title: Bedside estimation of risk from percutaneous coronary intervention: the new Mayo Clinic risk scores.
abstract: OBJECTIVE
  To derive risk models for percutaneous coronary intervention (PCI) outcomes from clinical and laboratory variables available before the procedure so they can be used for preprocedure risk stratification.
  
  
  METHODS
  Using the Mayo Clinic registry, we analyzed 9035 PCIs on 7640 unique patients from January 1, 2000, through April 30, 2005. We included only the first PCI per patient (n=7457). Logistic regression was used to model the calculated risk score and major procedural complications. Separate risk models were made for mortality and major adverse cardiovascular events (MACE) derived solely from baseline and laboratory characteristics. Final risk scores for procedural death, defined as any death during the index hospitalization, and MACE contained the same 7 variables (age, myocardial infarction less than or equal to 24 hours, preprocedural shock, serum creatinine level, left ventricular ejection fraction, congestive heart failure, and peripheral artery disease).
  
  
  RESULTS
  Models had adequate goodness of fit, and areas under the receiver operating characteristic curve were 0.74 and 0.89 for MACE and procedural death, respectively, indicating excellent overall discrimination. The model was robust across many subgroups, including those undergoing elective PCI, those having diabetes mellitus, and elderly patients. Bootstrap analysis indicated that the model was not overfit to the available data set.
  
  
  CONCLUSIONS
  Before coronary angiography is performed, a risk-scoring system based on 7 variables can be used conveniently to predict cardiovascular complications after PCI. This model may be useful for providing patients with individualized, evidence-based estimates of procedural risk as part of the informed consent process.
authors.affiliation: Division of Cardiovascular Diseases, College of Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. singh.mandeep@mayo.edu
authors.forename: Mandeep
authors.initials: M
authors.lastname: Singh
authors.forename: Charanjit S
authors.initials: CS
authors.lastname: Rihal
authors.forename: Ryan J
authors.initials: RJ
authors.lastname: Lennon
authors.forename: John
authors.initials: J
authors.lastname: Spertus
authors.forename: John S
authors.initials: JS
authors.lastname: Rumsfeld
authors.forename: David R
authors.initials: DR
authors.lastname: Holmes
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015906:Angioplasty, Balloon, Coronary / Q000009:adverse effects* / Q000706:statistics & numerical data; D002318:Cardiovascular Diseases / Q000401:mortality / Q000628:therapy*; D003404:Creatinine / Q000097:blood; D005260:Female; D006304:Health Status; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D019095:Point-of-Care Systems; D011379:Prognosis; D012042:Registries; D018570:Risk Assessment
chemical_list: D003404:Creatinine