Validation of Childhood Pneumonia Prognostic Models for Use in Emergency Care Settings

Author:

Antoon James W1ORCID,Nian Hui2,Ampofo Krow3,Zhu Yuwei2,Sartori Laura F14,Johnson Jakobi1,Arnold Donald H1,Stassun Justine1,Pavia Andrew T3ORCID,Grijalva Carlos G5,Williams Derek J1

Affiliation:

1. Department of Pediatrics, Vanderbilt University School of Medicine , Nashville, Tennessee , USA

2. Department of Biostatistics, Vanderbilt University School of Medicine , Nashville, Tennessee , USA

3. Department of Pediatrics, University of Utah School of Medicine , Nashville, Tennessee , USA

4. Department of Pediatrics, University of Pennsylvania School of Medicine , Philadelphia, Pennsylvania , USA

5. Departments of Health Policy and Biomedical Informatics, Vanderbilt University Medical Center , Nashville, Tennessee , USA

Abstract

Abstract Background Unwarranted variation in disposition decisions exist among children with pneumonia. We validated three prognostic models for predicting pneumonia severity among children in the emergency department (ED) and hospital. Methods We performed a two-center, prospective study of children 6 months to <18 years presenting to the ED with pneumonia from January 2014 to May 2019. We evaluated three previously developed disease-specific prognostic models which use demographic, clinical, and diagnostic predictor variables, with each model estimating risk for Very Severe (mechanical ventilation or shock), Severe (ICU without very severe features), and Moderate/Mild (Hospitalization without severe features or ED discharge) pneumonia. Predictive accuracy was measured using discrimination (concordance or c-statistic) and re-calibration. Results There were 1088 children included in one or more of the three models. Median age was 3.6 years and the majority of children were male (53.7%) and identified as non-Hispanic White (63.7%). The distribution for the ordinal severity outcome was mild or moderate (79.1%), severe (15.9%), and very severe (4.9%). The three models each demonstrated excellent discrimination (C-statistic range across models [0.786–0.803]) with no appreciable degradation in predictive accuracy from the derivation cohort. Conclusions All three prognostic models accurately identified risk for three clinically meaningful levels of pneumonia severity and demonstrated very good predictive performance. Physiologic variables contributed the most to model prediction. Application of these objective tools may help standardize and improve disposition and other management decisions for children with pneumonia.

Funder

National Institute of Allergy and Infectious Diseases

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,General Medicine,Pediatrics, Perinatology and Child Health

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