- Email: [email protected]
Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis
G Model
NEPHRO-821; No. of Pages 4 Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx
Available online at
ScienceDirect www.sciencedirect.com
Original article
Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis ¨ zpelit a, Nihat Pekel a Akar Yilmaz a,*, Banu Yilmaz b, Selc¸uk Ku¨c¸u¨kseymen c, Emre O a
Izmir University, Faculty of Medicine, Department of Cardiology, Izmir, Turkey Tepecik Training and Research Hospital, Clinic of Nephrology, Izmir, Turkey c Antalya Training and Research Hospital, Clinic of Cardiology, Izmir, Turkey b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 4 June 2015 Accepted 1st August 2015
Background/Aim. – Fluid overload and cardiac dysfunction is well established in hemodialysis patients. But in predialysis chronic kidney disease, the association of fluid overload and cardiac dysfunction is relatively unknown. In this study, we aimed to investigate the relationship between fluid overload and cardiac dysfunction in predialysis chronic kidney disease patients. Method. – We enrolled 107 consecutive patients in our study. Fluid overload was assessed via body composition monitor. Patients were dichotomized according to the fluid overload status. The patients with FO < 1.1 L were determined as normovolemic and those with FO 1.1 L as hypervolemic according to the previously reported physiologic model. Left atrial volume index (LAVI), left ventricular enddiastolic–end-systolic index (LVEDVI, LVESVI), E/e’, LVMI and global longitudinal left ventricular left ventricular strain (GLS-%) were evaluated in each patient as markers of cardiac dysfunction. Arterial stiffness was also assessed by Mobil-O-Graph1 24 h pulse wave analysis monitor and pWV values were recorded. Results. – Fifty-five patients were normovolemic and 52 patients were hypervolemic. LAVI, LVMI, LDEDVI, LVEDSVI, E/e’ were increased in hypervolemic patients. Also in hypervolemic patients pulse wave velocity was increased and GLS was decreased. Multivariate analysis showed that FO was independently associated with GLS which is the most specific echo-parameter for left ventricular dysfunction. Conclusion. – FO was independently associated with cardiac dysfunction in patients with chronic kidney disease not ongoing dialysis. Effective treatment of hypervolemia may be important in these patients to avoid further cardiac damage. ß 2015 Association Socie´te´ de ne´phrologie. Published by Elsevier Masson SAS. All rights reserved.
Keywords: Arterial stiffness Chronic kidney disease Fluid overload Global left ventricular strain Pulse wave velocity
1. Introduction Hypervolemia/volume overload, apart from hypertension, age and atherosclerosis, may be another cause of cardiac injury in patients with chronic kidney failure [1]. Volume overload increases circulating volume, venous return and filling pressures. The result is myocardial systolic and diastolic stress. The effect of volume overload on systolic and diastolic functions of left ventricle had been investigated through several echocardiographic parameters. The effect of FO on mitral inflow and pulmonary vein Doppler velocities had also been proven in previous studies [2]. Some other
* Corresponding author. E-mail address: [email protected] (A. Yilmaz).
studies demonstrated the association between FO and left ventricular mass and also pulse wave velocity [3]. However, up to now there is no study investigating the association between FO and myocardial strain. In general, parameters of myocardial strain have been used to detect subclinical myocardial disease [4]. The myocardial involvement in cardiorenal syndrome and its association with fluid overload had never been studied in terms of myocardial strain before. In patients with chronic kidney failure, mortality is correlated with the left ventricular mass index (LVMI) [5]. Quantification of fluid overload and its optimal management through bioimpedance method may reduce left ventricular hypertrophy and so the mortality in chronic kidney disease patients [6]. The aim of our study was to investigate the association between global left ventricular longitudinal strain (GLS) (a parameter which while showing subtle systolic dysfunction is independent from the
http://dx.doi.org/10.1016/j.nephro.2015.08.003 1769-7255/ß 2015 Association Socie´te´ de ne´phrologie. Published by Elsevier Masson SAS. All rights reserved.
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
G Model
NEPHRO-821; No. of Pages 4 A. Yilmaz et al. / Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx
2
parameters showing diastolic dysfunction) and FO in patients with chronic kidney failure (eGFR < 60 mL/min/1.73 m2) who weren’t undergoing dialysis.
2. Methods 2.1. Patient selection This observational study was conducted at Antalya education and research hospital. This study was approved by the Institutional review board at Antalya education and research hospital. Exclusion criteria were as follows: any diagnosed acute or chronic inflammatory state within 3 months, hospitalization related dialysis within 3 months, diseases that produce local fluid accumulation and edema, active malignancy, currently taking diuretics, currently taking any medication with the potential to influence body composition, malnutrition, pregnancy, insertion of a cardiac pacemaker or defibrillator, or the amputation of any extremity. All of the patients provided informed consent. eGFR was calculated using the 4-variable MDRD Study equation [7]. 2.2. Body composition and fluid overload analysis A body composition monitor (BCM) (Fresenius Medical Care, Bad Homburg, Germany) was used to determine the extracellular and total body water. FO was calculated using a physiological BCM model that is based on tissue properties [8]. In the light of the physiological data reported by Moissl et al., 1.1 L was accepted as cut-off value for FO [9]. The BCM measures the impedance spectroscopy at 50 different frequencies between 5 kHz and 1 MHz. Electrodes were attached to one hand and one foot at the ipsilateral side, after the patient had been in recumbent position for at least 5 minutes. For determination of weight, we used the weight measured in morning and in fasting state. FO were determined from the measured impedance data following the model of Moissl et al. [9]. 2.3. Assessment of pulse wave velocity Mobil-O-Graph1 24 hour pulse wave analysis monitor (I.E.M. Industrielle Entwicklung Medizintechnik und Vertriebsgesellschaft mbH Cockerillstraße Stolberg (Rheinland), Germany) was used for the measurements of arterial stiffness and central blood pressure analysis [10]. Built-in combining algorithms in the device were used for central aortic and brachial blood pressure measurements and PWV analysis. Assessment of pulsatile hemodynamics: PWV was determined as a measure of arterial stiffness. Also central blood pressure data were obtained with pulse wave analysis monitor. 2.4. Echocardiography Echocardiography was performed with synchronized electrocardiography with a commercially available system (Philips iE33, Bothell, WA, USA) equipped with a broadband S5-1 transducer The Automated Function Imaging algorithm allowed GLS. Ts-SD was automatically calculated by echo system from longitudinal strain using time-to peak variation, defined as the standard-deviation of time-to-peak over all 17 segments. LVMI was calculated, according to the method of Devereux [11]. LAVI was calculated by automatic algorithm based on the modified Simpson’s method built on the device [12]. LVEDVI and LVESVI along with the LVEF were calculated by the biplane Simpson’s method from apical 4-chamber views Tissue Doppler-derived early (e’), and early diastolic (E) velocities were derived from the septal mitral annulus.
2.5. Statistical analysis Data were analyzed utilizing the SPSS software version 17.0 for Windows (SPSS Inc., Chicago, IL, USA). Whether the data is normal distribution or not, were analyzed with Kolmogorow Smirnov and Shapiro Wilk test. Data with normal distribution were presented as mean SD, non-normally distributed data were presented as median [max–min]. Continuous variables without normal distribution were analyzed using Mann-Whitney U test. Normal distribution data were compared by Student t test. In the analysis of categorical data, chisquare and Fisher’s exact tests were used. The association pf different variables with FO and GLS were calculated by univariate analysis for each. The variables for which the unadjusted P value was <0.05 in univariate analysis were included in the multivariable Cox regression model. A p value <0.05 was considered to be statistically significant.
3. Results By using 1.1 as a cut-off point, the patients were divided in two groups according to their FO state [9]. In the overhydrated group albumin and hemoglobin values were significantly lower (respectively P = 0.03 and P = 0.01). Diabetes (DM) were more frequent (31% vs. 18%; P = 0.05) in the overhydrated group and the central systolic blood pressure (P = 0.008) and pulse wave velocity (P = 0.02) were also significantly higher in this group. There was no significant difference between the groups in respect of the medications they were using (Table 1). When assessed in combination with data form conventional echocardiography, GLS (P < 0.001), was significantly lower whereas ts-SD (P = 0.007) and LVMI (P < 0.001) values were significantly higher in the overhydrated group. The values of LVEDVI (P = 0.02), LVESVI (P = 0.09), E/e’ (P = 0.02) and LAVI (P = 0.001) were also found to be higher in the overhydrated group. There was no significant difference between the groups in respect of EF (Table 2). In the univariate analysis, a relationship was found between fluid overload and DM (b = 3.157; 95% CI [1.395–7.496]; P = 0.06), PWv (b = 1.309; 95% CI [1.050–1.631]; P = 0.016), systolic blood pressure (b = 1.027; 95% CI [1.007–1.047]; P = 0.07), pulse pressure (b = 1.036; 95% CI [1.009–1.063]; P = 0.008), mean arterial pressure (b = 1.034; 95% CI [1.006–1.064]; P = 0.018), central systolic blood pressure (b = 1.037; 95% CI [1.007–1.0053]; P = 0.011), serum albumin levels (b = 0.245; 95% CI [0.065–0.925]; P = 0.038) and hemoglobin levels (b = 0.720; 95% CI [0.555–0.935]; P = 0.014). However, no relation was detected between FO and age, gender, parathormone (PTH) levels and eGFR. Multivariate logistic regression analysis showed an independent association between overhydration and DM (b = 1.221; 95% CI [1.268–9.064]; P = 0.015] and also hemoglobin levels (b = 0.472; 95% CI [0.442–0.879]). During the echocardiographic analysis, the GLS values were found to be lower in the overhydrated group while the EDVI, ESVI, ts-SD, LVMI, LAVI and E/e’ values were found to be higher (Table 2). A univariate regression analysis was performed between the GLS and clinical and laboratory parameters. According this analysis FO, diabetes, age, gender, PWv and PTH were found to be significantly associated with GLS. However eGFR, blood pressure and hemoglobin levels were not associated with GLS. On multivariate analysis FO and PTH levels were found as the independent associates of GLS (Table 3 and Fig. 1).
4. Discussion In patients who do not undergo dialysis, a decrease in GFR is associated with an increase in cardiovascular events [13]. As the majority of these patients have severe cardiac risk factors such as
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
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NEPHRO-821; No. of Pages 4 A. Yilmaz et al. / Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx Table 1 Baseline demographic data.
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Table 2 Comparison of echocardiographic variables.
Age (years) eGFR (mL/min/1.73 m2) Gender (n = male) Diabetes mellitus (n) Blood urea nitrogen (mg/dL) Sodium (mmol/L) Potassium (mmol/L) Uric acid (mg/dL) Total protein (g/dL) Albumin (g/dL) Parathormone (pg/mL) Spot urine micro total protein/Cr Hemoglobin (g/dL) Systolic Blood Pressure (BP) (mmHg) Diastolic BP (mmHg) Central systolic BP (mmHg) Central diastolic BP (mmHg) Pwv (m/s) Medications Furosemide (n) Aspirin for CAD (n) Vitamin D replacement (n) Erythropoietin replacement (n) Alpha blocker (n) Thiazide (n) ACE-I/ARB (n) Beta-blocker (n)
Normohydrated (FO < 1.1 L)
Overhydrated (FO > 1.1 L)
P
N = 55
N = 52
58.6 13.9 28.1 11.5 33 18 39.8 17.0
62.3 11.0 26.2 10.1 37 31 42.6 14.3
Ns Ns Ns 0.05 Ns
138.6 2.5 4.7 0.4 7.1 1.5 7.1 0.9 4.0 0.2 99 [44–382] 1.6 2.2
139.3 2.0 5.0 0.5 6.7 1.2 7.1 0.7 3.9 0.2 110 [42–570] 2.2 2.3
Ns 0.09 Ns Ns 0.03 Ns Ns
12.2 1.6 133.4 14.8
11.6 1.3 145.0 11.8
0.01 0.005
84.8 14.2 119.3 22.8
87.1 10.1 130.4 18.2
Ns 0.008
86.1 12.8
88.5 10.4
Ns
8.6 1.7
9.5 1.9
0.02
– 9 33 11 9 16 33 22
4 7 27 14 8 20 30 18
Ns Ns Ns Ns Ns Ns Ns Ns
GLS LVMI Ts-SD EF EDVI ESVI LAVI E/e’
FO < 1.1 L
FO 1.1 L
P
18 [15–23] 103.6 26.0 53 [6–120] 70.9 6.7 53.7 15.5 15.0 5.3 28.2 8.0 8.1 3.9
16.5 [10–20] 126.7 27.7 62.5 [14–190] 69.8 7.4 60.5 10.1 18.0 7.0 35.7 11.7 10.4 4.3
< 0.001 < 0.001 0.007 Ns 0.02 0.09 0.001 0.02
undergone dialysis in the past, the data acquired can difficultly be compared to the data of our study. In our study, despite detecting a significant difference between the groups with regard to pulse wave velocity, the multivariate model could not prove the independent relation between fluid overload and pulse wave velocity. This situation may be due to the low number of patients enrolled in our study. In a study, Goto et al. have reported that secondary hyperparathyroidism was associated with cardiac dysfunction in chronic kidney disease [16]. However there are only a limited number of studies investigating the cardiac effects of hyperparathyroidism in patients who do not undergo dialysis. On the other hand compared the effect of alfacalcidol versus no treatment in patients with CKD stage 4, in the alfacalcidol-treated patients LV systolic function (shortening fraction) significantly increased, while PTH decreased by 72% [17]. In another study, despite lowering the PTH levels with paricalcitol replacement, a decrease in LVMI, EDVI, ESVI and E/e’ could not be obtained [18]. All of these parameters are afterload-dependent and they may be influenced by many factors (such as hypervolemic status) in patients who undergo hemodialysis. Our study detected an independent association between GLS and PTH levels. However, further studies with sensitive cardiac imaging techniques are needed to determine the independent effects of hyperparathyroidism on cardiac functions. Previous studies have shown that hypertensive patients with left ventricular hypertrophy have decreased myocardial strain levels [19]. Therefore, factors like hypertension, increased pulse pressure and an increased pulse wave velocity (as an indicator of an increased aortic stiffness), which would somehow increase the afterload, may cause lower myocardial strain values. Left ventricular hypertrophy due to a cardiorenal-syndrome-related-hypervolemia may also reduce myocardial strain, however this issue has not yet fully been discussed. Our study could not demonstrate a relationship between FO and age, PWv, diabetes and PTH levels. When focusing on the GLS, multivariate analysis showed that only the PTH levels and fluid overload were independently associated with GLS values. To our knowledge, this study is the first that reports the association between fluid overload and GLS.
ACE-I: angiotensin converting enzyme inhibitor; ARB: angiotensin receptor blocker.
DM and HT, this increase in CV events may also be due to cardiac complications of DM and HT. In patients undergoing hemodialysis, the effects of hypervolemia on cardiac parameters are well known. However, there are limited number of studies focusing on cardiac findings in patients who do not undergo hemodialysis. Essig et al. demonstrated that hypervolemia was associated with an increase in arterial stiffness, carotid intima media thickness and with echocardiographic diastolic dysfunction parameters in patients on an early stage of chronic kidney failure [14]. The association of hypervolemia with diastolic dysfunction, left ventricular hypertrophy and arterial hypertension are well known. These factors are all associated with a decrease in global left ventricular strain values. Pirat et al. compared the strain values of patients with end-stage renal disease and a control group and found lower values in the patients group [15]. Because the patients in that study had already
Table 3 GLS and its relations. Univariate analysis
Gender (male) Age DM PWv PTH FO
Multivariate analysis
b
95% CI
P
1.354 0.042 1.082 0.330 0.006 0.661
0.298; 2.411 0.082; 0.021 2.164; 0.012 0.607; 0.053 0.012; 0.001 0.996; 0.326
0.011 0.04 0.05 0.020 0.020 < 0.001
b
95% CI
0.007 0.517
0.013; 0.916;
P
0.002 0.119
0.011 0.012
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
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NEPHRO-821; No. of Pages 4 A. Yilmaz et al. / Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx
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Fig. 1. Relationship between GLS (-%) and FO.
5. Limitations Our study was a sectional one and the number on patients included was relatively small. Cardiac functions were not reevaluated after volume balance was medically treated. Therefore, the relation between fluid overload and GLS cannot be seen as a cause-and-effect relationship. However, it can be deduced that a decrease in GLS values might be an early warning of a positive fluid balance onset. 6. Conclusion In patients with predialysis chronic kidney disease whom providing fluid balance endogenously, there is an independent relationship between GLS and FO regardless of age, gender, diabetes and arterial stiffness. Disclosure of interest The authors declare that they have no competing interest. References [1] Kalantar-Zadeh K, Regidor DL, Kovesdy CP, Van Wyck D, Bunnapradist S, Horwich TB, et al. Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis. Circulation 2009;119:671–9. [2] Chih CW, Yao PL, Wen CY, Lee WS, Hsu TL, Ding PY, et al. The assessment of fluid status in haemodialysis patients: usefulness of the Doppler echocardiographic parameters. Nephrol Dial Transplant 2004;19:644–51. [3] Kocyigit I, Sipahioglu MH, Orscelik O, Unal A, Celik A, Abbas SR, et al. The association between arterial stiffness and fluid status in peritoneal dialysis patients. Perit Dial Int 2014;34:781–90. [4] Marwick TH. Measurement of strain and strain rate by echocardiography: ready for prime time? J Am Coll Cardiol 2006;47:1313–27. [5] Hur E, Usta M, Toz H, Asci G, Wabel P, Kahvecioglu S, et al. Effect of fluid management guided by bioimpedance spectroscopy on cardiovascular parameters in hemodialysis patients: a randomized controlled trial. Am J Kidney Dis 2013;61:957–65. [6] Stack AG, Saran R. Clinical correlates and mortality impact of left ventricular hypertrophy among new ESRD patients in the United States. Am J Kidney Dis 2002;40:1202–10.
[7] Levey AS, Bosch JP, Lewis JB, Green T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Inter Med 1999;130:461–70. [8] Chamney PW, Wabel P, Moissl UM, Mu¨ller MJ, Bosy-Westhpal A, Korth O, et al. A whole-body model to distinguish excess fluid from the hydration of major body tissues. Am J Clin Nutr 2007;85:80–9. [9] Moissl UM, Wabel P, Chamney PW, Bosaeus I, Levin NW, Bosy-Westphal A, et al. Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Meas 2006;27:921–33. [10] Feistritzer HJ, Reinstadler SJ, Klug G, Kremser C, Seidner B, Esterhammer R, et al. Comparison of an oscillometric method with cardiac magnetic resonance for the analysis of aortic pulse wavevelocity. PLoS One 2015;22(10): e0116862. [11] Devereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol 1986;57:450–8. [12] Lang RM, Bierig M, Devereux RB, Flachskampf FA, Foster E, Pelikka PA, et al. Recommendations for chamber quantification: a report from the American Society of Echocardiography’s guidelines and standards committee and the chamber quantification writing group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr 2005;12:1440–63. [13] Anavekar NS, McMurray JJ, Velazquez EJ, Solomon SD, Kober L, Rouleau JL, et al. Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction. N Engl J Med 2004;351:1285–95. [14] Essig M, Escoubet B, Zuttere D, Blanchet F, Arnoult F, Dupuis E, et al. Cardiovascular remodelling and extracellular fluid excess in early stages of chronic kidney disease. Nephrol Dial Transplant 2008;23:239–48. [15] Pirat B, Bozbas H, Simsek V, Sade LE, Sayin B, Mu¨derrisog˘lu H, et al. Assessment of myocardial mechanics in patients with end-stage renal disease and renal transplant recipients using speckle tracking echocardiography. Exp Clin Transplant 2015;13(Suppl 1):235–41. [16] Goto N, Tominaga Y, Matsuoka S, Sato T, Katayama A, Haba T, et al. Cardiovascular complications caused by advanced secondary hyperparathyroidism in chronic dialysis patients; special focus on dilated cardiomyopathy. Clin Exp Nephrol 2005;9:138–41. [17] Ivarsen P, Povlsen JV, Christensen KL. Effect of alfacalcidol on cardiac function in patients with chronic kidney disease stage 4 and secondary hyperparathyroidism: a pilot study. Scand J Urol Nephrol 2012;46:381–8. [18] Wang AY, Fang F, Chan J, Wen YY, Qing S, Chan IH, et al. Effect of paricalcitol on left ventricular mass and function in CKD–the OPERA trial. J Am Soc Nephrol 2014;25:175–86. [19] Mizuguchi Y, Oishi Y, Miyoshi H, Iuchi A, Nagase N, Oki T. Concentric left ventricular hypertrophy brings deterioration of systolic longitudinal, circumferential, and radial myocardial deformation in hypertensive patients with preserved left ventricular pump function. J Cardiol 2010; 55:23–33.
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
NEPHRO-821; No. of Pages 4 Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx
Available online at
ScienceDirect www.sciencedirect.com
Original article
Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis ¨ zpelit a, Nihat Pekel a Akar Yilmaz a,*, Banu Yilmaz b, Selc¸uk Ku¨c¸u¨kseymen c, Emre O a
Izmir University, Faculty of Medicine, Department of Cardiology, Izmir, Turkey Tepecik Training and Research Hospital, Clinic of Nephrology, Izmir, Turkey c Antalya Training and Research Hospital, Clinic of Cardiology, Izmir, Turkey b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 4 June 2015 Accepted 1st August 2015
Background/Aim. – Fluid overload and cardiac dysfunction is well established in hemodialysis patients. But in predialysis chronic kidney disease, the association of fluid overload and cardiac dysfunction is relatively unknown. In this study, we aimed to investigate the relationship between fluid overload and cardiac dysfunction in predialysis chronic kidney disease patients. Method. – We enrolled 107 consecutive patients in our study. Fluid overload was assessed via body composition monitor. Patients were dichotomized according to the fluid overload status. The patients with FO < 1.1 L were determined as normovolemic and those with FO 1.1 L as hypervolemic according to the previously reported physiologic model. Left atrial volume index (LAVI), left ventricular enddiastolic–end-systolic index (LVEDVI, LVESVI), E/e’, LVMI and global longitudinal left ventricular left ventricular strain (GLS-%) were evaluated in each patient as markers of cardiac dysfunction. Arterial stiffness was also assessed by Mobil-O-Graph1 24 h pulse wave analysis monitor and pWV values were recorded. Results. – Fifty-five patients were normovolemic and 52 patients were hypervolemic. LAVI, LVMI, LDEDVI, LVEDSVI, E/e’ were increased in hypervolemic patients. Also in hypervolemic patients pulse wave velocity was increased and GLS was decreased. Multivariate analysis showed that FO was independently associated with GLS which is the most specific echo-parameter for left ventricular dysfunction. Conclusion. – FO was independently associated with cardiac dysfunction in patients with chronic kidney disease not ongoing dialysis. Effective treatment of hypervolemia may be important in these patients to avoid further cardiac damage. ß 2015 Association Socie´te´ de ne´phrologie. Published by Elsevier Masson SAS. All rights reserved.
Keywords: Arterial stiffness Chronic kidney disease Fluid overload Global left ventricular strain Pulse wave velocity
1. Introduction Hypervolemia/volume overload, apart from hypertension, age and atherosclerosis, may be another cause of cardiac injury in patients with chronic kidney failure [1]. Volume overload increases circulating volume, venous return and filling pressures. The result is myocardial systolic and diastolic stress. The effect of volume overload on systolic and diastolic functions of left ventricle had been investigated through several echocardiographic parameters. The effect of FO on mitral inflow and pulmonary vein Doppler velocities had also been proven in previous studies [2]. Some other
* Corresponding author. E-mail address: [email protected] (A. Yilmaz).
studies demonstrated the association between FO and left ventricular mass and also pulse wave velocity [3]. However, up to now there is no study investigating the association between FO and myocardial strain. In general, parameters of myocardial strain have been used to detect subclinical myocardial disease [4]. The myocardial involvement in cardiorenal syndrome and its association with fluid overload had never been studied in terms of myocardial strain before. In patients with chronic kidney failure, mortality is correlated with the left ventricular mass index (LVMI) [5]. Quantification of fluid overload and its optimal management through bioimpedance method may reduce left ventricular hypertrophy and so the mortality in chronic kidney disease patients [6]. The aim of our study was to investigate the association between global left ventricular longitudinal strain (GLS) (a parameter which while showing subtle systolic dysfunction is independent from the
http://dx.doi.org/10.1016/j.nephro.2015.08.003 1769-7255/ß 2015 Association Socie´te´ de ne´phrologie. Published by Elsevier Masson SAS. All rights reserved.
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
G Model
NEPHRO-821; No. of Pages 4 A. Yilmaz et al. / Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx
2
parameters showing diastolic dysfunction) and FO in patients with chronic kidney failure (eGFR < 60 mL/min/1.73 m2) who weren’t undergoing dialysis.
2. Methods 2.1. Patient selection This observational study was conducted at Antalya education and research hospital. This study was approved by the Institutional review board at Antalya education and research hospital. Exclusion criteria were as follows: any diagnosed acute or chronic inflammatory state within 3 months, hospitalization related dialysis within 3 months, diseases that produce local fluid accumulation and edema, active malignancy, currently taking diuretics, currently taking any medication with the potential to influence body composition, malnutrition, pregnancy, insertion of a cardiac pacemaker or defibrillator, or the amputation of any extremity. All of the patients provided informed consent. eGFR was calculated using the 4-variable MDRD Study equation [7]. 2.2. Body composition and fluid overload analysis A body composition monitor (BCM) (Fresenius Medical Care, Bad Homburg, Germany) was used to determine the extracellular and total body water. FO was calculated using a physiological BCM model that is based on tissue properties [8]. In the light of the physiological data reported by Moissl et al., 1.1 L was accepted as cut-off value for FO [9]. The BCM measures the impedance spectroscopy at 50 different frequencies between 5 kHz and 1 MHz. Electrodes were attached to one hand and one foot at the ipsilateral side, after the patient had been in recumbent position for at least 5 minutes. For determination of weight, we used the weight measured in morning and in fasting state. FO were determined from the measured impedance data following the model of Moissl et al. [9]. 2.3. Assessment of pulse wave velocity Mobil-O-Graph1 24 hour pulse wave analysis monitor (I.E.M. Industrielle Entwicklung Medizintechnik und Vertriebsgesellschaft mbH Cockerillstraße Stolberg (Rheinland), Germany) was used for the measurements of arterial stiffness and central blood pressure analysis [10]. Built-in combining algorithms in the device were used for central aortic and brachial blood pressure measurements and PWV analysis. Assessment of pulsatile hemodynamics: PWV was determined as a measure of arterial stiffness. Also central blood pressure data were obtained with pulse wave analysis monitor. 2.4. Echocardiography Echocardiography was performed with synchronized electrocardiography with a commercially available system (Philips iE33, Bothell, WA, USA) equipped with a broadband S5-1 transducer The Automated Function Imaging algorithm allowed GLS. Ts-SD was automatically calculated by echo system from longitudinal strain using time-to peak variation, defined as the standard-deviation of time-to-peak over all 17 segments. LVMI was calculated, according to the method of Devereux [11]. LAVI was calculated by automatic algorithm based on the modified Simpson’s method built on the device [12]. LVEDVI and LVESVI along with the LVEF were calculated by the biplane Simpson’s method from apical 4-chamber views Tissue Doppler-derived early (e’), and early diastolic (E) velocities were derived from the septal mitral annulus.
2.5. Statistical analysis Data were analyzed utilizing the SPSS software version 17.0 for Windows (SPSS Inc., Chicago, IL, USA). Whether the data is normal distribution or not, were analyzed with Kolmogorow Smirnov and Shapiro Wilk test. Data with normal distribution were presented as mean SD, non-normally distributed data were presented as median [max–min]. Continuous variables without normal distribution were analyzed using Mann-Whitney U test. Normal distribution data were compared by Student t test. In the analysis of categorical data, chisquare and Fisher’s exact tests were used. The association pf different variables with FO and GLS were calculated by univariate analysis for each. The variables for which the unadjusted P value was <0.05 in univariate analysis were included in the multivariable Cox regression model. A p value <0.05 was considered to be statistically significant.
3. Results By using 1.1 as a cut-off point, the patients were divided in two groups according to their FO state [9]. In the overhydrated group albumin and hemoglobin values were significantly lower (respectively P = 0.03 and P = 0.01). Diabetes (DM) were more frequent (31% vs. 18%; P = 0.05) in the overhydrated group and the central systolic blood pressure (P = 0.008) and pulse wave velocity (P = 0.02) were also significantly higher in this group. There was no significant difference between the groups in respect of the medications they were using (Table 1). When assessed in combination with data form conventional echocardiography, GLS (P < 0.001), was significantly lower whereas ts-SD (P = 0.007) and LVMI (P < 0.001) values were significantly higher in the overhydrated group. The values of LVEDVI (P = 0.02), LVESVI (P = 0.09), E/e’ (P = 0.02) and LAVI (P = 0.001) were also found to be higher in the overhydrated group. There was no significant difference between the groups in respect of EF (Table 2). In the univariate analysis, a relationship was found between fluid overload and DM (b = 3.157; 95% CI [1.395–7.496]; P = 0.06), PWv (b = 1.309; 95% CI [1.050–1.631]; P = 0.016), systolic blood pressure (b = 1.027; 95% CI [1.007–1.047]; P = 0.07), pulse pressure (b = 1.036; 95% CI [1.009–1.063]; P = 0.008), mean arterial pressure (b = 1.034; 95% CI [1.006–1.064]; P = 0.018), central systolic blood pressure (b = 1.037; 95% CI [1.007–1.0053]; P = 0.011), serum albumin levels (b = 0.245; 95% CI [0.065–0.925]; P = 0.038) and hemoglobin levels (b = 0.720; 95% CI [0.555–0.935]; P = 0.014). However, no relation was detected between FO and age, gender, parathormone (PTH) levels and eGFR. Multivariate logistic regression analysis showed an independent association between overhydration and DM (b = 1.221; 95% CI [1.268–9.064]; P = 0.015] and also hemoglobin levels (b = 0.472; 95% CI [0.442–0.879]). During the echocardiographic analysis, the GLS values were found to be lower in the overhydrated group while the EDVI, ESVI, ts-SD, LVMI, LAVI and E/e’ values were found to be higher (Table 2). A univariate regression analysis was performed between the GLS and clinical and laboratory parameters. According this analysis FO, diabetes, age, gender, PWv and PTH were found to be significantly associated with GLS. However eGFR, blood pressure and hemoglobin levels were not associated with GLS. On multivariate analysis FO and PTH levels were found as the independent associates of GLS (Table 3 and Fig. 1).
4. Discussion In patients who do not undergo dialysis, a decrease in GFR is associated with an increase in cardiovascular events [13]. As the majority of these patients have severe cardiac risk factors such as
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
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NEPHRO-821; No. of Pages 4 A. Yilmaz et al. / Ne´phrologie & The´rapeutique xxx (2015) xxx–xxx Table 1 Baseline demographic data.
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Table 2 Comparison of echocardiographic variables.
Age (years) eGFR (mL/min/1.73 m2) Gender (n = male) Diabetes mellitus (n) Blood urea nitrogen (mg/dL) Sodium (mmol/L) Potassium (mmol/L) Uric acid (mg/dL) Total protein (g/dL) Albumin (g/dL) Parathormone (pg/mL) Spot urine micro total protein/Cr Hemoglobin (g/dL) Systolic Blood Pressure (BP) (mmHg) Diastolic BP (mmHg) Central systolic BP (mmHg) Central diastolic BP (mmHg) Pwv (m/s) Medications Furosemide (n) Aspirin for CAD (n) Vitamin D replacement (n) Erythropoietin replacement (n) Alpha blocker (n) Thiazide (n) ACE-I/ARB (n) Beta-blocker (n)
Normohydrated (FO < 1.1 L)
Overhydrated (FO > 1.1 L)
P
N = 55
N = 52
58.6 13.9 28.1 11.5 33 18 39.8 17.0
62.3 11.0 26.2 10.1 37 31 42.6 14.3
Ns Ns Ns 0.05 Ns
138.6 2.5 4.7 0.4 7.1 1.5 7.1 0.9 4.0 0.2 99 [44–382] 1.6 2.2
139.3 2.0 5.0 0.5 6.7 1.2 7.1 0.7 3.9 0.2 110 [42–570] 2.2 2.3
Ns 0.09 Ns Ns 0.03 Ns Ns
12.2 1.6 133.4 14.8
11.6 1.3 145.0 11.8
0.01 0.005
84.8 14.2 119.3 22.8
87.1 10.1 130.4 18.2
Ns 0.008
86.1 12.8
88.5 10.4
Ns
8.6 1.7
9.5 1.9
0.02
– 9 33 11 9 16 33 22
4 7 27 14 8 20 30 18
Ns Ns Ns Ns Ns Ns Ns Ns
GLS LVMI Ts-SD EF EDVI ESVI LAVI E/e’
FO < 1.1 L
FO 1.1 L
P
18 [15–23] 103.6 26.0 53 [6–120] 70.9 6.7 53.7 15.5 15.0 5.3 28.2 8.0 8.1 3.9
16.5 [10–20] 126.7 27.7 62.5 [14–190] 69.8 7.4 60.5 10.1 18.0 7.0 35.7 11.7 10.4 4.3
< 0.001 < 0.001 0.007 Ns 0.02 0.09 0.001 0.02
undergone dialysis in the past, the data acquired can difficultly be compared to the data of our study. In our study, despite detecting a significant difference between the groups with regard to pulse wave velocity, the multivariate model could not prove the independent relation between fluid overload and pulse wave velocity. This situation may be due to the low number of patients enrolled in our study. In a study, Goto et al. have reported that secondary hyperparathyroidism was associated with cardiac dysfunction in chronic kidney disease [16]. However there are only a limited number of studies investigating the cardiac effects of hyperparathyroidism in patients who do not undergo dialysis. On the other hand compared the effect of alfacalcidol versus no treatment in patients with CKD stage 4, in the alfacalcidol-treated patients LV systolic function (shortening fraction) significantly increased, while PTH decreased by 72% [17]. In another study, despite lowering the PTH levels with paricalcitol replacement, a decrease in LVMI, EDVI, ESVI and E/e’ could not be obtained [18]. All of these parameters are afterload-dependent and they may be influenced by many factors (such as hypervolemic status) in patients who undergo hemodialysis. Our study detected an independent association between GLS and PTH levels. However, further studies with sensitive cardiac imaging techniques are needed to determine the independent effects of hyperparathyroidism on cardiac functions. Previous studies have shown that hypertensive patients with left ventricular hypertrophy have decreased myocardial strain levels [19]. Therefore, factors like hypertension, increased pulse pressure and an increased pulse wave velocity (as an indicator of an increased aortic stiffness), which would somehow increase the afterload, may cause lower myocardial strain values. Left ventricular hypertrophy due to a cardiorenal-syndrome-related-hypervolemia may also reduce myocardial strain, however this issue has not yet fully been discussed. Our study could not demonstrate a relationship between FO and age, PWv, diabetes and PTH levels. When focusing on the GLS, multivariate analysis showed that only the PTH levels and fluid overload were independently associated with GLS values. To our knowledge, this study is the first that reports the association between fluid overload and GLS.
ACE-I: angiotensin converting enzyme inhibitor; ARB: angiotensin receptor blocker.
DM and HT, this increase in CV events may also be due to cardiac complications of DM and HT. In patients undergoing hemodialysis, the effects of hypervolemia on cardiac parameters are well known. However, there are limited number of studies focusing on cardiac findings in patients who do not undergo hemodialysis. Essig et al. demonstrated that hypervolemia was associated with an increase in arterial stiffness, carotid intima media thickness and with echocardiographic diastolic dysfunction parameters in patients on an early stage of chronic kidney failure [14]. The association of hypervolemia with diastolic dysfunction, left ventricular hypertrophy and arterial hypertension are well known. These factors are all associated with a decrease in global left ventricular strain values. Pirat et al. compared the strain values of patients with end-stage renal disease and a control group and found lower values in the patients group [15]. Because the patients in that study had already
Table 3 GLS and its relations. Univariate analysis
Gender (male) Age DM PWv PTH FO
Multivariate analysis
b
95% CI
P
1.354 0.042 1.082 0.330 0.006 0.661
0.298; 2.411 0.082; 0.021 2.164; 0.012 0.607; 0.053 0.012; 0.001 0.996; 0.326
0.011 0.04 0.05 0.020 0.020 < 0.001
b
95% CI
0.007 0.517
0.013; 0.916;
P
0.002 0.119
0.011 0.012
Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003
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Fig. 1. Relationship between GLS (-%) and FO.
5. Limitations Our study was a sectional one and the number on patients included was relatively small. Cardiac functions were not reevaluated after volume balance was medically treated. Therefore, the relation between fluid overload and GLS cannot be seen as a cause-and-effect relationship. However, it can be deduced that a decrease in GLS values might be an early warning of a positive fluid balance onset. 6. Conclusion In patients with predialysis chronic kidney disease whom providing fluid balance endogenously, there is an independent relationship between GLS and FO regardless of age, gender, diabetes and arterial stiffness. Disclosure of interest The authors declare that they have no competing interest. References [1] Kalantar-Zadeh K, Regidor DL, Kovesdy CP, Van Wyck D, Bunnapradist S, Horwich TB, et al. Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis. Circulation 2009;119:671–9. [2] Chih CW, Yao PL, Wen CY, Lee WS, Hsu TL, Ding PY, et al. The assessment of fluid status in haemodialysis patients: usefulness of the Doppler echocardiographic parameters. Nephrol Dial Transplant 2004;19:644–51. [3] Kocyigit I, Sipahioglu MH, Orscelik O, Unal A, Celik A, Abbas SR, et al. The association between arterial stiffness and fluid status in peritoneal dialysis patients. Perit Dial Int 2014;34:781–90. [4] Marwick TH. Measurement of strain and strain rate by echocardiography: ready for prime time? J Am Coll Cardiol 2006;47:1313–27. [5] Hur E, Usta M, Toz H, Asci G, Wabel P, Kahvecioglu S, et al. Effect of fluid management guided by bioimpedance spectroscopy on cardiovascular parameters in hemodialysis patients: a randomized controlled trial. Am J Kidney Dis 2013;61:957–65. [6] Stack AG, Saran R. Clinical correlates and mortality impact of left ventricular hypertrophy among new ESRD patients in the United States. Am J Kidney Dis 2002;40:1202–10.
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Please cite this article in press as: Yilmaz A, et al. Association of overhydration and cardiac dysfunction in patients have chronic kidney disease but not yet dialysis. Ne´phrol ther (2015), http://dx.doi.org/10.1016/j.nephro.2015.08.003