Marginal kidney transplantation: the road less traveled

Outcomes Using High KDPI Kidneys in Recipients Over 65 y of Age

BACKGROUND

Kidney transplantation has been shown to improve life expectancy when compared with remaining on dialysis. However, there is an ever-expanding shortage of available organs for transplantation. The use of high kidney donor profile index (KDPI; >85) kidneys is 1 strategy to address this shortage. The current study aims to evaluate the advantage of accepting a high KDPI versus a low KDPI kidney (KDPI ≤85) in patients 65 y or older.

METHODS

A single-center retrospective review of all patients, ages 65 y or older, who underwent deceased donor kidney transplantation between 2010 and 2020 was performed. Outcomes and wait times of recipients undergoing low KDPI (KDPI ≤85) versus high KDPI (KDPI >85) kidney transplantation were compared. Significance was defined as P < 0.05.

RESULTS

Four hundred ninety-two patients were identified; 317 (64.4%) were men with a median age at transplantation of 69 y. Four hundred five patients received low KDPI kidneys, whereas the remaining received high KDPI grafts. High KDPI kidneys were procured from older donors (60 versus 47, P < 0.001) and had shorter cold ischemic time (25.0 versus 28.3 h, P = 0.01) compared with low KDPI kidneys. There was no significant difference in graft and patient survival between low and high KDPI recipients, with 85.1% and 86.2% grafts functioning at a follow-up of 4.85 (2.9-7.0) y, respectively. Pretransplant wait time was significantly shorter in the high KDPI group (2.7 [1.8-4.1] versus 3.5 [2.3-4.8] y; P = 0.004).

CONCLUSIONS

In patients 65 y or older undergoing deceased donor kidney transplantation, high KDPI kidneys may offer shorter pretransplant waiting times without compromising graft or patient survival.

Landscape of the immune infiltration and identification of molecular diagnostic markers associated with immune cells in patients with kidney transplantation

Rejection seriously affects the success of kidney transplantations. However, the molecular mechanisms underlying this rejection remain unclear. The GSE21374 and GSE36059 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Next, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to infer the proportions of 22 immune cells. Moreover, infiltrating immune cell-related genes were identified using weighted gene co-expression network analysis (WGCNA), and enrichment analysis was conducted to observe their biological functions. Extreme Gradient Boosting (XGBoost) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithms were used to screen hub genes. Quantitative real-time PCR was conducted to verify the number of immune cells and hub gene expression levels. The rejection and non-rejection groups showed significantly different distributions (P < 0.05) of eight immune cells (B cell memory, Plasma cells, mast cells, follicular helper T cells, T CD8 cells, Macrophages M1, T Cells CD4 memory activated, and gamma delta T cells). Subsequently, CD8A, CRTAM, GBP2, WARS, and VAMP5 were screened as hub genes using the XGBoost and LASSO algorithms and could be used as diagnostic biomarkers. Finally, differential analysis and quantitative real-time PCR suggested that CD8A, CRTAM, GBP2, WARS, and VAMP5 were upregulated in rejection samples compared to non-rejection samples. The present study identified five key infiltrating immune cell-related genes (CD8A, CRTAM, GBP2,WARS, and VAMP5) involved in kidney transplant rejection, which may explain the molecular mechanism of rejection in kidney transplantation development.

The Use of Kidneys With Lower Longevity From Deceased Donors to Improve Access to Preemptive Renal Transplantation for Elderly Patients: A Qualitative Study

Background

There is a gap between the number of patients waiting for a transplant and the number of kidneys available. Some deceased donor kidneys are currently nonutilized, as medical teams fear that they will experience suboptimal graft survival. However, these organs could provide an acceptable therapeutic option if they were allocated for preemptive kidney transplantation in elderly candidates.

Objective

This project aims to gather patients' perspectives on the allocation of kidneys with lower longevity for preemptive kidney transplantation in elderly patients.

Design

Individual interviews.

Setting

The Center hospitalier de l'Université de Montréal (CHUM) chronic kidney disease (CKD) clinic.

Participants

Patients aged between 64 and 75 years with CKD G4-5 ND, followed at the CHUM and who have not initiated dialysis yet.

Methods

Between March and July 2023, we conducted 14 individual interviews with patients aged between 64 and 75 years who had CKD G4-5 ND and were followed at the CHUM. The interviews were digitally recorded and transcribed. Thematic analysis was conducted.

Results

Most participants were in favor of using kidneys with lower longevity to increase their access to transplantation, improve their quality of life, enable accelerated transplantation, and avoid dialysis. Patients also wanted to be engaged in the decision-making process, underlining the importance of informed consent. Although the use of kidneys with lower longevity offers the hope of returning to "normal" life, some patients were concerned about the risk of reduced graft survival and the need for a subsequent kidney transplant. In these cases, patients were interested in using mitigation strategies, such as prioritization for kidney transplantation from standard donors in case of early graft loss associated with receiving kidneys with lower longevity. They also recommended the development of a separate waiting list for patients consenting to preemptive transplantation with kidneys with lower longevity.

Limitations

This study was conducted in only 1 nephrology clinic in the province of Quebec with French-speaking patients. Consequently, the results may not be generalizable to other populations, including ethnic minorities.

Conclusion

The use of kidneys with lower longevity for preemptive kidney transplantation appears to be an interesting option for elderly kidney transplant candidates. However, patient information and participation in the decision-making process are essential. Moreover, organ donation organizations and transplant programs should develop a separate waitlist for transplant candidates who have preconsented to receive organ offers of deceased donor kidneys with lower longevity.

Trial registration

Not registered.

Roles of Akirin1 in early prediction and treatment of graft kidney ischemia‒reperfusion injury

Ferroptosis is a predominant contributor to graft kidney ischemia‒reperfusion injury (IRI), resulting in delayed graft function (DGF). However, much less is known about the early predicting biomarkers and therapeutic targets of DGF, especially aiming at ferroptosis. Here, we propose a precise predicting model for DGF, relying on the Akirin1 level in extracellular vesicles (EVs) derived from recipient urine 48 h after kidney transplant. In addition, we decipher a new molecular mechanism whereby Akirin1 induces ferroptosis by strengthening TP53-mediated suppression of SLC7A11 during the graft kidney IRI process, that is, Akirin1 activates the EGR1/TP53 axis and inhibits MDM2-mediated TP53 ubiquitination, accordingly upregulating TP53 in two ways. Meanwhile, we present the first evidence that miR-136-5p enriched in EVs secreted by human umbilical cord mesenchymal stem cells (UM-EVs) confers robust protection against ferroptosis and graft kidney IRI by targeted inhibition of Akirin1 but knockout of miR-136-5p in UM sharply mitigates the protection of UM-EVs. The functional and mechanistic regulation of Akirin1 is further corroborated in an allograft kidney transplant model in wild-type and Akirin1-knockout mice. In summary, these findings suggest that Akirin1, which prominently induces ferroptosis, is a pivotal biomarker and target for early diagnosis and treatment of graft kidney IRI and DGF after kidney transplant.

Considerable Variability Among Transplant Nephrologists in Judging Deceased Donor Kidney Offers

Introduction

Transplant clinicians may disagree on whether or not to accept a deceased donor kidney offer. We investigated the interobserver variability between transplant nephrologists regarding organ acceptance and whether the use of a prediction model impacted their decisions.

Methods

We developed an observational online survey with 6 real-life cases of deceased donor kidneys offered to a waitlisted recipient. Per case, nephrologists were asked to estimate the risk of adverse outcome and whether they would accept the offer for this patient, or for a patient of their own choice, and how certain they felt. These questions were repeated after revealing the risk of adverse outcome, calculated by a validated prediction model.

Results

Sixty Dutch nephrologists completed the survey. The intraclass correlation coefficient of their estimated risk of adverse outcome was poor (0.20, 95% confidence interval [CI] 0.08-0.62). Interobserver agreement of the decision on whether or not to accept the kidney offer was also poor (Fleiss kappa 0.13, 95% CI 0.129-0.130). The acceptance rate before and after providing the outcome of the prediction model was significantly influenced in 2 of 6 cases. Acceptance rates varied considerably among transplant centers.

Conclusion

In this study, the estimated risk of adverse outcome and subsequent decision to accept a suboptimal donor kidney varied greatly among transplant nephrologists. The use of a prediction model could influence this decision and may enhance nephrologists' certainty about their decision.

Development and validation of the Chinese version of the self-management support scale for kidney transplant recipients

BACKGROUND

Providing self-management support to kidney transplant recipients is essential. However, a scale to identify the self-management support they have received is lacking. The purpose of this study is to develop a Self-management Support Scale for Kidney Transplant Recipients (SMSSKTR) and test its psychometric properties.

METHODS

This is an instrument development and validation study, which has a three-stage cross-sectional design. In Stage 1, a preliminary item pool was formed using a literature review, semi-structured interviews, and the Delphi method. In Stage 2, six experts were invited to assess content validity. A convenience sample of 313 participants was used to explore the factor structure by using exploratory factor analysis. The test-retest reliability was assessed using the intra-class correlation coefficient (ICC). In Stage 3, two hundred and sixty-five participants were recruited to validate the factor structure by using confirmatory factor analysis. Convergent validity was examined using Spearman's correlation coefficient. Cronbach's alpha coefficient and corrected item-total correlation coefficient were used to test the reliability of the entire scale and its dimensions. The study was reported according to the STARD and GRRAS checklists.

RESULTS

An initial 40-item scale was developed in Stage 1. In Stage 2, three factors with 22 items emerged from the exploratory factor analysis: instrumental support, psychosocial support, and relational support. The content validity index of the scale was 0.97. The intra-class correlation coefficient for the entire scale and the subscales were 0.915, 0.771, 0.896, and 0.832, respectively. In Stage 3, the confirmatory factor analysis indicated that the three-factor model had a good fit. The score of the scale was positively associated with that of the Self-Management Scale of Renal Transplant Recipients (r = 0.532). Cronbach's alpha was 0.959 for the entire scale and 0.956-0.958 for the three subscales. The corrected item-total correlation coefficient ranged from 0.62 to 0.82.

CONCLUSION

The 22-item SMSSKTR has sufficient psychometric properties to assess the self-management support they have received, which has not been measured before.

Untargeted metabolomics of perfusate and their association with hypothermic machine perfusion and allograft failure

Although hypothermic machine perfusion (HMP) is associated with improved kidney graft viability and function, the underlying biological mechanisms are unknown. Untargeted metabolomic profiling may identify potential metabolites and pathways that can help assess allograft viability and contribute to organ preservation. Therefore, in this multicenter study, we measured all detectable metabolites in perfusate collected at the beginning and end of deceased-donor kidney perfusion and evaluated their associations with graft failure. In our cohort of 190 kidney transplants, 33 (17%) had death-censored graft failure over a median follow-up of 5.0 years (IQR 3.0-6.1 years). We identified 553 known metabolites in perfusate and characterized their experimental and biological consistency through duplicate samples and unsupervised clustering. After perfusion-time adjustment and false discovery correction, six metabolites in post-HMP perfusate were significantly associated with death-censored graft failure, including alpha-ketoglutarate, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, 1-carboxyethylphenylalanine, and three glycerol-phosphatidylcholines. All six metabolites were associated with an increased risk of graft failure (Hazard Ratio per median absolute deviation range 1.04-1.45). Four of six metabolites also demonstrated significant interaction with donation after cardiac death with notably greater risk in the donation after cardiac death group (Hazard Ratios up to 1.69). Discarded kidneys did not have significantly different levels of any death-censored graft failure-associated metabolites. On interrogation of pathway analysis, production of reactive oxygen species and increased metabolism of fatty acids were upregulated in kidneys that subsequently developed death-censored graft failure. Thus, further understanding the role of these metabolites may inform the HMP process and help improve the objective evaluation of allograft offers, thereby reducing the discard of potentially viable organs.

Kidney utilization in the Netherlands - do we optimally use our donor organs?

BACKGROUND

To ensure optimal utilization of deceased donor kidneys, it is important to understand the precise reasons why kidneys are discarded. In this study we aimed to obtain a comprehensive overview of kidney utilization and discard during the entire donation process in the Netherlands.

METHODS

In this retrospective cohort study we analysed kidney utilization of 3856 kidneys in the Netherlands between 1 January 2015 and 31 December 2020. For every kidney that was not transplanted, we determined the moment of and reason for discard through a unique case-by-case assessment.

RESULTS

Kidney discard according to the traditional definition (procured but not transplanted) was 7.8%. However, when kidneys that seemed medically suitable at the beginning of the donation process were also included, many more potential donor kidneys were lost and the total non-utilization was 24.4%. Subjectively presumed impaired organ quality was responsible for 34.2% of all discarded kidneys. Two-thirds of kidneys discarded due to acute kidney injury (AKI) had only AKI stage 1 or 2.

CONCLUSION

The classical definition of organ discard underestimates the non-utilization of deceased donor kidneys. Strategies to improve kidney utilization could be a revision of the maximum allowed agonal time in donation after circulatory death, careful consideration in reporting and accepting kidneys from donors with AKI and a prospectively filled registry of detailed organ discard reasons, including the 'silent' non-utilization before procurement.

Survival Benefit in Older Patients Transplanted With Viremic Hepatitis C Positive Kidneys When Compared With High KDPI Kidneys

BACKGROUND

Because of the continued demand in kidney transplantation, organs from donors with risk criteria for blood-borne viruses, high Kidney Donor Profile Index (KDPI) kidneys, and hepatitis C virus (HCV)-positive kidneys are being considered. There continues to be reluctance on the part of the providers and the candidates to accept HCV-positive kidneys.

METHODS

We conducted a retrospective analysis of the Organ Procurement and Transplantation Network database of all adult (≥18 y old) recipients undergoing kidney transplant from May 10, 2013, to June 30, 2021. We compared patient and graft survival in candidates who received HCV-positive kidneys versus non-hepatitis C (Hep C) high KDPI kidneys by estimated posttransplant survival (EPTS) groups.

RESULTS

HCV-viremic kidneys were transplanted in 5.6% of patients in the EPTS >61% group compared with 5.1% of patients in the 21%-60% EPTS group and 1.9% of 0%-20% EPTS group (P < 0.001). Of all transplants performed in the EPTS 61%-100% group, 11.9% were KDPI >85% compared with 5.2% in the EPTS 21%-60%, and 0.5% in the EPTS 0%-20%. Patient survival was significantly longer at 1, 3, and 5 y in the EPTS >61% group who received Hep C-viremic or -nonviremic allografts compared with non-Hep C kidneys with KDPI >85%. When it comes to listing, only 25% of candidates in the EPTS >61% group were listed for Hep C nucleic acid testing-positive kidneys in 2021.

CONCLUSIONS

Our findings could be used for counseling candidates on the types of kidneys they should consider for transplantation. Also, listing practices for viremic Hep C kidneys need continued re-evaluation.

Deep Learning Algorithms for the Prediction of Posttransplant Renal Function in Deceased-Donor Kidney Recipients: A Preliminary Study Based on Pretransplant Biopsy

Background

Posttransplant renal function is critically important for kidney transplant recipients. Accurate prediction of graft function would greatly help in deciding acceptance or discard of allocated kidneys.

Methods

: Whole-slide images (WSIs) of H&E-stained donor kidney biopsies at × 200 magnification between January 2015 and December 2019 were collected. The clinical characteristics of each donor and corresponding recipient were retrieved. Graft function was indexed with a stable estimated glomerular filtration rate (eGFR) and reduced graft function (RGF). We used convolutional neural network (CNN)-based models, such as EfficientNet-B5, Inception-V3, and VGG19 for the prediction of these two outcomes.

Results

In total, 219 recipients with H&E-stained slides of the donor kidneys were included for analysis [biopsies from standard criteria donor (SCD)/expanded criteria donor (ECD) was 191/28]. The results showed distinct improvements in the prediction performance of the deep learning algorithm plus the clinical characteristics model. The EfficientNet-B5 plus clinical data model showed the lowest mean absolute error (MAE) and root mean square error (RMSE). Compared with the clinical data model, the area under the receiver operating characteristic (ROC) curve (AUC) of the clinical data plus image model for eGFR classification increased from 0.69 to 0.83. In addition, the predictive performance for RGF increased from 0.66 to 0.80. Gradient-weighted class activation mappings (Grad-CAMs) showed that the models localized the areas of the tubules and interstitium near the glomeruli, which were discriminative features for RGF.

Conclusion

Our results preliminarily show that deep learning for formalin-fixed paraffin-embedded H&E-stained WSIs improves graft function prediction accuracy for deceased-donor kidney transplant recipients.

Expanding the Donor Pool: First Use of Hepatitis B Virus Nat Positive Solid Organ Allografts Into Seronegative Recipients

OBJECTIVES

The aim of this study was to assess the 1-year safety and effectiveness of HBV Nucleic Acid Test positive (HBV NAT+) allografts in seronegative kidney transplant (KT) and liver transplant (LT) recipients.

SUMMARY BACKGROUND DATA

Despite an ongoing organ shortage, the utilization of HBV NAT+ allografts into seronegative recipients has not been investigated.

METHODS

From January 2017 to October 2020, a prospective cohort study was conducted among consecutive KT and LT recipients at a single institution. Primary endpoints were post-transplant HBV viremia, graft and patient survival.

RESULTS

With median follow-up of 1-year, there were no HBV-related complications in the 89 HBV NAT+ recipients. Only 9 of 56 KTs (16.1%) and 9 of 33 LTs (27.3%) experienced post-transplant HBV viremia at a median of 185 (KT) and 269 (LT) days postoperatively. Overall, viremic episodes resolved to undetected HBV DNA after a median of 80 days of entecavir therapy in 16 of 18 recipients. Presently, 100% of KT recipients and 93.9% of LT recipients are HBV NAT- with median follow-up of 13 months, whereas 0 KT and 8 LT (24.2%) recipients are HBV surface antigen positive indicating chronic infection. KT and LT patient and allograft survival were not different between HBV NAT+ and HBV NAT- recipients (P > 0.05), whereas HBV NAT+ KT recipients had decreased waitlist time and pretransplant duration on dialysis (P < 0.01).

CONCLUSIONS

This is the largest series describing the transplantation of HBV NAT+ kidney and liver allografts into HBV seronegative recipients without chronic HBV viremia or decreased 1-year patient and graft survival. Increasing the utilization of HBV NAT+ organs in nonviremic recipients can play a role in decreasing the national organ shortage.

Donor Kidney Quality and Transplant Outcome: An Economic Evaluation of Contemporary Practice

OBJECTIVES

The study had two main aims. First, we assessed the cost-effectiveness of transplanting deceased donor kidneys of differing quality levels based on the Kidney Donor Profile Index (KDPI). Second, we assessed the cost-effectiveness of remaining on the waiting list until a high-quality kidney becomes available compared to transplanting a lower-quality kidney.

METHODS

A decision analytic model to estimate cost-effectiveness was developed using a Markov process. Separate models were developed for 4 separate KDPI bands, with higher values indicating lower quality. Models were simulated in 1-year cycles for a 20-year time horizon, with transitions through distinct health states relevant to the kidney recipient from the healthcare payer's perspective. Weibull regression was used to calculate the time-dependent transition probabilities in the base analysis. The impact uncertainty arising in model parameters was included by probabilistic sensitivity analysis using the Monte Carlo simulation method. Willingness to pay was considered as Australian $28 000.

RESULTS

Transplanting a kidney of any quality is cost-effective compared to remaining on a waitlist. Transplanting a lower KDPI kidney is cost-effective compared to a higher KDPI kidney. Transplanting lower KDPI kidneys to younger patients and higher KDPI kidneys to older patients is also cost-effective. Depending on dialysis in hopes of receiving a lower KDPI kidney is not a cost-effective strategy for any age group.

CONCLUSION

Efforts should be made by the health systems to reduce the discard rates of low-quality kidneys with the view of increasing the transplant rates.

The Role of Metabolomics in Current Concepts of Organ Preservation

In solid organ transplantation (Tx), both survival rates and quality of life have improved dramatically over the last few decades. Each year, the number of people on the wait list continues to increase, widening the gap between organ supply and demand. Therefore, the use of extended criteria donor grafts is growing, despite higher susceptibility to ischemia-reperfusion injury (IRI) and consecutive inferior Tx outcomes. Thus, tools to characterize organ quality prior to Tx are crucial components for Tx success. Innovative techniques of metabolic profiling revealed key pathways and mechanisms involved in IRI occurring during organ preservation. Although large-scale trials are needed, metabolomics appears to be a promising tool to characterize potential biomarkers, for the assessment of graft quality before Tx and evaluate graft-related outcomes. In this comprehensive review, we summarize the currently available literature on the use of metabolomics in solid organ Tx, with a special focus on metabolic profiling during graft preservation to assess organ quality prior to Tx.