ArticleJournal of the Pediatric Infectious Diseases Society2023
Validation of Childhood Pneumonia Prognostic Models for Use in Emergency Care Settings.
Article in Journal of the Pediatric Infectious Diseases Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Prognostic clinical decision support for pneumonia in the emergency department: A randomized trial.Journal of hospital medicine · 2024Trial
- User-Centered Design and Implementation of an Interoperable FHIR Application for Pediatric Pneumonia Prognostication in a Randomized Trial.Applied clinical informatics · 2024Trial
- Narrative review of clinical prediction models for paediatric community acquired pneumonia.Paediatric respiratory reviews · 2025Review
- Guideline-Concordant Antibiotic Use in Children With Community-Acquired Pneumonia.Hospital pediatrics · 2025Article
- External Validation of Brief Resolved Unexplained Events Prediction Rules for Serious Underlying Diagnosis.JAMA pediatrics · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundUnwarranted 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.
methodsWe 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.
resultsThere 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.
conclusionsAll 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.
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