scholarly journals A Comparison between Continuous Indirect Calorimetry and Single Weight-Based Formula in Estimating Resting Energy Expenditure in Nutritional Therapy: A Prospective Randomized Controlled Study in Critically Ill Patients

2021 ◽  
Vol 16 (2) ◽  
pp. 207-215
Author(s):  
Cheah Saw Kian ◽  
Keyword(s):  
Energy Expenditure ◽  
Critically Ill ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Nutritional Therapy ◽  
Controlled Study ◽  
Rank Test ◽  
Icu Mortality ◽  
Cumulative Energy ◽  
Resting Energy

Optimal nutritional therapy is important to improve outcome in critically ill population in an intensive care unit (ICU). Although indirect calorimetry (IC) is currently a gold standard for resting energy expenditure (REE) measurement, yet it is still not routinely used in the ICU. A total of 146 mechanically ventilated patients were randomised to receive enteral nutrition (EN) with energy targeted based on continuous indirect calorimetry (IC) measurements (IC group, n=73) or according to 25 kcal/kg/day (SWB group, n=73). Patient characteristics were equally distributed and the IC group showed lower mean measured REE (1668.1 + 231.7 vs 1512.0 + 177.1 kcal, p<0.001). Results also showed a significant deficiency in the daily (-148.8 + 105.1 vs. -4.99 + 44.0 kcal, p<0.001) and total cumulative energy balances (-1165.3 + 958.1 vs. 46.5 + 369.5 kcal, p<0.001) in the SWB group as compared to the IC group. From the Kaplan-Meier survival analysis, we found that ICU mortality was significantly lower in the IC group with better survival probability compared to the SWB group (log-rank test, p = 0.03). However, both groups showed comparable results in terms of ICU length of stay, duration of mechanical ventilation and incidence of feeding intolerance. In conclusion, this study showed that tightly supervised nutritional therapy based on continuous IC measurement provides significantly less mean daily and cumulative energy deficits as well as significantly reduced ICU mortality rate.

scholarly journals Associations of measured resting energy expenditure with predictive equations, NUTRIC score, and patient outcomes

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Elham Sobhy ◽  
Radwa Abdel Kader ◽  
Alshaimaa Aboulfotouh ◽  
Mohammed Eshra ◽  
Mohamed Sayed
Keyword(s):  
Energy Expenditure ◽  
Critically Ill ◽  
Patient Outcomes ◽  
Indirect Calorimetry ◽  
Reference Method ◽  
Resting Energy Expenditure ◽  
Nutrition Therapy ◽  
Nutrition Risk ◽  
Penn State ◽  
Resting Energy

Abstract Background Indirect calorimetry is the reference method for measuring resting energy expenditure (REE), but the necessary equipment and technical expertise are not always available. Meanwhile, the NUTrition Risk in the Critically ill (NUTRIC) scale is designed to identify patients who would benefit from nutrition therapy, but no data are available regarding the association of NUTRIC scores with REE. Several predictive formulas are available as alternatives to indirect calorimetry for calculation of energy requirements, but they have not been compared in a homogeneous group of critically ill patients. The purpose of the study is to examine the correlations between energy expenditure and NUTRIC scores or patient outcomes, and to compare measured REE with estimations of energy expenditure. Methods In this observational, prospective study, indirect calorimetry was performed on 50 mechanically ventilated patients. Energy expenditure was also estimated with the bodyweight-based, Faisy–Fagon, and Penn-State PSUm equations. Results REE was higher in patients who survived treatment than in those who died, and was positively correlated with length of stay and duration of ventilation. NUTRIC scores did not correlate with REE. The Faisy–Fagon equation overestimated expenditure, whereas PSUm was unbiased and accurate. Calculations based on 25 kcal/kg bodyweight/day overestimated expenditure, whereas 23 kcal/kg/day produced unbiased estimates with greater accuracy than PSUm. Conclusion REE was positively associated with patient outcomes. Energy expenditure was accurately predicted by calculations of 23 kcal/kg bodyweight/day.

Can Vco2-Based Estimates of Resting Energy Expenditure Replace the Need for Indirect Calorimetry in Critically Ill Children?

2016 ◽  
Vol 41 (4) ◽  
pp. 619-624 ◽  
Author(s):  
Marialena Mouzaki ◽  
Steven M. Schwartz ◽  
Haifa Mtaweh ◽  
Gustavo La Rotta ◽  
Kandice Mah ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Critically Ill ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Critically Ill Children ◽  
Resting Energy

ACCURACY OF PREDICTED RESTING ENERGY EXPENDITURE ON PATIENTS WITH INVASIVE MECHANICAL VENTILATION

2017 ◽  
pp. 68-73
Author(s):  
Ngoc Son Do ◽  
Son Tung Vu ◽  
Van Chi Nguyen
Keyword(s):  
Mechanical Ventilation ◽  
Energy Expenditure ◽  
Critically Ill ◽  
Indirect Calorimetry ◽  
Critically Ill Patients ◽  
Invasive Mechanical Ventilation ◽  
Resting Energy Expenditure ◽  
Prediction Equations ◽  
Penn State ◽  
Resting Energy

Objectives: to compare the accuracy among the resting energy expenditure (REE) calculated by using prediction equations by Harris – Benedict (H-B), Harris – Benedict with stress factor 1.2 (H-Bx1.2), Penn State 2003 (PS2003), 25kcal/kg and 30 kcal/kg versus REE measured by indirect calorimetry (IC). Patients: 40 mechanically ventilated patients from the Emergency Department at Bach Mai Hospital between April 2016 and October 2016. Methods: a prospective observatory study. REE of all patients were measured by IC and compared with REE calculated by prediction equations. Pearson ratio was used to assess correlation between measured and calculated REE. Results: the accuracy of the estimated equation was 37.5% (H-B); 35% (H-Bx1.2); 47.5% (PS2003); 25% (25kcal/kg); 32.5% (30 kcal/kg). Penn State 2003 was estimated accurately in 60% among female patients and 64.7% among patients with BMI<18.5. There was a proportional correlation between H-B and H-Bx1.2 (r=0.56; p<0.001) and PS2003 (r=0.48; p<0.001) and 25kcal/kg and 30 kcal/kg (r=0.48; p<0.001). Conclusions: Among prediction equations vs IC, PS2003 had the highest accuracy and correlation, therefore, it should be the tool of choice on the critically ill patients who were female and/or whose BMI <18.5 where IC was not available. Key words: Energy expenditure, indirect calorimetry, critically ill patients, prediction equations, invasive mechanical ventilation.

Energy Needs Are Poorly Predicted in Critically Ill Elderly

1997 ◽  
Vol 12 (1) ◽  
pp. 45-49 ◽  
Author(s):  
R. Sheridan ◽  
K. Prelack ◽  
L. Yin ◽  
Vincent Riggi
Keyword(s):  
Energy Expenditure ◽  
Elderly Patients ◽  
Critically Ill ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Apache Ii Score ◽  
Mechanically Ventilated ◽  
Energy Needs ◽  
Expired Gas ◽  
Resting Energy

Changes in energy expenditure with age have been described, but this physiology is not routinely considered when managing critically ill elderly patients. To allow us to avoid the potential problems associated with underfeeding or overfeeding the critically ill elderly population, with approval of the human studies committee and appropriate consent from legal guardians, 25 critically ill patients over 65 years of age requiring mechanical ventilation underwent expired gas indirect calorimetry. If they had a pulmonary artery catheter in place for clinical reasons, reverse-Fick indirect calorimetry was also performed. Data obtained by indirect calorimetry was compared with commonly applied equations for predicting energy expenditure by statistical methods of correlation and limits of agreement. These 25 patients had an average age of 74 ± 1.23 (standard error of the mean) and an average APACHE II score of 15. Predictive equations correlated poorly with measured resting energy expenditure, and although they showed reasonable bias, they were imprecise in their estimation of resting energy expenditure. These data suggest that energy expenditure in critically ill, mechanically ventilated elderly patients is highly variable. Although generally overestimating energy needs, currently available equations for predicting energy expenditure in this population are associated with significant bias and imprecision, which may lead to both overfeeding and underfeeding. Although these equations may be suitable as a basis of initiating nutritional support, energy provisions should ideally be guided by indirect calorimetry.

scholarly journals The Diagnostic-Measurement Method—Resting Energy Expenditure Assessment of Polish Children Practicing Football

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 340
Author(s):  
Edyta Łuszczki ◽  
Anna Bartosiewicz ◽  
Katarzyna Dereń ◽  
Maciej Kuchciak ◽  
Łukasz Oleksy ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Composition ◽  
Energy Expenditure ◽  
Muscle Mass ◽  
Indirect Calorimetry ◽  
Energy Demand ◽  
Body Height ◽  
Resting Energy Expenditure ◽  
Blood Pressure Monitor ◽  
Resting Energy

Establishing the amount of energy needed to cover the energy demand of children doing sport training and thus ensuring they achieve an even energy balance requires the resting energy expenditure (REE) to be estimated. One of the methods that measures REE is the indirect calorimetry method, which may be influenced by many factors, including body composition, gender, age, height or blood pressure. The aim of the study was to assess the correlation between the resting energy expenditure of children regularly playing football and selected factors that influence the REE in this group. The study was conducted among 219 children aged 9 to 17 using a calorimeter, a device used to assess body composition by the electrical bioimpedance method by means of segment analyzer and a blood pressure monitor. The results of REE obtained by indirect calorimetry were compared with the results calculated using the ready-to-use formula, the Harris Benedict formula. The results showed a significant correlation of girls’ resting energy expenditure with muscle mass and body height, while boys’ resting energy expenditure was correlated with muscle mass and body water content. The value of the REE was significantly higher (p ≤ 0.001) than the value of the basal metabolic rate calculated by means of Harris Benedict formula. The obtained results can be a worthwhile suggestion for specialists dealing with energy demand planning in children, especially among those who are physically active to achieve optimal sporting successes ensuring proper functioning of their body.

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