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Can Cardiac Risk Predictor Models Be Trusted in Kidney Transplant Recipients?

K. L. Hoffman1, R. R. Alloway1, A. Shields2, E. Woodle2, A. Govil1

1Nephrology & Transplant Medicine, University of Cincinnati, Cincinnati, OH, 2Transplant Surgery, University of Cincinnati, Cincinnati, OH

Meeting: 2019 American Transplant Congress

Abstract number: 537

Keywords: Heart, Kidney transplantation, Outcome, Prediction models

Session Information

Date: Tuesday, June 4, 2019

Session Name: Concurrent Session: Kidney: Cardiovascular and Metabolic III

Session Time: 4:30pm-6:00pm

 Presentation Time: 4:42pm-4:54pm

Location: Ballroom C

Related Abstracts
  • Validation of a Simplified Cost-Effective Clinical Risk Stratification That Predicts Myocardial Ischemic Events in Kidney Transplant Candidates.
  • Cardiac Risk Assessment in Kidney Transplant Candidates: Clinical Usefulness of Different Guidelines

*Purpose: Kidney transplant recipients (KTR) bear a higher risk of developing cardiovascular disease due to comorbid conditions. Non-invasive cardiovascular risk stratification tools have not been validated in this population. The purpose of this study is to predict cardiovascular events (CVE) at 1 and 3 years post-transplant for KTR using Framingham Risk Score (FRS) and Revised Cardiac Risk Index (RCRI), measures commonly used in the general population to measure 10 year cardiovascular risk to estimate perioperative surgical risk, respectively.

*Methods: 231 KTR (91 living- and 140 deceased- donor allografts) between 2001 to 2011 were reviewed. FRS tool was applied to the subject’s baseline data findings, and the RCRI was calculated using both pre- and immediate post-transplant serum creatinine. The data evaluated each participant at 1 and 3 year post-transplant timeframe to assess for a cardiovascular event or death. This cohort included pre-surgical CVE risks of BMI> 35 (33), known coronary disease (42), smoking (23), total cholesterol >200 (40), hypertension (183) and diabetes on insulin (79). The hypotheses were tested using t-tests with a p-value < 0.05 for significance.

*Results: Eighteen deaths and 43 CVE were observed. FRS and RCRI (utilizing pre-transplant creatinine) were unable to predict CVE or mortality at 1 or 3 years post-transplant. RCRI (utilizing post-transplant creatinine) was not statistically significant for CVE or death at one year. At 3 years, RCRI was not substantial for death but did show a significant prediction of CVE (p = < 0.05).

*Conclusions: This data identifies the potential for RCRI to measure CVE risks outside of the perioperative timeframe at 1 and 3 years with predictability at the 3 year time point. FRS was unable to significantly predict CVE at 1 and 3 years in this sample. Longer follow-up is necessary to accurately assess both mortality and CVE. Studies using these and other cardiovascular risk tools prospectively could yield a credible non-invasive approach in assessing this at-risk population.

RCRI Post and CVE 3 years
CVE3 YR Method Mean 95%CL Mean 95 %CLMean StdDev 95 % CL StdDev 95 %

CL
Std
Dev
N 1.7389 1.6266 1.8513 0.8119 0.7399 0.8996
Y 2.3000 1.7718 2.8282 1.1286 0.8583 1.6484
Diff(1-2) Pooled -0.5611 -.9508 -0.1713 0.8438 0.7720 0.9306
Diff (1-2) Satterthwaite -0.5611 -1.0991 -0.0230
Method Variance DF t Value Pr> l t l
Pooled Equal 221 -2.84 0.0050

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To cite this abstract in AMA style:

Hoffman KL, Alloway RR, Shields A, Woodle E, Govil A. Can Cardiac Risk Predictor Models Be Trusted in Kidney Transplant Recipients? [abstract]. Am J Transplant. 2019; 19 (suppl 3). https://atcmeetingabstracts.com/abstract/can-cardiac-risk-predictor-models-be-trusted-in-kidney-transplant-recipients/. Accessed February 26, 2021.

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