Narrative review of clinical prediction models for paediatric community acquired pneumonia
Chris A Rees1, Stuart Haggie2, Todd A Florin3
1Division of Pediatric Emergency Medicine, Emory University School of Medicine, Atlanta, GA, United States of America; Department of Emergency Medicine, Children's Healthcare of Atlanta, Atlanta, GA, United States of America.
Insights
Clinical prediction models for pediatric community-acquired pneumonia (CAP) are crucial for identifying at-risk children. While models exist for LMICs and HICs, further validation and implementation are needed, especially in LMICs.
Area of Science:
- Pediatrics
- Infectious Diseases
- Epidemiology
Background:
- Community-acquired pneumonia (CAP) significantly impacts global child health, with varying morbidity and mortality rates between low- and middle-income countries (LMICs) and high-income countries (HICs).
- The disparity in CAP outcomes necessitates the development of setting-specific clinical prediction models to identify children at high risk.
Purpose of the Study:
- To review and outline published clinical prediction models for pediatric CAP-related outcomes in both LMICs and HICs.
- To assess the current landscape of predictive modeling for pediatric CAP and identify gaps in research and implementation.
Main Methods:
- Systematic review of published clinical prediction models for pediatric CAP.
- Categorization of models based on predicted outcomes (treatment failure, poor outcomes, mortality, disease severity, need for major medical interventions) and geographical setting (LMICs vs. HICs).
Main Results:
- In LMICs, four models predict treatment failure, two predict poor outcomes, and eight predict mortality for pediatric CAP. No LMIC models have documented clinical implementation impact.
- In HICs, three models assess disease severity and one predicts the need for major medical interventions for pediatric CAP.
Conclusions:
- Existing clinical prediction models offer a foundation for risk stratification in high-income countries, but require broader external validation and implementation.
- There is a critical need for the development, validation, and implementation of effective clinical prediction models for pediatric CAP, particularly in LMICs, to improve patient outcomes.
Abstract:
Community acquired pneumonia (CAP) is a disease experienced by children the world over, though CAP-related morbidity and mortality differ markedly between low- and middle-income countries (LMICs) and high-income countries (HICs). Thus, setting-specific clinical prediction models are needed to identify children at risk for CAP-related morbidity and mortality. Here, we outline published clinical prediction models from LMICs and HICs for pediatric CAP-related outcomes. To date, there have been four clinical prediction models to predict treatment failure, two to predict a composite outcome of poor outcomes, and eight models for mortality prediction for CAP in LMICs. No prediction models developed in LMICs had publications that described their impact on clinical care through implementation. In HICs, to date there are three published clinical prediction models evaluating disease severity and one examining the need for major medical interventions. While clinical prediction models described in this review provide a strong foundation for risk stratification for children with CAP in HICs, there is a need for widespread external validation and implementation of optimally performing models.
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