aEEG as a useful tool for neuromonitoring in critically ill children - Current evidence and knowledge gaps

Association of bilaterally suppressed EEG amplitudes and outcomes in critically ill children

Background and objectives

Amplitude-integrated EEG (aEEG) is used to assess electrocortical activity in pediatric intensive care if (continuous) full channel EEG is unavailable but evidence regarding the meaning of suppressed aEEG amplitudes in children remains limited. This retrospective cohort study investigated the association of suppressed aEEG amplitudes in critically ill children with death or decline of neurological functioning at hospital discharge.

Methods

Two hundred and thirty-five EEGs derived from individual patients <18 years in the pediatric intensive care unit at the University Hospital Essen (Germany) between 04/2014 and 07/2021, were converted into aEEGs and amplitudes analyzed with respect to age-specific percentiles. Crude and adjusted odds ratios (OR) for death, and functional decline at hospital discharge in patients with bilateral suppression of the upper or lower amplitude below the 10th percentile were calculated. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) were assessed.

Results

The median time from neurological insult to EEG recording was 2 days. PICU admission occurred due to neurological reasons in 43% and patients had high overall disease severity. Thirty-three (14%) patients died and 68 (29%) had a functional decline. Amplitude suppression was observed in 48% (upper amplitude) and 57% (lower amplitude), with unilateral suppression less frequent than bilateral suppression. Multivariable regression analyses yielded crude ORs between 4.61 and 14.29 and adjusted ORs between 2.55 and 8.87 for death and functional decline if upper or lower amplitudes were bilaterally suppressed. NPVs for bilaterally non-suppressed amplitudes were above 95% for death and above 83% for pediatric cerebral performance category Scale (PCPC) decline, whereas PPVs ranged between 22 and 32% for death and 49-52% for PCPC decline.

Discussion

This study found a high prevalence of suppressed aEEG amplitudes in critically ill children. Bilaterally normal amplitudes predicted good outcomes, whereas bilateral suppression was associated with increased odds for death and functional decline. aEEG assessment may serve as an element for risk stratification of PICU patients if conventional EEG is unavailable with excellent negative predictive abilities but requires additional information to identify patients at risk for poor outcomes.

Successful Diagnosis of Neuroleptic Malignant Syndrome in an Unconscious Patient Using Amplitude-Integrated Electroencephalography: A Case Report

Neuroleptic malignant syndrome (NMS) is a rare but life-threatening medical condition often characterized by altered consciousness and clinical features resembling seizures. This case report presents a unique and successful diagnosis of NMS in an unconscious patient with an unknown medical history. We demonstrate the potential utility of amplitude-integrated electroencephalography (aEEG) as a valuable tool for the differential diagnosis of seizure-like medical conditions, including NMS. The application of aEEG allowed for early diagnosis and prompt initiation of appropriate treatment, potentially contributing to improved patient outcomes.

[Pediatric neurocritical care]

Pediatric neurocritical care requires multidisciplinary expertise for the care of critically ill children. Approximately 14-16% of critically ill children in pediatric intensive care suffer from a primary neurological disease, whereby cardiac arrest and severe traumatic brain injury play major roles in Europe. The short-term goal of interventions in the pediatric intensive care unit is to stabilize vital functions, whereas the overarching goal is to achieve survival without neurological damage that enables fulfillment of the individual developmental physiological potential. For this reason, evidence-based methods for brain monitoring during the acute phase and recovery are necessary, which can be performed clinically or with technical devices. This applies to critically ill children with primary neurological diseases and for all children at risk for secondary neurological insults. Patients with diseases of the peripheral nervous system are also treated in pediatric intensive care medicine. In these patients, the primary aim frequently consists of bridging the time until recovery after acute deterioration, for example during an infection. In these patients, monitoring the cerebral function can be especially challenging, because due to the underlying disease the results of the examination cannot be interpreted in the same way as for previously neurologically healthy children. This article summarizes the complexity of pediatric neurocritical care by presenting examples of diagnostic and therapeutic approaches in the context of various neurological diseases that can be routinely encountered in the pediatric intensive care unit and can only be successfully treated by multidisciplinary teams.

Amplitude Integrated Electroencephalography - Reference Values in Children aged 2 months to 16 years

AIM

Amplitude integrated electroencephalography (aEEG) is a bedside neuromonitoring tool, standard within neonatal critical care provision. Its application in children is increasing but normative data underpinning such use are lacking. We present a dataset of normative aEEG values for children aged 2 months to 16 years.

METHODS

This retrospective observational cohort study derives aEEG normative amplitude characteristics from electroencephalograms (EEGs) recorded in Children's Health Ireland at Crumlin. aEEG was derived from 350 normal EEGs, recorded in children aged 2 months to 16 years. Supplementary aEEGs were derived from children with abnormal EEG traces. Median upper and lower margin amplitudes, and bandwidth were calculated from 5-minute waking and sleeping EEG epochs.

RESULTS

aEEG amplitudes vary with age and state, increasing over the first two years of life before diminishing. Upper and lower margin amplitudes, and bandwidth are greater during sleep for children < 6 years. Reference ranges may be cohorted into 2 groups (upper and lower reference limits; < 6 years - 38μV/7μV awake, 54μV/10μV asleep; > 6 years - 33μV/5μV awake, 36μV/6μV asleep) CONCLUSION: aEEG traces evolve with age in childhood and differ from neonatal values. We provide a comprehensive set of aEEG normatives to facilitate clinical interpretation in older children.

Amplitude-Integrated EEG Monitoring in Pediatric Intensive Care: Prognostic Value in Meningitis before One Year of Age

Pediatric morbidity from meningitis remains considerable. Preventing complications is a major challenge to improve neurological outcome. Seizures may reveal the meningitis itself or some complications of this disease. Amplitude-integrated electroencephalography (aEEG) is gaining interest for the management of patients with acute neurological distress, beyond the neonatal age. This study aimed at evaluating the predictive value of aEEG monitoring during the acute phase in meningitis among a population of infants hospitalized in the pediatric intensive care unit (PICU), and at assessing the practicability of the technique. AEEG records of 25 infants younger than one year of age hospitalized for meningitis were retrospectively analyzed and correlated to clinical data and outcome. Recording was initiated, on average, within the first six hours for n = 18 (72%) patients, and overall quality was considered as good. Occurrence of seizure, of status epilepticus, and the background pattern were significantly associated with unfavorable neurological outcomes. AEEG may help in the management and prognostic assessment of pediatric meningitis. It is an easily achievable, reliable technique, and allows detection of subclinical seizures with minimal training. However, it is important to consider the limitations of aEEG, and combinate it with conventional EEG for the best accuracy.

EEG monitoring during anesthesia in children aged 0 to 18 months: amplitude-integrated EEG and age effects

Background

The amplitude-integrated EEG (aEEG) is a widely used monitoring tool in neonatology / pediatric intensive care. It takes into account the amplitudes, but not the frequency composition, of the EEG. Advantages of the aEEG are clear criteria for interpretation and time compression. During the first year of life, the electroencephalogram (EEG) during sedation / anesthesia changes from a low-differentiated to a differentiated EEG; higher-frequency waves develop increasingly. There are few studies on the use of aEEG during pediatric anesthesia. A systematic evaluation of the aEEG in defined EEG stages during anesthesia / sedation is not yet available. Parameters of pediatric EEGs (power, median frequency, spectral edge frequency) recorded during anesthesia and of the corresponding aEEGs (upper and lower value of the aEEG trace) should be examined for age-related changes. Furthermore, it should be examined whether the aEEG can distinguish EEG stages of sedation / anesthesia in differentiated EEGs.

Methods

In a secondary analysis of a prospective observational study EEGs and aEEGs (1-channel recordings, electrode positions on forehead) of 50 children (age: 0–18 months) were evaluated. EEG stages: A (awake), Slow EEG, E2, F0, and F1 in low-differentiated EEGs and A (awake), B0–2, C0–2, D0–2, E0–2, F0–1 in differentiated EEGs.

Results

Median and spectral edge frequency increased significantly with age (p < 0.001 each). In low-differentiated EEGs, the power of the Slow EEG increased significantly with age (p < 0.001). In differentiated EEGs, the power increased significantly with age in each of the EEG stages B1 to E1 (p = 0.04, or less), and the upper and lower values of the aEEG trace increased with age (p < 0.001). A discriminant analysis using the upper and lower values of the aEEG showed that EEG epochs from the stages B1 to E1 were assigned to the original EEG stage in only 19.3% of the cases. When age was added as the third variable, the rate of correct reclassifications was 28.5%.

Conclusions

The aEEG was not suitable for distinguishing EEG stages above the burst suppression range. For this purpose, the frequency composition of the EEG should be taken into account.

Characterization of aEEG During Sleep and Wakefulness in Healthy Children

INTRODUCTION

Interpretation of amplitude-integrated EEG (aEEG) is hindered by lacking knowledge on physiological background patterns in children. The aim of this study was to find out whether aEEG differs between wakefulness and sleep in children.

METHODS

Forty continuous full-channel EEGs (cEEG) recorded during the afternoon and overnight in patients <18 years of age without pathologies or only solitary interictal epileptiform discharges were converted into aEEGs. Upper and lower amplitudes of the C3-C4, P3-P4, C3-P3, C4-P4, and Fp1-Fp2 channels were measured during wakefulness and sleep by two investigators and bandwidths (BW) calculated. Sleep states were assessed according to the American Academy of Sleep Medicine. Median and interquartile ranges (IQR) were calculated to compare the values of amplitudes and bandwidth between wakefulness and sleep.

RESULTS

Median age was 9.9 years (IQR 6.1-14.7). All patients displayed continuous background patterns. Amplitudes and BW differed between wakefulness and sleep with median amplitude values of the C3-C4 channel 35 μV (IQR: 27-49) for the upper and 13 μV (10-19) for the lower amplitude. The BW was 29 μV (21-34). During sleep, episodes with high amplitudes [upper: 99 μV (71-125), lower: 35 μV (25-44), BW 63 μV (44-81)] corresponded to sleep states N2-N3. High amplitude-sections were interrupted by low amplitude-sections, which became the longer toward the morning [upper amplitude: 39 μV (30-51), lower: 16 μV (11-20), BW 23 μV (19-31)]. Low amplitude-sections were associated with sleep states REM, N1, and N2. With increasing age, amplitudes and bandwidths declined.

CONCLUSION

aEEGs in non-critically ill children displayed a wide range of amplitudes and bandwidths. Amplitudes were low during wakefulness and light sleep and high during deep sleep. Interpretation of pediatric aEEG background patterns must take into account the state of wakefulness in in clinical practice and research.