Faculty Bibliography

We surveyed US transplant centers to assess practices regarding the evaluation and selection of living kidney donors based on metabolic, cardiovascular, and substance use risk factors. Our companion article describes renal aspects of the evaluation. Response rate was 31%. Compared with 2005, programs have become more accepting of hypertensive candidates: 65% in 2017% vs 41% in 2005 consider candidates with hypertension well controlled with 1 medication. One notable exception is black hypertensive candidates, who are frequently excluded regardless of severity. The most common body mass index (BMI) cutoff remains 35 kg/m² , and fewer programs now consider candidates with BMI >40 kg/m² . A 2-hour oral glucose tolerance test of ≥140 mg/dL remains the most common criterion for exclusion of prediabetic candidates. One quarter to one third of programs exclude based on isolated cardiac abnormalities, such as mild aortic stenosis; a similar proportion consider these candidates only if older than 50 years. Cigarette or marijuana smoking are infrequently criteria for exclusion, although 45% and 37% programs, respectively, require cessation 4 weeks prior to surgery. In addition to providing an overview of current practices in living kidney donor evaluation, our study highlights the importance of research evaluating outcomes with various comorbidities to guide practice.

BACKGROUND:Optimizing amino acid (eplet) histocompatibility at first transplant decreases the risk of de novo donor-specific antibody (dnDSA) development and may improve long-term graft survival in pediatric kidney transplant recipients (KTR). We performed a retrospective analysis of pediatric KTR and their respective donors to identify eplets most commonly associated with dnDSA formation. METHODS:Eplet mismatch analysis was performed in a cohort of 125 pediatric KTR-donor pairs (2006-2018). We determined the prevalence of each eplet mismatch and quantified the percentage of exposed patients who developed dnDSA for each mismatched eplet. RESULTS:Recipient median age was 14 (IQR 8-17) years with a racial distribution of 42% Black, 48% Caucasian, and 5.6% Middle-Eastern. Median eplet load varied significantly by recipient race, Black 82 (IQR 58-98), White 60 (IQR 44-81) and Other 66 (IQR 61-76), p = 0.002. Forty-four percent of patients developed dnDSA after median 37.1 months. Compared to dnDSA- patients, dnDSA+ patients had higher median eplet load, 64 (IQR 46-83) vs. 77 (IQR 56-98), p = 0.012. The most common target of dnDSA were eplets expressed in HLA-A*11 and A2 in Class I, and HLA-DQ6 and DQA5 in Class II. The most commonly mismatched eplets were not the most likely to result in dnDSA formation. CONCLUSIONS:In a racially diverse population, only a subset of eplets was linked to antibody formation. Eplet load alone is not a sufficient surrogate for eplet immunogenicity. These findings illustrate the need to optimize precision in donor selection and allocation to improve long-term graft outcomes. Graphical Abstract A higher resolution version of the Graphical abstract is available as Supplementary information.

We surveyed US transplant programs to assess practices used to assess kidney health in living kidney donor candidates in 2017; the response rate was 31%. In this report, we focus on the kidney; a companion piece focuses on the metabolic and cardiovascular aspects of candidate evaluation. Compared to 2005, programs have become more stringent in accepting younger candidates and less stringent in accepting older candidates. The 24-hour creatinine clearance remains the mainstay for kidney function assessment, with 74% continuing to use a value below 80 mL/min/1.73 m² for exclusion and 22% using age-based criteria. ApoL1 genotyping is obtained routinely or selectively by 45%, half of which use the high-risk genotype as an absolute exclusion criterion. For history of symptomatic stones, 49% accept if there is no current radiographic evidence of stones and urine profile is low risk, 80%-95% consider candidates with unilateral asymptomatic stones, but only 33%-48% consider if stones are bilateral. In addition, 14% use the risk assessment tool developed by Grams et al routinely for decision-making, and 42% use it sometimes. Also, 57% reported not having yet determined a risk threshold for acceptable postdonation risk above which candidates are excluded. Contemporary practice variation underscores the need for better evidence to guide the donor selection process.

The transmission of cancer from a donor organ is a rare event but has important consequences. Aim of this systematic review was to summarize all the published evidence on cancer transmission in kidney recipients. We reviewed published case reports and series describing the outcome of recipients with donor-transmitted cancer until August 2019. A total of 128 papers were included, representing 234 recipients. The most common transmitted cancers were lymphoma (n = 48, 20.5%), renal cancer (42, 17.9%), melanoma (40, 17.1%), non-small cell lung cancer (n = 13, 5.6%), neuroendocrine cancers comprising small cell lung cancer (n = 11, 4.7%) and choriocarcinoma (n = 10, 4.3%). There was a relative lack of glioblastoma and gastrointestinal cancers with only 6 and 5 cases, respectively. Melanoma and lung cancer had the worst prognosis, with 5-years overall survival of 43% and 19%, respectively; while renal cell cancer and lymphomas had a favorable prognosis with 5-years overall survival of 93 and 63%, respectively. Metastasis of cancer outside the graft was the most important adverse prognostic factor. Overall reporting was good, but information on donors' cause of death and investigations at procurement was often lacking. Epidemiology of transmitted cancer has evolved, thanks to screening with imaging and blood tests, as choriocarcinoma transmission have almost abolished, while melanoma and lymphoma are still difficult to detect and prevent.

The first sustained increase in live kidney donation in the United States in 15 years was observed from 2017 to 2019. To help sustain this surge, we studied 35 900 donors (70.3% white, 14.5% Hispanic, 9.3% black, 4.4% Asian) to understand the increase in 2017-2019 vs 2014-2016 using Poisson regression. Among biologically related donors aged <35, 35-49, and ≥50 years, the number of donors did not change across race/ethnicity but increased by 38% and 29% for Hispanic and black ≥50. Among unrelated donors <35, 35-49, and ≥50, white donors increased by 18%, 14%, and 27%; Hispanic donors <35 did not change but increased by 22% and 35% for 35-49 and ≥50; black donors <35 declined by 23% and did not change for 35-49 and ≥50; Asian donors did not change. Among kidney paired donors <35, 35-49, and ≥50, white donors increased by 42%, 50%, and 68%; Hispanic donors <35 and 35-49 increased by 36% and 55% and did not change for ≥50; black donors did not change; Asian donors <35 did not change but increased by 107% and 82% for 35-49 and ≥50. The increase in donation was driven predominantly by unrelated and paired white donors. Donation among unrelated black individuals should be promoted.

BACKGROUND:Live kidney donors (LKDs) account for nearly a third of kidney transplants in the United States. While donor nephrectomy poses minimal post-surgical risk, LKDs face an elevated adjusted risk of developing chronic diseases such as hypertension, diabetes, and end-stage renal disease. Routine screening presents an opportunity for the early detection and management of chronic conditions. Transplant hospital reporting requirements mandate the submission of laboratory and clinical data at 6-months, 1-year, and 2-years after kidney donation, but less than 50% of hospitals are able to comply. Strategies to increase patient engagement in follow-up efforts while minimizing administrative burden are needed. We seek to evaluate the effectiveness of using small financial incentives to promote patient compliance with LKD follow-up. METHODS/DESIGN:We are conducting a two-arm randomized controlled trial (RCT) of patients who undergo live donor nephrectomy at The Johns Hopkins Hospital Comprehensive Transplant Center (MDJH) and the University of Maryland Medical Center Transplant Center (MDUM). Eligible donors will be recruited in-person at their first post-surgical clinic visit or over the phone. We will use block randomization to assign LKDs to the intervention ($25 gift card at each follow-up visit) or control arm (current standard of care). Follow-up compliance will be tracked over time. The primary outcome will be complete (all components addressed) and timely (60 days before or after expected visit date), submission of LKD follow-up data at required 6-month, 1-year, and 2-year time points. The secondary outcome will be transplant hospital-level compliance with federal reporting requirements at each visit. Rates will be compared between the two arms following the intention-to-treat principle. DISCUSSION:Small financial incentivization might increase patient compliance in the context of LKD follow-up, without placing undue administrative burden on transplant providers. The findings of this RCT will inform potential center- and national-level initiatives to provide all LKDs with small financial incentives to promote engagement with post-donation monitoring efforts. TRIAL REGISTRATION:ClinicalTrials.gov number: NCT03090646 Date of registration: March 2, 2017 Sponsors: Johns Hopkins University, University of Maryland Medical Center Funding: The Living Legacy Foundation of Maryland.

An increasing number of studies claim machine learning (ML) predicts transplant outcomes more accurately. However, these claims were possibly confounded by other factors, namely, supplying new variables to ML models. To better understand the prospects of ML in transplantation, we compared ML to conventional regression in a "common" analytic task: predicting kidney transplant outcomes using national registry data. We studied 133 431 adult deceased-donor kidney transplant recipients between 2005 and 2017. Transplant centers were randomly divided into 70% training set (190 centers/97 787 recipients) and 30% validation set (82 centers/35 644 recipients). Using the training set, we performed regression and ML procedures [gradient boosting (GB) and random forests (RF)] to predict delayed graft function, one-year acute rejection, death-censored graft failure C, all-cause graft failure, and death. Their performances were compared on the validation set using -statistics. In predicting rejection, regression (C = _0.601 0.611_0.621 ) actually outperformed GB (C = _0.581 0.591_0.601 ) and RF (C = _0.569 0.579_0.589 ). For all other outcomes, the C-statistics were nearly identical across methods (delayed graft function, 0.717-0.723; death-censored graft failure, 0.637-0.642; all-cause graft failure, 0.633-0.635; and death, 0.705-0.708). Given its shortcomings in model interpretability and hypothesis testing, ML is advantageous only when it clearly outperforms conventional regression; in the case of transplant outcomes prediction, ML seems more hype than helpful.

Kidney transplant recipients who develop symptoms consistent with coronavirus disease 2019 (COVID-19) are bringing unique challenges to health care professionals. Telemedicine has surged dramatically since the pandemic in effort to maintain patient care and reduce the risk of COVID-19 exposure to patients, health care workers, and the public. Herein we present reports of 3 kidney transplant recipients with COVID-19 who were managed using telemedicine via synchronous video visits integrated with an electronic medical record system, from home to inpatient settings. We demonstrate how telemedicine helped assess, diagnose, triage, and treat patients with COVID-19 while avoiding a visit to an emergency department or outpatient clinic. While there is limited information about the duration of viral shedding for immunosuppressed patients, our findings underscore the importance of using telemedicine in the follow-up care for kidney transplant recipients with COVID-19 who have recovered from symptoms but might have persistently positive nucleic acid tests. Our experience emphasizes the opportunities of telemedicine in the management of kidney transplant recipients with COVID-19 and in the maintenance of uninterrupted follow-up care for such immunosuppressed patients with prolonged viral shedding. Telemedicine may help increase access to care for kidney transplant recipients during and beyond the pandemic as it offers a prompt, safe, and convenient platform in the delivery of care for these patients. Yet, to advance the practice of telemedicine in the field of kidney transplantation, barriers to increasing the widespread implementation of telemedicine should be removed, and research studies are needed to assess the effectiveness of telemedicine in the care of kidney transplant recipients.

Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our poor understanding of these risks, many centers have paused or reduced KT activity, yet data to inform such decisions are lacking. To quantify the benefit/harm of KT in this context, we conducted a simulation study of immediate-KT vs delay-until-after-pandemic for different patient phenotypes under a variety of potential COVID-19 scenarios. A calculator was implemented (http://www.transplantmodels.com/covid_sim), and machine learning approaches were used to evaluate the important aspects of our modeling. Characteristics of the pandemic (acquisition risk, CFR) and length of delay (length of pandemic, waitlist priority when modeling deceased donor KT) had greatest influence on benefit/harm. In most scenarios of COVID-19 dynamics and patient characteristics, immediate KT provided survival benefit; KT only began showing evidence of harm in scenarios where CFRs were substantially higher for KT recipients (eg, ≥50% fatality) than for waitlist registrants. Our simulations suggest that KT could be beneficial in many centers if local resources allow, and our calculator can help identify patients who would benefit most. Furthermore, as the pandemic evolves, our calculator can update these predictions.

In March 2020, coronavirus disease 2019 (COVID-19) spread rapidly nationally, causing widespread emergent changes to the health system. Our goal was to understand the impact of the epidemic on kidney transplantation (KT), at both the national and center levels, accounting statistically for waitlist composition. Using Scientific Registry of Transplant Recipients data, we compared data on observed waitlist registrations, waitlist mortality, and living-donor and deceased-donor kidney transplants (LDKT/DDKT) March 15-April 30, 2020 to expected events calculated from preepidemic data January 2016-February 2020. There were few changes before March 15, at which point the number of new listings/DDKT/LDKT dropped to 18%/24%/87% below the expected value (all P < .001). Only 12 centers performed LDKT March 15-31; by April 30, 40 centers had resumed LDKT. The decline in new listings and DDKT was greater among states with higher per capita confirmed COVID-19 cases. The number of waitlist deaths was 2.2-fold higher than expected in the 5 states with highest COVID-19 burden (P < .001). DCD DDKT and regional/national imports declined nationwide but most steeply in states with the highest COVID-19 burden. The COVID-19 epidemic has resulted in substantial changes to KT; we must adapt and learn rapidly to continue to provide safe access to transplantation and limit the growing indirect toll of an already deadly disease.