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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Pediatric Early Warning Scores Before Rapid Response Poorly Predict Intensive Care Unit Transfers.
Jimin Lee1,2, Jennifer L Ciuchta1,3, Jacqueline Weingarten-Arams1
1Department of Pediatrics, Children's Hospital at Montefiore, Bronx, New York.
The Pediatric Early Warning Score (PEWS) did not effectively predict unplanned PICU transfers or rapid escalation after pediatric rapid response team (RRT) activation. This study suggests PEWS may not be a reliable tool in high-resource settings for identifying at-risk children.
Area of Science:
- Pediatric critical care medicine
- Clinical risk assessment tools
- Patient safety
Background:
- The Pediatric Early Warning Score (PEWS) is used to identify children at risk of deterioration.
- Its effectiveness, especially in high-resource settings, is debated.
- This study evaluated PEWS for predicting unplanned PICU transfers post-RRT activation.
Purpose of the Study:
- To assess the predictive performance of the Pediatric Early Warning Score (PEWS).
- To determine if PEWS can predict unplanned PICU transfers following pediatric rapid response team (RRT) activation.
- To evaluate PEWS's ability to predict rapid escalation of care.
Main Methods:
- Retrospective cohort study of pediatric patients (up to 21 years) with RRT activations.
- Collected demographic, clinical data, RRT reason, and modified Brighton PEWS.
- Analyzed PICU transfer and rapid escalation of care as outcomes; calculated sensitivity, specificity, and AUROC.
Main Results:
- 183 of 297 RRT activations (63%) led to PICU transfer, mostly respiratory.
- PEWS was recorded within 4 hours for 89% of RRT activations.
- PEWS showed low predictive value for PICU transfer or rapid escalation (AUROC 0.495-0.613).
Conclusions:
- PEWS within 4 hours before RRT activation poorly predicted PICU transfer or rapid escalation.
- Current PEWS may lack sensitivity and specificity for this purpose.
- Development of improved predictive tools is necessary.
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