A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor.

Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and energy expenditure (EE) estimation. Traditionally, sensors are attached to the hip or wrist. The primary aim of this research is to investigate the use of an eyeglass-mounted wearable energy intake sensor (Automatic Ingestion Monitor v2, AIM-2) for simultaneous recognition of physical activity (PAR) and estimation of steady-state EE as compared to a traditional hip-worn device. Study data were collected from six participants performing six structured activities, with the reference EE measured using indirect calorimetry (COSMED K5) and reported as metabolic equivalents of tasks (METs). Next, a novel deep convolutional neural network-based multitasking model (Multitasking-CNN) was developed for PAR and EE estimation. The Multitasking-CNN was trained with a two-step progressive training approach for higher accuracy, where in the first step the model for PAR was trained, and in the second step the model was fine-tuned for EE estimation. Finally, the performance of Multitasking-CNN on AIM-2 attached to eyeglasses was compared to the ActiGraph GT9X (AG) attached to the right hip. On the AIM-2 data, Multitasking-CNN achieved a maximum of 95% testing accuracy of PAR, a minimum of 0.59 METs mean square error (MSE), and 11% mean absolute percentage error (MAPE) in EE estimation. Conversely, on AG data, the Multitasking-CNN model achieved a maximum of 82% testing accuracy in PAR, a minimum of 0.73 METs MSE, and 13% MAPE in EE estimation. These results suggest the feasibility of using an eyeglass-mounted sensor for both PAR and EE estimation.

An appraisal of whole-room indirect calorimeters and a metabolic cart for measuring resting and active metabolic rates.

Whole-room indirect calorimeters (WRICs) have traditionally been used for real-time resting metabolic rate (RMR) measurements, while metabolic rate (MR) during short-interval exercises has commonly been measured by metabolic carts (MCs). This study aims to investigate the feasibility of incorporating short-interval exercises into WRIC study protocols by comparing the performance of WRICs and an MC. We assessed the 40-min RMR of 15 subjects with 2-day repeats and the 10-15 min activity MR (AMR) of 14 subjects at three intensities, using a large WRIC, a small WRIC, and an MC. We evaluated the biases between the instruments and quantified sources of variation using variance component analysis. All three instruments showed good agreement for both RMR (maximum bias = 0.07 kcal/min) and AMR assessment (maximum bias = 0.53 kcal/min). Moreover, the majority of the variability was between-subject and between-intensity variation, whereas the types of instrument contributed only a small amount to total variation in RMR (2%) and AMR (0.2%) data. In Conclusion, the good reproducibility among the instruments indicates that they may be used interchangeably in well-designed studies. Overall, WRICs can serve as an accurate and versatile means of assessing MR, capable of integrating RMR and short-interval AMR assessments into a single protocol.

The clinical evaluation of the new indirect calorimeter developed by the ICALIC project.

BACKGROUND & AIMS: The ICALIC project was initiated for developing an accurate, reliable and user friendly indirect calorimeter (IC) and aimed at evaluating its ease of use and the feasibility of the EE measurements in intensive care unit (ICU). METHODS: This was a prospective unblinded, observational, multi-center study. Simultaneous IC measurements in mechanically ventilated ICU patients were performed using the new IC (Q-NRG®) and currently used devices. Time required to obtain EE was recorded to evaluate the ease of use of Q-NRG® versus currently used ICs and EE measurements were compared. Conventional descriptive statistics were used: data as mean ± SD. RESULTS: Six centers out of nine completed the required number of patients for the primary analysis. Mean differences in the time needed by Q-NRG® against currently used ICs were -32.3 ± 2.5 min in Geneva (vs. Deltatrac®; p < 0.01), -32.3 ± 3.1 in Lausanne (vs. Quark RMR®; p < 0.05), -33.7 ± 1.4 in Brussels (vs. V-Max Encore®; p < 0.05), -26.4 ± 7.8 in Tel Aviv (vs. Deltatrac®; p < 0.05), -28.5 ± 3.5 in Vienna (vs. Deltatrac®; p < 0.05), and 0.3 ± 1.2 in Chiba (vs. E-COVX®; p = 0.17). EE (kcal/day) measurements by the Q-NRG® were similar to the Deltatrac® in Geneva and Vienna (mean differences±SD: -63.1 ± 157.8 (p = 0.462) and -22.9 ± 328.2 (=0.650)), but significantly different in Tel Aviv (307.4 ± 324.5, p < 0.001). Significant differences were observed in Lausanne (Quark RMR®: -224.4 ± 514.9, p = 0.038) and in Brussels (V-max®: -449.6 ± 667.4, p < 0.001), but none was found in Chiba (E-COVX®; 55.0 ± 204.1, p = 0.165). CONCLUSION: The Q-NRG® required a much shorter time than most other ICs to determine EE in mechanically ventilated ICU patients. The Q-NRG® is the only commercially available IC tested against mass spectrometry to ensure gas accuracy, while being very easy-to use.

The effect of cisatracurium infusion on the energy expenditure of critically ill patients: an observational cohort study.

BACKGROUND: Both overfeeding and underfeeding of intensive care unit (ICU) patients are associated with worse outcomes. A reliable estimation of the energy expenditure (EE) of ICU patients may help to avoid these phenomena. Several factors that influence EE have been studied previously. However, the effect of neuromuscular blocking agents on EE, which conceptually would lower EE, has not been extensively investigated. METHODS: We studied a cohort of adult critically ill patients requiring invasive mechanical ventilation and treatment with continuous infusion of cisatracurium for at least 12 h. The study aimed to quantify the effect of cisatracurium infusion on EE (primary endpoint). EE was estimated based on ventilator-derived VCO2 (EE in kcal/day = VCO2 × 8.19). A subgroup analysis of septic and non-septic patients was performed. Furthermore, the effects of body temperature and sepsis on EE were evaluated. A secondary endpoint was hypercaloric feeding (> 110% of EE) after cisatracurium infusion. RESULTS: In total, 122 patients were included. Mean EE before cisatracurium infusion was 1974 kcal/day and 1888 kcal/day after cisatracurium infusion. Multivariable analysis showed a significantly lower EE after cisatracurium infusion (MD - 132.0 kcal (95% CI - 212.0 to - 52.0; p = 0.001) in all patients. This difference was statistically significant in both sepsis and non-sepsis patients (p = 0.036 and p = 0.011). Non-sepsis patients had lower EE than sepsis patients (MD - 120.6 kcal; 95% CI - 200.5 to - 40.8, p = 0.003). Body temperature and EE were positively correlated (Spearman's rho = 0.486, p < 0.001). Hypercaloric feeding was observed in 7 patients. CONCLUSIONS: Our data suggest that continuous infusion of cisatracurium in mechanically ventilated ICU patients is associated with a significant reduction in EE, although the magnitude of the effect is small. Sepsis and higher body temperature are associated with increased EE. Cisatracurium infusion is associated with overfeeding in only a minority of patients and therefore, in most patients, no reductions in caloric prescription are necessary.

Evaluation of the accuracy and precision of a new generation indirect calorimeter in canopy dilution mode.

BACKGROUND & AIMS: Indirect calorimetry (IC) is the only way to measure in real time energy expenditure (EE) and to optimize nutrition support in acutely and chronically ill patients. Unfortunately, most of the commercially available indirect calorimeters are rather complex to use, expensive and poorly accurate and precise. Therefore, an innovative device (Q-NRG®, COSMED, Rome, Italy) that matches clinicians' needs has been developed as part of the multicenter ICALIC study supported by the two academic societies ESPEN and ESICM. The aim of this study was to evaluate the accuracy and intra- and inter-unit precision of this new device in canopy dilution mode in vitro and in spontaneously breathing adults. METHODS: Accuracy and precision of oxygen consumption (VO2) and carbon dioxide production (VCO2) measurements were evaluated in vitro and in 15 spontaneously breathing healthy adults by interchanging three Q-NRG® units in a random order. In vitro validation was performed by gas exchange simulation using high-precision gas mixture and mass flow controller. Accuracy was calculated as error of measured values against expected ones based on volume of gas infused. Respiratory coefficient (RQ) accuracy was furthermore assessed using the ethanol-burning test. To evaluate the intra- and inter-unit precisions, the coefficient of variation (CV% = SD/Mean*100) was calculated, respectively, from the mean ± SD or the mean ± SD of the three mean values of VO2, VCO2, RQ and EE measured by each Q-NRG® units. In vivo accuracy measurement of the Q-NRG® was assessed by simultaneous comparison with mass spectrometry (MS) gas analysis, using Bland-Altman plot, Pearson correlation and paired t-test (significance level of p = 0.05). RESULTS: In vitro evaluation of the Q-NRG® accuracy showed measurement errors <1% for VO2, VCO2 and EE and <1.5% for RQ. Evaluation of the intra- and inter-unit precision showed CV% ≤1% for VO2 and EE and CV% ≤1.5% for VCO2 and RQ measurements, except for one Q-NRG® unit where CV% was 2.3% for VO2 and 3% for RQ. Very good inter-unit precision was confirmed in vivo with CV% equal to 2.4%, 3%, 2.8% and 2.3% for VO2, VCCO2, RQ and EE, respectively. Comparison with MS showed correlation of 0.997, 0.987, 0.913 and 0.997 for VO2, VCO2, RQ and EE respectively (p ≤ 0.05). Mean deviation of paired differences was 1.6 ± 1.4% for VO2, -1.5 ± 2.5% for VCO2, -3.1 ± 2.6% for RQ and 0.9 ± 1.4% for EE. CONCLUSION: Both in vitro and in vivo measurements of VO2, VCO2, RQ and EE on three Q-NRG® units showed minimal differences compared to expected values and MS and very low intra- and inter-unit variability. These results confirm the very good accuracy and precision of the Q-NRG® indirect calorimeter in canopy dilution mode in spontaneously breathing adults.

Use of consumer monitors for estimating energy expenditure in youth.

The purpose of this study was to compare energy expenditure (EE) estimates from 5 consumer physical activity monitors (PAMs) to indirect calorimetry in a sample of youth. Eighty-nine youth (mean (SD); age, 12.3 (3.4) years; 50% female) performed 16 semi-structured activities. Activities were performed in duplicate across 2 visits. Participants wore a Cosmed K4b2 (criterion for EE), an Apple Watch 2 (left wrist), Mymo Tracker (right hip), and Misfit Shine 2 devices (right hip; right shoe). Participants were randomized to wear a Samsung Gear Fit 2 or a Fitbit Charge 2 on the right wrist. Oxygen consumption was converted to EE by subtracting estimated basal EE (Schofield's equation) from the measured gross EE. EE from each visit was summed across the 2 visit days for comparison with the total EE recorded from the PAMs. All consumer PAMs estimated gross EE, except for the Apple Watch 2 (net Active EE). Paired t tests were used to assess differences between estimated (PAM) and measured (K4b2) EE. Mean absolute percent error (MAPE) was used to assess individual-level error. The Mymo Tracker was not significantly different from measured EE and was within 15.9 kcal of measured kilocalories (p = 0.764). Mean percent errors ranged from 3.5% (Mymo Tracker) to 48.2% (Apple Watch 2). MAPE ranged from 16.8% (Misfit Shine 2 - right hip) to 49.9% (Mymo Tracker). Novelty Only the Mymo Tracker was not significantly different from measured EE but had the greatest individual error. The Misfit Shine 2 - right hip had the lowest individual error. Caution is warranted when using consumer PAMs in youth for tracking EE.

In vitro validation of indirect calorimetry device developed for the ICALIC project against mass spectrometry.

RATIONALE: Accurate evaluation of the energy needs is required to optimize nutrition support of critically ill patients. Recent evaluations of indirect calorimeters revealed significant differences among the devices available on the market. A new indirect calorimeter (Q-NRG®, Cosmed, Roma, Italy) has been developed by a group of investigators supporting the international calorimetry study initiative (ICALIC) to achieve ultimate accuracy for measuring energy expenditure while being easy to use, and affordable. This study aims to validate the precision and the accuracy of the Q-NRG® in the in-vitro setting, within the clinically relevant range for adults on mechanical ventilation in the ICU. Mass spectrometry is the reference method for the gas composition analysis to evaluate the analytic performances of the Q-NRG®. METHODS: The accuracy and precision of the O2 and CO2 measurements by the Q-NRG were evaluated by comparing the measurements of known O2 and CO2 gas mixtures with the measurements by the mass spectrometer (Extrel, USA). The accuracy and precision of the Q-NRG® for measurements of VO2 (oxygen consumption) and VCO2 (CO2 production) at clinically relevant ranges (150, 250 and 400 ml/min STPD) were evaluated by measuring simulated gas exchange under mechanically ventilated setting at different FiO2 settings (21-80%), in comparison to the reference measurements by the mass spectrometer-based mixing chamber system. RESULTS: The measurements of gas mixtures of predefined O2 and CO2 concentrations by the Q-NRG® were within 2% accuracy versus the mass spectrometer measurements in Passing Bablok regression analysis. In a mechanically ventilated setting of FiO2 from 21 up to 70%, the Q-NRG® measurements of simulated VO2 and VCO2 were within 5% difference of the reference mass spectrometer measurements. CONCLUSION: In vitro evaluation confirms that the accuracy of the Q-NRG® indirect calorimeter is within 5% at oxygen enrichment to 70%; i.e. maximum expected for clinical use. Further recommendations for the clinical use of the Q-NRG® by will be released once the ongoing multi-center study is completed.

Indirect Calorimetry Performance Using a Handheld Device Compared to the Metabolic Cart in Outpatients with Cirrhosis.

Addressing malnutrition is important to improve health outcomes in outpatients with cirrhosis, yet assessing energy requirements in this population is challenging. Predictive equations of resting energy expenditure (REE) are thought to be unreliable, and traditional indirect calorimetry is expensive and infrequently available for clinical use. The accuracy of REE predictions using a MedGem® handheld indirect calorimeter, the Harris Benedict Equation (HBE), the Mifflin St. Jeor equation (MSJ), and the gold standard Vmax Encore® (Vmax) metabolic cart was compared. The REE of cirrhotic pre-liver transplant outpatients was analyzed using each of the four methods. Agreement between methods was calculated using Bland-Altman analysis. Fourteen patients with cirrhosis participated, and were primarily male (71%) and malnourished (subjective global assessment (SGA) B or C 64%). Lin's concordance coefficient (ρC) for MedGem® vs. Vmax demonstrated poor levels of precision and accuracy (ρC = 0.80, 95% confidence interval 0.55-0.92) between measures, as did the HBE compared to Vmax (ρC = 0.56, 95% confidence interval 0.19-0.79). Mean REE by MedGem® was similar to that measured by Vmax (-1.5%); however, only 21% of REE measures by MedGem® were within ±5% of Vmax measures. Wide variability limits the use of MedGem® at an individual level; a more accurate and feasible method for determination of REE in patients with cirrhosis and malnutrition is needed.

Handheld Indirect Calorimetry as a Clinical Tool for Measuring Resting Energy Expenditure in Children with and without Obesity.

Background: Resting energy expenditure (REE) is a valuable measure in clinical management of obesity and other chronic illnesses. Gold standard methods for measuring REE (e.g., Douglas bags and metabolic cart) are too expensive and cumbersome for an outpatient clinical setting. The purpose of this study was to determine the accuracy of a handheld indirect calorimeter (HHIC) and prediction equations (PEs) for measurement of REE in youth with and without obesity. Methods: Fifty-three children and adolescents (12.8 ± 4.3 years, 50.9% female) had REE measured first with a MedGem™ HHIC for 10 minutes, followed by a reference indirect calorimeter system (ParvoMedics TrueOne 2400™) with hood canopy and dilution pump for 30 minutes. REE was also estimated using nine PEs as follows: Henry-1, Henry-2, Schofield, World Health Organization, Molnar, Muller, Herrmann, Schmelzle, and Harris-Benedict. Concordance correlation coefficients and Bland-Altman analyses were used for comparisons among PEs, MedGem HHIC, and metabolic cart. Results: The observed correlation between the HHIC and the reference system was rc = 0.89 with a mean bias of 2.27 ± 3.41 kcal/(kg·d) (9.1% ± 14.7%). Regarding PE, Molnar had the highest agreement with the reference system [rc = 0.93, bias of 2.17 ± 2.04 kcal/(kg·d); 9.8% ± 8.1%], followed by Harris-Benedict (rc = 0.89; 13.8% ± 8.9%), Henry-2 (rc = 0.89; 15% ± 7.6%), and Henry-1 (rc = 0.86; 16.7% ± 7.3%). All PEs were less accurate for children with overweight/obesity. Conclusions: Compared to PE, the HHIC provided more accurate REE estimates for children across the age and BMI spectrum, although positive bias was present throughout. Difference in positive bias between the HHIC and the Molnar equation may be clinically significant for youth with overweight/obesity.

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 .

Accuracy of a Portable Indirect Calorimeter for Measuring Resting Energy Expenditure in Individuals With Cancer.

BACKGROUND: Determining optimal caloric intake for an individual with cancer is complicated by metabolic changes that occur, namely, alterations in resting energy expenditure (REE). There is currently no validated clinically available equation or tool to measure energy expenditure in these patients. METHODS: Patients with newly diagnosed solid tumors underwent REE assessments using the FitMate GS portable indirect calorimeter and reference VMax metabolic cart; both used canopy hoods. REE was also estimated from the Harris-Benedict, Mifflin St. Jeor, and Henry equations for comparison. Data were analyzed using paired samples t-test and the Bland-Altman approach to assess group-level and individual-level agreement compared with the metabolic cart. RESULTS: A total 26 patients (19 males; body mass index: 27.8 ± 5.5 kg/m2 ; age: 62 ± 10 years) participated in the study. Biases for the FitMate GS and both equations were low (ranging from -44 to -92 kcal or -2.3% to -5.1%), indicating good group-level accuracy. The FitMate GS had low bias, but the widest limits of agreement (-28.0% to 21.2%) compared with the 3 equations (Harris-Benedict: -15.8% to 11.2%; Mifflin St. Jeor: -17.1% to 6.9%; Henry: -15.4% to 11.5%). These differences were not due to volume of oxygen, BMI category, or sex. CONCLUSION: FitMate GS performed well on a group level, but its accuracy was poor on an individual level. Further research should develop better equations and validate tools to measure energy expenditure for accurate dietary recommendations for patients at nutrition risk.

Test-retest variability of VO2max using total-capture indirect calorimetry reveals linear relationship of VO2 and Power.

This study aimed to analyze the intra-individual variation in VO2max of human subjects using total-capture and free-flow indirect calorimetry. Twenty-seven men (27 ± 5 year; VO2max 49-79 mL•kg-1 •min-1 ) performed two maximal exertion tests (CPETs) on a cycle ergometer, separated by a 7 ± 2 day interval. VO2 and VCO2 were assessed using an indirect calorimeter (Omnical) with total capture of exhalation in a free-flow airstream. Thirteen subjects performed a third maximal exertion test using a breath-by-breath calorimeter (Oxycon Pro). On-site validation was deemed a requirement. For the Omnical, the mean within-subject CV for VO2max was 1.2 ± 0.9% (0.0%-4.4%) and for ergometer workload P max 1.3 ± 1.3% (0%-4.6%). VO2max values with the Oxycon Pro were significantly lower in comparison with Omnical (P < 0.001; t test) with mean 3570 vs 4061 and difference SD 361 mL•min-1 . Validation results for the Omnical with methanol combustion were -0.05 ± 0.70% (mean ± SD; n = 31) at the 225 mL•min-1 VO2 level and -0.23 ± 0.80% (n = 31) at the 150 mL•min-1 VCO2 level. Results using gas infusion were 0.04 ± 0.75% (n = 34) and -0.99 ± 1.05% (n = 24) over the respective 500-6000 mL•min-1 VO2 and VCO2 ranges. Validation results for the Oxycon Pro in breath-by-breath mode were - 2.2 ± 1.6% (n = 12) for VO2 and 5.7 ± 3.3% (n = 12) for VCO2 over the 1000-4000 mL•min-1 range. On a Visual analog scale, participants reported improved breathing using the free-flow indirect calorimetry (score 7.6 ± 1.2 vs 5.1 ± 2.7, P = 0.008). We conclude that total capturing free-flow indirect calorimetry is suitable for measuring VO2 even with the highest range. VO2max was linear with the incline in P max over the full range.

Indirect calorimetry in critically ill mechanically ventilated patients: Comparison of E-sCOVX with the deltatrac.

BACKGROUND & AIMS: Indirect calorimetry is recommended to measure energy expenditure (EE) in critically ill, mechanically ventilated patients. The most validated system, the Deltatrac® (Datex-Ohmeda, Helsinki, Finland) is no longer in production. We tested the agreement of a new breath-by-breath metabolic monitor E-sCOVX® (GE healthcare, Helsinki, Finland), with the Deltatrac. We also compared the performance of the E-sCOVX to commonly used predictive equations. METHODS: We included mechanically ventilated patients eligible to undergo indirect calorimetry. After a stabilization period, EE was measured simultaneously with the Deltatrac and the E-sCOVX for 2 h. Agreement and precision of the E-sCOVX was tested by determining bias, limits of agreement and agreement rates compared to the Deltatrac. Performance of the E-sCOVX was also compared to four predictive equations: the 25 kcal/kg, Penn State University 2003b, Faisy, and Harris-Benedict equation. RESULTS: We performed 29 measurements in 16 patients. Mean EE-Deltatrac was 1942 ± 274 kcal/day, and mean EE-E-sCOVX was 2177 ± 319 kcal/day (p < 0.001). E-sCOVX overestimated EE with a bias of 235 ± 149 kcal/day, being 12.1% of EE-Deltatrac. Limits of agreement were -63 to +532 kcal/day. The 10% and 15% agreement rates of EE-E-sCOVX compared to the Deltatrac were 34% and 72% respectively. The bias of E-sCOVX was lower than the bias of the 25 kcal/kg-equation, but higher than bias of the other equations. Agreement rates for E-sCOVX were similar to the equations. The Faisy-equation had the highest 15% agreement rate. CONCLUSION: The E-sCOVX metabolic monitor is not accurate in estimating EE in critically ill mechanically ventilated patients when compared to the Deltatrac, the present reference method. The E-sCOVX overestimates EE with a bias and precision that are clinically unacceptable.

Resting metabolic rate in muscular physique athletes: validity of existing methods and development of new prediction equations.

Estimation of resting metabolic rate (RMR) is an important step for prescribing an individual's energy intake. The purpose of this study was to evaluate the validity of portable indirect calorimeters and RMR prediction equations in muscular physique athletes. Twenty-seven males (n = 17; body mass index (BMI): 28.8 ± 2.0 kg/m2; body fat: 12.5% ± 2.7%) and females (n = 10; BMI: 22.8 ± 1.6 kg/m2; body fat: 19.2% ± 3.4%) were evaluated. The reference RMR value was obtained from the ParvoMedics TrueOne 2400 indirect calorimeter, and the Cosmed Fitmate and Breezing Metabolism Tracker provided additional RMR estimates. Existing RMR prediction equations based on body weight (BW) or dual-energy X-ray absorptiometry fat-free mass (FFM) were also evaluated. Errors in RMR estimates were assessed using validity statistics, including t tests with Bonferroni correction, linear regression, and calculation of the standard error of the estimate, total error, and 95% limits of agreement. Additionally, new prediction equations based on BW (RMR (kcal/day) = 24.8 × BW (kg) + 10) and FFM (RMR (kcal/day) = 25.9 × FFM (kg) + 284) were developed using stepwise linear regression and evaluated using leave-one-out cross-validation. Nearly all existing BW- and FFM-based prediction equations, as well as the Breezing Tracker, did not exhibit acceptable validity and typically underestimated RMR. The ten Haaf and Weijs (PLoS ONE, 9: e1084602014 (2014)) and Cunningham (1980) (Am. J. Clin. Nutr. 33: 2372-2374 (1980)) FFM-based equations may produce acceptable RMR estimates, although the Cosmed Fitmate and newly developed BW- and FFM-based equations may be most suitable for RMR estimation in male and female physique athletes. Future research should provide additional external cross-validation of the newly developed equations to refine the ability to predict RMR in physique athletes.

Innovations in energy expenditure assessment.

PURPOSE OF REVIEW: Optimal nutritional therapy has been associated with better clinical outcomes and requires providing energy as closed as possible to measured energy expenditure. We reviewed the current innovations in energy expenditure assessment in humans, focusing on indirect calorimetry and other new alternative methods. RECENT FINDINGS: Although considered the reference method to measure energy expenditure, the use of indirect calorimetry is currently limited by the lack of an adequate device. However, recent technical developments may allow a broader use of indirect calorimetry for in-patients and out-patients. An ongoing international academic initiative to develop a new indirect calorimeter aimed to provide innovative and affordable technical solutions for many of the current limitations of indirect calorimetry. New alternative methods to indirect calorimetry, including CO2 measurements in mechanically ventilated patients, isotopic approaches and accelerometry-based fitness equipments, show promises but have been either poorly studied and/or are not accurate compared to indirect calorimetry. Therefore, to date, energy expenditure measured by indirect calorimetry remains the gold standard to guide nutritional therapy. SUMMARY: Some new innovative methods are demonstrating promises in energy expenditure assessment, but still need to be validated. There is an ongoing need for easy-to-use, accurate and affordable indirect calorimeter for daily use in in-patients and out-patients.

Congruent validity and inter-day reliability of two breath by breath metabolic carts to measure resting metabolic rate in young adults.

BACKGROUND & AIMS: Achieving high inter-day reliability is a key factor to analyze the magnitude of change in RMR, for instance after an intervention. The aims of this study were: i) to determine the congruent validity of RMR and respiratory quotient (RQ) with two breath by breath commercially available metabolic carts [CCM Express (CCM) and Ultima CardiO2 (MGU)]; and ii) to analyze the inter-day reliability of RMR and RQ measurements. METHODS & RESULTS: Seventeen young adults participated in the study. RMR measurements were performed during two consecutive 30-min periods, on two consecutive days with both metabolic carts. The 5-min period that met the steady state criteria [Coefficient of variance (CV) < 10% for VO2, VCO2, and VE, and CV<5% for RQ] and with the lowest CV average was included in further analysis. RMR values were higher with the MGU than with the CCM on both days (two-way ANOVA, P = 0.021), however, no differences were found on RQ values obtained by both metabolic carts (P = 0.642). Absolute inter-day RMR differences obtained with the MGU were higher than those obtained with the CCM (219 ± 185 vs. 158 ± 154 kcal/day, respectively, P = 0.002; 18.3 ± 17.2% vs. 13.5 ± 15.3%, respectively, P = 0.046). We observed a significant positive association of absolute inter-day differences in RMR obtained with both metabolic carts (ß = 0.717; R2 = 0.743; P < 0.001). CONCLUSIONS: The CCM metabolic cart provides lower RMR values and seems more reliable than the MGU in our sample of young adults. Our findings also suggest that a great part of inter-day variability is explained by the individuals.

Improving temporal accuracy of human metabolic chambers for dynamic metabolic studies.

Metabolic chambers are powerful tools for assessing human energy expenditure, providing flexibility and comfort for the subjects in a near free-living environment. However, the flexibility offered by the large living room size creates challenges in the assessment of dynamic human metabolic signals-such as those generated during high-intensity interval training and short-term involuntary physical activities-with sufficient temporal accuracy. Therefore, this paper presents methods to improve the temporal accuracy of metabolic chambers. The proposed methods include 1) adopting a shortest possible step size, here one minute, to compute the finite derivative terms for the metabolic rate calculation, and 2) applying a robust noise reduction method-total variation denoising-to minimize the large noise generated by the short derivative term whilst preserving the transient edges of the dynamic metabolic signals. Validated against 24-hour gas infusion tests, the proposed method reconstructs dynamic metabolic signals with the best temporal accuracy among state-of-the-art approaches, achieving a root mean square error of 0.27 kcal/min (18.8 J/s), while maintaining a low cumulative error in 24-hour total energy expenditure of less than 45 kcal/day (188280 J/day). When applied to a human exercise session, the proposed methods also show the best performance in terms of recovering the dynamics of exercise energy expenditure. Overall, the proposed methods improve the temporal resolution of the chamber system, enabling metabolic studies involving dynamic signals such as short interval exercises to carry out the metabolic chambers.

Determining the Accuracy and Reliability of Indirect Calorimeters Utilizing the Methanol Combustion Technique.

BACKGROUND: Several indirect calorimetry (IC) instruments are commercially available, but comparative validity and reliability data are lacking. Existing data are limited by inconsistencies in protocols, subject characteristics, or single-instrument validation comparisons. The aim of this study was to compare accuracy and reliability of metabolic carts using methanol combustion as the cross-laboratory criterion. METHODS: Eight 20-minute methanol burn trials were completed on 12 metabolic carts. Respiratory exchange ratio (RER) and percent O2 and CO2 recovery were calculated. RESULTS: For accuracy, 1 Omnical, Cosmed Quark CPET (Cosmed), and both Parvos (Parvo Medics trueOne 2400) measured all 3 variables within 2% of the true value; both DeltaTracs and the Vmax Encore System (Vmax) showed similar accuracy in measuring 1 or 2, but not all, variables. For reliability, 8 instruments were shown to be reliable, with the 2 Omnicals ranking best (coefficient of variation [CV] < 1.26%). Both Cosmeds, Parvos, DeltaTracs, 1 Jaeger Oxycon Pro (Oxycon), Max-II Metabolic Systems (Max-II), and Vmax were reliable for at least 1 variable (CV ≤ 3%). For multiple regression, humidity and amount of combusted methanol were significant predictors of RER (R2 = 0.33, P < .001). Temperature and amount of burned methanol were significant predictors of O2 recovery (R2 = 0.18, P < .001); only humidity was a predictor for CO2 recovery (R2 = 0.15, P < .001). CONCLUSIONS: Omnical, Parvo, Cosmed, and DeltaTrac had greater accuracy and reliability. The small number of instruments tested and expected differences in gas calibration variability limits the generalizability of conclusions. Finally, humidity and temperature could be modified in the laboratory to optimize IC conditions.

Comparison of Resting Energy Expenditure Assessment in Pediatric Oncology Patients.

BACKGROUND: Evaluation of energy requirements is an important part of the nutrition assessment of pediatric oncology patients. Adequate provision of energy in this population is of extreme importance because of the prevalence of malnutrition and its effect on growth, development, quality of life, morbidity, and mortality. Numerous methods are used in clinical practice for estimating the resting energy expenditures (REE), specifically indirect calorimetry and predictive equations. A relatively new instrument used to assess REE is the hand-held indirect calorimeter. The purpose of this quality improvement project was to compare the accuracy of REE measurements taken by a hand-held indirect calorimeter and predictive equations to that of a standard indirect calorimeter metabolic cart. METHODS: Patients receiving therapy for pediatric cancer, aged 7-18 years, and having a weight ≥15 kg and scheduled for a REE nutrition assessment were eligible. Sequentially, the patient's REE was assessed with the cart and the hand-held indirect calorimeter along with the predictive equation calculation. RESULTS: Post hoc pairwise comparisons revealed that all 3 methods were significantly different from one another (P < .0001). When compared with the cart, the portable hand-held calorimeter was found to underestimate REE by 11.9%, whereas predictive equations overestimated REE by 12.4%. CONCLUSION: Our quality improvement project suggests that the hand-held indirect calorimeter underestimated REE, and predictive equations overestimated REE in pediatric oncology nutrition assessment. Therefore, we recommend that these limitations in assessment be considered when assessing REE using a hand-held indirect calorimeter or predictive equations.