Faculty Bibliography

BACKGROUND/UNASSIGNED:Advancements in medical technology, healthcare delivery, and organ allocation resulted in improved patient/graft survival for older (age ≥65) kidney transplant (KT) recipients. However, the recent trends in these post-KT outcomes are uncertain in light of the mounting burden of cardiovascular disease, changing kidney allocation policies, heterogeneity in candidates' risk profile, and the coronavirus disease 2019 pandemic. Thus, we examined secular trends in post-KT outcomes among older and younger KT recipients over the last 3 decades. METHODS/UNASSIGNED:We identified 73 078 older and 378 800 younger adult (aged 18-64) recipients using Scientific Registry of Transplant Recipients (1990-2022). KTs were grouped into 6 prepandemic eras and 1 postpandemic-onset era. Kaplan-Meier and Cox proportional hazards models were used to examine temporal trends in post-KT mortality and death-censored graft failure. RESULTS/UNASSIGNED:From 1990 to 2022, a 19-fold increase in the proportion of older KT recipients was observed compared to a 2-fold increase in younger adults despite a slight decline in the absolute number of older recipients in 2020. The mortality risk for older recipients between 2015 and March 14, 2020, was 39% (adjusted hazard ratio [aHR] = 0.61, 95% confidence interval [CI], 0.50-0.75) lower compared to 1990-1994, whereas that for younger adults was 47% lower (aHR = 0.53, 95% CI, 0.48-0.59). However, mortality risk during the pandemic was 25% lower (aHR = 0.75, 95% CI, 0.61-0.93) in older adults and 37% lower in younger adults (aHR = 0.63, 95% CI, 0.56-0.70) relative to 1990-1994. For both populations, the risk of graft failure declined over time and was unaffected during the pandemic relative to the preceding period. CONCLUSIONS/UNASSIGNED:The steady improvements in 5-y mortality and graft survival were disrupted during the pandemic, particularly among older adults. Specifically, mortality among older adults reflected rates seen 20 y prior.

BACKGROUND:The prevalence of sarcopenia is markedly higher in kidney transplant candidates than in the general population. It is a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, which increases the risk of adverse postoperative outcomes. METHODS:We studied the impact of computed tomography defined preoperative sarcopenia, defined as a skeletal muscle index below age and gender specific cut-off values, on postoperative physical functional outcomes (grip strength, 4-m walking test, timed up and go, and sit to stand) at 6 months follow up. RESULTS: = 0.154). CONCLUSIONS:We identified a significant association between sarcopenia existing pre-transplantation and poorer 6 months post-transplantation physical functioning with respect to hand grip strength and timed up and go tests in kidney transplant recipients. These results could be used to preoperatively identify patients with an increased risk of poor postoperative physical functional outcome, allowing for preoperative interventions to mitigate these risks.

Older compatible living donor kidney transplant (CLDKT) recipients have higher mortality and death-censored graft failure (DCGF) compared to younger recipients. These risks may be amplified in older incompatible living donor kidney transplant (ILDKT) recipients who undergo desensitization and intense immunosuppression. In a 25-center cohort of ILDKT recipients transplanted between September 24, 1997, and December 15, 2016, we compared mortality, DCGF, delayed graft function (DGF), acute rejection (AR), and length of stay (LOS) between 234 older (age ≥60 years) and 1172 younger (age 18-59 years) recipients. To investigate whether the impact of age was different for ILDKT recipients compared to 17 542 CLDKT recipients, we used an interaction term to determine whether the relationship between posttransplant outcomes and transplant type (ILDKT vs CLDKT) was modified by age. Overall, older recipients had higher mortality (hazard ratio: _1.632.07_2.65, P < .001), lower DCGF (hazard ratio: _0.360.53_0.77, P = .001), and AR (odds ratio: _0.390.54_0.74, P < .001), and similar DGF (odds ratio: _0.461.03_2.33, P = .9) and LOS (incidence rate ratio: _0.880.98_1.10, P = 0.8) compared to younger recipients. The impact of age on mortality (interaction P = .052), DCGF (interaction P = .7), AR interaction P = .2), DGF (interaction P = .9), and LOS (interaction P = .5) were similar in ILDKT and CLDKT recipients. Age alone should not preclude eligibility for ILDKT.

A more granular donor kidney grading scale, the kidney donor profile index (KDPI), has recently emerged in contradistinction to the standard criteria donor/expanded criteria donor framework. In this paper, we built a Markov decision process model to evaluate the survival, quality-adjusted life years (QALY), and cost advantages of using high-KDPI kidneys based on multiple KDPI strata over a 60-month time horizon as opposed to remaining on the waiting list waiting for a lower-KDPI kidney. Data for the model were gathered from the Scientific Registry of Transplant Recipients and the United States Renal Data System Medicare parts A, B, and D databases. Of the 129,024 phenotypes delineated in this model, 65% of them would experience a survival benefit, 81% would experience an increase in QALYs, 87% would see cost-savings, and 76% would experience cost-savings per QALY from accepting a high-KDPI kidney rather than remaining on the waiting list waiting for a kidney of lower-KDPI. Classification and regression tree analysis (CART) revealed the main drivers of increased survival in accepting high-KDPI kidneys were wait time ≥30 months, panel reactive antibody (PRA) <90, age ≥45 to 65, diagnosis leading to renal failure, and prior transplantation. The CART analysis showed the main drivers of increased QALYs in accepting high-kidneys were wait time ≥30 months, PRA <90, and age ≥55 to 65.

The latent viral reservoir(LVR) remains a major barrier to HIV-1 curative strategies. It is unknown whether receiving a liver transplant from a donor with HIV might lead to an increase in the LVR since the liver is a large lymphoid organ. We found no differences in intact provirus, defective provirus, or the ratio of intact to defective provirus between recipients with ART-supporesed HIV who received a liver from a donor with(n = 19) or without HIV(n = 10). All measures remained stable from baseline by one-year post transplant. These data demonstrate that the LVR is stable after liver transplantation in people living with HIV.

BACKGROUND:The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variability), provides a ripe opportunity for AI-based clinical decision support (CDS). However, AI-CDS for transplant applications must consider important concerns regarding fairness (ie, health equity). The objective of this study was to use human-centered design methods to elicit providers' perceptions of AI-CDS for liver transplant listing decisions. METHODS:In this multicenter qualitative study conducted from December 2020 to July 2021, we performed semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. We used inductive coding and constant comparison analysis of interview data. RESULTS:Analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient's role in the AI-CDS. CONCLUSIONS:Overall, providers interviewed were cautiously optimistic about the potential for AI-CDS to improve clinical and equitable outcomes for patients. These findings can guide multidisciplinary developers in the design and implementation of AI-CDS that deliberately considers health equity.