Volume overload correlates with cardiovascular risk factors in patients with chronic kidney disease
2013; Elsevier BV; Volume: 85; Issue: 3 Linguagem: Inglês
10.1038/ki.2013.336
ISSN1523-1755
AutoresSzu-Chun Hung, Ko‐Lin Kuo, Ching-Hsiu Peng, Che‐Hsiung Wu, Yu-Chung Lien, Yi-Chun Wang, Der‐Cherng Tarng,
Tópico(s)Cardiovascular Function and Risk Factors
ResumoVolume overload is a predictor of mortality in dialysis patients. However, the fluid status of patients with chronic kidney disease (CKD) but not yet on dialysis has not been accurately characterized. We used the Body Composition Monitor, a multifrequency bioimpedance device, to measure the level of overhydration in CKD patients, focusing on the association between overhydration and cardiovascular disease risk factors. Overhydration was the difference between the amount of extracellular water measured by the Body Composition Monitor and the amount of water predicted under healthy euvolemic conditions. Volume overload was defined as an overhydration value at and above the 90th percentile for the normal population. Of the 338 patients with stages 3–5 CKD, only 48% were euvolemic. Patients with volume overload were found to use significantly more antihypertensive medications and diuretics but had higher systolic blood pressures and an increased arterial stiffness than patients without volume overload. In a multivariate analysis, male sex, diabetes, pre-existing cardiovascular disease, systolic blood pressure, serum albumin, TNF-α, and proteinuria were independently all associated with overhydration. Thus, volume overload is strongly associated with both traditional and novel risk factors for cardiovascular disease. Bioimpedance devices may aid in clinical assessment by helping to identify a high-risk group with volume overload among stages 3–5 CKD patients. Volume overload is a predictor of mortality in dialysis patients. However, the fluid status of patients with chronic kidney disease (CKD) but not yet on dialysis has not been accurately characterized. We used the Body Composition Monitor, a multifrequency bioimpedance device, to measure the level of overhydration in CKD patients, focusing on the association between overhydration and cardiovascular disease risk factors. Overhydration was the difference between the amount of extracellular water measured by the Body Composition Monitor and the amount of water predicted under healthy euvolemic conditions. Volume overload was defined as an overhydration value at and above the 90th percentile for the normal population. Of the 338 patients with stages 3–5 CKD, only 48% were euvolemic. Patients with volume overload were found to use significantly more antihypertensive medications and diuretics but had higher systolic blood pressures and an increased arterial stiffness than patients without volume overload. In a multivariate analysis, male sex, diabetes, pre-existing cardiovascular disease, systolic blood pressure, serum albumin, TNF-α, and proteinuria were independently all associated with overhydration. Thus, volume overload is strongly associated with both traditional and novel risk factors for cardiovascular disease. Bioimpedance devices may aid in clinical assessment by helping to identify a high-risk group with volume overload among stages 3–5 CKD patients. Chronic kidney disease (CKD) substantially increases the risks of death and cardiovascular disease (CVD) and the use of specialized health care.1.Go A.S. Chertow G.M. Fan D. et al.Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization.N Engl J Med. 2004; 351: 1296-1305Crossref PubMed Scopus (9021) Google Scholar Although traditional Framingham risk factors for CVD are more prevalent in patients with CKD than in the general population, these risk factors do not fully account for the accelerated progression of CVD in CKD patients.2.Longenecker J.C. Coresh J. Powe N.R. et al.Traditional cardiovascular disease risk factors in dialysis patients compared with the general population: the CHOICE Study.J Am Soc Nephrol. 2002; 13: 1918-1927Crossref PubMed Scopus (529) Google Scholar Therefore, many recent studies have focused on the novel risk factors such as malnutrition, inflammation, and volume overload in the CKD population. Volume overload is related to CVD3.Demirci M.S. Demirci C. Ozdogan O. et al.Relations between malnutrition-inflammation-atherosclerosis and volume status. The usefulness of bioimpedance analysis in peritoneal dialysis patients.Nephrol Dial Transplant. 2011; 26: 1708-1716Crossref PubMed Scopus (102) Google Scholar,4.Wang A.Y. Lam C.W. Yu C.M. et al.N-terminal pro-brain natriuretic peptide: an independent risk predictor of cardiovascular congestion, mortality, and adverse cardiovascular outcomes in chronic peritoneal dialysis patients.J Am Soc Nephrol. 2007; 18: 321-330Crossref PubMed Scopus (119) Google Scholar and is a predictor of outcome in hemodialysis and peritoneal dialysis patients.5.Kalantar-Zadeh K. Regidor D.L. Kovesdy C.P. et al.Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis.Circulation. 2009; 119: 671-679Crossref PubMed Scopus (401) Google Scholar,6.Agarwal R. Hypervolemia is associated with increased mortality among hemodialysis patients.Hypertension. 2010; 56: 512-517Crossref PubMed Scopus (111) Google Scholar Although a large body of experimental evidence on fluid status has been collected for dialysis patients, only a limited number of studies have been conducted in CKD patients not yet on dialysis.7.Bellizzi V. Scalfi L. Terracciano V. et al.Early changes in bioelectrical estimates of body composition in chronic kidney disease.J Am Soc Nephrol. 2006; 17: 1481-1487Crossref PubMed Scopus (95) Google Scholar Furthermore, the fluid status of predialysis CKD patients has not been characterized using a valid method. The prevalence of volume overload during the earlier stages of CKD is unclear and its significance has not been elucidated. The clinical assessment of fluid status is relatively difficult, because physical signs of edema are of limited value in diagnosing excess intravascular volume.8.Agarwal R. Andersen M.J. Pratt J.H. On the importance of pedal edema in hemodialysis patients.Clin J Am Soc Nephrol. 2008; 3: 153-158Crossref PubMed Scopus (105) Google Scholar Ultrasonic evaluation of the diameter of the inferior vena cava can be used to assess intravascular volume (preload) but not tissue hydration.9.Kraemer M. Rode C. Wizemann V. Detection limit of methods to assess fluid status changes in dialysis patients.Kidney Int. 2006; 69: 1609-1620Abstract Full Text Full Text PDF PubMed Scopus (115) Google Scholar Interpatient and interoperator variability and the presence of diastolic dysfunction or right-sided failure also limit the use of this technique.10.Jaeger J.Q. Mehta R.L. Assessment of dry weight in hemodialysis: an overview.J Am Soc Nephrol. 1999; 10: 392-403PubMed Google Scholar,11.Moreno F.L. Hagan A.D. Holmen J.R. et al.Evaluation of size and dynamics of the inferior vena cava as an index of right-sided cardiac function.Am J Cardiol. 1984; 53: 579-585Abstract Full Text PDF PubMed Scopus (250) Google Scholar Biomarkers such as brain natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (NT-proBNP) can reflect changes in the fluid status but are also influenced by CVD, and they can be accumulated in CKD patients.12.Wang A.Y. Lai K.N. Use of cardiac biomarkers in end-stage renal disease.J Am Soc Nephrol. 2008; 19: 1643-1652Crossref PubMed Scopus (152) Google Scholar The most direct and accurate method involves isotope dilution, but the use of this method is limited to the research environment. Bioimpedance spectroscopy is a simple and effective approach for the assessment of fluid status.13.Matthie J.R. Bioimpedance measurements of human body composition: critical analysis and outlook.Expert Rev Med Devices. 2008; 5: 239-261Crossref PubMed Scopus (129) Google Scholar,14.Jaffrin M.Y. Morel H. Body fluid volumes measurements by impedance: a review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods.Med Eng Phys. 2008; 30: 1257-1269Abstract Full Text Full Text PDF PubMed Scopus (318) Google Scholar The Body Composition Monitor (BCM, Fresenius Medical Care, Bad Homburg, Germany) is a bedside bioimpedance spectroscopy device for clinical use. The accuracy of fluid status and body composition measurements has been validated against available gold standard reference methods,15.Moissl U.M. Wabel P. Chamney P.W. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006; 27: 921-933Crossref PubMed Scopus (460) Google Scholar,16.Wabel P. Chamney P. Moissl U. et al.Importance of whole-body bioimpedance spectroscopy for the management of fluid balance.Blood Purif. 2009; 27: 75-80Crossref PubMed Scopus (258) Google Scholar and the device has been used to monitor patients receiving hemodialysis17.Wizemann V. Wabel P. Chamney P. et al.The mortality risk of overhydration in haemodialysis patients.Nephrol Dial Transplant. 2009; 24: 1574-1579Crossref PubMed Scopus (489) Google Scholar,18.Machek P. Jirka T. Moissl U. et al.Guided optimization of fluid status in haemodialysis patients.Nephrol Dial Transplant. 2010; 25: 538-544Crossref PubMed Scopus (175) Google Scholar or peritoneal dialysis.19.Devolder I. Verleysen A. Vijt D. et al.Body composition, hydration, and related parameters in hemodialysis versus peritoneal dialysis patients.Perit Dial Int. 2010; 30: 208-214Crossref PubMed Scopus (85) Google Scholar,20.Van Biesen W. Williams J.D. Covic A.C. on behalf of the EuroBCM study group et al.Fluid status in peritoneal dialysis patients: the European Body Composition Monitoring (EuroBCM) Study cohort.PLoS One. 2011; 6: e17148Crossref PubMed Scopus (196) Google Scholar We hypothesized that volume overload develops early during the course of CKD and may contribute significantly to the development of CVD.21.Pecoits-Filho R. Goncalves S. Barberato S.H. et al.Impact of residual renal function on volume status in chronic renal failure.Blood Purif. 2004; 22: 285-292Crossref PubMed Scopus (40) Google Scholar The primary objectives of this study were to determine the fluid status in a representative sample of CKD patients using the BCM device, and the measured fluid status was compared with that of an age- and sex-matched healthy cohort.22.Wieskotten S. Heinke S. Wabel P. et al.Bioimpedance-based identification of malnutrition using fuzzy logic.Physiol Meas. 2008; 29: 639-654Crossref PubMed Scopus (61) Google Scholar We also sought to identify CVD risk factors associated with volume overload. After the exclusion criteria were applied, 338 clinically stable patients (233 men and 105 women; mean age 65.7±13.5 years) were enrolled in the study. All patients had moderate-to-severe CKD (mean estimated glomerular filtration rate (eGFR) 28.7ml/minper1.73m2; 151 in stage 3, 108 in stage 4, and 79 in stage 5). In this population, 45.3% were diabetic (n=153) and 23.4% had CVD (n=79) (coronary artery disease (n=38), congestive heart failure (n=29), and/or cerebrovascular accident (n=25)). At least one type of antihypertensive drug was taken by 83.7% of the patients (calcium-channel blockers 51.2%, renin–angiotensin system (RAS) blockers 59.2%), with a mean of 2.0±1.4 drugs prescribed per patient. A total of 113 (33.4%) patients were receiving diuretic treatment. The baseline characteristics for the patient groups divided on the basis of the absence or presence of volume overload (defined as overhydration (OH)≥7%) are presented in Table 1. Overall, 52% (n=175) of the study population showed evidence of volume overload (Figure 1). The patients in the two groups were similar with regard to age, sex, and smoking history, but there were greater numbers of patients with diabetes mellitus (DM) and CVD in the volume overload group. The proportion of patients with volume overload receiving antihypertensive agents and diuretics was higher. Patients with volume overload were found to have a similar body mass index and fat tissue index but a significantly lower lean tissue index compared with patients without volume overload. In addition, there were important differences in the blood pressure (BP), arterial stiffness, routine biochemical parameters, and inflammatory markers between the groups. Patients with volume overload had significantly higher systolic BP, brachial-ankle pulse wave velocity (baPWV), extracellular water (ECW), ECW to total body water ratio (ECW/TBW), NT-proBNP, urine protein-to-creatinine ratio (UPCR), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) levels and significantly lower intracellular water (ICW), eGFR, serum albumin, and hemoglobin levels. The results of the analysis were similar when volume overload was defined as absolute OH≥1.1L (Supplementary Table S1 online).Table 1Comparisons of CKD patients with and without volume overload according to the OH valuesOHVariable<7% (n=163)≥7% (n=175)P-valueAge (years)65.0±14.266.4±12.80.324Male sex, n (%)111 (68.1%)122 (69.7%)0.748Smoking history, n (%)32 (19.6%)39 (22.3%)0.550DM, n (%)45 (27.6%)108 (61.7%)<0.001CVD, n (%)23 (14.1%)56 (32%)<0.001Hypertension, n (%)132 (81%)156 (89.1%)0.035Systolic BP (mmHg)133±15142±18<0.001baPWV (m/s)15.1±2.816.2±2.8<0.001Total number of antihypertensives1.8±1.42.3±1.30.001Diuretics, n (%)42 (25.8%)71 (40.6%)0.004RAS blockers, n (%)95 (58.3%)105 (60%)0.748Statin, n (%)37 (22.7%)50 (28.6%)0.217ECW (l)15.8±3.117.8±3.8<0.001ICW (l)19.6±4.618.4±4.40.017TBW (l35.4±7.536.2±8.00.367ECW/TBW (%)44.9±2.449.3±2.7<0.001Body mass index (kg/m2)25.7±4.126.1±4.30.455Lean tissue index (kg/m2)16.0±3.214.7±3.1<0.001Fat tissue index (kg/m2)9.5±4.410.0±4.30.285NT-proBNP (ng/l)112.0 (46.0–280.5)530.7 (177.4–1275.0)<0.001eGFR (ml/minper1.73 m2)31.5±14.826.1±14.70.001UPCR (g/g)0.49 (0.22–1.26)1.67 (0.62–4.19)<0.001Albumin (g/dl)3.8±0.33.4±0.4<0.001Fasting glucose (mg/dl)116±35124±450.73Total cholesterol (mg/dl)173±33177±460.35Triglyceride (mg/dl)164±117161±1090.803hs-CRP (mg/l)3.7 (1.6–8.4)4.4 (1.1–10.8)0.712IL-6 (pg/ml)2.87 (1.64–4.59)4.28 (2.62–8.33)<0.001TNF-a (pg/ml)5.63 (4.13–8.07)7.96 (5.37–10.34)<0.001Hemoglobin (g/dl)12.5±2.010.9±1.9<0.001Abbreviations: baPWV, brachial-ankle pulse wave velocity; BP, blood pressure; CKD, chronic kidney disease; CVD, cardiovascular disease; DM, diabetes mellitus; ECW, extracellular water; eGFR, estimated glomerular filtration rate; hs-CRP, high-sensitivity C-reactive protein; ICW, intracellular water; IL-6, interleukin-6; NT-proBNP, N-terminal pro-brain natriuretic peptide; OH, overhydration; RAS, renin–angiotensin system; TBW, total body water; TNF-α, tumor necrosis factor α; UPCR, urine protein-to-creatinine ratio. Open table in a new tab Download .doc (.06 MB) Help with doc files Supplementary Table S1 Abbreviations: baPWV, brachial-ankle pulse wave velocity; BP, blood pressure; CKD, chronic kidney disease; CVD, cardiovascular disease; DM, diabetes mellitus; ECW, extracellular water; eGFR, estimated glomerular filtration rate; hs-CRP, high-sensitivity C-reactive protein; ICW, intracellular water; IL-6, interleukin-6; NT-proBNP, N-terminal pro-brain natriuretic peptide; OH, overhydration; RAS, renin–angiotensin system; TBW, total body water; TNF-α, tumor necrosis factor α; UPCR, urine protein-to-creatinine ratio. Correlations between OH and other variables in the overall sample are presented in Figures 2, 3, 4. OH was positively and strongly correlated with ln NT-proBNP (r2=0.292; Figure 2). A number of patients had high ln NT-proBNP levels despite normohydration or even underhydration. These patients were most likely patients with CVD or worse kidney function. Figure 2a illustrates the linear regression of OH on ln NT-proBNP and reveals that, for each value of OH, patients with CVD had a higher ln NT-proBNP than patients without CVD. Similar results were observed for stages 4 and 5 CKD compared with stage 3 CKD (Figure 2b).Figure 3Factors associated with overhydration (OH). Univariate analysis of the correlations of OH with the (a) systolic blood pressure (BP), (b) brachial-ankle pulse wave velocity (baPWV), (c) ln urine protein-to-creatinine ratio (UPCR), and (d) estimated glomerular filtration rate (eGFR).View Large Image Figure ViewerDownload (PPT)Figure 4Malnutrition and inflammation associated with overhydration (OH). Univariate analysis of the correlations of OH with (a) ln interleukin-6 (IL-6), (b) ln tumor necrosis factor-α (TNF-α), (c) albumin, and (d) lean tissue index.View Large Image Figure ViewerDownload (PPT) OH also correlated positively with systolic BP (r2=0.097; Figure 3a), baPWV (r2=0.021; Figure 3b), and ln UPCR (r2=0.193; Figure 3c) and correlated negatively with the eGFR (r2=0.023; Figure 3d). With regard to malnutrition–inflammation complex syndrome in CKD patients, OH was positively correlated with ln IL-6 (r2=0.065; Figure 4a) and ln TNF-α (r2=0.113; Figure 4b) and was negatively correlated with serum albumin (r2=0.255; Figure 4c) and lean tissue index (r2=0.038; Figure 4d). No association was found with high-sensitivity C-reactive protein or the lipid profile. Multivariate regression analysis included OH as the dependent variable and several relevant demographic (age and sex), clinical (DM, CVD, systolic BP, and diuretic use), and laboratory factors (eGFR, ln UPCR, serum albumin, and ln TNF-α) that were previously identified in univariate analyses as independent variables. As shown in Table 2, the novel risk factors (serum albumin, ln TNF-α, and ln UPCR), as well as the traditional risk factors (DM, systolic BP, male sex, and pre-existing CVD), were independently associated with OH (adjusted R2 of the model=0.401).Table 2Stepwise multivariate linear regression model identifying determinants of OHVariableStandard errorBeta coefficienttP-valueAlbumin (g/dl)1.059-0.304-5.756<0.001DM0.8310.2134.429<0.001Systolic BP (mmHg)0.0230.1693.665<0.001Male sex0.8220.1563.5080.001ln TNF-a (pg/ml)0.6500.1142.3750.018ln UPCR (g/g)0.3570.1312.3460.020CVD0.9090.0942.1170.035Abbreviations: BP, blood pressure; CVD, cardiovascular disease; DM, diabetes mellitus; OH, overhydration; TNF-α, tumor necrosis factor α; UPCR, urine protein-to-creatinine ratio. Open table in a new tab Abbreviations: BP, blood pressure; CVD, cardiovascular disease; DM, diabetes mellitus; OH, overhydration; TNF-α, tumor necrosis factor α; UPCR, urine protein-to-creatinine ratio. To better distinguish individuals with evidence of MIA syndrome, a previously described composite variable combining the serum albumin level (<3.0g/dl), the IL-6 level (3.0pg/ml or higher), and CVD was used to categorize the study population into four subgroups: patients with none (MIA score=0), one (MIA score=1), two (MIA score=2), or three (MIA score=3) of these comorbid conditions.23.Liu Y. Coresh J. Eustace J.A. et al.Association between cholesterol level and mortality in dialysis patients: role of inflammation and malnutrition.JAMA. 2004; 291: 451-459Crossref PubMed Scopus (613) Google Scholar The presence of MIA has additive effects on the OH level (Figure 5). The means and s.ds. of OH in the four subgroups (none (n=110), one (n=150), two (n=70), three (n=8)) were 4.99±7.14, 8.09±7.96, 12.49±8.81, and 23.36±7.57% (P<0.001), respectively. As shown in Table 3, only OH was strongly associated with all of the components of MIA syndrome, whereas measures of kidney function (eGFR and UPCR) were not.Table 3Multivariate logistic regression model showing the associations of the eGFR, UPCR, and OH with malnutrition, inflammation, and atherosclerosis syndromeMalnutritionInflammationAtherosclerosisVariableAlbumin<3.0g/dlIL-6≥3.0pg/mlCVDeGFR (ml/minper1.73m2)1.014 (0.986, 1.043)P=0.3190.998 (0.982, 1.015)P=0.8240.972 (0.952, 0.992)P=0.006UPCR (g/g)2.456 (1.819, 3.316)P<0.0011.211 (1.035, 1.416)P=0.0170.994 (0.864, 1.143)P=0.929OH (%)1.121 (1.061, 1.184)P 15% or an excess of fluid of >2.5l). The study by Wizemann et al.,17.Wizemann V. Wabel P. Chamney P. et al.The mortality risk of overhydration in haemodialysis patients.Nephrol Dial Transplant. 2009; 24: 1574-1579Crossref PubMed Scopus (489) Google Scholar which included 269 chronic hemodialysis patients, showed that this degree of OH is an independent predictor of mortality, second only to the presence of DM. In the present study, OH was associated with important risk factors, including male sex, diabetes, pre-existing CVD, systolic BP, serum albumin, TNF-α, and proteinuria, suggesting an explanation for the increased risk. Volume overload has been recognized as an important contributor to an adverse prognosis and an effect modifier in CKD patients.24.Hung S.C. Lin Y.P. Huang H.L. et al.Aldosterone and mortality in hemodialysis patients: role of volume overload.PLoS One. 2013; 8: e57511Crossref PubMed Scopus (24) Google Scholar However, it is not known whether a biomarker can identify this complication in CKD patients, thus allowing earlier intervention to improve fluid control. BNP is a peptide hormone released primarily from the cardiac ventricles in response to increased left ventricular wall stress. There is ample evidence that the elevation of NT-pro-BNP may partly reflect volume overload in addition to being a biomarker of ventricular dysfunction related to background CVD.25.Mak G.S. DeMaria A. Clopton P. et al.Utility of B-natriuretic peptide in the evaluation of left ventricular diastolic function: comparison with tissue Doppler imaging recordings.Am Heart J. 2004; 148: 895-902Abstract Full Text Full Text PDF PubMed Scopus (109) Google Scholar Nevertheless, its diagnostic value has been considered to be limited in CKD patients because renal dysfunction itself may affect BNP levels, and the interpretation of its clinical significance should take renal status into consideration.26.Takami Y. Horio T. Iwashima Y. et al.Diagnostic and prognostic value of plasma brain natriuretic peptide in non-dialysis-dependent CRF.Am J Kidney Dis. 2004; 44: 420-428Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar We found that, although there was a strong association between NT-proBNP and OH, the values for a number of patients did not comply with this correlation. In our study, patients with CVD had significantly higher NT-pro-BNP levels than patients without CVD at the same degree of OH (Figure 2a). Similarly, patients with stages 4 and 5 CKD had significantly higher NT-pro-BNP levels than patients with stage 3 CKD at the same degree of OH (Figure 2b). The differential diagnosis of volume overload or congestive heart failure among CKD patients is often not clinically straightforward. Determining the optimal cutoff values for NT-pro-BNP, adjusted for the eGFR, for the detection of CVD across various OH levels in CKD patients requires further investigations. In CKD patients, reduced glomerular filtration of sodium, activation of the RAS, and superimposed CVD lead to sodium and water retention. Volume expansion is a major cause of hypertension in CKD patients, and nearly all CKD patients are hypertensive upon the initiation of dialysis.27.Collins A.J. Foley R.N. Herzog C. et al.United States Renal Data System 2008 Annual Data Report.Am J Kidney Dis. 2009; 53: S1-S374Abstract Full Text Full Text PDF PubMed Scopus (15) Google Scholar Hypertension causes ventricular hypertrophy and increased arterial stiffness, both of which are associated with a higher mortality among CKD patients. Nevertheless, there might be effects beyond traditional risk factors that link fluid retention to cardiovascular death. Previous studies have demonstrated that CKD is not merely an independent risk factor for CVD but is also associated with increased levels of inflammatory biomarkers. In our study, there was a strong association between malnutrition–inflammation complex syndrome and volume overload. However, it is impossible to determine whether malnutrition–inflammation complex syndrome is a consequence or cause of volume overload. Thus, our data may be viewed as hypothesis-generating data. We found that the TNF-α level was elevated in CKD patients with volume overload. Interestingly, previous studies have shown that the TNF-α level was also elevated in patients with congestive heart failure and that there is a direct relationship between the level of TNF-α and the severity of disease.28.Torre-Amione G. Kapadia S. Benedict C. et al.Proinflammatory cytokine levels in patients with depressed left ventricular ejection fraction. a report from the Studies of Left Ventricular Dysfunction (SOLVD).J Am Coll Cardiol. 1996; 27: 1201-1206Abstract Full Text PDF PubMed Scopus (1078) Google Scholar Patients with CKD have similarities to heart failure patients in that both populations frequently retain fluid and have excessively high CVD mortality. The mechanisms by which fluid retention influences cardiovascular survival in CKD patients may be similar to those in congestive heart failure patients.5.Kalantar-Zadeh K. Regidor D.L. Kovesdy C.P. et al.Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis.Circulation. 2009; 119: 671-679Crossref PubMed Scopus (401) Google Scholar It has been previously shown that TNF-α mRNA and protein are rapidly expressed in the hearts of animal models subjected to significant volume overload.29.Kapadia S.R. Oral H. Lee J. et al.Hemodynamic regulation of tumor necrosis factor-alpha gene and protein expression in adult feline myocardium.Circ Res. 1997; 81: 187-195Crossref PubMed Scopus (262) Google Scholar Moreover, both basic and clinical studies strongly support the hypothesis that the myocardial expression of TNF-α is an important step in the pathophysiological pathway leading to progressive cardiac dilatation and failure.30.Feldman A.M. Combes A. Wagner D. et al.The role of tumor necrosis factor in the pathophysiology of heart failure.J Am Coll Cardiol. 2000; 35: 537-544Abstract Full Text Full Text PDF PubMed Scopus (427) Google Scholar Inflammation is a pivotal process in the progression of atherosclerosis. Our data are consistent with previous experimental observations that volume overload is a process that involves immune activation. In our study cohort, the use of diuretic agents was associated with volume overload. We believe this observation is hampered by ‘bias by indication’, and thus the prevalence of volume overload among CKD patients may be even higher. Another interesting finding was that male gender was an independent predictor for OH, corroborating previous findings.31.Wabel P. Moissl U. Chamney P. et al.Towards improved cardiovascular management: the necessity of combining blood pressure and fluid overload.Nephrol Dial Transplant. 2008; 23: 2965-2971Crossref PubMed Scopus (235) Google Scholar It is not clear from this study whether this is related to lower compliance to fluid restriction in male patients or to other factors. In the present study, OH had a strong and positive association with proteinuria. In contrast, there was only a modest inverse association with the GFR, and this association disappeared in the multivariate analysis. This finding suggests that kidney dysfunction may be associated with fluid retention only when proteinur
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