TY - JOUR
TI - Development and validation of a prediction model for invasive bacterial
infections in febrile children at European Emergency Departments:
MOFICHE, a prospective observational study
AU - Hagedoorn, Nienke N.
AU - Borensztajn, Dorine
AU - Nijman, Ruud Gerard and
AU - Nieboer, Daan
AU - Herberg, Jethro Adam
AU - Balode, Anda
AU - von Both,
AU - Ulrich
AU - Carrol, Enitan
AU - Eleftheriou, Irini
AU - Emonts, Marieke and
AU - van der Flier, Michiel
AU - de Groot, Ronald
AU - Kohlmaier, Benno and
AU - Lim, Emma
AU - Maconochie, Ian
AU - Martinon-Torres, Federico
AU - Pokorn,
AU - Marko
AU - Strle, Franc
AU - Tsolia, Maria
AU - Zavadska, Dace
AU - Zenz,
AU - Werner
AU - Levin, Michael
AU - Vermont, Clementien
AU - Moll, Henriette A.
JO - Archives of Disease in Childhood
PY - 2021
VL - 106
TODO - 7
SP - 641-647
PB - BMJ Publishing Group
SN - 0003-9888, 1468-2044
TODO - 10.1136/archdischild-2020-319794
TODO - epidemiology; therapeutics
TODO - 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.
ER -