Natascha J.H. Broers

Out of control: accelerated aging in uremia

Next to a high morbidity, patients with end-stage renal failure (ESRD) suffer from a complex spectrum of clinical manifestations. Both the phenotype of patients with ESRD as well as the pathophysiology of uremia show interesting parallels with the general aging process. Phenotypically, patients with ESRD have an increased susceptibility for both cardiovascular as well as infectious disease and show a reduction in functional capacity as well as muscular mass (sarcopenia), translating into a high prevalence of frailty also in younger patients. Pathophysiologically, the immune dysfunction, telomere attrition and the presence of low-grade inflammation in uremic patients also show parallels with the aging process. System models of aging, such as the homeodynamic model and reliability theory of Gavrilov may also have relevance for ESRD. The reduction in the redundancy of compensatory mechanisms and the multisystem impairment in ESRD explain the rapid loss of homeodynamic/homeostatic balance and the increased susceptibility to external stressors in these patients. System theories may also explain the relative lack of success of interventions focusing on single aspects of renal disease. The concept of accelerated aging, which also shares similarities with other organ diseases, may be of relevance both for a better understanding of the uremic process, as well as for the design of multidimensional interventions in ESRD patients, including an important role for early rehabilitation. Research into processes akin to both aging and uremia may result in novel therapeutic approaches.

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.

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.

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.

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.

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.

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.

Wearable sensors : can they benefit patients with chronic kidney disease?

ABSTRACT Introduction: This article ponders upon wearable medical measurement devices in relation to Chronic Kidney Disease (CKD) and its’ associated comorbidities – and whether these might benefit CKD-patients. We aimed to map the intersection(s) of nephrology and wearable sensor technology to help technologists understand medical aspects, and clinicians to understand technological possibilities that are available (or soon will become so). Areas covered: A structured literature search on main comorbidities and complications CKD patients suffer from, was used to steer mini-reviews on wearable sensor technologies clustered around 3 themes being: Cardiovascular-related, diabetes-related and physical fitness/frailty. This review excludes wearable dialysis – although also strongly enabled by miniaturization – because that highly important theme deserves separate in-depth reviewing. Expert commentary: Continuous progress in integrated electronics miniaturization enormously lowered price, size, weight and energy consumption of electronic sensors, processing power, memory and wireless connectivity. These combined factors boost opportunities for wearable medical sensors. Such devices can be regarded as enablers for: Remote monitoring, influencing human behaviour (exercise, dietary), enhanced home care, remote consults, patient education and peer networks. However, to make wearable medical devices succeed, the challenge to fit them into health care structures will be dominant over the challenge to realize the bare technologies themselves.

Effects of Ultrapure Hemodialysis and Low Molecular Weight Heparin on the Endothelial Surface Layer

Background: Chronic kidney disease patients show changes in the endothelial surface layer (ESL). Whether hemodialysis (HD) itself or low molecular weight heparins (LMWH) induce ESL alterations is unknown. Methods: We studied the ESL in 20 HD patients with Sidestream Dark Field Imaging [measuring perfused boundary region (PBR)] and measurement of ESL constituents in plasma during HD in 2 studies. LMWH was administered at the start of HD in study A, and 120 min after the start of HD in study B. Mean platelet volume (MPV) and platelet large cell ratio (P-LCR) were also measured. Results: Syndecan-1 increased significantly 30 min after LMWH administration. sP-Selectin increased 120 min after HD start, and MPV and P-LCR decreased significantly during HD. No significant changes of PBR, sE-Selectin, sICAM-1, or sVCAM-1 were perceived. Conclusions: HD caused a significant increase in Syndecan-1 without a change in PBR. The administration of LMWH appeared to precede the rise in Syndecan-1.

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.