Jadlowiec, Caroline

ABSTRACTThis single‐center retrospective study investigated subclinical rejection prevalence and significance in simultaneous pancreas and kidney transplant (SPKT) recipients. We analyzed 352 SPKT recipients from July 2003 to April 2022. Our protocol included pancreas allograft surveillance biopsies at 1, 4, and 12months post‐transplant. After excluding 153 patients unable to undergo pancreas biopsy, our study cohort comprised 199 recipients. Among the 199 patients with protocol pancreas biopsies, 107 had multiple protocol pancreas biopsies in the first year, totaling 323. Subclinical rejection was identified in 132 episodes (41%). Of these, 72% were Grade 1, 20% were indeterminate, and 8% were Banff Grade 2 or higher. All episodes of subclinical rejection were treated. Rates of pancreas graft loss (10% vs. 7%) and clinical rejection (21% vs. 20%) at 3 years were similar between those with and without subclinical rejection. Subclinical rejection Banff Grade 2 or more was associated with poor pancreas graft survival HR of 5.5 (95% CI: 1.24–24.37, p = 0.025). Of 236 simultaneous protocol kidney and pancreas biopsies, 102 (43%) showed pancreas subclinical rejection, while only 17% had concurrent kidney subclinical rejection. Our findings suggest limited predictive value of pancreatic enzymes and euglycemia in detecting pancreas rejection. Furthermore, poor concordance existed between pancreas and kidney subclinical rejection.

Ex-situ machine perfusion of the liver has surmounted traditional limitations associated with static cold storage in the context of organ preservation. This innovative technology has changed the landscape of liver transplantation by mitigating ischemia perfusion injury, offering a platform for continuous assessment of organ quality, and providing an avenue for optimizing the use of traditionally marginal allografts. This review summarizes the contemporary clinical applications of machine perfusion devices and discusses potential future strategies for real-time viability assessment, therapeutic interventions, and modulation of organ function after recovery.

Background: Pancreas transplantation is a crucial surgical intervention for managing diabetes, but it faces challenges such as its invasive nature, stringent patient selection criteria, organ scarcity, and centralized expertise. Despite the steadily increasing number of pancreas transplants in the United States, there is a need to understand global trends in interest to increase awareness of and participation in pancreas and islet cell transplantation. Methods: We analyzed Google Search trends for “Pancreas Transplantation” and “Islet Cell Transplantation” from 2004 to 14 November 2023, assessing variations in search interest over time and across geographical locations. The Augmented Dickey–Fuller (ADF) test was used to determine the stationarity of the trends (p < 0.05). Results: Search interest for “Pancreas Transplantation” varied from its 2004 baseline, with a general decline in peak interest over time. The lowest interest was in December 2010, with a slight increase by November 2023. Ecuador, Kuwait, and Saudi Arabia showed the highest search interest. “Islet Cell Transplantation” had its lowest interest in December 2016 and a more pronounced decline over time, with Poland, China, and South Korea having the highest search volumes. In the U.S., “Pancreas Transplantation” ranked 4th in interest, while “Islet Cell Transplantation” ranked 11th. The ADF test confirmed the stationarity of the search trends for both procedures. Conclusions: “Pancreas Transplantation” and “Islet Cell Transplantation” showed initial peaks in search interest followed by a general downtrend. The stationary search trends suggest a lack of significant fluctuations or cyclical variations. These findings highlight the need for enhanced educational initiatives to increase the understanding and awareness of these critical transplant procedures among the public and professionals.

AbstractBackgroundWe 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.

Kidney transplantation is a critical treatment option for end-stage kidney disease patients, offering improved quality of life and increased survival rates. However, the complexities of kidney transplant care necessitate continuous advancements in decision making, patient communication, and operational efficiency. This article explores the potential integration of a sophisticated chatbot, an AI-powered conversational agent, to enhance kidney transplant practice and potentially improve patient outcomes. Chatbots and generative AI have shown promising applications in various domains, including healthcare, by simulating human-like interactions and generating contextually appropriate responses. Noteworthy AI models like ChatGPT by OpenAI, BingChat by Microsoft, and Bard AI by Google exhibit significant potential in supporting evidence-based research and healthcare decision making. The integration of chatbots in kidney transplant care may offer transformative possibilities. As a clinical decision support tool, it could provide healthcare professionals with real-time access to medical literature and guidelines, potentially enabling informed decision making and improved knowledge dissemination. Additionally, the chatbot has the potential to facilitate patient education by offering personalized and understandable information, addressing queries, and providing guidance on post-transplant care. Furthermore, under clinician or transplant pharmacist supervision, it has the potential to support post-transplant care and medication management by analyzing patient data, which may lead to tailored recommendations on dosages, monitoring schedules, and potential drug interactions. However, to fully ascertain its effectiveness and safety in these roles, further studies and validation are required. Its integration with existing clinical decision support systems may enhance risk stratification and treatment planning, contributing to more informed and efficient decision making in kidney transplant care. Given the importance of ethical considerations and bias mitigation in AI integration, future studies may evaluate long-term patient outcomes, cost-effectiveness, user experience, and the generalizability of chatbot recommendations. By addressing these factors and potentially leveraging AI capabilities, the integration of chatbots in kidney transplant care holds promise for potentially improving patient outcomes, enhancing decision making, and fostering the equitable and responsible use of AI in healthcare.

Longer pre-transplant dialysis duration is known to be associated with worse post-transplant outcomes. Our study aimed to cluster kidney transplant recipients with prolonged dialysis duration before transplant using an unsupervised machine learning approach to better assess heterogeneity within this cohort. We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 5092 kidney transplant recipients who had been on dialysis ≥ 10 years prior to transplant in the OPTN/UNOS database from 2010 to 2019. We characterized each assigned cluster and compared the posttransplant outcomes. Overall, the majority of patients with ≥10 years of dialysis duration were black (52%) or Hispanic (25%), with only a small number (17.6%) being moderately sensitized. Within this cohort, three clinically distinct clusters were identified. Cluster 1 patients were younger, non-diabetic and non-sensitized, had a lower body mass index (BMI) and received a kidney transplant from younger donors. Cluster 2 recipients were older, unsensitized and had a higher BMI; they received kidney transplant from older donors. Cluster 3 recipients were more likely to be female with a higher PRA. Compared to cluster 1, cluster 2 had lower 5-year death-censored graft (HR 1.40; 95% CI 1.16–1.71) and patient survival (HR 2.98; 95% CI 2.43–3.68). Clusters 1 and 3 had comparable death-censored graft and patient survival. Unsupervised machine learning was used to characterize kidney transplant recipients with prolonged pre-transplant dialysis into three clinically distinct clusters with variable but good post-transplant outcomes. Despite a dialysis duration ≥ 10 years, excellent outcomes were observed in most recipients, including those with moderate sensitization. A disproportionate number of minority recipients were observed within this cohort, suggesting multifactorial delays in accessing kidney transplantation.

(1) Background: Acute kidney injury (AKI) kidneys have high non-utilization rates due to concerns regarding unfavorable outcomes. In this paper, we aimed to review the past, present, and future opinions on AKI kidneys. (2) Methods: A PubMed search was conducted for topics relevant to AKI kidney transplantation. (3) Results: Current short- and long-term data on AKI kidneys have demonstrated good outcomes including favorable graft function and survival. The role of procurement biopsies is controversial, but they have been shown to be beneficial in AKI kidneys by allowing clinicians to differentiate between reversible tubular injury and irreversible cortical necrosis. Machine perfusion has also been applied to AKI kidneys and has been shown to reduce delayed graft function (DGF). The incidence of DGF increases with AKI severity and its management can be challenging. Strategies employed to counteract this have included early initiation of dialysis after kidney transplantation, early targeting of adequate immunosuppression levels to minimize rejection risk, and establishment of outpatient dialysis. (4) Conclusions: Despite good outcomes, there continue to be barriers that impact AKI kidney utilization. Successful strategies have included use of procurement biopsies or machine perfusion and expectant management of DGF. With increasing experience, better use of AKI kidneys can result in additional opportunities to expand the donor pool.

AbstractIntroductionExpedited out‐of‐sequence deceased donor kidney allocation is a strategy to avoid discards after early placement attempts have been unsuccessful. Our study aimed to assess outcomes and characteristics of these transplanted kidneys.MethodsKDPI matching was performed between expedited allocation (EA) and standard allocation (SA) deceased donor kidney transplants performed at our center.ResultsBetween 2018 and 2021, there were 225 EA offers, and 189 (84%) were transplanted. EA recipients were older (p = .007) and had shorter dialysis vintage (p < .0001). EA kidneys were likely to be nationally allocated (p < .001), have AKI (p < .0001) and longer CIT (p < .0001). There were no differences in EA and SA time‐zero kidney biopsies (ci, p = .07; ct, p = .89; cv, p = .95; ah, p = .79). EA kidneys had more DGF (p = .0006), but there were no differences in DGF duration (p = .83), hospital length of stay (p = .43), 1‐ and 2‐year eGFR (p = .16, p = .99), patient (p = .34), or death‐censored graft (p = .66) survival.ConclusionDuring this study period, our center transplanted 189 kidneys through EA following local‐regional declines. These kidneys often came from AKI donors and had more DGF but had similar outcomes to KDPI‐matched SA kidneys. Although it has been suggested that EA has the potential to worsen transplant disparities, transplant center level decisions on organ acceptance contribute to these variations.

Clinical outcomes of deceased donor kidney transplants coming from diabetic donors currently remain inconsistent, possibly due to high heterogeneities in this population. Our study aimed to cluster recipients of diabetic deceased donor kidney transplants using an unsupervised machine learning approach in order to identify subgroups with high risk of inferior outcomes and potential variables associated with these outcomes. Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 7876 recipients of diabetic deceased donor kidney transplants 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 the clusters. Consensus cluster analysis identified three clinically distinct clusters. Recipients in cluster 1 (n = 2903) were characterized by oldest age (64 ± 8 years), highest rate of comorbid diabetes mellitus (55%). They were more likely to receive kidney allografts from donors that were older (58 ± 6.3 years), had hypertension (89%), met expanded criteria donor (ECD) status (78%), had a high rate of cerebrovascular death (63%), and carried a high kidney donor profile index (KDPI). Recipients in cluster 2 (n = 687) were younger (49 ± 13 years) and all were re-transplant patients with higher panel reactive antibodies (PRA) (88 [IQR 46, 98]) who received kidneys from younger (44 ± 11 years), non-ECD deceased donors (88%) with low numbers of HLA mismatch (4 [IQR 2, 5]). The cluster 3 cohort was characterized by first-time kidney transplant recipients (100%) who received kidney allografts from younger (42 ± 11 years), non-ECD deceased donors (98%). Compared to cluster 3, cluster 1 had higher incidence of primary non-function, delayed graft function, patient death and death-censored graft failure, whereas cluster 2 had higher incidence of delayed graft function and death-censored graft failure but comparable primary non-function and patient death. An unsupervised machine learning approach characterized diabetic donor kidney transplant patients into three clinically distinct clusters with differing outcomes. Our data highlight opportunities to improve utilization of high KDPI kidneys coming from diabetic donors in recipients with survival-limiting comorbidities such as those observed in cluster 1.

AbstractThe objective of this study was to compare the long‐term outcomes of Hispanic versus white recipients who underwent simultaneous pancreas kidney transplantation (SPKT). This single‐center study, conducted from 2003 to 2022, had a median follow‐up of 7.5 years. The study included 91 Hispanic and 202 white SPKT recipients. The mean age (44 vs. 46 years), percentage of males (67% vs. 58%), and body mass index (BMI) (25.6 vs. 25.3 kg/m2) were similar between the Hispanic and white groups. The Hispanic group had more recipients with type 2 diabetes (38%) compared to the white group (5%, p < .001). The duration of dialysis was longer in Hispanics (640 vs. 473 days, p = .02), and fewer patients received preemptive transplants (10% vs. 29%, p < .01) compared to whites. Hospital length of stay, rates of BK Viremia, and acute rejection episodes within 1 year were similar between the groups. The estimated 5‐year kidney, pancreas, and patient survival rates were also similar between the groups, 94%, 81%, and 95% in Hispanics, compared to 90%, 79%, and 90% in whites. Increasing age and longer duration of dialysis were risk factors for death. Although Hispanic recipients had a longer duration on dialysis and fewer preemptive transplants, the survival rates were similar to those of white recipients. However, referring providers and many transplant centers continue to overlook pancreas transplants for appropriately selected patients with type 2 diabetes, particularly among minority populations. As a transplant community, it is crucial that we make efforts to comprehend and tackle these obstacles to transplantation.