Prior transplant regulations have resulted in unintended consequences, including decreased volumes. A new waitlist mortality metric for centers was approved on December 6, 2021. We hypothesized that kidney candidates waiting for transplant after this approval would be at increased risk of delisting. Adult kidney candidates waiting between January 1, 2022, and December 2, 2024 (era 2) were subject to the new metric and compared to candidates waiting between June 1, 2020, and December 31, 2021 (era 1). We estimated the time to removal from the waitlist for being too sick for transplant or "other" causes, accounting for the competing risk of death and transplant, before and after metric approval. We assessed for effect modification by demographics. The cause-specific hazard of delisting for being too sick increased by 25% among candidates in era 2 compared to era 1 (95% confidence interval [CI]: 1.20, 1.30); the cause-specific hazard of delisting for "other" causes increased by 34% (95% CI: 1.28, 1.40). These increases were accompanied by a decrease in waitlist mortality (cause-specific hazard ratio: 0.80, 95% CI: 0.78, 0.83) and an increase in transplant (cause-specific hazard ratio: 1.09, 95% CI: 1.08, 1.11) among those remaining on the list. Delisting disproportionately increased among Black candidates and candidates with insurance other than private, Medicare, or Medicaid. Implementation of outcome metrics without a corresponding focus on access may result in unintended consequences.

Solid organ transplant (SOT) recipients frequently undergo cytomegalovirus (CMV) PCR testing throughout their post-transplant course. While CMV infections are common early (< 2 years) after SOT, the prevalence of CMV infections beyond 2 years has not been reported.Figure 1:CMV PCR testing and CMV DNAemia beyond two years after transplant in solid organ transplant recipients who survived to two yearsTable 1:Solid organ transplant recipients who underwent CMV PCR testing at least once beyond two years after transplanta) Chi squared and Fisher exact tests were used for categorical variables and the Mann-Whitney U test was used for continuous variables.b) Heart includes 3 heart-liver recipients and 21 heart-kidney recipients. Kidney includes 61 kidney-pancreas recipients. Liver includes 54 liver-kidney recipients. Intestine includes 4 intestine-liver-pancreas recipients. We performed a single center retrospective study to determine the period prevalence of CMV PCR testing, CMV DNAemia, and CMV disease beyond 2 years after non-lung SOT. All non-lung, adult SOT recipients (SOTR) who underwent their first SOT between 2/24/14-8/1/22 and who survived through 2 years were included. Patients were followed until death, re-transplant, or 8/1/24 (whichever came first). CMV DNAemia was defined as any plasma CMV load ≥ 450 IU/mL, which was a common threshold to initiate preemptive CMV therapy at our institution. CMV PCRs were performed for evaluation of symptoms of CMV disease or as asymptomatic screening at clinician discretion. Patients did not receive CMV prophylaxis beyond 6 months, except for the 30-days following treatment with lymphodepleting antibodies for rejection.Figure 2:Solid organ transplant recipients with CMV infections beyond two years after transplanta) All cases of CMV disease in D+R- and D-R- consisted of CMV syndrome.b ) This seropositive recipient (R+) was an intestine-liver-pancreas recipient who developed proven CMV enteritis involving the small bowel allograft within two weeks after starting corticosteroids for treatment of rejection.c ) Patients were considered to have received high-dose steroids if they had received ≥ 40 mg/day of prednisone (or equivalent) for at least 7 days within the 30 days before the first occurrence of CMV ≥ 450 IU/mL beyond the 2-year post-transplant date.d) Two seropositive (R+) kidney recipients with asymptomatic CMV DNAemia who received high-dose steroids also received anti-thymocyte globulin within the previous 30 days. Both were taking valganciclovir prophylaxis that was underdosed for renal function at the time of initial CMV DNAemia. No other patients with CMV DNAemia received lymphodepleting antibodies within 30 days prior to their first CMV viral load ≥ 450 IU/mL.e) One case of CMV disease (CMV syndrome) in a D-R- kidney recipient was likely due to community acquired CMV infection Of 2261 SOTR who survived to 2 years after their first SOT, 1695 (75%) underwent CMV PCR testing at least once in the period beyond 2 years, with a mean of 8 CMV PCRs per tested patient (range 1-85) during a mean follow-up time of 2.5 years (range 0.1-8.40) beyond the 2-year mark. CMV DNAemia occurred in 36/1695 tested patients (2.1%, Figure 1). Heart transplant and CMV donor positive/recipient negative (D+R-) status were associated with DNAemia (Table 1). Nine of 15 (60%) CMV seropositive (R+) SOTR with DNAemia received high-dose steroids within 30 days of DNAemia onset compared to 1/20 (5%) D+R- SOTR with DNAemia (Fisher exact p < 0.001). CMV disease occurred in 7 tested patients (0.4%), including five D+R- SOTR without prior CMV infection, one R+ patient who received recent high-dose steroids for rejection, and one CMV D-R- patient with primary, community-acquired infection (Figure 2). CMV infections were rare beyond 2 years after non-lung SOT. Late CMV disease occurred in a small number of CMV seronegative SOTR without prior CMV infection and one CMV seropositive SOTR recently treated with high-dose steroids. However, CMV PCR testing beyond the 2-year mark likely has low diagnostic yield for most non-lung SOTR. Madeleine R. Heldman, MD, MS, Karius, Inc: Advisor/Consultant Jennifer Saullo, MD, Pharm D, RMEI Medical Education: Honoraria|UpToDate: Royalties Julie M. Steinbrink, MD, MHS, Biomeme: patents for gene expression classifiers of fungal infection|McGraw Hill Publishing: royalties

Background:Normothermic machine perfusion (NMP) improves utilization of extended criteria liver grafts, but the optimal delivery strategy-whether in-transit or back-to-base-remains uncertain. Methods:Adult recipients of donation after circulatory death (DCD) liver transplants between January 1, 2022, and January 1, 2024, were identified using the national transplant database. In-transit NMP was defined as grafts coded as machine perfused; back-to-base NMP was inferred for noncoded grafts with a cold ischemia time of ≥10 h. Baseline characteristics, geographic distribution, and outcomes-including acute rejection, length of stay, and graft survival-were compared. Multivariable Cox regression was used to adjust for dialysis and recipient hospitalization status. A sensitivity analysis was performed, limited to cases with cold ischemia time of ≥10 h across both groups. Results:Among 1217 DCD liver transplants using NMP, 936 (77%) were in-transit and 281 (23%) were back-to-base. In-transit NMP was more commonly used in the Western United States, whereas back-to-base was concentrated in the Midwest and Southeast. In-transit recipients had higher rates of pretransplant dialysis (3.1% versus 0.7%; P < 0.05) and shorter preservation times (14.1 versus 16.0 h; P < 0.05). Median hospital stay was shorter in the in-transit group (8 versus 9 d, P < 0.001). There were no significant differences in acute rejection (P = 0.15) or 1-y graft survival (93.3% versus 90.5%, P = 0.23). In adjusted analysis, back-to-base NMP was not associated with increased graft failure risk (hazard ratio 1.46; 95% confidence interval, 0.90-2.38; P = 0.13). Findings were consistent in the sensitivity analysis (n = 1001). Conclusions:In-transit and back-to-base NMP strategies yield comparable clinical outcomes in DCD liver transplantation. Strategy selection may be guided by logistical infrastructure and center-level expertise without compromising recipient outcomes.

Carli J. Lehr, MD, PhD; Lyla Mourany, MS; Paul Gunsalus, MS; Johnie Rose, MD, PhD; Maryam Valapour, MD, MPP; Jarrod E. Dalton, PhD

Advances in solid organ transplantation, such as improved organ preservation technologies and novel approaches to immunosuppression management, have the potential to improve outcomes in transplant recipients. However, despite these developments, there are persistent disparities in access to transplantation across, and within, certain countries. Low-income and middle-income countries have particularly low rates of transplantation, as well as less access to new technologies, mainly due to limited infrastructure and resources. Additionally, marginalised groups, especially racially and ethnically minoritised people and individuals from low socioeconomic backgrounds, might be most susceptible to these inequities worldwide. In this Series paper, we focus on how policies can advance equity in the field of transplantation, both within individual health systems and across different countries. We propose policy solutions to make progress towards equity in access to transplantation and better outcomes for all patients with end-stage organ disease who could benefit from transplantation.

Non-White patients with interstitial lung disease (ILD) experience racial disparities in lung transplant waitlist mortality. Race-specific equations for spirometry may contribute by underestimating restriction severity in non-White candidates. We analyzed US lung transplant candidates to assess for disparities in forced vital capacity (FVC) at listing, comparing absolute and adjusted values using race-specific and race-neutral equations. We identified 17,457 adults with ILD listed May 4, 2005 to September 31, 2023. At listing, mean absolute FVC was higher for White patients (2.03 ± 0.80 liters) than Black patients (1.61 ± 0.67 liters) and Asian patients (1.49 ± 0.86 liters). Differences were attenuated after applying race-specific equations (White patients 50.0 ± 17.5%, Black patients 47.7 ± 17.9%, Asian patients 46.2 ± 24.2%). Compared with race-neutral equations, race-specific equations had higher odds of classifying FVC as severe (≤40%) requiring listing in White patients (OR 1.37, 95% CI 1.28-1.40) but lower odds in Black patients (OR 0.82, 95% CI 0.74-0.90). Using race-neutral equations might help improve racial disparities for lung transplant candidates with ILD.

This cohort study examines the validity of an electronic health record data model for organ transplantation.

OBJECTIVE:Nearly 30% of kidneys from deceased donors are discarded annually in the USA. A recent study indicated that a significant number of patients would accept lower-quality kidneys to avoid long waits. We expand on previous work to assess how the distribution of patient preferences for lower-quality kidneys would change with patient time on the transplant list. METHODS:We conducted a discrete-choice experiment with US pre-transplant patients waitlisted for kidneys from deceased donors. Respondents were asked to evaluate tradeoffs between expected graft survival and waiting time. We used a logit-based regression with patient covariates to explain membership of three patient-preference phenotypes previously identified with these data. Specifically, we tested the degree to which phenotype membership changed with waiting time and how such changes were moderated by observable patient characteristics such as age, insulin use, recipient function, time on dialysis, and household income. RESULTS:Waiting time had a nonlinear effect on phenotype probabilities, with more patients expected to be willing to accept lower-quality kidneys as waiting time increases. Patients with longer insulin dependence, lower income, and limited function were more likely to accept lower-quality kidneys. Higher income was significantly associated with the probability of being willing to wait for better future kidneys. Dialysis time had no significant effect. CONCLUSIONS:Our analysis provides insights into time-varying effects using cross-sectional data. Results suggest that patient preferences for organ acceptability vary with waiting time and are moderated by health status and socioeconomic factors. Longer waits and worse health statuses were generally associated with greater willingness to accept lower-quality kidneys.

Background:Transplant center processes for determining candidacy are complex, poorly documented, ambiguous, and variable across centers. Opaque and nonstandardized transplant processes can compromise data collection and lead to inconsistent outcomes. Methods:To understand process variation and data quality in transplantation, we surveyed 8 abdominal transplant centers in an existing research consortium about their processes of care for liver, kidney, and pancreas transplants. We used the Systems Engineering Initiative for Patient Safety model to identify variation related to people, tasks, tools, environment, and processes. Results:Centers varied in their processes across phases of transplant care, including screening referral, waitlist maintenance, and posttransplant follow-up. Regarding referrals, transplant centers chose their locations for outreach to and education for referring providers based on historical density or by request (63%). Additionally, screening of referred patients for transplant evaluation varied across centers related to screening method, screening timing/attempts, and who determines eligibility. For patients declined for listing, only 25% of centers had a formal appeal process (liver only), and most centers had either an informal appeal process (liver: 50%, kidney and pancreas: 87.5%) or none (liver: 25%, kidney and pancreas: 12.5%). Conclusions:In light of increased national attention to improving data collection, processes of care, and workforce efficiency, our findings provide insight into processes that may inform effective transplant practices and identify targets for future interventions.