Predicting cardiac arrests in pediatric intensive care units.

ABSTRACT:

Background

Early identification of children at risk for cardiac arrest would allow for skill training associated with improved outcomes and provides a prevention opportunity.

Objective

Develop and assess a predictive model for cardiopulmonary arrest using data available in the first 4 h.

Methods

Data from PICU patients from 8 institutions included descriptive, severity of illness, cardiac arrest, and outcomes.

Results

Of the 10074 patients, 120 satisfying inclusion criteria sustained a cardiac arrest and 67 (55.9%) died. In univariate analysis, patients with cardiac arrest prior to admission were over 6 times and those with cardiac arrests during the first 4 h were over 50 times more likely to have a subsequent arrest. The multivariate logistic regression model

SUBMITTER: Pollack MM 

PROVIDER: S-EPMC6258339 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature