Center-level patterns of indicated willingness to and actual acceptance of marginal kidneys

Single-center analysis of organ offers and workload for liver and kidney allocation

The volume of abdominal organ offers received by the Baylor Simmons Transplant Institute has increased over time, resulting in a higher workload for our donor call team. To quantify the increase in organ offers, determine the characteristics of these offers, and estimate the impact on our transplant center workload, we collected center-specific organ offer data from May 2019 to July 2021 using the UNOS Center Acceptance and Refusal Evaluation Report and performed a time study that collected the number of communications and time spent on communications for organ offers made during a typical week. The total offers per month increased by 140% (270/month to 648/month), while the number of transplanted organs remained stable. In addition, the percentage of offers for organs that were never transplanted increased from 54% to 75%. In a representative week-long time study, surgeons made 505, center coordinators 590, and answering service coordinators 318 distinct communications, averaging 3, 4, and 2 communications/hour. Between November 2019 and July 2021, offer-related workload increased by an estimated 97%. These results demonstrate a sizeable inefficiency in abdominal organ allocation associated with a nonrecoverable cost to our transplant center.

National Variation in Increased Infectious Risk Kidney Offer Acceptance

BACKGROUND

Despite providing survival benefit, increased risk for infectious disease (IRD) kidney offers are declined at 1.5 times the rate of non-IRD kidneys. Elucidating sources of variation in IRD kidney offer acceptance may highlight opportunities to expand use of these life-saving organs.

METHODS

To explore center-level variation in offer acceptance, we studied 6765 transplanted IRD kidneys offered to 187 transplant centers between 2009 and 2017 using Scientific Registry of Transplant Recipients data. We used multilevel logistic regression to determine characteristics associated with offer acceptance and to calculate the median odds ratio (MOR) of acceptance (higher MOR indicates greater heterogeneity).

RESULTS

Higher quality kidneys (per 10 units kidney donor profile index; adjusted odds ratio [aOR], 0.94; 95% confidence interval [CI], 0.92-0.95), higher yearly volume (per 10 deceased donor kidney transplants; aOR, 1.08, 95% CI, 1.06-1.10), smaller waitlist size (per 100 candidates; aOR, 0.97; 95% CI, 0.95-0.98), and fewer transplant centers in the donor service area (per center; aOR, 0.88; 95% CI, 0.85-0.91) were associated with greater odds of IRD acceptance. Adjusting for donor and center characteristics, we found wide heterogeneity in IRD offer acceptance (MOR, 1.96). In other words, if listed at a center with more aggressive acceptance practices, a candidate could be 2 times more likely to have an IRD kidney offer accepted.

CONCLUSIONS

Wide national variation in IRD kidney offer acceptance limits access to life-saving kidneys for many transplant candidates.

Changes in Utilization and Discard of HCV Antibody-Positive Deceased Donor Kidneys in the Era of Direct-Acting Antiviral Therapy

BACKGROUND

The availability of direct-acting antiviral (DAA) therapy might have impacted use of hepatitis C virus (HCV)-infected (HCV+) deceased donor kidneys for transplantation.

METHODS

We used 2005 to 2018 Scientific Registry of Transplant Recipients data to identify 18 936 candidates willing to accept HCV+ kidneys and 3348 HCV+ recipients of HCV+ kidneys. We compared willingness to accept, utilization, discard, and posttransplant outcomes associated with HCV+ kidneys between 2 treatment eras (interferon [IFN] era, January 1, 2005 to December 5, 2013 vs DAA era, December 6, 2013 to August 2, 2018). Models were adjusted for candidate, recipient, and donor factors where appropriate.

RESULTS

In the DAA era, candidates were 2.2 times more likely to list as willing to accept HCV+ kidneys (adjusted odds ratio, 2.072.232.41; P < 0.001), and HCV+ recipients were 1.95 times more likely to have received an HCV+ kidney (adjusted odds ratio, 1.761.952.16; P < 0.001). Median Kidney Donor Profile Index of HCV+ kidneys decreased from 77 (interquartile range [IQR], 59-90) in 2005 to 53 (IQR, 40-67) in 2017. Kidney Donor Profile Index of HCV- kidneys remained unchanged from 45 (IQR, 21-74) to 47 (IQR, 24-73). After adjustment, HCV+ kidneys were 3.7 times more likely to be discarded than HCV- kidneys in the DAA era (adjusted relative rate, 3.363.674.02; P < 0.001); an increase from the IFN era (adjusted relative rate, 2.783.023.27; P < 0.001). HCV+ kidney use was concentrated within a subset of centers; 22.5% of centers performed 75% of all HCV+ kidney transplants in the DAA era. Mortality risk associated with HCV+ kidneys remained unchanged (aHR, 1.071.191.32 in both eras).

CONCLUSIONS

Given the elevated risk of death on dialysis facing HCV+ candidates, improving quality of HCV+ kidneys, and DAA availability, broader utilization of HCV+ kidneys is warranted to improve access in this era of organ shortage.

Prospective Validation of Prediction Model for Kidney Discard

BACKGROUND

Many kidneys are discarded every year, with 3631 kidneys discarded in 2016 alone. Identifying kidneys at high risk of discard could facilitate "rescue" allocation to centers more likely to transplant them. The Probability of Delay or Discard (PODD) model was developed to identify marginal kidneys at risk of discard or delayed allocation beyond 36 hours of cold ischemia time. However, PODD has not been prospectively validated, and patterns of discard may have changed after policy changes such as the introduction of Kidney Donor Profile Index and implementation of the Kidney Allocation System (KAS).

METHODS

We prospectively validated the PODD model using Scientific Registry of Transplant Recipients data in the KAS era (January 1, 2015, to March 1, 2018). C statistic was calculated to assess accuracy in predicting kidney discard. We assessed clustering in centers' utilization of kidneys with PODD >0.6 ("high-PODD") using Gini coefficients. Using match run data from January 1, 2015, to December 31, 2016, we examined distribution of these high-PODD kidneys offered to centers that never accepted a high-PODD kidney.

RESULTS

The PODD model predicted discard accurately under KAS (C-statistic, 0.87). Compared with utilization of low-PODD kidneys (Gini coefficient = 0.41), utilization of high-PODD kidneys was clustered more tightly among a few centers (Gini coefficient, 0.84 with >60% of centers never transplanted a high-PODD kidneys). In total, 11684 offers (35.0% of all high-PODD offers) were made to centers that never accepted a high-PODD kidney.

CONCLUSIONS

Prioritizing allocation of high-PODD kidneys to centers that are more likely to transplant them might help reduce kidney discard.

Hard-to-place kidney offers: Donor- and system-level predictors of discard

Understanding risk factors for deceased-donor kidney nontransplantation is important since discard rates remain high. We analyzed DonorNet^® data of consecutive deceased-donor nonmandatory share primary kidney-only offers to adult candidates at our center and beyond between July 1, 2015 and March 31, 2016 for donor- and system-level risk factors of discard, defined as nontransplantation at our or subsequent transplant centers. Exclusions were hepatitis C virus/hepatitis B virus core antibody status, blood type AB, and donor <1 year based on low candidate waitlist size. Of 456 individual kidney offers, from 296 donors, 73% were discarded. Most were national (93%) offers from Kidney Donor Profile Index 35-85% (n = 233) or >85% (n = 208) donors late in the allocation sequence with prior refusals logged for numerous candidates. On multivariate regression, factors significantly associated with discard were donor cerebrovascular accident (adjusted odds ratio [aOR]: 3.32), cancer transmission concern (aOR: 6.5), renal artery luminal compromise (aOR: 3.97), biopsy score ≥3 (aOR: 5.09), 2-hour pump resistive index >0.4 (aOR: 3.27), absence of pump (aOR: 2.58), nonspecific kidney abnormality (aOR: 2.76), increasing offer cold ischemia time category 11-15, 16-20, and >21 hours (aOR: 2.07, 2.33, 2.82), nighttime notification (aOR: 2.19), and neither kidney placed at time of offer (aOR: 2.74). Many traditional determinants of discard lack discriminatory value when granular factors are assessed. System-level factors also influence discard and warrant further study.

A novel technique for en bloc kidney transplantation from infant donors with extremely low body weight by using the distal abdominal aorta as an outflow tract

Pediatric kidney donors remain underutilized due to the high risk of postoperative thrombosis. To address this problem, we developed a novel en bloc kidney transplantation technique using donor thoracic aorta and the distal abdominal aorta as inflow and outflow tracts, respectively. Briefly, eight kidneys from deceased infant donors under five months old and with low body weight (1.9-4.9 kg) were transplanted en bloc into four pediatric and four adult patients. The donor's common iliac artery or external iliac artery was anastomosed to the recipient's distal external iliac artery or inferior epigastric artery, respectively, as an outflow tract. Recipients received basiliximab or antithymocyte globulin as induction therapy followed by tacrolimus, mycophenolate mofetil, and prednisone but without prophylactic anticoagulation. Delayed graft function was observed in one patient but was reversed at 90 days posttransplant. Two patients had urine leakage, which was cured by conservative treatment. Two recipients developed lung infections that eventually cleared. No patients experienced posttransplant vascular thrombosis. After 1-1.5 years of follow-up, all patients are well and have normal serum creatinine levels. In conclusion, this novel en bloc kidney transplantation technique using a modified arterial inflow and outflow tract can prevent vascular thrombosis and provide adequate graft function.

A Risk Index for Living Donor Kidney Transplantation

Choosing between multiple living kidney donors, or evaluating offers in kidney paired donation, can be challenging because no metric currently exists for living donor quality. Furthermore, some deceased donor (DD) kidneys can result in better outcomes than some living donor kidneys, yet there is no way to compare them on the same scale. To better inform clinical decision-making, we created a living kidney donor profile index (LKDPI) on the same scale as the DD KDPI, using Cox regression and adjusting for recipient characteristics. Donor age over 50 (hazard ratio [HR] per 10 years = 1.15 1.241.33 ), elevated BMI (HR per 10 units = 1.01 1.091.16 ), African-American race (HR = 1.15 1.251.37 ), cigarette use (HR = 1.09 1.161.23 ), as well as ABO incompatibility (HR = 1.03 1.271.58 ), HLA B (HR = 1.03 1.081.14 ) mismatches, and DR (HR = 1.04 1.091.15 ) mismatches were associated with greater risk of graft loss after living donor transplantation (all p < 0.05). Median (interquartile range) LKDPI score was 13 (1-27); 24.2% of donors had LKDPI < 0 (less risk than any DD kidney), and 4.4% of donors had LKDPI > 50 (more risk than the median DD kidney). The LKDPI is a useful tool for comparing living donor kidneys to each other and to deceased donor kidneys.

Association Between Organ Procurement Organization Social Network Centrality and Kidney Discard and Transplant Outcomes

BACKGROUND

Given growth in kidney transplant waitlists and discard rates, donor kidney acceptance is an important problem. We used network analysis to examine whether organ procurement organization (OPO) network centrality affects discard and outcomes.

METHODS

We identified 106,160 deceased donor kidneys recovered for transplant from 2000 to 2010 in Scientific Registry of Transplant Recipients. We constructed the transplant network by year with each OPO representing a node and each kidney-sharing relationship between OPOs representing a directed tie between nodes. Primary exposures were the number of different OPOs to which an OPO has given a kidney or from which an OPO has received a kidney in year preceding procurement year. Primary outcomes were discard, cold-ischemia time, delayed graft function, and 1-year graft loss. We used multivariable regression, restricting analysis to the 50% of OPOs with highest discard and stratifying remaining OPOs by kidney volume. Models controlled for kidney donor risk index, waitlist time, and kidney pumping.

RESULTS

An increase in one additional OPO to which a kidney was given by a procuring OPO in a year was associated with 1.4% lower likelihood of discard for a given kidney (odds ratio, 0.986; 95% confidence interval, 0.974-0.998) among OPOs procuring high kidney volume, but 2% higher likelihood of discard (odds ratio, 1.021; 95% confidence interval, 1.006-1.037) among OPOs procuring low kidney volume, with mixed associations with recipient outcomes.

CONCLUSIONS

Our study highlights the value of network analysis in revealing how broader kidney sharing is associated with levels of organ acceptance. We conclude interventions to promote broader inter-OPO sharing could be developed to reduce discard for a subset of OPOs.

Extraction Time of Kidneys From Deceased Donors and Impact on Outcomes

Cold ischemia time (from flush to out-of-ice) and warm ischemia time (from out-of-ice to reperfusion) are known to impact delayed graft function (DGF) rates and long-term allograft survival following deceased donor kidney transplantation. We propose an additional ischemia time, extraction time, beginning with aortic cross-clamp and perfusion/cooling of the kidneys, and ending with removal of the kidneys and placement on ice on the backtable. During this time the kidneys rewarm, suffering an additional ischemic insult, which may impair transplant function. We measured extraction times of 576 kidneys recovered and transplanted locally between January 2006 and December 2008, then linked to Scientific Registry of Transplant Recipients (SRTR) data for outcomes. Extraction time ranged from 14 to 123 min, with a mean of 44.7 min. In SRTR-adjusted analyses, longer extraction time and DGF were statistically associated (odds ratio [OR] = 1.19 per 5 min beyond 60 min, 95% confidence interval [CI] 1.02-1.39, p = 0.03). Up to 60 min of extraction time, DGF incidence was 27.8%; by 120 min it doubled to nearly 60%. Although not statistically significant (OR = 1.19, 95% CI 0.96-1.49, p = 0.11), primary nonfunction rate also rose dramatically to nearly 20% by 120 min extraction time. Extraction time is a novel and important factor to consider when evaluating a deceased donor kidney offer and when strategizing personnel for kidney recovery.

Improving Geographic Equity in Kidney Transplantation Using Alternative Kidney Sharing and Optimization Modeling

The national demand for kidney transplantation far outweighs the supply of kidney organs. Currently, a patient's ability to receive a kidney transplant varies depending on where he or she seeks transplantation. This reality is in direct conflict with a federal mandate from the Department of Health and Human Services. We analyze current kidney allocation and develop an alternative kidney sharing strategy using a multiperiod linear optimization model, KSHARE. KSHARE aims to improve geographic equity in kidney transplantation while also respecting transplant system constraints and priorities. KSHARE is tested against actual 2000–2009 kidney allocation using Organ Procurement and Transplant Network data. Geographic equity is represented by minimizing the range in kidney transplant rates around local areas of the country. In 2009, less than 25% of standard criteria donor kidneys were allocated beyond the local area of procurement, and Donor Service Area kidney transplantation rates varied from 3.0% to 30.0%, for an overall range of 27.0%. Given optimal sharing of kidneys within 600 miles of procurement for 2000–2009, kidney transplant rates vary from 5.0% to 12.5% around the country for an overall kidney transplant range of 7.5%. Nationally sharing kidneys optimally between local areas only further decreases the transplant rate range by 1.7%. Enhancing the practice of sharing kidneys by the KSHARE model may increase geographic equity in kidney transplantation.

Survival benefit of primary deceased donor transplantation with high-KDPI kidneys

The Kidney Donor Profile Index (KDPI) has been introduced as an aid to evaluating deceased donor kidney offers, but the relative benefit of high-KDPI kidney transplantation (KT) versus the clinical alternative (remaining on the waitlist until receipt of a lower KDPI kidney) remains unknown. Using time-dependent Cox regression, we evaluated the mortality risk associated with high-KDPI KT (KDPI 71-80, 81-90 or 91-100) versus a conservative, lower KDPI approach (remain on waitlist until receipt of KT with KDPI 0-70, 0-80 or 0-90) in first-time adult registrants, adjusting for candidate characteristics. High-KDPI KT was associated with increased short-term but decreased long-term mortality risk. Recipients of KDPI 71-80 KT, KDPI 81-90 KT and KDPI 91-100 KT reached a "break-even point" of cumulative survival at 7.7, 18.0 and 19.8 months post-KT, respectively, and had a survival benefit thereafter. Cumulative survival at 5 years was better in all three high-KDPI groups than the conservative approach (p < 0.01 for each comparison). Benefit of high-KDPI KT was greatest in patients age >50 years and patients at centers with median wait time ≥33 months. Recipients of high-KDPI KT can enjoy better long-term survival; a high-KDPI score does not automatically constitute a reason to reject a deceased donor kidney.

The association of center performance evaluations and kidney transplant volume in the United States

Report cards evaluating transplant center performance have received significant attention in recent years corresponding with the Centers for Medicare and Medicaid Services issue of the 2007 Conditions of Participation. Our primary aim was to evaluate the association of report card evaluations with transplant center volume. We utilized data from the Scientific Registry of Transplant Recipients (SRTR) along with six consecutive program-specific reports from January 2007 to July 2009 for adult kidney transplant centers. Among 203 centers, 46 (23%) were low performing (LP) with statistically significantly lower than expected 1-year graft or patient survival at least once during the study period. Among LP centers, there was a mean decline in transplant volume of 22.4 cases compared to a mean increase of 7.8 transplants among other centers (p = 0.001). Changes in volume between LP and other centers were significant for living, standard and expanded criteria deceased donor (ECD) transplants. LPs had a reduction in use of donors with extended cold ischemia time (p = 0.04) and private pay recipients (p = 0.03). Centers without low performance evaluations were more likely to increase the proportion of overall transplants that were ECDs relative to other centers (p = 0.04). Findings indicate a significant association between reduced kidney transplant volume and low performance report card evaluations.

The aggressive phenotype: center-level patterns in the utilization of suboptimal kidneys

Despite the fact that suboptimal kidneys have worse outcomes, differences in waiting times and wait-list mortality have led to variations in the use of these kidneys. It is unknown whether aggressive center-level use of one type of suboptimal graft clusters with aggressive use of other types of suboptimal grafts, and what center characteristics are associated with an overall aggressive phenotype. United Network for Organ Sharing (UNOS) data from 2005 to 2009 for adult kidney transplant recipients was aggregated to the center level. An aggressiveness score was assigned to each center based on usage of suboptimal grafts. Deceased-donor transplant volume correlated with aggressiveness in lower volume, but not higher volume centers. Aggressive centers were mostly found in regions 2 and 9. Aggressiveness was associated with wait-list size (RR 1.69, 95% CI 1.20-2.34, p = 0.002), organ shortage (RR 2.30, 95% CI 1.57-3.37, p < 0.001) and waiting times (RR 1.75, 95% CI 1.20-2.57, p = 0.004). No centers in single-center OPOs were classified as aggressive. In cluster analysis, the most aggressive centers were aggressive in all metrics and vice versa; however, centers with intermediate aggressiveness had phenotypic patterns in their usage of suboptimal kidneys. In conclusion, wait-list size, waiting times, geographic region and OPO competition seem to be driving factors in center-level aggressiveness.

MELD Exceptions and Rates of Waiting List Outcomes

Model for End-stage Liver Disease (MELD)-based allocation of deceased donor livers allows exceptions for patients whose score may not reflect their true mortality risk. We hypothesized that organ procurement organizations (OPOs) may differ in exception practices, use of exceptions may be increasing over time, and exception patients may be advantaged relative to other patients. We analyzed longitudinal MELD score, exception and outcome in 88 981 adult liver candidates as reported to the United Network for Organ Sharing from 2002 to 2010. Proportion of patients receiving an HCC exception was 0-21.4% at the OPO-level and 11.9-18.8% at the region level; proportion receiving an exception for other conditions was 0.0%-13.1% (OPO-level) and 3.7-9.5 (region-level). Hepatocellular carcinoma (HCC) exceptions rose over time (10.5% in 2002 vs. 15.5% in 2008, HR = 1.09 per year, p<0.001) as did other exceptions (7.0% in 2002 vs. 13.5% in 2008, HR = 1.11, p<0.001). In the most recent era of HCC point assignment (since April 2005), both HCC and other exceptions were associated with decreased risk of waitlist mortality compared to nonexception patients with equivalent listing priority (multinomial logistic regression odds ratio [OR] = 0.47 for HCC, OR = 0.43 for other, p<0.001) and increased odds of transplant (OR = 1.65 for HCC, OR = 1.33 for other, p<0.001). Policy advantages patients with MELD exceptions; differing rates of exceptions by OPO may create, or reflect, geographic inequity.