Thursday, November 21, 2024
11/21/2024
PROJECT SUMMARY Although community-acquired pneumonia (CAP) is one of the most common serious infections in children and a leading reason that children seek emergency care, no validated tools exist to predict CAP severity in children. Without objective tools, management decisions are inefficient and potentially inaccurate, resulting in unnecessary testing, treatment, and hospitalization in low-risk children or delays in critically important therapies in those at high risk of severe CAP. The long-term goal of this research is to improve risk stratification of children with CAP. In adults with CAP, the use of risk prediction rules decreases mortality and guides antibiotic decisions, while minimizing hospitalizations for those at low risk. No validated risk prediction rules exist for children presenting to the emergency department (ED) with CAP. We previously derived a 7-variable risk prediction rule in 1128 children 3 months to 18 years old who presented to a single pediatric ED with suspected CAP. To overcome limitations inherent in a rule derived in a single center, multicenter derivation and external validation of a pediatric CAP risk prediction rule is necessary to ensure generalizability and inform subsequent widespread implementation. We also found that biomarkers, including c-reactive protein, procalcitonin, proadrenomedullin, and viral detection, are associated with severe outcomes in children with CAP. It is unknown if the addition of these biomarkers to a clinical risk prediction rule will improve rule performance. Led by a multidisciplinary team of experts in CAP, pediatric emergency and hospital medicine, infectious diseases, biomarkers, epidemiology and biostatistics, prediction modeling, and machine learning, the proposed research will address these important knowledge and research gaps through the following specific aims: (1) To derive a severity risk prediction rule in a multicenter cohort of children presenting to the ED with CAP; (2) To externally validate the derived prediction rule in children with CAP; and (3) To evaluate the ability of biomarkers to improve predictive accuracy of a purely clinical risk prediction rule. This study will leverage the robust infrastructure, experience, and expertise of the Pediatric Emergency Care Applied Research Network (PECARN). We will accomplish the study aims by conducting a prospective multicenter observational study in two phases. First, we will enroll 2000 children with CAP presenting to one of 7 PECARN EDs to derive the rule over 2 years. We will then enroll 2000 children with CAP in 7 different PECARN EDs over the following 2 years to externally validate the rule. A risk prediction rule in children with CAP will be significant in (a) advancing our understanding of risk factors of CAP severity, (b) improving evidence-based management and clinical outcomes by guiding and standardizing clinical decision making, and (c) facilitating future research. This proposal is innovative as it will shift the paradigm of ED management of CAP, moving from subjective decisions toward a novel, objective approach where individualized, evidence-based risk estimates can augment and improve accuracy of clinical decision making.
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