Resting Energy Expenditure Values Research Articles

Resting Energy Expenditure in Patients with Extreme Obesity: Comparison of the Harris-Benedict Equation with Indirect Calorimetry.

Background: The main objective of the work was the analysis and description of data on body composition and resting energy expenditure (REE) values of selected groups of patients with obesity whose REE measurement results using indirect calorimetry reached a level below 95% of the predicted REE calculated using the Harris-Benedict (H-B) equation. The sub-goals were to describe the dependence of body composition on the size of the REE and to find out if the deviations between the number of the total measured REE and the REE calculated using H-B in the adapted group (patients with altered REE values, lower than expected caused by long caloric restriction) are significant. Methods: For the research, 71 (39 women and 32 men) patients treated in obesitology were selected. Patients underwent the measurement of resting metabolism using indirect calorimetry (IC) and body composition measurement on the bioimpedance device and, at the same time, the value of resting metabolism was calculated for everyone using the H-B equation. The whole group was divided into five groups according to the deviation of the measurement using IC and the calculation of the H-B equation. Results: In the total set of examined individuals, there were 32.4% with a reduced REE value compared to the REE calculation according to the H-B equation, which corresponds to 23 individuals. In the adapted group, the average measured REE was 2242 ± 616 kcal compared to the H-B calculation of 2638 ± 713 kcal. Statistically, these results were not significant, but a high case-to-case variation was found. The highest deviation from the H-B predictive calculation was -42% and +43% in the whole research group. The amount of muscle tissue in the adapted group averaged 44.3 ± 11.9 kg and the amount of fat-free mass (FFM) 77.9 ± 20.1 kg. When statistically testing the dependence of REE on FFM and muscle tissue in the adapted group, a strong correlation was found. Conclusions: The H-B equation alone is not suitable for setting a suitable diet therapy for an individual with obesity. In order to select and characterize a group of adapted individuals, it will be necessary to use other methods or a larger research sample, and preferably examine and divide patients with specific comorbidities or include their health status.

Sum of Skinfold-Corrected Girths Correlates with Resting Energy Expenditure: Development of the NRGCO Equation.

Our study aimed to validate existing equations and develop the new NRGCO equation to estimate resting energy expenditure (REE) in the Colombian population with moderate-to-high physical activity levels. Upon satisfying the inclusion criteria, a total of 86 (43F, 43M) healthy adults (mean [SD]: 27.5 [7.7] years; 67.0 [13.8] kg) were evaluated for anthropometric variables and REE by indirect calorimetry using wearable gas analyzers (COSMED K4 and K5). Significant positive correlations with REE were found for body mass (r = 0.65), body mass-to-waist (r = 0.58), arm flexed and tensed girth (r = 0.66), corrected thigh girth (r = 0.56), corrected calf girth (r = 0.61), and sum of breadths (∑3D, r = 0.59). As a novelty, this is the first time a significant correlation between REE and the sum of corrected girths (∑3CG, r = 0.63) is reported. Although existing equations such as Harris-Benedict (r = 0.63), Mifflin-St. Jeor (r = 0.67), and WHO (r = 0.64) showed moderate-to-high correlations with REE, the Bland-Altman analysis revealed significant bias (p < 0.05), indicating that these equations may not be valid for the Colombian population. Thus, participants were randomly distributed into either the equation development group (EDG, n = 71) or the validation group (VG, n = 15). A new model was created using body mass, sum of skinfolds (∑8S), corrected thigh, corrected calf, and age as predictors (r = 0.755, R2 = 0.570, RMSE = 268.41 kcal). The new NRGCO equation to estimate REE (kcal) is: 386.256 + (24.309 × BM) - (2.402 × ∑8S) - (21.346 × Corrected Thigh) + (38.629 × Corrected Calf) - (7.417 × Age). Additionally, a simpler model was identified through Bayesian analysis, including only body mass and ∑8S (r = 0.724, R2 = 0.525, RMSE = 282.16 kcal). Although external validation is needed, our validation resulted in a moderate correlation and concordance (bias = 91.5 kcal) between measured and estimated REE values using the new NRGCO equation.

Evaluating predictive equations for energy requirements throughout breast cancer trajectory: A comparative study

Background & AimsAccurately estimating resting energy requirements is crucial for optimizing energy intake, particularly in the context of patients with varying energy needs, such as individuals with cancer. We sought to evaluate the agreement between resting energy expenditure (REE) predicted by 40 equations and that measured by reference methods in women undergoing active breast cancer treatment stage (I-IV) and post-completion (i.e., survivors). MethodsData from 4 studies were combined. REE values estimated from 40 predictive equations identified by a systematic search were compared with REE assessed by indirect calorimetry (IC) using a metabolic cart (MC-REE N=46) or a whole-room indirect calorimeter (WRIC-REE N=44). Agreement between methods was evaluated using Bland-Altman and Lin's concordance coefficient correlation (Lin's CCC). Results90 participants (24 % survivors, 61.1% had early-stage breast cancer I or II, mean age: 56.8 ± 11 years; body mass index: 28.7 ± 6.4 kg/m2) were included in this analysis. Mean MC-REE and WRIC-REE values were 1389 ± 199 kcal/day and 1506 ± 247 kcal/day, respectively. Limits of agreement were wide for all equations compared to both MC and WRIC (∼ 300kcal for both methods), including the most commonly used ones, such as Harris-Benedict and Mifflin ST. Jeor equations; none had a bias within ±10% of measured REE, and all had low agreement per Lin's CCC analysis (< 0.90). The Korth equation exhibited the best performance against WRIC and the Lvingston-Kohlstadt equation against MC. Similar patterns of bias were observed between survivors and patients and between patients with stages I-III versus IV cancer. ConclusionMost equations failed to accurately predict REE at the group level, and none were effective at the individual level. This inaccuracy has significant implications for women with or surviving breast cancer, who may experience weight gain, maintenance, or loss due to inaccurate energy needs estimations. Therefore, our research underscores the need for further efforts to improve REE estimation.

Resting Energy Expenditure, comparison of predictive formulas with bioimpedance: Peruvian population

ntroduction: In areas with limited access to healthcare systems, Resting Energy Expenditure (REE) estimation is performed using predictive equations to calculate an individual’s caloric requirement. One problem is that these equations were validated in populations with different characteristics from those in Latin America, such as race, height, or body mass, leading to potential errors in the prediction of this parameter. Objective: To determine the REE using predictive formulas compared with bioimpedance in Peruvians. Materials and methods: A comparative analytical cross-sectional study with secondary database analysis of the CRONICAS cohort. Results: we worked with a total of 666 subjects. The Mjeor equation was the one with the highest rating of 0.95, a lower mean absolute percentage error (MAPE) of 4.69%, and equivalence was found with the REE values. In the multiple regression, it was observed that the Mjeor equation was the one that least overestimated the REE, increasing 0.77 Kcal/day (95% CI: 0.769-0.814; p&lt;0.001) for each point that increased the REE determined by bioimpedance. The strength of association between Mjeor and bioimpedance was 0.9037. Furthermore, in the regression of the data (weight, height, age) in the Mjeor equation it was observed that the coefficients obtained were the same as those used in the original equation. Conclusions: The Mjeor equation seems to be the most adequate to estimate the REE in the Peruvian population. Future prospective studies should confirm the usefulness of this formula with potential utility in primary health care.

Prediction of resting energy expenditure in Italian older adults with severe obesity.

In the last decade a large number of studies proposed and/or validated equations to estimate the Resting Energy Expenditure (REE) in adults and/or older adults, however, no equation currently available showed good accuracy for older adults with severe obesity. Thus, this study aimed to develop and validate new predictive equations for REE, based on data from the indirect calorimetry, in Italian older adults with severe obesity. A retrospective study was as conducted with 764 Caucasian older adults with severe obesity (age range: 60-74 years and BMI ≥ 35 kg/m/²). Four models were used to test the accuracy of anthropometry and body composition variables in multivariable prediction of REE. All models were derived by stepwise multiple regression analysis using a calibration group of 382 subjects [295 females and 87 males] and the equations were cross-validated in the remaining 382 subjects [295 females and 87 males] as validation group. The new prediction equations and the other published equations were tested using the Bland-Altman method. Prediction accuracy was defined as the percentage of subjects whose REE was predicted within ± 10% of measured REE. All the equations analyzed predicted higher energy requirements for males than females, and most of them underestimated the energy requirement values of our sample. The highest accuracy values were observed in the new equations, with 62% in the anthropometric model and 63% in the body composition model. Although the accuracy of our equations was slightly higher in comparison with the other taken into consideration, they cannot be considered completely satisfactory for predicting REE in Italians older adults with severe obesity. When predicting equations cannot guarantee precise or acceptable values of REE, the use of indirect calorimetry (if available) should be always recommended, especially in clinical practice.

Determining the appropriate resting energy expenditure requirement for severe trauma patients using indirect calorimetry in Korea: a retrospective observational study.

This study aimed to compare the resting energy expenditure (REE) measured using indirect calorimetry with that estimated using predictive equations in severe trauma patients to determine the appropriate caloric requirements. Patients admitted to the surgical intensive care unit between January 2020 and March 2023 were included in this study. Indirect calorimetry was used to measure the patients' REE values. These values were subsequently compared with those estimated using predictive equations: the weight-based equation (rule of thumb, 25 kcal/kg/day), Harris-Benedict, Ireton-Jones, and the Penn State 2003 equations. A total of 27 severe trauma patients were included in this study, and 47 indirect calorimetric measurements were conducted. The weight-based equation (mean difference [MD], -28.96±303.58 kcal) and the Penn State 2003 equation (MD, -3.56±270.39 kcal) showed the closest results to REE measured by indirect calorimetry. However, the REE values estimated using the Harris-Benedict equation (MD, 156.64±276.54 kcal) and Ireton-Jones equation (MD, 250.87±332.54 kcal) displayed significant differences from those measured using indirect calorimetry. The concordance rate, which the predictive REE differs from the measured REE value within 10%, was up to 36.2%. The REE values estimated using predictive equations exhibited substantial differences from those measured via indirect calorimetry. Therefore, it is necessary to measure the REE value through indirect calorimetry in severe trauma patients.

Changes in Energy Expenditure Determined by Indirect Calorimetry in Severe Burn Patients During the Acute Phase.

Severe burn injuries are a major health problemglobally. A profound and prolonged hypermetabolic response develops in severe burn injuries and it is crucial to monitor the patients' energy requirements in order to meet them adequately.The aim of the present study was to examine the energy changes during the acute phase using the indirect calorimetry (IC) method in severe burn patients. The study included 15severe burn patients. Patients with FiO2>60%, tube thoracostomy, closed underwater drain (CUWD) and air leakage were excluded from the study. Patients' demographic data, burn percentages, burn types, duration of stay in intensive care, mortality and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were recorded. Indirect calorimeter measurements were taken once from the patients upon their first arrival and during the following four weeks. Resting energy expenditure (REE), basal metabolic rate (BMR), oxygen consumption (VO₂), carbon dioxide production (VCO₂), body temperatures, presence of sepsis, Sequential Organ Failure Assessment (SOFA) and Modified Nutrition Risk in Critically Ill (mNUTRIC) scores were recorded. The data were analysed usingSPSS 24and p-values <0.05 were considered statistically significant. In the study, 13 (86.67%) of the patients were male. Patients' mean age was 45.27±18.16 years, and mean BMI 25.99±4.22 kg/m2. Five patients (33.33%) had chronic diseases. The average burn percentage was 45%, with 7 (46.67%) patients having a burn percentage of ≤40%, while 8 (53.33%) had a burn percentage of >40%. A total of 14 (93.33%) had flame burns; 3 (20.00%) patients deceased, and 12 (80.00%) were discharged. The mean APACHE II score was 11.53±6.83. The measured mean values of REE, VO₂, VCO₂ and fever were seen to be the highest in the first week after admission and decreases were observed in the subsequent weeks. SOFA score averages were the highest at admission, and decreased in the following weeks. Severe burn patients were observed to go through the hypermetabolic process in the acute phase and their energy requirements were high particularly in the first week. It was concluded that regular IC monitoring can be beneficial to fully meet the energy requirements of severe burn patients due to the prolonged hypermetabolic process.

Resting energy expenditure in children and adolescents with cerebral palsy: accuracy of available prediction formulas and development of population-specific methods.

Energy requirements are difficult to estimate in children with cerebral palsy (CP). Resting energy expenditure (REE), necessary to implement personalized nutritional interventions, is most commonly estimated using prediction formulae since indirect calorimetry, the reference method, is not available in all nutrition units. The aims of the present study were: (1) to evaluate the accuracy of the most commonly used REE prediction formulae developed for healthy children, in children with CP; (2) to assess the accuracy of the REE population-specific formula for CP children proposed in our preliminary report; (3) to develop new population-specific methods. REE was measured by indirect calorimetry in 100 children and adolescents with spastic quadriplegic cerebral palsy (SQCP) and estimated on the basis of predictive formulas selected by the clinicians [World Health Organization (WHO), Harris-Benedict, Schofield weight, Schofield weight & height, Oxford, Mifflin formulae and a population-specific formula for CP children developed in our preliminary report]. 100 children with SQCP (35 girls, 35%) classified as level V according to gross motor function classification system (GMFCS-V); 64% with oral nutrition, 29% total enteral nutrition (nasogastric tube feeding, percutaneous endoscopic gastrostomy, percutaneous endoscopic transgastric jejunostomy) and 7% mixed nutrition. The median (IQR) REE was 41.96 (17.5) kcal/kg/day.Statistical analysis highlighted a proportional bias between the indirect calorimetry and all considered predictive formulae for REE determination. By studying the relationship between the bias and the mean values of REE, specific conversion equations were obtained. With a pre-specified model having as predictors the variable weight and the variable Triceps Skinfold (TSF) and, as response the variable REE measured by indirect calorimetry, a predictive nomogram was developed to estimate the REE in this population of children. We suggest using predictive formulae for healthy children with caution, and where possible carrying out indirect calorimetry to assess REE in children with CP. However, we propose a new tool which could be developed to become an additional help for assessment of REE in the clinical practice.Future objectives will be to obtain a larger sample size, in a multicenter perspective study, to build a specific predictive model for the REE of the studied population.

Влияние пищевого термогенеза низкокалорийной углеводной нагрузки на энерготраты покоя

Basal metabolic rate (BMR) differs from resting energy expenditure (REE) by less than 10 %, the latter being measured under similar conditions, but after a low-calorie meal. Presently, the two terms are used interchangeably, although resting energy expenditure is the preferred one. However, the cycling to exhaustion test commonly used in assessing the physical performance of elite athletes should not follow a 12-hour fasting. Consequently, the subjects are given a standardized low-calorie highcarbohydrate breakfast before the test, which, according to the authors, does not distort the obtained REE values. Therefore, the aim of this study was to determine the thermic effect of a standardized high-carbohydrate meal on resting energy expenditure and body composition. Materials and methods. The anthropometry and body composition were analysed in healthy young men (n = 10) using the ACCUNIQ BC380 system; REE was assessed using indirect calorimetry; the thermic effect of a low-calorie high-carbohydrate breakfast was calculated as a difference between fasting REE and postprandial metabolism. Results. The research showed that a high-carbohydrate (91 %) food intake (250–300 kcal) produces no significant effect on REE. The meal’s thermic effect was 36.0 ± 5.7 kcal, which increased REE (1887.2 ± 111.7 kcal) by 2 % compared to baseline BMR (1851.2 ± 106.0 kcal). In the subjects, REE varied depending on the total amount of water in the body (p = 0.038), fat mass (p = 0.021), and an energy substrate (carbohydrate) intake (р = 0.046). Thus, in people, including athletes, it is acceptable to measure REE after a high-carbohydrate breakfast that does not exceed 300 kcal.

Effects of a ready-to-drink thermogenic beverage on resting energy expenditure, hemodynamic function, and subjective outcomes.

Thermogenic supplements are often consumed by individuals seeking to improve energy levels and reduce body fat. These supplements are sold in powdered or ready-to-drink (RTD) forms and consist of a blend of ingredients such as caffeine, green tea extract, and other botanical compounds. While there is evidence that thermogenic supplements can positively affect resting energy expenditure (REE), the effect varies based on the combination of active ingredients. Additionally, there is some concern that thermogenic supplements may cause unwanted side effects on hemodynamic variables, like heart rate (HR) and blood pressure (BP). Therefore, further investigation into the efficacy and safety of commercially available products is warranted. Twenty-eight individuals (14 F, 14 M; age: 23.3 ± 3.9 yrs; height: 169.4 ± 8.6 cm; body mass: 73.3 ± 13.1 kg) completed two visits in a randomized, double-blind, crossover fashion. Each visit began with baseline REE, HR, and BP assessments, which were followed by ingestion of an active RTD thermogenic beverage (RTD; OxyShred Ultra Energy) or placebo (PL). Assessments were repeated at the intervals of 35-50- and 85-100-minutes post-ingestion. In addition, subjective outcomes of energy, focus, concentration, alertness, and mood were collected five times throughout each visit. Repeated-measures analysis of variance was performed with condition and time specified as within-subjects factors and sex and resistance training (RT) status as between-subjects factors. Statistical significance was accepted at p < 0.05. A significant condition × time interaction was observed for REE (p < 0.001). Higher REE values were demonstrated at 35-50 min (0.08 ± 0.02 kcal/min; p = 0.001; 5.2% difference) and 85-100 min (0.08 ± 0.02 kcal/min; p = 0.001; 5.5% difference) after RTD ingestion as compared to PL. No significant condition × time interactions were observed for respiratory quotient, HR, or BP. Condition main effects indicated lower HR (3.0 ± 0.9 bpm; p = 0.003), higher SBP (3.5 ± 1.1 mm Hg; p = 0.003) and higher DBP (3.5 ± 0.9 mm Hg; p < 0.001) in RTD as compared to PL, irrespective of time. Condition × time interactions were observed for all subjective outcomes (p ≤ 0.02). Post hoc tests indicated statistically significant benefits of the RTD over PL for energy, focus, concentration, and alertness, without significant differences for mood after correction for multiple comparisons. Sex and RT status were not involved in interactions for any outcomes, except for a Sex × RT status interaction for energy, indicating higher energy ratings in non-resistance-trained vs. resistance-trained males. These data suggest that acute ingestion of a thermogenic RTD beverage significantly increases REE, and this elevated caloric expenditure is sustained for at least 100 minutes following ingestion. Furthermore, the RTD beverage increased measures of energy, focus, concentration, and alertness as compared to placebo. While minor differences in hemodynamic variables were observed between conditions, all values stayed within normal ranges. Individuals aiming to increase energy expenditure may benefit from acute ingestion of an RTD thermogenic supplement.

Indirect Calorimetry to Measure Metabolic Rate and Energy Expenditure in Psychiatric Populations: A Systematic Review.

Psychiatric and metabolic disorders are highly comorbid and the relationship between these disorders is bidirectional. The mechanisms underlying the association between psychiatric and metabolic disorders are presently unclear, which warrants investigation into the dynamics of the interplay between metabolism, substrate utilization, and energy expenditure in psychiatric populations, and how these constructs compare to those in healthy controls. Indirect calorimetry (IC) methods are a reliable, minimally invasive means for assessing metabolic rate and substrate utilization in humans. This review synthesizes the extant literature on the use of IC on resting metabolism in psychiatric populations to investigate the interaction between psychiatric and metabolic functioning. Consistently, resting energy expenditures and/or substrate utilization values were significantly different between psychiatric and healthy populations in the studies contained in this review. Furthermore, resting energy expenditure values were systematically overestimated when derived from predictive equations, compared to when measured by IC, in psychiatric populations. High heterogeneity between study populations (e.g., differing diagnoses and drug regimens) and methodologies (e.g., differing posture, time of day, and fasting status at measurement) impeded the synthesis of results. Standardized IC protocols would benefit this line of research by enabling meta-analyses, revealing trends within and between different psychiatric disorders.

Resting energy expenditure in Korean type 2 diabetes patients: comparison between measured and predicted values.

Estimation of energy demand using resting energy expenditure (REE) is a reasonable approach for optimizing glycemic control and weight management in patients with type 2 diabetes mellitus (T2DM). This study aimed to compare REE predictions and objective measurements in patients with T2DM in Korea. This study enrolled 36 participants with T2DM (age range, 20-60 years). Anthropometric variables including height, weight, waist-hip ratio, blood pressure, body fat, body fat percentage, and total body weight were measured using bioimpedance. REE was evaluated using indirect calorimetry. The measured REE values were compared to values estimated using five predictive equations: the Harris-Benedict, Mifflin, Owen, Food and Agriculture Organization of the United Nations/World Health Organization (FAO/WHO), and Schofield equations. This study evaluated the associations between measured REE values and anthropometric/clinical data, including height, weight, and age, using multivariate linear regression. The mean measured REE value was 1891.79 ± 288.03 kcal/day (male), 1,502.00 ± 202.96 kcal/day (female). REE estimates generated from the Mifflin equation showed the largest differences from measured REE values, whereas estimates derived from the FAO/WHO equation were the closest to the measured REE values. This study also identified associations between measured REE values and various anthropometric/clinical variables. The accuracy of REE prediction equations is critically important in promoting the efficacy of dietary counseling and the effective treatment of diabetes. Our results indicate the need for additional studies informing more suitable methods for determining the energy requirements of Korean patients with T2DM.

Abstract 10593: Resting Energy Expenditure is an Important Factor to Predict Cardiac Mortality in Chronic Heart Failure

Introduction: Parameters derived from cardiopulmonary exercise testing (CPET) with respiratory gas analyzer are important prognostic factors in patients with chronic heart failure (CHF). However, all patients with CHF cannot undergo CPET for reasons such as frailty and comorbidity. On the other hands, resting energy expenditure (REE) derived from respiratory gas analyzer can be easily measured in most patients with CHF, but clinical significance of this parameter had not been fully elucidated in patients with CHF. Aims: We aimed to determine the clinical importance including the prognostic impact of REE in patients with CHF. Methods: A total of 1185 consecutive CHF patients who underwent CPET were enrolled. REE was calculated by Weir's formula (3.941resting oxygen consumption (VO 2 )+1.106resting carbon dioxide production (VCO 2 )). The study population was divided into two groups according to median REE and we compered the clinical characteristics between two groups. Also, we examined the value of REE to predict cardiac mortality in CHF patients. Results: In all subjects, 966 were males, median age was 63 years. Median resting VO 2 was 236 ml/min, median resting VCO 2 was 222 ml/min and median REE was 1178 kcal/day. Patients with low REE (&lt;1178 kcal/day) were older and had higher prevalence of female and anemia, lower body mass index (BMI), more impaired renal function, lower parameters of nutrition such as serum total protein and albumin, higher levels of plasma type-B natriuretic peptide, lower resting VO 2 , lower resting VCO 2 and lower peak VO 2 than those with high REE (&gt;1178 kcal/day). But left ventricular ejection fraction was similar between two groups. Patients with low REE had significantly higher rates of cardiac death, all cause death and composite cardiac event (cardiac death and re-hospitalization due to worsening heart failure). Furthermore, REE was the independent predictor of cardiac death, all-cause death and composite cardiac events in the Cox proportional hazard analysis after adjusted cofounding variables including peak VO 2 . Conclusions: REE as well as peak VO 2 is important predictor of cardiac mortality in patients with CHF.

Resting Energy Expenditure of Patients on Venovenous Extracorporeal Membrane Oxygenation for Adult Respiratory Distress Syndrome: A Pilot Study.

OBJECTIVES:The objectives of this study were to 1) in patients without pulmonary function, determine resting energy expenditure (REE) in venovenous extracorporeal membrane oxygenation (ECMO) acute respiratory distress syndrome (ARDS) patients by paralysis status and 2) determine the threshold tidal volume (TV) associated with meaningful gas exchange as determined by measurable end-tidal carbon dioxide elimination (etV̇co2).DESIGN:Retrospective observational study.SETTING:A tertiary high ECMO volume academic institution.PATIENTS/SUBJECTS:Ten adult ARDS patients on venovenous ECMO.INTERVENTIONS:None.MEASUREMENTS AND MAIN RESULTS:The modified Weir equation, Fick principle, Henderson-Hasselbalch equation, ECMO flow, hemoglobin, and pre and post oxygenator blood gases were used to determine ECMO carbon dioxide production (V̇co2), ECMO oxygen consumption, and REE. REE values were matched to patients’ paralysis status based on medication flowsheets and compared using a paired t test. Linear regression was performed to determine the threshold TV normalized to ideal body weight (IBW) associated with measurable ventilator etV̇co2, above which meaningful ventilation occurs. When lungs were not functioning, patients had significantly lower mean REE when paralyzed (23.4 ± 2.8 kcal/kg/d) than when not paralyzed (29.2 ± 5.8 kcal/kg/d) (p = 0.02). Furthermore, mean REE was not similar between patients and varied as much as 1.7 times between patients when paralyzed and as much as 1.4 times when not paralyzed. Linear regression showed that ventilator V̇co2 was measurable and increased linearly when TV was greater than or equal to 0.7 mL/kg.CONCLUSIONS:REE is patient-specific and varies significantly with and without patient paralysis. When TV exceeds 0.7 mL/kg IBW, ventilator V̇co2 increases measurably and must be considered in determining total REE.

A comparative study of indirect calorimetry and prediction equations in overweight and obese Chinese adults

ObjectivesTo determine the resting energy expenditure (REE) in Chinese adults using indirect calorimetry (IC), and evaluate the validity of published predictive equations for estimating REE in overweight and obese subjects comparing to IC. Material and methods181 subjects with different body mass index (BMI) were recruited. Body composition was determined by bio-electrical impedance analysis (BIA). REE was measured by IC and estimated by 29 REE prediction equations to analyze the accuracy of REE prediction equations. ResultsFor all participants combined, the Bernstein et al. and Bernestin et al. (BC) equations similarly predicted REE values between -4% and 8% (P>0.05) of measured REE. When participant data were stratified by sex, BMI, the accuracy of each regression equation is different. In male overweight and obese group, the highest accuracy of the Bernestin et al. (BC) was 65.5% and 70.4%. In female overweight and obese group, the highest accuracy of the Bernestin et al. (BC) and Bernestin et al. was 79.6% and 69.4%. ConclusionThe Bernestin et al. (BC) was closest to IC in male overweight/obese and female overweight, and the Bernestin et al was closest to IC in female obese. However, because those equations have shown considerable variability, they should be used cautiously when estimating the individual REE. When the IC method cannot be used, the Bernestin et al. (BC) and Bernestin et al are more accurate.

Energy expenditure profiles and the risk of early limiting toxicity in older patients with cancer: The ELCAPA-25 prospective cohort survey

Predicting the risk of early limiting toxicity (ELT) is major challenge for the clinician seeking an effective, safe treatment for older patients with cancer. The Cancer and Aging Research Group (CARG) and CRASH (Chemotherapy Risk Assessment Scale for High-Age Patients) toxicity scores were designed to predict chemotherapy-related toxicity. Elevated resting energy expenditure (REE) may predispose to cachexia and increase ELT and mortality in older patients with cancer. The primary objective was to assess the association between elevated REE and ELT in older patients with cancer. The secondary objectives were to assess the discriminant ability of a predictive model including REE (relative to the CARG and CRASH scores) and the prognostic value of elevated REE. We assessed patients aged 70 or over included in the prospective ELCAPA cohort between 2014 and 2018. The inclusion criteria were a solid tumour, a measurement of REE at baseline (mREE, by indirect calorimetry), and a geriatric assessment prior to cancer treatment in a teaching hospital (Paris, France). The mREE was compared with the predicted REE (pREE), as defined by the Harris-Benedict equation. Depending on the mREE/pREE ratio, study participants were classified as hypermetabolic, hypometabolic or normometabolic. The primary endpoint was 3-month ELT, defined as any unplanned hospitalization or any event leading to dose reduction, a treatment delay of more than 7 days, or treatment discontinuation within 3 months of initiation. The secondary endpoint was the 3-month mortality rate. A total of 179 patients were included. The median age was 80 [interquartile range: 76-84] years, 37% of the patients were female, 81.8% had metastatic disease, 67.6% received chemotherapy, 20.7% received hormone therapy, and 11.7% received targeted therapies. According to the mREE/pREE ratio, 85 patients (47%) were hypermetabolic, 63 (35%) were normometabolic, and 31 (18%) were hypometabolic. Sixty patients (33.5%; 95% confidence interval (CI): 26.7-40.9) experienced ELT. The discriminant ability (as assessed by the C-index) of a multivariate model including REE and adjustment factors was 0.82 [95%CI: 0.73-0.91]. In comparison, the discriminant ability of the CARG and CRASH models was 0.57 [0.45-0.68] and 0.51 [0.40-0.62], respectively. In our model, hypermetabolism was an independent risk factor for ELT (adjusted odds ratio=2.44; 95%CI: 1.02-5.80). Other risk factors were the cancer type and stage, the treatment protocol, a clinical diagnosis of depression, the presence of grade 3 or 4 comorbidities, and the serum lactate dehydrogenase level. Hypermetabolism status is an independent predictor of ELT in older patients with cancer, relative to normometabolic status. Baseline REE measurement might improve the ELT risk assessment and decision-making process.

POS-726 NOVEL EQUATIONS FOR ESTIMATING RESTING ENERGY EXPENDITURE IN PERITONEAL DIALYSIS PATIENTS

With the development of chronic kidney disease (CKD), the risk of protein-energy wasting is increasing. It is urgent to have a convenient method to assess energy expenditure accurately in these patients. However, besides the direct measurement, which is expensive and time-consuming, there is no resting energy expenditure (REE) equations focus on peritoneal dialysis patients. We aimed to develop and validate REE equations in peritoneal dialysis patients. This cross-sectional study enrolled 140 patients with peritoneal dialysis according to inclusion and exclusion criteria. After random sampling matched 1:1 by age, gender and dialysis duration, stepwise linear regression analysis was used to derive a new REE equation (eREEpd) according to actual REE (aREE) measured using indirect calorimetry in the development dataset. The eREEpd value was then validated with aREE in the validation dataset in terms of bias, precision, and accuracy. Bias was assessed as the difference between the estimated and measured REE values, precision was assessed as the absolute value of difference, and accuracy was assessed as the percentage of estimates that differed >20% from the measured REE (1- P20). The eREEpd equation: eREEpd (kcal) = (1 if male; 0 if female) × 144.08 − 5.8 × age (y) + 10.33 × weight (kg)+ 850.71 (R2 = 0.649). The bias, precision, and accuracy of the eREEpd equation were -11.3 (IQR: −195.7, 115.0) kcal, 22.2 (IQR:64.9, 249.3) kcal, and 20.3%, respectively with indirect calorimetry as the reference method. Besides, we found hemoglobin was an independent predictive factor of REE developed an REE equation using age, sex, weight, and hemoglobin data, as eREEpd_Hb (kcal) = (1 if male; 0 if female) × 172.16 − 4.87 × age (y) + 9.63 × weight (kg)-3.05×hemoglobin (g/L)+ 1180.04 (R2 = 0.673).The bias, precision, and accuracy (percentage of estimates that differed >20% from the measured REE) of the eREEpd_Hb equation were 31.5 (IQR: −174.3, 102.0) kcal, 120.8 (IQR:59.6, 239.2) kcal, and 18.6%, respectively with indirect calorimetry as the reference method. The REE equation using age, sex, weight with or without hemoglobin data could serve as a reliable tool for estimating REE in patients with peritoneal dialysis.

Abstract 9577: Resting Energy Expenditure is Important Factor to Predict Cardiac Mortality in Chronic Heart Failure

Introduction: Parameters derived from cardiopulmonary exercise testing (CPX) including peak oxygen consumption (VO 2 ) are important prognostic factors in patients with chronic heart failure (CHF). However, all patients with CHF cannot undergo CPX because of such as exercise intolerance. On the other hands, resting parameters derived from respiratory gas analyzer including resting energy expenditure (REE) could be easily measured and clinical significance of these parameters had not been fully elucidated in patients with CHF. We aimed to determine the prognostic impact of REE in patients with CHF. Methods: A total of 1185 consecutive CHF patients underwent CPX were enrolled. The subjects of this study were divided into two groups according to median REE and we compered the clinical characteristics between two groups. Also, we examined the value of REE (Weir’ formula: 3.941resting VO 2 +1.106resting VCO 2 ) to predict cardiac mortality in CHF patients. Results: In all subjects, 966 were males, median age was 63 years. Median resting VO 2 was 236 ml/min, median resting VCO 2 was 222 ml/min and median REE was 1178 kcal/day. Patients with low REE (&lt;1178 kcal/day) were older and had higher prevalence of female and anemia, lower body mass index (BMI), more impaired renal function, lower parameters of nutrition such as serum total protein and albumin, higher levels of plasma type-B natriuretic peptide, lower resting VO 2 and lower resting VCO 2 and lower peak VO 2 than those with high REE ( &gt; 1178 kcal/day). But left ventricular ejection fraction was similar between two groups. Patients with low REE had significantly higher rates of cardiac death, all cause death and composite cardiac events (cardiac death and re-hospitalization due to worsening heart failure) than those with high REE. Furthermore, REE was the independent predictor of cardiac death, all-cause death and composite cardiac events in the Cox proportional hazard analysis after adjusting for cofounding variables including peak VO 2 . Conclusions: REE as well as peak VO 2 is important predictor of cardiac mortality in patients with CHF.

Energy expenditure and oxygen uptake kinetics in critically ill elderly patients.

Resting energy expenditure (REE) measurement of critically ill patients is essential for better nutrition management. Younger people increase their oxygen delivery ( ) to meet energy demands, but few reports have investigated oxygen uptake kinetics in elderly patients, which are the main target population in today's intensive care units (ICUs). In this study, we evaluated REE, , and oxygen extraction ratio (O2 Ext: oxygen consumption [ ]/ ) to clarify appropriate energy needs and consumption in elderly ICU patients. This retrospective observational study included ventilated ICU patients who were divided into elderly participants (age ≥ 65 years) and nonelderly participants (age ≤64 years). , CO2 production, and cardiac output were measured by indirect calorimetry and noninvasive hemodynamic monitoring for up to 5 days. The initial values of REE, , and O2 Ext were compared between elderly and nonelderly patients. This study included 102 patients, of whom 52% (n = 53) were elderly. The absolute deviation of measured REE per ideal body weight (IBW) was significantly higher in elderly than in nonelderly patients (9.3 ± 6.9 vs 6.3 ± 6.6 kcal/kg; P < .01). had a strong negative correlation with age (P < .01). The O2 Ext value was significantly higher in elderly than in nonelderly patients (37 ± 19% vs 29 ± 13%; P = .03). Elderly critically ill patients were characterized by higher deviations in REE, lower , and higher O2 Ext. In elderly patients, O2 Ext rather than could be increased to meet energy consumption demands.

Comparison of Resting Energy Expenditure Using Indirect Calorimetry and Predictive Equations in Trauma Patients: A Pilot Study

Purpose Nutritional therapy in the intensive care unit is an essential factor for patient progress. The purpose of this study was to compare resting energy expenditure (REE) calculated by prediction equations (PEs) to the REE measured by indirect calorimetry (IC) in trauma patients. Methods Patients admitted to the trauma intensive care unit who received mechanical ventilation between January and December 2015 were enrolled. REE was measured by IC (CCM Express, MGC Diagnostics) and calculated by the following PEs: Harris-Benedict, Fleisch, Robertson and Reid, Ireton-Jones, and the maximum value (25 kcal/kg/ day) of the European Society for Clinical Nutrition and Metabolism (ESPEN). All patients were ventilated at a fraction of inspired oxygen (FiO2) below 60%. Results Of the 31 patients included in this study, 24 (77.4%) were men and seven (22.6%) were women. The mean age of the patients was 49.7±13.2 years, their mean weight was 68.1±9.6 kg, and their mean Injury Severity Score was 26.1±11.3. The mean respiratory quotient on IC was 0.93±0.19, and their mean FiO2 was 38.72%±6.97%. The mean REE measured by IC was 2,146±444.36 kcal/day, and the mean REE values calculated by the PEs were 1,509.39±205.34 kcal/day by the Harris and Benedict equation, 1,509.39±154.33 kcal/day by the Fleisch equation, and 1,443.39±159.61 kcal/day by the Robertson and Reid equation. The Ireton-Jones equation yielded a higher value (2,278.90±202.35 kcal/ day), which was not significantly different from the value measured using IC (p=0.53). The ESPEN maximum value (1,704.03±449.36 kcal/day) was lower, but this difference was likewise not significant (p=0.127). Conclusions The REE measured by IC was somewhat higher than that calculated using PEs. Further studies are needed to determine the proper nutritional support for trauma patients. Keywords: Energy metabolism; Calorimetry, indirect; Wounds and injuries