Measurement Of Resting Energy Expenditure Research Articles

(850) - Measured Resting Energy Expenditure and Predicted Basal Metabolic Rate Early After Left Ventricular Assist Device Implantation

(850) - Measured Resting Energy Expenditure and Predicted Basal Metabolic Rate Early After Left Ventricular Assist Device Implantation

Estimates of resting energy expenditure using predictive equations in adults with severe burns: A systematic review and meta-analysis.

Many equations to estimate the resting energy expenditure (REE) of patients with burns are currently available, but which of them provides the best guide to optimize nutrition support is controversial. This review examined the bias and precision of commonly used equations in patients with severe burns. A systematic search of the PubMed, Web of Science, Embase, and Cochrane Library databases was undertaken on June 1, 2023, to identify studies comparing predicted REE (using equations) with measured REE (by indirect calorimetry [IC]) in adults with severe burns. Meta-analyses of bias and calculations of precisions were performed in each predictive equation, respectively. Nine eligible studies and 12 eligible equations were included. Among the equations, the Toronto equation had the lowest bias (26.1 kcal/day; 95% CI, -417.0 to 469.2), followed by the Harris-Benedict equation × 1.5 (1.5HB) and the Milner equation. The Ireton-Jones equation (303.4 kcal/day; 95% CI, 224.5-382.3) acceptably overestimated the REE. The accuracy of all of the equations was <50%. The Ireton-Jones equation had the relatively highest precision (41.2%), followed by the 1.5HB equation (37.0%) and the Toronto equation (34.7%). For adult patients with severe burns, all of the commonly used equations for the prediction of REE are inaccurate. It is recommended to use IC for accurate REE measurements and to use the Toronto equation, 1.5HB equation, or Ireton-Jones equation as a reference when IC is not available. Further studies are needed to propose more accurate REE predictive models.

Measured Resting Energy Expenditure by Indirect Calorimetry and Energy Intake in Long-Term Growth Hormone-Treated Children with PWS

Introduction: Severe obesity can develop in children with PWS when food intake is not controlled. Maintenance of body weight requires an energy balance, of which energy intake and energy expenditure are important components. Previous studies described a decreased resting energy expenditure (REE) in growth hormone (GH)-untreated children with PWS. In short-term studies, no difference in REE was found between GH-treated and untreated children with PWS. However, there are limited data on REE in children with PWS who were GH-treated for a long period. Methods: This study describes measured REE (mREE), energy intake, and body composition during long-term GH treatment in children with PWS. Patients were treated with 1.0 mg GH/m2/day (∼0.035 mg/kg/day). REE was determined by indirect calorimetry; dietary energy intake was calculated using a 3-day dietary record. Body composition by dual-energy X-ray absorptiometry (DXA) scans. Results: We included 52 GH-treated children with PWS with a mean (SD) age of 8.53 (4.35) years and a median (IQR) GH-treatment duration of 7 (4–11) years. mREE increased with age, but was not associated with GH-treatment duration. A higher LBM was associated with higher mREE. Mean energy intake was significantly lower compared to daily energy requirements (DER) for age- and sex-matched healthy children (p Conclusion: In children with PWS, mREE increases with age. GH-treatment duration is not associated, whereas LBM is an important determinant of mREE. Children with PWS have a low to very low energy intake compared to DER for age- and sex-matched children, with a declining intake when becoming older.

Trajectories of resting energy expenditure and performance of predictive equations in children hospitalized with an acute illness and malnutrition: a longitudinal study

There is scarce data on energy expenditure in ill children with different degrees of malnutrition. This study aimed to determine resting energy expenditure (REE) trajectories in hospitalized malnourished children during and after hospitalization. We followed a cohort of children in Bangladesh and Malawi (2–23 months) with: no wasting (NW); moderate wasting (MW), severe wasting (SW), or edematous malnutrition (EM). REE was measured by indirect calorimetry at admission, discharge, 14-and-45-days post-discharge. 125 children (NW, n = 23; MW, n = 29; SW, n = 51; EM, n = 22), median age 9 (IQR 6, 14) months, provided 401 REE measurements. At admission, the REE of children with NW and MW was 67 (95% CI [58, 75]) and 70 (95% CI [63, 76]) kcal/kg/day, respectively, while REE in children with SW was higher, 79 kcal/kg/day (95% CI [74, 84], p = 0.018), than NW. REE in these groups was stable over time. In children with EM, REE increased from admission to discharge (65 kcal/kg/day, 95% CI [56, 73]) to 79 (95% CI [72, 86], p = 0.0014) and was stable hereafter. Predictive equations underestimated REE in 92% of participants at all time points. Recommended feeding targets during the acute phase of illness in severely malnourished children exceeded REE. Acutely ill malnourished children are at risk of being overfed when implementing current international guidelines.

Validation of predictive equations for resting energy expenditure in children and adolescents with different body mass indexes

BackgroundAccurate estimation of resting energy expenditure (REE) in children and adolescents is important to establish estimated energy requirements. The objective of this study was to assess the validity of existing equations in literature and a newly developed equation in estimating REE in children and adolescents.Methods275 participants (148 boys, 127 girls) aged 6–18 years included in the study were classified as normal-weighted, overweight, obese based on BMI z-scores for age according to WHO-2007 growth curves for 5–19 years of age. REEs were measured using an indirect calorimeter, with various equations, and a newly established equation [REE = 505.412+(24.383*FFM);Adjusted R2 = 0.649] were compared with REE measured using Bland-Altman and further validation parameters.ResultsWhen the predicted REEs were compared with the measured REEs, the highest prediction accuracy was achieved using the new Eq. (64.8%) and IOM (63.8%) for normal-weight participants, Müller FFM and new Eq. (59.6%) for overweight participants and Lazzer (44.9%) for obese participants. In normal and overweight participants, lowest root mean squared error (RMSE) values were acquired from Schmelzle’s equation (respectively 136.2;159.9 kcal/d), and the highest values were found in Kim’s Eq. (315.2; 295.2 kcal/d respectively). RMSE value of the new equation was 174.7 kcal/d for normal-weight children and adolescents, and 201.9 kcal/d for overweight ones. In obese participants, the lowest RMSE value was obtained from Schmelzle’s Eq. (305.4 kcal/d) and the new Eq. (317.4 kcal/d), while the highest value was obtained from IOM Eq. (439.9 kcal/d). RMSE was higher in obese groups compared to the other BMI groups.ConclusionIndirect-calorimeter is the most suitable method for REE measurement in especially obese children and adolescents. The new equation and Schmelzle’s equation appear to be most accurate equations for normal and overweight children and adolescents.

Predicting resting energy expenditure: a critical appraisal.

The most commonly used prediction models for resting energy expenditure (REE) are Harris-Benedict (1919), Schofield (1985), Owen (1986), and Mifflin-St Jeor (1990), based on height, weight, age and gender, and Cunningham (1991), based on body composition. Here, the five models are compared with reference data, consisting of individual REE measurements (n = 353) from 14 studies, covering a large range of participant characteristics. For white adults, prediction of REE with the Harris-Benedict model approached measured REE most closely, with estimates within 10% for more than 70% of the reference population. Sources of differences between measured and predicted REE include measurement validity and measurement conditions. Importantly, a 12- to 14-h overnight fast may not be sufficient to reach post-absorptive conditions and may explain differences between predicted REE and measured REE. In both cases complete fasting REE may not have been achieved, especially in participants with high energy intake. In white adults, measured resting energy expenditure was closest to predicted values with the classic Harris-Benedict model. Suggestions for improving resting energy expenditure measurements, as well as prediction models, include the definition of post-absorptive conditions, representing complete fasting conditions with respiratory exchange ratio as indicator.

Measuring Energy Requirements of Traumatic Brain Injury Patients in Pediatric Intensive Care With Indirect Calorimetry: A Comparison With Empiric Methods.

Energy requirements following moderate or severe pediatric traumatic brain injury (TBI) have not been fully elucidated. Indirect calorimetry (IC) is the gold standard for measuring resting energy expenditure (MREE) in PICU. However, technical complexity limits its use. We aimed to determine whether MREE differs from standard of care energy estimation and delivery in a cohort of pediatric patients following moderate to severe TBI during PICU admission. Retrospective case series study. Single-center, 16-bed general PICU in Canada between May 2011 and January 2019. Children (0-18 yr) admitted to a PICU for moderate (Glasgow Coma Scale [GCS] 9-12) to severe TBI (GCS < 9) and had an IC study performed while mechanically ventilated. None. During the study period, 245 patients were admitted with the diagnosis of trauma with TBI. The study includes a convenience sample of 26 patients with severe ( n = 23) and moderate ( n = 3) TBI who underwent a total of 34 IC measurements. MREE varied considerably from 29% to 144% of predicted energy expenditure. Using Bland-Altman comparative analysis, neither Schofield nor World Health Organization predictive equations were in agreement with MREE. Only one measurement revealed that the patient was appropriately fed (energy provided in nutrition support was within 10% of MREE); 10 (38%) measurements revealed overfeeding and 15 (58%) underfeeding at the time of testing. The present study adds to the small body of literature highlighting the limitations of predictive equations to evaluate energy requirements following moderate to severe pediatric TBI. IC, when feasible, should be used as the preferred method to orient PICU teams to feed such vulnerable patients.

The Berlin-Buch respiration chamber for energy expenditure measurements

PurposeWe present a methodological overview of a respiration chamber at the Experimental and Clinical Research Center in Berlin, Germany. Since 2010, we investigated 750 healthy subjects and patients with various diseases. We routinely measure resting energy expenditure (REE), dietary-induced thermogenesis, and activity energy expenditure.MethodsThe chamber is a pull calorimeter with a total volume of 11,000 L. The majority of measurements is done with a flow rate of 120 L/min, yielding a favorable time constant of 1.53 h. The gas analysis system consists of two paramagnetic O2 sensors and two infrared CO2 sensors, one for incoming and one for outgoing air samples. O2 and CO2 sensors are calibrated simultaneously before each measurement with a 6 min calibration routine. To verify the accuracy of the whole the calorimetric system, it is validated every 2 weeks by 2 h acetone burning tests.ResultsValidation factors (calculated/measured) of 20 representative 2 h acetone burning tests were 1.03 ± 0.03 for dot{V}{text{O}}_{2}, 1.02 ± 0.02 for dot{V}{text{CO}}_{{2}}, 0.99 ± 0.02 for RER, and 1.03 ± 0.03 for EE. Four repeated 60 min REE measurements of a healthy woman showed variabilities of 231.9 ± 4.8 ml/min for dot{V}{text{O}}_{2} (CV 2.1%), 166.0 ± 6.3 ml/min for dot{V}{text{CO}}_{{2}} (CV 3.8%), 0.73 ± 0.03 for RER (CV 4.6%), and 4.55 ± 0.07 kJ/min for EE (CV 1.6%).ConclusionsThe data presented show that our respiration chamber produces precise and valid EE measurements with an exceptionally fast responsiveness.Graphical

Accuracy of predictive equations for resting energy expenditure estimation in mechanically ventilated Thai patients.

Indirect calorimetry (IC) is the most precise approach for estimating calorie demand in critically ill patients. Despite this, owing to unaffordable devices, it is rarely used in practice. Predictive equations are the alternatives. To assess the accuracy of 14 predictive resting energy expenditure(REE) equations in ventilated Thai patients. We compared the accuracy and agreement of 14 equations. The equations included the American College of Chest Physicians(ACCP) equation, Harris-Benedict equation(HBE), 1.2×HBE, 1.5×HBE, Mifflin-St. Jeor(MSJ), Ireton-Jones 1992 and 2002, Penn State 2003(HBE and MSJ) and 2010, Swinamer 1990, Faisy, Brandi 1999, and 25 kcal/kg equation. An equation was ascertained as accurate if the calculated values fell within ±10% of the measured REEs. Spearman correlation coefficient, Bland-Altman method, and intraclass correlation coefficient were used to analysis. We obtained data from 24 ventilated patients undergoing REE measurement by IC. Fifty percent of them were male with a median age of 64.5 years, a median height of 160 cm, and a median body mass index of 22.95 kg/m2. The predictive precision of all equations was poor, with largely different accuracies from 6.7% to 48.1%. The most reliable equation was Penn State 2010. The ACCP, HBE, MSJ, and Penn State 2003(HBE) tended to underestimate calorie need. Contrastingly, the other equations tended to overestimate REEs. Despite a moderate degree of correlations, the Bland-Altman plots demonstrated clinically unacceptable discrepancies between measured REE and REE calculated by each equation. In ventilated Thai patients, there were no precise equations for determining REE.

Triglycerides and systolic blood pressure negatively mediate the direct relationship of vitamin D status to resting energy expenditure: A cross sectional analysis

Background and aimsWe determined whether individual components of metabolic syndrome (MetS) mediated the direct association of vitamin D status (25OHD) on resting energy expenditure (REE). MethodsMultiple linear regression determined predictors of REE from data on 180 men and women from two ethnic groups. We then modelled a mediation pathway through components of MetS on the direct association between 25OHD and REE. The mediation modelling used the PROCESS SPSS Macro (version 4.0) based on 5000 bootstrapped samples, with the adjustment for different sets of covariates. ResultsREE was significantly predicted by age, fat mass (FM), fat free mass (FFM), ethnicity, inverse ln insulin, 25OHD, triglycerides (TG), systolic blood pressure (SBP) and, to some extent, by time of REE measurements (p < 0.094). Adjustment for all these covariates, resulted in a negative indirect mediation effect of TG [β coefficient (bootstrapped SE): 0.95 (0.519); bootstrapped 95% CI: 2.172, -0.165; p < 0.05] and a concurrent negative mediation of SBP [β coefficient (bootstrapped SE): 0.72(0.484); bootstrapped 95% CI: 1.851, -0.011; p < 0.05]. There remained a positive direct pathway from 25OHD to REE [β coefficient (S.E): 4.715 (2.129); p = 0.028], however the total effect of 25OHD was dampened [β coefficient (S.E): 3.04 (2.126); p = 0.154]. ConclusionsIndependent of insulin sensitivity, a negative mediation by TG and SBP dampened the overall effect of 25OHD on REE.

Comparison between predicted and measured resting energy expenditures in Korean male collegiate soccer players

This study aimed to evaluate the differences between predicted resting energy expenditure (REE), using fat-free mass (FFM)-based prediction equations, and measured REE in Korean male collegiate soccer players. Fifteen male collegiate soccer players (18-21 years) participated in this study. The REE measurements were conducted using the Douglas bag method. Body composition was measured by dual-energy X-ray absorptiometry (DXA). The differences between the measured REE and predicted REE, using the five FFM-based REE equations, were analyzed using the t-test, calculation of errors, regression analysis, and the Bland-Altman method. The Cunningham (1980) and ten Haaf and Weijs (2014) equations showed significantly overestimated REE (1,808 ± 99 kcal/d, p <0.01; 1,838 ± 103 kcal/d, p <0.01; respectively), but the Owen (1988), Taguchi (2011), and Kim (2015) equations' estimations were not significantly different from the measured REE (1,589 ± 106 kcal/d, 1,640 ± 124 kcal/d, and 1,622 ± 68 kcal/d, respectively). The Taguchi equation gave the best prediction of REE with the lowest constant error (-6 ± 125) and effect size (-0.05), and a non-significant proportional bias (p = 0.95). The Taguchi equation is recommended for predicting REE in Korean collegiate soccer players. The selection process of a REE-prediction equation must take into consideration the target population's characteristics. Future studies are recommended to evaluate the validity of the different FFM-based REE-prediction equations in various Korean athletes.

Association of Energy Expenditure and Efficacy in Metastatic Renal Cell Carcinoma Patients Treated with Nivolumab.

Simple SummaryImmune checkpoint inhibitors have improved the tumor response and survival of patients with metastatic renal cell carcinoma. However, no predictive factor of response to immunotherapy is currently available. The aim of our study was to evaluate metabolism, assessed with resting energy expenditure as a biomarker of response, in patients with metastatic renal cell carcinoma treated with nivolumab. We found that the 15 patients (29% of the cohort) that had hypermetabolism also had decreased tumor control and tended to have a worse overall survival compared to patients with normal or low metabolism. We conclude that the measurement of resting energy expenditure could help identify patients who will benefit most from immunotherapy in metastatic renal cell carcinoma.Background: Nivolumab improved patients’ survival in metastatic renal cell carcinoma (mRCC). We aimed to evaluate resting energy expenditure (REE) (i.e., patients’ basal metabolism) to predict efficacy. Methods: We conducted a monocentric, observational study of mRCC patients receiving nivolumab between October 2015 and May 2020. REE was measured prior to initiating immunotherapy using indirect calorimetry to determine hypo, normo and hypermetabolism. Primary endpoint was 6-month, progression-free survival (PFS), and secondary endpoints were response rate, PFS and overall survival (OS). Results: Of the 51 consecutive patients, 15 (29%) were hypermetabolic, 24 (47%) normometabolic, and 12 (24%) hypometabolic. The 6-month PFS was 15% for hypermetabolic patients and 65% for non-hypermetabolic patients (p < 0.01). In the multivariate analysis, hypermetabolism was the only baseline factor predicting 6-month PFS (OR 9.91, 95%CI [1.62–60.55], p = 0.01). Disease progression was noted as the best response in 73% of hypermetabolic patients and 26% of non-hypermetabolic patients (p = 0.02). Median PFS was 2.8 and 8.7 months (p < 0.01), and median OS was 20.2 and 35.1 months (p = 0.13) in the hypermetabolic and non-hypermetabolic groups, respectively. Conclusions: Our study identifies an association between mRCC patients’ energy expenditure and nivolumab efficacy. The measurement of REE by indirect calorimetry in routine practice could help identify patients at risk of nivolumab failure.

Resting energy expenditure in children at risk of hypothalamic dysfunction.

ObjectiveChildren with suprasellar brain damage are at risk of hypothalamic dysfunction (HD). HD may lead to decreased resting energy expenditure (REE). Decreased REE, however, is not present in all children with HD. Our aim was to assess which children suspect for HD have low REE, and its association with clinical severity of HD or radiological hypothalamic damage.Patients and methodsA retrospective cohort study was performed. Measured REE (mREE) of children at risk of HD was compared to predicted REE (pREE). Low REE was defined as mREE <90% of predicted. The mREE/pREE quotient was associated to a clinical score for HD symptoms and to radiological hypothalamic damage.ResultsIn total, 67 children at risk of HD (96% brain tumor diagnosis) with a mean BMI SDS of +2.3 ± 1.0 were included. Of these, 45 (67.2%) had low mREE. Children with severe HD had a significant lower mean mREE/pREE quotient compared to children with no, mild, or moderate HD. Mean mREE/pREE quotient of children with posterior hypothalamic damage was significantly lower compared to children with no or anterior damage. Tumor progression or tumor recurrence, severe clinical HD, and panhypopituitarism with diabetes insipidus (DI) were significant risk factors for reduced REE.ConclusionREE may be lowered in children with hypothalamic damage and is associated to the degree of clinical HD. REE is, however, not lowered in all children suspect for HD. For children with mild or moderate clinical HD symptoms, REE measurements may be useful to distinguish between those who may benefit from obesity treatment that increases REE from those who would be better helped using other obesity interventions.

RARE-07. Low resting energy expenditure is associated with clinical and radiological hypothalamic damage in children surviving a suprasellar brain tumor

INTRODUCTION: Children with suprasellar brain damage are at risk for hypothalamic dysfunction (HD). HD may lead to decreased resting energy expenditure (REE) contributing to the development of hypothalamic obesity. Decreased REE, however, is not present in all children with hypothalamic damage. Our aim was to assess which children suspect for HD have low REE, and if REE outcome can be associated with clinical severity of HD or with radiological posterior hypothalamic damage. METHODS: A retrospective cohort study was performed evaluating all children diagnosed with brain injury at risk for HD in whom REE measurement was performed. Measured REE (mREE) was compared to predicted REE (pREE) using amongst others the Schofield equation. Low REE was defined as mREE<90% compared to pREE. Radiologic hypothalamic damage was scored using Muller grading score. The mREE/pREE quotient was associated to a clinical score for HD symptoms and to radiological hypothalamic damage. RESULTS: Sixty-seven children suspected for HD (94% brain tumor diagnosis) with a mean BMI SDS of +2.3 ± 1.0 were included. Of these, 45 (67.2%) had mREE <90% compared to the pREE. Children with severe HD symptoms had a significant lower mean mREE/pREE quotient compared to children with no, mild, or moderate HD symptoms. Mean mREE/pREE quotient of children with posterior hypothalamic damage was significantly lower compared to children with no damage or with anterior damage. Tumor progression or tumor recurrence, severe clinical HD, and panhypopituitarism with DI were significant risk factors for reduced REE. CONCLUSION: Not all children suspect for HD have a low REE. Low REE is associated with clinical and radiological scores for hypothalamic damage. REE measurements in childhood brain tumor survivors may be useful to distinguish between those who may benefit from obesity treatment that increases REE from those who would be better helped using other obesity interventions.

Clinical evaluation of the new indirect calorimeter in canopy and face mask mode for energy expenditure measurement in spontaneously breathing patients

The new indirect calorimeter developed in the framework of the ICALIC project was first evaluated in ventilation mode. This second phase aimed to compare its ease of use and precision with another commonly used device in spontaneously breathing adult patients using a canopy hood or a face mask. The time required to measure resting energy expenditure (REE) with Q-NRG® in canopy and face mask mode was compared with Quark RMR® in canopy mode by sequential measurements in 45 and 40 spontaneously breathing adult patients, respectively. Their precision was assessed at different time intervals, using coefficients of variation (CV%) and repeated measures one-way ANOVA. Agreement between the two devices was evaluated by correlation coefficients, Bland-Altman plots, and paired t-test. Patients' characteristics potentially affecting the measurement were assessed using linear regression analysis. REE measurement with Q-NRG® was faster than Quark RMR® (19.7±2.9min vs 24.5±4.3min, P<0.001). In canopy mode, Q-NRG® gave values similar to Quark RMR®, with 73% of patients achieving a steady state (CV% <10%) within the 5-15min interval. In face mask mode, Q-NRG® was less stable than Quark RMR® in canopy mode, and steady state was achieved in only 40% of the patients within the 5-15min interval. Correlation between the two devices was stronger when Q-NRG® was used in canopy than in face mask mode, with Pearson coefficients of 0.96 and 0.86, respectively. Compared to Quark RMR® in canopy mode, systematic bias±1.96∗SD with Q-NRG® was-14±236kcal/day in canopy and 73±484kcal/day in face mask mode. Q-NRG® in face mask mode overestimated REE by 150±51kcal/day in men compared to Quark RMR® in canopy mode. Q-NRG® in canopy mode made it possible to save at least 5min compared to Quark RMR® while maintaining the same measurement precision. However, its use in face mask mode could lead to REE overestimation in men and, therefore, should not be recommended in the clinical setting. ClinicalTrials.gov no. NCT03947294.

Measuring the Resting Energy Expenditure in Children on Extracorporeal Membrane Oxygenation: A Prospective Pilot Study.

Both overfeeding and underfeeding critically ill children are problematic. This prospective pilot study evaluated the resting energy expenditure in infants and children requiring extracorporeal membrane oxygenation (ECMO) support. An indirect calorimeter was used to measure oxygen consumption (VO 2 ) and carbon dioxide production (VCO 2 ) from the mechanical ventilator. Blood gases were used to determine VO 2 and VCO 2 from the ECMO circuit. Values from the mechanical ventilator and ECMO circuit were added, and the resting energy expenditure (REE) (Kcal/kg/day) was calculated. Measurements were obtained > 24 hours after ECMO support was initiated (day 2 of ECMO), 1 day before ECMO discontinuation or transfer, and 1 day after decannulation. Data were compared with the predicted energy expenditure. Seven patients aged 3 months to 13 years were included. The REE varied greatly both above and below predicted values, from 26 to 154 KCal/kg/day on day 2 of ECMO support. In patients with septic shock, the REE was > 300% above the predicted value on day 2 of ECMO. Before ECMO discontinuation, two of six (33%) children continued to have a REE > 110% of predicted. Three patients had measurements after decannulation, all with a REE < 90% of predicted. REE measurements can be obtained by indirect calorimetry in children receiving ECMO support. ECMO may not provide metabolic rest for all children as a wide variation in REE was observed. For optimal care, individual testing should be considered to match calories provided with the metabolic demand.

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.

A Smart System for the Contactless Measurement of Energy Expenditure.

Energy Expenditure (EE) (kcal/day), a key element to guide obesity treatment, is measured from CO2 production, VCO2 (mL/min), and/or O2 consumption, VO2 (mL/min). Current technologies are limited due to the requirement of wearable facial accessories. A novel system, the Smart Pad, which measures EE via VCO2 from a room’s ambient CO2 concentration transients was evaluated. Resting EE (REE) and exercise VCO2 measurements were recorded using Smart Pad and a reference instrument to study measurement duration’s influence on accuracy. The Smart Pad displayed 90% accuracy (±1 SD) for 14–19 min of REE measurement and for 4.8–7.0 min of exercise, using known room’s air exchange rate. Additionally, the Smart Pad was validated measuring subjects with a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m2), successfully validating the system accuracy across REE’s measures of ~1200 to ~3000 kcal/day. Furthermore, high correlation between subjects’ VCO2 and λ for CO2 accumulation was observed (p < 0.00001, R = 0.785) in a 14.0 m3 sized room. This finding led to development of a new model for REE measurement from ambient CO2 without λ calibration using a reference instrument. The model correlated in nearly 100% agreement with reference instrument measures (y = 1.06x, R = 0.937) using an independent dataset (N = 56).

Interaction effect of systemic inflammation and modifiable rheumatoid cachexia risk factors on resting energy expenditure in patients with rheumatoid arthritis.

In rheumatoid cachexia (RC), high resting energy expenditure (REE) is associated with loss of muscle mass driven by proinflammatory cytokines. The objectives of this study were to investigate parameters associated with RC, and the interaction between systemic inflammation and modifiable risk factors for RC on REE. Thirty-five rheumatoid arthritis (RA) and nineteen non-RA controls comparable in age, sex, race and BMI underwent measures of REE by indirect calorimetry. Clinical, dietary, body composition and physical function data were collected. Homeostasis model assessment for insulin resistance (HOMA-IR) and serum interleukin-6 (IL-6) were used as parameters of IR and systemic inflammation, respectively. Regression models tested association between REE and dependent variables, including pre-specified interaction tests involving HOMA-IR and IL-6 and dietary intake of protein per weight (PPW) and IL-6. RA subjects were mostly women (94%) and had a median age of 54 years (50.5, 70) and BMI of 30.5 kg/m2 (26.1, 36.9). We observed a significant interaction effect between PPW and serum IL-6 on REE among RA subjects in the multiple regression model among RA. The upper tertile of PPW demonstrated a significant negative correlation between REE and IL-6 (β=-19.97, 95% CI [-35.41, -4.54], p=0.01). The lower tertile of PPW demonstrated a significant positive correlation between REE and IL-6 (β=42.24, 95% CI [4.25, 80.23], p=0.03). While IR can lead to muscle catabolism, IR was not significantly associated with REE in RA individuals. Higher dietary protein intake could attenuate the effect of systemic inflammation on REE in RA patients.

Effect of Intermittent Fasting (18/6) on Energy Expenditure, Nutritional Status, and Body Composition in Healthy Adults.

Objective This study was aimed at evaluating the effect of intermittent fasting of Ramadan on resting energy expenditure (REE), body composition, and nutritional status. Methods The study was conducted on a total of 27 adults (16 females, 11 males) who were fasting (18 h) in the Ramadan month (May 6–June 3) of 2019. REE was measured using the indirect calorimeter. Dietary energy and nutrient intakes were evaluated by 3-day food records in baseline and post-Ramadan. Body composition and some metabolic parameters were analyzed simultaneously with REE measurements. All measurements were performed two times at baseline, and post-Ramadan. Results Body weight (−2.9% vs. −1.4%), body mass index (BMI) (−3.1% vs. −2.1%), fat-free mass (−2.7% vs. −1.4%), and hydration status were decreased in both males and females after the Ramadan fasting (p < 0.05). REEs (kcal/d) of the participants were 1708.1 ± 262.50 kcal/d and 1596.5 ± 302.27 kcal/d at baseline and post-Ramadan, respectively (6.5%) (p < 0.05). This decrease in REE (kcal/d) in females was greater than that in males (−8.1% vs. −4.6%). However, no statistically significant difference was found in sleep duration (h), physical activity levels, dietary energy and nutrient intakes, and blood pressures (mm Hg) of both genders compared to baseline (p > 0.05). Conclusion Intermittent circadian fasting may lead to a decreased energy expenditure and a change in fat-free mass in healthy individuals, and this effect is interpreted as gender-dependent.