Conflict of Interest Declaration
The ILCOR Continuous Evidence Evaluation process is guided by a rigorous ILCOR Conflict of Interest policy. The following Task Force members and other authors were recused from the discussion as they declared a conflict of interest: (none applicable)
The following Task Force members and other authors declared an intellectual conflict of interest and this was acknowledged and managed by the Task Force Chairs and Conflict of Interest committees:
Dr Topjian was an author and investigator in pediatric post-cardiac arrest neuro-prognostication studies.
Dr Scholefield was an author and investigator in pediatric post-cardiac arrest neuro-prognostication studies and received UK NIHR funding for research into post-cardiac arrest neuro-prognostication research.
Dr Rodriguez-Nunez was an author and investigator in pediatric post-cardiac arrest neuro-prognostication studies.
Barnaby R Scholefield, Janice Tijssen, Saptharishi Lalgudi Ganesan, Mirjam Kool, Alexis Topjian, Thomaz Bittencourt Couto, Anne-Marie Guerguerian on behalf of the International Liaison Committee on Resuscitation Pediatric Life Support Task Force. Electrophysiology testing for the prediction of survival with good neurological outcome after return of circulation following pediatric cardiac arrest Consensus on Science with Treatment Recommendations [Internet] Brussels, Belgium: International Liaison Committee on Resuscitation (ILCOR) Pediatric Life Support Task Force, 2022 XXXX. Available from: http://ilcor.orgg
Methodological Preamble and Link to Published Systematic Review
The continuous evidence evaluation process for the production of Consensus on Science with Treatment Recommendations (CoSTR) started with a systematic review (Scholefield, 2021, PROSPERO CRD42021279221)conducted by the members of the PLS TF with involvement of clinical content experts. Evidence for pediatric literature was sought and considered by the Pediatric Life Support Task Force. Additional scientific literature was published after the completion of the systematic review and identified by the Pediatric Task Force, and is described before the justifications and evidence to decision highlights section of this CoSTR. These data were taken into account when formulating the Treatment Recommendations.
Scholefield B et al. Electrophysiology testing for the prediction of survival with good neurological outcome after return of circulation following pediatric cardiac arrest (in preparation)
The PICOST (Population, Intervention, Comparator, Outcome, Study Designs and Timeframe)
Population: This review is studying children (<18 years) who achieve a return of spontaneous or mechanical circulation (ROC) after resuscitation from in-hospital cardiac arrest (IHCA) and out-of-hospital (OHCA), from any cause.
Studies which include newly born infants or patients in hypoxic coma from causes other than cardiac arrest (e.g., respiratory arrest, toxidromes, drowning, hanging) will be excluded, except when a subpopulation of cardiac arrest patients can be evaluated separately.
Intervention: Index prognostic tests, recorded less than 12 hours, 12 to <24 hours, 24 to <48 hours, 48 to <72 hours, 72hrs to <7 days, and/or 7 to10 days after cardiac arrest and will include:
Electrophysiology: These included surface bioelectrical recordings from the central nervous system such as electroencephalogram (EEG) and evoked potentials (EPs) (e.g. brainstem auditory evoked potentials, and short-latency somatosensory evoked potentials (SSEPs)). We included studies of the interpretation of raw signals or summary measures derived from processed EEG signals such as amplitude-integrated EEG (aEEG), quantitative EEG (qEEG) or bispectral index (BIS).
Comparators: There is no control group for intervention/exposure. However, the accuracy of the prognostic (index) test will be assessed by comparing the predicted outcome with the final outcome, which represents the comparator.
Outcomes: Primary outcome of interest is survival with good neurological outcome*.
*Good neurological outcome is defined as a Pediatric Cerebral Performance Category (PCPC) score of 1, 2 or 3, or Vineland Adaptive Behavioural scale-II ≥ 70. PCPC score ranges 1 (normal), 2 (mild disability), 3 (moderate disability), 4 (severe disability), 5 (coma), and 6 (brain death). We will also separately report studies defining good neurological outcomes with other assessment tools, or as a PCPC score 1 or 2, or change in PCPC score from baseline ≤2.
Outcome time point(s) will include hospital discharge, 30 days, 60 days, 180 days and/or 1 year.
Study Designs: Randomized controlled trials (RCTs) and non-randomized studies (non-randomized controlled trials, interrupted time series, controlled before-and-after studies, cohort studies) were eligible for inclusion. Case series were considered if greater than 5 cases reported. Unpublished studies (e.g., conference abstracts, trial protocols*) and animal studies were excluded. We selected studies where the sensitivity and false-positive rate (FPR) of the prognostic (index) test are reported.
*please note that the search for unpublished trials was limited to a comprehensive search of three clinical trial registries for unpublished completed trials.
1. International Clinical Trials Registry Platform (www.who.int/ictrp/en/)
2. US clinical trials registry (www.ClinicalTrials.gov)
3. Cochrane CENTRAL (http://www.cochranelibrary.com/about/central-landing-page.html)
Timeframe: All years and all languages were included as long as there was an English abstract; unpublished studies (e.g., conference abstracts, trial protocols) were excluded. Literature search updated to Feb 17th 2022.
PROSPERO Registration CRD42021279221
Consensus on Science
The systematic review identified studies reporting the absence or presence of seizures, with and without information from confirmatory EEG, and identified studies reporting specific EEG-based indices for predicting survival and good neurological outcome; however only some used the American Clinical Neurophysiology Society (ACNS) definition of seizures and EEG indices.
For the consensus on science we defined good neurological outcome prediction as imprecise when the false positive rate (FPR) was above 30%. However, there is no universal consensus on what the acceptable limits for imprecision should be in prediction for infants and children after cardiac arrest.
A low false positive rate means that a low proportion of patients, predicted to have a good outcome will have a falsely optimistic prediction (test predicted a good outcome, but patient went on to have a bad outcome). The task force felt that when focused on accuracy of predicting a good outcome - a low false positive rate (eg <30%) is more desirable to avoid falsely optimistic prediction than a high sensitivity. The cut off of 30% FPR (equivalent to 70% specificity) was chosen as the consequences of false optimism were felt by the task force to be less critical than false pessimism. False optimism may result in continued life sustaining therapy in a patient who will eventually have a poor outcome. This will involve increased resources and treatment; however, may also allow more time for further prognostic evaluation. Also, reasons for not achieving a very low false positive rate may be non-neurological causes of poor outcome or death, not attributable to the index test assessment.
A high sensitivity means the majority of patients, who have a good outcome, tested positive and therefore a corresponding low proportion will have a falsely pessimistic prediction (test predicted a poor outcome, but patient went on to have a good outcome). When considering the accuracy of predicting a poor outcome (compared to predicting a good outcome), then a low rate of falsely pessimistic predictions is very important. Our cut off threshold for considering precise sensitivity was therefore higher (>95%), as the consequences of inaccurate poor outcome prediction (e.g. false pessimism) may lead to a decision to limit or withdraw life sustaining therapies in a patient who could have a good neurological outcome.
The overall quality of evidence was rated as very low for all outcomes primarily due to a very serious risk of bias, assessed using the QUIPS tool. The individual studies were all at a moderate to high risk of bias due to confounding. Because of this and a high degree of heterogeneity, no meta-analyses could be performed.
Absence of clinical or electrographic seizure
Twelve studies reported the relationship between absence or presence of seizures in children post-cardiac arrest and good neurological outcomes at PICU/hospital discharge, 6 months and 12 month [Brooks 2018 324, Ducharme-Crevier 2017 452, Fung 2019 349, Kirschen 2021 e719, Lin 2019 534, Meert 2019 393, Moler 2017 318, Moler 2015 1898, Ostendorf 2016 667, Topjian 2016 547, Yang 2019 223]. These studies included 1165 children, of which 4/12 studies reported using the ACNS criteria [Ducharme-Crevier 2017 452, Fung 2019 349, Ostendorf 2016 667, Yang 2019 223].
Absence of seizures up to 24 hours post-ROC had a sensitivity of 50-100% with a FPR of 63-98% for predicting good neurological outcome at various time points. Absence of seizure after 24 hours had a sensitivity of 50-100% with a FPR of 42-100% for predicting good neurological outcome.
Absence of status epilepticus
Absence of status epilepticus was reported in three studies [Fung 2019 349, Topjian 2016 547, Yang 2019 223]. Two of these studies used ACNS criteria to define status epilepticus. Good neurological outcome at PIC/hospital discharge were predicted with a high sensitivity of >90%, although FPR remained high 81-91%.
Absence of myoclonic epilepsy
Based on two studies, absence of myoclonic seizures predicted good neurological outcomes with a sensitivity of 100% but a very high FPR of 79-83% at PICU/hospital discharge [Brooks 2018 324, Ostendorf 2016 667].
Somatosensory evoked potential (SSEPs)
SSEPs, evaluating presence or absence of N20 waves, were reported in only one study, with a small sample size (n=12), reporting good neurological outcome (PCPC 1 to 3) at 3 timepoints (24, 48 and 72 hours) [McDevitt 2021 30]. Clinicians were blinded to test results and the SSEP assessor was blinded to outcome. The predicted sensitivity was 100% at 24 and 48 hours and 83% at 72 hours, with a very low FPR 0% at all time points, but wide 95% confidence intervals (0-71%).
Presence of continuous or normal background EEG
The presence of a normal EEG background (defined as normal, continuous and reactive, continuous and unreactive, and nearly continuous by ACNS definitions) were reported in 10 studies with 18 different testing timings, and included 563 patients (although there was a risk of overlapping patient populations). [Brooks 2018 324, Ducharme-Crevier 2017 452, Fink 2014 664, Fung 2019 349, Kessler 2011 37, Kirschen 2021 e719, Ostendorf 2016 667, Topjian 2016 547, Topjian 2021 282, Yang 2019 223]. Studies using normal or continuous EEG reported a low to moderate sensitivity 10/18 time points were less than 50%. However, FPR was also low with all tests less than 50% and 11/18 < 30%. In the largest study by Topjian 2016, the sensitivity of continuous EEG at 6-12 hours was 7.3% with a FPR of 0%. FPR was higher in studies assessing prognostic accuracy at and beyond 48 hours post-ROC.
Absence of attenuated, isoelectric or flat EEG background
The absence of an attenuated, isoelectric, or flat EEG was reported in 10 studies including up to 526 patients (although there was a risk of overlapping patient populations) [Brooks 2018 324, Ducharme-Crevier 2017 452, Fink 2014 664, Fung 2019 349, Kessler 2011 37, Kirschen 2021 e719, Ostendorf 2016 667, Topjian 2016 547, Topjian 2021 282, Yang 2019 223]. The sensitivity to predict a good neurological outcome was very high in 8 studies (91-100%); however there was a wide range of FPR of 0-83% with the majority of studies reporting >40% FPR.
Absence of burst suppression, burst attenuation or generalized periodic epileptiform discharges (GPEDS) on EEG
Absence of burst suppression, burst attenuation or GPEDS were reported in 6 unblinded studies including 395 patients [Brooks 2018 324, Fung 2019 349, Ostendorf 2016 667, Topjian 2016 547, Topjian 2021 282, Yang 2019 223] . Sensitivity increased from 81-100% within 6-12 hours, to a highly sensitive test (100% with high precision (95%CI 100-100) at 24, 48 and 72 hours. However, the FPR was high at all time periods (67-100%) for predicting a good neurodevelopmental outcome. Electrophysiology EEG attenuated isoelectric ETD
Presence of reactivity on EEG
The presence of reactivity within an EEG trace was reported in 3 studies with a moderate predictive sensitivity for good neurological outcome of 53-80% between 6 to 72 hours. [Ostendorf 2016 667, Topjian 2016 547, Yang 2019 223] FPR ranged 7 to 27% up to 24 hours post ROC in 2 studies [Ostendorf 2016 667, Topjian 2016]. However, it increased to 50% at 48 hours post-ROC in one study.
Presence of sleep II architecture or sleep spindles on EEG
The presence of sleep II architecture or sleep spindles were reported in two studies including 123 patients at 6-12 and 24 hours post-ROC after cardiac arrest. The presence of these features had a predicted sensitivity of 57-80% and low FPR (8.3-16%) [Ducharme-Crevier 2017 452, Topjian 2021 282].
Presence of EEG variability and EEG voltage variability
EEG variability, defined using ACNS criteria, had a moderate sensitivity for predicting good outcome (60-80%) in two studies of 132 patients, with a corresponding FPR of 18 to 50% [Ostendorf 2016 667, Topjian 2021 282]. However, EEG voltage variability had a higher sensitivity (75-100%) in one study at all measured time points (6-12, 24 and 48 hours post ROC) and also a higher corresponding FPR of 36 to 67% [Ostendorf 2016 667].
Quantitative EEG scoring
Only one study reported a composite score assessing EEG background from a 24 hour monitoring period, obtained from quantitative EEG using the amplitude integrated EEG trace in 30 patients [Bourgoin 2020 248]. A score of >15 had a predicted sensitivity of 94% and FPR 67% for a good neurological outcome.
- All evaluated tests were used in combination with other tests by clinicians in these studies. Although the predictive accuracy of tests were evaluated individually, we recommend that no single test should be used in isolation for prediction of good neurological outcome (good practice statement).
- We suggest using electroencephalography (EEG) within 6 to 72hs after ROC for predicting good neurological outcome in children after cardiac arrest (weak recommendation, low-certainty evidence).
- We suggest using the following EEG features for predicting good neurological outcome: presence of sleep spindle and sleep II architecture at 12-24 hours, or continuous or normal background EEG between 1 to 72 hours, or EEG reactivity between 6 to 24 hours (weak recommendation, very-low-certainty evidence).
- We suggest against using the following EEG feature to predict good neurological outcome: absence of clinical or electrographic seizures, absence of status epilepticus, absence of myoclonic epilepsy, absence of burst suppression, burst attenuation or GPEDs, or absence of attenuated, isoelectric or flat EEG. (weak recommendation, very-low-certainty evidence).
- We cannot make a recommendation for or against the use of presence/absence of N20 response SSEPs for predicting good neurological outcome (weak recommendation, very-low-certainty evidence).
- We cannot make a recommendation for or against the use of EEG variability or EEG voltage, or quantitative EEG score for predicting good neurological outcomes. (weak recommendation, very-low-certainty evidence).
Justification and Evidence to Decision Framework Highlights
The Task Force considered the use of individual imaging tests to help the clinician in predicting a good neurological outcome. This assessment is different to predicting a poor neurological outcome, which may involve consideration of withdrawal of life sustaining therapies. Recommendations for or against tests to predict good neurological outcomes cannot be transferred to recommendations for poor outcome prediction.
- The available scientific evidence had a high risk of bias based on high heterogeneity across studies, small number of studies and small number of patients included in addition to lack of blinding, variation in test assessment and performance, and variability in outcome measurement. Therefore, no meta-analysis was performed. Overall assessment of test performance was based on visual assessment of forest plots.
- If only one study was available (with small patient sample size) then a suggestion or recommendation could not be made.
- American Clinical Neurophysiology Society (ACNS) definitions for seizures and EEG indices were followed in only some studies. EEG and SSEP prognostic criteria require clear and reproducible definitions and require validation in the pediatric ICU environment.
- The complex interpretation of normality in background EEG patterns in preterm and term infants, and the impact of brain maturation on EEG patterns in infancy and childhood, requires expert neurophysiology input. Studies reported limited information on handling of this area and further refinement of definitions and application of recommendation are required.
- There was limited or no context of when tests were undertaken in relation to concurrent pharmacological exposure, sedation and ongoing treatment (e.g. TTM) in patients following cardiac arrest.
- SSEPs have a high level of precision in adult studies of neuro-prognostication in comatose patients after cardiac arrest. The Task Force recognises the lack of available data in children and strongly encourages further multi-centre evaluation.
- Electrophysiology tests for prognostication after cardiac arrest appear promising but more research is required in infants and children.
- More research is required on type of monitoring, intermittent or continuous EEG, use of reduced channel monitoring, quantitative EEG systems, duration and timing of prognostic assessment.
- Validation of ACNS or other international definitions of EEG indices within the pediatric ICU environment for infants and children after cardiac arrest.
- Further work on multi-modal prognostication, timing, definitions of testing, accurate outcome timing and definition.
- We encourage wider research and consultation with patients, children, parents, guardians and caregivers, health care professionals and members of the wider society on understanding survivorship after pediatric cardiac arrest to inform correct definitions and framework of good neurological outcome for prediction research.
BROOKS, G. A. & PARK, J. T. 2018. Clinical and Electroencephalographic Correlates in Pediatric Cardiac Arrest: Experience at a Tertiary Care Center. Neuropediatrics, 49, 324.
DUCHARME-CREVIER, L., PRESS, C. A., KURZ, J. E., MILLS, M. G., GOLDSTEIN, J. L. & WAINWRIGHT, M. S. 2017. Early presence of sleep spindles on electroencephalography is associated with good outcome after pediatric cardiac arrest. Pediatric Critical Care Medicine, 18, 452.
FINK, E. L., BERGER, R. P., CLARK, R. S. B., WATSON, R. S., ANGUS, D. C., RICHICHI, R., PANIGRAHY, A., CALLAWAY, C. W., BELL, M. J. & KOCHANEK, P. M. 2014. Serum biomarkers of brain injury to classify outcome after pediatric Cardiac Arrest*. Critical Care Medicine, 42, 664.
FUNG, F. W., TOPJIAN, A. A., XIAO, R. & ABEND, N. S. 2019. Early EEG Features for Outcome Prediction After Cardiac Arrest in Children. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society, 36, 349.
KESSLER, S. K., TOPJIAN, A. A., GUTIERREZ-COLINA, A. M., ICHORD, R. N., DONNELLY, M., NADKARNI, V. M., BERG, R. A., DLUGOS, D. J., CLANCY, R. R. & ABEND, N. S. 2011. Short-term outcome prediction by electroencephalographic features in children treated with therapeutic hypothermia after cardiac arrest. Neurocrit Care, 14, 37.
KIRSCHEN, M. P., LICHT, D. J., FAERBER, J., MONDAL, A., GRAHAM, K., WINTERS, M., BALU, R., DIAZ-ARRASTIA, R., BERG, R. A., TOPJIAN, A. & VOSSOUGH, A. 2021. Association of MRI brain injury with outcome after pediatric out-of-hospital cardiac arrest. Neurology, 96, e719.
MCDEVITT, W. M., ROWBERRY, T. A., DAVIES, P., BILL, P. R., NOTGHI, L. M., MORRIS, K. P. & SCHOLEFIELD, B. R. 2021. The Prognostic Value of Somatosensory Evoked Potentials in Children After Cardiac Arrest: The SEPIA Study. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society 30-35.
OSTENDORF, A. P., HARTMAN, M. E. & FRIESS, S. H. 2016. Early electroencephalographic findings correlate with neurologic outcome in children following cardiac arrest. Pediatric Critical Care Medicine, 17, 667.
TOPJIAN, A. A., SANCHEZ, S. M., SHULTS, J., BERG, R. A., DLUGOS, D. J. & ABEND, N. S. 2016. Early Electroencephalographic Background Features Predict Outcomes in Children Resuscitated from Cardiac Arrest. Pediatric Critical Care Medicine, 17, 547.
TOPJIAN, A. A., ZHANG, B., XIAO, R., FUNG, F. W., BERG, R. A., GRAHAM, K. & ABEND, N. S. 2021. Multimodal monitoring including early EEG improves stratification of brain injury severity after pediatric cardiac arrest. Resuscitation, 167, 282.
YANG, D., RYOO, E. & KIM, H. J. 2019. Combination of early EEG, brain CT, and ammonia level is useful to predict neurologic outcome in children resuscitated from cardiac arrest. Frontiers in Pediatrics, 7, 223.