Alkaline phosphatase to treat ischaemia-reperfusion injury in living-donor kidney transplantation: APhIRI I feasibility pilot study.

AIMS: Ischemia-reperfusion injury (IRI) during kidney transplant procedures is associated with adverse outcome. Alkaline phosphatase (AP) is an enzyme that has the potential to dampen IRI. Prior to this study, it had not been tested in the setting of kidney transplantation. This study aimed to evaluate the safety and feasibility of peri-procedural AP administration in living donor kidney transplantation. METHODS: In this double blind, randomized, placebo-controlled, single-center pilot study, all eligible recipients of living donor kidneys were asked to give informed consent. AP (bRESCAP) or a placebo was administered intravenously over 24 hours after the transplantation procedure. The primary outcome-graft function at 1 year-was represented by iohexol measured glomerular filtration rate (mGFR). Serum and urine biomarkers within seven days after surgery were used as surrogate markers of kidney function and injury. RESULTS: Eleven patients were enrolled of whom five were treated with bRESCAP and six with placebo. After 1 year, mGFR was not different between groups. No specific adverse events were observed in the bRESCAP group. Urine expression of injury biomarkers CCL14, NGAL and Cystatin C was lower in the bRESCAP group at day seven. This was statistically significant. CONCLUSION: This study illustrates that bRESCAP treatment is feasible in kidney transplantation, might have a dampening effect on IRI induced renal inflammation, and raises no safety concerns. Future research will evaluate the effects of bRESCAP treatment in donation after circulatory death kidney transplantation where IRI is more pronounced.

Donor characteristics and their impact on kidney transplantation outcomes: Results from two nationwide instrumental variable analyses based on outcomes of donor kidney pairs accepted for transplantation.

Background: Donor-characteristics and donor characteristics-based decision algorithms are being progressively used in the decision process whether or not to accept an available donor kidney graft for transplantation. While this may improve outcomes, the performance characteristics of the algorithms remains moderate. To estimate the impact of donor factors of grafts accepted for transplantation on transplant outcomes, and to test whether implementation of donor-characteristics-based algorithms in clinical decision-making is justified, we applied an instrumental variable analysis to outcomes for kidney donor pairs transplanted in different individuals. Methods: This analysis used (dis)congruent outcomes of kidney donor pairs as an instrument and was based on national transplantation registry data for all donor kidney pairs transplanted in separate individuals in the Netherlands (1990-2018, 2,845 donor pairs), and the United Kingdom (UK, 2000-2018, 11,450 pairs). Incident early graft loss (EGL) was used as the primary discriminatory factor. It was reasoned that a scenario with a dominant impact of donor variables on transplantation outcomes would result in high concordance of EGL in both recipients, whilst dominance of asymmetrical outcomes could indicate a more complex scenario, involving an interaction of donor, procedural and recipient factors. Findings: Incidences of congruent EGL (Netherlands: 1·2%, UK: 0·7%) were slightly lower than the arithmetical (stochastic) incidences, suggesting that once a graft has been accepted for transplantation, donor factors minimally contribute to incident EGL. A long-term impact of donor factors was explored by comparing outcomes for functional grafts from donor pairs with asymmetrical vs. symmetrical outcomes. Recipient survival was similar for both groups, but a slightly compromised graft survival was observed for grafts with asymmetrical outcomes in the UK cohort: (10-years Hazard Ratio for graft loss: 1·18 [1·03-1·35] p<0·018); and 5 years eGFR (48·6 [48·3-49·0] vs. 46·0 [44·5-47·6] ml/min in the symmetrical outcome group, p<0·001). Interpretation: Our results suggest that donor factors for kidney grafts deemed acceptable for transplantation impact minimally on transplantation outcomes. A strong reliance on donor factors and/or donor-characteristics-based decision algorithms could result in unjustified rejection of grafts. Future efforts to optimize transplant outcomes should focus on a better understanding of the recipient factors underlying transplant outcomes. Funding: None.

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study.

BACKGROUND: Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable expertise, time, and effort. We aimed to analyse the utility of deep learning to preclassify histology of kidney allograft biopsies into three main broad categories (ie, normal, rejection, and other diseases) as a potential biopsy triage system focusing on transplant rejection. METHODS: We performed a retrospective, multicentre, proof-of-concept study using 5844 digital whole slide images of kidney allograft biopsies from 1948 patients. Kidney allograft biopsy samples were identified by a database search in the Departments of Pathology of the Amsterdam UMC, Amsterdam, Netherlands (1130 patients) and the University Medical Center Utrecht, Utrecht, Netherlands (717 patients). 101 consecutive kidney transplant biopsies were identified in the archive of the Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany. Convolutional neural networks (CNNs) were trained to classify allograft biopsies as normal, rejection, or other diseases. Three times cross-validation (1847 patients) and deployment on an external real-world cohort (101 patients) were used for validation. Area under the receiver operating characteristic curve (AUROC) was used as the main performance metric (the primary endpoint to assess CNN performance). FINDINGS: Serial CNNs, first classifying kidney allograft biopsies as normal (AUROC 0·87 [ten times bootstrapped CI 0·85-0·88]) and disease (0·87 [0·86-0·88]), followed by a second CNN classifying biopsies classified as disease into rejection (0·75 [0·73-0·76]) and other diseases (0·75 [0·72-0·77]), showed similar AUROC in cross-validation and deployment on independent real-world data (first CNN normal AUROC 0·83 [0·80-0·85], disease 0·83 [0·73-0·91]; second CNN rejection 0·61 [0·51-0·70], other diseases 0·61 [0·50-0·74]). A single CNN classifying biopsies as normal, rejection, or other diseases showed similar performance in cross-validation (normal AUROC 0·80 [0·73-0·84], rejection 0·76 [0·66-0·80], other diseases 0·50 [0·36-0·57]) and generalised well for normal and rejection classes in the real-world data. Visualisation techniques highlighted rejection-relevant areas of biopsies in the tubulointerstitium. INTERPRETATION: This study showed that deep learning-based classification of transplant biopsies could support pathological diagnostics of kidney allograft rejection. FUNDING: European Research Council; German Research Foundation; German Federal Ministries of Education and Research, Health, and Economic Affairs and Energy; Dutch Kidney Foundation; Human(e) AI Research Priority Area of the University of Amsterdam; and Max-Eder Programme of German Cancer Aid.

ABO-incompatible kidney transplantation in perspective of deceased donor transplantation and induction strategies: a propensity-matched analysis.

Kidney transplant candidates are blood group incompatible with roughly one out of three potential living donors. We compared outcomes after ABO-incompatible (ABOi) kidney transplantation with matched ABO-compatible (ABOc) living and deceased donor transplantation and analyzed different induction regimens. We performed a retrospective study with propensity matching and compared patient and death-censored graft survival after ABOi versus ABOc living donor and deceased donor kidney transplantation in a nationwide registry from 2006 till 2019. 296 ABOi were compared with 1184 center and propensity-matched ABOc living donor and 1184 deceased donor recipients (matching: recipient age, sex, blood group, and PRA). Patient survival was better compared with deceased donor [hazard ratio (HR) for death of HR 0.69 (0.49-0.96)] and non-significantly different from ABOc living donor recipients [HR 1.28 (0.90-1.81)]. Rate of graft failure was higher compared with ABOc living donor transplantation [HR 2.63 (1.72-4.01)]. Rejection occurred in 47% of 140 rituximab versus 22% of 50 rituximab/basiliximab, and 4% of 92 alemtuzumab-treated recipients (P < 0.001). ABOi kidney transplantation is superior to deceased donor transplantation. Rejection rate and graft failure are higher compared with matched ABOc living donor transplantation, underscoring the need for further studies into risk stratification and induction therapy [NTR7587, www.trialregister.nl].

Improving outcomes for donation after circulatory death kidney transplantation: Science of the times.

The use of kidneys donated after circulatory death (DCD) remains controversial due to concerns with regard to high incidences of early graft loss, delayed graft function (DGF), and impaired graft survival. As these concerns are mainly based on data from historical cohorts, they are prone to time-related effects and may therefore not apply to the current timeframe. To assess the impact of time on outcomes, we performed a time-dependent comparative analysis of outcomes of DCD and donation after brain death (DBD) kidney transplantations. Data of all 11,415 deceased-donor kidney transplantations performed in The Netherlands between 1990-2018 were collected. Based on the incidences of early graft loss, two eras were defined (1998-2008 [n = 3,499] and 2008-2018 [n = 3,781]), and potential time-related effects on outcomes evaluated. Multivariate analyses were applied to examine associations between donor type and outcomes. Interaction tests were used to explore presence of effect modification. Results show clear time-related effects on posttransplant outcomes. The 1998-2008 interval showed compromised outcomes for DCD procedures (higher incidences of DGF and early graft loss, impaired 1-year renal function, and inferior graft survival), whereas DBD and DCD outcome equivalence was observed for the 2008-2018 interval. This occurred despite persistently high incidences of DGF in DCD grafts, and more adverse recipient and donor risk profiles (recipients were 6 years older and the KDRI increased from 1.23 to 1.39 and from 1.35 to 1.49 for DBD and DCD donors). In contrast, the median cold ischaemic period decreased from 20 to 15 hours. This national study shows major improvements in outcomes of transplanted DCD kidneys over time. The time-dependent shift underpins that kidney transplantation has come of age and DCD results are nowadays comparable to DBD transplants. It also calls for careful interpretation of conclusions based on historical cohorts, and emphasises that retrospective studies should correct for time-related effects.

A nationwide evaluation of deceased donor kidney transplantation indicates detrimental consequences of early graft loss.

Early graft loss (EGL) is a feared outcome of kidney transplantation. Consequently, kidneys with an anticipated risk of EGL are declined for transplantation. In the most favorable scenario, with optimal use of available donor kidneys, the donor pool size is balanced by the risk of EGL, with a tradeoff dictated by the consequences of EGL. To gauge the consequence of EGL we systematically evaluated its impact in an observational study that included all 10,307 deceased-donor kidney transplantations performed in The Netherlands between 1990 and 2018. Incidence of EGL, defined as graft loss within 90 days, in primary transplantation was 8.2% (699/8,511). The main causes were graft rejection (30%), primary nonfunction (25%), and thrombosis or infarction (20%). EGL profoundly impacted short- and long-term patient survival (adjusted hazard ratio; 95% confidence interval: 8.2; 5.1-13.2 and 1.7; 1.3-2.1, respectively). Of the EGL recipients who survived 90 days after transplantation (617/699) only 440 of the 617 were relisted for re-transplantation. Of those relisted, only 298 were ultimately re-transplanted leading to an actual re-transplantation rate of 43%. Noticeably, re-transplantation was associated with a doubled incidence of EGL, but similar long-term graft survival (adjusted hazard ratio 1.1; 0.6-1.8). Thus, EGL after kidney transplantation is a medical catastrophe with high mortality rates, low relisting rates, and increased risk of recurrent EGL following re-transplantation. This implies that detrimental outcomes also involve convergence of risk factors in recipients with EGL. The 8.2% incidence of EGL minimally impacted population mortality, indicating this incidence is acceptable.

Prediction models for delayed graft function: external validation on The Dutch Prospective Renal Transplantation Registry.

Background: Delayed graft function (DGF) is a common complication after kidney transplantation in the era of accepting an equal number of brain- and circulatory-death donor kidneys in the Netherlands. To identify those cases with an increased risk of developing DGF, various multivariable algorithms have been proposed. The objective was to validate the reproducibility of four predictive algorithms by Irish et al. (A risk prediction model for delayed graft function in the current era of deceased donor renal transplantation. Am J Transplant 2010;10:2279-2286) (USA), Jeldres et al. (Prediction of delayed graft function after renal transplantation. Can Urol Assoc J 2009;3:377-382) (Canada), Chapal et al. (A useful scoring system for the prediction and management of delayed graft function following kidney transplantation from cadaveric donors. Kidney Int 2014;86:1130-1139) (France) and Zaza et al. (Predictive model for delayed graft function based on easily available pre-renal transplant variables. Intern Emerg Med 2015;10:135-141) (Italy) according to a novel framework for external validation. Methods: We conducted a prospective observational study with data from the Dutch Organ Transplantation Registry (NOTR). Renal transplant recipients from all eight Dutch academic medical centers between 2002 and 2012 who received a deceased allograft were included (N = 3333). The four prediction algorithms were reconstructed from donor, recipient and transplantation data. Their predictive value for DGF was validated by c-statistics, calibration statistics and net benefit analysis. Case-mix (un)relatedness was investigated with a membership model and mean and standard deviation of the linear predictor. Results: The prevalence of DGF was 37%. Despite a significantly different case-mix, the US algorithm by Irish was best reproducible, with a c-index of 0.761 (range 0.756 - 0.762), and well-calibrated over the complete range of predicted probabilities of having DGF. The US model had a net benefit of 0.242 at a threshold probability of 0.25, compared with 0.089 net benefit for the same threshold in the original study, equivalent to correctly identifying DGF in 24 cases per 100 patients (true positive results) without an increase in the number of false-positive results. Conclusions: The US model by Irish et al. was generalizable and best transportable to Dutch recipients with a deceased donor kidney. The algorithm detects an increased risk of DGF after allocation and enables us to improve individual patient management.

Equivalent Long-term Transplantation Outcomes for Kidneys Donated After Brain Death and Cardiac Death: Conclusions From a Nationwide Evaluation.

BACKGROUND: Despite growing waiting lists for renal transplants, hesitations persist with regard to the use of deceased after cardiac death (DCD) renal grafts. We evaluated the outcomes of DCD donations in The Netherlands, the country with the highest proportion of DCD procedures (42.9%) to test whether these hesitations are justified. METHODS: This study included all procedures with grafts donated after brain death (DBD) (n = 3611) and cardiac death (n = 2711) performed between 2000 and 2017. Transplant outcomes were compared by Kaplan Meier and Cox regression analysis, and factors associated with short (within 90 days of transplantation) and long-term graft loss evaluated in multi-variable analyses. FINDINGS: Despite higher incidences of early graft loss (+ 50%) and delayed graft function (+ 250%) in DCD grafts, 10-year graft and recipient survival were similar for the two graft types (Combined 10-year graft survival: 73.9% (95% CI: 72.5-75.2), combined recipient survival: 64.5% (95 CI: 63.0-66.0%)). Long-term outcome equivalence was explained by a reduced impact of delayed graft function on DCD graft survival (RR: 0.69 (95% CI: 0.55-0.87), p < 0.001). Mid and long-term graft function (eGFR), and the impact of incident delayed graft function on eGFR were similar for DBD and DCD grafts. INTERPRETATION: Mid and long term outcomes for DCD grafts are equivalent to DBD kidneys. Poorer short term outcomes are offset by a lesser impact of delayed graft function on DCD graft survival. This nation-wide evaluation does not justify the reluctance to use of DCD renal grafts. A strong focus on short-term outcome neglects the superior recovery potential of DCD grafts.

Stretching the Limits of Renal Transplantation in Elderly Recipients of Grafts from Elderly Deceased Donors.

An increasing number of elderly patients (≥65 years) receive a donor kidney from elderly donors after brain death (DBD) or after circulatory death (DCD). These organs are allocated within the Eurotransplant Senior Program, but outcomes must be evaluated. From the Dutch Organ Transplantation Registry, we selected 3597 recipients (≥18 years) who received a first DBD or DCD kidney during 2002-2012, and categorized them as young or elderly recipients receiving a graft from either a young or elderly donor, stratified by donor type. In multiple logistic regression analysis, elderly recipients of elderly DCD kidneys experienced more delayed graft function and acute rejection than did elderly recipients of young DBD kidneys (odds ratios 10.43 [95% confidence interval (95% CI), 5.75 to 18.91] and 2.78 [95% CI, 1.35 to 5.73], respectively). In Cox regression analysis, elderly recipients of elderly DCD kidneys had a 5-year mortality risk higher than that of elderly recipients of young DBD kidneys (hazard ratio, 1.86; 95% CI, 1.15 to 3.02). Elderly recipients of elderly kidneys had a 5-year mortality rate comparable to that of waitlisted elderly patients remaining on dialysis. Among elderly recipients, 63.8% of those who received elderly DCD kidneys, 45.5% of those who received elderly DBD kidneys, and approximately 26% of those who received young DBD or DCD kidneys had an eGFR<30 ml/min per 1.73 m2 (including primary nonfunction) after 1 year. In conclusion, improving donor selection and preservation is warranted if the allocation of elderly DCD grafts to elderly recipients is to be expanded.

Similar 5-Year Estimated Glomerular Filtration Rate Between Kidney Transplants From Uncontrolled and Controlled Donors After Circulatory Death-A Dutch Cohort Study.

BACKGROUND: Organ shortage persists despite a high rate of donation after circulatory death (DCD) in the Netherlands. The median waiting time for a deceased donor kidney in 2013 was 3.5 years. Most DCD kidneys are from controlled DCD (cDCD; Maastricht category III). Experience with uncontrolled donors after cardiac death (uDCD), that is, donors with an unexpected and irreversible cardiac arrest (Maastricht categories I and II), is increasing; and its effect on transplant outcomes needs evaluation. METHODS: We used the Dutch Organ Transplantation Registry to include recipients (≥18 years old) from all Dutch centers who received transplants from 2002 to 2012 with a first DCD kidney. We compared transplant outcome in uDCD (n = 97) and cDCD (n = 1441). RESULTS: Primary nonfunction in uDCD was higher than in the cDCD (19.6% vs 9.6%, P < 0.001, respectively). Delayed graft function was also higher in uDCD than in cDCD, but not significantly (73.7% vs 63.3%, P = .074, respectively). If censored for primary nonfunction, estimated glomerular filtration rates after 1 year and 5 years were comparable between uDCD and cDCD (1 year: uDCD, 44.3 (23.4) mL/min/m and cDCD, 45.8 (24.1) mL/min/m; P = 0.621; 5 years: uDCD, 49.1 (25.6) mL/min/m and cDCD, 47.7 (21.7) mL/min/m; P = 0.686). The differences in primary nonfunction between kidneys from uDCD and cDCD were explained by differences in the first warm ischemic period, cold ischemic time, and donor age. CONCLUSIONS: We conclude that uDCD kidneys have potential for excellent function and can constitute a valuable extension of the donor pool. However, further efforts are necessary to address the high rate of primary nonfunction.