Electroencephalography in infants with periventricular leukomalacia: Prognostic features at preterm and term age

Enrico Biagioni, Laura Bartalena, Antonio Boldrini, Rossella Pieri, Giovanni Cioni

Research output: Contribution to journalArticlepeer-review


Cystic periventricular leukomalacia represents the most severe white- matter lesion in preterm infants and its occurrence accounts for most cases of neurologic impairment in these subjects. Electroencephalographic (EEG) findings and their prognostic value in relation to motor and cognitive outcome were investigated in a group of preterm infants affected by different degrees of cystic periventricular leukomalacia. EEG recordings were carried out in the early postnatal period (first 2 weeks of life) on 24 infants and at term age on 29. In the early postnatal period, background EEG abnormalities ('dysmaturity') were significantly more apparent in affected infants than in a control group, and, among infants with cystic periventricular leukomalacia, this parameter related to the occurrence of cerebral palsy; moreover, at the same age, the incidence of abnormal EEG transients seemed to show a correlation with cognitive outcome. At term age, these latter abnormalities were significantly more apparent in neonates with cystic periventricular leukomalacia than in control subjects, but they did not show any prognostic value. In conclusion, these data indicate that, during the early postnatal period, the EEG is a useful diagnostic and prognostic tool for preterm infants with white-matter lesions, whereas at term age, the role of EEG tracings appears secondary.

Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalJournal of Child Neurology
Issue number1
Publication statusPublished - Jan 2000

ASJC Scopus subject areas

  • Clinical Neurology
  • Pediatrics, Perinatology, and Child Health


Dive into the research topics of 'Electroencephalography in infants with periventricular leukomalacia: Prognostic features at preterm and term age'. Together they form a unique fingerprint.

Cite this