Faculty Bibliography

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.

Using nonideal kidneys for transplant quickly might reduce the discard rate of kidney transplants. We studied changing kidney allocation to eliminate sequential offers, instead making offers to multiple centers for all nonlocally allocated kidneys, so that multiple centers must accept or decline within the same 1 hour. If more than 1 center accepted an offer, the kidney would go to the highest-priority accepting candidate. Using 2010 Kidney-Pancreas Simulated Allocation Model-Scientific Registry for Transplant Recipients data, we simulated the allocation of 12 933 kidneys, excluding locally allocated and zero-mismatch kidneys. We assumed that each hour of delay decreased the probability of acceptance by 5% and that kidneys would be discarded after 20 hours of offers beyond the local level. We simulated offering kidneys simultaneously to small, medium-size, and large batches of centers. Increasing the batch size increased the percentage of kidneys accepted and shortened allocation times. Going from small to large batches increased the number of kidneys accepted from 10 085 (92%) to 10 802 (98%) for low-Kidney Donor Risk Index kidneys and from 1257 (65%) to 1737 (89%) for high-Kidney Donor Risk Index kidneys. The average number of offers that a center received each week was 10.1 for small batches and 16.8 for large batches. Simultaneously expiring offers might allow faster allocation and decrease the number of discards, while still maintaining an acceptable screening burden.

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:Cannabis is categorized as an illicit drug in most US states, but legalization for medical indications is increasing. Policies and guidance on cannabis use in transplant patients remain controversial. METHODS:We examined a database linking national kidney transplant records (n = 52 689) with Medicare claims to identify diagnoses of cannabis dependence or abuse (CDOA) and associations [adjusted hazard ratio (aHR) with 95% upper and lower confidence limits (CLs)] with graft, patient, and other clinical outcomes. RESULTS:CDOA was diagnosed in only 0.5% (n = 254) and 0.3% (n = 163) of kidney transplant recipients in the years before and after transplant, respectively. Patients with pretransplant CDOA were more likely to be 19 to 30 years of age and of black race, and less likely to be obese, college-educated, and employed. After multivariate and propensity adjustment, CDOA in the year before transplant was not associated with death or graft failure in the year after transplant, but was associated with posttransplant psychosocial problems such as alcohol abuse, other drug abuse, noncompliance, schizophrenia, and depression. Furthermore, CDOA in the first year posttransplant was associated with an approximately 2-fold increased risk of death-censored graft failure (aHR, 2.29; 95% CL, 1.59-3.32), all-cause graft loss (aHR, 2.09; 95% CL, 1.50-2.91), and death (aHR, 1.79; 95% CL, 1.06-3.04) in the subsequent 2 years. Posttransplant CDOA was also associated with cardiovascular, pulmonary, and psychosocial problems, and with events such as accidents and fractures. CONCLUSIONS:Although associations likely, in part, reflect associated conditions or behaviors, clinical diagnosis of CDOA in the year after transplant appears to have prognostic implications for allograft and patient outcomes. Recipients with posttransplant CDOA warrant focused monitoring and support.

BACKGROUND:Transplant recipients are living longer than ever before, and occasionally require acute care surgery for nontransplant-related issues. We hypothesized that while both acute care surgeons (ACS) and transplant surgeons would feel comfortable operating on this unique patient population, both would believe transplant centers provide superior care. METHODS:, Fisher's exact, and Kruskal-Wallis tests. RESULTS:We obtained 230 responses from ACS and 204 from transplant surgeons. ACS and transplant surgeons believed care is better at transplant centers (78% and 100%), and transplant recipients requiring acute care surgery should be transferred to a transplant center (80.2% and 87.2%). ACS felt comfortable operating (97.5%) and performing laparoscopy (94.0%) on transplant recipients. ACS cited transplant medication use as the most important underlying cause of increased surgical complications for transplant recipients. Transplant surgeons felt it was their responsibility to perform acute care surgery on transplant recipients (67.3%), but less so if patient underwent transplant at a different institution (26.5%). Transplant surgeons cited poor transplanted organ resiliency as the most important underlying cause of increased surgical complications for transplant recipients. CONCLUSIONS:ACS and transplant surgeons feel comfortable performing laparoscopic and open acute care surgery on transplant recipients, and recommend treating transplant recipients at transplant centers, despite the lack of supportive evidence. Elucidating common goals allows surgeons to provide optimal care for this unique patient population.

BACKGROUND:Recipients of nonkidney solid organ transplants (nkSOT) are living longer, and 11%-18% will develop end stage renal disease (ESRD). While our general inclination is to treat nkSOT recipients who develop ESRD with a kidney transplant (KT), an increasing number are developing ESRD at an older age where KT may not be the most appropriate treatment. It is possible that the risk of older age and prior nkSOT might synergize to make KT too risky, but this has never been explored. METHODS:To examine death-censored graft loss and mortality for KT recipients with and without prior nkSOT, we used Scientific Registry of Transplant Recipients data to identify 42 089 older (age ≥65) KT recipients between 1995 and 2016. Additionally, to better understand treatment options for these patients and survival benefit of KT, we identified 5023 older (age ≥65) with prior nkSOT recipients listed for subsequent KT, of whom 863 received transplants. RESULTS:Compared with 41 159 older KT recipients without prior nkSOT, death-censored graft loss was similar (adjusted hazard ratio [aHR]: 1.13, 95% CI: 0.93-1.37, P = 0.2), but mortality (aHR: 1.40, 95% CI: 1.28-1.54, P < 0.001) was greater for older KT recipients with prior nkSOT. Nonetheless, in a survival benefit model (survival with versus without the transplant), among older prior nkSOT recipients, KT decreased the risk of mortality by more than half (aHR: 0.47, 95% CI: 0.42-0.54, P < 0.001). CONCLUSIONS:Older prior nkSOT recipients who subsequently develop ESRD derive survival benefit from KT, but graft longevity is limited by overall survival in this population. These findings can help guide patient counseling for this challenging population.

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:Neighborhood poverty has been associated with worse outcomes after live donor kidney transplantation (LDKT), and prior work suggests that women with kidney disease may be more susceptible to the negative influence of poverty than men. As such, our goal was to examine whether poverty differentially affects women in influencing LDKT outcomes. METHODS:Using data from the Scientific Registry of Transplant Recipients and US Census, we performed multivariable Cox regression to compare outcomes among 18 955 women and 30 887 men who received a first LDKT in 2005-2014 with follow-up through December 31, 2016. RESULTS:Women living in poor (adjusted hazard ratio [aHR], 1.30; 95% confidence interval [CI], 1.13-1.50) and middle-income (aHR, 1.26; 95% CI, 1.14-1.40) neighborhoods had higher risk of graft loss than men, but there were no differences in wealthy areas (aHR, 1.07; 95% CI, 0.88-1.29). Women living in wealthy (aHR, 0.71; 95% CI, 0.59-0.87) and middle-income (aHR, 0.82; 95% CI, 0.74-0.92) neighborhoods incurred a survival advantage over men, but there were no statistically significant differences in mortality in poor areas (aHR, 0.85; 95% CI, 0.72-1.01). CONCLUSIONS:Given our findings that poverty is more strongly associated with graft loss in women, targeted efforts are needed to specifically address mechanisms driving these disparities in LDKT outcomes.

Pediatric kidney transplant candidates often have multiple potential living donors (LDs); no evidence-based tool exists to compare potential LDs, or to decide between marginal LDs and deceased donor (DD) kidney transplantation (KT). We developed a pediatric living kidney donor profile index (P-LKDPI) on the same scale as the DD KDPI by using Cox regression to model the risk of all-cause graft loss as a function of living donor characteristics and DD KDPI. HLA-B mismatch (adjusted hazard ratio [aHR] per mismatch = _1.04 1.27_1.55 ), HLA-DR mismatch (aHR per mismatch = _1.02 1.23_1.49 ), ABO incompatibility (aHR = _1.20 3.26_8.81 ), donor systolic blood pressure (aHR per 10 mm Hg = _1.01 1.07_1.18 ), and donor estimated GFR (eGFR; aHR per 10 mL/min/1.73 m² = _0.88 0.94_0.99 ) were associated with graft loss after LDKT. Median (interquartile range [IQR]) P-LKDPI was -25 (-56 to 12). 68% of donors had P-LKDPI <0 (less risk than any DD kidney) and 25% of donors had P-LKDPI >14 (more risk than median DD kidney among pediatric KT recipients during the study period). Strata of LDKT recipients of kidneys with higher P-LKDPI had a higher cumulative incidence of graft loss (39% at 10 years for P-LDKPI ≥20, 28% for 20> P-LKDPI ≥-20, 23% for -20 > P-LKDPI ≥-60, 19% for P-LKDPI <-60 [log rank P < .001]). The P-LKDPI can aid in organ selection for pediatric KT recipients by allowing comparison of potential LD and DD kidneys.