A NICE combination for predicting hospitalisation at the Emergency Department: a European multicentre observational study of febrile children


Borensztajn, Dorine M, Hagedoorn, Nienke N, Carrol, Enitan D ORCID: 0000-0001-8357-7726, von Both, Ulrich, Dewez, Juan Emmanuel, Emonts, Marieke, van der Flier, Michiel, de Groot, Ronald, Herberg, Jethro, Kohlmaier, Benno et al (show 16 more authors) (2021) A NICE combination for predicting hospitalisation at the Emergency Department: a European multicentre observational study of febrile children. LANCET REGIONAL HEALTH-EUROPE, 8. 100173-.

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Abstract

<h4>Background</h4>Prolonged Emergency Department (ED) stay causes crowding and negatively impacts quality of care. We developed and validated a prediction model for early identification of febrile children with a high risk of hospitalisation in order to improve ED flow.<h4>Methods</h4>The MOFICHE study prospectively collected data on febrile children (0-18 years) presenting to 12 European EDs. A prediction models was constructed using multivariable logistic regression and included patient characteristics available at triage. We determined the discriminative values of the model by calculating the area under the receiver operating curve (AUC).<h4>Findings</h4>Of 38,424 paediatric encounters, 9,735 children were admitted to the ward and 157 to the PICU. The prediction model, combining patient characteristics and NICE alarming, yielded an AUC of 0.84 (95%CI 0.83-0.84).The model performed well for a rule-in threshold of 75% (specificity 99.0% (95%CI 98.9-99.1%, positive likelihood ratio 15.1 (95%CI 13.4-17.1), positive predictive value 0.84 (95%CI 0.82-0.86)) and a rule-out threshold of 7.5% (sensitivity 95.4% (95%CI 95.0-95.8), negative likelihood ratio 0.15 (95%CI 0.14-0.16), negative predictive value 0..95 (95%CI 0.95-9.96)). Validation in a separate dataset showed an excellent AUC of 0.91 (95%CI 0.90- 0.93). The model performed well for identifying children needing PICU admission (AUC 0.95, 95%CI 0.93-0.97). A digital calculator was developed to facilitate clinical use.<h4>Interpretation</h4>Patient characteristics and NICE alarming signs available at triage can be used to identify febrile children at high risk for hospitalisation and can be used to improve ED flow.<h4>Funding</h4>European Union, NIHR, NHS.

Item Type: Article
Uncontrolled Keywords: Emgerency Department, Febrile children, Crowding, Admission prediction
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences
Depositing User: Symplectic Admin
Date Deposited: 17 Aug 2021 09:22
Last Modified: 18 Jan 2023 21:33
DOI: 10.1016/j.lanepe.2021.100173
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3133798
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