Does online high-volume hemodiafiltration offer greater efficiency and sustainability compared with high-flux hemodialysis? A detailed simulation analysis anchored in real-world data.

Recent findings, including the CONVINCE (comparison of high-dose HDF with high-flux HD) study report, suggest the superiority of high-volume hemodiafiltration (HDF) over high-flux hemodialysis (HD) in improving patients' outcomes. Despite positive patient outcomes, concerns have arisen about the potential negative environmental impact of high-volume HDF, as it may lead to increased water and dialysis fluid consumption and higher waste production. In this manuscript, we address the environmental impact of high-volume HDF, focusing on three key factors: water treatment consumption, dialysis fluid consumption, and solute efficiency markers of HD and HDF. By optimizing HDF prescription through adjustments in operational capabilities, while keeping a high blood flow (i.e., >350 ml/min) such as reducing the QD/QB ratio to 1.2 rather than 1.4 or 1.5 and incorporating automated ultrafiltration and substitution control, we demonstrate that HDF delivers a higher dialysis dose for small- and middle-molecule uremic compounds with the same dialysis fluid consumption, and at equal dialysis doses dialysis fluid consumption is reduced. This finding is supported by real-world data from 26 031 patients who underwent high-volume postdilution HDF at a reduced dialysis flow (430 mL/min) and achieved an effective OCMKt/V of 1.70 (where "OCM" stands for online clearance measurement, "K" represents effective dialysis clearance and "V" denotes total body water measured by multifrequency bioimpedance). In addition, simulation modeling calculations, using blood extraction coefficient, dialysate saturation coefficient and solute clearances with urea (small molecular weight) and ß2-microglobulin (middle molecular weight), consistently show the superiority of postdilution HDF to HD. This holds true even with a significant reduction in dialysis flow down to 430 mL/min, reflecting QD/QB ratio of 1.2. Postdilution HDF generates high ultrafiltrate flow (up to 35% of blood flow), delivering saturated ultrafiltrate to the lower solute concentration containing effluent dialysate, thus enhancing solute clearance which opens the way to reduce the dialysis flow. In conclusion, our analysis, combining simulation and real-world data, suggests that postdilution HDF could be a more environmentally friendly treatment option compared with conventional HD. Additionally, automated user-friendly functions that minimize dialysis fluid use can further strengthen this environmental benefit while enhancing efficiency.

The Use of Anemia Control Model Is Associated with Improved Hemoglobin Target Achievement, Lower Rates of Inappropriate Erythropoietin Stimulating Agents, and Severe Anemia among Dialysis Patients.

INTRODUCTION: The 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. METHODS: This 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. RESULTS: After 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. CONCLUSION: ACM 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.

How to assess the risks associated with the usage of a medical device based on predictive modeling: the case of an anemia control model certified as medical device.

BACKGROUND: The successful application of Machine Learning (ML) to many clinical problems can lead to its implementation as a medical device (MD), which is important to assess the associated risks. METHODS: An anemia control model (ACM), certified as MD, may face adverse events as a result of wrong predictions that are translated into suggestions of doses of erythropoietic stimulating agents to dialysis patients. Risks are assessed as the combination of severity and probability of a given hazard. While severities are typically assessed by clinicians, probabilities are tightly related to the performance of the predictive model. RESULTS: A postmarketing data set formed by all adult patients registered in French, Portuguese, and Spanish clinics, belonging to an international network, was considered; 3876 patients and 11,508 suggestions were eventually included. The achieved results show that there are no statistical differences between the probabilities of adverse events that are estimated in the ACM test set (using only Spanish clinics) and those actually observed in the postmarketing cohort. CONCLUSIONS: The risks of an ACM-MD can be accurately and robustly estimated, thus enhancing patients' safety. The proposed methodology is applicable to other clinical decisions based on predictive models since our proposal does not depend on the particular predictive model.

Mixed hemodiafiltration reduces erythropoiesis stimulating agents requirement in dialysis patients: a prospective randomized study.

BACKGROUND: Improved responsiveness to erythropoiesis stimulating agents (ESAs) in patients on on-line post-dilution hemodiafiltration (Post-HDF) compared with conventional hemodialysis (HD) was reported by some authors but challenged by others. This prospective, cross-over randomized study tested the hypothesis that an alternative infusion modality of HDF, mixed-dilution HDF (Mixed HDF), could further reduce ESAs requirement in dialysis patients compared to the traditional Post-HDF. METHODS: One-hundred-twenty prevalent patients from 6 Dialysis Centers were randomly assigned to two six-months treatment sequences: A-B and B-A (A, Mixed HDF; B, Post-HDF). Primary outcome was comparative evaluation of ESA (darbepoetin alfa) requirement and ESA resistance. Treatments efficiency, iron and vitamins status, inflammation and nutrition parameters were monitored. RESULTS: In sequence A, darbepoetin requirement decreased during Mixed HDF from 29.5 to 23.7 µg/month and increased significantly during Post-HDF (32.3 µg/month at 6th month) while, in sequence B, it increased during Post-HDF from 38.2 to 43.7 µg/month and decreased during Mixed HDF (23.9 µg/month at 6th month). Overall, EPO doses at 6 months on Mixed and Post-HDF were 23.8 and 38.4 µg/month, respectively, P < 0.01. A multiple linear model confirmed that Mixed HDF vs Post-HDF reduced significantly ESA requirement and ESA resistance (P < 0.0001), by a mean of 29% (CI 23-35%) in the last three months of the observation periods. CONCLUSIONS: Mixed HDF decreased darbepoetin-alfa requirement in dialysis patients. This might help preventing the untoward side effects of high ESA doses, besides having a remarkable economic impact. Additional evidence is needed to confirm this potential benefit of Mixed-HDF.

Effects of high-volume online mixed-hemodiafiltration on anemia management in dialysis patients.

BACKGROUND: Anemia is a major comorbidity of patients with end-stage renal disease and poses an enormous economic burden to health-care systems. High dose erythropoiesis-stimulating agents (ESAs) have been associated with unfavorable clinical outcomes. We explored whether mixed-dilution hemodiafiltration (Mixed-HDF), based on its innovative substitution modality, may improve anemia outcomes compared to the traditional post-dilution hemodiafiltration (Post-HDF). METHODS: We included 174 adult prevalent dialysis patients (87 on Mixed-HDF, 87 on Post-HDF) treated in 24 NephroCare dialysis centers between January 2010 and August 2016 into this retrospective cohort study. All patients were dialyzed three times per week and had fistula/graft as vascular access. Patients were matched at baseline and followed over a one-year period. The courses of hemoglobin levels (Hb) and monthly ESA consumption were compared between the two groups with linear mixed models. RESULTS: Mean baseline Hb was 11.9±1.3 and 11.8±1.1g/dl in patients on Mixed- and Post-HDF, respectively. While Hb remained stable in patients on Mixed-HDF, it decreased slightly in patients on Post-HDF (at month 12: 11.8±1.2 vs 11.1±1.2g/dl). This tendency was confirmed by our linear mixed model (p = 0.0514 for treatment x time interaction). Baseline median ESA consumption was 6000 [Q1:0;Q3:16000] IU/4 weeks in both groups. Throughout the observation period ESA doses tended to be lower in the Mixed-HDF group (4000 [Q1:0;Q3:16000] vs 8000 [Q1:0;Q3:20000] IU/4 weeks at month 12; p = 0.0791 for treatment x time interaction). Sensitivity analyses, adjusting for differences not covered by matching at baseline, strengthened our results (Hb: p = 0.0124; ESA: p = 0.0687). CONCLUSIONS: Results of our explorative study suggest that patients on Mixed-HDF may have clinical benefits in terms of anemia management. This may also have a beneficial economic impact. Future studies are needed to confirm our hypothesis-generating results and to provide additional evidence on the potential beneficial effects of Mixed-HDF.

Increased mortality in haemodialysis patients administered high doses of erythropoiesis-stimulating agents: a propensity score-matched analysis.

Background: Erythropoiesis-stimulating agents (ESAs) are widely used to treat anaemia in patients with chronic kidney disease. The issue of ESA safety has been raised in multiple studies, with correlates derived for elevated cancer incidence and mortality. Whether these associations are related to ESA dose or the typology of the patient remains obscure. Methods: A multicentre, observational retrospective propensity score-matched study was designed to analyse the effects of weekly ESA dose in 1679 incident haemodialysis (HD) patients. ESA administration was according to standard medical practice. Patients were grouped as quintiles, according to ESA dose, in order to compare mortality and hospitalization data. Using propensity score matching (PSM), we defined two groups of 324 patients receiving weekly threshold ESA doses of either > or ≤8000 IU. Results: Kaplan-Meier survival curves indicated significant increases in the risk of mortality in patients administered with high doses of ESAs (>8127.4 IU/week). Multivariate Cox models identified a high ESA dose as an independent predictor for all-cause and cardiovascular (CV) mortality. Moreover, logistic regression models identified high ESA doses as an independent predictor for all-cause, CV and infectious hospitalization. PSM analyses confirmed that weekly ESA doses of >8000 IU constitute an independent predictor of all-cause mortality and hospitalization, even though the adjusted cohort displayed the same demographic features, inflammatory profile, clinical HD parameters and haemoglobin levels. Conclusions: Our data suggest that ESA doses of >8000 IU/week are associated with an increased risk of all-cause mortality and hospitalization in HD patients.

Relationships between iron dose, hospitalizations and mortality in incident haemodialysis patients: a propensity-score matched approach.

Background: Intravenous iron management is common in the haemodialysis population. However, the safest dosing strategy remains uncertain, in terms of the risk of hospitalization and mortality. We aimed to determine the effects of cumulative monthly iron doses on mortality and hospitalization. Methods: This multicentre observational retrospective propensity-matched score study included 1679 incident haemodialysis patients. We measured baseline demographic variables, haemodialysis clinical parameters and laboratory analytical values. We compared outcomes among quartiles of cumulative iron dose (mg/kg/month). We implemented propensity-score matching (PSM) to reduce confounding due to indication. In the PSM cohort (330 patients), we compared outcomes between groups that received cumulative iron doses above and below 5.66 mg/kg/month. Results: Kaplan-Meier analyses showed that the high iron dose group had significantly worse survival than the low iron dose group. A univariate analysis indicated that the monthly iron dose could significantly predict mortality. However, a multivariate regression did not confirm that finding. The multivariate regression analysis revealed that iron doses >5.58 mg/kg/month were not associated with elevated mortality risk, but they were associated with elevated risks of all-cause and cardiovascular-related hospitalizations. These results were ratified in the PSM population. Conclusions: Intravenous iron administration is advisable for maintaining haemoglobin levels in patients that receive haemodialysis. Our data suggested that large monthly iron doses, adjusted for body weight, were associated with more hospitalizations, but not with mortality or infection-related hospitalizations.

An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.

Managing anemia in hemodialysis patients can be challenging because of competing therapeutic targets and individual variability. Because therapy recommendations provided by a decision support system can benefit both patients and doctors, we evaluated the impact of an artificial intelligence decision support system, the Anemia Control Model (ACM), on anemia outcomes. Based on patient profiles, the ACM was built to recommend suitable erythropoietic-stimulating agent doses. Our retrospective study consisted of a 12-month control phase (standard anemia care), followed by a 12-month observation phase (ACM-guided care) encompassing 752 patients undergoing hemodialysis therapy in 3 NephroCare clinics located in separate countries. The percentage of hemoglobin values on target, the median darbepoetin dose, and individual hemoglobin fluctuation (estimated from the intrapatient hemoglobin standard deviation) were deemed primary outcomes. In the observation phase, median darbepoetin consumption significantly decreased from 0.63 to 0.46 µg/kg/month, whereas on-target hemoglobin values significantly increased from 70.6% to 76.6%, reaching 83.2% when the ACM suggestions were implemented. Moreover, ACM introduction led to a significant decrease in hemoglobin fluctuation (intrapatient standard deviation decreased from 0.95 g/dl to 0.83 g/dl). Thus, ACM support helped improve anemia outcomes of hemodialysis patients, minimizing erythropoietic-stimulating agent use with the potential to reduce the cost of treatment.

Dynamics of the erythropoiesis stimulating agent resistance index in incident hemodiafiltration and high-flux hemodialysis patients.

Hyporesponsiveness to erythropoiesis-stimulating agent therapy in dialysis patients is poorly understood. Some studies report an improvement in the erythropoiesis-stimulating agent resistance index (ERI) with hemodiafiltration (HDF) versus high-flux hemodialysis (HD). We explored ERI dynamics in 38,340 incident HDF and HD patients treated in 22 countries over a 7-year period. Groups were matched by propensity score at baseline (6 months after dialysis initiation). The follow-up period (mean of 1.31 years) was stratified into 1 month intervals with delta analyses performed for key ERI-related parameters. Dialysis modality, time interval, and polycystic kidney disease were included in a linear mixed model with the outcome ERI. Baseline ERI was nonsignificantly higher in HDF versus HD treatment. ERI decreased significantly faster in HDF-treated patients than in HD-treated patients, was decreased in both HD and HDF when patients were treated with intravenous darbepoetin alfa, but only in HDF when treated with intravenous recombinant human erythropoietin (rHuEPO). A clear difference between HD- and HDF-treated patients could only be found for patients with high baseline ERI and assigned to intravenous rHuEPO treatment. A significant advantage in terms of lower ERI for patients treated by HDF was found. Sensitivity analysis limited this advantage for HDF to those patients treated with intravenous rHuEPO (not darbepoetin alfa or subcutaneous rHuEPO) and to patients with a high baseline ERI. Thus, our results allow more accurate planning for future clinical trials addressing anemia management in dialysis patients.

Performance of a Predictive Model for Long-Term Hemoglobin Response to Darbepoetin and Iron Administration in a Large Cohort of Hemodialysis Patients.

Anemia management, based on erythropoiesis stimulating agents (ESA) and iron supplementation, has become an increasingly challenging problem in hemodialysis patients. Maintaining hemodialysis patients within narrow hemoglobin targets, preventing cycling outside target, and reducing ESA dosing to prevent adverse outcomes requires considerable attention from caregivers. Anticipation of the long-term response (i.e. at 3 months) to the ESA/iron therapy would be of fundamental importance for planning a successful treatment strategy. To this end, we developed a predictive model designed to support decision-making regarding anemia management in hemodialysis (HD) patients treated in center. An Artificial Neural Network (ANN) algorithm for predicting hemoglobin concentrations three months into the future was developed and evaluated in a retrospective study on a sample population of 1558 HD patients treated with intravenous (IV) darbepoetin alfa, and IV iron (sucrose or gluconate). Model inputs were the last 90 days of patients' medical history and the subsequent 90 days of darbepoetin/iron prescription. Our model was able to predict individual variation of hemoglobin concentration 3 months in the future with a Mean Absolute Error (MAE) of 0.75 g/dL. Error analysis showed a narrow Gaussian distribution centered in 0 g/dL; a root cause analysis identified intercurrent and/or unpredictable events associated with hospitalization, blood transfusion, and laboratory error or misreported hemoglobin values as the main reasons for large discrepancy between predicted versus observed hemoglobin values. Our ANN predictive model offers a simple and reliable tool applicable in daily clinical practice for predicting the long-term response to ESA/iron therapy of HD patients.