Contribution of impaired renal function to cardiovascular risk prediction models in renal transplant recipients Benguzzi M, Mansell H, Hassan A, Elmoselhi H, Mainra R, Shoker A. Contribution of impaired renal function to cardiovascular risk prediction models in renal transplant recipients. Abstract: Background: The Framingham risk score (FRS) and cardiovascular risk calculator for renal transplant recipients (CRCRTR- MACE) quantify cardiovascular risk in renal transplant recipients (RTR). In contrast to the FRS, the CRCRTR-MACE includes serum creatinine as a variable in the risk prediction equation. Objective: To determine the influence of impaired renal function on performances of the two equations. Methods: A chart review of 270 RTR transplanted from 1979 to 2012. High risk was defined at scores ≥20%. Standard statistical analyses included multivariate analysis (MVA), stepwise analysis, and odds ratio to estimate contributions of risk factors. Results: Mean transplant duration was 9.51 Æ 6.65 yr. Mean eGFR was 59.19 Æ 28.26 mL/min/1.73 m 2 . FRS and CRCRTR-MACE scores of least 20% were present in 9.3% and 24.8%, respectively, while 7.2% and 11.2% of RTR with eGFR ≥60 mL/min/1.73 m 2 were high risk, respectively. Mean age, blood pressure, TC:HDL ratio, smoking, and diabetes were evenly distributed in patients with varying eGFR. FRS scores remained similar at wide eGFR range (≤30 mL/min/ 1.73 m 2 –≥90 mL/min/1.73 m 2 ), while CRCRTR-MACE scores significantly increased as eGFR decreased. Conclusions: CRCRTR-MACE identified more patients at high cardiovascular risk, even in those with more favorable renal function, suggesting a fundamental difference between the two calculators beyond renal function. Mowad Benguzzi a , Holly Mansell b , Abubakar Hassan b , Hamdi Elmoselhi b , Rahul Mainra b and Ahmed Shoker a,b,c a University of Saskatchewan, College of Medicine, b St. Paul’s Hospital, Saskatchewan Renal Transplant Program and c Department of Medicine, University of Saskatchewan, Saskatoon, SK, Canada Key words: cardiovascular events – cardiovascular risk factors – Framingham risk score – GFR – kidney transplantation – MACE Corresponding author: Ahmed Shoker, St. Paul’s Hospital, Saskatchewan Renal Transplant Program, 1702 20th Street West, Saskatoon, SK, S7M 0Z9. Tel.: 306-655-5934; fax: 306-655-5959; e-mail: ahmed.shoker@usask.ca Conflict of Interest: None. Accepted for publication 17 September 2014 Cardiovascular disease (CVD), a leading cause of morbidity and mortality, remains a significant challenge before and after kidney transplantation (1). Both traditional risk factors (such as hyperten- sion, weight gain, DM, and hyperlipidemia) and non-traditional risk factors (such as impaired renal transplant function) are believed to impart cardio- vascular risk (2, 3). As global screening of total burden of risk assists in predicting future cardio- vascular events and tailoring preventative therapy, researchers have attempted to develop, modify, and validate prediction risk scores in kidney trans- plant recipients (4). The Framingham Heart study has generated risk prediction algorithms from the general population based on traditional risk fac- tors (5, 6). These factors (age, gender, blood pres- sure, HDL cholesterol, diabetes, smoking history) are common among renal transplant recipients (RTR). The negative impact of impaired renal function on CVE is well known (7) and has been extensively reviewed by Sarnak (8). It is confounded by the increased prevalence of traditional risk factors in patients with impaired renal function (9). Many researchers will argue, however, that the effect of diminished eGFR on CVD cannot be explained by traditional factors alone (10, 11), and this has sparked the search for non-traditional risk causes. The relative contribution of increased traditional risk versus impaired renal function has come to the forefront of research to define the relative contri- butions of increased traditional risks versus impaired renal function on CVD scores and CVE (11). 1383 © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Clin Transplant 2014: 28: 1383–1392 DOI: 10.1111/ctr.12466 Clinical Transplantation