Faculty Bibliography

BACKGROUND:In March 2020, COVID-19 infections began to rise exponentially in the USA, placing substantial burden on the healthcare system. As a result, there was a rapid change in transplant practices and policies, with cessation of most procedures. Our goal was to understand changes to pediatric kidney transplantation (KT) at the national level during the COVID-19 epidemic. METHODS:Using SRTR data, we examined changes in pediatric waitlist registration, waitlist removal or inactivation, and deceased donor and living donor (DDKT/LDKT) events during the start of the disease transmission in the USA compared with the same time the previous year. RESULTS:) in states with high vs. low COVID activity. Transplant recipients during the pandemic were more likely to have received a DDKT, but had similar calculated panel-reactive antibody (cPRA) values, waitlist time, and cause of kidney failure as before the pandemic. CONCLUSIONS:The COVID-19 pandemic initially reduced access to kidney transplantation among pediatric patients in the USA but has not had a sustained effect.

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.

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 AND OBJECTIVES:Patients with sickle cell disease-associated kidney failure have high mortality, which might be lowered by kidney transplantation. However, because they show higher post-transplant mortality compared with patients with other kidney failure etiologies, kidney transplantation remains controversial in this population, potentially limiting their chance of receiving transplantation. We aimed to quantify the decrease in mortality associated with transplantation in this population and determine the chance of receiving transplantation with sickle cell disease as the cause of kidney failure as compared with other etiologies of kidney failure. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:Using a national registry, we studied all adults with kidney failure who began maintenance dialysis or were added to the kidney transplant waiting list in 1998-2017. To quantify the decrease in mortality associated with transplantation, we measured the absolute risk difference and hazard ratio for mortality in matched pairs of transplant recipients versus waitlisted candidates in the sickle cell and control groups. To compare the chance of receiving transplantation, we estimated hazard ratios for receiving transplantation in the sickle cell and control groups, treating death as a competing risk. RESULTS:=0.8). Nonetheless, the sickle cell group was less likely to receive transplantation than the controls (subdistribution hazard ratio, 0.73; 95% confidence interval, 0.61 to 0.87). Similar disparities were found among waitlisted candidates (subdistribution hazard ratio, 0.62; 95% confidence interval, 0.53 to 0.72). CONCLUSIONS:Patients with sickle cell disease-associated kidney failure exhibited similar decreases in mortality associated with kidney transplantation as compared with those with other kidney failure etiologies. Nonetheless, the sickle cell population was less likely to receive transplantation, even after waitlist registration.

BACKGROUND:Kidney allograft failure is a common cause of end-stage renal disease. We aimed to develop a dynamic artificial intelligence approach to enhance risk stratification for kidney transplant recipients by generating continuously refined predictions of survival using updates of clinical data. METHODS:In this observational study, we used data from adult recipients of kidney transplants from 18 academic transplant centres in Europe, the USA, and South America, and a cohort of patients from six randomised controlled trials. The development cohort comprised patients from four centres in France, with all other patients included in external validation cohorts. To build deeply phenotyped cohorts of transplant recipients, the following data were collected in the development cohort: clinical, histological, immunological variables, and repeated measurements of estimated glomerular filtration rate (eGFR) and proteinuria (measured using the proteinuria to creatininuria ratio). To develop a dynamic prediction system based on these clinical assessments and repeated measurements, we used a Bayesian joint models-an artificial intelligence approach. The prediction performances of the model were assessed via discrimination, through calculation of the area under the receiver operator curve (AUC), and calibration. This study is registered with ClinicalTrials.gov, NCT04258891. FINDINGS/RESULTS:13 608 patients were included (3774 in the development cohort and 9834 in the external validation cohorts) and contributed 89 328 patient-years of data, and 416 510 eGFR and proteinuria measurements. Bayesian joint models showed that recipient immunological profile, allograft interstitial fibrosis and tubular atrophy, allograft inflammation, and repeated measurements of eGFR and proteinuria were independent risk factors for allograft survival. The final model showed accurate calibration and very high discrimination in the development cohort (overall dynamic AUC 0·857 [95% CI 0·847-0·866]) with a persistent improvement in AUCs for each new repeated measurement (from 0·780 [0·768-0·794] to 0·926 [0·917-0·932]; p<0·0001). The predictive performance was confirmed in the external validation cohorts from Europe (overall AUC 0·845 [0·837-0·854]), the USA (overall AUC 0·820 [0·808-0·831]), South America (overall AUC 0·868 [0·856-0·880]), and the cohort of patients from randomised controlled trials (overall AUC 0·857 [0·840-0·875]). INTERPRETATION/CONCLUSIONS:Because of its dynamic design, this model can be continuously updated and holds value as a bedside tool that could refine the prognostic judgements of clinicians in everyday practice, hence enhancing precision medicine in the transplant setting. FUNDING/BACKGROUND:MSD Avenir, French National Institute for Health and Medical Research, and Bettencourt Schueller Foundation.

BACKGROUND:Transplant surgery fellowship has evolved over the years and today there are 66 accredited training programs in the US and Canada. There is growing concern, however, about the number of US-trained general surgery residents pursuing transplant surgery. In this study, we examined the transplant surgery pipeline, comparing it with other surgical subspecialty fellowships, and characterized the resident transplantation experience. METHODS:Datasets were compiled and analyzed from surgical fellowship match data obtained from the National Resident Matching Program and ACGME reports and relative fellowship competitiveness was assessed. The surgical resident training experience in transplantation was evaluated. RESULTS:From 2006 to 2018, a total of 1,094 applicants have applied for 946 transplant surgery fellowship positions; 299 (27.3%) were US graduates. During this period, there was a 0.8% decrease per year in US-trained surgical residents matching into transplant surgery (p = 0.042). In addition, transplant surgery was one of the least competitive fellowships compared with other National Resident Matching Program surgical subspeciality fellowships, as measured by the number of US applicants per available fellowship position, average number of fellowship programs listed on each applicant's rank list, and proportion of unfilled fellowship positions (each, p < 0.05). Finally, from 2015 to 2017, there were 57 general surgery residency programs that produced 77 transplant surgery fellows, but nearly one-half of the fellows (n = 36 [46.8%]) came from 16 (28.1%) programs. CONCLUSIONS:Transplant surgery is one of the least competitive and sought after surgical fellowships for US-trained residents. These findings highlight the need for dedicated efforts to increase exposure, mentorship, and interest in transplantation to recruit strong US graduates.