Key messages
• Amplitude-integrated electroencephalography (aEEG) may not be sufficiently accurate to identify babies with seizures and also individual seizure episodes in a baby.
• Treatment based only on aEEG may lead to inadequate or unnecessary treatment with anti-seizure medications.
Why is it important to accurately detect seizures?
Seizure is an abnormal and short-term electrical activity of the brain. They are uncommon, but a serious problem in the newborn period. They occur in response to problems such as reduced oxygen or blood supply to the brain, low blood sugar, and brain infections. Babies can have a single or many seizures. Each seizure can be as short as 10 seconds or as long as several minutes.
Seizures in newborn babies can harm the brain and have long-lasting effects. Therefore, it is important to identify seizures accurately.
What is the aEEG test?
Electroencephalography (EEG) is the non-invasive measurement of the brain’s electric signals. Recording the electrical activity of the brain with 10 to 20 leads (small wires attached to the head) is the best way to detect seizures. This is called conventional electroencephalography, or cEEG. However, cEEG is not always easily available in neonatal intensive care units, is difficult to perform, and needs a high level of expertise to interpret.
Amplitude-integrated electroencephalography (aEEG) is a simplified and easy-to-perform form of EEG but provides less information than cEEG. aEEG is prepared from EEG signals and needs only 2 to 4 leads, which neonatal nurses can apply. Bedside doctors caring for babies can interpret aEEG to detect seizures.
There are several different aEEG recording machines: some use 2 electrodes while others use 4 electrodes. Some machines also show the original EEG signal from which aEEG was prepared. aEEG can be prepared from already recorded cEEG for research purposes.
What did we want to find out?
How accurate is aEEG in identifying babies who are having seizures and individual seizure episodes in a baby?
What did we do?
We searched for studies that compared aEEG with cEEG for detecting seizures in newborn babies. We read the details of how the studies were conducted and their findings. We summarised the results and estimated their reliability.
What did we find?
We found 16 relevant studies with a total of 562 newborn babies. Out of 16 studies, 3 described the accuracy of the aEEG only for identifying babies with seizures, 3 described it only for detecting individual seizures, and 10 for detecting both babies with seizures and individual seizures.
The duration of recording, the number of aEEG leads, the use of unprocessed EEG signals, and the training and experience of aEEG interpreters were variable in the studies.
In only 2 studies, bedside doctors read the aEEG, reflecting real-life clinical practice. In the rest of the studies, newborn baby specialists interpreted the aEEG at a later stage. The method of later interpretation of the aEEG is not very useful for the immediate management of the babies.
On average, aEEG detected 71 out of 100 babies who were having seizures. That means it missed 29 babies with seizures. It labelled 16 babies as having seizures when, in fact, they did not have seizures.
Included studies reported variable accuracy of aEEG in detecting individual seizures, ranging from as low as 0 to as high as 86 correctly detected seizures out of 100.
The review findings suggest that aEEG may not be sufficiently accurate for identifying babies with seizures and individual seizure episodes in a baby.
What are the limitations of the evidence?
The review had several limitations, the most important of which was that the results of studies varied widely without any obvious reason, decreasing the reliability of the evidence. Another limitation of the evidence was that only 2 studies reported the effect of real-life bedside aEEG interpretation on the accuracy of aEEG.
How current is this review?
The evidence is current to July 2022.
Read the full abstract
Conventional video-electroencephalography (cEEG) is the reference standard for diagnosing and managing neonatal seizures. However, continuous bedside cEEG services are not available in most neonatal units. Hence, an alternative and relatively simple method called amplitude-integrated EEG (aEEG), which uses a limited number of scalp electrodes, has become popular. aEEG allows continuous bedside monitoring of the electrical activity of the brain in neonates.
Objectives
The primary objective of the review was to assess the accuracy of aEEG against the reference standard cEEG for the detection of 'neonates with seizures' and 'individual seizures'. Detection of 'neonates with seizures' refers to the ability of the test to correctly identify a 'neonate' as 'seizure positive' or 'seizure negative' based on the detection of at least one seizure episode in the entire aEEG recording. Detection of 'individual seizures' refers to the ability of the test to correctly identify 'individual' seizure episodes within the same neonate rather than just diagnosing the neonate as 'seizure positive' or 'seizure negative'.
Search strategy
We searched CENTRAL, MEDLINE, Embase, clinical trials registries, and grey literature (Open Grey, Trove, and American Doctoral Dissertations) to 26 July 2022. We did not apply any language or publication status restrictions or any other filters.
Selection criteria
We included prospective and retrospective studies investigating the accuracy of aEEG (index test) against the reference standard cEEG for the detection of neonatal seizures. To be eligible for inclusion, the studies must have compared aEEG with simultaneously recorded cEEG. There was no restriction on the number of leads, use of raw EEG traces, or experience and training of an aEEG interpreter. cEEG should have been recorded using at least nine electrodes and interpreted by a qualified person experienced in the interpretation of neonatal cEEG.
Data collection and analysis
Working independently, two review authors collected data from the included studies in a prespecified form and assessed the quality of the included studies using the QUADAS-2 tool.
For the outcome of 'neonates with seizures', we used a bivariate mixed-effects regression model to conduct a meta-analysis to derive pooled sensitivity, specificity, positive and negative likelihood ratios (LR), and their respective 95% confidence intervals (CI). We generated a summary receiver operating characteristic (SROC) curve to display the results of individual studies. We calculated post-test probabilities based on Bayes' theorem through Fagan nomograms.
For the outcome of 'individual seizures', pooling of data was not possible because of the 'unit of analysis' issue. Instead, we performed a narrative synthesis.
We assessed the certainty of the evidence using GRADE guidelines.
Main results
We included 16 studies (562 infants) in the systematic review, of which only two studies interpreted the aEEGs prospectively at the bedside. Out of 16 studies, three studies (97 infants) described the accuracy of aEEG only for detecting ‘infants with seizures’, three studies (72 infants) described only ‘individual seizures’, while 10 studies (393 infants) described the accuracy of aEEG for detecting both.
Ten of 16 studies were conducted in term and late preterm infants. Half of the included studies did not use raw EEG traces. Fourteen studies reported outcomes based only on retrospective interpretation. Ten of 16 studies used four electrodes (making this the most common approach amongst the included studies), and 10 studies' aEEG recordings exceeded six hours. Only two included studies used a seizure detection algorithm. In 14 studies, a neonatal or neurology consultant performed aEEG interpretation, and most (in 10 of 14 studies) had prior experience in aEEG interpretation.
Accuracy of aEEG to diagnose 'neonates with seizures'. The only two prospective studies (53 participants) which interpreted aEEGs 'live' at the bedside, reported sensitivities of zero and 0.57 and specificities of 0.82 and 0.92, respectively.
Meta-analysis of 13 studies (490 neonates) found that aEEG had a pooled sensitivity of 0.71 (95% CI 0.57 to 0.83), specificity of 0.84 (95% CI 0.59 to 0.95), positive LR of 4.50 (95% CI 1.55 to 13.04), and negative LR of 0.34 (95% CI 0.22 to 0.53) for the detection of 'neonates with seizures'. However, when we analysed only studies with low risk of bias (3 studies), sensitivity (0.56, 95% CI 0.02 to 0.99) and specificity (0.78, 95% CI 0.60 to 0.90) were even lower.
There was significant statistical heterogeneity, which could not be explained based on threshold effect and exploratory analyses of forest plots. We graded the certainty of the evidence as low, in view of the high or unclear risk of bias in many studies, imprecision, and significant heterogeneity.
Accuracy of aEEG to detect 'individual seizures' in neonates. The reported sensitivities of aEEG for the detection of 'individual seizures' ranged from 0 to 0.86 (13 studies, 465 neonates). We rated the certainty of the evidence as low.
The common causes of missed seizures on aEEG (i.e. false negative) as reported by studies were short duration of seizures, localisation of seizures away from aEEG leads, low voltage, and inexperienced interpreter. The false-positive rates were high when interpreted live at the bedside and if the interpreters were inexperienced. Artefacts resulting from muscle movement, patting, hiccups, and insufficient electrode attachment were other common causes of false-positive results.
Authors' conclusions
Low-certainty evidence suggests that aEEG has only moderate sensitivity and specificity for detecting 'neonates with seizures', and its ability to detect 'individual seizures' varies widely. These findings suggest that aEEG may not be sufficiently accurate for diagnosing neonatal seizures as it can under-diagnose or over-diagnose seizures. Studies with low risk of bias are needed to address the issue definitively.
