Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes : what can we use?
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
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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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 |
dc.date.accessioned.fl_str_mv |
2020-12-11T04:11:45Z |
dc.date.issued.fl_str_mv |
2020 |
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Estrangeiro info:eu-repo/semantics/article |
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http://hdl.handle.net/10183/216389 |
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2055-0928 |
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001118962 |
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http://hdl.handle.net/10183/216389 |
dc.language.iso.fl_str_mv |
eng |
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eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
BMC nutrition. London. vol. 6, 56, 11 f. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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