title: Evaluation of triage methods used to select patients with suspected pandemic influenza for hospital admission.
abstract: OBJECTIVE
  Prepandemic projections anticipated huge excess attendances and mortality in an influenza pandemic. A number of tools had been suggested for triaging patients with influenza for inpatient and critical care admission, but none had been validated in these patients. The authors aimed to evaluate three potential triage tools--CURB-65, PMEWS and the Department of Health community assessment tool (CAT)--in patients in the first waves of the 2009 H1N1 pandemic.
  
  
  METHODS
  Prospective cohort study in three urban emergency departments (one adult, one paediatric, one mixed) in two cities.
  
  
  METHODS
  All patients presenting to the three emergency departments fulfilling the national definition of suspected pandemic influenza.
  
  
  METHODS
  30-day follow-up identified patients who had died or had required advanced respiratory, cardiovascular or renal support.
  
  
  RESULTS
  The pandemic was much less severe than expected. A total of 481 patients (347 children) were recruited, of which only five adults fulfilled the outcome criteria for severe illness. The c-statistics for CURB-65, PMEWS and CAT in adults in terms of discriminating between those admitted and discharged were 0.65 (95% CI 0.54 to 0.76), 0.76 (95% CI 0.66 to 0.86) and 0.62 (95% CI 0.51 to 0.72), respectively. In detecting adverse outcome, sensitivities were 20% (95% CI 4% to 62%), 80% (95% CI 38% to 96%) and 60% (95% CI 23% to 88%), and specificities were 94% (95% CI 88% to 97%), 40% (95% CI 32% to 49%) and 81% (95% CI 73% to 87%) for CURB-65, PMEWS and CAT, respectively.
  
  
  CONCLUSIONS
  Although limited by a paucity of cases, this research shows that current triage methods for suspected pandemic influenza did not reliably discriminate between patients with good and poor outcomes.
authors.affiliation: School of Health and Related Research, University of Sheffield, Sheffield, UK. kirstychallen@hotmail.com
authors.forename: Kirsty
authors.initials: K
authors.lastname: Challen
authors.forename: Steve W
authors.initials: SW
authors.lastname: Goodacre
authors.forename: Richard
authors.initials: R
authors.lastname: Wilson
authors.forename: Andrew
authors.initials: A
authors.lastname: Bentley
authors.forename: Mike
authors.initials: M
authors.lastname: Campbell
authors.forename: Christopher
authors.initials: C
authors.lastname: Fitzsimmons
authors.forename: Darren
authors.initials: D
authors.lastname: Walter
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks / Q000517:prevention & control / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000175:diagnosis* / Q000453:epidemiology / Q000401:mortality / Q000628:therapy; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D058873:Pandemics; D011446:Prospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D014218:Triage / Q000379:methods*; D006113:United Kingdom / Q000453:epidemiology; D055815:Young Adult