Measurement of pediatric illness severity using simple pretransport variables

Area of Science:

• Pediatric critical care medicine
• Transport medicine
• Health services research

Background:

• Interfacility transport of critically ill children is complex.
• Predicting in-hospital mortality is crucial for resource allocation and care planning.
• Understanding factors influencing transport outcomes is essential for improving patient safety.

Purpose of the Study:

• To identify pretransport variables that predict in-hospital mortality in pediatric interfacility transport.
• To assess the correlation between predicted mortality risk and the occurrence of major interventions and unplanned events during transport.

Main Methods:

• A cohort of 2,253 children transported by a specialized pediatric team was analyzed.
• Logistic regression was used to identify predictive variables from pretransport data.
• A validated model calculated the probability of in-hospital mortality.
• Interventions and unplanned events were categorized across five mortality risk groups.

Main Results:

• Systolic blood pressure, respiratory rate, oxygen requirement, and altered mental status were significant predictors of in-hospital mortality.
• The model accurately predicted mortality in a validation cohort.
• Higher predicted mortality risk was associated with increased rates of major interventions and unplanned events.

Conclusions:

• Four pretransport variables effectively predict in-hospital mortality in pediatric interfacility transport.
• The risk stratification model correlates with the intensity of interventions and the frequency of adverse events.
• This model can aid in severity-adjusted comparisons of pediatric transport systems.