Background: Infants with COVID-19 can often present with fever without source, which is a challenging situation in infants <90 days old. The "step-by-step" algorithm has been proposed to identify children at high risk of bacterial infection. In the context of the COVID-19 pandemic, we aimed to reassess the diagnostic performance of this algorithm.
Methods: We performed a multicentric retrospective study in 3 French pediatric emergency departments between 2018 and 2020. We applied the "step-by-step" algorithm to 4 clinical entities: COVID-19, febrile urinary tract infections (FUTI), invasive bacterial infection (IBI), and enterovirus infections. The main outcome was the proportion of infants classified at high risk (ill-appearing, ≤21 days old, with leukocyturia or procalcitonin level ≥0.5 ng/mL).
Results: Among the 199 infants included, 40 had isolated COVID-19, 25 had IBI, 60 had FUTI, and 74 had enterovirus infection. All but 1 infant with bacterial infection were classified at high risk (96% for IBI and 100% for FUTI) as well as 95% with enterovirus and 82% with COVID-19. Infants with COVID-19 were classified at high risk because an ill-appearance (72%), an age ≤21 days (27%), or leukocyturia (19%). All these infants had procalcitonin values <0.5 ng/mL and only 1 had C-reactive protein level >20 mg/L.
Conclusions: The "step-by-step" algorithm remains effective to identify infants with bacterial infection but misclassifies most infants with COVID-19 as at high risk of bacterial infection leading to unnecessary cares. An updated algorithm based adding viral testing may be needed to discriminate fever related to isolated COVID-19 in infants <90 days old.
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