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Saudi Journal of Kidney Diseases and Transplantation
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ORIGINAL ARTICLE  
Year : 2016  |  Volume : 27  |  Issue : 1  |  Page : 81-87
The relationship between malnutrition subgroups and volume parameters in pre-dialysis patients


1 Department of Nephrology, Kartal Kosuyolu High Speciality Training and Research Hospital, Istanbul, Turkey
2 Department of Nephrology, Celal Bayar University, Faculty of Medicine, Manisa, Turkey
3 Department of Nephrology, Antalya Education and Research Hospital, Ministry of Health, Antalya, Turkey
4 Department of Biochemistry and Clinical Biochemistry, Celal Bayar University, Faculty of Medicine, Manisa, Turkey
5 Department of Cardiology, Celal Bayar University, Faculty of Medicine, Manisa, Turkey

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Date of Web Publication15-Jan-2016
 

   Abstract 

There are two types of malnutrition in patients with chronic renal failure (CRF); type 1 and type 2. The aim of this study was to investigate the relationship between malnutrition and inflammation and also the relationship between malnutrition and volume status. Ninety-four pre-dialysis CRF patients were included in the study. Nutritional status of the patients was calculated using the subjective global assessment. Scores of 1-5 were given according to the severity of the symptoms and physical examination findings. Serum inflammation markers [high-sensitive C-reactive protein (hs-CRP), interleukin-1β, interleukin-6 and tumor necrosis factor-alfa] and nutrition parameters (albumin, pre-albumin, transferrin, fetuin-A, insulin like growth factor-1 and insulin-like growth factor-binding protein-3)] were measured in all the patients. Serum N-terminal pro-brain natriuretic peptide levels and echocardiography were performed to evaluate the volume status of the patients. The mean age of the patients was 59.6 ± 13.3 years, the mean malnutrition score was 17.2 ± 6.01, the mean and the median of hs-CRP levels were 18.5 ± 40.7 and 5.6 mg/L, respectively, the mean albumin level was 3.46 ± 0.48 and the mean creatinine clearance was 23.7 ± 13.5 mL/min. A positive correlation between malnutrition scores with inflammation and volume parameters was found in the bivariate and multivariate analysis. In the multiple regression analysis, volume parameters proved to be the most important factors influencing malnutrition scores. Thus, the elimination of volume excess would ameliorate both inflammation and malnutrition. This hypothesis needs to be supported or proved with prospective studies.

How to cite this article:
Kutsal DA, Kürşat S, İnci A, Ulman C, Ütük I O. The relationship between malnutrition subgroups and volume parameters in pre-dialysis patients. Saudi J Kidney Dis Transpl 2016;27:81-7

How to cite this URL:
Kutsal DA, Kürşat S, İnci A, Ulman C, Ütük I O. The relationship between malnutrition subgroups and volume parameters in pre-dialysis patients. Saudi J Kidney Dis Transpl [serial online] 2016 [cited 2021 Oct 22];27:81-7. Available from: https://www.sjkdt.org/text.asp?2016/27/1/81/174082

   Introduction Top


Malnutrition rates are as high as 40% in patients with chronic renal failure (CRF), and are defined as an independent risk factor that increases cardiovascular mortality. [1] The salient features of CRF include an accumulation of toxic waste materials in the body, excess of volume and insufficient protein and energy intake. [2],[3]

The etiology of malnutrition in CRF is complex. It is divided into two subgroups as malnutrition type 1 and type 2. Type 1 emerges with insufficient protein and energy intake due to anorexia and nausea that improve with adequate dialysis and nutritional support. Type 2 malnutrition mediated by inflammation and cytokines in circulation, either partially or completely, may or may not improve with sufficient nutritional support. [4]

Inflammation is prevalent in 30-60% of uremic patients. [5] Pro-inflammatory cytokines such as high-sensitive C-reactive protein (hs-CRP), interleukin-6 (IL-6) and tumor necrosis factor-alfa (TNF-α) have a negative effect on protein synthesis. It has been demonstrated that pro-inflammatory cytokines have an important role on not only the development of malnutrition but also on the pathogenesis of accelerated atherosclerosis, and it is related with increased mortality rates of CRF patients. Furthermore, volume overload is one of the important features that occurs together with a decrease of renal function and is associated with inflammation in uremia. [6],[7]

We aimed in this study to determine whether there is a statistical difference among malnutrition subgroups and volume status. We also attempted to assess the volume status in the malnutrition subtype associated with inflamemation (type 2 malnutrition).


   Materials and Methods Top


One hundred and twenty-two pre-dialysis CRF patients who applied to the Celal Bayar University Nephrology Clinic either as outpatient or hospitalized patients between 01-102009 and 01-11-2011 were considered for the study. Chronic hepatic disease, chronic obstructive pulmonary disease, malignancy, myocardial infarction, acute disease history within a three-month period of the study, presence of active infection and cases with acute renal failure were excluded from the study. Twenty-eight patients enrolled initially in the study were excluded from it due to technical incompatibility during testing. A total of 94 cases completed the study. The results obtained from these patients were analyzed.

After all the patients' medical histories were taken and necessary examinations were performed, fasting serum samples of the patients were obtained on the day of application, centrifuged immediately and stored at -80°C till the study. All the samples were analyzed at the Celal Bayar University Biochemistry Laboratory. Of the blood samples, CRP (hs-CRP), interleukin-1 beta (IL-1β), IL-6, TNF-α, pre-albumin, transferrin, N-terminal pro-brain natriuretic peptide (NT-ProBNP), insulin growth factor-1 (IGF-1), insulin-like growth factor-binding protein 3 (IGFBP-3) and fetuin-A tests were performed on all the patients.

The human transferrin levels in serum samples were measured with the enzyme-linked immunosorbent assay (ELISA) method using the Alpha Diagnostic, San Antonio, USA kits. The human IL-1β levels in serum samples were measured with the ELISA method using the Gen-Probe BasençonCedex-France kits. The human TNF-α value in serum samples were measured with the ELISA method using the Gen-Probe, Basencon Cedex-France kits. The human fetuin-A levels were measured with the ELISA method using the BioVendor, Heidelberg-Germany kits. The human IL-6 levels in serum samples were measured with the ELISA method using the Gen-Probe, BesançonCedex-France kits. The pre-albumin levels in serum samples were measured with the ELISA method using the immune diagnostic Bensheim-Germany kits. The NT-ProBNP levels were measured in the Bio-merrio-minividas analyzer using the Biomerio kart tests. The hs-CRP levels were measured with Siemens kits using the immulite 2000 (Immulite 2000, Los Angeles, CA, USA) analyzer. The IGFBP3 levels were measured using the Siemens kits with the immulite 2000 (Immulite 2000, Los Angeles, CA, USA) analyzer. Finally, the IGF-1 levels were measured using Siemens kits with the immulite 2000 analyzer.

The malnutrition status of the patients was evaluated with history and the subjective global assessment (SGA), depending on physical examination. Weight changes were evaluated by scores between 1 and 5 points (body weight change within the last six months, 5%, 5-10% or >%10 loss), food intake through the diet, gastrointestinal symptoms, functional capacity, presence of comorbid diseases and indicators for fat and muscle loss in the physical examination.

Anthropometric characteristics of all the cases were recorded using standard techniques. After the measurement of body lengths and weights, the body mass indices (BMI) were obtained by dividing the body weights by square of heights of the patients and were recorded. The mid-arm circumferences (MAC) were measured and recorded. Triceps skin-fold (TSF) and biceps skin-fold (BSF) measurements were performed using the Harpender scale. On basis of these parameters, the mid-arm muscle circumference (MAMC) was calculated using the below-mentioned formula [MAMC = MAC - (3.1415 × TSF)].

Two-dimensional and M-mode standard echocardiography were performed on all the patients (General Electric VINGMED VIVID 3 Pro with 2.25 MHz probe). Left ventricle mass was calculated by using the thick-wall prolate-ellipsoidal model (LVM) and LVM index (LVMI) was calculated by dividing LVM by body surface area (BSA) and the LVM was normalized [calculated by the formula BSA = 0.007184 × [weight (kg)] 0.425 × [length (cm)] 0.725]. Vena cava inferior (VCI) diameters for all the patients were measured after 10 min in a supine position during maximal inspiration and expiration. The VCI collapse index was measured using the formula collapse index = (maximum diameter during expiration minimum diameter during deep inspiration) / maximum diameter during expiration.


   Statistical analysis Top


The Statistical Package for Social Sciences (SPSS19) program was used for the analysis of the data. For the analysis of quantitative data, the Kolmogrov-Simirnov test was used for the confirmation of normal distribution, and its homogeneity was analyzed with the Levene test. Parametric methods were used for the analysis of normally distributed variables and non-parametric methods were used for the analysis of variables unevenly distributed. For the parametric methods, an independent t-test was used for the comparison of the independent groups. For the non-parametric methods, the Mann-Whitney U test was used for the pairwise comparison of the independent groups and the Kruskal-Wallis H test was used for the comparison of multiple groups. Non-parametric Tukey's test was used to determine the intergroup differences. Kendall's tau-b, Pearson correlation and Spearman's rho tests were used in order to evaluate the intergroup relations between the variables.

Logistic regression tests were performed to determine the cause and effect relationship by explanatory variables of the categorical response variable in the diotom and multi-nominal categories. The Pearson chi-square, chisquare, continuity correction and Fisher exact tests were used for the comparison of the categorical variables. Data were assessed at the 95% confidential level and P-values <0.005 were considered to be significant.


   Results Top


The mean age of the study patients (94 cases) was 59.6 ± 13.3 years, and the cohort included 41 females and 53 males. The primary renal diseases of the patients included diabetic nephropathy (n = 32; 34%), hypertensive nephrosclerosis (n = 46; 48.9%), adult autosomal dominant polycystic renal disease (n = 5; 5.3%), undetermined cases (n = 8; 8.5%) and chronic glomerulonephritis (n = 3; 3.2%).

[Table 1] shows the mean values of the demographic characteristics, the inflammation indicators, echocardiography (ECHO) parameters and nutrition parameters of the study patients. [Table 2] shows the distribution of the status of nutrition of the patients according to the malnutrition score and SGA.
Table 1: The mean values of demographic characteristics, inflammation indicators, ECHO and nutrition parameters of the patients.

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Table 2: Distribution of the status of nutrition and malnutrition score of the patients according to SGA.

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When we assessed the correlation between the malnutrition score and the nutritional parameters, a significant correlation was found between hs-CRP and IL-6, low albumin (r: -0.307, P = 0.003), low transferring (r: -0.239, P = 0.020) and low fetuin-A (r: -0.272, P = 0.008). A positive correlation was found between IL-6 and malnutrition scores (r: 0.283, P = 0.006), but there was a negative correlation of IL-6 with pre albumin (r: -0.243, P = 0.018), albumin (r: -0.306, P = 0.003) and fetuin-A (r: 0.306, P = 0.003).

When the volume parameters and the nutrition parameters were compared with the malnutrition scores, NT-ProBNP had a significantly positive correlation with the malnutrition scores (r: 0.391, P = 0.000), but there was a significant negative correlation with albumin (r: -0.353, P = 0.000), transferrin (r: -0.222, P= 0.032) and fetuin-A (r: -0.214, P = 0.038).

When the general volume parameters and the inflammation indicators of the patients were compared without dividing them into subgroups according to the inflammation parameters (Pearson-correlation test), we found a significant positive correlation between hsCRP and NT-ProBNP (r: 0.327, P = 0.001), LA (r: 0.244, P = 0.018), LVM (r: 0.292, P = 0.004) and LVMI (r: 0.310, P = 0.002), but there was a significant negative correlation with the VCI index (r: -0.358, P = 0.000).

There was no significant correlation between TNF-α and IL-1β with the volume parameters. However, a significant correlation was observed between IL-6 and NT-ProBNP (r: 0.379, P = 0.000). Furthermore, a weak correlation was observed between IL-6 and LVM and LVMI (r: 0.224, P = 0.030 and r: 0.220, P = 0.033, respectively).


   Discussion Top


Several metabolic and nutritional disorders are still observed in CRF patients in spite of improvements in the understanding of the uremic environment and the consequences and improvements in renal replacement therapy. [8] Malnutrition begins when the glomerular filtration rate is about 28-35 mL/min/1.73 m 2 , and increases gradually. SGA provides objective results related to clinical consequences. [9],[10],[11]

In spite of the developments in renal replacement treatments of the patients with CRF, the incidence of malnutrition was reported to be 10-70% for hemodialysis patients, 18-51% in peritoneum dialysis patients and 30-51% for pre-dialysis patients. In the pre-dialysis patient group included our study, mild-moderate malnutrition cases were 53.2% and severe malnutrition cases was determined as 21.3% [Table 2]. [12],[13]

The risk of cardiovascular mortality is increased significantly in CRF patients. [14],[15] In addition to the traditional risk factors such as diabetes mellitus, hypertension and dyslipidemia, there are non-traditional risk factors such as inflammation. [14],[16],[17]

In our study, the inflammation indicators were found to be high in both individual and mean values. High levels of hs-CRP and proinflammatory cytokine IL-6 determine mortality independently in CRF patients and are a reliable predictor for determining malnutrition and cardiovascular disease. [18],[19]

There are many publications in the literature that associate inflammation with volume status. It has been demonstrated that inflammation increases BNP and NT-ProBNP production; in cases with high NT-ProBNP levels, there are higher CRP levels independent from heart failure stage. In patients without heart failure, increased NT-ProBNP/BNP levels were discovered in the presence of inflammation. [20]

When the studies that investigate the relationship between excess volumes with malnutrition were reviewed, there was a probable relationship between insufficient food intake and volume overload in 266 peritoneal dialysis patients. In this cross-sectional study, attention was drawn not to insufficient dietary intake secondary to insufficient dialysis alone as the reason of malnutrition but also the complex relationship between volume overload, inflammation and dietary intake. [21] NT-ProBNP, an indicator of volume overload and myocardial damage, is an independent predictor of mortality, and its correlation with malnutrition and inflammation parameters has been demonstrated. [22],[23],[24] In CRF patients with malnutrition, excess volume may be a mechanism that explains the increased mortality and morbidity.

The nutritional status of the patients worsens parallel to inflammation. The results of our study are concurrent with the malnutrition- inflammation relationship demonstrated in other studies. [7],[25],[26],[27]

In our study, a correlation between NT-ProBNP with malnutrition score and albumin was found. Other studies demonstrated the presence of malnutrition in CRF patients with volume overload, but the cause-effect relationship is still not confirmed. [28] Furthermore, there was a correlation in our study between the volume status parameters and the inflammation indicators of the patients. This result is compatible with that of other studies. [20],[29],[30] In many studies, the association of inflammation in CRF patients with volume overload could be the mechanism explaining the relationship of cardiovascular morbidity and mortality.

Chronic activation of the systemic inflammatory response in end-stage renal failure is common. Eliminating the factors through the development of new treatment methods that prevent inflammation, which has a potential role in the development of protein-energy malnutrition, will reduce the mortality and morbidity and successfully manage malnutrition during the progression of CRF. [31]

In the regression analysis of our patients' parameters of the ongoing inflammation and volume overload, significantly higher scores of malnutrition have been found. The factors that most influence the malnutrition score are the volume parameters; this strengthens the relationship between volume and malnutrition. In other words, the relationship between volume and malnutrition is stronger than the relationship between inflammation and malnutrition.

Although the prevalence of inflammation is high in the terminal-stage renal failure patients, there are no current recommendations on how chronic inflammation will be managed. Current data have demonstrated that pro-inflammatory cytokines play the basic role in both the beginning and the progression of malnutrition and cardiovascular diseases.

We conclude that excess volume is highly associated with both inflammation and malnutrition, but the cause-effect relationship is yet to be established. Prospective studies are required to assess the different treatment strategies on the outcome of CRF patients with respect to these factors.

Conflict of Interest: None declared.

 
   References Top

1.
Leavey SF, Strawderman RL, Jones CA, Port FK, Held PJ. Simple nutritional indicators as independent predictors of mortality in hemodialysis patients. Am J Kidney Dis 1998;31: 997-1006.  Back to cited text no. 1
    
2.
Essig M, Escoubet B, de Zuttere D, et al. Cardiovascular remodelling and extracellular fluid excess in early stages of chronic kidney disease. Nephrol Dial Transplant 2008;23:239-48.  Back to cited text no. 2
    
3.
Ersan S, Çamsarı T. Nutritional Disorders in Chronic Renal Failure (Protein-Energy Wasting) Turkiye Klinikleri Journal of Nephrol Spec Topics 2009;2(2):1-6. (Article in Turkish)  Back to cited text no. 3
    
4.
Stenvinkel P, Heimbürger O, Lindholm B, Kaysen GA, Bergström J. Are there two types of malnutrition in chronic renal failure? Evidence for relationships between malnutrition, inflammation and atherosclerosis (MIA syndrome). Nephrol Dial Transplant 2000;15: 953-60.  Back to cited text no. 4
    
5.
Jofré R, Rodriguez-Benitez P, López-Gómez JM, Pérez-Garcia R. Inflammatory syndrome in patients on hemodialysis. J Am Soc Nephrol 2006;17 12 Suppl 3:S274-80.  Back to cited text no. 5
    
6.
Zoccali C, Tripepi G, Mallamaci F. Dissecting inflammation in ESRD: Do cytokines and Creactive protein have a complementary prognostic value for mortality in dialysis patients? J Am Soc Nephrol 2006;17 12 Suppl 3:S169-73.  Back to cited text no. 6
    
7.
Stenvinkel P, Heimbürger O, Paultre F, et al. Strong association between malnutrition, inflammation, and atherosclerosis in chronic renal failure. Kidney Int 1999;55:1899-911.  Back to cited text no. 7
    
8.
Ikizler TA. Nutrition, inflammation and chronic kidney disease. Curr Opin Nephrol Hypertens 2008;17:162-7.  Back to cited text no. 8
    
9.
Steiber A, Leon JB, Secker D, et al. Multicenter study of the validity and reliability of subjective global assessment in the hemodialysis population. J Ren Nutr 2007;17:336-42.  Back to cited text no. 9
    
10.
Cooper BA, Bartlett LH, Aslani A, Allen BJ, Ibels LS, Pollock CA. Validity of subjective global assessment as a nutritional marker in end-stage renal disease. Am J Kidney Dis 2002;40:126-32.  Back to cited text no. 10
    
11.
Janardhan V, Soundararajan P, Rani NV, et al. Prediction of malnutrition using modified subjective global assessment-dialysis malnutrition score in patients on hemodialysis. Indian J Pharm Sci 2011;73:38-45.  Back to cited text no. 11
[PUBMED]  Medknow Journal  
12.
Mehrotra R, Kopple JD. Nutritional management of maintenance dialysis patients: Why aren't we doing better? Annu Rev Nutr 2001; 21:343-79.  Back to cited text no. 12
    
13.
Chung SH, Lindholm B, Lee HB. Influence of initial nutritional status on continuous ambulatory peritoneal dialysis patient survival. Perit Dial Int 2000;20:19-26.  Back to cited text no. 13
    
14.
Shlipak MG, Fried LF, Cushman M, et al. Cardiovascular mortality risk in chronic kidney disease: Comparison of traditional and novel risk factors. JAMA 2005;293:1737-45.  Back to cited text no. 14
    
15.
Foley RN, Parfrey PS, Sarnak MJ. Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis 1998; 32 5 Suppl 3:S112-9.  Back to cited text no. 15
    
16.
Muntner P, Hamm LL, Kusek JW, Chen J, Whelton PK, He J. The prevalence of nontraditional risk factors for coronary heart disease in patients with chronic kidney disease. Ann Intern Med 2004;140:9-17.  Back to cited text no. 16
    
17.
Muntner P, He J, Astor BC, Folsom AR, Coresh J. Traditional and nontraditional risk factors predict coronary heart disease in chronic kidney disease: Results from the atherosclerosis risk in communities study. J Am Soc Nephrol 2005;16:529-38.  Back to cited text no. 17
    
18.
Stenvinkel P. Inflammation in end-stage renal disease: The hidden enemy. Nephrology (Carlton) 2006;11:36-41.  Back to cited text no. 18
    
19.
Honda H, Qureshi AR, Heimbürger O, et al. Serum albumin, C-reactive protein, interleukin 6, and fetuin a as predictors of malnutrition, cardiovascular disease, and mortality in patients with ESRD. Am J Kidney Dis 2006; 47:139-48.  Back to cited text no. 19
    
20.
Jensen J, Ma LP, Fu ML, Svaninger D, Lundberg PA, Hammarsten O. Inflammation increases NT-proBNP and the NT-proBNP/ BNP ratio. Clin Res Cardiol 2010;99:445-52.  Back to cited text no. 20
    
21.
Wang AY, Sanderson J, Sea MM, et al. Important factors other than dialysis adequacy associated with inadequate dietary protein and energy intakes in patients receiving maintenance peritoneal dialysis. Am J Clin Nutr 2003;77:834-41.  Back to cited text no. 21
    
22.
Ortega O, Gallar P, Muñoz M, et al. Association between C-reactive protein levels and N-terminal pro-B-type natriuretic peptide in pre-dialysis patients. Nephron Clin Pract 2004;97:c125-30.  Back to cited text no. 22
    
23.
Paniagua R, Amato D, Mujais S, et al. Predictive value of brain natriuretic peptides in patients on peritoneal dialysis: Results from the ADEMEX trial. Clin J Am Soc Nephrol 2008; 3:407-15.  Back to cited text no. 23
    
24.
Paniagua R, Ventura MD, Avila-Díaz M, et al. NT-proBNP, fluid volume overload and dialysis modality are independent predictors of mortality in ESRD patients. Nephrol Dial Transplant 2010;25:551-7.  Back to cited text no. 24
    
25.
Kalantar-Zadeh K, Block G, McAllister CJ, Humphreys MH, Kopple JD. Appetite and inflammation, nutrition, anemia, and clinical outcome in hemodialysis patients. Am J Clin Nutr 2004;80:299-307.  Back to cited text no. 25
    
26.
Kamimura MA, Draibe SA, Dalboni MA, et al. Serum and cellular interleukin-6 in haemodialysis patients: Relationship with energy expenditure. Nephrol Dial Transplant 2007;22: 839-44.  Back to cited text no. 26
    
27.
Cano NJ, Heng AE, Pison C. Multimodal approach to malnutrition in malnourished maintenance hemodialysis patients. J Ren Nutr 2011;21:23-6.  Back to cited text no. 27
    
28.
Fein PA, Mittman N, Gadh R, et al. Malnutrition and inflammation in peritoneal dialysis patients. Kidney Int Suppl 2003;87:S87-91.  Back to cited text no. 28
    
29.
Vicenté-Martínez M, Martínez-Ramírez L, et al. Inflammation in patients on peritoneal dialysis is associated with increased extracellular fluid volume. Arch Med Res 2004;35:220-4.  Back to cited text no. 29
    
30.
Jacobs LH, van de Kerkhof JJ, Mingels AM, et al. Inflammation, overhydration and cardiac biomarkers in haemodialysis patients: A longitudinal study. Nephrol Dial Transplant 2010;25:243-8.  Back to cited text no. 30
    
31.
Bistrian BR. Role of the systemic inflammatory response syndrome in the development of protein-calorie malnutrition in ESRD. Am J Kidney Dis 1998;32 6 Suppl 4:S113-7.  Back to cited text no. 31
    

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Correspondence Address:
Dilek Aslan Kutsal
Department of Nephrology, Kartal Kosuyolu High Speciality Training and Research Hospital, Istanbul
Turkey
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DOI: 10.4103/1319-2442.174082

PMID: 26787571

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