Resting Energy Expenditure Early after Cardiac Surgery and Validity of Predictive Equations: A Prospective Observational Study

Objective: Several predictive equations have been used to estimate patients’ energy expenditure. The study aimed to describe the characteristics of resting energy expenditure (REE) in patients undergoing mechanical ventilation during early postoperative stage after cardiac surgery and evaluate the validity of 9 REE predictive equations. Methods: This was a prospective observational study. Patients aged 18–80 years old, undergone open-heart surgery, were enrolled between January 2017 and 2018. The measured REE (mREE) was evaluated via indirect calorimetry (IC). The predictive resting energy expenditure (pREE) was suggested by 9 predictive equations, including Harris-Benedict (HB), HB coefficient method, Ireton-Jones, Owen, Mifflin, Liu, 25 × body weight (BW), 30 × BW, and 35 × BW. The association between mREE and pREE was assessed by Pearson’s correlation, paired t test, Bland-Altman method, and the limits of agreement (LOA). Results: mREE was related to gender, BMI, age, and body temperature. mREE was significantly correlated with pREE, as calculated by 9 equations (all p < 0.05). There was no significant difference between pREE and mREE, as calculated by 30 × BW kcal/kg/day (t = 0.782, p = 0.435), while significant differences were noted between mREE and pREE calculated by other equations (all p < 0.05). Taking the 30 × BW equation as a suitable candidate, most of the data points were within LOA, and the percentage was 95.6% (129/135). Considering the rationality of clinical use, accurate predictions (%) were calculated, and only 40.74% was acceptable. Conclusions: The 30 × BW equation is relatively acceptable for estimating REE in 9 predictive equations in the early stage after heart surgery. However, the IC method should be the first choice if it is feasible.

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The validity of resting energy expenditure predictive equations in adults with central obesity: A sub-sample of the RaNCD cohort study

Nutrition and Health ◽

10.1177/0260106019856816 ◽

2019 ◽

Vol 25 (3) ◽

pp. 217-224 ◽

Cited By ~ 2

Author(s):

Yahya Pasdar ◽

Shima Moradi ◽

Behrooz Hamzeh ◽

Farid Najafi ◽

Seyed Mostafa Nachvak ◽

...

Keyword(s):

Cohort Study ◽

Energy Expenditure ◽

Central Obesity ◽

Pearson Correlation ◽

Resting Energy Expenditure ◽

World Health ◽

Predictive Equations ◽

Significant Difference ◽

Health Organization ◽

Resting Energy

Background: There are different equations for estimating Resting Energy Expenditure (REE). However, these equations were mainly developed based on populations of western countries. Aim: The present study was conducted to determine the validity of REE predictive equations in adults with central obesity. Methods: This study was conducted with 129 adults with central obesity aged 35–65 years, a sub-sample from a large cohort study (Western Iran), Kurdish population. REE was measured by indirect calorimetry (IC) and REE predictive equations. Data were analysed using Pearson correlation, paired t-test, concordance correlation coefficient (CCC), mean squared deviation (MSD), level of agreement (LOA) and Bland-Altman plot. Results: All REE predictive equations had low CCC and high LOA. Although there was no statistically significant difference in the REE measured with IC and the REE predicted with the Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU), FAO/WHO/UNU (Height), Muller and revised Harris-Benedict equations ( P = 0.874, 0.113, 0.619, 0.143 and P = 0.121), other equations had statistically significant differences with IC ( P<0.001). In addition, the highest correlation was found between the IC (r = 0.682). The least difference was related to the FAO/WHO/UNU equation, with an agreement limit of -507.96 to 500.79 Kcal/day, with a 95% confidence interval. Conclusions: The results of this study showed that the FAO/WHO/UNU, Muller, revised Harris-Benedict equations and Mifflin St Jeor equations are relatively acceptable for estimating REE. However, these prediction equations are not good at predicting REE; more precise equations are needed to apply for different ethnic groups.

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Effects of the ketogenic diet on nutritional status, resting energy expenditure, and substrate oxidation in patients with medically refractory epilepsy: A 6-month prospective observational study

Clinical Nutrition ◽

10.1016/j.clnu.2011.09.012 ◽

2012 ◽

Vol 31 (2) ◽

pp. 246-249 ◽

Cited By ~ 33

Author(s):

Anna Tagliabue ◽

Simona Bertoli ◽

Claudia Trentani ◽

Paola Borrelli ◽

Pierangelo Veggiotti

Keyword(s):

Energy Expenditure ◽

Observational Study ◽

Nutritional Status ◽

Ketogenic Diet ◽

Prospective Observational Study ◽

Refractory Epilepsy ◽

Resting Energy Expenditure ◽

Substrate Oxidation ◽

Medically Refractory Epilepsy ◽

Resting Energy

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Resting Energy Expenditure in CrossFit® Participants: Predictive Equations versus Indirect Calorimetry

International Journal of Kinesiology and Sports Science ◽

10.7575/aiac.ijkss.v.9n.2p.7 ◽

2021 ◽

Vol 9 (2) ◽

pp. 7

Author(s):

Maraline Santos Sena ◽

Marcio Leandro Ribeiro de Souza ◽

Valden Luis Matos Capistrano Junior

Keyword(s):

Energy Expenditure ◽

Indirect Calorimetry ◽

Resting Energy Expenditure ◽

World Health ◽

Predictive Equations ◽

Portable Ultrasound ◽

Significant Difference ◽

Health Organization ◽

Functional Movements ◽

Resting Energy

Background: CrossFit® involves high-intensity functional movements and research has shown that the program increases metabolic rates in participants. Objective: To measure resting energy expenditure (REE) in CrossFit® participants using indirect calorimetry (IC) and to verify the most appropriate predictive equation to estimate REE. Methods: Overall, 142 CrossFit® participants (18–59 years; 91 [64.1%], women) underwent weight, height, waist circumference, and body mass index (BMI) measurements. Body composition was evaluated using a portable ultrasound system (BodyMetrix®). REEs were measured (mREE) by IC and predicted by six different equations (pREE): Harris-Benedict, World Health Organization (WHO), Henry and Rees, Cunningham (1980 and 1991), and Mifflin–St. Jeor. Results: The mean age was 33.0 (6.3) years, with no significant difference between men and women; mean mREE, 1583.2(404.4) kcal/d; and pREE, 1455.5(230.9) to 1711.3(285.5) kcal/d. The best REE predictive equations for this population were Cunningham (1991) (P=0.338), WHO (P=0.494), and Harris-Benedict (P=0.705) equations. The Harris-Benedict equation presented a smaller difference compared with IC [12.9(307.6) kcal], the Cunningham (1991) equation showed improved adequacy (102.5%), and the WHO equation presented highest accuracy (59.9%). The equations that were closest to the mREE were the Harris-Benedict for women and the WHO equation for men. Conclusion: Therefore, for CrossFit® participants, the REE can accurately be predicted with the Cunningham (1991), WHO, and Harris-Benedict equations.

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A Single-Center Prospective Observational Study Comparing Resting Energy Expenditure in Different Phases of Critical Illness

Critical Care Medicine ◽

10.1097/ccm.0000000000004282 ◽

2020 ◽

Vol 48 (5) ◽

pp. e380-e390

Author(s):

Pei Chien Tah ◽

Zheng-Yii Lee ◽

Bee Koon Poh ◽

Hazreen Abdul Majid ◽

Vineya-Rai Hakumat-Rai ◽

...

Keyword(s):

Critical Illness ◽

Energy Expenditure ◽

Observational Study ◽

Prospective Observational Study ◽

Resting Energy Expenditure ◽

Single Center ◽

Resting Energy

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Validation of carbon dioxide production (VCO2) as a tool to calculate resting energy expenditure (REE) in mechanically ventilated critically ill patients: a retrospective observational study

Critical Care ◽

10.1186/s13054-018-2108-8 ◽

2018 ◽

Vol 22 (1) ◽

Cited By ~ 11

Author(s):

I. Kagan ◽

O. Zusman ◽

I. Bendavid ◽

M. Theilla ◽

J. Cohen ◽

...

Keyword(s):

Carbon Dioxide ◽

Energy Expenditure ◽

Observational Study ◽

Critically Ill ◽

Critically Ill Patients ◽

Resting Energy Expenditure ◽

Carbon Dioxide Production ◽

Retrospective Observational Study ◽

Mechanically Ventilated ◽

Resting Energy

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Accuracy of the Common Predictive Equations for Estimating Resting Energy Expenditure among Normal and Overweight Girl University Students

Journal of the American College of Nutrition ◽

10.1080/07315724.2014.938280 ◽

2015 ◽

Vol 35 (2) ◽

pp. 136-142 ◽

Cited By ~ 3

Author(s):

Nazli Namazi ◽

Soghra Aliasgharzadeh ◽

Reza Mahdavi ◽

Fariba Kolahdooz

Keyword(s):

Energy Expenditure ◽

University Students ◽

Resting Energy Expenditure ◽

Predictive Equations ◽

The Common ◽

Resting Energy

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Reliability of resting energy expenditure in major burns: Comparison between measured and predictive equations

Clinical Nutrition ◽

10.1016/j.clnu.2018.12.003 ◽

2019 ◽

Vol 38 (6) ◽

pp. 2763-2769 ◽

Cited By ~ 5

Author(s):

Jinwoo Jeon ◽

Dohern Kym ◽

Yong Suk Cho ◽

Youngmin Kim ◽

Jaechul Yoon ◽

...

Keyword(s):

Energy Expenditure ◽

Resting Energy Expenditure ◽

Predictive Equations ◽

Resting Energy

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Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle

Journal of the International Society of Sports Nutrition ◽

10.1186/s12970-021-00465-x ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Maurizio Marra ◽

Olivia Di Vincenzo ◽

Iolanda Cioffi ◽

Rosa Sammarco ◽

Delia Morlino ◽

...

Keyword(s):

Energy Expenditure ◽

Phase Angle ◽

Elite Athletes ◽

Resting Energy Expenditure ◽

Sport Performance ◽

Accurate Estimation ◽

Anthropometric Parameters ◽

Predictive Equations ◽

Good Prediction Accuracy ◽

Resting Energy

Abstract Background An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. Methods Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. Results One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). Conclusion In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

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