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Increase in BMI Over Time Is Associated With Fluid Overload and Signs of Wasting in Incident Peritoneal Dialysis Patients
ORIGINAL RESEARCH
Increase in BMI Over Time Is Associated With Fluid Overload and Signs of Wasting in Incident Peritoneal Dialysis Patients Viviana Teixeira Henriques, RD, PhD,* Edson Zangiacomi Martinez, DSc, PhD,* Jose Carolino Divino-Filho, MD, PhD,† Roberto Pecoits-Filho, MD, PhD,‡ and Jose Abr~ao Cardeal da Costa, MD, PhD,* on behalf of the Brazilian Peritoneal Dialysis Multicenter Study BRAZPD Group Objectives: Peritoneal dialysis (PD) patients may suffer changes in nutritional status after starting PD. Several markers can be used to evaluate these modifications, such as body mass index (BMI), serum albumin, and serum creatinine. Fluid overload should be considered because it can overestimate or underestimate nutritional status. The objective of this study was to evaluate the BMI changes over time in incident PD patients and identify interactions among BMI, signs of fluid overload, serum albumin, and serum creatinine. Design: The study included a cohort of 1,997 incident PD patients of the BRAZPD recruited from 2004 to 2007. Sociodemographic data and BMI classification were obtained at baseline. The evolutions of BMI and body weight were assessed over a period of 29 months. Changes in the evolution were analyzed when a patient presented with albumin , 3.8 g/dL, creatinine , 7.0 mg/dL, or the presence of edema. Data analysis was performed using linear mixed-effects regression models as the main statistical procedure. Results: BMI increased over time (29 months) by an average of 0.05 kg/m2 per month, and body weight increased by 0.11 kg/month for a total increase of 3.08 kg. BMI decreased by 0.12 kg/m2 in the presence of albumin , 3.8 g/dL and by 0.38 kg/m2 in the presence of creatinine , 7.0 mg/dL. BMI increased by 0.61 kg/m2 in the presence of edema. BMI increased in the presence of edema and albumin , 3.8 mg/dL or edema and creatinine , 7.0 mg/dL. Conclusions: There is a mean increase in the BMI of incident PD patients over time, and these changes may be, at least partly, due to fluid overload, leading to distortions of body weight. When the patients presented with lower serum albumin or creatinine levels, the BMI values were reduced, suggesting that a reduction in lean mass and an increase in fat mass may be occurring in these patients. Ó 2013 by the National Kidney Foundation, Inc. All rights reserved.
Introduction
T
HE NUTRITIONAL STATUS of patients on renal replacement therapy (RRT) is important because of its correlation with the risk of morbidity and mortality. The initial nutritional status of dialysis patients can be influenced by various physiological and metabolic alterations, which must be evaluated over the duration of therapy. Several markers of nutritional status can be used, including
* Universidade de S~ao Paulo/Faculdade de Medicina de Ribeir~ao Preto, Ribeir~ao Preto, S~ao Paulo, Brazil. † Division of Renal Medicine, CLINTEC, Karolinska Institutet, Stockholm, Sweden. ‡ School of Medicine, Pontifıcia Universidade Catolica do Parana, Curitiba, Parana, Brazil. Financial Disclosure: During the data collection and analysis, J.C.D.-F. was employed by Baxter; his employment by Baxter ended on March 31, 2011. See Acknowledgments on page e56. The other authors declare that they have no relevant financial interests. Address correspondence to Viviana Teixeira Henriques, RD, PhD, Av. dos Bandeirantes 3900, Rua Pedreira de Freitas, Casa 13-Universidade de S~ao Paulo, CEP: 14040-900, Ribeir~ao Preto, S~ao Paulo, Brazil. E-mail:
[email protected] Ó 2013 by the National Kidney Foundation, Inc. All rights reserved. 1051-2276/$36.00 http://dx.doi.org/10.1053/j.jrn.2012.08.008
Journal of Renal Nutrition, Vol 23, No 3 (May), 2013: pp e51-e57
body mass index (BMI),1 serum albumin,2 and serum creatinine.3 In incident PD patients, the BMI can change over time because of modifications in body weight, including fat and lean mass; the latter includes muscle and hydration status.4 Weight changes in peritoneal dialysis (PD) patients can be influenced by dextrose contained in the dialysis solution, which is absorbed by the peritoneal membrane and serves as a source of energy for the organism. If the quantity of ingested food is not modified, then there may be an excess of energy, leading to weight gain.1 Genetic factors involved in basal metabolism may also provoke changes in body weight.5 The metabolism of patients on RRT is usually altered, presenting greater insulin resistance as well as metabolic acidosis.6 Additionally, endotoxemia, caused by volume overload, may lead to translocation of bacteria from the gut into the circulation.7 These changes cause inflammation, catabolism, and loss of lean and/or fat mass. The loss of muscle causes a decrease in serum creatinine.8 Albumin synthesis may also be affected because it depends on hepatic function, which responds to acute or chronic inflammation by producing positive acute phase proteins and e51
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HENRIQUES ET AL
reducing serum albumin levels.9 In addition, insufficient food intake exacerbates the reduction of serum albumin. Incident PD patients may present with increased body fat and decreased lean mass, leading to sarcopenic obesity. However, edema should always be considered because it can overestimate this nutritional status.10 We hypothesized that BMI increases over time in patients on PD, that hypervolemia may be a confounding factor for defining malnutrition in an edematous state, and that monitoring other markers of nutritional status may identify patients with a high BMI and sarcopenic obesity. The objective of the study presented here was to monitor BMI changes over time in incident PD patients and to identify interactions among BMI, signs of fluid overload, serum albumin, and serum creatinine.
Methods This was a prospective, national, multicenter cohort study conducted in Brazil (BRAZPD). A detailed description of BRAZPD has been previously reported.11 The study was approved by the ethics committee of each participating institution, and the protocol was approved by the ethics committee of the University Hospital, School of Medicine of Ribeir~ao Preto, University of S~ao Paulo (HCFMRP-USP).
Patients and Study Design The study was conducted in 1,997 incident PD patients receiving continuous ambulatory peritoneal dialysis (CAPD) or automated peritoneal dialysis (APD) at 114 public and private RRT centers in all regions of Brazil. All adult ($18 years) patients who began PD between December 2004 and October 2007, who remained at least 90 days on PD and provided complete information on body weight and height, were included in the study (Fig. 1). The data were collected monthly at the various centers using the PDnet software developed specifically for the BRAZPD study.11
Social and Demographic Data Baseline social and demographic data included the following: age (years), elderly status (.65 years old), gender, race (white, non-white), primary cause of renal disease (chronic glomerulonephritis, hypertensive renal disease, diabetic nephropathy, other, unknown), PD modality (CAPD or APD), family income (no income, #2, 3-5, 5-10, 10-20, .20 minimum wages per month [U.S. $150.42 {U.S. $4.94/day}), Brazilian region (northern, midwestern, northeastern, southern, eastern), educational level (illiterate, elementary, secondary, and higher), original treatment (hemodialysis, kidney transplant, unknown, PD as a first option), and diabetes (presence or absence). Anthropometric Data Weight (kilograms) was determined monthly, and height (centimeters) was measured at baseline. BMI (kilograms per square meter) was calculated and classified according to the World Health Organization criteria.12 Laboratory and Clinical Data Serum albumin was collected quarterly. The patients were classified according to cutoff points as having albumin depletion (,3.8 g/dL) or normal albumin ($3.8 g/dL). Serum creatinine was determined monthly and divided into two groups: ,7.0 mg/dL or $7.0 mg/dL. The cutoff points for serum albumin and serum creatinine were set according to the median of each of the variables. Fluid overload was defined by a monthly clinical evaluation (presence or absence of edema). Statistical Methods The analyses were performed using the SAS statistical package, version 9.2 (SAS Institute Inc., Cary, NC).13 The percentages, means, and standard deviations were used to summarize the variables of interest. Linear mixed-effects regression models (SAS proc mixed)13 were used to identify the evolution of BMI and weight over time and to determine the effects of the
Figure 1. Participants in the BRAZPD study. Data set for analysis, including patients in the BRAZPD study starting PD in the period 2004-2007.
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INCREASE OF BMI IS AFFECTED BY FLUID OVERLOAD
following factors: serum albumin level, serum creatinine level, and fluid overload. A random-subject effect was included in this model, along with fixed effects, to allow for modeling of the within-subject correlation that may arise because of the longitudinal nature of the data.14
Results The sociodemographic characteristics of the patients are listed in Table 1. Of the patients studied, 53.8% were from the eastern region, 11.8% were illiterate, and most earned up to 5 minimum wages. These percentages were similar when the patients were distributed by gender and PD modality. Most of the patients were transferred from hemodialysis. Table 2 presents the mean values of age as well as anthropometric and laboratory variables. At the start of therapy, the mean BMI was 24.39 6 4.73 kg/m2. The nutritional statuses of the patients were classified according to BMI,11 serum albumin, and serum creatinine and simultaneously by BMI and serum albumin depletion, BMI and serum creatinine , 7.0 mg/dL, BMI and serum albumin depletion, and serum creatinine , 7.0 mg/dL. These statuses at baseline are presented in Table 3. The depletions of serum albumin and serum creatinine , 7.0 mg/dL were present mainly in patients classified as normal and overweight. At baseline, a total of 559 patients (28% of the total population) presented with edema. The models used to assess the evolution of BMI and body weight over the 29-month period were applied to 1,101 patients (Table 4 and Table 5, respectively). The results showed a mean basal BMI value of 24.8 kg/m2, with a mean increase of 0.05 kg/m2 per month over a period of 29 months in patients with serum albumin . 3.8 g/dL, serum creatinine . 7.0 mg/dL, and no edema. The model used for the evolution of body weight estimated a mean increase of 0.11 kg/month and a total gain of 3.08 kg for the entire study period with respect to the mean basal value of 65.15 kg. During months in which the patients showed serum albumin levels ,3.8 g/dL, a change in the evolution of the BMI occurred, suggesting a mean reduction in the BMI of 0.12 kg/m2. In addition, the BMI values seemed to decrease by an average of 0.38 kg/m2 during months in which the patients presented with serum creatinine levels ,7.0 mg/dL. A decrease in body weight was also observed when serum albumin levels were ,3.8 g/dL and serum creatinine levels were ,7.0 mg/dL, with a mean reduction of 0.39 and 1.22 kg, respectively. A change in the evolution of BMI and body weight was also observed in the presence of edema, with a mean increase of 0.61 kg/m2 and 1.47 kg, respectively. When patients had edema and serum albumin , 3.8 g/dL, the BMI increased by an average of 0.23 kg/m2 and body weight increased by 0.64 kg. An increase of
Table 1. Sociodemographic Characteristics of Incident PD Patients—Brazil 2004-2007 Variable Gender Male/female Regions Northern Northeastern Midwestern Eastern Southern Race White/Non-white Primary kidney disease Chronic glomerulonephritis Hypertensive renal disease Diabetic nephropathy Others Unknown PD modality APD/CAPD Educational level Illiterate Elementary Secondary Higher Income (minimal wages per month) Without income #2 3-5 5-10 10-20 .20 Elderly (.65 y) Yes/no Original treatment Hemodialysis Kidney transplant Unknown PD as a first option Diabetic Yes/no
Frequency
%
919/1,078
46.0/54.0
94 384 71 1,074 374
4.7 19.2 3.6 53.8 18.7
1,240/757
62.0/38.0
219 479 758 262 279
11.0 24.0 38.0 13.0 14.0
998/999
49.0/51.0
235 1,111 495 156
11.8 55.6 24.8 7.8
31 689 872 321 67 17
1.6 34.5 43.7 16.0 3.4 0.9
712/1,285
35.6/64.4
1,371 12 6 608
68.6 0.6 0.3 30.4
842/1,155
42.2/57.8
0.07 kg/m2 in BMI and 0.17 kg in body weight also appeared with an interaction between edema and serum creatinine , 7.0 mg/dL.
Table 2. Age and Anthropometric and Laboratory Variables of Incident PD Patients at Baseline—Brazil 2004-2007 Variable Age (y) Weight (kg) Height (cm) BMI (kg/m2) Albumin (g/dL) Creatinine (mg/dL)
Frequency
Mean
Standard Deviation
1,997 1,997 1,997 1,997 531 1,766
58.73 63.98 161.69 24.39 4.20 7.67
15.81 14.24 9.67 4.73 1.32 3.60
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HENRIQUES ET AL
Table 3. Nutritional Status of Incident PD Patients—Brazil 2004-2007 Frequency/ % (baseline)
Variable BMI (kg/m2) Malnutrition Normal Overweight Obesity Total Serum albumin (g/dL) Depletion Normal Total Serum creatinine (mg/dL) ,7.0 $7.0 Total Albumin depletion and BMI (kg/m2) Malnutrition Normal Overweight Obesity Total Serum creatinine , 7.0 mg/dL and BMI (kg/m2) Malnutrition Normal Overweight Obesity Total Albumin depletion serum creatinine , 7.0 mg/dL and BMI (kg/m2) Malnutrition Normal Overweight Obesity Total
#18.4 18.5-24.9 25.0-29.9 $30.0 -
170/8.5 1,035/51.8 564/28.2 228/11.4 1,997/100
,3.8 $3.8 -
261/49.1 270/50.8 531/100
,7.0 $7.0 -
864/48.9 901/51.0 1,765/100
#18.4 18.5-24.9 25.0-29.9 $30.0 -
25/9.6 141/54.0 69/26.4 26/10.0 261/100
#18.4 18.5-24.9 25.0-29.9 $30.0 -
80/9.3 458/53.0 221/25.5 105/12.2 864/100
#18.4 18.5-24.9 25.0-29.9 $30.0 -
12/9.2 67/51.1 35/26.8 17/13.0 131/100
Data from reference.12
Discussion BMI has limitations for the evaluation of nutritional status because it does not represent body composition or distinguish between fat and lean mass. It is an indicator of body fat, but it does not express the distribution of body fat (visceral or subcutaneous). However, it is widely used in epidemiological studies because the measurement is relatively simple and important for assessing the risk of morbidity and mortality.15,16 Changes in BMI can occur during PD therapy. BMI is one of the variables found in the BRAZPD study. In the study presented here, according to BMI classification at baseline, most patients were normal, followed by overweight, obese, and malnourished. The same sequence of BMI classification was observed by Snyder et al.17 using the same cutoff points. In this population of PD patients, the BMI and body weight evolutions presented a linear mean increase over
the 29 months of the study. This weight gain may have been influenced by several factors, among them the extra energy provided by dextrose in the dialysate, which was absorbed through the peritoneal membrane. Although our analysis did not include this result, the relationship has been suggested in previous reports.1,18,19 However, Jakic et al.20 did not find a relationship between weight gain and the caloric contribution of glucose absorbed from the dialysate. Another hypothesis for the increase in body weight involves less restriction of food intake for PD patients when compared with those following conservative treatment. We also considered that the weight gain of some of the patients studied was perhaps due to genetic factors related to the reduction of basal metabolism. On the basis of their results, Nordfords et al.5 suggested that mitochondrial uncoupling protein 2 polymorphisms contribute to variations in body composition and adipose tissue accumulation in patients treated with PD. The lack of body composition variables is a limitation of the study presented here. We can confirm an increase in body weight and BMI; however, we cannot conclude whether this was due to a gain of lean mass and/or fat mass (subcutaneous or visceral). Choi et al.4 detected a linear increase in body weight due to subcutaneous and visceral fat during the first 6 months of PD. However, from 6 to 12 months, the weight gain was lower and practically stabilized. Vasselai et al.1 detected a 53% increase in body fat after 12 months of PD compared with baseline. An increase in BMI and body weight is suggested in edematous patients in our study. Thus, a patient classified as malnourished who gains weight because of fluid overload may be reclassified as normal, a normal patient as overweight, and an overweight patient as obese, perhaps with little or no change in adipose tissue. Because edema is often classified in a subjective manner, an edematous state may overestimate the nutritional status and should therefore be taken into consideration in studies involving the evaluation of nutritional status to avoid systematic distortion of the relationship between BMI and fat mass. Data regarding the classification of edema, whether edema was subtracted, and how much was subtracted from body weight are not included in the BRAZPD study. Renal patients usually have insulin resistance and inflammation.5 Studies21,22 have detected an association among the inflammatory process, malnutrition, and hypervolemia. Hypervolemia characterized by the presence of edema may interfere with body weight.23 In the study by Jakic et al.,20 weight gain in patients on PD was caused, at least in part, by fluid retention. In our models, when a patient presented with albumin depletion, a reduction in mean BMI and body weight was estimated. Low serum albumin levels may be due to the protein catabolism caused by the inflammatory process, which, together with the deterioration of nutritional status, reduces albumin synthesis.9 Catabolism may lead to a reduction of muscle mass, affecting body weight, although the
e55
INCREASE OF BMI IS AFFECTED BY FLUID OVERLOAD Table 4. Linear Mixed-effects Regression Model–evolution of BMI (kg/m2) of Incident PD Patients—Brazil 2004-2007 Variable Fixed effects BMI (baseline) Time (each month) Albumin depletion vs. normal Creatinine , 7.0 mg/dL vs. $7.0 mg/dL Fluid overload yes vs. no Interaction effects Fluid overload 3 albumin depletion Fluid overload 3 creatinine , 7.0 mg/dL Patients (n) Total period (mo)
Estimate
24.80 0.05 20.12 20.38 0.61 0.23 0.07 1,101 29
correlation of lean mass with BMI is not strong because this index is more correlated to fat mass.24,25 Albumin is considered to be a powerful health indicator as observed in the NECOSAD study,2 in which a 1-g/dL reduction in serum albumin levels increased the risk of mortality by 38% in patients on PD. A reduction in mean BMI and body weight was also suggested in our study when a patient presented with serum creatinine , 7.0 mg/dL. Because creatinine is a nitrogenated nonprotein organic compound formed from the dehydration of creatine in skeletal muscle, a reduction may be the result of muscle mass loss.3,8 Serum creatinine levels are altered in patients on dialysis. However, lower serum creatinine levels are detected in malnourished patients,3 and levels below the specific cutoff point suggest an association of creatinine with lean body mass and survival.3,26 On the other hand, Stosovic et al.10 found a poor relationship between mid-arm muscle circumference and serum creatinine and stated that creatinine concentration depends on the balance between production and elimination. Approximately two-thirds of the BRAZPD patients had undergone hemodialysis as a first therapy and then were transferred to PD, which means that creatinine elimination by residual renal function was most likely not present. Other factors, such as low food intake and reduced physical activity, may also cause reduced muscle mass and serum creatinine levels.8
Standard Error
t
P
0.16 0.006 0.09 0.11 0.15
7.97 21.30 23.31 3.98
.01 .19 .01 .01
1.34 0.43
.17 .66
0.16 0.17
An increase in BMI and body weight was suggested when the effects of the synergistic interaction between albumin depletion and edema or between serum creatinine levels ,7.0 mg/dL and edema were analyzed. On the basis of the results of these interactions, we could possibly infer that edema reduces the serum albumin and/or serum creatinine values and that these biochemical values may not be a result of depletion of lean body mass. However, as a result of the reduced oncotic pressure associated with low plasma albumin, fluid leakage occurs from the plasma fluid to the interstitial compartment.27,28 In addition, hypervolemia can overestimate the nutritional status of these patients and mask the reduction of lean mass, as previously discussed. Volume overload leads to an impaired intestinal barrier, increased permeability in the gut, and bacterial translocation.7 In uremia, the gut bacterial population is increased,29 which can lead to endotoxemia. Additionally, chronic inflammation may occur in patients with edema, contributing to protein catabolism and malnutrition, which in turn lead to atrophy of intestinal mucosa and endotoxemia.7 Cheng et al.30 concluded that deterioration in fluid status is associated with malnutrition. According to Fein et al.,31 fluid overload is a risk factor independent of long-term survival in PD patients. Ferreira-Filho et al.32 observed an initial blood pressure level reduction in the first five months and stabilization from five to twelve months in the same cohort of incident BRAZPD patients. The edematous group
Table 5. Linear Mixed-effects Regression Model: Evolution of Body Weight (kg) of Incident PD Patients—Brazil 2004-2007 Variable Fixed effects Body weight (baseline) Time (each month) Albumin depletion vs. normal Creatinine , 7.0 mg/dL vs. $7.0 mg/dL Fluid overload yes vs. no Interaction effects Fluid overload 3 albumin depletion Fluid overload 3 creatinine , 7.0 mg/dL Patients (n) Total period (mo)
Estimate
65.15 0.11 20.39 21.22 1.47 0.64 0.17 1,101 29
Standard Error
t
P
0.47 0.015 0.25 0.30 0.40
7.38 21.58 24.00 3.61
0.01 0.11 0.01 0.01
1.41 0.39
0.15 0.69
0.45 0.45
e56
HENRIQUES ET AL
exhibited higher blood pressure levels than the group without edema during the follow-up. Although we do not know the peritoneal membrane transport characteristics of patients, patients with a hightransporter peritoneal membrane may have a greater risk of malnutrition, related to an increased loss of creatinine and proteins (e.g., albumin) through the dialysate. In addition, there may be a high absorption of glucose at the peritoneal level, contributing to early satiety and poor food intake.33,34 It was not possible to evaluate data regarding the effectiveness of the dialysis because of the low number of patients with this information. In conclusion, we present data showing that although BMI may increase over time in patients on PD, these changes are, at least in part, due to fluid overload. In addition, when patients presented with lower serum albumin or serum creatinine levels, the BMI values were reduced, suggesting that a reduction of lean mass and an increase in fat mass may be occurring in these patients. In some patients, the development of wasting, even in the presence of high BMI, may occur. To clarify the assumptions made by the data analyzed in our study, body composition should be evaluated in future studies.
Practical Application Edema is often present in patients with PD and may mask the results. Edema should be included in analyses of BMI. BMI is a useful tool in epidemiological studies when combined with other variables, generating hypotheses for clinical studies.
Acknowledgments
The authors thank Coordenac¸~ao de Aperfeic¸oamento de Pessoal de Nıvel Superior (CAPES), Brazil. This study was financed by Baxter Healthcare, Brazil. J.C.D.F. was employed by Baxter Healthcare when this study was performed.
References 1. Vasselai P, Kamimura MA, Bazanelli AP, et al. Factors associates with body-fat changes in prevalent peritoneal dialysis patients. J Ren Nutr. 2008;18:363-369. 2. Mutsert R, Grootendorst DC, Indemans F, Boeschoten EW, Krediet RT, Dekker FW. Association between serum albumin and mortality in dialysis patients is partly explained by inflammation, and not by malnutrition. J Ren Nutr. 2009;19:127-135. 3. Avram MM, Bonomini LV, Sreedhara R, Mittman N. Predictive value of nutritional markers (albumin, creatinine, cholesterol, and hematocrit) for patients on dialysis for up to 30 years. Am J Kidney Dis. 1996;28:910-917. 4. Choi SJ, Kim NR, Hong SA, et al. Changes in body fat mass in patients after starting peritoneal dialysis. Perit Dial Int. 2011;31:67-73. 5. Nordfords L, Heimburger O, Lonnqvist F, et al. Fat tissue accumulation during peritoneal dialysis is associated with a polymorphism in uncoupling protein 2. Kidney Int. 2000;57:1713-1719. 6. O’Sullivan AJ, Kelly JJ. Insulin resistance and protein catabolism in nondiabetic hemodialysis patients. Kidney Int. 2007;71:98-100. 7. Hauser AB, Stinghen AE, Gonc¸alves SM, Bucharles S, Pecoits-Filho R. A gut feeling on endotoxemia: causes and consequences in chronic kidney disease. Nephron Clin Pract. 2011;118:165-172.
8. Szeto C, Kong J, Wu AKL, Wong TYH, Wang AYM, Li PKT. The role of lean body mass as a nutritional index in Chinese peritoneal dialysis patients—comparison of creatinine kinetics method and anthropometric method. Perit Dial Int. 2000;20:708-713. 9. Whicher J, Spence C. When is serum albumin worth measuring? Ann Clin Biochem. 1987;24:572-580. 10. Stosovic M, Stanojevic M, Simic-Ogrizovic S, Jovanovic D, Djukanovic L. The predictive value of anthropometric parameters on mortality in haemodialysis patients. Nephrol Dial Transplant. 2011;26:1367-1374. 11. Fernandes N, Bastos MG, Cassi HV, et al. The Brazilian Peritoneal Dialysis Multicenter Study (BRAZPD): characterization of the cohort. Kidney Int. 2008;73:S145-S151. 12. World Health Organization. Obesity: preventing and managing the global epidemic. In: Report of WHO Consultation on Obesity. Geneva, Switzerland: World Health Organization; 1997. 13. Statistical Analysis System Institute. Advanced General Linear Models with Emphasis on Mixed Models. Cary, NC: Statistical Analysis System Institute; 1996:614. 14. Burnham KP, Anderson DR, eds. Model Selection and Multimodel Inference: a Practical Information-Theoretic Approach. 2nd ed. New York, NY: Springer-Verlag; 2002. 2002. 15. Heng A, Cano NJM. Nutritional problems in adult patients with stage 5 chronic kidney disease on dialysis (both hemodialysis and peritoneal dialysis). Nephrol Dial Transplant. 2010;3:109-117. 16. Cervi A, Franceschini SCC, Priore SE. Critical analysis of the use of the body mass index for the elderly. Rev Nutr. 2005;18:765-775. 17. Snyder JJ, Foley RN, Gilbertson DT, Vonesh EF, Collins AJ. Body size and outcomes on peritoneal dialysis in the United States. Kidney Int. 2003;64:1838-1844. 18. Bouma SF, Dwyer JT. Glucose absorption and weight change in 18 months of continuous ambulatory peritoneal dialysis. J Am Diet Assoc. 1984;84:194-197. 19. Jolly S, Chatatalsingh C, Bargman J, Vas S, Chu M, Oreopoulos DG. Excessive weight gain during peritoneal dialysis. Int J Artif Organs. 2001;24: 197-202. 20. Jakic M, Stipanic S, Mihaljevic D, et al. The impact of glucose absorbed from dialysis solution on body weight gain in peritoneal dialysis treated patients. J Ren Nutr. 2008;18:323-331. 21. Demirci MS, Demirci C, Ozdogan O, et al. Relations between malnutrition-inflamamation-atherosclerosis and volume status. The usefulness of bioimpedance analysis in peritoneal dialysis patients. Nephrol Dial Transplant. 2011;26:1708-1716. 22. Vicente-Martinez M, Martınez-Ramırez L, Mu~ noz R, et al. Inflammation in patients on peritoneal dialysis is associated with increased extracellular fluid volume. Arch Med Res. 2004;35:220-224. 23. Abbott KC, Glanton CW, Trespalacios FC, et al. Body mass index, dialysis modality and survival: analysis of the United States Renal Data System Dialysis Morbidity and Mortality Wave II Study. Kidney Int. 2004;65: 597-605. 24. Nagaya T, Yoshida H, Takahaski H, Matsuda Y, Kawai M. Body mass index (weight/height2) or percentage body fat by bioelectrical impedance analysis: Which variable better reflects serum lipid profile? Int J Obes. 1999;23:771-774. 25. Micozzi MS, Harris TM. Age variations in the relation of body mass indices to estimates of body fat and muscle mass. Am J Phys Anthropol. 1990;81:375-379. 26. Streja E, Kovesdy CP, Molnar MZ, et al. Role of nutritional status and inflammation in higher survival of African American and Hispanic hemodialysis patients. Am J Kidney Dis. 2011;57:883-893. 27. Jones CH, Akbani H, Croft DC, Worth PD. The relationship between serum albumin and hydration status in hemodialysis patients. J Ren Nutr. 2002;12:209-212. 28. Santos NSJ, Draibe SA, Kamimura MA, Cuppari L. Albumina serica como marcador nutricional de pacientes em hemodialise. Rev Nutr. 2004;17:339-349.
INCREASE OF BMI IS AFFECTED BY FLUID OVERLOAD 29. Simenhoff MI, Saukkonen JJ, Burke JF, Werson LG Jr, Schaedler RW, Gordon SJ. Bacterial populations of the small intestine in uremic. Nephron. 1978;22:63-68. 30. Cheng LT, Tang W, Wang T. Strong association between volume status and nutritional status in peritoneal dialysis patients. Am J Kidney Dis. 2005;45:891-902. 31. Fein P, Chattopadhyay J, Paluch MM, Borawski C, Matza B, Avram MM. Enrollment fluid status is independently associated with long-term survival of peritoneal dialysis patients. Adv Perit Dial. 2008;24: 79-83.
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32. Ferreira-Filho SR, Machado GR, Ferreira VC, Rodrigues CFMA, Moraes TP, Divino-Filho JC, Olandoski M, Mclntyre C. Pecoits Filho, R on behalf of the BRAZPD study investigators. Back to basics: pitting edema and the optimization of hypertension treatment in incident peritoneal dialysis patients (BRAZPD). PLoS ONE. 2012;7:1-6. 33. Kang DH, Yoon KI, Choi KB, et al. Relationship of peritoneal membrane transport characteristics to the nutritional status in CAPD patients. Nephrol Dial Transplant. 1999;14:1715-1722. 34. Blake P. What is the problem with high transporters? Perit Dial Int. 1997;17:317-320.
Increase in BMI Over Time Is Associated With Fluid Overload and Signs of Wasting in Incident Peritoneal Dialysis Patients Viviana Teixeira Henriques, RD, PhD,* Edson Zangiacomi Martinez, DSc, PhD,* Jose Carolino Divino-Filho, MD, PhD,† Roberto Pecoits-Filho, MD, PhD,‡ and Jose Abr~ao Cardeal da Costa, MD, PhD,* on behalf of the Brazilian Peritoneal Dialysis Multicenter Study BRAZPD Group Objectives: Peritoneal dialysis (PD) patients may suffer changes in nutritional status after starting PD. Several markers can be used to evaluate these modifications, such as body mass index (BMI), serum albumin, and serum creatinine. Fluid overload should be considered because it can overestimate or underestimate nutritional status. The objective of this study was to evaluate the BMI changes over time in incident PD patients and identify interactions among BMI, signs of fluid overload, serum albumin, and serum creatinine. Design: The study included a cohort of 1,997 incident PD patients of the BRAZPD recruited from 2004 to 2007. Sociodemographic data and BMI classification were obtained at baseline. The evolutions of BMI and body weight were assessed over a period of 29 months. Changes in the evolution were analyzed when a patient presented with albumin , 3.8 g/dL, creatinine , 7.0 mg/dL, or the presence of edema. Data analysis was performed using linear mixed-effects regression models as the main statistical procedure. Results: BMI increased over time (29 months) by an average of 0.05 kg/m2 per month, and body weight increased by 0.11 kg/month for a total increase of 3.08 kg. BMI decreased by 0.12 kg/m2 in the presence of albumin , 3.8 g/dL and by 0.38 kg/m2 in the presence of creatinine , 7.0 mg/dL. BMI increased by 0.61 kg/m2 in the presence of edema. BMI increased in the presence of edema and albumin , 3.8 mg/dL or edema and creatinine , 7.0 mg/dL. Conclusions: There is a mean increase in the BMI of incident PD patients over time, and these changes may be, at least partly, due to fluid overload, leading to distortions of body weight. When the patients presented with lower serum albumin or creatinine levels, the BMI values were reduced, suggesting that a reduction in lean mass and an increase in fat mass may be occurring in these patients. Ó 2013 by the National Kidney Foundation, Inc. All rights reserved.
Introduction
T
HE NUTRITIONAL STATUS of patients on renal replacement therapy (RRT) is important because of its correlation with the risk of morbidity and mortality. The initial nutritional status of dialysis patients can be influenced by various physiological and metabolic alterations, which must be evaluated over the duration of therapy. Several markers of nutritional status can be used, including
* Universidade de S~ao Paulo/Faculdade de Medicina de Ribeir~ao Preto, Ribeir~ao Preto, S~ao Paulo, Brazil. † Division of Renal Medicine, CLINTEC, Karolinska Institutet, Stockholm, Sweden. ‡ School of Medicine, Pontifıcia Universidade Catolica do Parana, Curitiba, Parana, Brazil. Financial Disclosure: During the data collection and analysis, J.C.D.-F. was employed by Baxter; his employment by Baxter ended on March 31, 2011. See Acknowledgments on page e56. The other authors declare that they have no relevant financial interests. Address correspondence to Viviana Teixeira Henriques, RD, PhD, Av. dos Bandeirantes 3900, Rua Pedreira de Freitas, Casa 13-Universidade de S~ao Paulo, CEP: 14040-900, Ribeir~ao Preto, S~ao Paulo, Brazil. E-mail:
[email protected] Ó 2013 by the National Kidney Foundation, Inc. All rights reserved. 1051-2276/$36.00 http://dx.doi.org/10.1053/j.jrn.2012.08.008
Journal of Renal Nutrition, Vol 23, No 3 (May), 2013: pp e51-e57
body mass index (BMI),1 serum albumin,2 and serum creatinine.3 In incident PD patients, the BMI can change over time because of modifications in body weight, including fat and lean mass; the latter includes muscle and hydration status.4 Weight changes in peritoneal dialysis (PD) patients can be influenced by dextrose contained in the dialysis solution, which is absorbed by the peritoneal membrane and serves as a source of energy for the organism. If the quantity of ingested food is not modified, then there may be an excess of energy, leading to weight gain.1 Genetic factors involved in basal metabolism may also provoke changes in body weight.5 The metabolism of patients on RRT is usually altered, presenting greater insulin resistance as well as metabolic acidosis.6 Additionally, endotoxemia, caused by volume overload, may lead to translocation of bacteria from the gut into the circulation.7 These changes cause inflammation, catabolism, and loss of lean and/or fat mass. The loss of muscle causes a decrease in serum creatinine.8 Albumin synthesis may also be affected because it depends on hepatic function, which responds to acute or chronic inflammation by producing positive acute phase proteins and e51
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HENRIQUES ET AL
reducing serum albumin levels.9 In addition, insufficient food intake exacerbates the reduction of serum albumin. Incident PD patients may present with increased body fat and decreased lean mass, leading to sarcopenic obesity. However, edema should always be considered because it can overestimate this nutritional status.10 We hypothesized that BMI increases over time in patients on PD, that hypervolemia may be a confounding factor for defining malnutrition in an edematous state, and that monitoring other markers of nutritional status may identify patients with a high BMI and sarcopenic obesity. The objective of the study presented here was to monitor BMI changes over time in incident PD patients and to identify interactions among BMI, signs of fluid overload, serum albumin, and serum creatinine.
Methods This was a prospective, national, multicenter cohort study conducted in Brazil (BRAZPD). A detailed description of BRAZPD has been previously reported.11 The study was approved by the ethics committee of each participating institution, and the protocol was approved by the ethics committee of the University Hospital, School of Medicine of Ribeir~ao Preto, University of S~ao Paulo (HCFMRP-USP).
Patients and Study Design The study was conducted in 1,997 incident PD patients receiving continuous ambulatory peritoneal dialysis (CAPD) or automated peritoneal dialysis (APD) at 114 public and private RRT centers in all regions of Brazil. All adult ($18 years) patients who began PD between December 2004 and October 2007, who remained at least 90 days on PD and provided complete information on body weight and height, were included in the study (Fig. 1). The data were collected monthly at the various centers using the PDnet software developed specifically for the BRAZPD study.11
Social and Demographic Data Baseline social and demographic data included the following: age (years), elderly status (.65 years old), gender, race (white, non-white), primary cause of renal disease (chronic glomerulonephritis, hypertensive renal disease, diabetic nephropathy, other, unknown), PD modality (CAPD or APD), family income (no income, #2, 3-5, 5-10, 10-20, .20 minimum wages per month [U.S. $150.42 {U.S. $4.94/day}), Brazilian region (northern, midwestern, northeastern, southern, eastern), educational level (illiterate, elementary, secondary, and higher), original treatment (hemodialysis, kidney transplant, unknown, PD as a first option), and diabetes (presence or absence). Anthropometric Data Weight (kilograms) was determined monthly, and height (centimeters) was measured at baseline. BMI (kilograms per square meter) was calculated and classified according to the World Health Organization criteria.12 Laboratory and Clinical Data Serum albumin was collected quarterly. The patients were classified according to cutoff points as having albumin depletion (,3.8 g/dL) or normal albumin ($3.8 g/dL). Serum creatinine was determined monthly and divided into two groups: ,7.0 mg/dL or $7.0 mg/dL. The cutoff points for serum albumin and serum creatinine were set according to the median of each of the variables. Fluid overload was defined by a monthly clinical evaluation (presence or absence of edema). Statistical Methods The analyses were performed using the SAS statistical package, version 9.2 (SAS Institute Inc., Cary, NC).13 The percentages, means, and standard deviations were used to summarize the variables of interest. Linear mixed-effects regression models (SAS proc mixed)13 were used to identify the evolution of BMI and weight over time and to determine the effects of the
Figure 1. Participants in the BRAZPD study. Data set for analysis, including patients in the BRAZPD study starting PD in the period 2004-2007.
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INCREASE OF BMI IS AFFECTED BY FLUID OVERLOAD
following factors: serum albumin level, serum creatinine level, and fluid overload. A random-subject effect was included in this model, along with fixed effects, to allow for modeling of the within-subject correlation that may arise because of the longitudinal nature of the data.14
Results The sociodemographic characteristics of the patients are listed in Table 1. Of the patients studied, 53.8% were from the eastern region, 11.8% were illiterate, and most earned up to 5 minimum wages. These percentages were similar when the patients were distributed by gender and PD modality. Most of the patients were transferred from hemodialysis. Table 2 presents the mean values of age as well as anthropometric and laboratory variables. At the start of therapy, the mean BMI was 24.39 6 4.73 kg/m2. The nutritional statuses of the patients were classified according to BMI,11 serum albumin, and serum creatinine and simultaneously by BMI and serum albumin depletion, BMI and serum creatinine , 7.0 mg/dL, BMI and serum albumin depletion, and serum creatinine , 7.0 mg/dL. These statuses at baseline are presented in Table 3. The depletions of serum albumin and serum creatinine , 7.0 mg/dL were present mainly in patients classified as normal and overweight. At baseline, a total of 559 patients (28% of the total population) presented with edema. The models used to assess the evolution of BMI and body weight over the 29-month period were applied to 1,101 patients (Table 4 and Table 5, respectively). The results showed a mean basal BMI value of 24.8 kg/m2, with a mean increase of 0.05 kg/m2 per month over a period of 29 months in patients with serum albumin . 3.8 g/dL, serum creatinine . 7.0 mg/dL, and no edema. The model used for the evolution of body weight estimated a mean increase of 0.11 kg/month and a total gain of 3.08 kg for the entire study period with respect to the mean basal value of 65.15 kg. During months in which the patients showed serum albumin levels ,3.8 g/dL, a change in the evolution of the BMI occurred, suggesting a mean reduction in the BMI of 0.12 kg/m2. In addition, the BMI values seemed to decrease by an average of 0.38 kg/m2 during months in which the patients presented with serum creatinine levels ,7.0 mg/dL. A decrease in body weight was also observed when serum albumin levels were ,3.8 g/dL and serum creatinine levels were ,7.0 mg/dL, with a mean reduction of 0.39 and 1.22 kg, respectively. A change in the evolution of BMI and body weight was also observed in the presence of edema, with a mean increase of 0.61 kg/m2 and 1.47 kg, respectively. When patients had edema and serum albumin , 3.8 g/dL, the BMI increased by an average of 0.23 kg/m2 and body weight increased by 0.64 kg. An increase of
Table 1. Sociodemographic Characteristics of Incident PD Patients—Brazil 2004-2007 Variable Gender Male/female Regions Northern Northeastern Midwestern Eastern Southern Race White/Non-white Primary kidney disease Chronic glomerulonephritis Hypertensive renal disease Diabetic nephropathy Others Unknown PD modality APD/CAPD Educational level Illiterate Elementary Secondary Higher Income (minimal wages per month) Without income #2 3-5 5-10 10-20 .20 Elderly (.65 y) Yes/no Original treatment Hemodialysis Kidney transplant Unknown PD as a first option Diabetic Yes/no
Frequency
%
919/1,078
46.0/54.0
94 384 71 1,074 374
4.7 19.2 3.6 53.8 18.7
1,240/757
62.0/38.0
219 479 758 262 279
11.0 24.0 38.0 13.0 14.0
998/999
49.0/51.0
235 1,111 495 156
11.8 55.6 24.8 7.8
31 689 872 321 67 17
1.6 34.5 43.7 16.0 3.4 0.9
712/1,285
35.6/64.4
1,371 12 6 608
68.6 0.6 0.3 30.4
842/1,155
42.2/57.8
0.07 kg/m2 in BMI and 0.17 kg in body weight also appeared with an interaction between edema and serum creatinine , 7.0 mg/dL.
Table 2. Age and Anthropometric and Laboratory Variables of Incident PD Patients at Baseline—Brazil 2004-2007 Variable Age (y) Weight (kg) Height (cm) BMI (kg/m2) Albumin (g/dL) Creatinine (mg/dL)
Frequency
Mean
Standard Deviation
1,997 1,997 1,997 1,997 531 1,766
58.73 63.98 161.69 24.39 4.20 7.67
15.81 14.24 9.67 4.73 1.32 3.60
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HENRIQUES ET AL
Table 3. Nutritional Status of Incident PD Patients—Brazil 2004-2007 Frequency/ % (baseline)
Variable BMI (kg/m2) Malnutrition Normal Overweight Obesity Total Serum albumin (g/dL) Depletion Normal Total Serum creatinine (mg/dL) ,7.0 $7.0 Total Albumin depletion and BMI (kg/m2) Malnutrition Normal Overweight Obesity Total Serum creatinine , 7.0 mg/dL and BMI (kg/m2) Malnutrition Normal Overweight Obesity Total Albumin depletion serum creatinine , 7.0 mg/dL and BMI (kg/m2) Malnutrition Normal Overweight Obesity Total
#18.4 18.5-24.9 25.0-29.9 $30.0 -
170/8.5 1,035/51.8 564/28.2 228/11.4 1,997/100
,3.8 $3.8 -
261/49.1 270/50.8 531/100
,7.0 $7.0 -
864/48.9 901/51.0 1,765/100
#18.4 18.5-24.9 25.0-29.9 $30.0 -
25/9.6 141/54.0 69/26.4 26/10.0 261/100
#18.4 18.5-24.9 25.0-29.9 $30.0 -
80/9.3 458/53.0 221/25.5 105/12.2 864/100
#18.4 18.5-24.9 25.0-29.9 $30.0 -
12/9.2 67/51.1 35/26.8 17/13.0 131/100
Data from reference.12
Discussion BMI has limitations for the evaluation of nutritional status because it does not represent body composition or distinguish between fat and lean mass. It is an indicator of body fat, but it does not express the distribution of body fat (visceral or subcutaneous). However, it is widely used in epidemiological studies because the measurement is relatively simple and important for assessing the risk of morbidity and mortality.15,16 Changes in BMI can occur during PD therapy. BMI is one of the variables found in the BRAZPD study. In the study presented here, according to BMI classification at baseline, most patients were normal, followed by overweight, obese, and malnourished. The same sequence of BMI classification was observed by Snyder et al.17 using the same cutoff points. In this population of PD patients, the BMI and body weight evolutions presented a linear mean increase over
the 29 months of the study. This weight gain may have been influenced by several factors, among them the extra energy provided by dextrose in the dialysate, which was absorbed through the peritoneal membrane. Although our analysis did not include this result, the relationship has been suggested in previous reports.1,18,19 However, Jakic et al.20 did not find a relationship between weight gain and the caloric contribution of glucose absorbed from the dialysate. Another hypothesis for the increase in body weight involves less restriction of food intake for PD patients when compared with those following conservative treatment. We also considered that the weight gain of some of the patients studied was perhaps due to genetic factors related to the reduction of basal metabolism. On the basis of their results, Nordfords et al.5 suggested that mitochondrial uncoupling protein 2 polymorphisms contribute to variations in body composition and adipose tissue accumulation in patients treated with PD. The lack of body composition variables is a limitation of the study presented here. We can confirm an increase in body weight and BMI; however, we cannot conclude whether this was due to a gain of lean mass and/or fat mass (subcutaneous or visceral). Choi et al.4 detected a linear increase in body weight due to subcutaneous and visceral fat during the first 6 months of PD. However, from 6 to 12 months, the weight gain was lower and practically stabilized. Vasselai et al.1 detected a 53% increase in body fat after 12 months of PD compared with baseline. An increase in BMI and body weight is suggested in edematous patients in our study. Thus, a patient classified as malnourished who gains weight because of fluid overload may be reclassified as normal, a normal patient as overweight, and an overweight patient as obese, perhaps with little or no change in adipose tissue. Because edema is often classified in a subjective manner, an edematous state may overestimate the nutritional status and should therefore be taken into consideration in studies involving the evaluation of nutritional status to avoid systematic distortion of the relationship between BMI and fat mass. Data regarding the classification of edema, whether edema was subtracted, and how much was subtracted from body weight are not included in the BRAZPD study. Renal patients usually have insulin resistance and inflammation.5 Studies21,22 have detected an association among the inflammatory process, malnutrition, and hypervolemia. Hypervolemia characterized by the presence of edema may interfere with body weight.23 In the study by Jakic et al.,20 weight gain in patients on PD was caused, at least in part, by fluid retention. In our models, when a patient presented with albumin depletion, a reduction in mean BMI and body weight was estimated. Low serum albumin levels may be due to the protein catabolism caused by the inflammatory process, which, together with the deterioration of nutritional status, reduces albumin synthesis.9 Catabolism may lead to a reduction of muscle mass, affecting body weight, although the
e55
INCREASE OF BMI IS AFFECTED BY FLUID OVERLOAD Table 4. Linear Mixed-effects Regression Model–evolution of BMI (kg/m2) of Incident PD Patients—Brazil 2004-2007 Variable Fixed effects BMI (baseline) Time (each month) Albumin depletion vs. normal Creatinine , 7.0 mg/dL vs. $7.0 mg/dL Fluid overload yes vs. no Interaction effects Fluid overload 3 albumin depletion Fluid overload 3 creatinine , 7.0 mg/dL Patients (n) Total period (mo)
Estimate
24.80 0.05 20.12 20.38 0.61 0.23 0.07 1,101 29
correlation of lean mass with BMI is not strong because this index is more correlated to fat mass.24,25 Albumin is considered to be a powerful health indicator as observed in the NECOSAD study,2 in which a 1-g/dL reduction in serum albumin levels increased the risk of mortality by 38% in patients on PD. A reduction in mean BMI and body weight was also suggested in our study when a patient presented with serum creatinine , 7.0 mg/dL. Because creatinine is a nitrogenated nonprotein organic compound formed from the dehydration of creatine in skeletal muscle, a reduction may be the result of muscle mass loss.3,8 Serum creatinine levels are altered in patients on dialysis. However, lower serum creatinine levels are detected in malnourished patients,3 and levels below the specific cutoff point suggest an association of creatinine with lean body mass and survival.3,26 On the other hand, Stosovic et al.10 found a poor relationship between mid-arm muscle circumference and serum creatinine and stated that creatinine concentration depends on the balance between production and elimination. Approximately two-thirds of the BRAZPD patients had undergone hemodialysis as a first therapy and then were transferred to PD, which means that creatinine elimination by residual renal function was most likely not present. Other factors, such as low food intake and reduced physical activity, may also cause reduced muscle mass and serum creatinine levels.8
Standard Error
t
P
0.16 0.006 0.09 0.11 0.15
7.97 21.30 23.31 3.98
.01 .19 .01 .01
1.34 0.43
.17 .66
0.16 0.17
An increase in BMI and body weight was suggested when the effects of the synergistic interaction between albumin depletion and edema or between serum creatinine levels ,7.0 mg/dL and edema were analyzed. On the basis of the results of these interactions, we could possibly infer that edema reduces the serum albumin and/or serum creatinine values and that these biochemical values may not be a result of depletion of lean body mass. However, as a result of the reduced oncotic pressure associated with low plasma albumin, fluid leakage occurs from the plasma fluid to the interstitial compartment.27,28 In addition, hypervolemia can overestimate the nutritional status of these patients and mask the reduction of lean mass, as previously discussed. Volume overload leads to an impaired intestinal barrier, increased permeability in the gut, and bacterial translocation.7 In uremia, the gut bacterial population is increased,29 which can lead to endotoxemia. Additionally, chronic inflammation may occur in patients with edema, contributing to protein catabolism and malnutrition, which in turn lead to atrophy of intestinal mucosa and endotoxemia.7 Cheng et al.30 concluded that deterioration in fluid status is associated with malnutrition. According to Fein et al.,31 fluid overload is a risk factor independent of long-term survival in PD patients. Ferreira-Filho et al.32 observed an initial blood pressure level reduction in the first five months and stabilization from five to twelve months in the same cohort of incident BRAZPD patients. The edematous group
Table 5. Linear Mixed-effects Regression Model: Evolution of Body Weight (kg) of Incident PD Patients—Brazil 2004-2007 Variable Fixed effects Body weight (baseline) Time (each month) Albumin depletion vs. normal Creatinine , 7.0 mg/dL vs. $7.0 mg/dL Fluid overload yes vs. no Interaction effects Fluid overload 3 albumin depletion Fluid overload 3 creatinine , 7.0 mg/dL Patients (n) Total period (mo)
Estimate
65.15 0.11 20.39 21.22 1.47 0.64 0.17 1,101 29
Standard Error
t
P
0.47 0.015 0.25 0.30 0.40
7.38 21.58 24.00 3.61
0.01 0.11 0.01 0.01
1.41 0.39
0.15 0.69
0.45 0.45
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HENRIQUES ET AL
exhibited higher blood pressure levels than the group without edema during the follow-up. Although we do not know the peritoneal membrane transport characteristics of patients, patients with a hightransporter peritoneal membrane may have a greater risk of malnutrition, related to an increased loss of creatinine and proteins (e.g., albumin) through the dialysate. In addition, there may be a high absorption of glucose at the peritoneal level, contributing to early satiety and poor food intake.33,34 It was not possible to evaluate data regarding the effectiveness of the dialysis because of the low number of patients with this information. In conclusion, we present data showing that although BMI may increase over time in patients on PD, these changes are, at least in part, due to fluid overload. In addition, when patients presented with lower serum albumin or serum creatinine levels, the BMI values were reduced, suggesting that a reduction of lean mass and an increase in fat mass may be occurring in these patients. In some patients, the development of wasting, even in the presence of high BMI, may occur. To clarify the assumptions made by the data analyzed in our study, body composition should be evaluated in future studies.
Practical Application Edema is often present in patients with PD and may mask the results. Edema should be included in analyses of BMI. BMI is a useful tool in epidemiological studies when combined with other variables, generating hypotheses for clinical studies.
Acknowledgments
The authors thank Coordenac¸~ao de Aperfeic¸oamento de Pessoal de Nıvel Superior (CAPES), Brazil. This study was financed by Baxter Healthcare, Brazil. J.C.D.F. was employed by Baxter Healthcare when this study was performed.
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INCREASE OF BMI IS AFFECTED BY FLUID OVERLOAD 29. Simenhoff MI, Saukkonen JJ, Burke JF, Werson LG Jr, Schaedler RW, Gordon SJ. Bacterial populations of the small intestine in uremic. Nephron. 1978;22:63-68. 30. Cheng LT, Tang W, Wang T. Strong association between volume status and nutritional status in peritoneal dialysis patients. Am J Kidney Dis. 2005;45:891-902. 31. Fein P, Chattopadhyay J, Paluch MM, Borawski C, Matza B, Avram MM. Enrollment fluid status is independently associated with long-term survival of peritoneal dialysis patients. Adv Perit Dial. 2008;24: 79-83.
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32. Ferreira-Filho SR, Machado GR, Ferreira VC, Rodrigues CFMA, Moraes TP, Divino-Filho JC, Olandoski M, Mclntyre C. Pecoits Filho, R on behalf of the BRAZPD study investigators. Back to basics: pitting edema and the optimization of hypertension treatment in incident peritoneal dialysis patients (BRAZPD). PLoS ONE. 2012;7:1-6. 33. Kang DH, Yoon KI, Choi KB, et al. Relationship of peritoneal membrane transport characteristics to the nutritional status in CAPD patients. Nephrol Dial Transplant. 1999;14:1715-1722. 34. Blake P. What is the problem with high transporters? Perit Dial Int. 1997;17:317-320.