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This study is a Phase 3, multi-center, Bayesian Adaptive Sequential Platform Trial testing the effectiveness of different prehospital airway management strategies in the care of critically ill children. Emergency Medical Services (EMS) agencies affiliated with the Pediatric Emergency Care Applied Research Network (PECARN) will participate in the trial. The study interventions are strategies of prehospital airway management: [BVM-only], [BVM followed by SGA] and [BVM followed by ETI]. The primary outcome is 30-day ICU-free survival. The trial will be organized and executed in two successive stages. In Stage I of the trial, EMS personnel will alternate between two strategies: [BVM-only] or [BVM followed by SGA]. The [winner of Stage I] will advance to Stage II based upon results of Bayesian interim analyses. In Stage II of the trial, EMS personnel will alternate between [BVM followed by ETI] vs. [Winner of Stage I].
Full description
Cardiac arrest, respiratory failure, and major trauma are devastating critical conditions in children. Resuscitation from critical illness requires skillful airway management to optimize the delivery of oxygen to the lungs, preventing irreparable damage to the brain and heart. As the first to provide resuscitation care for critically ill children, prehospital EMS personnel are often the first to perform life-saving airway management.
The most common prehospital airway management techniques (bag-valve-mask ventilation [BVM], endotracheal intubation [ETI], and supraglottic airway insertion [SGA]) have important trade-offs between risks and benefits. Despite the challenges of ETI and national recommendations favoring BVM, many EMS personnel favor ETI over BVM. Newer SGA devices such as the laryngeal tube (LT), laryngeal mask airway (LMA), and i-gel® have not been compared with other techniques in children. National organizations, including the Agency for Healthcare Research and Quality, have declared the need for new, rigorous trials of all techniques to determine the best strategies for prehospital airway management in children. Interviews with front-line EMS personnel underscore the dire need for clear and strategic guidelines for managing the pediatric airway.
The Pediatric Prehospital Airway Resuscitation Trial (Pedi-PART) will determine the best strategies for prehospital airway management in critically ill children. The trial aims are Aim I-Primary Objective (Effectiveness)-Stage I: Determine if [BVM-only] or [BVM followed by SGA] results in better ICU-free survival in critically ill children with cardiac arrest, major trauma, or respiratory failure. Stage II: Determine if [winner of Stage I] or [BVM followed by ETI] results in better ICU-free survival. Bayesian analyses will determine the transition from Stage I to Stage II, ensuring optimal deployment of available subjects to address the postulated questions. Aim 2- Secondary Objective (Safety)-Stage I: Determine if [BVM followed by SGA] results in fewer prehospital and hospital safety events compared with [BVM-only] in critically ill children with cardiac arrest, major trauma, or respiratory failure. Stage II: Determine if the winner of Stage I results in fewer safety events compared with [BVM followed by ETI].
The trial will use a Bayesian Adaptive Sequential Comparison Platform Trial (BASiC-PT) design and will be executed in two sequential stages. Stage I: Determine if [BVM-only] or [BVM followed by SGA] results in better ICU-free survival in critically ill children with cardiac arrest, major trauma, or respiratory failure. Stage II: Determine if [winner of Stage I] or [BVM followed by ETI] results in better ICU-free survival. Bayesian analyses will determine the transition from Stage I to Stage II, ensuring optimal deployment of available subjects to address the postulated questions.
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Inclusion criteria are:
Exclusion criteria are:
EMS personnel will use bystander reports or follow local protocols to establish patient age and pregnancy status.
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3,000 participants in 3 patient groups
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Central trial contact
Henry E Wang, MD, MS; Jennifer Frey, PhD
Data sourced from clinicaltrials.gov
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