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Prediction of Extubation Readiness in Extreme Preterm Infants by the Automated Analysis of CardioRespiratory Behavior

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ClinicalTrials.gov Identifier: NCT01909947
Recruitment Status : Recruiting
First Posted : July 29, 2013
Last Update Posted : August 22, 2018
Sponsor:
Collaborators:
Canadian Institutes of Health Research (CIHR)
Wayne State University
Brown University
Information provided by (Responsible Party):
Guilherme Sant'Anna, MD, McGill University Health Center

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 extreme preterm infants. In this multicenter prospective study, cardiorespiratory signals will be recorded from 250 extreme preterm infants who are eligible for extubation. Automated signal analysis algorithms will compute a variety of metrics for each infant describing the cardiorespiratory state. Machine learning methods will then be used to find the optimal combination of these statistical measures and clinical features that provide the best overall predictor of extubation readiness. Finally, investigators will develop an Automated system for Prediction of EXtubation (APEX) that will integrate the software for data acquisition, signal analysis, and outcome prediction into a single application suitable for use by medical personnel in the Neonatal Intensive Care Unit (NICU). The performance of APEX will later be clinically validated in 50 additional infants prospectively.

Condition or disease Intervention/treatment
Prediction of Extubation Readiness Other: Cardiorespiratory signal acquisition

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. Management of these infants is difficult and most will require endotracheal intubation and mechanical ventilation (ETT-MV) within the first days of life to survive. ETT-MV is an invasive therapy that is associated with adverse clinical outcomes including ventilator-associated pneumonia, impaired neurodevelopment, and increased mortality. Consequently, clinicians try to remove ETT-MV as quickly as possible. However, 25 to 35% of these extubation attempts will fail and infants will require reintubation, an intervention that is also associated with increased morbidity and mortality. Therefore physicians must determine the optimal time for extubation which minimizes the duration of ETT-MV and maximizes the chances of success. A variety of objective measures have been proposed to assist with this decision but none has proven to be useful clinically. Investigators from this group have recently explored the predictive power of indices of autonomic nervous system function based on measurements of heart rate (HRV) and respiratory variability (RV). The use of sophisticated, automated algorithms to analyze those cardiorespiratory signals have shown some promising preliminary results in predicting which infants can be extubated successfully.

Study Type : Observational
Estimated Enrollment : 250 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Prediction of Extubation Readiness in Extreme Preterm Infants by the Automated Analysis of CardioRespiratory Behavior: the APEX Study
Actual Study Start Date : September 2013
Estimated Primary Completion Date : August 31, 2018
Estimated Study Completion Date : December 2018

Group/Cohort Intervention/treatment
Intubated extreme preterm infants
Infants with a birth weight ≤ 1250 grams and requiring endotracheal tube and mechanical ventilation
Other: Cardiorespiratory signal acquisition

Cardiorespiratory signals will measure heart rate (using electrocardiography), chest and abdominal movements (using respiratory inductance plethysmography) and oxygen saturation (using pulse oximetry). Data will be acquired during 2 recording periods:

  1. A 60-minute period while the infant receives any mode of conventional mechanical ventilation
  2. A 5-minute period prior to extubation while the mode of ventilation is switched to endotracheal tube CPAP (Continuous Positive Airway Pressure), so that the respiratory pattern will be controlled by the infant




Primary Outcome Measures :
  1. Extubation Failure [ Time Frame: Within 72 hours of extubation ]

    Infants will be considered to have failed extubation if they meet one or more of the following criteria within 72 hours of extubation:

    1. Fraction of inspired oxygen (FiO2) > 0.5 in order to maintain oxygen saturation (SpO2) > 88% or PaO2 > 45 mmHg (for 2 consecutive hours)
    2. PaCO2 > 55-60 mmHg with a pH < 7.25 in two consecutive blood gases done 1-2 hours apart
    3. 1 episode of apnea requiring positive pressure ventilation with bag and mask
    4. Multiple episodes of apnea (≥ 6 episodes / 6 hours).


Secondary Outcome Measures :
  1. The need for reintubation within 72h of the first planned extubation [ Time Frame: Within 72 hours of extubation ]
    The decision to re-intubate will be made by the responsible physician, who may not always follow the guidelines stated in the primary objective. Therefore, reintubation will be assessed as a secondary outcome.

  2. The need for reintubation [ Time Frame: Anytime from the first planned extubation until discharge from the neonatal intensive care unit ]
    Infants will be prospectively followed from birth until discharge from the NICU. Therefore, infants who require reintubation at any time point from the first planned extubation until discharge from the neonatal intensive care unit will be documented


Other Outcome Measures:
  1. Total duration of ETT-MV [ Time Frame: Participants will be followed for the duration of hospital stay, an expected average of 10 weeks ]
    Total duration (in days) of endotracheal tube mechanical ventilation from the time of birth until discharge from the hospital

  2. Intraventricular hemorrhage [ Time Frame: Participants will be followed for the duration of hospital stay, an expected average of 10 weeks ]
    Presence of Intraventricular Hemorrhage (IVH) from time of birth until discharge from the hospital. If IVH is present, the grade of the hemorrhage will be specified (as per Volpe's classification)

  3. Patent Ductus Arteriosus [ Time Frame: Participants will be followed for the duration of hospital stay, an expected average of 10 weeks ]
    Presence of a Patent Ductus Arteriosus (PDA) from the time of birth until discharge from hospital. If present, the therapeutic measures taken for closing the PDA (medical or surgical) will also be specified.

  4. Oxygen supplementation at 28 days of life [ Time Frame: This outcome will be assessed when participants have 28 days of life ]
    The need for any oxygen supplementation at 28 days of life

  5. Bronchopulmonary Dysplasia [ Time Frame: This outcome will be assessed when participants are 36 weeks post-conceptual age ]

    The presence of Bronchopulmonary Dysplasia (BPD) will be assessed at 36 weeks Post Conceptual Age (PCA) and classified as mild, moderate or severe.

    • Mild BPD: oxygen supplementation at 28 days of life but none at 36 weeks PCA
    • Moderate BPD: FiO2 requirements of less than 0.3 at 36 weeks PCA
    • Severe BPD: FiO2 requirements over 0.3 or CPAP or mechanical ventilation at 36 weeks PCA

  6. Retinopathy of Prematurity [ Time Frame: This outcome will be assessed at the time of the first eye exam (approximately 31 weeks PCA) until the final eye exam prior to hospital discharge ]
    Participants will be assessed for the presence or absence of Retinopathy of Prematurity (ROP)

  7. Necrotizing Enterocolitis [ Time Frame: Participants will be followed for the duration of hospital stay, an expected average of 10 weeks ]
    Participants will be assessed for the presence or absence of Necrotizing Enterocolitis (NEC) throughout the course of their hospitalization. NEC will be classified according to Bell's modified staging criteria.

  8. Death [ Time Frame: Participants will be followed for the duration of hospital stay in the NICU, an expected average of 10 weeks ]
    Death occuring anytime during the hospitalization course in the NICU.



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Ages Eligible for Study:   Child, Adult, Older Adult
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Extreme preterm infants who are requiring endotracheal tube mechanical ventilation (ETT-MV).
Criteria

Inclusion Criteria:

  • All infants admitted to the NICU with a birth weight ≤ 1250 grams AND
  • Need for endotracheal tube mechanical ventilation

Exclusion Criteria:

  • 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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01909947


Contacts
Contact: Wissam Shalish, MD 1-514-412-4400 ext 22341 wissam.shalish@mail.mcgill.ca
Contact: Guilherme M Sant'Anna, MD 1-514-412-4400 ext 23489 guilherme.santanna@mcgill.ca

Locations
United States, Michigan
Wayne State University Recruiting
Detroit, Michigan, United States, 48201
Contact: Sanjay Chawla, MD    313-745-5638    schawla@dmc.org   
Principal Investigator: Sanjay Chawla, MD         
United States, Rhode Island
Women and Infants Hospital of Rhode Island Recruiting
Providence, Rhode Island, United States, 02905
Contact: Martin Keszler, MD       mkeszler@wihri.org   
Canada, Quebec
Royal Victoria Hospital Recruiting
Montreal, Quebec, Canada, H3A 1A1
Contact: Guilherme M Sant'Anna, MD    1-514-412-4400 ext 23489    guilherme.santanna@mcgill.ca   
Contact: Wissam Shalish, MD    1-514-412-4400 ext 22341    wissam.shalish@mail.mcgill.ca   
Principal Investigator: Guilherme M Sant'Anna, MD         
Principal Investigator: Wissam Shalish, MD         
Sub-Investigator: Philippe Lamer, MN         
Sub-Investigator: Lara Kanbar         
Montreal Children's Hospital Recruiting
Montreal, Quebec, Canada, H3H 1P3
Contact: Guilherme Sant'Anna, MD    1-514-412-4400 ext 23489    guilherme.santanna@mcgill.ca   
Contact: Wissam Shalish, MD    1-514-412-4400 ext 22341    wissam.shalish@mail.mcgill.ca   
Principal Investigator: Wissam Shalish, MD         
Principal Investigator: Guilherme M Sant'Anna, MD         
Sub-Investigator: Philippe Lamer, MN         
Sub-Investigator: Lara Kanbar         
Jewish General Hospital Recruiting
Montreal, Quebec, Canada, H3T 1E2
Contact: Lajos Kovacs, MD       lajos.kovacs@mcgill.ca   
Principal Investigator: Wissam Shalish, MD         
Principal Investigator: Guilherme M Sant'Anna, MD         
Sub-Investigator: Philippe Lamer, MN         
Sub-Investigator: Lara Kanbar         
Sponsors and Collaborators
McGill University Health Center
Canadian Institutes of Health Research (CIHR)
Wayne State University
Brown University
Investigators
Study Chair: Guilherme M Sant'Anna, MD McGill University
Principal Investigator: Guilherme M Sant'Anna, MD McGill University
Principal Investigator: Robert E Kearney, PhD McGill University
Principal Investigator: Wissam Shalish, MD McGill University
Principal Investigator: Karen A Brown, MD McGill University
Principal Investigator: Doina Precup McGill University
Principal Investigator: Sanjay Chawla, MD Wayne State University
Principal Investigator: Martin Keszler, MD Brown University

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
Responsible Party: Guilherme Sant'Anna, MD, Associate Professor of Pediatrics, McGill University Health Center
ClinicalTrials.gov Identifier: NCT01909947     History of Changes
Other Study ID Numbers: APEX 01
288299 ( Other Grant/Funding Number: CIHR )
12-387-PED ( Other Identifier: MUHC )
First Posted: July 29, 2013    Key Record Dates
Last Update Posted: August 22, 2018
Last Verified: August 2018

Keywords provided by Guilherme Sant'Anna, MD, McGill University Health Center:
Respiratory rate variability
Heart rate variability
Extubation readiness
Extubation failure
Clinical predictors