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

Detalhes bibliográficos
Autor(a) principal: Grassi, Thaiciane
Data de Publicação: 2020
Outros Autores: Boeno, Francesco Pinto, Freitas, Mauren Minuzzo de, Paula, Tatiana Pedroso de, Viana, Luciana Verçoza, Oliveira, Álvaro Reischak de, Steemburgo, Thais
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/216389
Resumo: 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.
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spelling Grassi, ThaicianeBoeno, Francesco PintoFreitas, Mauren Minuzzo dePaula, Tatiana Pedroso deViana, Luciana VerçozaOliveira, Álvaro Reischak deSteemburgo, Thais2020-12-11T04:11:45Z20202055-0928http://hdl.handle.net/10183/216389001118962Background: 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.application/pdfengBMC nutrition. London. vol. 6, 56, 11 f.Metabolismo basalPacientesDiabetes mellitus tipo 2Indirect calorimetryType 2 diabetesResting energy expenditureEnergy metabolismPredictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?Estrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001118962.pdf.txt001118962.pdf.txtExtracted Texttext/plain47044http://www.lume.ufrgs.br/bitstream/10183/216389/2/001118962.pdf.txtb63c6bc719fe080eed2a32caf92c250aMD52ORIGINAL001118962.pdfTexto completo (inglês)application/pdf1291370http://www.lume.ufrgs.br/bitstream/10183/216389/1/001118962.pdf77e98113ecdc83b9682993f7f42035beMD5110183/2163892020-12-12 05:20:12.562053oai:www.lume.ufrgs.br:10183/216389Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2020-12-12T07:20:12Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
title Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
spellingShingle Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
Grassi, Thaiciane
Metabolismo basal
Pacientes
Diabetes mellitus tipo 2
Indirect calorimetry
Type 2 diabetes
Resting energy expenditure
Energy metabolism
title_short Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
title_full Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
title_fullStr Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
title_full_unstemmed Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
title_sort Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
author Grassi, Thaiciane
author_facet Grassi, Thaiciane
Boeno, Francesco Pinto
Freitas, Mauren Minuzzo de
Paula, Tatiana Pedroso de
Viana, Luciana Verçoza
Oliveira, Álvaro Reischak de
Steemburgo, Thais
author_role author
author2 Boeno, Francesco Pinto
Freitas, Mauren Minuzzo de
Paula, Tatiana Pedroso de
Viana, Luciana Verçoza
Oliveira, Álvaro Reischak de
Steemburgo, Thais
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Grassi, Thaiciane
Boeno, Francesco Pinto
Freitas, Mauren Minuzzo de
Paula, Tatiana Pedroso de
Viana, Luciana Verçoza
Oliveira, Álvaro Reischak de
Steemburgo, Thais
dc.subject.por.fl_str_mv Metabolismo basal
Pacientes
Diabetes mellitus tipo 2
topic Metabolismo basal
Pacientes
Diabetes mellitus tipo 2
Indirect calorimetry
Type 2 diabetes
Resting energy expenditure
Energy metabolism
dc.subject.eng.fl_str_mv Indirect calorimetry
Type 2 diabetes
Resting energy expenditure
Energy metabolism
description 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.
publishDate 2020
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dc.relation.ispartof.pt_BR.fl_str_mv BMC nutrition. London. vol. 6, 56, 11 f.
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