Estimation of Muscle Mass in the Integrated Assessment of Patients on Hemodialysis.

Assessment of muscle mass (MM) or its proxies, lean tissue mass (LTM) or fat-free mass (FFM), is an integral part of the diagnosis of protein-energy wasting (PEW) and sarcopenia in patients on hemodialysis (HD). Both sarcopenia and PEW are related to a loss of functionality and also increased morbidity and mortality in this patient population. However, loss of MM is a part of a wider spectrum, including inflammation and fluid overload. As both sarcopenia and PEW are amendable to treatment, estimation of MM regularly is therefore of major clinical relevance. Whereas, computer-assisted tomography (CT) or dual-energy X-ray absorptiometry (DXA) is considered a reference method, it is unsuitable as a method for routine clinical monitoring. In this review, different bedside methods to estimate MM or its proxies in patients on HD will be discussed, with emphasis on biochemical methods, simplified creatinine index (SCI), bioimpedance spectroscopy (BIS), and muscle ultrasound (US). Body composition parameters of all methods are related to the outcome and appear relevant in clinical practice. The US is the only parameter by which muscle dimensions are measured. BIS and SCI are also dependent on either theoretical assumptions or the use of population-specific regression equations. Potential caveats of the methods are that SCI can be influenced by residual renal function, BIS can be influenced by fluid overload, although the latter may be circumvented by the use of a three-compartment model, and that muscle US reflects regional and not whole body MM. In conclusion, both SCI and BIS as well as muscle US are all valuable methods that can be applied for bedside nutritional assessment in patients on HD and appear suitable for routine follow-up. The choice for either method depends on local preferences. However, estimation of MM or its proxies should always be part of a multidimensional assessment of the patient followed by a personalized treatment strategy.

Amino acid removal during hemodialysis can be compensated for by protein ingestion and is not compromised by intradialytic exercise: a randomized controlled crossover trial.

BACKGROUND: Patients with end-stage renal disease (ESRD) undergoing hemodialysis experience a rapid decline in skeletal muscle mass and strength. Hemodialysis removes amino acids (AAs) from the circulation, thereby lowering plasma AA concentrations and stimulating proteolysis. OBJECTIVES: In the present study, we evaluate the impact of intradialytic protein ingestion at rest and following exercise on AA removal and plasma AA availability in patients with ESRD. METHODS: Ten patients (age: 65 ± 16 y, male/female: 8/2, BMI: 24.2 ± 4.8 kg/m2, serum albumin: 3.4 ± 0.3 g/dL) with ESRD undergoing hemodialysis participated in this randomized controlled crossover trial. During 4 hemodialysis sessions, patients were assigned to ingest 40 g protein or a placebo 60 min after initiation, both at rest (PRO and PLA, respectively) and following exercise (PRO + EX and PLA + EX, respectively). Spent dialysate and blood samples were collected every 30 min throughout hemodialysis to assess AA removal and plasma AA availability. RESULTS: Plasma AA concentrations declined by 26.1 ± 4.5% within 30 min after hemodialysis initiation during all interventions (P < 0.001, η2p > 0.79). Protein ingestion, but not intradialytic exercise, increased AA removal throughout hemodialysis (9.8 ± 2.0, 10.2 ± 1.6, 16.7 ± 2.2, and 17.3 ± 2.3 g during PLA, PLA + EX, PRO, and PRO + EX interventions, respectively; protein effect P < 0.001, η2p = 0.97; exercise effect P = 0.32, η2p = 0.11). Protein ingestion increased plasma AA concentrations until the end of hemodialysis, whereas placebo ingestion resulted in decreased plasma AA concentrations (time effect P < 0.001, η2p > 0.84). Plasma AA availability (incremental AUC) was greater during PRO and PRO + EX interventions (49 ± 87 and 70 ± 34 mmol/L/240 min, respectively) compared with PLA and PLA + EX interventions (-227 ± 54 and -208 ± 68 mmol/L/240 min, respectively; protein effect P < 0.001, η2p = 0.98; exercise effect P = 0.21, η2p = 0.16). CONCLUSIONS: Protein ingestion during hemodialysis compensates for AA removal and increases plasma AA availability both at rest and during recovery from intradialytic exercise. Intradialytic exercise does not compromise AA removal or reduce plasma AA availability during hemodialysis in a postabsorptive or postprandial state.

The Effects of Chronic Dialysis on Physical Status, Quality of Life, and Arterial Stiffness: A Longitudinal Study in Prevalent Dialysis Patients.

INTRODUCTION: It is widely known that dialysis patients have significantly impaired functional outcomes and arterial stiffness, but still few studies have investigated the effects of dialysis longitudinally by a multidimensional approach. We aimed to assess longitudinal patterns of physical activity (PA), physical functioning (PF), health-related quality of life (HrQoL), body composition (BC), and arterial stiffness in prevalent dialysis patients. MATERIALS AND METHODS: Thirty-nine prevalent dialysis patients (23 conventional hemodialysis [CHD] and 16 peritoneal dialysis) with a mean vintage of 25.7 (±22.1) months were included in this observational prospective study with a 2-year follow-up, and at baseline 20 healthy controls were included. Measurements were performed every 6 months. HrQoL was assessed using the Short Form-36 (SF-36) questionnaire. PA was assessed using the SenseWear™ Pro3 accelerometer. PF was assessed by walking speed, the PF subscale of the SF-36, and handgrip strength (HGS). BC was assessed using the Body Composition Monitor® and arterial stiffness by measuring carotid-femoral pulse wave velocity (PWV). The longitudinal trend was assessed using linear mixed models, correcting for sex, age, and dialysis vintage. For PWV, the trend was additionally corrected for diabetes and systolic blood pressure. RESULTS: After correction, no statistically significant changes over time were observed for the parameters of PA, PF, HrQoL, and BC. In the combined group and in the group of CHD patients only, a significant change was observed for PWV (overall trend: p = 0.007 and p = 0.008, respectively). A statistically significant difference at baseline was observed between dialysis patients and healthy controls in all parameters, except for HGS and PWV. DISCUSSION/CONCLUSION: We observed no statistically significant changes in functional outcomes during a 2-year follow-up period, but a significant increase was observed for arterial stiffness. These results might suggest that after a certain period in time, a relatively stable course is present in functional outcomes, but an ongoing deterioration in arterial stiffness occurs, which might increase the risk of cardiovascular disease and all-cause mortality in these patients.

Advanced glycation endproducts and dicarbonyls in end-stage renal disease: associations with uraemia and courses following renal replacement therapy.

BACKGROUND: End-stage renal disease (ESRD) is strongly associated with cardiovascular disease (CVD) risk. Advanced glycation endproducts (AGEs) and dicarbonyls, major precursors of AGEs, may contribute to the pathophysiology of CVD in ESRD. However, detailed data on the courses of AGEs and dicarbonyls during the transition of ESRD patients to renal replacement therapy are lacking. METHODS: We quantified an extensive panel of free and protein-bound serum AGEs [N ∈-(carboxymethyl)lysine (CML), N ∈-(carboxyethyl)lysine (CEL), N δ-(5-hydro-5-methyl-4-imidazolon-2-yl)ornithine (MG-H1)], serum dicarbonyls [glyoxal (GO), methylglyoxal (MGO), 3-deoxyglucosone (3-DG)] and tissue AGE accumulation [estimated by skin autofluorescence (SAF)] in a combined cross-sectional and longitudinal observational study of patients with ESRD transitioning to dialysis or kidney transplantation (KTx), prevalent dialysis patients and healthy controls. Cross-sectional comparisons were performed with linear regression analyses, and courses following renal replacement therapy were analysed with linear mixed models. RESULTS: Free and protein-bound AGEs, dicarbonyls and SAF were higher in chronic kidney disease (CKD) Stage 5 non-dialysis (CKD 5-ND; n = 52) and CKD Stage 5 dialysis (CKD 5-D; n = 35) than in controls (n = 42). In addition, free AGEs, protein-bound CML, GO and SAF were even higher in CKD 5-D than in CKD5-ND. Similarly, following dialysis initiation (n = 43) free and protein-bound AGEs, and GO increased, whereas SAF remained similar. In contrast, following KTx (n = 21), free and protein-bound AGEs and dicarbonyls, but not SAF, markedly declined. CONCLUSIONS: AGEs and dicarbonyls accumulate in uraemia, which is even exaggerated by dialysis initiation. In contrast, KTx markedly reduces AGEs and dicarbonyls. Given their associations with CVD risk in high-risk populations, lowering AGE and dicarbonyl levels may be valuable.

End-Stage Renal Disease Patients Lose a Substantial Amount of Amino Acids during Hemodialysis.

BACKGROUND: Poor nutritional status is frequently observed in end-stage renal disease patients and associated with adverse clinical outcomes and increased mortality. Loss of amino acids (AAs) during hemodialysis (HD) may contribute to protein malnutrition in these patients. OBJECTIVE: We aimed to assess the extent of AA loss during HD in end-stage renal disease patients consuming their habitual diet. METHODS: Ten anuric chronic HD patients (mean ± SD age: 67.9 ± 19.3 y, BMI: 23.2 ± 3.5 kg/m2), undergoing HD 3 times per week, were selected to participate in this study. Spent dialysate was collected continuously and plasma samples were obtained directly before and after a single HD session in each participant. AA profiles in spent dialysate and in pre-HD and post-HD plasma were measured through ultra-performance liquid chromatography to determine AA concentrations and, as such, net loss of AAs. In addition, dietary intake before and throughout HD was assessed using a 24-h food recall questionnaire during HD. Paired-sample t tests were conducted to compare pre-HD and post-HD plasma AA concentrations. RESULTS: During an HD session, 11.95 ± 0.69 g AAs were lost via the dialysate, of which 8.26 ± 0.46 g were nonessential AAs, 3.69 ± 0.31 g were essential AAs, and 1.64 ± 0.17 g were branched-chain AAs. As a consequence, plasma total and essential AA concentrations declined significantly from 2.88 ± 0.15 and 0.80 ± 0.05 mmol/L to 2.27 ± 0.11 and 0.66 ± 0.05 mmol/L, respectively (P < 0.05). AA profiles of pre-HD plasma and spent dialysate were similar. Moreover, AA concentrations in pre-HD plasma and spent dialysate were strongly correlated (Spearman's ρ = 0.92, P < 0.001). CONCLUSIONS: During a single HD session, ∼12 g AAs are lost into the dialysate, causing a significant decline in plasma AA concentrations. AA loss during HD can contribute substantially to protein malnutrition in end-stage renal disease patients. This study was registered at the Netherlands Trial Registry (NTR7101).

Three compartment bioimpedance spectroscopy in the nutritional assessment and the outcome of patients with advanced or end stage kidney disease: What have we learned so far?

Bioimpedance spectroscopy (BIS) is an easily applicable tool to assess body composition. The three compartment model BIS (3C BIS) conventionally expresses body composition as lean tissue index (LTI) (lean tissue mass [LTM]/height in meters squared) and fat tissue index (FTI) (adipose tissue mass/height in meters squared), and a virtual compartment reflecting fluid overload (FO). It has been studied extensively in relation to diagnosis and treatment guidance of fluid status disorders in patients with advanced-stage or end-stage renal disease. It is the aim of this article to provide a narrative review on the relevance of 3C BIS in the nutritional assessment in this population. At a population level, LTI decreases after the start of hemodialysis, whereas FTI increases. LTI below the 10th percentile is a consistent predictor of outcome whereas a low FTI is predominantly associated with outcome when combined with a low LTI. Recent research also showed the connection between low LTI, inflammation, and FO, which are cumulatively associated with an increased mortality risk. However, studies toward nutritional interventions based on BIS data are still lacking in this population. In conclusion, 3C BIS, by disentangling the components of body mass index, has contributed to our understanding of the relevance of abnormalities in different body compartments in chronic kidney disease patients, and appears to be a valuable prognostic tool, at least at a population level. Studies assessing the effect of BIS guided nutritional intervention could further support its use in the daily clinical care for renal patients.

Citric-acid dialysate improves the calcification propensity of hemodialysis patients: A multicenter prospective randomized cross-over trial.

INTRODUCTION: The concentration of dialysate calcium (dCa) has been suggested to affect vascular calcification, but evidence is scarce. Calcification propensity reflects the intrinsic capacity of serum to prevent calcium and phosphate to precipitate. The use of citric-acid dialysate may have a beneficial effect on the calcification propensity due to the chelating effect on calcium and magnesium. The aim of this study was to compare the intradialytic and short-term effects of haemodialysis with either standard acetic-acid dialysate with dCa1.50 (A1.5) or dCa1.25 (A1.25), as well as citric-acid dialysate with dCa1.50 (C1.5) in bicarbonate dialysis on the calcification propensity of serum. METHODS: Chronic stable hemodialysis patients were included. This multicenter randomized cross-over study consisted out of a baseline week (A1.5), followed by the randomized sequence of A1.25 or C1.5 for one week after which the alternate treatment was provided after a washout week with A1.5. Calcification propensity of serum was assessed by time-resolved nephelometry where the T50 reflects the transition time between formation of primary and secondary calciprotein particles. RESULTS: Eighteen patients (median age 70 years) completed the study. Intradialytic change in T50 was increased with C1.5 (121 [90-152]min) compared to A1.25 (83 [43-108]min, p<0.001) and A1.5 (66 [18-102]min, p<0.001). During the treatment week, predialysis T50 increased significantly from the first to the third session with C1.5 (271 [234-291] to 280 [262-339]min, p = 0.002) and with A1.25 (274 [213-308] to 307 [256-337]min, p<0.001), but not with A1.5 (284 [235-346] to 300 [247-335]min, p = 0.33). CONCLUSION: Calcification propensity, as measured by the change in T50, improved significantly during treatment in C1.5 compared to A1.25 and A1.5. Long-term studies are needed to investigate the effects of different dialysate compositions concentrations on vascular calcification and bone mineral disorders.

Endothelial dysfunction and low-grade inflammation in the transition to renal replacement therapy.

INTRODUCTION: End-stage renal disease (ESRD) strongly associates with cardiovascular disease (CVD) risk. This risk is not completely mitigated by renal replacement therapy. Endothelial dysfunction (ED) and low-grade inflammation (LGI) may contribute to the increased CVD risk. However, data on serum biomarkers of ED and LGI during the transition to renal replacement therapy (dialysis and kidney transplantation) are scarce. METHODS: We compared serum biomarkers of ED and LGI between 36 controls, 43 participants with chronic kidney disease (CKD) stage 5 non-dialysis (CKD5-ND), 20 participants with CKD stage 5 hemodialysis (CKD5-HD) and 14 participants with CKD stage 5 peritoneal dialysis (CKD5-PD). Further, in 34 and 15 participants repeated measurements were available during the first six months following dialysis initiation and kidney transplantation, respectively. Serum biomarkers of ED (sVCAM-1, E-selectin, P-selectin, thrombomodulin, sICAM-1, sICAM-3) and LGI (hs-CRP, SAA, IL-6, IL-8, TNF-α) were measured with a single- or multiplex array detection system based on electro-chemiluminescence technology. RESULTS: In linear regression analyses adjusted for potential confounders, participants with ESRD had higher levels of most serum biomarkers of ED and LGI than controls. In addition, in CKD5-HD levels of serum biomarkers of ED and LGI were largely similar to those in CKD5-ND. In contrast, in CKD5-PD levels of biomarkers of ED were higher than in CKD5-ND and CKD5-HD. Similarly, in linear mixed model analyses sVCAM-1, thrombomodulin, sICAM-1 and sICAM-3 increased after PD initiation. In contrast, incident HD patients showed an increase in sVCAM-1, P-selectin and TNF-α, but a decline of hs-CRP, SAA and IL-6. Further, following kidney transplantation sVCAM-1, thrombomodulin, sICAM-3 and TNF-α were lower at three months post-transplantation and remained stable in the three months thereafter. CONCLUSIONS: Levels of serum biomarkers of ED and LGI were higher in ESRD as compared with controls. In addition, PD initiation and, less convincingly, HD initiation may increase levels of selected serum biomarkers of ED and LGI on top of uremia per se. In contrast to dialysis, several serum biomarkers of ED and LGI markedly declined following kidney transplantation.

Relations of advanced glycation endproducts and dicarbonyls with endothelial dysfunction and low-grade inflammation in individuals with end-stage renal disease in the transition to renal replacement therapy: A cross-sectional observational study.

BACKGROUND: Cardiovascular disease (CVD) related mortality and morbidity are high in end-stage renal disease (ESRD). The pathophysiology of CVD in ESRD may involve non-traditional CVD risk factors, such as accumulation of advanced glycation endproducts (AGEs), dicarbonyls, endothelial dysfunction (ED) and low-grade inflammation (LGI). However, detailed data on the relation of AGEs and dicarbonyls with ED and LGI in ESRD are limited. METHODS: We examined cross-sectional Spearman's rank correlations of AGEs and dicarbonyls with serum biomarkers of ED and LGI in 43 individuals with chronic kidney disease (CKD) stage 5 not on dialysis (CKD5-ND). Free and protein-bound serum AGEs (N∈-(carboxymethyl)lysine (CML), N∈-(carboxyethyl)lysine (CEL), Nδ-(5-hydro-5-methyl-4-imidazolon-2-yl)ornithine (MG-H1)) and serum dicarbonyls (glyoxal, methylglyoxal, 3-deoxyglucosone) were analyzed with tandem mass spectrometry, and tissue AGE accumulation was estimated by skin autofluorescence (SAF). Further, serum biomarkers of ED and LGI included sVCAM-1, sE-selectin, sP-selectin, sThrombomodulin, sICAM-1, sICAM-3, hs-CRP, SAA, IL-6, IL-8 and TNF-α. RESULTS: After adjustment for age, sex and diabetes status, protein-bound CML was positively correlated with sVCAM-1; free CEL with sVCAM-1 and sThrombomodulin; glyoxal with sThrombomodulin; and methylglyoxal with sVCAM-1 (correlation coefficients ranged from 0.36 to 0.44). In addition, free CML was positively correlated with SAA; protein-bound CML with IL-6; free CEL with hs-CRP, SAA and IL-6; free MG-H1 with SAA; protein-bound MG-H1 with IL-6; and MGO with hs-CRP and IL-6 (correlation coefficients ranged from 0.33 to 0.38). Additional adjustment for eGFR attenuated partial correlations of serum AGEs and serum dicarbonyls with biomarkers of ED and LGI. CONCLUSIONS: In individuals with CKD5-ND, higher levels of serum AGEs and serum dicarbonyls were related to biomarkers of ED and LGI after adjustment for age, sex and diabetes mellitus. Correlations were attenuated by eGFR, suggesting that eGFR confounds and/or mediates the relation of serum AGEs and dicarbonyls with ED and LGI.

Living-donor transplantation leads to a major improvement in physical functioning: an observational study on the impact on potential donors and their recipients.

BACKGROUND: Prospective studies combining physical functioning (PF), physical activity (PA), and body composition (BC) after living donor transplantation/donation are scarce. We aimed to study differences in these parameters between kidney transplant recipients and their living donors by examining changes in these parameters in the first post-operative year in both groups. METHODS: Twenty-two kidney transplant recipients and 22 healthy kidney donors were included in this prospective longitudinal study with a follow-up until twelve months. PF was assessed by handgrip strength (HGS), and by the physical domains of health-related quality of life (HRQOL) using the Short Form-36 questionnaire [PF (SF-36 PF) and physical component summary (PCS) score]. BC was measured by the Body Composition Monitor©, and PA was measured by the SenseWear™ pro3. RESULTS: At baseline, recipients had significantly lower HGS (after adjustment for sex and body weight), SF-36 PF, PCS, and PA, as compared with their donors. In recipients HGS significantly increased in the first year after transplantation, but PA did not change in the first six months after transplantation. Furthermore, no significant increase in lean tissue mass was observed. For healthy donors no significant changes in these parameters were observed, with exception of SF-36 PF, which declined in the first three months after donation, but equaled baseline values after twelve months. CONCLUSION: Recipients showed impressive improvements in PF and the physical domains of HRQOL in the first year after transplantation, reaching levels of healthy kidney donors already three to six months after transplantation. On the contrary, living kidney donation did not show any deterioration of the investigated parameters, supporting little impact for well-screened donors, while there is high benefit for transplant recipients.

Health-related quality of life in end-stage renal disease patients: the effects of starting dialysis in the first year after the transition period.

BACKGROUND/AIMS: Prevalent dialysis patients have low scores of health-related quality of life (HRQOL) which are associated with increased risk of hospitalization and mortality. Also in CKD-5 non-dialysis patients, HRQOL scores seem to be lower as compared with the general population. This study firstly aimed to compare HRQOL between CKD-5 non-dialysis and prevalent dialysis patients in a cross-sectional analysis and to assess longitudinal changes over 1 year after the dialysis initiation. Secondly, the correlation between HRQOL and physical activity (PA) was explored. METHODS: Cross-sectional 44 CKD-5 non-dialysis, 29 prevalent dialysis, and 20 healthy controls were included. HRQOL was measured by Short Form-36 questionnaires to measure physical and mental domains of health expressed by the physical component summary (PCS) and mental component summary (MCS) scores. PA was measured by a SenseWear™ pro3. Longitudinally, HRQOL was assessed in 38 CKD-5 non-dialysis patients (who were also part of the cross-sectional analysis), before dialysis initiation until 1 year after dialysis initiation. RESULTS: PCS scores were significantly lower both in CKD-5 non-dialysis patients and in prevalent dialysis patients as compared with healthy controls (p < 0.001). MCS scores were significantly lower in both CKD-5 non-dialysis patients (p = 0.003), and in dialysis patients (p = 0.022), as compared with healthy controls. HRQOL scores did not change significantly from the CKD-5 non-dialysis phase into the first year after dialysis initiation. PA was significantly related to PCS in both CKD-5 non-dialysis patients (r = 0.580; p < 0.001), and dialysis patients (r = 0.476; p = 0.009). CONCLUSIONS: HRQOL is already low in the CKD-5 non-dialysis phase. In the first year after dialysis initiation, HRQOL did not change significantly. Given the correlation between PCS score and PA, physical activity programs may be potential tools to improve HRQOL in both CKD-5 non-dialysis as well as in prevalent dialysis patients.

Cardiovascular and Patient Phenotype of Extended Haemodialysis: A Critical Analysis of Studying a Unique Patient Population.

BACKGROUND: Extended haemodialysis (EHD) has been associated with better outcomes compared to conventional (CHD) regimes. The cardiovascular (CV) profile of these patients has not been assessed in detail. METHODS: We report baseline demographic and CV phenotype of 36 CHD and 36 EHD participants to a longitudinal multicentre study. We measured pulse wave velocity (PWV), 24-h ambulatory blood pressure, sublingual dark-field capillaroscopy and vascular biomarkers. RESULTS: EHD patients were younger (p < 0.01), with less CV comorbidity (p = 0.04) and higher dialysis vintage (p < 0.01). Higher PWV in CHD (p = 0.02) was not independent of demographic differences in the 2 groups. Biomarker profiles were similar in EHD and CHD but abnormal compared to healthy controls. CONCLUSION: Although CV profiles in these 2 cohorts were similar, EHD patients were distinct from the CHD population in terms of age and dialysis vintage and appear to comprise a unique group. Direct comparison of outcomes in these groups is challenging due to clinical bias.

Inflammatory and Angiogenic Factors Linked to Longitudinal Microvascular Changes in Hemodialysis Patients Irrespective of Treatment Dose Intensity.

BACKGROUND: Cardiovascular disease is a major contributor to the poor outcomes observed in hemodialysis. We investigated the relationship between hemodialysis intensity and vascular parameters in high-dose (HDHD; >12hrs/week) and Conventional (CHD; ≤12hrs/week) hemodialysis intensity over a 6-month period. METHODS: We present the 6-month longitudinal analysis of a 2-year multicenter study investigating the effects of HDHD on cardiovascular parameters. We used pulse wave velocity, 24hr ambulatory blood pressure and sublingual dark field capillaroscopy measurements to assess macro- and microcirculation on 6-monthly basis. Pro-inflammatory and endothelial biomarkers were also measured at 6-monthly intervals. RESULTS: 47 participants (21 HDHD, 26 CHD) were studied. CHD were older (63.5±14.2 vs 53.7±12.6 yr; p=0.018), with shorter dialysis vintage (median 23 vs 61 months; p=0.001). There was considerable variability in the degree and direction of change of circulatory measurements over a 6-month period. Hemodialysis intensity (hrs/week) did not correlate to these changes, when adjusted for age, dialysis vintage and comorbidity. Higher levels of Interleukin (IL)-8 measured at baseline independently predicted an increase in the Perfused Boundary Region (5-25µm) of the endothelial glycocalyx (p=0.010) whilst higher levels of soluble Flt-1 had a significant inverse effect (p=0.002) in an adjusted linear model. CONCLUSION: Hemodialysis intensity did not predict changes in either macro- or microvascular parameters. Inflammation mediated through the IL-8 pathway predicted microvascular injury while Flt-1, a potential marker of angiogenesis and endothelial repair, might have a significant protective role. Further understanding of these pathways will be necessary to improve dialysis outcomes.

Extracellular overhydration linked with endothelial dysfunction in the context of inflammation in haemodialysis dependent chronic kidney disease.

BACKGROUND: Haemodialysis (HD) patients are predisposed to dysregulated fluid balance leading to extracellular water (ECW) expansion. Fluid overload has been closely linked with outcome in these patients. This has mainly been attributed to cardiac volume overload, but the relation between abnormalities in fluid status with micro- and macrovascular dysfunction has not been studied in detail. We studied the interaction of macro- and microvascular factors in states of normal and over- hydration in HD-dependent CKD. METHODS: Fluid compartments [total body water (TBW) and ECW] and overhydration index (OH) were measured with Multifrequency bio-impedance (BCM). Overhydration was defined as OH/ECW>7%. Overhydration was also assessed using the ECW/TBW ratio. Macrocirculation was assessed by pulse-wave velocity (PWV) and mean arterial pressure (MAP) measurements while microcirculation through sublingual capillaroscopy assessment of the Perfused Boundary Region of the endothelial glycocalyx (PBR 5-25mcg). A panel of pro-inflammatory and vascular serum biomarkers and growth factors was analysed. RESULTS: Of 72 HD participants, 30 were in normohydration (N) range and 42 overhydrated according to the OH/ECW ratio. Average ECW/TBW was 0.48±0.03. Overhydrated patients had higher MAP (122.9±22.5 v 111.7±22.2mmHg, p = 0.04) and comorbidities (median Davies score 1.5 v 1.0, p = 0.03). PWV (p = 0.25) and PBR 5-25mcg (p = 0.97) did not differ between the 2 groups. However, Vascular Adhesion Molecule (VCAM)-1, Interleukin-6 and Thrombomodulin, and reduced Leptin were observed in the overhydrated group. Elevation in VCAM-1 levels (OR 1.03; 95% CI 1.01-1.06; p = 0.02) showed a strong independent association with OH/ECW>7% in an adjusted logistic regression analysis and exhibited a strong linear relationship with ECW/TBW (Bata = 0.210, p = 0.03) in an also adjusted model. CONCLUSION: Extracellular fluid overload is significantly linked to microinflammation and markers of endothelial dysfunction. The study provides novel insight in the cardiovascular risk profile associated with overhydration in uraemia.

Physical Activity in End-Stage Renal Disease Patients: The Effects of Starting Dialysis in the First 6 Months after the Transition Period.

OBJECTIVES: Physical inactivity in end-stage renal disease (ESRD) patients is associated with increased mortality, and might be related to abnormalities in body composition (BC) and physical performance. It is uncertain to what extent starting dialysis influences the effects of ESRD on physical activity (PA). This study aimed to compare PA and physical performance between stage 5 chronic kidney disease (CKD-5) non-dialysis and dialysis patients, and healthy controls, to assess alterations in PA during the transition from CKD-5 non-dialysis to dialysis, and to relate PA to BC. METHODS: For the cross-sectional analyses 44 CKD-5 non-dialysis patients, 29 dialysis patients, and 20 healthy controls were included. PA was measured by the SenseWear™ pro3. Also, the walking speed and handgrip strength (HGS) were measured. BC was measured by the Body Composition Monitor©. Longitudinally, these parameters were assessed in 42 CKD-5 non-dialysis patients (who were also part of the cross-sectional analysis), before the start of dialysis and 6 months thereafter. RESULTS: PA was significantly lower in CKD-5 non-dialysis patients as compared to that in healthy controls but not as compared to that in dialysis patients. HGS was significantly lower in dialysis patients as compared to that in healthy controls. Walking speed was significantly lower in CKD-5 non-dialysis patients as compared to that in healthy controls but not as compared to that in dialysis patients. Six months after starting dialysis, activity related energy expenditure (AEE) and walking speed significantly increased. CONCLUSIONS: PA is already lower in CKD-5 non-dialysis patients as compared to that in healthy controls and does not differ from that of dialysis patients. However, the transition phase from CKD-5 non-dialysis to dialysis is associated only with a modest improvement in AEE.

Cardiac Troponin T: Smaller Molecules in Patients with End-Stage Renal Disease than after Onset of Acute Myocardial Infarction.

BACKGROUND: We have found previously that in acute myocardial infarction (AMI), cardiac troponin T (cTnT) is degraded in a time-dependent pattern. We investigated whether cTnT forms differed in patients with chronic cTnT increases, as seen with renal dysfunction, from those in the acute phase of myocardial infarction. METHODS: We separated cTnT forms by gel filtration chromatography (GFC) in end-stage renal disease (ESRD) patients: prehemodialysis (pre-HD) and post-HD (n = 10) and 2 months follow-up (n = 6). Purified (cTnT) standards, quality control materials of the clinical cTnT immunoassay (Roche), and AMI patients' sera also were analyzed. Immunoprecipitation and Western blotting were performed with the original cTnT antibodies from the clinical assay and antibodies against the N- and C-terminal end of cTnT. RESULTS: GFC analysis revealed the retention of purified cTnT at 27.5 mL, identical to that for cTnT in quality controls. For all ESRD patients, one cTnT peak was found at 45 mL, pre- and post-HD, and stable over time. Western blotting illustrated that this peak corresponded to cTnT fragments <18 kDa missing the N- and C-terminal ends. AMI patients' sera revealed cTnT peaks at 27.5 and 45 mL, respectively, corresponding to N-terminal truncated cTnT of 29 kDa and N- and C-terminal truncated fragments of <18 kDa, respectively. CONCLUSIONS: We found that cTnT forms in ESRD patients are small (<18 kDa) and different from forms seen in AMI patients. These insights may prove useful for development of a more specific cTnT immunoassay, especially for the acute and diagnostic phase of myocardial infarction.

Quality of Life in Dialysis Patients: A Retrospective Cohort Study.

BACKGROUND/AIM: Physical component summary (PCS) and mental component summary (MCS) scores are associated with hospitalization and mortality in patients with end-stage renal disease. Most studies in these patients are cross-sectional in nature. This study aimed to assess the dynamics of health-related quality of life (HRQOL) over time, as well as determinants of changes in HRQOL. Also, the relation between changes in HRQOL with respect to both hospitalization and mortality was assessed. METHODS: A cross-sectional analysis was performed in 77,848 hemodialysis (HD) patients whereas changes in HRQOL were assessed in 8,339 patients over a 1-year time period. HRQOL measurements were assessed with Kidney Disease Quality of Life-36 questionnaires. Also, relevant biomarkers (albumin, creatinine, hemoglobin, sodium) and equilibrated normalized protein catabolic rate (enPCR) were measured. RESULTS: HRQOL were found to be decreased in HD patients. Nutritional indices like creatinine (r = 0.23; p < 0.0001) and serum albumin (r = 0.21; p < 0.0001) positively correlated with PCS scores. An increase in levels of albumin, creatinine, hemoglobin, enPCR and serum sodium over time are significantly (p < 0.0001) associated with positive changes in PCS scores. Changes in PCS scores were found to be predictive for hospitalization and mortality. The correlates of predictors for MCS scores were less strong compared to that of PCS scores. The strongest positive predictors of MCS scores were age (r = 0.08; p < 0.0001), albumin (r = 0.05; p < 0.0001) and sodium (r = 0.05; p < 0.0001). CONCLUSIONS: Nutritional factors are strongly associated with changes in HRQOL, especially with regard to PCS scores (change over time in HRQOL was an independent predictor of hospitalization and mortality). Increased scores of HRQOL over time are positively associated with survival.

The first year on haemodialysis: a critical transition.

The first year following the start of haemodialysis (HD) is associated with increased mortality, especially during the first 90-120 days after the start of dialysis. Whereas the start of dialysis has important effects on the internal environment of the patient, there are relatively few studies assessing changes in phenotype and underlying mechanisms during the transition period following pre-dialysis to dialysis care, although more insight into these parameters is of importance in unravelling the causes of this increased early mortality. In this review, changes in cardiovascular, nutritional and inflammatory parameters during the first year of HD, as well as changes in physical and functional performance are discussed. Treatment-related factors that might contribute to these changes include vascular access and pre-dialysis care, dialysate prescription and the insufficient correction of the internal environment by current dialysis techniques. Patient-related factors include the ongoing loss of residual renal function and the progression of comorbid disease. Identifying phenotypic changes and targeting risk patterns might improve outcome during the transition period. Given the scarcity of data on this subject, more research is needed.

Body composition in dialysis patients: a functional assessment of bioimpedance using different prediction models.

OBJECTIVES: The assessment of body composition (BC) in dialysis patients is of clinical importance given its role in the diagnosis of malnutrition and sarcopenia. Bioimpedance techniques routinely express BC as a 2-compartment (2-C) model distinguishing fat mass (FM) and fat-free mass (FFM), which may be influenced by the hydration of adipose tissue and fluid overload (OH). Recently, the BC monitor was introduced which applies a 3-compartment (3-C) model, distinguishing OH, adipose tissue mass, and lean tissue mass. The aim of this study was to compare BC between the 2-C and 3-C models and assess their relation with markers of functional performance (handgrip strength [HGS] and 4-m walking test), as well as with biochemical markers of nutrition. METHODS: Forty-seven dialysis patients (30 males and 17 females) (35 hemodialysis, 12 peritoneal dialysis) with a mean age of 64.8 ± 16.5 years were studied. 3-C BC was assessed by BC monitor, whereas the obtained resistivity values were used to calculate FM and FFM according to the Xitron Hydra 4200 formulas, which are based on a 2-C model. RESULTS: FFM (3-C) was 0.99 kg (95% confidence interval [CI], 0.27 to 1.71, P = .008) higher than FFM (2-C). FM (3-C) was 2.43 kg (95% CI, 1.70-3.15, P < .001) lower than FM (2-C). OH was 1.4 ± 1.8 L. OH correlated significantly with ΔFFM (FFM 3-C - FFM 2-C) (r = 0.361; P < .05) and ΔFM (FM 3-C - FM 2-C) (r = 0.387; P = .009). HGS correlated significantly with FFM (2-C) (r = 0.713; P < .001), FFM (3-C) (r = 0.711; P < .001), body cell mass (2-C) (r = 0.733; P < .001), and body cell mass (3-C) (r = 0.767; P < .001). Both physical activity (r = 0.456; P = .004) and HGS (r = 0.488; P = .002), but not BC, were significantly related to walking speed. CONCLUSIONS: Significant differences between 2-C and 3-C models were observed, which are partly explained by the presence of OH. OH, which was related to ΔFFM and ΔFM of the 2-C and 3-C models, is therefore an important parameter for the differences in estimation of BC parameters of the 2-C and 3-C models. Both FFM (3-C) and FFM (2-C) were significantly related to HGS. Bioimpedance, HGS, and the 4-m walking test may all be valuable tools in the multidimensional nutritional assessment of both hemodialysis and peritoneal dialysis patients.

Season affects body composition and estimation of fluid overload in haemodialysis patients: variations in body composition; a survey from the European MONDO database.

BACKGROUND: Seasonal variations in blood pressure (BP) and inter-dialytic weight gain (IDWG) are well established in dialysis patients. However, no study has assessed changes in body composition (BC) in this population. METHODS: In this survey, seasonal variations in fat mass (FM), lean tissue mass (LTM), extracellular water (ECW) and fluid overload (FO) were assessed in 42 099 dialysis patients (mean age 61.2 years, 58% males) from the Fresenius Medical Care Europe database, as part of the MONitoring Dialysis Outcomes (MONDO) consortium, in relation to other nutritional parameters, IDWG and BP. BC was assessed by a body composition monitor (BCM®, Fresenius Medical Care, Bad Homburg, Germany). RESULTS: FM was highest in winter and lowest in summer (▵FM -1.17 kg; P < 0.001), whereas LTM was lowest during winter and highest in summer (▵LTM 0.86 kg; P < 0.0001). ECW and FO were lowest in winter, and highest in spring (▵ECW: 0.13 L; P < 0.0001, ▵FO: 0.31 L; P < 0.0001) and summer (▵ECW: 0.15 L; P < 0.0001 and ▵FO: 0.2 L; P < 0.0001), despite a higher systolic blood pressure (SBP; 136.7 ± 17.4 mmHg) and IDWG (3.0 ± 1.1 kg) during winter. C-reactive protein (CRP), serum sodium and haemoglobin levels were highest in winter, whereas serum albumin was lowest in fall. Normalized protein catabolic rate (nPCR) was lowest in winter and matched variations in BC only to a minor degree. CONCLUSIONS: BC and hydration state, assessed by bio-impedance spectroscopy, follows a seasonal pattern which may be of relevance for the estimation of target weight, and for the interpretation of longitudinal studies including estimates of BC. Whether these changes should lead to therapeutic interventions could be the focus of future studies.