21-Trends in Vital Signs Predict Critical Deterioration in Pediatric Intensive Care Unit Transfers
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Pediatrics, Quality and Patient Safety, 2021
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The Society of Critical Care Medicine's Critical Care Congress features internationally renowned faculty and content sessions highlighting the most up-to-date, evidence-based developments in critical care medicine. This is a presentation from the 2021 Critical Care Congress held virtually from January 31-February 12, 2021.


Anoop Mayampurath


Introduction/Hypothesis: Critical deterioration events, defined as transfer of a pediatric patient from the ward to the intensive care unit (ICU) followed by mechanical ventilation or vasopressor infusion within 12 hours, is associated with increased risk of in-hospital death. While scores exist to assess the risk of deterioration in a patient, there is currently no model that predicts the likelihood of a patient experiencing critical deterioration. Here, we utilize ward-level vital sign data recorded prior to ICU transfer to predict the risk of experiencing critical deterioration.

Methods: We conducted a retrospective study of all pediatric patients transferred from ward to ICU from 2009-2018 at the University of Chicago Comer Children's Hospital. The primary outcome was critical deterioration, defined as mechanical ventilation, vasopressor infusion, or mortality within 12 hours of ward to ICU transfer. Predictors include patient characteristics, last observed vital signs before ICU transfer as well as their prior 24-hours trends. We constructed a logistic regression (LR) and a random forest (RF) model to determine if vital signs and their prior 24-hour trends can predict risk of critical deterioration within 12 hours of ICU transfer. We used the area under the curve (AUC) metric to compare model performances.

Results: Our cohort had 1281 pediatric patients, among which 85 (6%) experienced a critical event after ICU transfer. Our RF model utilizing last observed vital signs and 24-hour trends predicted risk of experiencing a critical deterioration event better than (a) the LR model using only vital signs (AUC 0.72 vs. 0.61, P < 0.05), (b) the modified Bedside PEWS model utilizing physiological variables (AUC 0.72 vs. 0.64 P < 0.05), and (c) the LR model using vital signs and 24-hour trends (AUC 0.72 vs. 0.68, P < 0.05). Temperature change, mean temperature, and minimum diastolic blood pressure were important to predicting critical deterioration events.

Conclusions: We developed a random forest model that utilized trends in vital signs to determine the likelihood of a pediatric patient experiencing a critical deterioration event upon transfer to the ICU. Our model fulfills an important need in determining risk of developing critical deterioration patients who are transferred from ward to ICU.


Meta Tag
Content Type Presentation
Knowledge Area Pediatrics
Knowledge Area Quality and Patient Safety
Knowledge Level Intermediate
Knowledge Level Advanced
Membership Level Select
Tag Scoring Systems
Tag Mortality
Year 2021
vital signs
critical deterioration
pediatric patients
ICU transfer
random forest model


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