title: Renal function and risk stratification of diabetic and nondiabetic patients undergoing evaluation for coronary artery disease.
abstract: OBJECTIVE
  The aim of this study was to evaluate the impact of renal function by estimated glomerular filtration rate (eGFR) on risk stratification of diabetic and nondiabetic patients undergoing myocardial perfusion imaging (MPI) by single-photon emission computed tomography for suspected ischemia.
  
  
  BACKGROUND
  Coronary artery disease is the leading cause of death among diabetic persons; however, diabetic persons are a very heterogeneous group in terms of cardiovascular risk, necessitating further risk stratification.
  
  
  METHODS
  Patients (n = 1,747, age 65 +/- 10 years, 37% diabetic) undergoing MPI were followed for cardiac death (CD) for a mean of 2.15 +/- 0.8 years. Chronic kidney disease (CKD) was defined by an eGFR <60 ml/min.
  
  
  RESULTS
  In the presence of a normal scan, annual CD rate was 0.9% for those with no diabetes mellitus (DM) and no CKD, 0.5% in the DM alone group, 2.35% in CKD alone, and 2.9% in those with both DM and CKD (p < 0.001). Patients with DM+CKD had a 2.7-fold risk of CD compared with no DM no CKD (p = 0.001) after controlling for age, ejection fraction, history of coronary artery disease, and other risk factors. The risk of CD increased as a function of the presence and severity of perfusion defects, regardless of CKD or DM status. Presence of CKD conferred a several-fold higher risk of CD for the various strata of perfusion defects. Log-rank test for difference in probability of CD was nonsignificant for comparison between patients with no DM no CKD and those with DM alone (p = 0.73) but was significant for comparison between patients with no DM no CKD and patients with CKD alone (p < 0.001) or DM+CKD (p < 0.001).
  
  
  CONCLUSIONS
  MPI and eGFR provide valuable risk stratification for diabetic and nondiabetic patients. Diabetic patients without CKD seem to have similar short-term cardiac outcomes compared with nondiabetic patients. Underlying CKD seems to identify a high-risk subgroup of diabetic patients.
authors.affiliation: Division of Cardiovascular Diseases, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA. ahakeem@gmail.com
authors.forename: Abdul
authors.initials: A
authors.lastname: Hakeem
authors.forename: Sabha
authors.initials: S
authors.lastname: Bhatti
authors.forename: Kunal N
authors.initials: KN
authors.lastname: Karmali
authors.forename: Kathryn S
authors.initials: KS
authors.lastname: Dillie
authors.forename: Jeffrey R
authors.initials: JR
authors.lastname: Cook
authors.forename: Jiaqiong
authors.initials: J
authors.lastname: Xu
authors.forename: Zainab
authors.initials: Z
authors.lastname: Samad
authors.forename: Su Min
authors.initials: SM
authors.lastname: Chang
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002318:Cardiovascular Diseases / Q000209:etiology* / Q000401:mortality / Q000503:physiopathology; D016009:Chi-Square Distribution; D002908:Chronic Disease; D003324:Coronary Artery Disease / Q000150:complications / Q000000981:diagnostic imaging* / Q000401:mortality; D048909:Diabetes Complications / Q000209:etiology* / Q000401:mortality / Q000503:physiopathology; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D053208:Kaplan-Meier Estimate; D007668:Kidney / Q000503:physiopathology*; D007674:Kidney Diseases / Q000150:complications* / Q000401:mortality / Q000503:physiopathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D016017:Odds Ratio; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D013997:Time Factors; D015899:Tomography, Emission-Computed, Single-Photon; D014728:Veterans