Citations

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.

Background. The objective of this study was to compare the long-term outcomes of older (50–65 y) type 1 diabetics with body mass index <35 kg/m2 and type 2 diabetics with body mass index <30 kg/m2 who received simultaneous pancreas kidney transplantation (SPKT) versus living donor kidney transplants (LDKTs). All subjects had insulin-dependent diabetes. Methods. This is a retrospective single-center study from July 2003 to March 2021 with a median follow-up of 7.5 y. Results. There were 104 recipients in the SPKT and 80 in the LDKT group. The mean age was 56 y in SPKT and 58 y in LDKT. There were 55% male recipients in the SPKT group versus 75% in LDKT. The duration of diabetes was 32 y in SPKT versus 25 y in LDKT. The number of preemptive transplants and length of dialysis were similar. However, the wait time was shorter for LDKT (269 versus 460 d). Forty-nine percent of the LDKT recipients received the organ within 6 mo of being waitlisted compared with 28% of SPKT recipients (P = 0.001). Donor age was lower in the SPKT group (27 versus 41 y). The estimated 5-y death censored kidney survival was 92% versus 98%, and 5-y patient survival was 86% versus 89% for SPKT versus LDKT. Death censored kidney and patient survival, acute kidney rejection by 1 y, and BK viremia were similar between the 2 groups. There were 17 pancreas graft losses within 1 y of transplant, the majority related to surgical complications, and it was not associated with increased mortality. Conclusions. SPKT in selected recipients aged 50 and above can have excellent outcomes similar to LDKT recipients.

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.

AbstractDual kidney transplantation (DKT), utilizing two adult kidneys from the same donor for one recipient, has been used as a way to expand the available donor pool. These kidneys often come from high Kidney Donor Profile Index donors (KDPI > 85%). Data comparing outcomes between high KDPI DKT and single kidney transplants (SKT) remain limited. We assessed outcomes of 336 high KDPI kidney transplants performed at our center; 11.0% (n = 37) were DKT. Recipients of DKT were older (P = .02) and donors had a higher KDPI score (median 96% vs. 91%, P < .0001). DKT operative time was higher compared to SKT (+1.4 hours, P < .0001). There were no differences in delayed graft function (54.1% vs. 51.5%, P = .77) and hospital length of stay (median 4.0 vs. 3.0 days, P = .21) between DKT and SKT. Grade I Clavien‐Dindo complications occurred in 8.1% of DKT and 13.7% of SKT (P = .008). There were no grade IVa, IVb, or V complications in either group. DKT had more glomerulosclerosis (P = .04), interstitial fibrosis (P = .02), tubular atrophy (P = .01), and arterial thickening (P = .03) on 1‐year protocol biopsies. Estimated glomerular filtration was higher for DKT at 1‐ (P = .004) and 2‐years post‐transplant (P = .01). There were no differences in patient (HR 1.3, 95% CI .5‐3.3, P = .58) or graft (HR 1.1, 95% CI .5‐2.3, P = .83) survival. Good outcomes can be achieved with DKT using high KDPI kidneys with moderate chronic changes. DKT is a good option to help further utilize high KDPI kidneys and minimize discard.

Background: There have been concerns regarding increased perioperative mortality, length of hospital stay, and rates of graft loss in kidney transplant recipients with functional limitations. The application of machine learning consensus clustering approach may provide a novel understanding of unique phenotypes of functionally limited kidney transplant recipients with distinct outcomes in order to identify strategies to improve outcomes. Methods: Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 3205 functionally limited kidney transplant recipients (Karnofsky Performance Scale (KPS) < 40% at transplant) in the OPTN/UNOS database from 2010 to 2019. Each cluster’s key characteristics were identified using the standardized mean difference. Posttransplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection were compared among the clusters Results: Consensus cluster analysis identified two distinct clusters that best represented the clinical characteristics of kidney transplant recipients with limited functional status prior to transplant. Cluster 1 patients were older in age and were more likely to receive deceased donor kidney transplant with a higher number of HLA mismatches. In contrast, cluster 2 patients were younger, had shorter dialysis duration, were more likely to be retransplants, and were more likely to receive living donor kidney transplants from HLA mismatched donors. As such, cluster 2 recipients had a higher PRA, less cold ischemia time, and lower proportion of machine-perfused kidneys. Despite having a low KPS, 5-year patient survival was 79.1 and 83.9% for clusters 1 and 2; 5-year death-censored graft survival was 86.9 and 91.9%. Cluster 1 had lower death-censored graft survival and patient survival but higher acute rejection, compared to cluster 2. Conclusion: Our study used an unsupervised machine learning approach to characterize kidney transplant recipients with limited functional status into two clinically distinct clusters with differing posttransplant outcomes.