title: Pediatric Triage in a Severe Pandemic: Maximizing Survival by Establishing Triage Thresholds.
abstract: OBJECTIVE
  To develop and validate an algorithm to guide selection of patients for pediatric critical care admission during a severe pandemic when Crisis Standards of Care are implemented.
  
  
  METHODS
  Retrospective observational study using secondary data.
  
  
  METHODS
  Children admitted to VPS-participating PICUs between 2009-2012.
  
  
  METHODS
  A total of 111,174 randomly selected nonelective cases from the Virtual PICU Systems database were used to estimate each patient's probability of death and duration of ventilation employing previously derived predictive equations. Using real and projected statistics for the State of Ohio as an example, triage thresholds were established for casualty volumes ranging from 5,000 to 10,000 for a modeled pandemic with peak duration of 6 weeks and 280 pediatric intensive care beds. The goal was to simultaneously maximize casualty survival and bed occupancy. Discrete Event Simulation was used to determine triage thresholds for probability of death and duration of ventilation as a function of casualty volume and the total number of available beds. Simulation was employed to compare survival between the proposed triage algorithm and a first come first served distribution of scarce resources.
  
  
  RESULTS
  Population survival was greater using the triage thresholds compared with a first come first served strategy. In this model, for five, six, seven, eight, and 10 thousand casualties, the triage algorithm increased the number of lives saved by 284, 386, 547, 746, and 1,089, respectively, compared with first come first served (all p < 0.001).
  
  
  CONCLUSIONS
  Use of triage thresholds based on probability of death and duration of mechanical ventilation determined from actual critically ill children's data demonstrated superior population survival during a simulated overwhelming pandemic.
authors.affiliation: 1Virtual PICU Systems, LLC, Los Angeles, CA.2Department of Pediatrics and Anesthesiology, Children's Hospital Los Angeles, USC Keck School of Medicine, Los Angeles, CA.3API Healthcare, A GE Healthcare Company, Hartford, WI.4Department of Pediatrics, Virginia Tech Carilion School of Medicine, Roanoke, VA.5National Center for Disaster Preparedness, Columbia University, New York, NY.6Case Western University School of Medicine, Cleveland, OH.7Rainbow Babies and Children's Hospital, Cleveland, OH.
authors.forename: Christine
authors.initials: C
authors.lastname: Gall
authors.forename: Randall
authors.initials: R
authors.lastname: Wetzel
authors.forename: Alexander
authors.initials: A
authors.lastname: Kolker
authors.forename: Robert K
authors.initials: RK
authors.lastname: Kanter
authors.forename: Philip
authors.initials: P
authors.lastname: Toltzis
mesh_terms: D000465:Algorithms; D001509:Bed Occupancy; D002648:Child; D003198:Computer Simulation; D017052:Hospital Mortality; D006801:Humans; D015278:Intensive Care Units, Pediatric; D058873:Pandemics; D018579:Patient Selection; D012189:Retrospective Studies; D015996:Survival Rate; D014218:Triage / Q000379:methods*