Hagedoorn, NN, Borensztajn, D, Nijman, RG, Nieboer, D, Herberg, JA, Balode, A, Von Both, U, Carrol, E 
ORCID: 0000-0001-8357-7726, Eleftheriou, I, Emonts, M et al (show 14 more authors)
(2021)
Development and validation of a prediction model for invasive bacterial infections in febrile children at European Emergency Departments: MOFICHE, a prospective observational study
Archives of Disease in Childhood, 106 (7).
pp. 641-647.
ISSN 0003-9888, 1468-2044
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Development and validation of a prediction model for IBI MoFICHE ADC 2020.pdf - Published version Download (779kB) | Preview |
Abstract
Objectives To develop and cross-validate a multivariable clinical prediction model to identify invasive bacterial infections (IBI) and to identify patient groups who might benefit from new biomarkers. Design Prospective observational study. Setting 12 emergency departments (EDs) in 8 European countries. Patients Febrile children aged 0-18 years. Main outcome measures IBI, defined as bacteraemia, meningitis and bone/joint infection. We derived and cross-validated a model for IBI using variables from the Feverkidstool (clinical symptoms, C reactive protein), neurological signs, non-blanching rash and comorbidity. We assessed discrimination (area under the receiver operating curve) and diagnostic performance at different risk thresholds for IBI: sensitivity, specificity, negative and positive likelihood ratios (LRs). Results Of 16 268 patients, 135 (0.8%) had an IBI. The discriminative ability of the model was 0.84 (95% CI 0.81 to 0.88) and 0.78 (95% CI 0.74 to 0.82) in pooled cross-validations. The model performed well for the rule-out threshold of 0.1% (sensitivity 0.97 (95% CI 0.93 to 0.99), negative LR 0.1 (95% CI 0.0 to 0.2) and for the rule-in threshold of 2.0% (specificity 0.94 (95% CI 0.94 to 0.95), positive LR 8.4 (95% CI 6.9 to 10.0)). The intermediate thresholds of 0.1%-2.0% performed poorly (ranges: sensitivity 0.59-0.93, negative LR 0.14-0.57, specificity 0.52-0.88, positive LR 1.9-4.8) and comprised 9784 patients (60%). Conclusions The rule-out threshold of this model has potential to reduce antibiotic treatment while the rule-in threshold could be used to target treatment in febrile children at the ED. In more than half of patients at intermediate risk, sensitive biomarkers could improve identification of IBI and potentially reduce unnecessary antibiotic prescriptions.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | epidemiology, therapeutics |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 11 Dec 2020 11:52 |
| Last Modified: | 01 Mar 2026 12:28 |
| DOI: | 10.1136/archdischild-2020-319794 |
| Related Websites: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3109997 |
| Disclaimer: | The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate. |
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