Dataset Information

A Comparison of Different Algorithms for the Assessment of Cardiovascular Risk in Patients at Waiting List for Kidney Transplantation.

ABSTRACT:

Background

Cardiovascular disease (CVD) is the leading cause of death after renal transplantation with a high prevalence in dialysis patients. It is still a matter of debate how to assess the cardiovascular risk in kidney transplant candidates. Several approaches and scores exist and found their way into the guidelines.

Methods and results

We herein assessed PROCAM, Framingham, ESC-SCORE and our own dedicated algorithm in patients applying for renal transplantation at our transplantation center between July 2006 and August 2009. Data of 347 consecutive patients were recorded at baseline and during a follow-up of 4.1 years regarding cardiovascular (CV) events and event-free and overall survival. During follow-up 31 (8.9%) patients died, 24 (6.9%) myocardial infarctions occurred and 19 (5.5%) patients received a new diagnosis of cerebrovascular disease. Predictors for event-free survival identified by univariable Cox regression analysis were age at start of dialysis, ESC-SCORE as well as our own score. Final multivariable model with a stepwise model building procedure revealed age at start of dialysis and smoking to be prognostic for event-free (hazard ratio 1.07/year and 2.15) and overall survival (1.10/year and 3.72).

Conclusion

Comparison of CV risk assessment scores showed that ESC-SCORE most robustly predicted event-free and overall survival in our cohort. We conclude that CV risk assessment by ESC-SCORE can be reasonably performed in kidney transplant candidates.

SUBMITTER: Reuter S

PROVIDER: S-EPMC5074508 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Comparison of Different Algorithms for the Assessment of Cardiovascular Risk in Patients at Waiting List for Kidney Transplantation.

Reuter Stefan S Reiermann Stefanie S Malyar Viola V Schütte-Nütgen Katharina K Schmidt Renè R Pavenstädt Hermann H Reinecke Holger H Suwelack Barbara B

PloS one 20161021 10

<h4>Background</h4>Cardiovascular disease (CVD) is the leading cause of death after renal transplantation with a high prevalence in dialysis patients. It is still a matter of debate how to assess the cardiovascular risk in kidney transplant candidates. Several approaches and scores exist and found their way into the guidelines.<h4>Methods and results</h4>We herein assessed PROCAM, Framingham, ESC-SCORE and our own dedicated algorithm in patients applying for renal transplantation at our transpla ...[more]

PMID: 27768693

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Project description:BACKGROUND:Patients on organ transplant waiting lists are evaluated for preexisting alloimmunity to minimize episodes of acute and chronic rejection by regularly monitoring for changes in alloimmune status. There are few studies on how alloimmunity changes over time in patients on kidney allograft waiting lists, and an apparent lack of research-based evidence supporting currently used monitoring intervals. METHODS:To investigate the dynamics of alloimmune responses directed at HLA antigens, we retrospectively evaluated data on anti-HLA antibodies measured by the single-antigen bead assay from 627 waitlisted patients who subsequently received a kidney transplant at University Hospital Zurich, Switzerland, between 2008 and 2017. Our analysis focused on a filtered dataset comprising 467 patients who had at least two assay measurements. RESULTS:Within the filtered dataset, we analyzed potential changes in mean fluorescence intensity values (reflecting bound anti-HLA antibodies) between consecutive measurements for individual patients in relation to the time interval between measurements. Using multiple approaches, we found no correlation between these two factors. However, when we stratified the dataset on the basis of documented previous immunizing events (transplant, pregnancy, or transfusion), we found significant differences in the magnitude of change in alloimmune status, especially among patients with a previous transplant versus patients without such a history. Further efforts to cluster patients according to statistical properties related to alloimmune status kinetics were unsuccessful, indicating considerable complexity in individual variability. CONCLUSIONS:Alloimmune kinetics in patients on a kidney transplant waiting list do not appear to be related to the interval between measurements, but are instead associated with alloimmunization history. This suggests that an individualized strategy for alloimmune status monitoring may be preferable to currently used intervals.

Project description:BACKGROUND: Cardiovascular disease (CVD) is the major cause of death after renal transplantation. Not only conventional CVD risk factors, but also transplant-specific risk factors can influence the development of CVD in kidney transplant recipients. The main objective of this study will be to determine the incidence of post-transplant CVD after renal transplantation and related factors. A secondary objective will be to examine the ability of standard cardiovascular risk scores (Framingham, REGICOR, SCORE, and DORICA) to predict post-transplantation cardiovascular events in renal transplant recipients, and to develop a new score for predicting the risk of CVD after kidney transplantation. METHODS/DESIGN: Observational prospective cohort study of all kidney transplant recipients in the A Coruna Hospital (Spain) in the period 1981-2008 (2059 transplants corresponding to 1794 patients). The variables included will be: donor and recipient characteristics, chronic kidney disease-related risk factors, pre-transplant and post-transplant cardiovascular risk factors, routine biochemistry, and immunosuppressive, antihypertensive and lipid-lowering treatment. The events studied in the follow-up will be: patient and graft survival, acute rejection episodes and cardiovascular events (myocardial infarction, invasive coronary artery therapy, cerebral vascular events, new-onset angina, congestive heart failure, rhythm disturbances and peripheral vascular disease). Four cardiovascular risk scores were calculated at the time of transplantation: the Framingham score, the European Systematic Coronary Risk Evaluation (SCORE) equation, and the REGICOR (Registre Gironi del COR (Gerona Heart Registry)), and DORICA (Dyslipidemia, Obesity, and Cardiovascular Risk) functions. The cumulative incidence of cardiovascular events will be analyzed by competing risk survival methods. The clinical relevance of different variables will be calculated using the ARR (Absolute Risk Reduction), RRR (Relative Risk Reduction) and NNT (Number Needed to Treat). The ability of different cardiovascular risk scores to predict cardiovascular events will be analyzed by using the c index and the area under ROC curves. Based on the competing risks analysis, a nomogram to predict the probability of cardiovascular events after kidney transplantation will be developed. DISCUSSION: This study will make it possible to determine the post-transplant incidence of cardiovascular events in a large cohort of renal transplant recipients in Spain, to confirm the relationship between traditional and transplant-specific cardiovascular risk factors and CVD, and to develop a score to predict the risk of CVD in these patients.

Project description:Background and aimsThe Model for End-Stage Liver Disease (MELD) is used for clinical decision-making and organ allocation for orthotopic liver transplantation (OLT) and was previously upgraded through inclusion of serum sodium (Na) concentrations (MELD-Na). However, MELD-Na may underestimate complications arising from portal hypertension or infection. The von Willebrand factor (vWF) antigen (vWF-Ag) correlates with portal pressure and seems capable of predicting complications in patients with cirrhosis. Accordingly, this study aimed to evaluate vWF-Ag as an adjunct surrogate marker for risk stratification on the waiting list for OLT.Approach and resultsHence, WF-Ag at time of listing was assessed in patients listed for OLT. Clinical characteristics, MELD-Na, and mortality on the waiting list were recorded. Prediction of 3-month waiting-list survival was assessed by receiver operating characteristics and net reclassification improvement. Interestingly, patients dying within 3 months on the waiting list displayed elevated levels of vWF-Ag (P < 0.001). MELD-Na and vWF-Ag were comparable and independent in their predictive potential for 3-month mortality on the waiting list (area under the curve [AUC], vWF-Ag = 0.739; MELD-Na = 0.764). Importantly, a vWF-Ag cutoff at 413% identified patients at risk for death within 3 months of listing with a higher odds ratio (OR) than the previously published cutoff at a MELD-Na of 20 points (vWF-Ag, OR = 10.873, 95% confidence interval [CI], 3.160, 36.084; MELD-Na, OR = 7.594, 95% CI, 2.578, 22.372; P < 0.001, respectively). Ultimately, inclusion of vWF-Ag into the MELD-Na equation significantly improved prediction of 3-month waiting-list mortality (AUC, MELD-Na-vWF = 0.804).ConclusionsA single measurement of vWF-Ag at listing for OLT predicts early mortality. Combining vWF-Ag levels with MELD-Na improves risk stratification and may help to prioritize organ allocation to decrease waiting-list mortality.

Project description:ImportanceWith continuing improvements in medical devices and more than a decade since the 2006 United Network for Organ Sharing (UNOS) allocation policy, it is pertinent to assess survival among patients on the heart transplantation waiting list, especially given the recently approved 2018 UNOS allocation policy.ObjectivesTo assess survival outcomes among patients on the heart transplant waiting list during the past 3 decades and to examine the association of ventricular assist devices (VADs) and the 2006 UNOS allocation policy with survival.Design, setting, and participantsA retrospective cross-sectional used the UNOS database to perform an analysis of 95 323 candidates wait-listed for heart transplantation between January 1, 1987, and December 29, 2017. Candidates for all types of combined transplants were excluded (n = 2087). Patients were followed up from the time of listing to death, transplantation, or removal from the list due to clinical improvement. Competing-risk, Kaplan-Meier, and multivariable Cox proportional hazards regression analyses were used.Main outcomes and measuresThe analysis involved an unadjusted and adjusted survival analysis in which the primary outcome was death on the waiting list. Because of changing waiting list preferences and policies during the study period, the intrinsic risk of death for wait-listed candidates was assessed by individually analyzing, comparing, and adjusting for several candidate risk factors.ResultsIn total, 95 323 candidates (72 915 men [76.5%]; mean [SD] age, 51.9 [12.0] years) were studied. In the setting of changes in listing preferences, 1-year survival on the waiting list increased from 34.1% in 1987-1990 to 67.8% in 2011-2017 (difference in proportions, 0.34%; 95% CI, 0.32%-0.36%; P < .001). The 1-year waiting list survival for candidates with VADs increased from 10.2% in 1996-2000 to 70.0% in 2011-2017 (difference in proportions, 0.60%; 95% CI, 0.58%-0.62%; P < .001). Similarly, in the setting of changing mechanical circulatory support indications, the 1-year waiting list survival for patients without VADs increased from 53.9% in 1996-2000 to 66.5% in 2011-2017 (difference in proportions, 0.13%; 95% CI, 0.12%-0.14%; P < .001). In the decade prior to the 2006 UNOS allocation policy, the 1-year waiting list survival was 51.1%, while in the decade after it was 63.9% (difference in proportions, 0.13%; 95% CI, 0.12%-0.14%; P < .001). In adjusted analysis, each time period after 1987-1990 had a marked decrease in waiting list mortality.Conclusions and relevanceThis study found temporally associated increases in heart transplant waiting list survival for all patient groups (with or without VADs, UNOS status 1 and status 2 candidates, and candidates with poor functional status).

Dataset Information

A Comparison of Different Algorithms for the Assessment of Cardiovascular Risk in Patients at Waiting List for Kidney Transplantation.

Background

Methods and results

Conclusion

Publications

A Comparison of Different Algorithms for the Assessment of Cardiovascular Risk in Patients at Waiting List for Kidney Transplantation.

Similar Datasets

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