Faculty Bibliography

One criticism of kidney paired donation (KPD) is that easy-to-match candidates leave the registry quickly, thus concentrating the pool with hard-to-match sensitized and blood type O candidates. We studied candidate/donor pairs who registered with the National Kidney Registry (NKR), the largest US KPD clearinghouse, from January 2012-June 2016. There were no changes in age, gender, BMI, race, ABO blood type, or panel-reactive antibody (PRA) of newly registering candidates over time, with consistent registration of hard-to-match candidates (59% type O and 38% PRA ≥97%). However, there was no accumulation of type O candidates over time, presumably due to increasing numbers of nondirected type O donors. Although there was an initial accumulation of candidates with PRA ≥97% (from 33% of the pool in 2012% to 43% in 2014, P = .03), the proportion decreased to 17% by June 2016 (P < .001). Some of this is explained by an increase in the proportion of candidates with PRA ≥97% who underwent a deceased donor kidney transplantation (DDKT) after the implementation of the Kidney Allocation System (KAS), from 8% of 2012 registrants to 17% of 2015 registrants (P = .02). In this large KPD clearinghouse, increasing participation of nondirected donors and the KAS have lessened the accumulation of hard-to-match candidates, but highly sensitized candidates remain hard-to-match.

Development of end-stage renal disease (ESRD) in living kidney donors is associated with increased graft loss in the recipients of their kidneys. Our goal was to investigate if this relationship was reflected at an earlier stage postdonation, possibly early enough for recipient risk prediction based on donor response to nephrectomy. Using national registry data, we studied 29 464 recipients and their donors from 2008-2016 to determine the association between donor 6-month postnephrectomy estimated GFR (eGFR) and recipient death-censored graft failure (DCGF). We explored donor BMI as an effect modifier, given the association between obesity and hyperfiltration. On average, risk of DCGF increased with each 10 mL/min decrement in postdonation eGFR (adjusted hazard ratio [aHR] 1.06, 95% confidence interval [CI] 1.02-1.10, P = .007). The association was attenuated with higher donor BMI (interaction P = .049): recipients from donors with BMI = 20 (aHR 1.12, 95% CI 1.04-1.19, P = .002) and BMI = 25 (aHR 1.07, 95% CI 1.03-1.12, P = .001) had a higher risk of DCGF with each 10 mL/min decrement in postdonation eGFR, whereas recipients from donors with BMI = 30 and BMI = 35 did not have a higher risk. The relationship between postdonation eGFR, donor BMI, and recipient graft loss can inform counseling and management of living donor kidney transplant recipients.

PURPOSE OF REVIEW:Due to the organ shortage, which prevents over 90 000 individuals in the United States from receiving life-saving transplants, the transplant community has begun to critically reevaluate whether organ sources that were previously considered too risky provide a survival benefit to waitlist candidates. RECENT FINDINGS:Organs that many providers were previously unwilling to use for transplantation, including kidneys with a high Kidney Donor Profile Index or from increased risk donors who have risk factors for window period hepatitis C virus (HCV) and HIV infection, have been shown to provide a survival benefit to transplant waitlist candidates compared with remaining on dialysis. The development of direct-acting antivirals to cure HCV infection has enabled prospective trials on the transplantation of organs from HCV-infected donors into HCV-negative recipients, with promising preliminary results. Changes in legislation through the HIV Organ Policy Equity Act have legalized transplantations from HIV-positive deceased donors to HIV-positive recipients for the first time in the United States. SUMMARY:Critical reexamination of deceased donor organs that were previously discarded has resulted in greater utilization of these organs, an increased number of deceased donor transplants, and the provision of life-saving treatment to more transplant waitlist candidates.

BACKGROUND:Few objective tests can be performed at admission for kidney transplantation [KT] to discern risk of increased length of stay [LOS], which is important for patient counseling and is associated with increased costs and mortality. The short physical performance battery [SPPB] is an easily administered, potentially modifiable, 3-part test of lower extremity function. SPPB score is associated with longer hospital LOS in older adults, and may provide similar utility in KT recipients given that ESRD is a disease of accelerated aging. The aim of this study was to characterize the association between SPPB-derived lower extremity function and LOS. METHODS:The SPPB was administered at KT admission in a prospective cohort of 595 recipients (8/2009-6/2016). The independent association between SPPB impairment (score ≤ 10) and LOS was tested with an adjusted conventional generalized gamma parametric survival model. RESULTS:Impaired recipients experienced longer LOS (median: 10 vs. 8 days; P <  0.001) with the greatest difference in percent discharged on day 10 (impaired: 54.5%, unimpaired: 73.3%). Discharge typically took 13% longer in the impaired group (relative time = 1.13; 95%CI: 1.05, 1.21, P = 0.001). Discharge for impaired recipients compared to unimpaired was least likely at day 5 (hazard ratio = 0.71; 95% CI:0.68, 0.74, P <  0.001). No differences in the SPPB impairment-LOS relationship were found by age (interaction P = 0.74). CONCLUSIONS:Pre-KT SPPB impairment was independently associated with longer LOS regardless of age, indicating that it is a useful, objective tool for pre-KT risk assessment in younger and older recipients that may help inform discharge planning.

BACKGROUND:In 2013, the Organ Procurement and Transplantation Network began requiring transplant centers in the United States to collect and report postdonation living kidney donor follow-up data at 6 months, 1 year, and 2 years. Despite this requirement, <50% of transplant centers have been able to collect and report the required data. Previous work identified a number of barriers to living kidney donor follow-up, including logistical and administrative barriers for transplant centers and cost and functional barriers for donors. Novel smartphone-based mobile health (mHealth) technologies might reduce the burden of living kidney donor follow-up for centers and donors. However, the attitudes and perceptions toward the incorporation of mHealth into postdonation care among living kidney donors are unknown. Understanding donor attitudes and perceptions will be vital to the creation of a patient-oriented mHealth system to improve living donor follow-up in the United States. OBJECTIVE:The goal of this study was to assess living kidney donor attitudes and perceptions associated with the use of mHealth for follow-up. METHODS:We developed and administered a cross-sectional 14-question survey to 100 living kidney donors at our transplant center. All participants were part of an ongoing longitudinal study of long-term outcomes in living kidney donors. The survey included questions on smartphone use, current health maintenance behaviors, accessibility to health information, and attitudes toward using mHealth for living kidney donor follow-up. RESULTS:Of the 100 participants surveyed, 94 owned a smartphone (35 Android, 58 iPhone, 1 Blackberry), 37 had accessed their electronic medical record on their smartphone, and 38 had tracked their exercise and physical activity on their smartphone. While 77% (72/93) of participants who owned a smartphone and had asked a medical question in the last year placed the most trust with their doctors, nurses, or other health care professionals regarding answering a health-related question, 52% (48/93) most often accessed health information elsewhere. Overall, 79% (74/94) of smartphone-owning participants perceived accessing living kidney donor information and resources on their smartphone as useful. Additionally, 80% (75/94) perceived completing some living kidney donor follow-up via mHealth as useful. There were no significant differences in median age (60 vs 59 years; P=.65), median years since donation (10 vs 12 years; P=.45), gender (36/75, 36%, vs 37/75, 37%, male; P=.57), or race (70/75, 93%, vs 18/19, 95%, white; P=.34) between those who perceived mHealth as useful for living kidney donor follow-up and those who did not, respectively. CONCLUSIONS:Overall, smartphone ownership was high (94/100, 94.0%), and 79% (74/94) of surveyed smartphone-owning donors felt that it would be useful to complete their required follow-up with an mHealth tool, with no significant differences by age, sex, or race. These results suggest that patients would benefit from an mHealth tool to perform living donor follow-up.

BACKGROUND:A prolonged living kidney donor evaluation may result in worse outcomes for transplant recipients. Better knowledge of the duration of this process may help inform future donors and identify opportunities for improvement. STUDY DESIGN:1 prospective and 1 retrospective cohort study. SETTING & PARTICIPANTS:At 16 Canadian and Australian transplantation centers (prospective cohort) and 5 Ontario transplantation centers (retrospective cohort), we assessed the duration of living kidney donor evaluation and explored donor, recipient, and transplantation factors associated with longer evaluation times. Data were obtained from 2 sources: donor medical records using chart abstraction and health care administrative databases. PREDICTORS:Donor and recipient demographics, direct versus paired donation, center-level variables. OUTCOMES:Duration of living donor evaluation. RESULTS:The median total duration of transplantation evaluation (time from when the candidate started the evaluation until donation) was 10.3 (IQR, 6.5-16.7) months. The median duration from evaluation start until approval to donate was 7.9 (IQR, 4.6-14.1) months, and from approval until donation was 0.7 (IQR, 0.3-2.4) months, respectively. The median time between the first and last consultation among donors who completed a nephrology, surgery, and psychosocial assessment in the prospective cohort was 3.0 (IQR, 1.0-6.3) months, and between computed tomography angiography and donation was 4.8 (IQR, 2.6-9.2) months. After adjustment, the total duration of transplantation evaluation was longer if the donor participated in paired donation (6.6 [95% CI, 1.6-9.7] months) and if the recipient was referred later relative to the donor's evaluation start date (0.9 [95% CI, 0.8-1.0] months [per month of delayed referral]). Results depended on whether the recipient was receiving dialysis. LIMITATIONS:Living donor candidates who did not donate were not included and proxy measures were used for some dates in the donor evaluation process. CONCLUSIONS:The duration of kidney transplant donor evaluation is variable and can be lengthy. Better understanding of the reasons for a prolonged evaluation may inform quality improvement initiatives to reduce unnecessary delays.

BACKGROUND:Among community-dwelling older adults, frailty is associated with heightened markers of inflammation and subsequent mortality. Although frailty is common among end-stage renal disease (ESRD) patients, the role of frailty and markers of inflammation in this population remains unclear. We quantified these associations in patients on the kidney transplant waitlist and tested whether frailty and/or markers of inflammation improve waitlist mortality risk prediction. METHODS:We studied 1975 ESRD patients on the kidney transplant waitlist (November 1, 2009, to February 28, 2017) in a multi-center cohort study of frailty. Serum inflammatory markers (interleukin-6 [IL-6], soluble tumor necrosis factor-α receptor-1 [sTNFR1], and C-reactive protein [CRP]) were analyzed in 605 of these participants; we calculated the inflammatory index score using IL-6 and sTNFR1. We compared the C-statistic of an established registry-based prediction model for waitlist mortality adding frailty and/or inflammatory markers (1 SD change in log IL-6, sTNFR1, CRP, or inflammatory index). RESULTS:The registry-based model had moderate predictive ability (c-statistic = 0.655). Frailty was associated with increased mortality (2.19; 95% confidence interval [CI], 1.26-3.79) but did not improve risk prediction (c-statistic = 0.646; P = 0.65). Like frailty, IL-6 (2.13; 95% CI, 1.41-3.22), sTNFR1 (1.70; 95% CI, 1.12-2.59), CRP (1.68; 95% CI, 1.06-2.67), and the inflammatory index (2.09; 95% CI, 1.38-3.16) were associated with increased mortality risk; unlike frailty, adding IL-6 (c-statistic = 0.777; P = 0.02), CRP (c-statistic = 0.728; P = 0.02), or inflammatory index (c-statistic = 0.777; P = 0.02) substantially improved mortality risk prediction. CONCLUSIONS:Frailty and markers of inflammation were associated with increased waitlist mortality risk, but only markers of inflammation significantly improved ESRD risk prediction. These findings help clarify the accelerated aging physiology of ESRD and highlight easy-to-measure markers of increased waitlist mortality risk.

In the United States, the Scientific Registry of Transplant Recipients (SRTR) provides publicly available quality report cards. These reports have historically rated transplant programs using a 3-tier system. In 2016, the SRTR temporarily transitioned to a 5-tier system, which classified more programs as under-performing. As part of a larger survey about transplant quality metrics, we surveyed members of the American Society of Transplant Surgeons and American Society of Transplantation (N = 280 respondents) on transplant center experiences with patient and payer responses to the 5-tier SRTR ratings. Over half of respondents (n = 137, 52.1%) reported ≥1 negative effect of the new 5-tier ranking system, including losing patients, losing insurers, increased concern among patients, and increased concern among referring providers. Few respondents (n = 35, 13.7%) reported any positive effects of the 5-tier ranking system. Lower SRTR-reported scores on the 5-tier scale were associated with increased risk of reporting at least one negative effect in a logistic model (P < 0.01). The change to a more granular rating system provoked an immediate response in the transplant community that may have long-term implications for transplant hospital finances and patient options for transplantation.