Dataset Information

Sleep-Wake States and Feeding Progression in Preterm Infants.

ABSTRACT:

Background

Previous studies demonstrated a short-term relationship between infant sleep-wake states and oral feeding performance, with state being an indication of infants' neurobehavioral readiness for feeding. However, the relationship between sleep-wake states and feeding skills has not been evaluated longitudinally during hospitalization.

Objectives

The purpose of this study was to examine preterm infants' sleep-wake state developmental trajectories and their associations with feeding progression during hospitalization.

Methods

This descriptive and exploratory study was a secondary analysis using data from a longitudinal two-group, randomized controlled trial evaluating the effects of early and late cycled light on health and developmental outcomes among extremely preterm infants who were born ?28 weeks of gestational age. Sleep-wake states were assessed for two 2-hour interfeeding periods per day (day and night hours), 30 weeks postmenstrual age, and every 3 weeks until discharge. Occurrences of active sleep, quiet sleep, and waking were recorded every 10 seconds. Feeding progression was assessed based on an infant's postmenstrual age at five milestones: first enteral feeding, full enteral feeding, first oral feeding, half oral feeding, and full oral feeding. Trajectory analyses were used to describe developmental changes in sleep-wake states, feeding progression patterns, and associations between feeding progression and sleep-wake trajectories.

Results

Active sleep decreased while waking, and quiet sleep increased during hospitalization. Two distinct feeding groups were identified: typical and delayed feeding progression. In infants with delayed feeding progression, rates of active and quiet sleep development during the day were delayed compared to those with typical feeding progression. We also found that infants with delayed feeding progression were more likely to be awake more often during the night compared to infants with typical feeding progression.

Discussions

Findings suggest that delays in sleep-wake state development may be associated with delays in feeding progression during hospitalization. Infants with delayed feeding skill development may require more environmental protection to further support their sleep development.

SUBMITTER: Park J

PROVIDER: S-EPMC6919212 | biostudies-literature | 2020 Jan/Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sleep-Wake States and Feeding Progression in Preterm Infants.

Park Jinhee J Silva Susan G SG Thoyre Suzanne M SM Brandon Debra H DH

Nursing research 20200101 1

<h4>Background</h4>Previous studies demonstrated a short-term relationship between infant sleep-wake states and oral feeding performance, with state being an indication of infants' neurobehavioral readiness for feeding. However, the relationship between sleep-wake states and feeding skills has not been evaluated longitudinally during hospitalization.<h4>Objectives</h4>The purpose of this study was to examine preterm infants' sleep-wake state developmental trajectories and their associations with ...[more]

PMID: 31834117

Similar Datasets

Project description:Among infants born prematurely, competence at oral feeding is necessary for growth and hospital discharge. Extremely preterm (EP) infants (28 weeks of gestational age [GA]) are at risk for a variety of medical complications, which can limit the infant's capacity to develop oral feeding competence.This study examined feeding progression by assessing timing of acquisition of five early feeding milestones among EP infants and the impact of immaturity and medical complications.A chart review was conducted for 94 EP infants who participated in a larger longitudinal randomized study. Feeding progression was defined as infants' postmenstrual age (PMA) at five milestones: first enteral feeding, full enteral feeding, first oral feeding, half oral feeding, and full oral feeding. GA at birth and five medical complications (neurological risk, bronchopulmonary dysplasia, necrotizing enterocolitis, patent ductus arteriosus, and gastroesophageal reflux disease) were used as potential factors influencing the feeding progression. Linear mixed models were used to examine feeding progression across the milestones and contributions of GA at birth and five medical complications on the progression, after controlling for milk type as a covariate.EP infants gradually achieved feeding milestones; however, the attainment of the feeding milestones slowed significantly for infants with younger GA at birth and the presence of medical complications, including neurological risk, bronchopulmonary dysplasia, necrotizing enterocolitis, and patent ductus arteriosus but not gastroesophageal reflux disease. Milk type was a significant covariate for all analyses, suggesting that infants fed with breast milk achieved each of five milestones earlier than formula-fed infants.Improved understanding of the timing of essential feeding milestones among EP infants and the contribution of specific medical conditions to the acquisition of these milestones may allow for more targeted care to support feeding skill development.

Project description:BackgroundDifferentiating nonwear time from sleep and wake times is essential for the estimation of sleep duration based on actigraphy data. To efficiently analyze large-scale data sets, an automatic method of identifying these three different states is required. Therefore, we developed a classification algorithm to determine nonwear, sleep and wake periods from accelerometer data. Our work aimed to (I) develop a new pattern recognition algorithm for identifying nonwear periods from actigraphy data based on the influence of respiration rate on the power spectrum of the acceleration signal and implement it in an automatic classification algorithm for nonwear/sleep/wake states; (II) address motion artifacts that occur during nonwear periods and are known to cause misclassification of these periods; (III) adjust the algorithm depending on the sensor position (wrist, chest); and (IV) validate the algorithm on both healthy individuals and patients with sleep disorders.MethodsThe study involved 98 participants who wore wrist and chest acceleration sensors for one day of measurements. They spent one night in the sleep laboratory and continued to wear the sensors outside of the laboratory for the remainder of the day. The results of the classification algorithm were compared to those of the reference source: polysomnography for wake/sleep and manual annotations for nonwear/wear classification.ResultsThe median kappa values for the two locations were 0.83 (wrist) and 0.84 (chest). The level of agreement did not vary significantly by sleep health (good sleepers vs. subjects with sleep disorders) (p = 0.348, p = 0.118) or by sex (p = 0.442, p = 0.456). The intraclass correlation coefficients of nonwear total time between the reference and the algorithm were 0.92 and 0.97 with the outliers and 0.95 and 0.98 after the outliers were removed for the wrist and chest, respectively. There was no evidence of an association between the mean difference (and 95% limits of agreement) and the mean of the two methods for either sensor position (wrist p = 0.110, chest p = 0.164), and the mean differences (algorithm minus reference) were 5.11 [95% LoA -15.4-25.7] and 1.32 [95% LoA -9.59-12.24] min/day, respectively, after the outliers were removed.DiscussionWe studied the influence of the respiration wave on the power spectrum of the acceleration signal for the differentiation of nonwear periods from sleep and wake periods. The algorithm combined both spectral analysis of the acceleration signal and rescoring. Based on the Bland-Altman analysis, the chest-worn accelerometer showed better results than the wrist-worn accelerometer.

Dataset Information

Sleep-Wake States and Feeding Progression in Preterm Infants.

Background

Objectives

Methods

Results

Discussions

Publications

Sleep-Wake States and Feeding Progression in Preterm Infants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets