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Jadlowiec, Caroline C.

https://orcid.org/0000-0001-7860-9519

A5034172520 | I4210125099

Mayo Clinic

Divsion of Transplant Surgery

Citations 74

Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care

Journal of Personalized Medicine | August 21, 2023 | Volume: 13 | Issue: 8 | Pages: 1273

10.3390/jpm13081273 | PMID 37623523

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.
Past, Current, and Future Perspectives on Transplanting Acute Kidney Injury Kidneys

Clinics and Practice | August 14, 2023 | Volume: 13 | Issue: 4 | Pages: 944-958

10.3390/clinpract13040086 | PMID 37623267

(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.
Outcomes with transplanting kidneys offered through expedited allocation

Clinical Transplantation | August 11, 2023 | Volume: 37 | Issue: 11 | Pages: No page available

10.1111/ctr.15094 | PMID 37563488

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.
Differences between Kidney Transplant Recipients from Deceased Donors with Diabetes Mellitus as Identified by Machine Learning Consensus Clustering

Journal of Personalized Medicine | July 4, 2023 | Volume: 13 | Issue: 7 | Pages: 1094

10.3390/jpm13071094 | PMID 37511707

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.
Favorable outcomes in Hispanic recipients receiving simultaneous pancreas kidney transplantation

Clinical Transplantation | June 28, 2023 | Volume: 37 | Issue: 10 | Pages: No page available

10.1111/ctr.15062 | PMID 37378620

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.
Differences between Very Highly Sensitized Kidney Transplant Recipients as Identified by Machine Learning Consensus Clustering

Medicina | May 18, 2023 | Volume: 59 | Issue: 5 | Pages: 977

10.3390/medicina59050977 | PMID 37241209

Background and Objectives: The aim of our study was to categorize very highly sensitized kidney transplant recipients with pre-transplant panel reactive antibody (PRA) ≥ 98% using an unsupervised machine learning approach as clinical outcomes for this population are inferior, despite receiving increased allocation priority. Identifying subgroups with higher risks for inferior outcomes is essential to guide individualized management strategies for these vulnerable recipients. Materials and Methods: To achieve this, we analyzed the Organ Procurement and Transplantation Network (OPTN)/United Network for Organ Sharing (UNOS) database from 2010 to 2019 and performed consensus cluster analysis based on the recipient-, donor-, and transplant-related characteristics in 7458 kidney transplant patients with pre-transplant PRA ≥ 98%. The key characteristics of each cluster were identified by calculating the standardized mean difference. The post-transplant outcomes were compared between the assigned clusters. Results: We identified two distinct clusters and compared the post-transplant outcomes among the assigned clusters of very highly sensitized kidney transplant patients. Cluster 1 patients were younger (median age 45 years), male predominant, and more likely to have previously undergone a kidney transplant, but had less diabetic kidney disease. Cluster 2 recipients were older (median 54 years), female predominant, and more likely to be undergoing a first-time transplant. While patient survival was comparable between the two clusters, cluster 1 had lower death-censored graft survival and higher acute rejection compared to cluster 2. Conclusions: The unsupervised machine learning approach categorized very highly sensitized kidney transplant patients into two clinically distinct clusters with differing post-transplant outcomes. A better understanding of these clinically distinct subgroups may assist the transplant community in developing individualized care strategies and improving the outcomes for very highly sensitized kidney transplant patients.
Reassessing Geographic, Logistical, and Cold Ischemia Cutoffs in Liver Transplantation

Progress in Transplantation | April 4, 2023 | Volume: 33 | Issue: 2 | Pages: 168-174

10.1177/15269248231164169 | PMID 37013356

Introduction Liver acceptance patterns vary significantly between transplant centers. Data pertaining to outcomes of livers declined by local and regional centers and allocated nationally remains limited. Project aim The objective was to compare post-liver transplant outcomes between liver allografts transplanted as a result of national and local-regional allocation. Design This was a retrospective evaluation of 109 nationally allocated liver allografts used for transplant by a single center. Outcomes of nationally allocated grafts were compared to standard allocation grafts (N = 505) during the same period. Results Recipients of nationally allocated grafts had lower model for end stage liver disease scores (17 vs 22, P = .001). Nationally allocated grafts were more likely to be post-cross clamp offers (29.4% vs 13.4%, P = .001) and have longer cold ischemia times (median hours 7.8 vs 5.5, P = .001). Early allograft dysfunction was common (54.1% vs 52.5%, P = .75) and did not impact hospital length of stay (median 5 vs 6 days, P = .89). There were no differences in biliary complications ( P = .11). There were no differences in patient ( P = .88) or graft survival ( P = .35). In a multivariate model, after accounting for differences in cold ischemia time and posttransplant biliary complications, nationally allocated grafts were not associated with increased risk for graft loss (HR 0.9, 95% CI 0.4-1.8). Abnormal liver biopsy findings (33.0%) followed by donor donation after circulatory death status (22.9%) were the most common reasons for decline by local-regional centers. Conclusion Despite longer cold ischemia times, patient and graft survival outcomes remain excellent and comparable to those seen from standard allocation grafts.
Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering

Medicines | March 28, 2023 | Volume: 10 | Issue: 4 | Pages: 25

10.3390/medicines10040025 | PMID 37103780

Background: Better understanding of the different phenotypes/subgroups of non-U.S. citizen kidney transplant recipients may help the transplant community to identify strategies that improve outcomes among non-U.S. citizen kidney transplant recipients. This study aimed to cluster non-U.S. citizen kidney transplant recipients using an unsupervised machine learning approach; Methods: We conducted a consensus cluster analysis based on recipient-, donor-, and transplant- related characteristics in non-U.S. citizen kidney transplant recipients in the United States from 2010 to 2019 in the OPTN/UNOS database using recipient, donor, and transplant-related characteristics. Each cluster’s key characteristics were identified using the standardized mean difference. Post-transplant outcomes were compared among the clusters; Results: Consensus cluster analysis was performed in 11,300 non-U.S. citizen kidney transplant recipients and identified two distinct clusters best representing clinical characteristics. Cluster 1 patients were notable for young age, preemptive kidney transplant or dialysis duration of less than 1 year, working income, private insurance, non-hypertensive donors, and Hispanic living donors with a low number of HLA mismatch. In contrast, cluster 2 patients were characterized by non-ECD deceased donors with KDPI <85%. Consequently, cluster 1 patients had reduced cold ischemia time, lower proportion of machine-perfused kidneys, and lower incidence of delayed graft function after kidney transplant. Cluster 2 had higher 5-year death-censored graft failure (5.2% vs. 9.8%; p < 0.001), patient death (3.4% vs. 11.4%; p < 0.001), but similar one-year acute rejection (4.7% vs. 4.9%; p = 0.63), compared to cluster 1; Conclusions: Machine learning clustering approach successfully identified two clusters among non-U.S. citizen kidney transplant recipients with distinct phenotypes that were associated with different outcomes, including allograft loss and patient survival. These findings underscore the need for individualized care for non-U.S. citizen kidney transplant recipients.
Current opinions on DGF management practices: A survey of the United States and Canada

Clinical Transplantation | February 27, 2023 | Volume: 37 | Issue: 5 | Pages: No page available

10.1111/ctr.14949 | PMID 36849704

Abstract Introduction Significant center‐to‐center variation in attitudes and management of delayed graft function (DGF) remains common. Methods A survey to describe current DGF practices was developed by workgroup members sponsored by the National Kidney Foundation (NKF) and was distributed to both the NKF DGF workgroup members, kidney transplant program directors and the transplant community within the United States and Canada. Seventy‐one percent of NKF workgroup members completed the survey along with 70 unique the United States and three Canadian kidney transplant programs. All Organ Procurement and Transplantation Network (OPTN) regions were represented. Results DGF was reported to occur at rate of 20%–40% for most centers with 3.9% indicating their incidence to be >60%. Most centers reported longer hospital lengths of stay and more frequent outpatient visits. Despite the commonality of DGF, only half of centers reported having an established protocol to manage DGF. Kidney allograft biopsies were the only consistent DGF management strategy observed, although use of machine perfusion was also heavily favored. Other DGF management strategies voiced by a minority included having established outpatient practices to care for DGF patients and administering outpatient community‐based hemodialysis. Conclusion Although approximately a third of survey responders indicated that risk of DGF played a role in their willingness to accept organs, most did not feel that increased cost or clinical impact on outcomes was a deterrent. Future strategies, including broader sharing of best practices, redefining terminology specific to DGF, the establishment of DGF dialysis guidelines and improving access to machine perfusion across OPOs may help reduce discard and improve utilization of kidneys at risk for DGF.
Differences between kidney retransplant recipients as identified by machine learning consensus clustering

Clinical Transplantation | February 17, 2023 | Volume: 37 | Issue: 5 | Pages: No page available

10.1111/ctr.14943 | PMID 36799718

AbstractBackgroundOur study aimed to characterize kidney retransplant recipients using an unsupervised machine‐learning approach.MethodsWe 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 clustersResultsConsensus 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.ConclusionThe 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.