Prediction of Neonatal Seizures in Hypoxic-Ischemic Encephalopathy Using Electroencephalograph Power Analyses

Siddharth V. Jain, Amit Mathur, Preethi Srinivasakumar, Michael Wallendorf, Joseph P. Culver, John M. Zempel

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background The severity of the initial encephalopathy in neonatal hypoxic-ischemic encephalopathy correlates with seizure burden. Early electroencephalograph (EEG) background activity reflects the severity of encephalopathy. Thus, we hypothesized that early EEG background would be predictive of subsequent seizures in neonatal hypoxic-ischemic encephalopathy. Methods This study included infants undergoing therapeutic hypothermia at St. Louis Children's Hospital between January 2009 and April 2013. Two pediatric epilepsy specialists independently characterized EEG background qualitatively using amplitude-integrated EEG trends. Total EEG power in the 1-20 Hz frequency band was calculated for quantitative EEG background assessment. Seizures were identified on conventional full montage EEG. Statistical analysis was performed using logistic regression. Results Seventy-eight of the 93 eligible infants had artifact-free EEG data; 23 of 78 infants (29%) developed seizures, and of these, 11 developed status epilepticus. The best predictors of subsequent seizures during the first hour of EEG recording were a flat tracing pattern on amplitude-integrated EEG (sensitivity 26%, specificity 98%, likelihood ratio 13, positive predictive value 85%) and the total EEG power less than 10 μV2 (sensitivity 52%, specificity 98%, likelihood ratio 30, positive predictive value 92%). Conclusions Early EEG biomarkers predict subsequent seizures in infants with hypoxic-ischemic encephalopathy. Compared with the qualitative amplitude-integrated EEG background, total EEG power improves our ability to identify high-risk infants from the first hour of EEG recording. Infants with a total EEG power of less than 10 μV2 have a 90% risk of subsequent seizures. Quantitative EEG measures could stratify cohorts while evaluating novel neuroprotective strategies in neonatal hypoxic-ischemic encephalopathy.

Original languageEnglish (US)
Pages (from-to)64-70.e2
JournalPediatric Neurology
Volume67
DOIs
StatePublished - Feb 1 2017

Fingerprint

Brain Hypoxia-Ischemia
Seizures
Brain Diseases
Induced Hypothermia
Sensitivity and Specificity
Status Epilepticus
Artifacts
Epilepsy
Biomarkers
Logistic Models
Pediatrics

Keywords

  • aEEG
  • hypoxic-ischemic encephalopathy
  • neonatal EEG
  • neonatal seizures
  • quantitative EEG
  • seizure prediction
  • total EEG power

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Neurology
  • Developmental Neuroscience
  • Clinical Neurology

Cite this

Prediction of Neonatal Seizures in Hypoxic-Ischemic Encephalopathy Using Electroencephalograph Power Analyses. / Jain, Siddharth V.; Mathur, Amit; Srinivasakumar, Preethi; Wallendorf, Michael; Culver, Joseph P.; Zempel, John M.

In: Pediatric Neurology, Vol. 67, 01.02.2017, p. 64-70.e2.

Research output: Contribution to journalArticle

Jain, Siddharth V. ; Mathur, Amit ; Srinivasakumar, Preethi ; Wallendorf, Michael ; Culver, Joseph P. ; Zempel, John M. / Prediction of Neonatal Seizures in Hypoxic-Ischemic Encephalopathy Using Electroencephalograph Power Analyses. In: Pediatric Neurology. 2017 ; Vol. 67. pp. 64-70.e2.
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abstract = "Background The severity of the initial encephalopathy in neonatal hypoxic-ischemic encephalopathy correlates with seizure burden. Early electroencephalograph (EEG) background activity reflects the severity of encephalopathy. Thus, we hypothesized that early EEG background would be predictive of subsequent seizures in neonatal hypoxic-ischemic encephalopathy. Methods This study included infants undergoing therapeutic hypothermia at St. Louis Children's Hospital between January 2009 and April 2013. Two pediatric epilepsy specialists independently characterized EEG background qualitatively using amplitude-integrated EEG trends. Total EEG power in the 1-20 Hz frequency band was calculated for quantitative EEG background assessment. Seizures were identified on conventional full montage EEG. Statistical analysis was performed using logistic regression. Results Seventy-eight of the 93 eligible infants had artifact-free EEG data; 23 of 78 infants (29{\%}) developed seizures, and of these, 11 developed status epilepticus. The best predictors of subsequent seizures during the first hour of EEG recording were a flat tracing pattern on amplitude-integrated EEG (sensitivity 26{\%}, specificity 98{\%}, likelihood ratio 13, positive predictive value 85{\%}) and the total EEG power less than 10 μV2 (sensitivity 52{\%}, specificity 98{\%}, likelihood ratio 30, positive predictive value 92{\%}). Conclusions Early EEG biomarkers predict subsequent seizures in infants with hypoxic-ischemic encephalopathy. Compared with the qualitative amplitude-integrated EEG background, total EEG power improves our ability to identify high-risk infants from the first hour of EEG recording. Infants with a total EEG power of less than 10 μV2 have a 90{\%} risk of subsequent seizures. Quantitative EEG measures could stratify cohorts while evaluating novel neuroprotective strategies in neonatal hypoxic-ischemic encephalopathy.",
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AB - Background The severity of the initial encephalopathy in neonatal hypoxic-ischemic encephalopathy correlates with seizure burden. Early electroencephalograph (EEG) background activity reflects the severity of encephalopathy. Thus, we hypothesized that early EEG background would be predictive of subsequent seizures in neonatal hypoxic-ischemic encephalopathy. Methods This study included infants undergoing therapeutic hypothermia at St. Louis Children's Hospital between January 2009 and April 2013. Two pediatric epilepsy specialists independently characterized EEG background qualitatively using amplitude-integrated EEG trends. Total EEG power in the 1-20 Hz frequency band was calculated for quantitative EEG background assessment. Seizures were identified on conventional full montage EEG. Statistical analysis was performed using logistic regression. Results Seventy-eight of the 93 eligible infants had artifact-free EEG data; 23 of 78 infants (29%) developed seizures, and of these, 11 developed status epilepticus. The best predictors of subsequent seizures during the first hour of EEG recording were a flat tracing pattern on amplitude-integrated EEG (sensitivity 26%, specificity 98%, likelihood ratio 13, positive predictive value 85%) and the total EEG power less than 10 μV2 (sensitivity 52%, specificity 98%, likelihood ratio 30, positive predictive value 92%). Conclusions Early EEG biomarkers predict subsequent seizures in infants with hypoxic-ischemic encephalopathy. Compared with the qualitative amplitude-integrated EEG background, total EEG power improves our ability to identify high-risk infants from the first hour of EEG recording. Infants with a total EEG power of less than 10 μV2 have a 90% risk of subsequent seizures. Quantitative EEG measures could stratify cohorts while evaluating novel neuroprotective strategies in neonatal hypoxic-ischemic encephalopathy.

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