Second Renal Transplantations

Delmonico, Francis L.; Tolkoff-Rubin, Nina; Auchincloss, Hugh; Farrell, Mary Lin; Fitzpatrick, Donna; Saidman, Susan L.; Herrin, John T.; Cosimi, A. Benedict

doi:10.1001/archsurg.1994.01420280024003

Cited by 25 publications

(4 citation statements)

References 6 publications

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“…For such patients, repeat transplantation provides better long-term survival and improved quality of life compared to remaining on dialysis, although these studies have only focused on second transplants (17-19). We herein report the analysis of the UNOS experience evaluating outcomes of 3KT and we demonstrate that in selected patients, a third kidney transplant provides significant patient survival advantage over the waitlist while offering a slightly reduced graft outcome compared to first kidney transplants.…”

Section: Discussionmentioning

confidence: 99%

Graft and Patient Survival Outcomes of a Third Kidney Transplant

Redfield

Gupta²,

Rodríguez³

et al. 2015

Transplantation

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Background The waiting time for deceased donor renal transplantation in the United States continues to grow. Retransplant candidates make up a small but growing percentage of the overall transplant waiting list and raise questions about the stewardship of scarce resources. The utility of renal transplantation among individuals with two prior renal transplants is not described in the literature and we thus sought to determine the survival benefit associated with a third kidney transplant (3KT). Methods Multivariable Cox regression models were created to determine characteristics associated with 3KT outcomes and the survival benefit of 3KT among recipients wait listed and transplanted within the United States between 1995 and 2009. Results 4,334 patients were waitlisted for a 3KT and 2,492 patients received a 3KT. In a multivariate analysis, 3KT demonstrated an overall patient survival benefit compared to the wait list (HR-0.379, CI=0.302-0.475 p<0.001) for those awaiting their first, second or third kidney transplants, although an inferior graft outcome compared to first kidney transplants. The time to survival benefit did not accrue until 8-months after transplant. Additionally we found that the duration of second graft survival was predictive of third graft survival, such that second graft survival beyond 5 years is associated with superior 3KT graft survival. Second graft loss in 30 days or less was not associated with inferior 3KT graft survival. Conclusion 3KT achieves a survival benefit over remaining on the wait list, although is associated with inferior graft outcomes compared to first kidney transplants. Graft survival of the second transplant beyond 5 years is associated with superior 3KT graft survival.

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Section: Discussionmentioning

confidence: 99%

Graft and Patient Survival Outcomes of a Third Kidney Transplant

Redfield

Gupta²,

Rodríguez³

et al. 2015

Transplantation

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“…9,17,18 Nevertheless, kidney transplant patients, including recipients with kidney retransplant, are heterogeneous and there are many factors, including recipient, donor, and transplantrelated characteristics, that can result in varying outcomes. [2][3][4][5][6]19,20 Machine learning (ML), a subfield of artificial intelligence, has been applied to create clinical decision support tools and individualize patient care, including in kidney transplantation. [21][22][23][24][25][26] Studies have demonstrated that unsupervised ML consensus clustering can be utilized to discover novel data patterns and distinct subtypes, [27][28][29] and ultimately distinguish them into clinically meaningful clusters.…”

Section: Data From the United States Renal Data System And Canadianmentioning

confidence: 99%

“…As a result, some kidney transplant centers have lower kidney retransplant rates with highly selective criteria for retransplantation 9,17,18 . Nevertheless, kidney transplant patients, including recipients with kidney retransplant, are heterogeneous and there are many factors, including recipient, donor, and transplant‐related characteristics, that can result in varying outcomes 2–6,19,20 …”

Section: Introductionmentioning

confidence: 99%

“…Despite improvements in initial kidney allograft survival, 1 many patients continue to require retransplantation. [2][3][4][5][6] Over a hundred thousand candidates are currently on the kidney transplant waitlist at this time, based on the 2020 Scientific Registry of Transplant Recipients (SRTR) report, 1 and kidney retransplantation has been increasingly performed worldwide. 7,8 Candidates with prior kidney transplant account for 12% of the current waitlist candidates and 10.4% of transplants performed in 2019.…”

Section: Introductionmentioning

confidence: 99%

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Differences between kidney retransplant recipients as identified by machine learning consensus clustering

Vaitla

Jadlowiec

Mao

et al. 2023

Clinical Transplantation

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Background Our study aimed to characterize kidney retransplant recipients using an unsupervised machine‐learning approach. Methods We 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 clusters Results Consensus 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. Conclusion The 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.

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A Single-Center Experience With Six-Antigen—Matched Kidney Transplants

et al. 1995

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Identical HLA matching for cadaver recipients provides superior results for graft and patient survival. There is much less perioperative morbidity in comparison with the less well-matched cadaver recipients. The effect of HLA matching is reflected in the perioperative courses of these patients, in addition to the long-term benefits of graft survival. Allograft survival is superior for this select group of cadaver recipients. The 6-AgM recipients behave similarly to LRD recipients in this cohort of patients. Our results would support the continued sharing of 6-AgM kidneys to optimize outcome and best use the limited resources available to the patients undergoing transplantation.

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Second Renal Transplantations

Cited by 25 publications

References 6 publications

Graft and Patient Survival Outcomes of a Third Kidney Transplant

Graft and Patient Survival Outcomes of a Third Kidney Transplant

Differences between kidney retransplant recipients as identified by machine learning consensus clustering

A Single-Center Experience With Six-Antigen—Matched Kidney Transplants

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