Using an Allometric Equation to Accurately Predict the Energy Expenditure of Children and Adolescents With Nonalcoholic Fatty Liver Disease

Background : Pediatric patients with nonalcoholic fatty liver disease (NAFLD) require targeted nutrition therapy that relies on calculating energy needs. Common energy equations are inaccurate in predicting resting energy expenditure (REE), influencing total energy expenditure (TEE) estimates. Equations based on allometric scaling are simple, accurate, void of subjective activity and/or stress factor bias, and they estimate TEE. Objective : To investigate the predictive accuracy of an allometric energy equation (AEE) in predicting TEE of children and adolescents with NAFLD. Methods : Retrospective study performed in a single institution. The allometric equation was used to calculate AEE, and the results were compared with TEE calculated using indirect calorimetry data (measured REE) multiplied by an activity factor (AF) of 1.5 or 1.7. Results : Fifty‐six patients with a mean age of 13 years were included in this study. The agreement between TEE (using an AF of 1.5) and AEE was ?96 kcal/d (confidence interval, ?29 to 221). The predictive accuracy of the allometric equation was not different between obese and nonobese patients. Conclusions : Allometric equations allow for accurate estimation of TEE in children with NAFLD.     

Energy Expenditure in Critically Ill Elderly Patients: Indirect Calorimetry vs Predictive Equations

Background: Predictive equations (PEs) are used for estimating resting energy expenditure (REE) when the measurements obtained from indirect calorimetry (IC) are not available. This study evaluated the degree of agreement and the accuracy between the REE measured by IC (REE‐IC) and REE estimated by PE (REE‐PE) in mechanically ventilated elderly patients admitted to the intensive care unit (ICU). Methods: REE‐IC of 97 critically ill elderly patients was compared with REE‐PE by 6 PEs: Harris and Benedict (HB) multiplied by the correction factor of 1.2; European Society for Clinical Nutrition and Metabolism (ESPEN) using the minimum (ESPENmi), average (ESPENme), and maximum (ESPENma) values; Mifflin–St Jeor; Ireton‐Jones (IJ); Fredrix; and Lührmann. Degree of agreement between REE‐PE and REE‐IC was analyzed by the interclass correlation coefficient and the Bland‐Altman test. The accuracy was calculated by the percentage of male and/or female patients whose REE‐PE values differ by up to ±10% in relation to REE‐IC. Results: For both sexes, there was no difference for average REE‐IC in kcal/kg when the values obtained with REE‐PE by corrected HB and ESPENme were compared. A high level of agreement was demonstrated by corrected HB for both sexes, with greater accuracy for women. The best accuracy in the male group was obtained with the IJ equation but with a low level of agreement. Conclusions: The effectiveness of PEs is limited for estimating REE of critically ill elderly patients. Nonetheless, HB multiplied by a correction factor of 1.2 can be used until a specific PE for this group of patients is developed.     

Approximation of Resting Energy Expenditure in Intensive Care Unit Patients Using the SenseWear Bracelet: A Comparison With Indirect Calorimetry

Background and Aims: Indirect calorimetry (IC) is the gold standard for determining energy expenditure in patients requiring mechanical ventilation. Metabolic armbands using data derived from dermal measurements have been proposed as an alternative to IC in healthy subjects, but their utility during critical illness is unclear. The aim of this study was to determine the level of agreement between the SenseWear armband and the Deltatrac Metabolic Monitor in mechanically ventilated intensive care unit (ICU) patients. Methods: Adult ICU patients requiring invasive ventilator therapy were eligible for inclusion. Simultaneous measurements were performed with the SenseWear Armband and Deltatrac under stable conditions. Resting energy expenditure (REE) values were registered for both instruments and compared with Bland‐Altman plots. Results: Forty‐two measurements were performed in 30 patients. The SenseWear Armband measured significantly higher REE values as compared with IC (mean bias, 85 kcal/24 h; P = .027). Less variability was noted between individual SenseWear measurements and REE as predicted by the Harris‐Benedict equation (2 SD, ±327 kcal/24 h) than when IC was compared with SenseWear and Harris‐Benedict (2 SD, ±473 and ±543 kcal/24 h, respectively). Conclusions: The systematic bias and large variability of the SenseWear armband when compared with gas exchange measurements confer limited benefits over the Harris Benedict equation in determining caloric requirements of ICU patients.     

Total daily energy expenditure in wasted chronic obstructive pulmonary disease patients

OBJECTIVES: To investigate total daily energy expenditure in chronic obstructive pulmonary disease (COPD) patients during a rehabilitation programme. DESIGN: Observational study involving a case and a control group. SUBJECTS: Ten COPD patients (six with body mass index (BMI) <18.5 kg/m(2) and four with BMI >18.5 kg/m(2)) were evaluated for their energy expenditure profile. Four additional healthy age-matched volunteers were also included for methodology evaluation. INTERVENTIONS: Measurements of total daily energy expenditure (TEE), resting energy expenditure (REE) and diet-induced thermogenesis (DIT) and energy intake were undertaken by indirect calorimetry and bicarbonate-urea methods and dietary records. RESULTS: REE in COPD patients was not significantly different from that predicted by the Harris-Benedict equation. Before the exercise day the mean TEE was 1508 kcal/day and physical activity level (PAL as calculated by TEE/REE) was 1.52. On the exercise day the TEE increased to 1568 kcal/day and PAL was 1.60, but neither of these changes were significant. The energy cost of increased physical activity during rehabilitation exercise was estimated to be 191 kcal/day. No significant change was found in DIT between the two patient groups. However, overall energy balances were found to be negative (-363 kcal/day). CONCLUSION: The rehabilitation programme did not cause a significant energy demand in COPD patients. TEE in COPD patients was not greater than in free-living healthy subjects. Patients, who were underweight, did not have a higher TEE than patients with normal weight. This suggested that malnutrition in COPD patients was not due to an increased energy expenditure. On the other hand, a significant negative energy balance due to insufficient energy intake was found in seven out of 10 patients.     

Energy Expenditure After Liver Resection: Validation of a Mobile Device for Estimating Resting Energy Expenditure and an Investigation of Energy Expenditure Change After Liver Resection

Background: Resting energy expenditure (REE) is the major component of total energy expenditure. REE is traditionally performed by indirect calorimetry (IC) and is not well investigated after liver surgery. A mobile device (SenseWear Armband [SWA]) has been validated when estimating REE in other clinical settings but not liver resection. The aims of this study are to validate SWA vs IC, quantify REE change following liver resection, and determine factors associated with REE change. Materials and Methods: Patients listed for open liver resection prospectively underwent IC and SWA REE recordings pre‐ and postoperatively. In addition, the SWA was worn continuously postoperatively to estimate daily REE for the first 5 postoperative days. To determine acceptability of the SWA, validation analysis was performed. To assess REE change, peak postoperative REE was compared with preoperative levels. Factors associated with REE change were also analyzed. Results: SWA showed satisfactory validity compared with IC when estimating REE, although postoperatively, the 95% levels of agreement (–5.56 to 3.18 kcal/kg/d) may introduce error. Postoperative REE (median, 23.5 kcal/kg/d; interquartile range [IQR], 22.6–25.7 kcal/kg/d) was significantly higher than predicted REE (median, 19.7 kcal/kg/d; IQR, 19.1–21.0 kcal/kg/d; P < .0001). Median REE rise was 11% (IQR, –1% to 25%). Factors associated with REE rise of >11% were age (P = .017) and length of operation (P = .03). Conclusions: SWA offers a suitable alternative to IC when estimating postoperative REE, but the magnitude of the error (8.74 kcal/kg/d) could hinder its accuracy. REE quantification after liver resection is important to identify patients who could be prone to energy imbalance and therefore malnutrition.     

Resting Energy Expenditure in Critically Ill Patients With Spontaneous Intracranial Hemorrhage

Background: Data on energy requirements of patients with spontaneous intracranial hemorrhage (SICH) are scarce. The objective of this study was to determine the resting energy expenditure (REE) in critically ill patients with SICH and to compare it with the predicted basal metabolic rate (BMR). Methods: In 30 nonseptic patients with SICH, the REE was measured during the 10 first posthemorrhage days with the use of indirect calorimetry (IC). Predicted BMR was also evaluated by the Harris‐Benedict (HB) equation. Bland‐Altman analysis was used to evaluate the agreement between measured and predicted values. The possible effect of confounding factors (demographics, disease, and severity of illness score) on the evolution of continuous variables was also tested. Results: mean predicted BMR, calculated by the HB equation, was 1580.3 ± 262 kcal/d, while measured REE was 1878.9 ± 478 kcal/d (117.5% BMR). Compared with BMR, measured REE values showed a statistically significant increase at all studied points (P < .005). Measured and predicted values showed a good correlation (r = 0.73, P < .001), but the test of agreement between the 2 methods with the Bland‐Altman analysis showed a mean bias (294.6 ± 265.6 kcal/d) and limits of agreement (–226 to 815.29 kcal/d) that were beyond the clinically acceptable range. REE values presented a trend toward increase over time (P = .077), reaching significance (P < .005) after the seventh day. Significant correlation was found between REE and temperature (P = .002, r = 0.63), as well as between REE and cortisol level (P = .017, r = 0.62) on the 10th day. No correlation was identified between REE and depth of sedation, as well as Acute Physiology and Chronic Health Evaluation II, Glasgow Coma Scale, and Hunt and Hess scores. Conclusions: During the early posthemorrhagic stage, energy requirements of critically ill patients with SICH are increased, presenting a trend toward increase over time. Compared with IC, the HB equation underestimates energy requirements and is inefficient in detecting individual variability of REE in this group of patients.     

Resting energy expenditure and nutritional state in patients with liver cirrhosis before and after liver transplantation

Resting energy expenditure (REE), body composition, and the biochemical parameters of liver function were measured in 26 patients before and 432 days (range: 103-1022 days) after liver transplantation (LTX). PreLTX REE was variable (mean: 1638 +/- 308 kcal/day, range: 1220-2190 kcal/day or +10 +/- 11% of Harris Benedict = HB prediction, range: -19 - +33%) and was closely related to body cell mass (r = 0.66, p < 0.0003). PostLTX REE was variable (mean: 1612 +/- 358 kcal/day, range: 1010-2490 kcal/day or +5 +/- 15% of HB prediction, range: -20 - +37%) and was closely related to body cell mass (r = 0.65, p < 0.0006). When compared with preLTX values only small changes in mean REE (-71 +/- 43 kcal/day) and a close correlation between pre and postLTX REE (r = 0.82, p < 0.001) were observed. In contrast to REE, changes in body weight were highly variable (-16.5 - +32.7 kg/year). This variance was not explained by the number of postoperative complications, pre and postLTX liver function, possible graft rejection and/or hepatitis reinfection. Pre-operative hypermetabolism (i.e. REE >+20% of HB prediction) was associated with postoperative hypermetabolism and a reduced liver function before and after LTX. Hypermetabolic patients had a poorer nutritional outcome after LTX (weight change: 0 +/- 8.4 kg/year) when compared with normometabolic controls (weight change: +5.7 +/- 7.4 kg/year; p < 0.05). There was no significant association between deviations in pre and postLTX REE and changes in body weight. When corrected for changes in the nutritional state our data provide evidence for the persistence of resting energy expenditure in liver transplant patients.     

Low physical activity reduces total energy expenditure in women with rheumatoid arthritis: implications for dietary intake recommendations

BACKGROUND: Rheumatoid arthritis (RA) causes cachexia, a metabolic response characterized by loss of muscle mass and elevated resting energy expenditure (REE). However, energy expenditure in physical activity in subjects with RA is lower than that in healthy subjects. It is not known which effect predominates in regulating total energy expenditure (TEE), and thus whether the dietary energy requirements of subjects with RA are higher or lower than those of healthy subjects. OBJECTIVE: Our objective was to determine TEE in women with RA by using the reference method of doubly labeled water ((2)H(2)(18)O). DESIGN: In this case-control study, we examined 20 women with RA and 20 healthy women who were matched for age and body mass index. RESULTS: The patients with RA were cachectic (their body cell mass was 14% lower than that of the controls, P < 0.001), but REE was not elevated, reflecting good disease control. Mean (+/- SD) TEE was 1344 kJ/d lower in the patients than in the controls (9133 +/- 1335 compared with 10 477 +/- 1992 kJ/d; P < 0.02). The energy expenditure in physical activity of the patients was 1034 kJ/d lower than that of the controls (P < 0.04), which accounted for 77% of the difference in TEE between the 2 groups. The physical activity level (TEE/REE) of the patients also tended to be lower than that of the controls (1.70 +/- 0.24 compared with 1.89 +/- 0.36; P < 0.07). CONCLUSION: A low physical activity level is the main determinant of lower-than-normal TEE, and thus energy requirements, in women with RA.     

A feasibility study comparing two metabolic monitors in hospitalised patients following an ischaemic stroke

Background: Data on the energy requirements of patients following acute ischaemic stroke are scarce. A recent draft report highlighted the lack of data on physical activity levels during and following acute illness (SACN, 2009). The aims of this study were to establish if two metabolic monitors (CCM Express? and the Sensewear? armband) were feasible for use in hospitalised stroke patients and to determine the relative contributions of resting energy expenditure (REE) and physical activity to total energy expenditure (TEE). Methods: Eleven medically stable patients (seven male; four female) were recruited within 7 days of ischaemic stroke. Exclusion criteria: unable to give informed consent, receiving renal replacement therapy, body mass index (BMI) ≥ 50 kg m^?2, known nickel allergy or receiving end‐of‐life care. All subjects were fasted from midnight and REE was measured early in the morning using the CCM Express? for a period of up to 1 h (including establishment of steady‐state (i.e. <10% difference in minute to minute VO₂ and VCO₂ measurements over 5 min). Concurrently, TEE was measured using the Sensewear? armband for a period of 24 h. Assessments of patient acceptability and tolerance of both metabolic monitors were conducted by direct observation, completion of a checklist and, where clinically appropriate, a brief patient questionnaire. REE was compared with predicted basal metabolic rate (BMR) (Henry, 2005) and physical activity was estimated using the Metabolic Equivalent Task (MET) method, where 1.0 MET is equivalent to the energy expended at rest. Results: Mean age was 69.8 years (range 42–84 years) and mean (SD) BMI was 25.4 (5.2) kg m^?2. All subjects were able to tolerate measurement of REE using the CCM Express?, although the facemask caused some discomfort to one subject with facial abrasions. Mean (SD) REE was 1257 (357) kcal day^?1 and, perhaps unexpectedly, was lower than predicted BMR [1503 (226) kcal day^?1; t‐test, P = 0.07]. It was, however, difficult to achieve steady‐state in four patients; thus, these REE measurements were unreliable. All subjects were able to tolerate measurement of TEE using the Sensewear? armband. Mean (SD) TEE was 1663 (303) kcal day^?1. Physical activity on the ward was very low, with subjects expending very little more energy than would be expected at rest [METS = 1.01 (SD 0.15)]. Discussion: Both metabolic monitors were well tolerated by the subjects; however, the unreliable REE measurements in some patients made it impossible to determine the relative contribution of REE to TEE. The results obtained regarding TEE and the low activity level in this study were comparable to results reported in other metabolic studies of patients who have had a stroke (Weekes & Elia, 1992; Finestone et al., 2003; Leone & Pencharz, 2010). Conclusions: Both metabolic monitors were feasible for use in patients following ischaemic stroke; however, some measurements of REE using the CCM Express? were unreliable because of difficulties in establishing steady‐state and the reasons for this merit further investigation. In this group of patients, physical activity on the ward was very low following a stroke. References: Finestone, H.M., Greene‐Finestone, L.S., Foley, N.C. & Woodbury, M.G. (2003) Measuring longitudinally the metabolic demands of stroke patients. Stroke 34 , 502–507. Leone, A. & Pencharz, P.B. (2010) Resting energy expenditure in stroke patients who are dependent on tube feeding: a pilot study. Clin. Nutr. 29 , 370–372. Henry, C.J.K. (2005) Basal metabolic rate studies in humans: measurement and development of new equations. Public Health Nutr. 8 , 1133–1152. Scientific Advisory Committee on Nutrition (SACN) (2009) Energy Requirements Working Group Draft Report. London: SACN. Weekes, C.E. & Elia, M. (1992) Resting energy expenditure and body composition following cerebro‐vascular accident. Clin. Nutr. 11 , 18–22.     

Energy balance in cystic fibrosis when stable and during a respiratory exacerbation

Background & aims: Undernutrition is common in young adult patients with cystic fibrosis (CF) and implies an imbalance between energy intake and total energy expenditure (TEE). The aim of this study was to measure energy intake and TEE expenditure in a group of patients when they were clinically stable at home and during an exacerbation of respiratory symptoms when they were in hospital receiving intravenous antibiotics.Methods: Eleven patients aged between 15 and 40 years with moderate respiratory disease, mean FEV₁ 51.4% predicted took part. An exacerbation was defined as>15% decrease in FEV₁, an increase in sputum production and a decision to treat in hospital with intravenous antibiotics. Resting energy expenditure (REE) was measured using indirect calorimetry and energy intake by 3 day food diaries. TEE expenditure was measured using 24 h heart rate and doubly isotopically labelled water.Results: REE was higher at the beginning of an exacerbation than the end, P<0.05. There was no significant difference in TEE during the stable period compared to the exacerbation 10.53(2.39) MJ/day compared to 8.77(1.59) MJ/day using doubly isotopically labelled water. There was no difference in energy intake during the exacerbation compared to the stable period, 11.19(2.31) MJ/day compared to11.77(2.30) MJ/day.Conclusions: There was no difference in TEE and energy intake when patients were unwell in hospital compared to when they were stable at home despite an increase in REE.     

Energy balance in patients with pressure ulcers: a systematic review and meta-analysis of observational studies

Medical nutrition therapy is reported to contribute to wound healing. However, effective intervention requires an accurate estimation of individual energy needs, which, in turn, relies on accurate methods of assessment. The primary aims of this systematic review and meta-analysis were to evaluate the resting energy expenditure (REE) of patients with pressure ulcers (PUs) compared to matched control groups and the potential estimation bias of REE predictive equations. The recommended daily energy requirements of patients with PUs were also assessed, along with their energy balance (daily energy requirement vs intake). All language, original, full-text research articles published between January 1, 1950, and July 31, 2010, were searched through electronic databases. Relevant studies were also identified by reviewing citations. Observational (case-control and case-series) studies providing data on measured REE were initially included. Data extracted were measured REE, predicted REE, and daily energy intake. Five studies were included in the meta-analysis. Compared to controls (n=101), patients with PUs (n=92) presented higher measured REE (weighted mean 20.7±0.8 vs 23.7±2.2 kcal/kg/day; P<0.0001). In these patients, measured REE was also higher than predicted REE (calculated using the Harris-Benedict formula in all studies; 21.0±1.0 kcal/kg/day; P<0.0001), whereas energy intake (n=78; 21.7±3.1 kcal/kg/day) was significantly lower (P<0.0001) than total daily requirement, which was calculated as 29.4±2.7 kcal/kg/day. Patients with PUs are characterized by increased REE and reduced energy intake. In the estimation of REE using the Harris-Benedict formula, a correction factor (×1.1) should be considered to accurately assess energy needs. Moreover, an energy intake of 30 kcal/kg/day seems appropriate to cover the daily requirements of patients with PUs.     

A practical approach to estimate resting energy expenditure in frail elderly people

Objectives: Some prediction equations of resting energy expenditure (REE) are available and can be used in clinical wards to determine energy requirements of patients. The aim of the present study was to assess the accuracy of those equations in sick elderly patients, using the Bland & Altman methods with our database of 187 REE measurements.Design: The 3 equations tested were Harris & Benedict equation of 1919, WHO/FAO/UNU equation of 1985 and Fredrix et al. equation of 1990. In addition, three models developed from the present data were tested.Results: The present study shows that the Fredrix et al equation gave an accurate prediction of REE without significant bias along the whole range of REE. It also shows that under-weight sick elderly patients (BMI ≤ 21 kg/m²) had a greater weight-adjusted REE than their normal weight counterparts.Conclusion: A simple formula using a factor multiplying body weight, i.e. 22 kcal/kg/d in under-weight and 19 kcal/kg/d in normal weight sick elderly was accurate to predicting REE and bias was not influenced by the level of REE. This model included half of the group in the range of ±10% of the difference between predicted REE and measured REE, but the confidence interval of the bias was ±400 kcal/d. Conversely, the Harris & Benedict and WHO formulae did accurately predict REE.     

Measured versus predicted energy expenditure in children with inactive Crohn's disease

INTRODUCTION: The aim of the study was to assess if the estimated average requirements for energy for normal children (EAR) and the Schofield equation could reliably predict energy requirements in children with inactive Crohn's disease (CD). METHODS: Twenty-three children with inactive CD were studied, median age 14.3 years (range 7.8-16.9). Resting energy expenditure (REE) was measured by indirect calorimetry and compared with that predicted using the Schofield equation (BMR). Total energy expenditure (TEE) was measured using REE and a 3-day activity diary and compared with EAR. RESULTS: REE ranged from 79% to 136% of BMR. Mean REE was not significantly greater than mean BMR (P=0.25 2-tailed t-test). TEE ranged from 72% to 163% of estimated average requirements for energy for children of that weight (EARw). EARw tended to underestimate TEE in large children and overestimate TEE in small children (Bland-Altman plot R=0.5, P=0.002). EARw was a poor predictor of TEE (R=0.35, P=0.1). EAR underestimated energy requirements by >500 kcal/day in 40% of the children. CONCLUSIONS: The Schofield equation and EAR are unreliable methods of predicting total energy requirements in children with inactive CD with a significant potential to underestimate energy needs. When energy requirements were greater than EAR it was due to physical activity and body habitus rather than raised REE.     

Predicting resting energy expenditure in patients with musculoskeletal deformities

The aim of this study was to assess the validity of the commonly used equations (Harris-Benedict (HB), Schofield (S) and equations based on midarm circumference (MAC) and midarm muscle circumference (MAMC) in predicting resting energy expenditure (REE) in a population of patients with musculoskeletal deformities. 20 kyphoscoliotic patients (15 female (F); 5 male (M); mean age 59.6 years) and 10 controls (7 F; 3M; 59.8 years) were studied. REE measured by indirect calorimetry (IC) with a ventilated canopy system (Deltatrac metabolic monitor) was not significantly different between patients and controls (Mean (SD) REE (MJ/24 h): Patients: 5.48 (1.1); controls: 5.28(0.8)). In patients with deformities the Schofield equation gave values which were closest to measured REE (mean difference and limits of agreement IC vs S: 0.098 MJ/24 h; -0.822 and 1.018). The Harris-Benedict equation using height (Ht) and armspan (AS) in lieu of height also gave acceptable results (IC vs HB (Ht): 0.34; -0.638 and 1.318; IC vs HB (AS): 0.255; -0.683 and 1.253). Equations based on MAC and MAMC compared poorly (IC vs MAC equation: 0.398; -1.530 and 2.326; IC vs MAMC equation 0.687; -0.911 and 2.285). On regression analysis the equation REE = 0.295 (MAMC) + 0.0483 (AS) -0.0324 (age) -6.25 predicted REE best in the patient population (r(2) = 0.861).     

Indirect Calorimetry in Mechanically Ventilated Patients: A Prospective,Randomized, Clinical Validation of 2 Devices Against a Gold Standard

Background and Aims: The 2 currently available indirect calorimeters, CCM Express Indirect Calorimeter (MedGraphics, St Paul, MN) and Quark RMR ICU Indirect Calorimeter (COSMED, Rome, Italy), have not been validated against a gold standard in mechanically ventilated patients. Our aim was to do so using a gold‐standard, modified Tissot bell‐spirometer method in mechanically ventilated patients who were hemodynamically, respiratory, and metabolically stable. Methods: We studied 30 patients undergoing general anesthesia and major gynecological surgery. We measured oxygen consumption (O₂) and resting energy expenditure (REE) in a randomized, sequential, crossover design with double determination of each device. Results: Compared with the modified Tissot bell‐spirometer, the CCM Express Indirect Calorimeter demonstrated a mean Δ‐REE of +361 kcal/d, corresponding to a 31% overestimation of energy requirements. Bland‐Altman analysis for REE showed a mean (SD) bias of 384 (124) with limits of agreement 142–627 kcal/d. QUARK RMR ICU demonstrated a mean Δ‐REE of 81 kcal/d, corresponding to a 7% overestimation of energy requirements. Bland‐Altman plot analysis showed a mean (SD) bias of 77 (167) with limits of agreement ?249 to 404 kcal/d. Conclusions: The QUARK RMR ICU Indirect Calorimeter compared better with the gold standard for values of O₂ and REE than did the CCM Express Indirect Calorimeter in mechanically ventilated patients who were circulatory and respiratory stable. Both indirect calorimeters had low precision.     

Achievement of steady state optimizes results when performing indirect calorimetry

BACKGROUND: The use of steady state as the endpoint for performance of indirect calorimetry (IC) is controversial. We designed this prospective study to evaluate the necessity and significance of achieving steady state. METHODS: Patients with respiratory failure placed on mechanical ventilation in a short- or long-term acute care unit at any 1 of 3 university-based urban hospitals were eligible for the study. The 24-hour total energy expenditure (TEE) was determined by a Nellcor Puritan Bennett 7250 continuous IC monitor. Measured gas exchange parameters were obtained and averaged every 1 minute for the initial hour and then every 15 minutes for the next 23 hours. Over the initial hour, resting energy expenditure (REE) was averaged for intervals over the first 20, 30, 40, and 60 minutes, and for various definitions of steady state where oxygen consumption (VO2) and carbon dioxide production (VCO2) changed by <10%, 15%, and 20%. Coefficient of variation (CV) was calculated for VO2 over the first 30 minutes of study. RESULTS: Twenty-two patients (mean age, 52.8 years, 59% male, mean Acute Physiology and Chronic Health Evaluation (APACHE III) score 42.0) were entered in the study. The best correlation between short-term "snapshot" REE and the 24-hour TEE was achieved by the steady-state period defined by the most stringent criteria (change in VO2 and VCO2 by <10%). The average REE for all steady-state and interval periods correlated significantly to TEE with no significant difference in the absolute values for REE and TEE. Adding 10% for an activity factor to the average REE for each steady-state and interval period again correlated to TEE in a similar fashion with the same R value, but the absolute values for REE + 10% for all steady-state and interval periods were significantly different than the corresponding TEE. In those patients with less variation (CV for VO2 < or = 9.0), the REE obtained for the steady-state period defined by the most stringent criteria still had the best correlation, but similar correlation could be obtained by interval testing of > or = 30-minute duration. In those patients with greater variation (CV for VO2 >9.0), interval testing of at least 60 minutes or more was required to attain levels of correlation similar to that achieved by the steady-state period defined by the most stringent criteria. CONCLUSIONS: These data support the use of steady state, best defined as an interval of 5 consecutive minutes whereby VO2 and VCO2 change by <10%. The mean REE from this period correlates best to the 24-hour TEE regardless of CV. IC testing can be completed after achievement of steady state. Activity factors of 10% to 15% should not be added to the steady-state REE, because this practice significantly decreases the accuracy. In patients who fail to achieve steady state, the CV helps to determine the appropriate duration of IC testing. In those patients with a low CV (< or = 9.0), 30-minute test duration is adequate. In patients with CV >9.0, test duration of at least 60 minutes may be required. These latter patients should be considered for 24-hour IC testing.     

Hand-Held Indirect Calorimeter Offers Advantages Compared with Prediction Equations, in a Group of Overweight Women, to Determine Resting Energy Expenditures and Estimated Total Energy Expenditures during Research Screening

Objective

To compare standardized prediction equations to a hand-held indirect calorimeter in estimating resting energy and total energy requirements in overweight women.

Design

Resting energy expenditure (REE) was measured by hand-held indirect calorimeter and calculated by prediction equations Harris-Benedict, Mifflin-St Jeor, World Health Organization/Food and Agriculture Organization/United Nations University (WHO), and Dietary Reference Intakes (DRI). Physical activity level, assessed by questionnaire, was used to estimate total energy expenditure (TEE).

Subjects

Subjects (n=39) were female nonsmokers older than 25 years of age with body mass index more than 25.

Statistical analyses

Repeated measures analysis of variance, Bland-Altman plot, and fitted regression line of difference. A difference within ±10% of two methods indicated agreement.

Results

Significant proportional bias was present between hand-held indirect calorimeter and prediction equations for REE and TEE (P<0.01); prediction equations overestimated at lower values and underestimated at higher values. Mean differences (±standard error) for REE and TEE between hand-held indirect calorimeter and Harris-Benedict were −5.98±46.7 kcal/day (P=0.90) and 21.40±75.7 kcal/day (P=0.78); between hand-held indirect calorimeter and Mifflin-St Jeor were 69.93±46.7 kcal/day (P=0.14) and 116.44±75.9 kcal/day (P=0.13); between hand-held indirect calorimeter and WHO were −22.03±48.4 kcal/day (P=0.65) and −15.8±77.9 kcal/day (P=0.84); and between hand-held indirect calorimeter and DRI were 39.65±47.4 kcal/day (P=0.41) and 56.36±85.5 kcal/day (P=0.51). Less than 50% of predictive equation values were within ±10% of hand-held indirect calorimeter values, indicating poor agreement.

Conclusions

A significant discrepancy between predicted and measured energy expenditure was observed. Further evaluation of hand-held indirect calorimeter research screening is needed.