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Wolverhampton Intellectual Repository and E-Theses > Research Institutes > Research Institute in Healthcare Science > Sport, Exercise and Health Research Group > New resting energy expenditure prediction equations for patients with rheumatoid arthritis

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/40234
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Title: New resting energy expenditure prediction equations for patients with rheumatoid arthritis
Authors: Metsios, Giorgos S.
Stavropoulos-Kalinoglou, Antonios
Panoulas, Vasileios F.
Koutedakis, Yiannis
Nevill, Alan M.
Douglas, Karen M. J.
Kita, Marina D.
Kitas, George D.
Citation: Rheumatology, 47(4): 500-506
Publisher: Oxford University Press
Journal: Rheumatology
Issue Date: 2008
URI: http://hdl.handle.net/2436/40234
DOI: 10.1093/rheumatology/ken022
PubMed ID: 18304942
Additional Links: http://rheumatology.oxfordjournals.org/cgi/content/abstract/47/4/500
Abstract: OBJECTIVES: Resting energy expenditure (REE), one of the main components of total energy expenditure, can be measured via indirect calorimetry and/or predicted from equations. The latter may be misleading in RA, as they do not take into account the metabolic alterations occurring in RA. The objectives of this study are to evaluate the accuracy of widely used REE-predictive equations in RA patients against measured REE and to develop RA-specific equations. METHODS: We assessed REE (via indirect calorimetry and several predictive equations), fat-free mass (FFM; via bioelectrical impedance) and disease activity (CRP) in RA patients and healthy controls. Data from 60 RA patients (experimental group) were used to assess the accuracy of existing REE equations and to develop new equations. The new equations were validated in an independent cross-validation group of 22 RA patients. These two groups were merged and two final equations were developed. RESULTS: All equations significantly under-predicted measured REE (from 15% to 18.2%, all at P < 0.001) in the RA experimental group, but not in the control group. After both equations demonstrated a high validity in the cross-validation group, the new final REE prediction equations developed from the total RA sample (n = 82) were: Model 1: REE (kcal/day) = 126.1 x FFM(0.638) x CRP(0.045) (R(2) = 0.70) and Model 2: REE (kcal/day) = 598.8 x weight(0.47) x age(-0.29) x CRP(0.066) (R(2) = 0.62). CONCLUSION: The new equations provide an accurate prediction of REE in RA patients and could be used for clinical monitoring of resting metabolism of these patients without the requirement for specialized personnel.
Type: Article
Language: en
Keywords: Resting energy expenditure
Metabolism
Equation
Prediction
MeSH: Aged
Anthropometry
Antirheumatic Agents
Arthritis, Rheumatoid
Biological Markers
Body Weight
C-Reactive Protein
Calorimetry, Indirect
Energy Metabolism
Female
Humans
Male
Middle Aged
Models, Biological
Reproducibility of Results
Severity of Illness Index
Tumor Necrosis Factor-alpha
ISSN: 1462-0332
Appears in Collections: Sport, Exercise and Health Research Group
Learning and Teaching in Sport, Exercise and Performance

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