External validation of a risk stratification model to assist shared decision making for patients starting renal replacement therapy

BACKGROUND: Shared decision making is nowadays acknowledged as an essential step when deciding on starting renal replacement therapy. Valid risk stratification of prognosis is, besides discussing quality of life, crucial in this regard. We intended to validate a recently published risk stratification model in a large cohort of incident patients starting renal replacement therapy in Flanders. METHODS: During 3 years (2001-2003), the data set collected for the Nederlandstalige Belgische Vereniging voor Nefrologie (NBVN) registry was expanded with parameters of comorbidity. For all incident patients, the abbreviated REIN score(aREIN), being the REIN score without the parameter "mobility", was calculated, and prognostication of mortality at 3, 6 and 12 month after start of renal replacement therapy (RRT) was evaluated. RESULTS: Three thousand four hundred seventy-two patients started RRT in Flanders during the observation period (mean age 67.6 ± 14.3, 56.7 % men, 33.6 % diabetes). The mean aREIN score was 4.1 ± 2.8, and 56.8, 23.1, 12.6 and 7.4 % of patients had a score of ≤4, 5-6, 7-8 or ≥9 respectively. Mortality at 3, 6 and 12 months was 8.6, 14.1 and 19.6 % in the overall and 13.2, 21.5 and 31.9 % in the group with age >75 respectively. In RoC analysis, the aREIN score had an AUC of 0.74 for prediction of survival at 3, 6 and 12 months. There was an incremental increase in mortality with the aREIN score from 5.6 to 45.8 % mortality at 6 months for those with a score ≤4 or ≥9 respectively. CONCLUSION: The aREIN score is a useful tool to predict short term prognosis of patients starting renal replacement therapy as based on comorbidity and age, and delivers meaningful discrimination between low and high risk populations. As such, it can be a useful instrument to be incorporated in shared decision making on whether or not start of dialysis is worthwhile

Impact of gastric acid suppressants on cytochrome P450 3A4 and P-glycoprotein: Consequences for FK506 assimilation

Impact of gastric acid suppressants on cytochrome P450 3A4 and P-glycoprotein: Consequences for FK506 assimilation.BackgroundCytochrome P450 3A4 (CYP3A4) and P-glycoprotein (PGP) are important determinants of the oral bioavailability and clearance of tacrolimus. Cimetidine and omeprazole are known modulators of several CYPs in vitro. In the present study, the impact of cimetidine and omeprazole on tacrolimus exposure and on CYP3A4/PGP activity in vivo was examined.MethodsIn a cohort of 48 renal transplant recipients who switched standard ulcer prophylaxis with 400 mg of cimetidine daily to 20 mg of omeprazole, dose/weight normalized trough levels of tacrolimus during a 5-day interval before and after switch were compared and further studied using multivariate analysis. In a cohort of 6 healthy volunteers, the effect of a 5-day course of ranitidine, cimetidine, and omeprazole on overall CYP, CYP3A4, and PGP activity in vivo was assessed with the 13C-aminopyrin breath test and the combined per oral and intravenous 14C-erythromycin breath and urine test.ResultsDose/weight normalized trough levels of tacrolimus decreased significantly (-15%) after switch from cimetidine to omeprazole. In healthy volunteers, a significant increase of intestinal CYP3A4 activity was observed after omeprazole, whereas no change was noted after cimetidine/ranitidine. Overall CYP activity was significantly decreased after cimetidine and remained unchanged after omeprazole/ranitidine. No effects on PGP or hepatic CYP3A4 were seen.ConclusionSwitching treatment with cimetidine to omeprazole in renal transplant recipients is associated with a decrease of dose/weight normalized trough levels of tacrolimus. Studies in healthy volunteers suggest that this may be explained by an increase of intestinal CYP3A4 activity

Review on solving the forward problem in EEG source analysis

Background. The aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes. Methods. While other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field. Results. It starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter). In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM), the finite element method (FEM) and the finite difference method (FDM). In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative methods are required to solve these sparse linear systems. The following iterative methods are discussed: successive over-relaxation, conjugate gradients method and algebraic multigrid method. Conclusion. Solving the forward problem has been well documented in the past decades. In the past simplified spherical head models are used, whereas nowadays a combination of imaging modalities are used to accurately describe the geometry of the head model. Efforts have been done on realistically describing the shape of the head model, as well as the heterogenity of the tissue types and realistically determining the conductivity. However, the determination and validation of the in vivo conductivity values is still an important topic in this field. In addition, more studies have to be done on the influence of all the parameters of the head model and of the numerical techniques on the solution of the forward problem.peer-reviewe

Reversal of Dialysis-Dependent Anti-Glomerular Basement Membrane Disease Using Plasma Exchange, Glucocorticosteroids, and Rituximab

status: publishe