2022
DOI: 10.1097/pq9.0000000000000616
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Boston Febrile Infant Algorithm 2.0: Improving Care of the Febrile Infant 1–2 Months of Age

Abstract: Introduction: Significant variation exists in the management of febrile infants, particularly those between 1 and 2 months of age. An established algorithm for well-appearing febrile infants 1–2 months of age guided clinical care for three decades in our emergency department. With mounting evidence for procalcitonin (PCT) to detect invasive bacterial infection (IBI), we revised our algorithm intending to decrease lumbar punctures (LPs) and antibiotic administration without increasing hospitalizations, revisits… Show more

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Cited by 2 publications
(4 citation statements)
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“…Moreover, the published regression models that provide a post‐test probability of infection do not fit with the usual clinician process of treatment decisions 14,15 and seem to have little impact on ATB prescription rate and discharge from PEDs 20,21 . Dorney et al conducted an impact study of a the revised CPR proposed previously by Bachur et al 13 and showed reduction in lumbar punctures and antibiotic prescription but only for very young children from 1 to 2 months of age 19 . Thus, the appropriate care of children with fever without source is still an area of clinical debate.…”
Section: Introductionmentioning
confidence: 99%
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“…Moreover, the published regression models that provide a post‐test probability of infection do not fit with the usual clinician process of treatment decisions 14,15 and seem to have little impact on ATB prescription rate and discharge from PEDs 20,21 . Dorney et al conducted an impact study of a the revised CPR proposed previously by Bachur et al 13 and showed reduction in lumbar punctures and antibiotic prescription but only for very young children from 1 to 2 months of age 19 . Thus, the appropriate care of children with fever without source is still an area of clinical debate.…”
Section: Introductionmentioning
confidence: 99%
“…Clinical prediction rules (CPRs) can improve diagnostic decision‐making for rare but serious pathologies. However, previously published CPRs 11–18 focused on only clinical parameters 16,17 or laboratory parameters 12,13,18 when other approaches combining clinical and laboratory data are difficult to use in current practice because they require systematic blood sample investigation 11,14,15,19 . Moreover, the published regression models that provide a post‐test probability of infection do not fit with the usual clinician process of treatment decisions 14,15 and seem to have little impact on ATB prescription rate and discharge from PEDs 20,21 .…”
Section: Introductionmentioning
confidence: 99%
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