While cardiovascular events remain the primary form of mortality in haemodialysis (HD) patients, few centres are aware of the impact of the hydration status (HS). The aim of this study was to investigate how the magnitude of the prevailing overhydration influences long-term survival. We measured the hydration status in 269 prevalent HD patients (28% diabetics, dialysis vintage = 41.2 +/- 70 months) in three European centres with a body composition monitor (BCM) that enables quantitative assessment of hydration status and body composition. The survival of these patients was ascertained after a follow-up period of 3.5 years. The cut off threshold for the definition of hyperhydration was set to 15% relative to the extracellular water (ECW), which represents an excess of ECW of approximately 2.5 l. Cox-proportional hazard models were used to compare survival according to the baseline hydration status for a set of demographic data, comorbid conditions and other predictors. The median hydration state (HS) before the HD treatment (DeltaHSpre) for all patients was 8.6 +/- 8.9%. The unadjusted gross annual mortality of all patients was 8.5%. The hyperhydrated subgroup (n = 58) presented DeltaHSpre = 19.9 +/- 5.3% and a gross mortality of 14.7%. The Cox adjusted hazard ratios (HRs) revealed that age (HRage = 1.05, 1/year; P < 0.001), systolic blood pressure (BPsys) (HRBPsys = 0.986 1/mmHg; P = 0.014), diabetes (HRDia = 2.766; P < 0.001), peripheral vascular disease (PVD) (HRPVD = 1.68; P = 0.045) and relative hydration status (DeltaHSpre) (HRDeltaHSpre = 2.102 P = 0.003) were the only significant predictors of mortality in our patient population. The results of our study indicate that the hydration state is an important and independent predictor of mortality in chronic HD patients secondary only to the presence of diabetes. We believe that it is essential to measure the hydration status objectively and quantitatively in order to obtain a more clearly defined assessment of the prognosis of haemodialysis patients.

Background. A number of US observational studies reported an increased mortality risk with higher intact parathyroid hormone (iPTH), calcium and/or phosphate. The existence of such a link in a European haemodialysis population was explored as part of the Analysing Data, Recognising Excellence and Optimising Outcomes (ARO) Chronic Kidney Disease (CKD) Research Initiative. Methods. The association between the markers of mineral and bone disease and clinical outcomes was examined in 7970 patients treated in European Fresenius Medical Care facilities over a median of 21 months. Baseline and time-dependent (TD) Cox regression were performed using Kidney Disease Outcomes Quality Initiative (KDOQI) target ranges as reference categories, adjusting for demographics, medical history, dialysis parameters, inflammation, medications and laboratory parameters. Fractional polynomial (FP) models were also used. Results. Hazard ratio (HR) estimates from baseline analysis for iPTH were U-shaped [>600 pg/mL, HR = 2.10, 95% confidence interval (CI) 1.62–2.73; 2.75 mmol/L increased risk of death (HR = 1.70, 95% CI 1.19–2.42). TD analysis showed that both low (HR = 1.19, 95% CI 1.04–1.37) and high calcium (HR = 1.74, 95% CI 1.30–2.34) increased risk of death. Baseline analysis for phosphate showed a U-shaped pattern (1.78 mmol/L, HR = 1.32, 95% CI 1.13–1.55). TD analysis confirmed the results for phosphate <1.13 mmol/L. HR estimates were higher in patients with diabetes versus those without diabetes for baseline analysis only (P-value = 0.014). FP analysis confirmed the results of baseline and TD analyses. Conclusion. Patients with iPTH, calcium and phosphate levels within the KDOQI target ranges have the lowest risk of mortality compared with those outside the target ranges.

Background. Only few data are available on pregnancy in patients with lupus nephritis (LN) diagnosed before conception. The aim of this study was to identify the risk factors for complicated pregnancy in women with pre-existing LN. Methods. In a multicentre study, we collected data on 113 pregnancies occurring in 81 women with pre-existing biopsy-proven LN. Primary outcomes were fetal loss including perinatal death and renal flares during and 12 months after pregnancy. Univariate and logistic regression analyses were used to identify predictors of outcomes. Results. Renal biopsy performed 7.2 ± 4.9 years before pregnancy showed the following WHO classes: 6 patients in II, 8 in III, 48 in IV and 19 in V. At conception, most patients were in complete (49%) or partial (27%) remission. There were nine spontaneous abortions, one stillbirth and five neonatal deaths. Thirty-one deliveries were preterm. Birth weight was <2500 g in 34 newborns. During pregnancy or after delivery, there were 34 renal flares, most of which (20) were reversible. Three patients had a progressive decline of glomerular filtration rate (one on dialysis). At logistic regression analysis, the pregnancy outcome was predicted by hypocomplementaemia at conception (RR 19.02; 90% CI 4.58–78.96) and aspirin during pregnancy (RR 0.11; 90% CI 0.03–0.38). Renal flare was predicted by renal status (partial remission RR 3.0; 90% CI 1.23–7.34, nonremission RR 9.0; 90% CI 3.59–22.57). Conclusions. Pregnancy can be successful in most women with pre-existing LN, even for those with a severe renal involvement at onset. Renal flares during and after pregnancy are not uncommon and can be predicted by renal status assessed before pregnancy. Normocomplementaemia and low-dose aspirin therapy during pregnancy are independent predictors of a favourable fetal outcome.

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/m², 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/m² and FTI between 4 and 15 kg/m² (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.