- Email: [email protected]
Reliability of Bioelectrical Impedance Analysis in the Evaluation of the Nutritional Status of Hemodialysis Patients — A Comparison With Mini Nutritional Assessment
Reliability of Bioelectrical Impedance Analysis in the Evaluation of the Nutritional Status of Hemodialysis Patients d A Comparison With Mini Nutritional Assessment an, E. Tutal, M.E. Uyar, Z. Bal, B.G. Demirci, B. Sayın, and S. Sezer E. Erdog ABSTRACT Introduction. Protein-energy wasting (PEW) is a strong predictive factor for morbidity and mortality in patients who have end-stage renal disease (ESRD). Mini Nutritional Assessment (MNA) is an important and confirmed tool to evaluate PEW that has been recommended by many guidelines. Bioelectrical impedance analysis (BIA) is a noninvasive technique for assessing body composition. The aim of the present study was to analyze the reliability of BIA in malnutrition diagnosis by comparing it with standard MNA in a group of 100 ESRD patients. Methods. One hundred ESRD patients who were medically stable and under dialysis treatment for at least 6 months were enrolled to the study. Monthly assessed serum creatinine, albumin, C-reactive protein (CRP), and lipid profiles from the last 6 months prior to the study were retrospectively collected. A standard Full-MNA and body composition analyses were applied to all patients. Body compositions were analyzed with the BIA technique using the Body Composition Analyzer (Tanita BC-420MA; Tanita, Tokyo, Japan). Patients were classified into three groups according to MNA scores as PEW (n ¼ 15, score <17), moderate PEW or risk group (n ¼ 49, score 17e23.5), and well-nourished (n ¼ 36, score 24) patients. Results. Mean duration of maintenance hemodialysis treatment was significantly shorter in the PEW group compared to both of the other groups described (P ¼ .015). Well-nourished and risk groups had lower CRP and higher albumin levels compared to PEW patients; however, these values were statistically similar in these two groups (P ¼ .018, .01, respectively). According to BIA findings, well-nourished patients had the highest fat ratio, fat mass, muscle mass, visceral fat mass, and fat-free mass compared to both moderate the PEW/risk and the PEW groups (P < .05). Risk group patients also had higher muscle mass, visceral fat mass, and fat-free mass values compared to the PEW group (P < .05). A correlation analysis revealed that MNA scores were positively correlated with albumin (P ¼ .005), creatinine (P ¼ .049), fat mass (P ¼ .045), muscle mass (P ¼ .001), visceral fat ratio (P ¼ .007), and BMI (P ¼ .047) and in negative correlation with CRP (r ¼ 0.357, P ¼ .0001) levels. Conclusions. We recommend BIA as a complementary diagnostic tool to evaluate nutritional status of ESRD along with MNA, anthropometric measures, and classical biochemical markers.
D
ESPITE the advancements in current techniques of renal replacement therapy, mortality rates still remain high in patients who have end-stage renal disease (ESRD).1 Protein-energy wasting (PEW), a condition of loss of muscle and visceral protein stores is a common complication and an important predictive factor for morbidity and mortality in ESRD patients. Incidence of PEW in maintenance
From the Departments of Internal Medicine (E.E.) and Nephrology (E.T., M.E.U., Z.B., B.G.D., B.S., S.S.), Baskent University Faculty of Medicine, Ankara, Turkey. Address reprint requests to Emre Tutal, Associate Professor, Department of Nephrology, Baskent University Faculty of Medicine, Fevzi Cakmak Cad. 5. Sokak. No: 48 06490 Bahcelievler, Ankara, Turkey. E-mail: [email protected]
ª 2013 by Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010-1710
0041-1345/13/$esee front matter http://dx.doi.org/10.1016/j.transproceed.2013.08.096
Transplantation Proceedings, 45, 3485e3488 (2013)
3485
ERDOGAN, TUTAL, UYAR ET AL
3486
hemodialysis (MHD) patients varies from 23% to 76%.2 The decline in nutritional status during the course of renal failure might be secondary to reduction in dietary energy intake, dietary restrictions, chronic inflammation, several other comorbid conditions, and the dialysis procedure itself. Several approaches have been used to assess PEW including clinical evaluation and history of weight loss, biochemical markers such as serum albumin, creatinine, lipid levels, body mass index (BMI) and antropometric measurements.3 However, these methods could be misleading in some cases, so a combination of these classical methods with questionnaires such as the Mini Nutritional Assessment (MNA) or body composition analyses such as the dual-energy radiographic absorptiometry (DEXA) and bioelectrical impedance analysis (BIA) could be useful. MNA is an important tool to evaluate PEW and has been recommended by the European Society of Parenteral and Enteral Nutrition guidelines.4 Standard MNA comprises four components and 18 questions; declining food intake over 3 months, weight loss, physical activity, psychological stress or acute disease in the past 3 months, neuropsychological problems, anthropometric measurements, and BMI.5 BIA is a useful, simple, noninvasive technique for assessing body composition and its changes over time both in the healthy and chronic kidney disease (CKD) population.6 The aim of the present study was to analyze reliability of BIA in malnutrition diagnosis by comparing it with standard MNA in a group of 100 patients with ESRD who are waiting for transplantation.
METHODS One hundred patients with ERSD who are waiting for transplantation (62 male; aged 54.3 13.1 years) who had been receiving MHD for at least 6 months and had the ability to complete selfrating scales were enrolled to the study. Patients were selected from a group of 270 MHD patients according to the following exclusion criteria: hospitalization or acute illness in the preceding 6 months, psychiatric treatment in the last 6 months, cancer or tuberculosis history, rheumatologic or chronic inflammatory disease of unknown origin, systemic vasculitis, and chronic liver disease. The study was approved by the ethical committee. All patients who had been receiving bicarbonate dialysis using a low flux synthetic dialyzer with an average blood flow of 300 to 350 mL/min with a Kt/V value during each treatment were maintained at >1.2. Predialysis and immediate postdialysis blood urea nitrogen levels were used to calculate the monthly Kt/V values by means of a single-compartment model of hemodialysis urea kinetics. Monthly assessed biochemical parameters including serum creatinine, albumin, C-reactive protein (CRP), total cholesterol, low-density lipoprotein (LDL) cholesterol and triglyceride levels from the last 6 months were retrospectively collected and measured using standard laboratory techniques. The mean value of each parameter was recorded as final data. A standard MNA and body composition analysis were applied to all patients. Body compositions were measured using the Tanita BC-420MA Body Composition Analyzer (Tanita, Tokyo, Japan). For the BIA measurements, the subject stood in an upright position with bare feet on the analyzer footpads. The impedance between the two feet was measured while
an alternating current (50 kHz and w200 mA) passed through the lower body. Patients were classified into three groups according to MNA scores as PEW (n ¼ 15, score <17), moderate PEW or risk group (n ¼ 49, score 17e23.5), and well-nourished (n ¼ 36, score 24) patients. Statistical analyses were performed by using SPSS software (Statistical Package for the Social Sciences, version 11.0, SSPS Inc, Chicago, Ill, United States). Normality of data was analyzed by using a Kolmogorov-Smirnov test. All numerical variables with normal distribution were expressed as the means standard deviation (SD), whereas variables with skew distribution were expressed as medians and interquartile range. Categorical variables were expressed as percentages and compared by chi-square test. Normally distributed numeric variables were analyzed by independent samples t or one-way analysis of variance (Post-Hoc Tukey) tests. Skew distributed numeric variables were compared by using the Mann-Whitney U and Kruskal Wallis tests. Spearman and Pearson correlation tests were used for correlation anayses. A P value <.05 was considered to be statistically significant.
RESULTS
Patient groups were similar in means of demographic characteristics. Mean duration of being administered MHD treatment was significantly lower in PEW group compared to both of the other groups (Table 1, P ¼ .015). Wellnourished and risk groups had lower CRP and higher albumin levels compared to PEW patients; however, these values were statistically similar in these two groups (Table 1, P ¼ .018, 0.01, respectively). Well-nourished patients had highest, moderate PEW patients had intermediate, and PEW patients had the lowest values for total cholesterol, LDL cholesterol, and triglycerides (P ¼ .038, .02, .025, respectively). Creatinine levels were highest in the wellnourished group and also the moderately PEW /risk group had higher creatinine levels compared to the PEW group (Table 1, P ¼ .004). From the BIA findings we observed that well-nourished patients had the highest fat ratio, fat mass, muscle mass, visceral fat mass, and fat-free mass compared to both the moderate PEW/ risk and PEW groups. Risk group pattients also had higher muscle mass, visceral fat mass, and fat-free mass values compared to the PEW group (Table 1). A correlation analysis revealed that MNA scores were positively correlated with albumin (r ¼ 0.279, P ¼ .005), creatinine (r ¼ 0.197, P ¼ .049), fat mass (r ¼ 0.201, P ¼ .045), muscle mass (r ¼ 0.382, P ¼ .001), visceral fat ratio (r ¼ 0.270, P ¼ .007), and BMI (r ¼ 0.199, P ¼ .047), and in negative correlation with CRP (r ¼ 0.357, P ¼ .0001) levels. DISCUSSION
PEW is a common, severe complication and an important predictor of mortality in ESRD patients. Several approaches such as obtaining the history of weight loss and the determination of biochemical markers such as serum albumin, creatinine, lipid profile, BMI assessment and anthropometric measurements could be used alone or in combination to evaluate PEW.3 Additional to these classical
BIOELECTRICAL IMPEDANCE ANALYSIS
3487
Table 1. Comparison of Mini Nutritional Assessment Groups
Gender (M/F) Etiology (n, %) Diabetes mellitus Hypertension Polycystic kidney Other Unknown Age (y) MHD (y) Albumin (g/dL) Total cholesterol (mg/dL) LDL cholesterol (mg/dL) Triglyceride (mg/dL) Creatinine (mg/dL) CRP (mg/L) Fat ratio (%) Fat mass (kg) Muscle mass (kg) Visceral fat ratio (%) Fat-free mass (kg) BMI
Well-nourished (n ¼ 36)
Risk Group (n ¼ 49)
PEW Group (n ¼ 15)
24/12
34/15
6/9
12, 33.3 6, 16.7 1, 2.8 11, 30.5 6, 16.7 56.4 10.5 8.01 6.77 3.93 0.32 179.7 37.8 102.7 34.1 165 (109) 5.67 (4.4) 9.3 (13.1) 28.1 9.11 21.3 9.6 49.7 9.1 10.4 4.4 52.4 (11.1) 26.3 4.5
11, 22.4 11, 22.4 4, 8.2 15, 30.6 8, 16.4 51.3 13.8 11.4 6.48 3.93 0.35 153.6 44.7 92.8 33.1 134 (91) 4.72 (3.86) 8.6 (15.3) 21.08 10.6 13.8 8.9 44.3 8.4 8.08 4.76 48.4 (14.1) 22.8 4.5
5, 33.3 2, 13.3 e 6, 40 2, 13.4 59.4 14.8 6.86 5.02 3.61 0.53 139.7 38.7 73.8 30.6 98 (74) 3.46 (1.98) 16 (55) 23.8 12.9 14.6 10.2 38.4 8.9 6.66 3.67 40.6 (5.2) 23.1 4.96
P Value
.107
.835
.053 .015 .010 .038 .02 .025 .004 .018 .008 .001 .0001 .019 .001 .003
Abbreviations: PEW, protein-energy wasting; MHD, maintenance hemodialysis; LDL, low-density lipoprotein; CRP, C-reactive protein; BMI, body mass index.
methods, different techniques could also be used for nutritional assessment such as the MNA questionnaire and body composition analyses with DEXA or BIA. In the present study, we analyzed the diagnostic reliability of BIA in 100 patients who were being administered MHD and awaiting transplantation by comparing BIA findings with MNA results. Previous studies had already confirmed that a low serum albumin level is a strong predictor of increased mortality and a marker of for PEW in MHD patients.7e11 Although low serum albumin levels generally reflect poor nutritional status, albumin levels could also be influenced by inhibition of albumin synthesis, increased degradation, losses to dialysate during dialysis, dilution by fluid overload, exchange between intravascular and extravascular compartments, and most important of all by chronic inflammation.12 The mean serum albumin level has been reported as 3.5e4 gr/dL in 50.1% of MHD patients in Turkey in a recent report by the Turkish Nephrology Association.13 In the present study, serum albumin levels were detected between 3.5e4 gr/dL in 60% of the study group so we believe that our study population might also reflect general characteristics of Turkish MHD patient population in means of other nutritional parameters. Lowrie and Lew investigated nutritional status in more than 12,000 MHD patients and reported that serum albumin was the most powerful predictor of malnutrition and mortality.14 In the same study, similar to our results, low pre-dialysis serum creatinine levels predicted PEW; however, they also reported that these levels were not only affected by the residual renal function, but also by large skeletal muscle mass, advanced age, male gender, and large amounts of meat intake.14 MHD patients with
malnutrition often have signs of inflammation, characterized with an increase in plasma CRP levels and a decrease in albumin levels, a finding that we also observed in our study group. We observed that well-nourished MHD patients had lower CRP and higher albumin and cholesterol levels compared to the PEW group. Interestingly, we observed that the well-nourished and moderate PEW/risk groups had similar albumin and CRP levels but the risk group had lower pre-dialysis creatinine levels. We believe this could be a result of the MNA questionnaire method that identifies patients with short-term nutritional problems (eg, decreased food intake in the last 1e2 weeks) as under risk for PEW. However, the clinician should be aware that these intake problems of short duration might not have significant effects on all serum biochemical markers. Another finding that we observed in the PEW group was that these patients had the shortest duration of MHD history whereas moderate the PEW/risk group had the longest duration. We believe that higher malnutrition rates in the first few years of MHD might be related with pre-dialysis malnutrition and increased rates of complications that might be related to vascular access problems (infections, etc). Patients usually need a long time to recover from this MHD starting period. Supporting our hypothesis, we observed that the well-nourished group had an intermediate duration of MHD compared to the other two groups. We believe that after passing the first few years without mortality or any serious complications, malnutrition patients have a period of well-being by recovering from problems associated with ESRD and MHD initiation and then their nutritional status deteriorates again with increased MHD duration.
3488
Assessment of body composition, which is classically divided into fat and fat-free mass, is an important component for providing nutritional care to patients with ESRD. BIA is a simple, inexpensive, quick and noninvasive technique for assessing body composition and its changes over time.15 BIA could be used to assess fluid status and adequacy of dialysis treatment in MHD patients.16e18 From the BIA findings we observed that well-nourished patients had the highest fat ratio, fat mass, muscle mass, visceral fat mass, and fat-free mass compared to both the moderate PEW/risk and the PEW groups. Risk group patients also had higher muscle mass, visceral fat mass, and fat-free mass values compared to the PEW group (Table 1). According to Bellizzi et al, total body water ratio was higher and body cell mass was lower in patients with CKD. Although they could not show a significant difference in either BIA parameters or nutritional indexes, patients with CKD exhibit altered BIA variables from the early phases of renal disease.19 In a recent study, protein malnutrition and energy intake were detected as the most important predictors of dialysis malnutrition score. Energy and protein intake had significant relationship with BMI, fat mass, fat-free mass, and mid-arm muscle circumference (MAMC). Besides, authors reported a significant difference between inflammation and MAMC, fat mass, and fat-free mass.20 Chertoe et al analyzed a group of MHD patients and reported that there was no significant correlations among body cell mass and subjective global assessment scores, serum albumin, serum creatinine levels.21 Kurten et al used BIA in ESRD patients with ongoing dialysis treatment and noted that MHD patients had reduced fat-free mass when compared with other groups.22 In our study we also could not show any correlation between any compartment of BIA and albumin or CRP levels. We also observed that there was a gradual decrease in fat ratio, fat mass, muscle mass, visceral fat mass, and fatfree mass values form the well-nourished patients to moderate/risk group and the PEW group subjects. We believe that BIA is a useful complementary tool to diagnose malnutrition in MHD patients; however, it is not as sensitive as MNA to detect early effects of secondary causes of malnutrition such as chronic inflammation and acute changes in albumin or albumin-like biochemical markers. Although MNA itself is a subjective assessment, the combination of MNA with BIA could provide more accurate nutritional status evaluation results. In conclusion, we recommend that MNA, BIA, anthropometric measures, and biochemical markers be used as complementary diagnostic tools to evaluate the nutritional status of ESRD. REFERENCES 1. Bonanni A, Mannucci I, Verzola D, et al. Protein-energy wasting and mortality in chronic kidney disease. Int J Environ Res Public Health. 2011;8:1631e1654. 2. Heimburger O, Qureshi AR, Blaner WS. Hand-grip muscle strength, lean body mass and plasma proteins as marker of
ERDOGAN, TUTAL, UYAR ET AL nutritional status in patients with chronic renal failure close to start to dialysis therapy. Am J Kidney Dis. 2000;6:1213e1225. 3. Clinical practice guidelines for nutrition in chronic renal failure. K/DOQI, National Kidney Foundation. Am J Kidney Dis. 2000;35:1e140. 4. ESPEN Guidelines for Nutrition Screening. Clin Nutr. 2003; 22:415e421. 5. Vellas B, Guigoz Y, Garry PJ, et al. The mini nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition. 1999;15:116e122. 6. De Lorenzo A, Andreoli A, Matthie J, et al. Predicting body cell mass with bioimpedance by using theoretical methods: a technological review. J Appl Physiol. 1997;85:1542e1558. 7. Teehan BP, Schleifer CR, Brown JM, et al. Urea kinetic analysis and clinical outcome on CAPD: a five year longitudinal study. Adv Perit Dial. 1980;6:181e185. 8. Goldwasser P, Mittman N, Antignani A, et al. Predictors of mortality in hemodialysis lower patients. J Am Soc Nephrol. 1993;3: 1613e1622. 9. Blake PG, Flowerdew G, Blake RM, et al. Serum albumin in patients on continuous ambulatory peritoneal dialysis: predictors and correlations with outcomes. J Am Soc Nephrol. 1993;3: 1501e1507. 10. Rocco MV, Jordan JR, Burkart JM, et al. The efficacy number as a predictor of morbidity and mortality in peritoneal dialysis patients. J Am Soc Nephrol. 1993;4:1184e1191. 11. Davies SJ, Russell L, Bryan J, et al. Comorbidity, urea kinetics, and appetite in continuous ambulatory peritoneal dialysis patients: their interrelationship and prediction of survival. Am J Kidney Dis. 1995;26:353e361. 12. Klein S. The myth of serum albumin as a measure of nutritional status. Gastroenterology. 1990;99:1845e1846. 13. Süleymanlar G, Serdengeçti K, Altiparmak MR, et al. Trends in renal replacement therapy in Turkey, 1996-2008. Turkish Registry of Nephrology, Dialysis, and Transplantation. Am J Kidney Dis. 2011;57(3):456e465. 14. Lowrie EG, Lew NL. Death risk in hemodialysis patients: the predictive value of commonly measured variables and an evaluation of death rate differences between facilities. Am J Kidney Dis. 1990;15:458e482. 15. Walter-Kroker A, Kroker A, Muriel Mattiucci-Guehike M, et al. A practical guide to bioelectrical impedance analysis using the example of chronic obstructive pulmonary disease. Nutri J. 2001; 10(35):1e8. 16. Donadio C, Halim AB, Caprio F, et al. Single- and multifrequency bioelectrical impedance analyses to analyse body composition in maintenance haemodialysis patients: comparison with dual-energy x-ray absorptiometry. Physiol Meas. 2008;29: 517e524. 17. Chertow GM, Lazarus JM, Lew NL, et al. Development of a population-specific regression equation to estimate total body water in hemodialysis patients. Kidney Int. 1997;51:1578e1582. 18. Woodrow G, Oldroyd B, Turney JH, et al. Measurement of total body water by bioelectrical impedance in chronic renal failure. Eur J Clin Nutr. 1996;50:676e681. 19. Bellizzi V, Scalfi L, Terracciano, et al. Early Changes in bioelectrical estimates of body composition in chronic kidney disease. J Am Soc Nephrol. 2006;17:1481e1487. 20. Jahromi SR, Hosseini S, Razeghi E, et al. Malnutrition predicting factors in hemodialysis patients. Saudi J Kidney Dis Transpl. 2010;21(5):846e851. 21. Chertow GM, Lowrie EG, Wilmore DW, et al. Nutritional assessment with bioelectrical impedance analysis in maintenance hemodialysis patients. J Am Soc Nephrol. 1995;6(1):75e81. 22. Kurtin PS, Shapiro AC, Tomita H, et al. Volume status and body composition of chronic dialysis patients: utility of bioelectrical impedance plethysmography. Am J Nephrol. 1990;10:363e367.
D
ESPITE the advancements in current techniques of renal replacement therapy, mortality rates still remain high in patients who have end-stage renal disease (ESRD).1 Protein-energy wasting (PEW), a condition of loss of muscle and visceral protein stores is a common complication and an important predictive factor for morbidity and mortality in ESRD patients. Incidence of PEW in maintenance
From the Departments of Internal Medicine (E.E.) and Nephrology (E.T., M.E.U., Z.B., B.G.D., B.S., S.S.), Baskent University Faculty of Medicine, Ankara, Turkey. Address reprint requests to Emre Tutal, Associate Professor, Department of Nephrology, Baskent University Faculty of Medicine, Fevzi Cakmak Cad. 5. Sokak. No: 48 06490 Bahcelievler, Ankara, Turkey. E-mail: [email protected]
ª 2013 by Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010-1710
0041-1345/13/$esee front matter http://dx.doi.org/10.1016/j.transproceed.2013.08.096
Transplantation Proceedings, 45, 3485e3488 (2013)
3485
ERDOGAN, TUTAL, UYAR ET AL
3486
hemodialysis (MHD) patients varies from 23% to 76%.2 The decline in nutritional status during the course of renal failure might be secondary to reduction in dietary energy intake, dietary restrictions, chronic inflammation, several other comorbid conditions, and the dialysis procedure itself. Several approaches have been used to assess PEW including clinical evaluation and history of weight loss, biochemical markers such as serum albumin, creatinine, lipid levels, body mass index (BMI) and antropometric measurements.3 However, these methods could be misleading in some cases, so a combination of these classical methods with questionnaires such as the Mini Nutritional Assessment (MNA) or body composition analyses such as the dual-energy radiographic absorptiometry (DEXA) and bioelectrical impedance analysis (BIA) could be useful. MNA is an important tool to evaluate PEW and has been recommended by the European Society of Parenteral and Enteral Nutrition guidelines.4 Standard MNA comprises four components and 18 questions; declining food intake over 3 months, weight loss, physical activity, psychological stress or acute disease in the past 3 months, neuropsychological problems, anthropometric measurements, and BMI.5 BIA is a useful, simple, noninvasive technique for assessing body composition and its changes over time both in the healthy and chronic kidney disease (CKD) population.6 The aim of the present study was to analyze reliability of BIA in malnutrition diagnosis by comparing it with standard MNA in a group of 100 patients with ESRD who are waiting for transplantation.
METHODS One hundred patients with ERSD who are waiting for transplantation (62 male; aged 54.3 13.1 years) who had been receiving MHD for at least 6 months and had the ability to complete selfrating scales were enrolled to the study. Patients were selected from a group of 270 MHD patients according to the following exclusion criteria: hospitalization or acute illness in the preceding 6 months, psychiatric treatment in the last 6 months, cancer or tuberculosis history, rheumatologic or chronic inflammatory disease of unknown origin, systemic vasculitis, and chronic liver disease. The study was approved by the ethical committee. All patients who had been receiving bicarbonate dialysis using a low flux synthetic dialyzer with an average blood flow of 300 to 350 mL/min with a Kt/V value during each treatment were maintained at >1.2. Predialysis and immediate postdialysis blood urea nitrogen levels were used to calculate the monthly Kt/V values by means of a single-compartment model of hemodialysis urea kinetics. Monthly assessed biochemical parameters including serum creatinine, albumin, C-reactive protein (CRP), total cholesterol, low-density lipoprotein (LDL) cholesterol and triglyceride levels from the last 6 months were retrospectively collected and measured using standard laboratory techniques. The mean value of each parameter was recorded as final data. A standard MNA and body composition analysis were applied to all patients. Body compositions were measured using the Tanita BC-420MA Body Composition Analyzer (Tanita, Tokyo, Japan). For the BIA measurements, the subject stood in an upright position with bare feet on the analyzer footpads. The impedance between the two feet was measured while
an alternating current (50 kHz and w200 mA) passed through the lower body. Patients were classified into three groups according to MNA scores as PEW (n ¼ 15, score <17), moderate PEW or risk group (n ¼ 49, score 17e23.5), and well-nourished (n ¼ 36, score 24) patients. Statistical analyses were performed by using SPSS software (Statistical Package for the Social Sciences, version 11.0, SSPS Inc, Chicago, Ill, United States). Normality of data was analyzed by using a Kolmogorov-Smirnov test. All numerical variables with normal distribution were expressed as the means standard deviation (SD), whereas variables with skew distribution were expressed as medians and interquartile range. Categorical variables were expressed as percentages and compared by chi-square test. Normally distributed numeric variables were analyzed by independent samples t or one-way analysis of variance (Post-Hoc Tukey) tests. Skew distributed numeric variables were compared by using the Mann-Whitney U and Kruskal Wallis tests. Spearman and Pearson correlation tests were used for correlation anayses. A P value <.05 was considered to be statistically significant.
RESULTS
Patient groups were similar in means of demographic characteristics. Mean duration of being administered MHD treatment was significantly lower in PEW group compared to both of the other groups (Table 1, P ¼ .015). Wellnourished and risk groups had lower CRP and higher albumin levels compared to PEW patients; however, these values were statistically similar in these two groups (Table 1, P ¼ .018, 0.01, respectively). Well-nourished patients had highest, moderate PEW patients had intermediate, and PEW patients had the lowest values for total cholesterol, LDL cholesterol, and triglycerides (P ¼ .038, .02, .025, respectively). Creatinine levels were highest in the wellnourished group and also the moderately PEW /risk group had higher creatinine levels compared to the PEW group (Table 1, P ¼ .004). From the BIA findings we observed that well-nourished patients had the highest fat ratio, fat mass, muscle mass, visceral fat mass, and fat-free mass compared to both the moderate PEW/ risk and PEW groups. Risk group pattients also had higher muscle mass, visceral fat mass, and fat-free mass values compared to the PEW group (Table 1). A correlation analysis revealed that MNA scores were positively correlated with albumin (r ¼ 0.279, P ¼ .005), creatinine (r ¼ 0.197, P ¼ .049), fat mass (r ¼ 0.201, P ¼ .045), muscle mass (r ¼ 0.382, P ¼ .001), visceral fat ratio (r ¼ 0.270, P ¼ .007), and BMI (r ¼ 0.199, P ¼ .047), and in negative correlation with CRP (r ¼ 0.357, P ¼ .0001) levels. DISCUSSION
PEW is a common, severe complication and an important predictor of mortality in ESRD patients. Several approaches such as obtaining the history of weight loss and the determination of biochemical markers such as serum albumin, creatinine, lipid profile, BMI assessment and anthropometric measurements could be used alone or in combination to evaluate PEW.3 Additional to these classical
BIOELECTRICAL IMPEDANCE ANALYSIS
3487
Table 1. Comparison of Mini Nutritional Assessment Groups
Gender (M/F) Etiology (n, %) Diabetes mellitus Hypertension Polycystic kidney Other Unknown Age (y) MHD (y) Albumin (g/dL) Total cholesterol (mg/dL) LDL cholesterol (mg/dL) Triglyceride (mg/dL) Creatinine (mg/dL) CRP (mg/L) Fat ratio (%) Fat mass (kg) Muscle mass (kg) Visceral fat ratio (%) Fat-free mass (kg) BMI
Well-nourished (n ¼ 36)
Risk Group (n ¼ 49)
PEW Group (n ¼ 15)
24/12
34/15
6/9
12, 33.3 6, 16.7 1, 2.8 11, 30.5 6, 16.7 56.4 10.5 8.01 6.77 3.93 0.32 179.7 37.8 102.7 34.1 165 (109) 5.67 (4.4) 9.3 (13.1) 28.1 9.11 21.3 9.6 49.7 9.1 10.4 4.4 52.4 (11.1) 26.3 4.5
11, 22.4 11, 22.4 4, 8.2 15, 30.6 8, 16.4 51.3 13.8 11.4 6.48 3.93 0.35 153.6 44.7 92.8 33.1 134 (91) 4.72 (3.86) 8.6 (15.3) 21.08 10.6 13.8 8.9 44.3 8.4 8.08 4.76 48.4 (14.1) 22.8 4.5
5, 33.3 2, 13.3 e 6, 40 2, 13.4 59.4 14.8 6.86 5.02 3.61 0.53 139.7 38.7 73.8 30.6 98 (74) 3.46 (1.98) 16 (55) 23.8 12.9 14.6 10.2 38.4 8.9 6.66 3.67 40.6 (5.2) 23.1 4.96
P Value
.107
.835
.053 .015 .010 .038 .02 .025 .004 .018 .008 .001 .0001 .019 .001 .003
Abbreviations: PEW, protein-energy wasting; MHD, maintenance hemodialysis; LDL, low-density lipoprotein; CRP, C-reactive protein; BMI, body mass index.
methods, different techniques could also be used for nutritional assessment such as the MNA questionnaire and body composition analyses with DEXA or BIA. In the present study, we analyzed the diagnostic reliability of BIA in 100 patients who were being administered MHD and awaiting transplantation by comparing BIA findings with MNA results. Previous studies had already confirmed that a low serum albumin level is a strong predictor of increased mortality and a marker of for PEW in MHD patients.7e11 Although low serum albumin levels generally reflect poor nutritional status, albumin levels could also be influenced by inhibition of albumin synthesis, increased degradation, losses to dialysate during dialysis, dilution by fluid overload, exchange between intravascular and extravascular compartments, and most important of all by chronic inflammation.12 The mean serum albumin level has been reported as 3.5e4 gr/dL in 50.1% of MHD patients in Turkey in a recent report by the Turkish Nephrology Association.13 In the present study, serum albumin levels were detected between 3.5e4 gr/dL in 60% of the study group so we believe that our study population might also reflect general characteristics of Turkish MHD patient population in means of other nutritional parameters. Lowrie and Lew investigated nutritional status in more than 12,000 MHD patients and reported that serum albumin was the most powerful predictor of malnutrition and mortality.14 In the same study, similar to our results, low pre-dialysis serum creatinine levels predicted PEW; however, they also reported that these levels were not only affected by the residual renal function, but also by large skeletal muscle mass, advanced age, male gender, and large amounts of meat intake.14 MHD patients with
malnutrition often have signs of inflammation, characterized with an increase in plasma CRP levels and a decrease in albumin levels, a finding that we also observed in our study group. We observed that well-nourished MHD patients had lower CRP and higher albumin and cholesterol levels compared to the PEW group. Interestingly, we observed that the well-nourished and moderate PEW/risk groups had similar albumin and CRP levels but the risk group had lower pre-dialysis creatinine levels. We believe this could be a result of the MNA questionnaire method that identifies patients with short-term nutritional problems (eg, decreased food intake in the last 1e2 weeks) as under risk for PEW. However, the clinician should be aware that these intake problems of short duration might not have significant effects on all serum biochemical markers. Another finding that we observed in the PEW group was that these patients had the shortest duration of MHD history whereas moderate the PEW/risk group had the longest duration. We believe that higher malnutrition rates in the first few years of MHD might be related with pre-dialysis malnutrition and increased rates of complications that might be related to vascular access problems (infections, etc). Patients usually need a long time to recover from this MHD starting period. Supporting our hypothesis, we observed that the well-nourished group had an intermediate duration of MHD compared to the other two groups. We believe that after passing the first few years without mortality or any serious complications, malnutrition patients have a period of well-being by recovering from problems associated with ESRD and MHD initiation and then their nutritional status deteriorates again with increased MHD duration.
3488
Assessment of body composition, which is classically divided into fat and fat-free mass, is an important component for providing nutritional care to patients with ESRD. BIA is a simple, inexpensive, quick and noninvasive technique for assessing body composition and its changes over time.15 BIA could be used to assess fluid status and adequacy of dialysis treatment in MHD patients.16e18 From the BIA findings we observed that well-nourished patients had the highest fat ratio, fat mass, muscle mass, visceral fat mass, and fat-free mass compared to both the moderate PEW/risk and the PEW groups. Risk group patients also had higher muscle mass, visceral fat mass, and fat-free mass values compared to the PEW group (Table 1). According to Bellizzi et al, total body water ratio was higher and body cell mass was lower in patients with CKD. Although they could not show a significant difference in either BIA parameters or nutritional indexes, patients with CKD exhibit altered BIA variables from the early phases of renal disease.19 In a recent study, protein malnutrition and energy intake were detected as the most important predictors of dialysis malnutrition score. Energy and protein intake had significant relationship with BMI, fat mass, fat-free mass, and mid-arm muscle circumference (MAMC). Besides, authors reported a significant difference between inflammation and MAMC, fat mass, and fat-free mass.20 Chertoe et al analyzed a group of MHD patients and reported that there was no significant correlations among body cell mass and subjective global assessment scores, serum albumin, serum creatinine levels.21 Kurten et al used BIA in ESRD patients with ongoing dialysis treatment and noted that MHD patients had reduced fat-free mass when compared with other groups.22 In our study we also could not show any correlation between any compartment of BIA and albumin or CRP levels. We also observed that there was a gradual decrease in fat ratio, fat mass, muscle mass, visceral fat mass, and fatfree mass values form the well-nourished patients to moderate/risk group and the PEW group subjects. We believe that BIA is a useful complementary tool to diagnose malnutrition in MHD patients; however, it is not as sensitive as MNA to detect early effects of secondary causes of malnutrition such as chronic inflammation and acute changes in albumin or albumin-like biochemical markers. Although MNA itself is a subjective assessment, the combination of MNA with BIA could provide more accurate nutritional status evaluation results. In conclusion, we recommend that MNA, BIA, anthropometric measures, and biochemical markers be used as complementary diagnostic tools to evaluate the nutritional status of ESRD. REFERENCES 1. Bonanni A, Mannucci I, Verzola D, et al. Protein-energy wasting and mortality in chronic kidney disease. Int J Environ Res Public Health. 2011;8:1631e1654. 2. Heimburger O, Qureshi AR, Blaner WS. Hand-grip muscle strength, lean body mass and plasma proteins as marker of
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