Faculty Bibliography

The Kidney Allocation System (KAS) has resulted in fewer pediatric kidneys being allocated to pediatric deceased donor kidney transplant (pDDKT) recipients. This had prompted concerns that post-pDDKT outcomes may worsen. To study this, we used SRTR data to compare the outcomes of 953 pre-KAS pDDKT (age <18 years) recipients (December 4, 2012-December 3, 2014) with the outcomes of 934 post-KAS pDDKT recipients (December 4, 2014-December 3, 2016). We analyzed mortality and graft loss by using Cox regression, delayed graft function (DGF) by using logistic regression, and length of stay (LOS) by using negative binomial regression. Post-KAS recipients had longer pretransplant dialysis times (median 1.26 vs 1.07 years, P = .02) and were more often cPRA 100% (2.0% vs 0.1%, P = .001). Post-KAS recipients had less graft loss than pre-KAS recipients (hazard ratio [HR]: _0.35 0.54_0.83 , P = .005) but no statistically significant differences in mortality (HR: _0.29 0.72_1.83 , P = .5), DGF (odds ratio: _0.93 1.32_1.93 , P = .2), and LOS (LOS ratio: _0.96 1.06_1.19 , P = .4). After adjusting for donor-recipient characteristics, there were no statistically significant post-KAS differences in mortality (adjusted HR: _0.37 1.04_2.92 , P = .9), DGF (adjusted odds ratio: _0.94 1.41_2.13 , P = .1), or LOS (adjusted LOS ratio: _0.93 1.04_1.16 , P = .5). However, post-KAS pDDKT recipients still had less graft loss (adjusted HR: _0.38 0.59_0.91 , P = .02). KAS has had a mixed effect on short-term posttransplant outcomes for pDDKT recipients, although our results are limited by only 2 years of posttransplant follow-up.

BACKGROUND:Body mass index of living kidney donors has increased substantially. Determining candidacy for live kidney donation among obese individuals is challenging because many donation-related risks among this subgroup remain unquantified, including even basic postdonation mortality. METHODS:We used data from the Scientific Registry of Transplant Recipients linked to data from the Centers for Medicare and Medicaid Services to study long-term mortality risk associated with being obese at the time of kidney donation among 119,769 live kidney donors (1987-2013). Donors were followed for a maximum of 20 years (interquartile range 6.0-16.0). Cox proportional hazards estimated the risk of postdonation mortality by obesity status at donation. Multiple imputation accounted for missing obesity data. RESULTS:Obese (body mass index ≥ 30) living kidney donors were more likely male, African American, and had higher blood pressure. The estimated risk of mortality 20 years after donation was 304.3/10,000 for obese and 208.9/10,000 for nonobese living kidney donors. Adjusting for age, sex, race/ethnicity, blood pressure, baseline estimated glomerular filtration rate, relationship to recipient, smoking, and year of donation, obese living kidney donors had a 30% increased risk of long-term mortality compared with their nonobese counterparts (adjusted hazard ratio: 1.32, 95% CI: 1.09-1.60, P = .006). The impact of obesity on mortality risk did not differ significantly by sex, race or ethnicity, biologic relationship, baseline estimated glomerular filtration rate, or among donors who did and did not develop postdonation kidney failure. CONCLUSION:These findings may help to inform selection criteria and discussions with obese persons considering living kidney donation.

BACKGROUND:United States transplant centers are required to report follow-up data for living kidney donors for 2 years post-donation. However, living kidney donor (LKD) follow-up is often incomplete. Mobile health (mHealth) technologies could ease data collection burden but have not yet been explored in this context. METHODS:We conducted semi-structured in-depth interviews with a convenience sample of 21 transplant providers and thought leaders about challenges in LKD follow-up, and the potential role of mHealth in overcoming these challenges. RESULTS:Participants reported challenges conveying the importance of follow-up to LKDs, limited data from international/out-of-town LKDs, and inadequate staffing. They believed the 2-year requirement was insufficient, but expressed difficulty engaging LKDs for even this short time and inadequate resources for longer-term follow-up. Participants believed an mHealth system for post-donation follow-up could benefit LKDs (by simplifying communication/tasks and improving donor engagement) and transplant centers (by streamlining communication and decreasing workforce burden). Concerns included cost, learning curves, security/privacy, patient language/socioeconomic barriers, and older donor comfort with mHealth technology. CONCLUSIONS:Transplant providers felt that mHealth technology could improve LKD follow-up and help centers meet reporting thresholds. However, designing a secure, easy to use, and cost-effective system remains challenging.

Children receiving a LDLT have superior post-transplant outcomes, but this procedure is only used for 10% of transplant recipients. Better understanding about barriers toward LDLT and the sociodemographic characteristics that influence these underlying mechanisms would help to inform strategies to increase its use. We conducted an online, anonymous survey of parents/caregivers for children awaiting, or have received, a liver transplant regarding their knowledge and attitudes about LDLT. The survey was completed by 217 respondents. While 97% of respondents understood an individual could donate a portion of their liver, only 72% knew the steps in evaluation, and 69% understood the donor surgery was covered by the recipient's insurance. Individuals with public insurance were less likely than those with private insurance to know the steps for LDLT evaluation (44% vs 82%; P < 0.001). Respondents with public insurance were less likely to know someone that had been a living donor (44% vs 56%; P = 0.005) as were individuals without a college degree (64% vs 85%; P = 0.007). Nearly all respondents generally trusted their healthcare team. Among respondents, 82% believed they were well-informed about LDLT but individuals with public insurance were significantly less likely to feel well-informed (67% vs 87%; P = 0.03) and to understand how donor surgery might impact donor work/time off (44% vs 81%; P = 0.001). Substantial gaps exist in parental understanding about LDLT, including its evaluation, potential benefits, and complications. Greater emphasis on addressing these barriers, especially to individuals with fewer resources, will be helpful to expand the use of LDLT.

BACKGROUND AND OBJECTIVES:Hypertension in older kidney donor candidates is viewed as safe. However, hypertension guidelines have evolved and long-term outcomes have not been explored. We sought to quantify the 15-year risk of ESKD and mortality in older donors (≥50 years old) with versus those without hypertension. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:A United States cohort of 24,533 older donors from 1999 to 2016, including 2265 with predonation hypertension, were linked to Centers for Medicare and Medicaid Services data and the Social Security Death Master File to ascertain ESKD development and mortality. The exposure of interest was predonation hypertension. From 2004 to 2016, hypertension was defined as documented predonation use of antihypertensive therapy, regardless of systolic BP or diastolic BP; from 1999 to 2003, when there was no documentation of antihypertensive therapy, hypertension was defined as predonation systolic BP ≥140 or diastolic BP ≥90 mm Hg. RESULTS:=0.34). CONCLUSIONS:Compared with older donors without hypertension, older donors with hypertension had higher risk of ESKD, but not mortality, for 15 years postdonation. However, the absolute risk of ESKD was small.

Information about wait-list time has been reported as one of the single most frequently asked questions by individuals awaiting a transplant but data regarding wait-list time have not been processed in a useful way for pediatric candidates. To predict chance of receiving a DDLT, we identified 6471 pediatric (<18 years), non status-1A, liver-only transplant candidates between 2006 and 2017 from the SRTR. Cox regression with shared frailty for DSA level effect was used to model the association of blood type, weight, allocation PELD and MELD, and DSA with chance of DDLT. Jackknife technique was used for validation. Median (interquartile range) wait-list time was 100 (34-309) days. Non-O Blood type, higher PELD/MELD score at listing, and DSA were associated with increased chance of DDLT, while age 1-5 years and 10-18 years was associated with lower chance of DDLT (P < 0.001 for all variables). Our model accurately predicted chance of transplant (C-statistic = 0.68) and was able to predict DDLT at specific follow-up times (eg, 3 months). This model can serve as the basis for an online tool that would provide useful information for pediatric wait-list candidates.

BACKGROUND:Despite providing survival benefit, increased risk for infectious disease (IRD) kidney offers are declined at 1.5 times the rate of non-IRD kidneys. Elucidating sources of variation in IRD kidney offer acceptance may highlight opportunities to expand use of these life-saving organs. METHODS:To explore center-level variation in offer acceptance, we studied 6765 transplanted IRD kidneys offered to 187 transplant centers between 2009 and 2017 using Scientific Registry of Transplant Recipients data. We used multilevel logistic regression to determine characteristics associated with offer acceptance and to calculate the median odds ratio (MOR) of acceptance (higher MOR indicates greater heterogeneity). RESULTS:Higher quality kidneys (per 10 units kidney donor profile index; adjusted odds ratio [aOR], 0.94; 95% confidence interval [CI], 0.92-0.95), higher yearly volume (per 10 deceased donor kidney transplants; aOR, 1.08, 95% CI, 1.06-1.10), smaller waitlist size (per 100 candidates; aOR, 0.97; 95% CI, 0.95-0.98), and fewer transplant centers in the donor service area (per center; aOR, 0.88; 95% CI, 0.85-0.91) were associated with greater odds of IRD acceptance. Adjusting for donor and center characteristics, we found wide heterogeneity in IRD offer acceptance (MOR, 1.96). In other words, if listed at a center with more aggressive acceptance practices, a candidate could be 2 times more likely to have an IRD kidney offer accepted. CONCLUSIONS:Wide national variation in IRD kidney offer acceptance limits access to life-saving kidneys for many transplant candidates.

We examined a novel linkage of national US donor registry data with records from a pharmacy claims warehouse (2007-2016) to examine associations (adjusted hazard ratio, _LCL aHR_UCL ) of post-donation fills of antidiabetic medications (ADM, insulin or non-insulin agents) with body mass index (BMI) at donation and other demographic and clinical factors. In 28 515 living kidney donors (LKDs), incidence of ADM use at 9 years rose in a graded manner with higher baseline BMI: underweight, 0.9%; normal weight, 2.1%; overweight, 3.5%; obese, 8.5%. Obesity was associated with higher risk of ADM use compared with normal BMI (aHR, _3.36 4.59_6.27 ). Metformin was the most commonly used ADM and was filled more often by obese than by normal weight donors (9-year incidence, 6.87% vs 1.85%, aHR, _3.55 5.00_7.04 ). Insulin use was uncommon and did not differ significantly by BMI. Among a subgroup with BMI data at the 1-year post-donation anniversary (n = 19 528), compared with stable BMI, BMI increase >0.5 kg/m² by year 1 was associated with increased risk of subsequent ADM use (aHR, _1.03 1.48_2.14, P = .04). While this study did not assess the impact of donation on the development of obesity, these data support that among LKD, obesity is a strong correlate of ADM use.

BACKGROUND AND OBJECTIVES:The risk of hypertension attributable to living kidney donation remains unknown as does the effect of developing postdonation hypertension on subsequent eGFR. We sought to understand the association between living kidney donation, hypertension, and long-term eGFR by comparing donors with a cohort of healthy nondonors. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:We compared 1295 living kidney donors with median 6 years of follow-up with a weighted cohort of 8233 healthy nondonors. We quantified the risk of self-reported hypertension using a parametric survival model. We examined the association of hypertension with yearly change in eGFR using multilevel linear regression and clustering by participant, with an interaction term for race. RESULTS:=0.01, respectively, after hypertension). CONCLUSIONS:Kidney donors are at higher risk of hypertension than similar healthy nondonors, regardless of race. Donors who developed hypertension had a plateau in the usual postdonation increase of eGFR.

Background/UNASSIGNED:Limited data are available regarding clinical implications of lower renal function after living kidney donation. We examined a novel integrated database to study associations between postdonation estimated glomerular filtration rate (eGFR) and use of antihypertensive medication (AHM) treatment after living kidney donation. Methods/UNASSIGNED:) between AHM use and postdonation eGFR levels (random effect) with fixed effects for baseline donor factors. Results/UNASSIGNED:). Conclusions/UNASSIGNED:This novel linkage illustrates the ability to identify postdonation kidney function and associate it with clinically meaningful outcomes; lower eGFR after living kidney donation is a correlate of AHM treatment requirements. Further work should define relationships of postdonation renal function, hypertension, and other morbidity measures.