Jadlowiec, Caroline

Background and Objectives: The aim of our study was to categorize very highly sensitized kidney transplant recipients with pre-transplant panel reactive antibody (PRA) ≥ 98% using an unsupervised machine learning approach as clinical outcomes for this population are inferior, despite receiving increased allocation priority. Identifying subgroups with higher risks for inferior outcomes is essential to guide individualized management strategies for these vulnerable recipients. Materials and Methods: To achieve this, we analyzed the Organ Procurement and Transplantation Network (OPTN)/United Network for Organ Sharing (UNOS) database from 2010 to 2019 and performed consensus cluster analysis based on the recipient-, donor-, and transplant-related characteristics in 7458 kidney transplant patients with pre-transplant PRA ≥ 98%. The key characteristics of each cluster were identified by calculating the standardized mean difference. The post-transplant outcomes were compared between the assigned clusters. Results: We identified two distinct clusters and compared the post-transplant outcomes among the assigned clusters of very highly sensitized kidney transplant patients. Cluster 1 patients were younger (median age 45 years), male predominant, and more likely to have previously undergone a kidney transplant, but had less diabetic kidney disease. Cluster 2 recipients were older (median 54 years), female predominant, and more likely to be undergoing a first-time transplant. While patient survival was comparable between the two clusters, cluster 1 had lower death-censored graft survival and higher acute rejection compared to cluster 2. Conclusions: The unsupervised machine learning approach categorized very highly sensitized kidney transplant patients into two clinically distinct clusters with differing post-transplant outcomes. A better understanding of these clinically distinct subgroups may assist the transplant community in developing individualized care strategies and improving the outcomes for very highly sensitized kidney transplant patients.

Introduction Liver acceptance patterns vary significantly between transplant centers. Data pertaining to outcomes of livers declined by local and regional centers and allocated nationally remains limited. Project aim The objective was to compare post-liver transplant outcomes between liver allografts transplanted as a result of national and local-regional allocation. Design This was a retrospective evaluation of 109 nationally allocated liver allografts used for transplant by a single center. Outcomes of nationally allocated grafts were compared to standard allocation grafts (N = 505) during the same period. Results Recipients of nationally allocated grafts had lower model for end stage liver disease scores (17 vs 22, P = .001). Nationally allocated grafts were more likely to be post-cross clamp offers (29.4% vs 13.4%, P = .001) and have longer cold ischemia times (median hours 7.8 vs 5.5, P = .001). Early allograft dysfunction was common (54.1% vs 52.5%, P = .75) and did not impact hospital length of stay (median 5 vs 6 days, P = .89). There were no differences in biliary complications ( P = .11). There were no differences in patient ( P = .88) or graft survival ( P = .35). In a multivariate model, after accounting for differences in cold ischemia time and posttransplant biliary complications, nationally allocated grafts were not associated with increased risk for graft loss (HR 0.9, 95% CI 0.4-1.8). Abnormal liver biopsy findings (33.0%) followed by donor donation after circulatory death status (22.9%) were the most common reasons for decline by local-regional centers. Conclusion Despite longer cold ischemia times, patient and graft survival outcomes remain excellent and comparable to those seen from standard allocation grafts.

Background: Better understanding of the different phenotypes/subgroups of non-U.S. citizen kidney transplant recipients may help the transplant community to identify strategies that improve outcomes among non-U.S. citizen kidney transplant recipients. This study aimed to cluster non-U.S. citizen kidney transplant recipients using an unsupervised machine learning approach; Methods: We conducted a consensus cluster analysis based on recipient-, donor-, and transplant- related characteristics in non-U.S. citizen kidney transplant recipients in the United States from 2010 to 2019 in the OPTN/UNOS database using recipient, donor, and transplant-related characteristics. Each cluster’s key characteristics were identified using the standardized mean difference. Post-transplant outcomes were compared among the clusters; Results: Consensus cluster analysis was performed in 11,300 non-U.S. citizen kidney transplant recipients and identified two distinct clusters best representing clinical characteristics. Cluster 1 patients were notable for young age, preemptive kidney transplant or dialysis duration of less than 1 year, working income, private insurance, non-hypertensive donors, and Hispanic living donors with a low number of HLA mismatch. In contrast, cluster 2 patients were characterized by non-ECD deceased donors with KDPI <85%. Consequently, cluster 1 patients had reduced cold ischemia time, lower proportion of machine-perfused kidneys, and lower incidence of delayed graft function after kidney transplant. Cluster 2 had higher 5-year death-censored graft failure (5.2% vs. 9.8%; p < 0.001), patient death (3.4% vs. 11.4%; p < 0.001), but similar one-year acute rejection (4.7% vs. 4.9%; p = 0.63), compared to cluster 1; Conclusions: Machine learning clustering approach successfully identified two clusters among non-U.S. citizen kidney transplant recipients with distinct phenotypes that were associated with different outcomes, including allograft loss and patient survival. These findings underscore the need for individualized care for non-U.S. citizen kidney transplant recipients.

Abstract Introduction Significant center‐to‐center variation in attitudes and management of delayed graft function (DGF) remains common. Methods A survey to describe current DGF practices was developed by workgroup members sponsored by the National Kidney Foundation (NKF) and was distributed to both the NKF DGF workgroup members, kidney transplant program directors and the transplant community within the United States and Canada. Seventy‐one percent of NKF workgroup members completed the survey along with 70 unique the United States and three Canadian kidney transplant programs. All Organ Procurement and Transplantation Network (OPTN) regions were represented. Results DGF was reported to occur at rate of 20%–40% for most centers with 3.9% indicating their incidence to be >60%. Most centers reported longer hospital lengths of stay and more frequent outpatient visits. Despite the commonality of DGF, only half of centers reported having an established protocol to manage DGF. Kidney allograft biopsies were the only consistent DGF management strategy observed, although use of machine perfusion was also heavily favored. Other DGF management strategies voiced by a minority included having established outpatient practices to care for DGF patients and administering outpatient community‐based hemodialysis. Conclusion Although approximately a third of survey responders indicated that risk of DGF played a role in their willingness to accept organs, most did not feel that increased cost or clinical impact on outcomes was a deterrent. Future strategies, including broader sharing of best practices, redefining terminology specific to DGF, the establishment of DGF dialysis guidelines and improving access to machine perfusion across OPOs may help reduce discard and improve utilization of kidneys at risk for DGF.

AbstractBackgroundOur study aimed to characterize kidney retransplant recipients using an unsupervised machine‐learning approach.MethodsWe performed consensus cluster analysis based on the recipient‐, donor‐, and transplant‐related characteristics in 17 443 kidney retransplant recipients in the OPTN/UNOS database from 2010 to 2019. We identified each cluster's key characteristics using the standardized mean difference of >.3. We compared the posttransplant outcomes, including death‐censored graft failure and patient death among the assigned clustersResultsConsensus cluster analysis identified three distinct clusters of kidney retransplant recipients. Cluster 1 recipients were predominantly white and were less sensitized. They were most likely to receive a living donor kidney transplant and more likely to be preemptive (30%) or need ≤1 year of dialysis (32%). In contrast, cluster 2 recipients were the most sensitized (median PRA 95%). They were more likely to have been on dialysis >1 year, and receive a nationally allocated, low HLA mismatch, standard KDPI deceased donor kidney. Recipients in cluster 3 were more likely to be minorities (37% Black; 15% Hispanic). They were moderately sensitized with a median PRA of 87% and were also most likely to have been on dialysis >1 year. They received locally allocated high HLA mismatch kidneys from standard KDPI deceased donors. Thymoglobulin was the most commonly used induction agent for all three clusters. Cluster 1 had the most favorable patient and graft survival, while cluster 3 had the worst patient and graft survival.ConclusionThe use of an unsupervised machine learning approach characterized kidney retransplant recipients into three clinically distinct clusters with differing posttransplant outcomes. Recipients with moderate allosensitization, such as those represented in cluster 3, are perhaps more disadvantaged in the kidney retransplantation process. Potential opportunities for improvement specific to these re‐transplant recipients include working to improve opportunities to improve access to living donor kidney transplantation, living donor paired exchange and identifying strategies for better HLA matching.

Background and Objectives: Our study aimed to cluster dual kidney transplant recipients using an unsupervised machine learning approach to characterize donors and recipients better and to compare the survival outcomes across these various clusters. Materials and Methods: We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 2821 dual kidney transplant recipients from 2010 to 2019 in the OPTN/UNOS database. We determined the important characteristics of each assigned cluster and compared the post-transplant outcomes between clusters. Results: Two clinically distinct clusters were identified by consensus cluster analysis. Cluster 1 patients was characterized by younger patients (mean recipient age 49 ± 13 years) who received dual kidney transplant from pediatric (mean donor age 3 ± 8 years) non-expanded criteria deceased donor (100% non-ECD). In contrast, Cluster 2 patients were characterized by older patients (mean recipient age 63 ± 9 years) who received dual kidney transplant from adult (mean donor age 59 ± 11 years) donor with high kidney donor profile index (KDPI) score (59% had KDPI ≥ 85). Cluster 1 had higher patient survival (98.0% vs. 94.6% at 1 year, and 92.1% vs. 76.3% at 5 years), and lower acute rejection (4.2% vs. 6.1% within 1 year), when compared to cluster 2. Death-censored graft survival was comparable between two groups (93.5% vs. 94.9% at 1 year, and 89.2% vs. 84.8% at 5 years). Conclusions: In summary, DKT in the United States remains uncommon. Two clusters, based on specific recipient and donor characteristics, were identified through an unsupervised machine learning approach. Despite varying differences in donor and recipient age between the two clusters, death-censored graft survival was excellent and comparable. Broader utilization of DKT from high KDPI kidneys and pediatric en bloc kidneys should be encouraged to better address the ongoing organ shortage.

Background: Our study aimed to characterize kidney transplant recipients who received high kidney donor profile index (KDPI) kidneys using unsupervised machine learning approach. Methods: We used the OPTN/UNOS database from 2010 to 2019 to perform consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 8935 kidney transplant recipients from deceased donors with KDPI ≥ 85%. We identified each cluster’s key characteristics using the standardized mean difference of >0.3. We compared the posttransplant outcomes among the assigned clusters. Results: Consensus cluster analysis identified 6 clinically distinct clusters of kidney transplant recipients from donors with high KDPI. Cluster 1 was characterized by young, black, hypertensive, non-diabetic patients who were on dialysis for more than 3 years before receiving kidney transplant from black donors; cluster 2 by elderly, white, non-diabetic patients who had preemptive kidney transplant or were on dialysis less than 3 years before receiving kidney transplant from older white donors; cluster 3 by young, non-diabetic, retransplant patients; cluster 4 by young, non-obese, non-diabetic patients who received dual kidney transplant from pediatric, black, non-hypertensive non-ECD deceased donors; cluster 5 by low number of HLA mismatch; cluster 6 by diabetes mellitus. Cluster 4 had the best patient survival, whereas cluster 3 had the worst patient survival. Cluster 2 had the best death-censored graft survival, whereas cluster 4 and cluster 3 had the worst death-censored graft survival at 1 and 5 years, respectively. Cluster 2 and cluster 4 had the best overall graft survival at 1 and 5 years, respectively, whereas cluster 3 had the worst overall graft survival. Conclusions: Unsupervised machine learning approach kidney transplant recipients from donors with high KDPI based on their pattern of clinical characteristics into 6 clinically distinct clusters.

AbstractBackgroundThe pleiotropic effects of statin therapy on inflammation and coagulation may reduce the risk of venous thromboembolism. This study evaluated whether statin therapy is associated with decreased venous thromboembolic (VTE) events following kidney transplantation.MethodsWe performed a retrospective analysis of all primary kidney transplants performed between January 2014 and December 2019 at Mayo Clinic Arizona. Patients were divided into two groups depending on sustained statin therapy during the first year following transplantation. Recipient and donor clinical and demographic data were collected. The primary outcome was admission for symptomatic VTE events (deep vein thrombosis [DVT] or pulmonary embolism [PE]).ResultsSustained statin therapy in the first year following transplant was observed in 16.1% (n = 223) of 1384 kidney transplants. The overall incidence of VTE events in the year following kidney transplant was 3.8%. VTE occurred in 4.1% of recipients treated with statins and 3.8% of the controls – (hazard ratio [HR] .92, 95% confidence interval [95% CI] .39, 2.21, p = .86). However, there were significant differences between the groups in terms of age, sex, race/ethnicity, body mass index, indication for transplant, diagnosis of diabetes and discharge antiplatelet or anticoagulant therapy. Following sensitivity analysis in which cohort matching was performed to account for these differences, there was no difference in VTE event‐free survival (HR .89, 95% CI .41, 1.96, p = .78) or overall survival (HR .54, 95% CI .15, 1.94, p = .35) between patients treated with statins compared to controls.ConclusionStatin therapy in the year following successful kidney transplant was not associated with a reduction in risk of VTE.

Background and Objectives: Early allograft dysfunction (EAD) is considered a surrogate marker for adverse post-liver transplant (LT) outcomes. With the increasing use of nonconventional donors, EAD has become a more frequent occurrence. Given this background, we aimed to assess the prevalence and impact of EAD in an updated cohort inclusive of both conventional and nonconventional liver allografts. Materials and Methods: Perioperative and one-year outcomes were assessed for a total of 611 LT recipients with and without EAD from Mayo Clinic Arizona. EAD was defined as the presence of one or more of the following: bilirubin > 10 mg/dL on day 7, INR > 1.6 on day 7, or ALT and/or AST > 2000 IU/L within the first 7 days of LT. Results: Within this cohort, 31.8% of grafts (n = 194) came from donation after circulatory death (DCD) donors, 17.7% (n = 108) were nationally shared, 16.4% (n = 100) were allocated as post-cross clamp, and 8.7% contained moderate steatosis. EAD was observed in 52.2% (n = 321) of grafts in the study cohort (79% in DCD grafts and 40% in DBD grafts). EAD grafts had higher donor risk index (DRI) scores (1.9 vs. 1.6, p < 0.0001), were more likely to come from DCD donors (48% vs. 13.8%, p < 0.0001), were regionally allocated (p = 0.003), and had higher cold ischemia times (median 6.0 vs. 5.5 h, p = 0.001). Primary nonfunction events were rare in both groups (1.3% vs. 0.3%, p = 0.22). Post-LT acute kidney injury occurred at a similar frequency in recipients with and without EAD (43.6% vs. 30.3%, p = 0.41), and there were no differences in ICU (median 2 vs. 1 day, p = 0.60) or hospital (6 vs. 5 days, p = 0.24) length of stay. For DCD grafts, the rate of ischemic cholangiopathy was similar in the two groups (14.9% EAD vs. 17.5% no EAD, p = 0.69). One-year patient survival for grafts with and without EAD was 96.0% and 94.1% (HR 1.2, 95% CI 0.7–1.8; p = 0.54); one-year graft survival was 92.5% and 92.1% (HR 1.0, 95% CI 0.7–1.5; p = 0.88). Conclusions: In this cohort, EAD occurred in 52% of grafts. The occurrence of EAD, however, did not portend inferior outcomes. Compared to those without EAD, recipients with EAD had similar post-operative outcomes, as well as one-year patient and graft survival. EAD should be managed supportively and should not be viewed as a deterrent to utilization of non-ideal grafts.

Background: This study aimed to better characterize morbidly obese kidney transplant recipients, their clinical characteristics, and outcomes by using an unsupervised machine learning approach. Methods: Consensus cluster analysis was applied to OPTN/UNOS data from 2010 to 2019 based on recipient, donor, and transplant characteristics in kidney transplant recipients with a pre-transplant BMI ≥ 40 kg/m2. Key cluster characteristics were identified using the standardized mean difference. Post-transplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection, were compared among the clusters. Results: Consensus clustering analysis identified 3204 kidney transplant recipients with a BMI ≥ 40 kg/m2. In this cohort, five clinically distinct clusters were identified. Cluster 1 recipients were predominantly white and non-sensitized, had a short dialysis time or were preemptive, and were more likely to receive living donor kidney transplants. Cluster 2 recipients were older and diabetic. They were likely to have been on dialysis >3 years and receive a standard KDPI deceased donor kidney. Cluster 3 recipients were young, black, and had kidney disease secondary to hypertension or glomerular disease. Cluster 3 recipients had >3 years of dialysis and received non-ECD, young, deceased donor kidney transplants with a KDPI < 85%. Cluster 4 recipients were diabetic with variable dialysis duration who either received non-ECD standard KDPI kidneys or living donor kidney transplants. Cluster 5 recipients were young retransplants that were sensitized. One-year patient survival in clusters 1, 2, 3, 4, and 5 was 98.0%, 94.4%, 98.5%, 98.7%, and 97%, and one-year death-censored graft survival was 98.1%, 93.0%, 96.1%, 98.8%, and 93.0%, respectively. Cluster 2 had the worst one-year patient survival. Clusters 2 and 5 had the worst one-year death-censored graft survival. Conclusions: With the application of unsupervised machine learning, variable post-transplant outcomes are observed among morbidly obese kidney transplant recipients. Recipients with earlier access to transplant and living donation show superior outcomes. Unexpectedly, reduced graft survival in cluster 3 recipients perhaps underscores socioeconomic access to post-transplant support and minorities being disadvantaged in access to preemptive and living donor transplants. Despite obesity-related concerns, one-year patient and graft survival were favorable in all clusters, and obesity itself should be reconsidered as a hard barrier to kidney transplantation.