You are here

Article Text

Article menu
Download PDFPDF
Original article
Clinical prediction models for young febrile infants at the emergency department: an international validation study
  1. Evelien de Vos-Kerkhof1,
  2. Borja Gomez2,3,
  3. Karen Milcent4,
  4. Ewout W Steyerberg5,
  5. Ruud Gerard Nijman6,
  6. Frank J Smit7,
  7. Santiago Mintegi2,3,
  8. Henriette A Moll1,
  9. Vincent Gajdos8,
  10. Rianne Oostenbrink1
  1. 1 Department of General Paediatrics, Erasmus MC-Sophia Children’s Hospital, Rotterdam, The Netherlands
  2. 2 Paediatric Emergency Department, Cruces University Hospital, Bilbao, Spain
  3. 3 University of the Basque Country, Bilbao, Spain
  4. 4 AP-HP Department of Paediatrics, Hôpitaux Universitaires Paris Sud–Antoine Béclère, Clamart, France
  5. 5 Department of Public Health and Clinical Decision Making, Erasmus MC–University Medical Centre Rotterdam, Rotterdam, The Netherlands
  6. 6 Department of Paediatric Accident and Emergency, St Mary’s Hospital, Imperial College–NHS Healthcare Trust, Rotterdam, The Netherlands
  7. 7 Department of General Paediatrics, Maasstad Hospital, Rotterdam, The Netherlands
  8. 8 Université Paris-Saclay, Université Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
  1. Correspondence to Dr Rianne Oostenbrink, Department of General Paediatrics, Erasmus MC-Sophia Children’s Hospital, Rotterdam 3015, The Netherlands; r.oostenbrink{at}erasmusmc.nl

Abstract

Objective To assess the diagnostic value of existing clinical prediction models (CPM; ie, statistically derived) in febrile young infants at risk for serious bacterial infections.

Methods A systematic literature review identified eight CPMs for predicting serious bacterial infections in febrile children. We validated these CPMs on four validation cohorts of febrile children in Spain (age <3 months), France (age <3 months) and two cohorts in the Netherlands (age 1–3 months and >3–12 months). We evaluated the performance of the CPMs by sensitivity/specificity, area under the receiver operating characteristic curve (AUC) and calibration studies.

Results The original cohorts in which the prediction rules were developed (derivation cohorts) ranged from 381 to 15 781 children, with a prevalence of serious bacterial infections varying from 0.8% to 27% and spanned an age range of 0–16 years. All CPMs originally performed moderately to very well (AUC 0.60–0.93). The four validation cohorts included 159–2204 febrile children, with a median age range of 1.8 (1.2–2.4) months for the three cohorts <3 months and 8.4 (6.0–9.6) months for the cohort >3–12 months of age. The prevalence of serious bacterial infections varied between 15.1% and 17.2% in the three cohorts <3 months and was 9.8% for the cohort >3–12 months of age. Although discriminative values varied greatly, best performance was observed for four CPMs including clinical signs and symptoms, urine dipstick analyses and laboratory markers with AUC ranging from 0.68 to 0.94 in the three cohorts <3 months (ranges sensitivity: 0.48–0.94 and specificity: 0.71–0.97). For the >3–12 months’ cohort AUC ranges from 0.80 to 0.89 (ranges sensitivity: 0.70–0.82 and specificity: 0.78–0.90). In general, the specificities exceeded sensitivities in our cohorts, in contrast to derivation cohorts with high sensitivities, although this effect was stronger in infants <3 months than in infants >3–12 months.

Conclusion We identified four CPMs, including clinical signs and symptoms, urine dipstick analysis and laboratory markers, which can aid clinicians in identifying serious bacterial infections. We suggest clinicians should use CPMs as an adjunctive clinical tool when assessing the risk of serious bacterial infections in febrile young infants.

  • epidemiology
  • evidence-based medicine
  • general paediatrics
  • infectious diseases

https://doi.org/10.1136/archdischild-2017-314011

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Contributors EdVK: conceptualised and designed the study, was responsible for data collection at one of the three sites, carried out the initial analyses, drafted the initial manuscript and approved the final manuscript as submitted. BG, KM, RGN, FJS, SM, VG: coordinated and supervised data collection at one of the three sites, critically reviewed the manuscript and approved the final manuscript as submitted. EWS: supervised the analyses, reviewed and revised the manuscript, and approved the final manuscript as submitted. HAM: conceptualised and designed the study, supervised data collection at one of the three sites, reviewed and revised the manuscript, and approved the final manuscript as submitted. RO: conceptualised and designed the study, supervised data collection at one of the three sites, supervised the analyses, reviewed and revised the manuscript, and approved the final manuscript as submitted. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Disclaimer To our best knowledge this article is not accessible as full paper (pdf), only the reference (title) can be retrieved from https://repub.eur.nl/pub/93311, the online e-publication of the PhD thesis: Integrating Clinical Decision Making and Patient Care at the Paediatric Emergency Department–focusing on children with serious bacterial infections. Erasmus University Rotterdam. EdVK (2016 September 20).

    • Competing interests None declared.

    • Patient consent Parental/guardian consent obtained.

    • Ethics approval The study was approved by the local institutional medical ethics committee.

    • Provenance and peer review Not commissioned; externally peer reviewed.