# Derivation and validation of a clinical prediction rule to identify febrile infants 61 to 90 days old at low and non-negligible risk of invasive bacterial infections

> **NIH NIH R03** · YALE UNIVERSITY · 2024 · $92,228

## Abstract

PROJECT SUMMARY
Of the ~200,000 infants S90 days old evaluated for fever annually in U.S. emergency departments (EDs), ~2%
will harbor invasive bacterial infections (I Bis), defined by bacteremia and/or bacterial meningitis. To reduce
unnecessary invasive procedures and hospitalizations, clinicians frequently rely on prediction rules to identify
febrile infants at low risk of I Bis who may be safely discharged from the ED without lumbar punctures (LPs) or
empirical antibiotics. Newer clinical prediction rules such as the Step-by-Step approach, Pediatric Emergency
Care Applied Research Network (PECARN) prediction rule, and IBI score have high sensitivity for IBI in febrile
infants and potentially obviate the need for LPs. However, these rules have been derived, validated, and/or
studied exclusively in febrile infants S60 days old or in cohorts with few infants 61 to 90 days old with IBI. The
recently published American Academy of Pediatrics clinical practice guideline for the evaluation and
management of febrile infants only addresses infants 8 to 60 days old due to the lack of evidence regarding
febrile infants 61 to 90 days old. Consequently, there is wide variation in the management of these infants. In
addition, although bacterial meningitis is rare in this age group, ~18% of febrile infants 61 to 90 days old
undergo LPs, and 16% are hospitalized; at some hospitals, the proportion approaches two-thirds.
Nevertheless, I Bis occur in approximately 1 % to 1.5% of febrile infants 61 to 90 days old, which underscores
the need for risk stratifying these infants to identify those with non-negligible risk of IBI who require LPs and
hospitalization. The long-term goal of this research is to improve the management of febrile infants 61 to 90
days old by providing clinicians with an evidence-based risk stratification tool. The objective of this proposal is
to derive and internally validate such a clinical prediction rule using objective demographic, clinical, and
laboratory data to identify infants at low versus non-negligible risk of IBI. To accomplish this objective, we will
use the PECARN Registry, which includes data from >5.5 million visits from 12 EDs in 9 health systems,
including nearly 14,000 visits for febrile infants 61 to 90 days old. Recursive partitioning analysis will be used to
derive the clinical prediction rule with 10-fold cross internal validation.
Collectively, the investigative team is well-positioned to conduct this research with expertise in febrile infants,
clinical prediction modeling, and natural language processing. The principal investigator, Paul L. Aronson, MD,
MHS, has studied febrile infants for a decade, including the derivation and internal validation of a prediction
rule for febrile infants S60 days old. After the derivation and internal validation of a highly sensitive and specific
prediction rule for febrile infants 61 to 90 days old at risk for IBI, the rule will be externally validated in a
multicenter prospective ...

## Key facts

- **NIH application ID:** 10833593
- **Project number:** 5R03HD110741-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** PAUL L ARONSON
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $92,228
- **Award type:** 5
- **Project period:** 2023-05-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10833593

## Citation

> US National Institutes of Health, RePORTER application 10833593, Derivation and validation of a clinical prediction rule to identify febrile infants 61 to 90 days old at low and non-negligible risk of invasive bacterial infections (5R03HD110741-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10833593. Licensed CC0.

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