10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Pre-Transplant Cardiovascular Risk Factors Affect Kidney Allograft Survival: A Multi-Center Study in Korea

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Pre-transplant cardiovascular (CV) risk factors affect the development of CV events even after successful kidney transplantation (KT). However, the impact of pre-transplant CV risk factors on allograft failure (GF) has not been reported.

          Methods and Findings

          We analyzed the graft outcomes of 2,902 KT recipients who were enrolled in a multi-center cohort from 1997 to 2012. We calculated the pre-transplant CV risk scores based on the Framingham risk model using age, gender, total cholesterol level, smoking status, and history of hypertension. Vascular disease (a composite of ischemic heart disease, peripheral vascular disease, and cerebrovascular disease) was noted in 6.5% of the patients. During the median follow-up of 6.4 years, 286 (9.9%) patients had developed GF. In the multivariable-adjusted Cox proportional hazard model, pre-transplant vascular disease was associated with an increased risk of GF (HR 2.51; 95% CI 1.66–3.80). The HR for GF (comparing the highest with the lowest tertile regarding the pre-transplant CV risk scores) was 1.65 (95% CI 1.22–2.23). In the competing risk model, both pre-transplant vascular disease and CV risk score were independent risk factors for GF. Moreover, the addition of the CV risk score, the pre-transplant vascular disease, or both had a better predictability for GF compared to the traditional GF risk factors.

          Conclusions

          In conclusion, both vascular disease and pre-transplant CV risk score were independently associated with GF in this multi-center study. Pre-transplant CV risk assessments could be useful in predicting GF in KT recipients.

          Related collections

          Most cited references19

          • Record: found
          • Abstract: found
          • Article: not found

          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Patient survival and cardiovascular risk after kidney transplantation: the challenge of diabetes.

            An increasing proportion of kidney recipients have diabetes mellitus (DM). Herein, we assessed the impact of DM on morbidity and mortality. The study included 933 recipients of first transplants. DM was present in 212 (23%). Compared to non-diabetics (NoDM), DM were older, heavier and had more pretransplant cardiovascular (CV) disease (16% vs. 48%, p < 0.0001). DM had reduced survival (5 years, 93% vs. 70%, p < 0.0001) and higher incidence of CV events (9% vs. 37%, p < 0.0001). CV disease was the most common cause of death in DM (61%) but not in NoDM (26%). Mortality from infections was also higher in DM (p = 0.001). In NoDM, survival related to recipient age (hazard ratio (HR) = 1.07, p < 0.0001) and dialysis pretransplant HR = 2.21, p = 0.01, while in DM, survival related to dialysis (HR = 2.89, p = 0.01) and pretransplant CV disease (HR = 2.79, p = 0.007). In NoDM, the incidence of posttransplant CV events was related to traditional CV risk factors, while in DM only the pretransplant CV history related to this outcome. In conclusion, survival differs between NoDM and DM recipients quantitatively, by cause of death and by risk factors. In NoDM, survival is excellent, and the main threat to survival relates to immunosuppression. In DM, survival is inferior primarily due to CV disease generally present prior to transplantation.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Risk factors for accelerated atherosclerosis in renal transplant recipients.

              The factors responsible for atherosclerosis in renal transplant recipients are not known. In the present study, cardiovascular disease was investigated in 403 patients who received 464 kidney transplants during a 10-year period. Among those who had no clinical evidence of vascular disease at the time of transplantation, atherosclerotic complications developed in 15.8 percent during the post-transplant follow-up period (46.1 +/- 36.2 months). Pre- and post-transplant vascular diseases were closely linked. However, after taking pre-transplant vascular disease into account, multivariate analysis showed that a number of known risk factors (age, sex, diabetes, cigarette smoking, hypertension, and serum cholesterol) were independently associated with post-transplant vascular disease. In addition, the number of acute rejection episodes (all treated with high doses of corticosteroids) was also independently linked to vascular disease. These results suggest that an increased prevalence of known risk factors, and events linked to allograft rejection, explain the high incidence of cardiovascular disease in renal transplant recipients.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 August 2016
                2016
                : 11
                : 8
                : e0160607
                Affiliations
                [1 ]Division of Nephrology, Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
                [2 ]Department of Critical Care Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
                [3 ]Department of Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, Gangwon-do, Korea
                [4 ]Department of Internal Medicine, Gyeongsang National University Hospital, Changwon, Korea
                [5 ]Division of Nephrology, Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
                [6 ]Division of Cardiology, Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
                [7 ]Division of Cardiology, Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
                [8 ]Department of Surgery, Asan Medical Center and University of Ulsan College of Medicine, Seoul, Korea
                University of Edinburgh MRC Centre for Inflammation Research, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: JNA SVA JPL YHK CSL.

                • Data curation: JNA SVA YSK YHK CSL.

                • Formal analysis: JNA SVA JPL.

                • Investigation: JNA SVA EB EK.

                • Methodology: JNA SVA JPL.

                • Resources: JNA SVA HLK YJK YKO.

                • Software: SVA.

                • Supervision: YHK CSL.

                • Visualization: JNA SVA.

                • Writing - original draft: JNA SVA.

                • Writing - review & editing: JNA SVA YHK CSL.

                Article
                PONE-D-16-16276
                10.1371/journal.pone.0160607
                4976895
                27501048
                b38a4fa0-9cb1-426e-9673-2f13555c165d
                © 2016 An et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 April 2016
                : 21 July 2016
                Page count
                Figures: 2, Tables: 5, Pages: 12
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Vascular Medicine
                Vascular Diseases
                Medicine and Health Sciences
                Health Care
                Health Risk Analysis
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Hypertension
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                Medicine and Health Sciences
                Women's Health
                Biology and Life Sciences
                Biochemistry
                Lipids
                Cholesterol
                Medicine and Health Sciences
                Nephrology
                Glomerulonephritis
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article