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Saudi Journal of Kidney Diseases and Transplantation
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Table of Contents   
ORIGINAL ARTICLE  
Year : 2011  |  Volume : 22  |  Issue : 4  |  Page : 695-704
Factors predicting malnutrition in hemodialysis patients


1 Department of Nephrology, Dialysis and Transplantation, Military Hospital Mohammed V, Rabat, Morocco
2 Critical Care Unit, Idrissi Hospital, Kenitra, Morocco

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Date of Web Publication9-Jul-2011
 

   Abstract 

Signs of protein-energy malnutrition are common in maintenance hemodialyis (HD) patients and are associated with increased morbidity and mortality. To evaluate the nutritional status and relationship between various parameters used for assessing malnutrition, we performed a cross-sectional study in 37 HD patients treated with thrice weekly sessions for at least two weeks. Global nutritional status was evaluated by the dual-energy X-ray absorptiometry (DEXA) scan. Body weight and several laboratory values, including serum albumin (Salb), serum prealbumin, bicarbonate, cholesterol, serum C-reactive protein (SCRP), and hemoglobin, were recorded. Dose of dialysis was evaluated by urea kinetic modeling. The patients were subdivided into two groups based on body mass index: group I, normal nutritional status (71%) and group II, malnutrition (29%). The clinical factors associated with malnutrition included advanced age and cardio-vascular diseases (CVD), decreased fat mass (FM) measured by DEXA, low Salb and prealbumin, and severe anemia. The Salb level was not only a predictor of nutritional status, but also was independently influenced by age and SCRP, which was more common in malnourished patients than in patients with normal nutritional status. Both low Kt/V and less weekly dialysis time were associated with malnutrition. The FM and lean body mass (LBM) calculated by DEXA correlated with CVD and other markers of malnutrition (Salb, total cholesterol).

How to cite this article:
Kadiri ME, Nechba RB, Oualim Z. Factors predicting malnutrition in hemodialysis patients. Saudi J Kidney Dis Transpl 2011;22:695-704

How to cite this URL:
Kadiri ME, Nechba RB, Oualim Z. Factors predicting malnutrition in hemodialysis patients. Saudi J Kidney Dis Transpl [serial online] 2011 [cited 2019 Apr 24];22:695-704. Available from: http://www.sjkdt.org/text.asp?2011/22/4/695/82646

   Introduction Top


Protein-energy malnutrition and wasting are present in a large proportion of patients with chronic renal failure. This may be a consequence of multiple factors, including disturbances in protein and energy metabolism, hormonal derangements, infections and other superimposed illnesses as well as reduced food intake because of anorexia, nausea and vomiting, caused by uremic toxicity. After commencement of maintenance dialysis treatment, most of the overt symptoms of uremia diminish or disappear and the patients generally experience increased well-being and improved appetite. However, several reports show that the prevalence of protein-energy malnutrition in dialysis patients remains elevated; 23-76% of hemodialysis (HD) patients are reported to be malnourished, and the variability presumably is related to factors such as age, case mix, co-morbid conditions and quality of dialysis therapy. [1],[2],[3],[4],[5],[6],[7] During recent years, several studies in HD patients have shown an association between signs of malnutrition, particularly low serum albumin(Salb), and increased morbidity and mortality. [8],[9],[10],[11]

In addition, atherosclerosis often coexists with inflammation and malnutrition in HD patients, [2],[3],[4],[5],[6],[7],[8],[9] and a low body mass index (BMI) and a low Salb level, the markers of malnutrition, are both predictors of poor survival in these patients. [3],[4],[5],[6],[7],[8],[9],[10]

The aim of our study was to assess the prevalence and degree of protein-energy malnutrition in a population of HD patients, determine the relationship between various parameters used to evaluate the nutritional status, and analyze how co-morbid factors influence these parameters.


   Patients and Methods Top


All patients with chronic renal failure who were treated with maintenance HD at the dialysis unit of the military hospital of Rabat, and who had been on HD for at least three months, were eligible for inclusion in the present study.

We studied 37 patients (17 females and 20 males) of median age 50 years (range 21-74 years). The median length of time on HD treatment was 4 ± 2 years. The causes of renal failure included diabetic nephropathy (n = 12), interstitial nephritis (n = 4), hypertensive nephropathy (n = 4), cystic kidney disease (n = 3), and amyloidosis (n = 2); the etiology of kidney disease was labeled as unknown in 12 patients, and seven of the diabetic patients were insulin dependent.

Nine (24%) patients presented with signs of cardiovascular and/or peripheral vascular disease (grouped as CVD), [Table 1]. Of these, two had suffered one or more myocardial infarctions, three had ischemic heart disease but no prior myocardial infarction, and four had peripheral ischemic atherosclerotic vascular disease. Three patients had cerebrovascular disease with neurological symptoms; all these patients also had signs of cardiovascular disease. Of the 12 diabetic patients, seven had CVD. The patients were treated with oral sodium bicarbonate, calcium carbonate, and/or sevelamer as required to prevent acidosis and hyperphosphatemia. Eleven patients were taking anti-hypertensive drugs such as angiotensin-converting enzyme inhibitors, beta-blockers, and calcium-channel inhibitors. Nine patients with residual renal function were treated with high doses of furosemide (250-500 mg/day) to increase urinary output and renal sodium excretion. Recombinant human erythropoietin was applied to 30 patients. All patients were prescribed vitamins (B and C). HD was performed three times per week. Dialyzers with low-permeability (polysulfone) were used in all patients; membrane surface areas were 1.0 m 2 (N 2), 1.3 m 2 (N 16), 1.6 m 2 (N 17) and 1.8 m 2 (N 2). The dialyzers were not reused. Prescribed Kt/V urea for one single dialysis was calculated from dialyzer 1 renal urea clearance (K), dialysis time (t) and V obtained by urea kinetic modeling. [12] Outcome Kt/V urea was calculated by the Daugirdas method, [13] based on the reduction in the serum urea concentration during dialysis and taking the effect of ultrafiltration into consideration.
Table 1: Baseline characteristics of the study patients.

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The study patients agreed for comparative analysis of nutritional status, anthropometric, and biochemical variables. The study protocol was approved by the local Ethics Committee and informed consent was obtained from each patient. The nutritional status, anthropometric measurements (except absolute) and blood sampling for biochemical analyses were performed in all the patients after an overnight fast; the HD patients were investigated on a mid-week, dialysis-free day.

Dual-energy X-ray absorptiometry (DEXA) is considered to be superior than the other noninvasive methods for determining the body composition in renal failure, [14] and has been widely applied for the study of body composition in dialysis patients. [14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26],[27]

In the present study, by using DEXA that provides reliable information on body composition, [20] we evaluated the differential contributions of fat mass (FM) and lean mass (LM) to determine the nutritional status of HD patients.

BMI and nutrition are strong and independent predictors of survival in HD. Additionally, high BMI is associated with increased survival. [23] BMI was calculated by the standard formula (post-dialysis weight in kg/height in m 2 ). Body weight was recorded post-dialysis with the subjects lightly dressed and without shoes. According to the definition of World Health Organization (WHO), a BMI less than 18.5 kg/m 2 was defined as being underweight, 18.5-24.99 kg/m 2 was considered to be normal weight and a BMI ≥25 kg/m 2 was considered to be overweight. [17] Our patients fell into two distinct groups according to this definition, with statistically different BMI [Figure 1].
Figure 1: The body mass index in the study patients.

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Venous blood samples from HD patients were collected immediately before the anthropometric measurements were performed. Blood was also drawn before and after the first dialysis of the week, and again before the next dialysis for urea determinations used to calculate urea kinetics. Blood hemoglobin and serum biochemical parameters were analyzed using routine methods. Salb was determined by the reference method using immunonephelometry. [15] Prealbumin has a shorter half-life than albumin and a close relationship with nutritional status and is a good predictor of clinical outcome. [19] Serum prealbumin was determined by immuno-nephelemetry. [26] Serum C-reactive protein (SCRP) was also measured using an immunonephelometric method. The upper limit for normal values was set by the laboratory at 8 mg/L, [16] and levels below this limit were reported as normal but not quantified.


   Statistical Analyses Top


Data were presented as the mean values ± SD, and a P <0.05 was considered as statically significant. Continuous variables were compared using the Student's "t" test or with the Mann-Whitney test for variables not normally distributed, while the nominal variables were compared by the chi-squared test. Spearman's rank correlation was used to determine the correlation between two variables.


   Results Top


The mean of BMI for all patients was 23 ± 4 kg/m 2 (for females 23 ± 4 kg/m 2 and for males 24 ± 4 kg/m 2 ) [Figure 2]. The patients were divided into two groups based on BMI [Table 1]. Twenty-six (71%) patients had a normal nutritional status (group I) and 11 (29%) patients were considered to be malnourished (group II) [Table 2].
Figure 2: Frequency of distribution of Body Mass Index (BMI) in all the study patients.

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Table 2: Comparison of the clinical and dialysis data in the study subgroups.

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The median age was lower in group I (46 ± 17 years) than in group II (52 ± 14 years). The proportion of female patients was higher in group I (13 of 26 patients, 50%) than in group II (4 of 11 patients, 36%). The distribution of renal diseases was similar in the two groups, except for a higher percentage of diabetic patients in group II (5 of 11 patients, 45%) than in group I (7 of 26 patients, 27%) respectively. The percentages of patients with residual renal function were 27% in group I and 18% in group II. The prevalence of CVD was higher in group II (45%) than in group I (19%). The mean blood pressure [diastolic pressure + (systolic -diastolic pressure)/3] was similar in both study groups.

The median length of time on HD treatment was longer in group I (3.5 ± 2 years) than in group II (4.5 ± 2 years). The weekly dialysis time was higher in group I than in group II and the difference was significant (P = 0.02) [Table 2]. The mean Kt/V urea normalized to DBW was significantly lower in group II than in group I (1.1 ± 0.2 vs. 1.2 ± 0.2) [Table 2].

The levels of serum cholesterol, transferrin and blood standard bicarbonate count were similar in both the study groups [Table 2]. Salb and serum prealbumin concentrations were significantly reduced in group II as compared to group I. The difference was highly significant for Salb (P <0.001) and significant for serum prealbumin (P = 0.011). SCRP was normal in 23 patients and elevated in 14 patients. SCRP was elevated in group II than in group I patients; however, the difference between the two groups was not significant. The relationship between Salb and SCRP is shown in [Figure 3], demonstrating that patients with SCRP higher than 8 mg/L had low Salb values (below 35 g/L). The patients with elevated SCRP were found to have a significant negative association with Salb (P <0.001) and serum prealbumin (P <0.001) [Figure 3]. There was a significant relationship between inflammation, lower BMI (P = 0.021) and CVD (P = 0.007). However, there was no significant association between inflammation and higher serum total cholesterol concentration, [Table 3].
Figure 3: Relationship between serum C-reactive protein (SCRP) and serum albumin. There was a significant association between (log) SCRP and Salb (P < 0.001), SCRP and serum prealbumin (P <0.001).

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Table 3: Relationship between inflammation, atherosclerosis, malnutrition and CVD.

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There was a statistically significant association between lower BMI (group II) and anemia (P = 0.002) [Table 2], and a significant association between higher SCRP and anemia (P = 0.032) [Table 3].

BMI positively correlated with FM (r = 0.493, P = 0.002). However, there was no significant correlation of BMI with lean body mass (LBM) (r = 0.278, P = 0.085) [Figure 4].
Figure 4: Correlation between body mass index (BMI), fat mass (FM), and lean body mass (LBM) in the total number of subjects at baseline.

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Finally, [Table 4] shows the correlations of BMI, FM, and LBM with other clinical data at baseline. BMI positively correlated with Salb and anemia. FM positively correlated with Salb, anemia and CVD. LBM positively correlated with gender (males) and serum calcium, and negatively correlated with serum total cholesterol and CVD.
Table 4: Correlation between body composition and other clinical variables in the study patients.

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   Discussion Top


In our primary analysis of the incidence of protein-energy malnutrition, we used BMI, which is considered as the marker of malnutrition. [3],[4],[5],[6],[7],[8],[9],[10] The prevalence of malnutrition, according to BMI, was 29%. This value was higher than in most previously reported studies. [7],[18],[19],[20],[21]

The mean of age was high in the malnourished group. It is well known that senescence per se involves a gradual involution of body cell mass. [22],[23],[24] The elderly patients had low Salb, serum prealbumin and Kt/V.

In our study, diabetes mellitus and CVD were more frequent, and SCRP levels were higher among the malnourished than among the well-nourished patients. It has recently been reported that hypoalbuminemia is associated with the presence of and de novo development of cardiac disease in HD and CAPD patients. [25],[26],[27] It is possible that the relationship is inverse, i.e. cardiac disease leads to malnutrition and hypo-albuminemia. Several studies show that patients having chronic cardiac failure without renal disease may develop weight loss and other signs of malnutrition, a condition called cardiac cachexia. [28] Cardiac failure patients have increased resting metabolic rate [29] and fat malabsorption. [30] There is evidence that tumor necrosis factor and other cytokines are major pathogenetic factors in the development of cardiac cachexia. [31] These factors may also elicit an acute phase response resulting in reduced synthesis of Salb. [32],[33]

Among the biochemical parameters, Salb is most frequently used to assess protein malnutrition, based on the concept that the level of Salb reflects the visceral protein status. However, this is only partly true, since there are many other factors that influence the generation, distribution, and catabolism of albumin, such as albumin synthesis inhibition, albumin degradation, albumin losses from the body, dilution by fluid overload and exchange between intravascular and extravascular compartments. [34] Serum albumin also decreases with age in apparently healthy subjects. [35] In our study, Salb was low in the malnourished patients, which decreased in proportion to the degree of malnutrition. SCRP was also a significant independent predictor of Salb and serum pre-albumin. The earlier observations in HD patients demonstrated that albumin generation is reduced during the acute phase response and that Salb is inversely correlated with serum concentrations of CRP and α2-macroglobulin. [36] An independent factor that influences Salb in HD patients is albumin leakage through the dialysis membranes, which has been observed with polysulfone dialyzers, after repeated reuses using bleach as the disinfectant. [37] In our study, this was not a factor of importance, since none of the dialyzers was reused. Liver disease may also reduce albumin synthesis, but it was probably not important in this study, since only one patient had increased serum aspartate aminotransferase levels. In several earlier studies of nutritional status in HD patients, low serum transferrin has been shown to be a useful marker of malnutrition. However, in our study, serum transferrin concentrations failed to distinguish between the well-nourished and the malnourished patients. This was largely due to treatment with recombinant human erythropoietin (rhEPO) and i.v. or oral iron, which may independently modify serum transferrin. [38],[39]

Earlier studies have shown no apparent association between total CO2 or plasma bicarbonate levels and nutritional status. [40],[41] Only one study of CAPD patients reported that the increases in body weight and mid-arm circumference were greater in a group with fully corrected acidosis than in the group with low plasma bicarbonate levels. [42] In our study, we observed no significant correlation between standard blood bicarbonate and any of the nutritional variables recorded (BMI, FM, LBM, albumin or prealbumin). However, it should be emphasized that the acid-base balance was well controlled in most of the patients, with only 21% having a pre-dialysis standard bicarbonate lower than 22 mmol/L. Therefore, it cannot be excluded that a higher degree of acidosis may have a harmful effect on nutritional status by enhancing muscle proteolysis. Nevertheless, our observations of no association between blood bicarbonate and any of the anthropometric and biochemical variables strongly suggest that metabolic acidosis was not an important factor for the development of protein malnutrition in our patients.

There are a few studies in the literature that examined the relationship between DEXA-based body composition and the outcome of HD patients. Kato et al [43] showed that a lower ratio of limb/trunk lean mass by DEXA was a significant predictor of a higher risk of all-cause mortality in men and that a lower percentage of fat content in the trunk was a significant predictor of death in women. Although they suggested the importance of regional body composition, their study did not answer which was more predictive of the outcome of HD patients: total body FM or lean mass. Kakia et al [20] found that a higher fat mass index FMI was an independent predictor of a lower risk of all-cause and non-CVD death and that a high LMI was an independent predictor of a lower risk of CVD mortality. Our study found a positive correlation between FM and CVD and a negative correlation between LBM and CVD. In addition, we found that FM and LBM correlated differently with other markers of nutrition, such as the total cholesterol and Salb, which correlated positively with FM, while total cholesterol correlated negatively with LBM. These results indicate that FM and lean mass reflect the different aspects of protein-energy malnutrition in HD patients.

BMI, FM, lean mass, Salb, serum prealbumin and total cholesterol appear to form one group of markers for protein-energy malnutrition in the HD population. Therefore, DEXA will be a usual tool for assessing the nutritional status in these patients.

Finally, our study demonstrated a positive correlation between LBM and hemoglobin, and an association between low BMI and anemia, suggesting anemia as a marker of malnutrition in HD patients.

In summary, this study showed elevated prevalence of malnutrition in HD patients. Factors associated with malnutrition included advanced age, presence of cardiovascular disease, and anemia. The Salb level was influenced not only by nutritional status but also independently by SCRP. Elevated SCRP was more common in malnourished patients. The FM and LBM calculated by DEXA correlated with CVD and others markers of malnutrition (Salb, total cholesterol).

 
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Correspondence Address:
Moncef El M'Barki Kadiri
Department of Nephrology, Dialysis and Transplantation, Military Hospital, Rabat
Morocco
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