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Pediatrics. 2016 Oct;138(4). pii: e20161019.

Predicting Severe Pneumonia Outcomes in Children.

Author information

1
Departments of Pediatrics, derek.williams@vanderbilt.edu.
2
Biostatistics.
3
Health Policy, and.
4
Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
5
Centers for Disease Control and Prevention, Atlanta, Georgia.
6
Department of Pediatrics, University of Utah Health Sciences Center, Salt Lake City, Utah.
7
Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee.
8
Departments of Pediatrics and Medicine, Emory University School of Medicine, Atlanta, Georgia; and.
9
Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
10
Departments of Pediatrics.

Abstract

BACKGROUND:

Substantial morbidity and excessive care variation are seen with pediatric pneumonia. Accurate risk-stratification tools to guide clinical decision-making are needed.

METHODS:

We developed risk models to predict severe pneumonia outcomes in children (<18 years) by using data from the Etiology of Pneumonia in the Community Study, a prospective study of community-acquired pneumonia hospitalizations conducted in 3 US cities from January 2010 to June 2012. In-hospital outcomes were organized into an ordinal severity scale encompassing severe (mechanical ventilation, shock, or death), moderate (intensive care admission only), and mild (non-intensive care hospitalization) outcomes. Twenty predictors, including patient, laboratory, and radiographic characteristics at presentation, were evaluated in 3 models: a full model included all 20 predictors, a reduced model included 10 predictors based on expert consensus, and an electronic health record (EHR) model included 9 predictors typically available as structured data within comprehensive EHRs. Ordinal regression was used for model development. Predictive accuracy was estimated by using discrimination (concordance index).

RESULTS:

Among the 2319 included children, 21% had a moderate or severe outcome (14% moderate, 7% severe). Each of the models accurately identified risk for moderate or severe pneumonia (concordance index across models 0.78-0.81). Age, vital signs, chest indrawing, and radiologic infiltrate pattern were the strongest predictors of severity. The reduced and EHR models retained most of the strongest predictors and performed as well as the full model.

CONCLUSIONS:

We created 3 risk models that accurately estimate risk for severe pneumonia in children. Their use holds the potential to improve care and outcomes.

PMID:
27688362
PMCID:
PMC5051209
DOI:
10.1542/peds.2016-1019
[Indexed for MEDLINE]
Free PMC Article

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