Citations

Chronic kidney disease (CKD) poses a significant public health challenge, affecting approximately 11% to 13% of the global population [...]

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.

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.

Patients with IgA nephropathy (IgAN), including Henoch-Schönlein purpura nephritis (HSP), who present with rapidly progressive glomerulonephritis (RPGN) have a poor prognosis despite aggressive immunosuppressive therapy. The utility of plasmapheresis/plasma exchange (PLEX) for IgAN/HSP is not well established. This systematic review aims to assess the efficacy of PLEX for IgAN and HSP patients with RPGN. A literature search was conducted using MEDLINE, EMBASE, and through Cochrane Database from inception through September 2022. Studies that reported outcomes of PLEX in IgAN or HSP patients with RPGN were enrolled. The protocol for this systematic review is registered with PROSPERO (no. CRD42022356411). The researchers systematically reviewed 38 articles (29 case reports and 9 case series articles) with a total of 102 RPGN patients (64 (62.8%) had IgAN and 38 (37.2%) had HSP). The mean age was 25 years and 69% were males. There was no specific PLEX regimen utilized in these studies, but most patients received at least 3 PLEX sessions that were titrated based on the patient’s response/kidney recovery. The number of PLEX sessions ranged from 3 to 18, and patients additionally received steroids and immunosuppressive treatment (61.6% of patients received cyclophosphamide). Follow-up time ranged from 1 to 120 months, with the majority being followed for at least 2 months after PLEX. Among IgAN patients treated with PLEX, 42.1% (n = 27/64) achieved remission; 20.3% (n = 13/64) achieved complete remission (CR) and 18.7% (n = 12/64) partial remission (PR). 60.9% (n = 39/64) progressed to end-stage kidney disease (ESKD). Among HSP patients treated with PLEX, 76.3% (n = 29/38) achieved remission; of these, 68.4% (n = 26/38) achieved CR and 7.8% achieved (n = 3/38) PR. 23.6% (n = 9/38) progressed to ESKD. Among kidney transplant patients, 20% (n = 1/5) achieved remission and 80% (n = 4/5) progressed to ESKD. Adjunctive plasmapheresis/plasma exchange with immunosuppressive therapy showed benefits in some HSP patients with RPGN and possible benefits in IgAN patients with RPGN. Future prospective, multi-center, randomized clinical studies are needed to corroborate this systematic review’s findings.

Background: The utilization of multi-dimensional patient data to subtype hepatorenal syndrome (HRS) can individualize patient care. Machine learning (ML) consensus clustering may identify HRS subgroups with unique clinical profiles. In this study, we aim to identify clinically meaningful clusters of hospitalized patients for HRS using an unsupervised ML clustering approach. Methods: Consensus clustering analysis was performed based on patient characteristics in 5564 patients primarily admitted for HRS in the National Inpatient Sample from 2003–2014 to identify clinically distinct HRS subgroups. We applied standardized mean difference to evaluate key subgroup features, and compared in-hospital mortality between assigned clusters. Results: The algorithm revealed four best distinct HRS subgroups based on patient characteristics. Cluster 1 patients (n = 1617) were older, and more likely to have non-alcoholic fatty liver disease, cardiovascular comorbidities, hypertension, and diabetes. Cluster 2 patients (n = 1577) were younger and more likely to have hepatitis C, and less likely to have acute liver failure. Cluster 3 patients (n = 642) were younger, and more likely to have non-elective admission, acetaminophen overdose, acute liver failure, to develop in-hospital medical complications and organ system failure, and to require supporting therapies, including renal replacement therapy, and mechanical ventilation. Cluster 4 patients (n = 1728) were younger, and more likely to have alcoholic cirrhosis and to smoke. Thirty-three percent of patients died in hospital. In-hospital mortality was higher in cluster 1 (OR 1.53; 95% CI 1.31–1.79) and cluster 3 (OR 7.03; 95% CI 5.73–8.62), compared to cluster 2, while cluster 4 had comparable in-hospital mortality (OR 1.13; 95% CI 0.97–1.32). Conclusions: Consensus clustering analysis provides the pattern of clinical characteristics and clinically distinct HRS phenotypes with different outcomes.

Antifibrotic treatment has been approved for reducing disease progression in fibrotic interstitial lung disease (ILD). As a result of increased bleeding risk, some experts suggest cessation of antifibrotics prior to lung transplantation (LT). However, extensive knowledge regarding the impact of antifibrotic treatment on postoperative complications remains unclear. We performed a comprehensive search of several databases from their inception through to 30 September 2021. Original studies were included in the final analysis if they compared postoperative complications, including surgical wound dehiscence, anastomosis complication, bleeding complications, and primary graft dysfunction, between those with and without antifibrotic treatment undergoing LT. Of 563 retrieved studies, 6 studies were included in the final analysis. A total of 543 ILD patients completing LT were included, with 161 patients continuing antifibrotic treatment up to the time of LT and 382 without prior treatment. Antifibrotic treatment was not significantly associated with surgical wound dehiscence (RR 1.05; 95% CI, 0.31–3.60; I2 = 0%), anastomotic complications (RR 0.88; 95% CI, 0.37–2.12; I2 = 31%), bleeding complications (RR 0.76; 95% CI, 0.33–1.76; I2 = 0%), or primary graft dysfunction (RR 0.87; 95% CI, 0.59–1.29; I2 = 0%). Finally, continuing antifibrotic treatment prior to LT was not significantly associated with decreased 1-year mortality (RR 0.80; 95% CI, 0.41–1.58; I2 = 0%). Our study suggests a similar risk of postoperative complications in ILD patients undergoing LT who received antifibrotic treatment compared to those not on antifibrotic therapy.

Introduction: Posttransplant anemia is a common finding after kidney transplantation. A previous meta-analysis reported an association between anemia and graft loss. However, data on cardiovascular outcomes have not yet been reported. Objective: We conducted an updated meta-analysis to examine the association between posttransplant anemia and outcomes after transplantation including cardiovascular mortality in adult kidney transplant recipients. Methods: We comprehensively searched the databases of MEDLINE and EMBASE from inception to November 2021. Data from each study were combined using the random-effects model. Generic inverse variance method of DerSimonian and Laird was employed to calculate the risk ratios and 95% CIs. Results: Seventeen studies from August 2006 to April 2019 were included (16 463 kidney transplantation recipients). Posttransplant anemia was associated with overall mortality (pooled risk ratio = 1.72 [1.39, 2.13], I 2 = 56%), graft loss (pooled risk ratio = 2.28 [1.77, 2.93], I 2 = 94%), cardiovascular death (pooled risk ratio = 2.06 [1.35, 3.16], I 2 = 0%), and cardiovascular events (pooled risk ratio = 1.33 [1.10, 1.61], I 2 = 0%). Early anemia (≤6 months), compared with late anemia (>6 months), has higher risk of overall mortality and graft loss with a pooled risk ratio of 2.63 (95% CI 1.79-3.86; I 2 = 0%) and 2.96 (95% CI 2.29-3.82; I 2 = 0%), respectively. Discussion: In addition to increased risk of graft loss, our updated meta-analysis demonstrated that posttransplant anemia was significantly associated with poor outcomes after kidney transplantation including overall mortality, graft loss, cardiovascular death, and cardiovascular events. Future studies are required to assess the effects of treatment strategies for posttransplant anemia on posttransplant outcomes including cardiovascular mortality.

Background: The Mediterranean, Dietary Approach to Stop Hypertension (DASH), and plant-based diets may provide cardiovascular benefit to the general population. However, data on their effect on end stage kidney disease (ESKD) patients are limited. This systematic review aims to assess the impact of Mediterranean, DASH, and plant-based diets on outcomes among ESKD patients. Methods: A literature review was conducted in EMBASE, MEDLINE, and Cochrane databases from inception through September 2022 to identify studies that assess the clinical outcomes of Mediterranean, DASH, or plant-based diets on ESKD patients on hemodialysis (HD) or peritoneal dialysis (PD). Effect estimates from the individual studies were derived utilizing the random-effect, generic inverse variance approach of DerSimonian and Laird. Results: Seven studies with 9400 ESKD patients (8395 HD and 1005 PD) met the eligibility criteria and were included in the data analysis. Pooled odds ratios (ORs) of mortality for ESKD patients who adhered to the Mediterranean versus plant-based diet were 0.49 (95% CI: 0.07–3.54; two studies, I2 = 67%) and 0.87 (95% CI: 0.75–1.01; two studies, I2 = 0%), respectively. Data on mortality for ESKD patients on a DASH diet were limited to one study with an OR of 1.00 (95% CI: 0.89–1.12). The pooled OR of cardiovascular mortality among ESKD patients who adhered to a plant-based diet was 0.86 (95% CI: 0.68–1.08; two studies, I2 = 0%), compared to those who did not. Data on cardiovascular mortality among those with Mediterranean and DASH diet were limited to one study with ORs of 1.14 (95% CI: 0.90–1.43) and 1.19 (95% CI: 0.99–1.43), respectively. Mediterranean diet adherence was found to be associated with reduced risk of left ventricular hypertrophy (LVH) with an OR of 0.82 (95% CI: 0.68–0.99) in a study including 127 ESKD patients. The risk of hyperkalemia was not significant among those with a plant-based diet with an OR of 1.00 (95% CI: 0.94–1.07) in a study including 150 ESKD patients. Conclusions: While our systematic review demonstrated no significant associations of Mediterranean, DASH, and plant-based diets with reduced all-cause mortality or cardiovascular mortality, there was also no evidence that suggested harmful effects of these diets to ESKD patients.

Background and Objectives: Our study aimed to cluster dual kidney transplant recipients using an unsupervised machine learning approach to characterize donors and recipients better and to compare the survival outcomes across these various clusters. Materials and Methods: We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 2821 dual kidney transplant recipients 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 clusters. Results: Two clinically distinct clusters were identified by consensus cluster analysis. Cluster 1 patients was characterized by younger patients (mean recipient age 49 ± 13 years) who received dual kidney transplant from pediatric (mean donor age 3 ± 8 years) non-expanded criteria deceased donor (100% non-ECD). In contrast, Cluster 2 patients were characterized by older patients (mean recipient age 63 ± 9 years) who received dual kidney transplant from adult (mean donor age 59 ± 11 years) donor with high kidney donor profile index (KDPI) score (59% had KDPI ≥ 85). Cluster 1 had higher patient survival (98.0% vs. 94.6% at 1 year, and 92.1% vs. 76.3% at 5 years), and lower acute rejection (4.2% vs. 6.1% within 1 year), when compared to cluster 2. Death-censored graft survival was comparable between two groups (93.5% vs. 94.9% at 1 year, and 89.2% vs. 84.8% at 5 years). Conclusions: In summary, DKT in the United States remains uncommon. Two clusters, based on specific recipient and donor characteristics, were identified through an unsupervised machine learning approach. Despite varying differences in donor and recipient age between the two clusters, death-censored graft survival was excellent and comparable. Broader utilization of DKT from high KDPI kidneys and pediatric en bloc kidneys should be encouraged to better address the ongoing organ shortage.