Effectiveness of Bivalent mRNA COVID-19 Vaccine Among Adults With Kidney Failure Receiving Dialysis: A Cohort Study From the Centers for Medicare and Medicaid Services

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.

Luca Neri, Caterina Lonati, Jasmine Ion Titapiccolo, Jennifer Nadal, Heike Meiselbach, Matthias Schmid, Barbara Baerthlein, Ulrich Tschulena, Markus P Schneider, Ulla T Schultheiss, Carlo Barbieri, Christoph Moore, Sonia Steppan, Kai-Uwe Eckardt, Stefano Stuard, Francesco Bellocchio

RESULTSCALIBRA showed good discrimination in both the EuCliD® medical registry (AUC 0.79, 95%CI 0.76-0.81) and the GCKD cohort (AUC 0.73, 95%CI 0.70-0.76). CALIBRA demonstrated improved accuracy compared to the benchmark models in EuCliD® (FHS: ΔAUC=-0.22, p<0.001; ASCVD: ΔAUC=-0.17, p<0.001; INDANA: ΔAUC=-0.14, p<0.001) and GCKD (FHS: ΔAUC=-0.16, p<0.001; ASCVD: ΔAUC=-0.12, p<0.001; INDANA: ΔAUC=-0.04, p<0.001) populations. Accuracy of the CALIBRA score was stable also for patients showing missing variables.BACKGROUND AND OBJECTIVESCardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA).CONCLUSIONCALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings.METHODSCALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD®) and the German Chronic Kidney Disease (GCKD) study prospective cohort. CALIBRA performance was evaluated by c-statistics and calibration charts. In addition, CALIBRA discrimination was compared with that of three validated tools currently used for CV prediction in CKD, namely the Framingham Heart Study (FHS) risk score, the atherosclerotic cardiovascular disease risk score (ASCVD), and the Individual Data Analysis of Antihypertensive Intervention Trials (INDANA) calculator. Superiority was defined as a ΔAUC>0.05.

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.

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.

Connie M Rhee, Meijiao Zhou, Rachael Woznick, Claudy Mullon, Michael S Anger, Linda H Ficociello

RESULTSAt baseline, older patients had lower mean sP, serum albumin, and pre-dialysis weights compared with younger patients. Prescription of SO was associated with a 62% increase in the proportion of patients achieving sP ≤ 5.5 mg/dl and a 42% reduction in daily pill burden. The proportion of patients achieving sP ≤ 5.5 mg/dl after transitioning to SO increased by 113, 96, 68, 77, 61, 37 and 40% among those aged 19-29, 30-39, 40-49, 50-59, 60-69, 70-79, and ≥ 80 years, respectively.CONCLUSIONSOlder patients had worse nutritional parameters, lower pill burden, and lower sP at baseline versus younger counterparts. Prescription of SO was associated with improved sP control and reduced pill burden across all ages.OBJECTIVEDespite the growing number of elderly hemodialysis patients, the influence of age on nutritional parameters, serum phosphorus (sP), and use of phosphate-binder (PB) medications has not been well characterized. We aimed to describe age-related differences in patient characteristics in a large, real-world cohort of maintenance hemodialysis patients, and to examine the impact of age on sP management with sucroferric oxyhydroxide (SO).METHODSWe retrospectively analyzed de-identified data from 2017 adult, in-center hemodialysis patients who switched from another PB to SO monotherapy as part of routine clinical care. Changes in baseline PB pill burden, sP levels, and nutritional and dialytic clearance parameters were assessed across varying age groups through 6 months.

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.

Eric M Montminy, Meijiao Zhou, Colleen Long, Sachin Wani, Swati G Patel, Jordan J Karlitz

No abstract available

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.

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.

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.

Linda H Ficociello, Joanna Willetts, Claudy Mullon, Curtis Johnson, Michael S Anger, Jeffrey L Hymes

No abstract available

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.

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.

Joanna Willetts, Linda H Ficociello, Curtis D Johnson, Sandra E Alexander, Claudy Mullon, Jeffrey L Hymes

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.

Peter Kotanko, Hanjie Zhang, Yuedong Wang

No abstract available

Derek M Blankenship, Len Usvyat, Rachel Lasky, Franklin W Maddux

No abstract available

Derek M Blankenship, Len Usvyat, Michael A Kraus, Dinesh K Chatoth, Rachel Lasky, Joseph E Turk, Franklin W Maddux

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

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.

Adam M Zawada, Melanie Wolf, Abraham Rincon Bello, Rosa Ramos-Sanchez, Sara Hurtado Munoz, Laura Ribera Tello, Josep Mora-Macia, M Amparo Fernández-Robres, Jordi Soler-Garcia, Josep Aguilera Jover, Francesc Moreso, Stefano Stuard, Manuela Stauss-Grabo, Anke Winter, Bernard Canaud

RESULTSPatients who died during follow-up had a significantly lower T50 at baseline as compared to those who survived (269.6 vs. 287.7 min, p = 0.001). A cross-validated model (mean c statistic: 0.5767) identified T50 as a linear predictor of all-cause-mortality (subdistribution hazard ratio (per min): 0.9957, 95% CI [0.9933;0.9981]). T50 remained significant after inclusion of known predictors. There was no evidence for prediction of CV-related outcomes, but for all-cause hospitalizations (mean c statistic: 0.5284).CONCLUSIONT50 was identified as an independent predictor of all-cause mortality among an unselected cohort of hemodialysis patients. However, the additional predictive value of T50 added to known mortality predictors was limited. Future studies are needed to assess the predictive value of T50 for CV-related events in unselected hemodialysis patients.BACKGROUNDVascular calcification is a major contributor to the high cardiac burden among hemodialysis patients. A novel in vitro T50-test, which determines calcification propensity of human serum, may identify patients at high risk for cardiovascular (CV) disease and mortality. We evaluated whether T50 predicts mortality and hospitalizations among an unselected cohort of hemodialysis patients.METHODSThis prospective clinical study included 776 incident and prevalent hemodialysis patients from 8 dialysis centers in Spain. T50 and fetuin-A were determined at Calciscon AG, all other clinical data were retrieved from the European Clinical Database. After their baseline T50 measurement, patients were followed for two years for the occurrence of all-cause mortality, CV-related mortality, all-cause and CV-related hospitalizations. Outcome assessment was performed with proportional subdistribution hazards regression modelling.

Jennifer Rose Parker, Jeanette M Andrade, John Tibbetts, Yue Jiao, John W Larkin, Jeffrey L Hymes

RESULTSLinear regression models showed positive associations between higher serum alb and enPCR with higher whole food snack consumption across follow up (all P < .05). Assessments from baseline to each follow-up month show some increases in serum alb, yet t test comparisons were not significant. No significant changes were seen in serum phosphorus levels during follow-up.OBJECTIVEProtein-energy wasting is common among patients on hemodialysis (HD). This study sought to define effects that a novel, post-HD, high-calorie, high-protein whole food snack had on patients' serum albumin (serum alb), serum phosphorus and equilibrated normalized protein catabolic rate (enPCR).CONCLUSIONAlbeit the catabolic effects of HD are well-known, effective nutritional interventions are scarce. Results showed that providing a whole food snack post-HD to individuals with serum alb <4.0 g/dL may be beneficial but further studies are recommended.METHODSA 12-month (6 months intervention, 6 months pre/post data collection), single-center, unblinded study was conducted. Participants (n = 67) consumed, ad libitum, a whole food snack post-HD for 6 treatments each month. Upon analysis, regression models identified relationships between serum alb and whole food snack consumption across follow up. Predefined effect size anticipated was + 0.2 g/dL. Patients were stratified by high (≥4 g/dL) or low (<4 g/dL) mean serum alb during a 3-month baseline period. Paired t-tests compared mean per patient difference in serum alb, enPCR and serum phosphorus from baseline to each month of follow up, stratified by high (≥640 g) or low (<640 g) consumption of the whole food snack (a priori caloric estimation).

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.

Denny Treu, Michael Ashenuga, Kara Massingham, James Brugger, Luis Medina, Linda H Ficociello, David Thompson

Continuous kidney replacement therapy (CKRT) is often utilized to stabilize patients with severe acute kidney injury associated with significant electrolyte abnormalities and/or oliguria and concomitant fluid accumulation. Circuit downtime may reduce daily treatment time and affect delivered doses of CKRT. Studies have found clotting to be the leading cause of downtime and underdosing, which are associated with negative treatment outcomes. The NxStage Cartridge Express with Speedswap (NxStage Medical, Inc.) was designed to minimize downtime by allowing filter priming to occur in parallel with ongoing CKRT and by permitting filter exchanges without the need to replace the entire cartridge. Data from pilot studies suggest that filter exchanges using this system interrupt treatment by an average of 4 minutes per exchange-a considerable reduction from traditional systems that require treatment to be discontinued while the filter is primed, which can take 30 minutes or more. In addition to increasing patient time on therapy, this system has the potential to reduce costs for patients who require a high number of filter changes, and reduce nursing labor and environmental impact (reduced plastic waste). Future studies should confirm whether patients at higher risk of clotted/clogged filters benefit from CKRT with a system designed for rapid filter changes.

John Larkin, Pasqual Barretti, Thyago Proença de Moraes

No abstract available

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.

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.

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.

Jasmine Ion Titapiccolo, Caterina Lonati, Berit Goethel-Paal, Abraham Rincon Bello, Francesco Bellocchio, Alessandro Pizzo, Maxime Theodose, Maria Eva Baro Salvador, Michaela Schofield, Mario Cioffi, Kolitha Basnayake, Chis Chisholm, Suzanne Mitrovic, Marjelka Trkulja, Hans-Juergen Arens, Stefano Stuard, Luca Neri

RESULTSA total of 6221 patients were included, of which 1238 were from France, 163 Ireland, 1469 Italy, 2633 Spain, and 718 UK. The prevalence of mild-to-severe pruritus was 47.9% (n = 2977 patients). Increased pruritus severity was associated with increased use of antidepressants, antihistamines, and gabapentin. Patients with severe pruritus more likely suffered from diabetes, more frequently missed dialysis sessions, and underwent more hospitalizations due to infections. Both mental and physical QOL scores were progressively lower as the severity of pruritus increased; this association was robust to adjustment for potential confounders.CONCLUSIONThis international real-world analysis confirms that chronic pruritus is a highly prevalent condition among dialysis patients and highlights its considerable burden on several dimensions of patients' life.PURPOSEChronic pruritus significantly impairs hemodialysis patients' health status and quality of life (QOL) and it is associated with higher mortality rate, more frequent hospitalizations, poorer dialysis and medication adherence, and deteriorated mental status. However, pruritus is still underestimated, underdiagnosed, and undertreated in the real-life clinical scenario. We investigated prevalence, clinical characteristics, clinical correlates, severity as well as physical and psychological burden of chronic pruritus among adult hemodialysis patients in a large international real-world cohort.METHODSWe conducted a retrospective cross-sectional study of patients registered in 152 Fresenius Medical Care (FMC) NephroCare clinics located in Italy, France, Ireland, United Kingdom, and Spain. Demographic and medical data were retrieved from the EuCliD® (European Clinical) database, while information on pruritus and QoL were abstracted from KDQOL™-36 and 5-D Itch questionnaire scores.

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.

Carlo Barbieri, Luca Neri, Stefano Stuard, Flavio Mari, José D Martín-Guerrero

Healthcare systems worldwide are currently undergoing significant transformations in response to increasing costs, a shortage of healthcare professionals and the growing complexity of medical needs among the population. Value-based healthcare reimbursement systems are emerging as an attempt to incentivize patient-centricity and cost containment. From a technological perspective, the transition to digitalized services is intended to support these transformations. A Health Information System (HIS) is a technological solution designed to govern the data flow generated and consumed by healthcare professionals and administrative staff during the delivery of healthcare services. However, the exponential growth of digital capabilities and applied advanced analytics has expanded their traditional functionalities and brought the promise of automating administrative procedures and simple repetitive tasks, while enhancing the efficiency and outcomes of healthcare services by incorporating decision support tools for clinical management. The future of HIS is headed towards modular architectures that can facilitate implementation and adaptation to different environments and systems, as well as the integration of various tools, such as artificial intelligence (AI) models, in a seamless way. As an example, we present the experience and future developments of the European Clinical Database (EuCliD®). EuCliD is a multilingual HIS used by 20 000 nurses and physicians on a daily basis to manage 105 000 patients treated in 1100 clinics in 43 different countries. EuCliD encompasses patients' follow-up, automatic reporting and mobile applications while enabling efficient management of clinical processes. It is also designed to incorporate multiagent systems to automate repetitive tasks, AI modules and advanced dynamic dashboards.

Francesco Bellocchio, Hanjie Zhang

No abstract available

Federica Gervasoni, Francesco Bellocchio, Jaroslav Rosenberger, Otto Arkossy, Jasmine Ion Titapiccolo, Vratislava Kovarova, John Larkin, Milind Nikam, Stefano Stuard, Giovanni Luigi Tripepi, Len A Usvyat, Anke Winter, Luca Neri, Carmine Zoccali

RESULTSThe final dataset included 1,249,813 dialysis sessions, and the incidence rate of intradialytic hypotension was 10.07% (95% CI 10.02-10.13). Our models retained good discrimination (AUC around 0.8) and a suitable calibration yielding to the selection of three classification thresholds identifying four distinct risk groups. Variables providing the most significant impact on risk estimates were blood pressure dynamics and other metrics mirroring hemodynamic instability over time.CONCLUSIONSRecurrent symptomatic intradialytic hypotension could be reliably and accurately predicted using routinely collected data during dialysis treatment and standard clinical care. Clinical application of these prediction models would allow for personalized risk-based interventions for preventing and managing intradialytic hypotension.BACKGROUNDIntradialytic hypotension remains one of the most recurrent complications of dialysis sessions. Inadequate management can lead to adverse outcomes, highlighting the need to develop personalized approaches for the prevention of intradialytic hypotension. Here, we sought to develop and validate two AI-based risk models predicting the occurrence of symptomatic intradialytic hypotension at different time points.METHODSThe models were built using the XGBoost algorithm and they predict the occurrence of intradialytic hypotension in the next dialysis session and in the next month. The initial dataset, obtained from routinely collected data in the EuCliD® Database, was split to perform model derivation, training and validation. Model performance was evaluated by concordance statistic and calibration charts; the importance of features was assessed with the Shapley Additive Explanation (SHAP) methodology.

John Larkin, Jeffrey Hymes, Marcus L Britton, Yemmie Oluwatosin, Jacqueline Nolen, Lixia Zhu, Arnold Silva

DISCUSSIONRoxadustat effectively achieved and/or maintained mean Hb levels ≥10.0 g/dL in patients receiving dialysis. The feasibility of incorporating oral roxadustat into dialysis organizations was successfully demonstrated with high dosing adherence. No new safety signals were identified.INTRODUCTIONRoxadustat is an oral hypoxia-inducible factor prolyl hydroxylase inhibitor approved in several regions for the treatment of anemia of chronic kidney disease (CKD). DENALI, a phase 3b study, evaluated the efficacy, safety, and feasibility of roxadustat in patients with anemia of CKD receiving in-center or home dialysis.FINDINGSOf 281 patients screened, 203 were treated and 201 included in the full analysis set. Overall, 166 patients completed the 24-week treatment period and 126 continued into the extension period. Mean baseline Hb was 10.4 g/dL and 82.6% received in-center hemodialysis. Overall, 84.6% of patients achieved a mean Hb ≥ 10.0 g/dL averaged Weeks 16-24. Mean (standard deviation) Hb change from baseline averaged Weeks 16-24 was 0.5 (1.0) g/dL. Prespecified subgroup analyses were consistent with primary analyses. Dosing adherence was 94%. Overall, 3.0% of patients received a red blood cell transfusion at up to Week 24. TEAEs and TESAEs were reported by 71.4% and 25.6% of patients, respectively. The most frequently reported TESAEs were COVID-19 (n = 5; 2.5%), and acute myocardial infarction, pneumonia, and sepsis (each n = 4; 2.0%).METHODSEligible patients received open-label roxadustat, dosed three times weekly for 24 weeks, with an optional extension of ≤1 year. Initial dosing depended on erythropoiesis-stimulating agent (ESA) dose at screening for patients receiving ESAs (≥6 weeks) and weight-based for those not (total <6 weeks). Primary efficacy endpoints were proportion of patients with mean hemoglobin (Hb) ≥10.0 g/dL averaged over Weeks 16-24, and mean Hb change from baseline to the average during Weeks 16-24. Treatment-emergent adverse events (TEAEs) and treatment-emergent serious adverse events (TESAEs) were assessed.

Matteo Savoia, Giovanni Tripepi, Berit Goethel-Paal, Maria Eva Baró Salvador, Pedro Ponce, Daniela Voiculescu, Martin Pachmann, Tomas Jirka, Serkan Kubilay Koc, Wojciech Marcinkowski, Mario Cioffi, Luca Neri, Len Usvyat, Jeffrey L Hymes, Franklin W Maddux, Carmine Zoccali, Stefano Stuard

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

Carol Lee, Katie Bam, Andrea M Bernard, Kimberly Livingston, Patricia B McCarley, Chance Mysayphonh, John W Larkin, Jeffrey L Hymes

The outpatient dialysis setting presents unique challenges in the medication process. Dialysis staff conduct all steps in the medication process, including transcribing and verifying orders, preparing and administering medications, and monitoring for therapeutic and adverse effects. When addressing best medication practices, consideration should be given to education and resources provided to staff. This article explores the multiple strategies taken by a national dialysis network to support clinical staff and improve patient safety.

Juan A Medaura, Meijiao Zhou, Linda H Ficociello, Michael S Anger, Stuart M Sprague

RESULTSThe overall cohort included 596 patients, 286 of whom had a dialysis vintage ≤3 months. In the 3 months preceding SO initiation, sP rapidly increased (mean increases of 1.02 and 1.65 mg/dL in the overall cohort and incident cohort, respectively). SO treatment was associated with significant decreases in quarterly sP (mean decreases of 0.26-0.36; p < 0.0001 for each quarter and overall). While receiving SO, 55-60% of patients achieved sP ≤5.5 mg/dL and 21-24% achieved sP ≤4.5 mg/dL (p < 0.0001 for each quarter and overall vs. baseline). Daily PB pill burden was approximately 4 pills. Serum calcium concentrations increased and intact parathyroid hormone concentrations decreased during SO treatment (p < 0.0001 vs. baseline).CONCLUSIONSAmong patients on hemodialysis, initiating SO as a first-line PB resulted in significant reductions in sP while maintaining a relatively low PB pill burden.INTRODUCTIONSucroferric oxyhydroxide (SO), a non-calcium, chewable, iron-based phosphate binder (PB), effectively lowers serum phosphorus (sP) concentrations while reducing pill burden relative to other PBs. To date, SO studies have largely examined treatment-experienced, prevalent hemodialysis populations. We aimed to explore the role of first-line SO initiated during the first year of dialysis.METHODSWe retrospectively analyzed deidentified data from adults receiving in-center hemodialysis who were prescribed SO monotherapy within the first year of hemodialysis as part of routine clinical care. All patients continuing SO monotherapy for 12 months were included. Changes from baseline in sP, achievement of sP ≤5.5 and ≤4.5 mg/dL, and other laboratory parameters were analyzed quarterly for 1 year.

Harold E Giles, Vidhya Parameswaran, Rachel Lasky, Linda H Ficociello, Claudy Mullon, Dinesh K Chatoth, Michael Kraus, Michael S Anger

RESULTSThe cohort included 11,659 patients. The mean age at PD initiation increased from 2015 (56 [15] years) through 2019 (58 [15] years), whereas most other variables demonstrated no clear temporal change. Most patients (86%) had nighttime PD prescribed, with an average of 4.9 (1.3) cycles per day, a mean total treatment volume of 9.3 (2.5) L, and a median daily total dwell time of 7 (6–9.5) hours. Relative to day 1 nighttime prescriptions, there were (1) small increases in the proportion of patients receiving three or fewer cycles per day and those receiving 6+ cycles per day, (2) a 100 ml mean increase in fill volume per exchange, and (3) a mean 0.5 L increase in total nighttime treatment volume at day 120. When changes in nighttime APD prescriptions were examined at the patient level, 49% of patients had day 120 prescriptions that were unchanged from their initial prescription.KEY POINTSThis is the largest analysis of incident automated peritoneal dialysis (PD) prescriptions conducted in the United States to date. There was limited variability of automated PD prescriptions across the first 4 months of therapy. PD prescriptions tailored to meet the dialysis needs and lifestyle of patients may make PD a more attractive choice and increase longevity on PD.CONCLUSIONSIn the largest analysis of incident APD prescriptions conducted in the United States to date, most patients were prescribed nocturnal PD only with limited variability across the first 4 months of therapy.BACKGROUNDChanges in health care policies and recognition of patient benefit have contributed to increases in home-based dialysis, including peritoneal dialysis (PD). Frequent monitoring and early individualization of PD prescriptions are key prerequisites for the delivery of high-quality PD. The present analysis aimed to assess variations in PD prescriptions among incident automated PD (APD) patients who remain on PD for 120+ days.METHODSThis retrospective analysis examined data from patients within a large dialysis organization that initiated PD with APD between 2015 and 2019. PD prescription data were described by calendar year, timing of PD, and residual renal function categories. Changes in prescriptions from PD initiation (day 1) to day 120 were assessed descriptively.

Mario Garbelli, Francesco Bellocchio, Maria Eva Baro Salvador, Milena Chermisi, Abraham Rincon Bello, Isabel Berdud Godoy, Sofia Ortego Perez, Kateryna Shkolenko, Alicia Sobrino Perez, Diana Samaniego Toro, Christian Apel, Jovana Petrovic, Stefano Stuard, Carlo Barbieri, Flavio Mari, Luca Neri

RESULTSAfter matching, we obtained four groups with 85,512 patient-months each. ACM had 18% higher target achievement rate, 63% smaller inappropriate ESA administration rate, and 59% smaller severe anemia risk compared to Tier 1 centers (all p < 0.01). The corresponding risk ratios for ACM compared to Tier 2 centers were 1.08 (95% CI: 1.08-1.09), 0.49 (95% CI: 0.47-0.51), and 0.64 (95% CI: 0.61-0.68); for ACM compared to Tier 3 centers, 1.01 (95% CI: 1.01-1.02), 0.66 (95% CI: 0.63-0.69), and 0.94 (95% CI: 0.88-1.00), respectively. ACM was associated with statistically significant reductions in ESA dose administration.CONCLUSIONACM was associated with increased hemoglobin target achievement rate, decreased inappropriate ESA usage and a decreased incidence of severe anemia among patients treated according to ACM suggestion.INTRODUCTIONThe Anemia Control Model (ACM) is a certified medical device suggesting the optimal ESA and iron dosage for patients on hemodialysis. We sought to assess the effectiveness and safety of ACM in a large cohort of hemodialysis patients.METHODSThis is a retrospective study of dialysis patients treated in NephroCare centers between June 1, 2013 and December 31, 2019. We compared patients treated according to ACM suggestions and patients treated in clinics where ACM was not activated. We stratified patients belonging to the reference group by historical target achievement rates in their referral centers (tier 1: <70%; tier 2: 70-80%; tier 3: >80%). Groups were matched by propensity score.

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.

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.

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.

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.

Kamyar Kalantar-Zadeh, Linda H Ficociello, Meijiao Zhou, Michael S Anger

RESULTSThe mean age of the 402 patients who completed 1 year of SO was 55.2 years at baseline, and they had been on PD for an average of 19.9 months. SO was initiated with no baseline PB recorded in 36.1% of patients, whereas the remaining 257 patients were switched to SO from sevelamer (39.7%), calcium acetate (30.4%), lanthanum (1.2%), ferric citrate (14.0%), or more than one PB (14.8%). Mean sP at baseline was 6.26 mg/dL. After being prescribed SO, the percentage of patients achieving sP ≤ 5.5 mg/dL increased from 32.1% (baseline) to 46.5-54.0% during the 1-year follow-up, whereas the mean number of PB pills taken per day decreased from 7.7 at baseline (among patients on a baseline PB) to 4.6 to 5.4. Serum phosphorus and PB pill burden decreased regardless of changes in residual kidney function over the 12-month period. Similar results were observed for the full cohort (976 patients who either completed or discontinued SO during the 1-year follow-up).CONCLUSIONSPatients on PD who were prescribed SO as part of routine care for phosphorus management experienced significant reductions in SP and PB pills per day and improvements in sP target achievement, suggesting the effectiveness of SO on SP management with a concurrent reduction in pill burden.BACKGROUNDHyperphosphatemia is associated with increased morbidity and mortality in patients with end-stage kidney disease (ESKD). Whereas clinical and observational studies have demonstrated the effectiveness of sucroferric oxyhydroxide (SO) in controlling serum phosphorus (sP) in ESKD, data on the real-world impact of switching to SO in patients on peritoneal dialysis (PD) are limited. In this retrospective database analysis, we examine the impact of SO on sP management over a 1-year period among PD patients prescribed SO as part of routine clinical care.METHODSWe analyzed de-identified data from adults on PD in Fresenius Kidney Care clinics who were prescribed SO monotherapy between May 2018 and December 2019 as part of routine clinical management. Changes from baseline in sP levels, phosphate binder (PB) pill burden, and laboratory parameters were evaluated during the four consecutive 91-day intervals of SO treatment.

Götz Ehlerding, Wolfgang Ries, Manuela Kempkes-Koch, Ekkehard Ziegler, Petra Ronová, Mária Krizsán, Jana Verešová, Mária Böke, Ansgar Erlenkötter, Robert Nitschel, Adam M Zawada, James P Kennedy, Jennifer Braun, John W Larkin, Natalia Korolev, Thomas Lang, Bertram Ottillinger, Manuela Stauss-Grabo, Bettina Griesshaber

RESULTS82 patients were included and 76 analyzed as intention-to-treat (ITT) population. FX CorAL showed the highest β2-m RR (76.28%), followed by FX CorDiax (75.69%) and xevonta (74.48%). Non-inferiority to both comparators and superiority to xevonta were statistically significant. Secondary endpoints related to middle molecules corroborated these results; performance for small molecules was comparable between dialyzers. Regarding intradialytic hemocompatibility, FX CorAL showed lower complement, white blood cell, and platelet activation. There were no differences in interdialytic hemocompatibility, PROs, or clinical safety.CONCLUSIONSThe novel FX CorAL with increased membrane hydrophilicity showed strong performance and a favorable hemocompatibility profile as compared to other commonly used dialyzers in clinical practice. Further long-term investigations should examine whether the benefits of FX CorAL will translate into improved cardiovascular and mortality endpoints.TRIAL REGISTRATIONeMPORA III registration on 19/01/2021 at ClinicalTrials.gov (NCT04714281).BACKGROUNDHemodialyzers should efficiently eliminate small and middle molecular uremic toxins and possess exceptional hemocompatibility to improve well-being of patients with end-stage kidney disease. However, performance and hemocompatibility get compromised during treatment due to adsorption of plasma proteins to the dialyzer membrane. Increased membrane hydrophilicity reduces protein adsorption to the membrane and was implemented in the novel FX CorAL dialyzer. The present randomized controlled trial compares performance and hemocompatibility profiles of the FX CorAL dialyzer to other commonly used dialyzers applied in hemodiafiltration treatments.METHODSThis prospective, open, controlled, multicentric, interventional, crossover study randomized stable patients on post-dilution online hemodiafiltration (HDF) to FX CorAL 600, FX CorDiax 600 (both Fresenius Medical Care) and xevonta Hi 15 (B. Braun) each for 4 weeks. Primary outcome was β2-microglobulin removal rate (β2-m RR). Non-inferiority and superiority of FX CorAL versus comparators were tested. Secondary endpoints were RR and/or clearance of small and middle molecules, and intra- and interdialytic profiles of hemocompatibility markers, with regards to complement activation, cell activation/inflammation, platelet activation and oxidative stress. Further endpoints were patient reported outcomes (PROs) and clinical safety.

Carmine Zoccali, Giovanni Tripepi, Paola Carioni, Edouard L Fu, Friedo Dekker, Vianda Stel, Kitty J Jager, Francesca Mallamaci, Jeffrey L Hymes, Franklin W Maddux, Stefano Stuard

RESULTSCalcium channel blocker (CCB) use was associated with an IDH incidence rate of 7.4 events per person-year (95% confidence interval [CI], 6.2 to 8.6). Compared with CCB use, use of β and α–β blockers was strongly associated with a higher likelihood of IDH (odds ratio [OR] [95% CI, 2.27; 1.50 to 3.43]). The use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (OR [95% CI, 1.71; 1.14 to 2.57]) and diuretics (OR [95% CI, 1.52; 1.07 to 2.16]) were also associated with a higher likelihood of IDH compared with CCB use.KEY POINTSAntihypertensive medications are often used by hemodialysis patients, and intradialytic hypotension is a common complication in these patients. The study emulates a randomized clinical trial comparing antihypertensive drug treatment for the risk of hemodialysis hypotension in 4072 incident patients. Compared with calcium antagonists, β and α–β blockers, angiotensin converting enzyme inhibitors or angiotensin II antagonists, and diuretics may increase the risk of hemodialysis hypotension.CONCLUSIONSThe study suggests that using β and α–β blockers, angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, and diuretics may increase the risk of IDH in hemodialysis patients compared with CCB use.BACKGROUNDAntihypertensive medications are often prescribed to manage hypertension in hemodialysis patients, and intradialytic hypotension (IDH) is a common complication in these patients. We investigated the risk of IDH in incident hemodialysis patients who initiated treatment with antihypertensive drugs in monotherapy.METHODSThe study was conducted as an emulation of a randomized clinical trial in 4072 incident hemodialysis patients who started antihypertensive drug treatment between January 2016 and December 2019. The primary outcome was the occurrence of IDH during hemodialysis sessions. The generalized estimating equation analysis was adjusted by inverse probability treatment weighting.

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.

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.

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.

Mario Garbelli, Maria Eva Baro Salvador, Abraham Rincon Bello, Diana Samaniego Toro, Francesco Bellocchio, Luca Fumagalli, Milena Chermisi, Christian Apel, Jovana Petrovic, Dana Kendzia, Jasmine Ion Titapiccolo, Julianna Yeung, Carlo Barbieri, Flavio Mari, Len Usvyat, John Larkin, Stefano Stuard, Luca Neri

RESULTSA total of 20,209 eligible patients were considered (reference group: 17,101; ACM adherent group: 3108). Before matching, the mean age was 65.3 ± 14.5 years, with 59.2% men. Propensity score matching resulted in two groups of 1950 patients each. Matched ACM adherent and non-ACM patients showed negligible differences in baseline characteristics. Hospitalization rates were lower in the ACM group both before matching (71.3 vs. 82.6 per 100 person-years, p < 0.001) and after matching (74.3 vs. 86.7 per 100 person-years, p < 0.001). During follow-up, 385 patients died, showing no significant survival benefit for ACM-guided care (hazard ratio = 0.93; p = 0.51).CONCLUSIONSACM-guided anemia management was associated with a significant reduction in hospitalization risk among hemodialysis patients. These results further support the utility of ACM as a decision-support tool enhancing anemia management in clinical practice.INTRODUCTIONThe management of anemia in chronic kidney disease (CKD-An) presents significant challenges for nephrologists due to variable responsiveness to erythropoietin-stimulating agents (ESAs), hemoglobin (Hb) cycling, and multiple clinical factors affecting erythropoiesis. The Anemia Control Model (ACM) is a decision support system designed to personalize anemia treatment, which has shown improvements in achieving Hb targets, reducing ESA doses, and maintaining Hb stability. This study aimed to evaluate the association between ACM-guided anemia management with hospitalizations and survival in a large cohort of hemodialysis patients.METHODSThis multi-center, retrospective cohort study evaluated adult hemodialysis patients within the European Fresenius Medical Care NephroCare network from 2014 to 2019. Patients treated according to ACM recommendations were compared to those from centers without ACM. Data on demographics, comorbidities, and dialysis treatment were used to compute a propensity score estimating the likelihood of receiving ACM-guided care. The primary endpoint was hospitalizations during follow-up; the secondary endpoint was survival. A 1:1 propensity score-matched design was used to minimize confounding bias.

Karlien J Ter Meulen, Paola Carioni, Francesco Bellocchio, Frank M van der Sande, Heleen J Bouman, Stefano Stuard, Luca Neri, Jeroen P Kooman

RESULTSWe included 12 897 patients with dialysate calcium 1.25 mmol/l and 26 989 patients with dialysate calcium 1.50 mmol/l. The median age was 65 years, and 61% were male. The unadjusted risk of all-cause mortality was higher for dialysate calcium 1.50 mmol/l [hazard ratio (HR) 1.07, 95% confidence intervals (CI) 1.01-1.12]. However, in the fully adjusted model, no significant differences were noted (HR 1.05, 95% CI 0.99-1.12). Similar results were observed for the risk of cardiovascular mortality (HR 1.03, 95% CI 0.94-1.13). Adjusted risk of sudden cardiac death was lower for dialysate calcium 1.50 mmol/l (HR 0.81, 95% CI 0.67-0.97). Significant and positive associations with all outcomes were observed with larger serum-to-dialysate calcium gradients, primarily mediated by the serum calcium level.CONCLUSIONSIn contrast to the unadjusted analysis that showed a higher risk for dialysate calcium of 1.50 mmol/l, after adjusting for confounders, there were no significant differences in the risk of all-cause and cardiovascular mortality between dialysate calcium concentrations of 1.50 and 1.25 mmol/l. After adjustment, a lower risk of sudden cardiac death was observed in patients with dialysate calcium 1.50 mmol/l. A higher serum-to-dialysate calcium gradient is associated with an increased risk for adverse outcomes.BACKGROUNDThe appropriate prescription of dialysate calcium concentration for hemodialysis is debated. We investigated the association between dialysate calcium and all-cause, cardiovascular mortality and sudden cardiac death.METHODSIn this historical cohort study, we included adult incident hemodialysis patients who initiated dialysis between 1 January 2010 and 30 June 2017 who survived for at least 6 months (grace period). We evaluated the association between dialysate calcium 1.25 or 1.50 mmol/l and outcomes in the 2 years after the grace period, using multivariable Cox regression models. Moreover, we examined the association between the serum dialysate to calcium gradient and outcomes.

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.

John W Larkin, Suman Lama, Sheetal Chaudhuri, Joanna Willetts, Anke C Winter, Yue Jiao, Manuela Stauss-Grabo, Len A Usvyat, Jeffrey L Hymes, Franklin W Maddux, David C Wheeler, Peter Stenvinkel, Jürgen Floege

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

Abraham Rincon Bello, Jasmine Ion Titapiccolo, Isabel Berdud Godoy, Diana J C Samaniego, Sofia Ortego Perez, Alicia Sobrino Perez, Kateryna Shkolenko, Stefano Stuard, Luca Neri, Maria Eva Baró Salvador

RESULTSA total of 2280 (51.5%) completed the self-administrated survey, and 1838 patients met the inclusion/exclusion criteria of the study. Higher HRQoL scores were associated with significantly lower mortality and hospitalization risk. Risk estimates were robust to adjustment for potential confounders.RATIONALE & OBJECTIVEEnd-stage kidney disease (ESKD) negatively affects patients' physical, emotional, and social functioning. Furthermore, adjustment to dialysis require substantial lifestyle changes that may further impact on patients physical and emotional well-being. However, the relationship between Health-Related Quality of life impairment with future adverse outcomes in dialysis is not well characterized. Our study aims to investigate the relationship between Health-Related Quality of Life (HRQoL) and patients' survival and hospitalization rates within a large European dialysis network.CONCLUSIONSSeveral dimensions of HRQoL are associated with patient-centered outcomes (i.e., mortality and hospitalizations at 1 year). Patient-Reported Outcomes contribute unique pieces of information characterizing patients' health. Residual confounding cannot be fully ruled out; moreover, the high attrition rate could result in selection bias, which may limit the generalizability of the findings to a broader population.METHODSA historical cohort study was conducted to evaluate association of HRQoL with hospitalization and mortality rates over a 12-month follow-up period. Patients responded to a self-administered survey as part of a Continuous Quality Improvement Program implemented in clinics affiliated with the Spanish FMC-Nephrocare organization. Health-Related Quality of Life (HRQoL) was measured with the KDQOL-36. Potential confounders included socio-demographic characteristics, comorbidities, biochemical parameters, dialysis treatment. We used Cox's Proportional Hazard regression to assess the hazard of death and Logistic Regression to assess the likelihood of hospital admissions during 12-month follow-up period.

Christopher Atzinger, Hans-Jürgen Arens, Luca Neri, Otto Arkossy, Mario Garbelli, Alina Jiletcovici, Robert Snijder, Kirsten Leyland, Najib Khalife, Mahmood Ali, Astrid Feuersenger

RESULTSIn total, 85,259 patients were included in the analysis; 59.9% were male, median (interquartile range) ESA starting dose was 733.3 (400.0, 1200.0) IU/week and follow-up duration was 2.2 (1.0, 4.2) years. Incidence of ESA hyporesponsiveness varied when applying different definitions; NICE 0.05/1000 days (5.2% of patients), ERI 0.40/1000 days (40.7%), KDIGO 0.15/1000 days (15.4%), and clinical practicality algorithm 0.48/1000 days (47.9%). ESA doses remained higher in hyporesponsive versus responsive patients, yet haemoglobin levels were similar between groups.Some people living with kidney disease may also have anaemia (low numbers of blood cells). This can increase their risk of heart disease and reduce their quality of life. Treatments for anaemia in people living with kidney disease include iron supplements and drugs that stimulate the production of red blood cells, known as erythropoiesis-stimulating agents. However, some people have weak responses to erythropoiesis-stimulating agents, and high doses can cause side effects. We looked at how the percentage of people with weak responses to erythropoiesis-stimulating agents varied when using different criteria to identify them. We also looked at the clinical characteristics of people who experienced a weak response after 1 year and those who did not. To do this, we reviewed medical records from people treated at specialist kidney care centres across 24 countries from Europe and South Africa. We included medical records between 1 January 2015 and 31 December 2021. Depending on what criteria we used, the percentage of people living with kidney disease and anaemia who were identified as having weak responses to erythropoiesis-stimulating agents varied greatly, from 5.2% to 47.9%. People living with kidney disease and anaemia who have weak responses to treatment with erythropoiesis-stimulating agents need adjustments to their care to address this. However, our research shows that the different criteria used to identify these patients can affect how many are identified, and may affect their care. Therefore, all patients with kidney disease and anaemia should be carefully monitored.TRIAL REGISTRATIONNCT05530291.CONCLUSIONThe results from this study, which applied multiple hyporesponsiveness definitions to a large, geographically diverse population of patients with anaemia of CKD, showed variation in ESA hyporesponsiveness incidence rates depending on definitions used and higher ESA doses in hyporesponsive versus responsive patients. These results underscore the need for individualised clinical assessment and thorough evaluation when considering ESA dose adjustments to reach haemoglobin targets. Graphical abstract available for this article.INTRODUCTIONHyporesponsiveness to erythropoiesis-stimulating agents (ESAs) in patients with anaemia of chronic kidney disease may lead to increased ESA doses to achieve target haemoglobin levels; however, elevated doses may be associated with increased mortality. Furthermore, patients with hyporesponsiveness to ESAs have poorer clinical outcomes than those who respond well to ESAs. Incidence and clinical characteristics of patients with ESA hyporesponsiveness were explored in a real-world setting.METHODSThis was a retrospective study of electronic medical records of adults with stage 5 chronic kidney disease receiving renal replacement therapy and ESA treatment, from 1 January 2015 to 31 December 2021. The primary objective was ESA hyporesponsiveness rate/1000 days, with a hyporesponsive event defined as ESA use at an elevated dose, according to National Institute for Health and Care Excellence (NICE) criteria. Other hyporesponsiveness definitions applied were erythropoietin resistance index-defined ESA hyporesponsiveness (ERI) Kidney Disease Improving Global Outcomes (KDIGO) and a clinical practicality algorithm.

Paul Bennett, Madeleine Warren, Zehra Aydin, Joachim Beige, Elaine Bowes, Michael Cheung, Jeanette Finderup, Daniel Gallego, Manfred Hecking, Helen Hurst, Jennifer M King, Werner Kleophas, Anastasia Liossatou, Pedro Martins, Afra Masià-Plana, Yvette Meuleman, Luca Neri, Edita Noruišienė, John Ortiz, Marianne Rix, Stefano Stuard, Yusuke Tsukamoto

Adults with kidney failure receiving dialysis frequently report high symptom burden that can limit life participation and decrease the quality of life. Fatigue, itch, pain, anxiety, depressive symptoms, sleep problems, nausea, vomiting, muscle cramps, breathlessness, and decreased cognition can negatively impact important daily activities. Nurses are the majority health professional group that provides care for people receiving dialysis and have a major role in managing these symptoms. However, routine symptom management by nurses is not universal or standardized in dialysis care. In December of 2023, Kidney Disease: Improving Global Outcomes (KDIGO) held a workshop on the Nurse's Role in Managing the Symptoms of People Receiving Dialysis. The discussions focused on the current barriers nurses face when identifying and assessing symptoms, strategies for identifying symptoms, and the ongoing monitoring and management of symptoms. Nephrology nurses are pivotal in supporting the person with kidney failure receiving dialysis to minimize symptoms, optimize symptom management, decrease dialysis treatment burden, and improve life participation and quality of life.

Lin-Chun Wang, Hanjie Zhang

No abstract available

Caitlin K Monaghan, Joanna Willetts, Hao Han, Sheetal Chaudhuri, Linda H Ficociello, Michael A Kraus, Harold E Giles, Len Usvyat, Joseph Turk

No abstract available

Carmine Zoccali, Giovanni Tripepi, Paola Carioni, Francesca Mallamaci, Matteo Savoia, Len S Usvyat, Franklin W Maddux, Stefano Stuard

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

Jasmine Ion Titapiccolo, Luca Neri, Thilo Schaufler, Hans-Jurgen Arens, Len Usvyat, Stefano Stuard, Marco Soro

RESULTSWe observed a consistent and graded association between the severity of CKD-aP and the use of antidepressant, systemic antihistamines, and gabapentinoid medications. This association remained consistent and intensified over the duration of the year after pruritus screening. This trend was robust even after accounting for potential confounding factors.CONCLUSIONSPatterns of antipruritic medication use in a cohort of patients with CKD-aP was identified and the frequent use of off-label treatments in the absence of approved therapies was highlighted. These observations reflect clinical practices aimed at managing severe pruritus but do not imply a causal relationship between the medications and pruritus severity. Even though we cannot exclude the possibility that these drugs have been prescribed to treat medical conditions warranting their use, previous evidence suggested that doctors may also use such medications in an attempt to buffer CKD-aP. These findings underline the importance of further elucidating current treatment strategies adopted in clinical practice to address CKD-aP.INTRODUCTIONChronic kidney disease-associated pruritus (CKD-aP) is a common, yet underdiagnosed condition among patients on hemodialysis. Considering the lack of established treatment pathways, we sought to evaluate the use of antidepressant, systemic antihistamines, or gabapentinoid medications among patients with CKD-aP in the year following pruritus assessment.METHODSWe included 6209 patients on hemodialysis in the analysis. We retrospectively extracted clinical and patient-reported data from electronic health records. The intensity of CKD-aP was assessed by KDQOL-36 and 5-D Itch questionnaires. Prescription of antidepressant, antihistamine, and gabapentinoids was ascertained by the occurrence of a relevant active medical order in patients' medical records.

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.

Ashwini R Sehgal, Suman Lama, Sheetal Chaudhuri, Xiaoyue Zhang, Hossein T Ghazvini, Franklin W Maddux

No abstract available

Paolo Fabbrini, Federico Pieruzzi, Francesco Bellocchio, Raul Casana Eslava, Jordi Silvestre Llopis, Kevin Morillo Navarro, Paola Ferraresi, Len Usvyat, John Larkin, Jaroslav Rosemberg, Stefano Stuard, Luca Neri

RESULTSWe included 2005 patients who underwent 11,757 outpatient nephrology visits in 4 years. Most visits occurred for NDD-CKD stage 4 patients; the incidence of KRT onset was 10.8 and 9.32/100 patient-years at the 6 and 24-month prediction horizon cohorts, respectively. PROGRES-CKD demonstrated high accuracy in predicting KRT initiation at 6 and 24 months (AUROC = 0.88 and AUROC = 0.85, respectively). Nephrologists' prognostic performance was highly operator-dependent, albeit always significantly lower than PROGRES-CKD. In the simulation exercise, allocation based on PROGRES-CKD resulted in more follow-up visits for patients progressing to end-stage kidney disease (ESKD) and fewer visits for non-progressing patients, compared to allocation determined by nephrologists' prognosis.CONCLUSIONSPROGRES-CKD showed high accuracy in a real-world application. Waiting list simulation suggests that PROGRES-CKD may enable more efficient allocation of resources.BACKGROUNDThe management of patients with non-dialysis dependent chronic kidney disease (NDD-CKD) is challenging due to coexisting diseases, competing risks and uncertainties around optimal transition planning. Such clinical challenges are further exacerbated by physician shortage, coupled with rising service demands, which may hinder timely medical access due to long waiting times. Accurate progression risk assessment may help optimize resource allocation and adapting care based on individual patients' needs. This study validated the Prognostic Reasoning System for Chronic Kidney Disease Progression (PROGRES-CKD) in an Italian public hospital and compared its potential impact on waiting list optimization against physician-based protocols.METHODSFirst we first validated PROGRES-CKD by assessing its accuracy in predicting kidney replacement therapy (KRT) initiation within 6 months and 24 months in a historical cohort of patients treated at the San Gerardo Hospital (Italy) between 01-01-2015 and 31-12-2019. In a second study we compared PROGRES-CKD to attending nephrologists' prognostic ratings and simulated their potential impact on a waiting list management protocol.

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.

Linda H Ficociello, Rachel Lasky, Hans-Juergen Arens, Despina Ruessmann, Michael S Anger

RESULTSMean (SD) baseline WI-NRS scores were 8.5 (1.7), indicative of severe pruritic symptomatology. In the 22% of patients with follow-up data, mean WI-NRS scores improved by 2.9 points (8.4 [severe] to 5.4 [moderate]; P < 0.0001). This mean improvement was more pronounced in CRG patients (n = 84; 3.6) compared with IRG patients (n = 84; 2.2). Overall, 46% of patients experienced a 3-point reduction in itch severity. Difelikefalin initiation was not associated with changes in rates of nausea, diarrhea, vomiting, headache, or trouble walking. Dizziness and hyperkalemia were infrequent, but statistically significant with increases in dizziness (0.09% vs. 0.20%) and hyperkalemia (2.0% vs. 2.6%) were observed during treatment with difelikefalin.CONCLUSIONSIn this analysis of real-world difelikefalin use in a US hemodialysis population, patients experienced significant reductions in CKD-aP, based on a validated measure of pruritus. Patients remaining on therapy for 12 weeks demonstrated greater symptom reductions than those patients receiving partial treatment. In combination with controlled trials, these data suggest that difelikefalin is an effective and well-tolerated treatment for the management of CKD-aP in adult patients receiving hemodialysis.BACKGROUNDChronic kidney disease-associated pruritus (CKD-aP) can negatively impact quality of life and survival among patients receiving maintenance hemodialysis. Difelikefalin, a selective κ-opioid receptor agonist, is the first medication approved for treatment of moderate-to-severe CKD-aP among patients on chronic hemodialysis. This retrospective database study assessed the real-world safety and effectiveness of difelikefalin across a large US dialysis organization.METHODSWe analyzed de-identified data from 715 adult hemodialysis patients treated with difelikefalin who had a Worst Itching Intensity Numerical Rating Scale (WI-NRS) score (0 = no itching to 10 = worst itch imaginable) assessed before therapy. Patients were classified as having received at least 30 difelikefalin doses over 12 weeks (complete regimen group; CRG) or fewer doses over that time period (incomplete regimen group; IRG). Mean baseline and follow-up WI-NRS scores were compared and potential adverse events evaluated.

Amanda B Payne, Shannon Novosad, Heng-Ming Sung, Yue Zhang, Ryan Wiegand, Carla S Gomez Victor, Megan Wallace, Danica J Gomes, Morgan Najdowski, Bradley Lufkin, Yoganand Chillarige, Eduardo Lacson, Lorien S Dalrymple, Ruth Link-Gelles

RESULTSDuring September 17, 2023 - April 13, 2024, 17,749/112,250 (16 %) Medicare beneficiaries aged ≥18 years with ESKD without additional immunocompromising conditions received a 2023-2024 COVID-19 vaccine dose, with a maximum 209 days of follow-up since vaccination. During the follow-up period 6539 medically attended COVID-19 events, including 3605 COVID-19-associated hospitalizations, 789 COVID-19-associated deaths, and 896 COVID-19-associated thromboembolic events, were recorded. VE against COVID-19-associated hospitalization was 55 % (95 % confidence interval [CI]: 42 % - 65 %) at 7-59 days after vaccination and 47 % (95 % CI: 35 % - 57 %) at ≥60 days after vaccination. VE against COVID-19-associated death was 71 % (95 % CI: 46 % - 84 %) at 7-59 days after vaccination and 51 % (95 % CI: 24 % - 69 %) ≥60 days after vaccination. VE against COVID-19-associated thromboembolic events was 44 % (95 % CI, 24 %, 59 %).CONCLUSIONSThe 2023-2024 COVID-19 vaccines provided protection against COVID-19-associated hospitalization, death, and thromboembolic events among adults with ESKD. These data support the recommendation that adults with ESKD receive the updated COVID-19 vaccine.BACKGROUNDPersons with end stage kidney disease (ESKD) on dialysis are at high risk for severe COVID-19 disease. In September 2023, 2023-2024 COVID-19 vaccination was recommended in the United States for all persons aged ≥6 months. Due to possible immune dysfunction, advanced age, and high prevalence of additional underlying conditions, including immunocompromising conditions, among individuals with ESKD, reduced vaccine effectiveness (VE) is a concern. Understanding effectiveness of 2023-2024 COVID-19 vaccine among persons with ESKD can inform COVID-19 vaccine recommendations for this population.METHODSA retrospective cohort investigation was conducted among Medicare fee-for-service beneficiaries aged ≥18 years with ESKD receiving dialysis using Medicare enrollment and claims records. Follow-up began on September 17, 2023, and continued until the earliest occurrence of claim for a COVID-19-associated outcome, other censoring event, or end of follow-up. A marginal structural Cox model was used to estimate VE (calculated as [1 - hazard ratio]*100 %), interpreted as the benefit of 2023-2024 COVID-19 vaccination compared with no 2023-2024 vaccine dose. VE was estimated by presence of additional immunocompromising conditions, age group, and time since vaccination.

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.

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.

Linda H Ficociello, Rachel Lasky, Hans-Juergen Arens, Despina Ruessmann, Michael S Anger

No abstract available

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.

Jyana G Morais, Murilo Guedes, Ana B Barra, John W Larkin, Maria E F Canziani, Roberto Pecoits-Filho, Fabiana B Nerbass

CONCLUSIONIn a multicenter HD population, higher thirst perception was an independent determinant of diminished health-related quality of life.INTRODUCTIONThirst distress is a common yet underexplored symptom among hemodialysis (HD) patients, with limited understanding of its impact on quality of life. This study aims to evaluate thirst perception, identify factors associated with its intensity, and examine its relationship with quality of life in a multicenter cohort of HD patients.FINDINGSThe study sample comprised 195 patients (male: 71%; median age: 54 [41-66] years; 29% with diabetes) from 13 dialysis centers, with chronic HD duration up to 24 months. The median DTI score was 17 (14-22). Participants with higher thirst perception (DTI > 17) were younger, had a higher prevalence of lower income and educational levels, and a lower prevalence of fluid overload. Multiple regression analysis, adjusted for demographic, clinical, and nutritional variables, revealed that increased thirst perception was independently associated with poorer physical and mental HRQoL.METHODSThis cross-sectional analysis utilized baseline data from the Hemodiafiltration on Physical Activity and Self-Reported Outcomes: A Randomized Controlled Trial (HDFit). Participants were over 18 years old from 13 dialysis units across Brazil. Thirst perception was assessed using the Dialysis Thirst Inventory (DTI) questionnaire, and health-related quality of life (HRQoL) was measured with the SF-36 questionnaire. We compared participants with low versus high thirst perception based on the median DTI score and conducted multiple regression analysis to identify independent determinants of physical and mental HRQoL components.

Na'amah Razon, Yi Zhang, Bethney Bonilla-Herrera, Lorien S Dalrymple, Amanda Stennett, Baback Roshanravan, Daniel Tancredi, Joshua J Fenton

RESULTSIn this study, 115,982 individuals (mean age 63 years, 43% female, 74% residing in urban setting) met the inclusion criteria. Nearly one-third (27%) did not have private transportation, defined as driving themselves or having a friend or family member drive them to dialysis. All individuals who lacked private transportation had higher mortality at one-year follow-up compared to those with private transportation: adjusted Incident Rate Ratio (aIRRs) (95%CI's) 1.25 (1.19-1.30), 1.21 (1.15-1.28), 1.70 (1.55-1.86), and 1.09 (1.02-1.17) for Medicaid, paratransit (available for individuals with a disability or a disabling health condition), private pay non-emergency medical transportation, and public transit, respectively. Medicaid, paratransit, and public transportation users were more likely to miss dialysis treatments compared to those with a private ride: aIRRs (95%CIs) 1.31 (1.27-1.35), 1.15 (1.11-1.20), and 1.24 (1.18-1.30), respectively. All non-private transportation users had higher likelihood of missed dialysis treatments attributed to transportation: aIRRs (95%CIs) 2.78 (2.62-2.94), 2.55 (2.35-2.76), 1.83 (1.58-2.12), and 2.73 (2.47-3.01) for Medicaid, paratransit, private pay non-emergency medical transportation, and public transit, respectively.CONCLUSIONA lack of private transportation was associated with higher risk of missed dialysis treatments and mortality in adults with ESKD treated with in-center HD.BACKGROUNDTransportation insecurity for people with end stage kidney disease (ESKD) treated with in-center hemodialysis (HD) may be a modifiable social risk that if addressed could improve access to dialysis treatments and lower mortality and complications associated with ESKD.METHODSRetrospective, national cohort study between April 1, 2022 through March 31, 2023. The study included all adults with ESKD receiving in-center HD within a large dialysis organization for at least 90 days prior to April 1, 2022 and having completed at least one transportation assessment. Primary outcomes were missed dialysis treatments and mortality. Primary exposure was the mode of transportation to dialysis.

Zaipul I Md Dom, Salina Moon, Eiichiro Satake, Daigoro Hirohama, Nicholette D Palmer, Heather Lampert, Linda H Ficociello, Amin Abedini, Karen Fernandez, Xiujie Liang, Sara Pickett, Jonathan Levinsohn, Kristina O'Neil, Simon T Dillon, Michael Mauer, Andrzej T Galecki, Barry I Freedman, Katalin Susztak, Alessandro Doria, Andrzej S Krolewski, Monika A Niewczas

Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes and advanced DKD followed for 1,804 person-years. The top 5% urinary proteins representing multiple components of the Complement system (C2, C5a, CL-K1, C6, CFH and C7) are robustly associated with 10-year kidney failure risk, independent of clinical covariates. We confirm the top proteins in three early-to-moderate DKD cohorts (2,982 person-years). Associations are especially pronounced in advanced kidney disease stages, similar between the two diabetes types and far stronger for urinary than circulating proteins. We also observe increased Complement protein and single cell/spatial RNA expressions in diabetic kidney tissue. Here, our study shows Complement engagement in DKD progression and lays the groundwork for developing biomarker-guided treatments.

Carmine Zoccali, Giovanni Tripepi, Paola Carioni, Francesca Mallamaci, Matteo Savoia, Len A Usvyat, Franklin W Maddux, Stefano Stuard

RESULTSHigher variability in fluid overload significantly increased mortality risk. A 1 % increase in the SD of the FO/ECW ratio was linked to a 5.3 % increase in the hazard ratio for mortality (HR: 1.053, 95 % CI: 1.045-1.062, p < 0.001). Patients in the highest quartile of fluid overload variability had a 46 % higher risk of death than those in the lowest quartile (HR: 1.46, 95 % CI: 1.28-1.67, p < 0.001). These associations remained consistent in patients who survived beyond the first and second years.CONCLUSIONSFluid overload variability significantly predicts mortality in KF patients, independent of average fluid overload levels, variability in BP pressure, and other potential confounders. Comprehensive fluid management strategies addressing both the level and variability of fluid status may improve clinical outcomes. Randomized controlled trials are necessary to confirm our hypothesis-generating findings.BACKGROUNDThe prognosis for kidney failure (KF) patients on long-term hemodialysis is poor, with fluid overload being a significant modifiable risk factor for mortality. Previous studies have focused on static measurements of fluid status, but the impact of long-term fluid fluctuations on clinical outcomes has not been thoroughly investigated.METHODSWe studied a cohort of 9,178 incident KF patients at Fresenius NephroCare dialysis centers across seven countries in Europe and the Middle East. Fluid status was assessed using bioimpedance spectroscopy, providing precise measurements of the fluid overload/extracellular water (FO/ECW) ratio. Fluid overload variability was calculated as the standard deviation (SD) of the FO/ECW ratio over the first three years. Time-dependent Cox regression models, adjusted for 47 covariates, evaluated the association between fluid overload variability and one-year mortality. We also analyzed mortality risk by quartiles of fluid overload variability.

Afschin Gandjour, Christian Apel, Dana Kendzia, Luca Neri, Francesco Bellocchio, Len Usvyat, John Larkin, Jovana Petrovic Vorkapic

RESULTSThis study finds that ACM provides more QALYs and incurs lower costs compared to standard of care. The net monetary value of ACM is €38,423 per patient in the base case scenario. In the sensitivity analysis, the annual cost of erythropoiesis-stimulating agents emerged as the variable with the largest impact on the value of ACM. The probabilistic sensitivity analysis shows that 100% of cost-effect pairs fall within the dominant southeast quadrant, indicating cost-effectiveness.CONCLUSIONSThis modelling study demonstrates that ACM is cost-effective for managing anemia in German in-center HD patients.BACKGROUNDThe Anemia Control Model (ACM) is a decision support system powered by an artificial intelligence core designed to assist nephrologists in managing anemia therapy for in-center hemodialysis (HD) patients. This study aims to evaluate the cost-effectiveness of the ACM compared to standard of care in Germany, defined as the absence of ACM and a hemoglobin (Hb) target achievement rate of less than 70% among in-center HD patients, based on results from matched observational studies.METHODSThis simulation study adopted the perspective of the German statutory health insurance. A Markov (cohort) state-transition model was used to project the effects of the ACM over the remaining lifetime of patients. All costs were expressed in 2024 euros, and both costs and quality-adjusted life years (QALYs) were discounted at a rate of 3% per year. To test the sensitivity of the results, one-way sensitivity analyses and a probabilistic sensitivity analysis were performed.

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.

Carmine Zoccali, Giovanni Tripepi, Francesca Mallamaci, Len S Usvyat, Franklin W Maddux, Stefano Stuard

Intradialytic hypotension (IDH) is a significant complication in haemodialysis (HD) patients, affecting cardiovascular stability and treatment outcomes. Antihypertensive medications, while crucial for blood pressure control, can exacerbate IDH, necessitating careful drug selection and management. This review highlights the differential effects at the HD population level of drug classes such as beta and alpha-beta blockers, angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II antagonists, diuretics and calcium antagonists. Beta and alpha-beta blockers are linked to a higher risk of IDH due to their impact on heart rate and myocardial contractility, which can impair cardiovascular reflexes during dialysis. ACEIs and angiotensin II antagonists may increase the risk of hypotension by reducing vascular resistance. Diuretics can worsen volume depletion, especially when combined with ultrafiltration. Conversely, calcium antagonists have been associated with a lower risk of IDH in low-power clinical studies. Target trials represent an opportunity to generate high-quality evidence in the absence of randomized controlled trial (RCT) data. To fill the knowledge gap, this review discusses a target trial emulation study by Zoccali et al. that provides insights into the comparative risks of antihypertensive drugs using observational data. This study underscores the need for individualized treatment plans and highlights the importance of further research, particularly RCTs, to validate findings and explore long-term cardiovascular outcomes. This review aims to guide clinicians in optimizing antihypertensive therapy for HD patients, balancing effective blood pressure control with minimizing IDH risk.

Kunal Malhotra, Tejas Desai, Linda H Ficociello, Hans-Juergen Arens, Rachel A Lasky, Michael S Anger

RESULTSOf the 243,168 adults receiving hemodialysis during the study period who completed a KDQOL-36, 47,477 reported at least moderate bother from pruritus. An additional randomly sampled 33,833 adults not reporting at least moderate pruritus were also included. The KDQOL-36 ratings for each symptom (sleep disturbance, depression, pain, anxiety, and low energy/fatigue) exhibited a significantly (P < 0.001) greater burden with increased pruritus severity. Similar results were observed for KDQOL-36 summary scores. Extreme pruritus was associated with greater than 5-fold and 3-fold increased risk of depressive symptoms and sleep disturbance, respectively. Pruritus was also independently associated with Patient Health Questionnaire-2-defined depressive symptoms. The association of pruritus with co-occurring symptoms was demonstrated across all serum phosphorus concentration subgroups. Patients reporting higher degrees of bother from pruritus were significantly more likely to miss multiple hemodialysis sessions or have shortened treatment sessions.This study of adults receiving hemodialysis examined the relationship between pruritus and the individual symptoms of sleep disturbance, depression, pain, anxiety, and low energy/fatigue. Data from the Kidney Disease Quality of Life 36-Item Short Form Survey and the Patient Health Questionnaire-2 were extracted from electronic medical records. The analysis found that the presence of at least moderate patient-reported pruritus was independently associated with depressive symptoms. The risk of sleep disturbance, depressive symptoms, pain, anxiety, and low energy is significantly increased among patients with pruritus. Routine quality-of-life screening is warranted; identification of one symptom should prompt inquiry about other symptoms.RATIONALE & OBJECTIVEChronic kidney disease-associated pruritus is commonly related to reduced health-related quality of life, decreased adherence to dialysis, and increased mortality, yet it remains underrecognized and underdiagnosed. We conducted an analysis to characterize the relationship between pruritus and a recognized symptom cluster among hemodialysis patients.CONCLUSIONSAmong hemodialysis patients, pruritus is commonly reported and associated with reduced health-related quality of life. It should be considered alongside the following symptoms commonly observed: sleep disturbance, depression, pain, anxiety, and low energy/fatigue. The presence of one symptom should prompt further investigation, allowing for appropriate diagnosis and management.LIMITATIONSThe cross-sectional nature of the study limits exploration of temporal relationships between the symptoms.STUDY DESIGNThis retrospective study of adults receiving hemodialysis in a large US dialysis organization analyzed pruritus and the individual symptoms of sleep disturbance, depression, pain, anxiety, and low energy/fatigue. Data from the Kidney Disease Quality of Life 36-Item Short Form Survey (KDQOL-36) and the Patient Health Questionnaire-2 were extracted from electronic medical records.

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.

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.

Carmine Zoccali, Giovanni Tripepi, Luca Neri, Matteo Savoia, Maria Eva Baró Salvador, Pedro Ponce, Jeffrey Hymes, Frank Maddux, Francesca Mallamaci, Stefano Stuard

RESULTSTwenty-seven percent of patients in the study cohort were systematically treated with a dialysate temperature ≤35.5°C. Over a median follow-up of 13.6 months (interquartile range 5.2-26.1 months), a 0.5°C reduction of the dialysate temperature was associated with a small (-2.4%) reduction of the risk of IDH [odds ratio (OR) 0.976, 95% confidence interval (CI) 0.957-0.995, P = .013]. In case-mix, facility-level adjusted analysis, the association became much stronger (OR 0.67, 95% CI 0.63-0.72, risk reduction = 33%, P < .001). In contrast, colder dialysate temperature had no effect on mortality both in the unadjusted [hazard ratio (HR) (0.5°C decrease) 1.074, 95% CI 0.972-1.187, P = .16] and case-mix-adjusted analysis at facility level (HR 1.01, 95% CI 0.88-1.16, P = .84). Similar results were registered in additional analyses by instrumental variables applying the median dialysate temperature or the facility percentage of patients prescribed a dialysate temperature <36°C. Further analyses restricted to patients with recurrent IDH fully confirmed these findings.CONCLUSIONSCold HD was associated with IDH in the HD population but had no association with all-cause mortality.BACKGROUNDCold hemodialysis (HD) prevented intradialysis hypotension (IDH) in small, short-term, randomized trials in selected patients with IDH. Whether this treatments prevents IDH and mortality in the HD population at large is unknown.METHODSWe investigated the relationship between dialysate temperature and the risk of IDH, i.e. nadir blood pressure <90 mmHg (generalized estimating equation model) and all-cause mortality (Cox's regression) in an incident cohort of HD patients (n = 8071). To control for confounding by bias by indication and other factors we applied instrumental variables adjusting for case mix at facility level.

Na'amah Razon, Yi Zhang, Bethney Bonilla-Herrera, Lorien S Dalrymple, Amanda K Stennett, Baback Roshanravan, Daniel Tancredi, Joshua J Fenton

RESULTSIndividuals who lacked private transportation were significantly less likely to transition to home dialysis compared with those who drove themselves or had a family member/friend drive them to HD. Adjusted incidence rate ratios for home dialysis transition were 47%-58% lower in nonprivate transportation groups compared with those with private transportation, ranging from 0.42 in individuals relying on Medicaid transportation benefits (95% confidence interval, 0.35-0.50; P < 0.001) to 0.53 (95% confidence interval, 0.41-0.67; P < 0.001) among paratransit users.Transportation is a key barrier for many individuals receiving in-center dialysis care. Nonetheless, the majority of individuals in the United States receive their dialysis treatment at an in-center facility. In a study of patients with end-stage kidney disease treated at in-center dialysis facilities, we examined the association between mode of transportation to dialysis and transition to home dialysis. We found that individuals who do not drive themselves or have a family member or friend drive them to dialysis were less likely to transition to home dialysis in the follow-up period. Our findings raise policy opportunities to support individuals who may face transportation challenges with ways to receive dialysis at home and reduce their transportation needs.RATIONALE & OBJECTIVETransportation insecurity is a social risk factor of particular importance to individuals with end-stage kidney disease (ESKD), as most individuals need to travel multiple times a week to dialysis treatment. Advancing home modalities for individuals with ESKD experiencing transportation insecurity may be beneficial by reducing travel burden and improving access.CONCLUSIONSIndividuals with ESKD receiving in-center HD who lack private transportation may have reduced access to home dialysis, even though this group may benefit from home modalities. Better identifying transportation barriers and targeting home modalities for those with transportation insecurity may reduce the adverse consequences of missed dialysis related to transportation barriers and be an additional opportunity to increase home dialysis uptake.LIMITATIONSSingle transportation assessment, exclusion of individuals already on home dialysis, and absence of caregiver data.STUDY DESIGNRetrospective cohort study.EXPOSURESThe main transportation mode to HD is categorized into private transportation (individuals who drive themselves or have a family member/friend drive) or those who lack private transportation (Medicaid non-emergency medical transportation, paratransit, public transportation, private pay non-emergency medical transportation, and other).SETTING & PARTICIPANTSIndividuals with ESKD treated with in-center hemodialysis (HD) at a large, national dialysis organization.OUTCOMESTransition to home dialysis is defined as an individual who has completed at least 1 training treatment for home therapies or at least 1 dialysis treatment at home.ANALYTIC APPROACHLog-binomial multivariate regression models to estimate adjusted incidence rate ratios of home dialysis transition by transportation mode.

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.

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

RESULTSA total of 71,669 patients were included, with 45% receiving hemodialysis and 55% receiving HDF. During the follow-up period, patients in the HDF group underwent a total of 12,741,453 HDF treatments, with a mean convection volume of 25.8 L (84% with CV≥23L). Compared with hemodialysis, treatment with HDF was associated with a lower incidence of both hospital admissions (adjusted IRR, 0.80; 95% confidence interval, 0.79 to 0.82) and days spent in the hospital (adjusted IRR, 0.80; 95% confidence interval, 0.78 to 0.82). These reductions were consistent across subgroups analyzed and across most major causes of hospitalization, including cardiovascular disease, infections, and fluid-related complications.KEY POINTSCompared with high-flux hemodialysis, postdilution high volume hemodiafiltration was associated with a lower number of hospital admissions. Compared with high-flux hemodialysis, postdilution high volume hemodiafiltration was associated with reduced days spent in the hospital.CONCLUSIONSIn this large, real-world cohort spanning multiple regions and dialysis centers, HV-HDF was associated with significantly lower rates of both hospital admissions and days spent in the hospital compared with treatment with high-flux hemodialysis. These findings suggest that HV-HDF may have the potential to reduce morbidity in patients with ESKD.BACKGROUNDPatients with ESKD undergoing hemodialysis experience high rates of hospitalizations and mortality, partly due to the incomplete removal of some toxic uremic molecules. To improve outcomes, multiple modalities of kidney replacement therapy have been developed, including high-flux hemodialysis and on-line hemodiafiltration (HDF). Notably, on-line high-volume HDF (HV-HDF) has demonstrated mortality benefits over high-flux hemodialysis in some randomized trials.METHODSThis retrospective cohort study evaluated hospitalization outcomes among in-center dialysis patients treated with HV-HDF and high-flux hemodialysis at Fresenius Medical Care NephroCare centers across Europe, the Middle East, and Africa between January 2019 and December 2022. Data were extracted from the European Clinical Database. The primary outcome was all-cause hospitalization; secondary outcomes included cause-specific hospitalizations. Negative binomial regression was used to estimate incidence rate ratios (IRRs) for hospital outcomes, incorporating inverse probability of treatment weighting to adjust for baseline differences between treatment groups.

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.

Jasmine Ion Titapiccolo, Max Botler, Francesco Bellocchio, Austin Vas, Felix Brockherde, Ricardo Peralta, Khaled Kahouli, Nathan Warren, Luca Neri

RESULTSMean age of patients was 68, and the average blood flow during the dialysis session was 352 ml/min. The model demonstrated excellent performance on independent testing datasets, achieving a sensitivity of 97.1%, specificity of 73.8%, and an overall accuracy of 82%. The area under the receiver operating characteristic curve (ROC-AUC) was 94%, reflecting strong discriminative ability. The model showed excellent calibration. Model performance across different experimental retraining folds indicates a stable and reliable training process.CONCLUSIONThe integration of this deep learning tool into clinical workflows could provide clinicians with a sensitive, objective, and time-efficient method for detecting high-pitched bruits which may be used in combination with other clinical signs for the detection of AVF complications such as stenosis. Implemented through a low-cost phono angiography protocol requiring minimal training, this approach has the potential to support earlier interventions and improve outcomes in the hemodialysis population.METHODAVF bruit recordings were collected from 65 patients across 12 dialysis centers in Europe and Asia using a digital stethoscope connected to the medical record of the patients. A deep learning model was developed to detect high-pitched bruits-an acoustic marker commonly associated with AVF stenosis. Expert-annotated recordings served as the reference standard for supervised training and evaluation.BACKGROUNDThe arteriovenous fistula (AVF) is the preferred vascular access for patients undergoing hemodialysis, and early identification of complications such as stenosis or dysfunction is essential to preserve access patency and reduce morbidity.

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.

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.

Xiao Fu, Yiting Shu, Yun Zhang

Neutrophil gelatinase-associated lipocalin (NGAL) is a biomarker extensively studied in multiple diseases. While its application in chronic kidney disease (CKD) and kidney transplant patients is relatively limited, NGAL has shown significant promise in the early detection and diagnosis of acute kidney injury (AKI), which may improve more timely management and potentially better clinical outcomes. In addition, NGAL has demonstrated promising utility in identifying peritoneal dialysis-related peritonitis (PDRP) and monitoring the treatment response. This review aims to provide an in-depth overview of the available research findings of NGAL in the management of AKI and PDRP, having these two conditions discussed together is particularly important for nephrologists who manage both conditions, especially to explore the potential of more specific NGAL forms, such as monomer NGAL and homodimer NGAL, to enhance early diagnosis and effective management of AKI and PDRP.

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

RESULTSA total of 324 patients participated in the study. HRSN was common with 56% of participants reporting at least one HRSN. Food insecurity (35%) and housing instability (24%) was most common. All QoL subscores were significantly lower in patients who had at least one HRSN. In regression models, housing and transportation insecurity most frequently emerged as significant variables associated with lower QoL subscores even after adjusting for patient demographics. Burden scores showed the largest effect sizes (housing instability β =-17.90, P < 0.001, transportation problems β =-14.03, P = 0.001).KEY POINTSHealth-related social needs are common in patients on in-center hemodialysis. All quality of life subscores are significantly lower in patients with at least one unmet health-related social needs.CONCLUSIONHRSN is significantly associated with lower QoL scores, with largest effect sizes seen with housing instability and transportation problems. Increased screening and intervention for HRSN may improve QoL among people on hemodialysis.BACKGROUNDPeople on hemodialysis often report lower quality of life (QoL) compared with people not on hemodialysis. People with kidney disease have a high prevalence of health-related social needs (HRSN). The association of HRSN and QoL in people on hemodialysis remains understudied. Although some groups of patients treated with hemodialysis tend to have lower QoL, there exists minimal research investigating the mechanism by which this occurs.METHODSWe surveyed people receiving hemodialysis at five urban dialysis units using the Kidney Disease Quality of Life and the Accountable Health Communities Health-Related Social Needs Screening Tool to assess their housing, food, transportation, utilities, and perceived safety. We calculated physical and mental component scores as well as subscores measuring burden, symptoms, and effect of kidney disease. We analyzed scores using Python packages. We used the Shapiro-Wilk test to assess normality. For analysis we used the Wilcoxon rank-sum test and univariate, multivariate, and least absolute shrinkage and selection operator regressions.

Harvey W Kaufman, Catherine Wang, Yuedong Wang, Hao Han, Sheetal Chaudhuri, Len Usvyat, Carly Hahn Contino, Robert Kossmann, Michael A Kraus

A case study explores patterns of kidney function decline using unsupervised learning methods first and then associating patterns with clinical outcomes using supervised learning methods. Predicting short-term risk of hospitalization and death prior to renal dialysis initiation may help target high-risk patients for more aggressive management. This study combined clinical data from patients presenting for renal dialysis at Fresenius Medical Care with laboratory data from Quest Diagnostics to identify disease trajectory patterns associated with the 90-day risk of hospitalization and death after beginning renal dialysis. Patients were clustered into 4 groups with varying rates of estimated glomerular filtration rate (eGFR) decline during the 2-year period prior to dialysis. Overall rates of hospitalization and death were 24.9% (582/2341) and 4.6% (108/2341), respectively. Groups with the steepest declines had the highest rates of hospitalization and death within 90 days of dialysis initiation. The rate of eGFR decline is a valuable and readily available tool to stratify short-term (90 days) risk of hospitalization and death after the initiation of renal dialysis. More intense approaches are needed that apply models that identify high risks to potentially avert or reduce short-term hospitalization and death of patients with a severe and rapidly progressive chronic kidney disease.

Cindy Chan, Sugandha Saxena, Yan Yi Cheung, Nandakumar Mooppil, Akira Wu, Luca Neri, Jeffrey L Hymes, Franklin W Maddux, Benjamin E Hippen, Milind Nikam

RESULTSOver 291,000 hemodiafiltration sessions were analyzed. The mean convection volumes achieved were 21.8 L in post-dilution and 40.8 L in pre-dilution mode. Higher blood flow rates and treatment durations were significantly associated with relatively high targeted convection volume (p < 0.001). The distribution of convection volume was similar among Chinese, Indian, and Malay patients. Ethnicity, age, and vascular access were not significant predictors. Approximately 29% of the variation in achieved convection volume was attributable to center-related factors.CONCLUSIONRelatively high targeted convection volume in hemodiafiltration was consistently achieved across a multiethnic cohort in Singapore. These findings support the feasibility of delivering high-volume hemodiafiltration to diverse real-world settings.BACKGROUNDHemodiafiltration has demonstrated improved outcomes in end-stage kidney disease, particularly with higher convection volumes than conventional hemodialysis. However, data on multiethnic Asian populations remain limited. This study evaluated the feasibility of achieving relatively high targeted convection volumes in hemodiafiltration in patients with end-stage kidney disease in Singapore.METHODSThis retrospective cohort analysis included 1404 patients undergoing hemodiafiltration between 2019 and 2023 at Fresenius Kidney Care clinics in Singapore using data obtained from the EuCliD database. Patients aged ≥ 18 years and on hemodiafiltration for > 3 months were included. Multivariate regression models were used to assess the factors associated with the attainment of convection volume.

Rachel Lasky, Linda H Ficociello, Jennifer E Flythe, Benjamin E Hippen

RESULTSMean dialysis vintage was > 4 years, and few patients likely had residual kidney function. Compared with individuals in the 180-194 minutes group, patients in the 240-254 minutes group had a 27% lower mortality (hazard ratio: 0.73 [0.69-0.76]), whereas patients in the 210-224 minutes and 225-239 minutes groups both had a 19% lower mortality (hazard ratio: 0.81 [0.77-0.85]) and 195-209 minutes group had 15%. These benefits were observed in patient subgroups across a wide range of mean UF volumes as well as with a spKt/V > 1.4, but not for patients with spKt/V < 1.4. In secondary analyses, similar associations were observed between longer treatment times (up to 240-254 minutes) and reduced hospitalization rates and shorter hospital stays.CONCLUSIONLonger dialysis treatment times are associated with better survival, fewer hospitalizations, and shorter hospital stays. Although the potential for selection bias cannot be excluded, these survival benefits were realized even when accounting for UF volume and spKt/V > 1.4.INTRODUCTIONThe relationship between hemodialysis treatment time, hospitalization rates, and mortality remains an area of controversy because of difficulties in separating the clinical effects of treatment time from urea clearance and ultrafiltration (UF) volume.METHODSData were obtained from a retrospective cohort of 146,127 maintenance in-center hemodialysis patients, aged 18 to 89 years, who dialyzed at Fresenius Kidney Care (FKC) clinics between January 1, 2022 and July 1, 2023 with 1-year follow-up after a 30-day run-in period. The patients were stratified into 6 treatment-time groups based on their mean delivered treatment time during the exposure period (180-194, 195-209, 210-224, 225-239, 240-254, and 255-269 minutes). The primary outcome was all-cause mortality; secondary outcomes included all-cause hospitalization rates and hospital length of stay.

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.

John Danziger, Joanna Willetts, John Larkin, Sheetal Chaudhuri, Kenneth J Mukamal, Len A Usvyat, Robert Kossmann

RESULTSAmong 6404 patients with incident kidney failure (male, 4182 [65%]; mean [SD] age, 57 [14] years) followed up for the first 90 days of dialysis therapy, 12% (n = 742) had measurable lead in household drinking water. A higher category of household lead contamination was associated with 15% (odds ratio [OR], 1.15 [95% CI, 1.04-1.27]) higher risk of maximum monthly ESA dosing, 4.5 (95% CI, 0.8-8.2) μg higher monthly ESA dose, and a 0.48% (95% CI, 0.002%-0.96%) higher monthly resistance index. Among patients with pre-kidney failure hemoglobin measures (n = 2648), a higher household lead categorization was associated with a 0.12 (95% CI, -0.23 to -0.002) g/dL lower hemoglobin concentration, particularly among those with concurrent iron deficiency (multiplicative interaction, P = .07), among whom hemoglobin concentrations were 0.25 (95% CI, -0.47 to -0.04) g/dL lower.OBJECTIVETo examine whether commonly encountered levels of lead in household water are associated with hematologic toxicity among individuals with advanced kidney disease, a group known to have disproportionate susceptibility to environmental toxicants.DESIGN, SETTING, AND PARTICIPANTSCross-sectional analysis of household water lead concentrations and hematologic outcomes was performed among patients beginning dialysis at a Fresenius Medical Care outpatient facility between January 1, 2017, and December 20, 2021. Data analysis was performed from April 1 to August 15, 2023.CONCLUSIONThe findings of this study suggest that levels of lead found commonly in US drinking water may be associated with lead poisoning among susceptible individuals.IMPORTANCEThe consequences of low levels of environmental lead exposure, as found commonly in US household water, have not been established.MAIN OUTCOMES AND MEASURESHematologic toxic effects were defined by monthly erythropoiesis-stimulating agent (ESA) dosing during the first 90 days of incident kidney failure care and examined as 3 primary outcomes: a proportion receiving maximum or higher dosing, continuously, and by a resistance index that normalized to body weight and hemoglobin concentrations. Secondarily, hemoglobin concentrations for patients with data prior to kidney failure onset were examined, overall and among those with concurrent iron deficiency, thought to increase gastrointestinal absorption of ingested lead.EXPOSUREConcentrations of lead in household water were examined in categorical proportions of the Environmental Protection Agency's allowable threshold (15 μg/L) and continuously.

Gabriela F Dias, Chenxi Fan, Maggie Han, Xiaoling Wang, Ohnmar Thwin, Lemuel Fuentes, Xin Wang, Hanjie Zhang, Wensheng Guo, Peter Kotanko, Nadja Grobe, Yuedong Wang

RESULTSAmong 417 metabolomic features, 10 showed significant changes between baseline and PIP. Two metabolites, α-guanidinoglutaric acid and N-acetylneuraminic acid, were identified through library matching, while the remainder were characterized by mass and retention time. Temporal analysis revealed both transient metabolic shifts, which returned to baseline, and persistent changes, which remained altered post-COVID.CONCLUSIONSThese findings suggest that early metabolic changes before COVID-19 diagnosis may be detected in routine serum samples, offering opportunities to develop predictive models for early detection. Identifying these unique metabolomics fingerprints could improve personalized surveillance strategies and enhance understanding of COVID-19's impact on hemodialysis patients.BACKGROUNDMaintenance hemodialysis patients experience higher morbidity and mortality from COVID-19, partly due to comorbidities like diabetes and cardiovascular disease. However, kidney disease-related metabolic processes may also contribute.METHODSIn this prospective, multi-center, observational study, we analyzed 201 routine serum samples from 30 hemodialysis patients (average age 59.2 ± 13.3 years, 57% male) with confirmed COVID-19, collected from 60 days before and 60 days after diagnosis. Untargeted liquid chromatography/mass spectrometry was used to profile metabolites. Linear and semi-parametric mixed-effects models were applied to assess changes across four phases: baseline (-60 to -15 days), putative incubation period (PIP; -14-0 days), acute (1-14 days), and post-COVID (15-60 days). Because infection and symptoms may vary across individuals, -14-0 days were used as an approximate pre-diagnosis window rather than a precise incubation interval.

Amun Georg Hofmann, Maria Elisabeth Leinweber, Suman Lama, Afshin Assadian, Jeffrey Hymes, Peter Kotanko, Len Usvyat, Jochen G Raimann

RESULTSAmong 146,967 incident HD patients, median survival was 1106 days for those initiating with a CVC compared with 1290 days for patients with an AVA, corresponding to a 184-day difference and an 88% restricted mean survival time (RMST) ratio. In the sustained access analysis, median survival was 448 days for CVC-only vs 1226 days for AVA-only patients (RMST difference = 778 days, RMST ratio = 52%). After inverse probability treatment weighting, AVA initiation was associated with a 25% lower mortality risk (hazard ratio: 0.75, 95% confidence interval: 0.73-0.76) and sustained AVA use with a 62% lower risk (hazard ratio: 0.38, 95% confidence interval: 0.36-0.40). Differences in infection-related deaths between the groups were small (8.6%-10.6% of deaths in all comparison groups).CONCLUSIONSCVC use was associated with higher mortality compared with AVA. Although AVA use remained linked with better survival across analyses, the precise magnitude of any access-related benefit cannot be determined within the constraints of observational data. There are strong indications that the excess risk at least partially reflects differences in baseline health and patient selection rather than a direct causal effect.OBJECTIVECentral venous catheters (CVCs) are commonly linked with higher mortality in hemodialysis (HD) patients compared with arteriovenous accesses (AVAs). However, patients with CVCs often have greater comorbidities, complicating causal interpretation. This study aimed to assess the association between vascular access type and survival adjusting for relevant confounders.METHODSIn this retrospective cohort study, data from 146,967 incident HD patients treated between 2016 and 2019 at a large North American dialysis organization (Fresenius Medical Care North America) were analyzed. Multiple analytic strategies were conducted including inverse probability treatment weighted and time-dependent survival analyses.

Yan Zhang, Anke Winter, Linda H Ficociello, Smriti Arya, Stefano Stuard, Len A Usvyat, Kamyar Kalantar-Zadeh

RESULTSBaseline characteristics between HDF and HD groups were comparable after IPTW. Over a median follow-up of 15.7 months (IQR, 6.4 -24.0 months), HDF was associated with a lower risk of all-cause mortality compared to HD (11.7 vs. 15.6 per 100 person-years; hazard ratio [HR], 0.80; 95% CI, 0.75-0.86). Furthermore, HDF was associated with a lower risk of CVD mortality compared to HD (4.1 vs. 6.7 per 100 person-years; HR, 0.71; 95% CI, 0.63-0.80).CONCLUSIONSIn the large real-world cohort of incident ESKD patients who are in early phase of dialysis treatment, online HDF was associated with a significant survival advantage compared to conventional HD. These findings reinforce the potential clinical benefits of HDF and support early adoption of HDF upon dialysis initiation.BACKGROUNDEvidence for a survival benefit of hemodiafiltration (HDF) over high-flux hemodialysis (HD) largely comes from studies based on prevalent end-stage kidney disease (ESKD) patients with longer dialysis exposure. In contrast, the effect of HDF on mortality of incident patients-those newly starting dialysis-remains less well understood.METHODSWe analyzed data from 18,515 incident patients (dialysis vintage <3 months) treated between 2019 and 2022 at Fresenius Medical Care NephroCare Clinics. Patients were classified as HDF or HD based on their predominant dialysis modality during the first year of follow-up (≥75% of sessions). To assess the effect of HDF on early phase after treatment initiation, follow-up was limited to two years. Cox proportional hazards models with inverse probability of treatment weighting (IPTW) were applied to estimate all-cause and cardiovascular (CVD) mortality risk.