Status:
COMPLETED
Prediction of Extubation Readiness in Extreme Preterm Infants by the Automated Analysis of CardioRespiratory Behavior
Lead Sponsor:
McGill University Health Centre/Research Institute of the McGill University Health Centre
Collaborating Sponsors:
Canadian Institutes of Health Research (CIHR)
Wayne State University
Conditions:
Prediction of Extubation Readiness
Eligibility:
All Genders
Brief Summary
The investigators hypothesize that machine learning methods using a combination of novel, quantitative measures of cardio-respiratory variability can accurately predict the optimal time to extubate ex...
Detailed Description
At birth, extreme preterm infants (≤28 weeks) have inconsistent respiratory drive, airway instability, surfactant deficiency and immature lungs that frequently result in respiratory failure. Managemen...
Eligibility Criteria
Inclusion
- All infants admitted to the NICU with a birth weight ≤ 1250 grams AND
- Need for endotracheal tube mechanical ventilation
Exclusion
- Infants with major congenital anomalies
- Infants with congenital heart disease and cardiac arrhythmias
- Infants receiving vasopressor or sedative drugs at the time of extubation
- Infants extubated directly from high frequency ventilation
- Infants extubated to room air, oxyhood or low-flow nasal cannula
Key Trial Info
Start Date :
September 1 2013
Trial Type :
OBSERVATIONAL
Allocation :
ACTUAL
End Date :
December 1 2018
Estimated Enrollment :
266 Patients enrolled
Trial Details
Trial ID
NCT01909947
Start Date
September 1 2013
End Date
December 1 2018
Last Update
April 1 2019
Active Locations (5)
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1
Wayne State University
Detroit, Michigan, United States, 48201
2
Women and Infants Hospital of Rhode Island
Providence, Rhode Island, United States, 02905
3
Royal Victoria Hospital
Montreal, Quebec, Canada, H3A 1A1
4
Montreal Children's Hospital
Montreal, Quebec, Canada, H3H 1P3