Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study

Background: To improve the objective assessment of continuous video-EEG (cEEG) monitoring of neonatal brain function, the aim was to relate automated derived amplitude and duration parameters of the suppressed periods in the EEG background (dynamic Interburst Interval= dIBIs) after neonatal hypoxic-ischemic encephalopathy (HIE) to favourable or adverse neurodevelopmental outcome. Methods: Nineteen neonates (gestational age 36-41 weeks) with HIE underwent therapeutic hypothermia and had cEEG-monitoring. EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals. Median duration and amplitude of the dIBIs were calculated at 1h-intervals. Sensitivity and specificity of automated EEG background grading for favorable and adverse outcomes were assessed at 6h-intervals. Results: Dynamic IBI values reached the best prognostic value between 18 and 24h (AUC of 0.93). EEGs with dIBI amplitude ≥15 μV and duration 10s were specific for adverse outcome (89-100%) at 18-24h (n = 10). Extremely low voltage and invariant EEG patterns were indicative of adverse outcome at all time points. Conclusions: Automated analysis of the suppressed periods in EEG of neonates with HIE undergoing TH provides objective and early prognostic information. This objective tool can be used in a multimodal strategy for outcome assessment. Implementation of this method can facilitate clinical practice, improve risk stratification and aid therapeutic decision-making. A multicenter trial with a quantifiable outcome measure is warranted to confirm the predictive value of this method in a more heterogeneous dataset

Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study

BACKGROUND: To improve the objective assessment of continuous video-EEG (cEEG) monitoring of neonatal brain function, the aim was to relate automated derived amplitude and duration parameters of the suppressed periods in the EEG background (dynamic Interburst Interval= dIBIs) after neonatal hypoxic-ischemic encephalopathy (HIE) to favourable or adverse neurodevelopmental outcome. METHODS: Nineteen neonates (gestational age 36-41 weeks) with HIE underwent therapeutic hypothermia and had cEEG-monitoring. EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals. Median duration and amplitude of the dIBIs were calculated at 1 h-intervals. Sensitivity and specificity of automated EEG background grading for favorable and adverse outcomes were assessed at 6 h-intervals. RESULTS: Dynamic IBI values reached the best prognostic value between 18 and 24 h (AUC of 0.93). EEGs with dIBI amplitude ≥15 μV and duration 10 s were specific for adverse outcome (89-100%) at 18-24 h (n = 10). Extremely low voltage and invariant EEG patterns were indicative of adverse outcome at all time points. CONCLUSIONS: Automated analysis of the suppressed periods in EEG of neonates with HIE undergoing TH provides objective and early prognostic information. This objective tool can be used in a multimodal strategy for outcome assessment. Implementation of this method can facilitate clinical practice, improve risk stratification and aid therapeutic decision-making. A multicenter trial with a quantifiable outcome measure is warranted to confirm the predictive value of this method in a more heterogeneous dataset.status: publishe

Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study

Background: To improve the objective assessment of continuous video-EEG (cEEG) monitoring of neonatal brain function, the aim was to relate automated derived amplitude and duration parameters of the suppressed periods in the EEG background (dynamic Interburst Interval= dIBIs) after neonatal hypoxic-ischemic encephalopathy (HIE) to favourable or adverse neurodevelopmental outcome. Methods: Nineteen neonates (gestational age 36–41 weeks) with HIE underwent therapeutic hypothermia and had cEEG-monitoring. EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals. Median duration and amplitude of the dIBIs were calculated at 1 h-intervals. Sensitivity and specificity of automated EEG background grading for favorable and adverse outcomes were assessed at 6 h-intervals. Results: Dynamic IBI values reached the best prognostic value between 18 and 24 h (AUC of 0.93). EEGs with dIBI amplitude ≥15 μV and duration 10 s were specific for adverse outcome (89–100%) at 18–24 h (n = 10). Extremely low voltage and invariant EEG patterns were indicative of adverse outcome at all time points. Conclusions: Automated analysis of the suppressed periods in EEG of neonates with HIE undergoing TH provides objective and early prognostic information. This objective tool can be used in a multimodal strategy for outcome assessment. Implementation of this method can facilitate clinical practice, improve risk stratification and aid therapeutic decision-making. A multicenter trial with a quantifiable outcome measure is warranted to confirm the predictive value of this method in a more heterogeneous dataset. Keywords: hypoxic-ischemic encephalopathy, automated EEG analysis, dynamic Interburst Interval, outcome predictio

Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database

OBJECTIVE: To assess interrater agreement based on majority voting in visual scoring of neonatal seizures. METHODS: An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on 'majority voting' and interrater agreement was estimated using Fleiss' Kappa. The influences of different factors on agreement were determined. RESULTS: 1919 Events extracted from 280h EEG of 71 neonates were reviewed by 4 raters. Majority voting was applied to assign a seizure/non-seizure classification. 44% of events were classified with high, 36% with moderate, and 20% with poor agreement, resulting in a Kappa value of 0.39. 68% of events were labelled as seizures, and in 46%, all raters were convinced about electrographic seizures. The most common seizure duration was <30s. Raters agreed best for seizures lasting 60-120s. There was a significant difference in electrographic characteristics of seizures versus dubious events, with seizures having longer duration, higher power and amplitude. CONCLUSIONS: There is a wide variability in identifying rhythmic ictal and non-ictal EEG events, and only the most robust ictal patterns are consistently agreed upon. Database composition and electrographic characteristics are important factors that influence interrater agreement. SIGNIFICANCE: The use of well-described databases and input of different experts will improve neonatal EEG interpretation and help to develop uniform seizure definitions, useful for evidence-based studies of seizure recognition and management.status: publishe

Early epileptiform EEG activity in infants with tuberous sclerosis complex predicts epilepsy and neurodevelopmental outcomes

Objective To study the association between timing and characteristics of the first electroencephalography (EEG) with epileptiform discharges (ED-EEG) and epilepsy and neurodevelopment at 24 months in infants with tuberous sclerosis complex (TSC).Methods Patients enrolled in the prospective Epileptogenesis in a genetic model of epilepsy - Tuberous sclerosis complex (EPISTOP) trial, had serial EEG monitoring until the age of 24 months. The timing and characteristics of the first ED-EEG were studied in relation to clinical outcome. Epilepsy-related outcomes were analyzed separately in a conventionally followed group (initiation of vigabatrin after seizure onset) and a preventive group (initiation of vigabatrin before seizures, but after appearance of interictal epileptiform discharges [IEDs]).Results Eighty-three infants with TSC were enrolled at a median age of 28 days (interquartile range [IQR] 14-54). Seventy-nine of 83 patients (95%) developed epileptiform discharges at a median age of 77 days (IQR 23-111). Patients with a pathogenic TSC2 variant were significantly younger (P-value .009) at first ED-EEG and more frequently had multifocal IED (P-value .042) than patients with a pathogenic TSC1 variant. A younger age at first ED-EEG was significantly associated with lower cognitive (P-value .010), language (P-value .001), and motor (P-value .013) developmental quotients at 24 months.In the conventional group, 48 of 60 developed seizures. In this group, the presence of focal slowing on the first ED-EEG was predictive of earlier seizure onset (P-value .030). Earlier recording of epileptiform discharges (P-value .019), especially when multifocal (P-value .026) was associated with higher risk of drug-resistant epilepsy.In the preventive group, timing, distribution of IED, or focal slowing, was not associated with the epilepsy outcomes. However, when multifocal IEDs were present on the first ED-EEG, preventive treatment delayed the onset of seizures significantly (P-value &lt;.001).Significance Early EEG findings help to identify TSC infants at risk of severe epilepsy and neurodevelopmental delay and those who may benefit from preventive treatment with vigabatrin