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Abstract Background Gastrointestinal 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. Methods An 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. Results Incidence 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. Conclusions Machine 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 registration This retrospective analysis of real-world data was not a prospective clinical trial and registration is not applicable. Graphical Abstract

Purpose of symposiumFrom September 6 – 8 2022, the Life/2022 Membrane Symposium was held in Frankfurt, Germany, and transmitted live to a worldwide internet audience. The event was part of the Life/Nephrology Campus initiative, a continuous educational platform for the nephrology community to expand knowledge and share expertise on contemporary topics in chronic kidney disease. We describe recent questions and advances in the field, and we underline challenges in the care of dialysis patients and opportunities for integration of new findings into clinical practice to improve patient outcomes in end stage kidney disease patients.TopicsMost patients with kidney failure are on maintenance hemodialysis (MHD). The scientific program of the symposium was developed around topics about the role, functional determinants, technical aspects, limitations, and clinical implications of membranes presently in use. International experts with clinical or technical expertise as well as scientific recognition within the nephrology community were asked to prepare their presentations based on their own experiences, perceptions, opinions, and sources of information. The symposium devoted a major portion to discussing novel approaches for improving membranes and treatment quality, including updates on innovative concepts that may could potentially transform the landscape of kidney replacement therapy for chronic kidney disease patients in the future.ImplicationsThe intent was to provide insights into current attention points for healthcare professionals new to the field of MHD, and to test a unique forum for continuing medical education integrating physician and patient experiences to promote changes in clinical practice. Furthermore, the symposium premiered a specifically developed mixed reality holographic 3D model to demonstrate recent dialyzer innovation diminishing protein fouling on membrane surfaces. As a continuous online educational platform for scientific exchange, this Life/2022 event provided online learning opportunities with on-demand content, with all symposium lectures freely available on nephrologycampus.com.

Abstract Background The consequences of chronic kidney disease (CKD) can be addressed with a range of pharmacotherapies primarily prescribed by nephrologists. More accurate information regarding future CKD-related pharmacotherapy requirements could guide clinical decisions including follow-up frequency. Methods Following assignment to derivation and validation groups (2,1), variables predicting individually future use of vitamin D receptor agonists (VDRA), phosphate binders, erythropoiesis stimulating agents (ESAs) and iron were identified using logistic regression in a prospective cohort study containing demography, comorbidity, hospitalization, laboratory, and mortality data in patients with CKD stage G4/G5 across six European countries. Discriminative ability was measured using C-statistics, and predicted probability of medication use used to inform follow-up frequency. Results A total of 2196 patients were included in the analysis. During a median follow-up of 735 days 648 initiated hemodialysis and 1548 did not. Combinations of age, diabetes status and iPTH, calcium, hemoglobin and serum albumin levels predicted the use of ESA, iron, phosphate binder or VDRA, with C-statistics of 0.70, 0.64, 0.73 and 0.63 in derivation cohorts respectively. Model performance in validation cohorts were similar. Sixteen percent of patients were predicted to have a likelihood of receiving any of these medications of less than 20%. Conclusions In a multi-country CKD cohort, prediction of ESA and phosphate binder use over a two-year period can be made based on patient characteristics with the potential to reduce frequency of follow-up in individuals with low risk for requiring these medications.

Background: Propolis possesses many bioactive compounds that could modulate the gut microbiota and reduce the production of uremic toxins in patients with chronic kidney disease (CKD) undergoing hemodialysis (HD). This clinical trial aimed to evaluate the effects of propolis on the gut microbiota profile and uremic toxin plasma levels in HD patients. These are secondary analyses from a previous double-blind, randomized clinical study, with 42 patients divided into two groups: the placebo and propolis group received 400 mg of green propolis extract/day for eight weeks. Indole-3 acetic acid (IAA), indoxyl sulfate (IS), and p-cresyl sulfate (p-CS) plasma levels were evaluated by reversed-phase liquid chromatography, and cytokines were investigated using the multiplex assay (Bio-Plex Magpix®). The fecal microbiota composition was analyzed in a subgroup of patients (n = 6) using a commercial kit for fecal DNA extraction. The V4 region of the 16S rRNA gene was then amplified by the polymerase chain reaction (PCR) using short-read sequencing on the Illumina NovaSeq PE250 platform in a subgroup. Forty-one patients completed the study, 20 in the placebo group and 21 in the propolis group. There was a positive correlation between IAA and TNF-α (r = 0.53, p = 0.01), IL-2 (r = 0.66, p = 0.002), and between pCS and IL-7 (r = 0.46, p = 0.04) at the baseline. No significant changes were observed in the values of uremic toxins after the intervention. Despite not being significant, microbial evenness and observed richness increased following the propolis intervention. Counts of the Fusobacteria species showed a positive correlation with IS, while counts of Firmicutes, Lentisphaerae, and Proteobacteria phyla were negatively correlated with IS. Two months of propolis supplementation did not reduce the plasma levels of uremic toxins (IAA, IS, and p-CS) or change the fecal microbiota.

The gut microbiota performs several crucial roles in a holobiont with its host, including immune regulation, nutrient absorption, synthesis, and defense against external pathogens, significantly influencing host physiology. Disruption of the gut microbiota has been linked to various chronic conditions, including cardiovascular, kidney, liver, respiratory, and intestinal diseases. Studying how animals adapt their gut microbiota across their life course at different life stages and under the dynamics of extreme environmental conditions can provide valuable insights from the natural world into how the microbiota modulates host biology, with a view to translating these into treatments or preventative measures for human diseases. By modulating the gut microbiota, opportunities to address many complications associated with chronic diseases appear. Such a biomimetic approach holds promise for exploring new strategies in healthcare and disease management.