title: Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients.
abstract: OBJECTIVE
  This study was undertaken to evaluate the accuracy of four different risk-adjusted models in predicting mortality in individual patients who are undergoing coronary artery by-pass graft surgery. In the last decade several models to stratify patients before open heart surgery, according to factors affecting mortality, were developed with the aim of retrospectively comparing outcomes of open heart surgery, based on reliable stratification of case-mix, and of prospectively identifying high risk patients as a basis for a meaningful informed consent for patients counseling.
  
  
  METHODS
  The pre-operative risk of death was calculated with four different models in 418 consecutive patients who underwent coronary artery by-pass surgery and then compared with the actual outcome. To discriminate patients with favorable and unfavorable outcome, the logistic regression analysis and the areas under the receiver-operating-characteristic curves were applied. The accuracy score was used to evaluate the reliability of each score to predict the individual outcome.
  
  
  RESULTS
  Seven deaths (1.7%) were observed within 30 days from the operation, and the overall incidence was similar to that predicted by all models. Only the NBI score was not able to discriminate survivors from patients who will die, and the areas under the curves were 0.596 for the Parsonnet score, 0.861 for the Cleveland Clinic Foundation score, 0.823 for the French score, and 0.806 for the EuroSCORE. The four models were highly accurate (between 0.97 and 0.98) to predict the overall mortality. In seven patients who died the mean predictive scores were very low and ranged between 2.1 and 4.6, but were significantly higher than those of patients who survived (between 1.1 and 2.2).
  
  
  CONCLUSIONS
  The four pre-surgical predictive models were similarly able to discriminate favorable vs. unfavorable outcomes and highly accurate to predict overall mortality, but very inaccurate to predict mortality in individual patients.
authors.affiliation: Arturo Pinna Pintor Foundation, Via A. Vespucci 61, 10129 Turin, Italy. fappto@tin.it
authors.forename: P
authors.initials: P
authors.lastname: Pinna-Pintor
authors.forename: M
authors.initials: M
authors.lastname: Bobbio
authors.forename: S
authors.initials: S
authors.lastname: Colangelo
authors.forename: F
authors.initials: F
authors.lastname: Veglia
authors.forename: M
authors.initials: M
authors.lastname: Giammaria
authors.forename: D
authors.initials: D
authors.lastname: Cuni
authors.forename: F
authors.initials: F
authors.lastname: Maisano
authors.forename: O
authors.initials: O
authors.lastname: Alfieri
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D015331:Cohort Studies; D001026:Coronary Artery Bypass / Q000379:methods* / Q000401:mortality*; D003324:Coronary Artery Disease / Q000175:diagnosis / Q000401:mortality / Q000601:surgery*; D005260:Female; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D007558:Italy / Q000453:epidemiology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D011300:Preoperative Care; D011336:Probability; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D017678:Sex Distribution; D016019:Survival Analysis