External validation of a multivariable prediction model for identification of pneumonia and other serious bacterial infections in febrile immunocompromised children.

OBJECTIVE: To externally validate and update the Feverkids tool clinical prediction model for differentiating bacterial pneumonia and other serious bacterial infections (SBIs) from non-SBI causes of fever in immunocompromised children. DESIGN: International, multicentre, prospective observational study embedded in PErsonalised Risk assessment in Febrile illness to Optimise Real-life Management across the European Union (PERFORM). SETTING: Fifteen teaching hospitals in nine European countries. PARTICIPANTS: Febrile immunocompromised children aged 0-18 years. METHODS: The Feverkids clinical prediction model predicted the probability of bacterial pneumonia, other SBI or no SBI. Model discrimination, calibration and diagnostic performance at different risk thresholds were assessed. The model was then re-fitted and updated. RESULTS: Of 558 episodes, 21 had bacterial pneumonia, 104 other SBI and 433 no SBI. Discrimination was 0.83 (95% CI 0.71 to 0.90) for bacterial pneumonia, with moderate calibration and 0.67 (0.61 to 0.72) for other SBIs, with poor calibration. After model re-fitting, discrimination improved to 0.88 (0.79 to 0.96) and 0.71 (0.65 to 0.76) and calibration improved. Predicted risk <1% ruled out bacterial pneumonia with sensitivity 0.95 (0.86 to 1.00) and negative likelihood ratio (LR) 0.09 (0.00 to 0.32). Predicted risk >10% ruled in bacterial pneumonia with specificity 0.91 (0.88 to 0.94) and positive LR 6.51 (3.71 to 10.3). Predicted risk <10% ruled out other SBIs with sensitivity 0.92 (0.87 to 0.97) and negative LR 0.32 (0.13 to 0.57). Predicted risk >30% ruled in other SBIs with specificity 0.89 (0.86 to 0.92) and positive LR 2.86 (1.91 to 4.25). CONCLUSION: Discrimination and calibration were good for bacterial pneumonia but poorer for other SBIs. The rule-out thresholds have the potential to reduce unnecessary investigations and antibiotics in this high-risk group.

Are children with prolonged fever at a higher risk for serious illness? A prospective observational study.

OBJECTIVES: To describe the characteristics and clinical outcomes of children with fever ≥5 days presenting to emergency departments (EDs). DESIGN: Prospective observational study. SETTING: 12 European EDs. PATIENTS: Consecutive febrile children <18 years between January 2017 and April 2018. INTERVENTIONS: Children with fever ≥5 days and their risks for serious bacterial infection (SBI) were compared with children with fever <5 days, including diagnostic accuracy of non-specific symptoms, warning signs and C-reactive protein (CRP; mg/L). MAIN OUTCOME MEASURES: SBI and other non-infectious serious illness. RESULTS: 3778/35 705 (10.6%) of febrile children had fever ≥5 days. Incidence of SBI in children with fever ≥5 days was higher than in those with fever <5 days (8.4% vs 5.7%). Triage urgency, life-saving interventions and intensive care admissions were similar for fever ≥5 days and <5 days. Several warning signs had good rule in value for SBI with specificities >0.90, but were observed infrequently (range: 0.4%-17%). Absence of warning signs was not sufficiently reliable to rule out SBI (sensitivity 0.92 (95% CI 0.87-0.95), negative likelihood ratio (LR) 0.34 (0.22-0.54)). CRP <20 mg/L was useful for ruling out SBI (negative LR 0.16 (0.11-0.24)). There were 66 cases (1.7%) of non-infectious serious illnesses, including 21 cases of Kawasaki disease (0.6%), 28 inflammatory conditions (0.7%) and 4 malignancies. CONCLUSION: Children with prolonged fever have a higher risk of SBI, warranting a careful clinical assessment and diagnostic workup. Warning signs of SBI occurred infrequently but, if present, increased the likelihood of SBI. Although rare, clinicians should consider important non-infectious causes of prolonged fever.

Shock Index in the early assessment of febrile children at the emergency department: a prospective multicentre study.

OBJECTIVE: (1) To derive reference values for the Shock Index (heart rate/systolic blood pressure) based on a large emergency department (ED) population of febrile children and (2) to determine the diagnostic value of the Shock Index for serious illness in febrile children. DESIGN/SETTING: Observational study in 11 European EDs (2017-2018). PATIENTS: Febrile children with measured blood pressure. MAIN OUTCOME MEASURES: Serious bacterial infection (SBI), invasive bacterial infection (IBI), immediate life-saving interventions (ILSIs) and intensive care unit (ICU) admission. The association between high Shock Index (>95th centile) and each outcome was determined by logistic regression adjusted for age, sex, referral, comorbidity and temperature. Additionally, we calculated sensitivity, specificity and negative/positive likelihood ratios (LRs). RESULTS: Of 5622 children, 461 (8.2%) had SBI, 46 (0.8%) had IBI, 203 (3.6%) were treated with ILSI and 69 (1.2%) were ICU admitted. High Shock Index was associated with SBI (adjusted OR (aOR) 1.6 (95% CI 1.3 to 1.9)), ILSI (aOR 2.5 (95% CI 2.0 to 2.9)), ICU admission (aOR 2.2 (95% CI 1.4 to 2.9)) but not with IBI (aOR: 1.5 (95% CI 0.6 to 2.4)). For the different outcomes, sensitivity for high Shock Index ranged from 0.10 to 0.15, specificity ranged from 0.95 to 0.95, negative LRs ranged from 0.90 to 0.95 and positive LRs ranged from 1.8 to 2.8. CONCLUSIONS: High Shock Index is associated with serious illness in febrile children. However, its rule-out value is insufficient which suggests that the Shock Index is not valuable as a screening tool for all febrile children at the ED.

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

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.

Diversity in the emergency care for febrile children in Europe: a questionnaire study.

OBJECTIVE: To provide an overview of care in emergency departments (EDs) across Europe in order to interpret observational data and implement interventions regarding the management of febrile children. DESIGN AND SETTING: An electronic questionnaire was sent to the principal investigators of an ongoing study (PERFORM (Personalised Risk assessment in Febrile illness to Optimise Real-life Management), www.perform2020.eu) in 11 European hospitals in eight countries: Austria, Germany, Greece, Latvia, the Netherlands, Slovenia, Spain and the UK. OUTCOME MEASURES: The questionnaire covered indicators in three domains: local ED quality (supervision, guideline availability, paper vs electronic health records), organisation of healthcare (primary care, immunisation), and local factors influencing or reflecting resource use (availability of point-of-care tests, admission rates). RESULTS: Reported admission rates ranged from 4% to 51%. In six settings (Athens, Graz, Ljubljana, Riga, Rotterdam, Santiago de Compostela), the supervising ED physicians were general paediatricians, in two (Liverpool, London) these were paediatric emergency physicians, in two (Nijmegen, Newcastle) supervision could take place by either a general paediatrician or a general emergency physician, and in one (München) this could be either a general paediatrician or a paediatric emergency physician. The supervising physician was present on site in all settings during office hours and in five out of eleven settings during out-of-office hours. Guidelines for fever and sepsis were available in all settings; however, the type of guideline that was used differed. Primary care was available in all settings during office hours and in eight during out-of-office hours. There were differences in routine immunisations as well as in additional immunisations that were offered; immunisation rates varied between and within countries. CONCLUSION: Differences in local, regional and national aspects of care exist in the management of febrile children across Europe. This variability has to be considered when trying to interpret differences in the use of diagnostic tools, antibiotics and admission rates. Any future implementation of interventions or diagnostic tests will need to be aware of this European diversity.