Cardiovascular Risk Assessment and Management in Prerenal Transplantation Candidates

Am J Cardiol. 2016 Jan 1;117(1):146-50. doi: 10.1016/j.amjcard.2015.10.016. Epub 2015 Oct 17.

Abstract

Cardiovascular (CV) assessment in prerenal transplant patients varies by center. Current guidelines recommend stress testing for candidates if ≥ 3 CV risk factors exist. We evaluated the CV assessment and management in 685 patients referred for kidney transplant over a 7-year period. All patients had CV risk factors, and the most common cause of end-stage renal disease was diabetes. Thirty-three percent (n = 229) underwent coronary angiography. The sensitivity of stress testing to detect obstructive coronary artery disease (CAD) was poor (0.26). Patients who had no CAD, nonobstructive CAD, or CAD with intervention had significantly higher event-free survival compared with patients with obstructive CAD without intervention. There were no adverse clinical events (death, myocardial infarction, stroke, revascularization, and graft failure) within 30 days post-transplant in patients who had preoperative angiography (n = 77). Of the transplanted patients who did not have an angiogram (n = 289), there were 8 clinical events (6 myocardial infarctions) in the first 30 days. In conclusion, our results indicate that stress testing and usual risk factors were poor predictors of obstructive CAD and that revascularization may prove beneficial in these patients.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Angiography / methods
  • Cardiovascular Diseases / diagnosis*
  • Cardiovascular Diseases / epidemiology
  • Cardiovascular Diseases / etiology
  • Disease Management*
  • Exercise Test
  • Female
  • Follow-Up Studies
  • Humans
  • Kidney Failure, Chronic / complications
  • Kidney Failure, Chronic / surgery*
  • Kidney Transplantation*
  • Male
  • Middle Aged
  • Morbidity / trends
  • Preoperative Care / methods*
  • Risk Assessment / methods*
  • Risk Factors
  • Survival Rate / trends
  • Time Factors
  • Utah / epidemiology