scholarly journals Resting Energy Expenditure Prediction Equations in the Pediatric Population: A Systematic Review

2021 ◽  
Vol 9 ◽  
Author(s):  
Jimena Fuentes-Servín ◽  
Azalia Avila-Nava ◽  
Luis E. González-Salazar ◽  
Oscar A. Pérez-González ◽  
María Del Carmen Servín-Rodas ◽  
...  
Keyword(s):  
Systematic Review ◽  
Energy Expenditure ◽  
Pediatric Patients ◽  
Assessment Tool ◽  
Pediatric Population ◽  
Resting Energy Expenditure ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Pediatric Populations ◽  
Resting Energy

Background and Aims: The determination of energy requirements is necessary to promote adequate growth and nutritional status in pediatric populations. Currently, several predictive equations have been designed and modified to estimate energy expenditure at rest. Our objectives were (1) to identify the equations designed for energy expenditure prediction and (2) to identify the anthropometric and demographic variables used in the design of the equations for pediatric patients who are healthy and have illness.Methods: A systematic search in the Medline/PubMed, EMBASE and LILACS databases for observational studies published up to January 2021 that reported the design of predictive equations to estimate basal or resting energy expenditure in pediatric populations was carried out. Studies were excluded if the study population included athletes, adult patients, or any patients taking medications that altered energy expenditure. Risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.Results: Of the 769 studies identified in the search, 39 met the inclusion criteria and were analyzed. Predictive equations were established for three pediatric populations: those who were healthy (n = 8), those who had overweight or obesity (n = 17), and those with a specific clinical situation (n = 14). In the healthy pediatric population, the FAO/WHO and Schofield equations had the highest R2 values, while in the population with obesity, the Molnár and Dietz equations had the highest R2 values for both boys and girls.Conclusions: Many different predictive equations for energy expenditure in pediatric patients have been published. This review is a compendium of most of these equations; this information will enable clinicians to critically evaluate their use in clinical practice.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=226270, PROSPERO [CRD42021226270].

scholarly journals Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

2020 ◽  
Author(s):  
Thaiciane Grassi ◽  
Francesco Pinto Boeno ◽  
Mauren Minuzzo de Freitas ◽  
Tatiana Pedroso de Paula ◽  
Luciana Vercoza Viana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Reference Method ◽  
Resting Energy Expenditure ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Resting Energy

Abstract Background: Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods: A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance and laboratory variables were evaluated. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by eleven predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results: 62 patients were evaluated [50% female; mean age 63.1 ± 5.2 years; diabetes duration of 11 (1-36) years, and mean A1C of 7.6 ± 1.2%]. There was a wide variation in the accuracy of REE values predicted by equations when compared to IC REE measurement. In all patients, Ikeda and Mifflin St-Jeor equations were that most underestimated REE. And, the equations that overestimated the REE were proposed by Dietary Reference Intakes and Huang. The most accurate equations were FAO/WHO/UNO in women (-1.8% difference) and Oxford in men (-1.3% difference).Conclusion: In patients with type 2 diabetes, in the absence of IC, FAO/WHO/UNO and Oxford equations provide the best REE prediction in comparison to measured REE for women and men, respectively.

scholarly journals Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: what can we use?

BMC Nutrition ◽  
2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Thaiciane Grassi ◽  
Francesco Pinto Boeno ◽  
Mauren Minuzzo de Freitas ◽  
Tatiana Pedroso de Paula ◽  
Luciana Vercoza Viana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Reference Method ◽  
Resting Energy Expenditure ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Resting Energy

Abstract Background Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method. Methods A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance and laboratory variables were evaluated. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by eleven predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients. Results Sixty-two patients were evaluated [50% female; mean age 63.1 ± 5.2 years; diabetes duration of 11 (1–36) years, and mean A1C of 7.6 ± 1.2%]. There was a wide variation in the accuracy of REE values predicted by equations when compared to IC REE measurement. In all patients, Ikeda and Mifflin St-Jeor equations were that most underestimated REE. And, the equations that overestimated the REE were proposed by Dietary Reference Intakes and Huang. The most accurate equations were FAO/WHO/UNO in women (− 1.8% difference) and Oxford in men (− 1.3% difference). Conclusion In patients with type 2 diabetes, in the absence of IC, FAO/WHO/UNO and Oxford equations provide the best REE prediction in comparison to measured REE for women and men, respectively.

Estimation of Resting Energy Expenditure Using Predictive Equations in Critically Ill Children: Results of a Systematic Review

2018 ◽  
Vol 42 (6) ◽  
pp. 976-986 ◽  
Author(s):  
Corinne Jotterand Chaparro ◽  
Clémence Moullet ◽  
Patrick Taffé ◽  
Jocelyne Laure Depeyre ◽  
Marie-Hélène Perez ◽  
...  
Keyword(s):  
Systematic Review ◽  
Energy Expenditure ◽  
Critically Ill ◽  
Resting Energy Expenditure ◽  
Critically Ill Children ◽  
Predictive Equations ◽  
Resting Energy

scholarly journals Accuracy of predictive equations for evaluation of resting energy expenditure in Brazilian patients with type 2 diabetes.

2020 ◽  
Author(s):  
Thaiciane Grassi ◽  
Francesco Pinto Boeno ◽  
Mauren Minuzzo de Freitas ◽  
Tatiana Pedroso de Paula ◽  
Luciana Vercoza Viana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Composition ◽  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Fat Free Mass ◽  
Composition Analysis ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Resting Energy

Abstract Background Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this study was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods A cross-sectional study was conducted in 62 patients (31 men and 31 women) with type 2 diabetes. Clinical and laboratory variables were evaluated, as well as body composition by electrical bioimpedance. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results Patients in the sample had a mean age of 63.1 ± 5.2 years, median diabetes duration of 11 (1–36) years, and mean A1C of 7.6 ± 1.2%. Body composition analysis revealed a mean fat free mass of 35.2 ± 11.8 kg and fat mass of 29.1 ± 8.8 kg. There was wide variation in the accuracy of REE values predicted by equations when compared to those measured by IC. For women, the FAO/WHO/UNO equation provided the best REE prediction in comparison to measured REE (-1.8% difference). For men, the Oxford equation yielded values closest to those measured by IC (-1.3% difference).Conclusions In this sample of the patients with type 2 diabetes, the best predictive equations to estimate REE were FAO/WHO/UNO and Oxford for women and men, respectively.

scholarly journals Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

2020 ◽  
Author(s):  
Thaiciane Grassi ◽  
Francesco Pinto Boeno ◽  
Mauren Minuzzo de Freitas ◽  
Tatiana Pedroso de Paula ◽  
Luciana Vercoza Viana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Reference Method ◽  
Resting Energy Expenditure ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Resting Energy

Abstract Background: Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods: A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance and laboratory variables were evaluated. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by eleven predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results: 62 patients were evaluated [50% female; mean age 63.1 ± 5.2 years; diabetes duration of 11 (1-36) years, and mean A1C of 7.6 ± 1.2%]. There was a wide variation in the accuracy of REE values predicted by equations when compared to IC REE measurement. In all patients, Ikeda and Mifflin St-Jeor equations were that most underestimated REE. And, the equations that overestimated the REE were proposed by Dietary Reference Intakes and Huang. The most accurate equations were FAO/WHO/UNO in women (-1.8% difference) and Oxford in men (-1.3% difference).Conclusion: In patients with type 2 diabetes, in the absence of IC, FAO/WHO/UNO and Oxford equations provide the best REE prediction in comparison to measured REE for women and men, respectively.

scholarly journals Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 458
Author(s):  
Honoria Ocagli ◽  
Corrado Lanera ◽  
Danila Azzolina ◽  
Gianluca Piras ◽  
Rozita Soltanmohammadi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Energy Expenditure ◽  
Web Application ◽  
Intraclass Correlation ◽  
Resting Energy Expenditure ◽  
The Elderly ◽  
Elderly Subjects ◽  
Experimental Population ◽  
Predictive Equations ◽  
Resting Energy

Elderly patients are at risk of malnutrition and need an appropriate assessment of energy requirements. Predictive equations are widely used to estimate resting energy expenditure (REE). In the study, we conducted a systematic review of REE predictive equations in the elderly population and compared them in an experimental population. Studies involving subjects older than 65 years of age that evaluated the performance of a predictive equation vs. a gold standard were included. The retrieved equations were then tested on a sample of 88 elderly subjects enrolled in an Italian nursing home to evaluate the agreement among the estimated REEs. The agreement was assessed using the intraclass correlation coefficient (ICC). A web application, equationer, was developed to calculate all the estimated REEs according to the available variables. The review identified 68 studies (210 different equations). The agreement among the equations in our sample was higher for equations with fewer parameters, especially those that included body weight, ICC = 0.75 (95% CI = 0.69–0.81). There is great heterogeneity among REE estimates. Such differences should be considered and evaluated when estimates are applied to particularly fragile populations since the results have the potential to impact the patient’s overall clinical outcome.

scholarly journals Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

2020 ◽  
Author(s):  
Thaiciane Grassi ◽  
Francesco Pinto Boeno ◽  
Mauren Minuzzo de Freitas ◽  
Tatiana Pedroso de Paula ◽  
Luciana Vercoza Viana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Reference Method ◽  
Resting Energy Expenditure ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Resting Energy

Abstract Background: Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods: A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance and laboratory variables were evaluated. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by eleven predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results: 62 patients were evaluated [50% female; mean age 63.1 ± 5.2 years; diabetes duration of 11 (1-36) years, and mean A1C of 7.6 ± 1.2%]. There was a wide variation in the accuracy of REE values predicted by equations when compared to IC REE measurement. In all patients, Ikeda and Mifflin St-Jeor equations were that most underestimated REE. And, the equations that overestimated the REE were proposed by Dietary Reference Intakes and Huang. The most accurate equations were FAO/WHO/UNO in women (-1.8% difference) and Oxford in men (-1.3% difference).Conclusion: In patients with type 2 diabetes, in the absence of IC, FAO/WHO/UNO and Oxford equations provide the best REE prediction in comparison to measured REE for women and men, respectively.

scholarly journals Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

2020 ◽  
Author(s):  
Thaiciane Grassi ◽  
Francesco Pinto Boeno ◽  
Mauren Minuzzo de Freitas ◽  
Tatiana Pedroso de Paula ◽  
Luciana Vercoza Viana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Reference Method ◽  
Resting Energy Expenditure ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Resting Energy

Abstract Background: Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods: A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance and, laboratory variables were evaluated. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by eleven predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results: 62 patients were evaluated [50% female; mean age 63.1 ± 5.2 years; diabetes duration of 11 (1-36) years, and mean A1C of 7.6 ± 1.2%]. There was a wide variation in the accuracy of REE values predicted by equations when compared to IC REE measurement. In all patients, Ikeda and Mifflin St-Jeor equations were that most underestimated REE. And, the equations that overestimated the REE were proposed by Dietary Reference Intakes and Huang. The most accurate equations were FAO/WHO/UNO in women (-1.8% difference) and Oxford in men (-1.3% difference).Conclusion: In patients with type 2 diabetes, in the absence of IC, FAO/WHO/UNO and Oxford equations provide the best REE prediction in comparison to measured REE for women and men, respectively.

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