Fresenius Medical Care

Background Vascular 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. Methods This 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. Results Patients 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). Conclusion T50 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.

Background: Attaining the optimal balance between achieving adequate volume removal while preserving organ perfusion is a challenge for patients receiving maintenance hemodialysis. Current strategies to guide ultrafiltration are inadequate. Methods: We developed an approach to calculate plasma refill rate throughout hemodialysis using hematocrit and ultrafiltration data in a retrospective cohort of patients receiving maintenance hemodialysis at 17 dialysis units from January 2017-October 2019. We studied whether (1) plasma refill rate is associated with traditional risk factors for hemodynamic instability using logistic regression, (2) low starting plasma refill rate is associated with intradialytic hypotension using Cox proportional hazard regression, and (3) time-varying plasma refill rate throughout hemodialysis is associated with hypotension using marginal structural modeling. Results: During 180,319 hemodialysis sessions among 2554 patients, plasma refill rate had high within- and between-patient variability. Female sex and hypoalbuminemia were associated with low plasma refill rate at multiple time points during the first hour of hemodialysis. Low starting plasma refill rate had higher hazards of intradialytic hypotension while high starting plasma refill rate was protective (HR 1.26, 95% CI 1.18, 1.35 versus HR 0.79, 95% CI 0.73, 0.85, respectively). However, when accounting for time-varying plasma refill rate and time-varying confounders, compared to a moderate plasma refill rate, while a consistently low plasma refill rate was associated with increased risk of hypotension (OR 1.09, 95% CI 1.02, 1.16), a consistently high plasma refill rate had a stronger association with hypotension within the next 15 minutes (OR 1.38, 95% CI 1.30, 1.45). Conclusions: We present a straightforward technique to quantify plasma refill that could easily integrate with devices that monitor hematocrit during hemodialysis. Our study highlights how examining patterns of plasma refill may enhance our understanding of circulatory changes during hemodialysis, an important step to understanding how current technology might be utilized to improve hemodynamic instability.

Die Betrachtung von Produkt-Systemen über alle Phasen des Lebenszyklus gewinnt durch aktuelle Trends und deren Änderungsfrequenz zunehmend an strategischer Bedeutung für die Produktentwicklung. Der Ansatz des Systems & Life Cycle Engineerings kann hier genutzt werden, um die Innovation von Produkten zu unterstützen, um die Strategische Souveränität zu befähigen.

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

Objectives: This study aimed to determine the lifetime cost-effectiveness of increasing home hemodialysis (HHD) as a treatment option for patients experiencing peritoneal dialysis (PD) technique failure compared to the current standard of care. Methods: A Markov model was developed to assess the lifetime costs, quality-adjusted life years (QALYs) and cost-effectiveness of increasing the usage an integrated home dialysis model compared to the current patient pathways in the UK. A secondary analysis was conducted including only the cost difference in treatments, minimizing the impact of the high cost of dialysis during life years gained (LYG). Sensitivity and scenario analyses were performed including analyses from a societal rather than a National Health Service (NHS) perspective. Results: The base case probabilistic analysis was associated with incremental costs of £3,413 and QALYs of 0.09, resulting in an incremental cost-effectiveness ratio (ICER) of £36,341. The secondary analysis found the integrated home dialysis model to be dominant. Conclusions on cost-effectiveness did not change under the societal perspective in either analysis. Conclusion: The base case analysis found that an integrated home dialysis model compared to current patient pathways is likely not cost-effective. These results were primarily driven by the high baseline costs of dialysis during life-years gained by HHD patients. When excluding baseline dialysis-related treatment costs, the integrated home dialysis model was dominant. New strategies in kidney care patient pathway management should be explored as, under the assumption that dialysis should be funded, the results provide cost-effectiveness evidence for an integrated home dialysis model.

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.

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

Artificial intelligence technology is trending in nearly every medical area. It offers the possibility for improving analytics, therapy outcome, and user experience during therapy. In dialysis, the application of artificial intelligence as a therapy-individualization tool is led more by start-ups than consolidated players, and innovation in dialysis seems comparably stagnant. Factors such as technical requirements or regulatory processes are important and necessary but can slow down the implementation of artificial intelligence due to missing data infrastructure and undefined approval processes. Current research focuses mainly on analyzing health records or wearable technology to add to existing health data. It barely uses signal data from treatment devices to apply artificial intelligence models. This article, therefore, discusses requirements for signal processing through artificial intelligence in health care and compares these with the status quo in dialysis therapy. It offers solutions for given barriers to speed up innovation with sensor data, opening access to existing and untapped sources, and shows the unique advantage of signal processing in dialysis compared to other health care domains. This research shows that even though the combination of different data is vital for improving patients' therapy, adding signal-based treatment data from dialysis devices to the picture can benefit the understanding of treatment dynamics, improving and individualizing therapy.

Background: A higher sodium (Na) dialysate concentration is recommended during renal replacement therapy (RRT) of acute kidney injury (AKI) to improve intradialytic hemodynamic tolerance, but it may lead to Na loading to the patient. We aimed to evaluate Na flux according to Na dialysate and infusate concentrations at 140 and 145mmol/L during hemodialysis (HD) and hemodiafiltration (HDF). Methods: Fourteen AKI patients that underwent consecutive HD or HDF sessions with Na dialysate/infusate at 140 and 145mmol/L were included. Per-dialytic flux of Na was estimated using mean sodium logarithmic concentration including diffusive and convective influx. We compared flux of sodium between HD140 and 145, and between HDF140 and 145. Results: 9 HD140, 10 HDF140, 9 HD145 and 11 HDF145 sessions were analyzed. A Na gradient from the dialysate/replacement fluid to the patient was observed with dialysate/infusate Na at 145mmol/l in both HD and HDF (p =0.01). The comparison of HD145 to HD140 showed that higher Na dialysate induced a diffusive Na gradient to the patient (163 mmol vs -25 mmol, p= 0.004) and that of HDF145 to -140 (211 vs 36 mmol, p= 0.03) as well . Intradialytic hemodynamic tolerance was similar across all RRT sessions. Conclusions: During both HD and HDF, a substantial Na loading occurred with a Na dialysate and infusate at 145mmol/L. This Na loading is smaller in HDF with Na dialysate and infusate concentration at 140mmol/L and inversed with HD140. Clinical and intradialytic hemodynamic tolerance was fair regardless of Na dialystate and infusate.

Background In chronic haemodialysis (HD) patients, the relationship between long-term peri-dialytic blood pressure (BP) changes and mortality has not been investigated before. Methods To evaluate whether long-term changes in peri-dialytic BP are related to mortality and whether treatment with HD or haemodiafiltration (HDF) differs in this respect, the combined individual participant data of three randomized controlled trials, comparing HD with HDF, were used. Time-varying Cox regression and joint models were applied. Results During a median follow-up of 2.94 years, 609 out of 2011 patients died. As for pre-dialytic systolic BP (pre-SBP), a severe decline (≥21 mmHg) in the preceding 6 months was independently related to increased mortality (HR 1.61, p = 0.01), if compared to a moderate increase. Likewise, a severe decline in post-dialytic DBP was associated with increased mortality (adjusted HR 1.96, p < 0.0005). Vice versa, joint models showed that every 5 mmHg increase during total follow-up in pre-SBP and post-DBP was related to reduced mortality (aHRs 0.97, p = 0.01 and 0.94, p = 0.03, resp.). No interaction was observed between BP-changes and treatment modality. Conclusion Severe declines in pre-SBP and post-DBP in the preceding 6 months were independently related to mortality. Therefore, peri-dialytic BP-values should be interpreted in the context of their changes and not solely as an absolute value.

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.

Background: This systematic review was performed to identify recent published comparative evidence on the efficacy, effectiveness, and safety of expanded hemodialysis (HDx) versus high-flux HD and/or hemodiafiltration (HDF) for long-term outcomes in end-stage kidney disease. Methods: Systematic literature review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Medline, Medline® Epub Ahead of Print, EconLit, Embase, and EBM reviews were searched to identify relevant publications from 2013 onwards. Eligibility criteria included clinical studies reporting mortality, hospitalizations, cardiovascular outcomes, economic evaluations, cost studies, and quality of life (QoL) studies. Results: A total of 79 relevant studies were identified with 29 prioritized for detailed analysis; four compared HDx to HD, one compared HDF and HDx, and 24 compared HDF with HD. A total of 13 randomized controlled trial (RCT)-based studies were identified; 11 compared HDF with HD, one compared HDx with HD, and one compared HDF with HDx. Follow-up duration ranged from 16 weeks to 7 years for HDF studies and from 12 weeks to 1 year for HDx studies. HDF showed significant improvements in mortality, cardiovascular outcomes, hospitalizations, and QoL versus high-flux HD. One study reported mortality outcomes for HDx and found no difference versus HDF. QoL benefits with HDx were reported in a small number of studies. Conclusion: The efficacy and safety of HDF is supported by a robust evidence base that includes several RCTs. While HDx may offer benefits over high-flux HD, long-term studies are required to compare HDx with online high volume HDF. Registration: PROSPERO registration number: CRD42022301009.

Background A functioning vascular access (VA) is crucial to providing adequate hemodialysis (HD) and considered a critically important outcome by patients and healthcare professionals. A validated, patient-important outcome measure for VA function that can be easily measured in research and practice to harvest reliable and relevant evidence for informing patient-centered HD care is lacking. Vascular Access outcome measure for function: a vaLidation study In hemoDialysis (VALID) aims to assess the accuracy and feasibility of measuring a core outcome for VA function established by the international Standardized Outcomes in Nephrology (SONG) initiative. Methods VALID is a prospective, multi-center, multinational validation study that will assess the accuracy and feasibility of measuring VA function, defined as the need for interventions to enable and maintain the use of a VA for HD. The primary objective is to determine whether VA function can be measured accurately by clinical staff as part of routine clinical practice (Assessor 1) compared to the reference standard of documented VA procedures collected by a VA expert (Assessor 2) during a 6-month follow-up period. Secondary outcomes include feasibility and acceptability of measuring VA function and the time to, rate of, and type of VA interventions. An estimated 612 participants will be recruited from approximately 10 dialysis units of different size, type (home-, in-center and satellite), governance (private versus public), and location (rural versus urban) across Australia, Canada, Europe, and Malaysia. Validity will be measured by the sensitivity and specificity of the data acquisition process. The sensitivity corresponds to the proportion of correctly identified interventions by Assessor 1, among the interventions identified by Assessor 2 (reference standard). The feasibility of measuring VA function will be assessed by the average data collection time, data completeness, feasibility questionnaires and semi-structured interviews on key feasibility aspects with the assessors. Discussion Accuracy, acceptability, and feasibility of measuring VA function as part of routine clinical practice are required to facilitate global implementation of this core outcome across all HD trials. Global use of a standardized, patient-centered outcome measure for VA function in HD research will enhance the consistency and relevance of trial evidence to guide patient-centered care. Trial registration Clinicaltrials.gov: NCT03969225. Registered on 31st May 2019.

Background Hemodialysis 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. Methods In 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. Results In 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%. Conclusion In 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.

Introduction Inflammation 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. Methods The 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, >31 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. Results We 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. Conclusion Our 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.

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

The dialyzer is the core element in the hemodialysis treatment of patients with end-stage kidney disease (ESKD). During hemodialysis treatment, the dialyzer replaces the function of the kidney by removing small and middle-molecular weight uremic toxins, while retaining essential proteins. Meanwhile, a dialyzer should have the best possible hemocompatibility profile as the perpetuated contact of blood with artificial surfaces triggers complement activation, coagulation and immune cell activation, and even low-level activation repeated chronically over years may lead to undesired effects. During hemodialysis, the adsorption of plasma proteins to the dialyzer membrane leads to a formation of a secondary membrane, which can compromise both the uremic toxin removal and hemocompatibility of the dialyzer. Hydrophilic modifications of novel dialysis membranes have been shown to reduce protein adsorption, leading to better hemocompatibility profile and performance stability during dialysis treatments. This review article focuses on the importance of performance and hemocompatibility of dialysis membranes for the treatment of dialysis patients and summarizes recent studies on the impact of protein adsorption and hydrophilic modifications of membranes on these two core elements of a dialyzer.

Introduction La mesure des résultats de soins rapportés par le patient à l’aide d’un système électronique (ePROMs) pourrait aider à simplifier et mieux partager le recueil de données sur la qualité de vie des patients hémodialysés. Description Du 20/09/2021 au 4/12/2021, les centres d’hémodialyse NephroCare ont débuté le programme ePROMs dans 5 pays européens dont la France. Le questionnaire comporte le KDQOL-36 (scores de santé physique SF-12PCS et mental SF-12 MCS, le poids (BKD), les effets (EKD) et les symptômes (SKD) de l’insuffisance rénale), le 5D-Itch et un score sur les symptômes intra-dialytiques. Méthodes Les données ePROMs ont été enregistrées dans EuCLiD® (système d’information pour les dossiers cliniques des centres NephroCare). Dans cette étude, nous rapportons une analyse rétrospective des données pour la France. Résultats Trente-neuf centres de dialyse NephroCare France ont participé au programme ePROM. Parmi les 2720 patients actifs hémodialysés, 2114 (77,7 %) ont été considérés comme éligibles (1484 sans aide et 630 avec aide). Au total, 278 (10 %) n’ont pas été inclus en raison de troubles cognitifs ou transfert. Au total, 236 (8 %) patients ont refusé de participer à l’enquête. Au total, 1662 (61 %) patients ont complété ce questionnaire. Les scores KDQOL-36 sont présentés dans le tableau 1. Le taux d’absence de réponses aux questions était inférieur à 2 % tout au long de l’enquête, à l’exception de celle concernant la vie intime (18 %). Quinze pour cent des patients ont signalé une complication au cours de leur séance de dialyse conduisant chez 8 % d’entre eux à suspendre leur traitement. La prévalence du temps de récupération supérieur à 3 heures était de 34,8 % (Tableau 1). Conclusion La démarche du recueil des ePROM a obtenu une bonne adhésion des patients et du personnel soignant avec une mise en œuvre aisée dans les centres de dialyse. Cette phase de dépistage a permis d’identifier les patients ayant besoin d’une intervention thérapeutique ou de consultations spécialisées.

Background: Peritoneal dialysis (PD) is a renal replacement technique that requires repeated exposure of the peritoneum to hyperosmolar PD fluids (PDFs). Unfortunately, it promotes alterations of the peritoneal membrane (PM) that affects its functionality, including mesothelial-mesenchymal transition (MMT) of mesothelial cells (MCs), inflammation, angiogenesis, and fibrosis. Glucose is the most used osmotic agent, but it is known to be at least partially responsible, together with its degradation products (GDP), for those changes. Therefore, there is a need for more biocompatible osmotic agents to better maintain the PM. Herein we evaluated the biocompatibility of Steviol glycosides (SG)-based fluids. Methods: The ultrafiltration and transport capacities of SG-containing and glucose-based fluids were analyzed using artificial membranes and an in vivo mouse model, respectively. To investigate the biocompatibility of the fluids, Met-5A and human omental peritoneal MCs (HOMCs) were exposed in vitro to different types of glucose-based PDFs (conventional 4.25% glucose solution with high-GDP level and biocompatible 2.3% glucose solution with low-GDP level), SG-based fluids or treated with TGF-β1. Mice submitted to surgery of intraperitoneal catheter insertion were treated for 40 days with SG or glucose-based fluids. Peritoneal tissues were collected to determine thickness, MMT, angiogenesis, as well as peritoneal washings to analyze inflammation. Results: Dialysis membrane experiments demonstrated that SG-based fluids at 1.5%, 1%, and 0.75% had a similar trend in weight gain, based on curve slope, as glucose-based fluids. Analyzing transport capacity in vivo, 1% and 0.75% SG-based fluid-exposed nephrectomized mice extracted a similar amount of urea as the glucose 2.3% group. In vitro, PDF with high-glucose (4.25%) and high-GDP content induced mesenchymal markers and angiogenic factors (Snail1, Fibronectin, VEGF-A, FGF-2) and downregulates the epithelial marker E-Cadherin. In contrast, exposition to low-glucose-based fluids with low-GDP content or SG-based fluids showed higher viability and had less MMT. In vivo, SG-based fluids preserved MC monolayer, induced less PM thickness, angiogenesis, leukocyte infiltration, inflammatory cytokines release, and MMT compared with glucose-based fluids. Conclusion: SG showed better biocompatibility as an osmotic agent than glucose in vitro and in vivo, therefore, it could alternatively substitute glucose in PDF.