Advances in perinatal care have led to decreased mortality of premature infants;however, these infants remain at high risk for cerebral palsy (CP), developmental delay, and sensory-motor deficits in infancy and learning disabilities, dyslexia, and hyperactivity-inattention syndromes at school age. Certain risk factors for poor outcomes are not altered by neonatal care such as socioeconomic status, sex, birth weight and gestational age at birth. However there are other risks for both term and preterm infants that may be modifiable through medical or social interventions. These include: 1) prenatal factors such as fetal exposure to alcohol and tobacco smoke, drugs of use and abuse and, in some cases, mode of delivery;2) intra-partum factors such as presence and duration of labor and rupture of membranes, chorioamnionitis, antenatal corticosteroids, and mode of delivery;and 3) postnatal factors such as intraventricular hemorrhage, nosocomial infections and sepsis, days on mechanical ventilation, necrotizing enterocolitis and chronic lung disease. It is notable that prior research has associated these risks with adverse neurodevelopmental outcome. Recent multicenter studies have shown that adverse outcomes can occur in prematurely born infants with no evidence of neurological compromise at hospital discharge and there are significant sequellae even for those born close to term. These findings point to a gap in prognostic markers readily available during the course of neonatal care that identify cerebral abnormalities that presage abnormal development manifest later in life. Based on our preliminary research, we propose that EEG data acquired at term post menstrual age (PMA) can yield information that identifies at-risk infants. We will test these hypotheses with a secondary analysis of the NICHD Collaborative Home Infant Monitoring Evaluation (CHIME) data collected from 1994 to 1998. The CHIME study is unique in that it acquired data relevant to prenatal and intra-partum risk, neonatal disorders, EEG and polysomnographic data in early infancy along with neurobehavioral testing later in infancy. These data are from groups with varying degrees of vulnerability to sudden infant death syndrome (SIDS) and include prematurely born infants, infants with apparent life threatening events (ALTE), siblings of infants with SIDS and typical infants born at term. These analyses of the CHIME data will test hypotheses relating risk information to quantitative measures of EEG power, synchrony and nonlinear coupling to sleep state, and neurodevelopmental outcome. It is our hypothesis that parameters of cortical synchrony and coupling derived from EEG data acquired at term PMA are early markers relating perinatal risk to cognitive outcome. To evaluate this hypothesis we will develop new algorithms to compute measures of synchrony and nonlinear coupling in CHIME EEG waveforms using recently developed theory and relate these parameters of cortical function to risk factors for and measures of adverse outcome.

Public Health Relevance

There is a gap in prognostic markers readily available during the course of neonatal care that identifies cerebral abnormalities that presage abnormal development manifest later in life. We propose that EEG data acquired at term age can yield information that identifies at-risk infants. We will test these hypotheses with a secondary analysis of the NICHD Collaborative Home Infant Monitoring Evaluation (CHIME) data collected from 1994 to 1998.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Small Research Grants (R03)
Project #
5R03HD060671-02
Application #
7826645
Study Section
Pediatrics Subcommittee (CHHD)
Program Officer
Willinger, Marian
Project Start
2009-05-06
Project End
2012-04-30
Budget Start
2010-05-01
Budget End
2012-04-30
Support Year
2
Fiscal Year
2010
Total Cost
$80,442
Indirect Cost
Name
Columbia University (N.Y.)
Department
Pediatrics
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Myers, M M; Grieve, P G; Izraelit, A et al. (2012) Developmental profiles of infant EEG: overlap with transient cortical circuits. Clin Neurophysiol 123:1502-11