG abnormalities (including the presence of epileptiform discharges and abnormal background continuity, amplitude, asymmetry, asynchrony, excessive sharp transients, and burst suppression) on time to first seizure and overall seizure risk using Kaplan-Meier survival curves and multivariable Cox proportional hazards models.

RESULTS

Seizures occurred in 28% of high-risk neonates. Discontinuation of monitoring after 24 hours of seizure-freedom would have missed 8.5% of neonates with seizures. Overall seizure risk was lower in neonates monitored for ANE compared to OHR (P = .004) and trended lower compared to SCE (P = .097). The time course of seizure presentation varied by group, where the probability of future seizure was less than 1% after 17 hours of seizure-free monitoring in the SCE group, but required 42 hours in the OHR group, and 73 hours in the ANE group. The presence of early epileptiform discharges increased seizure risk in each group (ANE: adjusted hazard ratio [aHR] 4.32, 95% confidence interval [CI] 1.23-15.13, P = .022; SCE: aHR 10.95, 95% CI 4.77-25.14, P < 1e-07; OHR: aHR 56.90, 95% CI 10.32-313.72, P < 1e-05).

SIGNIFICANCE

Neonates who undergo cEEG are at high risk for seizures, and risk varies by monitoring indication and early EEG findings. Seizures are captured in nearly all neonates undergoing monitoring for SCE within 24 hours of cEEG monitoring. Neonates monitored for OHR and ANE can present with delayed seizures and require longer durations of monitoring. Early epileptiform discharges are the best early EEG feature to predict seizure risk.

Interrater and Intrarater Agreement in Neonatal Electroencephalogram Background Scoring

PURPOSE

Many neonates undergo electroencephalogram (EEG) monitoring to identify and manage acute symptomatic seizures. Information about brain function contained in the EEG background data may also help predict neurobehavioral outcomes. For EEG background features to be useful as prognostic indicators, the interpretation of these features must be standardized across electroencephalographers. We aimed at determining the interrater and intrarater agreement among electroencephalographers interpreting neonatal EEG background patterns.

METHODS

Five neonatal electroencephalographers reviewed 5-to-7.5-minute epochs of EEG from full-term neonates who underwent continuous conventional EEG monitoring. The EEG assessment tool used to classify background patterns was based on the American Clinical Neurophysiology Society's guideline for neonatal EEG terminology. Interrater and intrarater agreement were measured using Kappa coefficients.

RESULTS

Interrater agreement was consistently highest for voltage (binary: substantial, kappa = 0.783; categorical: moderate, kappa = 0.562), seizure presence (fair-substantial; kappa = 0.375-0.697), continuity (moderate; kappa = 0.481), burst voltage (moderate; kappa = 0.574), suppressed background presence (moderate-substantial; kappa = 0.493-0.643), delta activity presence (fair-moderate; kappa = 0.369-0.432), theta activity presence (fair-moderate; kappa = 0.347-0.600), presence of graphoelements (fair; kappa = 0.381), and overall impression (binary: moderate, kappa = 0.495; categorical: fair-moderate, kappa = 0.347, 0.465). Agreement was poor or inconsistent for all other patterns. Intrarater agreement was variable, with highest average agreement for voltage (binary: substantial, kappa = 0.75; categorical: substantial, kappa = 0.714) and highest consistent agreement for continuity (moderate-substantial; kappa = 0.43-0.67) and overall impression (moderate-substantial; kappa = 0.42-0.68).

CONCLUSIONS

This study demonstrates substantial variability in neonatal EEG background interpretation across electroencephalographers, indicating a need for educational and technological strategies aimed at improving performance.

Predictive value of early EEG for seizures in neonates with hypoxic-ischemic encephalopathy undergoing therapeutic hypothermia

OBJECTIVES

To assess the prognostic significance of an early normal/mildly abnormal conventional EEG (cEEG) on seizure risk in neonates undergoing therapeutic hypothermia.

METHODS

We reviewed the video-EEG recordings from a large cohort of neonates treated with therapeutic hypothermia for hypoxic-ischemic encephalopathy from 2008 to 2017 in a single tertiary center. Continuous video-EEG was started as soon as possible (median 8.2 h) and continued throughout hypothermia and rewarming. We studied those neonates with a normal/mildly abnormal EEG during the first 24 h of monitoring.

RESULTS

A total of 331 neonates were treated with hypothermia and 323 had cEEG recordings available for review; 99 were excluded because of a moderately/severely abnormal cEEG background and/or seizure during the first 24 h of recording, and an additional eight because of early rewarming. The remaining 216 had a normal/mildly abnormal cEEG in the first 24 h. None of these patients subsequently developed seizures.

CONCLUSION

A normal/mildly abnormal cEEG during the first 24 h indicates a very low risk of subsequent seizures. This suggests that cEEG monitoring can be safely discontinued after 24 h if it has remained normal or excessively discontinuous and no seizures are detected, limiting the need for this resource-intensive and expensive tool.

Outcomes following electrographic seizures and electrographic status epilepticus in the pediatric and neonatal ICUs

PURPOSE OF REVIEW

Increasing recognition of electrographic seizures and electrographic status epilepticus in critically ill neonates and children has highlighted the importance of identifying their potential contributions to neurological outcomes to guide optimal management.

RECENT FINDINGS

Recent studies in children and neonates have found an independent association between increasing seizure burden and worse short-term and long-term outcomes, even after adjusting for other important contributors to outcome such as seizure cause and illness severity. The risk of worse neurological outcome has been shown to increase above a seizure burden threshold of 12-13 min/h, which is considerably lower than the conventional definition of status epilepticus of 30 min/h. Randomized controlled trials in neonates have demonstrated that electroencephalography-targeted therapy can successfully reduce seizure burden, but due to their small size these trials have not been able to demonstrate that more aggressive electroencephalography-targeted treatment of both subclinical and clinical seizures results in improved outcome.

SUMMARY

Despite mounting evidence for an independent association between increasing seizure burden and worse outcome, further study is needed to determine whether early seizure identification and aggressive antiseizure treatment can improve neurodevelopmental outcomes.

Prediction of Neonatal Seizures in Hypoxic-Ischemic Encephalopathy Using Electroencephalograph Power Analyses

BACKGROUND

The severity of the initial encephalopathy in neonatal hypoxic-ischemic encephalopathy correlates with seizure burden. Early electroencephalograph (EEG) background activity reflects the severity of encephalopathy. Thus, we hypothesized that early EEG background would be predictive of subsequent seizures in neonatal hypoxic-ischemic encephalopathy.

METHODS

This study included infants undergoing therapeutic hypothermia at St. Louis Children's Hospital between January 2009 and April 2013. Two pediatric epilepsy specialists independently characterized EEG background qualitatively using amplitude-integrated EEG trends. Total EEG power in the 1-20 Hz frequency band was calculated for quantitative EEG background assessment. Seizures were identified on conventional full montage EEG. Statistical analysis was performed using logistic regression.

RESULTS

Seventy-eight of the 93 eligible infants had artifact-free EEG data; 23 of 78 infants (29%) developed seizures, and of these, 11 developed status epilepticus. The best predictors of subsequent seizures during the first hour of EEG recording were a flat tracing pattern on amplitude-integrated EEG (sensitivity 26%, specificity 98%, likelihood ratio 13, positive predictive value 85%) and the total EEG power less than 10 μV² (sensitivity 52%, specificity 98%, likelihood ratio 30, positive predictive value 92%).

CONCLUSIONS

Early EEG biomarkers predict subsequent seizures in infants with hypoxic-ischemic encephalopathy. Compared with the qualitative amplitude-integrated EEG background, total EEG power improves our ability to identify high-risk infants from the first hour of EEG recording. Infants with a total EEG power of less than 10 μV² have a 90% risk of subsequent seizures. Quantitative EEG measures could stratify cohorts while evaluating novel neuroprotective strategies in neonatal hypoxic-ischemic encephalopathy.

Evaluation of Dry Sensors for Neonatal EEG Recordings

PURPOSE

Neonatal seizures are a common neurologic diagnosis in neonatal intensive care units, occurring in approximately 14,000 newborns annually in the United States. Although the only reliable means of detecting and treating neonatal seizures is with an electroencephalography (EEG) recording, many neonates do not receive an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include (1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, (2) poor signal quality because of improper skin preparation and artifact, and (3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not previously been evaluated on neonates.

METHODS

Sequential and simultaneous recordings with wet and dry sensors were performed for 1 hour on 27 neonates from 35 to 42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined.

RESULTS

Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8), given the nonsuperimposed sensor positions and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically relevant EEG background and seizure patterns. There was no skin injury after 1 hour of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix.

CONCLUSIONS

Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury.

Monitoring of newborns at high risk for brain injury

Due to the increasing number of surviving preterm newborns and to the recognition of therapeutic hypothermia as the current gold standard in newborns with hypoxic-ischaemic encephalopathy, there has been a growing interest in the implementation of brain monitoring tools in newborns at high risk for neurological disorders.Among the most frequent neurological conditions and presentations in the neonatal period, neonatal seizures and neonatal status epilepticus, paroxysmal non-epileptic motor phenomena, hypoxic-ischaemic encephalopathy, white matter injury of prematurity and stroke require specific approaches to diagnosis. In this review we will describe the characteristics, aims, indications and limitations of routinely available diagnostic techniques such as conventional and amplitude-integrated EEG, evoked potentials, cranial ultrasound and brain MRI. We will conclude by briefly outlining potential future perspectives from research studies.

Diagnostic Yield of Continuous Video EEG for Neonatal Seizures

Investigators from the University of California, San Francisco studied the yield of continuous video EEG (vEEG) in diagnosing electrographic seizures in their neonatal intensive care unit.

Continuous long-term electroencephalography: the gold standard for neonatal seizure diagnosis

Newborn infants at risk for cerebral dysfunction, such as those with acute brain injury or with disorders of brain development, often have encephalopathy and seizures. Conventional electroencephalography (EEG) monitoring can enhance the care of these highly vulnerable patients, through identification of prognostically significant EEG background patterns and accurate diagnosis of seizures and non-seizure paroxysmal events. Neonatal seizures are usually subclinical, and abnormal neonatal movements are often not the result of seizures. Judicious use of conventional EEG monitoring can provide precise diagnosis, quantify seizures, and guide treatment--neonates with EEG-proven seizures should receive appropriate medications and those whose events are not seizures may be spared unnecessary exposure to medications that have potentially important side-effects.

Risk factors for EEG seizures in neonates treated with hypothermia: a multicenter cohort study

OBJECTIVE

To assess the risk factors for electrographic seizures among neonates treated with therapeutic hypothermia for hypoxic-ischemic encephalopathy (HIE).

METHODS

Three-center observational cohort study of 90 term neonates treated with hypothermia, monitored with continuous video-EEG (cEEG) within the first day of life (median age at onset of recording 9.5 hours, interquartile range 6.3-14.5), and continued for >24 hours (total recording 93.3 hours, interquartile range 80.1-112.8 among survivors). A pediatric electroencephalographer at each site reviewed cEEGs for electrographic seizures and initial EEG background category.

RESULTS

A total of 43 (48%) had electrographic seizures, including 9 (10%) with electrographic status epilepticus. Abnormal initial EEG background classification (excessively discontinuous, depressed and undifferentiated, burst suppression, or extremely low voltage), but not clinical variables (including pH <6.8, base excess ≤-20, or 10-minute Apgar ≤ 3), was strongly associated with seizures.

CONCLUSIONS

Electrographic seizures are common among neonates with HIE undergoing hypothermia and are difficult to predict based on clinical features. These results justify the recommendation for cEEG monitoring in neonates treated with hypothermia.

Electrographic seizures and status epilepticus in critically ill children and neonates with encephalopathy

Electrographic seizures are seizures that are evident on EEG monitoring. They are common in critically ill children and neonates with acute encephalopathy. Most electrographic seizures have no associated clinical changes, and continuous EEG monitoring is necessary for identification. The effect of electrographic seizures on outcome is the focus of active investigation. Studies have shown that a high burden of electrographic seizures is associated with worsened clinical outcome after adjustment for cause and severity of brain injury, suggesting that a high burden of such seizures might independently contribute to secondary brain injury. Further research is needed to determine whether identification and management of electrographic seizures reduces secondary brain injury and improves outcome in critically ill children and neonates.

Continuous EEG monitoring in the neonatal intensive care unit

Continuous EEG monitoring provides an opportunity to both accurately identify seizures and monitor the neurologic status of critically ill neonates in the intensive care unit. The incidence of seizures is higher in the neonatal period than at any other time in life. Seizures and abnormalities of EEG background are associated with significant risk of mortality and long-term neurodevelopmental morbidities. In the neonatal population the majority of seizures are not clinically evident and go undetected without EEG monitoring. We review the incidence and risk factors for neonatal seizures, and the utility of continuous EEG monitoring in the neonatal intensive care unit for seizure detection and for analysis of background to allow prognostication. We consider the role of amplitude-integrated EEG in the neonatal population. We consider the utility of continuous EEG for frequently encountered neurologic indications and discuss the outcome data and some new developments in continuous EEG monitoring.

Prognostic factors of developmental outcome in neonatal seizures in term infants

BACKGROUND

The purpose of this study was to identify prognostic indicators of neurodevelopmental outcome in term infants who experienced clinical neonatal seizure.

METHODS

This is a retrospective, observational hospital-based study. Term infants who experienced clinical neonatal seizure between January 1999 and December 2009 were enrolled. Adverse outcomes were defined as death, cerebral palsy, global developmental delay, and/or epilepsy. The associations between adverse outcomes and 17 variables, including sex, mode of delivery, being small of gestational age, maternal illness, perinatal insults, meconium stained liquor, Apgar score at 1 and 5 minutes, seizure onset age, seizure type, etiology, electroencephalography (EEG) findings, antiepileptic drug efficacy, presence of metabolic acidosis, and cranial ultrasonographic findings, and presence of congenital heart disease were analyzed.

RESULTS

Among the 232 enrolled infants, 125 had a normal outcome and 14 had mild functional disability (59.9%), and 55 (23.7%) survived with one or more neurodevelopmental impairments (7 with cerebral palsy, 48 with global developmental delay), and 38 (16.4%) died. Forty-seven (23.0%) of the 204 patients who survived after the first discharge had epilepsy. Ten variables were associated with adverse outcome on univariate analysis, but only four variables, i.e., including abnormal cranial ultrasonography findings, abnormal anterior cerebral artery resistance index, abnormal EEG findings, and presence of congenital heart disease were independent predictors on multivariate logistic regression analysis.

CONCLUSION

In term infants with neonatal seizures, several risk factors related to adverse outcome were recognized. Physicians should pay more attention to these factors when handling patients with neonatal seizures.

Prediction of neurodevelopmental outcome in term neonates with hypoxic-ischemic encephalopathy

BACKGROUND

Hypoxic ischemic encephalopathy may result in many neurological deficits. It is crucial to make early diagnosis and assess the prognosis correctly.

AIMS

We aimed to determine the factors to evaluate the prognosis of hypoxic ischemic encephalopathy.

METHODS

Electroencephalography, neuroimaging, periodic neurological exams and a developmental test at 44-48 months after discharge from the hospital were performed on twenty five term newborn infants with clinical evidence of hypoxic ischemic encephalopathy.

RESULTS

Normal/mildly abnormal neonatal electroencephalography correlated with favorable outcome, particularly if neuroimaging was normal. The cranial MRI sensitivity was 83.3%, while the specificity was 57.9%, the positive predictive value was 38.5%, and the negative predictive value was 91.6%. Moderate/severely abnormal electroencephalography and multifocal/diffuse cortical or deep gray matter lesions correlated with poor outcome.

CONCLUSIONS

Newborn infants with hypoxic ischemic encephalopathy should be treated in neonatal intensive care units, assessed with periodic neurological examination, electroencephalogram and brain imaging. This would help to initiate early intervention and improve the outcome of patients.

Continuous electroencephalography monitoring in neonates

As more critically ill term and premature neonates are surviving their acute illness, their long-term neurodevelopmental morbidity is being recognized. Continuous monitoring of cerebral function, with electroencephalography or derived digital trends, can provide key information regarding seizures and background patterns, with direct treatment and prognostic implications. Conventional video-electroencephalography remains the gold standard for neonatal seizure diagnosis and quantification, but can be supplemented by digital trending modalities. Both conventional and amplitude-integrated electroencephalography can provide valuable data regarding the background trends. This review describes indications and methods for continuous electroencephalography monitoring in high-risk neonates.

Evaluation of etiologic and prognostic factors in neonatal convulsions

This study evaluated etiologic and risk factors affecting long-term prognoses of neurologic outcomes in newborns with neonatal seizures. We enrolled patients at chronologic ages of 23-44 months, referred to the Department of Pediatric Neurology, Istanbul Medical Faculty, from January 1, 2007-December 31, 2009, after manifesting seizures in their first postnatal 28 days. Of 112 newborns, 41 were female, 71 were male, 33 were preterm, and 79 were full-term. Perinatal asphyxia (28.6%) and intracranial hemorrhage (17%) were the most common causes of neonatal seizures. Cerebral palsy developed in 27.6% of patients during follow-up. The incidence of epilepsy was 35.7%. Almost 50% of patients manifested developmental delay in one or more areas. Global developmental delay was the most common (50.8%) neurologic disorder. The correlation between gestational age or birth weight and adverse outcomes was nonsignificant. Etiology, Apgar score, need for resuscitation at birth, background electroencephalogram, neonatal status epilepticus, cranial imaging findings, type/duration of antiepileptic treatment, and response to acute treatment were all strong prognostic factors in neurologic outcomes. Neonatal seizures pose a threat of neurologic sequelae for preterm and full-term infants. Although the number of recognized etiologic factors in neonatal seizures has increased because of improvements in neonatology and diagnostic methods, perinatal asphyxia remains the most common factor.

State of consciousness and interictal epileptiform discharges predict seizure occurrence during routine EEG

OBJECTIVES

To identify the patients who are more likely to experience a seizure during routine electroencephalography (EEG) recording.

METHODS

We retrospectively reviewed the EEG recordings and medical records of 262 patients, who were admitted in the Neurology Department in Assaf Harofeh Medical Center and referred to the EEG laboratory between October 2006 and 2008 after a seizure.

RESULTS

Eighteen (6.8%) patients had seizures during routine EEG [patients with seizures (PWS)]. The likelihood of seizure occurrence during routine EEG was increased by the presence of interictal epileptiform discharges (odds ratio, 29.85; 95% confidence interval, 6.54-136.21; P=0.001) and abnormal state of consciousness (odds ratio, 9.04; 95% confidence interval, 1.02-80.33; P=0.037). Increased seizure frequency before admission, localization-related epilepsy, and EEG background slowing were significantly more common among PWS compared with patients without seizures on routine EEG (P=0.009, 0.042, and 0.036, respectively).

CONCLUSIONS

The presence of interictal epileptiform discharges and decreased state of consciousness increase significantly the likelihood of seizure occurrence during routine EEG. Localization-related epilepsy, increased seizure frequency before admission, and EEG background slowing are more common among PWS.

Ictal electroencephalograms in neonatal seizures: characteristics and associations

The characteristics of ictal electroencephalograms in 160 neonatal seizures of 43 babies were correlated with mortality and neurodevelopmental outcomes. Neonatal seizures are focal at onset, most frequently temporal, and often occur during sleep. Twenty-one percent of babies with seizures died, and 76% of survivors manifested neurodevelopmental impairment during 2-6-year follow-up. A low-amplitude ictal electroencephalogram discharge was associated with increased mortality, and a frequency of <2 Hz with increased morbidity. Status epilepticus, ictal fractions, multiple foci, and bihemispheric involvement did not influence outcomes. Of 160 seizures, 99 exhibited no associated clinical features (electrographic seizures). Neonatal seizures with clinical correlates (electroclinical seizures) exhibited a higher amplitude and frequency of ictal electroencephalogram discharge than electrographic seizures. During electroclinical seizures, the ictal electroencephalogram was more likely to involve larger areas of the brain and to cross the midline. Mortality and morbidity were similar in babies with electroclinical and electrographic seizures, emphasizing the need to diagnose and treat both types. Ictal electroencephalogram topography has implications for electrode application during limited-channel, amplitude-integrated electroencephalograms. We recommend temporal and paracentral electrodes. Video electroencephalograms are important in diagnosing neonatal seizures and providing useful information regarding ictal electroencephalogram characteristics.

The use of conventional EEG for the assessment of hypoxic ischaemic encephalopathy in the newborn: a review

Neonatal hypoxic ischaemic encephalopathy continues to be one of the leading causes of morbidity and mortality among neonates around the globe. With the advent of therapeutic hypothermia, the need to accurately classify the severity of injury in the early neonatal period is of great importance. As clinical measures cannot always accurately estimate the severity early enough for treatment to be initiated, clinicians have become more dependent on conventional and amplitude integrated EEG. Despite this, there is currently no single agreed classification scheme for the neonatal EEG in hypoxic ischaemic encephalopathy. In this review we discuss classification schemes of neonatal background EEG, published over the past 35 years, highlighting the urgent need for a universal visual analysis scheme.

Neonatal electroencephalography: review of a practical approach

Neonatal electroencephalography (EEG) recordings have routinely been performed for more than half a century. ''Old'' technical difficulties are no longer of concern with the advent of modern digital technology. Still, many ''old'' issues are at debate: characterization of neonatal EEG features, identification of EEG waveforms with potential clinical correlates, the role of neonatal EEG in prediction of neurodevelopmental outcome, and use of new devices. In the past decades, neonatal EEG and emerging issues' literature has greatly expanded. In this review, the authors have summarized some of these issues to increase the availability of the information for both clinical and research purposes. They propose an up-to-date concentrated practical approach to this rapidly expanding ''subfield'' of neonatal neurology.

Clinical seizures in neonatal hypoxic-ischemic encephalopathy have no independent impact on neurodevelopmental outcome: secondary analyses of data from the neonatal research network hypothermia trial

It remains controversial as to whether neonatal seizures have additional direct effects on the developing brain separate from the severity of the underlying encephalopathy. Using data collected from infants diagnosed with hypoxic-ischemic encephalopathy, and who were enrolled in an National Institute of Child Health and Human Development trial of hypothermia, we analyzed associations between neonatal clinical seizures and outcomes at 18 months of age. Of the 208 infants enrolled, 102 received whole body hypothermia and 106 were controls. Clinical seizures were generally noted during the first 4 days of life and rarely afterward. When adjustment was made for study treatment and severity of encephalopathy, seizures were not associated with death, or moderate or severe disability, or lower Bayley Mental Development Index scores at 18 months of life. Among infants diagnosed with hypoxic-ischemic encephalopathy, the mortality and morbidity often attributed to neonatal seizures can be better explained by the underlying severity of encephalopathy.

Neurodevelopmental outcomes in neonates with seizures: a numerical score of background encephalography to help prognosticate

There is a high incidence of mortality and neurodevelopmental sequelae in babies with neonatal seizures. The electroencephalography (EEG) background has been shown to be an excellent predictor of outcome by most studies, with a few suggesting limited value in prognostication. Previous studies suggest poor prognosis with severely abnormal backgrounds, but prediction was difficult with moderate abnormalities. The proposed numerical scoring system for the EEG background provides an objective method of evaluation with improved reproducibility, categorization, and prognostication. Our study showed that the numerical score of EEG background was a good predictor of outcome. Higher numerical scores reflecting greater abnormality of background EEG were associated with increasing incidence of mortality, neurodevelopmental impairment, cerebral palsy, vision and hearing impairment, and epilepsy. The numerical score also correlated with neuroimaging abnormalities. A numerical EEG score can help target interventional strategies for neonatal seizures.

Rapid oscillatory activity in delta brushes of premature and term neonatal EEG

We compared frequency and power of neonatal EEG delta brush rapid oscillatory activity (ROA) using multiple band frequency analysis (MBFA) in three groups; pre-term (PT, post-conceptional age 33-35.6 weeks, n=5); full-term (FT, 39.4-40.6 weeks, n=5) and pre-term or full-term with phenobarbital exposure (PB, n=5). Mean number of delta brushes analyzed was 29.4 (range 26-47) in PT, 20.8 (14-33) in FT and 20 (7-37) in PB. Mean frequency+/-standard deviation (s.d.) was 16.9+/-2.1 Hz (range 15-20 Hz) in PT, 17.3+/-1.9 Hz (15-20 Hz) in FT and 16.1+/-1.6 Hz (14-19 Hz) in PB. Mean power+/-s.d. was 22.9+/-6.2 microV(2) (range 16-39 microV(2)) in PT, 11.9+/-4.1 microV(2) (7-19 microV(2)) in FT and 17.1+/-6.2 microV(2) (9-26 microV(2)) in PB. Power was significantly higher in PT than FT (p<0.005). Power after merging PB into respective PT (PT', n=8) and FT (FT', n=7) groups, remained significantly higher in PT' (mean+/-s.d. 21.8+/-7.4 microV(2)) than FT' (11.4+/-3.6 microV(2)) (p<0.05). We characterise ROA in delta brushes in maturing neonates using MBFA, which may provide additional information for assessing future seizure recurrence and epilepsy risk.

Technical standards for recording and interpretation of neonatal electroencephalogram in clinical practice

Neonatal electroencephalogram (EEG), though often perceived as being difficult to record and interpret, is relatively easy to study due to the immature nature of the brain, which expresses only a few well-defined set of patterns. The EEG interpreter needs to be aware of the maturational changes as well as the effect of pathological processes and medication on brain activity. It gives valuable information for the treatment and prognostication in encephalopathic neonates. In this group, serial EEGs or EEG monitoring often gives additional information regarding deterioration/improvement of the brain function or occurrence of seizures.

Clinical Neonatal Seizures are Independently Associated with Outcome in Infants at Risk for Hypoxic-Ischemic Brain Injury

OBJECTIVE

To examine whether neonatal seizures are associated with neurodevelopmental outcomes in infants with hypoxia-ischemia independent of the presence and severity of brain injury seen on magnetic resonance imaging (MRI).

STUDY DESIGN

We used multivariate regression to examine the independent effect of clinical neonatal seizures and their treatment on neurodevelopment in 77 term newborns at risk for hypoxic-ischemic brain injury. Clinical seizures were recorded prospectively, and high-resolution newborn MRI measured the severity of brain injury. The outcome measure was the Full-Scale Intelligence Quotient (FSIQ) of the Wechsler Preschool and Primary Scale of Intelligence-Revised and neuromotor score at age 4 years.

RESULTS

After controlling for severity of injury on MRI, the children with neonatal seizures had worse motor and cognitive outcomes compared with those without seizures. The magnitude of effect varied with seizure severity; children with severe seizures had a lower FSIQ than those with mild/moderate seizures (P < .0001).

CONCLUSIONS

Clinical neonatal seizures in the setting of birth asphyxia are associated with worse neurodevelopmental outcome, independent of the severity of hypoxic-ischemic brain injury. Randomized controlled trials are needed to determine whether differences in seizure treatment can improve outcome.

Quality of general movements in term infants with asphyxia

BACKGROUND

Perinatal asphyxia may result in a developmental disorder. A recently developed non-invasive tool to investigate brain function at an early age is the assessment of general movements (GMs).

AIM

To evaluate relationships between perinatal risk factors and the quality of GMs in the neonatal period and at 3 months in term newborns with asphyxia in a secondary paediatric setting.

METHODS

64 term (>36 weeks postmenstrual age (PMA)) infants with perinatal asphyxia were studied. GMs were assessed at 'writhing' GM age (38-47 weeks PMA) and at 'fidgety' GM age (48-56 weeks PMA). Pre- and perinatal factors were collected in a standardized way.

RESULTS

Multivariate analysis revealed that DA GMs at 'writhing' age mainly correlated with asphyxia related illness. DA GMs at 'fidgety' age correlated in particular with abnormalities on the neonatal ultrasound scan of the brain.

CONCLUSION

In secondary paediatric settings GM-assessment especially around 3 months is a valuable tool for the assessment of the integrity of the nervous system in term infants with asphyxia.

Assessment of neonatal electroencephalography (EEG) background by conventional and two amplitude-integrated EEG classification systems

OBJECTIVE

To determine the agreement among conventional electroencephalography (CEEG) terminology background classification and a simple and an advanced amplitude-integrated EEG (aEEG) system, and to evaluate whether aEEG interpreter experience or electrographic seizures affect this agreement.

STUDY DESIGN

CEEG background was classified by traditional interpretive criteria for 144 neonatal recordings, from which a single channel was converted to aEEGs. These aEEGs were independently interpreted by neonatologists according to the simple and advanced classification systems.

RESULTS

Interreader agreement was better with the simple aEEG system compared with the advanced aEEG system (multirater kappa, 0.66 vs 0.44). Fair-to-moderate agreement was found between both of the aEEG classification systems and CEEG (simple: kappa, 0.34 to 0.45; advanced: kappa, 0.36 to 0.45). Agreement did not vary significantly based on the aEEG interpreter experience or the presence of seizures.

CONCLUSIONS

Neonatologists found better agreement using the simple aEEG system regardless of their expertise or the presence of seizures. This finding has implications for patient selection in future multicenter neonatal neuroprotection studies.

Predictive value of sequential electroencephalogram (EEG) in neonates with seizures and its relation to neurological outcome

The aim of this study was to evaluate the relationship of sequential neonatal electroencephalography (EEG) and neurological outcome in neonates with seizures to identify polysomnographic features predictive of outcome. Sequential EEGs recordings of 58 neonates that belonged to 2 historical cohorts of newborns with seizures from the same neonatal intensive care unit and who had follow-up at the Neurodevelopment Clinic of the Hospital São Lucas, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) in Porto Alegre, Brazil, were analyzed and classified into 4 groups: normal-normal, abnormal-normal, abnormal-abnormal, normal-abnormal. In patients with more than 2 recordings, during the neonatal period, the first EEG was compared with the following more abnormal. A total of 58 pairs of 2 sequential EEGs were analyzed. Considering the first EEG, a statistically significant difference was observed between the relationship of the result of this exam, if it was abnormal, with developmental delay (P = .030) and postnatal death (P = .030). Abnormal background activity was also related to neurodevelopment delay (P = .041). EEG sequences abnormal-abnormal and normal-abnormal significantly correlated to the outcome epilepsy ( P = .015). Abnormal sequential background activity was associated with neurodevelopment delay (P = .006) and epilepsy (P = .041). The burst suppression pattern when present in any EEG correlated with epilepsy (P = .013) and postnatal death (P = .034). Sequential abnormal background patterns in the first and second EEG increased the risk for epilepsy (relative risk [RR] = 1.8; 95% confidence interval [CI] = 1.03-3.0) and neurodevelopment delay (RR = 2.20; 95% CI = 1.3-3.0). Abnormal background activity only in the second electroencephalogram increased the risk for neurodevelopment delay (RR = 2.20; 95% CI = 1.3-3.0). All the neonates (n = 33) with seizures related to probable hypoxic ischemic encephalopathy had abnormalities in the first EEG (P = .030). Postnatal epilepsy was diagnosed in 24 infants (41.4%). Five (20.8%) presented West syndrome, 7 (29.2%) focal symptomatic epilepsy, 6 (25%) generalized symptomatic epilepsy, 2 (8.3%) early myoclonic encephalopathy, 1 (4.2%) early infantile epileptic encephalopathy, and in 3, the epileptic syndrome was undefined (12.5%). All infants (n = 5) with West syndrome had some degree of neurodevelopment delay. In conclusion, our findings suggest that sequential EEG in neonates with seizures has more predictive value to estimate the outcomes of neurodevelopment delay, epilepsy, and postnatal death than a single EEG recording. The abnormal background activity in even 1 EEG of the sequential recordings was more significant to determine neurological outcome than abnormal ictal activity or abnormalities in the organization of sleep state.

Prolonged electroencephalogram monitoring for seizures and their treatment

This article reviews the diagnosis of neonatal seizures using routine electroencephalogram (EEG) examinations and long-term EEG monitoring. EEG is considered the gold standard for identifying the presence and quantifying the burden of neonatal seizures. The most common medication used to treat neonatal seizures is phenobarbital, although its efficacy has never been demonstrated by a formal, randomized, placebo-controlled drug trial.

The current etiologic profile and neurodevelopmental outcome of seizures in term newborn infants

OBJECTIVES

The objectives of this study were to delineate the etiologic profile and neurodevelopmental outcome of neonatal seizures in the current era of neonatal intensive care and to identify predictors of neurodevelopmental outcome in survivors.

METHODS

Eighty-nine term infants with clinical neonatal seizures underwent neurologic examination, electroencephalography (EEG), neuroimaging, and extensive diagnostic tests in the newborn period. After discharge, all infants underwent regular neurologic evaluations and, at 12 to 18 months, formal neurodevelopmental testing. We tested the prognostic value of seizure etiology, neurologic examination, EEG, and neuroimaging.

RESULTS

Etiology was found in 77 infants. Global cerebral hypoxia-ischemia, focal cerebral hypoxia-ischemia, and intracranial hemorrhage were most common. Neonatal mortality was 7%; 28% of the survivors had poor long-term outcome. Association between seizure etiology and outcome was strong, with cerebral dysgenesis and global hypoxia-ischemia associated with poor outcome. Normal neonatal period/early infancy neurologic examination was associated with uniformly favorable outcome at 12 to 18 months; abnormal examination lacked specificity. Normal/mildly abnormal neonatal EEG had favorable outcome, particularly if neonatal neuroimaging was normal. Moderate/severely abnormal EEG, and multifocal/diffuse cortical or primarily deep gray matter lesions, had a worse outcome.

CONCLUSIONS

Mortality associated with neonatal seizures has declined although long-term neurodevelopmental morbidity remains unchanged. Seizure etiology and background EEG patterns remain powerful prognostic factors. Diagnostic advances have changed the etiologic distribution for neonatal seizures and improved accuracy of outcome prediction. Global cerebral hypoxia-ischemia, the most common etiology, is responsible for the large majority of infants with poor long-term outcome.

Prognostic value of EEG performed at term age in preterm infants

RATIONALE

Electroencephalography (EEG) was performed at term age on 32 infants born prematurely (25-32 weeks). EEG was assessed looking for overall background activity and transients.

METHODS

A quantitative analysis was performed, selecting 5-min epochs of "tracé alternant" free of artefacts during quiet sleep. EEG findings were compared with cranial ultrasound (US) findings at term age and with neurodevelopmental outcome at 2 years (Student's t-test).

RESULTS

The overall EEG background activity was not always related to the outcome or to the severity of cranial US. Infants with normal US and normal outcome had longer synchrony percentage of bursts, longer maximum duration of bursts and shorter mean of abnormal transients per interbursts than children with major lesions and abnormal outcome. Infants with minor lesions, who all had normal outcome, also had better results than those with major lesions and abnormal outcome, but the range of the EEG findings was more variable.

CONCLUSION

Our results suggest that the EEG performed at term age does not provide additional prognostic information compared to cranial US.

The relationship between ictal activity and sleep stages in the newborn EEG

OBJECTIVE

To verify the relationship of ictal activity and sleep organization (REM/NREM stages) in the neonatal EEG.

METHODS

A retrospective study was developed with 41 high-risk newborns, with clinical history suggestive of seizures and ictal activity identified by the EEG. In each EEG, sleep organization and number/duration of sleep stages were determined. Sleep stages (REM, NREM) were scored following behavior and EEG activity. When it was impossible to recognize stages the epoch was classified as unrecognizable sleep stages (UNSS). Ictal activity was classified according to morphology and correlated with sleep epochs. Density of ictal activity was calculated as the duration of the discharge divided by the duration of the sleep epoch.

RESULTS

Unrecognizable sleep stages were observed in 21 EEGs (51.2%). Comparing NREM X REM states there was a significant predominance of ictal activity in REM sleep (P = 0.01). Duration of discharges was longer on REM epochs; however, differences were not significant. Considering the type of discharges there was a predominance of monomorphic rhythmic discharges in all sleep epochs.

CONCLUSIONS

In this sample, epileptogenic activity occurred more frequently in UNSS, where sleep organization was already disrupted. When it was possible to recognize sleep stages, ictal activity was more frequently during REM sleep.

SIGNIFICANCE

This study speculates the relationship between sleep organization and ictal activity and raises the hypothesis that the expression of ictal activity in relation to sleep stages (REM/NREM) may have age-dependent mechanisms in the developing brain.

Electroencephalography in neonatal seizures: comparison of a reduced and a full 10/20 montage

This study compares a reduced electrode montage (9 electrodes) with the full 10/20 electrode montage for the ability to detect and characterize neonatal seizures and background electroencephalographic (EEG) characteristics, utilizing new digital technology allowing "remontage" of previously acquired records. A total of 151 neonatal EEG records were retrospectively and blindly analyzed by two readers. Records were first analyzed for seizure number, topography, duration, and characteristics of EEG background using the reduced montage, before reanalysis with the full montage. One hundred eighty-seven seizures were identified in 31 ictal recordings using the full montage. Using the reduced montage, 166 seizures were identified in 30 records. The sensitivity and specificity of the reduced montage for detecting electrographic seizures was 96.8% and 100% respectively. In only one patient's record, the single seizure was missed altogether. For grading background abnormalities, the sensitivity and specificity of reduced montage was 87% and 80%. Although there are inherent weaknesses in reduced montages with respect to both underestimation and overestimation of seizure number, a nine-electrode reduced montage can be a sensitive tool for identification of neonatal seizures and assessment of background characteristics of neonatal electroencephalography.