Faculty Bibliography

Out-of-sequence (OOS) allocation, the process by which organ procurement organizations (OPOs) can deviate from standard rank lists of potential recipients to expeditiously allocate deceased-donor kidneys, is rising in the U.S. We aimed to determine whether current OPO reporting practices obscure the extent of OOS allocation. Using match-run data for all U.S. deceased-donor kidney transplants from 2021-2023, we defined "miscoded" OOS (mOOS) allocation transplants as those with use of the 799 or 898 OPO- initiated refusal codes ("other, specify") with free text responses clearly indicating OOS allocation, and compared these to "explicit" OOS (eOOS) allocation, wherein OOS transplants are appropriately coded using refusal codes 861-863. We found that the prevalence of mOOS allocation increased from 2021 (122 transplants) to 2023 (430 transplants) and accounted for 12% of all OOS transplants by 2023. Organs allocated via mOOS had a lower median KDPI than those allocated via eOOS (51% vs 55%, p <0.01). While an increasing number of OPOs used mOOS throughout the study period, the practice remained concentrated overall, with 5 "outlier" OPOs performing 66% of mOOS allocations in 2023. These findings highlight the need for stricter oversight of organ allocation and underscore the responsibility of the OPTN to ensure proper data reporting.

RATIONALE & OBJECTIVE/OBJECTIVE:The kidney allocation system (KAS250), using circle-based distribution, attempts to address geographic disparities through broader sharing of deceased-donor kidney allografts. This study evaluated the association between KAS250 and likelihood of deceased-donor kidney transplantation (DDKT) among wait-listed candidates, and whether the policy has differentially affected centers with shorter versus longer waiting time. STUDY DESIGN/METHODS:Retrospective cohort study. SETTING & PARTICIPANTS/METHODS:160,941 candidates waitlisted at 176 transplant centers between March 2017 and March 2024. EXPOSURE/METHODS:KAS250 allocation policy. OUTCOME/RESULTS:Rate of DDKT. ANALYTICAL APPROACH/METHODS:Multivariable Cox regression, modeling KAS250 as a time-dependent variable. RESULTS:KAS250 was not independently associated with likelihood of DDKT overall (HR, 1.01 vs pre-KAS250 [95% CI, 0.97-1.04]). KAS250's association with likelihood of DDKT varied across centers from HR, 0.18 (DDKT less likely after KAS250), to HR, 17.12 (DDKT more likely) and varied even among neighboring centers. KAS250 was associated with decreased DDKT at 25.6% and increased DDKT at 18.2% of centers. Centers with previously long median waiting times (57+months) experienced increased likelihood of DDKT after KAS250 (HR, 1.20 [95% CI, 1.15-1.26]) whereas centers with previously short median waiting times (6-24 months; HR, 0.88 [95% CI, 0.84-0.92]) experienced decreased likelihood of DDKT. LIMITATIONS/CONCLUSIONS:Retrospective study of allocation policy changes, confounded by multiple changes over the study time frame. CONCLUSIONS:Association between KAS250 and DDKT varied across centers. For 1 in 4 centers, DDKT was less likely after KAS250 relative to pre-KAS250 trends. Candidates at centers with previously long waiting times experienced an increased likelihood of DDKT after KAS250. Thus, broader distribution of kidneys may be associated with improved equity in access to DDKT, but additional strategies may be needed to minimize disparities between centers. PLAIN-LANGUAGE SUMMARY/UNASSIGNED:This study examines how a recent policy change, KAS250, aimed at broadening the geographic sharing of deceased-donor kidneys, has impacted likelihood of kidney transplantation in the United States. Historically, kidney allocation occurred within local geographic boundaries, leading to unequal rates of transplantation across regions. KAS250, implemented in March 2021, replaced this system with a broader allocation radius of 250 miles around the donor hospital. Using national registry data, the study found that while there was no overall significant increase in the likelihood of transplantation nationally under KAS250, the policy's effect varied widely even among neighboring transplant centers. One quarter of centers experienced a decrease in the likelihood of DDKT after KAS250. In contrast, centers with longer pre-KAS250 waiting times experienced an increased likelihood of transplantation, suggesting some success in reducing disparities between centers. Ongoing surveillance will be needed to ensure KAS250 is meeting the intended aim of more equitably distributing organs.

Transmitted donor-derived glomerular diseases in the allograft kidney are rare, especially when encountered in an allograft from a living donor. To date, only individual reports of donor-derived membranous nephropathy (MN) have been described. In this report, we present a case of MN discovered in a postreperfusion biopsy of a living-donor allograft. A follow-up biopsy 3 weeks later demonstrated persistent deposits. Thirteen months posttransplant, the recipient showed mildly worsening proteinuria but stable kidney function. To further our understanding of this exceedingly rare complication, we share our experience with 7 additional in-house cases together with 6 cases described in the literature to date. A minority of the donors were living. Most donors did not exhibit significant proteinuria illustrating how predonation screening could potentially miss donor-derived MN. Reactivity for phospholipase A2 receptor and thrombospondin type 1 domain containing 7A were negative in all stained cases. On follow-up, recipients variably exhibited slow resolution of the immune deposits, variable degrees of proteinuria (mainly subnephrotic), and no significant impairment of kidney function. Donor-derived MN is rare, phospholipase A2 receptor-negative, and can still be encountered in living donors despite rigorous screening. This report provides a brief examination of the pathology, clinical, and laboratory features of such patients involved.

BACKGROUND:Among heart transplantation (HT) recipients, the accuracy of serum creatinine (sCr)-based estimated glomerular filtration rate (eGFR) may be limited by fluctuations in muscle mass. Cystatin C (cysC) is less influenced by muscle mass, but its levels may increase with obesity and steroid use. Herein, we (1) longitudinally compared eGFRcysC and eGFRsCr among HT recipients; (2) investigated the association of body mass index (BMI), steroid use, and muscle mass with discrepancies between eGFRs; and (3) explored the implications of eGFRcysC use on valganciclovir (VGC) dosing. METHODS:) were calculated with negative values corresponding to eGFRsCr > eGFRcysC and positive values to eGFRcysC > eGFRsCr. In a patient subset (n = 21), pectoralis muscle measures were obtained. RESULTS:values. The use of eGFRcysC would have led to VGC dose adjustment in 46% of samples, predominantly resulting in dose reduction. CONCLUSIONS:Among HT recipients, eGFRcysC and eGFRsCr markedly differ with implications for VGC dosing. The observed discrepancies may reflect changes in body composition and steroid use.

INTRODUCTION/BACKGROUND:How offer notifications are distributed early in the kidney allocation timeline, including how widely they are offered, is unclear. A better understanding of offer notification practices across organ procurement organizations (OPOs) may identify opportunities for more efficient allocation. METHODS:We merged the Scientific Registry of Transplant Recipients potential transplant recipient file with additional offer notification time stamps to identify 54 631 deceased-donor kidney match runs from 2017 to 2023. Offer notifications for a given match run are sent to candidates/centers in "batches." We quantified the number of offers in the initial batch-which theoretically reflects the OPO's initial estimate of how widely a kidney should be offered-and compared this metric across OPOs. RESULTS:Kidneys were offered to a median of 14 candidates (IQR 9-38) in the first batch of notifications, and this varied across OPOs from 3 to 746 candidates per initial batch. Batch size at the OPO-level did not correlate with rank at kidney placement or OPO nonuse rate. OPOs in the highest quartile of batch size sent more offers (median 100) than presumably necessary to place kidneys (median rank at placement 21), and OPOs in the lowest quartile of batch size sent fewer offers (6) than needed to place kidneys (rank at placement 19). CONCLUSIONS:Offer notification practices vary widely across OPOs, and many OPOs offer kidneys far more widely than necessary for placement. Optimization of offer notification practices may reduce unnecessary communications. Further research into allocation processes is needed to identify opportunities to improve efficiency of allocation for OPOs and transplant centers.

Administrative claims data could provide a unique opportunity to identify acute rejection (AR) events using specific antirejection medications and to validate rejected data reported to the Organ Procurement and Transplantation Network. This retrospective cohort study examined differences in registry-reported events and those identified using claims data among adult kidney transplant recipients from 2012 to 2017 using Standard Analysis Files from the US Renal Data System. Rejection rates, survival estimates, and center-level differences were assessed using each approach. Among 45 880 first-time kidney transplant recipients, we identified 3841 AR events within 12 months of transplant reported by centers in the registry; claims data yielded 2945 events. Of all events occurring within 12 months of transplant, 48.5% were reported using registry only, 32.9% were identified using claims only, and 18.6% were identified using both approaches. A 3-year death-censored graft survival probability was 90.0%, 88.4%, and 81.2% (P < .001) for ARs identified using registry only, claims data only, and both approaches, respectively. The large discordance between registry-reported and claims-based events suggests incomplete and potentially inaccurate reporting of events in the Organ Procurement Transplant Network registry. These findings have important implications for analyses that use AR data and underscore the need for improved capture of clinically meaningful events.