title: The predictive value of the NICE "red traffic lights" in acutely ill children.
abstract: 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.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
authors.affiliation: Erasmus MC-Sophia Children's Hospital, Department of General Pediatrics, Rotterdam, The Netherlands.
authors.forename: Evelien
authors.initials: E
authors.lastname: Kerkhof
authors.affiliation: Department of General and Adolescent Pediatrics, University College London, Institute of Child Health, London, United Kingdom.
authors.forename: Monica
authors.initials: M
authors.lastname: Lakhanpaul
authors.affiliation: Pediatric Intensive Care Unit, Great Ormond Street Hospital, London, United Kingdom.
authors.forename: Samiran
authors.initials: S
authors.lastname: Ray
authors.affiliation: Department of General Practice, Katholieke Universiteit Leuven, Leuven, Belgium.
authors.forename: Jan Y
authors.initials: JY
authors.lastname: Verbakel
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.
authors.forename: Ann
authors.initials: A
authors.lastname: Van den Bruel
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.
authors.forename: Matthew
authors.initials: M
authors.lastname: Thompson
authors.affiliation: Department of General Practice, University Groningen, University Medical Centre Groningen, Groningen, The Netherlands.
authors.forename: Marjolein Y
authors.initials: MY
authors.lastname: Berger
authors.affiliation: Erasmus MC-Sophia Children's Hospital, Department of General Pediatrics, Rotterdam, The Netherlands.
authors.forename: Henriette A
authors.initials: HA
authors.lastname: Moll
authors.affiliation: Erasmus MC-Sophia Children's Hospital, Department of General Pediatrics, Rotterdam, The Netherlands.
authors.forename: Rianne
authors.initials: R
authors.lastname: Oostenbrink
mesh_terms: D000208:Acute Disease; D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D042241:Early Diagnosis; D005260:Female; D005334:Fever; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016013:Likelihood Functions; D008297:Male