Validity of different pediatric early warning scores in the emergency department

Nienke Seiger1, Ian Maconochie, Rianne Oostenbrink

  • 1Department of Pediatrics, Room Sp 1540, Erasmus MC-Sophia Children's Hospital, University Medical Centre Rotterdam, PO Box 2060, 3000 CB Rotterdam, Netherlands. h.a.moll@erasmusmc.nl.

Pediatrics
|September 11, 2013
PubMed

Insights

Pediatric early warning scores (PEWS) can identify children needing intensive care unit (ICU) admission. Numeric scoring systems outperformed triggering systems in predicting critical illness in the emergency department (ED).

Area of Science:

  • Pediatric Emergency Medicine
  • Clinical Decision Support Tools
  • Healthcare Informatics

Background:

  • Pediatric early warning scores (PEWS) are increasingly recommended for emergency department (ED) use.
  • The effectiveness of various PEWS in pediatric ED settings requires thorough validation.

Purpose of the Study:

  • To compare the diagnostic accuracy of ten different pediatric early warning scores (PEWS).
  • To evaluate PEWS' validity in predicting intensive care unit (ICU) admission and hospitalization in a pediatric ED.

Main Methods:

  • Prospective cohort study of 17,943 children (<16 years) in a Dutch university hospital ED (2009-2012).
  • Ten distinct PEWS were assessed for their ability to predict ICU admission or hospitalization.
  • Validity was quantified using the area under the receiver operating characteristic (ROC) curves.

Main Results:

  • Areas under the ROC curves for ICU admission prediction ranged from 0.60 to 0.82 (moderate to good).
  • Areas under the ROC curves for hospitalization prediction ranged from 0.56 to 0.68 (poor to moderate).
  • No PEWS demonstrated consistently high sensitivity and specificity for predicting either ICU admission or hospitalization.

Conclusions:

  • PEWS are valuable for identifying pediatric patients requiring ICU admission in the ED.
  • Scoring systems that sum parameters to a numeric value are more effective than simple triggering systems.
  • Further refinement of PEWS may be needed to improve prediction accuracy for hospitalization.
Abstract

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