Emanuele Gatti

Effects of Telmisartan Added to Angiotensin-Converting Enzyme Inhibitors on Mortality and Morbidity in Hemodialysis Patients With Chronic Heart Failure : A Double-Blind, Placebo-Controlled Trial

OBJECTIVES the aim of this study was to determine whether telmisartan decreases all-cause and cardiovascular mortality and morbidity in hemodialysis patients with chronic heart failure (CHF) and impaired left ventricular ejection fraction (LVEF) when added to standard therapies with angiotensin-converting enzyme inhibitors. BACKGROUND in hemodialysis patients, CHF is responsible for a high mortality rate, but presently very few data are available with regard to this population. METHODS A 3-year randomized, double-blind, placebo-controlled, multicenter trial was performed involving 30 Italian clinics. Hemodialysis patients with CHF (New York Heart Association functional class II to III; LVEF ≤ 40%) were randomized to telmisartan or placebo in addition to angiotensin-converting enzyme inhibitor therapy. A total of 332 patients were enrolled (165 telmisartan, 167 placebo). Drug dosage was titrated to a target dose of telmisartan of 80 mg or placebo. Mean follow-up period was 35.5 ± 8.5 months (median: 36 months; range: 2 to 40 months). Primary outcomes were: 1) all-cause mortality; 2) cardiovascular mortality; and 3) CHF hospital stay. RESULTS at 3 years, telmisartan significantly reduced all-cause mortality (35.1% vs. 54.4%; p < 0.001), cardiovascular death (30.3% vs. 43.7%; p < 0.001), and hospital admission for CHF (33.9% vs. 55.1%; p < 0.0001). With Cox proportional hazards analysis, telmisartan was an independent determinant of all-cause mortality (hazard ratio [HR]: 0.51; 95% confidence interval [CI]: 0.32 to 0.82; p < 0.01), cardiovascular mortality (HR: 0.42; 95% CI: 0.38 to 0.61; p < 0.0001), and hospital stay for deterioration of heart failure (HR: 0.38; 95% CI: 0.19 to 0.51; p < 0.0001). Adverse effects, mainly hypotension, occurred in 16.3% of the telmisartan group versus 10.7% in the placebo group. CONCLUSIONS addition of telmisartan to standard therapies significantly reduces all-cause mortality, cardiovascular death, and heart failure hospital stays in hemodialysis patients with CHF and LVEF ≤ 40%. (Effects Of Telmisartan Added To Angiotensin Converting Enzyme Inhibitors On Mortality And Morbidity In Haemodialysed Patients With Chronic Heart Failure: A Double-Blind Placebo-Controlled Trial; NCT00490958).

Optimal convection volume for improving patient outcomes in an international incident dialysis cohort treated with online hemodiafiltration

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.

Body Composition and Survival in Dialysis Patients: Results from an International Cohort Study

BACKGROUND AND OBJECTIVES High body mass index appears protective in hemodialysis patients, but uncertainty prevails regarding which components of body composition, fat or lean body mass, are primarily associated with survival. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Data between April 2006 and December 2012 were extracted from the Fresenius Medical Care Europe subset of the international MONitoring Dialysis Outcomes initiative. Fresenius Medical Care Europe archives a unique repository of predialysis body composition measurements determined by multifrequency bioimpedance (BCM Body Composition Monitor). The BCM Body Composition Monitor reports lean tissue indices (LTIs) and fat tissue indices (FTIs), which are the respective tissue masses normalized to height squared, relative to an age- and sex-matched healthy population. The relationship between LTI and FTI and all-cause mortality was studied by Kaplan-Meier analysis, multivariate Cox regression, and smoothing spline ANOVA logistic regression. RESULTS In 37,345 hemodialysis patients, median (25th-75th percentile) LTI and FTI were 12.2 (10.3-14.5) and 9.8 (6.6-12.4) kg/m(2), respectively. Median (25th-75th percentile) follow-up time was 266 (132-379) days; 3458 (9.2%) patients died during follow-up. Mortality was lowest with both LTI and FTI in the 10th-90th percentile (reference group) and significantly higher at the lower LTI and FTI extreme (hazard ratio [HR], 3.37; 95% confidence interval [95% CI], 2.94 to 3.87; P<0.001). Survival was best with LTI between 15 and 20 kg/m(2) and FTI between 4 and 15 kg/m(2) (probability of death during follow-up: <5%). When taking the relation between both compartments into account, the interaction was significant (P=0.01). Higher FTI appeared protective in patients with low LTI (HR, 3.37; 95% CI, 2.94 to 3.87; P<0.001 at low LTI-low FTI, decreasing to HR, 1.79; 95% CI, 1.47 to 2.17; P<0.001 at low LTI-high FTI). CONCLUSIONS This large international study indicates best survival in patients with both LTI and FTI in the 10th-90th percentiles of a healthy population. In analyses of body composition, both lean tissue and fat tissue compartments and also their relationship should be considered.

Contribution of Polysulfone Membranes to the Success of Convective Dialysis Therapies

The majority of patients with chronic kidney disease are currently treated with dialyzers containing synthetic membranes. Of all the dialysis membranes made from these polymers, 93% are from the parent polyarylsulfone family of which 71% are from polysulfone (PSu) and 22% from polyethersulfone. The preference of nephrologists for PSu dialyzers signifies their versatility in terms of meeting the solute and fluid removal demands for all treatment modalities (low-and high-flux dialysis, online hemodiafiltration, hemofiltration). The unprecedented success and widespread usage of PSu membranes is attributed, in addition to efficient removal of a broad spectrum of uremic toxins, to other criteria required of modern dialysis therapies. Namely, effective endotoxin retention capacity, pronounced intrinsic biocompatibility and low cytotoxicity are factors which all contribute to minimal adverse clinical sequelae. Furthermore, PSu by virtue of its high thermal stability can be sterilized with steam, the preferred mode of sterilization as it does not have the disadvantages associated with other sterilization methods. However, there are significant differences between membranes made from PSu due to differences in membrane polymer recipes and manufacturing technologies. Although PSu may be the main constituent, these membranes are blended with other polymers, e.g. hydrophilizing agents, such as polyvinylpyrrolidone to give each membrane its characteristic profile. The relative amounts of the two (or more) co-polymers as well as the spinning conditions provide a fingerprint of each membrane in terms of solute separation characteristics, biocompatibility, cytotoxicity or endotoxin retention capabilities. PSu membrane-based dialyzers thus fulfill the crucial therapy requirements of current treatment modalities to varying extents. Thereby, different effects towards patient outcomes and treatment safety are achieved.

Impact of Hemodialysis Therapy on Anemia of Chronic Kidney Disease: The Potential Mechanisms

A significant and increasing number of chronic kidney disease (CKD) patients are treated with online hemodiafiltration (OL-HDF), even in the absence of more conclusive survival data. OL-HDF affords several clinical benefits including control of anemia of CKD, a common affliction in dialysis patients. In efforts to understand the underlying mechanisms that contribute to the purported benefits of OL-HDF, we examined the potential role and impact of OL-HDF on key stages of anemia and its correction: erythropoiesis of bone marrow, circulating erythrocytes and on anemia therapy. We review evidence that indicates OL-HDF may modulate key processes of anemia and its therapy, including underlying conditions and responses of uremic toxicity and inflammation that aggravate anemia. Our assessment indicates that OL-HDF favorably impacts anemia by not only eliminating putative uremic inhibitors that suppress erythropoiesis, reducing red cell destruction and increasing iron availability, but also by mechanisms restricting underlying inflammation and endothelial dysfunction that are crucial to both CKD and anemia.

Managing Complexity at Dialysis Service Centers across Europe

Introduction: Dialysis is probably one of the areas of medicine with more guidelines than any other. Issues such as dialysis dose are dealt with in those guidelines, and minimum values to be reached are defined. A target has to be set and reached by using a data-driven continuous quality improvement (CQI) approach. Data collection must be programmed and structured from the beginning. Methods: Fresenius started its activities as a dialysis provider in 1996, following the merger of its dialysis business with the leading service provider in the US, National Medical Care. Currently Fresenius Medical Care’s European activities involve more than 320 dialysis centers located in 15 countries and treating more than 24,000 patients. Management is based on a bi-dimensional organization where line managers can rely on international functional departments. Under this framework, the CQI techniques are applied in conjunction with benchmarking in a system driven by quality targets. In order to combine clinical governance with management targets, the Balanced ScoreCard system was selected. The Balanced ScoreCard monitors the efficiency of each dialysis center compared to an ideal model, targeting maximum possible efficiency whilst having a unique target for patient outcomes. Conclusion: A clear definition of targets is fundamental and activities need to be monitored and continuously improved; scientific collection of clinical data is the key.

Effects of fluid overload on heart rate variability in chronic kidney disease patients on hemodialysis

BackgroundWhile fluid overload (FO) and alterations in the autonomic nervous system (ANS) such as hypersympathetic activity, are known risk factors for cardiovascular morbidity and mortality in patients on chronic hemodialysis (HD), their relationship has not been thoroughly studied.MethodsIn this observational study involving 69 patients on chronic HD, FO was assessed by whole body bioimpedance measurements before the midweek HD session and ANS activity reflected by Heart Rate Variability (HRV) was measured using 24-hour Holter electrocardiogram recordings starting before the same HD treatment. In total, 13 different HRV indices were analyzed, comprising a mixture of time domain, frequency domain and complexity parameters. A correlation analysis was performed between the HRV indices and hydration status indices. Successively, patients were retrospectively assigned to a high FO (H, FO > 2.5 L) or low FO (L, FO ≤ 2.5 L) group and these were further compared also after stratification by diabetes mellitus. Finally, a small number of patients without diabetes with significant and persistent FO were followed up for 3 months post-study to investigate how normalization of fluid status affects HRV.ResultsSDANN, VLF, LZC and HF% parameters significantly correlate with FO (correlation coefficients were respectively r = –0.40, r = –0.37, r = –0.28 and r = 0.26, p-value < 0.05). Furthermore, LF% and LF/HF were inversely correlated with hydration status (correlation coefficients were respectively r = –0.31 and r = -0.33, p-value < 0.05). These results indicate an association between FO and reduced HRV, higher parasympathetic activation and reduced sympathetic response to the HD session. Indeed, group H tended to have lower values of SDANN, VLF and LZC, and higher values of HF% than patients in the L group. Finally, there was a trend towards lower LF% measured during the last 30 minutes of HD for the H group versus the L group. Reduction in FO achieved over 3 months by implementation of a strict fluid management plan resulted in an increase of HRV.ConclusionsOur results suggest that depressed HRV is associated with fluid overload and that normalization of hydration status is accompanied by improved HRV.

Role of Microvesicles in Acute Kidney Injury

The main function of microvesicles (MVs) is signaling through specific interactions with target cells and transferring gene products. Therefore, they may participate in physiological and pathological processes. Gaining further insights into the molecular specificity of MVs has allowed identifying the cellular source and may provide new diagnostic tools in the future. Indeed, an increasing body of evidence indicates that MVs may offer prognostic information in various diseases such as chronic inflammation, cardiovascular and renal diseases, pathological pregnancy, tumors, and sepsis. The presence of MVs in body fluids makes them readily accessible. Their number, cellular origin, composition and function can be dependent on the state of the disease. In sepsis for example, activated endothelial cells may shed MVs that might trigger leukocyte and monocyte production and release pro-oxidant and inflammatory mediators. MVs from platelets may trigger disseminated intravascular coagulopathy. MVs are no doubt also involved in modulating immunity and future studies will clarify their functional role in negatively modulating the cell response. In addition, the recognition of the signals delivered by MVs may open new therapeutic strategies. The removal of harmful MVs from plasma may be beneficial in pathological conditions where MVs deliver thrombogenic and inflammatory signals. On the other hand, MVs derived from stem cells may reprogram altered functions in target cells suggesting that they could be exploited in regenerative medicine to repair damaged tissues. We will discuss the role of stem cell-derived MVs in the repair of acute kidney injury.

Use of Self-Organizing Maps for Balanced Scorecard analysis to monitor the performance of dialysis clinic chains

The Balanced Scorecard (BSC) is a validated tool to monitor enterprise performances against specific objectives. Through the choice and the evaluation of strategic Key Performance Indicators (KPIs), it provides a measure of the past company’s outcome and allows planning future managerial strategies. The Fresenius Medical Care (FME) BSC makes use of 30 KPIs for a continuous quality improvement strategy within its dialysis clinics. Each KPI is monthly associated to a score that summarizes the clinic efficiency for that month. Standard statistical methods are currently used to analyze the BSC data and to give a comprehensive view of the corporate improvements to the top management. We herein propose the Self-Organizing Maps (SOMs) as an innovative approach to extrapolate information from the FME BSC data and to present it in an easy-readable informative form. A SOM is a computational technique that allows projecting high-dimensional datasets to a two-dimensional space (map), thus providing a compressed representation. The SOM unsupervised (self-organizing) training procedure results in a map that preserves similarity relations existing in the original dataset; in this way, the information contained in the high-dimensional space can be more easily visualized and understood. The present work demonstrates the effectiveness of the SOM approach in extracting useful information from the 30-dimensional BSC dataset: indeed, SOMs enabled both to highlight expected relationships between the KPIs and to uncover results not predictable with traditional analyses. Hence we suggest SOMs as a reliable complementary approach to the standard methods for BSC interpretation.

Optimization of anemia treatment in hemodialysis patients via reinforcement learning

OBJECTIVE Anemia is a frequent comorbidity in hemodialysis patients that can be successfully treated by administering erythropoiesis-stimulating agents (ESAs). ESAs dosing is currently based on clinical protocols that often do not account for the high inter- and intra-individual variability in the patients response. As a result, the hemoglobin level of some patients oscillates around the target range, which is associated with multiple risks and side-effects. This work proposes a methodology based on reinforcement learning (RL) to optimize ESA therapy. METHODS RL is a data-driven approach for solving sequential decision-making problems that are formulated as Markov decision processes (MDPs). Computing optimal drug administration strategies for chronic diseases is a sequential decision-making problem in which the goal is to find the best sequence of drug doses. MDPs are particularly suitable for modeling these problems due to their ability to capture the uncertainty associated with the outcome of the treatment and the stochastic nature of the underlying process. The RL algorithm employed in the proposed methodology is fitted Q iteration, which stands out for its ability to make an efficient use of data. RESULTS The experiments reported here are based on a computational model that describes the effect of ESAs on the hemoglobin level. The performance of the proposed method is evaluated and compared with the well-known Q-learning algorithm and with a standard protocol. Simulation results show that the performance of Q-learning is substantially lower than FQI and the protocol. When comparing FQI and the protocol, FQI achieves an increment of 27.6% in the proportion of patients that are within the targeted range of hemoglobin during the period of treatment. In addition, the quantity of drug needed is reduced by 5.13%, which indicates a more efficient use of ESAs. CONCLUSION Although prospective validation is required, promising results demonstrate the potential of RL to become an alternative to current protocols.