Impact of Cold Ischemia Time on Kidney Transplant: A Mate Kidney Analysis

Gorayeb-Polacchini, Fernanda Salomão; Caldas, Heloisa Cristina; Fernandes-Charpiot, Ida Maria Maximina; Ferreira-Baptista, M.A.S.; Gauch, Camila Ravazzi; Abbud-Filho, Mário

doi:10.1016/j.transproceed.2019.12.052

Cited by 13 publications

(12 citation statements)

References 14 publications

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“…The association of the assigned clusters with post‐transplant outcomes was not adjusted for clinical characteristics because clinically distinct clusters were purposefully generated using the consensus clustering approach. We used R, version 4.3 (RStudio, Inc., Boston, MA; http://www.rstudio.com/); Consensus ClusterPlus package (version 1.46.0) for consensus clustering analysis, and the MICE command in R for multivariable imputation by chained equation 1 …”

Section: Methodsmentioning

confidence: 99%

“…Donor and recipient factors both influence kidney transplant outcomes, and optimization of modifiable factors by transplant centers is essential. Cold ischemia time (CIT) is closely associated with delayed graft function (DGF) and other transplant‐related outcomes 1–3 . Despite efforts to minimize CIT, transplant centers remain challenged with balancing organ offers and organ discard 2 .…”

Section: Introductionmentioning

confidence: 99%

“…Within this context, the combination of CIT and donor and recipient variables may worsen transplant‐related ischemia‐reperfusion injury and impact outcomes 9,10 . Accordingly, many transplant centers try to limit CIT to 24 h and there remains hesitancy to further extend this time within the transplant community 1 . Despite these concerns, many transplant centers have adopted strategies to successfully utilize kidney allografts with prolonged CIT 11 …”

Section: Introductionmentioning

confidence: 99%

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Re‐assessing prolonged cold ischemia time in kidney transplantation through machine learning consensus clustering

Jadlowiec,

Thongprayoon,

Tangpanithandee

et al. 2023

Clinical Transplantation

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BackgroundWe aimed to cluster deceased donor kidney transplant recipients with prolonged cold ischemia time (CIT) using an unsupervised machine learning approach.MethodsWe performed consensus cluster analysis on 11 615 deceased donor kidney transplant patients with CIT exceeding 24 h using OPTN/UNOS data from 2015 to 2019. Cluster characteristics of clinical significance were identified, and post‐transplant outcomes were compared.ResultsConsensus cluster analysis identified two clinically distinct clusters. Cluster 1 was characterized by young, non‐diabetic patients who received kidney transplants from young, non‐hypertensive, non‐ECD deceased donors with lower KDPI scores. In contrast, the patients in cluster 2 were older and more likely to have diabetes. Cluster 2 recipients were more likely to receive transplants from older donors with a higher KDPI. There was lower use of machine perfusion in Cluster 1 and incrementally longer CIT in Cluster 2. Cluster 2 had a higher incidence of delayed graft function (42% vs. 29%), and lower 1‐year patient (95% vs. 98%) and death‐censored (95% vs. 97%) graft survival compared to Cluster 1.ConclusionsUnsupervised machine learning characterized deceased donor kidney transplant recipients with prolonged CIT into two clusters with differing outcomes. Although Cluster 1 had more favorable recipient and donor characteristics and better survival, the outcomes observed in Cluster 2 were also satisfactory. Overall, both clusters demonstrated good survival suggesting opportunities for transplant centers to incrementally increase CIT.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Re‐assessing prolonged cold ischemia time in kidney transplantation through machine learning consensus clustering

Jadlowiec,

Thongprayoon,

Tangpanithandee

et al. 2023

Clinical Transplantation

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“…There are several recent reports on elderly donors [ 28 – 32 ], generally showing no breakthrough research results. In recent reports, the number of cases included in the study increased, and some studies even included many cases of donors over 80 years old [ 28 , 30 ].…”

Section: Progress In Related Research On Aged Donorsmentioning

confidence: 99%

“…Many studies have explored the relationship between CIT and DGF [ 32 , 48 – 54 ]. It is generally felt that there is a certain threshold value for CIT, and once exceeded, the risk of DGF will increase significantly.…”

Section: Research Progress Of Citmentioning

confidence: 99%

Effect of Long Cold Ischemia Time of Kidneys from Aged Donors on Prognosis of Kidney Transplantation

Lian

Yang

et al. 2021

Ann Transplant

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With the increasing incidence of end-stage renal disease (ESRD), patients’ life span and life quality are significantly reduced. Kidney transplantation has gradually become the ideal method for treating ESRD, and the shortage of organ sources has become the main problem. In recent years, China has successfully realized the transformation of organ sources. Voluntary donation after the death of citizens has increased year by year, and the number of kidney transplantations has increased, which alleviates the organ shortage to a certain extent, but compared with the past, the increasing proportion of aged donors has also become an inevitable global problem. At the same time, due to the sudden and widespread distribution of voluntary donation, most donor kidneys have the problem of longer cold ischemic time (CIT). The probability of adverse events, such as delayed renal function recovery after transplantation, was also significantly increased. At present, there is little research on the effect of donor’s aging and long CIT on the prognosis of renal transplantation. This paper reviews the literature in recent years and explore this problem from 2 aspects: the elderly donor and the long CIT.

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Distinct global DNA methylation and NF-κB expression profile of preimplantation biopsies from ideal and non-ideal kidneys

et al. 2022

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Impact of Cold Ischemia Time on Kidney Transplant: A Mate Kidney Analysis

Cited by 13 publications

References 14 publications

Re‐assessing prolonged cold ischemia time in kidney transplantation through machine learning consensus clustering

Re‐assessing prolonged cold ischemia time in kidney transplantation through machine learning consensus clustering

Effect of Long Cold Ischemia Time of Kidneys from Aged Donors on Prognosis of Kidney Transplantation

Distinct global DNA methylation and NF-κB expression profile of preimplantation biopsies from ideal and non-ideal kidneys

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