The predictive value of the NICE "red traffic lights" in acutely ill children

PLoS One. 2014 Mar 14;9(3):e90847. doi: 10.1371/journal.pone.0090847. eCollection 2014.


Objective: Early recognition and treatment of febrile children with serious infections (SI) improves prognosis, however, early detection can be difficult. We aimed to validate the predictive rule-in value of the National Institute for Health and Clinical Excellence (NICE) most severe alarming signs or symptoms to identify SI in children.

Design, setting and participants: The 16 most severe ("red") features of the NICE traffic light system were validated in seven different primary care and emergency department settings, including 6,260 children presenting with acute illness.

Main outcome measures: We focussed on the individual predictive value of single red features for SI and their combinations. Results were presented as positive likelihood ratios, sensitivities and specificities. We categorised "general" and "disease-specific" red features. Changes in pre-test probability versus post-test probability for SI were visualised in Fagan nomograms.

Results: Almost all red features had rule-in value for SI, but only four individual red features substantially raised the probability of SI in more than one dataset: "does not wake/stay awake", "reduced skin turgor", "non-blanching rash", and "focal neurological signs". The presence of ≥ 3 red features improved prediction of SI but still lacked strong rule-in value as likelihood ratios were below 5.

Conclusions: The rule-in value of the most severe alarming signs or symptoms of the NICE traffic light system for identifying children with SI was limited, even when multiple red features were present. Our study highlights the importance of assessing the predictive value of alarming signs in clinical guidelines prior to widespread implementation in routine practice.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Disease*
  • Adolescent
  • Child
  • Child, Preschool
  • Early Diagnosis*
  • Female
  • Fever
  • Humans
  • Infant
  • Infant, Newborn
  • Likelihood Functions
  • Male

Grants and funding

EK is supported by ZonMW, a Dutch organisation for health research and development; RO is supported by an unrestricted grant of the Europe Container Terminals B.V and by a fellowship award of European Society of Pediatric Infectious Diseases. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.