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Cochrane Database of Systematic Reviews Protocol - Diagnostic

Amplitude‐integrated electroencephalography compared with conventional video‐electroencephalography for detection of neonatal seizures

Authors' declarations of interest

Version published: 09 March 2020 Version history

https://doi.org/10.1002/14651858.CD013546
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Abstract

This is a protocol for a Cochrane Review (Diagnostic test accuracy). The objectives are as follows:

Our primary objective is to assess the accuracy of aEEG against the reference standard cEEG for detection of 'neonates with seizures' and 'individual seizures'.

  1. Detection of 'neonates with seizures': this refers to the ability of the index test to identify a 'neonate' as 'seizure positive' or 'seizure negative' correctly based on the detection of at least one seizure episode in the entire aEEG recording of the neonate.

  2. Detection of 'individual seizures': this refers to the ability of the index test to identify an 'individual' seizure episode within the same neonate correctly rather than just diagnosing the neonate as 'seizure positive' or 'seizure negative'. Diagnosis of an 'individual seizure' episode is important for optimal management of seizures.

If data are available, we will perform subgroup analysis for seizure detection where duration of monitoring is less than or equal to six hours. This subgroup is particularly important as six hours is the cut‐off point to decide whether infants with hypoxic ischaemic encephalopathy require therapeutic hypothermia (Shankaran 2005).

Background

Target condition being diagnosed

A seizure is a paroxysmal transient occurrence of abnormal excessive or synchronous neuronal activity in the brain (Volpe 2008). Seizures associated with physical signs are called 'clinical' or 'electro‐clinical' seizures, while those without physical signs are called 'sub‐clinical', 'electrographic‐only', 'silent' or 'occult' seizures. Seizures occurring during the neonatal period are called neonatal seizures, one of the most common manifestations of central nervous system dysfunction in newborn infants. The risk of seizures is higher in the neonatal period than any other period of life with a reported incidence between 1 to 5 per 1000 live births (Silverstein 2008; Vasudevan 2013).

The detection and monitoring of seizures is a vital component of neonatal intensive care for the following reasons: (a) seizures could adversely affect vital functions including respiration and circulation in neonates; and (b) seizures themselves may disrupt the laying down of neural circuitry and so adversely affect neurodevelopmental outcomes (Wirrell 2001; Miller 2002; Sankar 2007; Nagarajan 2010; Van Rooij 2010; Nardou 2013; Shah 2014; Srinivasakumar 2015). Clinical observation alone can lead to under‐diagnosis of neonatal seizures, since 65% to 80% of seizures are occult (Clancy 2005; Murray 2008; Nagarajan 2011). It can also result in over‐diagnosis as clinically suspected episodes may not show corresponding electrographic evidence of seizures (Murray 2008). Evidence is accumulating that excessive use of antiepileptic drugs can cause apoptosis of developing neurons (Bittigau 2002; Kim 2007). Hence over‐diagnosis of seizures could result in inappropriate and excessive use of antiepileptic medications thereby adversely affecting the infant's developing brain. As reliance on clinical observation alone is inadequate, conventional video‐electroencephalography (cEEG) and amplitude‐integrated electroencephalography (aEEG) are currently used in neonates for detection and monitoring of seizures (Boylan 2010).

cEEG is considered the 'gold standard' for detection of neonatal seizures (Shellhaas 2011). cEEG uses the full complement of scalp electrodes applied according to the International 10‐20 system (often modified for neonates) by skilled technologists and interpreted by experienced neurologists or clinical neurophysiologists (American Clinical Neurophysiology Society 2006, Shellhaas 2011). The American Clinical Neurophysiology Society has recommended that neonates at high risk for seizures should be monitored with cEEG for 24 hours to screen for seizures (Shellhaas 2011). However, due to resource limitations, cEEG may not be readily available in many centres, especially for continuous bedside monitoring (Boylan 2010). In addition, the results are often not available in real time to assist with patient management (Jobe 2009).

Index test(s)

aEEG is a simplified method that uses fewer electrodes to collect electroencephalographic (EEG) information that is filtered, rectified, and compressed in time to generate a tracing that can be used for the detection and evaluation of seizures, providing information in real time (Shah 2008). The main advantages of aEEG over cEEG are: fewer number of scalp electrodes, which can be applied by neonatal staff and maintained for extended periods of time for continuous monitoring; the output is easier to interpret and could be interpreted by neonatal staff at the bedside; and less time is required to review the trace because of aEEG's time‐compressed nature. Because of the advantages, aEEG is gaining popularity in neonatal intensive care units (NICU) all over the world and is used by neonatal staff to assist patient management (Shah 2008). However, use of fewer leads and aEEG's time‐compressed nature is also responsible for the following drawbacks of aEEG for the detection of seizures: seizures with short duration especially those less than 30 seconds may be difficult to identify; localised seizure activity in brain areas (such as frontal and temporal lobes) away from the aEEG leads is likely to be missed; some artefacts (such as those arising from leads, movements, etc) may be interpreted as seizures; and there is a tendency to underestimate the duration of seizures compared with cEEG (Rakshasbhuvankar 2017; Hellstrom‐Westas 2018).

The newer aEEG monitoring systems display one or more channels of aEEG along with the unprocessed raw EEG trace to assist in the diagnosis of seizures. In addition, algorithms to help seizure detection have been developed and investigated (Navakatikyan 2006; Lommen 2007; El‐Dib 2009; Lawrence 2009). C3, P3, C4, and P4 lead positions of the International 10‐20 system of lead placement are commonly used as these leads are close to the watershed area of the brain, which is commonly affected in infants with hypoxic ischaemic encephalopathy, and lead positions are associated with fewer artefacts.

Clinical pathway

High‐risk neonates require monitoring for detection of seizures. The risk factors for seizures include hypoxia‐ischaemia, meningitis, intracranial bleed, cerebral infarct, metabolic encephalopathy, cardiac surgery, and any type of critical illness. Infants at risk of seizures should ideally be monitored using cEEG (Abend 2013), since this approach will provide the most accurate information regarding diagnosis and seizure burden, enabling management decisions. However, this approach requires considerable infrastructure and cost, which may not be available in a large number of neonatal units (Boylan 2010).

If aEEG has a high sensitivity for seizure detection, it can be used as a screening tool. Infants who screen positive can subsequently be monitored with cEEG. On the other hand, if aEEG has both high sensitivity and high specificity, it can be used as a definitive test for seizure detection, treatment, and to monitor the effect of antiepileptic therapy. Thus, the use of aEEG in both of these clinical pathways has the potential to decrease the need for cEEG, which is expensive and limited in availability.

Alternative test(s)

No alternative tests to aEEG are within the scope of this review.

Rationale

Bedside monitoring of background activity of the brain with aEEG has been shown to be useful in predicting neurodevelopmental outcomes in newborn infants with hypoxic ischaemic encephalopathy (Van Laerhoven 2013). However, the usefulness of aEEG for the detection of neonatal seizures is not yet well established. The need for a rigorous evaluation of the strengths and weaknesses as well as sensitivity and specificity of the aEEG for the diagnosis of neonatal seizures is well recognised (Freeman 2007; Silverstein 2008; Rakshasbhuvankar 2015; Sanchez Fernandez 2015). Since the previous systematic reviews investigating the utility of aEEG for detection of neonatal seizures (Ray 2011; Rakshasbhuvankar 2015), several new studies on this topic have been published (Rakshasbhuvankar 2017; Buttle 2019). Therefore, we plan to conduct this systematic review to synthesise current evidence regarding the accuracy of aEEG versus the gold standard cEEG for the diagnosis of neonatal seizures.

Objectives

Our primary objective is to assess the accuracy of aEEG against the reference standard cEEG for detection of 'neonates with seizures' and 'individual seizures'.

  1. Detection of 'neonates with seizures': this refers to the ability of the index test to identify a 'neonate' as 'seizure positive' or 'seizure negative' correctly based on the detection of at least one seizure episode in the entire aEEG recording of the neonate.

  2. Detection of 'individual seizures': this refers to the ability of the index test to identify an 'individual' seizure episode within the same neonate correctly rather than just diagnosing the neonate as 'seizure positive' or 'seizure negative'. Diagnosis of an 'individual seizure' episode is important for optimal management of seizures.

If data are available, we will perform subgroup analysis for seizure detection where duration of monitoring is less than or equal to six hours. This subgroup is particularly important as six hours is the cut‐off point to decide whether infants with hypoxic ischaemic encephalopathy require therapeutic hypothermia (Shankaran 2005).

Secondary objectives

Our secondary objective is to investigate variation in the accuracy of aEEG according to the potential sources of between‐study heterogeneity listed below.

  1. To compare 'aEEG without raw trace' versus 'aEEG with raw trace'

  2. To compare 'aEEG with raw trace' versus 'aEEG with raw trace and seizure detection algorithm'

  3. To compare single versus two versus more than two channels

  4. To compare different aEEG lead positions

  5. To compare surface electrodes versus needle electrodes

  6. To investigate the effect of training (yes/no) in the interpretation of aEEG

  7. To investigate the effect of clinicians' experience (yes/no) in the interpretation of aEEG

Methods

Criteria for considering studies for this review

Types of studies

We plan to include studies evaluating the accuracy of aEEG against the reference standard cEEG for detection of neonatal seizures. The studies must compare aEEG with simultaneously recorded cEEG.

The duration of aEEG monitoring can influence the outcome of detection of 'neonates with seizure'. Ideally, aEEG should be able to detect seizures as soon as possible, but no one knows the critical time window within which seizures should be detected and treated. At present there are no standard guidelines for the duration of aEEG monitoring in 'at‐risk' neonates. In clinical practice the duration of monitoring is variable and is guided by risk factors for seizures (e.g. hypoxic ischaemia) frequency of continuing seizures, seizure‐free period, aEEG background activity, and local practices (Shah 2015). Hence we will include studies with any duration of monitoring.

We plan to include prospective as well as retrospective studies. We will exclude studies that focus only on the background EEG pattern without addressing the issue of detection of neonatal seizures, and studies in which there is no simultaneous recording of aEEG and cEEG.

Participants

Newborn infants (post‐menstrual age under 44 weeks) admitted to NICU with suspected seizures or at risk of seizures. The risk factors include: hypoxia‐ischaemia, infectious or metabolic encephalopathy, intraventricular haemorrhage and other intracranial malformations, sick infants receiving muscle paralysis and newborn infants undergoing cardiac surgery (Clancy 2005; Shah 2012). Ideally the study participants' inclusion in the study should not be based on cEEG findings. In some studies, initially a neonate is confirmed to have had seizures based on the gold standard cEEG. Subsequently they are monitored with simultaneous aEEG and cEEG to identify ongoing seizure activity. While such studies are not the ideal design, they are still useful in evaluating the efficacy of aEEG to diagnose seizures that can occur subsequently in those neonates. Hence, we plan to include such studies in the main analysis. But since they are methodologically suboptimal in design, we will conduct a sensitivity analysis by excluding such studies.

Index tests

The index test is aEEG. We plan to include studies in which a separate machine was used to record aEEG, as well as studies in which aEEG was derived from signals from the cEEG recordings. We will include studies in which aEEG was interpreted 'real‐time' as well as studies in which aEEG was interpreted retrospectively. However, as 'aEEG derived from cEEG' and 'retrospective analysis of aEEG' will have significant applicability concerns, we will perform sensitivity analysis by excluding studies.

aEEG could have been measured using either single or multichannel EEG systems.

aEEG could have been measured with or without raw EEG trace.

aEEG could have been measured with or without automated seizure detection algorithms.

Target conditions

Electrographic seizure of at least 10 seconds' duration.

Reference standards

The reference standard is cEEG recorded using at least the following nine electrodes (Fp1, Fp2, C3, C4, Cz, T3 (or T7), T4 (or T8), O1, and O2) and interpreted by neurologists or clinical neurophysiologists experienced in the interpretation of neonatal cEEG (Tekgul 2005).

Search methods for identification of studies

Electronic searches

With the help of Cochrane Epilepsy's Information Specialist, we will undertake a systematic search of the following databases.

  1. MEDLINE via Ovid

  2. Embase via Ovid

  3. Cochrane Register of Studies (CRS Web; this includes the Cochrane Central Register of Controlled Trials (CENTRAL) and the Cochrane Epilepsy Group's Specialized Register)

  4. Clinical trials registers for proposed/ongoing/completed trials: ClinicalTrials.gov and World Health Organization: International Clinical Trials Registry Platform

  5. Grey literature: Open Grey (www.opengrey.eu; grey literature database for Europe); www.trove.nla.gov.au (Trove: Australian online library database aggregator); American Doctoral Dissertations (available from EBSCOhost)

We will not apply any language or publication status restrictions.

We outline a search strategy for MEDLINE (via Ovid) in Appendix 1.

We outline a search strategy for Embase (via Ovid) in Appendix 2.

Searching other resources

We will search reference lists of primary articles for relevant publications not captured by the literature search.

Data collection and analysis

Selection of studies

Two review authors (AR and SR) will independently review the titles and abstracts of all articles obtained on our initial broad screening to identify potential studies. The same two review authors will independently retrieve and read the full texts of such articles to decide on their eligibility for inclusion. AR and SR will resolve any disagreement regarding study selection by discussion with the co‐authors (ZZ and LN).

Data extraction and management

Two review authors (AR and SR) will collect data independently from the included studies in a prespecified form (Appendix 3), which will collect the following information: title of the article; author names; year of publication; sample size; study participant characteristics; details of cEEG (leads, montages, availability of video) and aEEG (leads, channels, availability of raw trace and seizure detection algorithm); characteristics of clinicians who interpreted the aEEG and cEEG; duration of simultaneous recording of aEEG and cEEG; data related to seizure detection including 2x2 tables; limitations; and original authors' conclusions.

For the outcome of detection of 'neonates with seizure' we will construct 2x2 tables to pool the data. If the studies have not reported adequate information for pooling the data, we will contact the study authors and request missing information. If the information is not available even after contacting study authors, we will include it in the systematic review, but exclude it from the meta‐analysis.

For the outcome of detection of 'individual seizures' we plan to extract the following data: percentage/number of 'individual seizures' detected correctly using aEEG; and percentage/number of false‐positive seizures on aEEG. Because of the reason explained in the 'Statistical analysis and data synthesis' section, only narrative synthesis will be performed without pooling the data for the outcome of 'individual seizures'.

Assessment of methodological quality

Two review authors (AR and ZZ) will assess all the included studies using QUADAS‐2 (Quality Assessment of Diagnostic Accuracy Studies) tool (Whiting 2011;Appendix 4). Any disagreement between the authors will be resolved by discussion with the co‐authors (SR and LN). We will use Review Manager 5 (RevMan 5) software to generate tables and graphs to represent the results of the 'Risk of bias' assessment and the assessment of applicability concerns in the included studies (Review Manager 2014) .

Statistical analysis and data synthesis

One review author (AR) will enter data into RevMan 5 and a second review author (ZZ) will check the data entry.

Detection of 'neonates with seizures'

Where possible, we plan to pool the results for the outcome of detection of 'neonates with seizures' to obtain the summary estimates of sensitivity and specificity.

We will plot study estimates of sensitivity and specificity on forest plots and in the ROC (Receiver Operating Characteristic Curve) space to explore between‐study variation in the 'neonates with seizures' outcome. If appropriate, we will pool the results to obtain summary estimates of sensitivity and specificity. As we anticipate little variation between studies in seizure detection criteria, we will use the bivariate random‐effects method, which preserves the two‐dimensional nature of the data, accounts for between‐study variability, and allows for the possibility of a negative correlation that may exist between sensitivity and specificity across studies (Reitsma 2005). We plan to use Stata/SE 15.0 for the analyses (Stata). We will plot the results in the SROC (Summary Receiver Operating Characteristic Curve) space with 95% confidence intervals (CI) and prediction regions. We will derive all other test accuracy measures (e.g. positive and negative predictive values and likelihood ratios) from the summary sensitivity and specificity.

Detection of 'individual seizures'

Within a single infant there may be a few correctly detected seizures (true positive), a few not‐detected seizures (false negative) and a few false‐positive seizures, so it will not be possible to construct a 2x2 table. Hence we do not plan to pool data and give summary statistics of sensitivity or specificity. Instead, we will perform a narrative synthesis.

We plan to add a 'Summary of findings' table with the outcomes of detection of 'neonates with seizures' and 'individual seizures'.

Investigations of heterogeneity

We will investigate heterogeneity for the outcome of detection of 'neonates with seizures' by visual inspection of the forest plots and the summary ROC plots. We will investigate the following sources of heterogeneity.

  1. Gestational age (term versus preterm) of infants

  2. Risk factors for seizure (hypoxic ischaemic encephalopathy versus other causes)

  3. Use of 'raw trace' along with aEEG

  4. Use of seizure detection algorithm

  5. Duration of monitoring (less than or equal to six hours versus more than six hours)

  6. Use of multiple channels

  7. Effect of training (yes/no) in the interpretation of aEEG

  8. Effect of experience (yes/no) in the interpretation of aEEG

If an adequate number of studies are available, we will formally explore heterogeneity by adding each of the above variables as a covariate in the bivariate model (meta‐regression with one covariate at a time) to investigate its impact on summary sensitivity and/or specificity.

Sensitivity analyses

We plan to perform the following sensitivity analyses for the outcome of detection of 'neonates with seizures'.

  1. Sensitivity analyses by excluding studies with high risk of bias. If a study has 'high' risk of bias in 'any' of the four QUADAS domains of risk of bias (patient selection, index test, reference standard, and flow and timing), we will judge the overall risk of bias as 'high'. If a study that is not a 'high' risk study and has 'unclear' risk of bias in 'any' of the four QUADAS domains of risk of bias, we will judge the overall risk of bias as 'unclear'. If a study has 'low' risk of bias in 'all' of the four QUADAS domains of risk of bias, we will judge the overall risk of bias as 'low'.

  2. Sensitivity analysis by excluding studies in which participants were enrolled based on knowledge of cEEG findings.

  3. Sensitivity analysis by excluding studies in which either aEEG was derived from cEEG or aEEG was interpreted retrospectively.

We will perform additional sensitivity analyses if we observe in the study participants, characteristics of the index and reference tests, and methodology, significant variations with a potential to alter the accuracy of the index test.

Assessment of reporting bias

We are not planning to investigate publication bias formally due to the limited knowledge base in this area (Macaskill 2010). We acknowledge, however, that publication bias might be present and might affect the results of the review. To mitigate the risks, we will conduct comprehensive searches, including searches of the grey literature, and contact experts in the field for unpublished data. If an adequate number of studies with different publication status are available (e.g. studies published as full text versus studies published as abstracts), we will include publication status as a covariate in the meta‐regression.