Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?

Detalhes bibliográficos
Autor(a) principal: Kamimura, Maria Ayako [UNIFESP]
Data de Publicação: 2011
Outros Autores: Avesani, Carla Maria [UNIFESP], Bazanelli, Ana Paula [UNIFESP], Baria, Flavia [UNIFESP], Draibe, Sergio Antonio [UNIFESP], Cuppari, Lilian [UNIFESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNIFESP
Texto Completo: http://dx.doi.org/10.1093/ndt/gfq452
http://repositorio.unifesp.br/handle/11600/33391
Resumo: Background. the determination of resting energy expenditure (REE) is the primary step for estimating the energy requirement of an individual. Although numerous equations have been formulated for predicting metabolic rates, there is a lack of studies addressing the reliability of those equations in chronic kidney disease (CKD). Thus, the aim of this study was to evaluate whether the main equations developed for estimating REE can be reliably applied for CKD patients.Methods. A total of 281 CKD patients (124 non-dialysis, 99 haemodialysis and 58 peritoneal dialysis) and 81 healthy control individuals were recruited. Indirect calorimetry and blood sample collection were performed after a 12-h fasting. Two most traditionally used equations for estimating REE were chosen for comparison with the REE measured by indirect calorimetry: (i) the equation proposed by Harris and Benedict, and (ii) the equation proposed by Schofield that is currently recommended by the FAO/WHO/UNU.Results. Schofield's equation exhibited higher REE [1492 +/- 220 kcal/day (mean +/- SD)] in relation to Harris and Benedict's equation (1431 +/- 214 kcal/day; P < 0.001), and both prediction equations showed higher REE in comparison with the reference indirect calorimetry (1352 +/- 252 kcal/day; P < 0.001). in patients with diabetes, inflammation or severe hyperparathyroidism, the REE estimated by the Harris and Benedict equation was equivalent to that measured by indirect calorimetry. the intraclass correlation of the REE measured by indirect calorimetry with the Schofield's equation was r = 0.48 (P < 0.001) and with the Harris and Benedict's equation was r = 0.58 (P < 0.001). According to the Bland and Altman analysis, there was a large limit of agreement between both prediction equations and the reference method. Acceptable prediction of REE (90-110% adequacy) was found in 47% of the patients by using the Harris and Benedict's equation and in only 37% by using the Schofield's equation.Conclusions. the most traditionally used prediction equations overestimated the REE of CKD patients, and the errors were minimized in the presence of comorbidities. There is a need to develop population-specific equations in order to adequately estimate the energy requirement of these patients.
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spelling Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?chronic kidney diseaseenergy requirementindirect calorimetryprediction equationsresting energy expenditureBackground. the determination of resting energy expenditure (REE) is the primary step for estimating the energy requirement of an individual. Although numerous equations have been formulated for predicting metabolic rates, there is a lack of studies addressing the reliability of those equations in chronic kidney disease (CKD). Thus, the aim of this study was to evaluate whether the main equations developed for estimating REE can be reliably applied for CKD patients.Methods. A total of 281 CKD patients (124 non-dialysis, 99 haemodialysis and 58 peritoneal dialysis) and 81 healthy control individuals were recruited. Indirect calorimetry and blood sample collection were performed after a 12-h fasting. Two most traditionally used equations for estimating REE were chosen for comparison with the REE measured by indirect calorimetry: (i) the equation proposed by Harris and Benedict, and (ii) the equation proposed by Schofield that is currently recommended by the FAO/WHO/UNU.Results. Schofield's equation exhibited higher REE [1492 +/- 220 kcal/day (mean +/- SD)] in relation to Harris and Benedict's equation (1431 +/- 214 kcal/day; P < 0.001), and both prediction equations showed higher REE in comparison with the reference indirect calorimetry (1352 +/- 252 kcal/day; P < 0.001). in patients with diabetes, inflammation or severe hyperparathyroidism, the REE estimated by the Harris and Benedict equation was equivalent to that measured by indirect calorimetry. the intraclass correlation of the REE measured by indirect calorimetry with the Schofield's equation was r = 0.48 (P < 0.001) and with the Harris and Benedict's equation was r = 0.58 (P < 0.001). According to the Bland and Altman analysis, there was a large limit of agreement between both prediction equations and the reference method. Acceptable prediction of REE (90-110% adequacy) was found in 47% of the patients by using the Harris and Benedict's equation and in only 37% by using the Schofield's equation.Conclusions. the most traditionally used prediction equations overestimated the REE of CKD patients, and the errors were minimized in the presence of comorbidities. There is a need to develop population-specific equations in order to adequately estimate the energy requirement of these patients.Universidade Federal de São Paulo, Nutr Program, São Paulo, BrazilUniversidade Federal de São Paulo, Div Nephrol, São Paulo, BrazilUniv Estado Rio de Janeiro, Inst Nutr, Rio de Janeiro, BrazilUniversidade Federal de São Paulo, Nutr Program, São Paulo, BrazilUniversidade Federal de São Paulo, Div Nephrol, São Paulo, BrazilWeb of ScienceFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Oswaldo Ramos FoundationOxford Univ PressUniversidade Federal de São Paulo (UNIFESP)Universidade do Estado do Rio de Janeiro (UERJ)Kamimura, Maria Ayako [UNIFESP]Avesani, Carla Maria [UNIFESP]Bazanelli, Ana Paula [UNIFESP]Baria, Flavia [UNIFESP]Draibe, Sergio Antonio [UNIFESP]Cuppari, Lilian [UNIFESP]2016-01-24T14:06:06Z2016-01-24T14:06:06Z2011-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion544-550http://dx.doi.org/10.1093/ndt/gfq452Nephrology Dialysis Transplantation. Oxford: Oxford Univ Press, v. 26, n. 2, p. 544-550, 2011.10.1093/ndt/gfq4520931-0509http://repositorio.unifesp.br/handle/11600/33391WOS:000286675400022engNephrology Dialysis Transplantationinfo:eu-repo/semantics/openAccesshttp://www.oxfordjournals.org/access_purchase/self-archiving_policyb.htmlreponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESP2023-05-18T14:42:42Zoai:repositorio.unifesp.br/:11600/33391Repositório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestbiblioteca.csp@unifesp.bropendoar:34652023-05-18T14:42:42Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false
dc.title.none.fl_str_mv Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
title Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
spellingShingle Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
Kamimura, Maria Ayako [UNIFESP]
chronic kidney disease
energy requirement
indirect calorimetry
prediction equations
resting energy expenditure
title_short Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
title_full Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
title_fullStr Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
title_full_unstemmed Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
title_sort Are prediction equations reliable for estimating resting energy expenditure in chronic kidney disease patients?
author Kamimura, Maria Ayako [UNIFESP]
author_facet Kamimura, Maria Ayako [UNIFESP]
Avesani, Carla Maria [UNIFESP]
Bazanelli, Ana Paula [UNIFESP]
Baria, Flavia [UNIFESP]
Draibe, Sergio Antonio [UNIFESP]
Cuppari, Lilian [UNIFESP]
author_role author
author2 Avesani, Carla Maria [UNIFESP]
Bazanelli, Ana Paula [UNIFESP]
Baria, Flavia [UNIFESP]
Draibe, Sergio Antonio [UNIFESP]
Cuppari, Lilian [UNIFESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Federal de São Paulo (UNIFESP)
Universidade do Estado do Rio de Janeiro (UERJ)
dc.contributor.author.fl_str_mv Kamimura, Maria Ayako [UNIFESP]
Avesani, Carla Maria [UNIFESP]
Bazanelli, Ana Paula [UNIFESP]
Baria, Flavia [UNIFESP]
Draibe, Sergio Antonio [UNIFESP]
Cuppari, Lilian [UNIFESP]
dc.subject.por.fl_str_mv chronic kidney disease
energy requirement
indirect calorimetry
prediction equations
resting energy expenditure
topic chronic kidney disease
energy requirement
indirect calorimetry
prediction equations
resting energy expenditure
description Background. the determination of resting energy expenditure (REE) is the primary step for estimating the energy requirement of an individual. Although numerous equations have been formulated for predicting metabolic rates, there is a lack of studies addressing the reliability of those equations in chronic kidney disease (CKD). Thus, the aim of this study was to evaluate whether the main equations developed for estimating REE can be reliably applied for CKD patients.Methods. A total of 281 CKD patients (124 non-dialysis, 99 haemodialysis and 58 peritoneal dialysis) and 81 healthy control individuals were recruited. Indirect calorimetry and blood sample collection were performed after a 12-h fasting. Two most traditionally used equations for estimating REE were chosen for comparison with the REE measured by indirect calorimetry: (i) the equation proposed by Harris and Benedict, and (ii) the equation proposed by Schofield that is currently recommended by the FAO/WHO/UNU.Results. Schofield's equation exhibited higher REE [1492 +/- 220 kcal/day (mean +/- SD)] in relation to Harris and Benedict's equation (1431 +/- 214 kcal/day; P < 0.001), and both prediction equations showed higher REE in comparison with the reference indirect calorimetry (1352 +/- 252 kcal/day; P < 0.001). in patients with diabetes, inflammation or severe hyperparathyroidism, the REE estimated by the Harris and Benedict equation was equivalent to that measured by indirect calorimetry. the intraclass correlation of the REE measured by indirect calorimetry with the Schofield's equation was r = 0.48 (P < 0.001) and with the Harris and Benedict's equation was r = 0.58 (P < 0.001). According to the Bland and Altman analysis, there was a large limit of agreement between both prediction equations and the reference method. Acceptable prediction of REE (90-110% adequacy) was found in 47% of the patients by using the Harris and Benedict's equation and in only 37% by using the Schofield's equation.Conclusions. the most traditionally used prediction equations overestimated the REE of CKD patients, and the errors were minimized in the presence of comorbidities. There is a need to develop population-specific equations in order to adequately estimate the energy requirement of these patients.
publishDate 2011
dc.date.none.fl_str_mv 2011-02-01
2016-01-24T14:06:06Z
2016-01-24T14:06:06Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1093/ndt/gfq452
Nephrology Dialysis Transplantation. Oxford: Oxford Univ Press, v. 26, n. 2, p. 544-550, 2011.
10.1093/ndt/gfq452
0931-0509
http://repositorio.unifesp.br/handle/11600/33391
WOS:000286675400022
url http://dx.doi.org/10.1093/ndt/gfq452
http://repositorio.unifesp.br/handle/11600/33391
identifier_str_mv Nephrology Dialysis Transplantation. Oxford: Oxford Univ Press, v. 26, n. 2, p. 544-550, 2011.
10.1093/ndt/gfq452
0931-0509
WOS:000286675400022
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Nephrology Dialysis Transplantation
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
http://www.oxfordjournals.org/access_purchase/self-archiving_policyb.html
eu_rights_str_mv openAccess
rights_invalid_str_mv http://www.oxfordjournals.org/access_purchase/self-archiving_policyb.html
dc.format.none.fl_str_mv 544-550
dc.publisher.none.fl_str_mv Oxford Univ Press
publisher.none.fl_str_mv Oxford Univ Press
dc.source.none.fl_str_mv reponame:Repositório Institucional da UNIFESP
instname:Universidade Federal de São Paulo (UNIFESP)
instacron:UNIFESP
instname_str Universidade Federal de São Paulo (UNIFESP)
instacron_str UNIFESP
institution UNIFESP
reponame_str Repositório Institucional da UNIFESP
collection Repositório Institucional da UNIFESP
repository.name.fl_str_mv Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)
repository.mail.fl_str_mv biblioteca.csp@unifesp.br
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