Respiratory Regularity Research Articles

Automated State Analyses: Proposed Applications to Neonatal Neurointensive Care

The two principal challenges of neonatal physiologic monitoring device are: (1) the development of computational strategies that consider the rudimentary forms of neonatal sleep state especially for preterm infants and (2) any physiologic monitoring device for clinical applications in a neonatal intensive care setting must be small, portable, and user-friendly. Our multicenter neonatal sleep consortium has acquired more than 1,100 multihour EEG-sleep recordings on over 370 neonates, ranging from 24 to 44 weeks gestation. Each recording was visually-scored for state, arousals, movements, and rapid eye movements, which were used as templates when applying spectral analyses. The authors have defined a brain dysmaturity index to represent functional brain reorganization as the prenate matures to a full-term age; delayed or accelerated physiologic behaviors have been described for the preterm cohort when compared to the full-term group at the same postmenstrual age. Seven EEG-sleep measures comprise this index: quiet sleep percentage, sleep cycle length, rapid eye movements, arousals, spectral beta EEG energies, spectral EEG correlations, and a spectral measure of respiratory regularity. Linear and nonlinear computational algorithms are being developed to automate the computation of the dysmaturity index and to identify new feature types that correlate with dysmaturity. Automated neonatal sleep monitoring system can potentially improve neonatal neurointensive care by facilitating analyses of pervasive neonatal brain disorders expressed primarily as altered sleep state organization, and help predict altered developmental trajectories of children at higher risk for neurologic sequelae.

Prevalence of and risk factors for respiratory dyskinesia.

We explored the prevalence of respiratory dyskinesia (RD), diagnosed objectively using a spirograph, and the major risk factors for tardive dyskinesia (TD) and RD. A total of 258 inpatients treated with neuroleptics was interviewed, and TD was evaluated using the Abnormal Involuntary Movement Scale (AIMS). Movement of the chest and respiratory regularity were assessed on clinical examination. Spirographs of patients with suspected RD were recorded, and RD was diagnosed based on spirographic data and the concurrence of two investigators. The prevalence of TD in this study was 22.1% (57 of 258). Aging and organic brain damage (OBD) were confirmed as risk factors; female gender, mood disorders, and the duration of neuroleptic exposure were not. Ten of 28 patients suspected of having RD were diagnosed with RD on the basis of persistent respiratory irregularities without other physiologic causes. The overall prevalence of RD was 3.9% (10 of 258) and was 17.5% (10 of 57) among the TD patient population. Four of these patients complained of dyspnea, and three demonstrated grunting. RD was more highly associated with aging and OBD than with TD itself. The identification of risk factors for RD is not only helpful in planning prophylactic strategies, but also facilitates the understanding of the pathogenesis of this syndrome.

Do lung volumes change with sleep state in the neonate?

We have studied 12 healthy full-term babies, mean age 3.2 days, using physiological criteria--EEG, electrooculogram, electromyogram, respiratory regularity and visible movement--to assess sleep state, and a respiratory jacket to record changes in functional residual capacity (FRC). A total of 593 min of sleep data were analysed. Of the recordings, 39% were scored as quiet sleep, 40% as active and 21% as indeterminate sleep. The mean maximum variation in FRC overall was 29 ml (SD +/- 15.4 ml). Examination of these figures showed that FRC variations during sleep state changes were smaller than those seen within a defined sleep state. We conclude that changes in sleep state are not associated with variations in FRC.