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Abstract
Objective: To test the hypothesis that neonatal sleep physiology reflects cerebral dysfunction, we compared neurologic examination scores to the proportions of recorded sleep/wake states, sleep depth, and sleep fragmentation in critically ill neonates.
Methods: Newborn infants (≥35 weeks gestation) who required intensive care and were at risk for seizures were monitored with 8- to 12-hour polysomnograms (PSGs). For each infant, the distribution of sleep-wake states, entropy of the sequence of state transitions, and delta power from the EEG portion of the PSG were quantified. Standardized neurologic examination (Thompson) scores were calculated.
Results: Twenty-eight infants participated (mean gestational age 39.0 ± 1.6 weeks). An increased fraction of quiet sleep correlated with worse neurologic examination scores (Spearman rho = 0.54, p = 0.003), but the proportion of active sleep did not (p > 0.1). Higher state entropy corresponded to better examination scores (rho = −0.43, p = 0.023). Decreased delta power during quiet sleep, but not the power at other frequencies, was also associated with worse examination scores (rho = −0.48, p = 0.009). These findings retained significance after adjustment for gestational age or postmenstrual age at the time of the PSG. Sleep stage transition probabilities were also related to examination scores.
Conclusions: Among critically ill neonates at risk for CNS dysfunction, several features of recorded sleep—including analyses of sleep stages, depth, and fragmentation—showed associations with neurologic examination scores. Quantitative PSG analyses may add useful objective information to the traditional neurologic assessment of critically ill neonates.
GLOSSARY
- FFT=
- fast Fourier transform;
- NICU=
- neonatal intensive care unit;
- PSG=
- polysomnography
Footnotes
Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
- Received July 4, 2013.
- Accepted in final form October 23, 2013.
- © 2014 American Academy of Neurology
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