Predictive tools aim to improve pediatric pneumonia outcomes

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).

Risk Model Predicts Children's Pneumonia Severity

A risk stratification tool can help determine which children with community-acquired pneumonia (CAP) are most likely to develop severe disease or need in-hospital care. The prediction tool appeared to perform better than clinical judgement alone and could help direct resources to those children at greatest risk of poor outcomes. The findings appear in The Lancet Child and Adolescent Health. “Emergency departments around the world see thousands o…

New Predictive Models Assess Pneumonia Severity in Children to Improve

A groundbreaking international study has produced pragmatic, data-driven models capable of accurately differentiating between mild, moderate, and severe pneumonia in pediatric patients. This research, conducted across 73 Emergency Departments in 14 countries as part of the Pediatric Emergency Research Network (PERN), represents a significant advancement in pediatric respiratory care. The newly developed predictive tools are designed to support c…

Models Predict Severity of Pneumonia in Kids to Help Guide Treatment

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).