Research Articles

Karin Bergling, Peter J Blankestijn

Online hemodiafiltration (OL-HDF) and medium cut-off (MCO) dialyzers augment diffusion-based hemodialysis (HD) with convective clearance to enhance removal of middle molecules. In large-scale randomized trials, OL-HDF appears to reduce all-cause, cardiovascular, and infection related mortality compared to high-flux HD, particularly when convection volumes exceed 23 L per session. Data suggests a graded effect; higher achieved convection volumes are associated with greater benefit, and advantages are observed across analysed subgroups. Evidence also indicates better preservation of patient-reported quality of life compared to high-flux HD. Large-scale observational registry data, while subject to inherent limitations, support beneficial outcomes and generalizability to routine clinical practice. MCO membranes enhance middle-molecule clearance on conventional hemodialysis machines via enlarged pore size and internal-filtration-back filtration. However, long-term clinical data remain limited, and the convective component is not externally measured or prescribed. This perspective distils mechanistic and clinical insights on both OL-HDF and MCO HD and evaluates published evidence, including solute clearance studies, mortality outcomes and patient-reported quality-of-life data. We outline actionable prescription strategies and opportunities for individualized treatment optimization. Our goal is to provide clinicians with a concise roadmap to personalize and integrate convection-enhancing therapies in everyday practice.

Xin Wang, Syed Zaidi, Cindy Chan, Yan Yi Cheung, Nadja Grobe, Peter Kotanko, Sandip Mitra, Milind Nikam

RESULTSWe studied 44 patients (26 males, age 68.0 ± 13.4 years, 34 Caucasians, 21 with diabetes), of whom 28 (63.6%) experienced successful fistula maturation. Metabolomic profiles with 2768 features were correlated with maturation outcomes. Lasso logistic regression identified six metabolites associated with maturation outcomes, with an area under the receiver operating characteristics curve of 0.917 (95% CI: 0.833-1.000). These metabolites are linked to cellular energy production and inflammation, offering new insights into AVF maturation biology. Importantly, our findings remained robust after adjusting for clinical and demographic variables.CONCLUSIONSSix metabolites identified in plasma samples collected prior to arteriovenous fistula creation were associated with subsequent vascular access maturation outcomes. If validated in larger studies, these biomarkers could aid personalized vascular access planning and inform research into potential novel therapeutic targets.BACKGROUNDArteriovenous fistulas are the preferred vascular access for most hemodialysis patients; however, poor maturation rates limit their widespread adoption. Here, we investigated plasma metabolites as potential biomarkers associated with fistula maturation outcomes before fistula creation.METHODSWe conducted untargeted metabolomics on plasma samples collected before fistula creation surgery in patients from the Manchester Vascular Access Study, a prospective observational study of the natural history of newly created fistulas. Successful fistula maturation was defined as either adequate hemodialysis using the newly created fistula, or a combination of ultrasound criteria (fistula diameter >4 mm with a blood flow ⩾ 500 mL/min) and clinical assessment. Metabolomics data were analyzed via unsupervised cluster analysis, and Lasso logistic regression was employed to assess associations between metabolites and fistula maturation outcomes.

Armin Ahmadi, Subhasis Dasgupta, Maggie Han, Peter Kotanko, Rakesh Malhotra

No abstract available

Jonathan P Dyke, Hasib Absar, Mark Kakembo, Zijun Dong, Lin-Chun Wang, Xiaoling Wang, Sarah Ren, Benjamin Cobb, Silvina P Dutruel, Nadja Grobe, Peter Kotanko

No abstract available

Hailey Yetman, Huei Hsun Wen, Lin-Chun Wang, Zijun Dong, Lela Tisdale, Yvette Foby, Carol R Horowitz, Len Usvyat, Jennifer Scherer, Stephan Thijssen, Peter Kotanko, Steven Coca, Girish Nadkarni, Lili Chan

No abstract available

Vladimir Rigodon, Murilo Guedes, Peter G Pecoits, Brianna Hartley, Yue Jiao, Len A Usvyat, Dinesh K Chatoth, Jeffrey L Hymes, Franklin W Maddux, Jeroen Kooman, Thyago P Moraes, Jochen G Raimann, Peter Kotanko, John W Larkin, Roberto Pecoits-Filho

Background and objectivesIron plays a critical role beyond erythropoiesis, yet the prognostic significance of iron deficiency (ID) independent of anemia remains poorly defined in the peritoneal dialysis (PD) population. This study aimed to evaluate the association between iron status, specifically transferrin saturation (TSAT), and mortality in PD patients, independent of hemoglobin levels.Design, setting, participants, and measurementsWe conducted a retrospective cohort study of 11,013 adults who initiated PD at a large US dialysis network between December 2004 and January 2011. Patients had at least 180 days on PD and baseline data on TSAT, ferritin, hemoglobin, albumin, and white blood cell count. The primary outcome was all-cause mortality. Broadly adjusted associations between iron parameters and mortality were assessed using Cox proportional hazards models and restricted cubic splines, with adjustments for demographic, clinical, treatment-related, and laboratory variables including hemoglobin and ESA use.ResultsIron deficiency, defined as TSAT ≤20%, was present in 10% of patients at PD initiation. The cohort was 54% male and 70% Caucasian, with a mean age of 55 years; 39% had diabetes. While 91% received erythropoiesis-stimulating agents, only 34% received IV iron. After comprehensive adjustment, TSAT ≤20% remained independently associated with increased mortality (adjusted HR: 1.26; 95% CI: 1.12-1.42). Spline analyses showed a sharp rise in mortality risk at TSAT levels below 25%. Ferritin was inconsistently associated with mortality risk. During follow-up, 2704 deaths occurred (24.6% of the cohort) over a median 440-day follow-up.ConclusionsIron deficiency is common in incident PD patients and is associated with increased mortality risk, independent of anemia. These findings challenge current anemia-centric treatment paradigms and suggest that iron status, particularly TSAT, should be routinely assessed in PD patients regardless of hemoglobin levels. A prospective, randomized trial is warranted to evaluate whether proactive iron management improves outcomes in this population.

Richard J Gray, Sheetal Chaudhuri, Hao Han, John Larkin, Murat Sor, Gregg M Miller

Background Ports have traditionally been inserted in hospitalized inpatients; however, there has been an increasing transition to outpatient placement by interventionalists in hospital imaging suites. To our knowledge, port implantation in nonhospital settings has not been reported in peer-reviewed literature. Here, we report our experience with port placement in freestanding outpatient vascular centers. Methodology The electronic medical record for 47 centers was retrospectively searched to identify port placements between January 1, 2012, and December 31, 2018. Data included indications, platelet inhibitor/anticoagulants, American Society of Anesthesiologists (ASA) classification, port type, site, tip position, peri-procedure medications, procedure time, and pain scores. Complications were determined by phone calls at 48-72 hours. Results No short-term malfunctions were reported. In total, 5,890 ports were placed for chemotherapy (n = 5,531), IV therapy (n = 77), antibiotics (n = 74), hyperalimentation (n = 19), phlebotomy (n = 7), medications (n = 4), miscellaneous (n = 74), and unknown (n = 104). Regarding ASA classifications, 1% (n = 65) were categorized as Class I, 20% (n = 1,203) as Class II, 78% (n = 4,592) as Class III, and 0.5% (n = 30) as Class IV. Overall, 3,712 were single-lumen power ports, 341 dual-lumen, 19 unknown, 7 arm, 1 other, and 1,810 were unspecified. There were 5,855 chest, 19 arm, 1 thigh, and 15 unspecified ports. Tips were positioned in the superior vena cava (n = 1,582), superior vena cava-right atrium (n = 497), right atrium (n = 272), inferior vena cava (n = 2), inferior vena cava-right atrium (n = 1), or not specified (n = 3,536). The mean procedure time was 29 minutes (range = 6-137). The mean peak pain score was 0.86 (range = 0-10). Complications (n = 33) included 16 emergency/hospital admissions <24 hours for port-site bleeding (2), infection (1), pneumothorax (1), EKG changes (1), respiratory symptoms (3), tachycardia (2), unconfirmed infection (1), fall (1), chest pain (1), syncope (1), pain (1), or other (1). Furthermore, 17 Other complications included unrelated/unconfirmed infection (4), death <30 days (1), shortness of breath (1), infection (1), reversal agent (1), hypoglycemia (1), fall (1), and other (7). No leaks were reported. Conclusions According to the study findings, port placement in outpatient centers appears to be safe and provides short-term effectiveness.

Afschin Gandjour, Dana Kendzia, Kevin Ho, Doris H Fuertinger, Carsten Hornig, Christian Apel, Jovana Petrovic Vorkapic

This study aimed to evaluate the cost-effectiveness and financial impact of an anemia management tool (AMT)-a software system that uses real-time blood volume and hemoglobin monitoring data-for adult patients receiving in-center hemodialysis (HD) in the United States. A Markov cohort model was developed to estimate lifetime costs and health outcomes for 1000 in-center HD patients with and without use of AMT. Clinical input parameters, including hemoglobin stability and dose reduction of erythropoiesis-stimulating agents (ESAs), were derived from a randomized controlled trial. The net monetary benefit (NMB) was calculated from the Medicare perspective, while a net financial impact analysis (NFIA) estimated provider-level savings based on ESA dose reductions, Quality Incentive Program (QIP)-related payment adjustments, and implementation costs. From the Medicare perspective, AMT yielded a positive NMB of $8419 per patient over a lifetime and remained cost-effective at a threshold of $2443 per patient per year. The NFIA showed an annual per-patient profit of $218. For a dialysis facility with 70 patients, this corresponds to an annual profit of $15,251. In conclusion, AMT is cost-effective from the Medicare perspective and financially beneficial for providers. Broader adoption may be supported by value-based reimbursement mechanisms and risk-sharing agreements to address residual uncertainties.

Yan Zhang, Anke Winter, Linda H Ficociello, Belén Alejos Ferrera, Paola Carioni, Christian Apel, Otto Arkossy, Michael Anger, Robert Kossmann, Len A Usvyat, Stefano Stuard

No abstract available

Vincent Peters, Niels Verhoeven, Wendy van der Valk, Dennis Hulsen, Karin Gerritsen, Dennis van der Schrier, Thijs de Graaf, Frank van der Sande, Bram Kamps, Wim de Jong, Constantijn Konings, Barend Schouten, Peter Kotanko, Len Usvyat, John Larkin

RESULTSFive decommissioning strategies were identified: disposal, donation, reuse, sale and recycling/trade-in. Substantial variability and limited formalization in these strategies were observed across and within hospitals. Economic consequences included repair costs, depreciation and resale value. Social consequences were important, yet typically secondary. Environmental consequences were recognized but rarely formalized, although indirect environmental benefits from economically driven repair activities were acknowledged.CONCLUSIONSDecommissioning strategies for hemodialysis machines in Dutch hospitals do not use formalized guidelines and are still predominantly shaped by economic drivers. The recognition that each decommissioning strategy entails distinct economic, social and environmental consequences highlights the need for more balanced decision-making. By embedding sustainability principles into hospital policies and standardizing decommissioning procedures, hospitals can move toward more circular and responsible dialysis care.BACKGROUNDThe decommissioning of hemodialysis machines, particularly in the context of transitioning from hemodialysis to hemodiafiltration, remains understudied despite its importance for sustainable healthcare. This study evaluates decommissioning strategies for hemodialysis machines used by Dutch hospitals, analyzing the economic, social and environmental consequences.METHODSA qualitative, exploratory study was conducted through semi-structured interviews with 15 professionals from 11 Dutch hospitals that retired hemodialysis machines. The analysis focused on understanding decommissioning strategies and their economic, social and environmental consequences.

Samir C Gautam, Alaa S Awad, Vandana Dua Niyyar, Jennifer E Flythe, Emaad M Abdel-Rahman, Jochen G Raimann, Jobira A Woldemichael, Hiba I Sheikh, Raman Gaurav, Peter Kotanko, Xiwei Yang, Nihan Gencerliler, Jasmin Divers, Mariana Murea

SUPPLEMENTARY INFORMATIONThe online version contains supplementary material available at 10.1186/s12882-025-04659-2.TRIAL REGISTRATIONNCT05828823.DISCUSSIONThis layered monitoring model balances feasibility, safety, and fidelity in a pragmatic trial where provider engagement and site-specific adaptation were essential. The monitoring approach adopted in TwoPlus will inform the design of monitoring frameworks for future pragmatic nephrology trials.METHODS/DESIGNTwoPlus is an ongoing multicenter RCT enrolling adults initiating chronic hemodialysis with residual kidney function (urine urea clearance ≥ 2.0 mL/min and urine output ≥ 500 mL/24 hours). Participants are randomized to incremental hemodialysis—twice-weekly treatment supported by diuretics and sodium bicarbonate, with transition to thrice-weekly as clinically indicated—or conventional thrice-weekly initiation. The primary outcome is a composite of all-cause death, hospitalization, or emergency department visits. Secondary outcomes include preservation of residual kidney function and treatment adherence. The monitoring framework combines automated dialysis data downloads, manual data abstraction, assessments conducted by investigators or clinical research coordinators and reviewed at the site level, structured team reviews, and regular communication with treating providers.BACKGROUNDPragmatic randomized controlled trials (RCTs) must be embedded within routine clinical workflows, which require monitoring strategies that are feasible in everyday practice. Incremental hemodialysis—initiating treatment twice weekly in patients with preserved residual kidney function and escalating frequency as needed—differs from conventional thrice-weekly initiation. Implementing this approach in a pragmatic trial among providers and dialysis staff unfamiliar with incremental dialysis necessitated additional preparation and oversight. The TwoPlus trial is a multicenter pragmatic RCT evaluating incremental versus conventional initiation of chronic hemodialysis. We describe the patient monitoring framework developed for TwoPlus, which integrates digital infrastructure, human touchpoints, and provider engagement to ensure participant safety.

Nicole E Sieck, Menglu Liang, Hyeonjin Song, Hao He, Jochen G Raimann, Raul Cruz, Ross J Salawitch, Amy R Sapkota, Frank W Maddux, Len A Usvyat, Peter Kotanko, Amir Sapkota

RESULTSThe cumulative lag 0-3 risk of hospitalization associated with heat exposure was highest in the West (rate ratio [RR]: 1.099; 95% confidence interval [CI]: 1.041, 1.160), whereas the highest risk of mortality was observed in the Northwest region (RR: 1.097; 95% CI: 1.007, 1.195). We observed significant increases in the risk of hospitalization at the low- and mid-latitude bands and a significant increase in the risk of mortality in the mid-latitude band.CONCLUSIONWe observed spatial heterogeneity across US climate regions. The strongest effects of heat exposure were observed in the Ohio Valley, South, and West regions for hospitalization and the Upper Midwest, Southeast, and Northwest regions for mortality. Findings may be used to inform targeted interventions to patients with ESKD residing in areas with higher risks of adverse health outcomes following heat exposure.BACKGROUNDThe impact of heat exposure on patients with end-stage kidney disease (ESKD) is of growing concern in the context of climate change. In this study, we investigated the association of heat exposure with hospitalization and mortality, and how the risk of these adverse health outcomes varied by climate region in the US.METHODSWe obtained hospitalization and mortality data for patients with ESKD receiving in-center hemodialysis treatment between 2012 and 2018 at Fresenius Kidney Care facilities located within the contiguous US. We used the treatment facility location to assign heat exposure using maximum universal thermal climate index temperature data. We conducted a space-time-stratified case-crossover study using conditional Poisson regression with distributed lag nonlinear models to examine the effects of heat exposure at the 95th percentile of the region-specific temperature distribution for lags of three days. Stratified analyses were run to assess differences in associations across nine climate regions and three latitude bands.

Hanjie Zhang, Lin-Chun Wang, Sheetal Chaudhuri, Aaron Pickering, Len Usvyat, John Larkin, Pete Waguespack, Zuwen Kuang, Jeroen P Kooman, Franklin W Maddux, Peter Kotanko

RESULTSWe 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.CONCLUSIONSReal-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.BACKGROUNDIn 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.METHODSWe 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.

Mariana Murea, Kristie L Foley, Samir C Gautam, Jennifer E Flythe, Jochen G Raimann, Emaad Abdel-Rahman, Alaa S Awad, Vandana Dua Niyyar, Cassandra Kovach, Glenda V Roberts, Nicole M Jefferson, Paul T Conway, Laura M Rosales, Jobira Woldemichael, Hiba I Sheikh, Gaurav Raman, Anne M Huml, Daphne H Knicely, Irtiza Hasan, Bhaktidevi Makadia, Janice Lea, John T Daugirdas, Nihan Gencerliler, Jasmin Divers, Peter Kotanko, Ucheoma C Nwaozuru

METHODS AND ANALYSISWe will use the Consolidated Framework for Implementation Research (CFIR) and the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) frameworks to inform process evaluation. Mixed methods include surveys conducted with treating providers (physicians) and dialysis personnel (nurses and dialysis administrators); semi-structured interviews with patient participants, caregivers of patient participants, treating providers (physicians and advanced practice practitioners), dialysis personnel (nurses, dieticians and social workers); and focus group meetings with study investigators and stakeholder partners. Data will be collected on the following implementation determinants: (a) organisational readiness to change, intervention acceptability and appropriateness; (b) inner setting characteristics underlying barriers and facilitators to the adoption of HD intervention at the enrollment centres; (c) external factors that mediate implementation; (d) adoption; (e) reach; (f) fidelity, to assess adherence to serial timed urine collection and HD treatment schedule; and (g) sustainability, to assess barriers and facilitators to maintaining intervention. Qualitative and quantitative data will be analysed iteratively and triangulated following a convergent parallel and pragmatic approach. Mixed methods analysis will use qualitative data to lend insight to quantitative findings. Process evaluation is important to understand factors influencing trial outcomes and identify potential contextual barriers and facilitators for the potential implementation of incremental-start HD into usual workflows in varied outpatient dialysis clinics and clinical practices. The process evaluation will help interpret and contextualise the trial clinical outcomes' findings.ETHICS AND DISSEMINATIONThe study protocol was approved by the Wake Forest University School of Medicine Institutional Review Board (IRB). Findings from this study will be disseminated through peer-reviewed journals and scientific conferences.TRIAL REGISTRATION NUMBERNCT05828823.INTRODUCTIONProcess evaluation provides insight into how interventions are delivered across varying contexts and why interventions work in some contexts and not in others. This manuscript outlines the protocol for a process evaluation embedded in a hybrid type 1 effectiveness-implementation randomised clinical trial of incremental-start haemodialysis (HD) versus conventional HD delivered to patients starting chronic dialysis (the TwoPlus Study). The trial will simultaneously assess the effectiveness of incremental-start HD in real-world settings and the implementation strategies needed to successfully integrate this intervention into routine practice. This manuscript describes the rationale and methods used to capture how incremental-start HD is implemented across settings and the factors influencing its implementation success or failure within this trial.

Peter Stenvinkel, Peter Kotanko, Johanna Painer-Gigler, Paul G Shiels, Pieter Evenepoel, Leon Schurgers, Barbara Natterson-Horowitz, Szilvia Kalogeropoulu, Joshua Schiffman, Richard J Johnson

This review explores the remarkable metabolic adaptations of species that thrive in extreme environments, providing insights into their resilience, flexibility and disease resistance. Species such as hibernating brown bears, migratory birds, cavefish, Greenland sharks and naked mole rats exhibit unique metabolic traits that challenge conventional paradigms of metabolic regulation. These adaptations, including resistance to hypoxia and metabolic ageing, offer potential solutions to human metabolic disorders, including obesity, type 2 diabetes and CVD. Insights from comparative physiology, particularly the mechanisms by which animals cope with food scarcity, extreme temperatures and hypoxia, could help identify novel therapeutic targets for advancing human health. For example, hibernation can serve as a model for understanding metabolic diseases, providing insights into reversible insulin resistance and energy homeostasis. This review also highlights the impact of environmental stressors, including climate change, on these species, which may jeopardise their survival despite their resilience. Accelerating anthropogenic environmental change threatens even the most resilient animal species. We call for a holistic approach to conservation and environmental protection to preserve these species and the valuable lessons they offer for managing our metabolic health.

Peter Kotanko, David Alonzo Poole, Beatriz Akemi Kondo Van Spitzenbergen, Nadja Grobe, Paul Jennings, Andrea Novais Moreno-Amaral

No abstract available

Luca Neri, Hanjie Zhang, Len A Usvyat

PURPOSE OF REVIEWArtificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, but their adoption in nephrology and dialysis remains relatively limited.SUMMARYAI in nephrology shows promise for personalized care and cost reduction, as demonstrated by tools like the Anemia Control Model. Yet, broad adoption requires rigorous validation, seamless workflow integration, regulatory clearance, and clinician trust. Future opportunities include digital twins, large language models, and multiomics integration, with AI poised to enhance both patient outcomes and system performance.RECENT FINDINGSThis review highlights key applications of AI in kidney disease, including prognostic modeling, imaging, personalized anemia and fluid management, patient engagement, and research acceleration. While numerous studies demonstrate improved prediction accuracy and clinical insights, translation into routine practice is rare. Examples such as the Anemia Control Model (ACM) demonstrate that AI can simultaneously improve clinical outcomes and reduce costs, though widespread adoption will require rigorous validation, seamless integration into clinical workflows, regulatory approval, and above all, clinician trust.

Navdeep Tangri, Wisit Cheungpasitporn, Stanley D Crittenden, Alessia Fornoni, Carmen A Peralta, Karandeep Singh, Len A Usvyat, Amy D Waterman

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and generative AI technologies. To meet this challenge, the American Society of Nephrology convened an AI Workgroup to provide a framework for the responsible use of AI in nephrology. The group outlines foundational principles to guide AI development: prioritizing patient benefit, ensuring clinician oversight, and advancing innovation in high-burden disease areas. Its set of foundational assumptions are grounded in the physician always being in the loop and an overarching goal to benefit patients with kidney diseases. This review provides an overview of the clinical uses of AI in nephrology and offers practical guidance for nephrologists seeking to incorporate AI into CKD and AKI management, dialysis, and transplantation care. It also highlights key challenges-such as data quality, equity, transparency, and clinical integration-that must be addressed to ensure the responsible and effective implementation of AI in kidney care.

Jochen G Raimann, Yoshitsugu Obi

No abstract available

Melanie Wolf, Yue Jiao, Kaitlyn Croft, Carly Hahn Contino, Justin Zimbelman, Kanti Singh, Mitesh Soni, Andrew Dickinson, Jeroen P Kooman, Dinesh Chatoth, Adrian Guinsburg, Stefano Stuard, Milind Nikam, Michelle Carver, Len Usvyat, Franklin W Maddux, Sheetal Chaudhuri, John Larkin

RESULTSApollo captures data from January 2018 to March 2021 from 40 countries and 543,169 patients worldwide (4.6% in Asia-Pacific [AP], 13.9% in Europe, Middle East, and Africa [EMEA], 7.0% in Latin America [LA], and 74.5% in North America [NA]). It contains demographic data, 35,874,039 laboratory, and 140,016,249 treatment observations as well as frequently recorded medication information, and clinical outcomes (e.g., hospitalization and mortality). Several regional differences can be observed using these data, such as age, treatment modality, and treatment time.CONCLUSIONCreating a robust multinational dialysis database offers vast opportunities to conduct real-world research and data analytics, including the development of artificial intelligence models. These activities hold promise of advancing the understanding of kidney disease and dialysis therapies. It can serve as comparative resource for the nephrology community.INTRODUCTIONLarge amounts of data are captured during dialysis, yet multinational datasets are scarce because of challenges in harmonizing and integrating clinical data, as well as complying with data protection regulations across the world. A global kidney care provider, Fresenius Medical Care, approached this challenge and finalized the creation of an anonymized dialysis database, coined ApolloDialDb (Apollo). We report on the approach used for database creation and detail dialysis patient characteristics globally.METHODSTo create this globally distributed multinational database, data from different electronic clinical systems were extracted, covering routinely collected medical information from dialysis clinics worldwide. This data were harmonized, and then anonymized following a reidentification risk assessment conducted by the external company Privacy Analytics, Ontario, Canada. The data was consolidated and is stored in a central cloud environment and will be updated periodically.

Maggie Han, Frank M van der Sande, Jeroen P Kooman, Xia Tao, Priscila Preciado, Lela Tisdale, Ohnmar Thwin, Peter Kotanko

RESULTSA total of 109 patients on hemodialysis were included (mean age 54 ± 11.6 years, 72% male, 23% diabetic). The observed number of steps was 6590 ± 4014 (mean ± standard deviation) per day; 44 (40%) participants walked <5000 steps/day. Participants walked 912 (95% confidence interval 768, 1057) fewer steps on Sundays and 284 (129, 440) fewer on the second interdialytic day vs dialysis day. Winter activity was reduced by 321 (162, 478) to 455 (312, 598) steps compared with other seasons. Older age, diabetes and higher equilibrated Kt/V were associated with lower physical activity levels; higher albumin was associated with increased physical activity levels.CONCLUSIONMost hemodialysis patients walked less than recommended level of 10 000 steps/day and physical activity levels vary greatly between and within patients. Dialysis-imposed, weekly and seasonal patterns affect physical activity. Lower physical activity levels on second interdialytic days and Sundays could provide opportunities for improvements of physical activity in shared the decision-making process.BACKGROUNDHemodialysis patients are often sedentary, and their life is structured around the dialysis schedule. Wearable activity trackers present an opportunity for long-term continuous monitoring of physical activity. We aimed to characterize dialysis-imposed, weekly and seasonal patterns of physical activity in hemodialysis patients.METHODSIn this prospective observational study, patients on in-center hemodialysis in New York City wore the Fitbit® Charge 2™ for 1 year. Physical activity was assessed by weekday, dialysis versus interdialytic days (post-hemodialysis day and second interdialytic day), dialysis start time and season. Linear mixed-effects models with random intercepts between patient were constructed to determine the effect of time-patterns and determinants of physical activity levels.

Beatriz Akemi Kondo Van Spitzenbergen, Gabriela Bohnen Andrade, Erika Sousa Dias, Júlia Bacarin Monte Alegre, Gabriela Ferreira Dias, Nadja Grobe, Andrea Novais Moreno-Amaral, Peter Kotanko

RESULTSIncubation of RBCs with CMPF and Jedi1 significantly increased RBC osmotic fragility, an effect prevented by GsMTx-4. At 6.0 g/L NaCl, incubation with CMPF and Jedi1 increased exposure of phosphatidylserine and elevated icCa2+ levels of RBCs, indicating increased eryptosis. Notably, at an isotonic NaCl concentration of 9.0 g/L, CMPF-but not Jedi1-significantly increased RBC phosphatidylserine exposure and icCa2+ levels; both effects were diminished by GsMTx-4.BACKGROUND AND HYPOTHESISIn patients with advanced CKD the lifespan of red blood cells (RBCs) is often shortened, a condition attributed to the 'uremic milieu.' We reported recently that the uremic solute 3-carboxy-4-methyl-5-propyl-2-furanpropionate (CMPF) shares structural similarities with Jedi1, a chemical activator of the mechanosensitive cation channel PIEZO1, whose activation increases calcium influx into cells. Against this backdrop, we hypothesized that CMPF may induce premature RBC death (eryptosis) through prolonged CMPF-induced activation of PIEZO1 located on RBCs. To test this hypothesis, we explored if CMPF, at concentrations found in uremia, interacts with PIEZO1 located on RBCs, increases intracellular calcium (icCa2+), and induces eryptosis.CONCLUSIONOur findings support the hypothesis that CMPF may function as an endogenous activator of PIEZO1, increase icCa2+ levels, trigger eryptosis, and, through this pathway, possibly shorten the RBC lifespan. To what extent these in vitro findings are operative in advanced CKD warrants clinical studies.METHODSRBCs from healthy individuals were incubated with CMPF or Jedi1 (both at a concentration of 87 µM), in the presence or absence of the PIEZO1 inhibitor GsMTx-4 (2 µM). We challenged RBCs osmotically through incubation in solutions of NaCl at concentrations between 3.0 and 9.0 g/L and determined their osmotic fragility. Using flow cytometry, we quantified in incubated RBCs icCa2+ levels and phosphatidylserine exposure, a cellular marker of eryptosis.

Xiaoling Wang, Nadja Grobe, Colleen Fisher, Kylie Colvin, Chih-Hu Ho, Peter Kotanko

Removal of middle-sized uremic toxins is one goal of hemodialysis. However, dialysis membranes are nonselective, raising the specter that salutary proteins may also be removed. To better understand the spectrum of proteins filtered by medium cut-off (MCO) and high-flux membranes, we conducted quantitative analyses of proteins in ultrafiltrates. We developed an ex vivo system that allows us to concurrently compare two dialyzers under the same conditions, using the same plasma source. We used this system to study the ultrafiltrate protein loss of two high-flux (Fresenius Optiflux F180NRe, USA; Fresenius FX CorAL80, Germany) and one MCO dialyzer (Baxter Theranova 400, Germany). Ultrafiltrates underwent analysis including gel electrophoresis, quantitative proteomics using liquid chromatography-tandem mass spectrometry, and immunoassays. We identified 244 proteins and semiquantified 113 of them, all of which were more prevalent in MCO compared with high-flux ultrafiltrate (MCO/Optiflux: median 8.25-fold; MCO/CorAL: median 9.14-fold). The protein distribution in MCO ultrafiltrate was skewed toward higher molecular mass. Notably, the ultrafiltered proteins include some with putative salutary functions. In conclusion, our data consistently show a higher protein loss with MCO membrane compared with high-flux dialyzers. The extent to which biological functions are impacted by the removal of proteins warrants bioinformatic analyses and clinical studies.

Stephan Thijssen, Lemuel Rivera Fuentes, Leticia Mirell Tapia Silva, Xiaoling Ye, Sabrina Casper, Doris H Fuertinger, Stefan Fuertinger, Peter Kotanko

RESULTSFifteen subjects (age 59±15 years, eight men) were studied during a total of 63 treatments. The controller functioned as intended and issued a total of 1037 recommendations. Compared with standard-of-care treatments, its use was associated with a higher probability of RBV target range attainment (69% versus 47%) and lower nadir systolic (106 versus 111 mm Hg) and diastolic (55 versus 59 mm Hg) BP.KEY POINTSThe ultrafiltration rate feedback controller functioned as intended, improving relative blood volume target attainment over standard care. Predialytic, postdialytic, and mean intradialytic BPs were not statistically different between treatments with versus without controller usage. Intradialytic nadir BP was on average slightly lower with use of the controller (106 versus 111 mm Hg systolic).CONCLUSIONSThe UFR feedback controller operated as intended, and its use led to a substantial increase in the rate of RBV target range attainment. This technology holds promise for improving fluid management in chronic hemodialysis patients.BACKGROUNDRelative blood volume (RBV) monitors are increasingly being used during hemodialysis. Manual ultrafiltration rate (UFR) adjustments to establish a favorable RBV trajectory are not feasible in routine practice. The goal of this study was to characterize the behavior of a new UFR feedback controller in vivo.METHODSIn this pilot trial, chronic hemodialysis patients were prospectively studied during up to six successful study dialysis treatments each. During each study visit, the feedback controller generated UFR recommendations designed to guide the subject's RBV curve toward a predefined target trajectory. Each recommendation was evaluated by licensed health care staff and then either implemented or disregarded. The results were compared with standard-of-care treatments in the same subjects.

Terry Ketchersid, Dinesh K Chatoth, Robert J Kossmann, Chance Mysayphonh, Peter Kotanko, Franklin W Maddux

This Festschrift in honor of Dr. Jeffrey Hymes, a distinguished leader in nephrology and a pioneer in the field of dialysis care. Dr. Hymes' career has been marked by his unwavering commitment to improving patient outcomes through innovative approaches and data-driven insights. His contributions have not only advanced the practice of nephrology but have also had a profound impact on the lives of countless patients.

Fansan Zhu, Laura Rosales Merlo, Lela Tisdale, Maricar Villarama, Jun Yi, Zahin Haq, Xiaoling Wang, Nadja Grobe, Karsten Fischer, Kulwinder Plahey, Richard A Lasher, Paul Chamney, Brigitte Schiller, Peter Kotanko

Monitoring intraperitoneal pressure (IPP) offers valuable insights into changes of intraperitoneal volume (IPV) during peritoneal dialysis (PD). This study aims to investigate the relationship between IPV and IPP during a PD dwell. Thirteen patients were studied during a 2-h dwell using 2 L of dialysate containing 2.5% dextrose. IPP was measured using a pressure sensor integrated into an automated PD cycler. IPV was monitored concurrently by segmental bioimpedance (Hydra 4200). The density (ρ) of the PD dialysate was measured using a meter, and the creatinine and glucose concentrations in both dialysate (D) and serum (P) were measured pre- and post-PD dwell. A physical model (IPP = ρ × g × h), was used to describe the relationship between IPP and IPV, where h is the apparent dialysate height and g is the gravitational acceleration. The change in IPP (ΔIPP, -21.2 ± 18%) was mainly determined by the change of h (Δh, -20.9 ± 18.5%), while the change ρ (Δρ, -0.34 ± 0.06%), was minor. The study demonstrated an association between ΔIPP and the ratio of D/P creatinine and D/D0 glucose, suggesting that ΔIPP may reflect membrane transport characteristics. Due to its noninvasive and seamless nature, the clinical utility of PD cycler-based measurement of IPP warrants further exploration.

Hanjie Zhang, Andrea Nandorine Ban, Peter Kotanko

RESULTSWe analyzed 4,075 consecutive 5-minute segments from 89 hemodialysis treatments in 22 hemodialysis patients. While 891 (21.9%) segments showed saw-tooth pattern, 3,184 (78.1%) did not. In the test data set, the rate of correct SaO2 pattern classification was 96% with an area under the receiver operating curve of 0.995 (95% CI: 0.993 to 0.998).CONCLUSIONOur 1D-CNN algorithm accurately classifies SaO2 saw-tooth pattern. The SaO2 pattern classification can be performed in real time during an ongoing hemodialysis treatment, provide timely alert in the event of respiratory instability or sleep apnea, and trigger further diagnostic and therapeutic interventions.BACKGROUNDMaintenance hemodialysis patients experience high morbidity and mortality, primarily from cardiovascular and infectious diseases. It was discovered recently that low arterial oxygen saturation (SaO2) is associated with a pro-inflammatory phenotype and poor patient outcomes. Sleep apnea is highly prevalent in maintenance hemodialysis patients and may contribute to intradialytic hypoxemia. In sleep apnea, normal respiration patterns are disrupted by episodes of apnea because of either disturbed respiratory control (i.e., central sleep apnea) or upper airway obstruction (i.e., obstructive sleep apnea). Intermittent SaO2 saw-tooth patterns are a hallmark of sleep apnea. Continuous intradialytic measurements of SaO2 provide an opportunity to follow the temporal evolution of SaO2 during hemodialysis. Using artificial intelligence, we aimed to automatically identify patients with repetitive episodes of intermittent SaO2 saw-tooth patterns.METHODSThe analysis utilized intradialytic SaO2 measurements by the Crit-Line device (Fresenius Medical Care, Waltham, MA). In patients with an arterio-venous fistula as vascular access, this FDA approved device records 150 SaO2 measurements per second in the extracorporeal blood circuit of the hemodialysis system. The average SaO2 of a 10-second segment is computed and streamed to the cloud. Periods comprising thirty 10-second segments (i.e., 300 s or five minutes) were independently adjudicated by two researchers for the presence or absence of SaO2 saw-tooth pattern. We built one-dimensional convolutional neural networks (1D-CNN), a state-of-the-art deep learning method, for SaO2 pattern classification and randomly assigned SaO2 time series segments to either a training (80%) or a test (20%) set.

Hyeonjin Song, Menglu Liang, Nicole E Sieck, Huang Lin, Jochen Raimann, Frank W Maddux, Priya Desai, Evan Andrew Ellicott, Xin He, Quynh Nguyen, Xin-Zhong Liang, Peter Kotanko, Amir Sapkota

RESULTSThe highest daily wildfire-related PM2.5 concentration observed (251.1 μg/m3) far exceeded the National Ambient Air Quality Standard (35 μg/m3). The presence of wildfire smoke plume was associated with an 18% increase in risk of same day (lag0) all-cause mortality (rate ratio [RR]:1.18; 95% confidence interval [CI], 1.13-1.24) and a 3% increase in risk of all-cause hospitalization (RR:1.03; 95% CI: 1.00-1.07). A 10 μg/m3 increase in wildfire-related PM2.5 was associated with a 139% increase in same day all-cause mortality (RR: 2.39; 95% CI: 1.79-3.18), and a 33% increase in all-cause hospitalization (RR:1.33; 95% CI: 1.10-1.62).CONCLUSIONOur findings suggest that air pollution from the 2023 Canadian wildfires resulted in increased risk of mortality and hospitalization among hemodialysis patients in Eastern and Midwestern USA.INTRODUCTIONSmoke plumes from the 2023 Canadian wildfires severely impacted air quality across the Eastern and Midwestern USA. However, a comprehensive health impact assessment is lacking in this large region. We investigated the association between wildfire-related air pollutants and the risk of mortality and hospitalization among hemodialysis patients in 22 heavily impacted states in the Eastern and Midwestern USA.METHODSWe conducted a retrospective observational study using a time-stratified case-crossover analysis with a conditional quasi-Poisson model. The study included 52,995 patients with end-stage kidney disease (ESKD) receiving hemodialysis at Fresenius Kidney Care clinics during June and July 2023. The presence of wildfire smoke and fine particulate matter (with aerodynamic diameter < 2.5 microns, PM2.5) concentrations were assessed using satellite-derived smoke polygons and ground-based monitors. Daily number of all-cause deaths, all-cause hospitalizations, respiratory disease hospitalizations, and cardiovascular disease hospitalizations were counted for each hemodialysis clinic.

Karin Bergling, Lin-Chun Wang, Oshini Shivakumar, Andrea Nandorine Ban, Linda W Moore, Nancy Ginsberg, Jeroen Kooman, Neill Duncan, Peter Kotanko, Hanjie Zhang

Large language models (LLMs) such as ChatGPT are increasingly positioned to be integrated into various aspects of daily life, with promising applications in healthcare, including personalized nutritional guidance for patients with chronic kidney disease (CKD). However, for LLM-powered nutrition support tools to reach their full potential, active collaboration of healthcare professionals, patients, caregivers and LLM experts is crucial. We conducted a comprehensive review of the literature on the use of LLMs as tools to enhance nutrition recommendations for patients with CKD, curated by our expertise in the field. Additionally, we considered relevant findings from adjacent fields, including diabetes and obesity management. Currently, the application of LLMs for CKD-specific nutrition support remains limited and has room for improvement. Although LLMs can generate recipe ideas, their nutritional analyses often underestimate critical food components such as electrolytes and calories. Anticipated advancements in LLMs and other generative artificial intelligence (AI) technologies are expected to enhance these capabilities, potentially enabling accurate nutritional analysis, the generation of visual aids for cooking and identification of kidney-healthy options in restaurants. While LLM-based nutritional support for patients with CKD is still in its early stages, rapid advancements are expected in the near future. Engagement from the CKD community, including healthcare professionals, patients and caregivers, will be essential to harness AI-driven improvements in nutritional care with a balanced perspective that is both critical and optimistic.

Maggie Han, Frank M van der Sande, Jeroen P Kooman, Xia Tao, Priscila Preciado, Lela Tisdale, Ohnmar Thwin, Peter Kotanko

RESULTSOne hundred nine patients contributed data (age 54±12 years, 73% male, 23% diabetic). Sleep duration was 276±91 minutes; 102 (94%) patients slept on average less than the recommended 420 minutes per night. On dialysis days, participants slept 55 (95% confidence interval [CI], 51 to 59) and 48 (95% CI, 43 to 54) minutes less compared with postdialysis and second interdialytic days, respectively. Early starters slept on average 40 (95% CI, 6 to 74) minutes less compared with late starters. On dialysis days, early starters slept 86 (95% CI, 55 to 118) minutes less compared with late starters. We observed greater sleep–wake disturbance in early starters. Irrespective of dialysis schedule, patients slept on average 26 (95% CI, 19 to 33) to 32 (95% CI, 24 to 40) minutes longer on Sundays. In winter, sleep was 7 (95% CI, 1 to 13) to 10 (95% CI, 5 to 16) minutes shorter. In multivariate analysis, higher BP and higher serum creatinine were significantly associated with shorter sleep duration.KEY POINTSPatients on hemodialysis do not sleep enough, and there is large variation in the sleep duration among them. Dialysis timing plays a major role in sleep duration; morning shift is associated with decreased sleep duration on the day of dialysis. Patients on hemodialysis sleep the longest on Sundays compared with other days of the week and irrespective of the dialysis schedule.CONCLUSIONSOn average, patients on hemodialysis slept less than the recommended amount of time. The timing of hemodialysis treatment has pronounced effects on sleep duration and could be considered in patient care.PODCASTThis article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/K360/2025_05_29_KID0000000761.mp3BACKGROUNDIn patients on hemodialysis, the effects of determinants of sleep duration are not widely studied. Using wearable activity trackers, we aimed to characterize natural and hemodialysis-imposed temporal patterns of nocturnal sleep.METHODSIn this yearlong prospective observational study, patients on in-center hemodialysis were equipped with activity trackers (Fitbit Charge 2). Nocturnal sleep duration was assessed according to dialysis start time (early starters: before 8 AM; late starters: others), dialysis versus interdialytic days (postdialysis day and second interdialytic day), weekdays, and seasons. Clinical, laboratory, and hemodialysis treatment data were extracted from electronic medical records. Linear mixed-effects models were constructed to determine the effect of various time patterns and predictors of nocturnal sleep duration.

Yan Zhang, Anke Winter, Belén Alejos Ferreras, Paola Carioni, Otto Arkossy, Michael Anger, Robert Kossmann, Len A Usvyat, Stefano Stuard, Franklin W Maddux

RESULTSAt 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.CONCLUSIONSOur 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.BACKGROUNDResults 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.METHODSIn 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.

Lin-Chun Wang, Hanjie Zhang

No abstract available

Jaime Uribarri, Murilo Guedes, Maria Ines Diaz Bessone, Lili Chan, Andres de la Torre, Ariella Mermelstein, Guillermo Garcia-Garcia, Jochen Raimann, Thyago Moraes, Vincent Peters, Constantijn Konings, Douglas Farrell, Shuchita Sharma, Adrian Guinsburg, Peter Kotanko

RESULTSThere were 16,796 incident PD patients analyzed. Age, body mass index, sex, PD modality, Kt/V, and CrCl, as well as serum phosphorus, varied significantly across the different cohorts, but >70% had residual renal function. For most cohorts, both CrCl total and urea Kt/V associated negatively with serum phosphorus levels, and log-likelihood ratio tests demonstrate that models including CrCltotal have more predictive information than those including only urea Kt/V for the largest cohorts. Models including CrCltotal increase information predicting longitudinal serum phosphorus levels irrespective of baseline urea Kt/V, age, use of phosphorus binder, and sex.KEY POINTSThis is a retrospective observational multinational peritoneal dialysis study to test whether creatinine clearance could be a better marker of serum phosphorus than urea Kt/V. Creatinine clearance was not more accurate predicting serum phosphorus than urea Kt/V, but its inclusion in multivariable models added more clarity. In conclusion, using both biomarkers, instead of just one, may better assist in the optimization of serum phosphorus levels.CONCLUSIONSCrCl was not more accurate in predicting serum phosphorus than urea Kt/V, but its inclusion in multivariable models predicting serum phosphorus added accuracy. In conclusion, both CrCl and Kt/V are associated with phosphorus levels, and using both biomarkers, instead of just one, may better assist in the optimization of serum phosphorus levels.BACKGROUNDHyperphosphatemia is associated with poor outcome and is still very common in peritoneal dialysis (PD) patients. Because peritoneal phosphorus clearance is closer to peritoneal creatinine clearance (CrCl) than urea clearance, we hypothesized that weekly CrCl could be a better marker of serum phosphorus in PD.METHODSIn a retrospective observational study, data from adult PD patients were collected across five institutions in North and South America: Fresenius Medical Care Latin America, Renal Research Institute, Mount Sinai Hospital, Hospital Civil de Guadalajara, and the Brazil PD cohort. All centers analyzed routinely available laboratory data, with exclusions for missing data on serum phosphorus, CrCl, or urea Kt/V. A unified statistical protocol was used across centers. Linear mixed-effect models examined associations between longitudinal serum phosphorus levels, CrCl, and Kt/V. Adjustments were made for age, sex, and baseline phosphorus binder usage. Mixed-effects meta-analysis determined the pooled effect size of CrCl and Kt/V on serum phosphorus trajectories, adjusted for confounders.

Lihao Xiao, Hanjie Zhang, Juntao Duan, Xiaoran Ma, Len A Usvyat, Peter Kotanko, Yuedong Wang

COVID-19 has a higher rate of morbidity and mortality among dialysis patients than the general population. Identifying infected patients early with the support of predictive models helps dialysis centers implement concerted procedures (e.g., temperature screenings, universal masking, isolation treatments) to control the spread of SARS-CoV-2 and mitigate outbreaks. We collect data from multiple sources, including demographics, clinical, treatment, laboratory, vaccination, socioeconomic status, and COVID-19 surveillance. Previous early prediction models, such as logistic regression, SVM, and XGBoost, require sophisticated feature engineering and need improved prediction performance. We create deep learning models, including Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), to predict SARS-CoV-2 infections during incubation. Our study shows deep learning models with minimal feature engineering can identify those infected patients more accurately than previously built models. Our Long Short-Term Memory (LSTM) model consistently performed well, with an AUC exceeding 0.80, peaking at 0.91 in August 2021. The CNN model also demonstrated strong results with an AUC above 0.75. Both models outperformed previous best XGBoost models by over 0.10 in AUC. Prediction accuracy declined as the pandemic evolved, dropping to approximately 0.75 between September 2021 and January 2022. Maintaining a 20% false positive rate, our LSTM and CNN models identified 66% and 64% of positive cases among patients, significantly outperforming XGBoost models at 42%. We also identify key features for dialysis patients by calculating the gradient of the output with respect to the input features. By closely monitoring these factors, dialysis patients can receive earlier diagnoses and care, leading to less severe outcomes. Our research highlights the effectiveness of deep neural networks in analyzing longitudinal data, especially in predicting COVID-19 infections during the crucial incubation period. These deep network approaches surpass traditional methods relying on aggregated variable means, significantly improving the accurate identification of SARS-CoV-2 infections.

Laura Rosales Merlo, Xiaoling Ye, Hanjie Zhang, Brenda Chan, Marilou Mateo, Seth Johnson, Frank M van der Sande, Jeroen P Kooman, Peter Kotanko

RESULTSThe QIP group comprised 44 patients (59 ± 17 years), the concurrent control group 48 patients (59 ± 16 years), the historic control group 57 patients (58 ± 15 years). Six-month post-AVF creation, the fraction of non-censored patients with catheter in place was 21% in the QIP cohort, 67% in the concurrent control group, and 68% in the historic control group. In unadjusted and adjusted analysis, catheter residence time post-fistula creation was shorter in QIP patients compared to either control groups (p < 0.001).CONCLUSIONScvO2-based assessment of fistula maturation is associated with shorter catheter residence post-AVF creation.INTRODUCTIONArteriovenous fistula (AVF) maturation assessment is essential to reduce venous catheter residence. We introduced central venous oxygen saturation (ScvO2) and estimated upper body blood flow (eUBBF) to monitor newly created fistula maturation and recorded catheter time in patients with and without ScvO2-based fistula maturation.METHODSFrom 2017 to 2019, we conducted a multicenter quality improvement project (QIP) in hemodialysis patients with the explicit goal to shorten catheter residence time post-AVF creation through ScvO2-based maturation monitoring. In patients with a catheter as vascular access, we tracked ScvO2 and eUBBF pre- and post-AVF creation. The primary outcome was catheter residence time post-AVF creation. We compared catheter residence time post-AVF creation between QIP patients and controls. One control group comprised concurrent patients; a second control group comprised historic controls (2014-2016). We conducted Kaplan-Meier analysis and constructed a Cox proportional hazards model with variables adjustment to assess time-to-catheter removal.

Vaibhav Maheshwari, Maria Esther Díaz-González de Ferris, Guido Filler, Peter Kotanko

Severe Neonatal Jaundice (SNJ) causes long-term neurocognitive impairment, cerebral palsy, auditory neuropathy, deafness, or death. We developed a mathematical model for allo-hemodialysis as a potential blood purification method for the treatment of SNJ in term or near-term infants. With allo-hemodialysis (allo-HD), the neonate's blood flows through hollow fibers of a miniature 0.075 m2 hemodialyzer, while the blood of a healthy adult ("buddy") flows counter-currently through the dialysate compartment. We simulated the kinetics of unconjugated bilirubin in allo-hemodialysis with neonate blood flow rates of 12.5 and 15 mL/min (for a 2.5 kg and 3.5 kg neonate, respectively), and 30 mL/min for the buddy. Bilirubin production rates in neonate and buddy were set to 6 and 3 mg/kg/day, respectively. Buddy bilirubin conjugation rate was calculated to obtain normal steady-state bilirubin levels. Albumin levels were set to 1.1, 2.1, 3.1 g/dL for the neonate and 3.3 g/dL for the buddy. Model simulations suggest that a 6-h allo-hemodialysis session could reduce neonatal bilirubin levels by > 35% and that this modality would be particularly effective with low neonatal serum albumin levels. Due to the high bilirubin conjugation capacity of an adult's healthy liver and the larger distribution volume, the buddy's bilirubin level increases only transiently during allo-hemodialysis. Our modelling suggests that a single allo-hemodialysis session may lower neonatal unconjugated bilirubin levels effectively. If corroborated in ex-vivo, animal, and clinical studies, this bilirubin reduction could lower the risks associated with SNJ, especially kernicterus, and possibly avoiding the morbidity associated with exchange transfusions.

Lin-Chun Wang, Hanjie Zhang, Nancy Ginsberg, Andrea Nandorine Ban, Jeroen P Kooman, Peter Kotanko

OBJECTIVESThe rising diversity of food preferences and the desire to provide better personalized care provide challenges to renal dietitians working in dialysis clinics. To address this situation, we explored the use of a large language model, specifically, ChatGPT using the GPT-4 model (openai.com), to support nutritional advice given to dialysis patients.RESULTSChatGPT generated a daily menu with five recipes. The renal dietitian rated the recipes at 3 (3, 3) [median (Q1, Q3)], the cooking instructions at 5 (5,5), and the nutritional analysis at 2 (2, 2) on the five-point Likert scale. ChatGPT's nutritional analysis underestimated calories by 36% (95% CI: 44-88%), protein by 28% (25-167%), fat 48% (29-81%), phosphorus 54% (15-102%), potassium 49% (40-68%), and sodium 53% (14-139%). The nutritional analysis of online available recipes differed only by 0 to 35%. The translations were rated as reliable by native speakers (4 on the five-point Likert scale).CONCLUSIONWhile ChatGPT-4 shows promise in providing personalized nutritional guidance for diverse dialysis patients, improvements are necessary. This study highlights the importance of thorough qualitative and quantitative evaluation of artificial intelligence-generated content, especially regarding medical use cases.METHODSWe tasked ChatGPT-4 with generating a personalized daily meal plan, including nutritional information. Virtual "patients" were generated through Monte Carlo simulation; data from a randomly selected virtual patient were presented to ChatGPT. We provided to ChatGPT patient demographics, food preferences, laboratory data, clinical characteristics, and available budget, to generate a one-day sample menu with recipes and nutritional analyses. The resulting daily recipe recommendations, cooking instructions, and nutritional analyses were reviewed and rated on a five-point Likert scale by an experienced renal dietitian. In addition, the generated content was rated by a renal dietitian and compared with a U. S. Department of Agriculture-approved nutrient analysis software. ChatGPT also analyzed nutrition information of two recipes published online. We also requested a translation of the output into Spanish, Mandarin, Hungarian, German, and Dutch.

Bernard Canaud, Jeroen P Kooman, Nicholas M Selby, Maarten Taal, Andreas Maierhofer, Pascal Kopperschmidt, Susan Francis, Allan Collins, Peter Kotanko

The development of maintenance hemodialysis (HD) for end stage kidney disease patients is a success story that continues to save many lives. Nevertheless, intermittent renal replacement therapy is also a source of recurrent stress for patients. Conventional thrice weekly short HD is an imperfect treatment that only partially corrects uremic abnormalities, increases cardiovascular risk, and exacerbates disease burden. Altering cycles of fluid loading associated with cardiac stretching (interdialytic phase) and then fluid unloading (intradialytic phase) likely contribute to cardiac and vascular damage. This unphysiologic treatment profile combined with cyclic disturbances including osmotic and electrolytic shifts may contribute to morbidity in dialysis patients and augment the health burden of treatment. As such, HD patients are exposed to multiple stressors including cardiocirculatory, inflammatory, biologic, hypoxemic, and nutritional. This cascade of events can be termed the dialysis stress storm and sickness syndrome. Mitigating cardiovascular risk and morbidity associated with conventional intermittent HD appears to be a priority for improving patient experience and reducing disease burden. In this in-depth review, we summarize the hidden effects of intermittent HD therapy, and call for action to improve delivered HD and develop treatment schedules that are better tolerated and associated with fewer adverse effects.

Zijun Dong, Lemuel Rivera Fuentes, Sharon Rao, Peter Kotanko

While life-sustaining, hemodialysis is a non-physiological treatment modality that exerts stress on the patient, primarily due to fluid shifts during ultrafiltration. Automated feedback control systems, integrated with sensors that continuously monitor bio-signals such as blood volume, can adjust hemodialysis treatment parameters, e.g., ultrafiltration rate, in real-time. These systems hold promise to mitigate hemodynamic stress, prevent intradialytic hypotension, and improve the removal of water and electrolytes in chronic hemodialysis patients. However, robust evidence supporting their clinical application remains limited. Based on an extensive literature research, we assess feedback-controlled ultrafiltration systems that have emerged over the past three decades in comparison to conventional hemodialysis treatment. We identified 28 clinical studies. Closed loop ultrafiltration control demonstrated effectiveness in 23 of them. No adverse effects of closed loop ultrafiltration control were reported across all trials. Closed loop ultrafiltration control represents an important advancement towards more physiological hemodialysis. Its development is driven by innovations in real-time bio-signals monitoring, advancement in control theory, and artificial intelligence. We expect these innovations will lead to the prevalent adoption of ultrafiltration control in the future, provided its clinical value is substantiated in adequately randomized controlled trials.

Xiaoran Ma, Wensheng Guo, Mengyang Gu, Len Usvyat, Peter Kotanko, Yuedong Wang

Some patients with COVID-19 show changes in signs and symptoms such as temperature and oxygen saturation days before being positively tested for SARS-CoV-2, while others remain asymptomatic. It is important to identify these subgroups and to understand what biological and clinical predictors are related to these subgroups. This information will provide insights into how the immune system may respond differently to infection and can further be used to identify infected individuals. We propose a flexible nonparametric mixed-effects mixture model that identifies risk factors and classifies patients with biological changes. We model the latent probability of biological changes using a logistic regression model and trajectories in the latent groups using smoothing splines. We developed an EM algorithm to maximize the penalized likelihood for estimating all parameters and mean functions. We evaluate our methods by simulations and apply the proposed model to investigate changes in temperature in a cohort of COVID-19-infected hemodialysis patients.

Yoshitsugu Obi, Jochen G Raimann, Kamyar Kalantar-Zadeh, Mariana Murea

Individuals afflicted with advanced kidney dysfunction who require dialysis for medical management exhibit different degrees of native kidney function, called residual kidney function (RKF), ranging from nil to appreciable levels. The primary focus of this manuscript is to delve into the concept of RKF, a pivotal yet under-represented topic in nephrology. To begin, we unpack the definition and intrinsic nature of RKF. We then juxtapose the efficiency of RKF against that of hemodialysis in preserving homeostatic equilibrium and facilitating physiological functions. Given the complex interplay of RKF and overall patient health, we shed light on the extent of its influence on patient outcomes, particularly in those living with advanced kidney dysfunction and on dialysis. This manuscript subsequently presents methodologies and measures to assess RKF, concluding with the potential benefits of targeted interventions aimed at preserving RKF.

Mariana Murea, Jochen G Raimann, Jasmin Divers, Harvey Maute, Cassandra Kovach, Emaad M Abdel-Rahman, Alaa S Awad, Jennifer E Flythe, Samir C Gautam, Vandana D Niyyar, Glenda V Roberts, Nichole M Jefferson, Islam Shahidul, Ucheoma Nwaozuru, Kristie L Foley, Erica J Trembath, Merlo L Rosales, Alison J Fletcher, Sheikh I Hiba, Anne Huml, Daphne H Knicely, Irtiza Hasan, Bhaktidevi Makadia, Raman Gaurav, Janice Lea, Paul T Conway, John T Daugirdas, Peter Kotanko

TRIAL REGISTRATIONClinicaltrials.gov NCT05828823. Registered on 25 April 2023.DISCUSSIONOur proposal challenges the status quo of HD care delivery. Our overarching hypothesis posits that CMIHD is non-inferior to CHD. If successful, the results will positively impact one of the highest-burdened patient populations and their caregivers.BACKGROUNDMost patients starting chronic in-center hemodialysis (HD) receive conventional hemodialysis (CHD) with three sessions per week targeting specific biochemical clearance. Observational studies suggest that patients with residual kidney function can safely be treated with incremental prescriptions of HD, starting with less frequent sessions and later adjusting to thrice-weekly HD. This trial aims to show objectively that clinically matched incremental HD (CMIHD) is non-inferior to CHD in eligible patients.METHODSAn unblinded, parallel-group, randomized controlled trial will be conducted across diverse healthcare systems and dialysis organizations in the USA. Adult patients initiating chronic hemodialysis (HD) at participating centers will be screened. Eligibility criteria include receipt of fewer than 18 treatments of HD and residual kidney function defined as kidney urea clearance ≥3.5 mL/min/1.73 m2 and urine output ≥500 mL/24 h. The 1:1 randomization, stratified by site and dialysis vascular access type, assigns patients to either CMIHD (intervention group) or CHD (control group). The CMIHD group will be treated with twice-weekly HD and adjuvant pharmacologic therapy (i.e., oral loop diuretics, sodium bicarbonate, and potassium binders). The CHD group will receive thrice-weekly HD according to usual care. Throughout the study, patients undergo timed urine collection and fill out questionnaires. CMIHD will progress to thrice-weekly HD based on clinical manifestations or changes in residual kidney function. Caregivers of enrolled patients are invited to complete semi-annual questionnaires. The primary outcome is a composite of patients' all-cause death, hospitalizations, or emergency department visits at 2 years. Secondary outcomes include patient- and caregiver-reported outcomes. We aim to enroll 350 patients, which provides ≥85% power to detect an incidence rate ratio (IRR) of 0.9 between CMIHD and CHD with an IRR non-inferiority of 1.20 (α = 0.025, one-tailed test, 20% dropout rate, average of 2.06 years of HD per patient participant), and 150 caregiver participants (of enrolled patients).

Vaibhav Maheshwari, Nadja Grobe, Xin Wang, Amrish Patel, Alhaji Cherif, Xia Tao, Joshua Chao, Alexander Heide, Dejan Nikolic, Jiaming Dong, Peter Kotanko

It has been estimated that in 2010, over two million patients with end-stage kidney disease may have faced premature death due to a lack of access to affordable renal replacement therapy, mostly dialysis. To address this shortfall in dialytic kidney replacement therapy, we propose a novel, cost-effective, and low-complexity hemodialysis method called allo-hemodialysis (alloHD). With alloHD, instead of conventional hemodialysis, the blood of a patient with kidney failure flows through the dialyzer's dialysate compartment counter-currently to the blood of a healthy subject (referred to as a "buddy") flowing through the blood compartment. Along the concentration and hydrostatic pressure gradients, uremic solutes and excess fluid are transferred from the patient to the buddy and subsequently excreted by the healthy kidneys of the buddy. We developed a mathematical model of alloHD to systematically explore dialysis adequacy in terms of weekly standard urea Kt/V. We showed that in the case of an anuric child (20 kg), four 4 h alloHD sessions are sufficient to attain a weekly standard Kt/V of >2.0. In the case of an anuric adult patient (70 kg), six 4 h alloHD sessions are necessary. As a next step, we designed and built an alloHD machine prototype that comprises off-the-shelf components. We then used this prototype to perform ex vivo experiments to investigate the transport of solutes, including urea, creatinine, and protein-bound uremic retention products, and to quantitate the accuracy and precision of the machine's ultrafiltration control. These experiments showed that alloHD performed as expected, encouraging future in vivo studies in animals with and without kidney failure.

Doris H Fuertinger, Lin-Chun Wang, David J Jörg, Lemuel Rivera Fuentes, Xiaoling Ye, Sabrina Casper, Hanjie Zhang, Ariella Mermelstein, Alhaji Cherif, Kevin Ho, Jochen G Raimann, Lela Tisdale, Peter Kotanko, Stephan Thijssen

RESULTSThe intervention group showed an improved median percentage of hemoglobin measurements within target at 47% (interquartile range, 39–58), with a 10% point median difference between the two groups (95% confidence interval, 3 to 16; P = 0.008). The odds ratio of being within the hemoglobin target in the standard-of-care group compared with the group receiving the personalized ESA recommendations was 0.68 (95% confidence interval, 0.51 to 0.92). The variability of hemoglobin levels decreased in the intervention group, with the percentage of patients experiencing fluctuating hemoglobin levels being 45% versus 82% in the standard-of-care group. ESA usage was reduced by approximately 25% in the intervention group.KEY POINTSWe conducted a randomized controlled pilot trial in patients on hemodialysis using a physiology-based individualized anemia therapy assistance software. Patients in the group receiving erythropoiesis-stimulating agent dose recommendations from the novel software showed improvement in hemoglobin stability and erythropoiesis-stimulating agent utilization.CONCLUSIONSOur results demonstrated an improved hemoglobin target attainment and variability by using personalized ESA recommendations using the physiology-based anemia therapy assistance software.CLINICAL TRIAL REGISTRATION NUMBER:NCT04360902.BACKGROUNDAnemia is common among patients on hemodialysis. Maintaining stable hemoglobin levels within predefined target levels can be challenging, particularly in patients with frequent hemoglobin fluctuations both above and below the desired targets. We conducted a multicenter, randomized controlled trial comparing our anemia therapy assistance software against a standard population-based anemia treatment protocol. We hypothesized that personalized dosing of erythropoiesis-stimulating agents (ESAs) improves hemoglobin target attainment.METHODSNinety-six patients undergoing hemodialysis and receiving methoxy polyethylene glycol-epoetin beta were randomized 1:1 to the intervention group (personalized ESA dose recommendations computed by the software) or the standard-of-care group for 26 weeks. The therapy assistance software combined a physiology-based mathematical model and a model predictive controller designed to stabilize hemoglobin levels within a tight target range (10–11 g/dl). The primary outcome measure was the percentage of hemoglobin measurements within the target. Secondary outcome measures included measures of hemoglobin variability and ESA utilization.

Amun G Hofmann, Suman Lama, Hanjie Zhang, Afshin Assadian, Murat Sor, Jeffrey Hymes, Peter Kotanko, Jochen Raimann

RESULTSIn total, 38 151 patients (52.2%) had complete data and made up the main cohort. Sensitivity analyses were conducted in 67 421 patients (92.3%) after eliminating variables with a high proportion of missing data points. Selected features diverged between datasets and workflows. A previously failed arteriovenous access appeared to be the most stable predictor for subsequent failure. Prediction of re-conversion based on the demographic and clinical information resulted in an area under the receiver operating characteristic curve (ROCAUC) between 0.541 and 0.571, whereas models predicting all cause mortality performed considerably better (ROCAUC 0.662 - 0.683).OBJECTIVEThe decision to convert from catheter to arteriovenous access is difficult yet very important. The ability to accurately predict fistula survival prior to surgery would significantly improve the decision making process. Many previously investigated demographic and clinical features have been associated with fistula failure. However, it is not conclusively understood how reliable predictions based on these parameters are at an individual level. The aim of this study was to investigate the probability of arteriovenous fistula maturation and survival after conversion using machine learning workflows.CONCLUSIONWhile group level depiction of major adverse outcomes after catheter to arteriovenous fistula or graft conversion is possible using the included variables, patient level predictions are associated with limited performance. Factors during and after fistula creation as well as biomolecular and genetic biomarkers might be more relevant predictors of fistula survival than baseline clinical conditions.METHODSA retrospective cohort study on multicentre data from a large North American dialysis organisation was conducted. The study population comprised 73 031 chronic in centre haemodialysis patients. The dataset included 49 variables including demographic and clinical features. Two distinct feature selection and prediction pipelines were used: LASSO regression and Boruta followed by a random forest classifier. Predictions were facilitated for re-conversion to catheter within one year. Additionally, all cause mortality predictions were conducted to serve as a comparator.

Bernard Canaud, Andrew Davenport, Hélène Leray-Moragues, Marion Morena-Carrere, Jean Paul Cristol, Jeroen Kooman, Peter Kotanko

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments.

Marcus Dariva, Murilo Guedes, Vladimir Rigodon, Peter Kotanko, John W Larkin, Bruno Ferlin, Roberto Pecoits-Filho, Pasqual Barretti, Thyago Proença de Moraes

RESULTSWe analysed data of 848 patients (814 starting on CAPD and 34 starting on APD). The SBP decreased by 4 (SD 22) mmHg when transitioning from CAPD to APD (p < 0.001) and increased by 4 (SD 21) mmHg when transitioning from APD to CAPD (p = 0.38); consistent findings were seen for DBP. There was no significant change in the number of antihypertensive drugs prescribed before and after transition.CONCLUSIONSTransition between PD modalities seems to directly impact on BP levels. Further studies are needed to confirm if switching to APD could be an effective treatment for uncontrolled hypertension among CAPD patients.BACKGROUNDHypertension is a leading cause of kidney failure, affects most dialysis patients and associates with adverse outcomes. Hypertension can be difficult to control with dialysis modalities having differential effects on sodium and water removal. There are two main types of peritoneal dialysis (PD), automated peritoneal dialysis (APD) and continuous ambulatory peritoneal dialysis (CAPD). It is unknown whether one is superior to the other in controlling blood pressure (BP). Therefore, the aim of our study was to analyse the impact of switching between these two PD modalities on BP levels in a nationally representative cohort.METHODSThis was a cohort study of patients on PD from 122 dialysis centres in Brazil (BRAZPD II study). Clinical and laboratory data were collected monthly throughout the study duration. We selected all patients who remained on PD at least 6 months and 3 months on each modality at minimum. We compared the changes in mean systolic/diastolic blood pressures (SBP/DBP) before and after modality transition using a multilevel mixed-model where patients were at first level and their clinics at the second level.

Sunpeng Duan, Yuedong Wang, Peter Kotanko, Hanjie Zhang

RESULTSOut of 978 patients, 193 (19.7%) tested positive for COVID-19 and had contact with other patients during the COV-Pos infectious period. Network diagrams showed no evidence that more exposed patients would have had a higher chance of infection. This finding was corroborated by logistic mixed effect regression (donor-to-potential recipient exposure OR: 0.63; 95% CI 0.32 to 1.17, p = 0.163). Separate analyses according to vaccination led to materially identical results.CONCLUSIONSTransmission of SARS-CoV-2 between in-center hemodialysis patients is unlikely. This finding supports the effectiveness of non-pharmaceutical interventions, such as universal masking and other procedures to control spread of COVID-19.BACKGROUNDIn-center hemodialysis entails repeated interactions between patients and clinic staff, potentially facilitating the spread of COVID-19. We examined if in-center hemodialysis is associated with the spread of SARS-CoV-2 between patients.METHODSOur retrospective analysis comprised all patients receiving hemodialysis in four New York City clinics between March 12th, 2020, and August 31st, 2022. Treatment-level clinic ID, dialysis shift, dialysis machine station, and date of COVID-19 diagnosis by RT-PCR were documented. To estimate the donor-to-potential recipient exposure ("donor" being the COVID-19 positive patient denoted as "COV-Pos"; "potential recipient" being other susceptible patients in the same shift), we obtained the spatial coordinates of each dialysis station, calculated the Euclidean distances between stations and weighted the exposure by proximity between them. For each donor, we estimated the donor-to-potential recipient exposure of all potential recipients dialyzed in the same shift and accumulated the exposure over time within the 'COV-Pos infectious period' as cumulative exposures. The 'COV-Pos infectious period' started 5 days before COVID-19 diagnosis date. We deployed network analysis to assess these interactions and summarized the donor-to-potential recipient exposure in 193 network diagrams. We fitted mixed effects logistic regression models to test whether more donor-to-potential recipient exposure conferred a higher risk of SARS-CoV-2 infection.

Susie Q Lew, Gulay Asci, Paul A Rootjes, Ercan Ok, Erik L Penne, Ramin Sam, Antonios H Tzamaloukas, Todd S Ing, Jochen G Raimann

The relationship between sodium, blood pressure and extracellular volume could not be more pronounced or complex than in a dialysis patient. We review the patients' sources of sodium exposure in the form of dietary salt intake, medication administration, and the dialysis treatment itself. In addition, the roles dialysis modalities, hemodialysis types, and dialysis fluid sodium concentration have on blood pressure, intradialytic symptoms, and interdialytic weight gain affect patient outcomes are discussed. We review whether sodium restriction (reduced salt intake), alteration in dialysis fluid sodium concentration and the different dialysis types have any impact on blood pressure, intradialytic symptoms, and interdialytic weight gain.

Ana Catalina Alvarez-Elias, Barry M Brenner, Valerie A Luyckx

PURPOSE OF REVIEWThe consequences of climate change, including heat and extreme weather events impact kidney function in adults and children. The impacts of climate change on kidney development during gestation and thereby on kidney function later in life have been poorly described. Clinical evidence is summarized to highlight possible associations between climate change and nephron mass.SUMMARYClimate change has important impacts on pregnant women and their unborn children. Being born too small or too soon is associated with life-time risk of kidney disease. Climate change may therefore have a dual effect of impacting fetal kidney development and contributing to cumulative postnatal kidney injury. The impact on population kidney health of future generations may be significant.RECENT FINDINGSPregnant women are vulnerable to the effects of climate change, being less able to thermoregulate, more sensitive to the effects of dehydration, and more susceptible to infections. Exposure to heat, wildfire smoke, drought, floods and climate-related infections are associated with low birth weight, preterm birth and preeclampsia. These factors are associated with reduced nephron numbers, kidney dysfunction and higher blood pressures in offspring in later life. Exposure to air pollution is associated with higher blood pressures in children and has variable effects on estimated glomerular filtration rate.

Xiaoling Wang, Ohnmar Thwin, Zahin Haq, Zijun Dong, Lela Tisdale, Lemuel Rivera Fuentes, Nadja Grobe, Peter Kotanko

RESULTSMask and saliva testing specificities were 99% and 100%, respectively. Test sensitivity was 62% for masks, and 81% for saliva (p = 0.16). Median viral RNA shedding duration was 11 days and longer in immunocompromised versus non-immunocompromised patients (22 vs. 11 days, p = 0.06, log-rank test).CONCLUSIONWhile SARS-CoV-2 testing on worn masks appears to be less sensitive compared to saliva, it may be a preferred screening method for individuals who are mandated to wear masks yet averse to more invasive sampling. However, optimized RNA extraction methods and automated procedures are warranted to increase test sensitivity and scalability. We corroborated longer viral RNA shedding in immunocompromised patients.BACKGROUNDExhaled SARS-CoV-2 can be detected on face masks. We compared tests for SARS-CoV-2 RNA on worn face masks and matched saliva samples.METHODSWe conducted this prospective, observational, case-control study between December 2021 and March 2022. Cases comprised 30 in-center hemodialysis patients with recent COVID-19 diagnosis. Controls comprised 13 hemodialysis patients and 25 clinic staff without COVID-19 during the study period and the past 2 months. Disposable 3-layer masks were collected after being worn for 4 hours together with concurrent saliva samples. ThermoFisher COVID-19 Combo Kit (A47814) was used for RT-PCR testing.

Ercan Ok, Cenk Demirci, Gulay Asci, Kivanc Yuksel, Fatih Kircelli, Serkan Kubilay Koc, Sinan Erten, Erkan Mahsereci, Ali Rıza Odabas, Stefano Stuard, Franklin W Maddux, Jochen G Raimann, Peter Kotanko, Peter G Kerr, Christopher T Chan

RESULTSThe 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.CONCLUSIONThese results indicate that extended HHD is associated with higher survival and better outcomes compared to ICHD.INTRODUCTIONMore 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.METHODSWe 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.

Francesco Bellocchio, Hanjie Zhang

No abstract available

Zahin Haq, Xin Wang, Qiuqiong Cheng, Gabriela F Dias, Christoph Moore, Dorothea Piecha, Peter Kotanko, Chih-Hu Ho, Nadja Grobe

Bisphenol A (BPA)-based materials are used in the manufacturing of hemodialyzers, including their polycarbonate (PC) housings and polysulfone (PS) membranes. As concerns for BPA's adverse health effects rise, the regulation on BPA exposure is becoming more rigorous. Therefore, BPA alternatives, such as Bisphenol S (BPS), are increasingly used. It is important to understand the patient risk of BPA and BPS exposure through dialyzer use during hemodialysis. Here, we report the bisphenol levels in extractables and leachables obtained from eight dialyzers currently on the market, including high-flux and medium cut-off membranes. A targeted liquid chromatography-mass spectrometry strategy utilizing stable isotope-labeled internal standards provided reliable data for quantitation with the standard addition method. BPA ranging from 0.43 to 32.82 µg/device and BPS ranging from 0.02 to 2.51 µg/device were detected in dialyzers made with BPA- and BPS-containing materials, except for the novel FX CorAL 120 dialyzer. BPA and BPS were also not detected in bloodline controls and cellulose-based membranes. Based on the currently established tolerable intake (6 µg/kg/day), the resulting margin of safety indicates that adverse effects are unlikely to occur in hemodialysis patients exposed to BPA and BPS quantified herein. With increasing availability of new data and information about the toxicity of BPA and BPS, the patient safety limits of BPA and BPS in those dialyzers may need a re-evaluation in the future.

Peter Kotanko, Girish N Nadkarni

No abstract available

Armando Armenta-Alvarez, Salvador Lopez-Gil, Iván Osuna, Nadja Grobe, Xia Tao, Gabriela Ferreira Dias, Xiaoling Wang, Joshua Chao, Jochen G Raimann, Stephan Thijssen, Hector Perez-Grovas, Bernard Canaud, Peter Kotanko, Magdalena Madero

RESULTSTwelve anuric patients were studied (six female patients; 44±19 years; dialysis vintage 35.2±28 months). The blood flow was 369±23 ml/min, dialysate flow was 495±61 ml/min, and ultrafiltration volume was 2.8±0.74 L. No significant differences were found regarding the removal of B2M, vitamin B12, and water-soluble solutes between dialytic modalities and dialyzers. Albumin and total protein loss were significantly higher in MCO groups than HFX groups when compared with the same modality. HDF groups had significantly higher albumin and total protein loss than HD groups when compared with the same dialyzer. MCO-HDF showed the highest protein loss among all groups.KEY POINTSHDF and MCO have shown greater clearance of middle-size uremic solutes in comparison with HF dialyzers; MCO has never been studied in HDF. MCO in HDF does not increase the clearance of B2M and results in a higher loss of albumin.CONCLUSIONSMCO-HD is not superior to HFX-HD and HFX-HDF for both middle molecule and water-soluble solute removal. Protein loss was more pronounced with MCO when compared with HFX on both HD and HDF modalities. MCO-HDF has no additional benefits regarding better removal of B2M but resulted in greater protein loss than MCO-HD.BACKGROUNDMiddle molecule removal and albumin loss have been studied in medium cutoff (MCO) membranes on hemodialysis (HD). It is unknown whether hemodiafiltration (HDF) with MCO membranes provides additional benefit. We aimed to compare the removal of small solutes and β2-microglobulin (B2M), albumin, and total proteins between MCO and high-flux (HFX) membranes with both HD and HDF, respectively.METHODSThe cross-over study comprised 4 weeks, one each with postdilutional HDF using HFX (HFX-HDF), MCO (MCO-HDF), HD with HFX (HFX-HD), and MCO (MCO-HD). MCO and HFX differ with respect to several characteristics, including membrane composition, pore size distribution, and surface area (HFX, 2.5 m2; MCO, 1.7 m2). There were two study treatments per week, one after the long interdialytic interval and another midweek. Reduction ratios of vitamin B12, B2M, phosphate, uric acid, and urea corrected for hemoconcentration were computed. Dialysis albumin and total protein loss during the treatment were quantified from dialysate samples.

Priscila Preciado, Laura Rosales Merlo, Hanjie Zhang, Jeroen P Kooman, Frank M van der Sande, Peter Kotanko

DISCUSSIONConcurrent combined monitoring of intradialytic ScvO2 and RBV change may provide additional insights into a patient's circulatory status. Patients with low ScvO2 and small changes in RBV may represent a specifically vulnerable group of patients at particularly high risk for adverse outcomes, possibly related to poor cardiac reserve and fluid overload.INTRODUCTIONIn maintenance hemodialysis (HD) patients, low central venous oxygen saturation (ScvO2 ) and small decline in relative blood volume (RBV) have been associated with adverse outcomes. Here we explore the joint association between ScvO2 and RBV change in relation to all-cause mortality.FINDINGSBaseline comprised 5231 dialysis sessions in 216 patients. The median RBV change was -5.5% and median ScvO2 was 58.8%. During follow-up, 44 patients (20.4%) died. In the adjusted model, all-cause mortality was highest in patients with ScvO2 below median and RBV change above median (HR 6.32; 95% confidence interval [CI] 1.37-29.06), followed by patients with ScvO2 below median and RBV change below median (HR 5.04; 95% CI 1.14-22.35), and ScvO2 above median and RBV change above median (HR 4.52; 95% CI 0.95-21.36).METHODSWe conducted a retrospective study in maintenance HD patients with central venous catheters as vascular access. During a 6-month baseline period, Crit-Line (Fresenius Medical Care, Waltham, MA) was used to measure continuously intradialytic ScvO2 and hematocrit-based RBV. We defined four groups per median change of RBV and median ScvO2 . Patients with ScvO2 above median and RBV change below median were defined as reference. Follow-up period was 3 years. We constructed Cox proportional hazards model with adjustment for age, diabetes, and dialysis vintage to assess the association between ScvO2 and RBV and all-cause mortality during follow-up.

Juntao Duan, Hanmo Li, Xiaoran Ma, Hanjie Zhang, Rachel Lasky, Caitlin K Monaghan, Sheetal Chaudhuri, Len A Usvyat, Mengyang Gu, Wensheng Guo, Peter Kotanko, Yuedong Wang

CONCLUSIONAs found in our study, the dynamics of the prediction model are frequently changing as the pandemic evolves. County-level infection information and vaccination information are crucial for the success of early COVID-19 prediction models. Our results show that the proposed model can effectively identify SARS-CoV-2 infections during the incubation period. Prospective studies are warranted to explore the application of such prediction models in daily clinical practice.BACKGROUNDThe coronavirus disease 2019 (COVID-19) pandemic has created more devastation among dialysis patients than among the general population. Patient-level prediction models for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are crucial for the early identification of patients to prevent and mitigate outbreaks within dialysis clinics. As the COVID-19 pandemic evolves, it is unclear whether or not previously built prediction models are still sufficiently effective.METHODSWe developed a machine learning (XGBoost) model to predict during the incubation period a SARS-CoV-2 infection that is subsequently diagnosed after 3 or more days. We used data from multiple sources, including demographic, clinical, treatment, laboratory, and vaccination information from a national network of hemodialysis clinics, socioeconomic information from the Census Bureau, and county-level COVID-19 infection and mortality information from state and local health agencies. We created prediction models and evaluated their performances on a rolling basis to investigate the evolution of prediction power and risk factors.RESULTFrom April 2020 to August 2020, our machine learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.75, an improvement of over 0.07 from a previously developed machine learning model published by Kidney360 in 2021. As the pandemic evolved, the prediction performance deteriorated and fluctuated more, with the lowest AUROC of 0.6 in December 2021 and January 2022. Over the whole study period, that is, from April 2020 to February 2022, fixing the false-positive rate at 20%, our model was able to detect 40% of the positive patients. We found that features derived from local infection information reported by the Centers for Disease Control and Prevention (CDC) were the most important predictors, and vaccination status was a useful predictor as well. Whether or not a patient lives in a nursing home was an effective predictor before vaccination, but became less predictive after vaccination.

Ariella Mermelstein, Jochen G Raimann, Yuedong Wang, Peter Kotanko, John T Daugirdas

RESULTSIn the studied 396,358 patients, the average ultrafiltration rate in ml/h was related to postdialysis weight (W) in kg: 3W+330. Ultrafiltration rates associated with 20% or 40% higher weight-specific mortality risk were 3W+500 and 3W+630 ml/h, respectively, and were 70 ml/h higher in men than in women. Nineteen percent or 7.5% of patients exceeded ultrafiltration rates associated with a 20% or 40% higher mortality risk, respectively. Low ultrafiltration rates were associated with subsequent weight loss. Ultrafiltration rates associated with a given mortality risk were lower in high-body weight older patients and higher in patients on dialysis for more than 3 years.CONCLUSIONSUltrafiltration rates associated with various levels of higher mortality risk depend on body weight, but not in a 1:1 ratio, and are different in men versus women, in high-body weight older patients, and in high-vintage patients.BACKGROUNDWe hypothesized that the association of ultrafiltration rate with mortality in hemodialysis patients was differentially affected by weight and sex and sought to derive a sex- and weight-indexed ultrafiltration rate measure that captures the differential effects of these parameters on the association of ultrafiltration rate with mortality.METHODSData were analyzed from the US Fresenius Kidney Care (FKC) database for 1 year after patient entry into a FKC dialysis unit (baseline) and over 2 years of follow-up for patients receiving thrice-weekly in-center hemodialysis. To investigate the joint effect of baseline-year ultrafiltration rate and postdialysis weight on survival, we fit Cox proportional hazards models using bivariate tensor product spline functions and constructed contour plots of weight-specific mortality hazard ratios over the entire range of ultrafiltration rate values and postdialysis weights (W).

Richard V Remigio, Hyeonjin Song, Jochen G Raimann, Peter Kotanko, Frank W Maddux, Rachel A Lasky, Xin He, Amir Sapkota

RESULTSWe 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.CONCLUSIONSInclement 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.BACKGROUNDNonadherence 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.METHODSWe 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.

Nadja Grobe, Josef Scheiber, Hanjie Zhang, Christian Garbe, Xiaoling Wang

Omics applications in nephrology may have relevance in the future to improve clinical care of kidney disease patients. In a short term, patients will benefit from specific measurement and computational analyses around biomarkers identified at various omics-levels. In mid term and long term, these approaches will need to be integrated into a holistic representation of the kidney and all its influencing factors for individualized patient care. Research demonstrates robust data to justify the application of omics for better understanding, risk stratification, and individualized treatment of kidney disease patients. Despite these advances in the research setting, there is still a lack of evidence showing the combination of omics technologies with artificial intelligence and its application in clinical diagnostics and care of patients with kidney disease.

Jonathan S Chávez-Iñiguez, Jochen G Raimann

No abstract available

Karlien J Ter Meulen, Xiaoling Ye, Yuedong Wang, Len A Usvyat, Frank M van der Sande, Constantijn J Konings, Peter Kotanko, Jeroen P Kooman, Franklin W Maddux

RESULTSWe included 302,613 patients. Baseline phosphate was 5.1±1.2 mg/dl, and mean DR was +0.6±3.3 mg/dl. Across different levels of phosphate, higher levels of DR of phosphate were associated with higher risk of all-cause mortality. In patients with lower levels of phosphate and serum albumin, the effect of a negative DR was most pronounced, whereas in patients with higher phosphate levels, a positive DR was related to increased mortality.KEY POINTSAn increase in serum phosphate variability is an independent risk factor of mortality. The effects of a positive directional range (DR) is most pronounced in patients with high serum phosphate levels whereas the effects of a negative DR is most pronounced in patients with low serum phosphate and/or serum albumin.CONCLUSIONSHigher variability of serum phosphate is related to mortality at all levels of phosphate, especially in lower levels with a negative DR and in low serum albumin levels. This could possibly reflect dietary intake in patients who are already inflamed or malnourished, where a further reduction in serum phosphate should prompt for nutritional evaluation.BACKGROUNDIn maintenance hemodialysis (HD) patients, previous studies have shown that serum phosphate levels have a bidirectional relation to outcome. Less is known about the relation between temporal dynamics of serum phosphate in relation to outcome. We aimed to further explore the relation between serum phosphate variability and all-cause mortality.METHODSAll adult incident HD patients treated in US Fresenius Kidney Care clinics between January 2010 and October 2018 were included. Baseline period was defined as 6 months after initiation of HD and months 7–18 as follow-up period. All-cause mortality was recorded during the follow-up period. The primary metric of variability used was directional range (DR) that is the difference between the largest and smallest values within a time period; DR was positive when the smallest value preceded the largest and negative otherwise. Cox proportional hazards models with spline terms were applied to explore the association between phosphate, DR, and all-cause mortality. In addition, tensor product smoothing splines were computed to further elucidate the interactions of phosphate, DR, and all-cause mortality.

Amir Sapkota, Peter Kotanko

No abstract available

Rakesh Malhotra, Sina Rahimi, Ushma Agarwal, Ronit Katz, Ujjala Kumar, Pranav S Garimella, Vineet Gupta, Tushar Chopra, Peter Kotanko, T Alp Ikizler, Britta Larsen, Lisa Cadmus-Bertram, Joachim H Ix

RESULTSOut of 55 participants, 46 participants completed the 12-week intervention (23 per arm). The mean age was 62 (± 14 SD) years; 44% were Black, and 36% were Hispanic. At baseline, step count (structured feedback intervention: 3,704 [1,594] vs wearable activity tracker alone: 3,808 [1,890]) and other participant characteristics were balanced between the arms. We observed a larger change in daily step count in the structured feedback arm at 12 weeks relative to use of the wearable activity tracker alone arm (Δ 920 [±580 SD] versus Δ 281 [±186 SD] steps; between-group difference Δ 639 [±538 SD] steps; P<0.05).RATIONALE & OBJECTIVEPeople with end-stage kidney disease (ESKD) have very low physical activity, and the degree of inactivity is strongly associated with morbidity and mortality. We assessed the feasibility and effectiveness of a 12-week intervention coupling a wearable activity tracker (FitBit) and structured feedback coaching versus wearable activity tracker alone on changes in physical activity in hemodialysis patients.INTERVENTIONSAll participants wore a Fitbit Charge 2 tracker for a minimum of 12 weeks. Participants were randomly assigned 1:1 to a wearable activity tracker plus a structured feedback intervention versus the wearable activity tracker alone. The structured feedback group was counseled weekly on steps achieved after randomization.TRIAL REGISTRATIONRegistered at ClinicalTrials.gov with study number NCT05241171.LIMITATIONSSingle-center study and small sample size.STUDY DESIGNRandomized controlled trial.OUTCOMEThe outcome was step count, and the main parameter of interest was the absolute change in daily step count, averaged per week, from baseline to completion of 12 weeks intervention. In the intention-to-treat analysis, mixed-effect linear regression analysis was used to evaluate change in daily step count from baseline to 12-weeks in both arms.FUNDINGGrants from industry (Satellite Healthcare) and government (National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK).CONCLUSIONThis pilot randomized controlled trial demonstrated that structured feedback coupled with a wearable activity tracker led to a greater daily step count that was sustained over 12 weeks relative to a wearable activity tracker alone. Future studies are required to determine longer-term sustainability of the intervention and potential health benefits in hemodialysis patients.SETTING & PARTICIPANTS55 participants with ESKD receiving hemodialysis who were able to walk with or without assistive devices recruited from a single academic hemodialysis unit between January 2019 and April 2020.

Christina H Wang, Dan Negoianu, Hanjie Zhang, Sabrina Casper, Jesse Y Hsu, Peter Kotanko, Jochen Raimann, Laura M Dember

RESULTSDuring 180,319 HD sessions among 2554 patients, PRR had high within-patient and between-patient variability. Female sex and hypoalbuminemia were associated with low PRR at multiple time points during the first hour of HD. Low starting PRR has a higher hazard of IDH, whereas high starting PRR was protective (hazard ratio [HR], 1.26, 95% confidence interval [CI], 1.18 to 1.35 versus HR, 0.79, 95% CI, 0.73 to 0.85, respectively). However, when accounting for time-varying PRR and time-varying confounders, compared with a moderate PRR, while a consistently low PRR was associated with increased risk of hypotension (odds ratio [OR], 1.09, 95% CI, 1.02 to 1.16), a consistently high PRR had a stronger association with hypotension within the next 15 minutes (OR, 1.38, 95% CI, 1.30 to 1.45).KEY POINTSDirectly studying plasma refill rate (PRR) during hemodialysis (HD) can offer insight into physiologic mechanisms that change throughout HD. PRR at the start and during HD is associated with intradialytic hypotension, independent of ultrafiltration rate. A rising PRR during HD may be an early indicator of compensatory mechanisms for impending circulatory instability.CONCLUSIONSWe present a straightforward technique to quantify plasma refill that could easily integrate with devices that monitor hematocrit during HD. Our study highlights how examining patterns of plasma refill may enhance our understanding of circulatory changes during HD, an important step to understand how current technology might be used to improve hemodynamic instability.BACKGROUNDAttaining the optimal balance between achieving adequate volume removal while preserving organ perfusion is a challenge for patients receiving maintenance hemodialysis (HD). Current strategies to guide ultrafiltration are inadequate.METHODSWe developed an approach to calculate the plasma refill rate (PRR) throughout HD using hematocrit and ultrafiltration data in a retrospective cohort of patients receiving maintenance HD at 17 dialysis units from January 2017 to October 2019. We studied whether (1) PRR is associated with traditional risk factors for hemodynamic instability using logistic regression, (2) low starting PRR is associated with intradialytic hypotension (IDH) using Cox proportional hazard regression, and (3) time-varying PRR throughout HD is associated with hypotension using marginal structural modeling.

Peter Kotanko, Hanjie Zhang, Yuedong Wang

No abstract available

David J Jörg, Doris H Fuertinger, Peter Kotanko

Patients with renal anemia are frequently treated with erythropoiesis-stimulating agents (ESAs), which are dynamically dosed in order to stabilize blood hemoglobin levels within a specified target range. During typical ESA treatments, a fraction of patients experience hemoglobin 'cycling' periods during which hemoglobin levels periodically over- and undershoot the target range. Here we report a specific mechanism of hemoglobin cycling, whereby cycles emerge from the patient's delayed physiological response to ESAs and concurrent ESA dose adjustments. We introduce a minimal theoretical model that can explain dynamic hallmarks of observed hemoglobin cycling events in clinical time series and elucidates how physiological factors (such as red blood cell lifespan and ESA responsiveness) and treatment-related factors (such as dosing schemes) affect cycling. These results show that in general, hemoglobin cycling cannot be attributed to patient physiology or ESA treatment alone but emerges through an interplay of both, with consequences for the design of ESA treatment strategies.

Paulo Paneque Galuzio, Alhaji Cherif

We reviewed some of the latest advancements in the use of mathematical models in nephrology. We looked over 2 distinct categories of mathematical models that are widely used in biological research and pointed out some of their strengths and weaknesses when applied to health care, especially in the context of nephrology. A mechanistic dynamical system allows the representation of causal relations among the system variables but with a more complex and longer development/implementation phase. Artificial intelligence/machine learning provides predictive tools that allow identifying correlative patterns in large data sets, but they are usually harder-to-interpret black boxes. Chronic kidney disease (CKD), a major worldwide health problem, generates copious quantities of data that can be leveraged by choice of the appropriate model; also, there is a large number of dialysis parameters that need to be determined at every treatment session that can benefit from predictive mechanistic models. Following important steps in the use of mathematical methods in medical science might be in the intersection of seemingly antagonistic frameworks, by leveraging the strength of each to provide better care.

Girish N Nadkarni, Peter Kotanko

No abstract available

Thomas Lang, Adam M Zawada, Lukas Theis, Jennifer Braun, Bertram Ottillinger, Pascal Kopperschmidt, Alfred Gagel, Peter Kotanko, Manuela Stauss-Grabo, James P Kennedy, Bernard Canaud

Despite the significant medical and technical improvements in the field of dialytic renal replacement modalities, morbidity and mortality are excessively high among patients with end-stage kidney disease, and most interventional studies yielded disappointing results. Hemodiafiltration, a dialysis method that was implemented in clinics many years ago and that combines the two main principles of hemodialysis and hemofiltration-diffusion and convection-has had a positive impact on mortality rates, especially when delivered in a high-volume mode as a surrogate for a high convective dose. The achievement of high substitution volumes during dialysis treatments does not only depend on patient characteristics but also on the dialyzer (membrane) and the adequately equipped hemodiafiltration machine. The present review article summarizes the technical aspects of online hemodiafiltration and discusses present and ongoing clinical studies with regards to hard clinical and patient-reported outcomes.

Hanjie Zhang, Max Botler, Jeroen P Kooman

Analysis of medical images, such as radiological or tissue specimens, is an indispensable part of medical diagnostics. Conventionally done manually, the process may sometimes be time-consuming and prone to interobserver variability. Image classification and segmentation by deep learning strategies, predominantly convolutional neural networks, may provide a significant advance in the diagnostic process. In renal medicine, most evidence has been generated around the radiological assessment of renal abnormalities and histological analysis of renal biopsy specimens' segmentation. In this article, the basic principles of image analysis by convolutional neural networks, brief descriptions of convolutional neural networks, and their system architecture for image analysis are discussed, in combination with examples regarding their use in image analysis in nephrology.

Murilo Guedes, Brian Bieber, Indranil Dasgupta, Almudena Vega, Kosaku Nitta, Steven Brunelli, John Hartman, Jochen G Raimann, Bruce M Robinson, Ronald L Pisoni

Mineral bone disorder (MBD) is a frequent consequence of chronic kidney disease, more so in patients with kidney failure treated by kidney replacement therapy. Despite the wide availability of interventions to control serum phosphate and parathyroid hormone levels, unmet gaps remain on optimal targets and best practices, leading to international practice pattern variations over time. In this Special Report, we describe international trends from the Dialysis Outcomes and Practice Patterns Study (DOPPS) for MBD biomarkers and treatments from 2002-2021, including data from a group of 7 European countries (Belgium, France, Germany, Italy, Spain, Sweden, United Kingdom), Japan, and the United States. From 2002-2012, mean phosphate levels declined in Japan (5.6 to 5.2 mg/dL), Europe (5.5 to 4.9 mg/dL), and the United States (5.7 to 5.0 mg/dL). Since then, levels rose in the United States (to mean 5.6 mg/dL, 2021), were stable in Japan (5.3 mg/dL), and declined in Europe (4.8 mg/dL). In 2021, 52% (United States), 27% (Europe), and 39% (Japan) had phosphate >5.5 mg/dL. In the United States, overall phosphate binder use was stable (80%-84% over 2015-2021), and parathyroid hormone levels rose only modestly. Although these results potentially stem from pervasive knowledge gaps in clinical practice, the noteworthy steady increase in serum phosphate in the United States over the past decades may be consequential to patient outcomes, an uncertainty that hopefully will soon be addressed by ongoing clinical trials. The DOPPS will continue to monitor international trends as new interventions and strategies ensue for MBD management in chronic kidney disease.

Sheetal Chaudhuri, John Larkin, Murilo Guedes, Yue Jiao, Peter Kotanko, Yuedong Wang, Len Usvyat, Jeroen P Kooman

MATERIALS AND METHODSWe included data HD patients who had data across a baseline period of at least 1 year and 1 day in the internationally representative Monitoring Dialysis Outcomes (MONDO) Initiative dataset. Twenty-three input parameters considered in the model were chosen in an a priori manner. The prediction model used 1 year baseline data to predict death in the following 3 years. The dataset was randomly split into 80% training data and 20% testing data for model development. Two different modeling techniques were used to build the mortality prediction model.DISCUSSIONIn the internationally representative MONDO data for HD patients, we describe the development of a ML model and a traditional statistical model that was suitable for classification of a prevalent HD patient's 3-year risk of death. While both models had a reasonably high AUROC, the ML model was able to identify levels of hematocrit (HCT) as an important risk factor in mortality. If implemented in clinical practice, such proof-of-concept models could be used to provide pre-emptive care for HD patients.INTRODUCTIONSeveral factors affect the survival of End Stage Kidney Disease (ESKD) patients on dialysis. Machine learning (ML) models may help tackle multivariable and complex, often non-linear predictors of adverse clinical events in ESKD patients. In this study, we used advanced ML method as well as a traditional statistical method to develop and compare the risk factors for mortality prediction model in hemodialysis (HD) patients.FINDINGSA total of 95,142 patients were included in the analysis sample. The area under the receiver operating curve (AUROC) of the model on the test data with XGBoost ML model was 0.84 on the training data and 0.80 on the test data. AUROC of the logistic regression model was 0.73 on training data and 0.75 on test data. Four out of the top five predictors were common to both modeling strategies.

Dalia E Yousif, Xiaoling Ye, Stefano Stuard, Juan Berbessi, Adrian M Guinsburg, Len A Usvyat, Jochen G Raimann, Jeroen P Kooman, Frank M van der Sande, Neill Duncan, Kevin J Woollard, Rupert Bright, Charles Pusey, Vineet Gupta, Joachim H Ix, Peter Kotanko, Rakesh Malhotra

RESULTSWe studied 18,726 incident hemodialysis patients. Their age at dialysis initiation was 71.3 ± 11.9 years; 10,802 (58%) were males. Within the first 6 months, 2068 (11%) patients died, and 12,295 patients (67%) survived >36 months (survivor cohort). Hemodialysis patients who died showed a distinct biphasic pattern of change in inflammatory markers where an initial decline of inflammation was followed by a rapid rise that was consistently evident approximately 6 months before death. This pattern was similar in all patients who died and was consistent across the survival time intervals. In contrast, in the survivor cohort, we observed initial decline of inflammation followed by sustained low levels of inflammatory biomarkers.CONCLUSIONOur international study of incident hemodialysis patients highlights a temporal relationship between serial measurements of inflammatory markers and patient survival. This finding may inform the development of prognostic models, such as the integration of dynamic changes in inflammatory markers for individual risk profiling and guiding preventive and therapeutic interventions.INTRODUCTIONInflammation is highly prevalent among patients with end-stage kidney disease and is associated with adverse outcomes. We aimed to investigate longitudinal changes in inflammatory markers in a diverse international incident hemodialysis patient population.METHODSThe MONitoring Dialysis Outcomes (MONDO) Consortium encompasses hemodialysis databases from 31 countries in Europe, North America, South America, and Asia. The MONDO database was queried for inflammatory markers (total white blood cell count [WBC], neutrophil count, lymphocyte count, serum albumin, and C-reactive protein [CRP]) and hemoglobin levels in incident hemodialysis patients. Laboratory parameters were measured every month. Patients were stratified by survival time (≤6 months, >6 to 12 months, >12 to 18 months, >18 to 24 months, >24 to 30 months, >30 to 36 months, and >36 months) following dialysis initiation. We used cubic B-spline basis function to evaluate temporal changes in inflammatory parameters in relationship with patient survival.

Ana Paula Bernardo, Paola Carioni, Stefano Stuard, Peter Kotanko, Len A Usvyat, Vratislava Kovarova, Otto Arkossy, Francesco Bellocchio, Antonio Tupputi, Federica Gervasoni, Anke Winter, Yan Zhang, Hanjie Zhang, Pedro Ponce, Luca Neri

RESULTSIn the effectiveness analysis concerning mRNA vaccines, we observed 850 SARS-CoV-2 infections and 201 COVID-19 related deaths among the 28110 patients during a mean follow up of 44 ± 40 days. In the effectiveness analysis concerning viral-carrier vaccines, we observed 297 SARS-CoV-2 infections and 64 COVID-19 related deaths among 12888 patients during a mean follow up of 48 ± 32 days. We observed 18.5/100-patient-year and 8.5/100-patient-year fewer infections and 5.4/100-patient-year and 5.2/100-patient-year fewer COVID-19 related deaths among patients vaccinated with mRNA and viral-carrier vaccines respectively, compared to matched unvaccinated controls. Estimated vaccine effectiveness at days 15, 30, 60 and 90 after the first dose of a mRNA vaccine was: for infection, 41.3%, 54.5%, 72.6% and 83.5% and, for death, 33.1%, 55.4%, 80.1% and 91.2%. Estimated vaccine effectiveness after the first dose of a viral-carrier vaccine was: for infection, 38.3% without increasing over time and, for death, 56.6%, 75.3%, 92.0% and 97.4%.CONCLUSIONIn this large, real-world cohort of hemodialyzed patients, mRNA and viral-carrier COVID-19 vaccines were associated with reduced COVID-19 related mortality. Additionally, we observed a strong reduction of SARS-CoV-2 infection in hemodialysis patients receiving mRNA vaccines.BACKGROUNDHemodialysis patients have high-risk of severe SARS-CoV-2 infection but were unrepresented in randomized controlled trials evaluating the safety and efficacy of COVID-19 vaccines. We estimated the real-world effectiveness of COVID-19 vaccines in a large international cohort of hemodialysis patients.METHODSIn this historical, 1:1 matched cohort study, we included adult hemodialysis patients receiving treatment from December 1, 2020, to May 31, 2021. For each vaccinated patient, an unvaccinated control was selected among patients registered in the same country and attending a dialysis session around the first vaccination date. Matching was based on demographics, clinical characteristics, past COVID-19 infections and a risk score representing the local background risk of infection at vaccination dates. We estimated the effectiveness of mRNA and viral-carrier COVID-19 vaccines in preventing infection and mortality rates from a time-dependent Cox regression stratified by country.

Adrián M Guinsburg, Yue Jiao, María Inés Díaz Bessone, Caitlin K Monaghan, Beatriz Magalhães, Michael A Kraus, Peter Kotanko, Jeffrey L Hymes, Robert J Kossmann, Juan Carlos Berbessi, Franklin W Maddux, Len A Usvyat, John W Larkin

RESULTSAmong 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.CONCLUSIONSFindings 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.BACKGROUNDWe 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.METHODSWe 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.

Paulo P Galuzio, Alhaji Cherif, Xia Tao, Ohnmar Thwin, Hanjie Zhang, Stephan Thijssen, Peter Kotanko

In patients with kidney failure treated by hemodialysis, intradialytic arterial oxygen saturation (SaO2) time series present intermittent high-frequency high-amplitude oximetry patterns (IHHOP), which correlate with observed sleep-associated breathing disturbances. A new method for identifying such intermittent patterns is proposed. The method is based on the analysis of recurrence in the time series through the quantification of an optimal recurrence threshold ([Formula: see text]). New time series for the value of [Formula: see text] were constructed using a rolling window scheme, which allowed for real-time identification of the occurrence of IHHOPs. The results for the optimal recurrence threshold were confronted with standard metrics used in studies of obstructive sleep apnea, namely the oxygen desaturation index (ODI) and oxygen desaturation density (ODD). A high correlation between [Formula: see text] and the ODD was observed. Using the value of the ODI as a surrogate to the apnea-hypopnea index (AHI), it was shown that the value of [Formula: see text] distinguishes occurrences of sleep apnea with great accuracy. When subjected to binary classifiers, this newly proposed metric has great power for predicting the occurrences of sleep apnea-related events, as can be seen by the larger than 0.90 AUC observed in the ROC curve. Therefore, the optimal threshold [Formula: see text] from recurrence analysis can be used as a metric to quantify the occurrence of abnormal behaviors in the arterial oxygen saturation time series.

Gabriela F Dias, Sara S Tozoni, Gabriela Bohnen, Beatriz A K van Spitzenbergen, Nadja Grobe, Lia S Nakao, Roberto Pecoits-Filho, Peter Kotanko, Andréa N Moreno-Amaral

Oxidative stress (OS) is essential in uremia-associated comorbidities, including renal anemia. Complications experienced by hemodialysis (HD) patients, such as hypoxemia and uremic toxins accumulation, induce OS and premature death of red blood cells (RBC). We aimed to characterize reactive oxygen species (ROS) production and antioxidant pathways in HD-RBC and RBC from healthy controls (CON-RBC) and evaluate the role of uremia and hypoxia in these pathways. ROS production, xanthine oxidase (XO) and superoxide dismutase (SOD) activities, glutathione (GSH), and heme oxygenase-1 (HO-1) levels were measured using flow cytometry or spectrophotometry in CON-RBC and HD-RBC (pre- and post-HD), at baseline and after 24 h incubation with uremic serum (S-HD) and/or under hypoxic conditions (5% O2 ). Ketoprofen was used to inhibit RBC uremic toxins uptake. HD-RBC showed higher ROS levels and lower XO activity than CON-RBC, particularly post-HD. GSH levels were lower, while SOD activity and HO-1 levels of HD-RBC were higher than control. Hypoxia per se triggered ROS production in CON-RBC and HD-RBC. S-HD, on top of hypoxia, increased ROS levels. Inhibition of uremic toxins uptake attenuated ROS of CON and HD-RBC under hypoxia and uremia. CON-RBC in uremia and hypoxia showed lower GSH levels than cells in normoxia and non-uremic conditions. Redox mechanisms of HD-RBC are altered and prone to oxidation. Uremic toxins and hypoxia play a role in unbalancing these systems. Hypoxia and uremia participate in the pathogenesis of OS in HD-RBC and might induce RBC death and thus compound anemia.

David J Jörg, Doris H Fuertinger, Alhaji Cherif, David A Bushinsky, Ariella Mermelstein, Jochen G Raimann, Peter Kotanko

Our bones are constantly being renewed in a fine-tuned cycle of destruction and formation that helps keep them healthy and strong. However, this process can become imbalanced and lead to osteoporosis, where the bones are weakened and have a high risk of fracturing. This is particularly common post-menopause, with one in three women over the age of 50 experiencing a broken bone due to osteoporosis. There are several drug types available for treating osteoporosis, which work in different ways to strengthen bones. These drugs can be taken individually or combined, meaning that a huge number of drug combinations and treatment strategies are theoretically possible. However, it is not practical to test the effectiveness of all of these options in human trials. This could mean that patients are not getting the maximum potential benefit from the drugs available. Jörg et al. developed a mathematical model to predict how different osteoporosis drugs affect the process of bone renewal in the human body. The model could then simulate the effect of changing the order in which the therapies were taken, which showed that the sequence had a considerable impact on the efficacy of the treatment. This occurs because different drugs can interact with each other, leading to an improved outcome when they work in the right order. These results suggest that people with osteoporosis may benefit from altered treatment schemes without changing the type or amount of medication taken. The model could suggest new treatment combinations that reduce the risk of bone fracture, potentially even developing personalised plans for individual patients based on routine clinical measurements in response to different drugs.

Xin Wang, Leticia M Tapia Silva, Milind Nikam, Sandip Mitra, Syed Shaukat Abbas Zaidi, Nadja Grobe

The aim of the paper is to summarize the current understanding of the molecular biology of arteriovenous fistula (AVF). It intends to encourage vascular access teams, care providers, and scientists, to explore new molecular tools for assessing the suitability of patients for AVF as vascular access for maintenance hemodialysis (HD). This review also highlights most recent discoveries and may serve as a guide to explore biomarkers and technologies for the assessment of kidney disease patients choosing to start kidney replacement therapy. Objective criteria for AVF eligibility are lacking partly because the underlying physiology of AVF maturation is poorly understood. Several molecular processes during a life cycle of an AVF, even before creation, can be characterized by measuring molecular fingerprints using newest "omics" technologies. In addition to hypothesis-driven strategies, untargeted approaches have the potential to reveal the interplay of hundreds of metabolites, transcripts, proteins, and genes underlying cardiovascular adaptation and vascular access-related adjustments at any given timepoint of a patient with kidney disease. As a result, regular monitoring of modifiable, molecular risk factors together with clinical assessment could help to reduce AVF failure rates, increase patency, and improve long-term outcomes. For the future, identification of vulnerable patients based on the assessment of biological markers of AVF maturation at different stages of the life cycle may aid in individualizing vascular access recommendations.

Xiaoling Wang, Maggie Han, Lemuel Rivera Fuentes, Ohnmar Thwin, Nadja Grobe, Kevin Wang, Yuedong Wang, Peter Kotanko

RESULTSForty-two patients had three doses of mRNA1273. Compared to levels prior to the third dose, nAb-WT increased 18-fold (peak at day 23) and nAb-Omicron increased 23-fold (peak at day 24) after the third dose. Peak nAb-WT exceeded peak nAb-Omicron 27-fold. Twenty-one patients had COVID-19 between December 24, 2021, and February 2, 2022. Following COVID-19, nAb-WT and nAb-Omicron increased 12- and 40-fold, respectively. While levels of vaccinal and post-COVID nAb-WT were comparable, post-COVID nAb-Omicron levels were 3.2 higher than the respective peak vaccinal nAb-Omicron. Four immunocompromised patients having reasons other than end-stage kidney disease have very low to no nAb after the third dose or COVID-19.CONCLUSIONSOur results suggest that most hemodialysis patients have a strong humoral response to the third dose of vaccination and an even stronger post-COVID-19 humoral response. Nevertheless, nAb levels clearly decay over time. These findings may inform ongoing discussions regarding a fourth vaccination in hemodialysis patients.BACKGROUNDIn hemodialysis patients, a third vaccination is frequently administered to augment protection against coronavirus disease 2019 (COVID-19). However, the newly emerged B.1.1.159 (Omicron) variant may evade vaccinal protection more easily than previous strains. It is of clinical interest to better understand the neutralizing activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants after booster vaccine or COVID-19 infection in these mostly immunocompromised patients.METHODSHemodialysis patients from four dialysis centers were recruited between June 2021 and February 2022. Each patient provided a median of six serum samples. SARS-CoV-2 neutralizing antibodies (nAbs) against wild type (WT) or Omicron were measured using the GenScript SARS-CoV-2 Surrogate Virus Neutralization Test Kit.

Jeroen Peter Kooman, Paola Carioni, Vratislava Kovarova, Otto Arkossy, Anke Winter, Yan Zhang, Francesco Bellocchio, Peter Kotanko, Hanjie Zhang, Len Usvyat, John Larkin, Stefano Stuard, Luca Neri

RESULTSWe included 9,211 patients (age 65.4 ± 13.7 years, dialysis vintage 4.2 ± 3.7 years) eligible for the study. The 30-day mortality rate was 20.8%. In LR models, several potentially modifiable factors were associated with higher mortality: body mass index (BMI) 30-40 kg/m2 (OR: 1.28, CI: 1.10-1.50), single-pool Kt/V (OR off-target vs on-target: 1.19, CI: 1.02-1.38), overhydration (OR: 1.15, CI: 1.01-1.32), and both low (<2.5 mg/dl) and high (≥5.5 mg/dl) serum phosphate levels (OR: 1.52, CI: 1.07-2.16 and OR: 1.17, CI: 1.01-1.35). On-line hemodiafiltration was protective in the model using KPIs (OR: 0.86, CI: 0.76-0.97). SHapley Additive exPlanations analysis in XGBoost models shows a high influence on prediction for several modifiable factors as well, including inflammatory parameters, high BMI, and fluid overload. In both LR and XGBoost models, age, gender, and comorbidities were strongly associated with mortality.CONCLUSIONBoth conventional and machine learning techniques showed that KPIs and modifiable risk factors in different dimensions ascertained 6 months before the COVID-19 suspicion date were associated with 30-day COVID-19-related mortality. Our results suggest that adequate dialysis and achieving KPI targets remain of major importance during the COVID-19 pandemic as well.INTRODUCTIONPatients with end-stage kidney disease face a higher risk of severe outcomes from SARS-CoV-2 infection. Moreover, it is not well known to what extent potentially modifiable risk factors contribute to mortality risk. In this historical cohort study, we investigated the incidence and risk factors for 30-day mortality among hemodialysis patients with SARS-CoV-2 infection treated in the European Fresenius Medical Care NephroCare network using conventional and machine learning techniques.METHODSWe included adult hemodialysis patients with the first documented SARS-CoV-2 infection between February 1, 2020, and March 31, 2021, registered in the clinical database. The index date for the analysis was the first SARS-CoV-2 suspicion date. Patients were followed for up to 30 days until April 30, 2021. Demographics, comorbidities, and various modifiable risk factors, expressed as continuous parameters and as key performance indicators (KPIs), were considered to tap multiple dimensions including hemodynamic control, nutritional state, and mineral metabolism in the 6 months before the index date. We used logistic regression (LR) and XGBoost models to assess risk factors for 30-day mortality.

Bernard Canaud, Jeroen Kooman, Andreas Maierhofer, Jochen Raimann, Jens Titze, Peter Kotanko

New physiologic findings related to sodium homeostasis and pathophysiologic associations require a new vision for sodium, fluid and blood pressure management in dialysis-dependent chronic kidney disease patients. The traditional dry weight probing approach that has prevailed for many years must be reviewed in light of these findings and enriched by availability of new tools for monitoring and handling sodium and water imbalances. A comprehensive and integrated approach is needed to improve further cardiac health in hemodialysis (HD) patients. Adequate management of sodium, water, volume and hemodynamic control of HD patients relies on a stepwise approach: the first entails assessment and monitoring of fluid status and relies on clinical judgement supported by specific tools that are online embedded in the HD machine or devices used offline; the second consists of acting on correcting fluid imbalance mainly through dialysis prescription (treatment time, active tools embedded on HD machine) but also on guidance related to diet and thirst management; the third consist of fine tuning treatment prescription to patient responses and tolerance with the support of innovative tools such as artificial intelligence and remote pervasive health trackers. It is time to come back to sodium and water imbalance as the root cause of the problem and not to act primarily on their consequences (fluid overload, hypertension) or organ damage (heart; atherosclerosis, brain). We know the problem and have the tools to assess and manage in a more precise way sodium and fluid in HD patients. We strongly call for a sodium first approach to reduce disease burden and improve cardiac health in dialysis-dependent chronic kidney disease patients.

Murilo Guedes, Liz Wallim, Camila R Guetter, Yue Jiao, Vladimir Rigodon, Chance Mysayphonh, Len A Usvyat, Pasqual Barretti, Peter Kotanko, John W Larkin, Franklin W Maddux, Roberto Pecoits-Filho, Thyago Proenca de Moraes

RESULTSWe 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.CONCLUSIONSAmong patients in Brazil and the United States, lower vitality score in the initial months of PD was independently associated with all-cause mortality.BACKGROUNDWe tested if fatigue in incident Peritoneal Dialysis associated with an increased risk for mortality, independently from main confounders.METHODSWe 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.

Lin-Chun Wang, Jochen G Raimann, Xia Tao, Priscila Preciado, Ohnmar Thwin, Laura Rosales, Stephan Thijssen, Peter Kotanko, Fansan Zhu

DISCUSSIONAlthough segmental eight-point bioimpedance techniques provided comparable TBW measurements not affected by standing over a period of 10-15 min, the ECW/TBW ratio appeared to be significantly lower in InBody compared with Seca and Hydra. Results from our study showed lack of agreement between different bioimpedance devices; direct comparison of ECW, ICW, and ECW/TBW between different devices should be avoided and clinicians should use the same device to track the fluid status in their HD population in a longitudinal direction.INTRODUCTIONSegmental eight-point bioimpedance has been increasingly used in practice. However, whether changes in bioimpedance analysis components before and after hemodialysis (HD) using this technique in a standing position is comparable to traditional whole-body wrist-to-ankle method is still unclear. We aimed to investigate the differences between two eight-point devices (InBody 770 and Seca mBCA 514) and one wrist-to-ankle (Hydra 4200) in HD patients and healthy subjects in a standing position.FINDINGSOverall, total body water (TBW) was not different between the three devices, but InBody showed lower extracellular water (ECW) and higher intracellular water (ICW) compared to the other two devices. When intradialytic weight loss was used as a surrogate for changes in ECW (∆ECW) and changes in TBW (∆TBW), ∆ECW was underestimated by Hydra (-0.79 ± 0.89 L, p < 0.01), InBody (-1.44 ± 0.65 L, p < 0.0001), and Seca (-0.32 ± 1.34, n.s.). ∆TBW was underestimated by Hydra (-1.14 ± 2.81 L, n.s.) and InBody (-0.52 ± 0.85 L, p < 0.05) but overestimated by Seca (+0.93 ± 3.55 L, n.s.).METHODSThirteen HD patients were studied pre- and post-HD, and 12 healthy subjects once. Four measurements were performed in the following order: InBody; Seca; Hydra; and InBody again. Electrical equivalent models by each bioimpedance method and the fluid volume estimates by each device were also compared.

Usama Hussein, Monica Cimini, Garry J Handelman, Jochen G Raimann, Li Liu, Samer R Abbas, Peter Kotanko, Nathan W Levin, Fredric O Finkelstein, Fansan Zhu

Diagnosis of fluid overload (FO) in early stage is essential to manage fluid balance of patients with chronic kidney disease (CKD) and to prevent cardiovascular disease (CVD). However, the identification of fluid status in patients with CKD is largely dependent on the physician's clinical acumen. The ratio of fluid overload to extracellular volume (FO/ECV) has been used as a reference to assess fluid status. The primary aim of this study was to compare FO/ECV with other bioimpedance methods and clinical assessments in patients with CKD. Whole body ECV, intracellular volume (ICV), total body water (TBW), and calf normalized resistivity (CNR) were measured (Hydra 4200). Thresholds of FO utilizing CNR and ECV/TBW were derived by receiver operator characteristic (ROC) analysis based on data from pooled patients with CKD and healthy subjects (HSs). Clinical assessments of FO in patients with CKD were performed by nephrologists. Patients with CKD (stage 3 and stage 4) (n = 50) and HSs (n = 189) were studied. The thresholds of FO were ≤14.3 (10-2 Ωm3/kg) for females and ≤13.1 (10-2 Ωm3/kg) for males using CNR and ≥0.445 in females and ≥0.434 in males using ECV/TBW. FO was diagnosed in 78%, 62%, and 52% of patients with CKD by CNR, FO/ECV, and ECV/TBW, respectively, whereas only 24% of patients with CKD were diagnosed to be FO by clinical assessment. The proportion of FO in patients with nondialysis CKD was largely underestimated by clinical assessment compared with FO/ECV, CNR, and ECV/TBW. CNR and FO/ECV methods were more sensitive than ECV/TBW in identifying fluid overload in these patients with CKD.NEW & NOTEWORTHY We found that fluid overload (FO) in patients with nondialysis CKD was largely underestimated by clinical assessment compared with bioimpedance methods, which was majorly due to lack of appropriate techniques to assess FO. In addition, although degree of FO by bioimpedance markers positively correlated with the age in healthy subjects (HSs), no difference was observed in the three hydration markers between groups of 50 ≤ age <70 yr and age ≥70 yr in the patients with CKD.

Peter Kotanko, David J Jörg, Nadja Grobe, Christoph Zaba

Erythropoietin deficiency is an extensively researched cause of renal anemia. The etiology and consequences of shortened red blood cell (RBC) life span in chronic kidney disease (CKD) are less well understood. Traversing capillaries requires RBC geometry changes, a process enabled by adaptions of the cytoskeleton. These changes are mediated by transient activation of the mechanosensory Piezo1 channel, resulting in calcium influx. Importantly, prolonged Piezo1 activation shortens RBC life span, presumably through activation of calcium-dependent intracellular pathways triggering RBC death. Two Piezo1-activating small molecules, Jedi1 and Jedi2, share remarkable structural similarities with 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF), a uremic retention solute cleared by the healthy kidney. We hypothesize that in CKD the accumulation of CMPF leads to prolonged activation of Piezo1 (similar in effect to Jedi1 and Jedi2), thus reducing RBC life span. This hypothesis can be tested through bench experiments and, ultimately, by studying the effect of CMPF removal on renal anemia.

Gudrun Schappacher-Tilp, Peter Kotanko, Markus Pirklbauer

Altered parathyroid gland biology is a major driver of chronic kidney disease-mineral bone disorder (CKD-MBD) in patients with chronic kidney disease. CKD-MBD is associated with a high risk of vascular calcification and cardiovascular events. A hallmark of CKD-MBD is secondary hyperparathyroidism with increased parathyroid hormone (PTH) synthesis and release and reduced expression of calcium-sensing receptors on the surface of parathyroid cells and eventually hyperplasia of parathyroid gland cells. The KDIGO guidelines strongly recommend the control of PTH in hemodialysis patients. Due to the complexity of parathyroid gland biology, mathematical models have been employed to study the interaction of PTH regulators and PTH plasma concentrations. Here, we present an overview of various model approaches and discuss the impact of different model structures and complexities on the clinical use of these models.

Jochen G Raimann, Yuedong Wang, Ariella Mermelstein, Peter Kotanko, John T Daugirdas

RESULTSIn the studied 2542 patients, UFR not scaled to body weight was strongly associated with MHR, whereas postdialysis weight was inversely associated with MHR. MHR crossed 1.5 when unscaled UFR exceeded 1000 ml/h, and this relationship was largely independent of postdialysis weight in the range of 80 to 140 kg. A UFR warning level associated with a lower MHR of 1.3 would be 900 ml/h, whereas the UFR associated with an MHR of 1.0 was patient-size dependent. The MHR when exceeding a UFR threshold of 13 ml/h per kg was dependent on patient weight (MHR = 1.20, 1.45, and >2.0 for a 60, 80, and 100 kg patient, respectively).CONCLUSIONUFR thresholds based on unscaled UFR give more uniform risk levels for patients of different sizes than thresholds based on UFR/kg.INTRODUCTIONOne proposed threshold ultrafiltration rate (UFR) of concern in hemodialysis patients is 13 ml/h per kg. We evaluated associations among UFR, postdialysis weight, and mortality to determine whether exceeding such a threshold would result in similar levels of risk for patients of different body weights.METHODSData were analyzed in this retrospective cohort study for 1 year following dialysis initiation (baseline) and over 2 years of follow-up in incident patients receiving thrice-weekly in-center hemodialysis. Patient-level UFR was averaged over the baseline period. To investigate the joint effect of UFR and postdialysis weight on survival, we fit Cox proportional hazards models using bivariate tensor product spline functions, adjusting for sex, race, age, diabetes, and predialysis serum albumin, phosphorus, and systolic blood pressure (BP). We constructed contour plots of mortality hazard ratios (MHRs) over the entire range of UFR values and postdialysis weights.

Orly F Kohn, Susie Q Lew, Steve Siu-Man Wong, Ramin Sam, Hung-Chun Chen, Jochen G Raimann, David J Leehey, Antonios H Tzamaloukas, Todd S Ing

Herbal medicine, a form of complementary and alternative medicine (CAM), is used throughout the world, in both developing and developed countries. The ingredients in herbal medicines are not standardized by any regulatory agency. Variability exists in the ingredients as well as in their concentrations. Plant products may become contaminated with bacteria and fungi during storage. Therefore, harm can occur to the kidney, liver, and blood components after ingestion. We encourage scientific studies to identify the active ingredients in herbs and to standardize their concentrations in all herbal preparations. Rigorous studies need to be performed in order to understand the effect of herbal ingredients on different organ systems as well as these substances' interaction with other medications.

Rasha Hussein, Murilo Guedes, Nada Ibraheim, Mazin M Ali, Amal El-Tahir, Nahla Allam, Hussain Abuakar, Roberto Pecoits-Filho, Peter Kotanko

OBJECTIVESDespite the possibility of concurrent infection with COVID-19 and malaria, little is known about the clinical course of coinfected patients. We analysed the clinical outcomes of patients with concurrent COVID-19 and malaria infection.RESULTSWe included 591 patients with confirmed COVID-19 diagnosis who were also tested for malaria. Mean (SD) age was 58 (16.2) years, 446/591 (75.5%) were males. Malaria was diagnosed in 270/591 (45.7%) patients. Most malaria patients were infected by Plasmodium falciparum (140/270; 51.9%), while 121/270 (44.8%) were coinfected with Plasmodium falciparum and Plasmodium vivax. Median follow-up was 29 days. Crude mortality rates were 10.71 and 5.87 per 1000 person-days for patients with and without concurrent malaria, respectively. In the fully adjusted Cox model, patients with concurrent malaria and COVID-19 had a greater mortality risk (hazard ratio 1.43, 95% confidence interval 1.21-1.69).DISCUSSIONCoinfection with COVID-19 and malaria is associated with increased all-cause in-hospital mortality compared to monoinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).METHODSWe conducted a retrospective cohort study that assessed prospectively collected data of all patients who were admitted between May and December 2020 to the Universal COVID-19 treatment center (UCTC), Khartoum, Sudan. UCTC compiled demographic, clinical, laboratory (including testing for malaria), and outcome data in all patients with confirmed COVID-19 hospitalized at that clinic. The primary outcome was all-cause mortality during the hospital stay. We built proportional hazard Cox models with malaria status as the main exposure and stepwise adjustment for age, sex, cardiovascular comorbidities, diabetes, and hypertension.

Bernard Canaud, Andrew Davenport, Thomas A Golper, Jochen G Raimann

No abstract available

Sabrina Casper, Doris H Fuertinger, Leticia M Tapia Silva, Lemuel Rivera Fuentes, Stephan Thijssen, Peter Kotanko

RESULTSIn all tests, the ultrafiltration controller performed as expected. In the in silico and ex vivo bench experiments, the controller showed robust reaction toward deliberate disruptive interventions (e.g. signal noise; extreme plasma refill rates). No adverse events were observed in the clinical study.CONCLUSIONSThe ultrafiltration controller can steer RBV trajectories toward desired RBV ranges while obeying to a set of constraints. Prospective studies in hemodialysis patients with diverse clinical characteristics are warranted to further explore the controllers impact on intradialytic hemodynamic stability, quality of life, and long-term outcomes.BACKGROUNDMost hemodialysis patients without residual kidney function accumulate fluid between dialysis session that needs to be removed by ultrafiltration. Ultrafiltration usually results in a decline in relative blood volume (RBV). Recent epidemiological research has identified RBV ranges that were associated with significantly better survival. The objective of this work was to develop an ultrafiltration controller to steer a patient's RBV trajectory into these favorable RBV ranges.METHODSWe designed a proportional-integral feedback ultrafiltration controller that utilizes signals from a device that reports RBV. The control goal is to attain the RBV trajectory associated with improved patient survival. Additional constraints such as upper and lower bounds of ultrafiltration volume and rate were realized. The controller was evaluated in in silico and ex vivo bench experiments, and in a clinical proof-of-concept study in two maintenance dialysis patients.

Sudhir K Bowry, Peter Kotanko, Rainer Himmele, Xia Tao, Michael Anger

Informed decision-making is paramount to the improvement of dialysis therapies and patient outcomes. A cornerstone of delivery of optimal dialysis therapy is to delineate which substances (uraemic retention solutes or 'uraemic toxins') contribute to the condition of uraemia in terms of deleterious biochemical effects they may exert. Thereafter, decisions can be made as to which of the accumulated compounds need to be targeted for removal and by which strategies. For haemodialysis (HD), the non-selectivity of membranes is sometimes considered a limitation. Yet, considering that dozens of substances with potential toxicity need to be eliminated, and targeting removal of individual toxins explicitly is not recommended, current dialysis membranes enable elimination of several molecules of a broad size range within a single therapy session. However, because HD solute removal is based on size-exclusion principles, i.e. the size of the substances to be removed relative to the mean size of the 'pores' of the membrane, only a limited degree of selectivity of removal is possible. Removal of unwanted substances during HD needs to be weighed against the unavoidable loss of substances that are recognized to be necessary for bodily functions and physiology. In striving to improve the efficiency of HD by increasing the porosity of membranes, there is a greater potential for the loss of substances that are of benefit. Based on this elementary trade-off and availability of recent guidance on the relative toxicity of substances retained in uraemia, we propose a new evidence-linked uraemic toxin elimination (ELUTE) approach whereby only those clusters of substances for which there is a sufficient body of evidence linking them to deleterious biological effects need to be targeted for removal. Our approach involves correlating the physical properties of retention solutes (deemed to express toxicity) with key determinants of membranes and separation processes. Our analysis revealed that in attempting to remove the relatively small number of 'larger' substances graded as having only moderate toxicity, uncontrolled (and efficient) removal of several useful compounds would take place simultaneously and may compromise the well-being or outcomes of patients. The bulk of the uraemic toxin load comprises uraemic toxins below <30 000 Da and are adequately removed by standard membranes. Further, removal of a few difficult-to-remove-by-dialysis (protein-bound) compounds that express toxicity cannot be achieved by manipulation of pore size alone. The trade-off between the benefits of effective removal of the bulk of the uraemic toxin load and risks (increased loss of useful substances) associated with targeting the removal of a few larger substances in 'high-efficiency' HD treatment strategies needs to be recognized and better understood. The removability during HD of substances, be they toxic, inert or beneficial, needs be revised to establish the pros and cons of current dialytic elimination strategies.  .

Hanjie Zhang, Dean Preddie, Warren Krackov, Murat Sor, Peter Waguespack, Zuwen Kuang, Xiaoling Ye, Peter Kotanko

No abstract available

Richard V Remigio, Hao He, Jochen G Raimann, Peter Kotanko, Frank W Maddux, Amy Rebecca Sapkota, Xin-Zhong Liang, Robin Puett, Xin He, Amir Sapkota

RESULTSFrom 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 PM2.5 concentration was associated with a 5% increase in ACM (rate ratio [RRLag0-3]: 1.05, 95% CI: 1.00-1.10) and same-day O3 (RRLag0: 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.CONCLUSIONOur 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.BACKGROUNDIncreasing 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).METHODSFresenius 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 PM2.5 and ozone (O3) 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.

Ulrich Moissl, Lemuel Rivera Fuentes, Mohamad I Hakim, Manuel Hassler, Dewangi A Kothari, Laura Rosales, Fansan Zhu, Jochen G Raimann, Stephan Thijssen, Peter Kotanko

DISCUSSIONWhile about half of the patients had normal fluid status pre-HD, a considerable proportion of patients was either fluid overloaded or depleted, indicating the need for tools to objectively quantify fluid status.INTRODUCTIONInadequate fluid status remains a key driver of cardiovascular morbidity and mortality in chronic hemodialysis (HD) patients. Quantification of fluid overload (FO) using bioimpedance spectroscopy (BIS) has become standard in many countries. To date, no BIS device has been approved in the United States for fluid status assessment in kidney patients. Therefore, no previous quantification of fluid status in US kidney patients using BIS has been reported. Our aim was to conduct a cross-sectional BIS-based assessment of fluid status in an urban US HD population.FINDINGSWe studied 170 urban HD patients (age 61 ± 14 years, 60% male). Pre- and post-HD FO (mean ± SD), were 2.2 ± 2.4 and -0.2 ± 2.7 L, respectively. Pre-HD, 43% of patients were fluid overloaded, 53% normally hydrated, and 4% fluid depleted. Post-HD, 12% were fluid overloaded, 55% normohydrated and 32% fluid depleted. Only 48% of fluid overloaded patients were hypertensive, while 38% were normotensive and 14% hypotensive. Fluid status did not differ significantly between African Americans (N = 90) and Caucasians (N = 61).METHODSWe determined fluid status in chronic HD patients using whole body BIS (Body Composition Monitor, BCM). The BCM reports FO in liters; negative FO denotes fluid depletion. Measurements were performed before dialysis. Post-HD FO was estimated by subtracting the intradialytic weight loss from the pre-HD FO.

Pablo Maggiani-Aguilera, Jochen G Raimann, Jonathan S Chávez-Iñiguez, Guillermo Navarro-Blackaller, Peter Kotanko, Guillermo Garcia-Garcia

RESULTSIn 1,632 patients from RRI, the CVC prevalence at month 1 was 64% and 97% among 174 HC patients. The conversion rate was 31.7% in RRI and 10.6% in HC. CVC to non-central venous catheter (NON-CVC) conversion reduced the risk of hospitalization in both HC (aHR 0.38 [95% CI: 0.21-0.68], p = 0.001) and RRI (aHR 0.84 [95% CI: 0.73-0.93], p = 0.001). NON-CVC patients had a lower mortality risk in both populations.INTRODUCTIONCentral venous catheter (CVC) as vascular access in hemodialysis (HD) associates with adverse outcomes. Early CVC to fistula or graft conversion improves these outcomes. While socioeconomic disparities between the USA and Mexico exist, little is known about CVC prevalence and conversion rates in uninsured Mexican HD patients. We examined vascular access practice patterns and their effects on survival and hospitalization rates among uninsured Mexican HD patients, in comparison with HD patients who initiated treatment in the USA.DISCUSSION/CONCLUSIONCVC prevalence and conversion rates of CVC to NON-CVC differed between the US and Mexican patients. An association exists between vascular access type and hospitalization and mortality risk. Prospective studies are needed to evaluate if accelerated and systematic catheter use reduction would improve outcomes in these populations.METHODSIn this retrospective study of incident HD patients at Hospital Civil (HC; Guadalajara, MX) and the Renal Research Institute (RRI; USA), we categorized patients by the vascular access at the first month of HD and after the following 6 months. Factors associated with continued CVC use were identified by a logistic regression model. We developed multivariate Cox proportional hazards models to investigate the effects of access and conversion on mortality and hospitalization over an 18-month follow-up period.

Jochen G Raimann, Christopher T Chan, John T Daugirdas, Thomas Depner, Tom Greene, George A Kaysen, Alan S Kliger, Peter Kotanko, Brett Larive, Gerald Beck, Robert McGregor Lindsay, Michael V Rocco, Glenn M Chertow, Nathan W Levin

RESULTSIn 197 enrolled subjects in the FHN Daily Trial, the treatment effect of frequent HD on ∆LVM was modified by SNa. When the FHN Daily Trial participants are divided into lower and higher predialysis SNa groups (less and greater than 138 mEq/L), the LVM reduction in the lower group was substantially higher (-28.0 [95% CI -40.5 to -15.4] g) than in the higher predialysis SNa group (-2.0 [95% CI -15.5 to 11.5] g). Accounting for GNa, TIFL also showed more pronounced effects among patients with higher GNa or higher TIFL. Results in the Nocturnal Trial were similar in direction and magnitude but did not reach statistical significance.INTRODUCTIONThe Frequent Hemodialysis Network (FHN) Daily and Nocturnal trials aimed to compare the effects of hemodialysis (HD) given 6 versus 3 times per week. More frequent in-center HD significantly reduced left-ventricular mass (LVM), with more pronounced effects in patients with low urine volumes. In this study, we aimed to explore another potential effect modifier: the predialysis serum sodium (SNa) and related proxies of plasma tonicity.DISCUSSION/CONCLUSIONIn the FHN Daily Trial, the favorable effects of frequent HD on left-ventricular hypertrophy were more pronounced among patients with lower predialysis SNa and higher GNa and TIFL. Whether these metrics can be used to identify patients most likely to benefit from frequent HD or other dialytic or nondialytic interventions remains to be determined. Prospective, adequately powered studies studying the effect of GNa reduction on mortality and hospitalization are needed.METHODSUsing data from the FHN Daily and Nocturnal Trials, we compared the effects of frequent HD on LVM among patients stratified by SNa, dialysate-to-predialysis serum-sodium gradient (GNa), systolic and diastolic blood pressure, time-integrated sodium-adjusted fluid load (TIFL), and extracellular fluid volume estimated by bioelectrical impedance analysis.

Richard V Remigio, Rodman Turpin, Jochen G Raimann, Peter Kotanko, Frank W Maddux, Amy Rebecca Sapkota, Xin-Zhong Liang, Robin Puett, Xin He, Amir Sapkota

RESULTSBased 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.CONCLUSIONWe 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.BACKGROUNDTypical 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).METHODSThe 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.

Markus Pirklbauer, David A Bushinsky, Peter Kotanko, Gudrun Schappacher-Tilp

Background: Personalized management of secondary hyperparathyroidism is a critical part of hemodialysis patient care. We used a mathematical model of parathyroid gland (PTG) biology to predict (1) short-term peridialytic intact PTH (iPTH) changes in response to diffusive calcium (Ca) fluxes and (2) to predict long-term iPTH levels. Methods: We dialyzed 26 maintenance hemodialysis patients on a single occasion with a dialysate Ca concentration of 1.75 mmol/l to attain a positive dialysate-to-blood ionized Ca (iCa) gradient and thus diffusive Ca loading. Intradialytic iCa kinetics, peridialytic iPTH change, and dialysate-sided iCa mass balance (iCaMB) were assessed. Patient-specific PTG model parameters were estimated using clinical, medication, and laboratory data. We then used the personalized PTG model to predict peridialytic and long-term (6-months) iPTH levels. Results: At dialysis start, the median dialysate-to-blood iCa gradient was 0.3 mmol/l (IQR 0.11). The intradialytic iCa gain was 488 mg (IQR 268). Median iPTH decrease was 75% (IQR 15) from pre-dialysis 277 to post-dialysis 51 pg/ml. Neither iCa gradient nor iCaMB were significantly associated with peridialytic iPTH changes. The personalized PTG model accurately predicted both short-term, treatment-level peridialytic iPTH changes (r = 0.984, p < 0.001, n = 26) and patient-level 6-months iPTH levels (r = 0.848, p < 0.001, n = 13). Conclusions: This is the first report showing that both short-term and long-term iPTH dynamics can be predicted using a personalized mathematical model of PTG biology. Prospective studies are warranted to explore further model applications, such as patient-level prediction of iPTH response to PTH-lowering treatment.