Clinical Accuracy of the MedGem Indirect Calorimeter for Measuring Resting Energy Expenditure in Cancer Patients

OBJECTIVE: To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGem) and predicted REE. DESIGN: Cross-sectional clinical validation study. SETTING: Private radiation oncology centre, Brisbane, Australia. SUBJECTS: Cancer patients (n = 18) and healthy subjects (n = 17) aged 37-86 y, with body mass indices ranging from 18 to 42 kg/m(2). INTERVENTIONS: Oxygen consumption (VO(2)) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris-Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%. RESULTS: The mean bias (MGN-VM) was 10% and limits of agreement were -42 to 21% for cancer patients; mean bias -5% with limits of -45 to 35% for healthy subjects. Less than half of the cancer patients (n = 7, 46.7%) and only a third (n = 5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB-VM) of -5% for cancer patients and 4% for healthy subjects, with limits of agreement of -30 to 20% and -27 to 34%, respectively. CONCLUSIONS: Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

Ability of commonly used prediction equations to predict resting energy expenditure in children with inflammatory bowel disease

Background: Paediatric onset inflammatory bowel disease (IBD) may cause alterations in energy requirements and invalidate the use of standard prediction equations. Our aim was to evaluate four commonly used prediction equations for resting energy expenditure (REE) in children with IBD. Methods: Sixty-three children had repeated measurements of REE as part of a longitudinal research study yielding a total of 243 measurements. These were compared with predicted REE from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict equations using the Bland-Altman method. Results: Mean (±SD) age of the patients was 14.2 (2.4) years. Mean measured REE was 1566 (336) kcal per day compared with 1491 (236), 1441 (255), 1481 (232), and 1435 (212) kcal per day calculated from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict, respectively. While the Schofield equation demonstrated the least difference between measured and predicted REE, it, along with the other equations tested, did not perform uniformly across all subjects, indicating greater errors at either end of the spectrum of energy expenditure. Smaller differences were found for all prediction equations for Crohn's disease compared with ulcerative colitis. Conclusions: Of the commonly used equations, the equation of Schofield should be used in pediatric patients with IBD when measured values are not able to be obtained. (Inflamm Bowel Dis 2010;) Copyright © 2010 Crohn's & Colitis Foundation of America, Inc.

Resting energy expenditure in children with inflammatory bowel disease

OBJECTIVES: There is controversy in the literature regarding the effect of inflammatory bowel disease (IBD) on resting energy expenditure (REE). In many cases this may have resulted from inappropriate adjustment of REE measurements to account for differences in body composition. This article considers how to appropriately adjust measurements of REE for differences in body composition between individuals with IBD. PATIENTS AND METHODS: Body composition, assessed via total body potassium to yield a measure of body cell mass (BCM), and REE measurements were performed in 41 children with Crohn disease and ulcerative colitis in the Royal Children's Hospital, Brisbane, Australia. Log-log regression was used to determine the power function to which BCM should be raised to appropriately adjust REE to account for differences in body composition between children. RESULTS: The appropriate value to "adjust" BCM was found to be 0.49, with a standard error of 0.10. CONCLUSIONS: Clearly, there is a need to adjust for differences in body composition, or at the very least body weight, in metabolic studies in children with IBD. We suggest that raising BCM to the power of 0.5 is both a numerically convenient and a statistically valid way of achieving this aim. Under circumstances in which the measurement of BCM is not available, raising body weight to the power of 0.5 remains appropriate. The important issue of whether REE is changed in cases of IBD can then be appropriately addressed. © 2007 Lippincott Williams & Wilkins, Inc.

Comparison of the Cosmed K4 b2 and the Deltatrac II™ metabolic cart in measuring resting energy expenditure in adults

Background and Aims: The objective of the study was to compare data obtained from the Cosmed K4 b2 and the Deltatrac II™ metabolic cart for the purpose of determining the validity of the Cosmed K4 b2 in measuring resting energy expenditure. Methods: Nine adult subjects (four male, five female) were measured. Resting energy expenditure was measured in consecutive sessions using the Cosmed K4 b2, the Deltatrac II™ metabolic cart separately and the Cosmed K4 b2 and Deltatrac II™ metabolic cart simultaneously, performed in random order. Resting energy expenditure (REE) data from both devices were then compared with values obtained from predictive equations. Results: Bland and Altman analysis revealed a mean bias for the four variables, REE, respiratory quotient (RQ), VCO2, VO2 between data obtained from Cosmed K4 b2 and Deltatrac II™ metabolic cart of 268 ± 702 kcal/day, -0.0±0.2, 26.4±118.2 and 51.6±126.5 ml/min, respectively. Corresponding limits of agreement for the same four variables were all large. Also, Bland and Altman analysis revealed a larger mean bias between predicted REE and measured REE using Cosmed K4 b2 data (-194±603 kcal/day) than using Deltatrac™ metabolic cart data (73±197 kcal/day). Conclusions: Variability between the two devices was very high and a degree of measurement error was detected. Data from the Cosmed K4 b2 provided variable results on comparison with predicted values, thus, would seem an invalid device for measuring adults. © 2002 Elsevier Science Ltd. All rights reserved.

Validity of Resting Energy Expenditure Predictive Equations before and after an Energy-Restricted Diet Intervention in Obese Women

11 p.

Resting energy expenditure in non-ventilated, non-sedated patients recovering from serious traumatic brain injury: Comparison of prediction equations with indirect calorimetry values

Background & aims: Little is known about energy requirements in brain injured (TBI) patients, despite evidence suggesting adequate nutritional support can improve clinical outcomes. The study aim was to compare predicted energy requirements with measured resting energy expenditure (REE) values, in patients recovering from TBI.

Methods: Indirect calorimetry (IC) was used to measure REE in 45 patients with TBI. Predicted energy requirements were determined using FAO/WHO/UNU and Harris–Benedict (HB) equations. Bland– Altman and regression analysis were used for analysis.

Results: One-hundred and sixty-seven successful measurements were recorded in patients with TBI. At an individual level, both equations predicted REE poorly. The mean of the differences of standardised areas of measured REE and FAO/WHO/UNU was near zero (9 kcal) but the variation in both directions was substantial (range 591 to þ573 kcal). Similarly, the differences of areas of measured REE and HB demonstrated a mean of 1.9 kcal and range 568 to þ571 kcal. Glasgow coma score, patient status, weight and body temperature were signi?cant predictors of measured REE (p < 0.001; R²⁼ 0.47).

Conclusions: Clinical equations are poor predictors of measured REE in patients with TBI. The variability in REE is substantial. Clinicians should be aware of the limitations of prediction equations when estimating energy requirements in TBI patients.

Lower resting energy expenditure and fat oxidation in Native American and Hispanic infants born to mothers with diabetes

OBJECTIVE: To determine whether exposure to diabetes in utero affects resting energy expenditure (REE) and fuel oxidation in infants.

STUDY DESIGN: At 35 ± 5 days after birth, body composition and REE were measured in full-term offspring of Native American and Hispanic women with either well-controlled diabetes (13 girls, 11 boys) or normal healthy pregnancies (18 girls, 17 boys).

RESULTS: Control of dysglycemia during gestation in the women with diabetes mellitus met current clinical standards, shown by average glycated hemoglobin (5.9 ± 0.2%; 40.6 ± 2.3 mmol/mol). Infant body mass (offspring of women with diabetes: 4.78 ± 0.13, control offspring: 4.56 ± 0.08 kg) and body fatness (offspring of women with diabetes: 25.2 ± 0.6, control offspring: 24.2 ± 0.5 %) did not differ between groups. REE, adjusted for lean body mass, was 14% lower in offspring of women with diabetes (41.7 ± 2.3 kJ/h) than control offspring (48.6 ± 2.0, P = .025). Fat oxidation was 26% lower in offspring of women with diabetes (0.54 ± 0.05 g/h) than control offspring (0.76 ± 0.04, P < .01) but carbohydrate oxidation did not differ. Thus, fat oxidation accounted for a lower fraction of REE in the offspring of women with diabetes (49 ± 4%) than control offspring (60 ± 3%, P = .022). Mothers with diabetes were older and had higher prepregnancy body mass index than control mothers.

CONCLUSIONS: Well-controlled maternal diabetes did not significantly affect body mass or composition of offspring at 1-month old. However, infants with mothers with diabetes had reduced REE and fat oxidation, which could contribute to adiposity and future disease risk. Further studies are needed to assess the impact differences in age and higher prepregnancy body mass index.

Resting energy expenditure and carbohydrate oxidation are higher in elderly patients with COPD: a case control study

Background: Elderly patients with chronic obstructive pulmonary disease (COPD) usually have a compromised nutritional status which is an independent predictor of morbidity and mortality. To know the Resting Energy Expenditure (REE) and the substrate oxidation measurement is essential to prevent these complications. This study aimed to compare the REE, respiratory quotient (RQ) and body composition between patients with and without COPD.Methods: This case-control study assessed 20 patients with chronic obstructive pulmonary disease attending a pulmonary rehabilitation program. The group of subjects without COPD (control group) consisted of 20 elderly patients attending a university gym, patients of a private service and a public healthy care. Consumption of oxygen (O-2) and carbon dioxide (CO2) was determined by indirect calorimetry and used for calculating the resting energy expenditure and respiratory quotient. Body mass index (BMI) and waist circumference (WC) were also measured. Percentage of body fat (%BF), lean mass (kg) and muscle mass (kg) were determined by bioimpedance. The fat free mass index (FFMI) and muscle mass index (MMI) were then calculated.Results: The COPD group had lower BMI than control (p = 0.02). However, WC, % BF, FFMI and MM-I did not differ between the groups. The COPD group had greater RQ (p = 0.01), REE (p = 0.009) and carbohydrate oxidation (p = 0.002).Conclusions: Elderly patients with COPD had higher REE, RQ and carbohydrate oxidation than controls.

Comparison of predictive equations for resting energy expenditure in overweight and obese adults

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Resting energy expenditure is lower than predicted in people taking atypical antipsychotic medication

Resting energy expenditure (REE) is lower than predicted in persons taking atypical antipsychotic medication, and weight management is a significant clinical challenge for some of them. However, to date there have been no published guidelines to assist clinicians in choosing appropriate prediction equations to estimate energy expenditure in persons taking atypical antipsychotic medications. The objectives of this study were to measure REE in a group of men taking the atypical antipsychotic clozapine and to determine whether REE can be accurately predicted for this population using previously published regression equations. REE was measured using indirect calorimetry via a ventilated hood on eight men who had completed at least 6 months of treatment with clozapine. Comparisons between measured REE and predicted REE using five different equations were undertaken. The commonly-used Harris-Benedict and Schofield equations systematically overestimated REE. Predictions of REE from other equations were too variable for clinical use. When estimating energy requirements as part of a weight-management program in men who have been taking clozapine for 6 months, predictions of REE from the equations of Harris-Benedict and Schofield should be reduced by 280 kcal/day.