Resting energy expenditure in pre-dialysis diabetic patients

Carla Maria Avesani1, Lilian Cuppari1, Antonio Carlos Silva2, Dirce Maria Sigulem3, Miguel Cendoroglo1, Ricardo Sesso1 and Sergio Antonio Draibe1,

1 Divisions of Nephrology and 2 Physiology 3 Department of Pediatrics, Federal Univertsity of São Paulo, UNIFESP, São Paulo, Brazil



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 
Background. The metabolic derangements of diabetes mellitus (DM) associated with those of chronic renal failure (CRF) may interfere with the energy and protein balance of patients with both diseases. The aim of this study was to verify whether the resting energy expenditure (REE) of non-dialysis chronic renal failure diabetic patients differs from that of chronic renal failure patients without DM.

Methods. REE was measured by indirect calorimetry in 24 CRF diabetic patients (CRF diabetes group), matched for age, gender, and degree of renal impairment to 24 CRF patients without DM (CRF control group).

Results. The CRF diabetes group had a significantly higher REE (1538±230 kcal/day) than the CRF control group (1339±315 kcal/day, P=0.009). This difference was maintained even when the REE was adjusted for lean body mass (LBM; 30.3±4.3 vs 26.3±5.4 kcal/kg LBM/day, P=0.004). Mean protein intake was significantly higher in the CRF diabetes than in the CRF control group (0.89±0.20 vs 0.76±0.25 g/kg/day, P=0.02). Mean protein equivalent of nitrogen appearance (PNA) was also significantly higher in the CRF diabetes patients (1.21±0.31 vs 1.03±0.22 g/kg/day, P=0.02), reflecting a higher protein intake and/or elevated protein breakdown. Accordingly, REE was directly correlated with PNA mainly in the CRF diabetes group (r=0.57, P<0.003).

Conclusion. Metabolic disturbances of poorly controlled DM may account for the higher REE observed in the CRF diabetes group. The role of the apparently higher protein breakdown in this increased REE remains to be clarified.

Keywords: chronic renal failure; diabetes; indirect calorimetry; protein intake



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 
The increase in gluconeogenesis and protein breakdown that occurs in diabetes mellitus (DM) has been frequently attributed to the lack of and/or resistance to insulin with concomitant hyperglucagonaemia [13]. Accordingly, many authors have shown that muscle proteins are degraded to supply amino acids for gluconeogenesis [35]. These metabolic derangements could also be responsible for an increase in energy expenditure [2,3,68]. In fact, patients with type II DM and fasting hyperglycaemia usually have an elevated basal metabolic rate, which is reduced when a better control of blood glucose is achieved [7,9]. Similar results were observed in patients with type I DM [6].

On the other hand, endocrinological and metabolic disturbances are frequently observed in CRF patients. Chronic renal failure leads to insulin and growth hormone resistance [10,11], increased levels of glucagon [12] and parathyroid hormone [13], metabolic acidosis [14], and accumulation of toxic uraemic metabolites [15]. Such conditions can impair carbohydrate and protein metabolism [16], hence leading to glucose intolerance [16] and elevated protein breakdown [14,17]. Monteon et al. [18] did not find difference in energy expenditure when they compared chronically uraemic non-dialysis and haemodialysis patients with healthy subjects. In agreement with this result, Schneeweiss et al. [19] found that renal failure had no influence on energy expenditure as long as septicaemia was absent. More recently, however, Ikizler et al. [20] found that haemodialysis patients have higher REE even on non-dialysis days. Thus, the status of REE in renal failure remains controversial.

The combination of renal failure and type I DM in haemodialysis patients can cause a reduction in protein synthesis and an elevation of proteolysis [21]. In the clinical setting, it is frequently observed that pre-dialysis CRF patients with DM have high urea nitrogen appearance, mainly when they have infections. Nevertheless, to our knowledge, studies addressing the REE of patients with CRF and DM have never been published before. Therefore this study was designed to compare the REE of non-dialysis diabetic CRF patients with that of CRF patients without DM.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 
Subjects
The study was performed in stable patients with mild to moderate CRF, followed at the Nephrology Division, Federal University of São Paulo—UNIFESP. Only patients older than 18 years, not taking glucocorticoids, without catabolic illness, and with normal thyroid function as judged by thyroxine (T4) and thyroid-stimulating hormone (TSH) determination, were included.

Two groups of patients were established: CRF patients with DM type I (n=3) and II (n=21) named CRF diabetes group (n=24) and a group of non-diabetic CRF patients (n=24; CRF control group), matched for age, gender and creatinine clearance to the former group of patients.

Most of the patients (19 in the CRF diabetes group and 21 in the CRF control) had been instructed to eat approximately 30–35 kcal/kg/day and 0.6–0.8 g/kg/day of protein. Twenty-one patients in the CRF diabetes group were treated with insulin and only three were taking hypoglycaemic agents. Almost all patients were receiving anti-hypertensive drugs; ß blockers were given only to two patients in the CRF diabetes group.

The study was approved by the Human Investigation Review Committee of the Federal University of São Paulo—UNIFESP and informed consent was obtained from each subject.



   Methods
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 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 
Study protocol
The patients of both groups were initially submitted to a first interview in order to meet the inclusion criteria, and to obtain informed consent. One to three weeks later, the patients came to the laboratories of physiology and endocrinology in order to be submitted to measurements of REE and body composition. On the same day, the patients were also carefully instructed to fill in a 4-day food diary and to collect urine in a 24-h period. One week later, 24-h urine collection and blood samples were obtained, under fasting conditions, for measurements of biochemical parameters. Additionally patients were submitted to a nutritional assessment.

Resting energy expenditure
The REE was calculated based on data collected by open circuit indirect calorimetry in a computerized metabolic system (Vista XT metabolic system; Vacumed Inc., Ventura, CA). Subjects breathed through a two-way valve and a clamp was placed on the nose to prevent nasal respiration. Expired airflow was measured with a turbine flowmeter, carbon dioxide concentration (FECO2) with an infrared sensor, and oxygen concentration (FEO2) with a fast differential paramagnetic sensor. The flow, FECO2, and FEO2 data were analysed with the Vista Turbofit software (Vacumed Inc., Ventura CA) to calculate O2 consumption and CO2 production. Based on these data, the REE was calculated using the Weir formula [22], without using urinary urea nitrogen. Gas analysers were calibrated with commercial gases of known composition; turbine flowmeter and volume measurements were calibrated with a 3-litre syringe.

The respiratory quotient was calculated as the ratio between the volume of CO2 expired (VCO2) and the volume of O2 consumed (VO2).

The patients were instructed to maintain their physical activities and regular medication on the day before the measurement. They were admitted to the unit at 7:30 a.m. after an overnight fast of 12 h. After 30 min of resting, the REE was measured in a quiet room at 23.5°C for 30 min and care was taken to keep the room quiet.

Nutritional assessment
Body weight and height were measured in the morning by the same observer. Body mass index was calculated as body weight divided by squared height.

Energy and nutrient intake were estimated from a 4-day food diary (3 week days and 1 weekend day) using a computer software developed at UNIFESP containing the US Department of Agriculture (USDA) tables as the nutrient data base. Protein equivalent of nitrogen appearance (PNA) was determined according to the formula of Sargent & Gotch [23] using 24-h urinary urea excretion.

Body composition
Body composition was determined by dual photon absorptiometry using a scanner DPX model (Lunar Radiation Corporation, Madison, WI) with the patient in the supine position. The software calculates three sets of body composition variables: grams of fat tissue, grams of lean tissue, and the percent of fat mass compared to the total soft tissue mass.

Biochemical data
The patients had blood drawn under fasting conditions for the determination of albumin (colorimetric method). Transferrin, bicarbonate, serum glucose, creatinine, and urea nitrogen (serum and urinary) measured with a standard autoanalyser. Glycated haemoglobin (HbA1c) was measured by the liquid chromatography method (normal range: 2.9–4.3%) and, intact parathyroid hormone (PTH, normal range 10–70 pg/ml), T4 (normal range 0.6–1.5 ng/dl) and TSH (normal range 0.5–6.0 µIU/ml) were determined using immunofluorometric assays.

Glomerular filtration rate was evaluated using standard creatinine clearance (24 h urine collection) corrected for the body surface area (1.73 m2).

Statistical analysis
All data are expressed as mean±standard deviation (SD). Group differences were tested by the Student t test [32]. Simple and multiple linear regression analysis were used in order to identify the relationship between the REE and its possible predictors. In the multivariate analysis, the selection of variables for the model was performed in a forward stepwise manner. The entry and removal of variables in the equation was based on values of F=4.0 or F=3.9 respectively.



   Results
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 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 
The main clinical characteristics of the patients are shown in Table 1Go. There was a predominance of males, with mean age comprised in the 6th decade in both groups. Most patients had moderate loss of renal function, as judged by mean serum creatinine and creatinine clearance (Table 1Go). The mean duration of diabetes was 16.0 years; almost all subjects had type II DM (87.5%). The duration of CRF of the CRF diabetes group was significantly lower than that of the CRF control group. In the CRF diabetes group, diabetic nephropathy was responsible for CRF in 18/24 patients (75%); the other causes of CRF were: hypertensive nephrosclerosis in two (8.3%), renal tuberculosis one (4.1%), ischaemic nephropathy in one (4.1%), and undetermined in two (8.3%). In the CRF control group, chronic glomerulonephritis and hypertensive nephrosclerosis accounted for 18/24 (75%) of the diagnosis.


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Table 1. Main demographic and clinical characteristics of the patients a

 
T4 and TSH of CRF diabetes and of CRF control patients were similar and within the normal range (T4 1.12±0.25 ng/dl and 1.22±0.32 ng/dl, P=non-significant; TSH 2.46±1.37 and 2.20±1.20 µIU/ml, P=non-significant respectively). The majority of the patients in both groups did not present acidosis (serum bicarbonate, CRF diabetes=24.7±3.21 mmol/l and CRF control=23.8±4.26 mmol/l; P=non-significant). Serum PTH was moderately and similarly increased, with mean values of 177±172 pg/ml in the CRF diabetes group and 192±206 pg/ml in the CRF control group. Serum albumin and transferrin mean levels were 4.06±0.7 g/dl and 297.2±82.3 mg/dl respectively in CRF diabetes group and 4.4±0.6 g/l and 284.8±53.4 mg/dl respectively in the CRF control group. There were no significant differences between groups.

As can be seen in Table 2Go, the serum glucose level of CRF diabetes patients was significantly higher than that of CRF control patients; in fact 54% of the CRF diabetes patients had serum glucose above 130 mg/dl. Accordingly, the HbA1c concentrations of the diabetic patients were above the normal limit in 96% of the patients and were also significantly higher than those of control patients. No differences between CRF diabetes and CRF control patients were found regarding body mass index, lean body mass, and body fat (Table 2Go). Except for one woman in the CRF control group, all female patients showed body fat stores above 30%, indicating obesity. On the other hand, only three male patients in the CRF diabetes and one in the CRF control group were obese (body fat >=25%).


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Table 2. Anthropometric and biochemical parameters, dietary intake and protein equivalent of nitrogen appearance (PNA)a

 
Total energy intake was similar in both groups (Table 2Go), even when adjusted for body weight. The mean protein intake, assessed by food diaries, and the PNA were significantly higher in CRF diabetes patients. Furthermore, in both groups the PNA was higher than the protein intake (Table 2Go). When both groups were analysed together, a positive correlation between PNA and protein intake was found (n=48, r=0.30, P=0.03).

As can be seen from Table 3Go and Figure 1Go, the REE was significantly higher in the CRF diabetes patients (12.5 %), even when adjusted for body weight (12.3 %) and for lean body mass (12.4%). The mean respiratory quotient was similar in both groups (Table 3Go).


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Table 3. Resting energy expenditure (REE)a

 


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Fig. 1. Resting energy expenditure (REE) adjusted for lean body mass (LBM) of CRF diabetes and CRF control groups. The mean REE for each group is indicated by a horizontal line (*P=0.004).

 
In the CRF diabetes group, the REE was significantly correlated with PNA (Figure 2Go, r=0.57, P=0.003), lean body mass (r=0.71, P=0.001), and creatinine clearance (r=0.60, P=0.001). No significant correlations were found between REE and serum glucose or HbA1c. In the same way, in the CRF control group, the REE was significantly correlated with PNA (r=0.40, P=0.05) and with lean body mass (r=0.57, P=0.003).



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Fig. 2. Correlation between the protein equivalent of nitrogen appearance (PNA) and resting energy expenditure (REE) in the CRF diabetes group (n=24; r=0.57; P=0.003).

 
In a multiple linear regression analysis of both groups of patients combined (n=48) evaluating REE as a dependent variable, we tested as independent variables those that were significant (P<=0.05) in the univariate analysis: patient group (CRF diabetes and CRF control), lean body mass, PNA and energy intake. This analysis showed that the only significant independent predictors of REE were lean body mass (r2=0.36) and patient group (r2=0.10); i.e the fact of being diabetic caused an increase in the REE of 182.24 kcal. The regression equation (r2=0.46) obtained for the REE of CRF patients was:

REE (kcal/day)=325.84+[19.792xlean body mass (kg)]+[182.24xpatient group*]

*Patient group=0, if CRF control and=1, if CRF diabetes.



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 
The main finding of this study was the demonstration that diabetic patients with CRF presented a significantly higher REE than renal failure patients without diabetes. In fact, CRF diabetes patients had a REE 12.5% higher than CRF controls matched for age, gender and renal function and remained significantly higher even when adjusted for lean body mass, the main determinant of REE [24]. Disturbances of thyroid function, secondary hyperparathyroidism and acid–base disorders did not seem to account for the higher REE observed in the CRF diabetes patients. The diabetic patients as well as their controls presented normal levels of T4 and TSH, most of them did not have acidosis and had similar and modest elevations in parathyroid hormone levels. Moreover, patients were not in ketoacidosis, since the mean respiratory quotient of CRF diabetes and of both groups indicates a mixed substrate utilization (Table 3Go). As only three patients of the CRF diabetes group had type I DM, the occurrence of large lipid consumption with ketonic bodies generation and acidosis in the whole population is unlikely. Previous measurements of REE in patients with CRF and DM are lacking. In the absence of renal impairment, it has been demonstrated that poorly controlled type I and II diabetic patients have enhanced REE [2,3,6,8] which is reduced after glucose control with insulin therapy [7,9], implicating the metabolic derangements of diabetes in that condition. In the present study, although we did not find a correlation between REE and HbA1c, many patients had a poor glucose control. In fact, fasting blood glucose was above 130 mg/dl in 54% of the patients and, more importantly, HbA1cwas higher than 4.3% in 96% of them. As both group of patients presented a similar degree of renal impairment, it is reasonable to attribute the higher REE observed in CRF diabetes patients to the metabolic derangements of diabetes. This assumption is further supported by the fact that in the multiple regression analysis, the fact of being diabetic added 182.24 kcal to the REE. In uncontrolled type I and II diabetic patients, some authors have stressed the role of insulin deficiency and/or hyperglucagonaemia in promoting an elevation in REE by increasing the rate of gluconeogenesis with proteolysis and amino-acid oxidation [2,3,68]. These metabolic pathways are known as high energy-consuming processes [2,3] and could be present in the diabetic patients of this study. An interaction between the metabolic alterations of renal failure and that of diabetes could also be hypothesized. In diabetic rats, Price et al. [25] demonstrated that insulinopenia causes muscle proteolysis by activating the ATP-dependent ubiquitin proteasome pathway. On the other hand, in CRF, acidosis induces proteolysis by the activation of the same pathway, and degradation of branched-chain amino acids [26]. Thus, we may speculate that the metabolic derangements of diabetes, interacting with those of CRF, could exacerbate protein breakdown and promote a negative nitrogen balance [10,11,14]. This assumption, however, needs further confirmation.

The diabetic patients included in this study did not present evidence of protein–energy malnutrition. In fact, besides presenting normal albumin and transferrin serum levels, they had a mean body mass index indicative of overweight and their body fat stores were normal or even increased. Contrasting with these nutritional indices, the diabetic patients as well as their controls had a low energy intake that could induce weight loss and malnutrition. Such a paradox was also observed in a longitudinal study [27]. However, a neutral or even positive nitrogen balance has been achieved in CRF patients with energy intake in the same range as that observed in this study [28]. This condition may have occurred in our patients, but eventual errors of food diaries hinder an appropriate analysis of these results. The diabetic patients presented higher PNA than controls, probably as a consequence of an increased protein intake. We cannot exclude, however, an enhanced protein catabolism. Indeed, the REE correlated significantly with PNA in both groups of patients. This observation might suggest a causal relationship between protein catabolism and increased REE.

Finally, this study showed that the REE is higher in CRF patients with DM and suggests that a poor glycaemic control may have contributed to this condition. The long-term repercussions on the increased REE on nutritional status of these patients need further investigations.



   Acknowledgments
 
This study was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and by Fundação Oswaldo Ramos.



   Notes
 
Correspondence and offprint requests to: Sérgio A. Draibe MD PhD, Rua Borges Lagoa, no. 960. CEP: 04038-002, São Paulo, SP, Brazil. Back



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Methods
 Results
 Discussion
 References
 

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Received for publication: 4. 2.00
Revision received 11.10.00.