Early Development of Sleep-wake Cycles in Premature Infants and Its Impact on Neurodevelopmental Outcome
SWC
1 other identifier
interventional
60
1 country
1
Brief Summary
Due to the development of neonatal intensive care the number of surviving premature infants increased significantly. The immature brain undergoes a fair amount of external stimuli, which have a great impact on later cognitive development. Increasingly data show, that a delayed emergence of sleep-wake-cycling in newborns can be the first sign of brain injury. Studies have shown that clearly defined sleep states can be identified from 31-32 weeks of gestation onwards. But a few studies show, that also extremely premature infants already show cyclical variations of the background pattern within amplitude-integrated EEG (aEEG= a time-compressed, simplified EEG) and conventional EEG. This might resemble early sleep-wake-states and their presence correlates to the integrity of the central nervous system, although no clearly defined "sleep states" according to the classical definition can be identified. Complex EEG analysis needs the use of automated methods to exclude personal bias and to ensure gestational age specific data analysis. The newly developed NLEO algorithm was specially designed for EEG analysis of premature infants. Conventional EEG within this study will be analyzed visually and with the automated algorithm. In our research project we will study the emergence of Sleep-wake-cycling in extremely premature infants and its impact on their neurodevelopmental outcome prospectively. The different sleep and wake states will be derived from analysis of the conventional Video-EEG, aEEG and polysomnographic measurements. Visual analysis will include assessment of amplitudes and frequencies as well as the latencies and durations of EEG-Bursts and Interburst intervals. The automated NLEO-algorithm will be firstly used for comparison with above described visual analysis and secondly to find regions of interest involved in the organization of these early sleep states. The aim of this study is first to understand and analyze in detail the emergence of sleep-wake cycling including its disturbances in premature infants and to compare automated NLEO algorithm to conventional visual analysis methods. Secondly to correlate neurodevelopmental outcome to the emergence of sleep-wake-cycling.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for not_applicable
Started Feb 2012
Longer than P75 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 1, 2012
CompletedFirst Submitted
Initial submission to the registry
January 4, 2013
CompletedFirst Posted
Study publicly available on registry
January 24, 2013
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2014
CompletedStudy Completion
Last participant's last visit for all outcomes
December 1, 2016
CompletedJanuary 24, 2013
January 1, 2013
2.8 years
January 4, 2013
January 20, 2013
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
description of Sleep-wake-cycles in aEEG and conventional EEG
parallel assessment of sleep-wake cycles in aEEG and conventional EEG
2 years
Secondary Outcomes (1)
Correlation of occurrance of sleep-wake-cycles to neurodevelopmental outcome
4 years
Study Arms (1)
preterm cohort
OTHERpreterm infants born at medical university of vienna and born at gestational age 23+0 - 28+6 weeks of gestation intervention: aEEG and conventional EEG measurements will be performed every two weeks untill 36 weeks of gestation
Interventions
aEEG and conventional EEG measurement including video-polysomnography
Eligibility Criteria
You may not qualify if:
- severe cerebral malformation
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Medical University of Viennalead
- Austrian Science Fund (FWF)collaborator
Study Sites (1)
Medical University Vienna
Vienna, Vienna, 1090, Austria
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Katrin Klebermass-Schrehof, MD
Medical University of Vienna
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- SUPPORTIVE CARE
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- MD
Study Record Dates
First Submitted
January 4, 2013
First Posted
January 24, 2013
Study Start
February 1, 2012
Primary Completion
December 1, 2014
Study Completion
December 1, 2016
Last Updated
January 24, 2013
Record last verified: 2013-01