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

Alexander James Martin, Fabian Johannes Stanislaus van der Velden, Ulrich von Both, Dace Zavadska, PERFORM consortium, Anda Balode (Member of the Working Group), Arta Bārzdiņa (Member of the Working Group), Dārta Deksne (Member of the Working Group), Dace Gardovska (Member of the Working Group), Dagne Grāvele (Member of the Working Group), Ilze Grope (Member of the Working Group), Anija Meiere (Member of the Working Group), Ieva Nokalna (Member of the Working Group), Jana Pavāre (Member of the Working Group), Zanda Pučuka (Member of the Working Group), Katrina Selecka (Member of the Working Group), Aleksandra Rudzāte (Member of the Working Group), Urzula Nora Urbāne (Member of the Working Group)

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Abstract

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.

Original languageEnglish
Pages (from-to)58-66
Number of pages9
JournalArchives of Disease in Childhood
Volume109
Issue number1
DOIs
Publication statusPublished - 1 Jan 2024

Field of Science*

  • 3.2 Clinical medicine

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database

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