Factors Affecting Energy Metabolism and Prognosis in Patients with Amyotrophic Lateral Sclerosis.

BACKGROUND/AIMS: Nutritional status is a factor affecting prognosis in patients with amyotrophic lateral sclerosis (ALS). Here, we aimed to clarify the factors associated with hypermetabolism and the prognosticators of ALS. METHODS: Forty-two inpatients (22 men, 20 women) diagnosed with ALS according to the revised El-Escorial criteria were investigated. The following data were retrospectively analyzed: anthropometric measurements, blood biochemistry, disease severity, basal energy expenditure (BEE), resting energy expenditure (REE) measured by indirect calorimetry, spirometry, and bioelectrical impedance analysis. Single and multiple regression analysis was performed to examine factors affecting REE and metabolic changes (defined as the ratio of REE to fat-free mass [FFM]). The Kaplan-Meier method was used to examine factors associated with the occurrence of cumulative events (death or tracheostomy). RESULTS: Among the 42 inpatients, REE was significantly higher than BEE, indicating hypermetabolism in ALS. Multiple regression analysis revealed that REE/FFM is strongly associated with the skeletal muscle index (-3.746 to -1.532, p < 0.0001) and percent forced vital capacity (%FVC) (-0.172 to -0.021, p = 0.013). Moreover, both the skeletal muscle index and %FVC were significant prognosticators associated with the occurrence of cumulative events. CONCLUSIONS: Energy metabolism was elevated in ALS, and respiratory status and muscle mass were associated with the hypermetabolism and poor prognosis. Adequate nutritional support may improve outcomes in ALS by preventing deterioration of respiratory status and reduction in muscle mass.

Estimation of Metabolic Energy Expenditure during Short Walking Bouts.

Assessment of metabolic energy expenditure from indirect calorimetry is currently limited to sustained (>4 min) cyclic activities, because of steady-state requirements. This is problematic for patient populations who are unable to perform such sustained activities. Therefore, this study explores validity and reliability of a method estimating metabolic energy expenditure based on oxygen consumption (V̇O2) during short walking bouts. Twelve able-bodied adults twice performed six treadmill walking trials (1, 2 and 6 min at 4 and 5 km/h), while V̇O2 was measured. Total V̇O2 was calculated by integrating net V̇O2 over walking and recovery. Concurrent validity with steady-state V̇O2 was assessed with Pearson's correlations. Test-retest reliability was assessed using intra-class correlation coefficients (ICC) and Bland-Altman analyses. Total V̇O2 was strongly correlated with steady-state V̇O2 (r=0.91-0.99), but consistently higher. Test-retest reliability of total V̇O2 (ICC=0.65-0.92) was lower than or comparable to steady-state V̇O2 (ICC=0.83-0.92), with lower reliability for shorter trials. Total V̇O2 discriminated between gait speeds. Total oxygen uptake provides a useful measure to estimate metabolic load of short activities from oxygen consumption. Although estimates are less reliable than steady-state measurements, they can provide insight in the yet unknown metabolic demands of daily activities for patient populations unable to perform sustained activities.

Point-Counterpoint: Indirect Calorimetry Is Essential for Optimal Nutrition Therapy in the Intensive Care Unit.

Iatrogenic malnutrition and underfeeding are ubiquitous in intensive care units (ICUs) worldwide for prolonged periods after ICU admission. A major driver leading to the lack of emphasis on timely ICU nutrition delivery is lack of objective data to guide nutrition care. If we are to ultimately overcome current fundamental challenges to effective ICU nutrition delivery, we must all adopt routine objective, longitudinal measurement of energy targets via indirect calorimetry (IC). Key evidence supporting the routine use of IC in the ICU includes (1) universal societal ICU nutrition guidelines recommending IC to determine energy requirements; (2) data showing predictive equations or body weight calculations that are consistently inaccurate and correlate poorly with measured energy expenditure, ultimately leading to routine overfeeding and underfeeding, which are both associated with poor ICU outcomes; (3) recent development and worldwide availability of a new validated, accurate, easy-to-use IC device; and (4) recent data in ICU patients with coronavirus disease 2019 (COVID-19) showing progressive hypermetabolism throughout ICU stay, emphasizing the inaccuracy of predictive equations and marked day-to-day variability in nutrition needs. Thus, given the availability of a new validated IC device, these findings emphasize that routine longitudinal IC measures should be considered the new standard of care for ICU and post-ICU nutrition delivery. As we would not deliver vasopressors without accurate blood pressure measurements, the ICU community is only likely to embrace an increased focus on the importance of early nutrition delivery when we can consistently provide objective IC measures to ensure personalized nutrition care delivers the right nutrition dose, in the right patient, at the right time to optimize clinical outcomes.

Reliability of bioimpedance and indirect calorimetry to evaluate resting metabolic rate in Brazilian women with metabolic syndrome.

BACKGROUND AND AIMS: Precise evaluation of resting metabolic rate (RMR) is critical, especially for seniors in syndromes conditions. The study aimed to compare different methods and devices to evaluate the resting metabolic rate and assess them' reliability in Brazilian women with metabolic syndrome. METHODS: A single-center prospective study with forty elderly postmenopausal women was performed to verify the reliability of indirect calorimetry (IC) versus Bioimpedance (BIA) on RMR fluctuations for an interval length of six months. RESULTS: Measurements showed a high correlation between devices at baseline [BIA vs IC, intraclass correlation coefficient (ICC) = 0.906 (0.822-0.950)]. Surprisingly, a high correlation was kept between BIA and IC after six months [BIA vs. IC, ICC = 0.909 (0.829-0.952)]. The results suggest that both BIA and IC are excellent strategies to measure RMR in elderly postmenopausal women and with metabolic syndrome. CONCLUSIONS: However, the BIA method presents greater convenience, optimizes patients' time, and does not require prolonged fasting to obtain good reliable results compared to IC.

Predictive equations for resting metabolic rate are not appropriate to use in Brazilian male adolescent football athletes.

High accuracy in estimating energy expenditure is essential for enhancing sports performance. The resting metabolic rate (RMR), as a primary component of total energy expenditure (TEE), is commonly estimated using predictive equations. However, these references may not be applicable to adolescent athletes. The purpose of this cross-sectional study was to analyse the differences between predicted RMR in relation to energy expenditure measured by indirect calorimetry (IC) among 45 Brazilian male adolescent football athletes. Indirect calorimetry (IC) and anthropometric (bioimpedance) measurements were recorded at a single visit to the laboratory after fasting overnight. The mean age was 15.6 ± 1.14 years, body mass was 63.05 ± 7.8 kg, and height was 172 ± 7.5 cm. The RMR values predicted by equations proposed by the Food and Agriculture Organization (FAO) (United Nations), Henry and Rees (HR), Harris Benedict (HB), and Cunningham (CUN) were compared with IC RMR values, by correlation analysis. The FAO and HR predictive equations yielded different values from IC (IC: 1716.26 ± 202.58, HR: 1864.87 ± 147.78, FAO: 1854.28 ± 130.19, p = 0.001). A moderate correlation of 0.504 was found between the results of HB and IC. In the survival-agreement model, the CUN equation showed low disagreement with the IC RMR, with error values between 200 and 300 kcal/day. The results showed that HB and CUN yielded similar values as IC, with the CUN equation showing low disagreement with IC; hence, adolescent athletes should undergo evaluation with precise laboratory methods to ensure that accurate information about RMR is recorded.

Prediction of resting energy expenditure in healthy older adults: A systematic review.

BACKGROUND & AIMS: Estimates of energy requirements, based on measured or predicted resting energy expenditure (REE), are needed to avoid undernutrition or overnutrition (and their clinical consequences) in elderly subjects. The aims of this systematic review were to evaluate the prediction accuracy of REE in healthy elderly subjects and to ascertain which equation is more reliable at group level and/or individual level. METHODS: Studies assessing prediction of REE in general elderly population were systematically searched using PubMed, EMBASE, Web of Science and CINAHL until March 2020. Prediction accuracy of REE was assessed at both group (bias) and individual (precision) level for each equation. RESULTS: Fourteen studies met the inclusion criteria of this systematic review. Bias was reported in 8 papers and calculated in another 5 from absolute values. There was a prevalent tendency towards an overestimation of REE across the studies. The least bias was observed for the Mifflin (-0.3%) and Harris-Benedict (+2.6%) equations, with values above 5% for the FAO/WHO/UNU, Fredrix and Muller equations. Precision widely varied between studies for the same equation. The higher precision was observed using the Harris-Benedict equation (~70%), while the Henry and Mifflin equations provided estimates within 10% of measured values in 65% and 61% of elderly individuals, respectively. CONCLUSIONS: None of the prediction equations considered provides accurate and precise REE estimates in healthy older adults. However, the best prediction is given by the Mifflin equation at group level and by the Harris-Benedict equation at individual level. Further studies with strong quality design are needed to evaluate the variability and accuracy of REE in the elderly general population.

A Single-Center Prospective Observational Study Comparing Resting Energy Expenditure in Different Phases of Critical Illness: Indirect Calorimetry Versus Predictive Equations.

OBJECTIVES: Several predictive equations have been developed for estimation of resting energy expenditure, but no study has been done to compare predictive equations against indirect calorimetry among critically ill patients at different phases of critical illness. This study aimed to determine the degree of agreement and accuracy of predictive equations among ICU patients during acute phase (≤ 5 d), late phase (6-10 d), and chronic phase (≥ 11 d). DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations. SETTING: General Intensive Care Unit, University of Malaya Medical Centre. PATIENTS: Mechanically ventilated critically ill patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy. CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.

Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study.

INTRODUCTION: Evaluation of total energy expenditure (TEE) and physical activity level (PAL) is important for treatment of patients with type 2 diabetes mellitus (T2DM). However, the validity of accelerometers (ACC) and physical activity questionnaires (PAQ) for estimating TEE and PAL remains unknown in elderly populations with T2DM. We evaluated the accuracy of TEE and PAL results estimated by an ACC (TEEACC and PALACC) and a PAQ (TEEPAQ and PALPAQ) in elderly patients with T2DM. METHODS: Fifty-one elderly patients with T2DM (aged 61-79 years) participated in this study. TEEACC was calculated with PALACC using a triaxial ACC (Active style Pro HJA-750c) over 2 weeks and predicted basal metabolic rate (BMR) by Ganpule's equation. TEEPAQ was estimated using predicted BMR and the PALPAQ from the -Japan Public Health Center Study-Long questionnaire. We compared the results to TEEDLW measured with the doubly labeled water (DLW) method and PALDLW calculated with BMR using indirect calorimetry. RESULTS: TEEDLW was 2,165 ± 365 kcal/day, and TEEACC was 2,014 ± 339 kcal/day; TEEACC was strongly correlated with TEEDLW (r = 0.87, p < 0.01) but significantly underestimated (-150 ± 183 kcal/day, p < 0.05). There was no significant difference in TEEPAQ and TEEDLW (-49 ± 284 kcal/day), while the range of difference seemed to be larger than TEEACC. PALDLW, PALACC, and PALPAQ were calculated to be 1.71 ± 0.17, 1.69 ± 0.16, and 1.78 ± 0.24, respectively. -PALACC was strongly correlated with PALDLW (r = 0.71, p < 0.01), and there was no significant difference between the 2 values. PALPAQ was moderately correlated with PALDLW (r = 0.43, p < 0.01) but significantly overestimated. Predicted BMR was significantly lower than the BMR -measured by indirect calorimetry (1,193 ± 186 vs. 1,262 ± 155 kcal/day, p < 0.01). CONCLUSIONS: The present ACC and questionnaire showed acceptable correlation of TEE and PAL compared with DLW method in elderly patients with T2DM. Systematic errors in estimating TEE may be improved by the better equation for predicting BMR.

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Athletes retiring from their sports career, an understudied population, are susceptible to become overweight/obese because of decreased energy expenditure not followed by a reduction in energy intake. Therefore, their energy requirements, through resting metabolic rate (RMR), should be accurately addressed for weight management purposes. This study aimed to determine the validity of predictive equations (PEq) for RMR estimation using indirect calorimetry as the reference method in a sample of overweight/obese former athletes. The study uses cross-sectional data collected during baseline measurements of a lifestyle intervention (NCT03031951). The RMR of 56 overweight/obese (31.5 (4.0 kg/m2)) individuals (78.6% male, 37.5% obese, 95.8 (14.8 kg), 174.2 (8.7 cm)) was measured by indirect calorimetry and predicted using seven PEq: Harris-Benedict, Cunningham, Schofield, FAO/WHO/UNU, Owen, Mifflin-St. Jeor, and Katch-McArdle. Dual-energy X-ray absorptiometry was used to assess body composition. The PEq overestimated the RMR measured by the indirect calorimetry, 70-300 kcal/day (4.3-14.9%). The linear regression between the reference and each of the PEq did not differ from the identity line with estimated values explaining around 50% of the variability of the measured values. The agreement between the methods was weak for all the PEq showing wide limits of agreement. The Harris-Benedict equation was the only one in which the difference between the methods was not related to the magnitude of the measured RMR. Given the weak performance of the various RMR models in overweight/obese former athletes, an effective weight management intervention based on estimated resting energy requirements may be compromised.

Clinical Nutrition of Critically Ill Patients in the Context of the Latest ESPEN Guidelines.

The group of patients most frequently in need of nutritional support are intensive care patients. This year (i.e., 2019), new European Society for Clinical Nutrition and Metabolism (ESPEN) guidelines of clinical nutrition in intensive care were published, updating and gathering current knowledge on the subject of this group of patients. Planning the right nutritional intervention is often a challenging task involving the necessity of the choice of the enteral nutrition (EN) or parenteral nutrition (PN) route of administration, time of initiation, energy demand, amino acid content and demand as well as the use of immunomodulatory nutrition. The aim of this study was to specify and discuss the basic aspects of the clinical nutrition of critically ill patients recommended by ESPEN guidelines. Clinical nutrition in intensive care seems to be the best-studied type of nutritional intervention. However, meta-analyses and clinical studies comparing EN and PN and their impact on the prognosis of the intensive care patients showed ambiguous results. The nutritional interventions, starting with EN, should be initiated within 24-48 h whereas PN, if recommended, should be implemented within 3-7 days. The recommended method of calculation of the energy demand is indirect calorimetry, however, there are also validated equations used worldwide in everyday practice. The recommended protein intake in this group of patients and the results of insufficient or too high supply was addressed. In light of the concept of immunomodulatory nutrition, the use of appropriate amino acid solutions and lipid emulsion that can bring a positive effect on the modulation of the immune response was discussed.

Accuracy of the Multisensory Wristwatch Polar Vantage's Estimation of Energy Expenditure in Various Activities: Instrument Validation Study.

BACKGROUND: Sport watches and fitness trackers provide a feasible way of obtaining energy expenditure (EE) estimations in daily life as well as during exercise. However, today's popular wrist-worn technologies show only poor-to-moderate EE accuracy. Recently, the invention of optical heart rate measurement and the further development of accelerometers in wrist units have opened up the possibility of measuring EE. OBJECTIVE: This study aimed to validate the new multisensory wristwatch Polar Vantage and its EE estimation in healthy individuals during low-to-high-intensity activities against indirect calorimetry. METHODS: Overall, 30 volunteers (15 females; mean age 29.5 [SD 5.1] years; mean height 1.7 [SD 0.8] m; mean weight 67.5 [SD 8.7] kg; mean maximal oxygen uptake 53.4 [SD 6.8] mL/min·kg) performed 7 activities-ranging in intensity from sitting to playing floorball-in a semistructured indoor environment for 10 min each, with 2-min breaks in between. These activities were performed while wearing the Polar Vantage M wristwatch and the MetaMax 3B spirometer. RESULTS: After EE estimation, a mean (SD) of 69.1 (42.7) kcal and 71.4 (37.8) kcal per 10-min activity were reported for the MetaMax 3B and the Polar Vantage, respectively, with a strong correlation of r=0.892 (P<.001). The systematic bias was 2.3 kcal (3.3%), with 37.8 kcal limits of agreement. The lowest mean absolute percentage errors were reported during the sitting and reading activities (9.1%), and the highest error rates during household chores (31.4%). On average, 59.5% of the mean EE values obtained by the Polar Vantage were within ±20% of accuracy when compared with the MetaMax 3B. The activity intensity quantified by perceived exertion (odds ratio [OR] 2.028; P<.001) and wrist circumference (OR -1.533; P=.03) predicted 29% of the error rates within the Polar Vantage. CONCLUSIONS: The Polar Vantage has a statistically moderate-to-good accuracy in EE estimation that is activity dependent. During sitting and reading activities, the EE estimation is very good, whereas during nonsteady activities that require wrist and arm movement, the EE accuracy is only moderate. However, compared with other available wrist-worn EE monitors, the Polar Vantage can be recommended, as it performs among the best.

Accuracy of Predictive Resting-Metabolic-Rate Equations in Chinese Mainland Adults.

Accurate measurement of the resting metabolic rate (RMR) is necessary when we make energy requirements and nutrition suggestions in clinical. However, indirect calorimetry is not always available. The objectives of this study were to make a comparison between RMR measured by indirect calorimetry and RMR predicted by different kinds of equations, and to develop new predictive equations for Chinese mainland adults. In this study, 315 Chinese mainland adults from different provinces all over China were recruited. Subjects underwent half a day of testing, which consisted of anthropometric assessment and RMR measurement. Measured and predicted RMR were compared; new optimal equations for Chinese mainland adults were developed and tested by splitting the subjects into a development and validation group. The measured RMR was in the range of 831-2776 kcal/day (mean 1651 ± 339 kcal/day). Our findings indicated that, except for the Harris-Benedict and Schofield equations, three Chinese equations and two fat-free mass (FFM) modeling equations all significantly underestimated RMR compared to the measured value (all p < 0.01). There were no significant differences between predicted and measured RMR using the new equations for females and males. Of the pre-existing equations, Schofield's is the most suitable for Chinese mainland adults. However, the two new equations developed in this study seem to be more effective for predicting the RMR of Chinese mainland adults, and need to be validated by a larger independent sample with different physiological and anthropometric characteristics.

Validity of basal metabolic rate prediction equations in elderly women living in an urban tropical city of Brazil.

OBJECTIVES: To measure basal metabolic rate (BMR) and to compare it with the values obtained from predictive equations in a sample of elderly (≥60 y) women. DESIGN: Cross-sectional study. PARTICIPANTS AND SETTING: Seventy-nine women living in Niterói, Rio de Janeiro, Brazil enrolled in physical activity programs open to the community. MEASUREMENTS: Anthropometric measures were obtained using standard procedures. Percent body fat (PBF) was assessed by DXA. BMR was measured (BMRm) by indirect calorimetry under standardized conditions and compared with BMR estimated by 14 predictive equations that included elderly individuals in their development. RESULTS: Mean (±SD) age, BMI and PBF were 69.7 ± 6.5 y, 27.2 ± 4.6 kg/m2 and 42.1 ± 5.9%. BMRm (4188.3 ± 707.2 kJ/day) was significantly lower than estimated BMR by all predictive equations, including the equation developed for the Niteroian adult population (4565.6 ± 607.9 kJ/day). This population-specific equation provided the largest number of results within ±10% of BMRm and the lowest overestimation (10.6 ± 15.4%), much lower than the results from the internationally recommended Schofield equation (27.2 ± 17.6%). Regression of calf circumference (CC), age and body mass on BMRm provided similar estimates in comparison to models with fat-free mass (FFM). CONCLUSIONS: All predictive equations provided biased, inaccurate estimates of BMR values in comparison to BMRm. Anthropometry and body composition explained only approximately 50% of the variability of BMRm. New equations should account for the variability of organ-metabolic rates and underlying undetected health conditions in older individuals living in tropical regions.

Concordance between 13 C:12 C ratio technique respect to indirect calorimetry to estimate carbohydrate and Fat oxidation rates by means stoichiometric equations during exercise. A reliability and agreement study.

Indirect calorimetry is a tool used routinely by sport/exercise physiologist to assess the metabolic response to training and to nutritional interventions. There are different stoichiometric equations to estimate fat (FatOxR ) and carbohydrates (CHOOxR ) oxidation rates, however there are not enough information in literature about what are the most accurate equations. The purpose of this study was to determine the concordance between indirect calorimetry and a method of reference for stoichiometric equations used to estimate FatOxR and CHOOxR . Concordance between indirect calorimetry and the method of reference (13 C to 12 C ratio (13 C:12 C ratio) technique) for key stoichiometric equations was assessed in well-trained triathletes. Subjects carried out a carbohydrate depletion-repletion protocol, labeling the glycogen stores with 13 C, and a laboratory test to assess the 13 C metabolic response during a wide range of aerobic intensities during exercise. All the equations showed a narrow agreement interval (Δ) (CHOOxR nPC (protein component negligible): -0.308, 0.308, CHOOxR PC (protein component): -0.268, 0.268, FatOxR nPC and PC: -0.032, 0.032 (g·min-1 )). FatOxR showed a similar concordance (28-32%) with CHOOxR nPC ranging from 55% to 75%, and for CHOOxR PC between 51% to 71%. None of the stoichiometric equations met a perfect agreement with the method of reference. The Jeukendrup and Wallis equation showed the best concordance for CHOOxR nPC whilst the Frayn and Ferrannini (Glu) equations had the best agreement for CHOOxR PC. All FatOxR equations showed similar concordances and they are able to be used indistinctly.

A Systematic Review of the Accuracy of Estimated and Measured Resting Metabolic Rate in Chronic Spinal Cord Injury.

The objective of this systematic review was to examine resting metabolic rate (RMR) measured through indirect calorimetry in adults with chronic spinal cord injury (SCI) and to evaluate the predication equations used for the estimation of RMR in this population. The authors additionally aimed to review the impact of sex and level of injury on RMR. A MEDLINE/PubMed, Google Scholar, Scopus, and Web of Science search was performed for studies published from the database inception to January 2018, identifying 326 articles. On the basis of the inclusion criteria, 22 studies remained for review. All articles that were identified were full-text, English language articles examining adults with chronic SCI who were fasted for a minimum of 8 hr before undergoing RMR through indirect calorimetry for at least 20 min. The measured RMR ranged from 1,256.0 to 1,854.0 kcal/day, whereas the estimated RMR ranged from 1,276.8 to 1,808.0 kcal/day in the chronic SCI population. Seven studies overestimated RMR from 4% to 15%, whereas two studies underestimated RMR from 2% to 17% using prediction equations established for the able-bodied population. Two studies produced SCI-specific equations to estimate RMR. With regard to sex and level of injury, RMR does not differ between individuals with tetraplegia and paraplegia, whereas sex-based differences remain inconclusive, given limited results. These data provide evidence for the use of indirect calorimetry to assess RMR and the need to validate SCI-specific prediction equations in the estimation of RMR.

Reliability of, and Agreement Between, two Breath-by-Breath Indirect Calorimeters at Varying Levels of Inspiratory Oxygen.

BACKGROUND: Indirect calorimetry (IC) is considered the accurate way of measuring energy expenditure (EE). IC devices often apply the Haldane transformation, introducing errors at inspiratory oxygen fraction (FiO2 ) >60%. The aim was to assess measurement reliability and agreement between an unevaluated IC (device 2) (Beacon Caresystem, Mermaid Care A/S, Noerresundby, Denmark) not using Haldane transformation and an IC that does (device 1) (Ecovx, GE, Helsinki, Finland) at varying FiO2 . METHODS: Twenty healthy male subjects participated, with 16 completing the study (33 ± 9 years, 83.3 ± 16 kg, 1.83 ± 0.08 m). Subjects were mechanically ventilated in pressure support (3cmH2 O; positive end-expiratory pressure: 3cmH2 O) at FiO2 of 21%, 50%, 85%, and 21% for 15 minutes at each FiO2 . Mean EE, oxygen consumption (VO2 ), and CO2 production (VCO2 ) were compared within and between devices across FiO2 levels. RESULTS: Device 2 showed within-device EE significant differences at 21% vs 50% FiO2 and device 1 for VCO2 at 50% vs. 85% FiO2 . For all variables, both devices showed reliable measurements at 21% and 50% FiO2 , but at 85%, FiO2 bias and limits of agreement increased. Between devices, there were significant differences for EE at both 21% and 85% FiO2 for VO2 and for VCO2 at 85% FiO2 . CONCLUSION: Both systems measured EE, VO2 , and VCO2 at 21%-85% FiO2 reliably but with bias at 85% FiO2 . The devices were in agreement at 21% and 50% FiO2 , but further studies need to confirm accuracy at high FiO2 .

Should we calculate or measure energy expenditure? practical aspects in the ICU.

Indirect calorimetry is currently a gold standard of resting energy expenditure (REE) assessment in critically ill patients. Many predictive equations of energy expenditure have been proved to imprecisely predict REE and lead to under- or overfeeding. The benefits of indirect calorimetry-guided nutrition therapy rather than calculation-based strategy have been demonstrated in randomized controlled trials. To minimize energy debt in the intensive care unit, we support early enteral feeding. REE should be measured as soon as the patient's conditions allow and the target of delivered calorie should be around 0.7 to 1 of measured REE to avoid overfeeding. The supplemental parenteral nutrition should be prescribed to close the caloric gap if the goal is not reached by enteral nutrition alone.

Validity of a population-specific BMR predictive equation for adults from an urban tropical setting.

BACKGROUND & AIMS: Basal metabolic rate (BMR) is an important physiologic measure in nutrition research. In many instances it is not measured but estimated by predictive equations. The purpose of this study was to compare measured BMR (BMRm) with estimated BMR (BMRe) obtained by different equations. METHODS: A convenient sample of 148 (89 women) 20-60 year-old subjects from the metropolitan area of Rio de Janeiro, Brazil participated in the study. BMRm values were measured by an indirect calorimeter and predicted by different equations (Schofield, Henry and Rees, Mifflin-St. Jeor and Anjos. All subjects had their body composition and anthropometric variables also measured. Accuracy of the estimations was established by the percentage of BMRe falling within ±10% of BMRm and bias when the 95% CI of the difference of BMRe and BMRm means did not include zero. RESULTS: Mean BMRm values were 4833.5 (SD 583.3) and 6278.8 (SD 724.0) kJ*day-1 for women and men, respectively. BMRe values were both biased and inaccurate except for values predicted by the Anjos equation. BMR overestimation was approximately 20% for the Schofield equation which was higher comparatively to the Henry and Rees (14.5% and 9.6% for women and men, respectively) and the Mifflin-St. Jeor (approximately 14.0%) equations. BMR estimated by the Anjos equation was unbiased (95% CI = -78.1; 96.3 kJ day-1 for women and -282.6; 30.7 kJ*day-1 for men). CONCLUSIONS: Population-specific BMR predictive equations yield unbiased and accurate BMR values in adults from an urban tropical setting.

Validation of whole room indirect calorimeters: refinement of current methodologies.

Whole room indirect calorimeter (WRIC) validation techniques consist of propane combustion (PC) or infusion of mixed carbon dioxide (CO2) and nitrogen (N2) by a precision blender (PB). To determine the best method, PC of 6, 10, 22-h and PB infusions of 6, 10, and 14-h, were conducted. The 14-h infusion consisted of two metabolic settings. Energy expenditure (EE; kJ), ventilation (V; liters/min) of oxygen (VO2), VCO2, and respiratory quotient (VCO2/VO2) obtained from the WRIC were extrapolated to the respective test durations and compared to similarly calculated values. Moreover, accurate equations (AE) were derived to correct infusions for additional N2 As a final evaluation of a PC validated WRIC, weight maintenance (WM), energy balance (EB), respiratory quotient (RQ), and food quotients (FQ) were determined in 22 subjects who had repeat 24-h EE measurements. Statistical analyses (P < 0.05) were conducted (SPSS, version 23). Significant differences in RQ existed between PC and stoichiometry after 6-h. Errors for the rest of the PC tests ranged from -1.5 ± 2.4 (VCO2) to 2.8 ± 4.6% (EE). When compared with the WRIC, all uncorrected metabolic parameters for six and 10-h PB infusions were significantly different with errors from -12.8 ± 1.6 (VO2) to 6.0 ± 2.8% (RQ). The AE reduced the magnitude of errors to -12.4 ± 1.5 (RQ) to 2.2 ± 3.0% (RQ). The PB infusion with two settings showed similar performance. No differences in WM, EB, RQ, or FQ existed in the subjects. In conclusion, 10-h PC tests are sufficient for validating WRICs.