Postdilution hemodiafiltration (HDF) combines diffusive and convective transport to enhance solute removal across a broad molecular weight spectrum compared with conventional high-flux hemodialysis. This review summarizes current evidence on drug dosing in patients undergoing HDF, integrating pharmacokinetic principles, available clinical data, and practical considerations for individualized therapy. Drug removal during HDF depends on multiple factors, including molecular weight, protein binding, volume of distribution, membrane characteristics, and treatment-related parameters, such as blood flow, dialysate flow, and convection volume. While the effect of HDF on small solute clearance is generally modest compared with high-flux hemodialysis, convective transport substantially enhances the removal of middle molecules. Estimation of total drug removal provides a framework for postdialysis supplementation, but interpretation must account for postdialysis rebound, particularly for drugs with large volumes of distribution or multicompartment kinetics, where redistribution may attenuate net removal. In this context, reliance on intradialytic clearance alone may overestimate drug elimination. The combined diffusive and convective clearance achieved with HDF can alter drug exposure. Higher elimination should be anticipated for small, water-soluble medications, with dosing individualized using established pharmacokinetic principles and supported by therapeutic drug monitoring. Given the limited availability of HDF-specific pharmacokinetic data, dosing recommendations often rely on extrapolation from hemodialysis studies combined with mechanistic considerations. A structured approach that integrates drug properties, treatment parameters, and clinical context may support safer and more effective medication management in patients receiving HDF.

PURPOSE OF REVIEW:The science and practice of xenotransplantation is advancing more rapidly than the regulatory infrastructure that will be necessary to ensure the promise of alleviating the organ shortage can be safely and equitably met. RECENT FINDINGS:While countries leading the way have developed some regulatory guidance to support first in human "compassionate use" xenotransplant interventions and the first clinical trials, existing legislative, regulatory, and operational frameworks for human allotransplantation have not been explicitly extended to nonhuman animal organs. SUMMARY:To address safety concerns and other ethics challenges unique to xenotransplantation, existing policies must be amended and new policies must be implemented to protect patients and ensure equitable access to xenotransplantation.

In the United States, the organ procurement & transplantation network (OPTN) provides publicly reported data on incident kidney-transplant patients, including proportions of patients receiving a living-donor (LD) or deceased-donor (DD) kidney. However, complete, longitudinal information is not available for the prevalent transplant population. Since LD and DD kidney transplantations differ both in frequency and survival prospects, it is unclear how the prevalent LD/DD distribution differs from the incident population. Here, we reconstruct the 2020 prevalent donor-type distribution by biological sex, using extrapolations of historical data on incidence and post-transplantation survival. Using annual kidney-transplant survival data from the US Renal Data System for the years 1996–2020 [1, 2], we inferred long-term post-transplantation survival curves per donor type (LD and DD) and biological sex via data fits with exponential and Gompertz-type survival functions. Together with reported annual incidence data by donor type, this enables a reconstruction of the 2020 prevalent kidney-transplant population. Post-2020 datasets were excluded because COVID-19-related changes in survival trends prevent the required extrapolation of earlier data. Results were validated by comparing donor type-pooled results to reported total prevalent counts for 2020, showing a deviation of –3.3% (or a total of –8.1k out of 245.5k) (Fig. 1a). The inferred prevalent counts for 2020 were 63.5k female patients and 90.8k male patients with a deceased-donor (DD) kidney transplant and 32.7k female patients and 50.4k male patients with a living-donor (LD) kidney transplant (Fig. 1b). This corresponds to living/deceased-donor ratios of 34% : 66% among female patients (96.2k in total) and 36% : 64% among male patients (141.2k in total). Inferred donor-type proportions suggest a 1 : 2 ratio of living- and deceased-donor kidney transplant patients in the United States, largely independent of biological sex, whereas incident LD/DD ratios increased from 1 : 1.8 in 2010 to 1 : 3.5 in 2020 [2] (Fig. 1c). This reflects better graft and patient survival in LD recipients.

Introduction:For individuals with both end-stage heart failure and end-stage kidney disease or persistent acute kidney injury (AKI), simultaneous heart-kidney transplantation (SHKT) emerges as a viable treatment option, potentially yielding superior survival rates compared with heart transplantation (HT) alone. Nevertheless, accurately forecasting kidney recovery following HT in patients with moderate kidney failure poses challenges, thereby complicating the decision-making process for SHKT. Methods:This study employed a random forest (RF) machine learning algorithm, using 15 variables with the highest feature importance scores in the Organ Procurement and Transplantation Network (OPTN) data in which we analyzed a retrospective cohort of adult HT recipients from October 18, 2018 to December 31, 2020 in the US, with a follow-up for at least 1 year. The algorithm's goal was to predict a composite binary outcome with a calculated probability. An adverse outcome included the need for SHKT or adverse kidney outcomes within the first-year posttransplant (defined as end-stage kidney disease requiring chronic dialysis, glomerular filtration rate (GFR) ≤ 20 ml/min per 1.73 m2 or listing for retransplant). The model underwent both internal and external validation. Results:Of the 6579 patients in the study cohort, 13.4% received SHKT or experienced adverse kidney outcomes within a year following HT (n = 880). The RF model demonstrated a high specificity (0.941-0.955) and negative predictive value (0.940-0.955). However, it exhibited a moderate level of sensitivity (0.605-0.694) and positive predictive value (0.604-0.680). The concordance (c)-statistics ranged between 0.849 and 0.899, indicating effective class differentiation. Conclusion:This tool supplements, not replace, clinical judgment in addressing the complexities of SHKT decision-making at the time of waitlisting.

End-stage kidney disease (ESKD) patients receiving dialysis often experience a diminished health-related quality of life (QoL) [1], making the collection of patient-reported outcome measures (PROMs) essential for identifying key to enhance dialysis effectiveness and patients’ experiences. Our study aims to explore the association between haemodialysis (HD) treatment related factors and PROMs. In this cross-sectional study, we analysed electronic-PROM survey results, targeting 1,485 patients at Fresenius Medical Care (FMC) Singapore clinics from August to December 2024. The study was approved by the local Institutional Review Board. Patients enrolled for ≥90 days, provided consent, and completed the survey were included in the analysis. The survey comprised 3 questionnaires: Kidney Disease (KD) QoL-36 [2], Itch-5D, and intradialytic symptom questionnaire. We also analysed hospitalisation outcomes in this cohort. The KDQoL-36 includes 36 multiple-choice questions that assess five domains, generating scores (0 to 100), with higher scores indicating better QoL. Only patients who reported they were ‘very much bothered’ by itching on the KDQoL were asked to fill in the Itch-5D questionnaire (score: 5—mild impact to 22—severe impact) and only those patients who experienced symptoms during the previous dialysis were asked to rate the severity (1—not at all to 5—severe) of the 12 common intradialytic symptoms. Patients who received haemodiafiltration (HDF) for ≥75% of all treatments were classified as HDF group. We used linear and logistic regression models for numerical and binary outcomes, respectively and Poisson regression for hospitalisation. We analysed the results using R (version 4.1.1) and considered a two-sided p-value of <0.05 as significant. In total, 1,023 patients agreed to participate in the ePROM survey, yielding a response rate of 69%. Of the 681 patients who completed the survey and met the inclusion criteria, 122 used central venous catheter (CVC), 555 used arteriovenous fistulas (AVF) or grafts (AVG) (non-CVC), and VA was not reported for 4 patients. Three hundred and two patients (44%) were in the HDF group and 56% in the conventional HD group. The characteristics of patients by VA type and dialysis modality are presented in Tables 1 and 2, respectively. Ninety-seven patients (14%) reported experiencing intradialytic symptoms during the last dialysis session, with the most common being tiredness (13%) and muscle cramping (10%). The CVC group had significantly higher odds of experiencing intradialytic symptoms, including dizziness [OR: 2.10, (95% C.I.: 1.06, 4.03)], tiredness [OR: 1.97, (95% C.I.: 1.14, 3.40)], and shivering [OR: 2.50, (95% C.I.: 1.29, 4.76)] compared to the non-CVC group (Table 3). Furthermore, CVC group reported more severe vomiting, dizziness, tiredness, and shivering (P < 0.05) albeit with small effect size. Tiredness and shivering are common symptoms of catheter infection, and we observed that CVC use was associated with higher risk of infection-related hospitalisation [Incidence rate ratio: 3.16 (95% C.I.: 1.46, 6.70)] in our cohort. The HDF group was significantly associated with lower occurrence of muscle cramps [OR: 0.57, (95% C.I.: 0.32, 0.98)], headache [OR: 0.51, (95% C.I.: 0.25, 0.98)], and tummy pain [OR: 0.31, (95% C.I.: 0.09, 0.87)] (Table 3). Headache was also reported to be less severe in the HDF group (P < 0.05) albeit with a small effect size. We observed no significant relationships between CVC use and HDF and the five KDQoL domain scores, Itch-5D score, or recovery time. Our results demonstrate that the use of AVF or AVG as VA and HDF modality are associated with fewer and less severe patient-reported intradialytic symptoms in our stable prevalent HD cohort.

There is evidence-based recommendation for the use of SGLT-2 inhibitors, GLP-1 receptor agonists to improve cardio-kidney outcomes in chronic kidney disease (CKD) patients. Although these recommendations are not extended to patients with kidney failure, it is plausible that many patients continue using these medications after the initiation of dialysis. The utilization and potential impact of the use in these patients on hemodialysis is unknown. This analysis aims to describe the utilization and the demographic and clinical characteristics of users in a large cohort of USA hemodialysis patients. This retrospective analysis included data from adult patients (≥18 years) undergoing hemodialysis between 2018 and 2020 at a large dialysis organization in U.S. Patient demographics, clinical parameters, and medication use were analyzed for the overall cohort (n = 380,541) and subgroups prescribed SGLT2 inhibitors (N=19,512, 5.13%) and GLP-1 agonists (n = 6,080, 1.60%). Descriptive statistics summarized key metrics, including age, race, HbA1c levels, and prevalence of comorbidities. (Table 1) The mean HbA1c and albumin values were calculated from available patient data spanning the years 2018–2020. The overall cohort had a mean age of 62.9 years, with 57.6% males and 54% White. Significant demographic and clinical differences were observed across the medication subgroups. Diabetes prevalence was highest among patients prescribed SGLT2 inhibitors (95%) and GLP-1 agonists (96%). Welch's ANOVA identified a significant age difference between patients prescribed SGLT2 inhibitors and GLP-1 agonists (P < 0.001). SGLT2 inhibitor users were older, with a mean age of 65.9 years (SD = 11.9), compared to GLP-1 agonist users, who had a mean age of 61.4 years (SD = 11.4). The proportion of White individuals was notably higher among GLP-1 agonist users (59%) compared to other groups, including SGLT2 inhibitors (54%). HbA1c levels were highest among GLP-1 agonist users, averaging 7.17%. Additionally, this group had the highest prevalence of obesity (BMI ≥ 30 kg/m²), affecting 60% of users. The prevalence of cardiovascular disease (CVD) varied slightly, 47% among those prescribed SGLT2 inhibitors or GLP-1 agonists. Albumin levels were similar across groups (mean = 3.65 g/dL), and COPD prevalence was consistent at 10%–11%. This analysis highlights key differences in the characteristics of dialysis patients prescribed different glucose-lowering medications with documented cardio-kidney benefits in CKD but not currently recommended for clinical use in dialysis patients. These findings provide critical insights into medication selection and tailoring treatment strategies for dialysis patients. Further studies are needed to evaluate the clinical outcomes associated with these prescribing patterns in dialysis patients.

BACKGROUND:The 2018 revision of the adult Heart Allocation Policy (aHAP) led to a notable increase in the rate of simultaneous heart-kidney transplants (SHKT) in the United States. However, this policy has faced criticism for its inability to enhance post-transplant survival rates or decrease mortality among SHKT recipients on the waitlist, although high-quality kidneys are used. METHODS:We analyzed data from the Organ Procurement and Transplantation Network, covering 1549 SHKT cases from 2015 to 2021. The study assessed 1-y post-transplant outcomes, including all-cause heart and kidney graft failures and adverse kidney outcomes such as end-stage kidney disease, significantly reduced kidney function or the need for retransplantation. Using a propensity score-matching approach, we compared 2 cohorts: patients treated before and after the policy implementation in October 2018. RESULTS:The multivariable Cox proportional hazard models indicated a significant increase in mortality (hazard ratio [HR] 1.62; 95% confidence interval [CI], 1.10-2.37) and all-cause graft failures for both heart (HR 1.59; 95% CI, 1.08-2.33) and kidney (HR 1.39; 95% CI, 1.03-1.85) during the period after the new aHAP implementation. One year post-transplant, the incidence of adverse kidney outcomes was 6.8% under the new aHAP compared with 5.3% in the previous period among survivors ( P = 0.33). CONCLUSIONS:The suboptimal outcomes of SHKT under the new aHAP, alongside its potential impacts on kidney-alone transplant candidates, suggest a need for regular monitoring of SHKT policies. This is crucial to ensure that the intentions of the Final Rule regarding equity and utility are effectively met.

Shorter dialysis treatment time has been shown to increase mortality in hemodialysis (HD) patients [1]. Treatment time is a modifiable factor of the dialysis prescription and extending it may be more under the purview of the care team than factors such as interdialytic weight gain. This study investigates the impact of mean delivered treatment time on mortality risk in a large cohort of in-center HD patients. A retrospective cohort analysis was performed on adult, chronic in-center HD patients dialyzing at Fresenius Kidney Care (FKC) clinics any time from 1/1/2022 to 7/1/2023. The date of first dialysis treatment from 1/1/2022 to 7/1/2023 was defined as the start of a 30-day period during which baseline characteristics were assessed. Mean delivered treatment time was calculated for each patient during a 30-day exposure period following the baseline period. After the exposure period, patients were followed until death, censoring (received transplant, left FKC, or changed dialysis modality) or end of 1 year. A Cox proportional hazards model adjusted for age, sex, race, BMI, and access type was used to estimate hazards ratios for each treatment group. 152,921 patients were included in the analysis. Patients were stratified into 7 treatment time groups at 15-minute intervals based on their mean delivered treatment time (hours). The most frequently delivered treatment time was 3:45–3:59 hours (23.2%), followed by 3:30–3:44 hours (21.6%) and 4:00–4:14 hours (19.9%). When compared to patients with a mean delivered treatment time between 3:00-3:14 hours, patients in the 4:00–4:14 group experienced a 19% (HR 0.81 [0.77–0.86], P < 0.0001) reduction in mortality. Patients in the 3:30–3:44 and 3:45–3:59 groups also experienced a reduction of 10% (HR 0.90 [0.86–0.95], P < 0.0001) and 8% (HR 0.92 [0.87–0.97], P < 0.0001) respectively, while there was no difference in mortality in the 3:15–3:29 or 4:15+ hour groups. There was an increase in mortality in the <3:00 hour group. Patients with delivered treatment times between 3:30 and 4:14 hours experienced a significant reduction in mortality when compared to patients with delivered treatment times 3:00 and 3:14 hours. This effect was most pronounced among patients with an average delivered treatment time between 4:00 and 4:14 hours. Additional information is needed to assess the impact of treatment time and mortality for patients in the <3:00 and 4:15+ groups, as these treatment times are not typically prescribed.

Delayed graft function (DGF) is a common complication after kidney transplant. Despite extensive literature on the topic, the extant definition of DGF has not been conducive to advancing the scientific understanding of the influences and mechanisms contributing to its onset, duration, resolution, or long-term prognostic implications. In 2022, the National Kidney Foundation sponsored a multidisciplinary scientific workshop to comprehensively review the current state of knowledge about the diagnosis, therapy, and management of DGF and conducted a survey of relevant stakeholders on topics of clinical and regulatory interest. In this Special Report, we propose and defend a novel taxonomy for the clinical and research definitions of DGF, address key regulatory and clinical practice issues surrounding DGF, review the current state of therapies to reduce and/or attenuate DGF, offer considerations for clinical practice related to the outpatient management of DGF, and outline a prospective research and policy agenda.

Abstract Background and Aims Kidney transplant failure contributes to a considerable proportion of new dialysis starters. In some centres there are dedicated clinics for patients with failing kidney transplants, however, the specific needs of patients with dialysis after graft loss (DAGL) may be lost in the non-specific clinical review practiced in the general dialysis community. This study examines the mortality and morbidity risk in patients returning with DAGL and compares it to transplant-naïve (T-N) dialysis starters, to determine if the former warrant a more specialised approach. Method This is a retrospective observational study of mortality in all adult patients who started dialysis treatments in Fresenius Medical Care (North America, Latin America, Europe, Middle East, Africa, and Asia Pacific) from 1st January 2018 to 31st March 2021, were identified in the Apollo Dial DB dataset. DAGL was identified from the ICD-10 codes ‘Kidney transplant failure’, ‘Unspecified complication of kidney transplant’ and ‘Other complication of kidney transplant’ at dialysis start. The T-N control group had not previously received a kidney transplant and had not received immunosuppressive medication during the first six months of dialysis start. The first six months on dialysis were defined as baseline, months 7 to the end of year 5 were defined as the follow-up period. All-cause mortality was recorded during follow-up. Cox proportional hazards models were applied to explore the association between DAGL and all-cause mortality. Results A total of 360 469 dialysis starter patients from 41 countries were included in the analysis. 10 010 patients had DAGL and were compared with 350 459 in the T-N control group. In univariate analysis, DAGL patients were significantly younger in all age categories and had a higher proportion of male sex. Serum creatinine, ferritin, phosphate and neutrophil-to-lymphocyte ratio were higher in the DAGL group. Haemoglobin was lower in the DAGL group (Table 1). In the Cox proportional model adjusted for age, gender, and other laboratory and clinical markers, patients with DAGL had an equivalent survival probability compared with T-N dialysis starters (HR: 0.93, 95% CI: 0.86, 1.02) (Table 2). Conclusion DAGL patients appeared to have an increased mortality compared to T-N dialysis starters historically in the literature. Our large and recent study is in line with other recent publications suggesting a more equivalent survival in the two groups. Our results are compatible with younger patients receiving kidney transplantation early in their renal replacement therapy journey, thus constituting a significant proportion of DAGL patients. We posit that DAGL patients may start dialysis at a lower level of renal function, with higher levels of inflammation. Our analysis is preliminary and limited, not fully accounting for confounding factors. Future analysis of this large and well recorded dataset will allow us to examine these interesting associations and design a more specialised management approach to DAGL more closely.

In the preface to his magisterial Elements of the Philosophy of Right, the 19th century German philosopher G.W.F. Hegel famously quipped, “…the owl of Minerva begins its flight only with the onset of dusk.”1Hegel G.W.F. Elements of the Philosophy of Right. Cambridge University Press, 1991Crossref Google Scholar Hegel meant that philosophical clarity on a historical period is only truly available at its end. For those hoping that philosophy will “…issue instructions on how the world ought to be,” Hegel demurs that philosophy “…always comes too late.” Although the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has largely receded to endemic status, the transplant community is still grappling with the implications of its effects on policy. Reviewingthe normative debates and discussions of coronavirus 2019 (COVID-19) vaccine mandates for transplant candidates from only a year ago should evoke a (Hegelian) sense of humility when reflecting on transplant policy in late 2023 and beyond. In this issue, Edwards et al2Edwards A.L. Tavakol M.M. Mello A. Kerney J. Roberts J P. Pretransplantation coronavirus disease 2019 vaccination requirements: A matched case-control study of factors associated with waitlist inactivation.Am J Transplant. 2024; 24: 134-140https://doi.org/10.1016/j.ajt.2023.09.009Abstract Full Text Full Text PDF Google Scholar reported a first-of-its-kind study of demographic trends in patients waitlisted for a kidney transplant at a large center in California who were required to demonstrate evidence of COVID-19 vaccination on the penalty of transition to waitlist inactive status. After reviewing patients between September 2022 and January 2023, with a 2-month “run-in” period for a vaccine mandate that began in July 2022, 20% of the center’s waiting list was rendered inactive 2 months after the mandate, and only 15% of the inactivated patients became waitlist active again through vaccination by May 2023, leaving 17% of the total waitlist population inactive due to vaccine mandate nonadherence. In multivariate analysis, waistlist inactivation was associated with public insurance (Medicare or Medicaid) and residing in zip codes most afflicted by social influencers of health. Of particular interest, race/ethnicity and education level did not correlate with the risk of waitlist inactivation, though Asian patients were less likely than all other groups to be inactivated due to nonvaccination. Edwards et al2Edwards A.L. Tavakol M.M. Mello A. Kerney J. Roberts J P. Pretransplantation coronavirus disease 2019 vaccination requirements: A matched case-control study of factors associated with waitlist inactivation.Am J Transplant. 2024; 24: 134-140https://doi.org/10.1016/j.ajt.2023.09.009Abstract Full Text Full Text PDF Google Scholar did not solicit the reasons why waitlisted patients did not get vaccinated, making it difficult to discern whether the absence of vaccination was a consequence of active decision-making or (perceived or actual) reduced access to the vaccine due to relative social privation. Either scenario might be associated with public insurance status, but each raises a different set of questions: How are disparities in vaccination rates distributed across the categories of patient active choice (active vaccine refusal), patient passive choice (perceived difficulties in securing vaccine access), or verified access barriers to COVID-19 vaccination? The answer(s) would suggest different public health interventions targeted at specific root causes, but there is insufficient data in this study to discern which factors are more prevalent. The time frame of this study bears mention. The vaccine mandate at this center was implemented in July 2022, when 67% of the US population had completed an initial set of vaccinations, 78% had received at least one vaccine dose, and the 7-day rolling average of case fatality rates from SARS-CoV-2 infection had stabilized to 0.9 to 1.3 deaths per million population (pmp), from a peak of 8.03 deaths pmp in February 2022. New incident cases in late July 2022 were around 400 cases pmp (from an overall peak of 2393 pmp in January 2022) and declined by more than 50%, to less than 200 cases pmp, from September 2022 to January 2023.3Mathieu E., Ritchie R., Rodés-Guirao L., et al. Coronavirus pandemic (COVID-19) OurWorldInData.org. Accessed October 25, 2023. https://ourworldindata.org/coronavirus.Google Scholar Although the fading of “natural” immunity after primary infection and the benefits of vaccination postinfection are well established, arguably the combination of population herd and vaccine-mediated immunity by mid-2022 resulted in patient risk that was qualitatively lower than even 6 or 12 months earlier. Unvaccinated transplant recipients on immunosuppression are at a higher relative risk of complications compared with the immunocompetent. But, when the absolute risk of infection is substantially lower for all populations through herd- and vaccine-mediated immunity, the benefits of a vaccine mandate policy, set against disproportionately reduced access to organs offers for patients with public insurance who live in the least well-off communities, are less obvious. Ostensibly, there is some “number needed to treat,” which is too large to justify a proscriptive policy that worsens entrenched health inequalities. Ethical constructs can offer useful heuristics to consider these challenges,4Kates O.S. Limaye A.P. Kaplan B. Vaccination, transplantation, and a social contract.J Am Soc Nephrol. 2022; 33: 1445-1447https://doi.org/10.1681/ASN.2021111501Crossref PubMed Scopus (2) Google Scholar but these arguments are unlikely to resolve deep normative disagreements between entrenched parties about the defensibility and prudence of vaccine mandate policies when untethered to declining trends in absolute and relative risks of SARS-CoV-2 infection and complications (and maybe not even then).5Hippen B.E. Mandating COVID-19 vaccination prior to kidney transplantation in the United States: no solutions, only decisions.Am J Transplant. 2022; 22: 381-385https://doi.org/10.1111/ajt.16891Abstract Full Text Full Text PDF PubMed Scopus (15) Google Scholar Edwards et al2Edwards A.L. Tavakol M.M. Mello A. Kerney J. Roberts J P. Pretransplantation coronavirus disease 2019 vaccination requirements: A matched case-control study of factors associated with waitlist inactivation.Am J Transplant. 2024; 24: 134-140https://doi.org/10.1016/j.ajt.2023.09.009Abstract Full Text Full Text PDF Google Scholar provide crucial data on the unintended consequences of a broad vaccine mandate. The association of health disparities with a mandate policy is not a dispositive argument against mandates but underscores the recursive need for reconsidering the justifications for a mandate. Whether our historically contingent judgments in this matter will be vindicated will have to wait until the pandemic’s “onset of dusk.” The author of this manuscript has conflicts of interest to disclose, as described by the American Journal of Transplantation. B.E. Hippen reported serving as a paid full-time employee for Fresenius Medical Care. B.E. Hippen also owns equity in InterWell Health. Pretransplantation coronavirus disease 2019 vaccination requirements: A matched case-control study of factors associated with waitlist inactivationAmerican Journal of TransplantationVol. 24Issue 1PreviewNumerous United States transplant centers require solid organ transplantation candidates to be vaccinated against the coronavirus disease of 2019 to be active on the United Network for Organ Sharing waiting list. This study examined characteristics of adult patients on one center's kidney transplantation waiting list whose status was inactivated due to a lack of coronavirus disease 2019 vaccination by July 1, 2022, and who did not subsequently provide proof of vaccination by August 31, 2022 (cases). Full-Text PDF

In the United States, kidney care payment models are migrating toward value-based care (VBC) models incentivizing quality of care at lower cost. Current kidney VBC models will continue through 2026. We propose a future transplant-inclusive VBC (TIVBC) model designed to supplement current models focusing on patients with advanced chronic kidney disease (CKD) and end-stage kidney disease (ESKD). The proposed TIVBC is structured as an episode-of-care model with risk-based reimbursement for “referral/evaluation/waitlisting” (REW, referencing kidney transplantation), “primary hospitalization to 180 days posttransplant,” and “long-term graft survival.” Challenges around organ acquisition costs, adjustments to quality metrics, and potential criticisms of the proposed model are discussed. We propose next steps in risk-adjustment and cost-prediction to develop as an end-to-end, TIVBC model.

Significant center‐to‐center variation in attitudes and management of delayed graft function (DGF) remains common.