Which symptoms and clinical features correctly identify serious respiratory infection in children attending a

C Blacklock1, R Mayon-White, N Coad

  • 1Department of Primary Health Care, Oxford University, Rosemary Rue Building, Old Road Campus, Headington, Oxford OX3 7LF, UK. claire.blacklock@dphpc.ox.ac.uk

Insights

Parent-reported symptoms are unreliable for identifying serious respiratory infections in children. Clinical assessment of respiratory distress by nurses is a better predictor of serious illness.

Area of Science:

  • Pediatric emergency medicine
  • Respiratory infections in children
  • Diagnostic accuracy studies

Background:

  • Parental symptom reporting is commonly used for triaging children with suspected infections.
  • Limited evidence exists on which symptoms accurately predict serious respiratory infections in pediatric patients.

Purpose of the Study:

  • To identify symptoms and triage findings that predict serious respiratory infection in children.
  • To quantify agreement between parental and nurse assessments of illness severity.

Main Methods:

  • Prospective diagnostic cohort study involving 535 children (3 months-12 years) with suspected acute infection.
  • Parents completed symptom questionnaires; nurses performed triage assessments including vital signs.
  • Diagnosis at discharge served as the outcome measure; agreement was assessed using kappa values.

Main Results:

  • Parent-reported symptoms showed poor predictive value (LR+ 0.56-1.93) and low agreement with nurse assessments (kappa 0.22-0.56).
  • Clinical assessment of respiratory distress was the strongest predictor (LR+ 5.04).
  • Low oxygen saturation (<94%) was highly specific (95.1%) but lacked sensitivity (35.6%); tachypnea showed limited discriminatory value.

Conclusions:

  • Parental symptom reporting is unreliable for discriminating serious respiratory infections in children presenting with acute infections.
  • Nurse triage, particularly the assessment of respiratory distress and specific vital signs, is crucial for identifying high-risk children.
Abstract

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