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.

Resting energy expenditure differs among individuals with different levels of perceived thermal sensitivity: A cross-sectional study.

Metabolic rate has been used in thermophysiological models for predicting the thermal response of humans. However, only a few studies have investigated the association between an individual's trait-like thermal sensitivity and resting energy expenditure (REE), which resulted in inconsistent results. This study aimed to explore the association between REE and perceived thermal sensitivity. The REE of healthy adults was measured using an indirect calorimeter, and perceived thermal intolerance and sensation in the body were evaluated using a self-administered questionnaire. In total, 1567 individuals were included in the analysis (women = 68.9%, age = 41.1 ±â€…13.2 years, body mass index = 23.3 ±â€…3.3 kg/m2, REE = 1532.1 ±â€…362.4 kcal/d). More women had high cold intolerance (31.8%) than men (12.7%), and more men had high heat intolerance (23.6%) than women (16.1%). In contrast, more women experienced both cold (53.8%) and heat (40.6%) sensations in the body than men (cold, 29.1%; heat, 27.9%). After adjusting for age, fat-free mass, and fat mass, lower cold intolerance, higher heat intolerance, and heat sensation were associated with increased REE only in men (cold intolerance, P for trend = .001; heat intolerance, P for trend = .037; heat sensation, P = .046), whereas cold sensation was associated with decreased REE only in women (P = .023). These findings suggest a link between the perceived thermal sensitivity and REE levels in healthy individuals.

Effects of Energy Delivery Guided by Indirect Calorimetry in Critically Ill Patients: A Systematic Review and Meta-Analysis.

BACKGROUND: The utility of using indirect calorimetry (IC) to estimate energy needs and methods for its application to this purpose remain unclear. This systematic review investigated whether using IC to estimate energy expenditure in critically ill patients is more meaningful for improving survival than other estimation methods. METHODS: Comprehensive searches were conducted in MEDLINE using PubMed, Cochrane Central Register of Controlled Trials, and Igaku-Chuo-Zasshi up to March 2023. RESULTS: Nine RCTs involving 1178 patients were included in the meta-analysis. The evidence obtained suggested that energy delivery by IC improved short-term mortality (risk ratio, 0.86; 95% confidence interval [CI], 0.70 to 1.06). However, the use of IC did not appear to affect the length of ICU stay (mean difference [MD], 0.86; 95% CI, -0.98 to 2.70) or the duration of mechanical ventilation (MD, 0.66; 95% CI, -0.39 to 1.72). Post hoc analyses using short-term mortality as the outcome found no significant difference by target calories in resting energy expenditure, whereas more frequent IC estimates were associated with lower short-term mortality and were more effective in mechanically ventilated patients. CONCLUSIONS: This updated meta-analysis revealed that the use of IC may improve short-term mortality in patients with critical illness and did not increase adverse events.

Indirect calorimetry directed feeding and cycling in the older ICU population: a pilot randomised controlled trial.

BACKGROUND: Older critically ill patients experience rapid muscle loss during stay in an intensive care unit (ICU) due to physiological stress and increased catabolism. This may lead to increased ICU length of stay, delayed weaning from ventilation and persistent functional limitations. We hypothesized that with optimal nutrition and early physical therapy acting in synergism, we can reduce muscle mass loss and improve functional outcomes. METHODS: This was a prospective, single blinded randomized, controlled single-center pilot study to compare the lean muscle mass (measured at bilateral quadriceps femoris using ultrasound) of older ICU patients at 4 time points over 14 days between the control and intervention groups. The control group received standard weight-based empiric feeding and standard ICU physiotherapy. The intervention group received indirect calorimetry directed feeding adjusted daily and 60 min per day of cycle ergometry. 21 patients were recruited and randomized with 11 patients in the control arm and 10 patients in the intervention arm. Secondary outcome measures included ICU and hospital mortality, length of stay, functional assessments of mobility and assessment of strength. RESULTS: Median age was 64 in the control group and 66 in the intervention group. Median calories achieved was 24.5 kcal/kg per day in the control group and 23.3 kcal/kg per day in the intervention group. Cycle ergometry was applied to patients in the intervention group for a median of 60 min a day and a patient had a median of 8.5 sessions in 14 days. Muscle mass decreased by a median of 4.7cm2 in the right quadriceps femoris in the control group and 1.8cm2 in the intervention group (p = 0.19), while the left quadriceps femoris decreased by 1.9cm2 in the control group and 0.1cm2 in the intervention group (p = 0.51). CONCLUSION: In this pilot study, we found a trend towards decrease muscle loss in bilateral quadriceps femoris with our combined interventions. However, it did not reach statistical significance likely due to small number of patients recruited in the study. However, we conclude that the intervention is feasible and potentially beneficial and may warrant a larger scale study to achieve statistical significance. TRIAL REGISTRATION: This study was registered on Clinicaltrials.gov on 30th May 2018 with identifier NCT03540732.

Development and validation of a smartwatch algorithm for differentiating physical activity intensity in health monitoring.

To develop and validate a machine learning based algorithm to estimate physical activity (PA) intensity using the smartwatch with the capacity to record PA and determine outdoor state. Two groups of participants, including 24 adults (13 males) and 18 children (9 boys), completed a sequential activity trial. During each trial, participants wore a smartwatch, and energy expenditure was measured using indirect calorimetry as gold standard. The support vector machine algorithm and the least squares regression model were applied for the metabolic equivalent (MET) estimation using raw data derived from the smartwatch. Exercise intensity was categorized based on MET values into sedentary activity (SED), light activity (LPA), moderate activity (MPA), and vigorous activity (VPA). The classification accuracy was evaluated using area under the ROC curve (AUC). The METs estimation accuracy were assessed via the mean absolute error (MAE), the correlation coefficient, Bland-Altman plots, and intraclass correlation (ICC). A total of 24 adults aged 21-34 years and 18 children aged 9-13 years participated in the study, yielding 1790 and 1246 data points for adults and children respectively for model building and validation. For adults, the AUC for classifying SED, MVPA, and VPA were 0.96, 0.88, and 0.86, respectively. The MAE between true METs and estimated METs was 0.75 METs. The correlation coefficient and ICC were 0.87 (p < 0.001) and 0.89, respectively. For children, comparable levels of accuracy were demonstrated, with the AUC for SED, MVPA, and VPA being 0.98, 0.89, and 0.85, respectively. The MAE between true METs and estimated METs was 0.80 METs. The correlation coefficient and ICC were 0.79 (p < 0.001) and 0.84, respectively. The developed model successfully estimated PA intensity with high accuracy in both adults and children. The application of this model enables independent investigation of PA intensity, facilitating research in health monitoring and potentially in areas such as myopia prevention and control.

Estimation of Heat Production Rate using Thermal Data During Exercise in Indoor Environments: A Study of Heat Storage Rate in Male Athletes.

The increasing preference for indoor exercise spaces highlights the relationship between indoor thermal environments and physiological responses, particularly concerning thermal comfort during physical activity. Determining the metabolic heat production rate during exercise is essential for optimizing the thermal comfort, well-being, and performance of individuals engaged in physical activities. This value can be determined during the activity using several methods, including direct calorimetry measurement, indirect calorimetry that uses analysis of respiratory gases, or approximations using collected data such as speed, body mass, and heart rate. The study aimed to calculate the metabolic heat production rate by infrared thermal evaluation (ITE) based on the body's thermal balance approach and compare it with the values determined by indirect calorimetry (IC). Fourteen participants volunteered for the study, using a cycling ergometer in a controlled climatic chamber. After the familiarization sessions, maximal O2 intake levels (VO2max) were determined through maximal graded exercise tests. Subsequently, constant work rate exercise tests were performed at 60% of VO2max for 20 min. The metabolic heat production rates were calculated by IC and ITE for each athlete individually. Respiratory gases were used to determine IC, while body skin and core temperatures, along with physical environmental data, were applied to calculate ITE using the human body thermal balance approximation of ASHRAE. According to the results, heat storage rates were misleading among the body's heat transfer modes, particularly during the first 8 min of the exercise. ITE showed a moderate level of correlation with IC (r: 0.03-0.86) with a higher level of dispersion relative to the mean (CV%: 12-84%). Therefore, a new equation (ITEnew) for the heat storage rates was proposed using the experimental data from this study. The results showed that ITEnew provided more precise estimations for the entire exercise period (p > 0.05). Correlations between ITEnew and IC values were consistently strong throughout the exercise period (r: 0.62-0.85). It can be suggested that ITEnew values can predict IC during the constant work rate steady-state exercise.

Describing Energy Expenditure in Children with a Chronic Disease: A Systematic Review.

Understanding energy expenditure in children with chronic disease is critical due to the impact on energy homeostasis and growth. This systematic review aimed to describe available literature of resting (REE) and total energy expenditure (TEE) in children with chronic disease measured by gold-standard methods of indirect calorimetry (IC) and doubly labeled water (DLW), respectively. A literature search was conducted using OVID Medline, Embase, CINAHL Plus, Cochrane, and Scopus until July 2023. Studies were included if the mean age of the participants was ≤18 y, participants had a chronic disease, and measurement of REE or TEE was conducted using IC or DLW, respectively. Studies investigating energy expenditure in premature infants, patients with acute illness, and intensive care patients were excluded. The primary outcomes were the type of data (REE, TEE) obtained and REE/TEE stratified by disease group. In total, 271 studies across 24 chronic conditions were identified. Over 60% of retrieved studies were published >10 y ago and conducted on relatively small population sizes (n range = 1-398). Most studies obtained REE samples (82%) rather than that of TEE (8%), with very few exploring both samples (10%). There was variability in the difference in energy expenditure in children with chronic disease compared with that of healthy control group across and within disease groups. Eighteen predictive energy equations were generated across the included studies. Quality assessment of the studies identified poor reporting of energy expenditure protocols, which may limit the validity of results. Current literature on energy expenditure in children with chronic disease, although extensive, reveals key future research opportunities. International collaboration and robust measurement of energy expenditure should be conducted to generate meaningful predictive energy equations to provide updated evidence that is reflective of emerging disease-modifying therapies. This study was registered in PROSPERO as CRD42020204690.

Measurement and estimation of energy in the critically ill.

PURPOSE OF REVIEW: Recent changes in guidelines recommendation during early phase of critical illness and use of indirect calorimetry. The aim of this review is to discuss methods of determining energy requirements in the critically ill and highlight factors impacting resting energy expenditure. RECENT FINDING: An appraisal of recent literature discussing indirect calorimetry guided-nutrition potential benefits or pitfalls. Recent attempts to devise strategy and pilot indirect calorimetry use in the critically ill patients requiring continuous renal replacement therapy or extracorporeal membrane oxygenation are also discussed. Additionally, we briefly touched on variability between guidelines recommended energy target and measured energy expenditure for adult critically ill patients with obesity. SUMMARY: While energy requirement in the critically ill continues to be an area of controversy, recent guidelines recommendations shift toward providing less aggressive calories during acute phase of illness in the first week of ICU.Use of indirect calorimetry may provide more accurate energy target compared to the use of predictive equations. Despite the absence of literature to support long term mortality benefits, there are many potential benefits for the use of indirect calorimetry when available.

Association between protocol change to a higher-protein formula with lower energy targets and nutrient delivery in critically ill patients with COVID-19: A retrospective cohort study.

BACKGROUND: Guidelines recommend prioritizing protein provision while avoiding excessive energy delivery to critically ill patients with coronavirus disease 2019 (COVID-19), but there are no prospective studies evaluating such a targeted approach in this group. We aimed to evaluate the effect of a "higher-protein formula protocol" on protein, energy, and volume delivery when compared with standard nutrition protocol. METHODS: This was a retrospective cohort study of adult patients with COVID-19 who received mechanical ventilation for >72 h and enteral nutrition. Before October 2021, the standard nutrition protocol for patients was 0.7 ml/kg/h ideal body weight (IBW) of a 63 g/L protein and 1250 kcal/L formula. From October 2021, we implemented a higher-protein formula protocol for patients with COVID-19. The initial prescription was 0.5 ml/kg/h IBW of a 100 g/L protein and 1260 kcal/L formula with greater emphasis on energy targets being directed by indirect calorimetry when possible. Measured outcomes included protein, energy, and volume delivered. RESULTS: There were 114 participants (standard protocol, 48; higher-protein protocol, 66) with 1324 days of nutrition support. The median (95% CI) differences in protein, energy, and volume delivery between targeted and standard protocol periods were 0.08 g/kg/day (-0.02 to 0.18 g/kg/day), -1.71 kcal/kg/day (-3.64 to 0.21 kcal/kg/day) and -1.5 ml/kg/day (-2.9 to -0.1 ml/kg/day). Thirty-three patients (standard protocol, 7; higher-protein protocol, 26) had 44 indirect calorimetry assessments. There was no difference in measured energy expenditure over time (increased by 0.49 kcal/kg/day [-0.89 to 1.88 kcal/kg/day]). CONCLUSION: Implementation of a higher-protein formula protocol to patients with COVID-19 modestly reduced volume administration without impacting protein and energy delivery.

Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults.

BACKGROUND: Predicting energy requirements for older adults is compromised by the underpinning data being extrapolated from younger adults. OBJECTIVES: To generate and validate new total energy expenditure (TEE) predictive equations specifically for older adults using readily available measures (age, weight, height) and to generate and test new physical activity level (PAL) values derived from 1) reference method of indirect calorimetry and 2) predictive equations in adults aged ≥65 y. METHODS: TEE derived from "gold standard" methods from n = 1657 (n = 1019 females, age range 65-90 y), was used to generate PAL values. PAL ranged 1.28-2.05 for males and 1.26-2.06 for females. Physical activity (PA) coefficients were also estimated and categorized (inactive to very active) from population means. Nonlinear regression was used to develop prediction equations for estimating TEE. Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split, and leave one out cross-validation were performed. Comparisons were made with existing equations. RESULTS: Equations predicting TEE using the Institute of Medicine method are as follows: For males, TEE = -5680.17 - 17.50 × age (years) + PA coefficient × (6.96 × weight [kilograms] + 44.21 × height [centimeters]) + 1.13 × resting metabolic rate (RMR) (kilojoule/day). For females, TEE = -5290.72 - 8.38 × age (years) + PA coefficient × (9.77 × weight [kilograms] + 41.51 × height [centimeters]) + 1.05 × RMR (kilojoule/day), where PA coefficient values range from 1 (inactive) to 1.51 (highly active) in males and 1 to 1.44 in females respectively. Predictive performance for TEE from anthropometric variables and population mean PA was moderate with limits of agreement approximately ±30%. This improved to ±20% if PA was adjusted for activity category (inactive, low active, active, and very active). Where RMR was included as a predictor variable, the performance improved further to ±10% with a median absolute prediction error of approximately 4%. CONCLUSIONS: These new TEE prediction equations require only simple anthropometric data and are accurate and reproducible at a group level while performing better than existing equations. Substantial individual variability in PAL in older adults is the major source of variation when applied at an individual level.

Adequacy of basal metabolic rate prediction equations in individuals with severe obesity: A systematic review and meta-analysis.

The determination of energy requirements in clinical practice is based on basal metabolic rate (BMR), frequently predicted by equations that may not be suitable for individuals with severe obesity. This systematic review and meta-analysis examined the accuracy and precision of BMR prediction equations in adults with severe obesity. Four databases were searched in March 2021 and updated in May 2023. Eligible studies compared BMR prediction equations with BMR measured by indirect calorimetry. Forty studies (age: 28-55 years, BMI: 40.0-62.4 kg/m2) were included, most of them with a high risk of bias. Studies reporting bias (difference between estimated and measured BMR) were included in the meta-analysis (n = 20). Six equations were meta-analyzed: Harris & Benedict (1919); WHO (weight) (1985); Owen (1986); Mifflin (1990); Bernstein (1983); and Cunningham (1980). The most accurate and precise equations in the overall analysis were WHO (-12.44 kcal/d; 95%CI: -81.4; 56.5 kcal/d) and Harris & Benedict (-18.9 kcal/d; 95%CI -73.2; 35.2 kcal/d). All the other equations tended to underestimate BMR. Harris & Benedict and WHO were the equations with higher accuracy and precision in predicting BMR in individuals with severe obesity. Additional analyses suggested that equations may perform differently according to obesity BMI ranges, which warrants further investigation.

Research Note: Effect of fasting time on the fasting heat production, blood metabolites, and body components of layer-type pullets.

Fasting heat production (FHP) is used to assess the maintenance net energy requirement of animals. Herein, the FHP of layer-type pullets was estimated. In trial 1, 16 40-day-old Jingfen layer-type pullets were divided into 4 groups of 4 chickens and placed in 4 respiratory chambers. Pullets had free access to feed and water. After 4-d acclimatization, feed was withdrawn, and chickens were measured for FHP for 3 consecutive days. In trial 2, twenty-four 40-day-old pullets were placed in 4 respiratory calorimetry chambers, with 6 pullets per chamber. After 4-d acclimatization, one chamber was randomly selected and all pullets in the chamber was sampled at 5, 25, 50, or 65 h after feed withdrawal. The result showed that FHP declined with fasting time and reached the lowest level between 48 and 72 h. Respiratory quotient was decreased (P < 0.05) between 24 and 48 h compared with that in the first 24 h after fasting. The FHP in the light period showed a significant to decline with fasting time (P < 0.01), whereas the FHP in the dark period was decreased (P < 0.01) 24 h after fasting. Body weight, thigh mass, and abdominal fat decreased (P < 0.05) at 25 h after fasting. Serum glucose were increased (P < 0.01) and while triglycerides were significantly decreased (P < 0.01) at 50 h compared with that at 5 and 25 h time point. The result suggests that the adequate measuring period for FHP for layer-type pullets is from 24 to 48 h after fasting. The FHP of 7-wk-old layer-type pullets was 562.20 kJ/kg of BW0.75/d under a 10-h light and 14-h dark lighting regime.

Low respiratory quotient correlates with high mortality in patients undergoing mechanical ventilation.

OBJECTIVE: Oxygen consumption (VO2), carbon dioxide generation (VCO2), and respiratory quotient (RQ), which is the ratio of VO2 to VCO2, are critical indicators of human metabolism. To seek a link between the patient's metabolism and pathophysiology of critical illness, we investigated the correlation of these values with mortality in critical care patients. METHODS: This was a prospective, observational study conducted at a suburban, quaternary care teaching hospital. Age 18 years or older healthy volunteers and patients who underwent mechanical ventilation were enrolled. A high-fidelity automation device, which accuracy is equivalent to the gold standard Douglas Bag technique, was used to measure VO2, VCO2, and RQ at a wide range of fraction of inspired oxygen (FIO2). RESULTS: We included a total of 21 subjects including 8 post-cardiothoracic surgery patients, 7 intensive care patients, 3 patients from the emergency room, and 3 healthy volunteers. This study included 10 critical care patients, whose metabolic measurements were performed in the ER and ICU, and 6 died. VO2, VCO2, and RQ of survivors were 282 +/- 95 mL/min, 202 +/- 81 mL/min, and 0.70 +/- 0.10, and those of non-survivors were 240 +/- 87 mL/min, 140 +/- 66 mL/min, and 0.57 +/- 0.08 (p = 0.34, p = 0.10, and p < 0.01), respectively. The difference of RQ was statistically significant (p < 0.01) and it remained significant when the subjects with FIO2 < 0.5 were excluded (p < 0.05). CONCLUSIONS: Low RQ correlated with high mortality, which may potentially indicate a decompensation of the oxygen metabolism in critically ill patients.

Determination of energy requirements after minor burns using indirect calorimetry: A descriptive cohort study.

BACKGROUND: Minor burns could be associated with moderate hypermetabolism. In this study, the primary outcome was measured energy expenditure (mEE) determined by indirect calorimetry in patients with minor burns. We also compared mEE with predictive values and actual energy intakes. METHODS: Adults with minor burns exclusively treated on an outpatient basis were included. During the week following injury, a dietitian performed indirect calorimetry (Q-NRG in canopy mode), calculated the estimated energy expenditure (eEE) based on the Harris-Benedict (HB) and Henry formulas, and evaluated daily energy intakes using a food anamnesis. RESULTS: Forty-nine patients (59.2% male; median age: 35 [interquartile range: 29-46.5] years; body mass index [BMI]: 26.2 [22.3-29.6] kg/m2; burn surface area [BSA]: 1.5% [1%-2%]) were included 4 (2-6) days after injury. The mEE was 1863 (1568-2199) kcal or 25 (22.4-28.5) kcal/kg and 1838 (1686-2026) kcal or 26.1 (23.7-27.7) kcal/kg in patients who were respectively fasting for >10 h or not (P = 0.991 or P = 0.805). The total mEE was 104% (95%-116%) and 108% (99%-122%) of the total eEE using the HB and Henry formulas, respectively, with diet-induced thermogenesis and physical activity level. Hypermetabolism (ie, oxygen consumption at rest ≥3.5 ml/kg/min) was observed in 21/49 (42.9%) patients. Energy intakes corresponded to 71% (60%-86%) of the total mEE. CONCLUSION: Performing indirect calorimetry in adults with minor burns revealed that ≥40% of the tested adults presented a hypermetabolism and that their mEE was not covered by their energy intakes.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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%). CONCLUSION: 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.

Indirect Calorimetry-Based Novel Approach for Evaluating Metabolic Flexibility and Its Association with Circulating Metabolic Markers in Middle-Aged Subjects.

We propose a novel method for assessing metabolic flexibility (MF) through indirect calorimetry. A total of twenty healthy volunteers (10 females; 10 males) aged 45-65 were categorized into a Low-Intensity activity group (LI, 0-1 session of 1 h per week) and a High-Intensity activity group (HI, 5-6 sessions of 2 h per week). Volunteers underwent a stepwise exercise test on a cycle ergometer, connected to a calorimeter, to examine respiratory gas exchange to evaluate peak fatty acid Oxidation (PFO) and peak carbohydrate oxidation (PCO). Circulating peroxisome proliferator-activated receptor α (PPARα) biomarkers, docosahexaenoic acid/eicosapentaenoic acid (DHA/EPA) ratio and N-oleoylethanolamine (OEA), and the endocannabinoid- 2-arachidonoylglycerol (2-AG), were evaluated. We developed two MF parameters: the MF index (MFI), calculated by the product of PFO normalized per kg of fat-free mass (FFM) and the percentage of VO2max at PFO, and the peak energy substrates' oxidation (PESO), computed by summing the kilocalories from the PFO and PCO, normalized per kg FFM. The MFI and PESO were significantly different between the HI and LI groups, showing strong correlations with the circulating bioactive substances. Higher DHA/EPA ratio (p ≤ 0.05) and OEA (p ≤ 0.01), but lower 2-AG levels (p ≤ 0.01) were found in the HI group. These new parameters successfully established a functional link between MF and the balance of PPARα/endocannabinoid systems.

An evaluation of intensive care nurses' performance of indirect calorimetry measurements.

BACKGROUND: Indirect calorimetry (IC) is the gold standard to monitor energy expenditure in critically ill patients. In several intensive care units (ICUs), nurses are responsible for carrying out the measurements. AIM: The aim of this study was to assess nurses' perception of their involvement in IC. STUDY DESIGN: This was a prospective survey conducted in the surgical ICU of a French university hospital after 18 months of use of the Q-NRG + ® calorimeter (COSMED©, Italy). All nurses who have used the calorimeter in the previous 6 months in this ICU were questioned through a questionnaire about their theoretical and practical knowledge and experience in using it. RESULTS: The participation rate was 93% (28/30 surveyed). All the respondents understood the objectives of performing an IC and 23 of them (82%) had used the device at least once in the previous 6 months. All the users thought it was pertinent that ICU nurses were in charge of the IC measurements, 16 of them (70%) reported having been formally trained, mostly by a colleague, and 17 (77%) felt comfortable with the device after 2 to 5 uses. The five non-users (8%) did not have the opportunity to do so. Theoretical and practical knowledge could be improved as only 5 of the users (22%) declared to know the main criteria of reliability of the IC measurement and 4 of them (18%) declared to know the maintenance and cleaning protocol of the device. CONCLUSION: Nurses quickly felt comfortable with the Q-NRG + ® in this ICU. Formal initial and ongoing training of all staff completing IC is essential to perform IC measurements safely and to obtain reliable and interpretable results in practice. RELEVANCE TO CLINICAL PRACTICE: Involving the nursing team in nutritional care, even if it is technical, seems to bring satisfaction in terms of overall patient care.

Basal metabolic rate using indirect calorimetry among individuals living with overweight or obesity: The accuracy of predictive equations for basal metabolic rate.

BACKGROUND & AIMS: Weight reduction programs in people with overweight or obesity can be informed by indirect calorimetry (IC) which is the gold standard to measure basal metabolic rate (BMR). Since IC is labor intensive and expensive, predictive equations are often used as an alternative. In this study the accuracy rate was assessed and bias statistics of predictive equations were compared to IC among subjects with overweight or obesity. Secondly, differences in clinical features between individuals with over-, accurate or underestimation of their BMR were evaluated. METHODS: This cross sectional study included 731 subjects from the outpatient obesity clinic of the Antwerp University Hospital, Belgium. Fourteen equations were evaluated. Overestimation and underestimation was defined as >10 % and <10 % of measured BMR. RESULTS: In the total population, mean age was 43 ± 13 years, mean BMI 35.6 ± 5.8 kg/m2 and 79.5 % were female. The highest accuracy rates were reached by the Henry (73 %), Ravussin (73 %) and Mifflin St. Jeor (73 %) equations. In the total population, the Mifflin St. Jeor and Henry equation were unbiased. The Akern, Livingston and Ravussin equations were biased to underestimation. All other equations were biased to overestimation. Subjects with an underestimation of BMR had significantly higher waist-hip ratio (1.02 ± 0.13 vs 0.91 ± 0.11; P < 0.001), higher visceral adipose tissue (239 ± 96 vs 162 ± 93; P < 0.001), lower fat free mass (kg) (67.6 (45.4-95.9) vs 54.0 (39.6-95.5); P < 0.001) and a higher prevalence of the Metabolic Syndrome (24 (77.4) vs 112 (37.5); P < 0.001). Individuals with an overestimation of BMR had significantly higher subcutaneous adipose tissue (545 ± 149 vs 612 ± 149; P < 0.05), lower fasting plasma insulin (81 (10-2019) vs 67 (27-253); P < 0.001) and lower 2-h plasma glucose (132 (30-430) vs 116 (43-193); P < 0.001) during OGTT. CONCLUSIONS: In this study, the Henry and Mifflin St. Jeor equations have the highest accuracy and lowest bias to estimate the basal metabolic rate in a Caucasian, predominantly female, population living with overweight or obesity. Visceral and subcutaneous adipose tissue and presence of metabolic syndrome were significantly different in individuals with over- or underestimation of BMR.

Validation of Indirect Calorimetry in Children Undergoing Single-Limb Non-Invasive Ventilation: A Proof of Concept, Cross-Over Study.

BACKGROUND: The accurate assessment of resting energy expenditure (REE) is essential for personalized nutrition, particularly in critically ill children. Indirect calorimetry (IC) is the gold standard for measuring REE. This methodology is based on the measurement of oxygen consumption (VO2) and carbon dioxide production (VCO2). These parameters are integrated into the Weir equation to calculate REE. Additionally, IC facilitates the determination of the respiratory quotient (RQ), offering valuable insights into a patient's carbohydrate and lipid consumption. IC validation is limited to spontaneously breathing and mechanically ventilated patients, but it is not validated in patients undergoing non-invasive ventilation (NIV). This study investigates the application of IC during NIV-CPAP (continuous positive airway pressure) and NIV-PS (pressure support). METHODS: This study was conducted in the Pediatric Intensive Care Unit of IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, between 2019 and 2021. Children < 6 years weaning from NIV were enrolled. IC was performed during spontaneous breathing (SB), NIV-CPAP, and NIV-PS in each patient. A Bland-Altman analysis was employed to compare REE, VO2, VCO2, and RQ measured by IC. RESULTS: Fourteen patients (median age 7 (4; 18) months, median weight 7.7 (5.5; 9.7) kg) were enrolled. The REE, VO2, VCO2, and RQ did not differ significantly between the groups. The Limits of Agreement (LoA) and bias of REE indicated good agreement between SB and NIV-CPAP (LoA +28.2, -19.4 kcal/kg/day; bias +4.4 kcal/kg/day), and between SB and NIV-PS (LoA -22.2, +23.1 kcal/kg/day; bias 0.4 kcal/kg/day). CONCLUSIONS: These preliminary findings support the accuracy of IC in children undergoing NIV. Further validation in a larger cohort is warranted.