title: SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission.
abstract: OBJECTIVE
  To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data.
  
  
  METHODS
  Prospective multicentre, multinational cohort study.
  
  
  METHODS
  A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002.
  
  
  RESULTS
  ICU admission data (recorded within +/-1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test H=10.56, p=0.39, C=14.29, p=0.16). Customized equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit.
  
  
  CONCLUSIONS
  The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels.
authors.affiliation: Unidade de Cuidados Intensivos Polivalente, Hospital de St. António dos Capuchos, Centro Hospitalar de Lisboa (Zona Central), Lisbon, Portugal. r.moreno@mail.telepac.pt
authors.forename: Rui P
authors.initials: RP
authors.lastname: Moreno
authors.forename: Philipp G H
authors.initials: PG
authors.lastname: Metnitz
authors.forename: Eduardo
authors.initials: E
authors.lastname: Almeida
authors.forename: Barbara
authors.initials: B
authors.lastname: Jordan
authors.forename: Peter
authors.initials: P
authors.lastname: Bauer
authors.forename: Ricardo Abizanda
authors.initials: RA
authors.lastname: Campos
authors.forename: Gaetano
authors.initials: G
authors.lastname: Iapichino
authors.forename: David
authors.initials: D
authors.lastname: Edbrooke
authors.forename: Maurizia
authors.initials: M
authors.lastname: Capuzzo
authors.forename: Jean-Roger
authors.initials: JR
authors.lastname: Le Gall
mesh_terms: D000328:Adult; D015897:Comorbidity; D016001:Confidence Intervals; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D016015:Logistic Models; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D012306:Risk; D012720:Severity of Illness Index