Lancaster EPrints

Predicting Risk of Serious Bacterial Infections in Febrile Children in the Emergency Department

Irwin, Adam D. and Grant, Alison and Williams, Rhian and Kolamunnage-Dona, Ruwanthi and Drew, Richard J. and Paulus, Stephane and Jeffers, Graham and Williams, Kim and Breen, Rachel and Preston, Jennifer and Appelbe, Duncan and Chesters, Christine and Newland, Paul and Marzouk, Omnia and McNamara, Paul S. and Diggle, Peter J. and Carrol, Enitan D. (2017) Predicting Risk of Serious Bacterial Infections in Febrile Children in the Emergency Department. Pediatrics. ISSN 0031-4005

[img]
Preview
PDF (Apr.17.risk_prediction.Peds.r2) - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (488Kb) | Preview

    Abstract

    BACKGROUND: Improving the diagnosis of serious bacterial infections (SBIs) in the children's emergency department is a clinical priority. Early recognition reduces morbidity and mortality, and supporting clinicians in ruling out SBIs may limit unnecessary admissions and antibiotic use. METHODS: A prospective, diagnostic accuracy study of clinical and biomarker variables in the diagnosis of SBIs (pneumonia or other SBI) in febrile children <16 years old. A diagnostic model was derived by using multinomial logistic regression and internally validated. External validation of a published model was undertaken, followed by model updating and extension by the inclusion of procalcitonin and resistin. RESULTS: There were 1101 children studied, of whom 264 had an SBI. A diagnostic model discriminated well between pneumonia and no SBI (concordance statistic 0.84, 95% confidence interval 0.78-0.90) and between other SBIs and no SBI (0.77, 95% confidence interval 0.71-0.83) on internal validation. A published model discriminated well on external validation. Model updating yielded good calibration with good performance at both high-risk (positive likelihood ratios: 6.46 and 5.13 for pneumonia and other SBI, respectively) and low-risk (negative likelihood ratios: 0.16 and 0.13, respectively) thresholds. Extending the model with procalcitonin and resistin yielded improvements in discrimination. CONCLUSIONS: Diagnostic models discriminated well between pneumonia, other SBIs, and no SBI in febrile children in the emergency department. Improvements in the classification of nonevents have the potential to reduce unnecessary hospital admissions and improve antibiotic prescribing. The benefits of this improved risk prediction should be further evaluated in robust impact studies.

    Item Type: Journal Article
    Journal or Publication Title: Pediatrics
    Additional Information: Copyright © 2017 by the American Academy of Pediatrics Predicting Risk of Serious Bacterial Infections in Febrile Children in the Emergency Department Adam D. Irwin, Alison Grant, Rhian Williams, Ruwanthi Kolamunnage-Dona, Richard J. Drew, Stephane Paulus, Graham Jeffers, Kim Williams, Rachel Breen, Jennifer Preston, Duncan Appelbe, Christine Chesters, Paul Newland, Omnia Marzouk, Paul S. McNamara, Peter J. Diggle, Enitan D. Carrol Pediatrics Jul 2017, e20162853; DOI: 10.1542/peds.2016-2853
    Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/2700/2735
    Subjects: ?? JOURNAL ARTICLEPEDIATRICS, PERINATOLOGY, AND CHILD HEALTH ??
    Departments: Faculty of Health and Medicine > Medicine
    ID Code: 87045
    Deposited By: ep_importer_pure
    Deposited On: 01 Aug 2017 09:00
    Refereed?: Yes
    Published?: Published
    Last Modified: 23 May 2019 11:06
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/87045

    Actions (login required)

    View Item