### Abstract:

Background Renal transplant candidates (RTC) are at increased risk for cardiovascular events (MACE). We developed a new risk-score model to predict MACE in pt with end-stage renal disease (ESRD). Methods 1,057 RTC (61% men, 53±11 years) were prospectively enrolled. The median follow-up was 16 (1 – 107) months. A logistic regression model was built from three clinically relevant co-variates as defined by the American Society of Transplantation (age, diabetes, and known CVD); the occurrence of the first or new fatal/non-fatal MACE (sudden death, acute myocardial infarction or unstable angina, stroke, peripheral artery disease, or overt heart failure) was regarded as the dependent variable. The logistic regression coefficient B for each variable was multiplied by 10 and rounded to the next whole number, allowing that, for each patient, a correspondent risk-score could be assigned. The receiver-operating-characteristic curve (ROC) was constructed to estimate the accuracy of the new-score. Finally, the prevalence of significant CAD for each risk-score was determined and a linear regression model between risk-score and the probability of MACE was calculated. Results There were 209 events during follow-up. The B coefficients for age, diabetes and CVD were 0.03, 0.62, and 0.89 (all P<.01), respectively. Thus, the risk-score could be calculated by the equation: Risk-Score = (Age * 0.3) + (DM * 6.2) + (CVD * 8.9). The respective area under the curve (ROC) was 0.70 (P=.0001) and the final equation relating the risk-score with the expected probability of the first occurrence of MACE was: Probability of MACE = (Risk-Score *1.45) – 14.2 (R2 = 0.94; P<.0001). As an example, a non-diabetic 40-year old RTC with no evidence of CVD will have an expected probability of suffering a first MACE of 3.2% whereas a 65-year old diabetic pt with peripheral artery disease will have an expected probability of 36.0%. Conclusions We developed and validated a new, simple risk-score to predict the occurrence of the first or new MACE among potential renal transplant recipients. This model should help cardiologists to better identify high-risk RTC, so that a cardiovascular risk reduction program can be aggressively implemented. ACC Moderated Poster Contributions McCormick Place South, Hall A Sunday, March 25, 2012, 11:00 a.m.-Noon Session Title: Prevention Abstract Category: 9. Prevention: Clinical Presentation Number: 1181-155