title: A comparison of four severity-adjusted models to predict mortality after coronary artery bypass graft surgery.
abstract: OBJECTIVE
  To assess the validity of four severity-adjusted models to predict mortality following coronary artery bypass graft surgery by using an independent surgical database.
  
  
  METHODS
  A prospective observational study wherein predicted mortality for each patient was obtained by using four different published severity-adjusted models.
  
  
  METHODS
  A university-affiliated teaching community hospital.
  
  
  METHODS
  Eight hundred sixty-eight consecutive patients who underwent coronary artery bypass graft surgery without accompanying valve or aneurysm repair during the period from 1991 to 1993.
  
  
  METHODS
  None.
  
  
  METHODS
  Predicted mortality rates for each model were obtained by averaging individual patient predictions and were compared with actual morality rates. We assessed the accuracy of overall prediction for the total series, as well as compared individual patient predictions created by each model. The discrimination of models was assessed with receiver operating characteristic curves and the Hosmer-Lemeshow goodness-of-fit statistic.
  
  
  RESULTS
  The observed crude mortality rate was 3.7%. The predicted mortality rate ranged from 2.8% to 9.2%, despite relatively good discrimination by the models (area under the receiver operating characteristic curve, 0.70 to 0.74). The individual patient mortality predicted by different models varied by as much as a ninefold difference.
  
  
  CONCLUSIONS
  The currently used coronary artery bypass graft predictive models, although generally accurate, have significant shortcomings and should be used with caution. The predicted mortality rate following coronary artery bypass graft surgery varied by a factor of 3.3 from lowest to highest, making the choice of model a critical factor when assessing outcome. The use of these models for individual patient risk estimations is risky because of the marked discrepancies in individual predictions created by each model.
authors.affiliation: Department of Surgery, Fallon Healthcare System, Worcester, Mass.
authors.forename: R K
authors.initials: RK
authors.lastname: Orr
authors.forename: B S
authors.initials: BS
authors.lastname: Maini
authors.forename: F D
authors.initials: FD
authors.lastname: Sottile
authors.forename: E M
authors.initials: EM
authors.lastname: Dumas
authors.forename: P
authors.initials: P
authors.lastname: O'Mara
mesh_terms: D000368:Aged; D001026:Coronary Artery Bypass / Q000401:mortality*; D016002:Discriminant Analysis; D005260:Female; D005544:Forecasting; D017052:Hospital Mortality; D006801:Humans; D007256:Information Systems; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D015233:Models, Statistical; D011446:Prospective Studies; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D012720:Severity of Illness Index; D016896:Treatment Outcome; D016277:Ventricular Function, Left