title: Incorporating glomerular filtration rate or creatinine clearance by the modification of diet in renal disease equation or the Cockcroft-Gault equations to improve the global accuracy of the Age, Creatinine, Ejection Fraction [ACEF] score in patients undergoing percutaneous coronary intervention.
abstract: BACKGROUND
  The aim of the present study was to appraise the comparative ability of different ACEF models incorporating glomerular filtration rate or creatinine clearance estimated by the Modification of Diet in Renal Disease [ACEFMDRD] or Cokcroft-Gault [ACEFCG] equations, respectively, over the original ACEF score (ACEFSrCr) in patients undergoing percutaneous coronary intervention (PCI).
  
  
  METHODS
  A total of 537 patients were analyzed by different measures of discrimination, calibration and net reclassification improvement (NRI).
  
  
  RESULTS
  A significant gradient in all-cause mortality was consistently seen with all the models at 30 days, 1 year and 5 years. The comparison of the three models showed that the best balance in terms of discrimination and calibration for all-cause mortality was offered by the ACEFCG at 30 days, the ACEFMDRD at 1 year and similarly by the ACEFCG and ACEFMDRD at 5 years. At 30 days, the NRI was +32.9% for ACEFMDRD over ACEFSrCr and +16% for ACEFCG over ACEFSrCr. At 1 year, the NRI was 13.8% for ACEFMDRD over ACEFSrCr and -7.8% for ACEFCG over ACEFSrCr. At 5 years, the NRI was +7.7% for both the ACEFMDRD and the ACEFCG over the ACEFSrCr.
  
  
  CONCLUSIONS
  In patients undergoing PCI, the ACEF score is associated with satisfactory early-, mid- and long-term discrimination regardless of the definition of renal function. However, incorporating glomerular filtration rate or creatinine clearance by the MDRD or CG formulas in the ACEF score yields superior calibration compared with the original SrCr-based equation, with the ACEFMDRD displaying superior reclassification ability over the ACEFCG and ACEFSrCr at 30 days and 1 year.
authors.affiliation: Cardiovascular Department, Ferrarotto Hospital, Catania, Italy. dcapodanno@gmail.com
authors.forename: Davide
authors.initials: D
authors.lastname: Capodanno
authors.forename: Carmelita
authors.initials: C
authors.lastname: Marcantoni
authors.forename: Margherita
authors.initials: M
authors.lastname: Ministeri
authors.forename: Fabio
authors.initials: F
authors.lastname: Dipasqua
authors.forename: Luca
authors.initials: L
authors.lastname: Zanoli
authors.forename: Stefania
authors.initials: S
authors.lastname: Rastelli
authors.forename: Sarah
authors.initials: S
authors.lastname: Mangiafico
authors.forename: Maria
authors.initials: M
authors.lastname: Sanfilippo
authors.forename: Gaetano
authors.initials: G
authors.lastname: Romano
authors.forename: Corrado
authors.initials: C
authors.lastname: Tamburino
mesh_terms: D000367:Age Factors; D000368:Aged; D015331:Cohort Studies; D003404:Creatinine / Q000378:metabolism*; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D007674:Kidney Diseases / Q000175:diagnosis / Q000378:metabolism* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D062645:Percutaneous Coronary Intervention / Q000639:trends*; D012720:Severity of Illness Index; D013318:Stroke Volume / Q000502:physiology*; D013997:Time Factors
chemical_list: D003404:Creatinine