Diagnostic value of amplitude-integrated electroencephalogram in neonatal seizures

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.

A method for AI assisted human interpretation of neonatal EEG

The study proposes a novel method to empower healthcare professionals to interact and leverage AI decision support in an intuitive manner using auditory senses. The method’s suitability is assessed through acoustic detection of the presence of neonatal seizures in electroencephalography (EEG). Neurophysiologists use EEG recordings to identify seizures visually. However, neurophysiological expertise is expensive and not available 24/7, even in tertiary hospitals. Other neonatal and pediatric medical professionals (nurses, doctors, etc.) can make erroneous interpretations of highly complex EEG signals. While artificial intelligence (AI) has been widely used to provide objective decision support for EEG analysis, AI decisions are not always explainable. This work developed a solution to combine AI algorithms with a human-centric intuitive EEG interpretation method. Specifically, EEG is converted to sound using an AI-driven attention mechanism. The perceptual characteristics of seizure events can be heard using this method, and an hour of EEG can be analysed in five seconds. A survey that has been conducted among targeted end-users on a publicly available dataset has demonstrated that not only does it drastically reduce the burden of reviewing the EEG data, but also the obtained accuracy is on par with experienced neurophysiologists trained to interpret neonatal EEG. It is also shown that the proposed communion of a medical professional and AI outperforms AI alone by empowering the human with little or no experience to leverage AI attention mechanisms to enhance the perceptual characteristics of seizure events.

aEEG vs cEEG's sensivity for seizure detection in the setting of neonatal intensive care units: A systematic review and meta-analysis

AIM

Amplitude-integrated electroencephalography (aEEG)'s accuracy compared to conventional electroencephalography (cEEG) has not been fully established. The aim of our study was to conduct a systematic review on the sensitivity of the aEEG for neonatal seizure detection.

METHODS

Studies from PubMed and Google Scholar databases comparing recordings of cEEG and aEEG in newborns were included according to the PRISMA method. A quality assessment using the QUADAS-2 tool was provided. A random-effect model was used to account for different sources of variations among studies. Publication biases were represented by a funnel plot, and funnel plot symmetry was assessed.

RESULTS

Fourteen studies were reported; sensitivity of each diagnostic tool used (single-channel aEEG, two-channel aEEG, two-channel aEEG plus raw trace EEG) was compared to that of the gold-standard cEEG and to those of the other methods used. Overall sensitivity of the aEEG ranged from 31.25% to 90%.

CONCLUSION

Our study provides evidence that sensitivity of aEEG varies significantly and that seizure detection rate is lower than that of cEEG. The two-channel aEEG with raw trace EEG shows a high sensitivity and might represent a valid alternative to the cEEG in the setting of neonatal intensive care units (NICUs).

Current and Future Uses of Continuous EEG in the NICU

Continuous EEG (cEEG) is a fundamental neurodiagnostic tool in the care of critically ill neonates and is increasingly recommended. cEEG enhances prognostication via assessment of the background brain activity, plays a role in predicting which neonates are at risk for seizures when combined with clinical factors, and allows for accurate diagnosis and management of neonatal seizures. Continuous EEG is the gold standard method for diagnosis of neonatal seizures and should be used for detection of seizures in high-risk clinical conditions, differential diagnosis of paroxysmal events, and assessment of response to treatment. High costs associated with cEEG are a limiting factor in its widespread implementation. Centralized remote cEEG interpretation, automated seizure detection, and pre-natal EEG are potential future applications of this neurodiagnostic tool.

How Helpful Is aEEG? Context and User Experience Matter

OBJECTIVE

The aim of the study is to model amplitude-integrated electroencephalography (aEEG) utility to diagnose seizures in common clinical scenarios.

STUDY DESIGN

Using reported neonatal seizure prevalence and aEEG sensitivities and specificities, likelihood ratios (LRs) and post-test probabilities were calculated to quantify aEEG utility to diagnose seizures in three typical clinical scenarios.

RESULTS

Prevalence data supported pretest probabilities for neonatal seizures of 0.4 in neonatal hypoxic ischemic encephalopathy (HIE), 0.27 in bacterial meningitis, and 0.05 in extreme prematurity. Reported sensitivity of 85% and specificity of 90% for seizures with expert aEEG interpretation yielded a positive likelihood ratio (LR+) of 8.7 and a negative likelihood ratio (LR-) of 0.17. Reported sensitivity of 65% and specificity of 70% with intermediate interpretation yielded LR+ 2.17 and LR- 0.5. Reported sensitivity of 40% and sensitivity of 50% with inexperienced interpretation gave LR+ 0.8 and LR- 1.2. These translate the ability to move pretest to post-test probability highly dependent on user expertise. For HIE, a pretest probability of seizure of 0.4 moves to a post-test probability of 0.85 when aEEG is positive for seizures by expert interpretation, and down to 0.1 when aEEG is negative. In contrast, no useful information was gained between pretest and post-test probability by aEEG interpreted as negative or positive for seizure at the inexperienced user level. Similarly, in the models of meningitis or extreme prematurity, incremental information gained from aEEG ranged widely based on interpreter experience.

CONCLUSION

aEEG is most useful to screen for neonatal seizures when used in conditions with high seizure prevalence, and when interpretation has a sensitivity and specificity as reported for expert users. In contrast, aEEG can become negligible in providing meaningful clinical information when applied in conditions having lower seizure prevalence or when interpretation has low accuracy. Appropriate patient selection and high quality interpretation are essential for aEEG utility in neonatal seizure detection.

KEY POINTS

· aEEG utility for neonatal seizure screening relies on patient selection and quality interpretation.. · Utility of aEEG is highest with high seizure prevalence and expert interpretation.. · Utility of aEEG can be negligible with lower seizure prevalence or low accuracy interpretation..

Seizures severity during rewarming can predict seizure outcomes of infants with neonatal hypoxic-ischemic encephalopathy following therapeutic hypothermia

Background

The aim of this study was to examine the predictive value of amplitude-integrated electroencephalography (aEEG) on 12-month seizure outcomes of infants with neonatal hypoxic-ischemic encephalopathy (HIE) treated with therapeutic hypothermia.

Methods

We conducted this retrospective cohort study in a tertiary neonatal intensive care unit between May 2012 and September 2017. Neonates with HIE who received both therapeutic hypothermia (TH) and aEEG were enrolled.

Results

A total of 23 infants (14 boys, nine girls) with a mean gestational age of 38.9 weeks were enrolled. Fifteen (65%) infants had moderate HIE and eight (35%) had severe HIE according to modified Sarnat staging. The mean aEEG recording time was 107.5 h. Twenty (86.9%) infants had seizure activity during the first 24 h after cooling and 14 (60.8%) had seizure activity during the first 24 h after rewarming. At 12 months, five (21.7%) infants had poor seizure outcomes. Repetitive seizures or status epilepticus pattern during the first 24 h after rewarming, but not the first 24 h after cooling, were associated with the presence of epilepsy at 12 months (p = 0.037).

Conclusions

We identified a high incidence of electrographic seizures in infants with neonatal HIE treated with therapeutic hypothermia, and post-neonatal epilepsy in the children who survived after HIE. Repetitive seizures or status epilepticus pattern during the first 24 h after rewarming, but not in the first 24 h after cooling, were associated with the presence of epilepsy at 12 months.

Amplitude-integrated electroencephalography for neonatal seizure detection. An electrophysiological point of view

Seizures in the newborn are associated with high morbidity and mortality, making their detection and treatment critical. Seizure activity in neonates is often clinically obscured, such that detection of seizures is particularly challenging. Amplitude-integrated EEG is a technique for simplified EEG monitoring that has found an increasing clinical application in neonatal intensive care. Its main value lies in the relative simplicity of interpretation, allowing nonspecialist members of the care team to engage in real-time detection of electrographic seizures. Nevertheless, to avoiding misdiagnosing rhythmic artifacts as seizures, it is necessary to recognize the electrophysiological ictal pattern in the conventional EEG trace available in current devices. The aim of this paper is to discuss the electrophysiological basis of the differentiation of epileptic seizures and extracranial artifacts to avoid misdiagnosis with amplitude-integrated EEG devices.

A Comparison Of Conventional Electroencephalography With Amplitude-Integrated EEG In Detection Of Neonatal Seizures

Introduction

Amplitude-integrated electroencephalogram (aEEG) is widely used in Neonatal Intensive Care Units (NICUs) to monitor neonatal seizures. This method is still not well established compared to conventional electroencephalogram (cEEG), the diagnostic gold standard. However, aEEG can be a good screening tool for the diagnosis of seizures in infants. Our aim in this review study is to evaluate aEEG diagnostic accuracy in comparison with cEEG, for detection of neonatal seizures.

Methods

In this work, we studied the published articles which used EEG and aEEG in the evaluation process of seizures in neonates and compared these techniques to obtain an approach for the detection of neonatal seizures.

Results

Seventeen articles were included. Using aEEG with raw trace to detect individual seizures showed median sensitivity of 78% (range: 68-85) and median specificity of 78% (range: 71-84). The median sensitivity and specificity were 54% (range: 25-95) and 81% (range: 50-100), respectively, in case of using aEEG without raw traces. Brief duration seizures and those occurring away from aEEG leads were less detected.

Conclusion

Studies showed that aEEG has variable sensitivity and specificity. Based on the evidences, aEEG cannot be recommended as the only way for diagnosis and management of seizures in neonates; however, it could complete the diagnosis of seizures in the infant and could be a very good tool for screening seizures.

Combined Conventional and Amplitude-Integrated EEG Monitoring in Neonates: A Prospective Study

BACKGROUND/OBJECTIVE

Seizure monitoring via amplitude-integrated EEG is standard of care in many neonatal intensive care units; however, conventional EEG is the gold standard for seizure detection. We compared the diagnostic yield of amplitude-integrated EEG interpreted at the bedside, amplitude-integrated EEG interpreted by an expert, and conventional EEG.

METHODS

Neonates requiring seizure monitoring received amplitude-integrated EEG and conventional EEG in parallel. Clinical events and amplitude-integrated EEG were interpreted at bedside. Subsequently, amplitude-integrated EEG and conventional EEG were independently analyzed by experienced neonatology and neurology readers. Sensitivity and specificity of bedside amplitude-integrated EEG as compared to expert amplitude-integrated EEG interpretation and conventional EEG were evaluated.

RESULTS

Thirteen neonates were monitored for an average duration of 33 hours (range 15-94, SD 25). Fourteen seizure-like events were detected by clinical observation, and 12 others by bedside amplitude-integrated EEG analysis. One of the clinical, and none of the bedside amplitude-integrated EEG events were confirmed as seizures on conventional EEG. Post hoc expert amplitude-integrated EEG interpretation revealed eight suspected seizures, all different from the ones detected by the bedside amplitude-integrated EEG team, of which one was confirmed via conventional EEG. Eight seizures were recorded on conventional EEG. Expert amplitude-integrated EEG interpretation had a sensitivity of 13% with 46% specificity for individual seizure detection, and a sensitivity of 50% with 46% specificity for detecting patients with seizures.

CONCLUSION

Real-world bedside amplitude-integrated EEG monitoring failed to detect all seizures evidenced via conventional EEG, while misclassifying other events as seizures. Even post hoc expert amplitude-integrated EEG interpretation provided limited sensitivity and specificity. Considering the poor sensitivity and specificity of bedside amplitude-integrated EEG interpretation, combined monitoring may provide limited clinical benefit.

Diagnosis of seizures and encephalopathy using conventional EEG and amplitude integrated EEG

Seizures are more common in the neonatal period than at any other time of life, partly due to the relative hyperexcitability of the neonatal brain. Brain monitoring of sick neonates in the NICU using either conventional electroencephalography or amplitude integrated EEG is essential to accurately detect seizures. Treatment of seizures is important, as evidence increasingly indicates that seizures damage the brain in addition to that caused by the underlying etiology. Prompt treatment has been shown to reduce seizure burden with the potential to ameliorate seizure-mediated damage. Neonatal encephalopathy most commonly caused by a hypoxia-ischemia results in an alteration of mental status and problems such as seizures, hypotonia, apnea, and feeding difficulties. Confirmation of encephalopathy with EEG monitoring can act as an important adjunct to other investigations and the clinical examination, particularly when considering treatment strategies such as therapeutic hypothermia. Brain monitoring also provides useful early prognostic indicators to clinicians. Recent use of machine learning in algorithms to continuously monitor the neonatal EEG, detect seizures, and grade encephalopathy offers the exciting prospect of real-time decision support in the NICU in the very near future.

Amplitude-integrated electroencephalography for seizure detection in newborn infants

The amplitude-integrated electroencephalogram (aEEG) is a filtered and compressed EEG trend that can be used for long-term monitoring of brain function in patients of all ages. aEEG is increasingly used in neonatal intensive care units since several studies have shown its utility in high-risk newborn infants. Main indications for aEEG monitoring include early evaluation of brain function after perinatal asphyxia and seizure detection. The aEEG is usually recorded from one or two channels derived from parietal, central, or frontal leads. Although the aEEG is very useful for identifying high-risk infants and infants with seizures, the compressed trend has limitations with regards to detection of individual seizures. However, modern monitors also display the corresponding EEG (aEEG/EEG), which increases the probability of detecting single brief seizures. For improved evaluation of electrocortical brain activity the aEEG/EEG should be assessed together with repeated conventional EEGs or multi-channel EEG monitoring in a multi-disciplinary team.

Severe neonatal hyperbilirubinemia induces temporal and occipital lobe seizures

To examine the origin of seizures induced by severe neonatal hyperbilirubinemia, The EEG characteristics of seizures were analyzed in newborns with and without severe neonatal hyperbilirubinemia. Fisher’s exact test was used to determine the specificity. In total, 931 patients had a total serum bilirubin (TSB) level of 340–425 μmol/L, only 2 of whom had seizures. Compared to patients with hyperbilirubinemia and a TSB level of 340–425 μmol/L, those with a TSB level >425 μmol/L had a significant risk of seizure (OR = 213.2, 95% CI = 113.0–405.8, P<0.001). Of all 28 patients with severe hyperbilirubinemia and seizure, 26 had seizures that originated in the temporal and/or occipital lobe. In seizure patients without severe hyperbilirubinemia, origination in the temporal/occipital and other lobes occurred in 19 and 117 cases, respectively. Compared to the risk of seizure origination in the temporal and/or occipital lobe in other diseases, the risk in patients with severe hyperbilirubinemia was increased by approximately 80 times (OR = 80.1, 95% CI = 28.3–226.4, P<0.001). Severe neonatal hyperbilirubinemia can selectively induce temporal and occipital lobe seizures. This is the first report of a new syndrome with the same etiology and electrophysiological features as epilepsy.

Amplitude Integrated Electroencephalography Compared With Conventional Video EEG for Neonatal Seizure Detection: A Diagnostic Accuracy Study

This diagnostic accuracy study compared the accuracy of seizure detection by amplitude-integrated electroencephalography with the criterion standard conventional video EEG in term and near-term infants at risk of seizures. Simultaneous recording of amplitude-integrated EEG (2-channel amplitude-integrated EEG with raw trace) and video EEG was done for 24 hours for each infant. Amplitude-integrated EEG was interpreted by a neonatologist; video EEG was interpreted by a neurologist independently. Thirty-five infants were included in the analysis. In the 7 infants with seizures on video EEG, there were 169 seizure episodes on video EEG, of which only 57 were identified by amplitude-integrated EEG. Amplitude-integrated EEG had a sensitivity of 33.7% for individual seizure detection. Amplitude-integrated EEG had an 86% sensitivity for detection of babies with seizures; however, it was nonspecific, in that 50% of infants with seizures detected by amplitude-integrated EEG did not have true seizures by video EEG. In conclusion, our study suggests that amplitude-integrated EEG is a poor screening tool for neonatal seizures.

Hyperbilirubinemia Influences Sleep-Wake Cycles of Term Newborns in a Non-Linear Manner

Hyperbilirubinemia is a common cause for irreversible neuronal influence in the brain of term newborns, while the feature of neurological symptoms associated with hyperbilirubinemia has not been well characterized yet. In the present study, we examined a total of 203 neonates suffering from hyperbilirubinemia with a bedside amplitude-integrated Electroencephalography (aEEG) device, in order to determine whether there is any special change in sleep-wake cycles (SWCs). Among these patients, 14 cases showed no recognizable SWCs with the total serum bilirubin (TSB) level at 483.9–996.2 μmol/L; 75 cases exhibited reduced SWCs with the TSB level at 311.2–688.5 μmol/L; and the rest cases had the normal SWCs. The number of the normal SWCs occurrence had a significant negative correlation with the increased TSB level in a non-linear manner (r = -0.689, p <0.001). In addition, the increased TSB reshaped the structure of SWC by narrowing down the broadband and broadening the narrowband. Spearman’s correlation analysis indicated a significant negative correlation between the TSB level and the ratio of broadband (r = -0.618, p < 0.001), a significant positive correlation between the TSB level and the narrowband ratio (r = 0.618, p < 0.001), respectively. Furthermore, the change of SWC seemed like a continuous phenomenon, and the hyperbilirubinemia caused SWC changes was fit into a loess model in this paper. In summary, the hyperbilirubinemia influenced SWC of term newborns significantly at a non-linear manner, and these results revealed the feature of the neurological sequela that is associated with TSB.

Newborns' sleep-wake cycle development on amplitude integrated electroencephalography

BACKGROUND

To observe the development of neonatal sleep among healthy infants of different conceptional age (CA) by analyzing the amplitude-integrated electroencephalography (aEEG) of their sleep-wake cycles (SWC).

METHODS

Bedside aEEG monitoring was carried out for healthy newborns from 32 to 46 weeks CA between September 1, 2011 and August 30, 2012. For each aEEG tracing, mean duration of every complete SWC, number of SWC repetition within 12 hours, mean duration of each narrow and broadband of SWC, mean voltage of the upper edge and lower edge of SWC, mean bandwidth of SWC were counted and calculated. Analysis of the correlations between voltages or bandwidth of SWC and CA was performed to assess the developmental changes of central nervous system of newborns with different CA.

RESULTS

The SWC of different CA on aEEG showed clearly identifiable trend after 32 weeks of CA. The occurrence of SWC gradually increases from preterm to post-term infants; term infants had longer SWC duration. The voltage of upper edge of the broadband decreased at 39 weeks, while the lower edge voltage increases and the bandwidth of broadband declined along with the growing CA. The upper edge of the narrowband dropped while the lower edge rised gradually, especially in preterm stage. The width of the narrowband narrowed down while CA increased.

CONCLUSIONS

The SWC on aEEG of 32-46 weeks infants showed a continuous, dynamic and developmental progress. The appearance of SWC and the narrowing bandwidth of narrowband is the main indicator to identify the CA-dependent SWC from the preterm to the late preterm period. The lower edge of the broadband identifies the term to post-term period.

Amplitude-integrated EEG for detection of neonatal seizures: a systematic review

PURPOSE

Amplitude-integrated electroencephalogram (aEEG) is being used increasingly for monitoring seizures in neonatal units. Its accuracy, compared with "the gold-standard" conventional elecroencephalogram (cEEG) is still not well established. We aimed to conduct a systematic review to evaluate the diagnostic accuracy of aEEG when compared with cEEG, for detection of neonatal seizures.

METHOD

A systematic review was conducted using the Cochrane methodology. EMBASE, CINAHL and PubMed databases were searched in September 2014. Studies comparing simultaneous recordings of cEEG and aEEG for detection of seizures in neonatal population were included. QUADAS 2 tool was used to examine "risk of bias" and "applicability".

RESULTS

Ten studies (patient sample 433) were included. Risk of bias was high in five studies, unclear in one and low in four. For the detection of individual seizures, when "aEEG with raw trace" was used, median sensitivity was 76% (range: 71-85), and specificity 85% (range: 39-96). When "aEEG without raw trace" was used, median sensitivity was 39% (range: 25-80) and specificity 95% (range: 50-100). Detailed meta-analysis could not be done because of significant clinical/methodological heterogeneity. Seizure detection was better when interpreted by experienced clinicians. Seizures with low amplitude/brief duration and those occurring away from aEEG leads were less likely to be detected.

CONCLUSION

Studies included in the systematic review showed aEEG to have relatively low and variable sensitivity and specificity. Based on the available evidence, aEEG cannot be recommended as the mainstay for diagnosis and management of neonatal seizures. There is an urgent need of well-designed studies to address this issue definitively.

Monitoring neonatal seizures

Neonatal seizures are a neurological emergency and prompt treatment is required. Seizure burden in neonates can be very high, status epilepticus a frequent occurrence, and the majority of seizures do not have any clinical correlate. Detection of neonatal seizures is only possible with continuous electroencephalogram (EEG) monitoring. EEG interpretation requires special expertise that is not available in most neonatal intensive care units (NICUs). As a result, a simplified method of EEG recording incorporating an easy-to-interpret compressed trend of the EEG output (amplitude integrated EEG) from one of the EEG output from one or two channels has emerged as a popular way to monitor neurological function in the NICU. This is not without limitations; short duration and low amplitude seizures can be missed, artefacts are problematic and may mimic seizure-like activity and only a restricted area of the brain is monitored. Continuous multichannel EEG is the gold standard for detecting seizures and monitoring response to therapy but expert interpretation of the EEG output is generally not available. Some centres have set up remote access for neurophysiologists to the cot-side EEG, but reliable interpretation is wholly dependent on the 24 h availability of experts, an expensive solution. A more practical solution for the NICU without such expertise is an automated seizure detection system. This review outlines the current state of the art regarding cot-side monitoring of neonatal seizures in the NICU.

Drug studies in newborns: a therapeutic imperative

Although some drugs have been developed for the neonate, drug development for the least mature and most vulnerable pediatric patients is lacking. Most of the drugs are off-label or off-patent and are empirically administered to newborns once efficacy has been demonstrated in adults and usefulness is suspected or demonstrated in the older pediatric population. Few drugs are approved by the Food and Drug Administration for use in this population. The factors that prevent the demonstration of efficacy and safety in the newborn are discussed and a change in the current approach for neonatal drug studies is suggested.