Verbakel, JY, Lemiengre, MB, De Burghgraeve, T et al. (6 more authors) (2015) Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. BMJ Open, 5 (8). e008657. ISSN 2044-6055
Abstract
OBJECTIVE: Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. DESIGN: Diagnostic accuracy study validating a clinical prediction rule. SETTING AND PARTICIPANTS: Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. INTERVENTION: Physicians were asked to score the decision tree in every child. PRIMARY OUTCOME MEASURES: The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. RESULTS: In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. CONCLUSIONS: In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Health Sciences (Leeds) > Academic Unit of Health Economics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Oct 2016 16:16 |
Last Modified: | 07 Oct 2016 16:16 |
Published Version: | https://doi.org/10.1136/bmjopen-2015-008657 |
Status: | Published |
Publisher: | BMJ Publishing Group |
Identification Number: | 10.1136/bmjopen-2015-008657 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101681 |