ArticlePediatrics2022
A Prediction Model for Pediatric Radiographic Pneumonia.
Article in Pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 27 citations in OpenAlex.
- Children Hospitalized With Pneumonia Who Complete Oral Antibiotic Treatment Without Complications.Hospital pediatrics · 2026Article
- Explainable machine learning for the early differentiation of pediatric bronchopneumonia using routine laboratory parameters.PloS one · 2026Article
- Article
- Community-Acquired Pneumonia Diagnosis Following Emergency Department Visits for Respiratory Illness.Clinical pediatrics · 2025Article
- Semiquantitative chest computed tomography scoring system to estimate severity in pediatric community-acquired pneumonia.Frontiers in pediatrics · 2025Article
- Testing and Treatment Thresholds for Pediatric Pneumonia in the Emergency Department.Hospital pediatrics · 2024Article
- Cost of Pediatric Pneumonia Episodes With or Without Chest Radiography.Hospital pediatrics · 2024Article
- Incorporation of biomarkers into a prediction model for paediatric radiographic pneumonia.ERJ open research · 2023Article
- A machine learning approach to the development and prospective evaluation of a pediatric lung sound classification model.Scientific reports · 2023Article
- The development of a novel natural language processing tool to identify pediatric chest radiograph reports with pneumonia.Frontiers in digital health · 2023Article
- Validation of Prediction Models for Pneumonia Among Children in the Emergency Department.Pediatrics · 2022Article
- A predictive model of delayed pseudoaneurysm formation in paediatric patients with isolated blunt splenic injury using logistic regression analysis.Acute medicine & surgeryArticle
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundChest radiographs (CXRs) are frequently used in the diagnosis of community-acquired pneumonia (CAP). We sought to construct a predictive model for radiographic CAP based on clinical features to decrease CXR use.
methodsWe performed a single-center prospective study of patients 3 months to 18 years of age with signs of lower respiratory infection who received a CXR for suspicion of CAP. We used penalized multivariable logistic regression to develop a full model and bootstrapped backward selection models to develop a parsimonious reduced model. We evaluated model performance at different thresholds of predicted risk.
resultsRadiographic CAP was identified in 253 (22.2%) of 1142 patients. In multivariable analysis, increasing age, prolonged fever duration, tachypnea, and focal decreased breath sounds were positively associated with CAP. Rhinorrhea and wheezing were negatively associated with CAP. The bootstrapped reduced model retained 3 variables: age, fever duration, and decreased breath sounds. The area under the receiver operating characteristic for the reduced model was 0.80 (95% confidence interval: 0.77-0.84). Of 229 children with a predicted risk of <4%, 13 (5.7%) had radiographic CAP (sensitivity of 94.9% at a 4% risk threshold). Conversely, of 229 children with a predicted risk of >39%, 140 (61.1%) had CAP (specificity of 90% at a 39% risk threshold).
conclusionsA predictive model including age, fever duration, and decreased breath sounds has excellent discrimination for radiographic CAP. After external validation, this model may facilitate decisions around CXR or antibiotic use in CAP.
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