Febrile infants risk score at triage (FIRST) for the early identification of serious bacterial infections

Abstract We aimed to derive the Febrile Infants Risk Score at Triage (FIRST) to quantify risk for serious bacterial infections (SBIs), defined as bacteremia, meningitis and urinary tract infections. We performed a prospective observational study on febrile infants < 3 months old at a tertiary hospital in Singapore between 2018 and 2021. We utilized machine learning and logistic regression to derive 2 models: FIRST, based on patient demographics, vital signs and history, and FIRST + , adding laboratory results to the same variables. SBIs were diagnosed in 224/1002 (22.4%) infants. Among 994 children with complete data, age (adjusted odds ratio [aOR] 1.01 95%CI 1.01–1.02, p < 0.001), high temperature (aOR 2.22 95%CI 1.69–2.91, p < 0.001), male sex (aOR 2.62 95%CI 1.86–3.70, p < 0.001) and fever of ≥ 2 days (aOR 1.79 95%CI 1.18–2.74, p = 0.007) were independently associated with SBIs. For FIRST + , abnormal urine leukocyte esterase (aOR 16.46 95%CI 10.00–27.11, p < 0.001) and procalcitonin (aOR 1.05 95%CI 1.01–1.09, p = 0.009) were further identified. A FIRST + threshold of ≥ 15% predicted risk had a sensitivity of 81.8% (95%CI 70.5–91.0%) and specificity of 65.6% (95%CI 57.8–72.7%). In the testing dataset, FIRST + had an area under receiver operating characteristic curve of 0.87 (95%CI 0.81–0.94). These scores can potentially guide triage and prioritization of febrile infants