title: The Simple Clinical Score predicts mortality for 30 days after admission to an acute medical unit.
abstract: BACKGROUND
  Predictive scores such as APACHE II and SAPS II have been used to assess patients in intensive care units, but only the modified early warning (MEW) score has been used to assess acutely ill general medical patients.
  
  
  METHODS
  Observational study of predictors of mortality.
  
  
  METHODS
  Small Irish rural hospital.
  
  
  METHODS
  From 17 February 2000 to 29 January 2004, 9,964 consecutive patients admitted as acute medical emergencies were divided into a derivation cohort of 6,736 patients and a validation cohort of 3,228 patients.
  
  
  RESULTS
  In the derivation cohort, 316 patients (4.7%) died within 30 days of hospital admission. Under univariate analysis, age, vital signs and 18 categorical variables were associated with increased risk of death, and nine with reduced risk. Logistic regression identified 16 independent predictors of 30-day mortality, from which the Simple Clinical Score was derived, stratifying patients into five risk classes. In each class, mortality was not significantly different between the derivation and validation cohorts: 0-0.1% for very low risk, 1.5-1.6% for low risk, 3.8-3.9% for average risk, 9.0-10.3% for high risk, and 29.2-34.4% for very high risk.
  
  
  CONCLUSIONS
  The Simple Clinical Score quickly and accurately identifies patients at both a low and high risk of death from the first to the 30th day after admission, enabling prompt triage and placement within a health-care facility.
authors.affiliation: Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net
authors.forename: J
authors.initials: J
authors.lastname: Kellett
authors.forename: B
authors.initials: B
authors.lastname: Deane
mesh_terms: D018806:APACHE; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017052:Hospital Mortality; D006780:Hospitals, Rural / Q000706:statistics & numerical data; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests