Hidden risks associated with conventional short intermittent hemodialysis: A call for action to mitigate cardiovascular risk and morbidity

Biological testing unification for hemodialysis membranes evaluation: A step towards standardization

Current hemodialysis treatments can cause adverse effects, many of which are linked to the membranes used in the process. These issues are being addressed through new materials and technologies, making it urgent to establish minimum guidelines for evaluating such membranes. This review proposes standardizing the biological tests and variables to evaluate the performance of new membranes, aiming to replicate hemodialysis conditions closely. The tests were categorized into protein adsorption, protein transmission, platelet adhesion, platelet activation, blood coagulation times, hemolysis, complement activation, and cytotoxicity. For protein adsorption, static tests are recommended as an initial step to rule out membrane adhesion, followed by dynamic tests that must be conducted using a crossflow system (>250 mL/min flow) and a solution mimicking real conditions (BSA, lysozyme, trypsin, pepsin, creatinine, urea, albumin, fibrinogen, and γ-globulin). Protein transmission tests must employ dynamic conditions, using human blood or platelet-rich plasma for a minimum time of 3.5 h. Complement activation should be tested using human blood and ELISA assays to detect C3, C5 TCC, and SC5b-9. Blood coagulation times (APTT, TT, FT, TCT, and TAT) should be measured with platelet-poor and platelet-rich plasma. Hemolysis tests should transition from water bath to continuous mode for at least 3.5 h. Cytotoxicity tests should compare the MTT assay with other methods (Alamar Blue, Lactate Dehydrogenase Assay, Flow Cytometry, or Trypan Blue Exclusion Test) and use different cell types for comprehensive validation. By implementing these minimum biological tests, membrane evaluations would more accurately reflect the real-world applications, ensuring biocompatibility, effectiveness, and efficiency.

Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials

Membrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility and performance of dialysis membranes by mitigating undesired membrane-protein interactions, which can lead to fouling and subsequent protein adsorption. Affinity energy, defined as the strength of interaction between membranes and human serum proteins, plays a crucial role in assessing membrane-protein interactions. These interactions may trigger adverse reactions, potentially harmful to patients. Researchers often rely on trial-and-error approaches to enhance membrane hemocompatibility by reducing these interactions. This study focuses on developing machine learning algorithms that accurately and rapidly predict affinity energy between novel chemical structures of membrane materials and human serum proteins, based on a molecular docking dataset. Various membrane materials with distinct characteristics, chemistry, and orientation are considered in conjunction with different proteins. A comparative analysis of linear regression, K-nearest neighbors regression, decision tree regression, random forest regression, XGBoost regression, lasso regression, and support vector regression is conducted to predict affinity energy. The dataset, comprising 916 records for both training and test segments, incorporates 12 parameters extracted from data points and involves six different proteins. Results indicate that random forest (R² = 0.8987, MSE = 0.36, MAE = 0.45) and XGBoost (R² = 0.83, MSE = 0.49, MAE = 0.49) exhibit comparable predictive performance on the training dataset. However, random forest outperforms XGBoost on the testing dataset. Seven machine learning algorithms for predicting affinity energy are analyzed and compared, with random forest demonstrating superior predictive accuracy. The application of machine learning in predicting affinity energy holds significant promise for researchers and professionals in hemodialysis. These models, by enabling early interventions in hemodialysis membranes, could enhance patient safety and optimize the care of hemodialysis patients.

Hemoincompatibility in Hemodialysis-Related Therapies and Their Health Economic Perspectives

Hemobiologic reactions associated with the hemoincompatibility of extracorporeal circuit material are an undesirable and inevitable consequence of all blood-contacting medical devices, typically considered only from a clinical perspective. In hemodialysis (HD), the blood of patients undergoes repetitive (at least thrice weekly for 4 h and lifelong) exposure to different polymeric materials that activate plasmatic pathways and blood cells. There is a general agreement that hemoincompatibility reactions, although unavoidable during extracorporeal therapies, are unphysiological contributors to non-hemodynamic dialysis-induced systemic stress and need to be curtailed. Strategies to lessen the periodic and direct effects of blood interacting with artificial surfaces to stimulate numerous biological pathways have focused mainly on the development of 'more passive' materials to decrease intradialytic morbidity. The indirect implications of this phenomenon, such as its impact on the overall delivery of care, have not been considered in detail. In this article, we explore, for the first time, the potential clinical and economic consequences of hemoincompatibility from a value-based healthcare (VBHC) perspective. As the fundamental tenet of VBHC is achieving the best clinical outcomes at the lowest cost, we examine the equation from the individual perspectives of the three key stakeholders of the dialysis care delivery processes: the patient, the provider, and the payer. For the patient, sub-optimal therapy caused by hemoincompatibility results in poor quality of life and various dialysis-associated conditions involving cost-impacting adjustments to lifestyles. For the provider, the decrease in income is attributed to factors such as an increase in workload and use of resources, dissatisfaction of the patient from the services provided, loss of reimbursement and direct revenue, or an increase in doctor-nurse turnover due to the complexity of managing care (nephrology encounters a chronic workforce shortage). The payer and healthcare system incur additional costs, e.g., increased hospitalization rates, including intensive care unit admissions, and increased medications and diagnostics to counteract adverse events and complications. Thus, hemoincompatibility reactions may be relevant from a socioeconomic perspective and may need to be addressed beyond just its clinical relevance to streamline the delivery of HD in terms of payability, future sustainability, and societal repercussions. Strategies to mitigate the economic impact and address the cost-effectiveness of the hemoincompatibility of extracorporeal kidney replacement therapy are proposed to conclude this comprehensive approach.

What is the role of the neutrophil extracellular traps in the cardiovascular disease burden associated with hemodialysis bioincompatibility?

Despite significant progress in dialysis modalities, intermittent renal replacement therapy remains an "unphysiological" treatment that imperfectly corrects uremic disorders and may lead to low-grade chronic inflammation, neutrophil activation, and oxidative stress due to repetitive blood/membrane interactions contributing to the "remaining uremic syndrome" and cardiovascular disease burden of hemodialysis patients. Understanding dialysis bioincompatibility pathways still remains a clinical and biochemical challenge. Indeed, surrogate biomarkers of inflammation including C-reactive protein could not discriminate between all components involved in these complex pathways. A few examples may serve to illustrate the case. Cytokine release during dialysis sessions may be underestimated due to their removal using high-flux dialysis or hemodiafiltration modalities. Complement activation is recognized as a key event of bioincompatibility. However, it appears as an early and transient event with anaphylatoxin level normalization at the end of the dialysis session. Complement activation is generally assumed to trigger leukocyte stimulation leading to proinflammatory mediators' secretion and oxidative burst. In addition to being part of the innate immune response involved in eliminating physically and enzymatically microbes, the formation of Neutrophil Extracellular Traps (NETs), known as NETosis, has been recently identified as a major harmful component in a wide range of pathologies associated with inflammatory processes. NETs result from the neutrophil degranulation induced by reactive oxygen species overproduction via NADPH oxidase and consist of modified chromatin decorated with serine proteases, elastase, bactericidal proteins, and myeloperoxidase (MPO) that produces hypochlorite anion. Currently, NETosis remains poorly investigated as a sensitive and integrated marker of bioincompatibility in dialysis. Only scarce data could be found in the literature. Oxidative burst and NADPH oxidase activation are well-known events in the bioincompatibility phenomenon. NET byproducts such as elastase, MPO, and circulating DNA have been reported to be increased in dialysis patients more specifically during dialysis sessions, and were identified as predictors of poor outcomes. As NETs and MPO could be taken up by endothelium, NETs could be considered as a vascular memory of intermittent bioincompatibility phenomenon. In this working hypothesis article, we summarized the puzzle pieces showing the involvement of NET formation during hemodialysis and postulated that NETosis may act as a disease modifier and may contribute to the comorbid burden associated with dialysis bioincompatibility.

Integrative phosphatidylcholine metabolism through phospholipase A2 in rats with chronic kidney disease

Dysregulation in lipid metabolism is the leading cause of chronic kidney disease (CKD) and also the important risk factors for high morbidity and mortality. Although lipid abnormalities were identified in CKD, integral metabolic pathways for specific individual lipid species remain to be clarified. We conducted ultra-high-performance liquid chromatography-high-definition mass spectrometry-based lipidomics and identified plasma lipid species and therapeutic effects of Rheum officinale in CKD rats. Adenine-induced CKD rats were administered Rheum officinale. Urine, blood and kidney tissues were collected for analyses. We showed that exogenous adenine consumption led to declining kidney function in rats. Compared with control rats, a panel of differential plasma lipid species in CKD rats was identified in both positive and negative ion modes. Among the 50 lipid species, phosphatidylcholine (PC), lysophosphatidylcholine (LysoPC) and lysophosphatidic acid (LysoPA) accounted for the largest number of identified metabolites. We revealed that six PCs had integral metabolic pathways, in which PC was hydrolysed into LysoPC, and then converted to LysoPA, which was associated with increased cytosolic phospholipase A2 protein expression in CKD rats. The lower levels of six PCs and their corresponding metabolites could discriminate CKD rats from control rats. Receiver operating characteristic curves showed that each individual lipid species had high values of area under curve, sensitivity and specificity. Administration of Rheum officinale significantly improved impaired kidney function and aberrant PC metabolism in CKD rats. Taken together, this study demonstrates that CKD leads to PC metabolism disorders and that the dysregulation of PC metabolism is involved in CKD pathology.

Fluid Overload and Tissue Sodium Accumulation as Main Drivers of Protein Energy Malnutrition in Dialysis Patients

Protein energy malnutrition is recognized as a leading cause of morbidity and mortality in dialysis patients. Protein-energy-wasting process is observed in about 45% of the dialysis population using common biomarkers worldwide. Although several factors are implicated in protein energy wasting, inflammation and oxidative stress mechanisms play a central role in this pathogenic process. In this in-depth review, we analyzed the implication of sodium and water accumulation, as well as the role of fluid overload and fluid management, as major contributors to protein-energy-wasting process. Fluid overload and fluid depletion mimic a tide up and down phenomenon that contributes to inducing hypercatabolism and stimulates oxidation phosphorylation mechanisms at the cellular level in particular muscles. This endogenous metabolic water production may contribute to hyponatremia. In addition, salt tissue accumulation likely contributes to hypercatabolic state through locally inflammatory and immune-mediated mechanisms but also contributes to the perturbation of hormone receptors (i.e., insulin or growth hormone resistance). It is time to act more precisely on sodium and fluid imbalance to mitigate both nutritional and cardiovascular risks. Personalized management of sodium and fluid, using available tools including sodium management tool, has the potential to more adequately restore sodium and water homeostasis and to improve nutritional status and outcomes of dialysis patients.

Sodium First Approach, to Reset Our Mind for Improving Management of Sodium, Water, Volume and Pressure in Hemodialysis Patients, and to Reduce Cardiovascular Burden and Improve Outcomes

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