Ana Paula Bazanelli

Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients

BACKGROUND The determination of resting energy expenditure (REE) is the primary step for estimating the energy requirement of an individual. Although numerous equations have been formulated for predicting metabolic rates, there is a lack of studies addressing the reliability of those equations in chronic kidney disease (CKD). Thus, the aim of this study was to evaluate whether the main equations developed for estimating REE can be reliably applied for CKD patients. METHODS A total of 281 CKD patients (124 non-dialysis, 99 haemodialysis and 58 peritoneal dialysis) and 81 healthy control individuals were recruited. Indirect calorimetry and blood sample collection were performed after a 12-h fasting. Two most traditionally used equations for estimating REE were chosen for comparison with the REE measured by indirect calorimetry: (i) the equation proposed by Harris and Benedict, and (ii) the equation proposed by Schofield that is currently recommended by the FAO/WHO/UNU. RESULTS Schofields equation exhibited higher REE [1492±220 kcal/day (mean±SD)] in relation to Harris and Benedicts equation (1431±214 kcal/day; P<0.001), and both prediction equations showed higher REE in comparison with the reference indirect calorimetry (1352±252 kcal/day; P<0.001). In patients with diabetes, inflammation or severe hyperparathyroidism, the REE estimated by the Harris and Benedict equation was equivalent to that measured by indirect calorimetry. The intraclass correlation of the REE measured by indirect calorimetry with the Schofields equation was r=0.48 (P<0.001) and with the Harris and Benedicts equation was r=0.58 (P<0.001). According to the Bland and Altman analysis, there was a large limit of agreement between both prediction equations and the reference method. Acceptable prediction of REE (90-110% adequacy) was found in 47% of the patients by using the Harris and Benedicts equation and in only 37% by using the Schofields equation. CONCLUSIONS The most traditionally used prediction equations overestimated the REE of CKD patients, and the errors were minimized in the presence of comorbidities. There is a need to develop population-specific equations in order to adequately estimate the energy requirement of these patients.

Underreporting of Energy Intake in Peritoneal Dialysis Patients

OBJECTIVES This study aimed to assess the prevalence of underreporting among patients treated by peritoneal dialysis (PD), and to investigate whether the reported energy intake is influenced by overweight status in this population. DESIGN This was a prospective, observational study. SETTING This study took place at the Dialysis Unit of the Nephrology Division, Federal University of São Paulo-Oswaldo Ramos Foundation, São Paulo, Brazil. PATIENTS Forty adult patients were recruited: 24 men and 16 women; age, 53.4+/-16.5 years; body mass index (BMI), 25.1+/-3.8 kg/m(2) (x+/-SD); median duration of dialysis, 19 months (range, 3 to 101 months). Only patients on PD >3 months, free of peritonitis for at least 3 months, without catabolic conditions and with normal thyroid function, were included. METHODS Energy intake was evaluated using a 3-day food record. Resting energy expenditure (REE) was measured by indirect calorimetry. Body composition was assessed using dual-energy x-ray absorptiometry. The total energy (TE) offered was considered the sum of energy intake plus energy provided by glucose absorption. All measurements were collected at baseline and after 6 months. Underreporting of energy intake was considered to have occurred when the TE/REE ratio was <1.40. RESULTS The TE/REE ratio was 1.35+/-0.31. Twenty-one patients (52.5%) had a TE/REE ratio <1.40. The TE/REE ratio correlated negatively with BMI (r=-0.52, P < .01), and positively with duration of dialysis (r=0.44, P < .01). No correlation was found between TE/REE ratio and any other variables. Patients were divided into two groups according to BMI <25 kg/m(2) and BMI > or =25 kg/m(2). The majority of patients (83.3%) in the higher BMI group had a TE/REE ratio <1.40. In a logistic regression analysis, using TE/REE ratio <1.40 or > or =1.40 as the dependent variable, BMI> or =25 kg/m2 was the only determinant of energy underreporting. After 6 months of follow-up, no change in either body weight or BMI was evident. CONCLUSIONS This study showed that a significant number of PD patients underreported the energy intake evaluated by 3-day food diaries. This finding was evidenced particularly in overweight patients.

Usefulness of waist circumference as a marker of abdominal adiposity in peritoneal dialysis: a cross-sectional and prospective analysis

BACKGROUND Waist circumference (WC) has been well recognized as a surrogate marker of abdominal adiposity. In peritoneal dialysis (PD) patients, however, aspects related to this dialysis modality, such as abdominal distension, presence of catheter and frequent hernia, raise questions regarding the reliability of WC measurements. Herein, we investigated for the first time whether WC is a reliable marker of abdominal adiposity in PD population. METHODS This study included 107 prevalent PD patients [56% male, age 52 ± 17 years, 35% diabetics, body mass index (BMI) 24.8 ± 3.9 kg/m(2)]. WC measured at umbilicus level was evaluated against the trunk fat assessed by dual-energy x-ray absorptiometry at baseline and after 6 months. All measurements were taken with the empty abdominal cavity. RESULTS At baseline, a strong correlation of WC with trunk fat (r = 0.81; P < 0.001) was observed. Adjusting for gender, age, dialysis vintage and BMI, WC was independently associated with trunk fat (β = 0.30; P < 0.001; R(2) = 0.77). The agreement between WC and trunk fat was 0.59 (kappa statistic) and the area under the curve was 0.90. In the prospective evaluation, we observed that changes in WC correlated with changes in trunk fat as well (r = 0.49; P < 0.001). The kappa statistic of 0.48 remained indicative of a moderate agreement between the methods. The receiver operating characteristic curve analysis showed that WC was sensitive to detect changes in trunk fat (area under the curve 0.76). In the logistic regression analysis adjusting for gender, age and BMI, changes in WC were independently associated with changes in trunk fat. CONCLUSION The simple anthropometric method of WC is a reliable marker of abdominal adiposity in PD patients.

Factors Associated With Body-Fat Changes in Prevalent Peritoneal Dialysis Patients

BACKGROUND Changes in body fat (BF) were shown to occur over time in peritoneal dialysis (PD) patients. However, the factors associated with BF changes have not been fully investigated in this population. METHODS We studied 45 patients (25 were male; age, 53, SD +/- 15 years; 21 continuous ambulatory peritoneal dialysis/24 automated peritoneal dialysis; PD vintage, 14 ([range, 3 to 104] months; 40% were diabetic; 31% were previously treated by hemodialysis). Body composition was assessed by dual-energy X-ray absorptiometry and bioelectric impedance analysis, nutritional status was assessed by subjective global assessment, energy intake was assessed by 3-day food records, and resting energy expenditure (REE) was assessed by indirect calorimetry. Glucose absorption, serum bicarbonate, and C-reactive protein were also evaluated. All measurements were performed at baseline and after 12 months. RESULTS Large variability in BF changes was observed among patients: 53% gained BF (+3.0 +/- 2.8), whereas 47% lost BF (-2.3, SD +/- 1.4). At baseline, groups were similar regarding sex, age, percent diabetics, DP modality, characteristics of peritoneal transport, residual renal function, energy intake, glucose absorption, and REE. However, patients who gained BF had lower BF (16.3, SD +/- 6.9 kg, versus 20.9, SD +/- 6.5 kg; P = .03), had a higher ratio of total energy offered (intake plus absorbed glucose) to REE (1.45, SD +/- 0.39, versus 1.26, SD +/- 0.24; P = .04), and were on PD for a shorter time (10 [range, 3 to 104] versus 20 [range, 4 to 76] months; P = .03). This group also had a higher proportion of malnourished patients (50% versus 19%; P = .03) and of patients previously treated by hemodialysis (46% versus 14%; P = .03). After 12 months, a reduction in the frequency of malnutrition (50% to 25%; P = .02) was observed in the group of patients with increased BF. Patients who lost BF reduced their body cell mass (from 21.7 [SD +/- 5.1 kg] to 20.7 [SD +/- 5.0 kg]; P < .01) and level of serum bicarbonate (from 22.7 [SD +/- 3.7 mmol/L] to 20.9 [SD +/- 3.1 mmol/L]; P < .01). Moreover, this group had an increase in frequency of malnutrition (from 19% to 38%; P = .02), a reduction in the proportion of patients with residual renal function (from 62% to 43%; P = .03), and a higher number of hospitalizations (from 25% to 4%; P = .02) during follow-up. Glucose absorption and C-reactive protein were not associated with BF changes. A regression analysis showed that baseline body mass index was independently associated with a gain of BF (-0.19, SE = 0.09, P = .04), and that hospitalization during follow-up was associated with a loss of BF (2.35, SE = 1.19, P = .04). CONCLUSIONS Prevalent PD patients exhibited a large variability in BF changes. Baseline body mass index and hospitalizations during follow-up were the most important factors associated with these changes.

Variations in adiponectin levels in patients with chronic kidney disease: a prospective study of 12 months

BACKGROUND Cardiovascular complications remain the main cause of mortality in patients with chronic kidney disease (CKD). Adiponectin is an adipose tissue-derived protein that carries important cardioprotective properties. We aimed at investigating the determinants of adiponectin levels in CKD patients. METHODS This prospective observational study included 98 CKD patients [glomerular filtration rate (GFR) 36.1+-14.4 ml/min, 56.5+-10.4 y, 63% male, 31% diabetics, and body mass index (BMI) 27.1+-5.2 kg/m²]. Evaluation of adiponectin (imunoenzimatic assay), laboratory parameters, nutritional status (subjective global assessment), total body fat (dual x-ray energy absorptiometry), and visceral and subcutaneous abdominal fat (computed tomography) was performed at baseline and after 12 months. RESULTS Adiponectin correlated with GFR (r = -0.45; p < 0.001), proteinuria (r = 0.21; p = 0.04), BMI (r = -0.33; p < 0.01), and visceral fat (r = -0.49; p < 0.001). In the linear regression analysis, the determinants of adiponectin levels were sex (female β = 3.8; p < 0.01), age (β = 0.14; p = 0.03), GFR (β = -0.15; p < 0.01) and visceral fat (β = -0.04; p < 0.001) (R² = 0.41). After 12 months, a progression of the disease was evidenced by the reduction of GFR (-1.6+-6.3 ml/min; p = 0.01) and increase of proteinuria (0.3+-0.8 g/d; p < 0.01). An accumulation of visceral fat was observed, from 97+-73 cm² to 111+-82 cm² (p < 0.001), with a concomitant reduction of adiponectin concentration, from 27.6+-7.5 mg/l to 22.2+-11.6 mg/l (p < 0.001). Body weight, BMI, total body fat, and subcutaneous abdominal fat remained unchanged. After adjustments for the baseline determinants of adiponectin, the increase in visceral fat was independently associated with overtime decrease in adiponectin levels (β = -0.04; p = 0.025; R² = 0.21). CONCLUSION Age, sex, renal function and visceral fat were independently associated with adiponectin levels in nondialyzed CKD patients. However, variation in visceral fat was the only predictor of variation in adiponectin levels over 12 months.BACKGROUND: Cardiovascular complications remain the main cause of mortality in patients with chronic kidney disease (CKD). Adiponectin is an adipose tissue-derived protein that carries important cardioprotective properties. We aimed at investigating the determinants of adiponectin levels in CKD patients. METHODS: This prospective observational study included 98 CKD patients [glomerular filtration rate (GFR) 36.1+-14.4 ml/min, 56.5+-10.4 y, 63% male, 31% diabetics, and body mass index (BMI) 27.1+-5.2 kg/m2]. Evaluation of adiponectin (imunoenzimatic assay), laboratory parameters, nutritional status (subjective global assessment), total body fat (dual x-ray energy absorptiometry), and visceral and subcutaneous abdominal fat (computed tomography) was performed at baseline and after 12 months. RESULTS: Adiponectin correlated with GFR (r = -0.45; p < 0.001), proteinuria (r = 0.21; p = 0.04), BMI (r = -0.33; p < 0.01), and visceral fat (r = -0.49; p < 0.001). In the linear regression analysis, the determinants of adiponectin levels were sex (female β = 3.8; p < 0.01), age (β = 0.14; p = 0.03), GFR (β = -0.15; p < 0.01) and visceral fat (β = -0.04; p < 0.001) (R2 = 0.41). After 12 months, a progression of the disease was evidenced by the reduction of GFR (-1.6+-6.3 ml/min; p = 0.01) and increase of proteinuria (0.3+-0.8 g/d; p < 0.01). An accumulation of visceral fat was observed, from 97+-73 cm2 to 111+-82 cm2 (p < 0.001), with a concomitant reduction of adiponectin concentration, from 27.6+-7.5 mg/l to 22.2+-11.6 mg/l (p < 0.001). Body weight, BMI, total body fat, and subcutaneous abdominal fat remained unchanged. After adjustments for the baseline determinants of adiponectin, the increase in visceral fat was independently associated with overtime decrease in adiponectin levels (β = -0.04; p = 0.025; R2 = 0.21). CONCLUSION: Age, sex, renal function and visceral fat were independently associated with adiponectin levels in nondialyzed CKD patients. However, variation in visceral fat was the only predictor of variation in adiponectin levels over 12 months.

Waist Circumference as a Predictor of Adiponectin Levels in Peritoneal Dialysis Patients: A 12-Month Follow-Up Study

♦ Objectives: This prospective study, conducted at the dialysis unit of the Nephrology Division, Federal University of Sao Paulo-Oswaldo Ramos Foundation, Brazil, aimed to evaluate whether waist circumference (WC) can predict adiponectin levels in patients undergoing peritoneal dialysis (PD). ♦ Methods: Among 115 patients on PD at a single dialysis center who were evaluated at 6 and 12 months, 57% were men, 31% had diabetes, mean age was 52.8 ± 16.1 years, body mass index was 25 ± 4.3 kg/m2, and dialysis vintage was 13 months (range: 5 - 33 months). We measured WC at the umbilicus level. Adiponectin was determined by an enzyme-linked immunosorbent assay. ♦ Results: At baseline, WC was inversely associated with adiponectin (r = -0.48, p < 0.01). After adjustment for sex, age, diabetes, peritoneal clearance, and residual renal function, WC was an independent determinant of serum adiponectin (β = -0.52; 95% confidence interval: -0.73 to -0.31; p < 0.001). In the prospective analysis, after adjustment for confounders, changes in WC predicted changes in adiponectin. For each unit increase in WC, adiponectin declined by 0.39 mg/L (p < 0.001). ♦ Conclusions: This study demonstrates that WC is associated with adiponectin and, more importantly, that this simple marker of central adiposity was able to predict changes in adiponectin levels over time.

Nutritional status and body composition after 6 months of patients switching from continuous ambulatorial peritoneal dialysis to automated peritoneal dialysis

Our objective was to determine if automated peritoneal dialysis (APD) leads to changes in nutritional parameters of patients treated by continuous ambulatory peritoneal dialysis (CAPD). Twenty-six patients (15 males; 50.5 +/- 14.3 years) were evaluated during CAPD while training for APD and after 3 and 6 months of APD. Body fat was assessed by the sum of skinfold thickness and the other body compartments were assessed by bioelectrical impedance. During the 6-month follow-up, 12 patients gained more than 1 kg (GW group), 8 patients lost more than 1 kg (LW group), and 6 patients maintained body weight (MW group). Except for length on dialysis that was longer for the LW group compared with the GW group, no other differences were found between the groups at baseline. After 6 months on APD, the LW group had a reduction in body fat (24.5 +/- 7.7 vs 22.1 +/- 7.3 kg; P = 0.01), body cell mass (22.6 +/- 6.2 vs 21.6 +/- 5.8 kg, P = 0.02) and phase angle (5.4 +/- 0.9 vs 5.1 +/- 0.8 degrees, P = 0.004). In the GW group, body fat (25 +/- 7.6 vs 27.2 +/- 7.6 kg, P = 0.001) and body cell mass (20.1 +/- 3.9 vs 20.8 +/- 4.0 kg, P = 0.05) were increased. In the present study, different patterns of change in body composition were found. The length of previous dialysis treatment seems to be the most important factor in determining these nutritional modifications.

Waist circumference as a predictor of mortality in peritoneal dialysis patients: a follow-up study of 48 months

Body-fat gain is a common finding among peritoneal dialysis (PD) patients, and the accumulation of adipose tissue occurs predominantly in the abdominal area. Waist circumference (WC) is a reliable marker of abdominal obesity and its association with worse outcomes has been demonstrated in non-dialysis and haemodialysis patients. We aimed at investigating whether WC measurements as well as the changes over time in WC were able to predict mortality in PD patients. This prospective study included 109 patients undergoing PD (57 % male, age 52 (sd 16) years, 32 % diabetics, 48 % BMI≥25 kg/m2). WC was measured at the umbilicus level (empty abdominal cavity), and values >88 cm for women and >102 cm for men were considered high. Nutritional status and laboratory parameters were also evaluated. WC was measured at baseline and after 6 months, and mortality was registered during a period of 48 months. High WC was observed in 55 % of women and in 23 % of men at baseline. After 6 months, 61 % of the patients showed an increased WC. At the end of the study, twenty-seven deaths were registered. A significant increase in WC was observed only in the non-survivor group. In the Cox regression analysis adjusting for sex, age, duration on dialysis, diabetes, BMI, serum albumin and C-reactive protein, high WC at baseline as well as the 6-month increase in WC were independently associated with mortality. This study demonstrated that a high WC and the increase over time in WC were both predictors of mortality in PD patients.