Calculation Of Energy Expenditure Research Articles

Estimating the Energy Expenditure of Grazing Farm Animals Based on Dynamic Body Acceleration

Indirect methods of measuring the energy expenditure of grazing animals using heartbeat variation or accelerometers are very convenient due to their low cost and low intrusiveness, allowing animals to maintain their usual routine. In the case of accelerometers, it is possible to use them to measure activity, as well as to classify animal behavior, allowing their usage in other scenarios. Despite the obvious convenience of use, it is important to evaluate the measurement error and understand the validity of the measurement through a simplistic method. In this paper, data from accelerometers were used to classify behavior and measure animal activity, and an algorithm was developed to calculate the energy expended by sheep. The results of the energy expenditure calculations were subsequently compared with the values reported in the literature, and it was verified that the values obtained were within the reference ranges. Although it cannot be used as a real metering of energy expended, the method is promising, as it can be integrated with other complementary sources of information, such as the evolution of the animal’s weight and ingestion time, thus providing assistance in animals’ dietary management.

Assessment and Prediction of Energy Expenditure: One-Mile Walks and Runs Among African American

Among ethnicities, African Americans exhibit the highest prevalence of obesity. A more comprehensive grasp of energy expenditure while walking and running can be instrumental in managing and averting obesity. Regrettably, there is a scarcity of research dedicated to scrutinizing energy expenditure in African Americans during walking and running. Consequently, the primary objective of this study was to contrast energy expenditure disparities during a one-mile walk and run between African Americans of normal-weight and those classified as overweight. Additionally, the secondary aim was to formulate and validate a predictive equation for energy expenditure tailored specifically to African Americans. A total of 68 African American participants were involved in this study, comprising 21 individuals classified as normal-weight walkers, 27 as overweight walkers, and 20 as runners. Energy expenditure was assessed using indirect calorimetry. To compare energy expenditure across these groups, an Analysis of Variance (ANOVA) was conducted, followed by a post hoc Scheffe test. Linear regression analysis was employed for predicting energy expenditure. Additionally, a dependent t-test and a Chow test were utilized for cross-validating the predictive equation. The findings revealed that runners exhibited significantly higher energy expenditure compared to normal-weight walkers. When energy expenditure was normalized to body weight, runners expended significantly more energy than both normal-weight and overweight walkers. However, when expressed relative to fat-free mass, normal-weight walkers expended less energy than runners and overweight walkers. A prediction equation tailored specifically for African Americans was formulated as follows: EE = 1.012 BW − 9.233 Gender (M = 1, F = 2) + 47.188. The results from cross-validation tests confirmed the validity of this equation. Consequently, we recommend the use of this energy expenditure prediction equation for calculating energy expenditure during one-mile walks or runs for African American adults, whether they fall within the normal-weight or overweight categories.

Comparative Analysis Of Energy Expenditure Assessments From The Graded Exercise Test Vs. Galaxy Watch And Apple Watch In Korean College Students During A 30-minute Workout: A Pilot Study

OBJECTIVES In the modern era, there is heightened interest in understanding energy expenditure during exercise. Consequently, wearable devices such as the Galaxy Watch and Apple Watch have emerged as pivotal tools for daily health monitoring, given their convenience and increasing popularity. This study aimed to compare the calculated energy expenditure derived from the graded exercise test with readings from Galaxy and Apple Watches during a 30-min exercise session among Korean university students. Through this, we anticipate offering both motivation and clear insights into energy expenditure, thereby potentially aiding in weight management strategies for contemporary individuals.METHODS This study involved 27 college students from Korea National University of Transportation in Chungcheongbuk-do, Korea. We utilized COSMED's exercise load respiratory gas analysis system (Quark- CPET, COSMED, Rome, Italy), along with the Galaxy Watch (Galaxy Watch 5, Samsung, Seoul, Korea) and the Apple Watch (Apple watch series 5, Apple, Cupertino, USA) for measurements. Energy expenditure was monitored in real-time every 5 min throughout the 30-min exercise session. For statistical evaluations, we employed a one-way analysis of variance. Subsequent post-tests utilized the Tukey post-hoc test and Pearson correlation, with a significance level set at p<0.05.RESULTS Initially, no statistically significant difference emerged between energy expenditure readings from the graded exercise test and those from the Galaxy Watch across all time intervals: 5, 10, 15, 20, 25, and 30 min (p>0.05). Conversely, a notable difference was observed when comparing energy expenditure data from the graded exercise test to that of the Apple Watch for time intervals of 10, 15, 20, 25, and 30 min (p>0.05), although the 5-min interval did not exhibit a significant difference (p>0.05). Furthermore, a robust positive correlation was evident between the energy expenditure values derived from the graded exercise test and those from both the Galaxy Watch (r=0.952, p<0.001) and the Apple Watch (r=0.917, p<0.001).CONCLUSIONS Both devices demonstrated high reliability in calculating energy expenditure. Notably, the Galaxy Watch exhibited a more precise calculation compared to the Apple Watch, with a relative reliability margin of 3.5% higher. For individuals, especially those struggling with obesity, precise wearable devices that accurately reflect energy consumption can significantly boost motivation for exercise. Consequently, this study lays a foundation for future advancements in energy expenditure measurement tools, emphasizing enhanced convenience, reliability, and mobility.

Wintering Conditions and Heat Loss during Hibernation in the Brown Long-Eared Bat

The aim of this study was to estimate heat loss in the brown long-eared bat during hibernation depending on the refugioclimate conditions. The measured values of refugioclimate parameters were: ambient temperature (Ta) 3–10 °C, relative humidity (Rh) 74–98% and air velocity (v) 0.06–0.95 m/s. Heat loss was calculated using convective heat transfer equations. Mean heat loss amounted to 4 W/m2. The results were compared to the heat loss calculated based on the fat burned during hibernation. Bats flying into underground systems during the hibernation period were captured and their body mass was measured. A loss of body mass of 2.6 g over the 126 days of hibernation was observed. Heat loss equalled 3.115 W/m2K.The presented method of calculating energy expenditure allows for non-invasive monitoring of the heat and fat losses of bats during hibernation. Such research may find application in designing artificial wintering sites.

The necessity of nutritional support for patients at the second stage of neurorehabilitation: problems and solutions

The aim of this research was to demonstrate the relevance of personalised nutritional support for patients at the 2nd stage of neurorehabilitation. The study involved work with patients in the neurorehabilitation. The nutritional status of the patient was assessed according to the data of protein fractions. Individual calculation of calorie intake was performed via the Harris–Benedict formula. The observation has established the necessity of application of the “Nutritional status assessment scale” for all patients entering the neurorehabilitation course. An algorithm for patient examination in nutritional deficiency has been tested: evaluation of protein fractions, calculation of calories intake with determination of the amount of proteins, fats and carbohydrates.Conclusion. It is quite difficult to calculate energy expenditure in the process of neurorehabilitation for every manipulation. However, through application of the common standard of nutritional status assessment for patients on admission, it is possible to distinguish the patients requiring nutritional support. This will make it possible to avoid development of protein deficiency and “exhaustion” of patients in the process of the sessions.

The cost of movement: assessing energy expenditure in a long-distant ectothermic migrant under climate change.

Migration is an energetically taxing phenomenon as animals move across vast, heterogenous landscapes where the cost of transport is impacted by permissible ambient conditions. In this study, we assessed the energetic demands of long-distance migration in a multigenerational ectothermic migrant, the monarch butterfly (Danaus plexippus). We tested the hypotheses that temperature-dependent physiological processes reduce energy reserves faster during migration than previously estimated, and that increasing climatic temperatures resulting from the climate crisis will intensify baseline daily energy expenditure. First, we reared monarchs under laboratory conditions to assess energy and mass conversion from fifth instar to adult stages, as a baseline for migratory adult mass and ontogenetic shifts in metabolic rate from larvae to adult. Then, using historical tag-recapture data, we estimated the movement propensity and migratory pace of fall migrants using computer simulations and subsequently calculated energy expenditure. Finally, we estimated the energy use of monarchs based on these tag-recapture data and used this information to estimate daily energy expenditure over a 57-year period. We found support for our two hypotheses, noting that incorporating standard metabolic rate into estimates of migratory energy expenditure shows higher energy demand and that daily energy expenditure has been gradually increasing over time since 1961. Our study shows the deleterious energetic consequences under current climate change trajectories and highlights the importance of incorporating energetic estimates for understanding migration by small, ectothermic migrants.

Efeito de um programa de exercício utilizando Rédea Pessoa sobre preditores de condicionamento físico em cavalos adultos

ABSTRACT The aim of this study was to evaluate the effect the Pessoa training aid (PTA) exercise program exerts in some physical conditioning predictors. Eight detrained adult horses were evaluated in 12 sessions of work with PTA (3 sessions per week). All horses used a heart rate monitor and GPS (V800, Polar Electro) and data was used to calculate energy expenditure (EE), net cost of transport (COT), metabolic energy requirement (Pmet), oxygen pulse, oxygen utilization, heart rate and heart rate variability (HRV). The horses were weighted, and the thoracolumbar shape were measured at the level of the 18th (T18), 13th (T13) and 8th (T8) thoracic vertebrae with a flexible ruler before and after the experimental period. Data obtained weekly were submitted to ANOVA and Tukey test (p≤0.05). Data obtained just before and after the experimental period were submitted to paired t test. There was a decrease in left-right asymmetry. In the third week there was an increase in HR, EE, oxygen pulse and oxygen utilization followed by a decrease in the fourth week. The biomechanics related parameters, COT and Pmet decreased week by week. The HRV showed a sympathetic stimulus in the third week followed by a shift to parasympathetic in the fourth week. We conclude that 12 sessions of lunge exercise with PTA contributed to physical condition improvement.

Dosage of Physical Activity to Avoid Impairment of Activities Due to Pain: Analysis of Population-based Conditional Processes

BackgroundPhysical activity's established health benefits include pain control, yet there is no consensus on the required dosage according to the literature. AimTo test the influence of exercise on perceived health in patients whose daily activities are limited due to pain. Besides, analyze the possible moderating effect of age and find a formula for exercise dosage based on the perceived level of health. MethodsCross-sectional study based on the 2017 Spanish National Health Survey with 4,123 participants reporting activity limitations in their daily activities due to pain. The International Physical Activity Questionnaire (short version) was used to calculate energy expenditure. Data included age, sex, leisure-time physical activity, sitting time, pain-related impairments, pain medication, and perceived health. Mediation regression analysis was conducted using the SPSS PROCESS 4.0 macro. ResultsResults indicate a decline in perceived health with age. The relationship between exercise (energy expenditure) and perceived health was highly significant (d=-0.224, p<0.001). Age moderated the association between pain and energy expenditure up to 75.61 years (0.1568, p=0.05) and between energy expenditure and perceived health up to 75.74 years (-0.289, p=0.05), but this effect diminished afterwards. A formula was developed to estimate energy expenditure based on the desired level of health. ConclusionsThe perception of health in people who are limited in their daily activities due to pain (moderate to very much) is mediated by the amount of physical activity they perform. Besides, this perception is moderated by age, up to 76 years.

Association of Playground "Playability" With Physical Activity and Energy Expenditure.

Children's physical activity, especially play, is important for healthy physical, social, and psychological development. Playgrounds are public spaces for children, but not all playgrounds are conducive to play and physical activity. We examined "playability," the ability of a space to promote active play, and associations with moderate-to-vigorous physical activity (MVPA) and energy expenditure. This cross-sectional study assessed playground features with the Play Space Audit Tool; we calculated playability scores from audit data, overall and by domain (general amenities, surface, path, and play structure), from playgrounds in 70 parks in Chicago, Illinois, in 2017. We observed 2,712 individuals during the audits and used the System for Observing Play and Recreation in Communities tool to assess MVPA and energy expenditure. We used generalized estimating equation negative binomial regression to calculate incidence rate ratios for MVPA and mixed effects models to calculate energy expenditure (in kcal/kg/min) associated with playability scores. General amenities and play structure scores were associated with 1.28 (95% CI, 1.08-1.52) and 1.15 (95% CI, 1.00-1.31) times as many individuals (any age) engaged in MVPA, respectively. The general amenities score was significantly associated with 0.51 (95% CI, 0.24-0.79) and 0.42 (95% CI, 0.15-0.68) higher energy expenditure in renovated playgrounds and in all playgrounds, respectively. Overall, general amenities and play structure scores were associated with MVPA and were robust to adjustment for weather, neighborhood socioeconomic characteristics, and crime. These playground playability indices may strengthen future evaluations of community infrastructure for children's physical activity.

Long-duration wind tunnel flights reveal exponential declines in protein catabolism over time in short- and long-distance migratory warblers

During migration, long-distance migratory songbirds may fly nonstop for days, whereas shorter-distance migrants complete flights of 6 to 10 h. Fat is the primary fuel source, but protein is also assumed to provide a low, consistent amount of energy for flight. However, little is known about how the use of these fuel sources differs among bird species and in response to flight duration. Current models predict that birds can fly until fat stores are exhausted, with little consideration of protein's limits on flight range or duration. We captured two related migratory species-ultra long-distance blackpoll warblers (Setophaga striata) and short-distance yellow-rumped warblers (Setophaga coronata)-during fall migration and flew them in a wind tunnel to examine differences in energy expenditure, overall fuel use, and fuel mixture. We measured fat and fat-free body mass before and after flight using quantitative magnetic resonance and calculated energy expenditure from body composition changes and doubly labeled water. Three blackpolls flew voluntarily for up to 28 h-the longest wind tunnel flight to date-and ended flights with substantial fat reserves but concave flight muscle, indicating that protein loss, rather than fat, may actually limit flight duration. Interestingly, while blackpolls had significantly lower mass-specific metabolic power in flight than that of yellow-rumped warblers and fuel use was remarkably similar in both species, with consistent fat use but exceptionally high rates of protein loss at the start of flight that declined exponentially over time. This suggests that protein may be a critical, dynamic, and often overlooked fuel for long-distance migratory birds.

Energetic synchrony throughout the non‐breeding season in common guillemots from four colonies

The non‐breeding season presents significant energetic challenges to birds that breed in temperate or polar regions, with clear implications for population dynamics. In seabirds, the environmental conditions at non‐breeding sites drive food availability and the energetic cost of regulatory processes, resulting in variation in diet, behaviour and energetics; however, very few studies have attempted to understand if and how these aspects vary between populations. We investigated whether non‐breeding location influenced diet, behaviour and energetics in the common guillemotUria aalge. We studied guillemots from four UK breeding colonies, two located on the west coast of Scotland and two on the east. We quantified non‐breeding distribution, foraging behaviour and activity budgets of 39 individuals from July to March, using geolocation–immersion loggers and time‐depth recorders, and used feather stable isotope signatures to infer diet during the post‐breeding moult. We calculated energy expenditure and investigated whether the peak (an indicator of the potential vulnerability to marine threats) varied between colonies. Individuals were spatially segregated according to the coastline they breed on, with west coast guillemots distributed off the west coast of the UK and east coast guillemots distributed off the east coast. Diet and behaviour were more similar in guillemots that shared a breeding coastline than those that did not, as west coast guillemots foraged at a lower trophic level, spent less time diving and engaged in more pelagic foraging than east coast guillemots. However, energy expenditure was remarkably similar between colonies, peaking during late February/early March, indicating that, during our study period, there was high synchrony between colonies in the timing of potential vulnerability to marine threats. Therefore, any anthropogenic changes that result in decreased food availability or increased energy expenditure during late winter may have greater impacts on energy balance, with consequences for population dynamics.

Physiological Workload Analysis on the Use of Face Masks during Physical Activities

During the COVID-19 pandemic people are required to limit outside activities and keep following social distancing protocol. However, several studies have reported that indoor exercises have a greater risk toward COVID-19 virus infection. Therefore, wearing a mask during light to moderate intensity of outdoor physical activity is still recommended. We conduct an experiment to analyze physiological ergonomics aspect, whether people wearing different type of masks during physical activities and distraction of music would affect heart rate. Analysis of the average heart rate data was carried out using the calculation of VO2max and Energy Expenditure to determine the workload level of the four scenarios of treatment combination. The result shows a heavy level of physical load on the use of surgical mask with distraction of music and moderate level of physical load on the use of surgical without distraction of music.

The role of individual variability on the predictive performance of machine learning applied to large bio-logging datasets

Animal-borne tagging (bio-logging) generates large and complex datasets. In particular, accelerometer tags, which provide information on behaviour and energy expenditure of wild animals, produce high-resolution multi-dimensional data, and can be challenging to analyse. We tested the performance of commonly used artificial intelligence tools on datasets of increasing volume and dimensionality. By collecting bio-logging data across several sampling seasons, datasets are inherently characterized by inter-individual variability. Such information should be considered when predicting behaviour. We integrated both unsupervised and supervised machine learning approaches to predict behaviours in two penguin species. The classified behaviours obtained from the unsupervised approach Expectation Maximisation were used to train the supervised approach Random Forest. We assessed agreement between the approaches, the performance of Random Forest on unknown data and the implications for the calculation of energy expenditure. Consideration of behavioural variability resulted in high agreement (> 80%) in behavioural classifications and minimal differences in energy expenditure estimates. However, some outliers with < 70% of agreement, highlighted how behaviours characterized by signal similarity are confused. We advise the broad bio-logging community, approaching these large datasets, to be cautious when upscaling predictions, as this might lead to less accurate estimates of behaviour and energy expenditure.

Impact of Ageing on Female Metabolic Flexibility: A Cross-Sectional Pilot Study in over-60 Active Women

BackgroundAgeing affects metabolic flexibility, although physical status could influence this relationship. This cross-sectional study aims to describe and analyse the metabolic flexibility/inflexibility in a group of active older women, together with the impact of ageing and physical status on their oxidation rates and maximal fat oxidation (MFO).MethodsFifteen volunteers (69.00 ± 6.97 years)—from 24 women—completed an incremental cycling test until the second ventilatory threshold. Intensity increased 10 W each 3 min 15 s, starting at 30 W. Gas exchange, heart rate, rate of perceived effort, pain scale and muscle power were registered, together with lactate. VO2 and VCO2 were considered for fat and carbohydrate oxidation (FATox and CHOox; Frayn’s equation) at intensities 60%, 80% and 100% from the peak power in the test (P100). Psychophysiological parameters were compared at MFO/FATmax and P100, together with the energy expenditure calculations around MFO (included FAT and CHO contributions), and the main correlation analyses, with and without P100 and VO2 as covariates.ResultsFATox was low at MFO (0.13; 95% CI [0.09–0.17] mg/min/kgFFM; 3.50; 95% CI [2.49–4.50] mg/min/kgFFM), with short oxidation-rate curves shifting down and leftward. CHOox and FATox were both low for reduced power with age (77.14 ± 18.58 W and 39.29 ± 9.17 W at P100 and MFO, respectively), all accompanied by a fall in energy expenditure (5.44 ± 2.58 kcal/min and 3.32 ± 1.55 kcal/min at P100 and MFO, respectively). Power appears as a determinant factor, given its strong and negative significant association with age (r = − 0.85, p < 0.005; R2 = 0.72) and moderate with MFO (r = − 0.54, p = 0.04; R2 = 0.29). In turn, energy expenditure shows a positive and moderate association with muscle power (r = 52, p = 0.04).ConclusionsDespite the drop in substrates oxidation with age, physical status (i.e. larger muscular power and energy expenditure) suggests a key role in the preservation of metabolic health with ageing in active women.

Energetic costs of hindlimb‐dominated locomotion in sifakas (Propithecus verreauxi)

Human bipedal locomotion is unique, requiring a suite of musculoskeletal adaptations that were acquired gradually throughout hominin evolution. For example, lordotic lumbar spines move the center of mass over the hip joint and resists axial compression, short, laterally‐oriented iliac blades increase the leverage of the hip extensors and abductors, and the adducted hallux facilitates weight transfer during a propulsive toe‐off. Sifakas and other primates occasionally move bipedally in the wild, especially in terrestrial settings, but because they lack specialized anatomy, bipedal locomotion should be less efficient. In this study we test the hypothesis that energy costs differ among sifaka locomotor modes and predict that terrestrial bipedal locomotion is associated with greater energy expenditure than their more habitual mode of arboreal locomotion, vertical clinging and leaping. Bipedal (n=77) and vertical clinging and leaping (n=74) gait cycles were filmed in nine sifakas at the Duke Lemur Center. Locomotor data (stride length, peak body height of the cycle, and velocity) were measured from these videos using ImageJ and used to calculate energy expenditure using published equations. Linear mixed models were used to statistically test the differences in energy expenditure between locomotor modes while accounting for the effects of velocity and repeatedly measuring the same individuals. Results demonstrate that the cost of bipedalism is significantly greater than that of vertical clinging and leaping (p&lt;0.0001). This result supports the idea that the locomotor adaptations in the hominin musculoskeletal system reduce the cost of locomoting bipedally. Furthermore, because sifakas rely on bipedal locomotion in terrestrial settings, these results have conservation implications for understanding the energetic demands of sifaka locomotion in deforested habitats.

The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors

Through this study, we developed and validated a system for energy expenditure calculation, which only requires low-cost inertial sensors and open source R software. Five healthy subjects ran at ten different speeds while their kinematic variables were recorded on the thigh and wrist. Two ActiGraph wireless inertial sensors and a low-cost Bluetooth-based inertial sensor (Lis2DH12), assembled by SensorID, were used. Ten energy expenditure equations were automatically calculated in a developed open source R software (our own creation). A correlation analysis was used to compare the results of the energy expenditure equations. A high interclass correlation coefficient of estimated energy expenditure on the thigh and wrist was observed with an Actigraph and Sensor ID accelerometer; the corrected Freedson equation showed the highest values, and the Santos-Lozano vector magnitude equation and Sasaki equation demonstrated the lowest one. Energy expenditure was compared between the wrist and thigh and showed low correlation values. Despite the positive results obtained, it was necessary to design specific equations for the estimation of energy expenditure measured with inertial sensors on the thigh. The use of the same formula equation in two different placements did not report a positive interclass correlation coefficient.

Comparative Analysis of the Indirect Calorimetry and the Metabolic Power Method to Calculate Energy Expenditure in Team Handball

Monitoring physical activity, e.g., training load and energy expenditure (EE), is important to optimize the training process in various sports. Especially in team handball, where there is little information about EE in training and competition. The objective of the study was to compare EE in team handball derived from a respiratory gas exchange analysis (spiroergometry) and a local position measurement (LPM) system. Eleven participants completed a validated, team handball game-based performance test and wore a portable spiroergometry system (K5 Cosmed) and an LPM transponder (Catapult ClearSky T6). EE was determined via indirect calorimetry for spiroergometry data and via the metabolic power model for EE for LPM data. EE estimated via the metabolic power model was −66 to −63 ± 12% lower than via indirect calorimetry (p &lt; 0.001, pη2 = 0.97). No correlation was found for the overall test (r = 0.32, p = 0.34), nor for every single heat (r ≤ 0.44, 0.18 ≤ p ≤ 0.99). Therefore, regression analyses predicting spiroergometry data based on LPM data were not feasible. In line with previous studies, the metabolic power model for EE in team handball (including short-distance movements, great accelerations, and non-locomotive actions) is not suitable.

Determination of energy expenditure in ventilated critically ill patients indirect calorimetry vs predictive formulas

Rationale: Critical illness is associated with hypercatabolism and hypermetabolism and critically ill patients hospitalized for more than 48 hours are considered at risk of malnutrition and adequate nutritional support should be provided. In hospital settings predictive formulas (PF) are used to calculate energy expenditure (EE), but in critically ill patients (CI), PF evidenced inaccurate determinations. Indirect Calorimetry (IC) is the gold standard method for determining the EE and guide the nutritional therapy of CI patients. Our objective was to compare the EE determined by IC and FP in ventilated CI patients.

Using Kinect body joint detection system to predict energy expenditures during physical activities

The purpose of this study was to explore the potential of Kinect body joint detection to facilitate the calculation of energy expenditure during exergame exercises. Two Kinect-based biomechanical models - mechanical energy (KineticE) and work (WorkE) were employed to estimate the energy expenditure during four Wii™ exergame session. Consequently, two stepwise regression models were developed from nineteen participants’ data and then validated by five holdout participants. The data collected using an accelerometer (r = 0.835, p < 0.001) had the highest correlation as compared to that of the WorkE (r = 0.805, p < 0.001) and KineticE (r = 0.466, p < 0.001) correlations with the reference indirect calorimetry using Quark activity energy expenditure (QuarkAEE). The regression results show that KineticE and the weight of the participant were significant factors for mechanical energy prediction (AEEKinetic). However, according to the work prediction equation (AEEWork), only WorkE was significant. The new energy prediction models showed significant agreement with the standard QuarkAEE (AEEKinect, r = 0.641, p = 0.02; AEEWork, r = 0.793, p < 0.001), and they were comparable to accelerometer predictions (r = 0.682, p = 0.001). The findings indicate that Kinect can be a potentially viable alternative to measure energy expenditures. The models can be applied with higher accuracy, especially when the activity demands high body movements.

Energy requirements of long-term ventilated COVID-19 patients with resolved SARS-CoV-2 infection.

Background & aimsCoronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can rapidly progress into acute respiratory distress syndrome accompanied by multi-organ failure requiring invasive mechanical ventilation and critical care treatment. Nutritional therapy is a fundamental pillar in the management of hospitalized patients. It is broadly acknowledged that overfeeding and underfeeding of intensive care unit (ICU) patients are associated with increased morbidity and mortality. This study aimed to assess the energy demands of long-term ventilated COVID-19 patients using indirect calorimetry and to evaluate the applicability of established predictive equations to estimate their energy expenditure.MethodsWe performed a retrospective, single-center study in 26 mechanically ventilated COVID-19 patients with resolved SARS-CoV-2 infection in three independent intensive care units. Resting energy expenditure (REE) was evaluated by repetitive indirect calorimetry (IC) measurements. Simultaneously the performance of 12 predictive equations was examined. Patient's clinical data were retrieved from electronic medical charts. Bland-Altman plots were used to assess agreement between measured and calculated REE.ResultsMean mREE was 1687 kcal/day and 20.0 kcal relative to actual body weight (ABW) per day (kcal/kg/day). Longitudinal mean mREE did not change significantly over time, although mREE values had a high dispersion (SD of mREE ±487). Obese individuals were found to have significantly increased mREE, but lower energy expenditure relative to their body mass. Calculated REE showed poor agreement with mREE ranging from 33 to 54%.ConclusionResolution of SARS-CoV-2 infection confirmed by negative PCR leads to stabilization of energy demands at an average 20 kcal/kg in ventilated critically ill patients. Due to high variations in mREE and low agreement with calculated energy expenditure IC remains the gold standard for the guidance of nutritional therapy.