Online hemodiafiltration (OL-HDF), the most efficient renal replacement therapy, enables enhanced removal of small and large uremic toxins by combining diffusive and convective solute transport. Randomized controlled trials on prevalent chronic kidney disease (CKD) patients showed improved patient survival with high-volume OL-HDF, underlining the effect of convection volume (CV). This retrospective international study was conducted in a large cohort of incident CKD patients to determine the CV threshold and range associated with survival advantage. Data were extracted from a cohort of adult CKD patients treated by post-dilution OL-HDF over a 101-month period. In total, 2293 patients with a minimum of 2 years of follow-up were analyzed using advanced statistical tools, including cubic spline analyses for determination of the CV range over which a survival increase was observed. The relative survival rate of OL-HDF patients, adjusted for age, gender, comorbidities, vascular access, albumin, C-reactive protein, and dialysis dose, was found to increase at about 55 l/week of CV and to stay increased up to about 75 l/week. Similar analysis of pre-dialysis β2-microglobin (marker of middle-molecule uremic toxins) concentrations found a nearly linear decrease in marker concentration as CV increased from 40 to 75 l/week. Analysis of log C-reactive protein levels showed a decrease over the same CV range. Thus, a convection dose target based on convection volume should be considered and needs to be confirmed by prospective trials as a new determinant of dialysis adequacy.

Support vector regression (SVR) is based on a linear combination of displaced replicas of the same function, called a kernel. When the function to be approximated is nonstationary, the single kernel approach may be ineffective, as it is not able to follow the variations in the frequency content in the different regions of the input space. The hierarchical support vector regression (HSVR) model presented here aims to provide a good solution also in these cases. HSVR consists of a set of hierarchical layers, each containing a standard SVR with Gaussian kernel at a given scale. Decreasing the scale layer by layer, details are incorporated inside the regression function. HSVR has been widely applied to noisy synthetic and real datasets and it has shown the ability in denoising the original data, obtaining an effective multiscale reconstruction of better quality than that obtained by standard SVR. Results also compare favorably with multikernel approaches. Furthermore, tuning the SVR configuration parameters is strongly simplified in the HSVR model.

Background Treatment of end-stage kidney disease patients is extremely challenging given the interconnected functional derangements and comorbidities characterizing the disease. Continuous quality improvement (CQI) in healthcare is a structured clinical governance process helping physicians adhere to best clinical practices. The digitization of patient medical records and data warehousing technologies has standardized and enhanced the efficiency of the CQI’s evidence generation process. There is limited evidence that ameliorating intermediate outcomes would translate into better patient-centred outcomes. We sought to evaluate the relationship between Fresenius Medical Care medical patient review CQI (MPR-CQI) implementation and patients’ survival in a large historical cohort study. Methods We included all incident adult patients with 6-months survival on chronic dialysis registered in the Europe, Middle East and Africa region between 2011 and 2018. We compared medical key performance indicator (KPI) target achievements and 2-year mortality for patients enrolled prior to and after MPR-CQI policy onset (Cohorts A and B). We adopted a structural equation model where MPR-CQI policy was the exogenous explanatory variable, KPI target achievements was the mediator variable and survival was the outcome of interest. Results About 4270 patients (Cohort A: 2397; Cohort B: 1873) met the inclusion criteria. We observed an increase in KPI target achievements after MPR-CQI policy implementation. Mediation analysis demonstrated a significant reduction in mortality due to an indirect effect of MPR-CQI implementation through improvement in KPI target achievement occurring in the post-implementation era [odds ratio 0.70 (95% confidence interval 0.65–0.76); P < 0.0001]. Conclusions Our study suggests that MPR-CQI achieved by standardized clinical practice and periodic structured MPR may improve patients’ survival through improvement in medical KPIs.

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.

Background: Stroke prevention in dialysis-dependent patients with atrial fibrillation (AF) is an unresolved clinical dilemma. Indeed, no randomized controlled trial evaluating the efficacy and safety of oral anticoagulants in this population, has been conducted so far. Observational research on the use of warfarin in patients on dialysis has shown conflicting results. This uncertainty is mirrored by the wide variations in warfarin prescription patterns across centers. We sought to evaluate the association between the use of vitamin K antagonists (VKAs) and mortality among hemodialysis patient with AF and to assess potential factors affecting the risk-benefit profile of warfarin in this population. Methods: A total of 91,987 patients registered in the European Clinical Dialysis Database® system from January 2004 to January 2015. Of which, 9,238 patients were identified with a diagnosis of AF. After excluding ineligible patients, a 1:1 propensity score matched cohort of 1,324 warfarin users and non-users were assembled. Results: VKA use was associated with both increased 90-day survival (hazard ratio, HR 0.47, p < 0.01) and 6-year survival (HR 0.76, p < 0.01); however, a trend indicated a stronger early benefit (p for time-interaction <0.01). Moderation analysis showed that patients' age and clinical history of stroke strongly influenced warfarin-related benefits on survival. Conclusion: VKA may provide an early survival benefit; however, this is partially offset later during the follow-up. In addition, heterogeneous risk-benefit profiles were observed among subgroups of dialysis-dependent patients with AF, further emphasizing the complexities of tailoring stroke prevention strategies in this population.