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Background: Results from the CONVINCE clinical trial suggest a 23% mortality risk reduction among patients receiving high-volume (> 23 L) hemodiafiltration. We assessed the real-world effectiveness of blood-based kidney replacement therapy (KRT) with hemodiafiltration vs. hemodialysis in a large, unselected patient population treated prior to and during the COVID-19 pandemic., Methods: In this retrospective cohort study, we analyzed pseudonymized data from 85,117 adults receiving in-center care across NephroCare clinics in Europe, the Middle East, and Africa during 2019-2022. Cox regression models with KRT modality and coronavirus disease 2019 (COVID-19) status as time-varying covariates, and adjusted for multiple confounders, were used to estimate all-cause (primary) and cardiovascular (secondary) mortality. Subgroup analyses were performed for age, dialysis vintage, COVID-19 status, diabetes, and cardiovascular disease., Results: At baseline, 55% of patients were receiving hemodialysis and 45% of patients were receiving hemodiafiltration. Baseline characteristics were similar between baseline modalities, except that hemodiafiltration patients were a median of 2 years younger, had higher percentage of fistula access (66% vs. 47%), and had longer mean dialysis vintages (4.4 years vs. 2.6 years). Compared with hemodialysis, hemodiafiltration was associated with an adjusted hazard ratio (HR) for all-cause mortality of 0.78 (95% confidence interval [Cl], 0.76-0.80), irrespective of COVID-19 infection. The pattern of a beneficial effect of hemodiafiltration was consistently observed among all analyzed subgroups. Among patients receiving high-volume hemodiafiltration (mean convection volume ≥ 23 L), the risk of death was reduced by 30% (HR, 0.70 [95% CI, 0.68-0.72]). Hemodiafiltration was also associated with a 31% reduced risk of cardiovascular death., Conclusions: Our results suggest that hemodiafiltration has a beneficial effect on all-cause and cardiovascular mortality in a large, unselected patient population and across patient subgroups in real-world settings. Our study complements evidence from the CONVINCE trial and adds to the growing body of real-world evidence on hemodiafiltration., Competing Interests: Declarations. Ethics approval and consent to participate: The study was reviewed and approved by the Ethics Committee of the Landesärztekammer Hessen (Medical Association of Hesse) in Frankfurt, Germany. All patients provided written informed consent for the secondary use of their data for scientific research purposes. In addition, pseudonymized data was extracted from the European Clinical Database (EuCliD®) database. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Fluid overload remains critical in managing patients with end-stage kidney disease. However, there is limited empirical understanding of fluid overload's impact on mortality. This study analyzes fluid overload trajectories and their association with mortality in hemodialysis patients., Methods and Patients: This longitudinal study included 9332 incident hemodialysis patients from the EuCliD database, treated in Fresenius Medical Care NephroCare dialysis centers across seven countries between January 2016 and December 2019, with follow-up until May 2023. Fluid overload was assessed using bioimpedance spectroscopy, and patients were grouped based on fluid overload trajectories using group-based trajectory modeling. Cox regression models, adjusted for potential confounders, were used to investigate the relationship between trajectory groups and mortality., Results: Four distinct fluid overload trajectories were identified. Patients in the highest trajectory group (8.5% of the cohort) had more frequent background cardiovascular complications, lower BMI and serum albumin, and their adjusted mortality risk was 2.20 times higher than the lowest trajectory. There was a dose-response relationship between trajectories and mortality. The incidence rate of death increased with the degree of fluid overload, from 8.6 deaths per 100 person-years in the lowest trajectory to 18.6 in the highest., Conclusions: This longitudinal study highlights the significant risk of chronic fluid overload in hemodialysis patients. Latent trajectory analysis provides novel information into the dynamic nature of fluid overload and its impact on mortality in the hemodialysis population., (© 2024 The Association for the Publication of the Journal of Internal Medicine.)

Background: Gastrointestinal bleeding (GIB) is a clinical challenge in kidney failure. INSPIRE group assessed if machine learning could determine a hemodialysis (HD) patient's 180-day GIB hospitalization risk., Methods: An eXtreme Gradient Boosting (XGBoost) and logistic regression model were developed using an HD dataset in United States (2017-2020). Patient data was randomly split (50% training, 30% validation, and 20% testing). HD treatments ≤ 180 days before GIB hospitalization were classified as positive observations; others were negative. Models considered 1,303 exposures/covariates. Performance was measured using unseen testing data., Results: Incidence of 180-day GIB hospitalization was 1.18% in HD population (n = 451,579), and 1.12% in testing dataset (n = 38,853). XGBoost showed area under the receiver operating curve (AUROC) = 0.74 (95% confidence interval (CI) 0.72, 0.76) versus logistic regression showed AUROC = 0.68 (95% CI 0.66, 0.71). Sensitivity and specificity were 65.3% (60.9, 69.7) and 68.0% (67.6, 68.5) for XGBoost versus 68.9% (64.7, 73.0) and 57.0% (56.5, 57.5) for logistic regression, respectively. Associations in exposures were consistent for many factors. Both models showed GIB hospitalization risk was associated with older age, disturbances in anemia/iron indices, recent all-cause hospitalizations, and bone mineral metabolism markers. XGBoost showed high importance on outcome prediction for serum 25 hydroxy (25OH) vitamin D levels, while logistic regression showed high importance for parathyroid hormone (PTH) levels., Conclusions: Machine learning can be considered for early detection of GIB event risk in HD. XGBoost outperforms logistic regression, yet both appear suitable. External and prospective validation of these models is needed. Association between bone mineral metabolism markers and GIB events was unexpected and warrants investigation., Trial Registration: This retrospective analysis of real-world data was not a prospective clinical trial and registration is not applicable., (© 2024. The Author(s).)

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., (© 2024 International Society of Nephrology. Published by Elsevier Inc.)

Introduction: The rapid advancement of artificial intelligence and big data analytics, including descriptive, diagnostic, predictive, and prescriptive analytics, has the potential to revolutionize many areas of medicine, including nephrology and dialysis. Artificial intelligence and big data analytics can be used to analyze large amounts of patient medical records, including laboratory results and imaging studies, to improve the accuracy of diagnosis, enhance early detection, identify patterns and trends, and personalize treatment plans for patients with kidney disease. Additionally, artificial intelligence and big data analytics can be used to identify patients' treatment who are not receiving adequate care, highlighting care inefficiencies in the dialysis provider, optimizing patient outcomes, reducing healthcare costs, and consequently creating values for all the involved stakeholders., Objectives: We present the results of a comprehensive survey aimed at exploring the attitudes of European physicians from eight countries working within a major hemodialysis network (Fresenius Medical Care NephroCare) toward the application of artificial intelligence in clinical practice., Methods: An electronic survey on the implementation of artificial intelligence in hemodialysis clinics was distributed to 1,067 physicians. Of the 1,067 individuals invited to participate in the study, 404 (37.9%) professionals agreed to participate in the survey., Results: The survey showed that a substantial proportion of respondents believe that artificial intelligence has the potential to support physicians in reducing medical malpractice or mistakes., Conclusion: While artificial intelligence's potential benefits are recognized in reducing medical errors and improving decision-making, concerns about treatment plan consistency, personalization, privacy, and the human aspects of patient care persist. Addressing these concerns will be crucial for successfully integrating artificial intelligence solutions in nephrology practice., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

Introduction: More frequent and/or longer hemodialysis (HD) has been associated with improvements in numerous clinical outcomes in patients on dialysis. Home HD (HHD), which allows more frequent and/or longer dialysis with lower cost and flexibility in treatment planning, is not widely used worldwide. Although, retrospective studies have indicated better survival with HHD, this issue remains controversial. In this multicenter study, we compared thrice-weekly extended HHD with in-center conventional HD (ICHD) in a large patient population with a long-term follow-up., Methods: We matched 349 patients starting HHD between 2010 and 2014 with 1047 concurrent patients on ICHD by using propensity scores. Patients were followed-up with from their respective baseline until September 30, 2018. The primary outcome was overall survival. Secondary outcomes were technique survival; hospitalization; and changes in clinical, laboratory, and medication parameters., Results: The mean duration of dialysis session was 418 ± 54 minutes in HHD and 242 ± 10 minutes in patients on ICHD. All-cause mortality rate was 3.76 and 6.27 per 100 patient-years in the HHD and the ICHD groups, respectively. In the intention-to-treat analysis, HHD was associated with a 40% lower risk for all-cause mortality than ICHD (hazard ratio [HR] = 0.60; 95% confidence interval [CI] 0.45 to 0.80; P  < 0.001). In HHD, the 5-year technical survival was 86.5%. HHD treatment provided better phosphate and blood pressure (BP) control, improvements in nutrition and inflammation, and reduction in hospitalization days and medication requirement., Conclusion: These results indicate that extended HHD is associated with higher survival and better outcomes compared to ICHD., (© 2023 International Society of Nephrology. Published by Elsevier Inc.)

Background: Nonadherence to hemodialysis appointments could potentially result in health complications that can influence morbidity and mortality. We examined the association between different types of inclement weather and hemodialysis appointment adherence., Methods: We analyzed health records of 60,135 patients with kidney failure who received in-center hemodialysis treatment at Fresenius Kidney Care clinics across the Northeastern US counties during 2001-2019. County-level daily meteorological data on rainfall, hurricane and tropical storm events, snowfall, snow depth, and wind speed were extracted using National Oceanic and Atmosphere Agency data sources. A time-stratified case-crossover study design with conditional Poisson regression was used to estimate the effect of inclement weather exposures within the Northeastern US region. We applied a distributed lag nonlinear model framework to evaluate the delayed effect of inclement weather for up to 1 week., Results: We observed positive associations between inclement weather and missed appointment (rainfall, hurricane and tropical storm, snowfall, snow depth, and wind advisory) when compared with noninclement weather days. The risk of missed appointments was most pronounced during the day of inclement weather (lag 0) for rainfall (incidence rate ratio [RR], 1.03 per 10-mm rainfall; 95% confidence interval [CI], 1.02 to 1.03) and snowfall (RR, 1.02; 95% CI, 1.01 to 1.02). Over 7 days (lag 0-6), hurricane and tropical storm exposures were associated with a 55% higher risk of missed appointments (RR, 1.55; 95% CI, 1.22 to 1.98). Similarly, 7-day cumulative exposure to sustained wind advisories was associated with 29% higher risk (RR, 1.29; 95% CI, 1.25 to 1.31), while wind gusts advisories showed a 34% higher risk (RR, 1.34; 95% CI, 1.29 to 1.39) of missed appointment., Conclusions: Inclement weather was associated with higher risk of missed hemodialysis appointments within the Northeastern United States. Furthermore, the association between inclement weather and missed hemodialysis appointments persisted for several days, depending on the inclement weather type., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Nephrology.)

Background: In maintenance hemodialysis patients, intradialytic hypotension (IDH) is a frequent complication that has been associated with poor clinical outcomes. Prediction of IDH may facilitate timely interventions and eventually reduce IDH rates., Methods: We developed a machine learning model to predict IDH in in-center hemodialysis patients 15-75 min in advance. IDH was defined as systolic blood pressure (SBP) <90 mmHg. Demographic, clinical, treatment-related and laboratory data were retrieved from electronic health records and merged with intradialytic machine data that were sent in real-time to the cloud. For model development, dialysis sessions were randomly split into training (80%) and testing (20%) sets. The area under the receiver operating characteristic curve (AUROC) was used as a measure of the model's predictive performance., Results: We utilized data from 693 patients who contributed 42 656 hemodialysis sessions and 355 693 intradialytic SBP measurements. IDH occurred in 16.2% of hemodialysis treatments. Our model predicted IDH 15-75 min in advance with an AUROC of 0.89. Top IDH predictors were the most recent intradialytic SBP and IDH rate, as well as mean nadir SBP of the previous 10 dialysis sessions., Conclusions: Real-time prediction of IDH during an ongoing hemodialysis session is feasible and has a clinically actionable predictive performance. If and to what degree this predictive information facilitates the timely deployment of preventive interventions and translates into lower IDH rates and improved patient outcomes warrants prospective studies., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Introduction: Inadequate predialysis care and education impacts the selection of a dialysis modality and is associated with adverse clinical outcomes. Transitional care units (TCUs) aim to meet the unmet educational needs of incident dialysis patients, but their impact beyond increasing home dialysis utilization has been incompletely characterized., Methods: This retrospective study included adults initiating in-center hemodialysis at a TCU, matched to controls (1:4) with no TCU history initiating in-center hemodialysis. Patients were followed for up to 14 months. TCUs are dedicated spaces where staff provide personalized education and as-needed adjustments to dialysis prescriptions. For many patients, therapy was initiated with four to five weekly dialysis sessions, with at least some sessions delivered by home dialysis machines. Outcomes included survival, first hospitalization, transplant waiting-list status, post-TCU dialysis modality, and vascular access type., Findings: The study included 724 patients initiating dialysis across 48 TCUs, with 2892 well-matched controls. At the end of 14 months, patients initiating dialysis in a TCU were significantly more likely to be referred and/or wait-listed for a kidney transplant than controls (57% vs. 42%; p < 0.0001). Initiation of dialysis at a TCU was also associated with significantly lower rates of receiving in-center hemodialysis at 14 months (74% vs. 90%; p < 0.0001) and higher rates of arteriovenous access (70% vs. 63%; p = 0.003). Although not statistically significant, TCU patients were more likely to survive and less likely to be hospitalized during follow-up than controls., Discussion: Although TCUs are sometimes viewed as only a means for enhancing utilization of home dialysis, patients attending TCUs exhibited more favorable outcomes across all endpoints. In addition to being 2.5-fold more likely to receive home dialysis, TCU patients were 42% more likely to be referred for transplantation. Our results support expanding utilization of TCUs for patients with inadequate predialysis support., (© 2023 International Society for Hemodialysis.)

In January 2021, there were 9648 patients in Ukraine on kidney replacement therapy, including 8717 on extracorporeal therapies and 931 on peritoneal dialysis. On 24 February 2022, foreign troops entered the territory of Ukraine. Before the war, the Fresenius Medical Care dialysis network in Ukraine operated three medical centres. These medical centres provided haemodialysis therapy to 349 end-stage kidney disease patients. In addition, Fresenius Medical Care Ukraine delivered medical supplies to almost all regions of Ukraine. Even though Fresenius Medical Care's share of end-stage kidney disease patients on dialysis is small, a brief narrative account of the managerial challenges that Fresenius Medical Care Ukraine and the clinical directors of the Fresenius Medical Care centres had to face, as well as the suffering of the dialysis population, is a useful testimony of the burden imposed by war on these frail, high-risk patients dependent on a complex technology such as dialysis. The war in Ukraine is causing immense suffering for the dialysis population of this country and has called for heroic efforts from dialysis personnel. The experience of a small dialysis network treating a minority of dialysis patients in Ukraine is described. Guaranteeing dialysis treatment has been and remains an enormous challenge in Ukraine and we are confident that the generosity and the courage of Ukrainian dialysis staff and international aid will help to mitigate this tragic suffering., Competing Interests: All authors are Fresenius Medical Care employees. The results presented in this paper have not been published previously in whole or part., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Background: We developed machine learning models to understand the predictors of shorter-, intermediate-, and longer-term mortality among hemodialysis (HD) patients affected by COVID-19 in four countries in the Americas., Methods: We used data from adult HD patients treated at regional institutions of a global provider in Latin America (LatAm) and North America who contracted COVID-19 in 2020 before SARS-CoV-2 vaccines were available. Using 93 commonly captured variables, we developed machine learning models that predicted the likelihood of death overall, as well as during 0-14, 15-30, > 30 days after COVID-19 presentation and identified the importance of predictors. XGBoost models were built in parallel using the same programming with a 60%:20%:20% random split for training, validation, & testing data for the datasets from LatAm (Argentina, Columbia, Ecuador) and North America (United States) countries., Results: Among HD patients with COVID-19, 28.8% (1,001/3,473) died in LatAm and 20.5% (4,426/21,624) died in North America. Mortality occurred earlier in LatAm versus North America; 15.0% and 7.3% of patients died within 0-14 days, 7.9% and 4.6% of patients died within 15-30 days, and 5.9% and 8.6% of patients died > 30 days after COVID-19 presentation, respectively. Area under curve ranged from 0.73 to 0.83 across prediction models in both regions. Top predictors of death after COVID-19 consistently included older age, longer vintage, markers of poor nutrition and more inflammation in both regions at all timepoints. Unique patient attributes (higher BMI, male sex) were top predictors of mortality during 0-14 and 15-30 days after COVID-19, yet not mortality > 30 days after presentation., Conclusions: Findings showed distinct profiles of mortality in COVID-19 in LatAm and North America throughout 2020. Mortality rate was higher within 0-14 and 15-30 days after COVID-19 in LatAm, while mortality rate was higher in North America > 30 days after presentation. Nonetheless, a remarkable proportion of HD patients died > 30 days after COVID-19 presentation in both regions. We were able to develop a series of suitable prognostic prediction models and establish the top predictors of death in COVID-19 during shorter-, intermediate-, and longer-term follow up periods., (© 2022. The Author(s).)

Background: We tested if fatigue in incident Peritoneal Dialysis associated with an increased risk for mortality, independently from main confounders., Methods: We conducted a side-by-side study from two of incident PD patients in Brazil and the United States. We used the same code to independently analyze data in both countries during 2004 to 2011. We included data from adults who completed KDQOL-SF vitality subscale within 90 days after starting PD. Vitality score was categorized in four groups: >50 (high vitality), ≥40 to ≤50 (moderate vitality), >35 to <40 (moderate fatigue), ≤35 (high fatigue; reference group). In each country's cohort, we built four distinct models to estimate the associations between vitality (exposure) and all-cause mortality (outcome): (i) Cox regression model; (ii) competing risk model accounting for technique failure events; (iii) multilevel survival model of clinic-level clusters; (iv) multivariate regression model with smoothing splines treating vitality as a continuous measure. Analyses were adjusted for age, comorbidities, PD modality, hemoglobin, and albumin. A mixed-effects meta-analysis was used to pool hazard ratios (HRs) from both cohorts to model mortality risk for each 10-unit increase in vitality., Results: We used data from 4,285 PD patients (Brazil n = 1,388 and United States n = 2,897). Model estimates showed lower vitality levels within 90 days of starting PD were associated with a higher risk of mortality, which was consistent in Brazil and the United States cohorts. In the multivariate survival model, each 10-unit increase in vitality score was associated with lower risk of all-cause mortality in both cohorts (Brazil HR = 0.79 [95%CI 0.70 to 0.90] and United States HR = 0.90 [95%CI 0.88 to 0.93], pooled HR = 0.86 [95%CI 0.75 to 0.98]). Results for all models provided consistent effect estimates., Conclusions: Among patients in Brazil and the United States, lower vitality score in the initial months of PD was independently associated with all-cause mortality., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: MG, LW, CRG, VMR, CM are students at Pontifícia Universidade Católica do Paraná. CRG is a student at Johns Hopkins Bloomberg School of Public Health. VMR, CM, YJ, JWL, LAU, FWM are employees of Fresenius Medical Care. PK is an employee of Renal Research Institute, a wholly owned subsidiary of Fresenius Medical Care. LAU, PK, FWM have share options/ownership in Fresenius Medical Care. JWL, LAU, PK, FWM are an inventor on patent(s) in the field of dialysis. PK receives honorarium from Up-To-Date and is on the Editorial Board of Blood Purification and Kidney and Blood Pressure Research. FWM has directorships in Fresenius Medical Care Management Board, Goldfinch Bio, and Vifor Fresenius Medical Care Renal Pharma. RPF, TPM are employed by Pontifícia Universidade Católica do Paraná, and are recipients of scholarships from the Brazilian Council for Research (CNPq). RPF is employed by Arbor Research Collaborative for Health, and receives research grants, consulting fees, and honoraria from AstraZeneca, Novo Nordisc, Akebia Therapeutics, and Fresenius Medical Care. JWL, PB, TPM are guest editors on the Editorial Board of Frontiers in Physiology. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Increasing number of studies have linked air pollution exposure with renal function decline and disease. However, there is a lack of data on its impact among end-stage kidney disease (ESKD) patients and its potential modifying effect from extreme heat events (EHE)., Methods: Fresenius Kidney Care records from 28 selected northeastern US counties were used to pool daily all-cause mortality (ACM) and all-cause hospital admissions (ACHA) counts. County-level daily ambient PM 2.5 and ozone (O 3 ) were estimated using a high-resolution spatiotemporal coupled climate-air quality model and matched to ESKD patients based on ZIP codes of treatment sites. We used time-stratified case-crossover analyses to characterize acute exposures using individual and cumulative lag exposures for up to 3 days (Lag 0-3) by using a distributed lag nonlinear model framework. We used a nested model comparison hypothesis test to evaluate for interaction effects between air pollutants and EHE and stratification analyses to estimate effect measures modified by EHE days., Results: From 2001 to 2016, the sample population consisted of 43,338 ESKD patients. We recorded 5217 deaths and 78,433 hospital admissions. A 10-unit increase in PM 2.5 concentration was associated with a 5% increase in ACM (rate ratio [RR Lag0 - 3 ]: 1.05, 95% CI: 1.00-1.10) and same-day O 3 (RR Lag0 : 1.02, 95% CI: 1.01-1.03) after adjusting for extreme heat exposures. Mortality models suggest evidence of interaction and effect measure modification, though not always simultaneously. ACM risk increased up to 8% when daily ozone concentrations exceeded National Ambient Air Quality Standards established by the United States, but the increases in risk were considerably higher during EHE days across lag periods., Conclusion: Our findings suggest interdependent effects of EHE and air pollution among ESKD patients for all-cause mortality risks. National level assessments are needed to consider the ESKD population as a sensitive population and inform treatment protocols during extreme heat and degraded pollution episodes., Competing Interests: Declaration of competing interest Dr. Raimann reported being an employee of the Renal Research Institute (a wholly owned subsidiary of Fresenius Medical Care [FMC]) and owning stock in FMC. Dr. Kotanko reported receiving honoraria from UpToDate, being an employee of the Renal Research Institute, and owning stock in FMC. Dr. Maddux reported owning stock in and being employed by FMC. No other disclosures were reported., (Copyright © 2021. Published by Elsevier B.V.)

Background: Typical thermoregulatory responses to elevated temperatures among healthy individuals include reduced blood pressure and perspiration. Individuals with end-stage kidney disease (ESKD) are susceptible to systemic fluctuations caused by ambient temperature changes that may increase morbidity and mortality. We investigated whether pre-dialysis systolic blood pressure (preSBP) and interdialytic weight gain (IDWG) can independently mediate the association between ambient temperature, all-cause hospital admissions (ACHA), and all-cause mortality (ACM)., Methods: The study population consisted of ESKD patients receiving hemodialysis treatments at Fresenius Medical Care facilities in Philadelphia County, PA, from 2011 to 2019 (n = 1981). Within a time-to-event framework, we estimated the association between daily maximum dry-bulb temperature (TMAX) and, as separate models, ACHA and ACM during warmer calendar months. Clinically measured preSBP and IDWG responses to temperature increases were estimated using linear mixed effect models. We employed the difference (c-c') method to decompose total effect models for ACHA and ACM using preSBP and IDWG as time-dependent mediators. Covariate adjustments for exposure-mediator and total and direct effect models include age, race, ethnicity, blood pressure medication use, treatment location, preSBP, and IDWG. We considered lags up to two days for exposure and 1-day lag for mediator variables (Lag 2-Lag 1) to assure temporality between exposure-outcome models. Sensitivity analyses for 2-day (Lag 2-only) and 1-day (Lag 1-only) lag structures were also conducted., Results: Based on Lag 2- Lag 1 temporal ordering, 1 °C increase in daily TMAX was associated with increased hazard of ACHA by 1.4% (adjusted hazard ratio (HR), 1.014; 95% confidence interval, 1.007-1.021) and ACM 7.5% (adjusted HR, 1.075, 1.050-1.100). Short-term lag exposures to 1 °C increase in temperature predicted mean reductions in IDWG and preSBP by 0.013-0.015% and 0.168-0.229 mmHg, respectively. Mediation analysis for ACHA identified significant indirect effects for all three studied pathways (preSBP, IDWG, and preSBP + IDWG) and significant indirect effects for IDWG and conjoined preSBP + IDWG pathways for ACM. Of note, only 1.03% of the association between temperature and ACM was mediated through preSBP. The mechanistic path for IDWG, independent of preSBP, demonstrated inconsistent mediation and, consequently, potential suppression effects in ACHA (-15.5%) and ACM (-6.3%) based on combined pathway models. Proportion mediated estimates from preSBP + IDWG pathways achieved 2.2% and 0.3% in combined pathway analysis for ACHA and ACM outcomes, respectively. Lag 2 discrete-time ACM mediation models exhibited consistent mediation for all three pathways suggesting that 2-day lag in IDWG and preSBP responses can explain 2.11% and 4.41% of total effect association between temperature and mortality, respectively., Conclusion: We corroborated the previously reported association between ambient temperature, ACHA and ACM. Our results foster the understanding of potential physiological linkages that may explain or suppress temperature-driven hospital admissions and mortality risks. Of note, concomitant changes in preSBP and IDWG may have little intermediary effect when analyzed in combined pathway models. These findings advance our assessment of candidate interventions to reduce the impact of outdoor temperature change on ESKD patients., (Copyright © 2021 Elsevier Inc. All rights reserved.)

As the prevalence of chronic kidney disease is expected to rise worldwide over the next decades, provision of renal replacement therapy (RRT), will further challenge budgets of all healthcare systems. Most patients today requiring RRT are treated with haemodialysis (HD) therapy and are elderly. This article demonstrates the interdependence of clinical and sustainability criteria that need to be considered to prepare for the future challenges of delivering dialysis to all patients in need. Newer, more sustainable models of high-value care need to be devised, whereby delivery of dialysis is based on value-based healthcare (VBHC) principles, i.e. improving patient outcomes while restricting costs. Essentially, this entails maximizing patient outcomes per amount of money spent or available. To bring such a meaningful change, revised strategies having the involvement of multiple stakeholders (i.e. patients, providers, payers and policymakers) need to be adopted. Although each stakeholder has a vested interest in the value agenda often with conflicting expectations and motivations (or motives) between each other, progress is only achieved if the multiple blocs of the delivery system are advanced as mutually reinforcing entities. Clinical considerations of delivery of dialysis need to be based on the entire patient disease pathway and evidence-based medicine, while the non-clinical sustainability criteria entail, in addition to economics, the societal and ecological implications of HD therapy. We discuss how selection of appropriate modes and features of delivery of HD (e.g. treatment modalities and schedules, selection of consumables, product life cycle assessment) could positively impact decision-making towards value-based renal care. Although the delivery of HD therapy is multifactorial and complex, applying cost-effectiveness analyses for the different HD modalities (conventional in-centre and home HD) can support in guiding payability (balance between clinical value and costs) for health systems. For a resource intensive therapy like HD, concerted and fully integrated care strategies need to be urgently implemented to cope with the global demand and burden of HD therapy., (© The Author(s) 2021. Published by Oxford University Press on behalf of ERA.)

Background: An integrated kidney disease company uses machine learning (ML) models that predict the 12-month risk of an outpatient hemodialysis (HD) patient having multiple hospitalizations to assist with directing personalized interdisciplinary interventions in a Dialysis Hospitalization Reduction Program (DHRP). We investigated the impact of risk directed interventions in the DHRP on clinic-wide hospitalization rates., Methods: We compared the hospital admission and day rates per-patient-year (ppy) from all hemodialysis patients in 54 DHRP and 54 control clinics identified by propensity score matching at baseline in 2015 and at the end of the pilot in 2018. We also used paired T test to compare the between group difference of annual hospitalization rate and hospitalization days rates at baseline and end of the pilot., Results: The between group difference in annual hospital admission and day rates was similar at baseline (2015) with a mean difference between DHRP versus control clinics of -0.008 ± 0.09 ppy and -0.05 ± 0.96 ppy respectively. The between group difference in hospital admission and day rates became more distinct at the end of follow up (2018) favoring DHRP clinics with the mean difference being -0.155 ± 0.38 ppy and -0.97 ± 2.78 ppy respectively. A paired t-test showed the change in the between group difference in hospital admission and day rates from baseline to the end of the follow up was statistically significant (t-value = 2.73, p-value < 0.01) and (t-value = 2.29, p-value = 0.02) respectively., Conclusions: These findings suggest ML model-based risk-directed interdisciplinary team interventions associate with lower hospitalization rates and hospital day rate in HD patients, compared to controls., (Copyright © 2021. Published by Elsevier B.V.)

Background: Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ultrafiltration rate which in turn has a positive effect on intradialytic symptoms. It has been clinically challenging to identify changes RBV in real time to proactively intervene and reduce potential negative consequences of volume depletion. Leveraging advanced technologies to process large volumes of dialysis and machine data in real time and developing prediction models using machine learning (ML) is critical in identifying these signals., Method: We conducted a proof-of-concept analysis to retrospectively assess near real-time dialysis treatment data from in-center patients in six clinics using Optical Sensing Device (OSD), during December 2018 to August 2019. The goal of this analysis was to use real-time OSD data to predict if a patient's relative blood volume (RBV) decreases at a rate of at least - 6.5 % per hour within the next 15 min during a dialysis treatment, based on 10-second windows of data in the previous 15 min. A dashboard application was constructed to demonstrate how reporting structures may be developed to alert clinicians in real time of at-risk cases. Data was derived from three sources: (1) OSDs, (2) hemodialysis machines, and (3) patient electronic health records., Results: Treatment data from 616 in-center dialysis patients in the six clinics was curated into a big data store and fed into a Machine Learning (ML) model developed and deployed within the cloud. The threshold for classifying observations as positive or negative was set at 0.08. Precision for the model at this threshold was 0.33 and recall was 0.94. The area under the receiver operating curve (AUROC) for the ML model was 0.89 using test data., Conclusions: The findings from our proof-of concept analysis demonstrate the design of a cloud-based framework that can be used for making real-time predictions of events during dialysis treatments. Making real-time predictions has the potential to assist clinicians at the point of care during hemodialysis., (© 2021. The Author(s).)

Background: We developed a machine learning (ML) model that predicts the risk of a patient on hemodialysis (HD) having an undetected SARS-CoV-2 infection that is identified after the following ≥3 days., Methods: As part of a healthcare operations effort, we used patient data from a national network of dialysis clinics (February-September 2020) to develop an ML model (XGBoost) that uses 81 variables to predict the likelihood of an adult patient on HD having an undetected SARS-CoV-2 infection that is identified in the subsequent ≥3 days. We used a 60%:20%:20% randomized split of COVID-19-positive samples for the training, validation, and testing datasets., Results: We used a select cohort of 40,490 patients on HD to build the ML model (11,166 patients who were COVID-19 positive and 29,324 patients who were unaffected controls). The prevalence of COVID-19 in the cohort (28% COVID-19 positive) was by design higher than the HD population. The prevalence of COVID-19 was set to 10% in the testing dataset to estimate the prevalence observed in the national HD population. The threshold for classifying observations as positive or negative was set at 0.80 to minimize false positives. Precision for the model was 0.52, the recall was 0.07, and the lift was 5.3 in the testing dataset. Area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) for the model was 0.68 and 0.24 in the testing dataset, respectively. Top predictors of a patient on HD having a SARS-CoV-2 infection were the change in interdialytic weight gain from the previous month, mean pre-HD body temperature in the prior week, and the change in post-HD heart rate from the previous month., Conclusions: The developed ML model appears suitable for predicting patients on HD at risk of having COVID-19 at least 3 days before there would be a clinical suspicion of the disease., Competing Interests: C. Monaghan, F. Maddux, H. Han, J. Larkin, L. Usvyat, S. Chaudhuri, and Y. Jiao are employees of Fresenius Medical Care in the Global Medical Office. E. Weinhandl, I. Dahne-Steuber, J. Hymes, K. Belmonte, K. Bermudez, and R. Kossmann are employees of Fresenius Medical Care North America. F. Maddux has directorships in the Fresenius Medical Care Management Board, Goldfinch Bio, and Vifor Fresenius Medical Care Renal Pharma. F. Maddux, I. Dahne-Steuber, J. Hymes, K. Belmonte, L. Usvyat, P. Kotanko, and R. Kossmann have share options/ownership in Fresenius Medical Care. L. Neri is an employee of Fresenius Medical Care Deutschland GmbH in the Europe, the Middle East, and Africa Medical Office. P. Kotanko is an employee of Renal Research Institute, a wholly owned subsidiary of Fresenius Medical Care; reports receiving honorarium from Up-To-Date; and is on the Editorial Board of Blood Purification and Kidney and Blood Pressure Research. All remaining authors have nothing to disclose., (Copyright © 2021 by the American Society of Nephrology.)

Artificial intelligence (AI) is considered as the next natural progression of traditional statistical techniques. Advances in analytical methods and infrastructure enable AI to be applied in health care. While AI applications are relatively common in fields like ophthalmology and cardiology, its use is scarcely reported in nephrology. We present the current status of AI in research toward kidney disease and discuss future pathways for AI. The clinical applications of AI in progression to end-stage kidney disease and dialysis can be broadly subdivided into three main topics: (a) predicting events in the future such as mortality and hospitalization; (b) providing treatment and decision aids such as automating drug prescription; and (c) identifying patterns such as phenotypical clusters and arteriovenous fistula aneurysm. At present, the use of prediction models in treating patients with kidney disease is still in its infancy and further evidence is needed to identify its relative value. Policies and regulations need to be addressed before implementing AI solutions at the point of care in clinics. AI is not anticipated to replace the nephrologists' medical decision-making, but instead assist them in providing optimal personalized care for their patients., (© 2020 The Authors. Seminars in Dialysis published by Wiley Periodicals LLC.)

Background/aims: Hepatitis B (HB) vaccination in hemodialysis patients is important as they are at a higher risk of contracting HB. However, hemodialysis patients have a lower HB seroconversion rate than their healthy counterparts. As better sleep has been associated with better seroconversion in healthy populations and early hemodialysis start has been linked to significant sleep-wake disturbances in hemodialysis patients, we examined if hemodialysis treatment start time is associated with HB vaccination response., Methods: Demographics, standard-of-care clinical, laboratory, and treatment parameters, dialysis shift data, HB antigen status, HB vaccination status, and HB titers were collected from hemodialysis patients in Fresenius clinics from January 2010 to December 2015. Patients in our analysis received 90% of dialysis treatments either before or after 8:30 a.m., were negative for HB antigen, and received a complete series of HB vaccination (Engerix B® or Recombivax HB™). Univariate and multivariate regression models examined whether dialysis start time is a predictor of HB vaccination response., Results: Patients were 65 years old, 57% male, and had a HD vintage of 10 months. Patients whose dialysis treatments started before 8:30 a.m. were more likely to be younger, male, and have a greater dialysis vintage. Patients receiving Engerix B® and starting dialysis before 8:30 a.m. had a significantly higher seroconversion rate compared to patients who started dialysis after 8:30 a.m. Early dialysis start was a significant predictor of seroconversion in univariate and multivariate regression including male gender, but not in multivariate regression including age, neutrophil-to-lymphocyte ratio, and vintage., Conclusion: While better sleep following vaccination is associated with seroconversion in the general population, this is not the case in hemodialysis patients after multivariate adjustment. In the context of end-stage kidney disease, early dialysis start is not a significant predictor of HB vaccination response. The association between objectively measured postvaccination sleep duration and seroconversion rate should be investigated., (© 2021 S. Karger AG, Basel.)

Background: Dialysis recovery time (DRT) surveys capture the perceived time after HD to return to performing regular activities. Prior studies suggest the majority of HD patients report a DRT > 2 h. However, the profiles of and modifiable dialysis practices associated with changes in DRT relative to the start of dialysis are unknown. We hypothesized hemodialysis (HD) dose and rates of intradialytic hypotension (IDH) would associate with changes in DRT in the first years after initiating dialysis., Methods: We analyzed data from adult HD patients who responded to a DRT survey ≤180 days from first date of dialysis (FDD) during 2014 to 2017. DRT survey was administered with annual KDQOL survey. DRT survey asks: "How long does it take you to be able to return to your normal activities after your dialysis treatment?" Answers are: < 0.5, 0.5-to-1, 1-to-2, 2-to-4, or > 4 h. An adjusted logistic regression model computed odds ratio for a change to a longer DRT (increase above DRT > 2 h) in reference to a change to a shorter DRT (decrease below DRT < 2 h, or from DRT > 4 h). Changes in DRT were calculated from incident (≤180 days FDD) to first prevalent (> 365-to- ≤ 545 days FDD) and second prevalent (> 730-to- ≤ 910 days FDD) years., Results: Among 98,616 incident HD patients (age 62.6 ± 14.4 years, 57.8% male) who responded to DRT survey, a higher spKt/V in the incident period was associated with 13.5% (OR = 0.865; 95%CI 0.801-to-0.935) lower risk of a change to a longer DRT in the first-prevalent year. A higher number of HD treatments with IDH episodes per month in the incident period was associated with a 0.8% (OR = 1.008; 95%CI 1.001-to-1.015) and 1.6% (OR = 1.016; 95%CI 1.006-to-1.027) higher probability of a change to a longer DRT in the first- and second-prevalent years, respectively. Consistently, an increased in incidence of IDH episodes/months was associated to a change to a longer DRT over time., Conclusions: Incident patients who had higher spKt/V and less sessions with IDH episodes had a lower likelihood of changing to a longer DRT in first year of HD. Dose optimization strategies with cardiac stability in fluid removal should be tested.

Background: Pre-dialysis systolic blood pressure (pre-HD SBP) and peridialytic SBP change have been associated with morbidity and mortality among hemodialysis (HD) patients in previous studies, but the nature of their interaction is not well understood., Methods: We analyzed pre-HD SBP and peridialytic SBP change (calculated as post-HD SBP minus pre-HD SBP) between January 2001 and December 2012 in HD patients treated in US Fresenius Medical Care facilities. The baseline period was defined as Months 4-6 after HD initiation, and all-cause mortality was noted during follow-up. Only patients who survived baseline and had no missing covariates were included. Censoring events were renal transplantation, modality change or study end. We fitted a Cox proportional hazard model with a bivariate spline functions for the primary predictors (pre-HD SBP and peridialytic SBP change) with adjustment for age, gender, race, diabetes, access-type, relative interdialytic weight gain, body mass index, albumin, equilibrated normalized protein catabolic rate and ultrafiltration rate., Results: A total of 172 199 patients were included. Mean age was 62.1 years, 61.6% were white and 55% were male. During a median follow-up of 25.0 months, 73 529 patients (42.7%) died. We found that a peridialytic SBP rise combined with high pre-HD SBP was associated with higher mortality. In contrast, when concurrent with low pre-HD SBP, a peridialytic SBP rise was associated with better survival., Conclusion: The association of pre-HD and peridialytic SBP change with mortality is complex. Our findings call for a joint, not isolated, interpretation of pre-HD SBP and peridialytic SBP change., (© The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA.)

The announcement of the Advancing American Kidney Health (AAKH) Initiative on July 10, 2019 was met with a mix of excitement and trepidation, befitting a proposed radical reconfiguration of the delivery of kidney disease care. Aspiring to reduce the incidence of end-stage renal disease, increase the prevalence of home dialysis, and double the number of organs available for transplant, the AAKH payment models primarily focus on incenting behaviors of general nephrologists, though actualizing positive incentives will require the active cooperation of dialysis providers and transplant centers. Here, we review the AAKH initiatives' potential impact on all stakeholders and opine on financial and regulatory pressures on kidney transplant programs, outlining areas of uncertainty and concern, and suggest key points of reflection for clinical and administrative leaders of kidney transplant centers weighing participation in any of the voluntary payment models., (© 2019 The American Society of Transplantation and the American Society of Transplant Surgeons.)

Maintaining phosphorus balance in in-center hemodialysis (ICHD) patients is problematic despite recommended dietary restriction, dialysis, and phosphate binder use. Rarely is P content in prescribed medications considered, but this source should raise concern. Data was obtained from the Fresenius Kidney Care (FKC) electronic data warehouse Knowledge Center and MedReview-eRx accessed Surescripts, housing > 80% of US-filled prescriptions. Adult FKC ICHD patients prescribed ≥ 1 medication in the MedReview-eRx database were analyzed (695,759 prescriptions). Information collected included medication dose, dose unit, dose timing, strength, start and stop dates, refills, demographic information, admission history, and modality type. Numbers of patients, prescriptions by individual medication, and drug class were then analyzed. Medications prescribed > 100 times were reported. Median doses/day (number of tablets) were calculated for each medication (open order on randomly selected day). Phosphate content of medications taken in FKC clinics was assessed using routinely used pharmacology references, and potential resulting phosphate and pill burden were also calculated. The top five prescribed drug classes in FKC dialysis patients were calcium-channel blockers (22%), proton pump inhibitors (PPIs; 18%), acetaminophen-opioid (AO; 13%), angiotensin-converting enzyme inhibitors (ACEi; 10%), and α2-agonists (9%). The maximum phosphate added for different medications varied by manufacturer. For instance, at median daily doses, phosphate contributions from the top five medications prescribed were 112 mg for amlodipine, 116.2 mg from lisinopril, 6.7 mg from clonidine, 0 mg from acetaminophen, and 200 mg for omeprazole. Prescribing these together could increase the daily phosphate load by 428 mg, forcing the patient to exceed the recommended daily intake (RDI) with food and drink. Phosphate content in medications prescribed to HD patients can substantially contribute to the daily phosphate load and, in combination, may even exceed the daily recommended dietary phosphate intake. Healthcare providers should monitor all medications containing phosphate prescribed in order to minimize risk of uncontrolled hyperphosphatemia and poor adherence.
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Background and Objectives: In the United States, intravenous vitamin D analogs are the first-line therapy for management of secondary hyperparathyroidism in hemodialysis patients. Outside the United States, oral calcitriol (1,25-dihydroxyvitamin D 3 ) is routinely used. We examined standard laboratory parameters of patients on in-center hemodialysis receiving intravenous vitamin D who switched to oral calcitriol., Design, Setting, Participants, & Measurements: We conducted a retrospective cohort study of adult patients treated within Fresenius Kidney Care clinics. During a 6-month period (December 2013 to May 2014), we identified patients on an intravenous vitamin D analog (doxercalciferol or paricalcitol) who switched to oral calcitriol and matched them to patients receiving an intravenous vitamin D analog. Mean serum calcium, phosphate, and intact parathyroid hormone (iPTH) concentrations were examined for up to 12 months of follow-up. We used Poisson and Cox proportional hazards regression models to examine hospitalization and survival rates. The primary analysis was conducted as intention-to-treat; secondary analyses included an as-treated evaluation., Results: A total of 2280 patients who switched to oral calcitriol were matched to 2280 patients receiving intravenous vitamin D. Compared with patients on intravenous vitamin D, mean calcium and phosphate levels in the oral calcitriol group were lower after the change to oral calcitriol. In contrast, iPTH levels were higher in the oral calcitriol group. At 12 months, the percentage of patients with composite laboratories in target range (calcium <10 mg/dl, phosphate 3.0-5.5 mg/dl, and iPTH 150-600 pg/ml) were comparable between groups (45% versus 45%; P =0.96). Hospital admissions, length of hospital stay, and survival were comparable between groups. An as-treated analysis and excluding those receiving cinacalcet did not reveal significant between-group differences., Conclusions: Among patients receiving in-center hemodialysis who were switched to oral calcitriol versus those on an intravenous vitamin D analog, the aggregate of all mineral and bone laboratory parameters in range was largely similar between groups., (Copyright © 2020 by the American Society of Nephrology.)

Background Hypertension remains a leading global cause for premature death and disease. Most treatment guidelines emphasize the importance of risk factors, but not all are known, modifiable, or easily avoided. Population blood pressure correlates with latitude and is lower in summer than winter. Seasonal variations in sunlight exposure account for these differences, with temperature believed to be the main contributor. Recent research indicates that UV light enhances nitric oxide availability by mobilizing storage forms in the skin, suggesting incident solar UV radiation may lower blood pressure. We tested this hypothesis by exploring the association between environmental UV exposure and systolic blood pressure (SBP) in a large cohort of chronic hemodialysis patients in whom SBP is determined regularly. Methods and Results We studied 342 457 patients (36% black, 64% white) at 2178 US dialysis centers over 3 years. Incident UV radiation and temperature data for each clinic location were retrieved from the National Oceanic and Atmospheric Administration database. Linear mixed effects models with adjustment for ambient temperature, sex/age, body mass index, serum Na + /K + and other covariates were fitted to each location and combined estimates of associations calculated using the DerSimonian and Laird procedure. Pre-dialysis SBP varied by season and was ≈4 mm Hg higher in black patients. Temperature, UVA and UVB were all linearly and inversely associated with SBP. This relationship remained statistically significant after correcting for temperature. Conclusions In hemodialysis patients, in addition to environmental temperature, incident solar UV radiation is associated with lower SBP. This raises the possibility that insufficient sunlight is a new risk factor for hypertension, perhaps even in the general population.

Background: An integrated kidney disease healthcare company implemented a peritoneal dialysis (PD) remote treatment monitoring (RTM) application in 2016. We assessed if RTM utilization associates with hospitalization and technique failure rates., Methods: We used data from adult (age ≥18 years) patients on PD treated from October 2016 through May 2019 who registered online for the RTM. Patients were classified by RTM use during a 30-day baseline after registration. Groups were: nonusers (never entered data), moderate users (entered one to 15 treatments), and frequent users (entered >15 treatments). We compared hospital admission/day and sustained technique failure (required >6 consecutive weeks of hemodialysis) rates over 3, 6, 9, and 12 months of follow-up using Poisson and Cox models adjusted for patient/clinical characteristics., Results: Among 6343 patients, 65% were nonusers, 11% were moderate users, and 25% were frequent users. Incidence rate of hospital admission was 22% (incidence rate ratio [IRR]=0.78; P =0.002), 24% (IRR=0.76; P <0.001), 23% (IRR=0.77; P ≤0.001), and 26% (IRR=0.74; P ≤0.001) lower in frequent users after 3, 6, 9, and 12 months, respectively, versus nonusers. Incidence rate of hospital days was 38% (IRR=0.62; P =0.013), 35% (IRR=0.65; P =0.001), 34% (IRR=0.66; P ≤0.001), and 32% (IRR=0.68; P <0.001) lower in frequent users after 3, 6, 9, and 12 months, respectively, versus nonusers. Sustained technique failure risk at 3, 6, 9, and 12 months was 33% (hazard ratio [HR]=0.67; P =0.020), 31% (HR=0.69; P =0.003), 31% (HR=0.69; P =0.001), and 27% (HR=0.73; P =0.001) lower, respectively, in frequent users versus nonusers. Among a subgroup of survivors of the 12-month follow-up, sustained technique failure risk was 26% (HR=0.74; P =0.023) and 21% (HR=0.79; P =0.054) lower after 9 and 12 months, respectively, in frequent users versus nonusers., Conclusions: Our findings suggest frequent use of an RTM application associates with less hospital admissions, shorter hospital length of stay, and lower technique failure rates. Adoption of RTM applications may have the potential to improve timely identification/intervention of complications., Competing Interests: S. Chaudhuri, H. Han, J. Larkin, F. Maddux, M. Mendoza, and L. Usvyat are employees of Fresenius Medical Care in the Global Medical Office. D. Chatoth, D. Maddux, C. Muchiutti, and J. Ryter are employees of Fresenius Medical Care North America. D. Maddux, F. Maddux, and L. Usvyat have share options/ownership in Fresenius Medical Care. F. Maddux has directorships in American National Bank & Trust and is chairman of Pacific Care Renal Foundation 501(c)(3) nonprofit., (Copyright © 2020 by the American Society of Nephrology.)

Background: All life on earth has adapted to the effects of changing seasons. The general and ESKD populations exhibit seasonal rhythms in physiology and outcomes. The ESKD population also shows secular trends over calendar time that can convolute the influences of seasonal variations. We conducted an analysis that simultaneously considered both seasonality and calendar time to isolate these trends for cardiovascular, nutrition, and inflammation markers., Methods: We used data from adult patients on hemodialysis (HD) in the United States from 2010 through 2014. An additive model accounted for variations over both calendar time and time on dialysis. Calendar time trends were decomposed into seasonal and secular trends. Bootstrap procedures and likelihood ratio methods tested if seasonal and secular variations exist., Results: We analyzed data from 354,176 patients on HD at 2436 clinics. Patients were 59±15 years old, 57% were men, and 61% had diabetes. Isolated average secular trends showed decreases in pre-HD systolic BP (pre-SBP) of 2.6 mm Hg (95% CI, 2.4 to 2.8) and interdialytic weight gain (IDWG) of 0.35 kg (95% CI, 0.33 to 0.36) yet increases in post-HD weight of 2.76 kg (95% CI, 2.58 to 2.97). We found independent seasonal variations of 3.3 mm Hg (95% CI, 3.1 to 3.5) for pre-SBP, 0.19 kg (95% CI, 0.17 to 0.20) for IDWG, and 0.62 kg (95% CI, 0.46 to 0.79) for post-HD weight as well as 0.12 L (95% CI, 0.11 to 0.14) for ultrafiltration volume, 0.41 ml/kg per hour (95% CI, 0.37 to 0.45) for ultrafiltration rates, and 3.30 (95% CI, 2.90 to 3.77) hospital days per patient year, which were higher in winter versus summer., Conclusions: Patients on HD show marked seasonal variability of key indicators. Secular trends indicate decreasing BP and IDWG and increasing post-HD weight. These methods will be of importance for independently determining seasonal and secular trends in future assessments of population health., Competing Interests: Fresenius Medical Care provided the deidentified data used for this study and infrastructural support for the management of the study data, analysis design, and composition of this manuscript. A. Long, M. Reviriego-Mendoza, J. Larkin, L. Usvyat, and F. Maddux are employees of Fresenius Medical Care in the Global Medical Office. L. Usvyat, P. Kotanko, and F. Maddux have share options/ownership in Fresenius Medical Care. P. Kotanko is an employee of Renal Research Institute, a wholly owned subsidiary of Fresenius Medical Care. P. Kotanko receives honoraria from Up-To-Date and is on the Editorial Boards of Blood Purification and Kidney and Blood Pressure Research. F. Maddux has directorships in the American National Bank & Trust and is chairman of Pacific Care Renal Foundation 501(c)(3) nonprofit. Z. Terner and Y. Wang declare no relevant conflicts of interest., (Copyright © 2020 by the American Society of Nephrology.)

Objective(s): Malnutrition and protein-energy wasting are associated with morbidity and mortality in hemodialysis patients. Existing nutritional scores rely primarily on cross-sectional data. Using readily available nutritional indicators, we developed models to predict the risk of mortality and hospitalization in prevalent hemodialysis patients., Design and Methods: In this retrospective study, we constructed prediction models of 1-year mortality and hospitalization using generalized linear models, generalized additive models (GAM), classification tree, and random forest models. The models were compared using area under the receiver-operating characteristics curve (AUC) and calibration curves. Model predictors included nutritional and inflammation indicators, demographics, comorbidities, and slopes of all continuous variables over 6 months. Patients were randomly split in the ratio 2:1:1 into training, testing, and validation cohorts, respectively. We included patients with hemodialysis vintage ≥1 year from Fresenius Medical Care North America clinics from July 2011 to December 2012 (N = 21,802 in mortality analysis; N = 13,892 in hospitalization analysis).The outcome variables were 1-year mortality and hospitalization., Results: For mortality prediction, GAM was the best model (AUC = 0.85, 95% confidence interval = 0.83-0.86), comprised of neutrophil-to-lymphocyte ratio slope, serum bicarbonate slope, and vintage as nonlinear predictors, and age, serum albumin, and creatinine as linear predictors. For hospitalization prediction, GAM was also the best model (AUC = 0.70, 95% confidence interval = 0.62-0.79) and included neutrophil-to-lymphocyte ratio slope, bicarbonate slope, volume of urea distribution, vintage, and phosphate slope as nonlinear predictors, in addition to albumin, congestive heart failure, age, phosphate, equilibrated normalized protein catabolic rate, and creatinine as linear predictors. Both models demonstrated good calibration, with mild overestimation of hospitalization risk at the highest risk interval., Conclusions: The GAM model can accurately predict the risk of mortality and hospitalization. Application of these prediction models could inform allocation of nutritional interventions to patients at highest nutritional risk., (Copyright © 2019 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Recent developments in US kidney-related healthcare policy have made chronic kidney disease (CKD) a societal focus in the United States. In the biggest policy change since the 1972 Social Security Amendments that extended Medicare coverage to patients with kidney failure regardless of age, a 2019 presidential executive order pledged to reduce end-stage kidney disease, slow CKD progression, increase kidney transplants, and focus on home dialysis care. This manuscript seeks to outline key factors that can enable this milestone moment to evolve a policy framework that improves the health of society while being economically sustainable. Understanding the sociohistorical context of healthcare policy and the related lessons learned demonstrates that policy must take a broader view of the societal and system wide factors that affect chronic illness. Addressing the full breadth of the CKD epidemic requires looking at factors from both inside and outside traditional medical-pathophysiological environments, including social determinants of health. This more fulsome insight will enable policy to better align the broad range of people and organizations who are working to combat the disease. By creating patient-centered policy that both evolves with the speed of innovation and addresses root causes of CKD instead of narrowly focusing on symptoms or comorbidities alone, leaders in the public square have an historic opportunity to thoughtfully create the common ground of a lasting policy legacy that improves society's health today and for generations to come., (© 2020 The Authors. Seminars in Dialysis published by Wiley Periodicals, Inc.)

Background: Sickle cell disease (SCD) is the most common inherited hematological disorder and a well-described risk factor for end-stage kidney disease (ESKD). Mortality and hospitalizations among patients with SCD who develop ESKD remain understudied. Furthermore, prior studies focused only on SCD patients where ESKD was caused by SCD. We aimed to describe mortality and hospitalization risk in all SCD patients initiating dialysis and explore risk factors for mortality and hospitalization., Methods: We performed a national observational cohort study of African American ESKD patients initiating dialysis (2000-2014) in facilities affiliated with a large dialysis provider. SCD was identified by diagnosis codes and matched to a reference population (non-SCD) by age, sex, dialysis initiation year, and geographic region of care. Sensitivity analyses were conducted by restricting to patients where SCD was recorded as the cause of ESKD., Results: We identified 504 SCD patients (mean age: 47 ± 14 years; 48% females) and 1,425 reference patients (mean age: 46 ± 14 years; 49% females). The median follow-up was 2.4 (IQR 1.0-4.5) years. Compared to the reference, SCD was associated with higher mortality risk (hazard ratio 1.66; 95% confidence interval [CI]: 1.36-2.03) and higher hospitalization rates (incidence rate ratio 2.12; 95% CI: 1.88-2.38) in multivariable analyses. Exploratory multivariable mortality risk models showed the largest mortality risk attenuation with the addition of time-varying hemoglobin and high-dose erythropoietin, but the association of SCD with mortality remained significant. Sensitivity analyses (restricted to ESKD caused by SCD) also showed significant associations between SCD and mortality and hospitalizations, but with larger effect estimates. High-dose erythropoietin was associated with the highest risk for mortality and hospitalization in SCD., Conclusions: Among ESKD patients, SCD is associated with a higher risk for mortality and hospitalization, particularly in patients where SCD is identified as the cause of ESKD., (© 2021 S. Karger AG, Basel.)

Background: Evidence indicates that the inverse relationships between phosphate levels and mortality maybe modified by age. Furthermore, malnutrition and inflammation could strengthen the risk associated with phosphate abnormalities. This study aimed to assess the associations between phosphate levels and mortality while accounting for the interactions with age and parameters associated with malnutrition and inflammation in hemodialysis (HD) patients., Methods: Adult HD patients ( n  = 245 853) treated in Fresenius Medical Care North America clinics from January 2010 to October 2018 were enrolled. Baseline was defined as Months 4-6 on dialysis, with the subsequent 12 months as the follow-up period. Univariate and multivariate Cox proportional hazard models with spline terms were applied to study the nonlinear relationships between serum phosphate levels and mortality. The interactions of phosphate levels with albumin, creatinine, normalized protein catabolic rate (nPCR) and neutrophil-lymphocyte ratio (NLR) were assessed with smoothing spline analysis of variance Cox proportional hazard models., Results: Older patients tended to have lower levels of serum phosphate, albumin, creatinine and nPCR. Additionally, both low (<4.0 mg/dL) and high (>5.5 mg/dL) phosphate levels were associated with higher risk of mortality across all age strata. The U-shaped relationships between phosphate levels and outcome persisted even for patients with low or high levels of serum albumin, creatinine, nPCR and NLR, respectively., Conclusion: The consistent U-shaped relationships between serum phosphate and mortality across age strata and levels of inflammatory and nutritional status should prompt the search for underlying causes and potentially nutritional intervention in clinical practice., (© The Author(s) 2019. Published by Oxford University Press on behalf of ERA-EDTA.)

Importance: Extreme heat events (EHEs) are increasing in frequency, duration, and intensity, and this trend is projected to continue as part of ongoing climate change. There is a paucity of data regarding how EHEs may affect highly vulnerable populations, such as patients with end-stage renal disease (ESRD). Such data are needed to inform ESRD patient management guidelines in a changing climate., Objectives: To investigate the association between EHEs and the risk of hospital admission or mortality among patients with ESRD and further characterize how this risk may vary among races/ethnicities or patients with preexisting comorbidities., Design, Setting, and Participants: This study used hospital admission and mortality records of patients with ESRD who underwent hemodialysis treatment at Fresenius Kidney Care clinics in Boston, Massachusetts; Philadelphia, Pennsylvania; or New York, New York, from January 1, 2001, to December 31, 2012. Data were analyzed using a time-stratified case-crossover design with conditional Poisson regression to investigate associations between EHEs and risk of hospital admission or mortality among patients with ESRD. Data were analyzed from July 1, 2017, to March 31, 2019., Exposures: Calendar day- and location-specific 95th-percentile maximum temperature thresholds were calculated using daily meteorological data from 1960 to 1989. These thresholds were used to identify EHEs in each of the 3 cities during the study., Main Outcomes and Measures: Daily all-cause hospital admission and all-cause mortality among patients with ESRD., Results: The study included 7445 patients with ESRD (mean [SD] age, 61.1 [14.1] years; 4283 [57.5%] men), among whom 2953 deaths (39.7%) and 44 941 hospital admissions (mean [SD], 6.0 [7.5] per patient) were recorded. Extreme heat events were associated with increased risk of same-day hospital admission (rate ratio [RR], 1.27; 95% CI, 1.13-1.43) and same-day mortality (RR, 1.31; 95% CI, 1.01-1.70) among patients with ESRD. There was some heterogeneity in risk, with patients in Boston showing statistically significant increased risk for hospital admission (RR, 1.15; 95% CI, 1.00-1.31) and mortality (RR, 1.45; 95% CI, 1.04-2.02) associated with cumulative exposure to EHEs, while such risk was absent among patients with ESRD in Philadelphia. While increases in risks were similar among non-Hispanic black and non-Hispanic white patients, findings among Hispanic and Asian patients were less clear. After stratifying by preexisting comorbidities, cumulative lag exposure to EHEs was associated with increased risk of mortality among patients with ESRD living with congestive heart failure (RR, 1.55; 95% CI, 1.27-1.89), chronic obstructive pulmonary disease (RR, 1.60; 95% CI, 1.24-2.06), or diabetes (RR, 1.83; 95% CI, 1.51-2.21)., Conclusions and Relevance: In this study, extreme heat events were associated with increased risk of hospital admission or mortality among patients with ESRD, and the association was potentially affected by geographic region and race/ethnicity. Future studies with larger populations and broader geographic coverage are needed to better characterize this variability in risk and inform ESRD management guidelines and differential risk variables, given the projected increases in the frequency, duration, and intensity of EHEs.

Introduction: Hemodialysis patients with an arteriovenous fistula can use buttonhole techniques for cannulation. Although buttonholes generally work well, patients may report difficult and painful cannulation, and buttonholes may fail over time. We aimed to assess the effectiveness of tract dilation in treatment of failing buttonholes., Methods: We retrospectively analyzed data from patients treated with buttonhole tract dilation at an outpatient vascular access center between January 2013 and August 2015., Results: Data from 23 patients were analyzed. There were 51 tract dilation procedures during 36 encounters for failing arteriovenous fistula buttonhole tract(s). The technical success rate for established tract dilation with "blunt-recanalization" was 90% (n = 46). The five remaining buttonholes had "sharp-recanalization" to create and dilate new tract through the buttonhole. For 46 buttonholes treated with "blunt-recanalization," there was an 85% clinical success rate at one week (39 buttonholes), and one was lost to follow-up; there was a 70% clinical success rate after one month (32 buttonholes). In the five buttonholes with "sharp-recanalization," there was only one clinical success with p < 0.05 for difference in success rate compared to "blunt-recanalization" at both one week and one month. There was one complication from "sharp-recanalization" requiring abandonment of the buttonhole tract., Discussion: Buttonhole tract dilation is a useful method to treat difficult cannulation and painful cannulation and has the potential to extend the life of failing buttonholes.

Background: Data from clinical trials to inform practice in maintenance hemodialysis are limited. Incorporating randomized trials into dialysis clinical care delivery should help generate practice-guiding evidence, but the feasibility of this approach has not been established., Methods: To develop approaches for embedding trials into routine delivery of maintenance hemodialysis, we performed a cluster-randomized, pragmatic trial demonstration project, the Time to Reduce Mortality in ESRD (TiME) trial, evaluating effects of session duration on mortality (primary outcome) and hospitalization rate. Dialysis facilities randomized to the intervention adopted a default session duration ≥4.25 hours (255 minutes) for incident patients; those randomized to usual care had no trial-driven approach to session duration. Implementation was highly centralized, with no on-site research personnel and complete reliance on clinically acquired data. We used multiple strategies to engage facility personnel and participating patients., Results: The trial enrolled 7035 incident patients from 266 dialysis units. We discontinued the trial at a median follow-up of 1.1 years because of an inadequate between-group difference in session duration. For the primary analysis population (participants with estimated body water ≤42.5 L), mean session duration was 216 minutes for the intervention group and 207 minutes for the usual care group. We found no reduction in mortality or hospitalization rate for the intervention versus usual care., Conclusions: Although a highly pragmatic design allowed efficient enrollment, data acquisition, and monitoring, intervention uptake was insufficient to determine whether longer hemodialysis sessions improve outcomes. More effective strategies for engaging clinical personnel and patients are likely required to evaluate clinical trial interventions that are fully embedded in care delivery., (Copyright © 2019 by the American Society of Nephrology.)

Background: Health-related quality of life (HrQoL) varies among dialysis patients. However, little is known about the association of dialysis modality with HrQoL over time. We describe longitudinal patterns of HrQoL among chronic dialysis patients by treatment modality., Methods: National retrospective cohort study of adult patients who initiated in-center dialysis or a home modality (peritoneal or home hemodialysis) between 1/2013 and 6/2015. Patients remained on the same modality for the first 120 days of the first two years. HrQoL was assessed by the Kidney Disease and Quality of Life-36 (KDQOL) survey in the first 120 days of the first two years after dialysis initiation. Home modality patients were matched to in-center patients in a 1:5 fashion., Results: In-center (n=4234) and home modality (n=880) patients had similar demographic and clinical characteristics. In-center dialysis patients had lower mean KDQOL scores across several domains compared to home modality patients. For patients who remained on the same modality, there was no change in HrQoL. However, there were trends towards clinically meaningful changes in several aspects of HrQoL for patients who switched modalities. Specifically, physical functioning decreased for patients who switched from home to in-center dialysis (p< 0.05)., Conclusions: Among a national cohort of chronic dialysis patients, there was a trend towards different patterns of HrQoL life that were only observed among patients who changed modality. Patients who switched from home to in-center modalities had significant lower physical functioning over time. Providers and patients should be mindful of HrQoL changes that may occur with dialysis modality change.

Background: Peritoneal dialysis (PD) starters generally have a better outcome compared with hemodialysis (HD) starters, perhaps related to treatment characteristics or case mix. We previously showed that pre- and post-dialysis start clinical parameter trajectories are related to outcomes. The aim of this study was to investigate these trajectories in PD and HD starters., Methods: This retrospective observational study analyzing data from the Fresenius Medical Care-chronic kidney disease (CKD) Registry from January 2009 to March 2018 examines trends in key clinical parameters through the transition period covering 12 months before to 12 months after dialysis start in 8,088 HD and 1,015 PD starters., Results: Hemodialysis starters differed from PD starters by a significantly greater decline in estimated glomerular filtration rate (eGFR) slope (-0.64 vs -0.45 mL/min/1.73 m2/month) before and higher eGFR (9.85 vs 7.84 mL/min/1.73 m2) at dialysis start. Relatedly, differences in phosphorus (0.07 vs 0.05 mg/dL/month) and hemoglobin (-0.08 vs -0.01 g/dL/month) slopes before the transition to dialysis therapy were observed. After dialysis start, HD starters experienced a greater increase in albumin (0.01 vs 0 g/dL/month) whereas PD starters experienced a decline in serum sodium and higher white blood cell counts compared with HD starters., Conclusion: For nephrology practice CKD patients, HD and PD starters appear clinically comparable in the year before dialysis start although HD starters exhibit a more rapid pre-dialytic eGFR decline. Ideally, studies comparing incident HD and PD outcomes should also consider CKD eGFR trajectories. In the first dialysis year, divergence occurs in albumin, white blood cell count, sodium and hemoglobin trends, which may be partly treatment-related.

Rationale & Objective: The relationship between tobacco smoking and comorbid condition outcomes in hemodialysis (HD) patients is not well understood. This study examined the association of tobacco smoking status with hospitalization and mortality in HD patients., Study Design: Retrospective cohort study., Setting & Participants: Adult HD patients at 2,223 US dialysis centers with HD vintage of 30 days or less who completed a tobacco smoking status survey as part of standard care between April 2013 and June 2015., Predictor: Tobacco smoking category: never smoked, currently living with smoker, former smoker, moderate smoker (<1 pack per day), or heavy smoker (≥1 pack per day)., Outcomes: Death and hospital admissions within 2 years of the tobacco smoking survey., Analytical Approach: Kaplan-Meier analysis and Cox proportional hazards regression for time to death; cumulative incidence function and Cox proportional hazards regression for time to first hospitalization; negative-binomial regression for number of hospitalizations., Results: Of 22,230 patients studied, 13% were active smokers. Mortality probabilities increased with greater exposure to smoking (17%, 22%, 23%, and 27% for never, moderate, former, and heavy smokers, respectively; P<0.001), as did incidence rates for first hospitalization (23%, 27%, 27%, and 30%, respectively; P<0.001). Compared to never smoked, heavy smokers had the highest mortality rate (HR for heavy smokers, 1.41 [95% CI, 1.18-1.69]; HR for moderate smokers, 1.39 [95% CI, 1.24-1.55]; HR for former smokers, 1.19 [95% CI, 1.11-1.28]). Living with a smoker was not associated with mortality (HR, 0.93; 95% CI, 0.72-1.22). HRs for first hospitalization followed similar patterns. The incidence rate of mortality for active smokers with diabetes was 173.7/1,000 patient-years and 103.5/1,000 patient-years for those who never smoked (incidence rate ratio, 1.68; P<0.001)., Limitations: Self-reported survey without detailed history of smoking/cessation., Conclusions: Risks for death and hospitalization are elevated among HD patients who smoke, being highest among younger individuals and those with diabetes. Second-hand smoke was not associated with poor clinical outcomes., (Copyright © 2018 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Fluid overload and interdialytic weight gain (IDWG) are discrete components of the dynamic fluid balance in haemodialysis patients. We aimed to disentangle their relationship, and the prognostic importance of two clinically distinct, bioimpedance spectroscopy (BIS)-derived measures, pre-dialysis and post-dialysis fluid overload (FOpre and FOpost) versus IDWG., Methods: We conducted a retrospective cohort study on 38 614 incident patients with one or more BIS measurement within 90 days of haemodialysis initiation (1 October 2010 through 28 February 2015). We used fractional polynomial regression to determine the association pattern between FOpre, FOpost and IDWG, and multivariate adjusted Cox models with FO and/or IDWG as longitudinal and time-varying predictors to determine all-cause mortality risk., Results: In analyses using 1-month averages, patients in quartiles 3 and 4 (Q3 and Q4) of FO had an incrementally higher adjusted mortality risk compared with reference Q2, and patients in Q1 of IDWG had higher adjusted mortality compared with Q2. The highest adjusted mortality risk was observed for patients in Q4 of FOpre combined with Q1 of IDWG [hazard ratio (HR) = 2.66 (95% confidence interval 2.21-3.20), compared with FOpre-Q2/IDWG-Q2 (reference)]. Using longitudinal means of FO and IDWG only slightly altered all HRs. IDWG associated positively with FOpre, but negatively with FOpost, suggesting a link with post-dialysis extracellular volume depletion., Conclusions: FOpre and FOpost were consistently positive risk factors for mortality. Low IDWG was associated with short-term mortality, suggesting perhaps an effect of protein-energy wasting. FOpost reflected the volume status without IDWG, which implies that this fluid marker is clinically most intuitive and may be best suited to guide volume management in haemodialysis patients.

Consistent with the increase of precision medicine, the care of patients with end-stage kidney disease (ESKD) requiring maintenance dialysis therapy should evolve to become more personalized. Precise and personalized care is nuanced and informed by a number of factors including an individual's needs and preferences, disease progression, and response to and tolerance of treatments. Technology can support the delivery of more precise and personalized care through multiple mechanisms, including more accurate and real-time assessments of key care elements, enhanced treatment monitoring, and remote monitoring of home dialysis therapies. Data from health care and non-health care sources and advanced analytical methods such as machine learning can be used to create novel insights, and large volumes of data can be integrated to support clinical decisions. Health care models continue to evolve and the opportunities and need for novel care approaches supported by technology and health informatics continue to expand as the delivery and organization of health care changes. Ultimately, precise personalized care for ESKD, including dialysis therapy, will become more feasible as the biological, social, and environmental determinants of health are more broadly understood and as advances in science, engineering, and information management create the means to provide truly precise care for ESKD., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Introduction: The transition from pre-dialysis chronic kidney disease (CKD) to post-dialysis start is a critical period associated with high patient mortality and increased hospital admissions. Little is known about the trends of key clinical and laboratory parameters through this time of transition to start dialysis., Methods: De-identified data including demographics, vital signs, lab results, and eGFR from the Fresenius Medical Care-CKD Registry were analyzed to determine trends in clinical and laboratory parameters through the time of transition from 12 months pre-dialysis start to 12 months post-dialysis start. Trends in key clinical and laboratory parameters associated with cardiovascular, nutritional, mineral metabolism and inflammatory domains were examined in association with the transition to dialysis start and first year dialysis survival., Findings: All parameters show divergence for patients who survive vs. do not survive the first year of dialysis. Of note, during pre-dialysis CKD the absolute systolic blood pressure (SBP) level is lower and the slope for SBP decline is significantly steeper for patients who do not survive the first year on dialysis., Discussion: This study uniquely demonstrates the trajectories of key parameters though the transition from pre-dialysis to post-dialysis start. Significant differences are noted in the pre-dialysis period for patients who survive vs. those who do not survive the first year of dialysis. Early recognition of adverse trends in the pre-dialysis period may create opportunity to intervene to improve early dialysis outcomes., (© 2017 International Society for Hemodialysis.)

Background: The prevalence of depressive affect is not well defined in the incident hemodialysis (HD) population. We investigated the prevalence of and associated risk factors and hospitalization rates for depressive affect in incident HD patients., Methods: We performed a prospective investigation using the Patient Health Questionnaire 2 (PHQ2) depressive affect assessment. From January to July of 2013 at 108 in-center clinics randomly selected across tertiles of baseline quality measures, we contacted 577 and 543 patients by telephone for depressive affect screening. PHQ2 test scores range from 0 to 6 (scores  ≥3 suggest the presence of depressive affect). The prevalence of depressive affect was measured at 1-30 and 121-150 days after initiating HD; depressive affect risk factors and hospitalization rates by depressive affect status at 1-30 days after starting HD were computed., Results: Of 1120 contacted patients, 340 completed the PHQ2. In patients screened at 1-30 or 121-150 days after starting HD, depressive affect prevalence was 20.2% and 18.5%, respectively (unpaired t -test, P = 0.7). In 35 patients screened at both time points, there were trends for lower prevalence of depressive affect at the end of incident HD, with 20.0% and 5.7% of patients positive for depressive affect at 1-30 and 121-150 days, respectively (paired t -test, P = 0.1). Hospitalization rates were higher in patients with depressive affect during the first 30 days, exhibiting 1.5 more admissions (P < 0.001) and 10.5 additional hospital days (P = 0.008) per patient-year. Females were at higher risk for depressive affect at 1-30 days (P = 0.01)., Conclusions: The prevalence of depressive affect in HD patients is high throughout the incident period. Rates of hospital admissions and hospital days are increased in incident HD patients with depressive affect.