Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care

Jan Y Verbakel; Marieke B Lemiengre; Tine De Burghgraeve; An De Sutter; Bert Aertgeerts; Dominique M A Bullens; Bethany Shinkins; Ann Van den Bruel; Frank Buntinx

doi:10.1136/bmjopen-2015-008657

Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care

BMJ Open. 2015 Aug 7;5(8):e008657. doi: 10.1136/bmjopen-2015-008657.

Authors

Jan Y Verbakel¹, Marieke B Lemiengre², Tine De Burghgraeve³, An De Sutter², Bert Aertgeerts³, Dominique M A Bullens⁴, Bethany Shinkins⁵, Ann Van den Bruel⁵, Frank Buntinx⁶

Affiliations

¹ Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
² Department of Family Practice and Primary Health Care, Ghent University, Ghent, Belgium.
³ Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
⁴ Clinical Department of Paediatrics, University Hospitals Leuven, Leuven, Belgium Paediatric Immunology, Department of Microbiology and Immunology, KU Leuven, Leuven, Belgium.
⁵ Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
⁶ Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium Research Institute Caphri, Maastricht University, Maastricht, The Netherlands.

Abstract

Objective: Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population.

Design: Diagnostic accuracy study validating a clinical prediction rule.

Setting and participants: Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department.

Intervention: Physicians were asked to score the decision tree in every child.

Primary outcome measures: The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values.

Results: In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%.

Conclusions: In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out.

Trial registration number: NCT02024282.

Keywords: ACCIDENT & EMERGENCY MEDICINE; EPIDEMIOLOGY; PRIMARY CARE.

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Publication types

Multicenter Study
Research Support, Non-U.S. Gov't
Validation Study

MeSH terms

Acute Disease
Adolescent
Ambulatory Care
Belgium
Child
Child, Preschool
Decision Support Techniques*
Decision Trees*
Female
Humans
Infant
Infections / diagnosis*
Male
Prospective Studies
Sensitivity and Specificity

Associated data

ClinicalTrials.gov/NCT02024282