Faculty Bibliography

A widely accepted severe acute respiratory syndrome 2 (SARS-CoV-2) vaccine could protect vulnerable populations, but the willingness of solid organ transplant recipients (SOTRs) to accept a potential vaccine remains unknown.

Allografts from living kidney donors with hypertension may carry subclinical kidney disease from the donor to the recipient and, thus, lead to adverse recipient outcomes. We examined eGFR trajectories and all-cause allograft failure in recipients from donors with versus without hypertension, using mixed-linear and Cox regression models stratified by donor age. We studied a US cohort from 1/1/2005 to 6/30/2017; 49 990 recipients of allografts from younger (<50 years old) donors including 597 with donor hypertension and 21 130 recipients of allografts from older (≥50 years old) donors including 1441 with donor hypertension. Donor hypertension was defined as documented predonation use of antihypertensive therapy. Among recipients from younger donors with versus without hypertension, the annual eGFR decline was -1.03 versus -0.53 ml/min/m² (P = 0.002); 13-year allograft survival was 49.7% vs. 59.0% (adjusted allograft failure hazard ratio [aHR] 1.23; 95% CI 1.05-1.43; P = 0.009). Among recipients from older donors with versus without hypertension, the annual eGFR decline was -0.67 versus -0.66 ml/min/m² (P = 0.9); 13-year allograft survival was 48.6% versus 52.6% (aHR 1.05; 95% CI 0.94-1.17; P = 0.4). In secondary analyses, our inferences remained similar for risk of death-censored allograft failure and mortality. Hypertension in younger, but not older, living kidney donors is associated with worse recipient outcomes.

During the COVID-19 pandemic, there has been wide heterogeneity in the medical management of transplant recipients. We aimed to pragmatically capture immunosuppression practices globally following the early months of the pandemic. From June to September 2020, we surveyed 1267 physicians; 40.5% from 71 countries participated. Management decisions were made on a case-by-case basis by the majority (69.6%) of the programs. Overall, 76.8% performed ≥1 transplantation and many commented on avoiding high-risk transplantations. For induction, 26.5% were less likely to give T-cell depletion and 14.8% were more likely to give non-depleting agents. These practices varied by program-level factors more so than the COVID-19 burden. In patients with mild, moderate and severe COVID-19 symptoms 59.7%, 76.0%, and 79.5% decreased/stopped anti-metabolites, 23.2%, 45.4%, and 68.2% decreased/stopped calcineurin inhibitors, and 25.7%, 43.9%, and 57.7% decreased/stopped mTOR inhibitors, respectively. Also, 2.1%, 30.6%, and 46.0% increased steroids in patients with mild, moderate, and severe COVID-19 symptoms. For prevalent transplant recipients, some programs also reported decreasing/stopping steroids (1.8%), anti-metabolites (10.3%), calcineurin inhibitors (4.1%), and mTOR inhibitors (5.5%). Transplant programs changed immunosuppression practices but also avoided high-risk transplants and increased maintenance steroids. The long-term ramifications of these practices remain to be seen as programs face the aftermath of the pandemic.

Frailty is a multidimensional condition and is the result of the body's age-associated decline in physical, cognitive, physiological, and immune reserves. The aim of this systematic review is to assess the quality of evidence of the included studies, determine the prevalence of frailty among kidney transplant candidates, and evaluate the relationship between frailty and associated patient characteristics and outcomes after kidney transplantation.

Fine particulate matter (PM_2.5 ), a common form of air pollution which can induce systemic inflammatory response, is a risk factor for adverse health outcomes. Kidney transplant (KT) recipients are likely vulnerable to PM_2.5 due to comorbidity and chronic immunosuppression. We sought to quantify the association between PM_2.5 and post-KT outcomes. For adult KT recipients (1/1/2010-12/31/2016) in the Scientific Registry of Transplant Recipients, we estimated annual zip-code level PM_2.5 concentrations at the time of KT using NASA's SEDAC Global PM_2.5 Grids. We determined the associations between PM_2.5 and delayed graft function (DGF) and 1-year acute rejection using logistic regression and death-censored graft failure (DCGF) and mortality using Cox proportional hazard models. All models were adjusted for sociodemographics, recipient, transplant, and ZIP code level confounders. Among 87 233 KT recipients, PM_2.5 was associated with increased odds of DGF (OR = 1.59; 95% CI: 1.48-1.71) and 1-year acute rejection (OR = 1.31; 95% CI: 1.17-1.46) and increased risk of all-cause mortality (HR = 1.15; 95% CI: 1.07-1.23) but not DCGF (HR = 1.05; 95% CI: 0.97-1.51). In conclusion, PM_2.5 was associated with higher odds of DGF and 1-year acute rejection and elevated risk of mortality among KT recipients. Our study highlights the importance of considering environmental exposure as risk factors for post-KT outcomes.

BACKGROUND:Weight loss before kidney transplant (KT) is a known risk factor for weight gain and mortality, however, while unintentional weight loss is a marker of vulnerability, intentional weight loss might improve health. We tested whether pre-KT unintentional and intentional weight loss have differing associations with post-KT weight gain, graft loss and mortality. METHODS:Among 919 KT recipients from a prospective cohort study, we used adjusted mixed-effects models to estimate post-KT BMI trajectories, and Cox models to estimate death-uncensored graft loss, death-censored graft loss and all-cause mortality by 1-year pre-KT weight change category [stable weight (change ≤ 5%), intentional weight loss (loss > 5%), unintentional weight loss (loss > 5%) and weight gain (gain > 5%)]. RESULTS:The mean age was 53 years, 38% were Black and 40% were female. In the pre-KT year, 62% of recipients had stable weight, 15% had weight gain, 14% had unintentional weight loss and 10% had intentional weight loss. In the first 3 years post-KT, BMI increases were similar among those with pre-KT weight gain and intentional weight loss and lower compared with those with unintentional weight loss {difference +0.79 kg/m2/year [95% confidence interval (CI) 0.50-1.08], P < 0.001}. Only unintentional weight loss was independently associated with higher death-uncensored graft loss [adjusted hazard ratio (aHR) 1.80 (95% CI 1.23-2.62)], death-censored graft loss [aHR 1.91 (95% CI 1.12-3.26)] and mortality [aHR 1.72 (95% CI 1.06-2.79)] relative to stable pre-KT weight. CONCLUSIONS:This study suggests that unintentional, but not intentional, pre-KT weight loss is an independent risk factor for adverse post-KT outcomes.

The SRTR maintains the liver-simulated allocation model (LSAM), a tool for estimating the impact of changes to liver allocation policy. Integral to LSAM is a model that predicts the decision to accept or decline a liver for transplant. LSAM implicitly assumes these decisions are made identically for adult and pediatric liver transplant (LT) candidates, which has not been previously validated. We applied LSAM's decision-making models to SRTR offer data from 2013 to 2016 to determine its efficacy for adult (≥18) and pediatric (<18) LT candidates, and pediatric subpopulations-teenagers (≥12 to <18), children (≥2 to <12), and infants (<2)-using the area under the receiver operating characteristic (ROC) curve (AUC). For nonstatus 1A candidates, all pediatric subgroups had higher rates of offer acceptance than adults. For non-1A candidates, LSAM's model performed substantially worse for pediatric candidates than adults (AUC 0.815 vs. 0.922); model performance decreased with age (AUC 0.898, 0.806, 0.783 for teenagers, children, and infants, respectively). For status 1A candidates, LSAM also performed worse for pediatric than adult candidates (AUC 0.711 vs. 0.779), especially for infants (AUC 0.618). To ensure pediatric candidates are not unpredictably or negatively impacted by allocation policy changes, we must explicitly account for pediatric-specific decision making in LSAM.