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Characterization of neonatal seizures in an animal model of hypoxic-ischemic encephalopathy.

ABSTRACT: In this study, we use time-locked video and electroencephalography (EEG) recordings to characterize acute seizures and EEG abnormalities in an animal model that replicates many salient features of human neonatal hypoxic-ischemic encephalopathy (HIE) including the brain injury pattern and long-term neurologic outcome.Hypoxia-ischemia (HI) was induced in 7-day-old rats by ligating the right carotid artery and exposing the pups to hypoxia for 2 h (Rice-Vannucci method). To identify seizures and abnormal EEG activity, pups were monitored by video-EEG during hypoxia and at various time points after HI. Occurrence of electroclinical seizures, purely electrographic seizures and other abnormal discharges on EEG, was quantified manually. A power spectrum analysis was done to evaluate the effects of HI on EEG spectra in the 1-50 Hz frequency band.During hypoxia, all pups exhibit short duration, but frequent electroclinical seizures. Almost all pups continue to have seizures in the immediate period following termination of hypoxia. In more than half of the HI rats, seizures persisted for 24 h; for some of them, the seizures continued for >48 h. Seizures were not observed in any rats at 72 h after HI induction. A significant reduction in background EEG voltage in the cortex ipsilateral to the ligated carotid artery occurred in rats subjected to HI. In addition, purely electrographic seizures, spikes, sharp waves, and brief runs of epileptiform discharges (BREDs) were also observed in these rats.HI induction in P7 rats using the Rice-Vannucci method resulted in the development of seizures and EEG abnormalities similar to that seen in human neonates with HIE. Therefore, we conclude that this is a valid model to test the efficacy of novel interventions to treat neonatal seizures.

SUBMITTER: Sampath D

PROVIDER: S-EPMC4107002 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Characterization of neonatal seizures in an animal model of hypoxic-ischemic encephalopathy.

Sampath Dayalan D White Andrew M AM Raol Yogendra H YH

Epilepsia 20140516 7

<h4>Objective</h4>In this study, we use time-locked video and electroencephalography (EEG) recordings to characterize acute seizures and EEG abnormalities in an animal model that replicates many salient features of human neonatal hypoxic-ischemic encephalopathy (HIE) including the brain injury pattern and long-term neurologic outcome.<h4>Methods</h4>Hypoxia-ischemia (HI) was induced in 7-day-old rats by ligating the right carotid artery and exposing the pups to hypoxia for 2 h (Rice-Vannucci met ...[more]

PMID: 24836645

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Project description:ObjectiveTo assess if early clinical and electroencephalography (EEG) features predict later seizure development in infants with hypoxic-ischemic encephalopathy (HIE).MethodsClinical and EEG parameters <12 h of birth from infants with HIE across eight European Neonatal Units were used to develop seizure-prediction models. Clinical parameters included intrapartum complications, fetal distress, gestational age, delivery mode, gender, birth weight, Apgar scores, assisted ventilation, cord pH, and blood gases. The earliest EEG hour provided a qualitative analysis (discontinuity, amplitude, asymmetry/asynchrony, sleep-wake cycle [SWC]) and a quantitative analysis (power, discontinuity, spectral distribution, inter-hemispheric connectivity) from full montage and two-channel amplitude-integrated EEG (aEEG). Subgroup analysis, only including infants without anti-seizure medication (ASM) prior to EEG was also performed. Machine-learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver-operating characteristic curve (AUC).ResultsThe study included 162 infants with HIE (53 had seizures). Low Apgar, need for ventilation, high lactate, low base excess, absent SWC, low EEG power, and increased EEG discontinuity were associated with seizures. The following predictive models were developed: clinical (MCC 0.368, AUC 0.681), qualitative EEG (MCC 0.467, AUC 0.729), quantitative EEG (MCC 0.473, AUC 0.730), clinical and qualitative EEG (MCC 0.470, AUC 0.721), and clinical and quantitative EEG (MCC 0.513, AUC 0.746). The clinical and qualitative-EEG model significantly outperformed the clinical model alone (MCC 0.470 vs 0.368, p-value .037). The clinical and quantitative-EEG model significantly outperformed the clinical model (MCC 0.513 vs 0.368, p-value .012). The clinical and quantitative-EEG model for infants without ASM (n = 131) had MCC 0.588, AUC 0.832. Performance for quantitative aEEG (n = 159) was MCC 0.381, AUC 0.696 and clinical and quantitative aEEG was MCC 0.384, AUC 0.720.SignificanceEarly EEG background analysis combined with readily available clinical data helped predict infants who were at highest risk of seizures, hours before they occur. Automated quantitative-EEG analysis was as good as expert analysis for predicting seizures, supporting the use of automated assessment tools for early evaluation of HIE.

Dataset Information

Characterization of neonatal seizures in an animal model of hypoxic-ischemic encephalopathy.

Publications

Characterization of neonatal seizures in an animal model of hypoxic-ischemic encephalopathy.

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