All patients who started chronic HD due to ESRD in Lithuania, between January 1, 1998 customer review and December 31, 2005, were enrolled in our study. Outcomes and mortality and survival rates were analysed in the study.Hb variability in HD patients was evaluated in another single-center, retrospective study (n = 100). This study was conducted in Lithuanian University of Health Sciences, Department of Nephrology. The study started on January 1, 2011 and the follow-up included 12 months till December 31, 2011. Serum Hb concentrations and ESA doses were measured each month for each patient. Monthly Hb values were categorized as low (L; <100g/L), intermediate (I; 100�C105g/L), and high (H; >105g/L), according to our local renal anemia management algorithm at that time, which defined a target range of Hb 100�C105g/L.

Then a six-group classification system (according to [20]) was used based on the lowest and highest Hb categories seen during the six-month observation period (01/2011�C06/2011): low-low (LL)��consistently low; intermediate-intermediate (II)��consistently within the target range; high-high (HH)��consistently high; low-intermediate (LI)��all six months with low or target range Hb values; intermediate-high (IH)��all six months with high or target range Hb values, and low-high (LH)��fluctuation of low, high, and target range Hb values within six-month period. The association of Hb levels and Hb variability with mortality was evaluated.2.1. Statistical AnalysisFor the statistical analysis we used Statistical Package for Social Science, version 20.0.

Variables included in the study were expressed as percentages or position (mean, median) and dispersion parameters as appropriate for the type of variable. For evaluation of continuous variables the statistical mean and standard deviation were used. Kolmogorov-Smirnov statistics were used to evaluate sample normality distribution. Comparison between groups was performed using the Student’s t test, chi-square test, and Mann-Whitney U test. Spearman’s rank correlation coefficient was used to evaluate relationship between sets of data. The cumulative survival rate was estimated using the Kaplan-Meier method. The event of interest was death. Univariate Cox proportional hazards analysis was used to select variables significantly associated with the risk of death; then these variables were included in multivariate Cox proportional hazards models.

Relative risk of hospitalization according to laboratory tests was estimated using Cox regression analysis model. Significant values were considered when P < 0.05.3. Results and Discussion3.1. Development of HD Service and Control of Anemia in Lithuania during 1996�C2010 PeriodTremendous changes were observed in HD service of Lithuania during this period. There was an increase in number of HD centres (from 17 to GSK-3 61) and HD stations (from 25p.m.p. to 201p.m.p.) in 1996�C2010. The prevalence of HD patients increased from 60p.m.p.