Dramatic secular changes in prognosis for kidney transplant candidates in the United States

The Medical Costs of Determining Eligibility and Waiting for a Kidney Transplantation

BACKGROUND

Recent efforts to increase access to kidney transplant (KTx) in the United States include increasing referrals to transplant programs, leading to more pretransplant services. Transplant programs reconcile the costs of these services through the Organ Acquisition Cost Center (OACC).

OBJECTIVE

The aim of this study was to determine the costs associated with pretransplant services by applying microeconomic methods to OACC costs reported by transplant hospitals.

RESEARCH DESIGN, SUBJECTS, AND MEASURES

For all US adult kidney transplant hospitals from 2013 through 2018 (n=193), we crosslinked the total OACC costs (at the hospital-fiscal year level) to proxy measures of volumes of pretransplant services. We used a multiple-output cost function, regressing total OACC costs against proxy measures for volumes of pretransplant services and adjusting for patient characteristics, to calculate the marginal cost of each pretransplant service.

RESULTS

Over 1015 adult hospital-years, median OACC costs attributable to the pretransplant services were $5 million. Marginal costs for the pretransplant services were: initial transplant evaluation, $9k per waitlist addition; waitlist management, $2k per patient-year on the waitlist; deceased donor offer management, $1k per offer; living donor evaluation, procurement and follow-up: $26k per living donor. Longer time on dialysis among patients added to the waitlist was associated with higher OACC costs at the transplant hospital.

CONCLUSIONS

To achieve the policy goals of more access to KTx, sufficient funding is needed to support the increase in volume of pretransplant services. Future studies should assess the relative value of each service and explore ways to enhance efficiency.

Age-modified risk factors for mortality of non-elderly adult kidney transplant recipients: a retrospective database analysis

PURPOSE

We aimed to investigate the role of the recipient's age strata in modifying the associations between risk factors and mortality in non-elderly adult kidney transplant (KT) recipients (KTR).

METHODS

We stratified 108,695 adult KTRs between 2000 and 2016 with conditional 1-year survival after KT into cohorts based on age at transplant: 18-49 years and 50-64 years. We excluded KTRs aged < 18 years or > / = 65 years. KTRs were observed for 5 years during the 2nd through 6th years post-KT for the outcome, all-cause mortality.

RESULTS

Increasing recipient age strata (18-49-year-old and 50-64-year-old) correlated with decreasing 6-year post-KT survival rates conditional on 1-year survival (79% and 57%, respectively, p < 0.0001). Middle adult age stratum was associated with a higher risk of all-cause mortality than young adult age stratum in KTRs of Hispanic/Latino and other races [HR = 1.23, 95% CI = 1.04-1.45 and HR = 1.51, 95% CI = 1.16-1.97, respectively] and with a primary native renal diagnosis of hypertension or glomerulonephritis [HR = 1.32, 95% CI = 1.12-1.55 and HR = 1.29, 95% CI = 1.10-151, respectively]. When compared with the young adult age stratum, the middle adult age stratum had a mitigating effect on the higher risk of mortality associated with sirolimus-mycophenolate or sirolimus-tacrolimus than the standard calcineurin inhibitor-mycophenolate regimen [HR = 0.75, 95% CI = 0.57-0.99 and HR = 0.71, 95% CI = 0.57-0.89, respectively].

CONCLUSION

Among adult non-elderly KTRs, the age strata, 18-49 years, and 50-64 years, have varying modifying effects on the strength and direction of associations between some specific risk factors and all-cause mortality.

Innovative Research Methods: Using Simulation to Evaluate Health Care Policy

SUMMARY STATEMENT

Health care policies have the potential to improve patient outcomes, access to care, and reduce health disparities. However, new policy is often tested in the field, where unintended consequences are paid for by patients. In this perspective, we argue that health care simulations, which can elucidate the potential for policy to hinder clinicians' ability to provide high-quality care, are a complement to large-scale policy evaluations in the field.

Competing Risks Analysis of Kidney Transplant Waitlist Outcomes: Two Important Statistical Perspectives

Modern competing risks analysis has 2 primary goals in clinical epidemiology as follows: (i) to maximize the clinician's knowledge of etiologic associations existing between potential predictor variables and various cause-specific outcomes via cause-specific hazard models, and (ii) to maximize the clinician's knowledge of noteworthy differences existing in cause-specific patient risk via cause-specific subdistribution hazard models (cumulative incidence functions [CIFs]). A perfect application exists in analyzing the following 4 distinct outcomes after listing for a deceased donor kidney transplant (DDKT): (i) receiving a DDKT, (ii) receiving a living donor kidney transplant (LDKT), (iii) waitlist removal due to patient mortality or a deteriorating medical condition, and (iv) waitlist removal due to other reasons. It is important to realize that obtaining a complete understanding of subdistribution hazard ratios (HRs) is simply not possible without first having knowledge of the multivariable relationships existing between the potential predictor variables and the cause-specific hazards (perspective #1), because the cause-specific hazards form the "building blocks" of CIFs. In addition, though we believe that a worthy and practical alternative to estimating the median waiting-time-to DDKT is to ask, "what is the conditional probability of the patient receiving a DDKT, given that he or she would not previously experience one of the competing events (known as the cause-specific conditional failure probability)," only an appropriate estimator of this conditional type of cumulative incidence should be used (perspective #2). One suggested estimator, the well-known "one minus Kaplan-Meier" approach (censoring competing events), simply does not represent any probability in the presence of competing risks and will almost always produce biased estimates (thus, it should never be used).

Referral and Evaluation for Kidney Transplantation Following Implementation of the 2014 National Kidney Allocation System

RATIONALE & OBJECTIVE

The national kidney allocation system (KAS) implemented in December 2014 in the United States redefined the start of waiting time from the time of waitlisting to the time of kidney failure. Waitlisting has declined post-KAS, but it is unknown if this is due to transplant center practices or changes in dialysis facility referral and evaluation. The purpose of this study was to assess the impact of the 2014 KAS policy change on referral and evaluation for transplantation among a population of incident and prevalent patients with kidney failure.

STUDY DESIGN

Cohort study.

SETTING & PARTICIPANTS

37,676 incident (2012-2016) patients in Georgia, North Carolina, and South Carolina identified within the US Renal Data System at 9 transplant centers and followed through December 2017. A prevalent population of 6,079 patients from the same centers receiving maintenance dialysis in 2012 but not referred for transplantation in 2012.

EXPOSURE

KAS era (pre-KAS vs post-KAS).

OUTCOME

Referral for transplantation, start of transplant evaluation, and waitlisting.

ANALYTICAL APPROACH

Multivariable time-dependent Cox models for the incident and prevalent population.

RESULTS

Among incident patients, KAS was associated with increased referrals (adjusted HR, 1.16 [95% CI, 1.12-1.20]) and evaluation starts among those referred (adjusted HR, 1.16 [95% CI, 1.10-1.21]), decreased overall waitlisting (adjusted HR, 0.70 [95% CI, 0.65-0.76]), and lower rates of active waitlisting among those evaluated compared to the pre-KAS era (adjusted HR, 0.81 [95% CI, 0.74-0.90]). Among the prevalent population, KAS was associated with increases in overall waitlisting (adjusted HR, 1.74 [95% CI, 1.15-2.63]) and active waitlisting among those evaluated (adjusted HR, 2.01 [95% CI, 1.16-3.49]), but had no significant impact on referral or evaluation starts among those referred.

LIMITATIONS

Limited to 3 states, residual confounding.

CONCLUSIONS

In the southeastern United States, the impact of KAS on steps to transplantation was different among incident and prevalent patients with kidney failure. Dialysis facilities referred more incident patients and transplant centers evaluated more incident patients after implementation of KAS, but fewer evaluated patients were placed onto the waitlist. Changes in dialysis facility and transplant center behaviors after KAS implementation may have influenced the observed changes in access to transplantation.

Emerging Evidence on Coronary Heart Disease Screening in Kidney and Liver Transplantation Candidates: A Scientific Statement From the American Heart Association: Endorsed by the American Society of Transplantation

Coronary heart disease is an important source of mortality and morbidity among kidney transplantation and liver transplantation candidates and recipients and is driven by traditional and nontraditional risk factors related to end-stage organ disease. In this scientific statement, we review evidence from the past decade related to coronary heart disease screening and management for kidney and liver transplantation candidates. Coronary heart disease screening in asymptomatic kidney and liver transplantation candidates has not been demonstrated to improve outcomes but is common in practice. Risk stratification algorithms based on the presence or absence of clinical risk factors and physical performance have been proposed, but a high proportion of candidates still meet criteria for screening tests. We suggest new approaches to pretransplantation evaluation grounded on the presence or absence of known coronary heart disease and cardiac symptoms and emphasize multidisciplinary engagement, including involvement of a dedicated cardiologist. Noninvasive functional screening methods such as stress echocardiography and myocardial perfusion scintigraphy have limited accuracy, and newer noninvasive modalities, especially cardiac computed tomography-based tests, are promising alternatives. Emerging evidence such as results of the 2020 International Study of Comparative Health Effectiveness With Medical and Invasive Approaches-Chronic Kidney Disease trial emphasizes the vital importance of guideline-directed medical therapy in managing diagnosed coronary heart disease and further questions the value of revascularization among asymptomatic kidney transplantation candidates. Optimizing strategies to disseminate and implement best practices for medical management in the broader end-stage organ disease population should be prioritized to improve cardiovascular outcomes in these populations.

A tool for decision-making in kidney transplant candidates with poor prognosis to receive deceased donor transplantation in the United States

The primary outcomes for kidney transplant candidates are receipt of deceased or living donor transplant, death or removal from the waiting list. Here, we conducted a retrospective analysis of national Scientific Registry of Transplant Recipients data to evaluate outcomes for 208,717 adult kidney transplant candidates following the 2014 Kidney Allocation System in the United States. Competing risks models were utilized to evaluate Time to Equivalent Risk (TiTER) of deceased donor transplantation (DDTX) and death versus waitlist removal. We also evaluated TiTER based on kidney donor profile index (KDPI) and donor age. For all groups, the cumulative incidence of DDTX was initially higher from time of listing than death or waitlist removal. However, following accrued time on the waiting list, the cumulative incidence of death or waitlist removal exceeded DDTX for certain patient groups, particularly older, diabetic, blood type B and O and shorter pre-listing dialysis time. TiTER for all candidates aged 65-69 averaged 41 months and for 70 and older patients 28 months. Overall, 39.6% of candidates were in risk groups with TiTER under 72 months and 18.5% in groups with TiTER under 24 months. Particularly for older candidates, TiTER for kidneys was substantially shorter for younger donors or lower KDPI. Thus, our findings reveal that a large proportion of waitlisted patients in the United States have poor prognoses to ever undergo DDTX and our data may improve shared decision-making for candidates at time of waitlist placement. Hence, for specific patient groups, TiTER may be a useful tool to disseminate and quantify benefits of accepting relatively high risk donor organs.

Costs in the Year Following Deceased Donor Kidney Transplantation: Relationships With Renal Function and Graft Failure

Relationships between renal function and medical costs for deceased donor kidney transplant recipients are not fully quantified post-transplant. We describe these relationships with renal function measured by estimated glomerular filtration rate (eGFR) and graft failure. The United States Renal Data System identified adults receiving single-organ deceased donor kidneys 2012–2015. Inpatient, outpatient, other facility costs and eGFRs at discharge, 6 and 12 months were included. A time-history of costs was constructed for graft failures and monthly costs in the first year post-transplant were compared to those without failure. The cohort of 24,021 deceased donor recipients had a 2.4% graft failure rate in the first year. Total medical costs exhibit strong trends with eGFR. Recipients with 6-month eGFRs of 30–59 ml/min/1.73m² have total costs 48% lower than those <30 ml/min/1.73m². For recipients with graft failure monthly costs begin to rise 3–4 months prior to failure, with incremental costs of over $38,000 during the month of failure. Mean annual total incremental costs of graft failure are over $150,000. Total costs post-transplant are strongly correlated with eGFR. Graft failure in the first year is an expensive, months-long process. Further reductions in early graft failures could yield significant human and economic benefits.

Deceased donor kidneys allocated out of sequence by organ procurement organizations

Deceased donor kidney allocation follows a ranked match-run of potential recipients. Organ procurement organizations (OPOs) are permitted to deviate from the mandated match-run in exceptional circumstances. Using match-run data for all deceased donor kidney transplants (Ktx) in the US between 2015 and 2019, we identified 1544 kidneys transplanted from 933 donors with an OPO-initiated allocation exception. Most OPOs (55/58) used this process at least once, but 3 OPOs performed 64% of the exceptions and just 2 transplant centers received 25% of allocation exception Ktx. At 2 of 3 outlier OPOs these transplants increased 136% and 141% between 2015 and 2019 compared to only a 35% increase in all Ktx. Allocation exception donors had less favorable characteristics (median KDPI 70, 41% with history of hypertension), but only 29% had KDPI ≥ 85% and the majority did not meet the traditional threshold for marginal kidneys. Allocation exception kidneys went to larger centers with higher offer acceptance ratios and to recipients with 2 fewer priority points-equivalent to 2 less years of waiting time. OPO-initiated exceptions for kidney allocation are growing increasingly frequent and more concentrated at a few outlier centers. Increasing pressure to improve organ utilization risks increasing out-of-sequence allocations, potentially exacerbating disparities in access to transplantation.

The Utility of Pre- and Post-Transplant Oral Glucose Tolerance Tests: Identifying Kidney Transplant Recipients With or at Risk of New Onset Diabetes After Transplant

Background: New onset diabetes after transplant (NODAT) is common in kidney transplant recipients (KTRs). Identifying patients at risk prior to transplant may enable strategies to mitigate NODAT, with a pre-transplant oral glucose tolerance test (OGTT) suggested by the KDIGO 2020 Guidelines for this purpose.

Methods: We investigated the utility of pre- and post-transplant OGTTs to stratify risk and diagnose NODAT in a retrospective, single-centre cohort study of all non-diabetic KTRs transplanted between 2003 and 2018.

Results: We identified 597 KTRs who performed a pre-transplant OGTT, of which 441 had their post-transplant glycaemic status determined by a clinical diagnosis of NODAT or OGTT. Pre-transplant dysglycaemia was identified in 28% of KTRs and was associated with increasing age (p < 0.001), BMI (p = 0.03), and peritoneal dialysis (p < 0.001). Post-transplant dysglycaemia was common with NODAT and impaired glucose tolerance (IGT) occurring in 143 (32%) and 121 (27%) patients, respectively. Pre-transplant IGT was strongly associated with NODAT development (OR 3.8, p < 0.001).

Conclusion: A pre-transplant OGTT identified candidates at increased risk of post-transplant dysglycaemia and NODAT, as diagnosed by an OGTT. Robust prospective trials are needed to determine whether various interventions can reduce post-transplant risk for candidates with an abnormal pre-transplant OGTT.

Managing Patients with Failing Kidney Allograft: Many Questions Remain

Patients who receive a kidney transplant commonly experience failure of their allograft. Transplant failure often comes with complex management decisions, such as when and how to wean immunosuppression and start the transition to a second transplant or to dialysis. These decisions are made in the context of important concerns about competing risks, including sensitization and infection. Unfortunately, the management of the failed allograft is, at present, guided by relatively poor-quality data and, as a result, practice patterns are variable and suboptimal given that patients with failed allografts experience excess morbidity and mortality compared with their transplant-naive counterparts. In this review, we summarize the management strategies through the often-precarious transition from transplant to dialysis, highlighting the paucity of data and the critical gaps in our knowledge that are necessary to inform the optimal care of the patient with a failing kidney transplant.

Machine learning support for decision making in kidney transplantation: step-by-step development of a technological solution (Preprint)

Background

Kidney transplantation is the preferred treatment option for patients with end-stage renal disease. To maximize patient and graft survival, the allocation of donor organs to potential recipients requires careful consideration.

Objective

This study aimed to develop an innovative technological solution to enable better prediction of kidney transplant survival for each potential donor-recipient pair.

Methods

We used deidentified data on past organ donors, recipients, and transplant outcomes in the United States from the Scientific Registry of Transplant Recipients. To predict transplant outcomes for potential donor-recipient pairs, we used several survival analysis models, including regression analysis (Cox proportional hazards), random survival forests, and several artificial neural networks (DeepSurv, DeepHit, and recurrent neural network [RNN]). We evaluated the performance of each model in terms of its ability to predict the probability of graft survival after kidney transplantation from deceased donors. Three metrics were used: the C-index, integrated Brier score, and integrated calibration index, along with calibration plots.

Results

On the basis of the C-index metrics, the neural network–based models (DeepSurv, DeepHit, and RNN) had better discriminative ability than the Cox model and random survival forest model (0.650, 0.661, and 0.659 vs 0.646 and 0.644, respectively). The proposed RNN model offered a compromise between the good discriminative ability and calibration and was implemented in a technological solution of technology readiness level 4.

Conclusions

Our technological solution based on the RNN model can effectively predict kidney transplant survival and provide support for medical professionals and candidate recipients in determining the most optimal donor-recipient pair.

Failure to Advance Access to Kidney Transplantation over Two Decades in the United States

BACKGROUND

Extensive research and policies have been developed to improve access to kidney transplantation among patients with ESKD. Despite this, wide variation in transplant referral rates exists between dialysis facilities.

METHODS

To evaluate the longitudinal pattern of access to kidney transplantation over the past two decades, we conducted a retrospective cohort study of adult patients with ESKD initiating ESKD or placed on a transplant waiting list from 1997 to 2016 in the United States Renal Data System. We used cumulative incidence models accounting for competing risks and multivariable Cox models to evaluate time to waiting list placement or transplantation (WLT) from ESKD onset.

RESULTS

Among the study population of 1,309,998 adult patients, cumulative 4-year WLT was 29.7%, which was unchanged over five eras. Preemptive WLT (prior to dialysis) increased by era (5.2% in 1997-2000 to 9.8% in 2013-2016), as did 4-year WLT incidence among patients aged 60-70 (13.4% in 1997-2000 to 19.8% in 2013-2016). Four-year WLT incidence diminished among patients aged 18-39 (55.8%-48.8%). Incidence of WLT was substantially lower among patients in lower-income communities, with no improvement over time. Likelihood of WLT after dialysis significantly declined over time (adjusted hazard ratio, 0.80; 95% confidence interval, 0.79 to 0.82) in 2013-2016 relative to 1997-2000.

CONCLUSIONS

Despite wide recognition, policy reforms, and extensive research, rates of WLT following ESKD onset did not seem to improve in more than two decades and were consistently reduced among vulnerable populations. Improving access to transplantation may require more substantial interventions.

Outcomes of Surgical Mitral and Aortic Valve Replacements Among Kidney Transplant Candidates: Implications for Valve Selection

Background

Limited literature exists that evaluated outcomes of kidney transplant–eligible patients who are having dialysis and who are undergoing valve replacement. Our main objective in this study was to compare mortality, reoperation, and bleeding episodes between bioprosthetic and mechanical valve procedures among kidney transplant–eligible patients who are having dialysis.

Methods and Results

We studied 887 and 1925 dialysis patients from the United States Renal Data System, who underwent mitral valve replacement and aortic valve replacement (AVR) after being waitlisted for a kidney transplant (2000–2015), respectively. Time to death, time to reoperation, and time to bleeding requiring hospitalizations were compared separately for AVR and mitral valve replacement. Kaplan–Meier survival curves, Cox proportional hazards model for time to death, accelerated time to event model for time to reoperation, and counting process model for time to recurrent bleeding were used. There were no differences in mortality (hazard ratio [HR], 0.92; 95% CI, 0.77–1.09) or risk of reoperation or risk of significant bleeding events between bioprosthetic and mechanical mitral valve replacement. However, mechanical AVR was associated with a modestly significant less hazard of death (HR, 0.83; 95% CI, 0.74–0.94) compared with bioprosthetic AVR. There were no differences in time to reoperation, or time to significant bleeding events between bioprosthetic and mechanical AVR.

Conclusions

For kidney transplant waitlisted patients who are on dialysis and who are undergoing surgical valve replacement, bioprosthetic and mechanical valves have comparable survival, reoperation rates, and bleeding episodes requiring hospitalizations at both mitral and aortic locations. These findings emphasize that an individualized informed decision is recommended when choosing the type of valve for this special group of patients having dialysis.

Kidney transplant program waitlisting rate as a metric to assess transplant access

Kidney transplant program performance in the United States is commonly measured by posttransplant outcomes. Inclusion of pretransplant measures could provide a more comprehensive assessment of transplant program performance and necessary information for patient decision-making. In this study, we propose a new metric, the waitlisting rate, defined as the ratio of patients who are waitlisted in a center relative to the person-years referred for evaluation to a program. Furthermore, we standardize the waitlisting rate relative to the state average in Georgia, North Carolina, and South Carolina. The new metric was used as a proof-of-concept to assess transplant-program access compared to the existing transplant rate metric. The study cohorts were defined by linking 2017 United States Renal Data System (USRDS) data with transplant-program referral data from the Southeastern United States between January 1, 2012 and December 31, 2016. Waitlisting rate varied across the 9 Southeastern transplant programs, ranging from 10 to 22 events per 100 patient-years, whereas the program-specific waitlisting rate ratio ranged between 0.76 and 1.33. Program-specific waitlisting rate ratio was uncorrelated with the transplant rate ratio (r = -.15, 95% CI, -0.83 to 0.57). Findings warrant collection of national data on early transplant steps, such as referral, for a more comprehensive assessment of transplant program performance and pretransplant access.

Major Variation across Local Transplant Centers in Probability of Kidney Transplant for Wait-Listed Patients

BACKGROUND

Geographic disparities in access to deceased donor kidney transplantation persist in the United States under the Kidney Allocation System (KAS) introduced in 2014, and the effect of transplant center practices on the probability of transplantation for wait-listed patients remains unclear.

METHODS

To compare probability of transplantation across centers nationally and within donation service areas (DSAs), we conducted a registry study that included all United States incident adult kidney transplant candidates wait listed in 2011 and 2015 (pre-KAS and post-KAS cohorts comprising 32,745 and 34,728 individuals, respectively). For each center, we calculated the probability of deceased donor kidney transplantation within 3 years of wait listing using competing risk regression, with living donor transplantation, death, and waiting list removal as competing events. We examined associations between center-level and DSA-level characteristics and the adjusted probability of transplant.

RESULTS

Candidates received deceased donor kidney transplants within 3 years of wait listing more frequently post-KAS (22%) than pre-KAS (19%). Nationally, the probability of transplant varied 16-fold between centers, ranging from 4.0% to 64.2% in the post-KAS era. Within DSAs, we observed a median 2.3-fold variation between centers, with up to ten-fold and 57.4 percentage point differences. Probability of transplantation was correlated in the post-KAS cohort with center willingness to accept hard-to-place kidneys (r=0.55, P<0.001) and local organ supply (r=0.44, P<0.001).

CONCLUSIONS

Large differences in the adjusted probability of deceased donor kidney transplantation persist under KAS, even between centers working with the same local organ supply. Probability of transplantation is significantly associated with organ offer acceptance patterns at transplant centers, underscoring the need for greater understanding of how centers make decisions about organs offered to wait-listed patients and how they relate to disparities in access to transplantation.

Validation of a survival benefit estimator tool in a cohort of European kidney transplant recipients

Pre-transplant prognostic scores help to optimize donor/recipient allocation and to minimize organ discard rates. Since most of these scores come from the US, direct application in non-US populations is not advisable. The Survival Benefit Estimator (SBE), built upon the Estimated Post-Transplant Survival (EPTS) and the Kidney Donor Profile Index (KDPI), has not been externally validated. We aimed to examine SBE in a cohort of Spanish kidney transplant recipients. We designed a retrospective cohort-based study of deceased-donor kidney transplants carried out in two different Spanish hospitals. Unadjusted and adjusted Cox models were applied for patient survival. Predictive models were compared using Harrell’s C statistics. SBE, EPTS and KDPI were independently associated with patient survival (p ≤ 0.01 in all models). Model discrimination measured with Harrell’s C statistics ranged from 0.57 (KDPI) to 0.69 (SBE) and 0.71 (EPTS). After adjustment, SBE presented similar calibration and discrimination power to that of EPTS. SBE tended to underestimate actual survival, mainly among high EPTS recipients/high KDPI donors. SBE performed acceptably well at discriminating post-transplant survival in a cohort of Spanish deceased-donor kidney transplant recipients, although its use as the main allocation guide, especially for high KDPI donors or high EPTS recipients requires further testing.

The association of pretransplant dialysis exposure with transplant failure is dependent on the state-specific rate of dialysis mortality

Longer pretransplant dialysis exposure is associated with a higher risk of transplant failure. Whether patients who receive dialysis in a region with a higher rate of dialysis mortality are a higher risk for transplant failure is unknown. Adjusted state-specific hemodialysis mortality rates were determined in 3-year intervals among prevalent dialysis patients in the United States between 1995 and 2012. The effect of state- and period-specific dialysis mortality on the association of pretransplant dialysis exposure with transplant survival through December 2017 was determined using multivariable models. Dialysis mortality within states ranged from 128 deaths/1000 patient-years to 330 deaths/1000 patient-years. Each additional year of dialysis was associated with a 4% higher risk of transplant failure in states within the lowest quartile of dialysis mortality, compared with an 8% higher risk in states within the highest quartile of dialysis mortality. Patients who received pretransplant dialysis treatment in a state with a high rate of dialysis mortality are at a higher risk for transplant failure compared with patients with the same duration of pretransplant dialysis treatment in a state with a lower mortality rate. The findings may have implications for dialysis care in transplant candidates and the design of future outcome metrics.

Kidney transplant outcomes in recipients with visual, hearing, physical and walking impairments: a prospective cohort study

BACKGROUND

Disability in general has been associated with poor outcomes in kidney transplant (KT) recipients. However, disability can be derived from various components, specifically visual, hearing, physical and walking impairments. Different impairments may compromise the patient through different mechanisms and might impact different aspects of KT outcomes.

METHODS

In our prospective cohort study (June 2013-June 2017), 465 recipients reported hearing, visual, physical and walking impairments before KT. We used hybrid registry-augmented Cox regression, adjusting for confounders using the US KT population (Scientific Registry of Transplant Recipients, N = 66 891), to assess the independent association between impairments and post-KT outcomes [death-censored graft failure (DCGF) and mortality].

RESULTS

In our cohort of 465 recipients, 31.6% reported one or more impairments (hearing 9.3%, visual 16.6%, physical 9.1%, walking 12.1%). Visual impairment was associated with a 3.36-fold [95% confidence interval (CI) 1.17-9.65] higher DCGF risk, however, hearing [2.77 (95% CI 0.78-9.82)], physical [0.67 (95% CI 0.08-3.35)] and walking [0.50 (95% CI 0.06-3.89)] impairments were not. Walking impairment was associated with a 3.13-fold (95% CI 1.32-7.48) higher mortality risk, however, visual [1.20 (95% CI 0.48-2.98)], hearing [1.01 (95% CI 0.29-3.47)] and physical [1.16 (95% CI 0.34-3.94)] impairments were not.

CONCLUSIONS

Impairments are common among KT recipients, yet only visual impairment and walking impairment are associated with adverse post-KT outcomes. Referring nephrologists and KT centers should identify recipients with visual and walking impairments who might benefit from targeted interventions pre-KT, additional supportive care and close post-KT monitoring.

Modest rates and wide variation in timely access to repeat kidney transplantation in the United States

Success of transplantation is not limited to initial receipt of a donor organ. Many kidney transplant recipients experience graft loss following initial transplantation and the benefits of expedited placement on the waiting list and retransplantation extend to this population. Factors associated with access to repeat transplantation may be unique given experience with the transplant process and prior viability as a candidate. We examined the incidence, risk factors, secular changes, and center-level variation of preemptive relisting or transplantation (PRLT) for kidney transplant recipients in the United States with graft failure (not due to death) using Scientific Registry of Transplant Recipients data from 2007 to 2018 (n = 39 557). Overall incidence of PRLT was 15% and rates of relisting declined over time. Significantly lower PRLT was evident among patients who were African American and Hispanic, males, older, obese, publicly insured, had lower educational attainment, were diabetic, had longer dialysis time prior to initial transplant, shorter graft survival, longer distance to transplant center, and resided in distressed communities. There was significant variation in PRLT by center, median = 13%, 10th percentile = 6%, 90th percentile = 24%. Cumulatively, results indicate that despite prior access to transplantation, incidence of PRLT is modest with pronounced clinical, social, and center-level sources of variation suggesting opportunities to improve preemptive care among patients with failing grafts.

Preoperative Factors Predicting Admission to the Intensive Care Unit After Kidney Transplantation

OBJECTIVE

To identify preoperative factors predicting early admission (within 30 days) of adult kidney transplant recipients to the intensive care unit (ICU).

PATIENTS AND METHODS

This is a single-center retrospective study of consecutive kidney transplant recipients between January 1, 2007, and December 31, 2016. Children (aged <18 years) and patients who underwent simultaneous multiorgan transplantation were excluded from the analysis. Associations between demographic, transplant-related, and comorbidity variables with ICU admission within 30 days of transplantation were analyzed using univariate and multivariate logistic regression models.

RESULTS

Of the 1527 eligible patients, 305 (20%) required early ICU admission. In univariate analysis, older age, higher body mass index (BMI), previous transplantation, myocardial infarction, congestive heart failure, obstructive pulmonary disease, longer ischemia time, pretransplant dialysis, and transplantation from a deceased donor were associated with increased odds of ICU admission. After multivariate adjustment, every 10-year increase in recipient age (odds ratio [OR], 1.26; 95% CI, 1.12-1.42; P<.001), 5-unit increase in BMI (OR, 1.11; 95% CI, 1.00-1.22; P=.049), pretransplant dialysis (OR, 1.57; 95% CI, 1.19-2.08; P=.002), and deceased donor transplantation (OR, 1.82; 95% CI, 1.29-2.55; P<.001) were associated with the increased risk of ICU admission. Preemptive transplantation (OR, 0.64; 95% CI, 0.48-0.84; P=.002) and living donor kidney transplantation (OR, 0.55; 95% CI, 0.39-0.77; P<.001) were associated with lower odds of ICU admission after transplantation.

CONCLUSION

Recipient age, BMI, and the need for pretransplant dialysis are associated with a higher risk of early ICU admission after kidney transplantation, whereas living donor kidney transplantation and preemptive transplantation decrease these odds. Early referral of patients with end-stage renal disease for preemptive transplantation and living donor kidney transplantation can significantly reduce transplant-related ICU admissions.

Access to Kidney Transplantation after a Failed First Kidney Transplant and Associations with Patient and Allograft Survival: An Analysis of National Data to Inform Allocation Policy

BACKGROUND AND OBJECTIVES

Patients who have failed a transplant are at increased risk of repeat transplant failure. We determined access to transplantation and transplant outcomes in patients with and without a history of transplant failure.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

In this observational study of national data, the proportion of waitlisted patients and deceased donor transplant recipients with transplant failure was determined before and after the new kidney allocation system. Among patients initiating maintenance dialysis between May 1995 and December 2014, the likelihood of deceased donor transplantation was determined in patients with (n=27,459) and without (n=1,426,677) a history of transplant failure. Among transplant recipients, allograft survival, the duration of additional kidney replacement therapy required within 10 years of transplantation, and the association of transplantation versus dialysis with mortality was determined in patients with and without a history of transplant failure.

RESULTS

The proportion of waitlist candidates (mean 14%) and transplant recipients (mean 12%) with transplant failure did not increase after the new kidney allocation system. Among patients initiating maintenance dialysis, transplant-failure patients had a higher likelihood of transplantation (hazard ratio [HR], 1.16; 95% confidence interval [95% CI], 1.12 to 1.20; P<0.001). Among transplant recipients, transplant-failure patients had a higher likelihood of death-censored transplant failure (HR, 1.44; 95% CI, 1.34 to 1.54; P<0.001) and a greater need for additional kidney replacement therapy required within 10 years after transplantation (mean, 9.0; 95% CI, 5.4 to 12.6 versus mean, 2.1; 95% CI, 1.5 to 2.7 months). The association of transplantation versus dialysis with mortality was clinically similar in waitlisted patients with (HR, 0.32; 95% CI, 0.29 to 0.35; P<0.001) and without transplant failure (HR, 0.40; 95% CI, 0.39 to 0.41; P<0.001).

CONCLUSIONS

Transplant-failure patients initiating maintenance dialysis have a higher likelihood of transplantation than transplant-naïve patients. Despite inferior death-censored transplant survival, transplantation was associated with a similar reduction in the risk of death compared with treatment with dialysis in patients with and without a prior history of transplant failure.

Assessing the outcome of organ allocation: choosing metrics

PURPOSE OF REVIEW

Organ allocation is a highly complex process with significant impact on outcomes of donor organs and end-stage organ disease patients. Policies governing allocation must incorporate numerous factors to meet stated objective. There have been significant alterations and ongoing discussion about changes in allocation policy for all solid organs in the United States. As with any policy change, rigorous evaluation of the impact of changes is important.

RECENT FINDINGS

This manuscript discusses metrics to consider to evaluate the impact of organ allocation policy that may be monitored on an ongoing basis including examples of research evaluating current policies. Potential metrics to evaluate allocation policy include the effectiveness, efficiency, equity, costs, donor rates, and transparency associated with the system.

SUMMARY

Ultimately, policies will often need to adapt to secular changes in donor and patient characteristics, clinical and technological advances, and overarching healthcare polices. Providing objective empirical evaluation of the impact of policies is a critical component for assessing quality of the allocation system and informing the effect of changes. The foundation of organ transplantation is built upon public trust and the dependence on the gift of donor organs, as such the importance of the most appropriate organ allocation policies cannot be overstated.

In-hospital outcomes for solid organ transplants according to type 2 diabetes status: An observational, 15-year study in Spain

AIMS

To describe trends and outcomes during admission for solid organ transplant in people with or without type 2 diabetes in Spain, 2001-2015.

METHODS

We used national hospital discharge data to select all hospital admissions for kidney, lung, heart, and liver transplant. We estimated admission rates stratified by type 2 diabetes status. We built Poisson regression models to compare the adjusted time trends in admission rates. We tested in-hospital mortality (IHM) in logistic regression analyses.

RESULTS

We identified 50 964 transplants (16.7% in people with type 2 diabetes): kidney, 30 919; lung, 2810; heart, 3649; liver, 13 586. The overall adjusted incidence rate ratios (95% confidence intervals) of admission in people with type 2 diabetes vs no diabetes were 2.4 (2.32-2.48) for kidney, 1.51 (1.33-1.70) for lung, 2.87 (2.63-3.13) for heart, and 4.16 (3.99-4.33) for liver transplant. In the multivariate analysis, IHM decreased significantly over time for all types of transplant. Type 2 diabetes independently predicted lower IHM during admission only for heart (Odds ratio, OR [95% CI] = 0.62 [0.47-0.81]) and liver transplant (OR [95% CI] = 0.69 [0.58-0.82]).

CONCLUSIONS

Admission rates for solid organ transplant were higher in people with type 2 diabetes than in people without diabetes. Type 2 diabetes was associated with lower in-hospital mortality during admission for heart and liver transplant.