Development and validation of a prediction model for invasive bacterial infections in febrile children at European Emergency Departments: MOFICHE, a prospective observational study

Nienke N. Hagedoorn, Dorine Borensztajn, Ruud Gerard Nijman, Daan Nieboer, Jethro Adam Herberg, Anda Balode, Ulrich Von Both, Enitan Carrol, Irini Eleftheriou, Marieke Emonts, Michiel Van Der Flier, Ronald De Groot, Benno Kohlmaier, Emma Lim, Ian MacOnochie, Federico Martinón-Torres, Marko Pokorn, Franc Strle, Maria Tsolia, Dace ZavadskaWerner Zenz, Michael Levin, Clementien Vermont, Henriette A. Moll*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.

Original languageEnglish
Pages (from-to)641-647
Number of pages7
JournalArchives of Disease in Childhood
Volume106
Issue number7
DOIs
Publication statusPublished - 18 Jun 2021

Bibliographical note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 668303. The research was supported by the National Institute for Health Research Biomedical Research Centres at Imperial College London, Newcastle Hospitals NHS Foundation Trust and Newcastle University.

Publisher Copyright:
© 2021 Archives of Disease in Childhood

Research programs

  • EMC MM-04-54-08-A

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