title: Risk stratification for long-term mortality after percutaneous coronary intervention.
abstract: BACKGROUND
  A simple risk score to predict long-term mortality after percutaneous coronary intervention (PCI) using preprocedural risk factors is currently not available. In this study, we created one by simplifying the results of a Cox proportional hazards model.
  
  
  RESULTS
  A total of 11,897 patients who underwent PCI from October through December 2003 in New York State were randomly divided into derivation and validation samples. Patients' vital statuses were tracked using the National Death Index through the end of 2008. A Cox proportional hazards model was fit to predict death after PCI using the derivation sample, and a simplified risk score was created. The Cox model identified 12 separate risk factors for mortality including older age, extreme body mass indexes, multivessel disease, a lower ejection fraction, unstable hemodynamic state or shock, several comorbidities (cerebrovascular disease, peripheral vascular disease, congestive heart failure, chronic obstructive pulmonary disease, diabetes mellitus, and renal failure), and a history of coronary artery bypass graft surgery. The C statistics of this model when applied to the validation sample were 0.787, 0.785, and 0.773 for risks of death within 1, 3, and 5 years after PCI, respectively. In addition, the point-based risk score demonstrated good agreement between patients' observed and predicted risks of death.
  
  
  CONCLUSIONS
  A simple risk score created from a more complicated Cox proportional hazards model can be used to accurately predict a patient's risk of long-term mortality after PCI.
authors.affiliation: From the Penn State Hershey College of Medicine, Hershey, PA (C.W., F.T.C.); St. Joseph's Health System, Atlanta, GA (S.B.K.); Johns Hopkins Medical Center, Baltimore, MD (G.W.); Mayo Clinic, Rochester, MN (D.R.H.); United Health Services, Binghamton, NY (N.J.S.); Geisinger Health System, Danville, PA (P.B.B.); Mt. Sinai Medical Center, New York, NY (S.S.); Yale University School of Medicine, New Haven, CT (J.P.C.); Albany Medical College, Albany, NY (F.J.V.); Boston Medical Center, Boston, MA (A.K.J.); and University at Albany, State University of New York, Albany, NY (E.L.H.).
authors.forename: Chuntao
authors.initials: C
authors.lastname: Wu
authors.forename: Fabian T
authors.initials: FT
authors.lastname: Camacho
authors.forename: Spencer B
authors.initials: SB
authors.lastname: King
authors.forename: Gary
authors.initials: G
authors.lastname: Walford
authors.forename: David R
authors.initials: DR
authors.lastname: Holmes
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Stamato
authors.forename: Peter B
authors.initials: PB
authors.lastname: Berger
authors.forename: Samin
authors.initials: S
authors.lastname: Sharma
authors.forename: Jeptha P
authors.initials: JP
authors.lastname: Curtis
authors.forename: Ferdinand J
authors.initials: FJ
authors.lastname: Venditti
authors.forename: Alice K
authors.initials: AK
authors.lastname: Jacobs
authors.forename: Edward L
authors.initials: EL
authors.lastname: Hannan
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D015331:Cohort Studies; D015897:Comorbidity; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000453:epidemiology* / Q000601:surgery; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D009518:New York; D062645:Percutaneous Coronary Intervention / Q000401:mortality; D011379:Prognosis; D016016:Proportional Hazards Models; D020379:Risk Adjustment; D012307:Risk Factors; D016019:Survival Analysis; D013997:Time Factors
keywords: follow-up studies; mortality; percutaneous coronary intervention