136 resultados para MedGem Indirect Calorimeter, Energy Expenditure, Ancer Patients

em Queensland University of Technology - ePrints Archive


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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.

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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.

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Background: Better understanding of body composition and energy metabolism in pediatric liver disease may provide a scientific basis for improved medical therapy aimed at achieving optimal nutrition, slowing progression to end-stage liver disease (ESLD), and improving the outcome of liver transplantation. Methods: Twenty-one children less than 2 years of age with ESLD awaiting liver transplantation and 15 healthy, aged-matched controls had body compartment analysis using a four compartment model (body cell mass, fat mass, extracellular water, and extracellular solids). Subjects also had measurements of resting energy expenditure (REE) and respiratory quotient (RQ) by indirect calorimetry. Nine patients and 15 control subjects also had measurements of total energy expenditure (TEE) using doubly labelled water. Results: Mean weights and heights were similar in the two groups. Compared with control subjects, children with ESLD had higher relative mean body cell mass (33 ± 2% vs 29 ± 1% of body weight, P < 0.05), but had similar fat mass, extracellular water, and extracellular solid compartments (18% vs 20%, 41% vs 38%, and 7% vs 13% of body weight respectively). Compared with control subjects, children with ESLD had 27% higher mean REE/body weight (0.285 ± 0.013 vs 0.218. ± 0.013 mJ/kg/24h, P < 0.001), 16% higher REE/unit cell mass (P < 0.05); and lower mean RQ (P < 0.05). Mean TEE of patients was 4.70 ± 0.49 mJ/24h vs 3.19 ± 0.76 in controls, (P < 0.01). Conclusions: In children, ESLD is a hypermetabolic state adversely affecting the relationship between metabolic and non-metabolic body compartments. There is increased metabolic activity within the body cell mass with excess lipid oxidation during fasting and at rest. These findings have implications for the design of appropriate nutritional therapy.

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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.

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Poor nutritional status in patients with cystic fibrosis (CF) is associated with severe lung disease, and possible causative factors include inadequate intake, malabsorption, and increased energy requirements. Body cell mass (which can be quantified by measurement of total body potassium) provides an ideal standard for measurements of energy expenditure. The aim of this study was to compare resting energy expenditure (REE) in patients with CF with both predicted values and age-matched healthy children and to determine whether REE was related to either nutritional status or pulmonary function. REE was measured by indirect calorimetry and body cell mass by scanning with total body potassium in 30 patients with CF (12 male, mean age = 13.07 ± 0.55 y) and 18 healthy children (six male, mean age = 12.56 ± 1.25 y). Nutritional status was expressed as a percentage of predicted total body potassium. Lung function was measured in the CF group by spirometry and expressed as the percentage of predicted forced expiratory volume in 1 s. Mean REE was significantly increased in the patients with CF compared with healthy children (119.3 ± 3.1% predicted versus 103.6 ± 5% predicted, P < 0.001) and, using multiple regression techniques, REE for total body potassium was significantly increased in patients with CF (P = 0.0001). There was no relation between REE and nutritional status or pulmonary disease status in the CF group. In conclusion, REE is increased in children and adolescents with CF but is not directly related to nutritional status or pulmonary disease.

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Objective: Walking is commonly recommended to help with weight management. We measured total energy expenditure (TEE) and its components to quantify the impact of increasing exercise-induced energy expenditure (ExEE) on other components of TEE. Methods: Thirteen obese women underwent an 8-week walking group intervention. TEE was quantified using doubly labeled water, ExEE was quantified using heart rate monitors, daily movement was assessed by accelerometry and resting metabolic rate was measured using indirect calorimetry. Results: Four of the 13 participants achieved the target of 1500 kcal wk−1 of ExEE and all achieved 1000 kcal wk−1. The average ExEE achieved by the group across the 8 weeks was 1434 ± 237 kcal wk−1. Vigorous physical activity, as assessed by accelerometry, increased during the intervention by an average of 30 min per day. Non-exercise activity thermogenesis (NEAT) decreased, on average, by 175 kcal d−1 (−22%) from baseline to the intervention and baseline fitness was correlated with change in NEAT. Conclusions: Potential alterations in non-exercise activity should be considered when exercise is prescribed. The provision of appropriate education on how to self-monitor daily activity levels may improve intervention outcomes in groups who are new to exercise. Practice implications: Strategies to sustain incidental and light physical activity should be offered to help empower individuals as they develop and maintain healthy and long-lasting lifestyle habits.

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Objectives In non-alcoholic fatty liver disease (NAFLD), hepatic steatosis is intricately linked with a number of metabolic alterations. We studied substrate utilisation in NAFLD during basal, insulin-stimulated and exercise conditions, and correlated these outcomes with disease severity. Methods 20 patients with NAFLD (mean±SD body mass index (BMI) 34.1±6.7 kg/m2) and 15 healthy controls (BMI 23.4±2.7 kg/m2) were assessed. Respiratory quotient (RQ), whole-body fat (Fatox) and carbohydrate (CHOox) oxidation rates were determined by indirect calorimetry in three conditions: basal (resting and fasted), insulin-stimulated (hyperinsulinaemic–euglycaemic clamp) and exercise (cycling at an intensity to elicit maximal Fatox). Severity of disease and steatosis were determined by liver histology, hepatic Fatox from plasma β-hydroxybutyrate concentrations, aerobic fitness expressed as , and visceral adipose tissue (VAT) measured by computed tomography. Results Within the overweight/obese NAFLD cohort, basal RQ correlated positively with steatosis (r=0.57, p=0.01) and was higher (indicating smaller contribution of Fatox to energy expenditure) in patients with NAFLD activity score (NAS) ≥5 vs <5 (p=0.008). Both results were independent of VAT, % body fat and BMI. Compared with the lean control group, patients with NAFLD had lower basal whole-body Fatox (1.2±0.3 vs 1.5±0.4 mg/kgFFM/min, p=0.024) and lower basal hepatic Fatox (ie, β-hydroxybutyrate, p=0.004). During exercise, they achieved lower maximal Fatox (2.5±1.4 vs. 5.8±3.7 mg/kgFFM/min, p=0.002) and lower (p<0.001) than controls. Fatox during exercise was not associated with disease severity (p=0.79). Conclusions Overweight/obese patients with NAFLD had reduced hepatic Fatox and reduced whole-body Fatox under basal and exercise conditions. There was an inverse relationship between ability to oxidise fat in basal conditions and histological features of NAFLD including severity of steatosis and NAS

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Purpose This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. Results None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.

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Purpose The aim of this study was to assess the predictive validity of three accelerometer prediction equations (Freedson et aL, 1997; Trost et aL, 1998; Puyau et al., 2002) for energy expenditure (EE) during overland walking and running in children and adolescents. Methods 45 healthy children and adolescents aged 10-18 completed the following protocol, each task 5-mins in duration, with a 5-min rest period in between; walking normally; walking briskly; running easily and running fast. During each task participants wore MTI (WAM 7164) Actigraphs on the left and right hips. VO2 was monitored breath by breath using the Cosmed K4b2 portable indirect calorimetry system. For each prediction equation, difference scores were calculated as EE measured minus EE predicted. The percentage of 1-min epochs correctly categorized as light (<3 METs), moderate (3-5.9 METs), and vigorous (≥6 METS) was also calculated. Results The Freedson and Trost equations consistently overestimated MET level. The level of overestimation was statistically significant across all tasks for the Freedson equation, and was significant for only the walking tasks for the Trost equation. The Puyau equation consistently underestimated AEE with the exception of the walking normally task. In terms of categorisation, the Freedson equation (72.8% agreement) demonstrated better agreement than the Puyau (60.6%). Conclusions These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overland walking and running. However, the cut points generated by these equations maybe useful for classifying activity as either, light, moderate, or vigorous.

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Although a number of studies have examined the role of gastric emptying (GE) in obesity, the influences of habitual physical activity level, body composition and energy expenditure (EE) on GE have received very little consideration. In this study, we have compared GE in active and inactive males, and we have characterised relationships with body composition (fat and fat free mass) and EE. Forty-four males (Active: n=22, Inactive: n=22; range BMI 21-36kg/m2; range percent fat mass 9-42%) were studied, with GE of a standardised (1676 kJ) pancake meal being assessed by 13C-octanoic acid breath test, body composition by air displacement plethysmography, resting metabolic rate (RMR) by indirect calorimetry and activity EE (AEE) by accelerometry. Results showed that GE was faster in active compared to inactive males (mean ±SD half time (t1/2): Active: 157±18 and Inactive: 179±21 min, p<0.001). When data from both groups were pooled, GE t1/2 was associated with percent fat mass (r=0.39, p<0.01) and AEE (r =-0.46, p<0.01). After controlling for habitual physical activity status, the association between AEE and GE remained, but not that for percent fat mass and GE. BMI and RMR were not associated with GE. In summary, faster GE is considered to be a marker of a habitually active lifestyle in males, and is associated with a higher AEE and lower percent fat mass. The possibility that GE contributes to a gross physiological regulation (or dysregulation) of food intake with physical activity level deserves further investigation.

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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.

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Background The most common pathway to development of diabetes foot ulcers is repetitive daily activity stress on the plantar surface of the neuropathic foot. Studies suggest an association between different diabetic foot complications and physical activity. However, to the best of the authors knowledge the steps/day and sleep patterns of people with diabetic foot ulcers has yet to be investigated. This observational study aims to investigate the physical activity and sleep patterns of three groups of adults with type 2 diabetes and different foot complications Methods Participants with type 2 diabetes were recruited into three groups: 1. those with no reported foot complications (DNIL), 2. those with diagnosis of neuropathy (DPN) and 3. those with a neuropathic ulcer (DFU). Exclusion criteria included peripheral arterial disease and mobility aid use. Participants wore a SenseWear Pro 3 Armband continuously for 7 days and completed an Epworth Sleepiness Scale. The Armband is a validated automated measure of activity (walking steps, average Metabolic Equivalent Task (MET), physical activity (>3 METs) duration), energy expenditure(kJ) (total and physical activity (>3 METs)) and sleep (duration). Data on age, sex, BMI, diabetes duration and HbA1c were also collected. Results Sixty-Six (14 DNIL, 22 DPN and 30 DFU's participants were recruited; 71% males, mean age 61(±12) years, diabetes duration 13(±9) years, HbA1c 8.3(±2.8), BMI 32.6(±5.9), average METs 1.2(0.2). Significant differences were reported in mean(SD) steps/day (5,859(±2,381) in DNIL; 5,007(±3,349) in DPN and 3,271(±2,417) in DFU's and daily energy expenditure (10,868(±1,307)kJ in DNIL; 11,060(±1,916)kJ in DPN and 13,006(± 3,559) in DFU's(p <0.05). No significant differences were reported for average METs, physical activity duration or energy expenditure, sleep time or Epworth score (p>0.1). Conclusions Preliminary findings suggest people with diabetes are sedentary. Results indicate that patients with a diabetic foot ulcer work significantly less than those with neuropathy or nil complications and use significantly more energy to do so. Sleep Parameters showed no differences. Recruitment is still on going.

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This book disseminates current information pertaining to the modulatory effects of foods and other food substances on behavior and neurological pathways and, importantly, vice versa. This ranges from the neuroendocrine control of eating to the effects of life-threatening disease on eating behavior. The importance of this contribution to the scientific literature lies in the fact that food and eating are an essential component of cultural heritage but the effects of perturbations in the food/cognitive axis can be profound. The complex interrelationship between neuropsychological processing, diet, and behavioral outcome is explored within the context of the most contemporary psychobiological research in the area. This comprehensive psychobiology- and pathology-themed text examines the broad spectrum of diet, behavioral, and neuropsychological interactions from normative function to occurrences of severe and enduring psychopathological processes