title: Multiscale Entropy of Electroencephalogram as a Potential Predictor for the Prognosis of Neonatal Seizures.
abstract: OBJECTIVE
  Increasing animal studies supported the harmful effects of prolonged or frequent neonatal seizures in developing brain, including increased risk of later epilepsy. Various nonlinear analytic measures had been applied to investigate the change of brain complexity with age. This study focuses on clarifying the relationship between later epilepsy and the changes of electroencephalogram (EEG) complexity in neonatal seizures.
  
  
  METHODS
  EEG signals from 19 channels of the whole brain from 32 neonates below 2 months old were acquired. The neonates were classified into 3 groups: 9 were normal controls, 9 were neonatal seizures without later epilepsy, and 14 were neonatal seizures with later epilepsy. Sample entropy (SamEn), multiscale entropy (MSE) and complexity index (CI) were analyzed.
  
  
  RESULTS
  Although there was no significant change in SamEn, the CI values showed significantly decreased over Channels C3, C4, and Cz in patients with neonatal seizures and later epilepsy compared with control group. More multifocal epileptiform discharges in EEG, more abnormal neuroimaging findings, and higher incidence of future developmental delay were noted in the group with later epilepsy.
  
  
  CONCLUSIONS
  Decreased MSE and CI values in patients with neonatal seizures and later epilepsy may reflect the mixed effects of acute insults, underlying brain immaturity, and prolonged seizures-related injuries. The analysis of MSE and CI can therefore provide a quantifiable and accurate way to decrypt the mystery of neonatal seizures, and could be a promising predictor.
authors.affiliation: Department of Pediatrics, New Taipei City Hospital, Taipei, Taiwan.|Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan.
authors.forename: Wen-Yu
authors.initials: WY
authors.lastname: Lu
authors.affiliation: Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Taiwan.
authors.forename: Jyun-Yu
authors.initials: JY
authors.lastname: Chen
authors.affiliation: Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Taiwan.
authors.forename: Chi-Feng
authors.initials: CF
authors.lastname: Chang
authors.affiliation: Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan.|Clinical Center for Neuroscience and Behavior, National Taiwan University Hospital, Taipei, Taiwan.
authors.forename: Wen-Chin
authors.initials: WC
authors.lastname: Weng
authors.affiliation: Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan.|Clinical Center for Neuroscience and Behavior, National Taiwan University Hospital, Taipei, Taiwan.|Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, Taiwan.
authors.forename: Wang-Tso
authors.initials: WT
authors.lastname: Lee
authors.affiliation: Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Taiwan.|Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan.
authors.forename: Jiann-Shing
authors.initials: JS
authors.lastname: Shieh
mesh_terms: D001921:Brain / Q000473:pathology* / Q000503:physiopathology; D016022:Case-Control Studies; D003289:Convalescence; D018450:Disease Progression; D004569:Electroencephalography / Q000379:methods*; D019277:Entropy; D020936:Epilepsy, Benign Neonatal / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D059906:Neuroimaging / Q000379:methods; D011379:Prognosis; D013997:Time Factors