US Renal Data System 2012 Annual Data Report Collins, Allan J., MD; Foley, Robert N., MB; Herzog, Charles, MD ...
American journal of kidney diseases,
01/2013, Letnik:
61, Številka:
1
Journal Article
US Renal Data System 2010 Annual Data Report Collins, Allan J., MD; Foley, Robert N., MB; Herzog, Charles, MD ...
American journal of kidney diseases,
01/2011, Letnik:
57, Številka:
1
Journal Article
US Renal Data System 2013 Annual Data Report Collins, Allan J., MD; Foley, Robert N., MB; Chavers, Blanche, MD ...
American journal of kidney diseases,
01/2014, Letnik:
63, Številka:
1
Journal Article
US Renal Data System 2011 Annual Data Report Collins, Allan J., MD; Foley, Robert N., MB; Chavers, Blanche, MD ...
American journal of kidney diseases,
01/2012, Letnik:
59, Številka:
1
Journal Article
Background Whether chronic kidney disease (CKD) staging provides a useful framework for predicting outcomes after kidney transplant is unclear. Study Design Retrospective cohort study. Setting & ...Participants We used data from the Patient Outcomes in Renal Transplantation (PORT) Study, including 13,671 transplants from 12 centers during 10 years of follow-up. Predictor Estimated glomerular filtration rate (eGFR; in milliliters per minute per 1.73 m2 ) at 12 months posttransplant. Outcomes All-cause graft failure (a composite end point consisting of return to dialysis therapy, pre-emptive retransplant, or death with function), death-censored graft failure, and death with a functioning graft. Measurements The relationship between 12-month eGFR and subsequent graft outcomes through 10 years posttransplant was assessed using Cox proportional hazards analyses. Results Stage 3 included 63% of patients and was subdivided into stages 3a (eGFR, 45-59 mL/min/1.73 m2 ; 34%) and 3b (eGFR, 30-44 mL/min/1.73 m2 ; 29%). Compared with stage 2 (eGFR, 60-89 mL/min/1.73 m2 ; 24%), adjusted Cox proportional HRs for graft failure were 1.12 (95% CI, 1.01-1.24; P = 0.04) for stage 3a, 1.50 (95% CI, 1.35-1.66; P < 0.001) for stage 3b, 2.86 (95% CI, 2.53-3.22; P < 0.001) for stage 4 (eGFR, 15-29 mL/min/1.73 m2 ; 9%), and 13.2 (95% CI, 10.7-16.4; P < 0.001) for stage 5 (eGFR <15 mL/min/1.73 m2 ; 1%). For stage 1 (eGFR ≥90 mL/min/1.73 m2 ; 3%), risk of graft failure was increased (1.41 95% CI, 1.13-1.75; P < 0.001), likely due to serum creatinine associations independent of kidney function. Similar associations were seen between CKD stages and mortality. Limitations Retrospective study; lack of gold-standard measurements of true GFR; lack of measures of comorbidity, inflammation, muscle mass, proteinuria, and other noncreatinine markers of eGFR. Conclusions CKD stages validated in the general population provide a useful framework for predicting outcomes after kidney transplant.
Background Surprisingly few tools have been developed to predict outcomes after kidney transplant. Study Design Retrospective observational cohort study. Setting & Participants Adult patients from US ...Renal Data System (USRDS) data who underwent deceased donor kidney transplant in 2000-2006. Predictor Full and abbreviated prediction tools for graft loss using candidate predictor variables available in the USRDS registry, including data from the Organ Procurement and Transplantation Network and the Centers for Medicare & Medicaid Services End-Stage Renal Disease Program. Outcomes Graft loss within 5 years, defined as return to maintenance dialysis therapy, preemptive retransplant, or death with a functioning graft. Measurements We used Cox proportional hazards analyses to develop separate tools for assessment (1) pretransplant, (2) at 7 days posttransplant, and (3) at 1 year posttransplant to predict subsequent risk of graft loss within 5 years of transplant. We used measures of discrimination and explained variation to determine the number of variables needed to predict outcomes at each assessment time in the full and abbreviated equations, creating simple user-friendly prediction tools. Results Although we could identify 32, 29, and 18 variables that predicted graft loss assessed pretransplant and at 7 days and 1 year posttransplant (“full” models), 98% of the discriminatory ability and >80% of the variability explained by the full models could be achieved using only 11, 8, and 6 variables, respectively. Limitations Comorbidity data were from the Centers for Medicare & Medicaid Medical Evidence Report, which may significantly underreport comorbid conditions; C statistic values may indicate only modest ability to discriminate risk for an individual patient. Conclusions This method produced risk-prediction tools that can be used easily by patients and clinicians to aid in understanding the absolute and relative risk of graft loss within 5 years of transplant.
Background Little is known about depression after kidney transplantation. Study Design Retrospective observational study. Setting & Participants US Renal Data System data; first kidney-only ...recipients who underwent transplantation in 1995 to 2003 with Medicare as primary payer (n = 47,899). Predictor Demographic and clinical characteristics of recipients (age, sex, race, ethnicity, primary cause of kidney disease, pretransplantation time on dialysis therapy, body mass index, initial immunosuppressive medications, and use of induction antibodies) and donors (age, sex, race, and living or deceased), transplantation year, and number of HLA mismatches. Outcomes & Measurements Depression incidence identified in Medicare claims and associations with clinical outcomes during the first 3 years posttransplantation. Results Depression was identified in 3,360 transplant recipients in the 3 years posttransplantation. Cumulative incidences were 5.05%, 7.29%, and 9.10% at 1, 2, and 3 years posttransplantation. In Cox proportional hazards analysis, white race, female sex, diabetes as primary cause of kidney disease, more than 3 years on dialysis therapy before transplantation, marked obesity (body mass index ≥ 35 kg/m2 ), rapamycin use, antilymphocyte globulin or antithymocyte globulin for antibody induction therapy, donor age of 65 years or older, more recent transplantation, and presence of 6 HLA mismatches were associated with more depression, as identified in claims. Controlling for other known risk factors, time-dependent Cox proportional hazards analysis showed that depression was associated with increased graft failure (hazard ratio, 2.10; 95% confidence interval, 1.94 to 2.27; P < 0.001), return to dialysis therapy (hazard ratio, 1.97; 95% confidence interval, 1.76 to 2.19; P < 0.001), and death with a functioning graft (hazard ratio, 2.24; 95% confidence interval, 2.00 to 2.50; P < 0.001). Limitations Depression identified through Medicare claims, limiting case ascertainment; limited number of recipient- or donor-related factors explored for potential associations; and limited depression treatment and pretransplantation depression information. Conclusions Depression is associated with several identifiable factors and a 2-fold greater risk of graft failure and death with a functioning graft.
Ventricular assist devices (VADs) have improved survival among end-stage heart disease patients. Since 2002, heart transplant candidates with VADs have been afforded 30 days of elective time at the ...highest urgency category (Status 1A) under Organ Procurement and Transplantation Network (OPTN) policy. We aimed to determine the effect of increasing elective time at the highest urgency category for heart transplant candidates with VADs. This analysis was requested by OPTN during its evaluation of heart allocation policy.
We simulated several allocation schemes wherein elective Status 1A time was increased to 45, 60, and 90 days; results were compared with a baseline simulation of 30 days and with the actual observed heart transplant waiting list cohort.
The simulations showed that increasing elective Status 1A time for candidates with VADs did not substantially change waiting list mortality overall or for sub-groups of concern, which were candidates with VADs listed at a lower-urgency category (Status 1B), those with with VAD complications, total artificial heart, or intraaortic balloon pump support; or those with extracorporeal membrane oxygenation. Across the different time allowances, the average post-transplant death rate remained stable. It also remained stable for recipients previously listed as Status 1A or 1B categories for VAD and for recipients with VAD complications or an intraaortic balloon pump at transplant, on extracorporeal membrane oxygenation, and those without devices.
Our results suggest that increasing time in the highest urgency category for candidates with VADs would not improve waiting list mortality or post-transplant outcomes for heart transplant candidates overall.
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