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Early Development of Sleep-wake Cycles in Premature Infants and Its Impact on Neurodevelopmental Outcome (SWC)

The recruitment status of this study is unknown. The completion date has passed and the status has not been verified in more than two years.
Verified January 2013 by Medical University of Vienna.
Recruitment status was:  Recruiting
Austrian Science Fund (FWF)
Information provided by (Responsible Party):
Katrin Klebermass-Schrehof, Medical University of Vienna Identifier:
First received: January 4, 2013
Last updated: January 20, 2013
Last verified: January 2013
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.

Condition Intervention
Sleep Disorders, Circadian Rhythm
Other: aEEG and conventional EEG measurement

Study Type: Interventional
Study Design: Intervention Model: Single Group Assignment
Masking: Open Label
Primary Purpose: Supportive Care
Official Title: Early Development of Sleep-wake Cycles in Premature Infants and Its Impact on Neurodevelopmental Outcome

Further study details as provided by Medical University of Vienna:

Primary Outcome Measures:
  • description of Sleep-wake-cycles in aEEG and conventional EEG [ Time Frame: 2 years ]
    parallel assessment of sleep-wake cycles in aEEG and conventional EEG

Secondary Outcome Measures:
  • Correlation of occurrance of sleep-wake-cycles to neurodevelopmental outcome [ Time Frame: 4 years ]
    correlation of sleep-wake-cycles to Bayley Scales of Infant Development assessed at the age of 2 years

Estimated Enrollment: 60
Study Start Date: February 2012
Estimated Study Completion Date: December 2016
Estimated Primary Completion Date: December 2014 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
preterm cohort
preterm 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
Other: aEEG and conventional EEG measurement
aEEG and conventional EEG measurement including video-polysomnography

  Show Detailed Description


Ages Eligible for Study:   23 Weeks to 29 Weeks   (Child)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No

Inclusion Criteria: preterm infant born below 29+0 weeks

Exclusion Criteria:

severe cerebral malformation

  Contacts and Locations
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Please refer to this study by its identifier: NCT01774318

Medical University Vienna Recruiting
Vienna, Austria, 1090
Contact: Katrin Klebermass-Schrehof, MD    0043/1/40400/2930   
Principal Investigator: Katrin Klebermass-Schrehof, MD         
Sponsors and Collaborators
Medical University of Vienna
Austrian Science Fund (FWF)
Principal Investigator: Katrin Klebermass-Schrehof, MD Medical University of Vienna
  More Information

Responsible Party: Katrin Klebermass-Schrehof, MD, Medical University of Vienna Identifier: NCT01774318     History of Changes
Other Study ID Numbers: KKS-01-2012
Study First Received: January 4, 2013
Last Updated: January 20, 2013

Keywords provided by Medical University of Vienna:
preterm infants
conventional EEG

Additional relevant MeSH terms:
Sleep Wake Disorders
Sleep Disorders, Circadian Rhythm
Nervous System Diseases
Neurologic Manifestations
Signs and Symptoms
Mental Disorders
Chronobiology Disorders
Occupational Diseases processed this record on May 22, 2017