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| ID | Type | Description | Link |
|---|---|---|---|
| 288299 | Other Grant/Funding Number | CIHR | |
| 12-387-PED | Other Identifier | MUHC |
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| Name | Class |
|---|---|
| Canadian Institutes of Health Research (CIHR) | OTHER_GOV |
| Wayne State University | OTHER |
| Brown University | OTHER |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intubated extreme preterm infants | Infants with a birth weight ≤ 1250 grams and requiring endotracheal tube and mechanical ventilation |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Cardiorespiratory signal acquisition | Other | 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:
|
| Measure | Description | Time Frame |
|---|---|---|
| Extubation Failure | Infants will be considered to have failed extubation if they meet one or more of the following criteria within 72 hours of extubation:
| Within 72 hours of extubation |
| Measure | Description | Time Frame |
|---|---|---|
| The need for reintubation within 72h of the first planned 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. | Within 72 hours of extubation |
| Measure | Description | Time Frame |
|---|---|---|
| Total duration of ETT-MV | Total duration (in days) of endotracheal tube mechanical ventilation from the time of birth until discharge from the hospital | Participants will be followed for the duration of hospital stay, an expected average of 10 weeks |
| Intraventricular hemorrhage |
Inclusion Criteria:
Exclusion Criteria:
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Extreme preterm infants who are requiring endotracheal tube mechanical ventilation (ETT-MV).
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| Name | Affiliation | Role |
|---|---|---|
| Guilherme M Sant'Anna, MD | McGill University | Study Chair |
| 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 | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Wayne State University | Detroit | Michigan | 48201 | United States | ||
| Women and Infants Hospital of Rhode Island |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37193586 | Derived | Alarcon-Martinez T, Latremouille S, Kovacs L, Kearney RE, Sant'Anna GM, Shalish W. Clinical usefulness of reintubation criteria in extremely preterm infants: a cohort study. Arch Dis Child Fetal Neonatal Ed. 2023 Nov;108(6):643-648. doi: 10.1136/archdischild-2022-325245. Epub 2023 May 16. | |
| 28716018 | Derived |
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| The need for reintubation |
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 |
| Anytime from the first planned extubation until discharge from the neonatal intensive care unit |
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) |
| Participants will be followed for the duration of hospital stay, an expected average of 10 weeks |
| Patent Ductus Arteriosus | 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. | Participants will be followed for the duration of hospital stay, an expected average of 10 weeks |
| Oxygen supplementation at 28 days of life | The need for any oxygen supplementation at 28 days of life | This outcome will be assessed when participants have 28 days of life |
| Bronchopulmonary Dysplasia | The presence of Bronchopulmonary Dysplasia (BPD) will be assessed at 36 weeks Post Conceptual Age (PCA) and classified as mild, moderate or severe.
| This outcome will be assessed when participants are 36 weeks post-conceptual age |
| Retinopathy of Prematurity | Participants will be assessed for the presence or absence of Retinopathy of Prematurity (ROP) | 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 |
| Necrotizing Enterocolitis | 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. | Participants will be followed for the duration of hospital stay, an expected average of 10 weeks |
| Death | Death occuring anytime during the hospitalization course in the NICU. | Participants will be followed for the duration of hospital stay in the NICU, an expected average of 10 weeks |
| Providence |
| Rhode Island |
| 02905 |
| United States |
| Royal Victoria Hospital | Montreal | Quebec | H3A 1A1 | Canada |
| Montreal Children's Hospital | Montreal | Quebec | H3H 1P3 | Canada |
| Jewish General Hospital | Montreal | Quebec | H3T 1E2 | Canada |
| Shalish W, Kanbar LJ, Rao S, Robles-Rubio CA, Kovacs L, Chawla S, Keszler M, Precup D, Brown K, Kearney RE, Sant'Anna GM. Prediction of Extubation readiness in extremely preterm infants by the automated analysis of cardiorespiratory behavior: study protocol. BMC Pediatr. 2017 Jul 17;17(1):167. doi: 10.1186/s12887-017-0911-z. |