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Derivation and validation of the Pediatric Community-Acquired Pneumonia Severity (PedCAPS) score: A prospective
Todd A Florin1, Ron Reeder2, Lilliam Ambroggio3
1Department of Pediatrics, Division of Pediatric Emergency Medicine, Northwestern University Feinberg School of Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, USA.
Insights
This study develops and validates a new prediction rule to assess the severity of community-acquired pneumonia (CAP) in children presenting to emergency departments. The rule aims to improve diagnosis and management of pediatric CAP using objective data and biomarkers.
Area of Science:
- Pediatric Emergency Medicine
- Infectious Diseases
- Clinical Epidemiology
Background:
- Community-acquired pneumonia (CAP) is a significant cause of pediatric emergency department visits and hospitalizations.
- Existing prognostic tools for pediatric CAP have limitations, including small sample sizes, retrospective designs, and lack of generalizability.
- There is a need for robust, validated tools to predict CAP severity in children within emergency settings.
Purpose of the Study:
- To derive and externally validate a prediction rule for pediatric CAP severity.
- To identify key clinical variables and biomarkers for predicting CAP severity in children.
- To improve the accuracy and generalizability of CAP severity assessment in pediatric emergency departments.
Main Methods:
- A large, multicenter prospective cohort study of children aged 3 months to 18 years with CAP presenting to emergency departments.
- Exclusion criteria include recent hospitalizations and chronic conditions.
- Data collection includes follow-up surveys, record reviews, and biological specimens (blood, nasal) for biomarker analysis (C-reactive protein, procalcitonin, proadrenomedullin, viral detection).
- Model derivation in ~4000 children and external validation in at least 2000 children using penalized regression, recursive partitioning, and machine learning.
Main Results:
- The study will derive and externally validate a prediction rule for pediatric CAP severity.
- The role of specific biomarkers in predicting CAP outcomes in children will be elucidated.
- A validated tool for implementation in clinical practice will be developed.
Conclusions:
- A validated prediction rule for pediatric CAP severity will be available for clinical implementation.
- The study will enhance understanding of biomarker utility in pediatric CAP management.
- This research aims to improve the care and outcomes for children with CAP.
Introduction:
Community-acquired pneumonia (CAP) is a frequent and costly cause of pediatric emergency department (ED) visits and hospitalizations. Previous prognostic tools for CAP are limited by small samples, single-center or retrospective designs, lack of generalizability to ED settings, lack of biomarkers, or limited objective data. To overcome these limitations, we will derive and externally validate a prediction rule for pediatric CAP severity in a large, multicenter prospective cohort.
Methods:
This is a prospective cohort study of children 3 months to 18 years old with CAP who present to EDs within the Pediatric Emergency Care Applied Research Network. Enrollment began 8/2023 and will end 7/2027. We exclude children with recent hospitalizations and chronic conditions (e.g., immunosuppression). A follow-up survey and record review is completed 8-15 days after the visit. Blood and nasal specimens are obtained to evaluate the role of C-reactive protein, procalcitonin, proadrenomedullin, and viral detection in severity prediction. The primary outcome is severity (three-tiered outcome of mild, moderate, or severe CAP) within 7 days of ED presentation. Model derivation will occur in ~4000 children from 7 EDs over 2 years. External validation will occur in a distinct cohort of at least 2000 children from 7 different EDs. Penalized regression, recursive partitioning, and machine learning will be used in model development.
Discussion:
At study completion, we will have a validated CAP severity prediction rule well-positioned for implementation and further evaluation. We will also understand the role of specific biomarkers in predicting outcomes in children with CAP.
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