Predictive tools aim to improve pediatric pneumonia outcomes

Researchers derived pragmatic models that accurately distinguish mild, moderate and severe pneumonia in children, based on evidence from a study performed in 73 Emergency Departments (EDs) in 14 countries through the international Pediatric Emergency Research Network (PERN). The new predictive tools are intended to complement clinician judgement in deciding whether a child's pneumonia warrants hospitalization or intensive care. The study was published in Lancet Child and Adolescent Health.

Community-acquired pneumonia is one of the most common infections in children worldwide and represents one of the most frequent and costliest reasons children are hospitalized in the United States. Although most children with pneumonia fully recover after a mild illness, around 5 percent become severely sick and develop serious complications.

"While only a small percentage of children with pneumonia will have severe outcomes, it's crucial to identify these patients early so clinicians can act swiftly and aggressively to prevent further deterioration in these children," said lead author Todd Florin, MD, MSCE, Associate Division Head for Academic Affairs & Research for the Division of Pediatric Emergency Medicine at Ann & Robert H. Lurie Children's Hospital of Chicago and Associate Professor of Pediatrics at Northwestern University Feinberg School of Medicine. "It is also important to know if the illness will likely be mild, in order to avoid potentially unnecessary tests or treatments or unnecessary hospital stays."

The study included more than 2,200 children, ages 3 months up to 14 years old, who presented to the ED with community-acquired pneumonia.

Dr. Florin and colleagues found that children with pneumonia who had a runny nose and congestion were more likely to have a mild illness. They also identified clinical features associated with the development of moderate or severe pneumonia for which hospitalization should be considered – abdominal pain, refusal to drink, on antibiotics for the current illness before the ED visit, chest retractions (indicating that the child is struggling to breathe), respiratory rate or heart rate above the 95th percentile for age and hypoxemia (low level of oxygen in the blood). These features are typically evaluated in patients with respiratory illness, which should make the model generalizable and easy to implement.

Emergency departments around the world see thousands of children with pneumonia every day, but until now, we haven't had a reliable way to predict who's truly at risk of getting sicker. This model gives clinicians a practical tool, rooted in data, to guide that decision and ultimately improve care and outcomes."

Nathan Kuppermann, MD, MPH, co-PI, senior author, Executive Vice President, Chief Academic Officer and Director of the Children's National Research Institute in Washington, D.C

The study also included models predicting pneumonia severity specifically in children with pneumonia present on chest radiograph. In addition to the features noted above, researchers found that risk of more severe illness increased if multiple regions of the lung were affected.

"Our pediatric pneumonia predictive models show good-to-excellent accuracy," said Dr. Florin. "They appear to perform better than clinician judgment alone in predicting illness severity, according to previous research from Lurie Children's. Once externally validated, our models will provide evidence-based information for clinicians to consider when evaluating pneumonia in children."