title: Predicting the occurrence of adverse events after coronary artery bypass surgery.
abstract: OBJECTIVE
  To determine whether adverse events occurring after coronary artery bypass surgery in Medicare patients can be predicted from clinical variables representing illness severity at admission.
  
  
  METHODS
  Retrospective analysis of clinical data abstracted from hospital charts, with development and validation using half-samples of the database. A logistic model was developed using illness severity at admission to predict the occurrence of an adverse event after bypass surgery.
  
  
  METHODS
  Hospitals in seven states.
  
  
  METHODS
  Random sample of 2213 Medicare patients 65 years of age or more who underwent bypass surgery between January 1985 and June 1986.
  
  
  METHODS
  The occurrence of death within 30 days of admission or any of 13 nonfatal postoperative adverse events (for example, myocardial infarction, congestive heart failure, and wound infection).
  
  
  RESULTS
  Thirty-three percent of patients had one or more postoperative adverse events or died within 30 days of admission. Mortality within 30 days of admission was 6.6%; each adverse event was associated with increased mortality (range, 7.5% to 66.7%). Admission predictors of the occurrence of an adverse event included a history of bypass surgery, emergent surgery, a history of chronic obstructive pulmonary disease, the presence of an infiltrate on admission chest radiograph, a pulse of 110 beats/min or more, age, blood urea nitrogen of 10.7 mmol/L (30 mg/dL) or more, acute myocardial infarction at admission, and a history of myocardial infarction; the presence of one- or two-vessel disease was negatively associated with the occurrence of an adverse event. The model c-statistic was 0.64.
  
  
  CONCLUSIONS
  Severity of illness at admission has modest predictive power with respect to adverse-event occurrence in Medicare patients who undergo bypass surgery.
authors.affiliation: Boston University Medical Center, Massachusetts.
authors.forename: J M
authors.initials: JM
authors.lastname: Geraci
authors.forename: A K
authors.initials: AK
authors.lastname: Rosen
authors.forename: A S
authors.initials: AS
authors.lastname: Ash
authors.forename: K J
authors.initials: KJ
authors.lastname: McNiff
authors.forename: M A
authors.initials: MA
authors.lastname: Moskowitz
mesh_terms: D000368:Aged; D001026:Coronary Artery Bypass / Q000009:adverse effects* / Q000401:mortality; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D006278:Medicare; D015995:Prevalence; D011787:Quality of Health Care; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index; D014481:United States