A pragmatic approach to selective genetic testing in kidney transplant candidates.

Introduction: Advances in the field of genetic testing have spurred its use in transplantation. Potential benefits of genetic testing in transplant nephrology include diagnosis, treatment, risk stratification of recurrent disease, and risk stratification in potential donors. However, it is unclear how to best apply genetic testing in this population to maximize its yield.

A comparative analysis of kidney allograft outcomes in steroid use versus steroid discontinuation after basiliximab and ATG induction: A UNOS database study.

Background And Objectives: The relative safety and efficacy of early steroid withdrawal in kidney transplant patients after basiliximab compared to anti-thymocyte globulin (ATG) induction therapy is unknown. We aimed to compare kidney allograft outcomes in steroid use versus steroid discontinuation after basiliximab and ATG induction from the United Network for Organ Sharing (UNOS) database.

Materials And Methods: We conducted a retrospective cohort analysis of the UNOS database and included first kidney transplant recipients who received ATG or basiliximab induction therapy.

Recurrence of membranous nephropathy after kidney transplantation: A multicenter retrospective cohort study.

Membranous nephropathy (MN) is a leading cause of kidney failure worldwide and frequently recurs after transplant. Available data originated from small retrospective cohort studies or registry analyses; therefore, uncertainties remain on risk factors for MN recurrence and response to therapy. Within the Post-Transplant Glomerular Disease Consortium, we conducted a retrospective multicenter cohort study examining the MN recurrence rate, risk factors, and response to treatment.

Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering.

Background: Educational attainment significantly influences post-transplant outcomes in kidney transplant patients. However, research on specific attributes of lower-educated subgroups remains underexplored. This study utilized unsupervised machine learning to segment kidney transplant recipients based on education, further analyzing the relationship between these segments and post-transplant results.

Case report: Successful simultaneous heart-kidney transplantation across a positive complement-dependent cytotoxic crossmatch.

Preformed donor-specific antibodies are associated with a higher risk of rejection and worse graft survival in organ transplantation. However, in heart transplantation, the risk and benefit balance between high mortality on the waiting list and graft survival may allow the acceptance of higher immunologic risk donors in broadly sensitized recipients. Transplanting donor-recipient pairs with a positive complement dependent cytotoxic (CDC) crossmatch carries the highest risk of hyperacute rejection and immediate graft loss and is usually avoided in kidney transplantation.

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

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.

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

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.

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

: 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. : 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%.

Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering.

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.

Distinct phenotypes of kidney transplant recipients aged 80 years or older in the USA by machine learning consensus clustering.

Objectives: This study aimed to identify distinct clusters of very elderly kidney transplant recipients aged ≥80 and assess clinical outcomes among these unique clusters.

Design: Cohort study with machine learning (ML) consensus clustering approach.

Setting And Participants: All very elderly (age ≥80 at time of transplant) kidney transplant recipients in the Organ Procurement and Transplantation Network/United Network for Organ Sharing database database from 2010 to 2019.

Differences between kidney retransplant recipients as identified by machine learning consensus clustering.

Background: Our study aimed to characterize kidney retransplant recipients using an unsupervised machine-learning approach.

Methods: We 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 >.

Clinical Phenotypes of Dual Kidney Transplant Recipients in the United States as Identified through Machine Learning Consensus Clustering.

: 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. : 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.

Characteristics of Kidney Recipients of High Kidney Donor Profile Index Kidneys as Identified by Machine Learning Consensus Clustering.

Background: Our study aimed to characterize kidney transplant recipients who received high kidney donor profile index (KDPI) kidneys using unsupervised machine learning approach. Methods: We used the OPTN/UNOS database from 2010 to 2019 to perform consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 8935 kidney transplant recipients from deceased donors with KDPI ≥ 85%. We identified each cluster’s key characteristics using the standardized mean difference of >0.

Immunogenicity of SARS-CoV-2 vaccines in patients with multiple myeloma: a systematic review and meta-analysis.

Patients with multiple myeloma (MM) have a diminished immune response to coronavirus disease 2019 (COVID-19) vaccines. Risk factors for an impaired immune response are yet to be determined. We aimed to summarize the COVID-19 vaccine immunogenicity and to identify factors that influence the humoral immune response in patients with MM.

Distinct Phenotypes of Kidney Transplant Recipients in the United States with Limited Functional Status as Identified through Machine Learning Consensus Clustering.

Background: There have been concerns regarding increased perioperative mortality, length of hospital stay, and rates of graft loss in kidney transplant recipients with functional limitations. The application of machine learning consensus clustering approach may provide a novel understanding of unique phenotypes of functionally limited kidney transplant recipients with distinct outcomes in order to identify strategies to improve outcomes. Methods: Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 3205 functionally limited kidney transplant recipients (Karnofsky Performance Scale (KPS) < 40% at transplant) in the OPTN/UNOS database from 2010 to 2019.

Machine Learning Consensus Clustering of Morbidly Obese Kidney Transplant Recipients in the United States.

Background: This study aimed to better characterize morbidly obese kidney transplant recipients, their clinical characteristics, and outcomes by using an unsupervised machine learning approach. Methods: Consensus cluster analysis was applied to OPTN/UNOS data from 2010 to 2019 based on recipient, donor, and transplant characteristics in kidney transplant recipients with a pre-transplant BMI ≥ 40 kg/m2. Key cluster characteristics were identified using the standardized mean difference.

Protocol-based donor-derived cell-free DNA surveillance in kidney transplant recipients: A single-center experience.

Aims: Donor-derived cell-free DNA (dd-cfDNA) surveillance testing has never been studied in comparison with other surveillance tests. In this study we aim to describe our center's clinical experience with routine dd-cfDNA monitoring and to assess whether monitoring dd-cfDNA by protocol provides additional information that aids in detection of acute rejection.

Materials And Methods: We implemented the dd-cfDNA (Allosure) surveillance protocol in addition to measurements of serum creatinine, proteinuria, and donor-Specific antibody.

Novel Glucose-Lowering Therapies in the Setting of Solid Organ Transplantation.

Post-transplant diabetes mellitus is a frequent consequence of or a pre-existing comorbidity in solid organ transplantation (SOT) that is associated with greater morbidity and mortality. Novel glucose-lowering agents that have been shown to have cardiovascular morbidity/mortality benefit and renal protective effects such as sodium glucose transporter 2 inhibitors and glucagon-like peptide-1 receptor agonists are being incorporated into new standard of care for diabetes mellitus. There is a paucity of data regarding the use of these agents in SOT.

Recurrence of IgA Nephropathy after Kidney Transplantation in Adults.

Background And Objectives: In patients with kidney failure due to IgA nephropathy, IgA deposits can recur in a subsequent kidney transplant. The incidence, effect, and risk factors of IgA nephropathy recurrence is unclear, because most studies have been single center and sample sizes are relatively small.

Design, Setting, Participants, & Measurements: We performed a multicenter, international, retrospective study to determine the incidence, risk factors, and treatment response of recurrent IgA nephropathy after kidney transplantation.

Eliminating racial disparities in kidney transplantation.

Kidney transplantation improves survival and quality of life among patients with kidney failure. Based on OPTN policy 8.4.

Serious Illness Conversations in advanced kidney disease: a mixed-methods implementation study.

Objective: Advanced kidney disease is associated with a high risk of morbidity and mortality. Consequently, invasive treatments such as dialysis may not yield survival benefits. Advance care planning has been encouraged.

Niacinamide May Be Associated with Improved Outcomes in COVID-19-Related Acute Kidney Injury: An Observational Study.

Background: AKI is a significant complication of coronavirus disease 2019 (COVID-19), with no effective therapy. Niacinamide, a vitamin B3 analogue, has some evidence of efficacy in non-COVID-19-related AKI. The objective of this study is to evaluate the association between niacinamide therapy and outcomes in patients with COVID-19-related AKI.