van de Maat, J;
Nieboer, D;
Thompson, M;
Lakhanpaul, M;
Moll, H;
Oostenbrink, R;
(2019)
Can clinical prediction models assess antibiotic need in childhood pneumonia? A validation study in paediatric emergency care.
PLoS One
, 14
(6)
, Article e0217570. 10.1371/journal.pone.0217570.
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Abstract
OBJECTIVES: Pneumonia is the most common bacterial infection in children at the emergency department (ED). Clinical prediction models for childhood pneumonia have been developed (using chest x-ray as their reference standard), but without implementation in clinical practice. Given current insights in the diagnostic limitations of chest x-ray, this study aims to validate these prediction models for a clinical diagnosis of pneumonia, and to explore their potential to guide decisions on antibiotic treatment at the ED. METHODS: We systematically identified clinical prediction models for childhood pneumonia and assessed their quality. We evaluated the validity of these models in two populations, using a clinical reference standard (1. definite/probable bacterial, 2. bacterial syndrome, 3. unknown bacterial/viral, 4. viral syndrome, 5. definite/probable viral), measuring performance by the ordinal c-statistic (ORC). Validation populations included prospectively collected data of children aged 1 month to 5 years attending the ED of Rotterdam (2012-2013) or Coventry (2005-2006) with fever and cough or dyspnoea. RESULTS: We identified eight prediction models and could evaluate the validity of seven, with original good performance. In the Dutch population 22/248 (9%) had a bacterial infection, in Coventry 53/301 (17%), antibiotic prescription was 21% and 35% respectively. Three models predicted a higher risk in children with bacterial infections than in those with viral disease (ORC ≥0.55) and could identify children at low risk of bacterial infection. CONCLUSIONS: Three clinical prediction models for childhood pneumonia could discriminate fairly well between a clinical reference standard of bacterial versus viral infection. However, they all require the measurement of biomarkers, raising questions on the exact target population when implementing these models in clinical practice. Moreover, choosing optimal thresholds to guide antibiotic prescription is challenging and requires careful consideration of potential harms and benefits.
| Type: | Article |
|---|---|
| Title: | Can clinical prediction models assess antibiotic need in childhood pneumonia? A validation study in paediatric emergency care |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1371/journal.pone.0217570 |
| Publisher version: | https://doi.org/10.1371/journal.pone.0217570 |
| Language: | English |
| Additional information: | © 2019 van de Maat et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Forecasting, Antibiotics, Pneumonia, Bacterial diseases, Fevers, Treatment guidelines, Critical care and emergency medicine, Viral transmission and infection |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10076230 |
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