Dataset Information

The Seattle Heart Failure Model in Kidney Transplant Recipients.

ABSTRACT: Cardiovascular disease is the leading cause of mortality following kidney transplantation. Heart failure affects 17-21% of patients with chronic kidney disease and increases along with time receiving dialysis. The Seattle Heart Failure Model (SHFM) is a validated mortality risk model for heart failure patients that incorporates clinical, therapeutic, and laboratory parameters but does not include measures of kidney function. We applied the SHFM to patients with end-stage renal disease (ESRD) who were being evaluated for kidney transplantation to determine if the model was associated with post-transplant mortality. This retrospective single-center study analyzed survival among 360 adult deceased-donor kidney transplant recipients. Cox regression was used to model post-transplant patient survival. Our findings indicated that a 1.0-point increase in the adapted SHFM score was significantly associated with post-transplant mortality (HR 1.76, 95% CI = 1.10-2.83, p = 0.02), independently of the Kidney Donor Profile Index and Estimated Post-Transplant Survival. Individual covariates of the SHFM were evaluated in univariate analyses, and age, sodium, cholesterol, and lymphocyte count were significantly related to mortality. This study provides preliminary evidence that an adapted SHFM score could be a useful tool in evaluating mortality risk post-transplant in patients with ESRD.

SUBMITTER: Perez-Gutierrez A

PROVIDER: S-EPMC10743453 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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The Seattle Heart Failure Model in Kidney Transplant Recipients.

Perez-Gutierrez Angelica A McGill Rita L RL Juengel Braden B Bachul Piotr J PJ Danz David N DN Josephson Michelle M Chung Ben B BB Nguyen Ann A Fung John J JJ Barth Rolf N RN Becker Yolanda T YT

Journal of clinical medicine 20231211 24

Cardiovascular disease is the leading cause of mortality following kidney transplantation. Heart failure affects 17-21% of patients with chronic kidney disease and increases along with time receiving dialysis. The Seattle Heart Failure Model (SHFM) is a validated mortality risk model for heart failure patients that incorporates clinical, therapeutic, and laboratory parameters but does not include measures of kidney function. We applied the SHFM to patients with end-stage renal disease (ESRD) who ...[more]

PMID: 38137683

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Project description:BackgroundGraft loss is a major health concern for kidney transplant (KTx) recipients. It is of clinical interest to develop a prognostic model for both graft function, quantified by estimated glomerular filtration rate (eGFR), and the risk of graft failure. Additionally, the model should be dynamic in the sense that it adapts to accumulating longitudinal information, including time-varying at-risk population, predictor-outcome association, and clinical history. Finally, the model should also properly account for the competing risk by death with a functioning graft. A model with the features above is not yet available in the literature and is the focus of this research.MethodsWe built and internally validated a prediction model on 3,893 patients from the Wisconsin Allograft Recipient Database (WisARD) who had a functioning graft 6 months after kidney transplantation. The landmark analysis approach was used to build a proof-of-concept dynamic prediction model to address the aforementioned methodological issues: the prediction of graft failure, accounted for competing risk of death, as well as the future eGFR value, are updated at each post-transplant time. We used 21 predictors including recipient characteristics, donor characteristics, transplant-related and post-transplant factors, longitudinal eGFR, hospitalization, and rejection history. A sensitivity analysis explored a less conservative variable selection rule that resulted in a more parsimonious model with reduced predictors.ResultsFor prediction up to the next 1 to 5 years, the model achieved high accuracy in predicting graft failure, with the AUC between 0.80 and 0.95, and moderately high accuracy in predicting eGFR, with the root mean squared error between 10 and 18 mL/min/1.73m2 and 70%-90% of predicted eGFR falling within 30% of the observed eGFR. The model demonstrated substantial accuracy improvement compared to a conventional prediction model that used only baseline predictors.ConclusionThe model outperformed conventional prediction model that used only baseline predictors. It is a useful tool for patient counseling and clinical management of KTx and is currently available as a web app.

Project description:BackgroundPredicting allograft failure in kidney transplant recipients can help plan renal replacement therapy and guide patient-provider communication. The kidney failure risk equation (KFRE) accurately predicts the need for dialysis in patients with chronic kidney disease (CKD), but has not been validated in kidney transplant recipients.ObjectiveWe sought to validate the 4-variable KFRE (age, sex, estimated glomerular filtration rate [eGFR], and urine albumin-to-creatinine ratio [ACR]) for prediction of 2- and 5-year death-censored allograft failure.DesignRetrospective cohort study.SettingFour independent North American Cohorts from Ontario, Canada; Alberta, Canada; Manitoba, Canada; and Wisconsin, United States, between January 1999 and December 2017.PatientsAdult kidney transplant patients at 1-year posttransplantation.MeasurementsKidney failure risk as measured by the KFRE (eGFR, urine ACR, age, and sex).MethodsWe included all adult patients who had at least 1 serum creatinine and at least 1 urine ACR measurement approximately 1 year following kidney transplantation. The performance of the KFRE was evaluated using the area under the receiver operating characteristic curve (C-statistic). C-statistics from the 4 cohorts were meta-analyzed using random-effects models.ResultsA total of 3659 patients were included. Pooled C-statistics were good in the entire population, at 0.81 (95% confidence interval: 0.72-0.91) for the 2-year KFRE and 0.73 (0.67-0.80) for the 5-year KFRE. Discrimination improved among patients with poorer kidney function (eGFR < 45 mL/min/1.73 m2), with a C-statistic of 0.88 (0.78-0.98) for the 2-year KFRE and 0.83 (0.74-0.91) for the 5-year KFRE.LimitationsThe KFRE does not predict episodes of acute rejection and there was heterogeneity between cohorts.ConclusionsThe KFRE accurately predicts kidney failure in kidney transplant recipients at 1-year posttransplantation. Further validation in larger cohorts with longer follow-up times can strengthen the case for clinical implementation.

Project description:BackgroundLong-term high-dose lithium therapy in bipolar disorder is known to adversely affect kidney function. However, recent animal studies have revealed that low amounts of lithium are beneficial for the kidney when it is damaged by exposure to nephrotoxic compounds, inflammation or oxidative stress. This study aimed to investigate whether urinary lithium excretion, reflecting dietary lithium intake, is associated with adverse long-term kidney graft outcomes and patient survival.MethodsUrinary lithium concentration was measured using inductively coupled plasma mass spectrometry in 642 stable kidney transplant recipients (KTRs). Graft failure was defined as the start of dialysis or retransplantation and kidney function decline was defined as a doubling of serum creatinine.ResultsThe median urinary lithium excretion was 3.03 μmol/24 h [interquartile range (IQR) 2.31-4.01]. Urinary lithium excretion was associated with energy, plant protein and water intake. During a median follow-up of 5.3 years (IQR 4.5-6.0), 79 (12%) KTRs developed graft failure and 127 (20%) KTRs developed kidney function decline. Higher urinary lithium excretion was associated with a lower risk of graft failure {hazard ratio [HR] per doubling 0.54 [95% confidence interval (CI) 0.38-0.79]} and kidney function decline [HR per doubling 0.73 (95% CI 0.54-0.99)]. These associations remained independent of adjustment for potential confounders and in sensitivity analyses. There was a significant effect modification with the use of proliferation inhibitors (P = .05) and baseline estimated glomerular filtration rate (eGFR; P < .001), with higher urinary lithium excretion being more protective in KTRs not using proliferation inhibitors and in KTRs with lower baseline eGFR. Furthermore, higher urinary lithium excretion was associated with a reduced risk of all-cause mortality [HR 0.64 (95% CI 0.49-0.83); P = .001].ConclusionDietary lithium intake may be a potentially modifiable, yet rather overlooked, risk factor for adverse long-term kidney graft outcomes and patient survival.Trial registrationhttps://clinicaltrials.gov/ct2/show/NCT02811835.

Project description:Rationale & objectiveThe Kidney Failure Risk Equation (KFRE) is a simple widely validated prediction model using age, sex, estimated glomerular filtration rate, and urinary albumin-creatinine ratio to predict the risk for end-stage kidney disease. Data are limited for its applicability to kidney transplant recipients.Study designValidation study of the KFRE as a post hoc analysis of the Folic Acid for Vascular Outcomes Reduction in Transplantation (FAVORIT) Trial.Setting & participantsAdult kidney transplant recipients with functioning kidney allografts at least 6 months posttransplantation from 30 centers in the United States, Canada, and Brazil. Participants with estimated glomerular filtration rates < 60 mL/min/1.73 m2 at study entry were included.Predictor2- and 5-year kidney failure risk predicted by the KFRE using variables at study entry.OutcomeGraft loss, defined by initiation of dialysis.Analytical approachDiscrimination of the KFRE was assessed using C statistics; calibration was assessed by plotting predicted risk against observed cumulative incidence of graft loss.Results2,889 participants were included. Within 2 years, 98 participants developed graft loss, 107 participants died with a functioning graft, and 129 participants were lost to follow-up, and by 5 years, 252 had developed graft loss, 265 died with a functioning graft, and 1,543 were lost to follow-up. The KFRE demonstrated accurate calibration and discrimination (C statistic, 0.85 [95% CI, 0.81-0.88] at 2 years and 0.81 [95% CI, 0.78-0.84] at 5 years); performance was similar regardless of donor type (living vs deceased) and graft vintage, with the noted exception of poorer calibration for graft vintage less than 2 years.LimitationsUnavailable cause of graft loss.ConclusionsThe KFRE accurately predicted the risk for graft loss among adult kidney transplant recipients with graft vintage longer than 2 years and may be a useful prognostic tool for nephrologists caring for kidney transplant recipients.

Dataset Information

The Seattle Heart Failure Model in Kidney Transplant Recipients.

Publications

The Seattle Heart Failure Model in Kidney Transplant Recipients.

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