title: Use of an admission early warning score to predict patient morbidity and mortality and treatment success.
abstract: BACKGROUND
  Early warning scores (EWS) are used to identify physiological deterioration in patients. Studies to date have primarily focused on the correlation between trends in serially recorded EWS of inpatients and clinical outcomes. This study examined the predictive value of an EWS calculated immediately on presentation to hospital for acute medical patients.
  
  
  METHODS
  A prospective study of 225 consecutive medical admissions. Pulse, systolic blood pressure, respiratory rate, oxygen saturation and neurological status were used to calculate an EWS. Patients were divided into four score categories based on their EWS. The primary endpoints examined were intensive care unit (ICU)/coronary care unit (CCU) admission, death, cardiac arrest and length of hospital stay.
  
  
  RESULTS
  For each rise in score category there was an increased risk of admission to ICU (odds ratio (OR) 3.35, CI 1.52 to 7.40, p = 0.003), admission to CCU (OR 1.82, CI 1.07 to 3.09, p = 0.027), death (OR 2.19, CI 1.41 to 3.39, p = 0.000) and reaching the combined endpoint of CCU/ICU admission or death (OR 2.19, CI 1.41 to 3.39, p = 0.000). The higher the score the longer the length of hospital admission (p = 0.04). A decrease in EWS between first presentation to hospital and transfer to the ward was associated with a decreased risk of reaching the combined endpoint of CCU or ICU admission or death (OR 2.56, CI 1.11 to 5.89, p = 0.028).
  
  
  CONCLUSIONS
  Higher admission EWS correlate with increased risk of CCU/ICU admission, death and longer hospital stays independent of patient age. An improvement in serial EWS within 4 h of presentation to hospital predicts improved clinical outcomes. The EWS is a potential triage tool in the emergency department for acute medical patients.
authors.affiliation: Department of Medicine, St Luke's Hospital, Kilkenny, Ireland. johngroarke1@eircom.net
authors.forename: J D
authors.initials: JD
authors.lastname: Groarke
authors.forename: J
authors.initials: J
authors.lastname: Gallagher
authors.forename: J
authors.initials: J
authors.lastname: Stack
authors.forename: A
authors.initials: A
authors.lastname: Aftab
authors.forename: C
authors.initials: C
authors.lastname: Dwyer
authors.forename: R
authors.initials: R
authors.lastname: McGovern
authors.forename: G
authors.initials: G
authors.lastname: Courtney
mesh_terms: D018806:APACHE; D001794:Blood Pressure; D003243:Consciousness; D003422:Critical Care / Q000706:statistics & numerical data*; D042241:Early Diagnosis; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D004812:Epidemiologic Methods; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D011674:Pulse; D012119:Respiration; D012720:Severity of Illness Index; D016896:Treatment Outcome; D014218:Triage / Q000706:statistics & numerical data*